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cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_template.py | """
This is a fully functional do nothing backend to provide a template to
backend writers. It is fully functional in that you can select it as
a backend with
import matplotlib
matplotlib.use('Template')
and your matplotlib scripts will (should!) run without error, though
no output is produced. This provides a nice starting point for
backend writers because you can selectively implement methods
(draw_rectangle, draw_lines, etc...) and slowly see your figure come
to life w/o having to have a full blown implementation before getting
any results.
Copy this to backend_xxx.py and replace all instances of 'template'
with 'xxx'. Then implement the class methods and functions below, and
add 'xxx' to the switchyard in matplotlib/backends/__init__.py and
'xxx' to the backends list in the validate_backend methon in
matplotlib/__init__.py and you're off. You can use your backend with::
import matplotlib
matplotlib.use('xxx')
from pylab import *
plot([1,2,3])
show()
matplotlib also supports external backends, so you can place you can
use any module in your PYTHONPATH with the syntax::
import matplotlib
matplotlib.use('module://my_backend')
where my_backend.py is your module name. This syntax is also
recognized in the rc file and in the -d argument in pylab, e.g.,::
python simple_plot.py -dmodule://my_backend
If your backend implements support for saving figures (i.e. has a print_xyz()
method) you can register it as the default handler for a given file type
from matplotlib.backend_bases import register_backend
register_backend('xyz', 'my_backend', 'XYZ File Format')
...
plt.savefig("figure.xyz")
The files that are most relevant to backend_writers are
matplotlib/backends/backend_your_backend.py
matplotlib/backend_bases.py
matplotlib/backends/__init__.py
matplotlib/__init__.py
matplotlib/_pylab_helpers.py
Naming Conventions
* classes Upper or MixedUpperCase
* variables lower or lowerUpper
* functions lower or underscore_separated
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
FigureCanvasBase, FigureManagerBase, GraphicsContextBase, RendererBase)
from matplotlib.figure import Figure
class RendererTemplate(RendererBase):
"""
The renderer handles drawing/rendering operations.
This is a minimal do-nothing class that can be used to get started when
writing a new backend. Refer to backend_bases.RendererBase for
documentation of the classes methods.
"""
def __init__(self, dpi):
self.dpi = dpi
def draw_path(self, gc, path, transform, rgbFace=None):
pass
# draw_markers is optional, and we get more correct relative
# timings by leaving it out. backend implementers concerned with
# performance will probably want to implement it
# def draw_markers(self, gc, marker_path, marker_trans, path, trans,
# rgbFace=None):
# pass
# draw_path_collection is optional, and we get more correct
# relative timings by leaving it out. backend implementers concerned with
# performance will probably want to implement it
# def draw_path_collection(self, gc, master_transform, paths,
# all_transforms, offsets, offsetTrans,
# facecolors, edgecolors, linewidths, linestyles,
# antialiaseds):
# pass
# draw_quad_mesh is optional, and we get more correct
# relative timings by leaving it out. backend implementers concerned with
# performance will probably want to implement it
# def draw_quad_mesh(self, gc, master_transform, meshWidth, meshHeight,
# coordinates, offsets, offsetTrans, facecolors,
# antialiased, edgecolors):
# pass
def draw_image(self, gc, x, y, im):
pass
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
pass
def flipy(self):
return True
def get_canvas_width_height(self):
return 100, 100
def get_text_width_height_descent(self, s, prop, ismath):
return 1, 1, 1
def new_gc(self):
return GraphicsContextTemplate()
def points_to_pixels(self, points):
# if backend doesn't have dpi, e.g., postscript or svg
return points
# elif backend assumes a value for pixels_per_inch
#return points/72.0 * self.dpi.get() * pixels_per_inch/72.0
# else
#return points/72.0 * self.dpi.get()
class GraphicsContextTemplate(GraphicsContextBase):
"""
The graphics context provides the color, line styles, etc... See the gtk
and postscript backends for examples of mapping the graphics context
attributes (cap styles, join styles, line widths, colors) to a particular
backend. In GTK this is done by wrapping a gtk.gdk.GC object and
forwarding the appropriate calls to it using a dictionary mapping styles
to gdk constants. In Postscript, all the work is done by the renderer,
mapping line styles to postscript calls.
If it's more appropriate to do the mapping at the renderer level (as in
the postscript backend), you don't need to override any of the GC methods.
If it's more appropriate to wrap an instance (as in the GTK backend) and
do the mapping here, you'll need to override several of the setter
methods.
The base GraphicsContext stores colors as a RGB tuple on the unit
interval, e.g., (0.5, 0.0, 1.0). You may need to map this to colors
appropriate for your backend.
"""
pass
########################################################################
#
# The following functions and classes are for pylab and implement
# window/figure managers, etc...
#
########################################################################
def draw_if_interactive():
"""
For image backends - is not required
For GUI backends - this should be overridden if drawing should be done in
interactive python mode
"""
def show(block=None):
"""
For image backends - is not required
For GUI backends - show() is usually the last line of a pylab script and
tells the backend that it is time to draw. In interactive mode, this may
be a do nothing func. See the GTK backend for an example of how to handle
interactive versus batch mode
"""
for manager in Gcf.get_all_fig_managers():
# do something to display the GUI
pass
def new_figure_manager(num, *args, **kwargs):
"""
Create a new figure manager instance
"""
# May be implemented via the `_new_figure_manager_template` helper.
# If a main-level app must be created, this (and
# new_figure_manager_given_figure) is the usual place to do it -- see
# backend_wx, backend_wxagg and backend_tkagg for examples. Not all GUIs
# require explicit instantiation of a main-level app (egg backend_gtk,
# backend_gtkagg) for pylab.
FigureClass = kwargs.pop('FigureClass', Figure)
thisFig = FigureClass(*args, **kwargs)
return new_figure_manager_given_figure(num, thisFig)
def new_figure_manager_given_figure(num, figure):
"""
Create a new figure manager instance for the given figure.
"""
# May be implemented via the `_new_figure_manager_template` helper.
canvas = FigureCanvasTemplate(figure)
manager = FigureManagerTemplate(canvas, num)
return manager
class FigureCanvasTemplate(FigureCanvasBase):
"""
The canvas the figure renders into. Calls the draw and print fig
methods, creates the renderers, etc...
Note GUI templates will want to connect events for button presses,
mouse movements and key presses to functions that call the base
class methods button_press_event, button_release_event,
motion_notify_event, key_press_event, and key_release_event. See,
e.g., backend_gtk.py, backend_wx.py and backend_tkagg.py
Attributes
----------
figure : `matplotlib.figure.Figure`
A high-level Figure instance
"""
def draw(self):
"""
Draw the figure using the renderer
"""
renderer = RendererTemplate(self.figure.dpi)
self.figure.draw(renderer)
# You should provide a print_xxx function for every file format
# you can write.
# If the file type is not in the base set of filetypes,
# you should add it to the class-scope filetypes dictionary as follows:
filetypes = FigureCanvasBase.filetypes.copy()
filetypes['foo'] = 'My magic Foo format'
def print_foo(self, filename, *args, **kwargs):
"""
Write out format foo. The dpi, facecolor and edgecolor are restored
to their original values after this call, so you don't need to
save and restore them.
"""
pass
def get_default_filetype(self):
return 'foo'
class FigureManagerTemplate(FigureManagerBase):
"""
Wrap everything up into a window for the pylab interface
For non interactive backends, the base class does all the work
"""
pass
########################################################################
#
# Now just provide the standard names that backend.__init__ is expecting
#
########################################################################
FigureCanvas = FigureCanvasTemplate
FigureManager = FigureManagerTemplate
| 9,529 | 33.157706 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_mixed.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import six
from matplotlib.backends.backend_agg import RendererAgg
from matplotlib.tight_bbox import process_figure_for_rasterizing
class MixedModeRenderer(object):
"""
A helper class to implement a renderer that switches between
vector and raster drawing. An example may be a PDF writer, where
most things are drawn with PDF vector commands, but some very
complex objects, such as quad meshes, are rasterised and then
output as images.
"""
def __init__(self, figure, width, height, dpi, vector_renderer,
raster_renderer_class=None,
bbox_inches_restore=None):
"""
Parameters
----------
figure : `matplotlib.figure.Figure`
The figure instance.
width : scalar
The width of the canvas in logical units
height : scalar
The height of the canvas in logical units
dpi : scalar
The dpi of the canvas
vector_renderer : `matplotlib.backend_bases.RendererBase`
An instance of a subclass of
`~matplotlib.backend_bases.RendererBase` that will be used for the
vector drawing.
raster_renderer_class : `matplotlib.backend_bases.RendererBase`
The renderer class to use for the raster drawing. If not provided,
this will use the Agg backend (which is currently the only viable
option anyway.)
"""
if raster_renderer_class is None:
raster_renderer_class = RendererAgg
self._raster_renderer_class = raster_renderer_class
self._width = width
self._height = height
self.dpi = dpi
self._vector_renderer = vector_renderer
self._raster_renderer = None
self._rasterizing = 0
# A reference to the figure is needed as we need to change
# the figure dpi before and after the rasterization. Although
# this looks ugly, I couldn't find a better solution. -JJL
self.figure = figure
self._figdpi = figure.get_dpi()
self._bbox_inches_restore = bbox_inches_restore
self._set_current_renderer(vector_renderer)
_methods = """
close_group draw_image draw_markers draw_path
draw_path_collection draw_quad_mesh draw_tex draw_text
finalize flipy get_canvas_width_height get_image_magnification
get_texmanager get_text_width_height_descent new_gc open_group
option_image_nocomposite points_to_pixels strip_math
start_filter stop_filter draw_gouraud_triangle
draw_gouraud_triangles option_scale_image
_text2path _get_text_path_transform height width
""".split()
def _set_current_renderer(self, renderer):
self._renderer = renderer
for method in self._methods:
if hasattr(renderer, method):
setattr(self, method, getattr(renderer, method))
renderer.start_rasterizing = self.start_rasterizing
renderer.stop_rasterizing = self.stop_rasterizing
def start_rasterizing(self):
"""
Enter "raster" mode. All subsequent drawing commands (until
stop_rasterizing is called) will be drawn with the raster
backend.
If start_rasterizing is called multiple times before
stop_rasterizing is called, this method has no effect.
"""
# change the dpi of the figure temporarily.
self.figure.set_dpi(self.dpi)
if self._bbox_inches_restore: # when tight bbox is used
r = process_figure_for_rasterizing(self.figure,
self._bbox_inches_restore)
self._bbox_inches_restore = r
if self._rasterizing == 0:
self._raster_renderer = self._raster_renderer_class(
self._width*self.dpi, self._height*self.dpi, self.dpi)
self._set_current_renderer(self._raster_renderer)
self._rasterizing += 1
def stop_rasterizing(self):
"""
Exit "raster" mode. All of the drawing that was done since
the last start_rasterizing command will be copied to the
vector backend by calling draw_image.
If stop_rasterizing is called multiple times before
start_rasterizing is called, this method has no effect.
"""
self._rasterizing -= 1
if self._rasterizing == 0:
self._set_current_renderer(self._vector_renderer)
height = self._height * self.dpi
buffer, bounds = self._raster_renderer.tostring_rgba_minimized()
l, b, w, h = bounds
if w > 0 and h > 0:
image = np.frombuffer(buffer, dtype=np.uint8)
image = image.reshape((h, w, 4))
image = image[::-1]
gc = self._renderer.new_gc()
# TODO: If the mixedmode resolution differs from the figure's
# dpi, the image must be scaled (dpi->_figdpi). Not all
# backends support this.
self._renderer.draw_image(
gc,
l * self._figdpi / self.dpi,
(height-b-h) * self._figdpi / self.dpi,
image)
self._raster_renderer = None
self._rasterizing = False
# restore the figure dpi.
self.figure.set_dpi(self._figdpi)
if self._bbox_inches_restore: # when tight bbox is used
r = process_figure_for_rasterizing(self.figure,
self._bbox_inches_restore,
self._figdpi)
self._bbox_inches_restore = r
| 5,860 | 36.570513 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/windowing.py | """
MS Windows-specific helper for the TkAgg backend.
With rcParams['tk.window_focus'] default of False, it is
effectively disabled.
It uses a tiny C++ extension module to access MS Win functions.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib import rcParams
try:
if not rcParams['tk.window_focus']:
raise ImportError
from matplotlib._windowing import GetForegroundWindow, SetForegroundWindow
except ImportError:
def GetForegroundWindow():
return 0
def SetForegroundWindow(hwnd):
pass
class FocusManager(object):
def __init__(self):
self._shellWindow = GetForegroundWindow()
def __del__(self):
SetForegroundWindow(self._shellWindow)
| 798 | 23.96875 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_pdf.py | # -*- coding: utf-8 -*-
"""
A PDF matplotlib backend
Author: Jouni K Seppänen <[email protected]>
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six import unichr
import codecs
import collections
from datetime import datetime
from functools import total_ordering
from io import BytesIO
import logging
from math import ceil, cos, floor, pi, sin
import os
import re
import struct
import sys
import time
import warnings
import zlib
import numpy as np
from matplotlib import cbook, __version__, rcParams
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
RendererBase)
from matplotlib.backends.backend_mixed import MixedModeRenderer
from matplotlib.cbook import (Bunch, get_realpath_and_stat,
is_writable_file_like, maxdict)
from matplotlib.figure import Figure
from matplotlib.font_manager import findfont, is_opentype_cff_font, get_font
from matplotlib.afm import AFM
import matplotlib.type1font as type1font
import matplotlib.dviread as dviread
from matplotlib.ft2font import (FIXED_WIDTH, ITALIC, LOAD_NO_SCALE,
LOAD_NO_HINTING, KERNING_UNFITTED)
from matplotlib.mathtext import MathTextParser
from matplotlib.transforms import Affine2D, BboxBase
from matplotlib.path import Path
from matplotlib.dates import UTC
from matplotlib import _path
from matplotlib import _png
from matplotlib import ttconv
_log = logging.getLogger(__name__)
# Overview
#
# The low-level knowledge about pdf syntax lies mainly in the pdfRepr
# function and the classes Reference, Name, Operator, and Stream. The
# PdfFile class knows about the overall structure of pdf documents.
# It provides a "write" method for writing arbitrary strings in the
# file, and an "output" method that passes objects through the pdfRepr
# function before writing them in the file. The output method is
# called by the RendererPdf class, which contains the various draw_foo
# methods. RendererPdf contains a GraphicsContextPdf instance, and
# each draw_foo calls self.check_gc before outputting commands. This
# method checks whether the pdf graphics state needs to be modified
# and outputs the necessary commands. GraphicsContextPdf represents
# the graphics state, and its "delta" method returns the commands that
# modify the state.
# Add "pdf.use14corefonts: True" in your configuration file to use only
# the 14 PDF core fonts. These fonts do not need to be embedded; every
# PDF viewing application is required to have them. This results in very
# light PDF files you can use directly in LaTeX or ConTeXt documents
# generated with pdfTeX, without any conversion.
# These fonts are: Helvetica, Helvetica-Bold, Helvetica-Oblique,
# Helvetica-BoldOblique, Courier, Courier-Bold, Courier-Oblique,
# Courier-BoldOblique, Times-Roman, Times-Bold, Times-Italic,
# Times-BoldItalic, Symbol, ZapfDingbats.
#
# Some tricky points:
#
# 1. The clip path can only be widened by popping from the state
# stack. Thus the state must be pushed onto the stack before narrowing
# the clip path. This is taken care of by GraphicsContextPdf.
#
# 2. Sometimes it is necessary to refer to something (e.g., font,
# image, or extended graphics state, which contains the alpha value)
# in the page stream by a name that needs to be defined outside the
# stream. PdfFile provides the methods fontName, imageObject, and
# alphaState for this purpose. The implementations of these methods
# should perhaps be generalized.
# TODOs:
#
# * encoding of fonts, including mathtext fonts and unicode support
# * TTF support has lots of small TODOs, e.g., how do you know if a font
# is serif/sans-serif, or symbolic/non-symbolic?
# * draw_markers, draw_line_collection, etc.
def fill(strings, linelen=75):
"""Make one string from sequence of strings, with whitespace
in between. The whitespace is chosen to form lines of at most
linelen characters, if possible."""
currpos = 0
lasti = 0
result = []
for i, s in enumerate(strings):
length = len(s)
if currpos + length < linelen:
currpos += length + 1
else:
result.append(b' '.join(strings[lasti:i]))
lasti = i
currpos = length
result.append(b' '.join(strings[lasti:]))
return b'\n'.join(result)
# PDF strings are supposed to be able to include any eight-bit data,
# except that unbalanced parens and backslashes must be escaped by a
# backslash. However, sf bug #2708559 shows that the carriage return
# character may get read as a newline; these characters correspond to
# \gamma and \Omega in TeX's math font encoding. Escaping them fixes
# the bug.
_string_escape_regex = re.compile(br'([\\()\r\n])')
def _string_escape(match):
m = match.group(0)
if m in br'\()':
return b'\\' + m
elif m == b'\n':
return br'\n'
elif m == b'\r':
return br'\r'
assert False
def pdfRepr(obj):
"""Map Python objects to PDF syntax."""
# Some objects defined later have their own pdfRepr method.
if hasattr(obj, 'pdfRepr'):
return obj.pdfRepr()
# Floats. PDF does not have exponential notation (1.0e-10) so we
# need to use %f with some precision. Perhaps the precision
# should adapt to the magnitude of the number?
elif isinstance(obj, (float, np.floating)):
if not np.isfinite(obj):
raise ValueError("Can only output finite numbers in PDF")
r = ("%.10f" % obj).encode('ascii')
return r.rstrip(b'0').rstrip(b'.')
# Booleans. Needs to be tested before integers since
# isinstance(True, int) is true.
elif isinstance(obj, bool):
return [b'false', b'true'][obj]
# Integers are written as such.
elif isinstance(obj, (six.integer_types, np.integer)):
return ("%d" % obj).encode('ascii')
# Unicode strings are encoded in UTF-16BE with byte-order mark.
elif isinstance(obj, six.text_type):
try:
# But maybe it's really ASCII?
s = obj.encode('ASCII')
return pdfRepr(s)
except UnicodeEncodeError:
s = codecs.BOM_UTF16_BE + obj.encode('UTF-16BE')
return pdfRepr(s)
# Strings are written in parentheses, with backslashes and parens
# escaped. Actually balanced parens are allowed, but it is
# simpler to escape them all. TODO: cut long strings into lines;
# I believe there is some maximum line length in PDF.
elif isinstance(obj, bytes):
return b'(' + _string_escape_regex.sub(_string_escape, obj) + b')'
# Dictionaries. The keys must be PDF names, so if we find strings
# there, we make Name objects from them. The values may be
# anything, so the caller must ensure that PDF names are
# represented as Name objects.
elif isinstance(obj, dict):
r = [b"<<"]
r.extend([Name(key).pdfRepr() + b" " + pdfRepr(obj[key])
for key in sorted(obj)])
r.append(b">>")
return fill(r)
# Lists.
elif isinstance(obj, (list, tuple)):
r = [b"["]
r.extend([pdfRepr(val) for val in obj])
r.append(b"]")
return fill(r)
# The null keyword.
elif obj is None:
return b'null'
# A date.
elif isinstance(obj, datetime):
r = obj.strftime('D:%Y%m%d%H%M%S')
z = obj.utcoffset()
if z is not None:
z = z.seconds
else:
if time.daylight:
z = time.altzone
else:
z = time.timezone
if z == 0:
r += 'Z'
elif z < 0:
r += "+%02d'%02d'" % ((-z) // 3600, (-z) % 3600)
else:
r += "-%02d'%02d'" % (z // 3600, z % 3600)
return pdfRepr(r)
# A bounding box
elif isinstance(obj, BboxBase):
return fill([pdfRepr(val) for val in obj.bounds])
else:
raise TypeError("Don't know a PDF representation for {} objects"
.format(type(obj)))
class Reference(object):
"""PDF reference object.
Use PdfFile.reserveObject() to create References.
"""
def __init__(self, id):
self.id = id
def __repr__(self):
return "<Reference %d>" % self.id
def pdfRepr(self):
return ("%d 0 R" % self.id).encode('ascii')
def write(self, contents, file):
write = file.write
write(("%d 0 obj\n" % self.id).encode('ascii'))
write(pdfRepr(contents))
write(b"\nendobj\n")
@total_ordering
class Name(object):
"""PDF name object."""
__slots__ = ('name',)
_regex = re.compile(r'[^!-~]')
def __init__(self, name):
if isinstance(name, Name):
self.name = name.name
else:
if isinstance(name, bytes):
name = name.decode('ascii')
self.name = self._regex.sub(Name.hexify, name).encode('ascii')
def __repr__(self):
return "<Name %s>" % self.name
def __str__(self):
return '/' + six.text_type(self.name)
def __eq__(self, other):
return isinstance(other, Name) and self.name == other.name
def __lt__(self, other):
return isinstance(other, Name) and self.name < other.name
def __hash__(self):
return hash(self.name)
@staticmethod
def hexify(match):
return '#%02x' % ord(match.group())
def pdfRepr(self):
return b'/' + self.name
class Operator(object):
"""PDF operator object."""
__slots__ = ('op',)
def __init__(self, op):
self.op = op
def __repr__(self):
return '<Operator %s>' % self.op
def pdfRepr(self):
return self.op
class Verbatim(object):
"""Store verbatim PDF command content for later inclusion in the
stream."""
def __init__(self, x):
self._x = x
def pdfRepr(self):
return self._x
# PDF operators (not an exhaustive list)
_pdfops = dict(
close_fill_stroke=b'b', fill_stroke=b'B', fill=b'f', closepath=b'h',
close_stroke=b's', stroke=b'S', endpath=b'n', begin_text=b'BT',
end_text=b'ET', curveto=b'c', rectangle=b're', lineto=b'l', moveto=b'm',
concat_matrix=b'cm', use_xobject=b'Do', setgray_stroke=b'G',
setgray_nonstroke=b'g', setrgb_stroke=b'RG', setrgb_nonstroke=b'rg',
setcolorspace_stroke=b'CS', setcolorspace_nonstroke=b'cs',
setcolor_stroke=b'SCN', setcolor_nonstroke=b'scn', setdash=b'd',
setlinejoin=b'j', setlinecap=b'J', setgstate=b'gs', gsave=b'q',
grestore=b'Q', textpos=b'Td', selectfont=b'Tf', textmatrix=b'Tm',
show=b'Tj', showkern=b'TJ', setlinewidth=b'w', clip=b'W', shading=b'sh')
Op = Bunch(**{name: Operator(value) for name, value in six.iteritems(_pdfops)})
def _paint_path(fill, stroke):
"""Return the PDF operator to paint a path in the following way:
fill: fill the path with the fill color
stroke: stroke the outline of the path with the line color"""
if stroke:
if fill:
return Op.fill_stroke
else:
return Op.stroke
else:
if fill:
return Op.fill
else:
return Op.endpath
Op.paint_path = _paint_path
class Stream(object):
"""PDF stream object.
This has no pdfRepr method. Instead, call begin(), then output the
contents of the stream by calling write(), and finally call end().
"""
__slots__ = ('id', 'len', 'pdfFile', 'file', 'compressobj', 'extra', 'pos')
def __init__(self, id, len, file, extra=None, png=None):
"""id: object id of stream; len: an unused Reference object for the
length of the stream, or None (to use a memory buffer); file:
a PdfFile; extra: a dictionary of extra key-value pairs to
include in the stream header; png: if the data is already
png compressed, the decode parameters"""
self.id = id # object id
self.len = len # id of length object
self.pdfFile = file
self.file = file.fh # file to which the stream is written
self.compressobj = None # compression object
if extra is None:
self.extra = dict()
else:
self.extra = extra.copy()
if png is not None:
self.extra.update({'Filter': Name('FlateDecode'),
'DecodeParms': png})
self.pdfFile.recordXref(self.id)
if rcParams['pdf.compression'] and not png:
self.compressobj = zlib.compressobj(rcParams['pdf.compression'])
if self.len is None:
self.file = BytesIO()
else:
self._writeHeader()
self.pos = self.file.tell()
def _writeHeader(self):
write = self.file.write
write(("%d 0 obj\n" % self.id).encode('ascii'))
dict = self.extra
dict['Length'] = self.len
if rcParams['pdf.compression']:
dict['Filter'] = Name('FlateDecode')
write(pdfRepr(dict))
write(b"\nstream\n")
def end(self):
"""Finalize stream."""
self._flush()
if self.len is None:
contents = self.file.getvalue()
self.len = len(contents)
self.file = self.pdfFile.fh
self._writeHeader()
self.file.write(contents)
self.file.write(b"\nendstream\nendobj\n")
else:
length = self.file.tell() - self.pos
self.file.write(b"\nendstream\nendobj\n")
self.pdfFile.writeObject(self.len, length)
def write(self, data):
"""Write some data on the stream."""
if self.compressobj is None:
self.file.write(data)
else:
compressed = self.compressobj.compress(data)
self.file.write(compressed)
def _flush(self):
"""Flush the compression object."""
if self.compressobj is not None:
compressed = self.compressobj.flush()
self.file.write(compressed)
self.compressobj = None
class PdfFile(object):
"""PDF file object."""
def __init__(self, filename, metadata=None):
self.nextObject = 1 # next free object id
self.xrefTable = [[0, 65535, 'the zero object']]
self.passed_in_file_object = False
self.original_file_like = None
self.tell_base = 0
fh, opened = cbook.to_filehandle(filename, "wb", return_opened=True)
if not opened:
try:
self.tell_base = filename.tell()
except IOError:
fh = BytesIO()
self.original_file_like = filename
else:
fh = filename
self.passed_in_file_object = True
self._core14fontdir = os.path.join(
rcParams['datapath'], 'fonts', 'pdfcorefonts')
self.fh = fh
self.currentstream = None # stream object to write to, if any
fh.write(b"%PDF-1.4\n") # 1.4 is the first version to have alpha
# Output some eight-bit chars as a comment so various utilities
# recognize the file as binary by looking at the first few
# lines (see note in section 3.4.1 of the PDF reference).
fh.write(b"%\254\334 \253\272\n")
self.rootObject = self.reserveObject('root')
self.pagesObject = self.reserveObject('pages')
self.pageList = []
self.fontObject = self.reserveObject('fonts')
self.alphaStateObject = self.reserveObject('extended graphics states')
self.hatchObject = self.reserveObject('tiling patterns')
self.gouraudObject = self.reserveObject('Gouraud triangles')
self.XObjectObject = self.reserveObject('external objects')
self.resourceObject = self.reserveObject('resources')
root = {'Type': Name('Catalog'),
'Pages': self.pagesObject}
self.writeObject(self.rootObject, root)
# get source date from SOURCE_DATE_EPOCH, if set
# See https://reproducible-builds.org/specs/source-date-epoch/
source_date_epoch = os.getenv("SOURCE_DATE_EPOCH")
if source_date_epoch:
source_date = datetime.utcfromtimestamp(int(source_date_epoch))
source_date = source_date.replace(tzinfo=UTC)
else:
source_date = datetime.today()
self.infoDict = {
'Creator': 'matplotlib %s, http://matplotlib.org' % __version__,
'Producer': 'matplotlib pdf backend %s' % __version__,
'CreationDate': source_date
}
if metadata is not None:
self.infoDict.update(metadata)
self.infoDict = {k: v for (k, v) in self.infoDict.items()
if v is not None}
self.fontNames = {} # maps filenames to internal font names
self.nextFont = 1 # next free internal font name
self.dviFontInfo = {} # maps dvi font names to embedding information
self._texFontMap = None # maps TeX font names to PostScript fonts
# differently encoded Type-1 fonts may share the same descriptor
self.type1Descriptors = {}
self.used_characters = {}
self.alphaStates = {} # maps alpha values to graphics state objects
self.nextAlphaState = 1
# reproducible writeHatches needs an ordered dict:
self.hatchPatterns = collections.OrderedDict()
self.nextHatch = 1
self.gouraudTriangles = []
self._images = collections.OrderedDict() # reproducible writeImages
self.nextImage = 1
self.markers = collections.OrderedDict() # reproducible writeMarkers
self.multi_byte_charprocs = {}
self.paths = []
self.pageAnnotations = [] # A list of annotations for the
# current page
# The PDF spec recommends to include every procset
procsets = [Name(x)
for x in "PDF Text ImageB ImageC ImageI".split()]
# Write resource dictionary.
# Possibly TODO: more general ExtGState (graphics state dictionaries)
# ColorSpace Pattern Shading Properties
resources = {'Font': self.fontObject,
'XObject': self.XObjectObject,
'ExtGState': self.alphaStateObject,
'Pattern': self.hatchObject,
'Shading': self.gouraudObject,
'ProcSet': procsets}
self.writeObject(self.resourceObject, resources)
def newPage(self, width, height):
self.endStream()
self.width, self.height = width, height
contentObject = self.reserveObject('page contents')
thePage = {'Type': Name('Page'),
'Parent': self.pagesObject,
'Resources': self.resourceObject,
'MediaBox': [0, 0, 72 * width, 72 * height],
'Contents': contentObject,
'Group': {'Type': Name('Group'),
'S': Name('Transparency'),
'CS': Name('DeviceRGB')},
'Annots': self.pageAnnotations,
}
pageObject = self.reserveObject('page')
self.writeObject(pageObject, thePage)
self.pageList.append(pageObject)
self.beginStream(contentObject.id,
self.reserveObject('length of content stream'))
# Initialize the pdf graphics state to match the default mpl
# graphics context: currently only the join style needs to be set
self.output(GraphicsContextPdf.joinstyles['round'], Op.setlinejoin)
# Clear the list of annotations for the next page
self.pageAnnotations = []
def newTextnote(self, text, positionRect=[-100, -100, 0, 0]):
# Create a new annotation of type text
theNote = {'Type': Name('Annot'),
'Subtype': Name('Text'),
'Contents': text,
'Rect': positionRect,
}
annotObject = self.reserveObject('annotation')
self.writeObject(annotObject, theNote)
self.pageAnnotations.append(annotObject)
def finalize(self):
"Write out the various deferred objects and the pdf end matter."
self.endStream()
self.writeFonts()
self.writeObject(
self.alphaStateObject,
{val[0]: val[1] for val in six.itervalues(self.alphaStates)})
self.writeHatches()
self.writeGouraudTriangles()
xobjects = {
name: ob for image, name, ob in six.itervalues(self._images)}
for tup in six.itervalues(self.markers):
xobjects[tup[0]] = tup[1]
for name, value in six.iteritems(self.multi_byte_charprocs):
xobjects[name] = value
for name, path, trans, ob, join, cap, padding, filled, stroked \
in self.paths:
xobjects[name] = ob
self.writeObject(self.XObjectObject, xobjects)
self.writeImages()
self.writeMarkers()
self.writePathCollectionTemplates()
self.writeObject(self.pagesObject,
{'Type': Name('Pages'),
'Kids': self.pageList,
'Count': len(self.pageList)})
self.writeInfoDict()
# Finalize the file
self.writeXref()
self.writeTrailer()
def close(self):
"Flush all buffers and free all resources."
self.endStream()
if self.passed_in_file_object:
self.fh.flush()
else:
if self.original_file_like is not None:
self.original_file_like.write(self.fh.getvalue())
self.fh.close()
def write(self, data):
if self.currentstream is None:
self.fh.write(data)
else:
self.currentstream.write(data)
def output(self, *data):
self.write(fill([pdfRepr(x) for x in data]))
self.write(b'\n')
def beginStream(self, id, len, extra=None, png=None):
assert self.currentstream is None
self.currentstream = Stream(id, len, self, extra, png)
def endStream(self):
if self.currentstream is not None:
self.currentstream.end()
self.currentstream = None
def fontName(self, fontprop):
"""
Select a font based on fontprop and return a name suitable for
Op.selectfont. If fontprop is a string, it will be interpreted
as the filename of the font.
"""
if isinstance(fontprop, six.string_types):
filename = fontprop
elif rcParams['pdf.use14corefonts']:
filename = findfont(
fontprop, fontext='afm', directory=self._core14fontdir)
if filename is None:
filename = findfont(
"Helvetica", fontext='afm', directory=self._core14fontdir)
else:
filename = findfont(fontprop)
Fx = self.fontNames.get(filename)
if Fx is None:
Fx = Name('F%d' % self.nextFont)
self.fontNames[filename] = Fx
self.nextFont += 1
_log.debug('Assigning font %s = %r', Fx, filename)
return Fx
@property
def texFontMap(self):
# lazy-load texFontMap, it takes a while to parse
# and usetex is a relatively rare use case
if self._texFontMap is None:
self._texFontMap = dviread.PsfontsMap(
dviread.find_tex_file('pdftex.map'))
return self._texFontMap
def dviFontName(self, dvifont):
"""
Given a dvi font object, return a name suitable for Op.selectfont.
This registers the font information in self.dviFontInfo if not yet
registered.
"""
dvi_info = self.dviFontInfo.get(dvifont.texname)
if dvi_info is not None:
return dvi_info.pdfname
psfont = self.texFontMap[dvifont.texname]
if psfont.filename is None:
raise ValueError(
"No usable font file found for {} (TeX: {}); "
"the font may lack a Type-1 version"
.format(psfont.psname, dvifont.texname))
pdfname = Name('F%d' % self.nextFont)
self.nextFont += 1
_log.debug('Assigning font %s = %s (dvi)', pdfname, dvifont.texname)
self.dviFontInfo[dvifont.texname] = Bunch(
dvifont=dvifont,
pdfname=pdfname,
fontfile=psfont.filename,
basefont=psfont.psname,
encodingfile=psfont.encoding,
effects=psfont.effects)
return pdfname
def writeFonts(self):
fonts = {}
for dviname, info in sorted(self.dviFontInfo.items()):
Fx = info.pdfname
_log.debug('Embedding Type-1 font %s from dvi.', dviname)
fonts[Fx] = self._embedTeXFont(info)
for filename in sorted(self.fontNames):
Fx = self.fontNames[filename]
_log.debug('Embedding font %s.', filename)
if filename.endswith('.afm'):
# from pdf.use14corefonts
_log.debug('Writing AFM font.')
fonts[Fx] = self._write_afm_font(filename)
else:
# a normal TrueType font
_log.debug('Writing TrueType font.')
realpath, stat_key = get_realpath_and_stat(filename)
chars = self.used_characters.get(stat_key)
if chars is not None and len(chars[1]):
fonts[Fx] = self.embedTTF(realpath, chars[1])
self.writeObject(self.fontObject, fonts)
def _write_afm_font(self, filename):
with open(filename, 'rb') as fh:
font = AFM(fh)
fontname = font.get_fontname()
fontdict = {'Type': Name('Font'),
'Subtype': Name('Type1'),
'BaseFont': Name(fontname),
'Encoding': Name('WinAnsiEncoding')}
fontdictObject = self.reserveObject('font dictionary')
self.writeObject(fontdictObject, fontdict)
return fontdictObject
def _embedTeXFont(self, fontinfo):
_log.debug('Embedding TeX font %s - fontinfo=%s',
fontinfo.dvifont.texname, fontinfo.__dict__)
# Widths
widthsObject = self.reserveObject('font widths')
self.writeObject(widthsObject, fontinfo.dvifont.widths)
# Font dictionary
fontdictObject = self.reserveObject('font dictionary')
fontdict = {
'Type': Name('Font'),
'Subtype': Name('Type1'),
'FirstChar': 0,
'LastChar': len(fontinfo.dvifont.widths) - 1,
'Widths': widthsObject,
}
# Encoding (if needed)
if fontinfo.encodingfile is not None:
enc = dviread.Encoding(fontinfo.encodingfile)
differencesArray = [Name(ch) for ch in enc]
differencesArray = [0] + differencesArray
fontdict['Encoding'] = \
{'Type': Name('Encoding'),
'Differences': differencesArray}
# If no file is specified, stop short
if fontinfo.fontfile is None:
_log.warning(
"Because of TeX configuration (pdftex.map, see updmap option "
"pdftexDownloadBase14) the font %s is not embedded. This is "
"deprecated as of PDF 1.5 and it may cause the consumer "
"application to show something that was not intended.",
fontinfo.basefont)
fontdict['BaseFont'] = Name(fontinfo.basefont)
self.writeObject(fontdictObject, fontdict)
return fontdictObject
# We have a font file to embed - read it in and apply any effects
t1font = type1font.Type1Font(fontinfo.fontfile)
if fontinfo.effects:
t1font = t1font.transform(fontinfo.effects)
fontdict['BaseFont'] = Name(t1font.prop['FontName'])
# Font descriptors may be shared between differently encoded
# Type-1 fonts, so only create a new descriptor if there is no
# existing descriptor for this font.
effects = (fontinfo.effects.get('slant', 0.0),
fontinfo.effects.get('extend', 1.0))
fontdesc = self.type1Descriptors.get((fontinfo.fontfile, effects))
if fontdesc is None:
fontdesc = self.createType1Descriptor(t1font, fontinfo.fontfile)
self.type1Descriptors[(fontinfo.fontfile, effects)] = fontdesc
fontdict['FontDescriptor'] = fontdesc
self.writeObject(fontdictObject, fontdict)
return fontdictObject
def createType1Descriptor(self, t1font, fontfile):
# Create and write the font descriptor and the font file
# of a Type-1 font
fontdescObject = self.reserveObject('font descriptor')
fontfileObject = self.reserveObject('font file')
italic_angle = t1font.prop['ItalicAngle']
fixed_pitch = t1font.prop['isFixedPitch']
flags = 0
# fixed width
if fixed_pitch:
flags |= 1 << 0
# TODO: serif
if 0:
flags |= 1 << 1
# TODO: symbolic (most TeX fonts are)
if 1:
flags |= 1 << 2
# non-symbolic
else:
flags |= 1 << 5
# italic
if italic_angle:
flags |= 1 << 6
# TODO: all caps
if 0:
flags |= 1 << 16
# TODO: small caps
if 0:
flags |= 1 << 17
# TODO: force bold
if 0:
flags |= 1 << 18
ft2font = get_font(fontfile)
descriptor = {
'Type': Name('FontDescriptor'),
'FontName': Name(t1font.prop['FontName']),
'Flags': flags,
'FontBBox': ft2font.bbox,
'ItalicAngle': italic_angle,
'Ascent': ft2font.ascender,
'Descent': ft2font.descender,
'CapHeight': 1000, # TODO: find this out
'XHeight': 500, # TODO: this one too
'FontFile': fontfileObject,
'FontFamily': t1font.prop['FamilyName'],
'StemV': 50, # TODO
# (see also revision 3874; but not all TeX distros have AFM files!)
# 'FontWeight': a number where 400 = Regular, 700 = Bold
}
self.writeObject(fontdescObject, descriptor)
self.beginStream(fontfileObject.id, None,
{'Length1': len(t1font.parts[0]),
'Length2': len(t1font.parts[1]),
'Length3': 0})
self.currentstream.write(t1font.parts[0])
self.currentstream.write(t1font.parts[1])
self.endStream()
return fontdescObject
def _get_xobject_symbol_name(self, filename, symbol_name):
return "%s-%s" % (
os.path.splitext(os.path.basename(filename))[0],
symbol_name)
_identityToUnicodeCMap = """/CIDInit /ProcSet findresource begin
12 dict begin
begincmap
/CIDSystemInfo
<< /Registry (Adobe)
/Ordering (UCS)
/Supplement 0
>> def
/CMapName /Adobe-Identity-UCS def
/CMapType 2 def
1 begincodespacerange
<0000> <ffff>
endcodespacerange
%d beginbfrange
%s
endbfrange
endcmap
CMapName currentdict /CMap defineresource pop
end
end"""
def embedTTF(self, filename, characters):
"""Embed the TTF font from the named file into the document."""
font = get_font(filename)
fonttype = rcParams['pdf.fonttype']
def cvt(length, upe=font.units_per_EM, nearest=True):
"Convert font coordinates to PDF glyph coordinates"
value = length / upe * 1000
if nearest:
return np.round(value)
# Perhaps best to round away from zero for bounding
# boxes and the like
if value < 0:
return floor(value)
else:
return ceil(value)
def embedTTFType3(font, characters, descriptor):
"""The Type 3-specific part of embedding a Truetype font"""
widthsObject = self.reserveObject('font widths')
fontdescObject = self.reserveObject('font descriptor')
fontdictObject = self.reserveObject('font dictionary')
charprocsObject = self.reserveObject('character procs')
differencesArray = []
firstchar, lastchar = 0, 255
bbox = [cvt(x, nearest=False) for x in font.bbox]
fontdict = {
'Type': Name('Font'),
'BaseFont': ps_name,
'FirstChar': firstchar,
'LastChar': lastchar,
'FontDescriptor': fontdescObject,
'Subtype': Name('Type3'),
'Name': descriptor['FontName'],
'FontBBox': bbox,
'FontMatrix': [.001, 0, 0, .001, 0, 0],
'CharProcs': charprocsObject,
'Encoding': {
'Type': Name('Encoding'),
'Differences': differencesArray},
'Widths': widthsObject
}
# Make the "Widths" array
from encodings import cp1252
# The "decoding_map" was changed
# to a "decoding_table" as of Python 2.5.
if hasattr(cp1252, 'decoding_map'):
def decode_char(charcode):
return cp1252.decoding_map[charcode] or 0
else:
def decode_char(charcode):
return ord(cp1252.decoding_table[charcode])
def get_char_width(charcode):
s = decode_char(charcode)
width = font.load_char(
s, flags=LOAD_NO_SCALE | LOAD_NO_HINTING).horiAdvance
return cvt(width)
widths = [get_char_width(charcode)
for charcode in range(firstchar, lastchar+1)]
descriptor['MaxWidth'] = max(widths)
# Make the "Differences" array, sort the ccodes < 255 from
# the multi-byte ccodes, and build the whole set of glyph ids
# that we need from this font.
glyph_ids = []
differences = []
multi_byte_chars = set()
for c in characters:
ccode = c
gind = font.get_char_index(ccode)
glyph_ids.append(gind)
glyph_name = font.get_glyph_name(gind)
if ccode <= 255:
differences.append((ccode, glyph_name))
else:
multi_byte_chars.add(glyph_name)
differences.sort()
last_c = -2
for c, name in differences:
if c != last_c + 1:
differencesArray.append(c)
differencesArray.append(Name(name))
last_c = c
# Make the charprocs array (using ttconv to generate the
# actual outlines)
rawcharprocs = ttconv.get_pdf_charprocs(
filename.encode(sys.getfilesystemencoding()), glyph_ids)
charprocs = {}
for charname in sorted(rawcharprocs):
stream = rawcharprocs[charname]
charprocDict = {'Length': len(stream)}
# The 2-byte characters are used as XObjects, so they
# need extra info in their dictionary
if charname in multi_byte_chars:
charprocDict['Type'] = Name('XObject')
charprocDict['Subtype'] = Name('Form')
charprocDict['BBox'] = bbox
# Each glyph includes bounding box information,
# but xpdf and ghostscript can't handle it in a
# Form XObject (they segfault!!!), so we remove it
# from the stream here. It's not needed anyway,
# since the Form XObject includes it in its BBox
# value.
stream = stream[stream.find(b"d1") + 2:]
charprocObject = self.reserveObject('charProc')
self.beginStream(charprocObject.id, None, charprocDict)
self.currentstream.write(stream)
self.endStream()
# Send the glyphs with ccode > 255 to the XObject dictionary,
# and the others to the font itself
if charname in multi_byte_chars:
name = self._get_xobject_symbol_name(filename, charname)
self.multi_byte_charprocs[name] = charprocObject
else:
charprocs[charname] = charprocObject
# Write everything out
self.writeObject(fontdictObject, fontdict)
self.writeObject(fontdescObject, descriptor)
self.writeObject(widthsObject, widths)
self.writeObject(charprocsObject, charprocs)
return fontdictObject
def embedTTFType42(font, characters, descriptor):
"""The Type 42-specific part of embedding a Truetype font"""
fontdescObject = self.reserveObject('font descriptor')
cidFontDictObject = self.reserveObject('CID font dictionary')
type0FontDictObject = self.reserveObject('Type 0 font dictionary')
cidToGidMapObject = self.reserveObject('CIDToGIDMap stream')
fontfileObject = self.reserveObject('font file stream')
wObject = self.reserveObject('Type 0 widths')
toUnicodeMapObject = self.reserveObject('ToUnicode map')
cidFontDict = {
'Type': Name('Font'),
'Subtype': Name('CIDFontType2'),
'BaseFont': ps_name,
'CIDSystemInfo': {
'Registry': 'Adobe',
'Ordering': 'Identity',
'Supplement': 0},
'FontDescriptor': fontdescObject,
'W': wObject,
'CIDToGIDMap': cidToGidMapObject
}
type0FontDict = {
'Type': Name('Font'),
'Subtype': Name('Type0'),
'BaseFont': ps_name,
'Encoding': Name('Identity-H'),
'DescendantFonts': [cidFontDictObject],
'ToUnicode': toUnicodeMapObject
}
# Make fontfile stream
descriptor['FontFile2'] = fontfileObject
length1Object = self.reserveObject('decoded length of a font')
self.beginStream(
fontfileObject.id,
self.reserveObject('length of font stream'),
{'Length1': length1Object})
with open(filename, 'rb') as fontfile:
length1 = 0
while True:
data = fontfile.read(4096)
if not data:
break
length1 += len(data)
self.currentstream.write(data)
self.endStream()
self.writeObject(length1Object, length1)
# Make the 'W' (Widths) array, CidToGidMap and ToUnicode CMap
# at the same time
cid_to_gid_map = ['\0'] * 65536
widths = []
max_ccode = 0
for c in characters:
ccode = c
gind = font.get_char_index(ccode)
glyph = font.load_char(ccode,
flags=LOAD_NO_SCALE | LOAD_NO_HINTING)
widths.append((ccode, cvt(glyph.horiAdvance)))
if ccode < 65536:
cid_to_gid_map[ccode] = unichr(gind)
max_ccode = max(ccode, max_ccode)
widths.sort()
cid_to_gid_map = cid_to_gid_map[:max_ccode + 1]
last_ccode = -2
w = []
max_width = 0
unicode_groups = []
for ccode, width in widths:
if ccode != last_ccode + 1:
w.append(ccode)
w.append([width])
unicode_groups.append([ccode, ccode])
else:
w[-1].append(width)
unicode_groups[-1][1] = ccode
max_width = max(max_width, width)
last_ccode = ccode
unicode_bfrange = []
for start, end in unicode_groups:
unicode_bfrange.append(
"<%04x> <%04x> [%s]" %
(start, end,
" ".join(["<%04x>" % x for x in range(start, end+1)])))
unicode_cmap = (self._identityToUnicodeCMap %
(len(unicode_groups),
"\n".join(unicode_bfrange))).encode('ascii')
# CIDToGIDMap stream
cid_to_gid_map = "".join(cid_to_gid_map).encode("utf-16be")
self.beginStream(cidToGidMapObject.id,
None,
{'Length': len(cid_to_gid_map)})
self.currentstream.write(cid_to_gid_map)
self.endStream()
# ToUnicode CMap
self.beginStream(toUnicodeMapObject.id,
None,
{'Length': unicode_cmap})
self.currentstream.write(unicode_cmap)
self.endStream()
descriptor['MaxWidth'] = max_width
# Write everything out
self.writeObject(cidFontDictObject, cidFontDict)
self.writeObject(type0FontDictObject, type0FontDict)
self.writeObject(fontdescObject, descriptor)
self.writeObject(wObject, w)
return type0FontDictObject
# Beginning of main embedTTF function...
# You are lost in a maze of TrueType tables, all different...
sfnt = font.get_sfnt()
try:
ps_name = sfnt[1, 0, 0, 6].decode('mac_roman') # Macintosh scheme
except KeyError:
# Microsoft scheme:
ps_name = sfnt[3, 1, 0x0409, 6].decode('utf-16be')
# (see freetype/ttnameid.h)
ps_name = ps_name.encode('ascii', 'replace')
ps_name = Name(ps_name)
pclt = font.get_sfnt_table('pclt') or {'capHeight': 0, 'xHeight': 0}
post = font.get_sfnt_table('post') or {'italicAngle': (0, 0)}
ff = font.face_flags
sf = font.style_flags
flags = 0
symbolic = False # ps_name.name in ('Cmsy10', 'Cmmi10', 'Cmex10')
if ff & FIXED_WIDTH:
flags |= 1 << 0
if 0: # TODO: serif
flags |= 1 << 1
if symbolic:
flags |= 1 << 2
else:
flags |= 1 << 5
if sf & ITALIC:
flags |= 1 << 6
if 0: # TODO: all caps
flags |= 1 << 16
if 0: # TODO: small caps
flags |= 1 << 17
if 0: # TODO: force bold
flags |= 1 << 18
descriptor = {
'Type': Name('FontDescriptor'),
'FontName': ps_name,
'Flags': flags,
'FontBBox': [cvt(x, nearest=False) for x in font.bbox],
'Ascent': cvt(font.ascender, nearest=False),
'Descent': cvt(font.descender, nearest=False),
'CapHeight': cvt(pclt['capHeight'], nearest=False),
'XHeight': cvt(pclt['xHeight']),
'ItalicAngle': post['italicAngle'][1], # ???
'StemV': 0 # ???
}
# The font subsetting to a Type 3 font does not work for
# OpenType (.otf) that embed a Postscript CFF font, so avoid that --
# save as a (non-subsetted) Type 42 font instead.
if is_opentype_cff_font(filename):
fonttype = 42
_log.warning("%r can not be subsetted into a Type 3 font. The "
"entire font will be embedded in the output.",
os.path.basename(filename))
if fonttype == 3:
return embedTTFType3(font, characters, descriptor)
elif fonttype == 42:
return embedTTFType42(font, characters, descriptor)
def alphaState(self, alpha):
"""Return name of an ExtGState that sets alpha to the given value."""
state = self.alphaStates.get(alpha, None)
if state is not None:
return state[0]
name = Name('A%d' % self.nextAlphaState)
self.nextAlphaState += 1
self.alphaStates[alpha] = \
(name, {'Type': Name('ExtGState'),
'CA': alpha[0], 'ca': alpha[1]})
return name
def hatchPattern(self, hatch_style):
# The colors may come in as numpy arrays, which aren't hashable
if hatch_style is not None:
edge, face, hatch = hatch_style
if edge is not None:
edge = tuple(edge)
if face is not None:
face = tuple(face)
hatch_style = (edge, face, hatch)
pattern = self.hatchPatterns.get(hatch_style, None)
if pattern is not None:
return pattern
name = Name('H%d' % self.nextHatch)
self.nextHatch += 1
self.hatchPatterns[hatch_style] = name
return name
def writeHatches(self):
hatchDict = dict()
sidelen = 72.0
for hatch_style, name in six.iteritems(self.hatchPatterns):
ob = self.reserveObject('hatch pattern')
hatchDict[name] = ob
res = {'Procsets':
[Name(x) for x in "PDF Text ImageB ImageC ImageI".split()]}
self.beginStream(
ob.id, None,
{'Type': Name('Pattern'),
'PatternType': 1, 'PaintType': 1, 'TilingType': 1,
'BBox': [0, 0, sidelen, sidelen],
'XStep': sidelen, 'YStep': sidelen,
'Resources': res,
# Change origin to match Agg at top-left.
'Matrix': [1, 0, 0, 1, 0, self.height * 72]})
stroke_rgb, fill_rgb, path = hatch_style
self.output(stroke_rgb[0], stroke_rgb[1], stroke_rgb[2],
Op.setrgb_stroke)
if fill_rgb is not None:
self.output(fill_rgb[0], fill_rgb[1], fill_rgb[2],
Op.setrgb_nonstroke,
0, 0, sidelen, sidelen, Op.rectangle,
Op.fill)
self.output(rcParams['hatch.linewidth'], Op.setlinewidth)
self.output(*self.pathOperations(
Path.hatch(path),
Affine2D().scale(sidelen),
simplify=False))
self.output(Op.fill_stroke)
self.endStream()
self.writeObject(self.hatchObject, hatchDict)
def addGouraudTriangles(self, points, colors):
name = Name('GT%d' % len(self.gouraudTriangles))
self.gouraudTriangles.append((name, points, colors))
return name
def writeGouraudTriangles(self):
gouraudDict = dict()
for name, points, colors in self.gouraudTriangles:
ob = self.reserveObject('Gouraud triangle')
gouraudDict[name] = ob
shape = points.shape
flat_points = points.reshape((shape[0] * shape[1], 2))
flat_colors = colors.reshape((shape[0] * shape[1], 4))
points_min = np.min(flat_points, axis=0) - (1 << 8)
points_max = np.max(flat_points, axis=0) + (1 << 8)
factor = 0xffffffff / (points_max - points_min)
self.beginStream(
ob.id, None,
{'ShadingType': 4,
'BitsPerCoordinate': 32,
'BitsPerComponent': 8,
'BitsPerFlag': 8,
'ColorSpace': Name('DeviceRGB'),
'AntiAlias': True,
'Decode': [points_min[0], points_max[0],
points_min[1], points_max[1],
0, 1, 0, 1, 0, 1]
})
streamarr = np.empty(
(shape[0] * shape[1],),
dtype=[(str('flags'), str('u1')),
(str('points'), str('>u4'), (2,)),
(str('colors'), str('u1'), (3,))])
streamarr['flags'] = 0
streamarr['points'] = (flat_points - points_min) * factor
streamarr['colors'] = flat_colors[:, :3] * 255.0
self.write(streamarr.tostring())
self.endStream()
self.writeObject(self.gouraudObject, gouraudDict)
def imageObject(self, image):
"""Return name of an image XObject representing the given image."""
entry = self._images.get(id(image), None)
if entry is not None:
return entry[1]
name = Name('I%d' % self.nextImage)
ob = self.reserveObject('image %d' % self.nextImage)
self.nextImage += 1
self._images[id(image)] = (image, name, ob)
return name
def _unpack(self, im):
"""
Unpack the image object im into height, width, data, alpha,
where data and alpha are HxWx3 (RGB) or HxWx1 (grayscale or alpha)
arrays, except alpha is None if the image is fully opaque.
"""
h, w = im.shape[:2]
im = im[::-1]
if im.ndim == 2:
return h, w, im, None
else:
rgb = im[:, :, :3]
rgb = np.array(rgb, order='C')
# PDF needs a separate alpha image
if im.shape[2] == 4:
alpha = im[:, :, 3][..., None]
if np.all(alpha == 255):
alpha = None
else:
alpha = np.array(alpha, order='C')
else:
alpha = None
return h, w, rgb, alpha
def _writePng(self, data):
"""
Write the image *data* into the pdf file using png
predictors with Flate compression.
"""
buffer = BytesIO()
_png.write_png(data, buffer)
buffer.seek(8)
written = 0
header = bytearray(8)
while True:
n = buffer.readinto(header)
assert n == 8
length, type = struct.unpack(b'!L4s', bytes(header))
if type == b'IDAT':
data = bytearray(length)
n = buffer.readinto(data)
assert n == length
self.currentstream.write(bytes(data))
written += n
elif type == b'IEND':
break
else:
buffer.seek(length, 1)
buffer.seek(4, 1) # skip CRC
def _writeImg(self, data, height, width, grayscale, id, smask=None):
"""
Write the image *data* of size *height* x *width*, as grayscale
if *grayscale* is true and RGB otherwise, as pdf object *id*
and with the soft mask (alpha channel) *smask*, which should be
either None or a *height* x *width* x 1 array.
"""
obj = {'Type': Name('XObject'),
'Subtype': Name('Image'),
'Width': width,
'Height': height,
'ColorSpace': Name('DeviceGray' if grayscale
else 'DeviceRGB'),
'BitsPerComponent': 8}
if smask:
obj['SMask'] = smask
if rcParams['pdf.compression']:
png = {'Predictor': 10,
'Colors': 1 if grayscale else 3,
'Columns': width}
else:
png = None
self.beginStream(
id,
self.reserveObject('length of image stream'),
obj,
png=png
)
if png:
self._writePng(data)
else:
self.currentstream.write(data.tostring())
self.endStream()
def writeImages(self):
for img, name, ob in six.itervalues(self._images):
height, width, data, adata = self._unpack(img)
if adata is not None:
smaskObject = self.reserveObject("smask")
self._writeImg(adata, height, width, True, smaskObject.id)
else:
smaskObject = None
self._writeImg(data, height, width, False,
ob.id, smaskObject)
def markerObject(self, path, trans, fill, stroke, lw, joinstyle,
capstyle):
"""Return name of a marker XObject representing the given path."""
# self.markers used by markerObject, writeMarkers, close:
# mapping from (path operations, fill?, stroke?) to
# [name, object reference, bounding box, linewidth]
# This enables different draw_markers calls to share the XObject
# if the gc is sufficiently similar: colors etc can vary, but
# the choices of whether to fill and whether to stroke cannot.
# We need a bounding box enclosing all of the XObject path,
# but since line width may vary, we store the maximum of all
# occurring line widths in self.markers.
# close() is somewhat tightly coupled in that it expects the
# first two components of each value in self.markers to be the
# name and object reference.
pathops = self.pathOperations(path, trans, simplify=False)
key = (tuple(pathops), bool(fill), bool(stroke), joinstyle, capstyle)
result = self.markers.get(key)
if result is None:
name = Name('M%d' % len(self.markers))
ob = self.reserveObject('marker %d' % len(self.markers))
bbox = path.get_extents(trans)
self.markers[key] = [name, ob, bbox, lw]
else:
if result[-1] < lw:
result[-1] = lw
name = result[0]
return name
def writeMarkers(self):
for ((pathops, fill, stroke, joinstyle, capstyle),
(name, ob, bbox, lw)) in six.iteritems(self.markers):
bbox = bbox.padded(lw * 0.5)
self.beginStream(
ob.id, None,
{'Type': Name('XObject'), 'Subtype': Name('Form'),
'BBox': list(bbox.extents)})
self.output(GraphicsContextPdf.joinstyles[joinstyle],
Op.setlinejoin)
self.output(GraphicsContextPdf.capstyles[capstyle], Op.setlinecap)
self.output(*pathops)
self.output(Op.paint_path(fill, stroke))
self.endStream()
def pathCollectionObject(self, gc, path, trans, padding, filled, stroked):
name = Name('P%d' % len(self.paths))
ob = self.reserveObject('path %d' % len(self.paths))
self.paths.append(
(name, path, trans, ob, gc.get_joinstyle(), gc.get_capstyle(),
padding, filled, stroked))
return name
def writePathCollectionTemplates(self):
for (name, path, trans, ob, joinstyle, capstyle, padding, filled,
stroked) in self.paths:
pathops = self.pathOperations(path, trans, simplify=False)
bbox = path.get_extents(trans)
if not np.all(np.isfinite(bbox.extents)):
extents = [0, 0, 0, 0]
else:
bbox = bbox.padded(padding)
extents = list(bbox.extents)
self.beginStream(
ob.id, None,
{'Type': Name('XObject'), 'Subtype': Name('Form'),
'BBox': extents})
self.output(GraphicsContextPdf.joinstyles[joinstyle],
Op.setlinejoin)
self.output(GraphicsContextPdf.capstyles[capstyle], Op.setlinecap)
self.output(*pathops)
self.output(Op.paint_path(filled, stroked))
self.endStream()
@staticmethod
def pathOperations(path, transform, clip=None, simplify=None, sketch=None):
return [Verbatim(_path.convert_to_string(
path, transform, clip, simplify, sketch,
6,
[Op.moveto.op, Op.lineto.op, b'', Op.curveto.op, Op.closepath.op],
True))]
def writePath(self, path, transform, clip=False, sketch=None):
if clip:
clip = (0.0, 0.0, self.width * 72, self.height * 72)
simplify = path.should_simplify
else:
clip = None
simplify = False
cmds = self.pathOperations(path, transform, clip, simplify=simplify,
sketch=sketch)
self.output(*cmds)
def reserveObject(self, name=''):
"""Reserve an ID for an indirect object.
The name is used for debugging in case we forget to print out
the object with writeObject.
"""
id = self.nextObject
self.nextObject += 1
self.xrefTable.append([None, 0, name])
return Reference(id)
def recordXref(self, id):
self.xrefTable[id][0] = self.fh.tell() - self.tell_base
def writeObject(self, object, contents):
self.recordXref(object.id)
object.write(contents, self)
def writeXref(self):
"""Write out the xref table."""
self.startxref = self.fh.tell() - self.tell_base
self.write(("xref\n0 %d\n" % self.nextObject).encode('ascii'))
i = 0
borken = False
for offset, generation, name in self.xrefTable:
if offset is None:
print('No offset for object %d (%s)' % (i, name),
file=sys.stderr)
borken = True
else:
if name == 'the zero object':
key = "f"
else:
key = "n"
text = "%010d %05d %s \n" % (offset, generation, key)
self.write(text.encode('ascii'))
i += 1
if borken:
raise AssertionError('Indirect object does not exist')
def writeInfoDict(self):
"""Write out the info dictionary, checking it for good form"""
def is_string_like(x):
return isinstance(x, six.string_types)
def is_date(x):
return isinstance(x, datetime)
check_trapped = (lambda x: isinstance(x, Name) and
x.name in ('True', 'False', 'Unknown'))
keywords = {'Title': is_string_like,
'Author': is_string_like,
'Subject': is_string_like,
'Keywords': is_string_like,
'Creator': is_string_like,
'Producer': is_string_like,
'CreationDate': is_date,
'ModDate': is_date,
'Trapped': check_trapped}
for k in self.infoDict:
if k not in keywords:
warnings.warn('Unknown infodict keyword: %s' % k)
else:
if not keywords[k](self.infoDict[k]):
warnings.warn('Bad value for infodict keyword %s' % k)
self.infoObject = self.reserveObject('info')
self.writeObject(self.infoObject, self.infoDict)
def writeTrailer(self):
"""Write out the PDF trailer."""
self.write(b"trailer\n")
self.write(pdfRepr(
{'Size': self.nextObject,
'Root': self.rootObject,
'Info': self.infoObject}))
# Could add 'ID'
self.write(("\nstartxref\n%d\n%%%%EOF\n" %
self.startxref).encode('ascii'))
class RendererPdf(RendererBase):
afm_font_cache = maxdict(50)
def __init__(self, file, image_dpi, height, width):
RendererBase.__init__(self)
self.height = height
self.width = width
self.file = file
self.gc = self.new_gc()
self.mathtext_parser = MathTextParser("Pdf")
self.image_dpi = image_dpi
def finalize(self):
self.file.output(*self.gc.finalize())
def check_gc(self, gc, fillcolor=None):
orig_fill = getattr(gc, '_fillcolor', (0., 0., 0.))
gc._fillcolor = fillcolor
orig_alphas = getattr(gc, '_effective_alphas', (1.0, 1.0))
if gc.get_rgb() is None:
# it should not matter what color here
# since linewidth should be 0
# unless affected by global settings in rcParams
# hence setting zero alpha just incase
gc.set_foreground((0, 0, 0, 0), isRGBA=True)
if gc._forced_alpha:
gc._effective_alphas = (gc._alpha, gc._alpha)
elif fillcolor is None or len(fillcolor) < 4:
gc._effective_alphas = (gc._rgb[3], 1.0)
else:
gc._effective_alphas = (gc._rgb[3], fillcolor[3])
delta = self.gc.delta(gc)
if delta:
self.file.output(*delta)
# Restore gc to avoid unwanted side effects
gc._fillcolor = orig_fill
gc._effective_alphas = orig_alphas
def track_characters(self, font, s):
"""Keeps track of which characters are required from
each font."""
if isinstance(font, six.string_types):
fname = font
else:
fname = font.fname
realpath, stat_key = get_realpath_and_stat(fname)
used_characters = self.file.used_characters.setdefault(
stat_key, (realpath, set()))
used_characters[1].update([ord(x) for x in s])
def merge_used_characters(self, other):
for stat_key, (realpath, charset) in six.iteritems(other):
used_characters = self.file.used_characters.setdefault(
stat_key, (realpath, set()))
used_characters[1].update(charset)
def get_image_magnification(self):
return self.image_dpi/72.0
def option_scale_image(self):
"""
pdf backend support arbitrary scaling of image.
"""
return True
def option_image_nocomposite(self):
"""
return whether to generate a composite image from multiple images on
a set of axes
"""
return not rcParams['image.composite_image']
def draw_image(self, gc, x, y, im, transform=None):
h, w = im.shape[:2]
if w == 0 or h == 0:
return
if transform is None:
# If there's no transform, alpha has already been applied
gc.set_alpha(1.0)
self.check_gc(gc)
w = 72.0 * w / self.image_dpi
h = 72.0 * h / self.image_dpi
imob = self.file.imageObject(im)
if transform is None:
self.file.output(Op.gsave,
w, 0, 0, h, x, y, Op.concat_matrix,
imob, Op.use_xobject, Op.grestore)
else:
tr1, tr2, tr3, tr4, tr5, tr6 = transform.frozen().to_values()
self.file.output(Op.gsave,
1, 0, 0, 1, x, y, Op.concat_matrix,
tr1, tr2, tr3, tr4, tr5, tr6, Op.concat_matrix,
imob, Op.use_xobject, Op.grestore)
def draw_path(self, gc, path, transform, rgbFace=None):
self.check_gc(gc, rgbFace)
self.file.writePath(
path, transform,
rgbFace is None and gc.get_hatch_path() is None,
gc.get_sketch_params())
self.file.output(self.gc.paint())
def draw_path_collection(self, gc, master_transform, paths, all_transforms,
offsets, offsetTrans, facecolors, edgecolors,
linewidths, linestyles, antialiaseds, urls,
offset_position):
# We can only reuse the objects if the presence of fill and
# stroke (and the amount of alpha for each) is the same for
# all of them
can_do_optimization = True
facecolors = np.asarray(facecolors)
edgecolors = np.asarray(edgecolors)
if not len(facecolors):
filled = False
can_do_optimization = not gc.get_hatch()
else:
if np.all(facecolors[:, 3] == facecolors[0, 3]):
filled = facecolors[0, 3] != 0.0
else:
can_do_optimization = False
if not len(edgecolors):
stroked = False
else:
if np.all(np.asarray(linewidths) == 0.0):
stroked = False
elif np.all(edgecolors[:, 3] == edgecolors[0, 3]):
stroked = edgecolors[0, 3] != 0.0
else:
can_do_optimization = False
# Is the optimization worth it? Rough calculation:
# cost of emitting a path in-line is len_path * uses_per_path
# cost of XObject is len_path + 5 for the definition,
# uses_per_path for the uses
len_path = len(paths[0].vertices) if len(paths) > 0 else 0
uses_per_path = self._iter_collection_uses_per_path(
paths, all_transforms, offsets, facecolors, edgecolors)
should_do_optimization = \
len_path + uses_per_path + 5 < len_path * uses_per_path
if (not can_do_optimization) or (not should_do_optimization):
return RendererBase.draw_path_collection(
self, gc, master_transform, paths, all_transforms,
offsets, offsetTrans, facecolors, edgecolors,
linewidths, linestyles, antialiaseds, urls,
offset_position)
padding = np.max(linewidths)
path_codes = []
for i, (path, transform) in enumerate(self._iter_collection_raw_paths(
master_transform, paths, all_transforms)):
name = self.file.pathCollectionObject(
gc, path, transform, padding, filled, stroked)
path_codes.append(name)
output = self.file.output
output(*self.gc.push())
lastx, lasty = 0, 0
for xo, yo, path_id, gc0, rgbFace in self._iter_collection(
gc, master_transform, all_transforms, path_codes, offsets,
offsetTrans, facecolors, edgecolors, linewidths, linestyles,
antialiaseds, urls, offset_position):
self.check_gc(gc0, rgbFace)
dx, dy = xo - lastx, yo - lasty
output(1, 0, 0, 1, dx, dy, Op.concat_matrix, path_id,
Op.use_xobject)
lastx, lasty = xo, yo
output(*self.gc.pop())
def draw_markers(self, gc, marker_path, marker_trans, path, trans,
rgbFace=None):
# Same logic as in draw_path_collection
len_marker_path = len(marker_path)
uses = len(path)
if len_marker_path * uses < len_marker_path + uses + 5:
RendererBase.draw_markers(self, gc, marker_path, marker_trans,
path, trans, rgbFace)
return
self.check_gc(gc, rgbFace)
fill = gc.fill(rgbFace)
stroke = gc.stroke()
output = self.file.output
marker = self.file.markerObject(
marker_path, marker_trans, fill, stroke, self.gc._linewidth,
gc.get_joinstyle(), gc.get_capstyle())
output(Op.gsave)
lastx, lasty = 0, 0
for vertices, code in path.iter_segments(
trans,
clip=(0, 0, self.file.width*72, self.file.height*72),
simplify=False):
if len(vertices):
x, y = vertices[-2:]
if (x < 0 or y < 0 or
x > self.file.width * 72 or y > self.file.height * 72):
continue
dx, dy = x - lastx, y - lasty
output(1, 0, 0, 1, dx, dy, Op.concat_matrix,
marker, Op.use_xobject)
lastx, lasty = x, y
output(Op.grestore)
def draw_gouraud_triangle(self, gc, points, colors, trans):
self.draw_gouraud_triangles(gc, points.reshape((1, 3, 2)),
colors.reshape((1, 3, 4)), trans)
def draw_gouraud_triangles(self, gc, points, colors, trans):
assert len(points) == len(colors)
assert points.ndim == 3
assert points.shape[1] == 3
assert points.shape[2] == 2
assert colors.ndim == 3
assert colors.shape[1] == 3
assert colors.shape[2] == 4
shape = points.shape
points = points.reshape((shape[0] * shape[1], 2))
tpoints = trans.transform(points)
tpoints = tpoints.reshape(shape)
name = self.file.addGouraudTriangles(tpoints, colors)
self.check_gc(gc)
self.file.output(name, Op.shading)
def _setup_textpos(self, x, y, angle, oldx=0, oldy=0, oldangle=0):
if angle == oldangle == 0:
self.file.output(x - oldx, y - oldy, Op.textpos)
else:
angle = angle / 180.0 * pi
self.file.output(cos(angle), sin(angle),
-sin(angle), cos(angle),
x, y, Op.textmatrix)
self.file.output(0, 0, Op.textpos)
def draw_mathtext(self, gc, x, y, s, prop, angle):
# TODO: fix positioning and encoding
width, height, descent, glyphs, rects, used_characters = \
self.mathtext_parser.parse(s, 72, prop)
self.merge_used_characters(used_characters)
# When using Type 3 fonts, we can't use character codes higher
# than 255, so we use the "Do" command to render those
# instead.
global_fonttype = rcParams['pdf.fonttype']
# Set up a global transformation matrix for the whole math expression
a = angle / 180.0 * pi
self.file.output(Op.gsave)
self.file.output(cos(a), sin(a), -sin(a), cos(a), x, y,
Op.concat_matrix)
self.check_gc(gc, gc._rgb)
self.file.output(Op.begin_text)
prev_font = None, None
oldx, oldy = 0, 0
for ox, oy, fontname, fontsize, num, symbol_name in glyphs:
if is_opentype_cff_font(fontname):
fonttype = 42
else:
fonttype = global_fonttype
if fonttype == 42 or num <= 255:
self._setup_textpos(ox, oy, 0, oldx, oldy)
oldx, oldy = ox, oy
if (fontname, fontsize) != prev_font:
self.file.output(self.file.fontName(fontname), fontsize,
Op.selectfont)
prev_font = fontname, fontsize
self.file.output(self.encode_string(unichr(num), fonttype),
Op.show)
self.file.output(Op.end_text)
# If using Type 3 fonts, render all of the multi-byte characters
# as XObjects using the 'Do' command.
if global_fonttype == 3:
for ox, oy, fontname, fontsize, num, symbol_name in glyphs:
if is_opentype_cff_font(fontname):
fonttype = 42
else:
fonttype = global_fonttype
if fonttype == 3 and num > 255:
self.file.fontName(fontname)
self.file.output(Op.gsave,
0.001 * fontsize, 0,
0, 0.001 * fontsize,
ox, oy, Op.concat_matrix)
name = self.file._get_xobject_symbol_name(
fontname, symbol_name)
self.file.output(Name(name), Op.use_xobject)
self.file.output(Op.grestore)
# Draw any horizontal lines in the math layout
for ox, oy, width, height in rects:
self.file.output(Op.gsave, ox, oy, width, height,
Op.rectangle, Op.fill, Op.grestore)
# Pop off the global transformation
self.file.output(Op.grestore)
def draw_tex(self, gc, x, y, s, prop, angle, ismath='TeX!', mtext=None):
texmanager = self.get_texmanager()
fontsize = prop.get_size_in_points()
dvifile = texmanager.make_dvi(s, fontsize)
with dviread.Dvi(dvifile, 72) as dvi:
page = next(iter(dvi))
# Gather font information and do some setup for combining
# characters into strings. The variable seq will contain a
# sequence of font and text entries. A font entry is a list
# ['font', name, size] where name is a Name object for the
# font. A text entry is ['text', x, y, glyphs, x+w] where x
# and y are the starting coordinates, w is the width, and
# glyphs is a list; in this phase it will always contain just
# one one-character string, but later it may have longer
# strings interspersed with kern amounts.
oldfont, seq = None, []
for x1, y1, dvifont, glyph, width in page.text:
if dvifont != oldfont:
pdfname = self.file.dviFontName(dvifont)
seq += [['font', pdfname, dvifont.size]]
oldfont = dvifont
# We need to convert the glyph numbers to bytes, and the easiest
# way to do this on both Python 2 and 3 is .encode('latin-1')
seq += [['text', x1, y1,
[six.unichr(glyph).encode('latin-1')], x1+width]]
# Find consecutive text strings with constant y coordinate and
# combine into a sequence of strings and kerns, or just one
# string (if any kerns would be less than 0.1 points).
i, curx, fontsize = 0, 0, None
while i < len(seq)-1:
elt, nxt = seq[i:i+2]
if elt[0] == 'font':
fontsize = elt[2]
elif elt[0] == nxt[0] == 'text' and elt[2] == nxt[2]:
offset = elt[4] - nxt[1]
if abs(offset) < 0.1:
elt[3][-1] += nxt[3][0]
elt[4] += nxt[4]-nxt[1]
else:
elt[3] += [offset*1000.0/fontsize, nxt[3][0]]
elt[4] = nxt[4]
del seq[i+1]
continue
i += 1
# Create a transform to map the dvi contents to the canvas.
mytrans = Affine2D().rotate_deg(angle).translate(x, y)
# Output the text.
self.check_gc(gc, gc._rgb)
self.file.output(Op.begin_text)
curx, cury, oldx, oldy = 0, 0, 0, 0
for elt in seq:
if elt[0] == 'font':
self.file.output(elt[1], elt[2], Op.selectfont)
elif elt[0] == 'text':
curx, cury = mytrans.transform_point((elt[1], elt[2]))
self._setup_textpos(curx, cury, angle, oldx, oldy)
oldx, oldy = curx, cury
if len(elt[3]) == 1:
self.file.output(elt[3][0], Op.show)
else:
self.file.output(elt[3], Op.showkern)
else:
assert False
self.file.output(Op.end_text)
# Then output the boxes (e.g., variable-length lines of square
# roots).
boxgc = self.new_gc()
boxgc.copy_properties(gc)
boxgc.set_linewidth(0)
pathops = [Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO,
Path.CLOSEPOLY]
for x1, y1, h, w in page.boxes:
path = Path([[x1, y1], [x1+w, y1], [x1+w, y1+h], [x1, y1+h],
[0, 0]], pathops)
self.draw_path(boxgc, path, mytrans, gc._rgb)
def encode_string(self, s, fonttype):
if fonttype in (1, 3):
return s.encode('cp1252', 'replace')
return s.encode('utf-16be', 'replace')
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
# TODO: combine consecutive texts into one BT/ET delimited section
# This function is rather complex, since there is no way to
# access characters of a Type 3 font with codes > 255. (Type
# 3 fonts can not have a CIDMap). Therefore, we break the
# string into chunks, where each chunk contains exclusively
# 1-byte or exclusively 2-byte characters, and output each
# chunk a separate command. 1-byte characters use the regular
# text show command (Tj), whereas 2-byte characters use the
# use XObject command (Do). If using Type 42 fonts, all of
# this complication is avoided, but of course, those fonts can
# not be subsetted.
self.check_gc(gc, gc._rgb)
if ismath:
return self.draw_mathtext(gc, x, y, s, prop, angle)
fontsize = prop.get_size_in_points()
if rcParams['pdf.use14corefonts']:
font = self._get_font_afm(prop)
l, b, w, h = font.get_str_bbox(s)
fonttype = 1
else:
font = self._get_font_ttf(prop)
self.track_characters(font, s)
font.set_text(s, 0.0, flags=LOAD_NO_HINTING)
fonttype = rcParams['pdf.fonttype']
# We can't subset all OpenType fonts, so switch to Type 42
# in that case.
if is_opentype_cff_font(font.fname):
fonttype = 42
def check_simple_method(s):
"""Determine if we should use the simple or woven method
to output this text, and chunks the string into 1-byte and
2-byte sections if necessary."""
use_simple_method = True
chunks = []
if not rcParams['pdf.use14corefonts']:
if fonttype == 3 and not isinstance(s, bytes) and len(s) != 0:
# Break the string into chunks where each chunk is either
# a string of chars <= 255, or a single character > 255.
s = six.text_type(s)
for c in s:
if ord(c) <= 255:
char_type = 1
else:
char_type = 2
if len(chunks) and chunks[-1][0] == char_type:
chunks[-1][1].append(c)
else:
chunks.append((char_type, [c]))
use_simple_method = (len(chunks) == 1 and
chunks[-1][0] == 1)
return use_simple_method, chunks
def draw_text_simple():
"""Outputs text using the simple method."""
self.file.output(Op.begin_text,
self.file.fontName(prop),
fontsize,
Op.selectfont)
self._setup_textpos(x, y, angle)
self.file.output(self.encode_string(s, fonttype), Op.show,
Op.end_text)
def draw_text_woven(chunks):
"""Outputs text using the woven method, alternating
between chunks of 1-byte characters and 2-byte characters.
Only used for Type 3 fonts."""
chunks = [(a, ''.join(b)) for a, b in chunks]
# Do the rotation and global translation as a single matrix
# concatenation up front
self.file.output(Op.gsave)
a = angle / 180.0 * pi
self.file.output(cos(a), sin(a), -sin(a), cos(a), x, y,
Op.concat_matrix)
# Output all the 1-byte characters in a BT/ET group, then
# output all the 2-byte characters.
for mode in (1, 2):
newx = oldx = 0
# Output a 1-byte character chunk
if mode == 1:
self.file.output(Op.begin_text,
self.file.fontName(prop),
fontsize,
Op.selectfont)
for chunk_type, chunk in chunks:
if mode == 1 and chunk_type == 1:
self._setup_textpos(newx, 0, 0, oldx, 0, 0)
self.file.output(self.encode_string(chunk, fonttype),
Op.show)
oldx = newx
lastgind = None
for c in chunk:
ccode = ord(c)
gind = font.get_char_index(ccode)
if gind is not None:
if mode == 2 and chunk_type == 2:
glyph_name = font.get_glyph_name(gind)
self.file.output(Op.gsave)
self.file.output(0.001 * fontsize, 0,
0, 0.001 * fontsize,
newx, 0, Op.concat_matrix)
name = self.file._get_xobject_symbol_name(
font.fname, glyph_name)
self.file.output(Name(name), Op.use_xobject)
self.file.output(Op.grestore)
# Move the pointer based on the character width
# and kerning
glyph = font.load_char(ccode,
flags=LOAD_NO_HINTING)
if lastgind is not None:
kern = font.get_kerning(
lastgind, gind, KERNING_UNFITTED)
else:
kern = 0
lastgind = gind
newx += kern/64.0 + glyph.linearHoriAdvance/65536.0
if mode == 1:
self.file.output(Op.end_text)
self.file.output(Op.grestore)
use_simple_method, chunks = check_simple_method(s)
if use_simple_method:
return draw_text_simple()
else:
return draw_text_woven(chunks)
def get_text_width_height_descent(self, s, prop, ismath):
if rcParams['text.usetex']:
texmanager = self.get_texmanager()
fontsize = prop.get_size_in_points()
w, h, d = texmanager.get_text_width_height_descent(s, fontsize,
renderer=self)
return w, h, d
if ismath:
w, h, d, glyphs, rects, used_characters = \
self.mathtext_parser.parse(s, 72, prop)
elif rcParams['pdf.use14corefonts']:
font = self._get_font_afm(prop)
l, b, w, h, d = font.get_str_bbox_and_descent(s)
scale = prop.get_size_in_points()
w *= scale / 1000
h *= scale / 1000
d *= scale / 1000
else:
font = self._get_font_ttf(prop)
font.set_text(s, 0.0, flags=LOAD_NO_HINTING)
w, h = font.get_width_height()
scale = (1.0 / 64.0)
w *= scale
h *= scale
d = font.get_descent()
d *= scale
return w, h, d
def _get_font_afm(self, prop):
key = hash(prop)
font = self.afm_font_cache.get(key)
if font is None:
filename = findfont(
prop, fontext='afm', directory=self.file._core14fontdir)
if filename is None:
filename = findfont(
"Helvetica", fontext='afm',
directory=self.file._core14fontdir)
font = self.afm_font_cache.get(filename)
if font is None:
with open(filename, 'rb') as fh:
font = AFM(fh)
self.afm_font_cache[filename] = font
self.afm_font_cache[key] = font
return font
def _get_font_ttf(self, prop):
filename = findfont(prop)
font = get_font(filename)
font.clear()
font.set_size(prop.get_size_in_points(), 72)
return font
def flipy(self):
return False
def get_canvas_width_height(self):
return self.file.width * 72.0, self.file.height * 72.0
def new_gc(self):
return GraphicsContextPdf(self.file)
class GraphicsContextPdf(GraphicsContextBase):
def __init__(self, file):
GraphicsContextBase.__init__(self)
self._fillcolor = (0.0, 0.0, 0.0)
self._effective_alphas = (1.0, 1.0)
self.file = file
self.parent = None
def __repr__(self):
d = dict(self.__dict__)
del d['file']
del d['parent']
return repr(d)
def stroke(self):
"""
Predicate: does the path need to be stroked (its outline drawn)?
This tests for the various conditions that disable stroking
the path, in which case it would presumably be filled.
"""
# _linewidth > 0: in pdf a line of width 0 is drawn at minimum
# possible device width, but e.g., agg doesn't draw at all
return (self._linewidth > 0 and self._alpha > 0 and
(len(self._rgb) <= 3 or self._rgb[3] != 0.0))
def fill(self, *args):
"""
Predicate: does the path need to be filled?
An optional argument can be used to specify an alternative
_fillcolor, as needed by RendererPdf.draw_markers.
"""
if len(args):
_fillcolor = args[0]
else:
_fillcolor = self._fillcolor
return (self._hatch or
(_fillcolor is not None and
(len(_fillcolor) <= 3 or _fillcolor[3] != 0.0)))
def paint(self):
"""
Return the appropriate pdf operator to cause the path to be
stroked, filled, or both.
"""
return Op.paint_path(self.fill(), self.stroke())
capstyles = {'butt': 0, 'round': 1, 'projecting': 2}
joinstyles = {'miter': 0, 'round': 1, 'bevel': 2}
def capstyle_cmd(self, style):
return [self.capstyles[style], Op.setlinecap]
def joinstyle_cmd(self, style):
return [self.joinstyles[style], Op.setlinejoin]
def linewidth_cmd(self, width):
return [width, Op.setlinewidth]
def dash_cmd(self, dashes):
offset, dash = dashes
if dash is None:
dash = []
offset = 0
return [list(dash), offset, Op.setdash]
def alpha_cmd(self, alpha, forced, effective_alphas):
name = self.file.alphaState(effective_alphas)
return [name, Op.setgstate]
def hatch_cmd(self, hatch, hatch_color):
if not hatch:
if self._fillcolor is not None:
return self.fillcolor_cmd(self._fillcolor)
else:
return [Name('DeviceRGB'), Op.setcolorspace_nonstroke]
else:
hatch_style = (hatch_color, self._fillcolor, hatch)
name = self.file.hatchPattern(hatch_style)
return [Name('Pattern'), Op.setcolorspace_nonstroke,
name, Op.setcolor_nonstroke]
def rgb_cmd(self, rgb):
if rcParams['pdf.inheritcolor']:
return []
if rgb[0] == rgb[1] == rgb[2]:
return [rgb[0], Op.setgray_stroke]
else:
return list(rgb[:3]) + [Op.setrgb_stroke]
def fillcolor_cmd(self, rgb):
if rgb is None or rcParams['pdf.inheritcolor']:
return []
elif rgb[0] == rgb[1] == rgb[2]:
return [rgb[0], Op.setgray_nonstroke]
else:
return list(rgb[:3]) + [Op.setrgb_nonstroke]
def push(self):
parent = GraphicsContextPdf(self.file)
parent.copy_properties(self)
parent.parent = self.parent
self.parent = parent
return [Op.gsave]
def pop(self):
assert self.parent is not None
self.copy_properties(self.parent)
self.parent = self.parent.parent
return [Op.grestore]
def clip_cmd(self, cliprect, clippath):
"""Set clip rectangle. Calls self.pop() and self.push()."""
cmds = []
# Pop graphics state until we hit the right one or the stack is empty
while ((self._cliprect, self._clippath) != (cliprect, clippath)
and self.parent is not None):
cmds.extend(self.pop())
# Unless we hit the right one, set the clip polygon
if ((self._cliprect, self._clippath) != (cliprect, clippath) or
self.parent is None):
cmds.extend(self.push())
if self._cliprect != cliprect:
cmds.extend([cliprect, Op.rectangle, Op.clip, Op.endpath])
if self._clippath != clippath:
path, affine = clippath.get_transformed_path_and_affine()
cmds.extend(
PdfFile.pathOperations(path, affine, simplify=False) +
[Op.clip, Op.endpath])
return cmds
commands = (
# must come first since may pop
(('_cliprect', '_clippath'), clip_cmd),
(('_alpha', '_forced_alpha', '_effective_alphas'), alpha_cmd),
(('_capstyle',), capstyle_cmd),
(('_fillcolor',), fillcolor_cmd),
(('_joinstyle',), joinstyle_cmd),
(('_linewidth',), linewidth_cmd),
(('_dashes',), dash_cmd),
(('_rgb',), rgb_cmd),
# must come after fillcolor and rgb
(('_hatch', '_hatch_color'), hatch_cmd),
)
def delta(self, other):
"""
Copy properties of other into self and return PDF commands
needed to transform self into other.
"""
cmds = []
fill_performed = False
for params, cmd in self.commands:
different = False
for p in params:
ours = getattr(self, p)
theirs = getattr(other, p)
try:
if ours is None or theirs is None:
different = ours is not theirs
else:
different = bool(ours != theirs)
except ValueError:
ours = np.asarray(ours)
theirs = np.asarray(theirs)
different = (ours.shape != theirs.shape or
np.any(ours != theirs))
if different:
break
# Need to update hatching if we also updated fillcolor
if params == ('_hatch', '_hatch_color') and fill_performed:
different = True
if different:
if params == ('_fillcolor',):
fill_performed = True
theirs = [getattr(other, p) for p in params]
cmds.extend(cmd(self, *theirs))
for p in params:
setattr(self, p, getattr(other, p))
return cmds
def copy_properties(self, other):
"""
Copy properties of other into self.
"""
GraphicsContextBase.copy_properties(self, other)
fillcolor = getattr(other, '_fillcolor', self._fillcolor)
effective_alphas = getattr(other, '_effective_alphas',
self._effective_alphas)
self._fillcolor = fillcolor
self._effective_alphas = effective_alphas
def finalize(self):
"""
Make sure every pushed graphics state is popped.
"""
cmds = []
while self.parent is not None:
cmds.extend(self.pop())
return cmds
########################################################################
#
# The following functions and classes are for pylab and implement
# window/figure managers, etc...
#
########################################################################
class PdfPages(object):
"""
A multi-page PDF file.
Examples
--------
>>> import matplotlib.pyplot as plt
>>> # Initialize:
>>> with PdfPages('foo.pdf') as pdf:
... # As many times as you like, create a figure fig and save it:
... fig = plt.figure()
... pdf.savefig(fig)
... # When no figure is specified the current figure is saved
... pdf.savefig()
Notes
-----
In reality :class:`PdfPages` is a thin wrapper around :class:`PdfFile`, in
order to avoid confusion when using :func:`~matplotlib.pyplot.savefig` and
forgetting the format argument.
"""
__slots__ = ('_file', 'keep_empty')
def __init__(self, filename, keep_empty=True, metadata=None):
"""
Create a new PdfPages object.
Parameters
----------
filename : str
Plots using :meth:`PdfPages.savefig` will be written to a file at
this location. The file is opened at once and any older file with
the same name is overwritten.
keep_empty : bool, optional
If set to False, then empty pdf files will be deleted automatically
when closed.
metadata : dictionary, optional
Information dictionary object (see PDF reference section 10.2.1
'Document Information Dictionary'), e.g.:
`{'Creator': 'My software', 'Author': 'Me',
'Title': 'Awesome fig'}`
The standard keys are `'Title'`, `'Author'`, `'Subject'`,
`'Keywords'`, `'Creator'`, `'Producer'`, `'CreationDate'`,
`'ModDate'`, and `'Trapped'`. Values have been predefined
for `'Creator'`, `'Producer'` and `'CreationDate'`. They
can be removed by setting them to `None`.
"""
self._file = PdfFile(filename, metadata=metadata)
self.keep_empty = keep_empty
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
def close(self):
"""
Finalize this object, making the underlying file a complete
PDF file.
"""
self._file.finalize()
self._file.close()
if (self.get_pagecount() == 0 and not self.keep_empty and
not self._file.passed_in_file_object):
os.remove(self._file.fh.name)
self._file = None
def infodict(self):
"""
Return a modifiable information dictionary object
(see PDF reference section 10.2.1 'Document Information
Dictionary').
"""
return self._file.infoDict
def savefig(self, figure=None, **kwargs):
"""
Saves a :class:`~matplotlib.figure.Figure` to this file as a new page.
Any other keyword arguments are passed to
:meth:`~matplotlib.figure.Figure.savefig`.
Parameters
----------
figure : :class:`~matplotlib.figure.Figure` or int, optional
Specifies what figure is saved to file. If not specified, the
active figure is saved. If a :class:`~matplotlib.figure.Figure`
instance is provided, this figure is saved. If an int is specified,
the figure instance to save is looked up by number.
"""
if not isinstance(figure, Figure):
if figure is None:
manager = Gcf.get_active()
else:
manager = Gcf.get_fig_manager(figure)
if manager is None:
raise ValueError("No figure {}".format(figure))
figure = manager.canvas.figure
# Force use of pdf backend, as PdfPages is tightly coupled with it.
try:
orig_canvas = figure.canvas
figure.canvas = FigureCanvasPdf(figure)
figure.savefig(self, format="pdf", **kwargs)
finally:
figure.canvas = orig_canvas
def get_pagecount(self):
"""
Returns the current number of pages in the multipage pdf file.
"""
return len(self._file.pageList)
def attach_note(self, text, positionRect=[-100, -100, 0, 0]):
"""
Add a new text note to the page to be saved next. The optional
positionRect specifies the position of the new note on the
page. It is outside the page per default to make sure it is
invisible on printouts.
"""
self._file.newTextnote(text, positionRect)
class FigureCanvasPdf(FigureCanvasBase):
"""
The canvas the figure renders into. Calls the draw and print fig
methods, creates the renderers, etc...
Attributes
----------
figure : `matplotlib.figure.Figure`
A high-level Figure instance
"""
fixed_dpi = 72
def draw(self):
pass
filetypes = {'pdf': 'Portable Document Format'}
def get_default_filetype(self):
return 'pdf'
def print_pdf(self, filename, **kwargs):
image_dpi = kwargs.get('dpi', 72) # dpi to use for images
self.figure.set_dpi(72) # there are 72 pdf points to an inch
width, height = self.figure.get_size_inches()
if isinstance(filename, PdfPages):
file = filename._file
else:
file = PdfFile(filename, metadata=kwargs.pop("metadata", None))
try:
file.newPage(width, height)
_bbox_inches_restore = kwargs.pop("bbox_inches_restore", None)
renderer = MixedModeRenderer(
self.figure, width, height, image_dpi,
RendererPdf(file, image_dpi, height, width),
bbox_inches_restore=_bbox_inches_restore)
self.figure.draw(renderer)
renderer.finalize()
if not isinstance(filename, PdfPages):
file.finalize()
finally:
if isinstance(filename, PdfPages): # finish off this page
file.endStream()
else: # we opened the file above; now finish it off
file.close()
class FigureManagerPdf(FigureManagerBase):
pass
@_Backend.export
class _BackendPdf(_Backend):
FigureCanvas = FigureCanvasPdf
FigureManager = FigureManagerPdf
| 98,115 | 36.664491 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_gtk3cairo.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from . import backend_cairo, backend_gtk3
from .backend_cairo import cairo, HAS_CAIRO_CFFI
from .backend_gtk3 import _BackendGTK3
from matplotlib.backend_bases import cursors
class RendererGTK3Cairo(backend_cairo.RendererCairo):
def set_context(self, ctx):
if HAS_CAIRO_CFFI and not isinstance(ctx, cairo.Context):
ctx = cairo.Context._from_pointer(
cairo.ffi.cast(
'cairo_t **',
id(ctx) + object.__basicsize__)[0],
incref=True)
self.gc.ctx = ctx
class FigureCanvasGTK3Cairo(backend_gtk3.FigureCanvasGTK3,
backend_cairo.FigureCanvasCairo):
def _renderer_init(self):
"""Use cairo renderer."""
self._renderer = RendererGTK3Cairo(self.figure.dpi)
def _render_figure(self, width, height):
self._renderer.set_width_height(width, height)
self.figure.draw(self._renderer)
def on_draw_event(self, widget, ctx):
"""GtkDrawable draw event."""
toolbar = self.toolbar
# if toolbar:
# toolbar.set_cursor(cursors.WAIT)
self._renderer.set_context(ctx)
allocation = self.get_allocation()
self._render_figure(allocation.width, allocation.height)
# if toolbar:
# toolbar.set_cursor(toolbar._lastCursor)
return False # finish event propagation?
class FigureManagerGTK3Cairo(backend_gtk3.FigureManagerGTK3):
pass
@_BackendGTK3.export
class _BackendGTK3Cairo(_BackendGTK3):
FigureCanvas = FigureCanvasGTK3Cairo
FigureManager = FigureManagerGTK3Cairo
| 1,740 | 30.089286 | 66 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_qt4.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from .backend_qt5 import (
backend_version, SPECIAL_KEYS, SUPER, ALT, CTRL, SHIFT, MODIFIER_KEYS,
cursord, _create_qApp, _BackendQT5, TimerQT, MainWindow, FigureManagerQT,
NavigationToolbar2QT, SubplotToolQt, error_msg_qt, exception_handler)
from .backend_qt5 import FigureCanvasQT as FigureCanvasQT5
@_BackendQT5.export
class _BackendQT4(_BackendQT5):
pass
| 498 | 30.1875 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_gtk3agg.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import warnings
from . import backend_agg, backend_gtk3
from .backend_cairo import cairo, HAS_CAIRO_CFFI
from .backend_gtk3 import _BackendGTK3
from matplotlib import transforms
if six.PY3 and not HAS_CAIRO_CFFI:
warnings.warn(
"The Gtk3Agg backend is known to not work on Python 3.x with pycairo. "
"Try installing cairocffi.")
class FigureCanvasGTK3Agg(backend_gtk3.FigureCanvasGTK3,
backend_agg.FigureCanvasAgg):
def __init__(self, figure):
backend_gtk3.FigureCanvasGTK3.__init__(self, figure)
self._bbox_queue = []
def _renderer_init(self):
pass
def _render_figure(self, width, height):
backend_agg.FigureCanvasAgg.draw(self)
def on_draw_event(self, widget, ctx):
""" GtkDrawable draw event, like expose_event in GTK 2.X
"""
allocation = self.get_allocation()
w, h = allocation.width, allocation.height
if not len(self._bbox_queue):
self._render_figure(w, h)
bbox_queue = [transforms.Bbox([[0, 0], [w, h]])]
else:
bbox_queue = self._bbox_queue
if HAS_CAIRO_CFFI and not isinstance(ctx, cairo.Context):
ctx = cairo.Context._from_pointer(
cairo.ffi.cast('cairo_t **',
id(ctx) + object.__basicsize__)[0],
incref=True)
for bbox in bbox_queue:
area = self.copy_from_bbox(bbox)
buf = np.fromstring(area.to_string_argb(), dtype='uint8')
x = int(bbox.x0)
y = h - int(bbox.y1)
width = int(bbox.x1) - int(bbox.x0)
height = int(bbox.y1) - int(bbox.y0)
if HAS_CAIRO_CFFI:
image = cairo.ImageSurface.create_for_data(
buf.data, cairo.FORMAT_ARGB32, width, height)
else:
image = cairo.ImageSurface.create_for_data(
buf, cairo.FORMAT_ARGB32, width, height)
ctx.set_source_surface(image, x, y)
ctx.paint()
if len(self._bbox_queue):
self._bbox_queue = []
return False
def blit(self, bbox=None):
# If bbox is None, blit the entire canvas to gtk. Otherwise
# blit only the area defined by the bbox.
if bbox is None:
bbox = self.figure.bbox
allocation = self.get_allocation()
w, h = allocation.width, allocation.height
x = int(bbox.x0)
y = h - int(bbox.y1)
width = int(bbox.x1) - int(bbox.x0)
height = int(bbox.y1) - int(bbox.y0)
self._bbox_queue.append(bbox)
self.queue_draw_area(x, y, width, height)
def print_png(self, filename, *args, **kwargs):
# Do this so we can save the resolution of figure in the PNG file
agg = self.switch_backends(backend_agg.FigureCanvasAgg)
return agg.print_png(filename, *args, **kwargs)
class FigureManagerGTK3Agg(backend_gtk3.FigureManagerGTK3):
pass
@_BackendGTK3.export
class _BackendGTK3Cairo(_BackendGTK3):
FigureCanvas = FigureCanvasGTK3Agg
FigureManager = FigureManagerGTK3Agg
| 3,296 | 31.009709 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_macosx.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, NavigationToolbar2,
TimerBase)
from matplotlib.figure import Figure
from matplotlib import rcParams
from matplotlib.widgets import SubplotTool
import matplotlib
from matplotlib.backends import _macosx
from .backend_agg import FigureCanvasAgg
########################################################################
#
# The following functions and classes are for pylab and implement
# window/figure managers, etc...
#
########################################################################
class TimerMac(_macosx.Timer, TimerBase):
'''
Subclass of :class:`backend_bases.TimerBase` that uses CoreFoundation
run loops for timer events.
Attributes
----------
interval : int
The time between timer events in milliseconds. Default is 1000 ms.
single_shot : bool
Boolean flag indicating whether this timer should operate as single
shot (run once and then stop). Defaults to False.
callbacks : list
Stores list of (func, args) tuples that will be called upon timer
events. This list can be manipulated directly, or the functions
`add_callback` and `remove_callback` can be used.
'''
# completely implemented at the C-level (in _macosx.Timer)
class FigureCanvasMac(_macosx.FigureCanvas, FigureCanvasAgg):
"""
The canvas the figure renders into. Calls the draw and print fig
methods, creates the renderers, etc...
Events such as button presses, mouse movements, and key presses
are handled in the C code and the base class methods
button_press_event, button_release_event, motion_notify_event,
key_press_event, and key_release_event are called from there.
Attributes
----------
figure : `matplotlib.figure.Figure`
A high-level Figure instance
"""
def __init__(self, figure):
FigureCanvasBase.__init__(self, figure)
width, height = self.get_width_height()
_macosx.FigureCanvas.__init__(self, width, height)
self._device_scale = 1.0
def _set_device_scale(self, value):
if self._device_scale != value:
self.figure.dpi = self.figure.dpi / self._device_scale * value
self._device_scale = value
def _draw(self):
renderer = self.get_renderer(cleared=self.figure.stale)
if self.figure.stale:
self.figure.draw(renderer)
return renderer
def draw(self):
self.invalidate()
self.flush_events()
def draw_idle(self, *args, **kwargs):
self.invalidate()
def blit(self, bbox):
self.invalidate()
def resize(self, width, height):
dpi = self.figure.dpi
width /= dpi
height /= dpi
self.figure.set_size_inches(width * self._device_scale,
height * self._device_scale,
forward=False)
FigureCanvasBase.resize_event(self)
self.draw_idle()
def new_timer(self, *args, **kwargs):
"""
Creates a new backend-specific subclass of `backend_bases.Timer`.
This is useful for getting periodic events through the backend's native
event loop. Implemented only for backends with GUIs.
Other Parameters
----------------
interval : scalar
Timer interval in milliseconds
callbacks : list
Sequence of (func, args, kwargs) where ``func(*args, **kwargs)``
will be executed by the timer every *interval*.
"""
return TimerMac(*args, **kwargs)
class FigureManagerMac(_macosx.FigureManager, FigureManagerBase):
"""
Wrap everything up into a window for the pylab interface
"""
def __init__(self, canvas, num):
FigureManagerBase.__init__(self, canvas, num)
title = "Figure %d" % num
_macosx.FigureManager.__init__(self, canvas, title)
if rcParams['toolbar']=='toolbar2':
self.toolbar = NavigationToolbar2Mac(canvas)
else:
self.toolbar = None
if self.toolbar is not None:
self.toolbar.update()
def notify_axes_change(fig):
'this will be called whenever the current axes is changed'
if self.toolbar != None: self.toolbar.update()
self.canvas.figure.add_axobserver(notify_axes_change)
if matplotlib.is_interactive():
self.show()
self.canvas.draw_idle()
def close(self):
Gcf.destroy(self.num)
class NavigationToolbar2Mac(_macosx.NavigationToolbar2, NavigationToolbar2):
def __init__(self, canvas):
NavigationToolbar2.__init__(self, canvas)
def _init_toolbar(self):
basedir = os.path.join(rcParams['datapath'], "images")
_macosx.NavigationToolbar2.__init__(self, basedir)
def draw_rubberband(self, event, x0, y0, x1, y1):
self.canvas.set_rubberband(int(x0), int(y0), int(x1), int(y1))
def release(self, event):
self.canvas.remove_rubberband()
def set_cursor(self, cursor):
_macosx.set_cursor(cursor)
def save_figure(self, *args):
filename = _macosx.choose_save_file('Save the figure',
self.canvas.get_default_filename())
if filename is None: # Cancel
return
self.canvas.figure.savefig(filename)
def prepare_configure_subplots(self):
toolfig = Figure(figsize=(6,3))
canvas = FigureCanvasMac(toolfig)
toolfig.subplots_adjust(top=0.9)
tool = SubplotTool(self.canvas.figure, toolfig)
return canvas
def set_message(self, message):
_macosx.NavigationToolbar2.set_message(self, message.encode('utf-8'))
########################################################################
#
# Now just provide the standard names that backend.__init__ is expecting
#
########################################################################
@_Backend.export
class _BackendMac(_Backend):
FigureCanvas = FigureCanvasMac
FigureManager = FigureManagerMac
@staticmethod
def trigger_manager_draw(manager):
# For performance reasons, we don't want to redraw the figure after
# each draw command. Instead, we mark the figure as invalid, so that it
# will be redrawn as soon as the event loop resumes via PyOS_InputHook.
# This function should be called after each draw event, even if
# matplotlib is not running interactively.
manager.canvas.invalidate()
@staticmethod
def mainloop():
_macosx.show()
| 6,821 | 31.331754 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_qt5cairo.py |
import six
from .backend_cairo import cairo, FigureCanvasCairo, RendererCairo
from .backend_qt5 import QtCore, QtGui, _BackendQT5, FigureCanvasQT
from .qt_compat import QT_API
class FigureCanvasQTCairo(FigureCanvasQT, FigureCanvasCairo):
def __init__(self, figure):
super(FigureCanvasQTCairo, self).__init__(figure=figure)
self._renderer = RendererCairo(self.figure.dpi)
self._renderer.set_width_height(-1, -1) # Invalid values.
def draw(self):
if hasattr(self._renderer.gc, "ctx"):
self.figure.draw(self._renderer)
super(FigureCanvasQTCairo, self).draw()
def paintEvent(self, event):
self._update_dpi()
dpi_ratio = self._dpi_ratio
width = dpi_ratio * self.width()
height = dpi_ratio * self.height()
if (width, height) != self._renderer.get_canvas_width_height():
surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, width, height)
self._renderer.set_ctx_from_surface(surface)
self._renderer.set_width_height(width, height)
self.figure.draw(self._renderer)
buf = self._renderer.gc.ctx.get_target().get_data()
qimage = QtGui.QImage(buf, width, height,
QtGui.QImage.Format_ARGB32_Premultiplied)
# Adjust the buf reference count to work around a memory leak bug in
# QImage under PySide on Python 3.
if QT_API == 'PySide' and six.PY3:
import ctypes
ctypes.c_long.from_address(id(buf)).value = 1
if hasattr(qimage, 'setDevicePixelRatio'):
# Not available on Qt4 or some older Qt5.
qimage.setDevicePixelRatio(dpi_ratio)
painter = QtGui.QPainter(self)
painter.drawImage(0, 0, qimage)
self._draw_rect_callback(painter)
painter.end()
@_BackendQT5.export
class _BackendQT5Cairo(_BackendQT5):
FigureCanvas = FigureCanvasQTCairo
| 1,938 | 37.78 | 76 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/tkagg.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import tkinter as Tk
import numpy as np
from matplotlib.backends import _tkagg
def blit(photoimage, aggimage, bbox=None, colormode=1):
tk = photoimage.tk
if bbox is not None:
bbox_array = bbox.__array__()
# x1, x2, y1, y2
bboxptr = (bbox_array[0, 0], bbox_array[1, 0],
bbox_array[0, 1], bbox_array[1, 1])
else:
bboxptr = 0
data = np.asarray(aggimage)
dataptr = (data.shape[0], data.shape[1], data.ctypes.data)
try:
tk.call(
"PyAggImagePhoto", photoimage,
dataptr, colormode, bboxptr)
except Tk.TclError:
if hasattr(tk, 'interpaddr'):
_tkagg.tkinit(tk.interpaddr(), 1)
else:
# very old python?
_tkagg.tkinit(tk, 0)
tk.call("PyAggImagePhoto", photoimage,
dataptr, colormode, bboxptr)
def test(aggimage):
r = Tk.Tk()
c = Tk.Canvas(r, width=aggimage.width, height=aggimage.height)
c.pack()
p = Tk.PhotoImage(width=aggimage.width, height=aggimage.height)
blit(p, aggimage)
c.create_image(aggimage.width,aggimage.height,image=p)
blit(p, aggimage)
while True: r.update_idletasks()
| 1,334 | 28.666667 | 67 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_gdk.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import warnings
import gobject
import gtk; gdk = gtk.gdk
import pango
pygtk_version_required = (2,2,0)
if gtk.pygtk_version < pygtk_version_required:
raise ImportError ("PyGTK %d.%d.%d is installed\n"
"PyGTK %d.%d.%d or later is required"
% (gtk.pygtk_version + pygtk_version_required))
del pygtk_version_required
import numpy as np
import matplotlib
from matplotlib import rcParams
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
RendererBase)
from matplotlib.cbook import warn_deprecated
from matplotlib.mathtext import MathTextParser
from matplotlib.transforms import Affine2D
from matplotlib.backends._backend_gdk import pixbuf_get_pixels_array
backend_version = "%d.%d.%d" % gtk.pygtk_version
# Image formats that this backend supports - for FileChooser and print_figure()
IMAGE_FORMAT = sorted(['bmp', 'eps', 'jpg', 'png', 'ps', 'svg']) # 'raw', 'rgb'
IMAGE_FORMAT_DEFAULT = 'png'
class RendererGDK(RendererBase):
fontweights = {
100 : pango.WEIGHT_ULTRALIGHT,
200 : pango.WEIGHT_LIGHT,
300 : pango.WEIGHT_LIGHT,
400 : pango.WEIGHT_NORMAL,
500 : pango.WEIGHT_NORMAL,
600 : pango.WEIGHT_BOLD,
700 : pango.WEIGHT_BOLD,
800 : pango.WEIGHT_HEAVY,
900 : pango.WEIGHT_ULTRABOLD,
'ultralight' : pango.WEIGHT_ULTRALIGHT,
'light' : pango.WEIGHT_LIGHT,
'normal' : pango.WEIGHT_NORMAL,
'medium' : pango.WEIGHT_NORMAL,
'semibold' : pango.WEIGHT_BOLD,
'bold' : pango.WEIGHT_BOLD,
'heavy' : pango.WEIGHT_HEAVY,
'ultrabold' : pango.WEIGHT_ULTRABOLD,
'black' : pango.WEIGHT_ULTRABOLD,
}
# cache for efficiency, these must be at class, not instance level
layoutd = {} # a map from text prop tups to pango layouts
rotated = {} # a map from text prop tups to rotated text pixbufs
def __init__(self, gtkDA, dpi):
# widget gtkDA is used for:
# '<widget>.create_pango_layout(s)'
# cmap line below)
self.gtkDA = gtkDA
self.dpi = dpi
self._cmap = gtkDA.get_colormap()
self.mathtext_parser = MathTextParser("Agg")
def set_pixmap (self, pixmap):
self.gdkDrawable = pixmap
def set_width_height (self, width, height):
"""w,h is the figure w,h not the pixmap w,h
"""
self.width, self.height = width, height
def draw_path(self, gc, path, transform, rgbFace=None):
transform = transform + Affine2D(). \
scale(1.0, -1.0).translate(0, self.height)
polygons = path.to_polygons(transform, self.width, self.height)
for polygon in polygons:
# draw_polygon won't take an arbitrary sequence -- it must be a list
# of tuples
polygon = [(int(np.round(x)), int(np.round(y))) for x, y in polygon]
if rgbFace is not None:
saveColor = gc.gdkGC.foreground
gc.gdkGC.foreground = gc.rgb_to_gdk_color(rgbFace)
self.gdkDrawable.draw_polygon(gc.gdkGC, True, polygon)
gc.gdkGC.foreground = saveColor
if gc.gdkGC.line_width > 0:
self.gdkDrawable.draw_lines(gc.gdkGC, polygon)
def draw_image(self, gc, x, y, im):
bbox = gc.get_clip_rectangle()
if bbox != None:
l,b,w,h = bbox.bounds
#rectangle = (int(l), self.height-int(b+h),
# int(w), int(h))
# set clip rect?
rows, cols = im.shape[:2]
pixbuf = gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB,
has_alpha=True, bits_per_sample=8,
width=cols, height=rows)
array = pixbuf_get_pixels_array(pixbuf)
array[:, :, :] = im[::-1]
gc = self.new_gc()
y = self.height-y-rows
try: # new in 2.2
# can use None instead of gc.gdkGC, if don't need clipping
self.gdkDrawable.draw_pixbuf (gc.gdkGC, pixbuf, 0, 0,
int(x), int(y), cols, rows,
gdk.RGB_DITHER_NONE, 0, 0)
except AttributeError:
# deprecated in 2.2
pixbuf.render_to_drawable(self.gdkDrawable, gc.gdkGC, 0, 0,
int(x), int(y), cols, rows,
gdk.RGB_DITHER_NONE, 0, 0)
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
x, y = int(x), int(y)
if x < 0 or y < 0: # window has shrunk and text is off the edge
return
if angle not in (0,90):
warnings.warn('backend_gdk: unable to draw text at angles ' +
'other than 0 or 90')
elif ismath:
self._draw_mathtext(gc, x, y, s, prop, angle)
elif angle==90:
self._draw_rotated_text(gc, x, y, s, prop, angle)
else:
layout, inkRect, logicalRect = self._get_pango_layout(s, prop)
l, b, w, h = inkRect
if (x + w > self.width or y + h > self.height):
return
self.gdkDrawable.draw_layout(gc.gdkGC, x, y-h-b, layout)
def _draw_mathtext(self, gc, x, y, s, prop, angle):
ox, oy, width, height, descent, font_image, used_characters = \
self.mathtext_parser.parse(s, self.dpi, prop)
if angle == 90:
width, height = height, width
x -= width
y -= height
imw = font_image.get_width()
imh = font_image.get_height()
pixbuf = gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB, has_alpha=True,
bits_per_sample=8, width=imw, height=imh)
array = pixbuf_get_pixels_array(pixbuf)
rgb = gc.get_rgb()
array[:,:,0] = int(rgb[0]*255)
array[:,:,1] = int(rgb[1]*255)
array[:,:,2] = int(rgb[2]*255)
array[:,:,3] = (
np.fromstring(font_image.as_str(), np.uint8).reshape((imh, imw)))
# can use None instead of gc.gdkGC, if don't need clipping
self.gdkDrawable.draw_pixbuf(gc.gdkGC, pixbuf, 0, 0,
int(x), int(y), imw, imh,
gdk.RGB_DITHER_NONE, 0, 0)
def _draw_rotated_text(self, gc, x, y, s, prop, angle):
"""
Draw the text rotated 90 degrees, other angles are not supported
"""
# this function (and its called functions) is a bottleneck
# Pango 1.6 supports rotated text, but pygtk 2.4.0 does not yet have
# wrapper functions
# GTK+ 2.6 pixbufs support rotation
gdrawable = self.gdkDrawable
ggc = gc.gdkGC
layout, inkRect, logicalRect = self._get_pango_layout(s, prop)
l, b, w, h = inkRect
x = int(x-h)
y = int(y-w)
if (x < 0 or y < 0 or # window has shrunk and text is off the edge
x + w > self.width or y + h > self.height):
return
key = (x,y,s,angle,hash(prop))
imageVert = self.rotated.get(key)
if imageVert != None:
gdrawable.draw_image(ggc, imageVert, 0, 0, x, y, h, w)
return
imageBack = gdrawable.get_image(x, y, w, h)
imageVert = gdrawable.get_image(x, y, h, w)
imageFlip = gtk.gdk.Image(type=gdk.IMAGE_FASTEST,
visual=gdrawable.get_visual(),
width=w, height=h)
if imageFlip == None or imageBack == None or imageVert == None:
warnings.warn("Could not renderer vertical text")
return
imageFlip.set_colormap(self._cmap)
for i in range(w):
for j in range(h):
imageFlip.put_pixel(i, j, imageVert.get_pixel(j,w-i-1) )
gdrawable.draw_image(ggc, imageFlip, 0, 0, x, y, w, h)
gdrawable.draw_layout(ggc, x, y-b, layout)
imageIn = gdrawable.get_image(x, y, w, h)
for i in range(w):
for j in range(h):
imageVert.put_pixel(j, i, imageIn.get_pixel(w-i-1,j) )
gdrawable.draw_image(ggc, imageBack, 0, 0, x, y, w, h)
gdrawable.draw_image(ggc, imageVert, 0, 0, x, y, h, w)
self.rotated[key] = imageVert
def _get_pango_layout(self, s, prop):
"""
Create a pango layout instance for Text 's' with properties 'prop'.
Return - pango layout (from cache if already exists)
Note that pango assumes a logical DPI of 96
Ref: pango/fonts.c/pango_font_description_set_size() manual page
"""
# problem? - cache gets bigger and bigger, is never cleared out
# two (not one) layouts are created for every text item s (then they
# are cached) - why?
key = self.dpi, s, hash(prop)
value = self.layoutd.get(key)
if value != None:
return value
size = prop.get_size_in_points() * self.dpi / 96.0
size = np.round(size)
font_str = '%s, %s %i' % (prop.get_name(), prop.get_style(), size,)
font = pango.FontDescription(font_str)
# later - add fontweight to font_str
font.set_weight(self.fontweights[prop.get_weight()])
layout = self.gtkDA.create_pango_layout(s)
layout.set_font_description(font)
inkRect, logicalRect = layout.get_pixel_extents()
self.layoutd[key] = layout, inkRect, logicalRect
return layout, inkRect, logicalRect
def flipy(self):
return True
def get_canvas_width_height(self):
return self.width, self.height
def get_text_width_height_descent(self, s, prop, ismath):
if ismath:
ox, oy, width, height, descent, font_image, used_characters = \
self.mathtext_parser.parse(s, self.dpi, prop)
return width, height, descent
layout, inkRect, logicalRect = self._get_pango_layout(s, prop)
l, b, w, h = inkRect
ll, lb, lw, lh = logicalRect
return w, h + 1, h - lh
def new_gc(self):
return GraphicsContextGDK(renderer=self)
def points_to_pixels(self, points):
return points/72.0 * self.dpi
class GraphicsContextGDK(GraphicsContextBase):
# a cache shared by all class instances
_cached = {} # map: rgb color -> gdk.Color
_joind = {
'bevel' : gdk.JOIN_BEVEL,
'miter' : gdk.JOIN_MITER,
'round' : gdk.JOIN_ROUND,
}
_capd = {
'butt' : gdk.CAP_BUTT,
'projecting' : gdk.CAP_PROJECTING,
'round' : gdk.CAP_ROUND,
}
def __init__(self, renderer):
GraphicsContextBase.__init__(self)
self.renderer = renderer
self.gdkGC = gtk.gdk.GC(renderer.gdkDrawable)
self._cmap = renderer._cmap
def rgb_to_gdk_color(self, rgb):
"""
rgb - an RGB tuple (three 0.0-1.0 values)
return an allocated gtk.gdk.Color
"""
try:
return self._cached[tuple(rgb)]
except KeyError:
color = self._cached[tuple(rgb)] = \
self._cmap.alloc_color(
int(rgb[0]*65535),int(rgb[1]*65535),int(rgb[2]*65535))
return color
#def set_antialiased(self, b):
# anti-aliasing is not supported by GDK
def set_capstyle(self, cs):
GraphicsContextBase.set_capstyle(self, cs)
self.gdkGC.cap_style = self._capd[self._capstyle]
def set_clip_rectangle(self, rectangle):
GraphicsContextBase.set_clip_rectangle(self, rectangle)
if rectangle is None:
return
l,b,w,h = rectangle.bounds
rectangle = (int(l), self.renderer.height-int(b+h)+1,
int(w), int(h))
#rectangle = (int(l), self.renderer.height-int(b+h),
# int(w+1), int(h+2))
self.gdkGC.set_clip_rectangle(rectangle)
def set_dashes(self, dash_offset, dash_list):
GraphicsContextBase.set_dashes(self, dash_offset, dash_list)
if dash_list == None:
self.gdkGC.line_style = gdk.LINE_SOLID
else:
pixels = self.renderer.points_to_pixels(np.asarray(dash_list))
dl = [max(1, int(np.round(val))) for val in pixels]
self.gdkGC.set_dashes(dash_offset, dl)
self.gdkGC.line_style = gdk.LINE_ON_OFF_DASH
def set_foreground(self, fg, isRGBA=False):
GraphicsContextBase.set_foreground(self, fg, isRGBA)
self.gdkGC.foreground = self.rgb_to_gdk_color(self.get_rgb())
def set_joinstyle(self, js):
GraphicsContextBase.set_joinstyle(self, js)
self.gdkGC.join_style = self._joind[self._joinstyle]
def set_linewidth(self, w):
GraphicsContextBase.set_linewidth(self, w)
if w == 0:
self.gdkGC.line_width = 0
else:
pixels = self.renderer.points_to_pixels(w)
self.gdkGC.line_width = max(1, int(np.round(pixels)))
class FigureCanvasGDK (FigureCanvasBase):
def __init__(self, figure):
FigureCanvasBase.__init__(self, figure)
if self.__class__ == matplotlib.backends.backend_gdk.FigureCanvasGDK:
warn_deprecated('2.0', message="The GDK backend is "
"deprecated. It is untested, known to be "
"broken and will be removed in Matplotlib 3.0. "
"Use the Agg backend instead. "
"See Matplotlib usage FAQ for"
" more info on backends.",
alternative="Agg")
self._renderer_init()
def _renderer_init(self):
self._renderer = RendererGDK (gtk.DrawingArea(), self.figure.dpi)
def _render_figure(self, pixmap, width, height):
self._renderer.set_pixmap (pixmap)
self._renderer.set_width_height (width, height)
self.figure.draw (self._renderer)
filetypes = FigureCanvasBase.filetypes.copy()
filetypes['jpg'] = 'JPEG'
filetypes['jpeg'] = 'JPEG'
def print_jpeg(self, filename, *args, **kwargs):
return self._print_image(filename, 'jpeg')
print_jpg = print_jpeg
def print_png(self, filename, *args, **kwargs):
return self._print_image(filename, 'png')
def _print_image(self, filename, format, *args, **kwargs):
width, height = self.get_width_height()
pixmap = gtk.gdk.Pixmap (None, width, height, depth=24)
self._render_figure(pixmap, width, height)
# jpg colors don't match the display very well, png colors match
# better
pixbuf = gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB, 0, 8,
width, height)
pixbuf.get_from_drawable(pixmap, pixmap.get_colormap(),
0, 0, 0, 0, width, height)
# set the default quality, if we are writing a JPEG.
# http://www.pygtk.org/docs/pygtk/class-gdkpixbuf.html#method-gdkpixbuf--save
options = {k: kwargs[k] for k in ['quality'] if k in kwargs}
if format in ['jpg', 'jpeg']:
options.setdefault('quality', rcParams['savefig.jpeg_quality'])
options['quality'] = str(options['quality'])
pixbuf.save(filename, format, options=options)
@_Backend.export
class _BackendGDK(_Backend):
FigureCanvas = FigureCanvasGDK
FigureManager = FigureManagerBase
| 15,793 | 34.977221 | 85 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_webagg_core.py | """
Displays Agg images in the browser, with interactivity
"""
# The WebAgg backend is divided into two modules:
#
# - `backend_webagg_core.py` contains code necessary to embed a WebAgg
# plot inside of a web application, and communicate in an abstract
# way over a web socket.
#
# - `backend_webagg.py` contains a concrete implementation of a basic
# application, implemented with tornado.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import datetime
import io
import json
import os
import warnings
import numpy as np
import tornado
from matplotlib.backends import backend_agg
from matplotlib.backend_bases import _Backend
from matplotlib import backend_bases
from matplotlib import _png
# http://www.cambiaresearch.com/articles/15/javascript-char-codes-key-codes
_SHIFT_LUT = {59: ':',
61: '+',
173: '_',
186: ':',
187: '+',
188: '<',
189: '_',
190: '>',
191: '?',
192: '~',
219: '{',
220: '|',
221: '}',
222: '"'}
_LUT = {8: 'backspace',
9: 'tab',
13: 'enter',
16: 'shift',
17: 'control',
18: 'alt',
19: 'pause',
20: 'caps',
27: 'escape',
32: ' ',
33: 'pageup',
34: 'pagedown',
35: 'end',
36: 'home',
37: 'left',
38: 'up',
39: 'right',
40: 'down',
45: 'insert',
46: 'delete',
91: 'super',
92: 'super',
93: 'select',
106: '*',
107: '+',
109: '-',
110: '.',
111: '/',
144: 'num_lock',
145: 'scroll_lock',
186: ':',
187: '=',
188: ',',
189: '-',
190: '.',
191: '/',
192: '`',
219: '[',
220: '\\',
221: ']',
222: "'"}
def _handle_key(key):
"""Handle key codes"""
code = int(key[key.index('k') + 1:])
value = chr(code)
# letter keys
if code >= 65 and code <= 90:
if 'shift+' in key:
key = key.replace('shift+', '')
else:
value = value.lower()
# number keys
elif code >= 48 and code <= 57:
if 'shift+' in key:
value = ')!@#$%^&*('[int(value)]
key = key.replace('shift+', '')
# function keys
elif code >= 112 and code <= 123:
value = 'f%s' % (code - 111)
# number pad keys
elif code >= 96 and code <= 105:
value = '%s' % (code - 96)
# keys with shift alternatives
elif code in _SHIFT_LUT and 'shift+' in key:
key = key.replace('shift+', '')
value = _SHIFT_LUT[code]
elif code in _LUT:
value = _LUT[code]
key = key[:key.index('k')] + value
return key
class FigureCanvasWebAggCore(backend_agg.FigureCanvasAgg):
supports_blit = False
def __init__(self, *args, **kwargs):
backend_agg.FigureCanvasAgg.__init__(self, *args, **kwargs)
# Set to True when the renderer contains data that is newer
# than the PNG buffer.
self._png_is_old = True
# Set to True by the `refresh` message so that the next frame
# sent to the clients will be a full frame.
self._force_full = True
# Store the current image mode so that at any point, clients can
# request the information. This should be changed by calling
# self.set_image_mode(mode) so that the notification can be given
# to the connected clients.
self._current_image_mode = 'full'
# Store the DPI ratio of the browser. This is the scaling that
# occurs automatically for all images on a HiDPI display.
self._dpi_ratio = 1
def show(self):
# show the figure window
from matplotlib.pyplot import show
show()
def draw(self):
renderer = self.get_renderer(cleared=True)
self._png_is_old = True
backend_agg.RendererAgg.lock.acquire()
try:
self.figure.draw(renderer)
finally:
backend_agg.RendererAgg.lock.release()
# Swap the frames
self.manager.refresh_all()
def draw_idle(self):
self.send_event("draw")
def set_image_mode(self, mode):
"""
Set the image mode for any subsequent images which will be sent
to the clients. The modes may currently be either 'full' or 'diff'.
Note: diff images may not contain transparency, therefore upon
draw this mode may be changed if the resulting image has any
transparent component.
"""
if mode not in ['full', 'diff']:
raise ValueError('image mode must be either full or diff.')
if self._current_image_mode != mode:
self._current_image_mode = mode
self.handle_send_image_mode(None)
def get_diff_image(self):
if self._png_is_old:
renderer = self.get_renderer()
# The buffer is created as type uint32 so that entire
# pixels can be compared in one numpy call, rather than
# needing to compare each plane separately.
buff = (np.frombuffer(renderer.buffer_rgba(), dtype=np.uint32)
.reshape((renderer.height, renderer.width)))
# If any pixels have transparency, we need to force a full
# draw as we cannot overlay new on top of old.
pixels = buff.view(dtype=np.uint8).reshape(buff.shape + (4,))
if self._force_full or np.any(pixels[:, :, 3] != 255):
self.set_image_mode('full')
output = buff
else:
self.set_image_mode('diff')
last_buffer = (np.frombuffer(self._last_renderer.buffer_rgba(),
dtype=np.uint32)
.reshape((renderer.height, renderer.width)))
diff = buff != last_buffer
output = np.where(diff, buff, 0)
# TODO: We should write a new version of write_png that
# handles the differencing inline
buff = _png.write_png(
output.view(dtype=np.uint8).reshape(output.shape + (4,)),
None, compression=6, filter=_png.PNG_FILTER_NONE)
# Swap the renderer frames
self._renderer, self._last_renderer = (
self._last_renderer, renderer)
self._force_full = False
self._png_is_old = False
return buff
def get_renderer(self, cleared=None):
# Mirrors super.get_renderer, but caches the old one
# so that we can do things such as produce a diff image
# in get_diff_image
_, _, w, h = self.figure.bbox.bounds
w, h = int(w), int(h)
key = w, h, self.figure.dpi
try:
self._lastKey, self._renderer
except AttributeError:
need_new_renderer = True
else:
need_new_renderer = (self._lastKey != key)
if need_new_renderer:
self._renderer = backend_agg.RendererAgg(
w, h, self.figure.dpi)
self._last_renderer = backend_agg.RendererAgg(
w, h, self.figure.dpi)
self._lastKey = key
elif cleared:
self._renderer.clear()
return self._renderer
def handle_event(self, event):
e_type = event['type']
handler = getattr(self, 'handle_{0}'.format(e_type),
self.handle_unknown_event)
return handler(event)
def handle_unknown_event(self, event):
warnings.warn('Unhandled message type {0}. {1}'.format(
event['type'], event))
def handle_ack(self, event):
# Network latency tends to decrease if traffic is flowing
# in both directions. Therefore, the browser sends back
# an "ack" message after each image frame is received.
# This could also be used as a simple sanity check in the
# future, but for now the performance increase is enough
# to justify it, even if the server does nothing with it.
pass
def handle_draw(self, event):
self.draw()
def _handle_mouse(self, event):
x = event['x']
y = event['y']
y = self.get_renderer().height - y
# Javascript button numbers and matplotlib button numbers are
# off by 1
button = event['button'] + 1
# The right mouse button pops up a context menu, which
# doesn't work very well, so use the middle mouse button
# instead. It doesn't seem that it's possible to disable
# the context menu in recent versions of Chrome. If this
# is resolved, please also adjust the docstring in MouseEvent.
if button == 2:
button = 3
e_type = event['type']
guiEvent = event.get('guiEvent', None)
if e_type == 'button_press':
self.button_press_event(x, y, button, guiEvent=guiEvent)
elif e_type == 'button_release':
self.button_release_event(x, y, button, guiEvent=guiEvent)
elif e_type == 'motion_notify':
self.motion_notify_event(x, y, guiEvent=guiEvent)
elif e_type == 'figure_enter':
self.enter_notify_event(xy=(x, y), guiEvent=guiEvent)
elif e_type == 'figure_leave':
self.leave_notify_event()
elif e_type == 'scroll':
self.scroll_event(x, y, event['step'], guiEvent=guiEvent)
handle_button_press = handle_button_release = handle_motion_notify = \
handle_figure_enter = handle_figure_leave = handle_scroll = \
_handle_mouse
def _handle_key(self, event):
key = _handle_key(event['key'])
e_type = event['type']
guiEvent = event.get('guiEvent', None)
if e_type == 'key_press':
self.key_press_event(key, guiEvent=guiEvent)
elif e_type == 'key_release':
self.key_release_event(key, guiEvent=guiEvent)
handle_key_press = handle_key_release = _handle_key
def handle_toolbar_button(self, event):
# TODO: Be more suspicious of the input
getattr(self.toolbar, event['name'])()
def handle_refresh(self, event):
figure_label = self.figure.get_label()
if not figure_label:
figure_label = "Figure {0}".format(self.manager.num)
self.send_event('figure_label', label=figure_label)
self._force_full = True
self.draw_idle()
def handle_resize(self, event):
x, y = event.get('width', 800), event.get('height', 800)
x, y = int(x) * self._dpi_ratio, int(y) * self._dpi_ratio
fig = self.figure
# An attempt at approximating the figure size in pixels.
fig.set_size_inches(x / fig.dpi, y / fig.dpi, forward=False)
_, _, w, h = self.figure.bbox.bounds
# Acknowledge the resize, and force the viewer to update the
# canvas size to the figure's new size (which is hopefully
# identical or within a pixel or so).
self._png_is_old = True
self.manager.resize(w, h)
self.resize_event()
def handle_send_image_mode(self, event):
# The client requests notification of what the current image mode is.
self.send_event('image_mode', mode=self._current_image_mode)
def handle_set_dpi_ratio(self, event):
dpi_ratio = event.get('dpi_ratio', 1)
if dpi_ratio != self._dpi_ratio:
# We don't want to scale up the figure dpi more than once.
if not hasattr(self.figure, '_original_dpi'):
self.figure._original_dpi = self.figure.dpi
self.figure.dpi = dpi_ratio * self.figure._original_dpi
self._dpi_ratio = dpi_ratio
self._force_full = True
self.draw_idle()
def send_event(self, event_type, **kwargs):
self.manager._send_event(event_type, **kwargs)
_JQUERY_ICON_CLASSES = {
'home': 'ui-icon ui-icon-home',
'back': 'ui-icon ui-icon-circle-arrow-w',
'forward': 'ui-icon ui-icon-circle-arrow-e',
'zoom_to_rect': 'ui-icon ui-icon-search',
'move': 'ui-icon ui-icon-arrow-4',
'download': 'ui-icon ui-icon-disk',
None: None,
}
class NavigationToolbar2WebAgg(backend_bases.NavigationToolbar2):
# Use the standard toolbar items + download button
toolitems = [(text, tooltip_text, _JQUERY_ICON_CLASSES[image_file],
name_of_method)
for text, tooltip_text, image_file, name_of_method
in (backend_bases.NavigationToolbar2.toolitems +
(('Download', 'Download plot', 'download', 'download'),))
if image_file in _JQUERY_ICON_CLASSES]
def _init_toolbar(self):
self.message = ''
self.cursor = 0
def set_message(self, message):
if message != self.message:
self.canvas.send_event("message", message=message)
self.message = message
def set_cursor(self, cursor):
if cursor != self.cursor:
self.canvas.send_event("cursor", cursor=cursor)
self.cursor = cursor
def draw_rubberband(self, event, x0, y0, x1, y1):
self.canvas.send_event(
"rubberband", x0=x0, y0=y0, x1=x1, y1=y1)
def release_zoom(self, event):
backend_bases.NavigationToolbar2.release_zoom(self, event)
self.canvas.send_event(
"rubberband", x0=-1, y0=-1, x1=-1, y1=-1)
def save_figure(self, *args):
"""Save the current figure"""
self.canvas.send_event('save')
class FigureManagerWebAgg(backend_bases.FigureManagerBase):
ToolbarCls = NavigationToolbar2WebAgg
def __init__(self, canvas, num):
backend_bases.FigureManagerBase.__init__(self, canvas, num)
self.web_sockets = set()
self.toolbar = self._get_toolbar(canvas)
def show(self):
pass
def _get_toolbar(self, canvas):
toolbar = self.ToolbarCls(canvas)
return toolbar
def resize(self, w, h):
self._send_event(
'resize',
size=(w / self.canvas._dpi_ratio, h / self.canvas._dpi_ratio))
def set_window_title(self, title):
self._send_event('figure_label', label=title)
# The following methods are specific to FigureManagerWebAgg
def add_web_socket(self, web_socket):
assert hasattr(web_socket, 'send_binary')
assert hasattr(web_socket, 'send_json')
self.web_sockets.add(web_socket)
_, _, w, h = self.canvas.figure.bbox.bounds
self.resize(w, h)
self._send_event('refresh')
def remove_web_socket(self, web_socket):
self.web_sockets.remove(web_socket)
def handle_json(self, content):
self.canvas.handle_event(content)
def refresh_all(self):
if self.web_sockets:
diff = self.canvas.get_diff_image()
if diff is not None:
for s in self.web_sockets:
s.send_binary(diff)
@classmethod
def get_javascript(cls, stream=None):
if stream is None:
output = io.StringIO()
else:
output = stream
with io.open(os.path.join(
os.path.dirname(__file__),
"web_backend", "js",
"mpl.js"), encoding='utf8') as fd:
output.write(fd.read())
toolitems = []
for name, tooltip, image, method in cls.ToolbarCls.toolitems:
if name is None:
toolitems.append(['', '', '', ''])
else:
toolitems.append([name, tooltip, image, method])
output.write("mpl.toolbar_items = {0};\n\n".format(
json.dumps(toolitems)))
extensions = []
for filetype, ext in sorted(FigureCanvasWebAggCore.
get_supported_filetypes_grouped().
items()):
if not ext[0] == 'pgf': # pgf does not support BytesIO
extensions.append(ext[0])
output.write("mpl.extensions = {0};\n\n".format(
json.dumps(extensions)))
output.write("mpl.default_extension = {0};".format(
json.dumps(FigureCanvasWebAggCore.get_default_filetype())))
if stream is None:
return output.getvalue()
@classmethod
def get_static_file_path(cls):
return os.path.join(os.path.dirname(__file__), 'web_backend')
def _send_event(self, event_type, **kwargs):
payload = {'type': event_type}
payload.update(kwargs)
for s in self.web_sockets:
s.send_json(payload)
class TimerTornado(backend_bases.TimerBase):
def _timer_start(self):
self._timer_stop()
if self._single:
ioloop = tornado.ioloop.IOLoop.instance()
self._timer = ioloop.add_timeout(
datetime.timedelta(milliseconds=self.interval),
self._on_timer)
else:
self._timer = tornado.ioloop.PeriodicCallback(
self._on_timer,
self.interval)
self._timer.start()
def _timer_stop(self):
if self._timer is None:
return
elif self._single:
ioloop = tornado.ioloop.IOLoop.instance()
ioloop.remove_timeout(self._timer)
else:
self._timer.stop()
self._timer = None
def _timer_set_interval(self):
# Only stop and restart it if the timer has already been started
if self._timer is not None:
self._timer_stop()
self._timer_start()
@_Backend.export
class _BackendWebAggCoreAgg(_Backend):
FigureCanvas = FigureCanvasWebAggCore
FigureManager = FigureManagerWebAgg
| 17,958 | 32.012868 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/_backend_tk.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import tkinter as Tk
import logging
import os.path
import sys
# Paint image to Tk photo blitter extension
import matplotlib.backends.tkagg as tkagg
from matplotlib.backends.backend_agg import FigureCanvasAgg
import matplotlib.backends.windowing as windowing
import matplotlib
from matplotlib import backend_tools, cbook, rcParams
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, NavigationToolbar2,
StatusbarBase, TimerBase, ToolContainerBase, cursors)
from matplotlib.backend_managers import ToolManager
from matplotlib._pylab_helpers import Gcf
from matplotlib.figure import Figure
from matplotlib.widgets import SubplotTool
_log = logging.getLogger(__name__)
backend_version = Tk.TkVersion
# the true dots per inch on the screen; should be display dependent
# see http://groups.google.com/groups?q=screen+dpi+x11&hl=en&lr=&ie=UTF-8&oe=UTF-8&safe=off&selm=7077.26e81ad5%40swift.cs.tcd.ie&rnum=5 for some info about screen dpi
PIXELS_PER_INCH = 75
cursord = {
cursors.MOVE: "fleur",
cursors.HAND: "hand2",
cursors.POINTER: "arrow",
cursors.SELECT_REGION: "tcross",
cursors.WAIT: "watch",
}
def raise_msg_to_str(msg):
"""msg is a return arg from a raise. Join with new lines"""
if not isinstance(msg, six.string_types):
msg = '\n'.join(map(str, msg))
return msg
def error_msg_tkpaint(msg, parent=None):
from six.moves import tkinter_messagebox as tkMessageBox
tkMessageBox.showerror("matplotlib", msg)
class TimerTk(TimerBase):
'''
Subclass of :class:`backend_bases.TimerBase` that uses Tk's timer events.
Attributes
----------
interval : int
The time between timer events in milliseconds. Default is 1000 ms.
single_shot : bool
Boolean flag indicating whether this timer should operate as single
shot (run once and then stop). Defaults to False.
callbacks : list
Stores list of (func, args) tuples that will be called upon timer
events. This list can be manipulated directly, or the functions
`add_callback` and `remove_callback` can be used.
'''
def __init__(self, parent, *args, **kwargs):
TimerBase.__init__(self, *args, **kwargs)
self.parent = parent
self._timer = None
def _timer_start(self):
self._timer_stop()
self._timer = self.parent.after(self._interval, self._on_timer)
def _timer_stop(self):
if self._timer is not None:
self.parent.after_cancel(self._timer)
self._timer = None
def _on_timer(self):
TimerBase._on_timer(self)
# Tk after() is only a single shot, so we need to add code here to
# reset the timer if we're not operating in single shot mode. However,
# if _timer is None, this means that _timer_stop has been called; so
# don't recreate the timer in that case.
if not self._single and self._timer:
self._timer = self.parent.after(self._interval, self._on_timer)
else:
self._timer = None
class FigureCanvasTk(FigureCanvasBase):
keyvald = {65507 : 'control',
65505 : 'shift',
65513 : 'alt',
65515 : 'super',
65508 : 'control',
65506 : 'shift',
65514 : 'alt',
65361 : 'left',
65362 : 'up',
65363 : 'right',
65364 : 'down',
65307 : 'escape',
65470 : 'f1',
65471 : 'f2',
65472 : 'f3',
65473 : 'f4',
65474 : 'f5',
65475 : 'f6',
65476 : 'f7',
65477 : 'f8',
65478 : 'f9',
65479 : 'f10',
65480 : 'f11',
65481 : 'f12',
65300 : 'scroll_lock',
65299 : 'break',
65288 : 'backspace',
65293 : 'enter',
65379 : 'insert',
65535 : 'delete',
65360 : 'home',
65367 : 'end',
65365 : 'pageup',
65366 : 'pagedown',
65438 : '0',
65436 : '1',
65433 : '2',
65435 : '3',
65430 : '4',
65437 : '5',
65432 : '6',
65429 : '7',
65431 : '8',
65434 : '9',
65451 : '+',
65453 : '-',
65450 : '*',
65455 : '/',
65439 : 'dec',
65421 : 'enter',
}
_keycode_lookup = {
262145: 'control',
524320: 'alt',
524352: 'alt',
1048584: 'super',
1048592: 'super',
131074: 'shift',
131076: 'shift',
}
"""_keycode_lookup is used for badly mapped (i.e. no event.key_sym set)
keys on apple keyboards."""
def __init__(self, figure, master=None, resize_callback=None):
super(FigureCanvasTk, self).__init__(figure)
self._idle = True
self._idle_callback = None
t1,t2,w,h = self.figure.bbox.bounds
w, h = int(w), int(h)
self._tkcanvas = Tk.Canvas(
master=master, background="white",
width=w, height=h, borderwidth=0, highlightthickness=0)
self._tkphoto = Tk.PhotoImage(
master=self._tkcanvas, width=w, height=h)
self._tkcanvas.create_image(w//2, h//2, image=self._tkphoto)
self._resize_callback = resize_callback
self._tkcanvas.bind("<Configure>", self.resize)
self._tkcanvas.bind("<Key>", self.key_press)
self._tkcanvas.bind("<Motion>", self.motion_notify_event)
self._tkcanvas.bind("<KeyRelease>", self.key_release)
for name in "<Button-1>", "<Button-2>", "<Button-3>":
self._tkcanvas.bind(name, self.button_press_event)
for name in "<Double-Button-1>", "<Double-Button-2>", "<Double-Button-3>":
self._tkcanvas.bind(name, self.button_dblclick_event)
for name in "<ButtonRelease-1>", "<ButtonRelease-2>", "<ButtonRelease-3>":
self._tkcanvas.bind(name, self.button_release_event)
# Mouse wheel on Linux generates button 4/5 events
for name in "<Button-4>", "<Button-5>":
self._tkcanvas.bind(name, self.scroll_event)
# Mouse wheel for windows goes to the window with the focus.
# Since the canvas won't usually have the focus, bind the
# event to the window containing the canvas instead.
# See http://wiki.tcl.tk/3893 (mousewheel) for details
root = self._tkcanvas.winfo_toplevel()
root.bind("<MouseWheel>", self.scroll_event_windows, "+")
# Can't get destroy events by binding to _tkcanvas. Therefore, bind
# to the window and filter.
def filter_destroy(evt):
if evt.widget is self._tkcanvas:
self._master.update_idletasks()
self.close_event()
root.bind("<Destroy>", filter_destroy, "+")
self._master = master
self._tkcanvas.focus_set()
def resize(self, event):
width, height = event.width, event.height
if self._resize_callback is not None:
self._resize_callback(event)
# compute desired figure size in inches
dpival = self.figure.dpi
winch = width/dpival
hinch = height/dpival
self.figure.set_size_inches(winch, hinch, forward=False)
self._tkcanvas.delete(self._tkphoto)
self._tkphoto = Tk.PhotoImage(
master=self._tkcanvas, width=int(width), height=int(height))
self._tkcanvas.create_image(int(width/2),int(height/2),image=self._tkphoto)
self.resize_event()
self.draw()
# a resizing will in general move the pointer position
# relative to the canvas, so process it as a motion notify
# event. An intended side effect of this call is to allow
# window raises (which trigger a resize) to get the cursor
# position to the mpl event framework so key presses which are
# over the axes will work w/o clicks or explicit motion
self._update_pointer_position(event)
def _update_pointer_position(self, guiEvent=None):
"""
Figure out if we are inside the canvas or not and update the
canvas enter/leave events
"""
# if the pointer if over the canvas, set the lastx and lasty
# attrs of the canvas so it can process event w/o mouse click
# or move
# the window's upper, left coords in screen coords
xw = self._tkcanvas.winfo_rootx()
yw = self._tkcanvas.winfo_rooty()
# the pointer's location in screen coords
xp, yp = self._tkcanvas.winfo_pointerxy()
# not figure out the canvas coordinates of the pointer
xc = xp - xw
yc = yp - yw
# flip top/bottom
yc = self.figure.bbox.height - yc
# JDH: this method was written originally to get the pointer
# location to the backend lastx and lasty attrs so that events
# like KeyEvent can be handled without mouse events. e.g., if
# the cursor is already above the axes, then key presses like
# 'g' should toggle the grid. In order for this to work in
# backend_bases, the canvas needs to know _lastx and _lasty.
# There are three ways to get this info the canvas:
#
# 1) set it explicitly
#
# 2) call enter/leave events explicitly. The downside of this
# in the impl below is that enter could be repeatedly
# triggered if the mouse is over the axes and one is
# resizing with the keyboard. This is not entirely bad,
# because the mouse position relative to the canvas is
# changing, but it may be surprising to get repeated entries
# without leaves
#
# 3) process it as a motion notify event. This also has pros
# and cons. The mouse is moving relative to the window, but
# this may surpise an event handler writer who is getting
# motion_notify_events even if the mouse has not moved
# here are the three scenarios
if 1:
# just manually set it
self._lastx, self._lasty = xc, yc
elif 0:
# alternate implementation: process it as a motion
FigureCanvasBase.motion_notify_event(self, xc, yc, guiEvent)
elif 0:
# alternate implementation -- process enter/leave events
# instead of motion/notify
if self.figure.bbox.contains(xc, yc):
self.enter_notify_event(guiEvent, xy=(xc,yc))
else:
self.leave_notify_event(guiEvent)
show = cbook.deprecated("2.2", name="FigureCanvasTk.show",
alternative="FigureCanvasTk.draw")(
lambda self: self.draw())
def draw_idle(self):
'update drawing area only if idle'
if self._idle is False:
return
self._idle = False
def idle_draw(*args):
try:
self.draw()
finally:
self._idle = True
self._idle_callback = self._tkcanvas.after_idle(idle_draw)
def get_tk_widget(self):
"""returns the Tk widget used to implement FigureCanvasTkAgg.
Although the initial implementation uses a Tk canvas, this routine
is intended to hide that fact.
"""
return self._tkcanvas
def motion_notify_event(self, event):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.figure.bbox.height - event.y
FigureCanvasBase.motion_notify_event(self, x, y, guiEvent=event)
def button_press_event(self, event, dblclick=False):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.figure.bbox.height - event.y
num = getattr(event, 'num', None)
if sys.platform=='darwin':
# 2 and 3 were reversed on the OSX platform I
# tested under tkagg
if num==2: num=3
elif num==3: num=2
FigureCanvasBase.button_press_event(self, x, y, num, dblclick=dblclick, guiEvent=event)
def button_dblclick_event(self,event):
self.button_press_event(event,dblclick=True)
def button_release_event(self, event):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.figure.bbox.height - event.y
num = getattr(event, 'num', None)
if sys.platform=='darwin':
# 2 and 3 were reversed on the OSX platform I
# tested under tkagg
if num==2: num=3
elif num==3: num=2
FigureCanvasBase.button_release_event(self, x, y, num, guiEvent=event)
def scroll_event(self, event):
x = event.x
y = self.figure.bbox.height - event.y
num = getattr(event, 'num', None)
if num==4: step = +1
elif num==5: step = -1
else: step = 0
FigureCanvasBase.scroll_event(self, x, y, step, guiEvent=event)
def scroll_event_windows(self, event):
"""MouseWheel event processor"""
# need to find the window that contains the mouse
w = event.widget.winfo_containing(event.x_root, event.y_root)
if w == self._tkcanvas:
x = event.x_root - w.winfo_rootx()
y = event.y_root - w.winfo_rooty()
y = self.figure.bbox.height - y
step = event.delta/120.
FigureCanvasBase.scroll_event(self, x, y, step, guiEvent=event)
def _get_key(self, event):
val = event.keysym_num
if val in self.keyvald:
key = self.keyvald[val]
elif val == 0 and sys.platform == 'darwin' and \
event.keycode in self._keycode_lookup:
key = self._keycode_lookup[event.keycode]
elif val < 256:
key = chr(val)
else:
key = None
# add modifier keys to the key string. Bit details originate from
# http://effbot.org/tkinterbook/tkinter-events-and-bindings.htm
# BIT_SHIFT = 0x001; BIT_CAPSLOCK = 0x002; BIT_CONTROL = 0x004;
# BIT_LEFT_ALT = 0x008; BIT_NUMLOCK = 0x010; BIT_RIGHT_ALT = 0x080;
# BIT_MB_1 = 0x100; BIT_MB_2 = 0x200; BIT_MB_3 = 0x400;
# In general, the modifier key is excluded from the modifier flag,
# however this is not the case on "darwin", so double check that
# we aren't adding repeat modifier flags to a modifier key.
if sys.platform == 'win32':
modifiers = [(17, 'alt', 'alt'),
(2, 'ctrl', 'control'),
]
elif sys.platform == 'darwin':
modifiers = [(3, 'super', 'super'),
(4, 'alt', 'alt'),
(2, 'ctrl', 'control'),
]
else:
modifiers = [(6, 'super', 'super'),
(3, 'alt', 'alt'),
(2, 'ctrl', 'control'),
]
if key is not None:
# note, shift is not added to the keys as this is already accounted for
for bitmask, prefix, key_name in modifiers:
if event.state & (1 << bitmask) and key_name not in key:
key = '{0}+{1}'.format(prefix, key)
return key
def key_press(self, event):
key = self._get_key(event)
FigureCanvasBase.key_press_event(self, key, guiEvent=event)
def key_release(self, event):
key = self._get_key(event)
FigureCanvasBase.key_release_event(self, key, guiEvent=event)
def new_timer(self, *args, **kwargs):
"""
Creates a new backend-specific subclass of :class:`backend_bases.Timer`.
This is useful for getting periodic events through the backend's native
event loop. Implemented only for backends with GUIs.
Other Parameters
----------------
interval : scalar
Timer interval in milliseconds
callbacks : list
Sequence of (func, args, kwargs) where ``func(*args, **kwargs)``
will be executed by the timer every *interval*.
"""
return TimerTk(self._tkcanvas, *args, **kwargs)
def flush_events(self):
self._master.update()
class FigureManagerTk(FigureManagerBase):
"""
Attributes
----------
canvas : `FigureCanvas`
The FigureCanvas instance
num : int or str
The Figure number
toolbar : tk.Toolbar
The tk.Toolbar
window : tk.Window
The tk.Window
"""
def __init__(self, canvas, num, window):
FigureManagerBase.__init__(self, canvas, num)
self.window = window
self.window.withdraw()
self.set_window_title("Figure %d" % num)
self.canvas = canvas
self.canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self._num = num
self.toolmanager = self._get_toolmanager()
self.toolbar = self._get_toolbar()
self.statusbar = None
if self.toolmanager:
backend_tools.add_tools_to_manager(self.toolmanager)
if self.toolbar:
backend_tools.add_tools_to_container(self.toolbar)
self.statusbar = StatusbarTk(self.window, self.toolmanager)
self._shown = False
def notify_axes_change(fig):
'this will be called whenever the current axes is changed'
if self.toolmanager is not None:
pass
elif self.toolbar is not None:
self.toolbar.update()
self.canvas.figure.add_axobserver(notify_axes_change)
def _get_toolbar(self):
if matplotlib.rcParams['toolbar'] == 'toolbar2':
toolbar = NavigationToolbar2Tk(self.canvas, self.window)
elif matplotlib.rcParams['toolbar'] == 'toolmanager':
toolbar = ToolbarTk(self.toolmanager, self.window)
else:
toolbar = None
return toolbar
def _get_toolmanager(self):
if rcParams['toolbar'] == 'toolmanager':
toolmanager = ToolManager(self.canvas.figure)
else:
toolmanager = None
return toolmanager
def resize(self, width, height=None):
# before 09-12-22, the resize method takes a single *event*
# parameter. On the other hand, the resize method of other
# FigureManager class takes *width* and *height* parameter,
# which is used to change the size of the window. For the
# Figure.set_size_inches with forward=True work with Tk
# backend, I changed the function signature but tried to keep
# it backward compatible. -JJL
# when a single parameter is given, consider it as a event
if height is None:
cbook.warn_deprecated("2.2", "FigureManagerTkAgg.resize now takes "
"width and height as separate arguments")
width = width.width
else:
self.canvas._tkcanvas.master.geometry("%dx%d" % (width, height))
if self.toolbar is not None:
self.toolbar.configure(width=width)
def show(self):
"""
this function doesn't segfault but causes the
PyEval_RestoreThread: NULL state bug on win32
"""
_focus = windowing.FocusManager()
if not self._shown:
def destroy(*args):
self.window = None
Gcf.destroy(self._num)
self.canvas._tkcanvas.bind("<Destroy>", destroy)
self.window.deiconify()
else:
self.canvas.draw_idle()
# Raise the new window.
self.canvas.manager.window.attributes('-topmost', 1)
self.canvas.manager.window.attributes('-topmost', 0)
self._shown = True
def destroy(self, *args):
if self.window is not None:
#self.toolbar.destroy()
if self.canvas._idle_callback:
self.canvas._tkcanvas.after_cancel(self.canvas._idle_callback)
self.window.destroy()
if Gcf.get_num_fig_managers()==0:
if self.window is not None:
self.window.quit()
self.window = None
def get_window_title(self):
return self.window.wm_title()
def set_window_title(self, title):
self.window.wm_title(title)
def full_screen_toggle(self):
is_fullscreen = bool(self.window.attributes('-fullscreen'))
self.window.attributes('-fullscreen', not is_fullscreen)
@cbook.deprecated("2.2")
class AxisMenu(object):
def __init__(self, master, naxes):
self._master = master
self._naxes = naxes
self._mbar = Tk.Frame(master=master, relief=Tk.RAISED, borderwidth=2)
self._mbar.pack(side=Tk.LEFT)
self._mbutton = Tk.Menubutton(
master=self._mbar, text="Axes", underline=0)
self._mbutton.pack(side=Tk.LEFT, padx="2m")
self._mbutton.menu = Tk.Menu(self._mbutton)
self._mbutton.menu.add_command(
label="Select All", command=self.select_all)
self._mbutton.menu.add_command(
label="Invert All", command=self.invert_all)
self._axis_var = []
self._checkbutton = []
for i in range(naxes):
self._axis_var.append(Tk.IntVar())
self._axis_var[i].set(1)
self._checkbutton.append(self._mbutton.menu.add_checkbutton(
label = "Axis %d" % (i+1),
variable=self._axis_var[i],
command=self.set_active))
self._mbutton.menu.invoke(self._mbutton.menu.index("Select All"))
self._mbutton['menu'] = self._mbutton.menu
self._mbar.tk_menuBar(self._mbutton)
self.set_active()
def adjust(self, naxes):
if self._naxes < naxes:
for i in range(self._naxes, naxes):
self._axis_var.append(Tk.IntVar())
self._axis_var[i].set(1)
self._checkbutton.append( self._mbutton.menu.add_checkbutton(
label = "Axis %d" % (i+1),
variable=self._axis_var[i],
command=self.set_active))
elif self._naxes > naxes:
for i in range(self._naxes-1, naxes-1, -1):
del self._axis_var[i]
self._mbutton.menu.forget(self._checkbutton[i])
del self._checkbutton[i]
self._naxes = naxes
self.set_active()
def get_indices(self):
a = [i for i in range(len(self._axis_var)) if self._axis_var[i].get()]
return a
def set_active(self):
self._master.set_active(self.get_indices())
def invert_all(self):
for a in self._axis_var:
a.set(not a.get())
self.set_active()
def select_all(self):
for a in self._axis_var:
a.set(1)
self.set_active()
class NavigationToolbar2Tk(NavigationToolbar2, Tk.Frame):
"""
Attributes
----------
canvas : `FigureCanvas`
the figure canvas on which to operate
win : tk.Window
the tk.Window which owns this toolbar
"""
def __init__(self, canvas, window):
self.canvas = canvas
self.window = window
NavigationToolbar2.__init__(self, canvas)
def destroy(self, *args):
del self.message
Tk.Frame.destroy(self, *args)
def set_message(self, s):
self.message.set(s)
def draw_rubberband(self, event, x0, y0, x1, y1):
height = self.canvas.figure.bbox.height
y0 = height - y0
y1 = height - y1
if hasattr(self, "lastrect"):
self.canvas._tkcanvas.delete(self.lastrect)
self.lastrect = self.canvas._tkcanvas.create_rectangle(x0, y0, x1, y1)
#self.canvas.draw()
def release(self, event):
try: self.lastrect
except AttributeError: pass
else:
self.canvas._tkcanvas.delete(self.lastrect)
del self.lastrect
def set_cursor(self, cursor):
self.window.configure(cursor=cursord[cursor])
self.window.update_idletasks()
def _Button(self, text, file, command, extension='.gif'):
img_file = os.path.join(
rcParams['datapath'], 'images', file + extension)
im = Tk.PhotoImage(master=self, file=img_file)
b = Tk.Button(
master=self, text=text, padx=2, pady=2, image=im, command=command)
b._ntimage = im
b.pack(side=Tk.LEFT)
return b
def _Spacer(self):
# Buttons are 30px high, so make this 26px tall with padding to center it
s = Tk.Frame(
master=self, height=26, relief=Tk.RIDGE, pady=2, bg="DarkGray")
s.pack(side=Tk.LEFT, padx=5)
return s
def _init_toolbar(self):
xmin, xmax = self.canvas.figure.bbox.intervalx
height, width = 50, xmax-xmin
Tk.Frame.__init__(self, master=self.window,
width=int(width), height=int(height),
borderwidth=2)
self.update() # Make axes menu
for text, tooltip_text, image_file, callback in self.toolitems:
if text is None:
# Add a spacer; return value is unused.
self._Spacer()
else:
button = self._Button(text=text, file=image_file,
command=getattr(self, callback))
if tooltip_text is not None:
ToolTip.createToolTip(button, tooltip_text)
self.message = Tk.StringVar(master=self)
self._message_label = Tk.Label(master=self, textvariable=self.message)
self._message_label.pack(side=Tk.RIGHT)
self.pack(side=Tk.BOTTOM, fill=Tk.X)
def configure_subplots(self):
toolfig = Figure(figsize=(6,3))
window = Tk.Toplevel()
canvas = type(self.canvas)(toolfig, master=window)
toolfig.subplots_adjust(top=0.9)
canvas.tool = SubplotTool(self.canvas.figure, toolfig)
canvas.draw()
canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
window.grab_set()
def save_figure(self, *args):
from six.moves import tkinter_tkfiledialog, tkinter_messagebox
filetypes = self.canvas.get_supported_filetypes().copy()
default_filetype = self.canvas.get_default_filetype()
# Tk doesn't provide a way to choose a default filetype,
# so we just have to put it first
default_filetype_name = filetypes.pop(default_filetype)
sorted_filetypes = ([(default_filetype, default_filetype_name)]
+ sorted(six.iteritems(filetypes)))
tk_filetypes = [(name, '*.%s' % ext) for ext, name in sorted_filetypes]
# adding a default extension seems to break the
# asksaveasfilename dialog when you choose various save types
# from the dropdown. Passing in the empty string seems to
# work - JDH!
#defaultextension = self.canvas.get_default_filetype()
defaultextension = ''
initialdir = os.path.expanduser(rcParams['savefig.directory'])
initialfile = self.canvas.get_default_filename()
fname = tkinter_tkfiledialog.asksaveasfilename(
master=self.window,
title='Save the figure',
filetypes=tk_filetypes,
defaultextension=defaultextension,
initialdir=initialdir,
initialfile=initialfile,
)
if fname in ["", ()]:
return
# Save dir for next time, unless empty str (i.e., use cwd).
if initialdir != "":
rcParams['savefig.directory'] = (
os.path.dirname(six.text_type(fname)))
try:
# This method will handle the delegation to the correct type
self.canvas.figure.savefig(fname)
except Exception as e:
tkinter_messagebox.showerror("Error saving file", str(e))
def set_active(self, ind):
self._ind = ind
self._active = [self._axes[i] for i in self._ind]
def update(self):
_focus = windowing.FocusManager()
self._axes = self.canvas.figure.axes
NavigationToolbar2.update(self)
class ToolTip(object):
"""
Tooltip recipe from
http://www.voidspace.org.uk/python/weblog/arch_d7_2006_07_01.shtml#e387
"""
@staticmethod
def createToolTip(widget, text):
toolTip = ToolTip(widget)
def enter(event):
toolTip.showtip(text)
def leave(event):
toolTip.hidetip()
widget.bind('<Enter>', enter)
widget.bind('<Leave>', leave)
def __init__(self, widget):
self.widget = widget
self.tipwindow = None
self.id = None
self.x = self.y = 0
def showtip(self, text):
"Display text in tooltip window"
self.text = text
if self.tipwindow or not self.text:
return
x, y, _, _ = self.widget.bbox("insert")
x = x + self.widget.winfo_rootx() + 27
y = y + self.widget.winfo_rooty()
self.tipwindow = tw = Tk.Toplevel(self.widget)
tw.wm_overrideredirect(1)
tw.wm_geometry("+%d+%d" % (x, y))
try:
# For Mac OS
tw.tk.call("::tk::unsupported::MacWindowStyle",
"style", tw._w,
"help", "noActivates")
except Tk.TclError:
pass
label = Tk.Label(tw, text=self.text, justify=Tk.LEFT,
background="#ffffe0", relief=Tk.SOLID, borderwidth=1)
label.pack(ipadx=1)
def hidetip(self):
tw = self.tipwindow
self.tipwindow = None
if tw:
tw.destroy()
class RubberbandTk(backend_tools.RubberbandBase):
def __init__(self, *args, **kwargs):
backend_tools.RubberbandBase.__init__(self, *args, **kwargs)
def draw_rubberband(self, x0, y0, x1, y1):
height = self.figure.canvas.figure.bbox.height
y0 = height - y0
y1 = height - y1
if hasattr(self, "lastrect"):
self.figure.canvas._tkcanvas.delete(self.lastrect)
self.lastrect = self.figure.canvas._tkcanvas.create_rectangle(
x0, y0, x1, y1)
def remove_rubberband(self):
if hasattr(self, "lastrect"):
self.figure.canvas._tkcanvas.delete(self.lastrect)
del self.lastrect
class SetCursorTk(backend_tools.SetCursorBase):
def set_cursor(self, cursor):
self.figure.canvas.manager.window.configure(cursor=cursord[cursor])
class ToolbarTk(ToolContainerBase, Tk.Frame):
_icon_extension = '.gif'
def __init__(self, toolmanager, window):
ToolContainerBase.__init__(self, toolmanager)
xmin, xmax = self.toolmanager.canvas.figure.bbox.intervalx
height, width = 50, xmax - xmin
Tk.Frame.__init__(self, master=window,
width=int(width), height=int(height),
borderwidth=2)
self._toolitems = {}
self.pack(side=Tk.TOP, fill=Tk.X)
self._groups = {}
def add_toolitem(
self, name, group, position, image_file, description, toggle):
frame = self._get_groupframe(group)
button = self._Button(name, image_file, toggle, frame)
if description is not None:
ToolTip.createToolTip(button, description)
self._toolitems.setdefault(name, [])
self._toolitems[name].append(button)
def _get_groupframe(self, group):
if group not in self._groups:
if self._groups:
self._add_separator()
frame = Tk.Frame(master=self, borderwidth=0)
frame.pack(side=Tk.LEFT, fill=Tk.Y)
self._groups[group] = frame
return self._groups[group]
def _add_separator(self):
separator = Tk.Frame(master=self, bd=5, width=1, bg='black')
separator.pack(side=Tk.LEFT, fill=Tk.Y, padx=2)
def _Button(self, text, image_file, toggle, frame):
if image_file is not None:
im = Tk.PhotoImage(master=self, file=image_file)
else:
im = None
if not toggle:
b = Tk.Button(master=frame, text=text, padx=2, pady=2, image=im,
command=lambda: self._button_click(text))
else:
# There is a bug in tkinter included in some python 3.6 versions
# that without this variable, produces a "visual" toggling of
# other near checkbuttons
# https://bugs.python.org/issue29402
# https://bugs.python.org/issue25684
var = Tk.IntVar()
b = Tk.Checkbutton(master=frame, text=text, padx=2, pady=2,
image=im, indicatoron=False,
command=lambda: self._button_click(text),
variable=var)
b._ntimage = im
b.pack(side=Tk.LEFT)
return b
def _button_click(self, name):
self.trigger_tool(name)
def toggle_toolitem(self, name, toggled):
if name not in self._toolitems:
return
for toolitem in self._toolitems[name]:
if toggled:
toolitem.select()
else:
toolitem.deselect()
def remove_toolitem(self, name):
for toolitem in self._toolitems[name]:
toolitem.pack_forget()
del self._toolitems[name]
class StatusbarTk(StatusbarBase, Tk.Frame):
def __init__(self, window, *args, **kwargs):
StatusbarBase.__init__(self, *args, **kwargs)
xmin, xmax = self.toolmanager.canvas.figure.bbox.intervalx
height, width = 50, xmax - xmin
Tk.Frame.__init__(self, master=window,
width=int(width), height=int(height),
borderwidth=2)
self._message = Tk.StringVar(master=self)
self._message_label = Tk.Label(master=self, textvariable=self._message)
self._message_label.pack(side=Tk.RIGHT)
self.pack(side=Tk.TOP, fill=Tk.X)
def set_message(self, s):
self._message.set(s)
class SaveFigureTk(backend_tools.SaveFigureBase):
def trigger(self, *args):
from six.moves import tkinter_tkfiledialog, tkinter_messagebox
filetypes = self.figure.canvas.get_supported_filetypes().copy()
default_filetype = self.figure.canvas.get_default_filetype()
# Tk doesn't provide a way to choose a default filetype,
# so we just have to put it first
default_filetype_name = filetypes.pop(default_filetype)
sorted_filetypes = ([(default_filetype, default_filetype_name)]
+ sorted(six.iteritems(filetypes)))
tk_filetypes = [(name, '*.%s' % ext) for ext, name in sorted_filetypes]
# adding a default extension seems to break the
# asksaveasfilename dialog when you choose various save types
# from the dropdown. Passing in the empty string seems to
# work - JDH!
# defaultextension = self.figure.canvas.get_default_filetype()
defaultextension = ''
initialdir = os.path.expanduser(rcParams['savefig.directory'])
initialfile = self.figure.canvas.get_default_filename()
fname = tkinter_tkfiledialog.asksaveasfilename(
master=self.figure.canvas.manager.window,
title='Save the figure',
filetypes=tk_filetypes,
defaultextension=defaultextension,
initialdir=initialdir,
initialfile=initialfile,
)
if fname == "" or fname == ():
return
else:
if initialdir == '':
# explicitly missing key or empty str signals to use cwd
rcParams['savefig.directory'] = initialdir
else:
# save dir for next time
rcParams['savefig.directory'] = os.path.dirname(
six.text_type(fname))
try:
# This method will handle the delegation to the correct type
self.figure.savefig(fname)
except Exception as e:
tkinter_messagebox.showerror("Error saving file", str(e))
class ConfigureSubplotsTk(backend_tools.ConfigureSubplotsBase):
def __init__(self, *args, **kwargs):
backend_tools.ConfigureSubplotsBase.__init__(self, *args, **kwargs)
self.window = None
def trigger(self, *args):
self.init_window()
self.window.lift()
def init_window(self):
if self.window:
return
toolfig = Figure(figsize=(6, 3))
self.window = Tk.Tk()
canvas = type(self.canvas)(toolfig, master=self.window)
toolfig.subplots_adjust(top=0.9)
_tool = SubplotTool(self.figure, toolfig)
canvas.draw()
canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
self.window.protocol("WM_DELETE_WINDOW", self.destroy)
def destroy(self, *args, **kwargs):
self.window.destroy()
self.window = None
backend_tools.ToolSaveFigure = SaveFigureTk
backend_tools.ToolConfigureSubplots = ConfigureSubplotsTk
backend_tools.ToolSetCursor = SetCursorTk
backend_tools.ToolRubberband = RubberbandTk
Toolbar = ToolbarTk
@_Backend.export
class _BackendTk(_Backend):
FigureManager = FigureManagerTk
@classmethod
def new_figure_manager_given_figure(cls, num, figure):
"""
Create a new figure manager instance for the given figure.
"""
_focus = windowing.FocusManager()
window = Tk.Tk(className="matplotlib")
window.withdraw()
# Put a mpl icon on the window rather than the default tk icon.
# Tkinter doesn't allow colour icons on linux systems, but tk>=8.5 has
# a iconphoto command which we call directly. Source:
# http://mail.python.org/pipermail/tkinter-discuss/2006-November/000954.html
icon_fname = os.path.join(
rcParams['datapath'], 'images', 'matplotlib.ppm')
icon_img = Tk.PhotoImage(file=icon_fname)
try:
window.tk.call('wm', 'iconphoto', window._w, icon_img)
except Exception as exc:
# log the failure (due e.g. to Tk version), but carry on
_log.info('Could not load matplotlib icon: %s', exc)
canvas = cls.FigureCanvas(figure, master=window)
manager = cls.FigureManager(canvas, num, window)
if matplotlib.is_interactive():
manager.show()
canvas.draw_idle()
return manager
@staticmethod
def trigger_manager_draw(manager):
manager.show()
@staticmethod
def mainloop():
Tk.mainloop()
| 39,322 | 35.613594 | 166 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_qt4cairo.py | from .backend_qt5cairo import _BackendQT5Cairo
@_BackendQT5Cairo.export
class _BackendQT4Cairo(_BackendQT5Cairo):
pass
| 125 | 17 | 46 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_ps.py | """
A PostScript backend, which can produce both PostScript .ps and .eps
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import StringIO
import glob, os, shutil, sys, time, datetime
import io
import logging
from tempfile import mkstemp
from matplotlib import cbook, __version__, rcParams, checkdep_ghostscript
from matplotlib.afm import AFM
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
RendererBase)
from matplotlib.cbook import (get_realpath_and_stat, is_writable_file_like,
maxdict, file_requires_unicode)
from matplotlib.compat.subprocess import subprocess
from matplotlib.font_manager import findfont, is_opentype_cff_font, get_font
from matplotlib.ft2font import KERNING_DEFAULT, LOAD_NO_HINTING
from matplotlib.ttconv import convert_ttf_to_ps
from matplotlib.mathtext import MathTextParser
from matplotlib._mathtext_data import uni2type1
from matplotlib.path import Path
from matplotlib import _path
from matplotlib.transforms import Affine2D
from matplotlib.backends.backend_mixed import MixedModeRenderer
import numpy as np
import binascii
import re
_log = logging.getLogger(__name__)
backend_version = 'Level II'
debugPS = 0
class PsBackendHelper(object):
def __init__(self):
self._cached = {}
@property
def gs_exe(self):
"""
executable name of ghostscript.
"""
try:
return self._cached["gs_exe"]
except KeyError:
pass
gs_exe, gs_version = checkdep_ghostscript()
if gs_exe is None:
gs_exe = 'gs'
self._cached["gs_exe"] = str(gs_exe)
return str(gs_exe)
@property
def gs_version(self):
"""
version of ghostscript.
"""
try:
return self._cached["gs_version"]
except KeyError:
pass
from matplotlib.compat.subprocess import Popen, PIPE
s = Popen([self.gs_exe, "--version"], stdout=PIPE)
pipe, stderr = s.communicate()
if six.PY3:
ver = pipe.decode('ascii')
else:
ver = pipe
try:
gs_version = tuple(map(int, ver.strip().split(".")))
except ValueError:
# if something went wrong parsing return null version number
gs_version = (0, 0)
self._cached["gs_version"] = gs_version
return gs_version
@property
def supports_ps2write(self):
"""
True if the installed ghostscript supports ps2write device.
"""
return self.gs_version[0] >= 9
ps_backend_helper = PsBackendHelper()
papersize = {'letter': (8.5,11),
'legal': (8.5,14),
'ledger': (11,17),
'a0': (33.11,46.81),
'a1': (23.39,33.11),
'a2': (16.54,23.39),
'a3': (11.69,16.54),
'a4': (8.27,11.69),
'a5': (5.83,8.27),
'a6': (4.13,5.83),
'a7': (2.91,4.13),
'a8': (2.07,2.91),
'a9': (1.457,2.05),
'a10': (1.02,1.457),
'b0': (40.55,57.32),
'b1': (28.66,40.55),
'b2': (20.27,28.66),
'b3': (14.33,20.27),
'b4': (10.11,14.33),
'b5': (7.16,10.11),
'b6': (5.04,7.16),
'b7': (3.58,5.04),
'b8': (2.51,3.58),
'b9': (1.76,2.51),
'b10': (1.26,1.76)}
def _get_papertype(w, h):
keys = list(six.iterkeys(papersize))
keys.sort()
keys.reverse()
for key in keys:
if key.startswith('l'): continue
pw, ph = papersize[key]
if (w < pw) and (h < ph): return key
return 'a0'
def _num_to_str(val):
if isinstance(val, six.string_types): return val
ival = int(val)
if val == ival: return str(ival)
s = "%1.3f"%val
s = s.rstrip("0")
s = s.rstrip(".")
return s
def _nums_to_str(*args):
return ' '.join(map(_num_to_str,args))
def quote_ps_string(s):
"Quote dangerous characters of S for use in a PostScript string constant."
s = s.replace(b"\\", b"\\\\")
s = s.replace(b"(", b"\\(")
s = s.replace(b")", b"\\)")
s = s.replace(b"'", b"\\251")
s = s.replace(b"`", b"\\301")
s = re.sub(br"[^ -~\n]", lambda x: br"\%03o" % ord(x.group()), s)
return s.decode('ascii')
def _move_path_to_path_or_stream(src, dst):
"""Move the contents of file at *src* to path-or-filelike *dst*.
If *dst* is a path, the metadata of *src* are *not* copied.
"""
if is_writable_file_like(dst):
fh = (io.open(src, 'r', encoding='latin-1')
if file_requires_unicode(dst)
else io.open(src, 'rb'))
with fh:
shutil.copyfileobj(fh, dst)
else:
# Py3: shutil.move(src, dst, copy_function=shutil.copyfile)
open(dst, 'w').close()
mode = os.stat(dst).st_mode
shutil.move(src, dst)
os.chmod(dst, mode)
class RendererPS(RendererBase):
"""
The renderer handles all the drawing primitives using a graphics
context instance that controls the colors/styles.
"""
afmfontd = maxdict(50)
def __init__(self, width, height, pswriter, imagedpi=72):
"""
Although postscript itself is dpi independent, we need to
imform the image code about a requested dpi to generate high
res images and them scale them before embeddin them
"""
RendererBase.__init__(self)
self.width = width
self.height = height
self._pswriter = pswriter
if rcParams['text.usetex']:
self.textcnt = 0
self.psfrag = []
self.imagedpi = imagedpi
# current renderer state (None=uninitialised)
self.color = None
self.linewidth = None
self.linejoin = None
self.linecap = None
self.linedash = None
self.fontname = None
self.fontsize = None
self._hatches = {}
self.image_magnification = imagedpi/72.0
self._clip_paths = {}
self._path_collection_id = 0
self.used_characters = {}
self.mathtext_parser = MathTextParser("PS")
self._afm_font_dir = os.path.join(
rcParams['datapath'], 'fonts', 'afm')
def track_characters(self, font, s):
"""Keeps track of which characters are required from
each font."""
realpath, stat_key = get_realpath_and_stat(font.fname)
used_characters = self.used_characters.setdefault(
stat_key, (realpath, set()))
used_characters[1].update([ord(x) for x in s])
def merge_used_characters(self, other):
for stat_key, (realpath, charset) in six.iteritems(other):
used_characters = self.used_characters.setdefault(
stat_key, (realpath, set()))
used_characters[1].update(charset)
def set_color(self, r, g, b, store=1):
if (r,g,b) != self.color:
if r==g and r==b:
self._pswriter.write("%1.3f setgray\n"%r)
else:
self._pswriter.write("%1.3f %1.3f %1.3f setrgbcolor\n"%(r,g,b))
if store: self.color = (r,g,b)
def set_linewidth(self, linewidth, store=1):
linewidth = float(linewidth)
if linewidth != self.linewidth:
self._pswriter.write("%1.3f setlinewidth\n"%linewidth)
if store: self.linewidth = linewidth
def set_linejoin(self, linejoin, store=1):
if linejoin != self.linejoin:
self._pswriter.write("%d setlinejoin\n"%linejoin)
if store: self.linejoin = linejoin
def set_linecap(self, linecap, store=1):
if linecap != self.linecap:
self._pswriter.write("%d setlinecap\n"%linecap)
if store: self.linecap = linecap
def set_linedash(self, offset, seq, store=1):
if self.linedash is not None:
oldo, oldseq = self.linedash
if np.array_equal(seq, oldseq) and oldo == offset:
return
if seq is not None and len(seq):
s="[%s] %d setdash\n"%(_nums_to_str(*seq), offset)
self._pswriter.write(s)
else:
self._pswriter.write("[] 0 setdash\n")
if store:
self.linedash = (offset, seq)
def set_font(self, fontname, fontsize, store=1):
if rcParams['ps.useafm']: return
if (fontname,fontsize) != (self.fontname,self.fontsize):
out = ("/%s findfont\n"
"%1.3f scalefont\n"
"setfont\n" % (fontname, fontsize))
self._pswriter.write(out)
if store: self.fontname = fontname
if store: self.fontsize = fontsize
def create_hatch(self, hatch):
sidelen = 72
if hatch in self._hatches:
return self._hatches[hatch]
name = 'H%d' % len(self._hatches)
linewidth = rcParams['hatch.linewidth']
pageheight = self.height * 72
self._pswriter.write("""\
<< /PatternType 1
/PaintType 2
/TilingType 2
/BBox[0 0 %(sidelen)d %(sidelen)d]
/XStep %(sidelen)d
/YStep %(sidelen)d
/PaintProc {
pop
%(linewidth)f setlinewidth
""" % locals())
self._pswriter.write(
self._convert_path(Path.hatch(hatch), Affine2D().scale(sidelen),
simplify=False))
self._pswriter.write("""\
fill
stroke
} bind
>>
matrix
0.0 %(pageheight)f translate
makepattern
/%(name)s exch def
""" % locals())
self._hatches[hatch] = name
return name
def get_canvas_width_height(self):
'return the canvas width and height in display coords'
return self.width * 72.0, self.height * 72.0
def get_text_width_height_descent(self, s, prop, ismath):
"""
get the width and height in display coords of the string s
with FontPropertry prop
"""
if rcParams['text.usetex']:
texmanager = self.get_texmanager()
fontsize = prop.get_size_in_points()
w, h, d = texmanager.get_text_width_height_descent(s, fontsize,
renderer=self)
return w, h, d
if ismath:
width, height, descent, pswriter, used_characters = \
self.mathtext_parser.parse(s, 72, prop)
return width, height, descent
if rcParams['ps.useafm']:
if ismath: s = s[1:-1]
font = self._get_font_afm(prop)
l,b,w,h,d = font.get_str_bbox_and_descent(s)
fontsize = prop.get_size_in_points()
scale = 0.001*fontsize
w *= scale
h *= scale
d *= scale
return w, h, d
font = self._get_font_ttf(prop)
font.set_text(s, 0.0, flags=LOAD_NO_HINTING)
w, h = font.get_width_height()
w /= 64.0 # convert from subpixels
h /= 64.0
d = font.get_descent()
d /= 64.0
return w, h, d
def flipy(self):
'return true if small y numbers are top for renderer'
return False
def _get_font_afm(self, prop):
key = hash(prop)
font = self.afmfontd.get(key)
if font is None:
fname = findfont(prop, fontext='afm', directory=self._afm_font_dir)
if fname is None:
fname = findfont(
"Helvetica", fontext='afm', directory=self._afm_font_dir)
font = self.afmfontd.get(fname)
if font is None:
with io.open(fname, 'rb') as fh:
font = AFM(fh)
self.afmfontd[fname] = font
self.afmfontd[key] = font
return font
def _get_font_ttf(self, prop):
fname = findfont(prop)
font = get_font(fname)
font.clear()
size = prop.get_size_in_points()
font.set_size(size, 72.0)
return font
def _rgb(self, rgba):
h, w = rgba.shape[:2]
rgb = rgba[::-1, :, :3]
return h, w, rgb.tostring()
def _hex_lines(self, s, chars_per_line=128):
s = binascii.b2a_hex(s)
nhex = len(s)
lines = []
for i in range(0,nhex,chars_per_line):
limit = min(i+chars_per_line, nhex)
lines.append(s[i:limit])
return lines
def get_image_magnification(self):
"""
Get the factor by which to magnify images passed to draw_image.
Allows a backend to have images at a different resolution to other
artists.
"""
return self.image_magnification
def option_scale_image(self):
"""
ps backend support arbitrary scaling of image.
"""
return True
def option_image_nocomposite(self):
"""
return whether to generate a composite image from multiple images on
a set of axes
"""
return not rcParams['image.composite_image']
def _get_image_h_w_bits_command(self, im):
h, w, bits = self._rgb(im)
imagecmd = "false 3 colorimage"
return h, w, bits, imagecmd
def draw_image(self, gc, x, y, im, transform=None):
"""
Draw the Image instance into the current axes; x is the
distance in pixels from the left hand side of the canvas and y
is the distance from bottom
"""
h, w, bits, imagecmd = self._get_image_h_w_bits_command(im)
hexlines = b'\n'.join(self._hex_lines(bits)).decode('ascii')
if transform is None:
matrix = "1 0 0 1 0 0"
xscale = w / self.image_magnification
yscale = h / self.image_magnification
else:
matrix = " ".join(map(str, transform.frozen().to_values()))
xscale = 1.0
yscale = 1.0
figh = self.height * 72
bbox = gc.get_clip_rectangle()
clippath, clippath_trans = gc.get_clip_path()
clip = []
if bbox is not None:
clipx,clipy,clipw,cliph = bbox.bounds
clip.append('%s clipbox' % _nums_to_str(clipw, cliph, clipx, clipy))
if clippath is not None:
id = self._get_clip_path(clippath, clippath_trans)
clip.append('%s' % id)
clip = '\n'.join(clip)
ps = """gsave
%(clip)s
%(x)s %(y)s translate
[%(matrix)s] concat
%(xscale)s %(yscale)s scale
/DataString %(w)s string def
%(w)s %(h)s 8 [ %(w)s 0 0 -%(h)s 0 %(h)s ]
{
currentfile DataString readhexstring pop
} bind %(imagecmd)s
%(hexlines)s
grestore
""" % locals()
self._pswriter.write(ps)
def _convert_path(self, path, transform, clip=False, simplify=None):
if clip:
clip = (0.0, 0.0, self.width * 72.0,
self.height * 72.0)
else:
clip = None
return _path.convert_to_string(
path, transform, clip, simplify, None,
6, [b'm', b'l', b'', b'c', b'cl'], True).decode('ascii')
def _get_clip_path(self, clippath, clippath_transform):
key = (clippath, id(clippath_transform))
pid = self._clip_paths.get(key)
if pid is None:
pid = 'c%x' % len(self._clip_paths)
ps_cmd = ['/%s {' % pid]
ps_cmd.append(self._convert_path(clippath, clippath_transform,
simplify=False))
ps_cmd.extend(['clip', 'newpath', '} bind def\n'])
self._pswriter.write('\n'.join(ps_cmd))
self._clip_paths[key] = pid
return pid
def draw_path(self, gc, path, transform, rgbFace=None):
"""
Draws a Path instance using the given affine transform.
"""
clip = rgbFace is None and gc.get_hatch_path() is None
simplify = path.should_simplify and clip
ps = self._convert_path(path, transform, clip=clip, simplify=simplify)
self._draw_ps(ps, gc, rgbFace)
def draw_markers(
self, gc, marker_path, marker_trans, path, trans, rgbFace=None):
"""
Draw the markers defined by path at each of the positions in x
and y. path coordinates are points, x and y coords will be
transformed by the transform
"""
if debugPS: self._pswriter.write('% draw_markers \n')
if rgbFace:
if len(rgbFace) == 4 and rgbFace[3] == 0:
return
if rgbFace[0] == rgbFace[1] == rgbFace[2]:
ps_color = '%1.3f setgray' % rgbFace[0]
else:
ps_color = '%1.3f %1.3f %1.3f setrgbcolor' % rgbFace[:3]
# construct the generic marker command:
ps_cmd = ['/o {', 'gsave', 'newpath', 'translate'] # don't want the translate to be global
lw = gc.get_linewidth()
stroke = lw != 0.0
if stroke:
ps_cmd.append('%.1f setlinewidth' % lw)
jint = gc.get_joinstyle()
ps_cmd.append('%d setlinejoin' % jint)
cint = gc.get_capstyle()
ps_cmd.append('%d setlinecap' % cint)
ps_cmd.append(self._convert_path(marker_path, marker_trans,
simplify=False))
if rgbFace:
if stroke:
ps_cmd.append('gsave')
ps_cmd.extend([ps_color, 'fill'])
if stroke:
ps_cmd.append('grestore')
if stroke:
ps_cmd.append('stroke')
ps_cmd.extend(['grestore', '} bind def'])
for vertices, code in path.iter_segments(
trans,
clip=(0, 0, self.width*72, self.height*72),
simplify=False):
if len(vertices):
x, y = vertices[-2:]
ps_cmd.append("%g %g o" % (x, y))
ps = '\n'.join(ps_cmd)
self._draw_ps(ps, gc, rgbFace, fill=False, stroke=False)
def draw_path_collection(self, gc, master_transform, paths, all_transforms,
offsets, offsetTrans, facecolors, edgecolors,
linewidths, linestyles, antialiaseds, urls,
offset_position):
# Is the optimization worth it? Rough calculation:
# cost of emitting a path in-line is
# (len_path + 2) * uses_per_path
# cost of definition+use is
# (len_path + 3) + 3 * uses_per_path
len_path = len(paths[0].vertices) if len(paths) > 0 else 0
uses_per_path = self._iter_collection_uses_per_path(
paths, all_transforms, offsets, facecolors, edgecolors)
should_do_optimization = \
len_path + 3 * uses_per_path + 3 < (len_path + 2) * uses_per_path
if not should_do_optimization:
return RendererBase.draw_path_collection(
self, gc, master_transform, paths, all_transforms,
offsets, offsetTrans, facecolors, edgecolors,
linewidths, linestyles, antialiaseds, urls,
offset_position)
write = self._pswriter.write
path_codes = []
for i, (path, transform) in enumerate(self._iter_collection_raw_paths(
master_transform, paths, all_transforms)):
name = 'p%x_%x' % (self._path_collection_id, i)
ps_cmd = ['/%s {' % name,
'newpath', 'translate']
ps_cmd.append(self._convert_path(path, transform, simplify=False))
ps_cmd.extend(['} bind def\n'])
write('\n'.join(ps_cmd))
path_codes.append(name)
for xo, yo, path_id, gc0, rgbFace in self._iter_collection(
gc, master_transform, all_transforms, path_codes, offsets,
offsetTrans, facecolors, edgecolors, linewidths, linestyles,
antialiaseds, urls, offset_position):
ps = "%g %g %s" % (xo, yo, path_id)
self._draw_ps(ps, gc0, rgbFace)
self._path_collection_id += 1
def draw_tex(self, gc, x, y, s, prop, angle, ismath='TeX!', mtext=None):
"""
draw a Text instance
"""
w, h, bl = self.get_text_width_height_descent(s, prop, ismath)
fontsize = prop.get_size_in_points()
thetext = 'psmarker%d' % self.textcnt
color = '%1.3f,%1.3f,%1.3f'% gc.get_rgb()[:3]
fontcmd = {'sans-serif' : r'{\sffamily %s}',
'monospace' : r'{\ttfamily %s}'}.get(
rcParams['font.family'][0], r'{\rmfamily %s}')
s = fontcmd % s
tex = r'\color[rgb]{%s} %s' % (color, s)
corr = 0#w/2*(fontsize-10)/10
if rcParams['text.latex.preview']:
# use baseline alignment!
pos = _nums_to_str(x-corr, y)
self.psfrag.append(r'\psfrag{%s}[Bl][Bl][1][%f]{\fontsize{%f}{%f}%s}'%(thetext, angle, fontsize, fontsize*1.25, tex))
else:
# stick to the bottom alignment, but this may give incorrect baseline some times.
pos = _nums_to_str(x-corr, y-bl)
self.psfrag.append(r'\psfrag{%s}[bl][bl][1][%f]{\fontsize{%f}{%f}%s}'%(thetext, angle, fontsize, fontsize*1.25, tex))
ps = """\
gsave
%(pos)s moveto
(%(thetext)s)
show
grestore
""" % locals()
self._pswriter.write(ps)
self.textcnt += 1
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
"""
Draw a Text instance.
"""
# local to avoid repeated attribute lookups
write = self._pswriter.write
if debugPS:
write("% text\n")
if len(gc.get_rgb()) == 4 and gc.get_rgb()[3] == 0:
return # Special handling for fully transparent.
if ismath=='TeX':
return self.draw_tex(gc, x, y, s, prop, angle)
elif ismath:
return self.draw_mathtext(gc, x, y, s, prop, angle)
elif rcParams['ps.useafm']:
self.set_color(*gc.get_rgb())
font = self._get_font_afm(prop)
fontname = font.get_fontname()
fontsize = prop.get_size_in_points()
scale = 0.001*fontsize
thisx = 0
thisy = font.get_str_bbox_and_descent(s)[4] * scale
last_name = None
lines = []
for c in s:
name = uni2type1.get(ord(c), 'question')
try:
width = font.get_width_from_char_name(name)
except KeyError:
name = 'question'
width = font.get_width_char('?')
if last_name is not None:
kern = font.get_kern_dist_from_name(last_name, name)
else:
kern = 0
last_name = name
thisx += kern * scale
lines.append('%f %f m /%s glyphshow'%(thisx, thisy, name))
thisx += width * scale
thetext = "\n".join(lines)
ps = """\
gsave
/%(fontname)s findfont
%(fontsize)s scalefont
setfont
%(x)f %(y)f translate
%(angle)f rotate
%(thetext)s
grestore
""" % locals()
self._pswriter.write(ps)
else:
font = self._get_font_ttf(prop)
font.set_text(s, 0, flags=LOAD_NO_HINTING)
self.track_characters(font, s)
self.set_color(*gc.get_rgb())
sfnt = font.get_sfnt()
try:
ps_name = sfnt[1, 0, 0, 6].decode('mac_roman')
except KeyError:
ps_name = sfnt[3, 1, 0x0409, 6].decode('utf-16be')
ps_name = ps_name.encode('ascii', 'replace').decode('ascii')
self.set_font(ps_name, prop.get_size_in_points())
lastgind = None
lines = []
thisx = 0
thisy = 0
for c in s:
ccode = ord(c)
gind = font.get_char_index(ccode)
if gind is None:
ccode = ord('?')
name = '.notdef'
gind = 0
else:
name = font.get_glyph_name(gind)
glyph = font.load_char(ccode, flags=LOAD_NO_HINTING)
if lastgind is not None:
kern = font.get_kerning(lastgind, gind, KERNING_DEFAULT)
else:
kern = 0
lastgind = gind
thisx += kern/64.0
lines.append('%f %f m /%s glyphshow'%(thisx, thisy, name))
thisx += glyph.linearHoriAdvance/65536.0
thetext = '\n'.join(lines)
ps = """gsave
%(x)f %(y)f translate
%(angle)f rotate
%(thetext)s
grestore
""" % locals()
self._pswriter.write(ps)
def new_gc(self):
return GraphicsContextPS()
def draw_mathtext(self, gc,
x, y, s, prop, angle):
"""
Draw the math text using matplotlib.mathtext
"""
if debugPS:
self._pswriter.write("% mathtext\n")
width, height, descent, pswriter, used_characters = \
self.mathtext_parser.parse(s, 72, prop)
self.merge_used_characters(used_characters)
self.set_color(*gc.get_rgb())
thetext = pswriter.getvalue()
ps = """gsave
%(x)f %(y)f translate
%(angle)f rotate
%(thetext)s
grestore
""" % locals()
self._pswriter.write(ps)
def draw_gouraud_triangle(self, gc, points, colors, trans):
self.draw_gouraud_triangles(gc, points.reshape((1, 3, 2)),
colors.reshape((1, 3, 4)), trans)
def draw_gouraud_triangles(self, gc, points, colors, trans):
assert len(points) == len(colors)
assert points.ndim == 3
assert points.shape[1] == 3
assert points.shape[2] == 2
assert colors.ndim == 3
assert colors.shape[1] == 3
assert colors.shape[2] == 4
shape = points.shape
flat_points = points.reshape((shape[0] * shape[1], 2))
flat_points = trans.transform(flat_points)
flat_colors = colors.reshape((shape[0] * shape[1], 4))
points_min = np.min(flat_points, axis=0) - (1 << 12)
points_max = np.max(flat_points, axis=0) + (1 << 12)
factor = np.ceil((2 ** 32 - 1) / (points_max - points_min))
xmin, ymin = points_min
xmax, ymax = points_max
streamarr = np.empty(
(shape[0] * shape[1],),
dtype=[('flags', 'u1'),
('points', '>u4', (2,)),
('colors', 'u1', (3,))])
streamarr['flags'] = 0
streamarr['points'] = (flat_points - points_min) * factor
streamarr['colors'] = flat_colors[:, :3] * 255.0
stream = quote_ps_string(streamarr.tostring())
self._pswriter.write("""
gsave
<< /ShadingType 4
/ColorSpace [/DeviceRGB]
/BitsPerCoordinate 32
/BitsPerComponent 8
/BitsPerFlag 8
/AntiAlias true
/Decode [ %(xmin)f %(xmax)f %(ymin)f %(ymax)f 0 1 0 1 0 1 ]
/DataSource (%(stream)s)
>>
shfill
grestore
""" % locals())
def _draw_ps(self, ps, gc, rgbFace, fill=True, stroke=True, command=None):
"""
Emit the PostScript sniplet 'ps' with all the attributes from 'gc'
applied. 'ps' must consist of PostScript commands to construct a path.
The fill and/or stroke kwargs can be set to False if the
'ps' string already includes filling and/or stroking, in
which case _draw_ps is just supplying properties and
clipping.
"""
# local variable eliminates all repeated attribute lookups
write = self._pswriter.write
if debugPS and command:
write("% "+command+"\n")
mightstroke = gc.shouldstroke()
stroke = stroke and mightstroke
fill = (fill and rgbFace is not None and
(len(rgbFace) <= 3 or rgbFace[3] != 0.0))
hatch = gc.get_hatch()
if mightstroke:
self.set_linewidth(gc.get_linewidth())
jint = gc.get_joinstyle()
self.set_linejoin(jint)
cint = gc.get_capstyle()
self.set_linecap(cint)
self.set_linedash(*gc.get_dashes())
self.set_color(*gc.get_rgb()[:3])
write('gsave\n')
cliprect = gc.get_clip_rectangle()
if cliprect:
x,y,w,h=cliprect.bounds
write('%1.4g %1.4g %1.4g %1.4g clipbox\n' % (w,h,x,y))
clippath, clippath_trans = gc.get_clip_path()
if clippath:
id = self._get_clip_path(clippath, clippath_trans)
write('%s\n' % id)
# Jochen, is the strip necessary? - this could be a honking big string
write(ps.strip())
write("\n")
if fill:
if stroke or hatch:
write("gsave\n")
self.set_color(store=0, *rgbFace[:3])
write("fill\n")
if stroke or hatch:
write("grestore\n")
if hatch:
hatch_name = self.create_hatch(hatch)
write("gsave\n")
write("%f %f %f " % gc.get_hatch_color()[:3])
write("%s setpattern fill grestore\n" % hatch_name)
if stroke:
write("stroke\n")
write("grestore\n")
class GraphicsContextPS(GraphicsContextBase):
def get_capstyle(self):
return {'butt':0,
'round':1,
'projecting':2}[GraphicsContextBase.get_capstyle(self)]
def get_joinstyle(self):
return {'miter':0,
'round':1,
'bevel':2}[GraphicsContextBase.get_joinstyle(self)]
def shouldstroke(self):
return (self.get_linewidth() > 0.0 and
(len(self.get_rgb()) <= 3 or self.get_rgb()[3] != 0.0))
class FigureCanvasPS(FigureCanvasBase):
_renderer_class = RendererPS
fixed_dpi = 72
def draw(self):
pass
filetypes = {'ps' : 'Postscript',
'eps' : 'Encapsulated Postscript'}
def get_default_filetype(self):
return 'ps'
def print_ps(self, outfile, *args, **kwargs):
return self._print_ps(outfile, 'ps', *args, **kwargs)
def print_eps(self, outfile, *args, **kwargs):
return self._print_ps(outfile, 'eps', *args, **kwargs)
def _print_ps(self, outfile, format, *args, **kwargs):
papertype = kwargs.pop("papertype", rcParams['ps.papersize'])
papertype = papertype.lower()
if papertype == 'auto':
pass
elif papertype not in papersize:
raise RuntimeError('%s is not a valid papertype. Use one of %s' %
(papertype, ', '.join(papersize)))
orientation = kwargs.pop("orientation", "portrait").lower()
if orientation == 'landscape': isLandscape = True
elif orientation == 'portrait': isLandscape = False
else: raise RuntimeError('Orientation must be "portrait" or "landscape"')
self.figure.set_dpi(72) # Override the dpi kwarg
imagedpi = kwargs.pop("dpi", 72)
facecolor = kwargs.pop("facecolor", "w")
edgecolor = kwargs.pop("edgecolor", "w")
if rcParams['text.usetex']:
self._print_figure_tex(outfile, format, imagedpi, facecolor, edgecolor,
orientation, isLandscape, papertype,
**kwargs)
else:
self._print_figure(outfile, format, imagedpi, facecolor, edgecolor,
orientation, isLandscape, papertype,
**kwargs)
def _print_figure(self, outfile, format, dpi=72, facecolor='w', edgecolor='w',
orientation='portrait', isLandscape=False, papertype=None,
metadata=None, **kwargs):
"""
Render the figure to hardcopy. Set the figure patch face and
edge colors. This is useful because some of the GUIs have a
gray figure face color background and you'll probably want to
override this on hardcopy
If outfile is a string, it is interpreted as a file name.
If the extension matches .ep* write encapsulated postscript,
otherwise write a stand-alone PostScript file.
If outfile is a file object, a stand-alone PostScript file is
written into this file object.
metadata must be a dictionary. Currently, only the value for
the key 'Creator' is used.
"""
isEPSF = format == 'eps'
if isinstance(outfile,
(six.string_types, getattr(os, "PathLike", ()),)):
outfile = title = getattr(os, "fspath", lambda obj: obj)(outfile)
passed_in_file_object = False
elif is_writable_file_like(outfile):
title = None
passed_in_file_object = True
else:
raise ValueError("outfile must be a path or a file-like object")
# find the appropriate papertype
width, height = self.figure.get_size_inches()
if papertype == 'auto':
if isLandscape: papertype = _get_papertype(height, width)
else: papertype = _get_papertype(width, height)
if isLandscape: paperHeight, paperWidth = papersize[papertype]
else: paperWidth, paperHeight = papersize[papertype]
if rcParams['ps.usedistiller'] and not papertype == 'auto':
# distillers will improperly clip eps files if the pagesize is
# too small
if width>paperWidth or height>paperHeight:
if isLandscape:
papertype = _get_papertype(height, width)
paperHeight, paperWidth = papersize[papertype]
else:
papertype = _get_papertype(width, height)
paperWidth, paperHeight = papersize[papertype]
# center the figure on the paper
xo = 72*0.5*(paperWidth - width)
yo = 72*0.5*(paperHeight - height)
l, b, w, h = self.figure.bbox.bounds
llx = xo
lly = yo
urx = llx + w
ury = lly + h
rotation = 0
if isLandscape:
llx, lly, urx, ury = lly, llx, ury, urx
xo, yo = 72*paperHeight - yo, xo
rotation = 90
bbox = (llx, lly, urx, ury)
# generate PostScript code for the figure and store it in a string
origfacecolor = self.figure.get_facecolor()
origedgecolor = self.figure.get_edgecolor()
self.figure.set_facecolor(facecolor)
self.figure.set_edgecolor(edgecolor)
dryrun = kwargs.get("dryrun", False)
if dryrun:
class NullWriter(object):
def write(self, *kl, **kwargs):
pass
self._pswriter = NullWriter()
else:
self._pswriter = io.StringIO()
# mixed mode rendering
_bbox_inches_restore = kwargs.pop("bbox_inches_restore", None)
ps_renderer = self._renderer_class(width, height, self._pswriter,
imagedpi=dpi)
renderer = MixedModeRenderer(self.figure,
width, height, dpi, ps_renderer,
bbox_inches_restore=_bbox_inches_restore)
self.figure.draw(renderer)
if dryrun: # return immediately if dryrun (tightbbox=True)
return
self.figure.set_facecolor(origfacecolor)
self.figure.set_edgecolor(origedgecolor)
# check for custom metadata
if metadata is not None and 'Creator' in metadata:
creator_str = metadata['Creator']
else:
creator_str = "matplotlib version " + __version__ + \
", http://matplotlib.org/"
def print_figure_impl(fh):
# write the PostScript headers
if isEPSF:
print("%!PS-Adobe-3.0 EPSF-3.0", file=fh)
else:
print("%!PS-Adobe-3.0", file=fh)
if title:
print("%%Title: "+title, file=fh)
print("%%Creator: " + creator_str, file=fh)
# get source date from SOURCE_DATE_EPOCH, if set
# See https://reproducible-builds.org/specs/source-date-epoch/
source_date_epoch = os.getenv("SOURCE_DATE_EPOCH")
if source_date_epoch:
source_date = datetime.datetime.utcfromtimestamp(
int(source_date_epoch)).strftime("%a %b %d %H:%M:%S %Y")
else:
source_date = time.ctime()
print("%%CreationDate: "+source_date, file=fh)
print("%%Orientation: " + orientation, file=fh)
if not isEPSF:
print("%%DocumentPaperSizes: "+papertype, file=fh)
print("%%%%BoundingBox: %d %d %d %d" % bbox, file=fh)
if not isEPSF:
print("%%Pages: 1", file=fh)
print("%%EndComments", file=fh)
Ndict = len(psDefs)
print("%%BeginProlog", file=fh)
if not rcParams['ps.useafm']:
Ndict += len(ps_renderer.used_characters)
print("/mpldict %d dict def" % Ndict, file=fh)
print("mpldict begin", file=fh)
for d in psDefs:
d = d.strip()
for l in d.split('\n'):
print(l.strip(), file=fh)
if not rcParams['ps.useafm']:
for font_filename, chars in six.itervalues(
ps_renderer.used_characters):
if len(chars):
font = get_font(font_filename)
glyph_ids = []
for c in chars:
gind = font.get_char_index(c)
glyph_ids.append(gind)
fonttype = rcParams['ps.fonttype']
# Can not use more than 255 characters from a
# single font for Type 3
if len(glyph_ids) > 255:
fonttype = 42
# The ttf to ps (subsetting) support doesn't work for
# OpenType fonts that are Postscript inside (like the
# STIX fonts). This will simply turn that off to avoid
# errors.
if is_opentype_cff_font(font_filename):
raise RuntimeError(
"OpenType CFF fonts can not be saved using "
"the internal Postscript backend at this "
"time; consider using the Cairo backend")
else:
fh.flush()
convert_ttf_to_ps(
font_filename.encode(
sys.getfilesystemencoding()),
fh, fonttype, glyph_ids)
print("end", file=fh)
print("%%EndProlog", file=fh)
if not isEPSF:
print("%%Page: 1 1", file=fh)
print("mpldict begin", file=fh)
print("%s translate" % _nums_to_str(xo, yo), file=fh)
if rotation:
print("%d rotate" % rotation, file=fh)
print("%s clipbox" % _nums_to_str(width*72, height*72, 0, 0),
file=fh)
# write the figure
content = self._pswriter.getvalue()
if not isinstance(content, six.text_type):
content = content.decode('ascii')
print(content, file=fh)
# write the trailer
print("end", file=fh)
print("showpage", file=fh)
if not isEPSF:
print("%%EOF", file=fh)
fh.flush()
if rcParams['ps.usedistiller']:
# We are going to use an external program to process the output.
# Write to a temporary file.
fd, tmpfile = mkstemp()
try:
with io.open(fd, 'w', encoding='latin-1') as fh:
print_figure_impl(fh)
if rcParams['ps.usedistiller'] == 'ghostscript':
gs_distill(tmpfile, isEPSF, ptype=papertype, bbox=bbox)
elif rcParams['ps.usedistiller'] == 'xpdf':
xpdf_distill(tmpfile, isEPSF, ptype=papertype, bbox=bbox)
_move_path_to_path_or_stream(tmpfile, outfile)
finally:
if os.path.isfile(tmpfile):
os.unlink(tmpfile)
else:
# Write directly to outfile.
if passed_in_file_object:
requires_unicode = file_requires_unicode(outfile)
if (not requires_unicode and
(six.PY3 or not isinstance(outfile, StringIO))):
fh = io.TextIOWrapper(outfile, encoding="latin-1")
# Prevent the io.TextIOWrapper from closing the
# underlying file
def do_nothing():
pass
fh.close = do_nothing
else:
fh = outfile
print_figure_impl(fh)
else:
with io.open(outfile, 'w', encoding='latin-1') as fh:
print_figure_impl(fh)
def _print_figure_tex(self, outfile, format, dpi, facecolor, edgecolor,
orientation, isLandscape, papertype, metadata=None,
**kwargs):
"""
If text.usetex is True in rc, a temporary pair of tex/eps files
are created to allow tex to manage the text layout via the PSFrags
package. These files are processed to yield the final ps or eps file.
metadata must be a dictionary. Currently, only the value for
the key 'Creator' is used.
"""
isEPSF = format == 'eps'
if isinstance(outfile, six.string_types):
title = outfile
elif is_writable_file_like(outfile):
title = None
else:
raise ValueError("outfile must be a path or a file-like object")
self.figure.dpi = 72 # ignore the dpi kwarg
width, height = self.figure.get_size_inches()
xo = 0
yo = 0
l, b, w, h = self.figure.bbox.bounds
llx = xo
lly = yo
urx = llx + w
ury = lly + h
bbox = (llx, lly, urx, ury)
# generate PostScript code for the figure and store it in a string
origfacecolor = self.figure.get_facecolor()
origedgecolor = self.figure.get_edgecolor()
self.figure.set_facecolor(facecolor)
self.figure.set_edgecolor(edgecolor)
dryrun = kwargs.get("dryrun", False)
if dryrun:
class NullWriter(object):
def write(self, *kl, **kwargs):
pass
self._pswriter = NullWriter()
else:
self._pswriter = io.StringIO()
# mixed mode rendering
_bbox_inches_restore = kwargs.pop("bbox_inches_restore", None)
ps_renderer = self._renderer_class(width, height,
self._pswriter, imagedpi=dpi)
renderer = MixedModeRenderer(self.figure,
width, height, dpi, ps_renderer,
bbox_inches_restore=_bbox_inches_restore)
self.figure.draw(renderer)
if dryrun: # return immediately if dryrun (tightbbox=True)
return
self.figure.set_facecolor(origfacecolor)
self.figure.set_edgecolor(origedgecolor)
# check for custom metadata
if metadata is not None and 'Creator' in metadata:
creator_str = metadata['Creator']
else:
creator_str = "matplotlib version " + __version__ + \
", http://matplotlib.org/"
# write to a temp file, we'll move it to outfile when done
fd, tmpfile = mkstemp()
try:
with io.open(fd, 'w', encoding='latin-1') as fh:
# write the Encapsulated PostScript headers
print("%!PS-Adobe-3.0 EPSF-3.0", file=fh)
if title:
print("%%Title: "+title, file=fh)
print("%%Creator: " + creator_str, file=fh)
# get source date from SOURCE_DATE_EPOCH, if set
# See https://reproducible-builds.org/specs/source-date-epoch/
source_date_epoch = os.getenv("SOURCE_DATE_EPOCH")
if source_date_epoch:
source_date = datetime.datetime.utcfromtimestamp(
int(source_date_epoch)).strftime(
"%a %b %d %H:%M:%S %Y")
else:
source_date = time.ctime()
print("%%CreationDate: "+source_date, file=fh)
print("%%%%BoundingBox: %d %d %d %d" % bbox, file=fh)
print("%%EndComments", file=fh)
Ndict = len(psDefs)
print("%%BeginProlog", file=fh)
print("/mpldict %d dict def" % Ndict, file=fh)
print("mpldict begin", file=fh)
for d in psDefs:
d = d.strip()
for l in d.split('\n'):
print(l.strip(), file=fh)
print("end", file=fh)
print("%%EndProlog", file=fh)
print("mpldict begin", file=fh)
print("%s translate" % _nums_to_str(xo, yo), file=fh)
print("%s clipbox" % _nums_to_str(width*72, height*72, 0, 0),
file=fh)
# write the figure
print(self._pswriter.getvalue(), file=fh)
# write the trailer
print("end", file=fh)
print("showpage", file=fh)
fh.flush()
if isLandscape: # now we are ready to rotate
isLandscape = True
width, height = height, width
bbox = (lly, llx, ury, urx)
# set the paper size to the figure size if isEPSF. The
# resulting ps file has the given size with correct bounding
# box so that there is no need to call 'pstoeps'
if isEPSF:
paperWidth, paperHeight = self.figure.get_size_inches()
if isLandscape:
paperWidth, paperHeight = paperHeight, paperWidth
else:
temp_papertype = _get_papertype(width, height)
if papertype == 'auto':
papertype = temp_papertype
paperWidth, paperHeight = papersize[temp_papertype]
else:
paperWidth, paperHeight = papersize[papertype]
if (width > paperWidth or height > paperHeight) and isEPSF:
paperWidth, paperHeight = papersize[temp_papertype]
_log.info('Your figure is too big to fit on %s paper. '
'%s paper will be used to prevent clipping.',
papertype, temp_papertype)
texmanager = ps_renderer.get_texmanager()
font_preamble = texmanager.get_font_preamble()
custom_preamble = texmanager.get_custom_preamble()
psfrag_rotated = convert_psfrags(tmpfile, ps_renderer.psfrag,
font_preamble,
custom_preamble, paperWidth,
paperHeight,
orientation)
if (rcParams['ps.usedistiller'] == 'ghostscript'
or rcParams['text.usetex']):
gs_distill(tmpfile, isEPSF, ptype=papertype, bbox=bbox,
rotated=psfrag_rotated)
elif rcParams['ps.usedistiller'] == 'xpdf':
xpdf_distill(tmpfile, isEPSF, ptype=papertype, bbox=bbox,
rotated=psfrag_rotated)
_move_path_to_path_or_stream(tmpfile, outfile)
finally:
if os.path.isfile(tmpfile):
os.unlink(tmpfile)
def convert_psfrags(tmpfile, psfrags, font_preamble, custom_preamble,
paperWidth, paperHeight, orientation):
"""
When we want to use the LaTeX backend with postscript, we write PSFrag tags
to a temporary postscript file, each one marking a position for LaTeX to
render some text. convert_psfrags generates a LaTeX document containing the
commands to convert those tags to text. LaTeX/dvips produces the postscript
file that includes the actual text.
"""
tmpdir = os.path.split(tmpfile)[0]
epsfile = tmpfile+'.eps'
shutil.move(tmpfile, epsfile)
latexfile = tmpfile+'.tex'
dvifile = tmpfile+'.dvi'
psfile = tmpfile+'.ps'
if orientation == 'landscape':
angle = 90
else:
angle = 0
if rcParams['text.latex.unicode']:
unicode_preamble = """\\usepackage{ucs}
\\usepackage[utf8x]{inputenc}"""
else:
unicode_preamble = ''
s = """\\documentclass{article}
%s
%s
%s
\\usepackage[dvips, papersize={%sin,%sin}, body={%sin,%sin}, margin={0in,0in}]{geometry}
\\usepackage{psfrag}
\\usepackage[dvips]{graphicx}
\\usepackage{color}
\\pagestyle{empty}
\\begin{document}
\\begin{figure}
\\centering
\\leavevmode
%s
\\includegraphics*[angle=%s]{%s}
\\end{figure}
\\end{document}
"""% (font_preamble, unicode_preamble, custom_preamble, paperWidth, paperHeight,
paperWidth, paperHeight,
'\n'.join(psfrags), angle, os.path.split(epsfile)[-1])
with io.open(latexfile, 'wb') as latexh:
if rcParams['text.latex.unicode']:
latexh.write(s.encode('utf8'))
else:
try:
latexh.write(s.encode('ascii'))
except UnicodeEncodeError:
_log.info("You are using unicode and latex, but have "
"not enabled the matplotlib 'text.latex.unicode' "
"rcParam.")
raise
# Replace \\ for / so latex does not think there is a function call
latexfile = latexfile.replace("\\", "/")
# Replace ~ so Latex does not think it is line break
latexfile = latexfile.replace("~", "\\string~")
command = [str("latex"), "-interaction=nonstopmode",
'"%s"' % latexfile]
_log.debug('%s', command)
try:
report = subprocess.check_output(command, cwd=tmpdir,
stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as exc:
raise RuntimeError(
('LaTeX was not able to process the following '
'file:\n%s\n\n'
'Here is the full report generated by LaTeX:\n%s '
'\n\n' % (latexfile,
exc.output.decode("utf-8"))))
_log.debug(report)
command = [str('dvips'), '-q', '-R0', '-o', os.path.basename(psfile),
os.path.basename(dvifile)]
_log.debug(command)
try:
report = subprocess.check_output(command, cwd=tmpdir,
stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as exc:
raise RuntimeError(
('dvips was not able to process the following '
'file:\n%s\n\n'
'Here is the full report generated by dvips:\n%s '
'\n\n' % (dvifile,
exc.output.decode("utf-8"))))
_log.debug(report)
os.remove(epsfile)
shutil.move(psfile, tmpfile)
# check if the dvips created a ps in landscape paper. Somehow,
# above latex+dvips results in a ps file in a landscape mode for a
# certain figure sizes (e.g., 8.3in,5.8in which is a5). And the
# bounding box of the final output got messed up. We check see if
# the generated ps file is in landscape and return this
# information. The return value is used in pstoeps step to recover
# the correct bounding box. 2010-06-05 JJL
with io.open(tmpfile) as fh:
if "Landscape" in fh.read(1000):
psfrag_rotated = True
else:
psfrag_rotated = False
if not debugPS:
for fname in glob.glob(tmpfile+'.*'):
os.remove(fname)
return psfrag_rotated
def gs_distill(tmpfile, eps=False, ptype='letter', bbox=None, rotated=False):
"""
Use ghostscript's pswrite or epswrite device to distill a file.
This yields smaller files without illegal encapsulated postscript
operators. The output is low-level, converting text to outlines.
"""
if eps:
paper_option = "-dEPSCrop"
else:
paper_option = "-sPAPERSIZE=%s" % ptype
psfile = tmpfile + '.ps'
dpi = rcParams['ps.distiller.res']
gs_exe = ps_backend_helper.gs_exe
if ps_backend_helper.supports_ps2write: # gs version >= 9
device_name = "ps2write"
else:
device_name = "pswrite"
command = [str(gs_exe), "-dBATCH", "-dNOPAUSE", "-r%d" % dpi,
"-sDEVICE=%s" % device_name, paper_option,
"-sOutputFile=%s" % psfile, tmpfile]
_log.debug(command)
try:
report = subprocess.check_output(command, stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as exc:
raise RuntimeError(
('ghostscript was not able to process your image.\n'
'Here is the full report generated by ghostscript:\n%s '
'\n\n' % exc.output.decode("utf-8")))
_log.debug(report)
os.remove(tmpfile)
shutil.move(psfile, tmpfile)
# While it is best if above steps preserve the original bounding
# box, there seem to be cases when it is not. For those cases,
# the original bbox can be restored during the pstoeps step.
if eps:
# For some versions of gs, above steps result in an ps file
# where the original bbox is no more correct. Do not adjust
# bbox for now.
if ps_backend_helper.supports_ps2write:
# fo gs version >= 9 w/ ps2write device
pstoeps(tmpfile, bbox, rotated=rotated)
else:
pstoeps(tmpfile)
def xpdf_distill(tmpfile, eps=False, ptype='letter', bbox=None, rotated=False):
"""
Use ghostscript's ps2pdf and xpdf's/poppler's pdftops to distill a file.
This yields smaller files without illegal encapsulated postscript
operators. This distiller is preferred, generating high-level postscript
output that treats text as text.
"""
pdffile = tmpfile + '.pdf'
psfile = tmpfile + '.ps'
# Pass options as `-foo#bar` instead of `-foo=bar` to keep Windows happy
# (https://www.ghostscript.com/doc/9.22/Use.htm#MS_Windows).
command = [str("ps2pdf"),
"-dAutoFilterColorImages#false",
"-dAutoFilterGrayImages#false",
"-dAutoRotatePages#false",
"-sGrayImageFilter#FlateEncode",
"-sColorImageFilter#FlateEncode",
"-dEPSCrop" if eps else "-sPAPERSIZE#%s" % ptype,
tmpfile, pdffile]
_log.debug(command)
try:
report = subprocess.check_output(command, stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as exc:
raise RuntimeError(
('ps2pdf was not able to process your image.\n'
'Here is the full report generated by ps2pdf:\n%s '
'\n\n' % exc.output.decode("utf-8")))
_log.debug(report)
command = [str("pdftops"), "-paper", "match", "-level2", pdffile, psfile]
_log.debug(command)
try:
report = subprocess.check_output(command, stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as exc:
raise RuntimeError(
('pdftops was not able to process your image.\n'
'Here is the full report generated by pdftops:\n%s '
'\n\n' % exc.output.decode("utf-8")))
_log.debug(report)
os.remove(tmpfile)
shutil.move(psfile, tmpfile)
if eps:
pstoeps(tmpfile)
for fname in glob.glob(tmpfile+'.*'):
os.remove(fname)
def get_bbox_header(lbrt, rotated=False):
"""
return a postscript header stringfor the given bbox lbrt=(l, b, r, t).
Optionally, return rotate command.
"""
l, b, r, t = lbrt
if rotated:
rotate = "%.2f %.2f translate\n90 rotate" % (l+r, 0)
else:
rotate = ""
bbox_info = '%%%%BoundingBox: %d %d %d %d' % (l, b, np.ceil(r), np.ceil(t))
hires_bbox_info = '%%%%HiResBoundingBox: %.6f %.6f %.6f %.6f' % (l, b, r, t)
return '\n'.join([bbox_info, hires_bbox_info]), rotate
# get_bbox is deprecated. I don't see any reason to use ghostscript to
# find the bounding box, as the required bounding box is alread known.
def get_bbox(tmpfile, bbox):
"""
Use ghostscript's bbox device to find the center of the bounding box.
Return an appropriately sized bbox centered around that point. A bit of a
hack.
"""
gs_exe = ps_backend_helper.gs_exe
command = [gs_exe, "-dBATCH", "-dNOPAUSE", "-sDEVICE=bbox", "%s" % tmpfile]
_log.debug(command)
p = subprocess.Popen(command, stdin=subprocess.PIPE,
stdout=subprocess.PIPE, stderr=subprocess.PIPE,
close_fds=True)
(stdout, stderr) = (p.stdout, p.stderr)
_log.debug(stdout.read())
bbox_info = stderr.read()
_log.info(bbox_info)
bbox_found = re.search('%%HiResBoundingBox: .*', bbox_info)
if bbox_found:
bbox_info = bbox_found.group()
else:
raise RuntimeError('Ghostscript was not able to extract a bounding box.\
Here is the Ghostscript output:\n\n%s' % bbox_info)
l, b, r, t = [float(i) for i in bbox_info.split()[-4:]]
# this is a hack to deal with the fact that ghostscript does not return the
# intended bbox, but a tight bbox. For now, we just center the ink in the
# intended bbox. This is not ideal, users may intend the ink to not be
# centered.
if bbox is None:
l, b, r, t = (l-1, b-1, r+1, t+1)
else:
x = (l+r)/2
y = (b+t)/2
dx = (bbox[2]-bbox[0])/2
dy = (bbox[3]-bbox[1])/2
l,b,r,t = (x-dx, y-dy, x+dx, y+dy)
bbox_info = '%%%%BoundingBox: %d %d %d %d' % (l, b, np.ceil(r), np.ceil(t))
hires_bbox_info = '%%%%HiResBoundingBox: %.6f %.6f %.6f %.6f' % (l, b, r, t)
return '\n'.join([bbox_info, hires_bbox_info])
def pstoeps(tmpfile, bbox=None, rotated=False):
"""
Convert the postscript to encapsulated postscript. The bbox of
the eps file will be replaced with the given *bbox* argument. If
None, original bbox will be used.
"""
# if rotated==True, the output eps file need to be rotated
if bbox:
bbox_info, rotate = get_bbox_header(bbox, rotated=rotated)
else:
bbox_info, rotate = None, None
epsfile = tmpfile + '.eps'
with io.open(epsfile, 'wb') as epsh, io.open(tmpfile, 'rb') as tmph:
write = epsh.write
# Modify the header:
for line in tmph:
if line.startswith(b'%!PS'):
write(b"%!PS-Adobe-3.0 EPSF-3.0\n")
if bbox:
write(bbox_info.encode('ascii') + b'\n')
elif line.startswith(b'%%EndComments'):
write(line)
write(b'%%BeginProlog\n'
b'save\n'
b'countdictstack\n'
b'mark\n'
b'newpath\n'
b'/showpage {} def\n'
b'/setpagedevice {pop} def\n'
b'%%EndProlog\n'
b'%%Page 1 1\n')
if rotate:
write(rotate.encode('ascii') + b'\n')
break
elif bbox and line.startswith((b'%%Bound', b'%%HiResBound',
b'%%DocumentMedia', b'%%Pages')):
pass
else:
write(line)
# Now rewrite the rest of the file, and modify the trailer.
# This is done in a second loop such that the header of the embedded
# eps file is not modified.
for line in tmph:
if line.startswith(b'%%EOF'):
write(b'cleartomark\n'
b'countdictstack\n'
b'exch sub { end } repeat\n'
b'restore\n'
b'showpage\n'
b'%%EOF\n')
elif line.startswith(b'%%PageBoundingBox'):
pass
else:
write(line)
os.remove(tmpfile)
shutil.move(epsfile, tmpfile)
class FigureManagerPS(FigureManagerBase):
pass
# The following Python dictionary psDefs contains the entries for the
# PostScript dictionary mpldict. This dictionary implements most of
# the matplotlib primitives and some abbreviations.
#
# References:
# http://www.adobe.com/products/postscript/pdfs/PLRM.pdf
# http://www.mactech.com/articles/mactech/Vol.09/09.04/PostscriptTutorial/
# http://www.math.ubc.ca/people/faculty/cass/graphics/text/www/
#
# The usage comments use the notation of the operator summary
# in the PostScript Language reference manual.
psDefs = [
# x y *m* -
"/m { moveto } bind def",
# x y *l* -
"/l { lineto } bind def",
# x y *r* -
"/r { rlineto } bind def",
# x1 y1 x2 y2 x y *c* -
"/c { curveto } bind def",
# *closepath* -
"/cl { closepath } bind def",
# w h x y *box* -
"""/box {
m
1 index 0 r
0 exch r
neg 0 r
cl
} bind def""",
# w h x y *clipbox* -
"""/clipbox {
box
clip
newpath
} bind def""",
]
@_Backend.export
class _BackendPS(_Backend):
FigureCanvas = FigureCanvasPS
FigureManager = FigureManagerPS
| 62,098 | 34.323663 | 129 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_cairo.py | """
A Cairo backend for matplotlib
==============================
:Author: Steve Chaplin and others
This backend depends on `cairo <http://cairographics.org>`_, and either on
cairocffi, or (Python 2 only) on pycairo.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import gzip
import sys
import warnings
import numpy as np
# cairocffi is more widely compatible than pycairo (in particular pgi only
# works with cairocffi) so try it first.
try:
import cairocffi as cairo
except ImportError:
try:
import cairo
except ImportError:
raise ImportError("cairo backend requires that cairocffi or pycairo "
"is installed")
else:
HAS_CAIRO_CFFI = False
else:
HAS_CAIRO_CFFI = True
if cairo.version_info < (1, 4, 0):
raise ImportError("cairo {} is installed; "
"cairo>=1.4.0 is required".format(cairo.version))
backend_version = cairo.version
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
RendererBase)
from matplotlib.mathtext import MathTextParser
from matplotlib.path import Path
from matplotlib.transforms import Affine2D
from matplotlib.font_manager import ttfFontProperty
class ArrayWrapper:
"""Thin wrapper around numpy ndarray to expose the interface
expected by cairocffi. Basically replicates the
array.array interface.
"""
def __init__(self, myarray):
self.__array = myarray
self.__data = myarray.ctypes.data
self.__size = len(myarray.flatten())
self.itemsize = myarray.itemsize
def buffer_info(self):
return (self.__data, self.__size)
class RendererCairo(RendererBase):
fontweights = {
100 : cairo.FONT_WEIGHT_NORMAL,
200 : cairo.FONT_WEIGHT_NORMAL,
300 : cairo.FONT_WEIGHT_NORMAL,
400 : cairo.FONT_WEIGHT_NORMAL,
500 : cairo.FONT_WEIGHT_NORMAL,
600 : cairo.FONT_WEIGHT_BOLD,
700 : cairo.FONT_WEIGHT_BOLD,
800 : cairo.FONT_WEIGHT_BOLD,
900 : cairo.FONT_WEIGHT_BOLD,
'ultralight' : cairo.FONT_WEIGHT_NORMAL,
'light' : cairo.FONT_WEIGHT_NORMAL,
'normal' : cairo.FONT_WEIGHT_NORMAL,
'medium' : cairo.FONT_WEIGHT_NORMAL,
'regular' : cairo.FONT_WEIGHT_NORMAL,
'semibold' : cairo.FONT_WEIGHT_BOLD,
'bold' : cairo.FONT_WEIGHT_BOLD,
'heavy' : cairo.FONT_WEIGHT_BOLD,
'ultrabold' : cairo.FONT_WEIGHT_BOLD,
'black' : cairo.FONT_WEIGHT_BOLD,
}
fontangles = {
'italic' : cairo.FONT_SLANT_ITALIC,
'normal' : cairo.FONT_SLANT_NORMAL,
'oblique' : cairo.FONT_SLANT_OBLIQUE,
}
def __init__(self, dpi):
self.dpi = dpi
self.gc = GraphicsContextCairo(renderer=self)
self.text_ctx = cairo.Context(
cairo.ImageSurface(cairo.FORMAT_ARGB32, 1, 1))
self.mathtext_parser = MathTextParser('Cairo')
RendererBase.__init__(self)
def set_ctx_from_surface(self, surface):
self.gc.ctx = cairo.Context(surface)
# Although it may appear natural to automatically call
# `self.set_width_height(surface.get_width(), surface.get_height())`
# here (instead of having the caller do so separately), this would fail
# for PDF/PS/SVG surfaces, which have no way to report their extents.
def set_width_height(self, width, height):
self.width = width
self.height = height
def _fill_and_stroke(self, ctx, fill_c, alpha, alpha_overrides):
if fill_c is not None:
ctx.save()
if len(fill_c) == 3 or alpha_overrides:
ctx.set_source_rgba(fill_c[0], fill_c[1], fill_c[2], alpha)
else:
ctx.set_source_rgba(fill_c[0], fill_c[1], fill_c[2], fill_c[3])
ctx.fill_preserve()
ctx.restore()
ctx.stroke()
@staticmethod
def convert_path(ctx, path, transform, clip=None):
for points, code in path.iter_segments(transform, clip=clip):
if code == Path.MOVETO:
ctx.move_to(*points)
elif code == Path.CLOSEPOLY:
ctx.close_path()
elif code == Path.LINETO:
ctx.line_to(*points)
elif code == Path.CURVE3:
ctx.curve_to(points[0], points[1],
points[0], points[1],
points[2], points[3])
elif code == Path.CURVE4:
ctx.curve_to(*points)
def draw_path(self, gc, path, transform, rgbFace=None):
ctx = gc.ctx
# We'll clip the path to the actual rendering extents
# if the path isn't filled.
if rgbFace is None and gc.get_hatch() is None:
clip = ctx.clip_extents()
else:
clip = None
transform = (transform
+ Affine2D().scale(1.0, -1.0).translate(0, self.height))
ctx.new_path()
self.convert_path(ctx, path, transform, clip)
self._fill_and_stroke(
ctx, rgbFace, gc.get_alpha(), gc.get_forced_alpha())
def draw_markers(self, gc, marker_path, marker_trans, path, transform,
rgbFace=None):
ctx = gc.ctx
ctx.new_path()
# Create the path for the marker; it needs to be flipped here already!
self.convert_path(
ctx, marker_path, marker_trans + Affine2D().scale(1.0, -1.0))
marker_path = ctx.copy_path_flat()
# Figure out whether the path has a fill
x1, y1, x2, y2 = ctx.fill_extents()
if x1 == 0 and y1 == 0 and x2 == 0 and y2 == 0:
filled = False
# No fill, just unset this (so we don't try to fill it later on)
rgbFace = None
else:
filled = True
transform = (transform
+ Affine2D().scale(1.0, -1.0).translate(0, self.height))
ctx.new_path()
for i, (vertices, codes) in enumerate(
path.iter_segments(transform, simplify=False)):
if len(vertices):
x, y = vertices[-2:]
ctx.save()
# Translate and apply path
ctx.translate(x, y)
ctx.append_path(marker_path)
ctx.restore()
# Slower code path if there is a fill; we need to draw
# the fill and stroke for each marker at the same time.
# Also flush out the drawing every once in a while to
# prevent the paths from getting way too long.
if filled or i % 1000 == 0:
self._fill_and_stroke(
ctx, rgbFace, gc.get_alpha(), gc.get_forced_alpha())
# Fast path, if there is no fill, draw everything in one step
if not filled:
self._fill_and_stroke(
ctx, rgbFace, gc.get_alpha(), gc.get_forced_alpha())
def draw_image(self, gc, x, y, im):
# bbox - not currently used
if sys.byteorder == 'little':
im = im[:, :, (2, 1, 0, 3)]
else:
im = im[:, :, (3, 0, 1, 2)]
if HAS_CAIRO_CFFI:
# cairocffi tries to use the buffer_info from array.array
# that we replicate in ArrayWrapper and alternatively falls back
# on ctypes to get a pointer to the numpy array. This works
# correctly on a numpy array in python3 but not 2.7. We replicate
# the array.array functionality here to get cross version support.
imbuffer = ArrayWrapper(im.flatten())
else:
# pycairo uses PyObject_AsWriteBuffer to get a pointer to the
# numpy array; this works correctly on a regular numpy array but
# not on a py2 memoryview.
imbuffer = im.flatten()
surface = cairo.ImageSurface.create_for_data(
imbuffer, cairo.FORMAT_ARGB32,
im.shape[1], im.shape[0], im.shape[1]*4)
ctx = gc.ctx
y = self.height - y - im.shape[0]
ctx.save()
ctx.set_source_surface(surface, float(x), float(y))
if gc.get_alpha() != 1.0:
ctx.paint_with_alpha(gc.get_alpha())
else:
ctx.paint()
ctx.restore()
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
# Note: x,y are device/display coords, not user-coords, unlike other
# draw_* methods
if ismath:
self._draw_mathtext(gc, x, y, s, prop, angle)
else:
ctx = gc.ctx
ctx.new_path()
ctx.move_to(x, y)
ctx.select_font_face(prop.get_name(),
self.fontangles[prop.get_style()],
self.fontweights[prop.get_weight()])
size = prop.get_size_in_points() * self.dpi / 72.0
ctx.save()
if angle:
ctx.rotate(np.deg2rad(-angle))
ctx.set_font_size(size)
if HAS_CAIRO_CFFI:
if not isinstance(s, six.text_type):
s = six.text_type(s)
else:
if six.PY2 and isinstance(s, six.text_type):
s = s.encode("utf-8")
ctx.show_text(s)
ctx.restore()
def _draw_mathtext(self, gc, x, y, s, prop, angle):
ctx = gc.ctx
width, height, descent, glyphs, rects = self.mathtext_parser.parse(
s, self.dpi, prop)
ctx.save()
ctx.translate(x, y)
if angle:
ctx.rotate(np.deg2rad(-angle))
for font, fontsize, s, ox, oy in glyphs:
ctx.new_path()
ctx.move_to(ox, oy)
fontProp = ttfFontProperty(font)
ctx.save()
ctx.select_font_face(fontProp.name,
self.fontangles[fontProp.style],
self.fontweights[fontProp.weight])
size = fontsize * self.dpi / 72.0
ctx.set_font_size(size)
if not six.PY3 and isinstance(s, six.text_type):
s = s.encode("utf-8")
ctx.show_text(s)
ctx.restore()
for ox, oy, w, h in rects:
ctx.new_path()
ctx.rectangle(ox, oy, w, h)
ctx.set_source_rgb(0, 0, 0)
ctx.fill_preserve()
ctx.restore()
def get_canvas_width_height(self):
return self.width, self.height
def get_text_width_height_descent(self, s, prop, ismath):
if ismath:
width, height, descent, fonts, used_characters = \
self.mathtext_parser.parse(s, self.dpi, prop)
return width, height, descent
ctx = self.text_ctx
ctx.save()
ctx.select_font_face(prop.get_name(),
self.fontangles[prop.get_style()],
self.fontweights[prop.get_weight()])
# Cairo (says it) uses 1/96 inch user space units, ref: cairo_gstate.c
# but if /96.0 is used the font is too small
size = prop.get_size_in_points() * self.dpi / 72
# problem - scale remembers last setting and font can become
# enormous causing program to crash
# save/restore prevents the problem
ctx.set_font_size(size)
y_bearing, w, h = ctx.text_extents(s)[1:4]
ctx.restore()
return w, h, h + y_bearing
def new_gc(self):
self.gc.ctx.save()
self.gc._alpha = 1
self.gc._forced_alpha = False # if True, _alpha overrides A from RGBA
return self.gc
def points_to_pixels(self, points):
return points / 72 * self.dpi
class GraphicsContextCairo(GraphicsContextBase):
_joind = {
'bevel' : cairo.LINE_JOIN_BEVEL,
'miter' : cairo.LINE_JOIN_MITER,
'round' : cairo.LINE_JOIN_ROUND,
}
_capd = {
'butt' : cairo.LINE_CAP_BUTT,
'projecting' : cairo.LINE_CAP_SQUARE,
'round' : cairo.LINE_CAP_ROUND,
}
def __init__(self, renderer):
GraphicsContextBase.__init__(self)
self.renderer = renderer
def restore(self):
self.ctx.restore()
def set_alpha(self, alpha):
GraphicsContextBase.set_alpha(self, alpha)
_alpha = self.get_alpha()
rgb = self._rgb
if self.get_forced_alpha():
self.ctx.set_source_rgba(rgb[0], rgb[1], rgb[2], _alpha)
else:
self.ctx.set_source_rgba(rgb[0], rgb[1], rgb[2], rgb[3])
# def set_antialiased(self, b):
# cairo has many antialiasing modes, we need to pick one for True and
# one for False.
def set_capstyle(self, cs):
if cs in ('butt', 'round', 'projecting'):
self._capstyle = cs
self.ctx.set_line_cap(self._capd[cs])
else:
raise ValueError('Unrecognized cap style. Found %s' % cs)
def set_clip_rectangle(self, rectangle):
if not rectangle:
return
x, y, w, h = np.round(rectangle.bounds)
ctx = self.ctx
ctx.new_path()
ctx.rectangle(x, self.renderer.height - h - y, w, h)
ctx.clip()
def set_clip_path(self, path):
if not path:
return
tpath, affine = path.get_transformed_path_and_affine()
ctx = self.ctx
ctx.new_path()
affine = (affine
+ Affine2D().scale(1, -1).translate(0, self.renderer.height))
RendererCairo.convert_path(ctx, tpath, affine)
ctx.clip()
def set_dashes(self, offset, dashes):
self._dashes = offset, dashes
if dashes == None:
self.ctx.set_dash([], 0) # switch dashes off
else:
self.ctx.set_dash(
list(self.renderer.points_to_pixels(np.asarray(dashes))),
offset)
def set_foreground(self, fg, isRGBA=None):
GraphicsContextBase.set_foreground(self, fg, isRGBA)
if len(self._rgb) == 3:
self.ctx.set_source_rgb(*self._rgb)
else:
self.ctx.set_source_rgba(*self._rgb)
def get_rgb(self):
return self.ctx.get_source().get_rgba()[:3]
def set_joinstyle(self, js):
if js in ('miter', 'round', 'bevel'):
self._joinstyle = js
self.ctx.set_line_join(self._joind[js])
else:
raise ValueError('Unrecognized join style. Found %s' % js)
def set_linewidth(self, w):
self._linewidth = float(w)
self.ctx.set_line_width(self.renderer.points_to_pixels(w))
class FigureCanvasCairo(FigureCanvasBase):
supports_blit = False
def print_png(self, fobj, *args, **kwargs):
width, height = self.get_width_height()
renderer = RendererCairo(self.figure.dpi)
renderer.set_width_height(width, height)
surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, width, height)
renderer.set_ctx_from_surface(surface)
self.figure.draw(renderer)
surface.write_to_png(fobj)
def print_pdf(self, fobj, *args, **kwargs):
return self._save(fobj, 'pdf', *args, **kwargs)
def print_ps(self, fobj, *args, **kwargs):
return self._save(fobj, 'ps', *args, **kwargs)
def print_svg(self, fobj, *args, **kwargs):
return self._save(fobj, 'svg', *args, **kwargs)
def print_svgz(self, fobj, *args, **kwargs):
return self._save(fobj, 'svgz', *args, **kwargs)
def _save(self, fo, fmt, **kwargs):
# save PDF/PS/SVG
orientation = kwargs.get('orientation', 'portrait')
dpi = 72
self.figure.dpi = dpi
w_in, h_in = self.figure.get_size_inches()
width_in_points, height_in_points = w_in * dpi, h_in * dpi
if orientation == 'landscape':
width_in_points, height_in_points = (
height_in_points, width_in_points)
if fmt == 'ps':
if not hasattr(cairo, 'PSSurface'):
raise RuntimeError('cairo has not been compiled with PS '
'support enabled')
surface = cairo.PSSurface(fo, width_in_points, height_in_points)
elif fmt == 'pdf':
if not hasattr(cairo, 'PDFSurface'):
raise RuntimeError('cairo has not been compiled with PDF '
'support enabled')
surface = cairo.PDFSurface(fo, width_in_points, height_in_points)
elif fmt in ('svg', 'svgz'):
if not hasattr(cairo, 'SVGSurface'):
raise RuntimeError('cairo has not been compiled with SVG '
'support enabled')
if fmt == 'svgz':
if isinstance(fo, six.string_types):
fo = gzip.GzipFile(fo, 'wb')
else:
fo = gzip.GzipFile(None, 'wb', fileobj=fo)
surface = cairo.SVGSurface(fo, width_in_points, height_in_points)
else:
warnings.warn("unknown format: %s" % fmt)
return
# surface.set_dpi() can be used
renderer = RendererCairo(self.figure.dpi)
renderer.set_width_height(width_in_points, height_in_points)
renderer.set_ctx_from_surface(surface)
ctx = renderer.gc.ctx
if orientation == 'landscape':
ctx.rotate(np.pi / 2)
ctx.translate(0, -height_in_points)
# Perhaps add an '%%Orientation: Landscape' comment?
self.figure.draw(renderer)
ctx.show_page()
surface.finish()
if fmt == 'svgz':
fo.close()
@_Backend.export
class _BackendCairo(_Backend):
FigureCanvas = FigureCanvasCairo
FigureManager = FigureManagerBase
| 18,010 | 33.570058 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_gtkagg.py | """
Render to gtk from agg
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib
from matplotlib.cbook import warn_deprecated
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.backends.backend_gtk import (
gtk, _BackendGTK, FigureCanvasGTK, FigureManagerGTK, NavigationToolbar2GTK,
backend_version, error_msg_gtk, PIXELS_PER_INCH)
from matplotlib.backends._gtkagg import agg_to_gtk_drawable
class NavigationToolbar2GTKAgg(NavigationToolbar2GTK):
def _get_canvas(self, fig):
return FigureCanvasGTKAgg(fig)
class FigureManagerGTKAgg(FigureManagerGTK):
def _get_toolbar(self, canvas):
# must be inited after the window, drawingArea and figure
# attrs are set
if matplotlib.rcParams['toolbar']=='toolbar2':
toolbar = NavigationToolbar2GTKAgg (canvas, self.window)
else:
toolbar = None
return toolbar
class FigureCanvasGTKAgg(FigureCanvasGTK, FigureCanvasAgg):
filetypes = FigureCanvasGTK.filetypes.copy()
filetypes.update(FigureCanvasAgg.filetypes)
def __init__(self, *args, **kwargs):
warn_deprecated('2.2',
message=('The GTKAgg backend is deprecated. It is '
'untested and will be removed in Matplotlib '
'3.0. Use the GTK3Agg backend instead. See '
'Matplotlib usage FAQ for more info on '
'backends.'),
alternative='GTK3Agg')
super(FigureCanvasGTKAgg, self).__init__(*args, **kwargs)
def configure_event(self, widget, event=None):
if widget.window is None:
return
try:
del self.renderer
except AttributeError:
pass
w,h = widget.window.get_size()
if w==1 or h==1: return # empty fig
# compute desired figure size in inches
dpival = self.figure.dpi
winch = w/dpival
hinch = h/dpival
self.figure.set_size_inches(winch, hinch, forward=False)
self._need_redraw = True
self.resize_event()
return True
def _render_figure(self, pixmap, width, height):
FigureCanvasAgg.draw(self)
buf = self.buffer_rgba()
ren = self.get_renderer()
w = int(ren.width)
h = int(ren.height)
pixbuf = gtk.gdk.pixbuf_new_from_data(
buf, gtk.gdk.COLORSPACE_RGB, True, 8, w, h, w*4)
pixmap.draw_pixbuf(pixmap.new_gc(), pixbuf, 0, 0, 0, 0, w, h,
gtk.gdk.RGB_DITHER_NONE, 0, 0)
def blit(self, bbox=None):
agg_to_gtk_drawable(self._pixmap, self.renderer._renderer, bbox)
x, y, w, h = self.allocation
self.window.draw_drawable(self.style.fg_gc[self.state], self._pixmap,
0, 0, 0, 0, w, h)
def print_png(self, filename, *args, **kwargs):
# Do this so we can save the resolution of figure in the PNG file
agg = self.switch_backends(FigureCanvasAgg)
return agg.print_png(filename, *args, **kwargs)
@_BackendGTK.export
class _BackendGTKAgg(_BackendGTK):
FigureCanvas = FigureCanvasGTKAgg
FigureManager = FigureManagerGTKAgg
| 3,353 | 33.57732 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/wx_compat.py | #!/usr/bin/env python
"""
A wx API adapter to hide differences between wxPython classic and phoenix.
It is assumed that the user code is selecting what version it wants to use,
here we just ensure that it meets the minimum required by matplotlib.
For an example see embedding_in_wx2.py
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from distutils.version import StrictVersion, LooseVersion
missingwx = "Matplotlib backend_wx and backend_wxagg require wxPython>=2.9"
try:
import wx
backend_version = wx.VERSION_STRING
is_phoenix = 'phoenix' in wx.PlatformInfo
except ImportError:
raise ImportError(missingwx)
try:
wx_version = StrictVersion(wx.VERSION_STRING)
except ValueError:
wx_version = LooseVersion(wx.VERSION_STRING)
# Ensure we have the correct version imported
if wx_version < str("2.9"):
raise ImportError(missingwx)
if is_phoenix:
# define all the wxPython phoenix stuff
# font styles, families and weight
fontweights = {
100: wx.FONTWEIGHT_LIGHT,
200: wx.FONTWEIGHT_LIGHT,
300: wx.FONTWEIGHT_LIGHT,
400: wx.FONTWEIGHT_NORMAL,
500: wx.FONTWEIGHT_NORMAL,
600: wx.FONTWEIGHT_NORMAL,
700: wx.FONTWEIGHT_BOLD,
800: wx.FONTWEIGHT_BOLD,
900: wx.FONTWEIGHT_BOLD,
'ultralight': wx.FONTWEIGHT_LIGHT,
'light': wx.FONTWEIGHT_LIGHT,
'normal': wx.FONTWEIGHT_NORMAL,
'medium': wx.FONTWEIGHT_NORMAL,
'semibold': wx.FONTWEIGHT_NORMAL,
'bold': wx.FONTWEIGHT_BOLD,
'heavy': wx.FONTWEIGHT_BOLD,
'ultrabold': wx.FONTWEIGHT_BOLD,
'black': wx.FONTWEIGHT_BOLD
}
fontangles = {
'italic': wx.FONTSTYLE_ITALIC,
'normal': wx.FONTSTYLE_NORMAL,
'oblique': wx.FONTSTYLE_SLANT}
# wxPython allows for portable font styles, choosing them appropriately
# for the target platform. Map some standard font names to the portable
# styles
# QUESTION: Is it be wise to agree standard fontnames across all backends?
fontnames = {'Sans': wx.FONTFAMILY_SWISS,
'Roman': wx.FONTFAMILY_ROMAN,
'Script': wx.FONTFAMILY_SCRIPT,
'Decorative': wx.FONTFAMILY_DECORATIVE,
'Modern': wx.FONTFAMILY_MODERN,
'Courier': wx.FONTFAMILY_MODERN,
'courier': wx.FONTFAMILY_MODERN}
dashd_wx = {'solid': wx.PENSTYLE_SOLID,
'dashed': wx.PENSTYLE_SHORT_DASH,
'dashdot': wx.PENSTYLE_DOT_DASH,
'dotted': wx.PENSTYLE_DOT}
# functions changes
BitmapFromBuffer = wx.Bitmap.FromBufferRGBA
EmptyBitmap = wx.Bitmap
EmptyImage = wx.Image
Cursor = wx.Cursor
EventLoop = wx.GUIEventLoop
NamedColour = wx.Colour
StockCursor = wx.Cursor
else:
# define all the wxPython classic stuff
# font styles, families and weight
fontweights = {
100: wx.LIGHT,
200: wx.LIGHT,
300: wx.LIGHT,
400: wx.NORMAL,
500: wx.NORMAL,
600: wx.NORMAL,
700: wx.BOLD,
800: wx.BOLD,
900: wx.BOLD,
'ultralight': wx.LIGHT,
'light': wx.LIGHT,
'normal': wx.NORMAL,
'medium': wx.NORMAL,
'semibold': wx.NORMAL,
'bold': wx.BOLD,
'heavy': wx.BOLD,
'ultrabold': wx.BOLD,
'black': wx.BOLD
}
fontangles = {
'italic': wx.ITALIC,
'normal': wx.NORMAL,
'oblique': wx.SLANT}
# wxPython allows for portable font styles, choosing them appropriately
# for the target platform. Map some standard font names to the portable
# styles
# QUESTION: Is it be wise to agree standard fontnames across all backends?
fontnames = {'Sans': wx.SWISS,
'Roman': wx.ROMAN,
'Script': wx.SCRIPT,
'Decorative': wx.DECORATIVE,
'Modern': wx.MODERN,
'Courier': wx.MODERN,
'courier': wx.MODERN}
dashd_wx = {'solid': wx.SOLID,
'dashed': wx.SHORT_DASH,
'dashdot': wx.DOT_DASH,
'dotted': wx.DOT}
# functions changes
BitmapFromBuffer = wx.BitmapFromBufferRGBA
EmptyBitmap = wx.EmptyBitmap
EmptyImage = wx.EmptyImage
Cursor = wx.StockCursor
EventLoop = wx.EventLoop
NamedColour = wx.NamedColour
StockCursor = wx.StockCursor
# wxPython Classic's DoAddTool has become AddTool in Phoenix. Otherwise
# they are the same, except for early betas and prerelease builds of
# Phoenix. This function provides a shim that does the RightThing based on
# which wxPython is in use.
def _AddTool(parent, wx_ids, text, bmp, tooltip_text):
if text in ['Pan', 'Zoom']:
kind = wx.ITEM_CHECK
else:
kind = wx.ITEM_NORMAL
if is_phoenix:
add_tool = parent.AddTool
else:
add_tool = parent.DoAddTool
if not is_phoenix or wx_version >= str("4.0.0b2"):
# NOTE: when support for Phoenix prior to 4.0.0b2 is dropped then
# all that is needed is this clause, and the if and else clause can
# be removed.
kwargs = dict(label=text,
bitmap=bmp,
bmpDisabled=wx.NullBitmap,
shortHelp=text,
longHelp=tooltip_text,
kind=kind)
else:
kwargs = dict(label=text,
bitmap=bmp,
bmpDisabled=wx.NullBitmap,
shortHelpString=text,
longHelpString=tooltip_text,
kind=kind)
return add_tool(wx_ids[text], **kwargs)
| 5,751 | 31.134078 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_qt5agg.py | """
Render to qt from agg
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import ctypes
from matplotlib import cbook
from matplotlib.transforms import Bbox
from .backend_agg import FigureCanvasAgg
from .backend_qt5 import (
QtCore, QtGui, QtWidgets, _BackendQT5, FigureCanvasQT, FigureManagerQT,
NavigationToolbar2QT, backend_version)
from .qt_compat import QT_API
class FigureCanvasQTAgg(FigureCanvasAgg, FigureCanvasQT):
def __init__(self, figure):
super(FigureCanvasQTAgg, self).__init__(figure=figure)
self._bbox_queue = []
@property
@cbook.deprecated("2.1")
def blitbox(self):
return self._bbox_queue
def paintEvent(self, e):
"""Copy the image from the Agg canvas to the qt.drawable.
In Qt, all drawing should be done inside of here when a widget is
shown onscreen.
"""
if self._update_dpi():
# The dpi update triggered its own paintEvent.
return
self._draw_idle() # Only does something if a draw is pending.
# if the canvas does not have a renderer, then give up and wait for
# FigureCanvasAgg.draw(self) to be called
if not hasattr(self, 'renderer'):
return
painter = QtGui.QPainter(self)
if self._bbox_queue:
bbox_queue = self._bbox_queue
else:
painter.eraseRect(self.rect())
bbox_queue = [
Bbox([[0, 0], [self.renderer.width, self.renderer.height]])]
self._bbox_queue = []
for bbox in bbox_queue:
l, b, r, t = map(int, bbox.extents)
w = r - l
h = t - b
reg = self.copy_from_bbox(bbox)
buf = reg.to_string_argb()
qimage = QtGui.QImage(buf, w, h, QtGui.QImage.Format_ARGB32)
# Adjust the buf reference count to work around a memory leak bug
# in QImage under PySide on Python 3.
if QT_API == 'PySide' and six.PY3:
ctypes.c_long.from_address(id(buf)).value = 1
if hasattr(qimage, 'setDevicePixelRatio'):
# Not available on Qt4 or some older Qt5.
qimage.setDevicePixelRatio(self._dpi_ratio)
origin = QtCore.QPoint(l, self.renderer.height - t)
painter.drawImage(origin / self._dpi_ratio, qimage)
self._draw_rect_callback(painter)
painter.end()
def blit(self, bbox=None):
"""Blit the region in bbox.
"""
# If bbox is None, blit the entire canvas. Otherwise
# blit only the area defined by the bbox.
if bbox is None and self.figure:
bbox = self.figure.bbox
self._bbox_queue.append(bbox)
# repaint uses logical pixels, not physical pixels like the renderer.
l, b, w, h = [pt / self._dpi_ratio for pt in bbox.bounds]
t = b + h
self.repaint(l, self.renderer.height / self._dpi_ratio - t, w, h)
def print_figure(self, *args, **kwargs):
super(FigureCanvasQTAgg, self).print_figure(*args, **kwargs)
self.draw()
@cbook.deprecated("2.2")
class FigureCanvasQTAggBase(FigureCanvasQTAgg):
pass
@_BackendQT5.export
class _BackendQT5Agg(_BackendQT5):
FigureCanvas = FigureCanvasQTAgg
| 3,357 | 30.679245 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_wx.py | """
A wxPython backend for matplotlib, based (very heavily) on
backend_template.py and backend_gtk.py
Author: Jeremy O'Donoghue ([email protected])
Derived from original copyright work by John Hunter
([email protected])
Copyright (C) Jeremy O'Donoghue & John Hunter, 2003-4
License: This work is licensed under a PSF compatible license. A copy
should be included with this source code.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import six
import sys
import os
import os.path
import math
import weakref
import warnings
import matplotlib
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
NavigationToolbar2, RendererBase, TimerBase, cursors)
from matplotlib.backend_bases import _has_pil
from matplotlib._pylab_helpers import Gcf
from matplotlib.cbook import is_writable_file_like, warn_deprecated
from matplotlib.figure import Figure
from matplotlib.path import Path
from matplotlib.transforms import Affine2D
from matplotlib.widgets import SubplotTool
from matplotlib import cbook, rcParams, backend_tools
from . import wx_compat as wxc
import wx
# Debugging settings here...
# Debug level set here. If the debug level is less than 5, information
# messages (progressively more info for lower value) are printed. In addition,
# traceback is performed, and pdb activated, for all uncaught exceptions in
# this case
_DEBUG = 5
if _DEBUG < 5:
import traceback
import pdb
_DEBUG_lvls = {1: 'Low ', 2: 'Med ', 3: 'High', 4: 'Error'}
def DEBUG_MSG(string, lvl=3, o=None):
if lvl >= _DEBUG:
cls = o.__class__
# Jeremy, often times the commented line won't print but the
# one below does. I think WX is redefining stderr, damned
# beast
# print("%s- %s in %s" % (_DEBUG_lvls[lvl], string, cls),
# file=sys.stderr)
print("%s- %s in %s" % (_DEBUG_lvls[lvl], string, cls))
def debug_on_error(type, value, tb):
"""Code due to Thomas Heller - published in Python Cookbook (O'Reilley)"""
traceback.print_exception(type, value, tb)
print()
pdb.pm() # jdh uncomment
class fake_stderr(object):
"""
Wx does strange things with stderr, as it makes the assumption that
there is probably no console. This redirects stderr to the console, since
we know that there is one!
"""
def write(self, msg):
print("Stderr: %s\n\r" % msg)
# the True dots per inch on the screen; should be display dependent
# see
# http://groups.google.com/groups?q=screen+dpi+x11&hl=en&lr=&ie=UTF-8&oe=UTF-8&safe=off&selm=7077.26e81ad5%40swift.cs.tcd.ie&rnum=5
# for some info about screen dpi
PIXELS_PER_INCH = 75
# Delay time for idle checks
IDLE_DELAY = 5
def error_msg_wx(msg, parent=None):
"""
Signal an error condition -- in a GUI, popup a error dialog
"""
dialog = wx.MessageDialog(parent=parent,
message=msg,
caption='Matplotlib backend_wx error',
style=wx.OK | wx.CENTRE)
dialog.ShowModal()
dialog.Destroy()
return None
def raise_msg_to_str(msg):
"""msg is a return arg from a raise. Join with new lines."""
if not isinstance(msg, six.string_types):
msg = '\n'.join(map(str, msg))
return msg
class TimerWx(TimerBase):
'''
Subclass of :class:`backend_bases.TimerBase` that uses WxTimer events.
Attributes
----------
interval : int
The time between timer events in milliseconds. Default is 1000 ms.
single_shot : bool
Boolean flag indicating whether this timer should operate as single
shot (run once and then stop). Defaults to False.
callbacks : list
Stores list of (func, args) tuples that will be called upon timer
events. This list can be manipulated directly, or the functions
`add_callback` and `remove_callback` can be used.
'''
def __init__(self, parent, *args, **kwargs):
TimerBase.__init__(self, *args, **kwargs)
# Create a new timer and connect the timer event to our handler.
# For WX, the events have to use a widget for binding.
self.parent = parent
self._timer = wx.Timer(self.parent, wx.NewId())
self.parent.Bind(wx.EVT_TIMER, self._on_timer, self._timer)
# Unbinding causes Wx to stop for some reason. Disabling for now.
# def __del__(self):
# TimerBase.__del__(self)
# self.parent.Bind(wx.EVT_TIMER, None, self._timer)
def _timer_start(self):
self._timer.Start(self._interval, self._single)
def _timer_stop(self):
self._timer.Stop()
def _timer_set_interval(self):
self._timer_start()
def _timer_set_single_shot(self):
self._timer.Start()
def _on_timer(self, *args):
TimerBase._on_timer(self)
class RendererWx(RendererBase):
"""
The renderer handles all the drawing primitives using a graphics
context instance that controls the colors/styles. It acts as the
'renderer' instance used by many classes in the hierarchy.
"""
# In wxPython, drawing is performed on a wxDC instance, which will
# generally be mapped to the client aread of the window displaying
# the plot. Under wxPython, the wxDC instance has a wx.Pen which
# describes the colour and weight of any lines drawn, and a wxBrush
# which describes the fill colour of any closed polygon.
fontweights = wxc.fontweights
fontangles = wxc.fontangles
# wxPython allows for portable font styles, choosing them appropriately
# for the target platform. Map some standard font names to the portable
# styles
# QUESTION: Is it be wise to agree standard fontnames across all backends?
fontnames = wxc.fontnames
def __init__(self, bitmap, dpi):
"""
Initialise a wxWindows renderer instance.
"""
warn_deprecated('2.0', message="The WX backend is "
"deprecated. It's untested "
"and will be removed in Matplotlib 3.0. "
"Use the WXAgg backend instead. "
"See Matplotlib usage FAQ for more info on backends.",
alternative='WXAgg')
RendererBase.__init__(self)
DEBUG_MSG("__init__()", 1, self)
self.width = bitmap.GetWidth()
self.height = bitmap.GetHeight()
self.bitmap = bitmap
self.fontd = {}
self.dpi = dpi
self.gc = None
def flipy(self):
return True
def offset_text_height(self):
return True
def get_text_width_height_descent(self, s, prop, ismath):
"""
get the width and height in display coords of the string s
with FontPropertry prop
"""
# return 1, 1
if ismath:
s = self.strip_math(s)
if self.gc is None:
gc = self.new_gc()
else:
gc = self.gc
gfx_ctx = gc.gfx_ctx
font = self.get_wx_font(s, prop)
gfx_ctx.SetFont(font, wx.BLACK)
w, h, descent, leading = gfx_ctx.GetFullTextExtent(s)
return w, h, descent
def get_canvas_width_height(self):
'return the canvas width and height in display coords'
return self.width, self.height
def handle_clip_rectangle(self, gc):
new_bounds = gc.get_clip_rectangle()
if new_bounds is not None:
new_bounds = new_bounds.bounds
gfx_ctx = gc.gfx_ctx
if gfx_ctx._lastcliprect != new_bounds:
gfx_ctx._lastcliprect = new_bounds
if new_bounds is None:
gfx_ctx.ResetClip()
else:
gfx_ctx.Clip(new_bounds[0],
self.height - new_bounds[1] - new_bounds[3],
new_bounds[2], new_bounds[3])
@staticmethod
def convert_path(gfx_ctx, path, transform):
wxpath = gfx_ctx.CreatePath()
for points, code in path.iter_segments(transform):
if code == Path.MOVETO:
wxpath.MoveToPoint(*points)
elif code == Path.LINETO:
wxpath.AddLineToPoint(*points)
elif code == Path.CURVE3:
wxpath.AddQuadCurveToPoint(*points)
elif code == Path.CURVE4:
wxpath.AddCurveToPoint(*points)
elif code == Path.CLOSEPOLY:
wxpath.CloseSubpath()
return wxpath
def draw_path(self, gc, path, transform, rgbFace=None):
gc.select()
self.handle_clip_rectangle(gc)
gfx_ctx = gc.gfx_ctx
transform = transform + \
Affine2D().scale(1.0, -1.0).translate(0.0, self.height)
wxpath = self.convert_path(gfx_ctx, path, transform)
if rgbFace is not None:
gfx_ctx.SetBrush(wx.Brush(gc.get_wxcolour(rgbFace)))
gfx_ctx.DrawPath(wxpath)
else:
gfx_ctx.StrokePath(wxpath)
gc.unselect()
def draw_image(self, gc, x, y, im):
bbox = gc.get_clip_rectangle()
if bbox is not None:
l, b, w, h = bbox.bounds
else:
l = 0
b = 0
w = self.width
h = self.height
rows, cols = im.shape[:2]
bitmap = wxc.BitmapFromBuffer(cols, rows, im.tostring())
gc = self.get_gc()
gc.select()
gc.gfx_ctx.DrawBitmap(bitmap, int(l), int(self.height - b),
int(w), int(-h))
gc.unselect()
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
if ismath:
s = self.strip_math(s)
DEBUG_MSG("draw_text()", 1, self)
gc.select()
self.handle_clip_rectangle(gc)
gfx_ctx = gc.gfx_ctx
font = self.get_wx_font(s, prop)
color = gc.get_wxcolour(gc.get_rgb())
gfx_ctx.SetFont(font, color)
w, h, d = self.get_text_width_height_descent(s, prop, ismath)
x = int(x)
y = int(y - h)
if angle == 0.0:
gfx_ctx.DrawText(s, x, y)
else:
rads = math.radians(angle)
xo = h * math.sin(rads)
yo = h * math.cos(rads)
gfx_ctx.DrawRotatedText(s, x - xo, y - yo, rads)
gc.unselect()
def new_gc(self):
"""
Return an instance of a GraphicsContextWx, and sets the current gc copy
"""
DEBUG_MSG('new_gc()', 2, self)
self.gc = GraphicsContextWx(self.bitmap, self)
self.gc.select()
self.gc.unselect()
return self.gc
def get_gc(self):
"""
Fetch the locally cached gc.
"""
# This is a dirty hack to allow anything with access to a renderer to
# access the current graphics context
assert self.gc is not None, "gc must be defined"
return self.gc
def get_wx_font(self, s, prop):
"""
Return a wx font. Cache instances in a font dictionary for
efficiency
"""
DEBUG_MSG("get_wx_font()", 1, self)
key = hash(prop)
fontprop = prop
fontname = fontprop.get_name()
font = self.fontd.get(key)
if font is not None:
return font
# Allow use of platform independent and dependent font names
wxFontname = self.fontnames.get(fontname, wx.ROMAN)
wxFacename = '' # Empty => wxPython chooses based on wx_fontname
# Font colour is determined by the active wx.Pen
# TODO: It may be wise to cache font information
size = self.points_to_pixels(fontprop.get_size_in_points())
font = wx.Font(int(size + 0.5), # Size
wxFontname, # 'Generic' name
self.fontangles[fontprop.get_style()], # Angle
self.fontweights[fontprop.get_weight()], # Weight
False, # Underline
wxFacename) # Platform font name
# cache the font and gc and return it
self.fontd[key] = font
return font
def points_to_pixels(self, points):
"""
convert point measures to pixes using dpi and the pixels per
inch of the display
"""
return points * (PIXELS_PER_INCH / 72.0 * self.dpi / 72.0)
class GraphicsContextWx(GraphicsContextBase):
"""
The graphics context provides the color, line styles, etc...
This class stores a reference to a wxMemoryDC, and a
wxGraphicsContext that draws to it. Creating a wxGraphicsContext
seems to be fairly heavy, so these objects are cached based on the
bitmap object that is passed in.
The base GraphicsContext stores colors as a RGB tuple on the unit
interval, e.g., (0.5, 0.0, 1.0). wxPython uses an int interval, but
since wxPython colour management is rather simple, I have not chosen
to implement a separate colour manager class.
"""
_capd = {'butt': wx.CAP_BUTT,
'projecting': wx.CAP_PROJECTING,
'round': wx.CAP_ROUND}
_joind = {'bevel': wx.JOIN_BEVEL,
'miter': wx.JOIN_MITER,
'round': wx.JOIN_ROUND}
_cache = weakref.WeakKeyDictionary()
def __init__(self, bitmap, renderer):
GraphicsContextBase.__init__(self)
# assert self.Ok(), "wxMemoryDC not OK to use"
DEBUG_MSG("__init__()", 1, self)
DEBUG_MSG("__init__() 2: %s" % bitmap, 1, self)
dc, gfx_ctx = self._cache.get(bitmap, (None, None))
if dc is None:
dc = wx.MemoryDC()
dc.SelectObject(bitmap)
gfx_ctx = wx.GraphicsContext.Create(dc)
gfx_ctx._lastcliprect = None
self._cache[bitmap] = dc, gfx_ctx
self.bitmap = bitmap
self.dc = dc
self.gfx_ctx = gfx_ctx
self._pen = wx.Pen('BLACK', 1, wx.SOLID)
gfx_ctx.SetPen(self._pen)
self._style = wx.SOLID
self.renderer = renderer
def select(self):
"""
Select the current bitmap into this wxDC instance
"""
if sys.platform == 'win32':
self.dc.SelectObject(self.bitmap)
self.IsSelected = True
def unselect(self):
"""
Select a Null bitmasp into this wxDC instance
"""
if sys.platform == 'win32':
self.dc.SelectObject(wx.NullBitmap)
self.IsSelected = False
def set_foreground(self, fg, isRGBA=None):
"""
Set the foreground color. fg can be a matlab format string, a
html hex color string, an rgb unit tuple, or a float between 0
and 1. In the latter case, grayscale is used.
"""
# Implementation note: wxPython has a separate concept of pen and
# brush - the brush fills any outline trace left by the pen.
# Here we set both to the same colour - if a figure is not to be
# filled, the renderer will set the brush to be transparent
# Same goes for text foreground...
DEBUG_MSG("set_foreground()", 1, self)
self.select()
GraphicsContextBase.set_foreground(self, fg, isRGBA)
self._pen.SetColour(self.get_wxcolour(self.get_rgb()))
self.gfx_ctx.SetPen(self._pen)
self.unselect()
def set_linewidth(self, w):
"""
Set the line width.
"""
w = float(w)
DEBUG_MSG("set_linewidth()", 1, self)
self.select()
if w > 0 and w < 1:
w = 1
GraphicsContextBase.set_linewidth(self, w)
lw = int(self.renderer.points_to_pixels(self._linewidth))
if lw == 0:
lw = 1
self._pen.SetWidth(lw)
self.gfx_ctx.SetPen(self._pen)
self.unselect()
def set_capstyle(self, cs):
"""
Set the capstyle as a string in ('butt', 'round', 'projecting')
"""
DEBUG_MSG("set_capstyle()", 1, self)
self.select()
GraphicsContextBase.set_capstyle(self, cs)
self._pen.SetCap(GraphicsContextWx._capd[self._capstyle])
self.gfx_ctx.SetPen(self._pen)
self.unselect()
def set_joinstyle(self, js):
"""
Set the join style to be one of ('miter', 'round', 'bevel')
"""
DEBUG_MSG("set_joinstyle()", 1, self)
self.select()
GraphicsContextBase.set_joinstyle(self, js)
self._pen.SetJoin(GraphicsContextWx._joind[self._joinstyle])
self.gfx_ctx.SetPen(self._pen)
self.unselect()
@cbook.deprecated("2.1")
def set_linestyle(self, ls):
"""
Set the line style to be one of
"""
DEBUG_MSG("set_linestyle()", 1, self)
self.select()
GraphicsContextBase.set_linestyle(self, ls)
try:
self._style = wxc.dashd_wx[ls]
except KeyError:
self._style = wx.LONG_DASH # Style not used elsewhere...
# On MS Windows platform, only line width of 1 allowed for dash lines
if wx.Platform == '__WXMSW__':
self.set_linewidth(1)
self._pen.SetStyle(self._style)
self.gfx_ctx.SetPen(self._pen)
self.unselect()
def get_wxcolour(self, color):
"""return a wx.Colour from RGB format"""
DEBUG_MSG("get_wx_color()", 1, self)
if len(color) == 3:
r, g, b = color
r *= 255
g *= 255
b *= 255
return wx.Colour(red=int(r), green=int(g), blue=int(b))
else:
r, g, b, a = color
r *= 255
g *= 255
b *= 255
a *= 255
return wx.Colour(
red=int(r),
green=int(g),
blue=int(b),
alpha=int(a))
class _FigureCanvasWxBase(FigureCanvasBase, wx.Panel):
"""
The FigureCanvas contains the figure and does event handling.
In the wxPython backend, it is derived from wxPanel, and (usually) lives
inside a frame instantiated by a FigureManagerWx. The parent window
probably implements a wx.Sizer to control the displayed control size - but
we give a hint as to our preferred minimum size.
"""
keyvald = {
wx.WXK_CONTROL: 'control',
wx.WXK_SHIFT: 'shift',
wx.WXK_ALT: 'alt',
wx.WXK_LEFT: 'left',
wx.WXK_UP: 'up',
wx.WXK_RIGHT: 'right',
wx.WXK_DOWN: 'down',
wx.WXK_ESCAPE: 'escape',
wx.WXK_F1: 'f1',
wx.WXK_F2: 'f2',
wx.WXK_F3: 'f3',
wx.WXK_F4: 'f4',
wx.WXK_F5: 'f5',
wx.WXK_F6: 'f6',
wx.WXK_F7: 'f7',
wx.WXK_F8: 'f8',
wx.WXK_F9: 'f9',
wx.WXK_F10: 'f10',
wx.WXK_F11: 'f11',
wx.WXK_F12: 'f12',
wx.WXK_SCROLL: 'scroll_lock',
wx.WXK_PAUSE: 'break',
wx.WXK_BACK: 'backspace',
wx.WXK_RETURN: 'enter',
wx.WXK_INSERT: 'insert',
wx.WXK_DELETE: 'delete',
wx.WXK_HOME: 'home',
wx.WXK_END: 'end',
wx.WXK_PAGEUP: 'pageup',
wx.WXK_PAGEDOWN: 'pagedown',
wx.WXK_NUMPAD0: '0',
wx.WXK_NUMPAD1: '1',
wx.WXK_NUMPAD2: '2',
wx.WXK_NUMPAD3: '3',
wx.WXK_NUMPAD4: '4',
wx.WXK_NUMPAD5: '5',
wx.WXK_NUMPAD6: '6',
wx.WXK_NUMPAD7: '7',
wx.WXK_NUMPAD8: '8',
wx.WXK_NUMPAD9: '9',
wx.WXK_NUMPAD_ADD: '+',
wx.WXK_NUMPAD_SUBTRACT: '-',
wx.WXK_NUMPAD_MULTIPLY: '*',
wx.WXK_NUMPAD_DIVIDE: '/',
wx.WXK_NUMPAD_DECIMAL: 'dec',
wx.WXK_NUMPAD_ENTER: 'enter',
wx.WXK_NUMPAD_UP: 'up',
wx.WXK_NUMPAD_RIGHT: 'right',
wx.WXK_NUMPAD_DOWN: 'down',
wx.WXK_NUMPAD_LEFT: 'left',
wx.WXK_NUMPAD_PAGEUP: 'pageup',
wx.WXK_NUMPAD_PAGEDOWN: 'pagedown',
wx.WXK_NUMPAD_HOME: 'home',
wx.WXK_NUMPAD_END: 'end',
wx.WXK_NUMPAD_INSERT: 'insert',
wx.WXK_NUMPAD_DELETE: 'delete',
}
def __init__(self, parent, id, figure):
"""
Initialise a FigureWx instance.
- Initialise the FigureCanvasBase and wxPanel parents.
- Set event handlers for:
EVT_SIZE (Resize event)
EVT_PAINT (Paint event)
"""
FigureCanvasBase.__init__(self, figure)
# Set preferred window size hint - helps the sizer (if one is
# connected)
l, b, w, h = figure.bbox.bounds
w = int(math.ceil(w))
h = int(math.ceil(h))
wx.Panel.__init__(self, parent, id, size=wx.Size(w, h))
def do_nothing(*args, **kwargs):
warnings.warn(
"could not find a setinitialsize function for backend_wx; "
"please report your wxpython version=%s "
"to the matplotlib developers list" %
wxc.backend_version)
pass
# try to find the set size func across wx versions
try:
getattr(self, 'SetInitialSize')
except AttributeError:
self.SetInitialSize = getattr(self, 'SetBestFittingSize',
do_nothing)
if not hasattr(self, 'IsShownOnScreen'):
self.IsShownOnScreen = getattr(self, 'IsVisible',
lambda *args: True)
# Create the drawing bitmap
self.bitmap = wxc.EmptyBitmap(w, h)
DEBUG_MSG("__init__() - bitmap w:%d h:%d" % (w, h), 2, self)
# TODO: Add support for 'point' inspection and plot navigation.
self._isDrawn = False
self.Bind(wx.EVT_SIZE, self._onSize)
self.Bind(wx.EVT_PAINT, self._onPaint)
self.Bind(wx.EVT_KEY_DOWN, self._onKeyDown)
self.Bind(wx.EVT_KEY_UP, self._onKeyUp)
self.Bind(wx.EVT_RIGHT_DOWN, self._onRightButtonDown)
self.Bind(wx.EVT_RIGHT_DCLICK, self._onRightButtonDClick)
self.Bind(wx.EVT_RIGHT_UP, self._onRightButtonUp)
self.Bind(wx.EVT_MOUSEWHEEL, self._onMouseWheel)
self.Bind(wx.EVT_LEFT_DOWN, self._onLeftButtonDown)
self.Bind(wx.EVT_LEFT_DCLICK, self._onLeftButtonDClick)
self.Bind(wx.EVT_LEFT_UP, self._onLeftButtonUp)
self.Bind(wx.EVT_MOTION, self._onMotion)
self.Bind(wx.EVT_LEAVE_WINDOW, self._onLeave)
self.Bind(wx.EVT_ENTER_WINDOW, self._onEnter)
# Add middle button events
self.Bind(wx.EVT_MIDDLE_DOWN, self._onMiddleButtonDown)
self.Bind(wx.EVT_MIDDLE_DCLICK, self._onMiddleButtonDClick)
self.Bind(wx.EVT_MIDDLE_UP, self._onMiddleButtonUp)
self.Bind(wx.EVT_MOUSE_CAPTURE_CHANGED, self._onCaptureLost)
self.Bind(wx.EVT_MOUSE_CAPTURE_LOST, self._onCaptureLost)
self.SetBackgroundStyle(wx.BG_STYLE_PAINT) # Reduce flicker.
self.SetBackgroundColour(wx.WHITE)
self.macros = {} # dict from wx id to seq of macros
def Destroy(self, *args, **kwargs):
wx.Panel.Destroy(self, *args, **kwargs)
def Copy_to_Clipboard(self, event=None):
"copy bitmap of canvas to system clipboard"
bmp_obj = wx.BitmapDataObject()
bmp_obj.SetBitmap(self.bitmap)
if not wx.TheClipboard.IsOpened():
open_success = wx.TheClipboard.Open()
if open_success:
wx.TheClipboard.SetData(bmp_obj)
wx.TheClipboard.Close()
wx.TheClipboard.Flush()
def draw_idle(self):
"""
Delay rendering until the GUI is idle.
"""
DEBUG_MSG("draw_idle()", 1, self)
self._isDrawn = False # Force redraw
# Triggering a paint event is all that is needed to defer drawing
# until later. The platform will send the event when it thinks it is
# a good time (usually as soon as there are no other events pending).
self.Refresh(eraseBackground=False)
def new_timer(self, *args, **kwargs):
"""
Creates a new backend-specific subclass of
:class:`backend_bases.Timer`. This is useful for getting periodic
events through the backend's native event loop. Implemented only
for backends with GUIs.
Other Parameters
----------------
interval : scalar
Timer interval in milliseconds
callbacks : list
Sequence of (func, args, kwargs) where ``func(*args, **kwargs)``
will be executed by the timer every *interval*.
"""
return TimerWx(self, *args, **kwargs)
def flush_events(self):
wx.Yield()
def start_event_loop(self, timeout=0):
"""
Start an event loop. This is used to start a blocking event
loop so that interactive functions, such as ginput and
waitforbuttonpress, can wait for events. This should not be
confused with the main GUI event loop, which is always running
and has nothing to do with this.
This call blocks until a callback function triggers
stop_event_loop() or *timeout* is reached. If *timeout* is
<=0, never timeout.
Raises RuntimeError if event loop is already running.
"""
if hasattr(self, '_event_loop'):
raise RuntimeError("Event loop already running")
id = wx.NewId()
timer = wx.Timer(self, id=id)
if timeout > 0:
timer.Start(timeout * 1000, oneShot=True)
self.Bind(wx.EVT_TIMER, self.stop_event_loop, id=id)
# Event loop handler for start/stop event loop
self._event_loop = wxc.EventLoop()
self._event_loop.Run()
timer.Stop()
def stop_event_loop(self, event=None):
"""
Stop an event loop. This is used to stop a blocking event
loop so that interactive functions, such as ginput and
waitforbuttonpress, can wait for events.
"""
if hasattr(self, '_event_loop'):
if self._event_loop.IsRunning():
self._event_loop.Exit()
del self._event_loop
def _get_imagesave_wildcards(self):
'return the wildcard string for the filesave dialog'
default_filetype = self.get_default_filetype()
filetypes = self.get_supported_filetypes_grouped()
sorted_filetypes = sorted(filetypes.items())
wildcards = []
extensions = []
filter_index = 0
for i, (name, exts) in enumerate(sorted_filetypes):
ext_list = ';'.join(['*.%s' % ext for ext in exts])
extensions.append(exts[0])
wildcard = '%s (%s)|%s' % (name, ext_list, ext_list)
if default_filetype in exts:
filter_index = i
wildcards.append(wildcard)
wildcards = '|'.join(wildcards)
return wildcards, extensions, filter_index
def gui_repaint(self, drawDC=None, origin='WX'):
"""
Performs update of the displayed image on the GUI canvas, using the
supplied wx.PaintDC device context.
The 'WXAgg' backend sets origin accordingly.
"""
DEBUG_MSG("gui_repaint()", 1, self)
if self.IsShownOnScreen():
if not drawDC:
# not called from OnPaint use a ClientDC
drawDC = wx.ClientDC(self)
# following is for 'WX' backend on Windows
# the bitmap can not be in use by another DC,
# see GraphicsContextWx._cache
if wx.Platform == '__WXMSW__' and origin == 'WX':
img = self.bitmap.ConvertToImage()
bmp = img.ConvertToBitmap()
drawDC.DrawBitmap(bmp, 0, 0)
else:
drawDC.DrawBitmap(self.bitmap, 0, 0)
filetypes = FigureCanvasBase.filetypes.copy()
filetypes['bmp'] = 'Windows bitmap'
filetypes['jpeg'] = 'JPEG'
filetypes['jpg'] = 'JPEG'
filetypes['pcx'] = 'PCX'
filetypes['png'] = 'Portable Network Graphics'
filetypes['tif'] = 'Tagged Image Format File'
filetypes['tiff'] = 'Tagged Image Format File'
filetypes['xpm'] = 'X pixmap'
def print_figure(self, filename, *args, **kwargs):
super(_FigureCanvasWxBase, self).print_figure(
filename, *args, **kwargs)
# Restore the current view; this is needed because the artist contains
# methods rely on particular attributes of the rendered figure for
# determining things like bounding boxes.
if self._isDrawn:
self.draw()
def _onPaint(self, evt):
"""
Called when wxPaintEvt is generated
"""
DEBUG_MSG("_onPaint()", 1, self)
drawDC = wx.PaintDC(self)
if not self._isDrawn:
self.draw(drawDC=drawDC)
else:
self.gui_repaint(drawDC=drawDC)
drawDC.Destroy()
def _onSize(self, evt):
"""
Called when wxEventSize is generated.
In this application we attempt to resize to fit the window, so it
is better to take the performance hit and redraw the whole window.
"""
DEBUG_MSG("_onSize()", 2, self)
sz = self.GetParent().GetSizer()
if sz:
si = sz.GetItem(self)
if sz and si and not si.Proportion and not si.Flag & wx.EXPAND:
# managed by a sizer, but with a fixed size
size = self.GetMinSize()
else:
# variable size
size = self.GetClientSize()
if getattr(self, "_width", None):
if size == (self._width, self._height):
# no change in size
return
self._width, self._height = size
# Create a new, correctly sized bitmap
self.bitmap = wxc.EmptyBitmap(self._width, self._height)
self._isDrawn = False
if self._width <= 1 or self._height <= 1:
return # Empty figure
dpival = self.figure.dpi
winch = self._width / dpival
hinch = self._height / dpival
self.figure.set_size_inches(winch, hinch, forward=False)
# Rendering will happen on the associated paint event
# so no need to do anything here except to make sure
# the whole background is repainted.
self.Refresh(eraseBackground=False)
FigureCanvasBase.resize_event(self)
def _get_key(self, evt):
keyval = evt.KeyCode
if keyval in self.keyvald:
key = self.keyvald[keyval]
elif keyval < 256:
key = chr(keyval)
# wx always returns an uppercase, so make it lowercase if the shift
# key is not depressed (NOTE: this will not handle Caps Lock)
if not evt.ShiftDown():
key = key.lower()
else:
key = None
for meth, prefix in (
[evt.AltDown, 'alt'],
[evt.ControlDown, 'ctrl'], ):
if meth():
key = '{0}+{1}'.format(prefix, key)
return key
def _onKeyDown(self, evt):
"""Capture key press."""
key = self._get_key(evt)
FigureCanvasBase.key_press_event(self, key, guiEvent=evt)
if self:
evt.Skip()
def _onKeyUp(self, evt):
"""Release key."""
key = self._get_key(evt)
FigureCanvasBase.key_release_event(self, key, guiEvent=evt)
if self:
evt.Skip()
def _set_capture(self, capture=True):
"""control wx mouse capture """
if self.HasCapture():
self.ReleaseMouse()
if capture:
self.CaptureMouse()
def _onCaptureLost(self, evt):
"""Capture changed or lost"""
self._set_capture(False)
def _onRightButtonDown(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 3, guiEvent=evt)
def _onRightButtonDClick(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 3,
dblclick=True, guiEvent=evt)
def _onRightButtonUp(self, evt):
"""End measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(False)
FigureCanvasBase.button_release_event(self, x, y, 3, guiEvent=evt)
def _onLeftButtonDown(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 1, guiEvent=evt)
def _onLeftButtonDClick(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 1,
dblclick=True, guiEvent=evt)
def _onLeftButtonUp(self, evt):
"""End measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(False)
FigureCanvasBase.button_release_event(self, x, y, 1, guiEvent=evt)
# Add middle button events
def _onMiddleButtonDown(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 2, guiEvent=evt)
def _onMiddleButtonDClick(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(True)
FigureCanvasBase.button_press_event(self, x, y, 2,
dblclick=True, guiEvent=evt)
def _onMiddleButtonUp(self, evt):
"""End measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
self._set_capture(False)
FigureCanvasBase.button_release_event(self, x, y, 2, guiEvent=evt)
def _onMouseWheel(self, evt):
"""Translate mouse wheel events into matplotlib events"""
# Determine mouse location
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
# Convert delta/rotation/rate into a floating point step size
delta = evt.GetWheelDelta()
rotation = evt.GetWheelRotation()
rate = evt.GetLinesPerAction()
step = rate * rotation / delta
# Done handling event
evt.Skip()
# Mac is giving two events for every wheel event
# Need to skip every second one
if wx.Platform == '__WXMAC__':
if not hasattr(self, '_skipwheelevent'):
self._skipwheelevent = True
elif self._skipwheelevent:
self._skipwheelevent = False
return # Return without processing event
else:
self._skipwheelevent = True
# Convert to mpl event
FigureCanvasBase.scroll_event(self, x, y, step, guiEvent=evt)
def _onMotion(self, evt):
"""Start measuring on an axis."""
x = evt.GetX()
y = self.figure.bbox.height - evt.GetY()
evt.Skip()
FigureCanvasBase.motion_notify_event(self, x, y, guiEvent=evt)
def _onLeave(self, evt):
"""Mouse has left the window."""
evt.Skip()
FigureCanvasBase.leave_notify_event(self, guiEvent=evt)
def _onEnter(self, evt):
"""Mouse has entered the window."""
FigureCanvasBase.enter_notify_event(self, guiEvent=evt)
class FigureCanvasWx(_FigureCanvasWxBase):
# Rendering to a Wx canvas using the deprecated Wx renderer.
def draw(self, drawDC=None):
"""
Render the figure using RendererWx instance renderer, or using a
previously defined renderer if none is specified.
"""
DEBUG_MSG("draw()", 1, self)
self.renderer = RendererWx(self.bitmap, self.figure.dpi)
self.figure.draw(self.renderer)
self._isDrawn = True
self.gui_repaint(drawDC=drawDC)
def print_bmp(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_BMP, *args, **kwargs)
if not _has_pil:
def print_jpeg(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_JPEG,
*args, **kwargs)
print_jpg = print_jpeg
def print_pcx(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_PCX, *args, **kwargs)
def print_png(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_PNG, *args, **kwargs)
if not _has_pil:
def print_tiff(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_TIF,
*args, **kwargs)
print_tif = print_tiff
def print_xpm(self, filename, *args, **kwargs):
return self._print_image(filename, wx.BITMAP_TYPE_XPM, *args, **kwargs)
def _print_image(self, filename, filetype, *args, **kwargs):
origBitmap = self.bitmap
l, b, width, height = self.figure.bbox.bounds
width = int(math.ceil(width))
height = int(math.ceil(height))
self.bitmap = wxc.EmptyBitmap(width, height)
renderer = RendererWx(self.bitmap, self.figure.dpi)
gc = renderer.new_gc()
self.figure.draw(renderer)
# image is the object that we call SaveFile on.
image = self.bitmap
# set the JPEG quality appropriately. Unfortunately, it is only
# possible to set the quality on a wx.Image object. So if we
# are saving a JPEG, convert the wx.Bitmap to a wx.Image,
# and set the quality.
if filetype == wx.BITMAP_TYPE_JPEG:
jpeg_quality = kwargs.get('quality',
rcParams['savefig.jpeg_quality'])
image = self.bitmap.ConvertToImage()
image.SetOption(wx.IMAGE_OPTION_QUALITY, str(jpeg_quality))
# Now that we have rendered into the bitmap, save it
# to the appropriate file type and clean up
if isinstance(filename, six.string_types):
if not image.SaveFile(filename, filetype):
DEBUG_MSG('print_figure() file save error', 4, self)
raise RuntimeError(
'Could not save figure to %s\n' %
(filename))
elif is_writable_file_like(filename):
if not isinstance(image, wx.Image):
image = image.ConvertToImage()
if not image.SaveStream(filename, filetype):
DEBUG_MSG('print_figure() file save error', 4, self)
raise RuntimeError(
'Could not save figure to %s\n' %
(filename))
# Restore everything to normal
self.bitmap = origBitmap
# Note: draw is required here since bits of state about the
# last renderer are strewn about the artist draw methods. Do
# not remove the draw without first verifying that these have
# been cleaned up. The artist contains() methods will fail
# otherwise.
if self._isDrawn:
self.draw()
self.Refresh()
########################################################################
#
# The following functions and classes are for pylab compatibility
# mode (matplotlib.pylab) and implement figure managers, etc...
#
########################################################################
class FigureFrameWx(wx.Frame):
def __init__(self, num, fig):
# On non-Windows platform, explicitly set the position - fix
# positioning bug on some Linux platforms
if wx.Platform == '__WXMSW__':
pos = wx.DefaultPosition
else:
pos = wx.Point(20, 20)
l, b, w, h = fig.bbox.bounds
wx.Frame.__init__(self, parent=None, id=-1, pos=pos,
title="Figure %d" % num)
# Frame will be sized later by the Fit method
DEBUG_MSG("__init__()", 1, self)
self.num = num
statbar = StatusBarWx(self)
self.SetStatusBar(statbar)
self.canvas = self.get_canvas(fig)
self.canvas.SetInitialSize(wx.Size(fig.bbox.width, fig.bbox.height))
self.canvas.SetFocus()
self.sizer = wx.BoxSizer(wx.VERTICAL)
self.sizer.Add(self.canvas, 1, wx.TOP | wx.LEFT | wx.EXPAND)
# By adding toolbar in sizer, we are able to put it at the bottom
# of the frame - so appearance is closer to GTK version
self.toolbar = self._get_toolbar(statbar)
if self.toolbar is not None:
self.toolbar.Realize()
# On Windows platform, default window size is incorrect, so set
# toolbar width to figure width.
if wxc.is_phoenix:
tw, th = self.toolbar.GetSize()
fw, fh = self.canvas.GetSize()
else:
tw, th = self.toolbar.GetSizeTuple()
fw, fh = self.canvas.GetSizeTuple()
# By adding toolbar in sizer, we are able to put it at the bottom
# of the frame - so appearance is closer to GTK version.
self.toolbar.SetSize(wx.Size(fw, th))
self.sizer.Add(self.toolbar, 0, wx.LEFT | wx.EXPAND)
self.SetSizer(self.sizer)
self.Fit()
self.canvas.SetMinSize((2, 2))
# give the window a matplotlib icon rather than the stock one.
# This is not currently working on Linux and is untested elsewhere.
# icon_path = os.path.join(matplotlib.rcParams['datapath'],
# 'images', 'matplotlib.png')
# icon = wx.IconFromBitmap(wx.Bitmap(icon_path))
# for xpm type icons try:
# icon = wx.Icon(icon_path, wx.BITMAP_TYPE_XPM)
# self.SetIcon(icon)
self.figmgr = FigureManagerWx(self.canvas, num, self)
self.Bind(wx.EVT_CLOSE, self._onClose)
def _get_toolbar(self, statbar):
if rcParams['toolbar'] == 'toolbar2':
toolbar = NavigationToolbar2Wx(self.canvas)
toolbar.set_status_bar(statbar)
else:
toolbar = None
return toolbar
def get_canvas(self, fig):
return FigureCanvasWx(self, -1, fig)
def get_figure_manager(self):
DEBUG_MSG("get_figure_manager()", 1, self)
return self.figmgr
def _onClose(self, evt):
DEBUG_MSG("onClose()", 1, self)
self.canvas.close_event()
self.canvas.stop_event_loop()
Gcf.destroy(self.num)
# self.Destroy()
def GetToolBar(self):
"""Override wxFrame::GetToolBar as we don't have managed toolbar"""
return self.toolbar
def Destroy(self, *args, **kwargs):
try:
self.canvas.mpl_disconnect(self.toolbar._idDrag)
# Rationale for line above: see issue 2941338.
except AttributeError:
pass # classic toolbar lacks the attribute
if not self.IsBeingDeleted():
wx.Frame.Destroy(self, *args, **kwargs)
if self.toolbar is not None:
self.toolbar.Destroy()
wxapp = wx.GetApp()
if wxapp:
wxapp.Yield()
return True
class FigureManagerWx(FigureManagerBase):
"""
This class contains the FigureCanvas and GUI frame
It is instantiated by GcfWx whenever a new figure is created. GcfWx is
responsible for managing multiple instances of FigureManagerWx.
Attributes
----------
canvas : `FigureCanvas`
a FigureCanvasWx(wx.Panel) instance
window : wxFrame
a wxFrame instance - wxpython.org/Phoenix/docs/html/Frame.html
"""
def __init__(self, canvas, num, frame):
DEBUG_MSG("__init__()", 1, self)
FigureManagerBase.__init__(self, canvas, num)
self.frame = frame
self.window = frame
self.tb = frame.GetToolBar()
self.toolbar = self.tb # consistent with other backends
def notify_axes_change(fig):
'this will be called whenever the current axes is changed'
if self.tb is not None:
self.tb.update()
self.canvas.figure.add_axobserver(notify_axes_change)
def show(self):
self.frame.Show()
self.canvas.draw()
def destroy(self, *args):
DEBUG_MSG("destroy()", 1, self)
self.frame.Destroy()
wxapp = wx.GetApp()
if wxapp:
wxapp.Yield()
def get_window_title(self):
return self.window.GetTitle()
def set_window_title(self, title):
self.window.SetTitle(title)
def resize(self, width, height):
'Set the canvas size in pixels'
self.canvas.SetInitialSize(wx.Size(width, height))
self.window.GetSizer().Fit(self.window)
# Identifiers for toolbar controls - images_wx contains bitmaps for the images
# used in the controls. wxWindows does not provide any stock images, so I've
# 'stolen' those from GTK2, and transformed them into the appropriate format.
# import images_wx
_NTB_AXISMENU = wx.NewId()
_NTB_AXISMENU_BUTTON = wx.NewId()
_NTB_X_PAN_LEFT = wx.NewId()
_NTB_X_PAN_RIGHT = wx.NewId()
_NTB_X_ZOOMIN = wx.NewId()
_NTB_X_ZOOMOUT = wx.NewId()
_NTB_Y_PAN_UP = wx.NewId()
_NTB_Y_PAN_DOWN = wx.NewId()
_NTB_Y_ZOOMIN = wx.NewId()
_NTB_Y_ZOOMOUT = wx.NewId()
# _NTB_SUBPLOT =wx.NewId()
_NTB_SAVE = wx.NewId()
_NTB_CLOSE = wx.NewId()
def _load_bitmap(filename):
"""
Load a bitmap file from the backends/images subdirectory in which the
matplotlib library is installed. The filename parameter should not
contain any path information as this is determined automatically.
Returns a wx.Bitmap object
"""
basedir = os.path.join(rcParams['datapath'], 'images')
bmpFilename = os.path.normpath(os.path.join(basedir, filename))
if not os.path.exists(bmpFilename):
raise IOError('Could not find bitmap file "%s"; dying' % bmpFilename)
bmp = wx.Bitmap(bmpFilename)
return bmp
class MenuButtonWx(wx.Button):
"""
wxPython does not permit a menu to be incorporated directly into a toolbar.
This class simulates the effect by associating a pop-up menu with a button
in the toolbar, and managing this as though it were a menu.
"""
def __init__(self, parent):
wx.Button.__init__(self, parent, _NTB_AXISMENU_BUTTON, "Axes: ",
style=wx.BU_EXACTFIT)
self._toolbar = parent
self._menu = wx.Menu()
self._axisId = []
# First two menu items never change...
self._allId = wx.NewId()
self._invertId = wx.NewId()
self._menu.Append(self._allId, "All", "Select all axes", False)
self._menu.Append(self._invertId, "Invert", "Invert axes selected",
False)
self._menu.AppendSeparator()
self.Bind(wx.EVT_BUTTON, self._onMenuButton, id=_NTB_AXISMENU_BUTTON)
self.Bind(wx.EVT_MENU, self._handleSelectAllAxes, id=self._allId)
self.Bind(wx.EVT_MENU, self._handleInvertAxesSelected,
id=self._invertId)
def Destroy(self):
self._menu.Destroy()
self.Destroy()
def _onMenuButton(self, evt):
"""Handle menu button pressed."""
if wxc.is_phoenix:
x, y = self.GetPosition()
w, h = self.GetSize()
else:
x, y = self.GetPositionTuple()
w, h = self.GetSizeTuple()
self.PopupMenuXY(self._menu, x, y + h - 4)
# When menu returned, indicate selection in button
evt.Skip()
def _handleSelectAllAxes(self, evt):
"""Called when the 'select all axes' menu item is selected."""
if len(self._axisId) == 0:
return
for i in range(len(self._axisId)):
self._menu.Check(self._axisId[i], True)
self._toolbar.set_active(self.getActiveAxes())
evt.Skip()
def _handleInvertAxesSelected(self, evt):
"""Called when the invert all menu item is selected"""
if len(self._axisId) == 0:
return
for i in range(len(self._axisId)):
if self._menu.IsChecked(self._axisId[i]):
self._menu.Check(self._axisId[i], False)
else:
self._menu.Check(self._axisId[i], True)
self._toolbar.set_active(self.getActiveAxes())
evt.Skip()
def _onMenuItemSelected(self, evt):
"""Called whenever one of the specific axis menu items is selected"""
current = self._menu.IsChecked(evt.GetId())
if current:
new = False
else:
new = True
self._menu.Check(evt.GetId(), new)
# Lines above would be deleted based on svn tracker ID 2841525;
# not clear whether this matters or not.
self._toolbar.set_active(self.getActiveAxes())
evt.Skip()
def updateAxes(self, maxAxis):
"""Ensures that there are entries for max_axis axes in the menu
(selected by default)."""
if maxAxis > len(self._axisId):
for i in range(len(self._axisId) + 1, maxAxis + 1, 1):
menuId = wx.NewId()
self._axisId.append(menuId)
self._menu.Append(menuId, "Axis %d" % i,
"Select axis %d" % i,
True)
self._menu.Check(menuId, True)
self.Bind(wx.EVT_MENU, self._onMenuItemSelected, id=menuId)
elif maxAxis < len(self._axisId):
for menuId in self._axisId[maxAxis:]:
self._menu.Delete(menuId)
self._axisId = self._axisId[:maxAxis]
self._toolbar.set_active(list(xrange(maxAxis)))
def getActiveAxes(self):
"""Return a list of the selected axes."""
active = []
for i in range(len(self._axisId)):
if self._menu.IsChecked(self._axisId[i]):
active.append(i)
return active
def updateButtonText(self, lst):
"""Update the list of selected axes in the menu button."""
self.SetLabel(
'Axes: ' + ','.join('%d' % (e + 1) for e in lst))
cursord = {
cursors.MOVE: wx.CURSOR_HAND,
cursors.HAND: wx.CURSOR_HAND,
cursors.POINTER: wx.CURSOR_ARROW,
cursors.SELECT_REGION: wx.CURSOR_CROSS,
cursors.WAIT: wx.CURSOR_WAIT,
}
@cbook.deprecated("2.2")
class SubplotToolWX(wx.Frame):
def __init__(self, targetfig):
wx.Frame.__init__(self, None, -1, "Configure subplots")
toolfig = Figure((6, 3))
canvas = FigureCanvasWx(self, -1, toolfig)
# Create a figure manager to manage things
figmgr = FigureManager(canvas, 1, self)
# Now put all into a sizer
sizer = wx.BoxSizer(wx.VERTICAL)
# This way of adding to sizer allows resizing
sizer.Add(canvas, 1, wx.LEFT | wx.TOP | wx.GROW)
self.SetSizer(sizer)
self.Fit()
tool = SubplotTool(targetfig, toolfig)
class NavigationToolbar2Wx(NavigationToolbar2, wx.ToolBar):
def __init__(self, canvas):
wx.ToolBar.__init__(self, canvas.GetParent(), -1)
NavigationToolbar2.__init__(self, canvas)
self.canvas = canvas
self._idle = True
self.statbar = None
self.prevZoomRect = None
# for now, use alternate zoom-rectangle drawing on all
# Macs. N.B. In future versions of wx it may be possible to
# detect Retina displays with window.GetContentScaleFactor()
# and/or dc.GetContentScaleFactor()
self.retinaFix = 'wxMac' in wx.PlatformInfo
def get_canvas(self, frame, fig):
return type(self.canvas)(frame, -1, fig)
def _init_toolbar(self):
DEBUG_MSG("_init_toolbar", 1, self)
self._parent = self.canvas.GetParent()
self.wx_ids = {}
for text, tooltip_text, image_file, callback in self.toolitems:
if text is None:
self.AddSeparator()
continue
self.wx_ids[text] = wx.NewId()
wxc._AddTool(self, self.wx_ids, text,
_load_bitmap(image_file + '.png'),
tooltip_text)
self.Bind(wx.EVT_TOOL, getattr(self, callback),
id=self.wx_ids[text])
self.Realize()
def zoom(self, *args):
self.ToggleTool(self.wx_ids['Pan'], False)
NavigationToolbar2.zoom(self, *args)
def pan(self, *args):
self.ToggleTool(self.wx_ids['Zoom'], False)
NavigationToolbar2.pan(self, *args)
def configure_subplots(self, evt):
frame = wx.Frame(None, -1, "Configure subplots")
toolfig = Figure((6, 3))
canvas = self.get_canvas(frame, toolfig)
# Create a figure manager to manage things
figmgr = FigureManager(canvas, 1, frame)
# Now put all into a sizer
sizer = wx.BoxSizer(wx.VERTICAL)
# This way of adding to sizer allows resizing
sizer.Add(canvas, 1, wx.LEFT | wx.TOP | wx.GROW)
frame.SetSizer(sizer)
frame.Fit()
tool = SubplotTool(self.canvas.figure, toolfig)
frame.Show()
def save_figure(self, *args):
# Fetch the required filename and file type.
filetypes, exts, filter_index = self.canvas._get_imagesave_wildcards()
default_file = self.canvas.get_default_filename()
dlg = wx.FileDialog(self._parent, "Save to file", "", default_file,
filetypes,
wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
dlg.SetFilterIndex(filter_index)
if dlg.ShowModal() == wx.ID_OK:
dirname = dlg.GetDirectory()
filename = dlg.GetFilename()
DEBUG_MSG(
'Save file dir:%s name:%s' %
(dirname, filename), 3, self)
format = exts[dlg.GetFilterIndex()]
basename, ext = os.path.splitext(filename)
if ext.startswith('.'):
ext = ext[1:]
if ext in ('svg', 'pdf', 'ps', 'eps', 'png') and format != ext:
# looks like they forgot to set the image type drop
# down, going with the extension.
warnings.warn(
'extension %s did not match the selected '
'image type %s; going with %s' %
(ext, format, ext), stacklevel=0)
format = ext
try:
self.canvas.figure.savefig(
os.path.join(dirname, filename), format=format)
except Exception as e:
error_msg_wx(str(e))
def set_cursor(self, cursor):
cursor = wxc.Cursor(cursord[cursor])
self.canvas.SetCursor(cursor)
self.canvas.Update()
@cbook.deprecated("2.1", alternative="canvas.draw_idle")
def dynamic_update(self):
d = self._idle
self._idle = False
if d:
self.canvas.draw()
self._idle = True
def press(self, event):
if self._active == 'ZOOM':
if not self.retinaFix:
self.wxoverlay = wx.Overlay()
else:
if event.inaxes is not None:
self.savedRetinaImage = self.canvas.copy_from_bbox(
event.inaxes.bbox)
self.zoomStartX = event.xdata
self.zoomStartY = event.ydata
self.zoomAxes = event.inaxes
def release(self, event):
if self._active == 'ZOOM':
# When the mouse is released we reset the overlay and it
# restores the former content to the window.
if not self.retinaFix:
self.wxoverlay.Reset()
del self.wxoverlay
else:
del self.savedRetinaImage
if self.prevZoomRect:
self.prevZoomRect.pop(0).remove()
self.prevZoomRect = None
if self.zoomAxes:
self.zoomAxes = None
def draw_rubberband(self, event, x0, y0, x1, y1):
if self.retinaFix: # On Macs, use the following code
# wx.DCOverlay does not work properly on Retina displays.
rubberBandColor = '#C0C0FF'
if self.prevZoomRect:
self.prevZoomRect.pop(0).remove()
self.canvas.restore_region(self.savedRetinaImage)
X0, X1 = self.zoomStartX, event.xdata
Y0, Y1 = self.zoomStartY, event.ydata
lineX = (X0, X0, X1, X1, X0)
lineY = (Y0, Y1, Y1, Y0, Y0)
self.prevZoomRect = self.zoomAxes.plot(
lineX, lineY, '-', color=rubberBandColor)
self.zoomAxes.draw_artist(self.prevZoomRect[0])
self.canvas.blit(self.zoomAxes.bbox)
return
# Use an Overlay to draw a rubberband-like bounding box.
dc = wx.ClientDC(self.canvas)
odc = wx.DCOverlay(self.wxoverlay, dc)
odc.Clear()
# Mac's DC is already the same as a GCDC, and it causes
# problems with the overlay if we try to use an actual
# wx.GCDC so don't try it.
if 'wxMac' not in wx.PlatformInfo:
dc = wx.GCDC(dc)
height = self.canvas.figure.bbox.height
y1 = height - y1
y0 = height - y0
if y1 < y0:
y0, y1 = y1, y0
if x1 < y0:
x0, x1 = x1, x0
w = x1 - x0
h = y1 - y0
rect = wx.Rect(x0, y0, w, h)
rubberBandColor = '#C0C0FF' # or load from config?
# Set a pen for the border
color = wxc.NamedColour(rubberBandColor)
dc.SetPen(wx.Pen(color, 1))
# use the same color, plus alpha for the brush
r, g, b, a = color.Get(True)
color.Set(r, g, b, 0x60)
dc.SetBrush(wx.Brush(color))
if wxc.is_phoenix:
dc.DrawRectangle(rect)
else:
dc.DrawRectangleRect(rect)
def set_status_bar(self, statbar):
self.statbar = statbar
def set_message(self, s):
if self.statbar is not None:
self.statbar.set_function(s)
def set_history_buttons(self):
can_backward = self._nav_stack._pos > 0
can_forward = self._nav_stack._pos < len(self._nav_stack._elements) - 1
self.EnableTool(self.wx_ids['Back'], can_backward)
self.EnableTool(self.wx_ids['Forward'], can_forward)
@cbook.deprecated("2.2", alternative="NavigationToolbar2Wx")
class Toolbar(NavigationToolbar2Wx):
pass
class StatusBarWx(wx.StatusBar):
"""
A status bar is added to _FigureFrame to allow measurements and the
previously selected scroll function to be displayed as a user
convenience.
"""
def __init__(self, parent):
wx.StatusBar.__init__(self, parent, -1)
self.SetFieldsCount(2)
self.SetStatusText("None", 1)
# self.SetStatusText("Measurement: None", 2)
# self.Reposition()
def set_function(self, string):
self.SetStatusText("%s" % string, 1)
# def set_measurement(self, string):
# self.SetStatusText("Measurement: %s" % string, 2)
# tools for matplotlib.backend_managers.ToolManager:
# for now only SaveFigure, SetCursor and Rubberband are implemented
# once a ToolbarWx is implemented, also FigureManagerWx needs to be
# modified, similar to pull request #9934
class SaveFigureWx(backend_tools.SaveFigureBase):
def trigger(self, *args):
# Fetch the required filename and file type.
filetypes, exts, filter_index = self.canvas._get_imagesave_wildcards()
default_dir = os.path.expanduser(
matplotlib.rcParams['savefig.directory'])
default_file = self.canvas.get_default_filename()
dlg = wx.FileDialog(self.canvas.GetTopLevelParent(), "Save to file",
default_dir, default_file, filetypes,
wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
dlg.SetFilterIndex(filter_index)
if dlg.ShowModal() != wx.ID_OK:
return
dirname = dlg.GetDirectory()
filename = dlg.GetFilename()
DEBUG_MSG('Save file dir:%s name:%s' % (dirname, filename), 3, self)
format = exts[dlg.GetFilterIndex()]
basename, ext = os.path.splitext(filename)
if ext.startswith('.'):
ext = ext[1:]
if ext in ('svg', 'pdf', 'ps', 'eps', 'png') and format != ext:
# looks like they forgot to set the image type drop
# down, going with the extension.
warnings.warn(
'extension %s did not match the selected '
'image type %s; going with %s' %
(ext, format, ext), stacklevel=0)
format = ext
if default_dir != "":
matplotlib.rcParams['savefig.directory'] = dirname
try:
self.canvas.figure.savefig(
os.path.join(dirname, filename), format=format)
except Exception as e:
error_msg_wx(str(e))
class SetCursorWx(backend_tools.SetCursorBase):
def set_cursor(self, cursor):
cursor = wxc.Cursor(cursord[cursor])
self.canvas.SetCursor(cursor)
self.canvas.Update()
if 'wxMac' not in wx.PlatformInfo:
# on most platforms, use overlay
class RubberbandWx(backend_tools.RubberbandBase):
def __init__(self, *args, **kwargs):
backend_tools.RubberbandBase.__init__(self, *args, **kwargs)
self.wxoverlay = None
def draw_rubberband(self, x0, y0, x1, y1):
# Use an Overlay to draw a rubberband-like bounding box.
if self.wxoverlay is None:
self.wxoverlay = wx.Overlay()
dc = wx.ClientDC(self.canvas)
odc = wx.DCOverlay(self.wxoverlay, dc)
odc.Clear()
dc = wx.GCDC(dc)
height = self.canvas.figure.bbox.height
y1 = height - y1
y0 = height - y0
if y1 < y0:
y0, y1 = y1, y0
if x1 < y0:
x0, x1 = x1, x0
w = x1 - x0
h = y1 - y0
rect = wx.Rect(x0, y0, w, h)
rubberBandColor = '#C0C0FF' # or load from config?
# Set a pen for the border
color = wxc.NamedColour(rubberBandColor)
dc.SetPen(wx.Pen(color, 1))
# use the same color, plus alpha for the brush
r, g, b, a = color.Get(True)
color.Set(r, g, b, 0x60)
dc.SetBrush(wx.Brush(color))
if wxc.is_phoenix:
dc.DrawRectangle(rect)
else:
dc.DrawRectangleRect(rect)
def remove_rubberband(self):
if self.wxoverlay is None:
return
self.wxoverlay.Reset()
self.wxoverlay = None
else:
# on Mac OS retina displays DCOverlay does not work
# and dc.SetLogicalFunction does not have an effect on any display
# the workaround is to blit the full image for remove_rubberband
class RubberbandWx(backend_tools.RubberbandBase):
def __init__(self, *args, **kwargs):
backend_tools.RubberbandBase.__init__(self, *args, **kwargs)
self._rect = None
def draw_rubberband(self, x0, y0, x1, y1):
dc = wx.ClientDC(self.canvas)
# this would be required if the Canvas is a ScrolledWindow,
# which is not the case for now
# self.PrepareDC(dc)
# delete old rubberband
if self._rect:
self.remove_rubberband(dc)
# draw new rubberband
dc.SetPen(wx.Pen(wx.BLACK, 1, wx.SOLID))
dc.SetBrush(wx.TRANSPARENT_BRUSH)
self._rect = (x0, self.canvas._height-y0, x1-x0, -y1+y0)
if wxc.is_phoenix:
dc.DrawRectangle(self._rect)
else:
dc.DrawRectangleRect(self._rect)
def remove_rubberband(self, dc=None):
if not self._rect:
return
if self.canvas.bitmap:
if dc is None:
dc = wx.ClientDC(self.canvas)
dc.DrawBitmap(self.canvas.bitmap, 0, 0)
# for testing the method on Windows, use this code instead:
# img = self.canvas.bitmap.ConvertToImage()
# bmp = img.ConvertToBitmap()
# dc.DrawBitmap(bmp, 0, 0)
self._rect = None
backend_tools.ToolSaveFigure = SaveFigureWx
backend_tools.ToolSetCursor = SetCursorWx
backend_tools.ToolRubberband = RubberbandWx
# < Additions for printing support: Matt Newville
class PrintoutWx(wx.Printout):
"""
Simple wrapper around wx Printout class -- all the real work
here is scaling the matplotlib canvas bitmap to the current
printer's definition.
"""
def __init__(self, canvas, width=5.5, margin=0.5, title='matplotlib'):
wx.Printout.__init__(self, title=title)
self.canvas = canvas
# width, in inches of output figure (approximate)
self.width = width
self.margin = margin
def HasPage(self, page):
# current only supports 1 page print
return page == 1
def GetPageInfo(self):
return (1, 1, 1, 1)
def OnPrintPage(self, page):
self.canvas.draw()
dc = self.GetDC()
(ppw, pph) = self.GetPPIPrinter() # printer's pixels per in
(pgw, pgh) = self.GetPageSizePixels() # page size in pixels
(dcw, dch) = dc.GetSize()
if wxc.is_phoenix:
(grw, grh) = self.canvas.GetSize()
else:
(grw, grh) = self.canvas.GetSizeTuple()
# save current figure dpi resolution and bg color,
# so that we can temporarily set them to the dpi of
# the printer, and the bg color to white
bgcolor = self.canvas.figure.get_facecolor()
fig_dpi = self.canvas.figure.dpi
# draw the bitmap, scaled appropriately
vscale = float(ppw) / fig_dpi
# set figure resolution,bg color for printer
self.canvas.figure.dpi = ppw
self.canvas.figure.set_facecolor('#FFFFFF')
renderer = RendererWx(self.canvas.bitmap, self.canvas.figure.dpi)
self.canvas.figure.draw(renderer)
self.canvas.bitmap.SetWidth(
int(self.canvas.bitmap.GetWidth() * vscale))
self.canvas.bitmap.SetHeight(
int(self.canvas.bitmap.GetHeight() * vscale))
self.canvas.draw()
# page may need additional scaling on preview
page_scale = 1.0
if self.IsPreview():
page_scale = float(dcw) / pgw
# get margin in pixels = (margin in in) * (pixels/in)
top_margin = int(self.margin * pph * page_scale)
left_margin = int(self.margin * ppw * page_scale)
# set scale so that width of output is self.width inches
# (assuming grw is size of graph in inches....)
user_scale = (self.width * fig_dpi * page_scale) / float(grw)
dc.SetDeviceOrigin(left_margin, top_margin)
dc.SetUserScale(user_scale, user_scale)
# this cute little number avoid API inconsistencies in wx
try:
dc.DrawBitmap(self.canvas.bitmap, 0, 0)
except Exception:
try:
dc.DrawBitmap(self.canvas.bitmap, (0, 0))
except Exception:
pass
# restore original figure resolution
self.canvas.figure.set_facecolor(bgcolor)
self.canvas.figure.dpi = fig_dpi
self.canvas.draw()
return True
# >
@_Backend.export
class _BackendWx(_Backend):
FigureCanvas = FigureCanvasWx
FigureManager = FigureManagerWx
_frame_class = FigureFrameWx
@staticmethod
def trigger_manager_draw(manager):
manager.canvas.draw_idle()
@classmethod
def new_figure_manager(cls, num, *args, **kwargs):
# Create a wx.App instance if it has not been created sofar.
wxapp = wx.GetApp()
if wxapp is None:
wxapp = wx.App(False)
wxapp.SetExitOnFrameDelete(True)
# Retain a reference to the app object so that it does not get
# garbage collected.
_BackendWx._theWxApp = wxapp
return super(_BackendWx, cls).new_figure_manager(num, *args, **kwargs)
@classmethod
def new_figure_manager_given_figure(cls, num, figure):
frame = cls._frame_class(num, figure)
figmgr = frame.get_figure_manager()
if matplotlib.is_interactive():
figmgr.frame.Show()
figure.canvas.draw_idle()
return figmgr
@staticmethod
def mainloop():
if not wx.App.IsMainLoopRunning():
wxapp = wx.GetApp()
if wxapp is not None:
wxapp.MainLoop()
| 69,524 | 33.710434 | 131 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_gtk.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import logging
import os
import sys
import warnings
if six.PY3:
warnings.warn(
"The gtk* backends have not been tested with Python 3.x",
ImportWarning)
try:
import gobject
import gtk; gdk = gtk.gdk
import pango
except ImportError:
raise ImportError("Gtk* backend requires pygtk to be installed.")
pygtk_version_required = (2,4,0)
if gtk.pygtk_version < pygtk_version_required:
raise ImportError ("PyGTK %d.%d.%d is installed\n"
"PyGTK %d.%d.%d or later is required"
% (gtk.pygtk_version + pygtk_version_required))
del pygtk_version_required
_new_tooltip_api = (gtk.pygtk_version[1] >= 12)
import matplotlib
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, NavigationToolbar2,
TimerBase, cursors)
from matplotlib.backends.backend_gdk import RendererGDK, FigureCanvasGDK
from matplotlib.cbook import is_writable_file_like, warn_deprecated
from matplotlib.figure import Figure
from matplotlib.widgets import SubplotTool
from matplotlib import (
cbook, colors as mcolors, lines, markers, rcParams)
_log = logging.getLogger(__name__)
backend_version = "%d.%d.%d" % gtk.pygtk_version
# the true dots per inch on the screen; should be display dependent
# see http://groups.google.com/groups?q=screen+dpi+x11&hl=en&lr=&ie=UTF-8&oe=UTF-8&safe=off&selm=7077.26e81ad5%40swift.cs.tcd.ie&rnum=5 for some info about screen dpi
PIXELS_PER_INCH = 96
# Hide the benign warning that it can't stat a file that doesn't
warnings.filterwarnings('ignore', '.*Unable to retrieve the file info for.*', gtk.Warning)
cursord = {
cursors.MOVE : gdk.Cursor(gdk.FLEUR),
cursors.HAND : gdk.Cursor(gdk.HAND2),
cursors.POINTER : gdk.Cursor(gdk.LEFT_PTR),
cursors.SELECT_REGION : gdk.Cursor(gdk.TCROSS),
cursors.WAIT : gdk.Cursor(gdk.WATCH),
}
# ref gtk+/gtk/gtkwidget.h
def GTK_WIDGET_DRAWABLE(w):
flags = w.flags();
return flags & gtk.VISIBLE != 0 and flags & gtk.MAPPED != 0
class TimerGTK(TimerBase):
'''
Subclass of :class:`backend_bases.TimerBase` using GTK for timer events.
Attributes
----------
interval : int
The time between timer events in milliseconds. Default is 1000 ms.
single_shot : bool
Boolean flag indicating whether this timer should operate as single
shot (run once and then stop). Defaults to False.
callbacks : list
Stores list of (func, args) tuples that will be called upon timer
events. This list can be manipulated directly, or the functions
`add_callback` and `remove_callback` can be used.
'''
def _timer_start(self):
# Need to stop it, otherwise we potentially leak a timer id that will
# never be stopped.
self._timer_stop()
self._timer = gobject.timeout_add(self._interval, self._on_timer)
def _timer_stop(self):
if self._timer is not None:
gobject.source_remove(self._timer)
self._timer = None
def _timer_set_interval(self):
# Only stop and restart it if the timer has already been started
if self._timer is not None:
self._timer_stop()
self._timer_start()
def _on_timer(self):
TimerBase._on_timer(self)
# Gtk timeout_add() requires that the callback returns True if it
# is to be called again.
if len(self.callbacks) > 0 and not self._single:
return True
else:
self._timer = None
return False
class FigureCanvasGTK (gtk.DrawingArea, FigureCanvasBase):
keyvald = {65507 : 'control',
65505 : 'shift',
65513 : 'alt',
65508 : 'control',
65506 : 'shift',
65514 : 'alt',
65361 : 'left',
65362 : 'up',
65363 : 'right',
65364 : 'down',
65307 : 'escape',
65470 : 'f1',
65471 : 'f2',
65472 : 'f3',
65473 : 'f4',
65474 : 'f5',
65475 : 'f6',
65476 : 'f7',
65477 : 'f8',
65478 : 'f9',
65479 : 'f10',
65480 : 'f11',
65481 : 'f12',
65300 : 'scroll_lock',
65299 : 'break',
65288 : 'backspace',
65293 : 'enter',
65379 : 'insert',
65535 : 'delete',
65360 : 'home',
65367 : 'end',
65365 : 'pageup',
65366 : 'pagedown',
65438 : '0',
65436 : '1',
65433 : '2',
65435 : '3',
65430 : '4',
65437 : '5',
65432 : '6',
65429 : '7',
65431 : '8',
65434 : '9',
65451 : '+',
65453 : '-',
65450 : '*',
65455 : '/',
65439 : 'dec',
65421 : 'enter',
65511 : 'super',
65512 : 'super',
65406 : 'alt',
65289 : 'tab',
}
# Setting this as a static constant prevents
# this resulting expression from leaking
event_mask = (gdk.BUTTON_PRESS_MASK |
gdk.BUTTON_RELEASE_MASK |
gdk.EXPOSURE_MASK |
gdk.KEY_PRESS_MASK |
gdk.KEY_RELEASE_MASK |
gdk.ENTER_NOTIFY_MASK |
gdk.LEAVE_NOTIFY_MASK |
gdk.POINTER_MOTION_MASK |
gdk.POINTER_MOTION_HINT_MASK)
def __init__(self, figure):
if self.__class__ == matplotlib.backends.backend_gtk.FigureCanvasGTK:
warn_deprecated('2.0', message="The GTK backend is "
"deprecated. It is untested, known to be "
"broken and will be removed in Matplotlib 3.0. "
"Use the GTKAgg backend instead. "
"See Matplotlib usage FAQ for"
" more info on backends.",
alternative="GTKAgg")
FigureCanvasBase.__init__(self, figure)
gtk.DrawingArea.__init__(self)
self._idle_draw_id = 0
self._need_redraw = True
self._pixmap_width = -1
self._pixmap_height = -1
self._lastCursor = None
self.connect('scroll_event', self.scroll_event)
self.connect('button_press_event', self.button_press_event)
self.connect('button_release_event', self.button_release_event)
self.connect('configure_event', self.configure_event)
self.connect('expose_event', self.expose_event)
self.connect('key_press_event', self.key_press_event)
self.connect('key_release_event', self.key_release_event)
self.connect('motion_notify_event', self.motion_notify_event)
self.connect('leave_notify_event', self.leave_notify_event)
self.connect('enter_notify_event', self.enter_notify_event)
self.set_events(self.__class__.event_mask)
self.set_double_buffered(False)
self.set_flags(gtk.CAN_FOCUS)
self._renderer_init()
self.last_downclick = {}
def destroy(self):
#gtk.DrawingArea.destroy(self)
self.close_event()
if self._idle_draw_id != 0:
gobject.source_remove(self._idle_draw_id)
def scroll_event(self, widget, event):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.allocation.height - event.y
if event.direction==gdk.SCROLL_UP:
step = 1
else:
step = -1
FigureCanvasBase.scroll_event(self, x, y, step, guiEvent=event)
return False # finish event propagation?
def button_press_event(self, widget, event):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.allocation.height - event.y
dblclick = (event.type == gdk._2BUTTON_PRESS)
if not dblclick:
# GTK is the only backend that generates a DOWN-UP-DOWN-DBLCLICK-UP event
# sequence for a double click. All other backends have a DOWN-UP-DBLCLICK-UP
# sequence. In order to provide consistency to matplotlib users, we will
# eat the extra DOWN event in the case that we detect it is part of a double
# click.
# first, get the double click time in milliseconds.
current_time = event.get_time()
last_time = self.last_downclick.get(event.button,0)
dblclick_time = gtk.settings_get_for_screen(gdk.screen_get_default()).get_property('gtk-double-click-time')
delta_time = current_time-last_time
if delta_time < dblclick_time:
del self.last_downclick[event.button] # we do not want to eat more than one event.
return False # eat.
self.last_downclick[event.button] = current_time
FigureCanvasBase.button_press_event(self, x, y, event.button, dblclick=dblclick, guiEvent=event)
return False # finish event propagation?
def button_release_event(self, widget, event):
x = event.x
# flipy so y=0 is bottom of canvas
y = self.allocation.height - event.y
FigureCanvasBase.button_release_event(self, x, y, event.button, guiEvent=event)
return False # finish event propagation?
def key_press_event(self, widget, event):
key = self._get_key(event)
FigureCanvasBase.key_press_event(self, key, guiEvent=event)
return True # stop event propagation
def key_release_event(self, widget, event):
key = self._get_key(event)
FigureCanvasBase.key_release_event(self, key, guiEvent=event)
return True # stop event propagation
def motion_notify_event(self, widget, event):
if event.is_hint:
x, y, state = event.window.get_pointer()
else:
x, y, state = event.x, event.y, event.state
# flipy so y=0 is bottom of canvas
y = self.allocation.height - y
FigureCanvasBase.motion_notify_event(self, x, y, guiEvent=event)
return False # finish event propagation?
def leave_notify_event(self, widget, event):
FigureCanvasBase.leave_notify_event(self, event)
def enter_notify_event(self, widget, event):
x, y, state = event.window.get_pointer()
FigureCanvasBase.enter_notify_event(self, event, xy=(x, y))
def _get_key(self, event):
if event.keyval in self.keyvald:
key = self.keyvald[event.keyval]
elif event.keyval < 256:
key = chr(event.keyval)
else:
key = None
for key_mask, prefix in (
[gdk.MOD4_MASK, 'super'],
[gdk.MOD1_MASK, 'alt'],
[gdk.CONTROL_MASK, 'ctrl'], ):
if event.state & key_mask:
key = '{0}+{1}'.format(prefix, key)
return key
def configure_event(self, widget, event):
if widget.window is None:
return
w, h = event.width, event.height
if w < 3 or h < 3:
return # empty fig
# resize the figure (in inches)
dpi = self.figure.dpi
self.figure.set_size_inches(w/dpi, h/dpi, forward=False)
self._need_redraw = True
return False # finish event propagation?
def draw(self):
# Note: FigureCanvasBase.draw() is inconveniently named as it clashes
# with the deprecated gtk.Widget.draw()
self._need_redraw = True
if GTK_WIDGET_DRAWABLE(self):
self.queue_draw()
# do a synchronous draw (its less efficient than an async draw,
# but is required if/when animation is used)
self.window.process_updates (False)
def draw_idle(self):
if self._idle_draw_id != 0:
return
def idle_draw(*args):
try:
self.draw()
finally:
self._idle_draw_id = 0
return False
self._idle_draw_id = gobject.idle_add(idle_draw)
def _renderer_init(self):
"""Override by GTK backends to select a different renderer
Renderer should provide the methods:
set_pixmap ()
set_width_height ()
that are used by
_render_figure() / _pixmap_prepare()
"""
self._renderer = RendererGDK (self, self.figure.dpi)
def _pixmap_prepare(self, width, height):
"""
Make sure _._pixmap is at least width, height,
create new pixmap if necessary
"""
create_pixmap = False
if width > self._pixmap_width:
# increase the pixmap in 10%+ (rather than 1 pixel) steps
self._pixmap_width = max (int (self._pixmap_width * 1.1),
width)
create_pixmap = True
if height > self._pixmap_height:
self._pixmap_height = max (int (self._pixmap_height * 1.1),
height)
create_pixmap = True
if create_pixmap:
self._pixmap = gdk.Pixmap (self.window, self._pixmap_width,
self._pixmap_height)
self._renderer.set_pixmap (self._pixmap)
def _render_figure(self, pixmap, width, height):
"""used by GTK and GTKcairo. GTKAgg overrides
"""
self._renderer.set_width_height (width, height)
self.figure.draw (self._renderer)
def expose_event(self, widget, event):
"""Expose_event for all GTK backends. Should not be overridden.
"""
toolbar = self.toolbar
# if toolbar:
# toolbar.set_cursor(cursors.WAIT)
if GTK_WIDGET_DRAWABLE(self):
if self._need_redraw:
x, y, w, h = self.allocation
self._pixmap_prepare (w, h)
self._render_figure(self._pixmap, w, h)
self._need_redraw = False
x, y, w, h = event.area
self.window.draw_drawable (self.style.fg_gc[self.state],
self._pixmap, x, y, x, y, w, h)
# if toolbar:
# toolbar.set_cursor(toolbar._lastCursor)
return False # finish event propagation?
filetypes = FigureCanvasBase.filetypes.copy()
filetypes['jpg'] = 'JPEG'
filetypes['jpeg'] = 'JPEG'
filetypes['png'] = 'Portable Network Graphics'
def print_jpeg(self, filename, *args, **kwargs):
return self._print_image(filename, 'jpeg')
print_jpg = print_jpeg
def print_png(self, filename, *args, **kwargs):
return self._print_image(filename, 'png')
def _print_image(self, filename, format, *args, **kwargs):
if self.flags() & gtk.REALIZED == 0:
# for self.window(for pixmap) and has a side effect of altering
# figure width,height (via configure-event?)
gtk.DrawingArea.realize(self)
width, height = self.get_width_height()
pixmap = gdk.Pixmap (self.window, width, height)
self._renderer.set_pixmap (pixmap)
self._render_figure(pixmap, width, height)
# jpg colors don't match the display very well, png colors match
# better
pixbuf = gdk.Pixbuf(gdk.COLORSPACE_RGB, 0, 8, width, height)
pixbuf.get_from_drawable(pixmap, pixmap.get_colormap(),
0, 0, 0, 0, width, height)
# set the default quality, if we are writing a JPEG.
# http://www.pygtk.org/docs/pygtk/class-gdkpixbuf.html#method-gdkpixbuf--save
options = {k: kwargs[k] for k in ['quality'] if k in kwargs}
if format in ['jpg', 'jpeg']:
options.setdefault('quality', rcParams['savefig.jpeg_quality'])
options['quality'] = str(options['quality'])
if isinstance(filename, six.string_types):
try:
pixbuf.save(filename, format, options=options)
except gobject.GError as exc:
error_msg_gtk('Save figure failure:\n%s' % (exc,), parent=self)
elif is_writable_file_like(filename):
if hasattr(pixbuf, 'save_to_callback'):
def save_callback(buf, data=None):
data.write(buf)
try:
pixbuf.save_to_callback(save_callback, format, user_data=filename, options=options)
except gobject.GError as exc:
error_msg_gtk('Save figure failure:\n%s' % (exc,), parent=self)
else:
raise ValueError("Saving to a Python file-like object is only supported by PyGTK >= 2.8")
else:
raise ValueError("filename must be a path or a file-like object")
def new_timer(self, *args, **kwargs):
"""
Creates a new backend-specific subclass of :class:`backend_bases.Timer`.
This is useful for getting periodic events through the backend's native
event loop. Implemented only for backends with GUIs.
Other Parameters
----------------
interval : scalar
Timer interval in milliseconds
callbacks : list
Sequence of (func, args, kwargs) where ``func(*args, **kwargs)``
will be executed by the timer every *interval*.
"""
return TimerGTK(*args, **kwargs)
def flush_events(self):
gtk.gdk.threads_enter()
while gtk.events_pending():
gtk.main_iteration(True)
gtk.gdk.flush()
gtk.gdk.threads_leave()
class FigureManagerGTK(FigureManagerBase):
"""
Attributes
----------
canvas : `FigureCanvas`
The FigureCanvas instance
num : int or str
The Figure number
toolbar : gtk.Toolbar
The gtk.Toolbar (gtk only)
vbox : gtk.VBox
The gtk.VBox containing the canvas and toolbar (gtk only)
window : gtk.Window
The gtk.Window (gtk only)
"""
def __init__(self, canvas, num):
FigureManagerBase.__init__(self, canvas, num)
self.window = gtk.Window()
self.window.set_wmclass("matplotlib", "Matplotlib")
self.set_window_title("Figure %d" % num)
if window_icon:
try:
self.window.set_icon_from_file(window_icon)
except:
# some versions of gtk throw a glib.GError but not
# all, so I am not sure how to catch it. I am unhappy
# diong a blanket catch here, but an not sure what a
# better way is - JDH
_log.info('Could not load matplotlib '
'icon: %s', sys.exc_info()[1])
self.vbox = gtk.VBox()
self.window.add(self.vbox)
self.vbox.show()
self.canvas.show()
self.vbox.pack_start(self.canvas, True, True)
self.toolbar = self._get_toolbar(canvas)
# calculate size for window
w = int (self.canvas.figure.bbox.width)
h = int (self.canvas.figure.bbox.height)
if self.toolbar is not None:
self.toolbar.show()
self.vbox.pack_end(self.toolbar, False, False)
tb_w, tb_h = self.toolbar.size_request()
h += tb_h
self.window.set_default_size (w, h)
def destroy(*args):
Gcf.destroy(num)
self.window.connect("destroy", destroy)
self.window.connect("delete_event", destroy)
if matplotlib.is_interactive():
self.window.show()
self.canvas.draw_idle()
def notify_axes_change(fig):
'this will be called whenever the current axes is changed'
if self.toolbar is not None: self.toolbar.update()
self.canvas.figure.add_axobserver(notify_axes_change)
self.canvas.grab_focus()
def destroy(self, *args):
if hasattr(self, 'toolbar') and self.toolbar is not None:
self.toolbar.destroy()
if hasattr(self, 'vbox'):
self.vbox.destroy()
if hasattr(self, 'window'):
self.window.destroy()
if hasattr(self, 'canvas'):
self.canvas.destroy()
self.__dict__.clear() #Is this needed? Other backends don't have it.
if Gcf.get_num_fig_managers()==0 and \
not matplotlib.is_interactive() and \
gtk.main_level() >= 1:
gtk.main_quit()
def show(self):
# show the figure window
self.window.show()
# raise the window above others and release the "above lock"
self.window.set_keep_above(True)
self.window.set_keep_above(False)
def full_screen_toggle(self):
self._full_screen_flag = not self._full_screen_flag
if self._full_screen_flag:
self.window.fullscreen()
else:
self.window.unfullscreen()
_full_screen_flag = False
def _get_toolbar(self, canvas):
# must be inited after the window, drawingArea and figure
# attrs are set
if rcParams['toolbar'] == 'toolbar2':
toolbar = NavigationToolbar2GTK (canvas, self.window)
else:
toolbar = None
return toolbar
def get_window_title(self):
return self.window.get_title()
def set_window_title(self, title):
self.window.set_title(title)
def resize(self, width, height):
'set the canvas size in pixels'
#_, _, cw, ch = self.canvas.allocation
#_, _, ww, wh = self.window.allocation
#self.window.resize (width-cw+ww, height-ch+wh)
self.window.resize(width, height)
class NavigationToolbar2GTK(NavigationToolbar2, gtk.Toolbar):
def __init__(self, canvas, window):
self.win = window
gtk.Toolbar.__init__(self)
NavigationToolbar2.__init__(self, canvas)
def set_message(self, s):
self.message.set_label(s)
def set_cursor(self, cursor):
self.canvas.window.set_cursor(cursord[cursor])
gtk.main_iteration()
def release(self, event):
try: del self._pixmapBack
except AttributeError: pass
def draw_rubberband(self, event, x0, y0, x1, y1):
'adapted from http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/189744'
drawable = self.canvas.window
if drawable is None:
return
gc = drawable.new_gc()
height = self.canvas.figure.bbox.height
y1 = height - y1
y0 = height - y0
w = abs(x1 - x0)
h = abs(y1 - y0)
rect = [int(val)for val in (min(x0,x1), min(y0, y1), w, h)]
try:
lastrect, pixmapBack = self._pixmapBack
except AttributeError:
#snap image back
if event.inaxes is None:
return
ax = event.inaxes
l,b,w,h = [int(val) for val in ax.bbox.bounds]
b = int(height)-(b+h)
axrect = l,b,w,h
self._pixmapBack = axrect, gtk.gdk.Pixmap(drawable, w, h)
self._pixmapBack[1].draw_drawable(gc, drawable, l, b, 0, 0, w, h)
else:
drawable.draw_drawable(gc, pixmapBack, 0, 0, *lastrect)
drawable.draw_rectangle(gc, False, *rect)
def _init_toolbar(self):
self.set_style(gtk.TOOLBAR_ICONS)
self._init_toolbar2_4()
def _init_toolbar2_4(self):
basedir = os.path.join(rcParams['datapath'],'images')
if not _new_tooltip_api:
self.tooltips = gtk.Tooltips()
for text, tooltip_text, image_file, callback in self.toolitems:
if text is None:
self.insert( gtk.SeparatorToolItem(), -1 )
continue
fname = os.path.join(basedir, image_file + '.png')
image = gtk.Image()
image.set_from_file(fname)
tbutton = gtk.ToolButton(image, text)
self.insert(tbutton, -1)
tbutton.connect('clicked', getattr(self, callback))
if _new_tooltip_api:
tbutton.set_tooltip_text(tooltip_text)
else:
tbutton.set_tooltip(self.tooltips, tooltip_text, 'Private')
toolitem = gtk.SeparatorToolItem()
self.insert(toolitem, -1)
# set_draw() not making separator invisible,
# bug #143692 fixed Jun 06 2004, will be in GTK+ 2.6
toolitem.set_draw(False)
toolitem.set_expand(True)
toolitem = gtk.ToolItem()
self.insert(toolitem, -1)
self.message = gtk.Label()
toolitem.add(self.message)
self.show_all()
def get_filechooser(self):
fc = FileChooserDialog(
title='Save the figure',
parent=self.win,
path=os.path.expanduser(rcParams['savefig.directory']),
filetypes=self.canvas.get_supported_filetypes(),
default_filetype=self.canvas.get_default_filetype())
fc.set_current_name(self.canvas.get_default_filename())
return fc
def save_figure(self, *args):
chooser = self.get_filechooser()
fname, format = chooser.get_filename_from_user()
chooser.destroy()
if fname:
startpath = os.path.expanduser(rcParams['savefig.directory'])
# Save dir for next time, unless empty str (i.e., use cwd).
if startpath != "":
rcParams['savefig.directory'] = (
os.path.dirname(six.text_type(fname)))
try:
self.canvas.figure.savefig(fname, format=format)
except Exception as e:
error_msg_gtk(str(e), parent=self)
def configure_subplots(self, button):
toolfig = Figure(figsize=(6,3))
canvas = self._get_canvas(toolfig)
toolfig.subplots_adjust(top=0.9)
tool = SubplotTool(self.canvas.figure, toolfig)
w = int(toolfig.bbox.width)
h = int(toolfig.bbox.height)
window = gtk.Window()
if window_icon:
try:
window.set_icon_from_file(window_icon)
except:
# we presumably already logged a message on the
# failure of the main plot, don't keep reporting
pass
window.set_title("Subplot Configuration Tool")
window.set_default_size(w, h)
vbox = gtk.VBox()
window.add(vbox)
vbox.show()
canvas.show()
vbox.pack_start(canvas, True, True)
window.show()
def _get_canvas(self, fig):
return FigureCanvasGTK(fig)
class FileChooserDialog(gtk.FileChooserDialog):
"""GTK+ 2.4 file selector which presents the user with a menu
of supported image formats
"""
def __init__ (self,
title = 'Save file',
parent = None,
action = gtk.FILE_CHOOSER_ACTION_SAVE,
buttons = (gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_SAVE, gtk.RESPONSE_OK),
path = None,
filetypes = [],
default_filetype = None
):
super(FileChooserDialog, self).__init__(title, parent, action, buttons)
super(FileChooserDialog, self).set_do_overwrite_confirmation(True)
self.set_default_response(gtk.RESPONSE_OK)
if not path:
path = os.getcwd() + os.sep
# create an extra widget to list supported image formats
self.set_current_folder (path)
self.set_current_name ('image.' + default_filetype)
hbox = gtk.HBox(spacing=10)
hbox.pack_start(gtk.Label ("File Format:"), expand=False)
liststore = gtk.ListStore(gobject.TYPE_STRING)
cbox = gtk.ComboBox(liststore)
cell = gtk.CellRendererText()
cbox.pack_start(cell, True)
cbox.add_attribute(cell, 'text', 0)
hbox.pack_start(cbox)
self.filetypes = filetypes
self.sorted_filetypes = sorted(six.iteritems(filetypes))
default = 0
for i, (ext, name) in enumerate(self.sorted_filetypes):
cbox.append_text("%s (*.%s)" % (name, ext))
if ext == default_filetype:
default = i
cbox.set_active(default)
self.ext = default_filetype
def cb_cbox_changed (cbox, data=None):
"""File extension changed"""
head, filename = os.path.split(self.get_filename())
root, ext = os.path.splitext(filename)
ext = ext[1:]
new_ext = self.sorted_filetypes[cbox.get_active()][0]
self.ext = new_ext
if ext in self.filetypes:
filename = root + '.' + new_ext
elif ext == '':
filename = filename.rstrip('.') + '.' + new_ext
self.set_current_name(filename)
cbox.connect("changed", cb_cbox_changed)
hbox.show_all()
self.set_extra_widget(hbox)
def get_filename_from_user (self):
while True:
filename = None
if self.run() != int(gtk.RESPONSE_OK):
break
filename = self.get_filename()
break
return filename, self.ext
class DialogLineprops(object):
"""
A GUI dialog for controlling lineprops
"""
signals = (
'on_combobox_lineprops_changed',
'on_combobox_linestyle_changed',
'on_combobox_marker_changed',
'on_colorbutton_linestyle_color_set',
'on_colorbutton_markerface_color_set',
'on_dialog_lineprops_okbutton_clicked',
'on_dialog_lineprops_cancelbutton_clicked',
)
linestyles = [ls for ls in lines.Line2D.lineStyles if ls.strip()]
linestyled = {s: i for i, s in enumerate(linestyles)}
markers = [m for m in markers.MarkerStyle.markers
if isinstance(m, six.string_types)]
markerd = {s: i for i, s in enumerate(markers)}
def __init__(self, lines):
import gtk.glade
datadir = matplotlib.get_data_path()
gladefile = os.path.join(datadir, 'lineprops.glade')
if not os.path.exists(gladefile):
raise IOError(
'Could not find gladefile lineprops.glade in %s' % datadir)
self._inited = False
self._updateson = True # suppress updates when setting widgets manually
self.wtree = gtk.glade.XML(gladefile, 'dialog_lineprops')
self.wtree.signal_autoconnect(
{s: getattr(self, s) for s in self.signals})
self.dlg = self.wtree.get_widget('dialog_lineprops')
self.lines = lines
cbox = self.wtree.get_widget('combobox_lineprops')
cbox.set_active(0)
self.cbox_lineprops = cbox
cbox = self.wtree.get_widget('combobox_linestyles')
for ls in self.linestyles:
cbox.append_text(ls)
cbox.set_active(0)
self.cbox_linestyles = cbox
cbox = self.wtree.get_widget('combobox_markers')
for m in self.markers:
cbox.append_text(m)
cbox.set_active(0)
self.cbox_markers = cbox
self._lastcnt = 0
self._inited = True
def show(self):
'populate the combo box'
self._updateson = False
# flush the old
cbox = self.cbox_lineprops
for i in range(self._lastcnt-1,-1,-1):
cbox.remove_text(i)
# add the new
for line in self.lines:
cbox.append_text(line.get_label())
cbox.set_active(0)
self._updateson = True
self._lastcnt = len(self.lines)
self.dlg.show()
def get_active_line(self):
'get the active line'
ind = self.cbox_lineprops.get_active()
line = self.lines[ind]
return line
def get_active_linestyle(self):
'get the active lineinestyle'
ind = self.cbox_linestyles.get_active()
ls = self.linestyles[ind]
return ls
def get_active_marker(self):
'get the active lineinestyle'
ind = self.cbox_markers.get_active()
m = self.markers[ind]
return m
def _update(self):
'update the active line props from the widgets'
if not self._inited or not self._updateson: return
line = self.get_active_line()
ls = self.get_active_linestyle()
marker = self.get_active_marker()
line.set_linestyle(ls)
line.set_marker(marker)
button = self.wtree.get_widget('colorbutton_linestyle')
color = button.get_color()
r, g, b = [val/65535. for val in (color.red, color.green, color.blue)]
line.set_color((r,g,b))
button = self.wtree.get_widget('colorbutton_markerface')
color = button.get_color()
r, g, b = [val/65535. for val in (color.red, color.green, color.blue)]
line.set_markerfacecolor((r,g,b))
line.figure.canvas.draw()
def on_combobox_lineprops_changed(self, item):
'update the widgets from the active line'
if not self._inited: return
self._updateson = False
line = self.get_active_line()
ls = line.get_linestyle()
if ls is None: ls = 'None'
self.cbox_linestyles.set_active(self.linestyled[ls])
marker = line.get_marker()
if marker is None: marker = 'None'
self.cbox_markers.set_active(self.markerd[marker])
rgba = mcolors.to_rgba(line.get_color())
color = gtk.gdk.Color(*[int(val*65535) for val in rgba[:3]])
button = self.wtree.get_widget('colorbutton_linestyle')
button.set_color(color)
rgba = mcolors.to_rgba(line.get_markerfacecolor())
color = gtk.gdk.Color(*[int(val*65535) for val in rgba[:3]])
button = self.wtree.get_widget('colorbutton_markerface')
button.set_color(color)
self._updateson = True
def on_combobox_linestyle_changed(self, item):
self._update()
def on_combobox_marker_changed(self, item):
self._update()
def on_colorbutton_linestyle_color_set(self, button):
self._update()
def on_colorbutton_markerface_color_set(self, button):
'called colorbutton marker clicked'
self._update()
def on_dialog_lineprops_okbutton_clicked(self, button):
self._update()
self.dlg.hide()
def on_dialog_lineprops_cancelbutton_clicked(self, button):
self.dlg.hide()
# set icon used when windows are minimized
# Unfortunately, the SVG renderer (rsvg) leaks memory under earlier
# versions of pygtk, so we have to use a PNG file instead.
try:
if gtk.pygtk_version < (2, 8, 0) or sys.platform == 'win32':
icon_filename = 'matplotlib.png'
else:
icon_filename = 'matplotlib.svg'
window_icon = os.path.join(rcParams['datapath'], 'images', icon_filename)
except:
window_icon = None
_log.info('Could not load matplotlib icon: %s', sys.exc_info()[1])
def error_msg_gtk(msg, parent=None):
if parent is not None: # find the toplevel gtk.Window
parent = parent.get_toplevel()
if parent.flags() & gtk.TOPLEVEL == 0:
parent = None
if not isinstance(msg, six.string_types):
msg = ','.join(map(str, msg))
dialog = gtk.MessageDialog(
parent = parent,
type = gtk.MESSAGE_ERROR,
buttons = gtk.BUTTONS_OK,
message_format = msg)
dialog.run()
dialog.destroy()
@_Backend.export
class _BackendGTK(_Backend):
FigureCanvas = FigureCanvasGTK
FigureManager = FigureManagerGTK
@staticmethod
def trigger_manager_draw(manager):
manager.canvas.draw_idle()
@staticmethod
def mainloop():
if gtk.main_level() == 0:
gtk.main()
| 36,244 | 33.918112 | 166 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/__init__.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib
import inspect
import traceback
import warnings
import logging
_log = logging.getLogger(__name__)
backend = matplotlib.get_backend()
_backend_loading_tb = "".join(
line for line in traceback.format_stack()
# Filter out line noise from importlib line.
if not line.startswith(' File "<frozen importlib._bootstrap'))
def pylab_setup(name=None):
'''return new_figure_manager, draw_if_interactive and show for pyplot
This provides the backend-specific functions that are used by
pyplot to abstract away the difference between interactive backends.
Parameters
----------
name : str, optional
The name of the backend to use. If `None`, falls back to
``matplotlib.get_backend()`` (which return :rc:`backend`).
Returns
-------
backend_mod : module
The module which contains the backend of choice
new_figure_manager : function
Create a new figure manager (roughly maps to GUI window)
draw_if_interactive : function
Redraw the current figure if pyplot is interactive
show : function
Show (and possibly block) any unshown figures.
'''
# Import the requested backend into a generic module object
if name is None:
# validates, to match all_backends
name = matplotlib.get_backend()
if name.startswith('module://'):
backend_name = name[9:]
else:
backend_name = 'backend_' + name
backend_name = backend_name.lower() # until we banish mixed case
backend_name = 'matplotlib.backends.%s' % backend_name.lower()
# the last argument is specifies whether to use absolute or relative
# imports. 0 means only perform absolute imports.
backend_mod = __import__(backend_name, globals(), locals(),
[backend_name], 0)
# Things we pull in from all backends
new_figure_manager = backend_mod.new_figure_manager
# image backends like pdf, agg or svg do not need to do anything
# for "show" or "draw_if_interactive", so if they are not defined
# by the backend, just do nothing
def do_nothing_show(*args, **kwargs):
frame = inspect.currentframe()
fname = frame.f_back.f_code.co_filename
if fname in ('<stdin>', '<ipython console>'):
warnings.warn("""
Your currently selected backend, '%s' does not support show().
Please select a GUI backend in your matplotlibrc file ('%s')
or with matplotlib.use()""" %
(name, matplotlib.matplotlib_fname()))
def do_nothing(*args, **kwargs):
pass
backend_version = getattr(backend_mod, 'backend_version', 'unknown')
show = getattr(backend_mod, 'show', do_nothing_show)
draw_if_interactive = getattr(backend_mod, 'draw_if_interactive',
do_nothing)
_log.debug('backend %s version %s', name, backend_version)
# need to keep a global reference to the backend for compatibility
# reasons. See https://github.com/matplotlib/matplotlib/issues/6092
global backend
backend = name
return backend_mod, new_figure_manager, draw_if_interactive, show
| 3,286 | 32.886598 | 73 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/_gtk3_compat.py | """
GObject compatibility loader; supports ``gi`` and ``pgi``.
The binding selection rules are as follows:
- if ``gi`` has already been imported, use it; else
- if ``pgi`` has already been imported, use it; else
- if ``gi`` can be imported, use it; else
- if ``pgi`` can be imported, use it; else
- error out.
Thus, to force usage of PGI when both bindings are installed, import it first.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import importlib
import sys
if "gi" in sys.modules:
import gi
elif "pgi" in sys.modules:
import pgi as gi
else:
try:
import gi
except ImportError:
try:
import pgi as gi
except ImportError:
raise ImportError("The Gtk3 backend requires PyGObject or pgi")
gi.require_version("Gtk", "3.0")
globals().update(
{name:
importlib.import_module("{}.repository.{}".format(gi.__name__, name))
for name in ["GLib", "GObject", "Gtk", "Gdk"]})
| 1,029 | 23.52381 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_nbagg.py | """Interactive figures in the IPython notebook"""
# Note: There is a notebook in
# lib/matplotlib/backends/web_backend/nbagg_uat.ipynb to help verify
# that changes made maintain expected behaviour.
import six
from base64 import b64encode
import io
import json
import os
import uuid
from IPython.display import display, Javascript, HTML
try:
# Jupyter/IPython 4.x or later
from ipykernel.comm import Comm
except ImportError:
# Jupyter/IPython 3.x or earlier
from IPython.kernel.comm import Comm
from matplotlib import rcParams, is_interactive
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, NavigationToolbar2)
from matplotlib.backends.backend_webagg_core import (
FigureCanvasWebAggCore, FigureManagerWebAgg, NavigationToolbar2WebAgg,
TimerTornado)
def connection_info():
"""
Return a string showing the figure and connection status for
the backend. This is intended as a diagnostic tool, and not for general
use.
"""
result = []
for manager in Gcf.get_all_fig_managers():
fig = manager.canvas.figure
result.append('{0} - {0}'.format((fig.get_label() or
"Figure {0}".format(manager.num)),
manager.web_sockets))
if not is_interactive():
result.append('Figures pending show: {0}'.format(len(Gcf._activeQue)))
return '\n'.join(result)
# Note: Version 3.2 and 4.x icons
# http://fontawesome.io/3.2.1/icons/
# http://fontawesome.io/
# the `fa fa-xxx` part targets font-awesome 4, (IPython 3.x)
# the icon-xxx targets font awesome 3.21 (IPython 2.x)
_FONT_AWESOME_CLASSES = {
'home': 'fa fa-home icon-home',
'back': 'fa fa-arrow-left icon-arrow-left',
'forward': 'fa fa-arrow-right icon-arrow-right',
'zoom_to_rect': 'fa fa-square-o icon-check-empty',
'move': 'fa fa-arrows icon-move',
'download': 'fa fa-floppy-o icon-save',
None: None
}
class NavigationIPy(NavigationToolbar2WebAgg):
# Use the standard toolbar items + download button
toolitems = [(text, tooltip_text,
_FONT_AWESOME_CLASSES[image_file], name_of_method)
for text, tooltip_text, image_file, name_of_method
in (NavigationToolbar2.toolitems +
(('Download', 'Download plot', 'download', 'download'),))
if image_file in _FONT_AWESOME_CLASSES]
class FigureManagerNbAgg(FigureManagerWebAgg):
ToolbarCls = NavigationIPy
def __init__(self, canvas, num):
self._shown = False
FigureManagerWebAgg.__init__(self, canvas, num)
def display_js(self):
# XXX How to do this just once? It has to deal with multiple
# browser instances using the same kernel (require.js - but the
# file isn't static?).
display(Javascript(FigureManagerNbAgg.get_javascript()))
def show(self):
if not self._shown:
self.display_js()
self._create_comm()
else:
self.canvas.draw_idle()
self._shown = True
def reshow(self):
"""
A special method to re-show the figure in the notebook.
"""
self._shown = False
self.show()
@property
def connected(self):
return bool(self.web_sockets)
@classmethod
def get_javascript(cls, stream=None):
if stream is None:
output = io.StringIO()
else:
output = stream
super(FigureManagerNbAgg, cls).get_javascript(stream=output)
with io.open(os.path.join(
os.path.dirname(__file__),
"web_backend", 'js',
"nbagg_mpl.js"), encoding='utf8') as fd:
output.write(fd.read())
if stream is None:
return output.getvalue()
def _create_comm(self):
comm = CommSocket(self)
self.add_web_socket(comm)
return comm
def destroy(self):
self._send_event('close')
# need to copy comms as callbacks will modify this list
for comm in list(self.web_sockets):
comm.on_close()
self.clearup_closed()
def clearup_closed(self):
"""Clear up any closed Comms."""
self.web_sockets = set([socket for socket in self.web_sockets
if socket.is_open()])
if len(self.web_sockets) == 0:
self.canvas.close_event()
def remove_comm(self, comm_id):
self.web_sockets = set([socket for socket in self.web_sockets
if not socket.comm.comm_id == comm_id])
class FigureCanvasNbAgg(FigureCanvasWebAggCore):
def new_timer(self, *args, **kwargs):
return TimerTornado(*args, **kwargs)
class CommSocket(object):
"""
Manages the Comm connection between IPython and the browser (client).
Comms are 2 way, with the CommSocket being able to publish a message
via the send_json method, and handle a message with on_message. On the
JS side figure.send_message and figure.ws.onmessage do the sending and
receiving respectively.
"""
def __init__(self, manager):
self.supports_binary = None
self.manager = manager
self.uuid = str(uuid.uuid4())
# Publish an output area with a unique ID. The javascript can then
# hook into this area.
display(HTML("<div id=%r></div>" % self.uuid))
try:
self.comm = Comm('matplotlib', data={'id': self.uuid})
except AttributeError:
raise RuntimeError('Unable to create an IPython notebook Comm '
'instance. Are you in the IPython notebook?')
self.comm.on_msg(self.on_message)
manager = self.manager
self._ext_close = False
def _on_close(close_message):
self._ext_close = True
manager.remove_comm(close_message['content']['comm_id'])
manager.clearup_closed()
self.comm.on_close(_on_close)
def is_open(self):
return not (self._ext_close or self.comm._closed)
def on_close(self):
# When the socket is closed, deregister the websocket with
# the FigureManager.
if self.is_open():
try:
self.comm.close()
except KeyError:
# apparently already cleaned it up?
pass
def send_json(self, content):
self.comm.send({'data': json.dumps(content)})
def send_binary(self, blob):
# The comm is ascii, so we always send the image in base64
# encoded data URL form.
data = b64encode(blob)
if six.PY3:
data = data.decode('ascii')
data_uri = "data:image/png;base64,{0}".format(data)
self.comm.send({'data': data_uri})
def on_message(self, message):
# The 'supports_binary' message is relevant to the
# websocket itself. The other messages get passed along
# to matplotlib as-is.
# Every message has a "type" and a "figure_id".
message = json.loads(message['content']['data'])
if message['type'] == 'closing':
self.on_close()
self.manager.clearup_closed()
elif message['type'] == 'supports_binary':
self.supports_binary = message['value']
else:
self.manager.handle_json(message)
@_Backend.export
class _BackendNbAgg(_Backend):
FigureCanvas = FigureCanvasNbAgg
FigureManager = FigureManagerNbAgg
@staticmethod
def new_figure_manager_given_figure(num, figure):
canvas = FigureCanvasNbAgg(figure)
manager = FigureManagerNbAgg(canvas, num)
if is_interactive():
manager.show()
figure.canvas.draw_idle()
canvas.mpl_connect('close_event', lambda event: Gcf.destroy(num))
return manager
@staticmethod
def trigger_manager_draw(manager):
manager.show()
@staticmethod
def show(*args, **kwargs):
## TODO: something to do when keyword block==False ?
from matplotlib._pylab_helpers import Gcf
managers = Gcf.get_all_fig_managers()
if not managers:
return
interactive = is_interactive()
for manager in managers:
manager.show()
# plt.figure adds an event which puts the figure in focus
# in the activeQue. Disable this behaviour, as it results in
# figures being put as the active figure after they have been
# shown, even in non-interactive mode.
if hasattr(manager, '_cidgcf'):
manager.canvas.mpl_disconnect(manager._cidgcf)
if not interactive and manager in Gcf._activeQue:
Gcf._activeQue.remove(manager)
| 8,839 | 31.619926 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_qt5.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import functools
import os
import re
import signal
import sys
from six import unichr
import traceback
import matplotlib
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, NavigationToolbar2,
TimerBase, cursors, ToolContainerBase, StatusbarBase)
import matplotlib.backends.qt_editor.figureoptions as figureoptions
from matplotlib.backends.qt_editor.formsubplottool import UiSubplotTool
from matplotlib.figure import Figure
from matplotlib.backend_managers import ToolManager
from matplotlib import backend_tools
from .qt_compat import (
QtCore, QtGui, QtWidgets, _getSaveFileName, is_pyqt5, __version__, QT_API)
backend_version = __version__
# SPECIAL_KEYS are keys that do *not* return their unicode name
# instead they have manually specified names
SPECIAL_KEYS = {QtCore.Qt.Key_Control: 'control',
QtCore.Qt.Key_Shift: 'shift',
QtCore.Qt.Key_Alt: 'alt',
QtCore.Qt.Key_Meta: 'super',
QtCore.Qt.Key_Return: 'enter',
QtCore.Qt.Key_Left: 'left',
QtCore.Qt.Key_Up: 'up',
QtCore.Qt.Key_Right: 'right',
QtCore.Qt.Key_Down: 'down',
QtCore.Qt.Key_Escape: 'escape',
QtCore.Qt.Key_F1: 'f1',
QtCore.Qt.Key_F2: 'f2',
QtCore.Qt.Key_F3: 'f3',
QtCore.Qt.Key_F4: 'f4',
QtCore.Qt.Key_F5: 'f5',
QtCore.Qt.Key_F6: 'f6',
QtCore.Qt.Key_F7: 'f7',
QtCore.Qt.Key_F8: 'f8',
QtCore.Qt.Key_F9: 'f9',
QtCore.Qt.Key_F10: 'f10',
QtCore.Qt.Key_F11: 'f11',
QtCore.Qt.Key_F12: 'f12',
QtCore.Qt.Key_Home: 'home',
QtCore.Qt.Key_End: 'end',
QtCore.Qt.Key_PageUp: 'pageup',
QtCore.Qt.Key_PageDown: 'pagedown',
QtCore.Qt.Key_Tab: 'tab',
QtCore.Qt.Key_Backspace: 'backspace',
QtCore.Qt.Key_Enter: 'enter',
QtCore.Qt.Key_Insert: 'insert',
QtCore.Qt.Key_Delete: 'delete',
QtCore.Qt.Key_Pause: 'pause',
QtCore.Qt.Key_SysReq: 'sysreq',
QtCore.Qt.Key_Clear: 'clear', }
# define which modifier keys are collected on keyboard events.
# elements are (mpl names, Modifier Flag, Qt Key) tuples
SUPER = 0
ALT = 1
CTRL = 2
SHIFT = 3
MODIFIER_KEYS = [('super', QtCore.Qt.MetaModifier, QtCore.Qt.Key_Meta),
('alt', QtCore.Qt.AltModifier, QtCore.Qt.Key_Alt),
('ctrl', QtCore.Qt.ControlModifier, QtCore.Qt.Key_Control),
('shift', QtCore.Qt.ShiftModifier, QtCore.Qt.Key_Shift),
]
if sys.platform == 'darwin':
# in OSX, the control and super (aka cmd/apple) keys are switched, so
# switch them back.
SPECIAL_KEYS.update({QtCore.Qt.Key_Control: 'cmd', # cmd/apple key
QtCore.Qt.Key_Meta: 'control',
})
MODIFIER_KEYS[0] = ('cmd', QtCore.Qt.ControlModifier,
QtCore.Qt.Key_Control)
MODIFIER_KEYS[2] = ('ctrl', QtCore.Qt.MetaModifier,
QtCore.Qt.Key_Meta)
cursord = {
cursors.MOVE: QtCore.Qt.SizeAllCursor,
cursors.HAND: QtCore.Qt.PointingHandCursor,
cursors.POINTER: QtCore.Qt.ArrowCursor,
cursors.SELECT_REGION: QtCore.Qt.CrossCursor,
cursors.WAIT: QtCore.Qt.WaitCursor,
}
# make place holder
qApp = None
def _create_qApp():
"""
Only one qApp can exist at a time, so check before creating one.
"""
global qApp
if qApp is None:
app = QtWidgets.QApplication.instance()
if app is None:
# check for DISPLAY env variable on X11 build of Qt
if is_pyqt5():
try:
from PyQt5 import QtX11Extras
is_x11_build = True
except ImportError:
is_x11_build = False
else:
is_x11_build = hasattr(QtGui, "QX11Info")
if is_x11_build:
display = os.environ.get('DISPLAY')
if display is None or not re.search(r':\d', display):
raise RuntimeError('Invalid DISPLAY variable')
qApp = QtWidgets.QApplication([b"matplotlib"])
qApp.lastWindowClosed.connect(qApp.quit)
else:
qApp = app
if is_pyqt5():
try:
qApp.setAttribute(QtCore.Qt.AA_UseHighDpiPixmaps)
qApp.setAttribute(QtCore.Qt.AA_EnableHighDpiScaling)
except AttributeError:
pass
def _allow_super_init(__init__):
"""
Decorator for ``__init__`` to allow ``super().__init__`` on PyQt4/PySide2.
"""
if QT_API == "PyQt5":
return __init__
else:
# To work around lack of cooperative inheritance in PyQt4, PySide,
# and PySide2, when calling FigureCanvasQT.__init__, we temporarily
# patch QWidget.__init__ by a cooperative version, that first calls
# QWidget.__init__ with no additional arguments, and then finds the
# next class in the MRO with an __init__ that does support cooperative
# inheritance (i.e., not defined by the PyQt4, PySide, PySide2, sip
# or Shiboken packages), and manually call its `__init__`, once again
# passing the additional arguments.
qwidget_init = QtWidgets.QWidget.__init__
def cooperative_qwidget_init(self, *args, **kwargs):
qwidget_init(self)
mro = type(self).__mro__
next_coop_init = next(
cls for cls in mro[mro.index(QtWidgets.QWidget) + 1:]
if cls.__module__.split(".")[0] not in [
"PyQt4", "sip", "PySide", "PySide2", "Shiboken"])
next_coop_init.__init__(self, *args, **kwargs)
@functools.wraps(__init__)
def wrapper(self, **kwargs):
try:
QtWidgets.QWidget.__init__ = cooperative_qwidget_init
__init__(self, **kwargs)
finally:
# Restore __init__
QtWidgets.QWidget.__init__ = qwidget_init
return wrapper
class TimerQT(TimerBase):
'''
Subclass of :class:`backend_bases.TimerBase` that uses Qt timer events.
Attributes
----------
interval : int
The time between timer events in milliseconds. Default is 1000 ms.
single_shot : bool
Boolean flag indicating whether this timer should
operate as single shot (run once and then stop). Defaults to False.
callbacks : list
Stores list of (func, args) tuples that will be called upon timer
events. This list can be manipulated directly, or the functions
`add_callback` and `remove_callback` can be used.
'''
def __init__(self, *args, **kwargs):
TimerBase.__init__(self, *args, **kwargs)
# Create a new timer and connect the timeout() signal to the
# _on_timer method.
self._timer = QtCore.QTimer()
self._timer.timeout.connect(self._on_timer)
self._timer_set_interval()
def _timer_set_single_shot(self):
self._timer.setSingleShot(self._single)
def _timer_set_interval(self):
self._timer.setInterval(self._interval)
def _timer_start(self):
self._timer.start()
def _timer_stop(self):
self._timer.stop()
class FigureCanvasQT(QtWidgets.QWidget, FigureCanvasBase):
# map Qt button codes to MouseEvent's ones:
buttond = {QtCore.Qt.LeftButton: 1,
QtCore.Qt.MidButton: 2,
QtCore.Qt.RightButton: 3,
# QtCore.Qt.XButton1: None,
# QtCore.Qt.XButton2: None,
}
@_allow_super_init
def __init__(self, figure):
_create_qApp()
super(FigureCanvasQT, self).__init__(figure=figure)
self.figure = figure
# We don't want to scale up the figure DPI more than once.
# Note, we don't handle a signal for changing DPI yet.
figure._original_dpi = figure.dpi
self._update_figure_dpi()
# In cases with mixed resolution displays, we need to be careful if the
# dpi_ratio changes - in this case we need to resize the canvas
# accordingly. We could watch for screenChanged events from Qt, but
# the issue is that we can't guarantee this will be emitted *before*
# the first paintEvent for the canvas, so instead we keep track of the
# dpi_ratio value here and in paintEvent we resize the canvas if
# needed.
self._dpi_ratio_prev = None
self._draw_pending = False
self._is_drawing = False
self._draw_rect_callback = lambda painter: None
self.setAttribute(QtCore.Qt.WA_OpaquePaintEvent)
self.setMouseTracking(True)
self.resize(*self.get_width_height())
# Key auto-repeat enabled by default
self._keyautorepeat = True
palette = QtGui.QPalette(QtCore.Qt.white)
self.setPalette(palette)
def _update_figure_dpi(self):
dpi = self._dpi_ratio * self.figure._original_dpi
self.figure._set_dpi(dpi, forward=False)
@property
def _dpi_ratio(self):
# Not available on Qt4 or some older Qt5.
try:
# self.devicePixelRatio() returns 0 in rare cases
return self.devicePixelRatio() or 1
except AttributeError:
return 1
def _update_dpi(self):
# As described in __init__ above, we need to be careful in cases with
# mixed resolution displays if dpi_ratio is changing between painting
# events.
# Return whether we triggered a resizeEvent (and thus a paintEvent)
# from within this function.
if self._dpi_ratio != self._dpi_ratio_prev:
# We need to update the figure DPI.
self._update_figure_dpi()
self._dpi_ratio_prev = self._dpi_ratio
# The easiest way to resize the canvas is to emit a resizeEvent
# since we implement all the logic for resizing the canvas for
# that event.
event = QtGui.QResizeEvent(self.size(), self.size())
self.resizeEvent(event)
# resizeEvent triggers a paintEvent itself, so we exit this one
# (after making sure that the event is immediately handled).
return True
return False
def get_width_height(self):
w, h = FigureCanvasBase.get_width_height(self)
return int(w / self._dpi_ratio), int(h / self._dpi_ratio)
def enterEvent(self, event):
FigureCanvasBase.enter_notify_event(self, guiEvent=event)
def leaveEvent(self, event):
QtWidgets.QApplication.restoreOverrideCursor()
FigureCanvasBase.leave_notify_event(self, guiEvent=event)
def mouseEventCoords(self, pos):
"""Calculate mouse coordinates in physical pixels
Qt5 use logical pixels, but the figure is scaled to physical
pixels for rendering. Transform to physical pixels so that
all of the down-stream transforms work as expected.
Also, the origin is different and needs to be corrected.
"""
dpi_ratio = self._dpi_ratio
x = pos.x()
# flip y so y=0 is bottom of canvas
y = self.figure.bbox.height / dpi_ratio - pos.y()
return x * dpi_ratio, y * dpi_ratio
def mousePressEvent(self, event):
x, y = self.mouseEventCoords(event.pos())
button = self.buttond.get(event.button())
if button is not None:
FigureCanvasBase.button_press_event(self, x, y, button,
guiEvent=event)
def mouseDoubleClickEvent(self, event):
x, y = self.mouseEventCoords(event.pos())
button = self.buttond.get(event.button())
if button is not None:
FigureCanvasBase.button_press_event(self, x, y,
button, dblclick=True,
guiEvent=event)
def mouseMoveEvent(self, event):
x, y = self.mouseEventCoords(event)
FigureCanvasBase.motion_notify_event(self, x, y, guiEvent=event)
def mouseReleaseEvent(self, event):
x, y = self.mouseEventCoords(event)
button = self.buttond.get(event.button())
if button is not None:
FigureCanvasBase.button_release_event(self, x, y, button,
guiEvent=event)
if is_pyqt5():
def wheelEvent(self, event):
x, y = self.mouseEventCoords(event)
# from QWheelEvent::delta doc
if event.pixelDelta().x() == 0 and event.pixelDelta().y() == 0:
steps = event.angleDelta().y() / 120
else:
steps = event.pixelDelta().y()
if steps:
FigureCanvasBase.scroll_event(
self, x, y, steps, guiEvent=event)
else:
def wheelEvent(self, event):
x = event.x()
# flipy so y=0 is bottom of canvas
y = self.figure.bbox.height - event.y()
# from QWheelEvent::delta doc
steps = event.delta() / 120
if event.orientation() == QtCore.Qt.Vertical:
FigureCanvasBase.scroll_event(
self, x, y, steps, guiEvent=event)
def keyPressEvent(self, event):
key = self._get_key(event)
if key is not None:
FigureCanvasBase.key_press_event(self, key, guiEvent=event)
def keyReleaseEvent(self, event):
key = self._get_key(event)
if key is not None:
FigureCanvasBase.key_release_event(self, key, guiEvent=event)
@property
def keyAutoRepeat(self):
"""
If True, enable auto-repeat for key events.
"""
return self._keyautorepeat
@keyAutoRepeat.setter
def keyAutoRepeat(self, val):
self._keyautorepeat = bool(val)
def resizeEvent(self, event):
# _dpi_ratio_prev will be set the first time the canvas is painted, and
# the rendered buffer is useless before anyways.
if self._dpi_ratio_prev is None:
return
w = event.size().width() * self._dpi_ratio
h = event.size().height() * self._dpi_ratio
dpival = self.figure.dpi
winch = w / dpival
hinch = h / dpival
self.figure.set_size_inches(winch, hinch, forward=False)
# pass back into Qt to let it finish
QtWidgets.QWidget.resizeEvent(self, event)
# emit our resize events
FigureCanvasBase.resize_event(self)
def sizeHint(self):
w, h = self.get_width_height()
return QtCore.QSize(w, h)
def minumumSizeHint(self):
return QtCore.QSize(10, 10)
def _get_key(self, event):
if not self._keyautorepeat and event.isAutoRepeat():
return None
event_key = event.key()
event_mods = int(event.modifiers()) # actually a bitmask
# get names of the pressed modifier keys
# bit twiddling to pick out modifier keys from event_mods bitmask,
# if event_key is a MODIFIER, it should not be duplicated in mods
mods = [name for name, mod_key, qt_key in MODIFIER_KEYS
if event_key != qt_key and (event_mods & mod_key) == mod_key]
try:
# for certain keys (enter, left, backspace, etc) use a word for the
# key, rather than unicode
key = SPECIAL_KEYS[event_key]
except KeyError:
# unicode defines code points up to 0x0010ffff
# QT will use Key_Codes larger than that for keyboard keys that are
# are not unicode characters (like multimedia keys)
# skip these
# if you really want them, you should add them to SPECIAL_KEYS
MAX_UNICODE = 0x10ffff
if event_key > MAX_UNICODE:
return None
key = unichr(event_key)
# qt delivers capitalized letters. fix capitalization
# note that capslock is ignored
if 'shift' in mods:
mods.remove('shift')
else:
key = key.lower()
mods.reverse()
return '+'.join(mods + [key])
def new_timer(self, *args, **kwargs):
"""
Creates a new backend-specific subclass of
:class:`backend_bases.Timer`. This is useful for getting
periodic events through the backend's native event
loop. Implemented only for backends with GUIs.
Other Parameters
----------------
interval : scalar
Timer interval in milliseconds
callbacks : list
Sequence of (func, args, kwargs) where ``func(*args, **kwargs)``
will be executed by the timer every *interval*.
"""
return TimerQT(*args, **kwargs)
def flush_events(self):
qApp.processEvents()
def start_event_loop(self, timeout=0):
if hasattr(self, "_event_loop") and self._event_loop.isRunning():
raise RuntimeError("Event loop already running")
self._event_loop = event_loop = QtCore.QEventLoop()
if timeout:
timer = QtCore.QTimer.singleShot(timeout * 1000, event_loop.quit)
event_loop.exec_()
def stop_event_loop(self, event=None):
if hasattr(self, "_event_loop"):
self._event_loop.quit()
def draw(self):
"""Render the figure, and queue a request for a Qt draw.
"""
# The renderer draw is done here; delaying causes problems with code
# that uses the result of the draw() to update plot elements.
if self._is_drawing:
return
self._is_drawing = True
try:
super(FigureCanvasQT, self).draw()
finally:
self._is_drawing = False
self.update()
def draw_idle(self):
"""Queue redraw of the Agg buffer and request Qt paintEvent.
"""
# The Agg draw needs to be handled by the same thread matplotlib
# modifies the scene graph from. Post Agg draw request to the
# current event loop in order to ensure thread affinity and to
# accumulate multiple draw requests from event handling.
# TODO: queued signal connection might be safer than singleShot
if not (self._draw_pending or self._is_drawing):
self._draw_pending = True
QtCore.QTimer.singleShot(0, self._draw_idle)
def _draw_idle(self):
if self.height() < 0 or self.width() < 0:
self._draw_pending = False
if not self._draw_pending:
return
try:
self.draw()
except Exception:
# Uncaught exceptions are fatal for PyQt5, so catch them instead.
traceback.print_exc()
finally:
self._draw_pending = False
def drawRectangle(self, rect):
# Draw the zoom rectangle to the QPainter. _draw_rect_callback needs
# to be called at the end of paintEvent.
if rect is not None:
def _draw_rect_callback(painter):
pen = QtGui.QPen(QtCore.Qt.black, 1 / self._dpi_ratio,
QtCore.Qt.DotLine)
painter.setPen(pen)
painter.drawRect(*(pt / self._dpi_ratio for pt in rect))
else:
def _draw_rect_callback(painter):
return
self._draw_rect_callback = _draw_rect_callback
self.update()
class MainWindow(QtWidgets.QMainWindow):
closing = QtCore.Signal()
def closeEvent(self, event):
self.closing.emit()
QtWidgets.QMainWindow.closeEvent(self, event)
class FigureManagerQT(FigureManagerBase):
"""
Attributes
----------
canvas : `FigureCanvas`
The FigureCanvas instance
num : int or str
The Figure number
toolbar : qt.QToolBar
The qt.QToolBar
window : qt.QMainWindow
The qt.QMainWindow
"""
def __init__(self, canvas, num):
FigureManagerBase.__init__(self, canvas, num)
self.canvas = canvas
self.window = MainWindow()
self.window.closing.connect(canvas.close_event)
self.window.closing.connect(self._widgetclosed)
self.window.setWindowTitle("Figure %d" % num)
image = os.path.join(matplotlib.rcParams['datapath'],
'images', 'matplotlib.svg')
self.window.setWindowIcon(QtGui.QIcon(image))
# Give the keyboard focus to the figure instead of the
# manager; StrongFocus accepts both tab and click to focus and
# will enable the canvas to process event w/o clicking.
# ClickFocus only takes the focus is the window has been
# clicked
# on. http://qt-project.org/doc/qt-4.8/qt.html#FocusPolicy-enum or
# http://doc.qt.digia.com/qt/qt.html#FocusPolicy-enum
self.canvas.setFocusPolicy(QtCore.Qt.StrongFocus)
self.canvas.setFocus()
self.window._destroying = False
self.toolmanager = self._get_toolmanager()
self.toolbar = self._get_toolbar(self.canvas, self.window)
self.statusbar = None
if self.toolmanager:
backend_tools.add_tools_to_manager(self.toolmanager)
if self.toolbar:
backend_tools.add_tools_to_container(self.toolbar)
self.statusbar = StatusbarQt(self.window, self.toolmanager)
if self.toolbar is not None:
self.window.addToolBar(self.toolbar)
if not self.toolmanager:
# add text label to status bar
statusbar_label = QtWidgets.QLabel()
self.window.statusBar().addWidget(statusbar_label)
self.toolbar.message.connect(statusbar_label.setText)
tbs_height = self.toolbar.sizeHint().height()
else:
tbs_height = 0
# resize the main window so it will display the canvas with the
# requested size:
cs = canvas.sizeHint()
sbs = self.window.statusBar().sizeHint()
self._status_and_tool_height = tbs_height + sbs.height()
height = cs.height() + self._status_and_tool_height
self.window.resize(cs.width(), height)
self.window.setCentralWidget(self.canvas)
if matplotlib.is_interactive():
self.window.show()
self.canvas.draw_idle()
def notify_axes_change(fig):
# This will be called whenever the current axes is changed
if self.toolbar is not None:
self.toolbar.update()
self.canvas.figure.add_axobserver(notify_axes_change)
self.window.raise_()
def full_screen_toggle(self):
if self.window.isFullScreen():
self.window.showNormal()
else:
self.window.showFullScreen()
def _widgetclosed(self):
if self.window._destroying:
return
self.window._destroying = True
try:
Gcf.destroy(self.num)
except AttributeError:
pass
# It seems that when the python session is killed,
# Gcf can get destroyed before the Gcf.destroy
# line is run, leading to a useless AttributeError.
def _get_toolbar(self, canvas, parent):
# must be inited after the window, drawingArea and figure
# attrs are set
if matplotlib.rcParams['toolbar'] == 'toolbar2':
toolbar = NavigationToolbar2QT(canvas, parent, False)
elif matplotlib.rcParams['toolbar'] == 'toolmanager':
toolbar = ToolbarQt(self.toolmanager, self.window)
else:
toolbar = None
return toolbar
def _get_toolmanager(self):
if matplotlib.rcParams['toolbar'] == 'toolmanager':
toolmanager = ToolManager(self.canvas.figure)
else:
toolmanager = None
return toolmanager
def resize(self, width, height):
'set the canvas size in pixels'
self.window.resize(width, height + self._status_and_tool_height)
def show(self):
self.window.show()
self.window.activateWindow()
self.window.raise_()
def destroy(self, *args):
# check for qApp first, as PySide deletes it in its atexit handler
if QtWidgets.QApplication.instance() is None:
return
if self.window._destroying:
return
self.window._destroying = True
self.window.destroyed.connect(self._widgetclosed)
if self.toolbar:
self.toolbar.destroy()
self.window.close()
def get_window_title(self):
return six.text_type(self.window.windowTitle())
def set_window_title(self, title):
self.window.setWindowTitle(title)
class NavigationToolbar2QT(NavigationToolbar2, QtWidgets.QToolBar):
message = QtCore.Signal(str)
def __init__(self, canvas, parent, coordinates=True):
""" coordinates: should we show the coordinates on the right? """
self.canvas = canvas
self.parent = parent
self.coordinates = coordinates
self._actions = {}
"""A mapping of toolitem method names to their QActions"""
QtWidgets.QToolBar.__init__(self, parent)
NavigationToolbar2.__init__(self, canvas)
def _icon(self, name):
if is_pyqt5():
name = name.replace('.png', '_large.png')
pm = QtGui.QPixmap(os.path.join(self.basedir, name))
if hasattr(pm, 'setDevicePixelRatio'):
pm.setDevicePixelRatio(self.canvas._dpi_ratio)
return QtGui.QIcon(pm)
def _init_toolbar(self):
self.basedir = os.path.join(matplotlib.rcParams['datapath'], 'images')
for text, tooltip_text, image_file, callback in self.toolitems:
if text is None:
self.addSeparator()
else:
a = self.addAction(self._icon(image_file + '.png'),
text, getattr(self, callback))
self._actions[callback] = a
if callback in ['zoom', 'pan']:
a.setCheckable(True)
if tooltip_text is not None:
a.setToolTip(tooltip_text)
if text == 'Subplots':
a = self.addAction(self._icon("qt4_editor_options.png"),
'Customize', self.edit_parameters)
a.setToolTip('Edit axis, curve and image parameters')
self.buttons = {}
# Add the x,y location widget at the right side of the toolbar
# The stretch factor is 1 which means any resizing of the toolbar
# will resize this label instead of the buttons.
if self.coordinates:
self.locLabel = QtWidgets.QLabel("", self)
self.locLabel.setAlignment(
QtCore.Qt.AlignRight | QtCore.Qt.AlignTop)
self.locLabel.setSizePolicy(
QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding,
QtWidgets.QSizePolicy.Ignored))
labelAction = self.addWidget(self.locLabel)
labelAction.setVisible(True)
# reference holder for subplots_adjust window
self.adj_window = None
# Esthetic adjustments - we need to set these explicitly in PyQt5
# otherwise the layout looks different - but we don't want to set it if
# not using HiDPI icons otherwise they look worse than before.
if is_pyqt5():
self.setIconSize(QtCore.QSize(24, 24))
self.layout().setSpacing(12)
if is_pyqt5():
# For some reason, self.setMinimumHeight doesn't seem to carry over to
# the actual sizeHint, so override it instead in order to make the
# aesthetic adjustments noted above.
def sizeHint(self):
size = super(NavigationToolbar2QT, self).sizeHint()
size.setHeight(max(48, size.height()))
return size
def edit_parameters(self):
allaxes = self.canvas.figure.get_axes()
if not allaxes:
QtWidgets.QMessageBox.warning(
self.parent, "Error", "There are no axes to edit.")
return
elif len(allaxes) == 1:
axes, = allaxes
else:
titles = []
for axes in allaxes:
name = (axes.get_title() or
" - ".join(filter(None, [axes.get_xlabel(),
axes.get_ylabel()])) or
"<anonymous {} (id: {:#x})>".format(
type(axes).__name__, id(axes)))
titles.append(name)
item, ok = QtWidgets.QInputDialog.getItem(
self.parent, 'Customize', 'Select axes:', titles, 0, False)
if ok:
axes = allaxes[titles.index(six.text_type(item))]
else:
return
figureoptions.figure_edit(axes, self)
def _update_buttons_checked(self):
# sync button checkstates to match active mode
self._actions['pan'].setChecked(self._active == 'PAN')
self._actions['zoom'].setChecked(self._active == 'ZOOM')
def pan(self, *args):
super(NavigationToolbar2QT, self).pan(*args)
self._update_buttons_checked()
def zoom(self, *args):
super(NavigationToolbar2QT, self).zoom(*args)
self._update_buttons_checked()
def set_message(self, s):
self.message.emit(s)
if self.coordinates:
self.locLabel.setText(s)
def set_cursor(self, cursor):
self.canvas.setCursor(cursord[cursor])
def draw_rubberband(self, event, x0, y0, x1, y1):
height = self.canvas.figure.bbox.height
y1 = height - y1
y0 = height - y0
rect = [int(val) for val in (x0, y0, x1 - x0, y1 - y0)]
self.canvas.drawRectangle(rect)
def remove_rubberband(self):
self.canvas.drawRectangle(None)
def configure_subplots(self):
image = os.path.join(matplotlib.rcParams['datapath'],
'images', 'matplotlib.png')
dia = SubplotToolQt(self.canvas.figure, self.parent)
dia.setWindowIcon(QtGui.QIcon(image))
dia.exec_()
def save_figure(self, *args):
filetypes = self.canvas.get_supported_filetypes_grouped()
sorted_filetypes = sorted(six.iteritems(filetypes))
default_filetype = self.canvas.get_default_filetype()
startpath = os.path.expanduser(
matplotlib.rcParams['savefig.directory'])
start = os.path.join(startpath, self.canvas.get_default_filename())
filters = []
selectedFilter = None
for name, exts in sorted_filetypes:
exts_list = " ".join(['*.%s' % ext for ext in exts])
filter = '%s (%s)' % (name, exts_list)
if default_filetype in exts:
selectedFilter = filter
filters.append(filter)
filters = ';;'.join(filters)
fname, filter = _getSaveFileName(self.parent,
"Choose a filename to save to",
start, filters, selectedFilter)
if fname:
# Save dir for next time, unless empty str (i.e., use cwd).
if startpath != "":
matplotlib.rcParams['savefig.directory'] = (
os.path.dirname(six.text_type(fname)))
try:
self.canvas.figure.savefig(six.text_type(fname))
except Exception as e:
QtWidgets.QMessageBox.critical(
self, "Error saving file", six.text_type(e),
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.NoButton)
class SubplotToolQt(UiSubplotTool):
def __init__(self, targetfig, parent):
UiSubplotTool.__init__(self, None)
self._figure = targetfig
for lower, higher in [("bottom", "top"), ("left", "right")]:
self._widgets[lower].valueChanged.connect(
lambda val: self._widgets[higher].setMinimum(val + .001))
self._widgets[higher].valueChanged.connect(
lambda val: self._widgets[lower].setMaximum(val - .001))
self._attrs = ["top", "bottom", "left", "right", "hspace", "wspace"]
self._defaults = {attr: vars(self._figure.subplotpars)[attr]
for attr in self._attrs}
# Set values after setting the range callbacks, but before setting up
# the redraw callbacks.
self._reset()
for attr in self._attrs:
self._widgets[attr].valueChanged.connect(self._on_value_changed)
for action, method in [("Export values", self._export_values),
("Tight layout", self._tight_layout),
("Reset", self._reset),
("Close", self.close)]:
self._widgets[action].clicked.connect(method)
def _export_values(self):
# Explicitly round to 3 decimals (which is also the spinbox precision)
# to avoid numbers of the form 0.100...001.
dialog = QtWidgets.QDialog()
layout = QtWidgets.QVBoxLayout()
dialog.setLayout(layout)
text = QtWidgets.QPlainTextEdit()
text.setReadOnly(True)
layout.addWidget(text)
text.setPlainText(
",\n".join("{}={:.3}".format(attr, self._widgets[attr].value())
for attr in self._attrs))
# Adjust the height of the text widget to fit the whole text, plus
# some padding.
size = text.maximumSize()
size.setHeight(
QtGui.QFontMetrics(text.document().defaultFont())
.size(0, text.toPlainText()).height() + 20)
text.setMaximumSize(size)
dialog.exec_()
def _on_value_changed(self):
self._figure.subplots_adjust(**{attr: self._widgets[attr].value()
for attr in self._attrs})
self._figure.canvas.draw_idle()
def _tight_layout(self):
self._figure.tight_layout()
for attr in self._attrs:
widget = self._widgets[attr]
widget.blockSignals(True)
widget.setValue(vars(self._figure.subplotpars)[attr])
widget.blockSignals(False)
self._figure.canvas.draw_idle()
def _reset(self):
for attr, value in self._defaults.items():
self._widgets[attr].setValue(value)
class ToolbarQt(ToolContainerBase, QtWidgets.QToolBar):
def __init__(self, toolmanager, parent):
ToolContainerBase.__init__(self, toolmanager)
QtWidgets.QToolBar.__init__(self, parent)
self._toolitems = {}
self._groups = {}
self._last = None
@property
def _icon_extension(self):
if is_pyqt5():
return '_large.png'
return '.png'
def add_toolitem(
self, name, group, position, image_file, description, toggle):
button = QtWidgets.QToolButton(self)
button.setIcon(self._icon(image_file))
button.setText(name)
if description:
button.setToolTip(description)
def handler():
self.trigger_tool(name)
if toggle:
button.setCheckable(True)
button.toggled.connect(handler)
else:
button.clicked.connect(handler)
self._last = button
self._toolitems.setdefault(name, [])
self._add_to_group(group, name, button, position)
self._toolitems[name].append((button, handler))
def _add_to_group(self, group, name, button, position):
gr = self._groups.get(group, [])
if not gr:
sep = self.addSeparator()
gr.append(sep)
before = gr[position]
widget = self.insertWidget(before, button)
gr.insert(position, widget)
self._groups[group] = gr
def _icon(self, name):
pm = QtGui.QPixmap(name)
if hasattr(pm, 'setDevicePixelRatio'):
pm.setDevicePixelRatio(self.toolmanager.canvas._dpi_ratio)
return QtGui.QIcon(pm)
def toggle_toolitem(self, name, toggled):
if name not in self._toolitems:
return
for button, handler in self._toolitems[name]:
button.toggled.disconnect(handler)
button.setChecked(toggled)
button.toggled.connect(handler)
def remove_toolitem(self, name):
for button, handler in self._toolitems[name]:
button.setParent(None)
del self._toolitems[name]
class StatusbarQt(StatusbarBase, QtWidgets.QLabel):
def __init__(self, window, *args, **kwargs):
StatusbarBase.__init__(self, *args, **kwargs)
QtWidgets.QLabel.__init__(self)
window.statusBar().addWidget(self)
def set_message(self, s):
self.setText(s)
class ConfigureSubplotsQt(backend_tools.ConfigureSubplotsBase):
def trigger(self, *args):
image = os.path.join(matplotlib.rcParams['datapath'],
'images', 'matplotlib.png')
parent = self.canvas.manager.window
dia = SubplotToolQt(self.figure, parent)
dia.setWindowIcon(QtGui.QIcon(image))
dia.exec_()
class SaveFigureQt(backend_tools.SaveFigureBase):
def trigger(self, *args):
filetypes = self.canvas.get_supported_filetypes_grouped()
sorted_filetypes = sorted(six.iteritems(filetypes))
default_filetype = self.canvas.get_default_filetype()
startpath = os.path.expanduser(
matplotlib.rcParams['savefig.directory'])
start = os.path.join(startpath, self.canvas.get_default_filename())
filters = []
selectedFilter = None
for name, exts in sorted_filetypes:
exts_list = " ".join(['*.%s' % ext for ext in exts])
filter = '%s (%s)' % (name, exts_list)
if default_filetype in exts:
selectedFilter = filter
filters.append(filter)
filters = ';;'.join(filters)
parent = self.canvas.manager.window
fname, filter = _getSaveFileName(parent,
"Choose a filename to save to",
start, filters, selectedFilter)
if fname:
# Save dir for next time, unless empty str (i.e., use cwd).
if startpath != "":
matplotlib.rcParams['savefig.directory'] = (
os.path.dirname(six.text_type(fname)))
try:
self.canvas.figure.savefig(six.text_type(fname))
except Exception as e:
QtWidgets.QMessageBox.critical(
self, "Error saving file", six.text_type(e),
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.NoButton)
class SetCursorQt(backend_tools.SetCursorBase):
def set_cursor(self, cursor):
self.canvas.setCursor(cursord[cursor])
class RubberbandQt(backend_tools.RubberbandBase):
def draw_rubberband(self, x0, y0, x1, y1):
height = self.canvas.figure.bbox.height
y1 = height - y1
y0 = height - y0
rect = [int(val) for val in (x0, y0, x1 - x0, y1 - y0)]
self.canvas.drawRectangle(rect)
def remove_rubberband(self):
self.canvas.drawRectangle(None)
backend_tools.ToolSaveFigure = SaveFigureQt
backend_tools.ToolConfigureSubplots = ConfigureSubplotsQt
backend_tools.ToolSetCursor = SetCursorQt
backend_tools.ToolRubberband = RubberbandQt
def error_msg_qt(msg, parent=None):
if not isinstance(msg, six.string_types):
msg = ','.join(map(str, msg))
QtWidgets.QMessageBox.warning(None, "Matplotlib",
msg, QtGui.QMessageBox.Ok)
def exception_handler(type, value, tb):
"""Handle uncaught exceptions
It does not catch SystemExit
"""
msg = ''
# get the filename attribute if available (for IOError)
if hasattr(value, 'filename') and value.filename is not None:
msg = value.filename + ': '
if hasattr(value, 'strerror') and value.strerror is not None:
msg += value.strerror
else:
msg += six.text_type(value)
if len(msg):
error_msg_qt(msg)
@_Backend.export
class _BackendQT5(_Backend):
FigureCanvas = FigureCanvasQT
FigureManager = FigureManagerQT
@staticmethod
def trigger_manager_draw(manager):
manager.canvas.draw_idle()
@staticmethod
def mainloop():
# allow KeyboardInterrupt exceptions to close the plot window.
signal.signal(signal.SIGINT, signal.SIG_DFL)
qApp.exec_()
| 41,139 | 35.732143 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_wxcairo.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import wx
from .backend_cairo import cairo, FigureCanvasCairo, RendererCairo
from .backend_wx import (
_BackendWx, _FigureCanvasWxBase, FigureFrameWx,
NavigationToolbar2Wx as NavigationToolbar2WxCairo)
import wx.lib.wxcairo as wxcairo
class FigureFrameWxCairo(FigureFrameWx):
def get_canvas(self, fig):
return FigureCanvasWxCairo(self, -1, fig)
class FigureCanvasWxCairo(_FigureCanvasWxBase, FigureCanvasCairo):
"""
The FigureCanvas contains the figure and does event handling.
In the wxPython backend, it is derived from wxPanel, and (usually) lives
inside a frame instantiated by a FigureManagerWx. The parent window
probably implements a wxSizer to control the displayed control size - but
we give a hint as to our preferred minimum size.
"""
def __init__(self, parent, id, figure):
# _FigureCanvasWxBase should be fixed to have the same signature as
# every other FigureCanvas and use cooperative inheritance, but in the
# meantime the following will make do.
_FigureCanvasWxBase.__init__(self, parent, id, figure)
FigureCanvasCairo.__init__(self, figure)
self._renderer = RendererCairo(self.figure.dpi)
def draw(self, drawDC=None):
width = int(self.figure.bbox.width)
height = int(self.figure.bbox.height)
surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, width, height)
self._renderer.set_ctx_from_surface(surface)
self._renderer.set_width_height(width, height)
self.figure.draw(self._renderer)
self.bitmap = wxcairo.BitmapFromImageSurface(surface)
self._isDrawn = True
self.gui_repaint(drawDC=drawDC, origin='WXCairo')
@_BackendWx.export
class _BackendWxCairo(_BackendWx):
FigureCanvas = FigureCanvasWxCairo
_frame_class = FigureFrameWxCairo
| 1,965 | 35.407407 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_webagg.py | """
Displays Agg images in the browser, with interactivity
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
# The WebAgg backend is divided into two modules:
#
# - `backend_webagg_core.py` contains code necessary to embed a WebAgg
# plot inside of a web application, and communicate in an abstract
# way over a web socket.
#
# - `backend_webagg.py` contains a concrete implementation of a basic
# application, implemented with tornado.
import six
from contextlib import contextmanager
import errno
import json
import os
import random
import sys
import signal
import socket
import threading
try:
import tornado
except ImportError:
raise RuntimeError("The WebAgg backend requires Tornado.")
import tornado.web
import tornado.ioloop
import tornado.websocket
from matplotlib import rcParams
from matplotlib.backend_bases import _Backend
from matplotlib._pylab_helpers import Gcf
from . import backend_webagg_core as core
from .backend_webagg_core import TimerTornado
class ServerThread(threading.Thread):
def run(self):
tornado.ioloop.IOLoop.instance().start()
webagg_server_thread = ServerThread()
class FigureCanvasWebAgg(core.FigureCanvasWebAggCore):
def show(self):
# show the figure window
show()
def new_timer(self, *args, **kwargs):
return TimerTornado(*args, **kwargs)
class WebAggApplication(tornado.web.Application):
initialized = False
started = False
class FavIcon(tornado.web.RequestHandler):
def get(self):
image_path = os.path.join(
os.path.dirname(os.path.dirname(__file__)),
'mpl-data', 'images')
self.set_header('Content-Type', 'image/png')
with open(os.path.join(image_path,
'matplotlib.png'), 'rb') as fd:
self.write(fd.read())
class SingleFigurePage(tornado.web.RequestHandler):
def __init__(self, application, request, **kwargs):
self.url_prefix = kwargs.pop('url_prefix', '')
tornado.web.RequestHandler.__init__(self, application,
request, **kwargs)
def get(self, fignum):
fignum = int(fignum)
manager = Gcf.get_fig_manager(fignum)
ws_uri = 'ws://{req.host}{prefix}/'.format(req=self.request,
prefix=self.url_prefix)
self.render(
"single_figure.html",
prefix=self.url_prefix,
ws_uri=ws_uri,
fig_id=fignum,
toolitems=core.NavigationToolbar2WebAgg.toolitems,
canvas=manager.canvas)
class AllFiguresPage(tornado.web.RequestHandler):
def __init__(self, application, request, **kwargs):
self.url_prefix = kwargs.pop('url_prefix', '')
tornado.web.RequestHandler.__init__(self, application,
request, **kwargs)
def get(self):
ws_uri = 'ws://{req.host}{prefix}/'.format(req=self.request,
prefix=self.url_prefix)
self.render(
"all_figures.html",
prefix=self.url_prefix,
ws_uri=ws_uri,
figures=sorted(Gcf.figs.items()),
toolitems=core.NavigationToolbar2WebAgg.toolitems)
class MplJs(tornado.web.RequestHandler):
def get(self):
self.set_header('Content-Type', 'application/javascript')
js_content = core.FigureManagerWebAgg.get_javascript()
self.write(js_content)
class Download(tornado.web.RequestHandler):
def get(self, fignum, fmt):
fignum = int(fignum)
manager = Gcf.get_fig_manager(fignum)
# TODO: Move this to a central location
mimetypes = {
'ps': 'application/postscript',
'eps': 'application/postscript',
'pdf': 'application/pdf',
'svg': 'image/svg+xml',
'png': 'image/png',
'jpeg': 'image/jpeg',
'tif': 'image/tiff',
'emf': 'application/emf'
}
self.set_header('Content-Type', mimetypes.get(fmt, 'binary'))
buff = six.BytesIO()
manager.canvas.figure.savefig(buff, format=fmt)
self.write(buff.getvalue())
class WebSocket(tornado.websocket.WebSocketHandler):
supports_binary = True
def open(self, fignum):
self.fignum = int(fignum)
self.manager = Gcf.get_fig_manager(self.fignum)
self.manager.add_web_socket(self)
if hasattr(self, 'set_nodelay'):
self.set_nodelay(True)
def on_close(self):
self.manager.remove_web_socket(self)
def on_message(self, message):
message = json.loads(message)
# The 'supports_binary' message is on a client-by-client
# basis. The others affect the (shared) canvas as a
# whole.
if message['type'] == 'supports_binary':
self.supports_binary = message['value']
else:
manager = Gcf.get_fig_manager(self.fignum)
# It is possible for a figure to be closed,
# but a stale figure UI is still sending messages
# from the browser.
if manager is not None:
manager.handle_json(message)
def send_json(self, content):
self.write_message(json.dumps(content))
def send_binary(self, blob):
if self.supports_binary:
self.write_message(blob, binary=True)
else:
data_uri = "data:image/png;base64,{0}".format(
blob.encode('base64').replace('\n', ''))
self.write_message(data_uri)
def __init__(self, url_prefix=''):
if url_prefix:
assert url_prefix[0] == '/' and url_prefix[-1] != '/', \
'url_prefix must start with a "/" and not end with one.'
super(WebAggApplication, self).__init__(
[
# Static files for the CSS and JS
(url_prefix + r'/_static/(.*)',
tornado.web.StaticFileHandler,
{'path': core.FigureManagerWebAgg.get_static_file_path()}),
# An MPL favicon
(url_prefix + r'/favicon.ico', self.FavIcon),
# The page that contains all of the pieces
(url_prefix + r'/([0-9]+)', self.SingleFigurePage,
{'url_prefix': url_prefix}),
# The page that contains all of the figures
(url_prefix + r'/?', self.AllFiguresPage,
{'url_prefix': url_prefix}),
(url_prefix + r'/js/mpl.js', self.MplJs),
# Sends images and events to the browser, and receives
# events from the browser
(url_prefix + r'/([0-9]+)/ws', self.WebSocket),
# Handles the downloading (i.e., saving) of static images
(url_prefix + r'/([0-9]+)/download.([a-z0-9.]+)',
self.Download),
],
template_path=core.FigureManagerWebAgg.get_static_file_path())
@classmethod
def initialize(cls, url_prefix='', port=None, address=None):
if cls.initialized:
return
# Create the class instance
app = cls(url_prefix=url_prefix)
cls.url_prefix = url_prefix
# This port selection algorithm is borrowed, more or less
# verbatim, from IPython.
def random_ports(port, n):
"""
Generate a list of n random ports near the given port.
The first 5 ports will be sequential, and the remaining n-5 will be
randomly selected in the range [port-2*n, port+2*n].
"""
for i in range(min(5, n)):
yield port + i
for i in range(n - 5):
yield port + random.randint(-2 * n, 2 * n)
success = None
if address is None:
cls.address = rcParams['webagg.address']
else:
cls.address = address
cls.port = rcParams['webagg.port']
for port in random_ports(cls.port, rcParams['webagg.port_retries']):
try:
app.listen(port, cls.address)
except socket.error as e:
if e.errno != errno.EADDRINUSE:
raise
else:
cls.port = port
success = True
break
if not success:
raise SystemExit(
"The webagg server could not be started because an available "
"port could not be found")
cls.initialized = True
@classmethod
def start(cls):
if cls.started:
return
"""
IOLoop.running() was removed as of Tornado 2.4; see for example
https://groups.google.com/forum/#!topic/python-tornado/QLMzkpQBGOY
Thus there is no correct way to check if the loop has already been
launched. We may end up with two concurrently running loops in that
unlucky case with all the expected consequences.
"""
ioloop = tornado.ioloop.IOLoop.instance()
def shutdown():
ioloop.stop()
print("Server is stopped")
sys.stdout.flush()
cls.started = False
@contextmanager
def catch_sigint():
old_handler = signal.signal(
signal.SIGINT,
lambda sig, frame: ioloop.add_callback_from_signal(shutdown))
try:
yield
finally:
signal.signal(signal.SIGINT, old_handler)
# Set the flag to True *before* blocking on ioloop.start()
cls.started = True
print("Press Ctrl+C to stop WebAgg server")
sys.stdout.flush()
with catch_sigint():
ioloop.start()
def ipython_inline_display(figure):
import tornado.template
WebAggApplication.initialize()
if not webagg_server_thread.is_alive():
webagg_server_thread.start()
with open(os.path.join(
core.FigureManagerWebAgg.get_static_file_path(),
'ipython_inline_figure.html')) as fd:
tpl = fd.read()
fignum = figure.number
t = tornado.template.Template(tpl)
return t.generate(
prefix=WebAggApplication.url_prefix,
fig_id=fignum,
toolitems=core.NavigationToolbar2WebAgg.toolitems,
canvas=figure.canvas,
port=WebAggApplication.port).decode('utf-8')
@_Backend.export
class _BackendWebAgg(_Backend):
FigureCanvas = FigureCanvasWebAgg
FigureManager = core.FigureManagerWebAgg
@staticmethod
def trigger_manager_draw(manager):
manager.canvas.draw_idle()
@staticmethod
def show():
WebAggApplication.initialize()
url = "http://127.0.0.1:{port}{prefix}".format(
port=WebAggApplication.port,
prefix=WebAggApplication.url_prefix)
if rcParams['webagg.open_in_browser']:
import webbrowser
webbrowser.open(url)
else:
print("To view figure, visit {0}".format(url))
WebAggApplication.start()
| 11,565 | 31.951567 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_tkagg.py | from __future__ import absolute_import, division, print_function
from .. import cbook
from . import tkagg # Paint image to Tk photo blitter extension.
from .backend_agg import FigureCanvasAgg
from ._backend_tk import (
_BackendTk, FigureCanvasTk, FigureManagerTk, NavigationToolbar2Tk)
class FigureCanvasTkAgg(FigureCanvasAgg, FigureCanvasTk):
def draw(self):
super(FigureCanvasTkAgg, self).draw()
tkagg.blit(self._tkphoto, self.renderer._renderer, colormode=2)
self._master.update_idletasks()
def blit(self, bbox=None):
tkagg.blit(
self._tkphoto, self.renderer._renderer, bbox=bbox, colormode=2)
self._master.update_idletasks()
@cbook.deprecated("2.2")
class FigureManagerTkAgg(FigureManagerTk):
pass
@cbook.deprecated("2.2")
class NavigationToolbar2TkAgg(NavigationToolbar2Tk):
pass
@_BackendTk.export
class _BackendTkAgg(_BackendTk):
FigureCanvas = FigureCanvasTkAgg
| 957 | 26.371429 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_wxagg.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import wx
import matplotlib
from matplotlib import cbook
from . import wx_compat as wxc
from .backend_agg import FigureCanvasAgg
from .backend_wx import (
_BackendWx, _FigureCanvasWxBase, FigureFrameWx,
NavigationToolbar2Wx as NavigationToolbar2WxAgg)
class FigureFrameWxAgg(FigureFrameWx):
def get_canvas(self, fig):
return FigureCanvasWxAgg(self, -1, fig)
class FigureCanvasWxAgg(FigureCanvasAgg, _FigureCanvasWxBase):
"""
The FigureCanvas contains the figure and does event handling.
In the wxPython backend, it is derived from wxPanel, and (usually)
lives inside a frame instantiated by a FigureManagerWx. The parent
window probably implements a wxSizer to control the displayed
control size - but we give a hint as to our preferred minimum
size.
"""
def draw(self, drawDC=None):
"""
Render the figure using agg.
"""
FigureCanvasAgg.draw(self)
self.bitmap = _convert_agg_to_wx_bitmap(self.get_renderer(), None)
self._isDrawn = True
self.gui_repaint(drawDC=drawDC, origin='WXAgg')
def blit(self, bbox=None):
"""
Transfer the region of the agg buffer defined by bbox to the display.
If bbox is None, the entire buffer is transferred.
"""
if bbox is None:
self.bitmap = _convert_agg_to_wx_bitmap(self.get_renderer(), None)
self.gui_repaint()
return
l, b, w, h = bbox.bounds
r = l + w
t = b + h
x = int(l)
y = int(self.bitmap.GetHeight() - t)
srcBmp = _convert_agg_to_wx_bitmap(self.get_renderer(), None)
srcDC = wx.MemoryDC()
srcDC.SelectObject(srcBmp)
destDC = wx.MemoryDC()
destDC.SelectObject(self.bitmap)
destDC.Blit(x, y, int(w), int(h), srcDC, x, y)
destDC.SelectObject(wx.NullBitmap)
srcDC.SelectObject(wx.NullBitmap)
self.gui_repaint()
filetypes = FigureCanvasAgg.filetypes
@cbook.deprecated("2.2", alternative="NavigationToolbar2WxAgg")
class Toolbar(NavigationToolbar2WxAgg):
pass
# agg/wxPython image conversion functions (wxPython >= 2.8)
def _convert_agg_to_wx_image(agg, bbox):
"""
Convert the region of the agg buffer bounded by bbox to a wx.Image. If
bbox is None, the entire buffer is converted.
Note: agg must be a backend_agg.RendererAgg instance.
"""
if bbox is None:
# agg => rgb -> image
image = wxc.EmptyImage(int(agg.width), int(agg.height))
image.SetData(agg.tostring_rgb())
return image
else:
# agg => rgba buffer -> bitmap => clipped bitmap => image
return wx.ImageFromBitmap(_WX28_clipped_agg_as_bitmap(agg, bbox))
def _convert_agg_to_wx_bitmap(agg, bbox):
"""
Convert the region of the agg buffer bounded by bbox to a wx.Bitmap. If
bbox is None, the entire buffer is converted.
Note: agg must be a backend_agg.RendererAgg instance.
"""
if bbox is None:
# agg => rgba buffer -> bitmap
return wxc.BitmapFromBuffer(int(agg.width), int(agg.height),
agg.buffer_rgba())
else:
# agg => rgba buffer -> bitmap => clipped bitmap
return _WX28_clipped_agg_as_bitmap(agg, bbox)
def _WX28_clipped_agg_as_bitmap(agg, bbox):
"""
Convert the region of a the agg buffer bounded by bbox to a wx.Bitmap.
Note: agg must be a backend_agg.RendererAgg instance.
"""
l, b, width, height = bbox.bounds
r = l + width
t = b + height
srcBmp = wxc.BitmapFromBuffer(int(agg.width), int(agg.height),
agg.buffer_rgba())
srcDC = wx.MemoryDC()
srcDC.SelectObject(srcBmp)
destBmp = wxc.EmptyBitmap(int(width), int(height))
destDC = wx.MemoryDC()
destDC.SelectObject(destBmp)
x = int(l)
y = int(int(agg.height) - t)
destDC.Blit(0, 0, int(width), int(height), srcDC, x, y)
srcDC.SelectObject(wx.NullBitmap)
destDC.SelectObject(wx.NullBitmap)
return destBmp
@_BackendWx.export
class _BackendWxAgg(_BackendWx):
FigureCanvas = FigureCanvasWxAgg
_frame_class = FigureFrameWxAgg
| 4,326 | 28.236486 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/backend_pgf.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import atexit
import codecs
import errno
import math
import os
import re
import shutil
import sys
import tempfile
import warnings
import weakref
import matplotlib as mpl
from matplotlib import _png, rcParams
from matplotlib.backend_bases import (
_Backend, FigureCanvasBase, FigureManagerBase, GraphicsContextBase,
RendererBase)
from matplotlib.backends.backend_mixed import MixedModeRenderer
from matplotlib.cbook import is_writable_file_like
from matplotlib.compat import subprocess
from matplotlib.compat.subprocess import check_output
from matplotlib.path import Path
###############################################################################
# create a list of system fonts, all of these should work with xe/lua-latex
system_fonts = []
if sys.platform.startswith('win'):
from matplotlib import font_manager
for f in font_manager.win32InstalledFonts():
try:
system_fonts.append(font_manager.get_font(str(f)).family_name)
except:
pass # unknown error, skip this font
else:
# assuming fontconfig is installed and the command 'fc-list' exists
try:
# list scalable (non-bitmap) fonts
fc_list = check_output([str('fc-list'), ':outline,scalable', 'family'])
fc_list = fc_list.decode('utf8')
system_fonts = [f.split(',')[0] for f in fc_list.splitlines()]
system_fonts = list(set(system_fonts))
except:
warnings.warn('error getting fonts from fc-list', UserWarning)
def get_texcommand():
"""Get chosen TeX system from rc."""
texsystem_options = ["xelatex", "lualatex", "pdflatex"]
texsystem = rcParams["pgf.texsystem"]
return texsystem if texsystem in texsystem_options else "xelatex"
def get_fontspec():
"""Build fontspec preamble from rc."""
latex_fontspec = []
texcommand = get_texcommand()
if texcommand != "pdflatex":
latex_fontspec.append("\\usepackage{fontspec}")
if texcommand != "pdflatex" and rcParams["pgf.rcfonts"]:
# try to find fonts from rc parameters
families = ["serif", "sans-serif", "monospace"]
fontspecs = [r"\setmainfont{%s}", r"\setsansfont{%s}",
r"\setmonofont{%s}"]
for family, fontspec in zip(families, fontspecs):
matches = [f for f in rcParams["font." + family]
if f in system_fonts]
if matches:
latex_fontspec.append(fontspec % matches[0])
else:
pass # no fonts found, fallback to LaTeX defaule
return "\n".join(latex_fontspec)
def get_preamble():
"""Get LaTeX preamble from rc."""
return "\n".join(rcParams["pgf.preamble"])
###############################################################################
# This almost made me cry!!!
# In the end, it's better to use only one unit for all coordinates, since the
# arithmetic in latex seems to produce inaccurate conversions.
latex_pt_to_in = 1. / 72.27
latex_in_to_pt = 1. / latex_pt_to_in
mpl_pt_to_in = 1. / 72.
mpl_in_to_pt = 1. / mpl_pt_to_in
###############################################################################
# helper functions
NO_ESCAPE = r"(?<!\\)(?:\\\\)*"
re_mathsep = re.compile(NO_ESCAPE + r"\$")
re_escapetext = re.compile(NO_ESCAPE + "([_^$%])")
repl_escapetext = lambda m: "\\" + m.group(1)
re_mathdefault = re.compile(NO_ESCAPE + r"(\\mathdefault)")
repl_mathdefault = lambda m: m.group(0)[:-len(m.group(1))]
def common_texification(text):
"""
Do some necessary and/or useful substitutions for texts to be included in
LaTeX documents.
"""
# Sometimes, matplotlib adds the unknown command \mathdefault.
# Not using \mathnormal instead since this looks odd for the latex cm font.
text = re_mathdefault.sub(repl_mathdefault, text)
# split text into normaltext and inline math parts
parts = re_mathsep.split(text)
for i, s in enumerate(parts):
if not i % 2:
# textmode replacements
s = re_escapetext.sub(repl_escapetext, s)
else:
# mathmode replacements
s = r"\(\displaystyle %s\)" % s
parts[i] = s
return "".join(parts)
def writeln(fh, line):
# every line of a file included with \\input must be terminated with %
# if not, latex will create additional vertical spaces for some reason
fh.write(line)
fh.write("%\n")
def _font_properties_str(prop):
# translate font properties to latex commands, return as string
commands = []
families = {"serif": r"\rmfamily", "sans": r"\sffamily",
"sans-serif": r"\sffamily", "monospace": r"\ttfamily"}
family = prop.get_family()[0]
if family in families:
commands.append(families[family])
elif family in system_fonts and get_texcommand() != "pdflatex":
commands.append(r"\setmainfont{%s}\rmfamily" % family)
else:
pass # print warning?
size = prop.get_size_in_points()
commands.append(r"\fontsize{%f}{%f}" % (size, size * 1.2))
styles = {"normal": r"", "italic": r"\itshape", "oblique": r"\slshape"}
commands.append(styles[prop.get_style()])
boldstyles = ["semibold", "demibold", "demi", "bold", "heavy",
"extra bold", "black"]
if prop.get_weight() in boldstyles:
commands.append(r"\bfseries")
commands.append(r"\selectfont")
return "".join(commands)
def make_pdf_to_png_converter():
"""
Returns a function that converts a pdf file to a png file.
"""
tools_available = []
# check for pdftocairo
try:
check_output([str("pdftocairo"), "-v"], stderr=subprocess.STDOUT)
tools_available.append("pdftocairo")
except:
pass
# check for ghostscript
gs, ver = mpl.checkdep_ghostscript()
if gs:
tools_available.append("gs")
# pick converter
if "pdftocairo" in tools_available:
def cairo_convert(pdffile, pngfile, dpi):
cmd = [str("pdftocairo"), "-singlefile", "-png", "-r", "%d" % dpi,
pdffile, os.path.splitext(pngfile)[0]]
check_output(cmd, stderr=subprocess.STDOUT)
return cairo_convert
elif "gs" in tools_available:
def gs_convert(pdffile, pngfile, dpi):
cmd = [str(gs),
'-dQUIET', '-dSAFER', '-dBATCH', '-dNOPAUSE', '-dNOPROMPT',
'-dUseCIEColor', '-dTextAlphaBits=4',
'-dGraphicsAlphaBits=4', '-dDOINTERPOLATE',
'-sDEVICE=png16m', '-sOutputFile=%s' % pngfile,
'-r%d' % dpi, pdffile]
check_output(cmd, stderr=subprocess.STDOUT)
return gs_convert
else:
raise RuntimeError("No suitable pdf to png renderer found.")
class LatexError(Exception):
def __init__(self, message, latex_output=""):
Exception.__init__(self, message)
self.latex_output = latex_output
class LatexManagerFactory(object):
previous_instance = None
@staticmethod
def get_latex_manager():
texcommand = get_texcommand()
latex_header = LatexManager._build_latex_header()
prev = LatexManagerFactory.previous_instance
# Check if the previous instance of LatexManager can be reused.
if (prev and prev.latex_header == latex_header
and prev.texcommand == texcommand):
if rcParams["pgf.debug"]:
print("reusing LatexManager")
return prev
else:
if rcParams["pgf.debug"]:
print("creating LatexManager")
new_inst = LatexManager()
LatexManagerFactory.previous_instance = new_inst
return new_inst
class LatexManager(object):
"""
The LatexManager opens an instance of the LaTeX application for
determining the metrics of text elements. The LaTeX environment can be
modified by setting fonts and/or a custem preamble in the rc parameters.
"""
_unclean_instances = weakref.WeakSet()
@staticmethod
def _build_latex_header():
latex_preamble = get_preamble()
latex_fontspec = get_fontspec()
# Create LaTeX header with some content, else LaTeX will load some math
# fonts later when we don't expect the additional output on stdout.
# TODO: is this sufficient?
latex_header = [r"\documentclass{minimal}",
latex_preamble,
latex_fontspec,
r"\begin{document}",
r"text $math \mu$", # force latex to load fonts now
r"\typeout{pgf_backend_query_start}"]
return "\n".join(latex_header)
@staticmethod
def _cleanup_remaining_instances():
unclean_instances = list(LatexManager._unclean_instances)
for latex_manager in unclean_instances:
latex_manager._cleanup()
def _stdin_writeln(self, s):
self.latex_stdin_utf8.write(s)
self.latex_stdin_utf8.write("\n")
self.latex_stdin_utf8.flush()
def _expect(self, s):
exp = s.encode("utf8")
buf = bytearray()
while True:
b = self.latex.stdout.read(1)
buf += b
if buf[-len(exp):] == exp:
break
if not len(b):
raise LatexError("LaTeX process halted", buf.decode("utf8"))
return buf.decode("utf8")
def _expect_prompt(self):
return self._expect("\n*")
def __init__(self):
# store references for __del__
self._os_path = os.path
self._shutil = shutil
self._debug = rcParams["pgf.debug"]
# create a tmp directory for running latex, remember to cleanup
self.tmpdir = tempfile.mkdtemp(prefix="mpl_pgf_lm_")
LatexManager._unclean_instances.add(self)
# test the LaTeX setup to ensure a clean startup of the subprocess
self.texcommand = get_texcommand()
self.latex_header = LatexManager._build_latex_header()
latex_end = "\n\\makeatletter\n\\@@end\n"
try:
latex = subprocess.Popen([str(self.texcommand), "-halt-on-error"],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
cwd=self.tmpdir)
except OSError as e:
if e.errno == errno.ENOENT:
raise RuntimeError(
"Latex command not found. Install %r or change "
"pgf.texsystem to the desired command." % self.texcommand)
else:
raise RuntimeError(
"Error starting process %r" % self.texcommand)
test_input = self.latex_header + latex_end
stdout, stderr = latex.communicate(test_input.encode("utf-8"))
if latex.returncode != 0:
raise LatexError("LaTeX returned an error, probably missing font "
"or error in preamble:\n%s" % stdout)
# open LaTeX process for real work
latex = subprocess.Popen([str(self.texcommand), "-halt-on-error"],
stdin=subprocess.PIPE, stdout=subprocess.PIPE,
cwd=self.tmpdir)
self.latex = latex
self.latex_stdin_utf8 = codecs.getwriter("utf8")(self.latex.stdin)
# write header with 'pgf_backend_query_start' token
self._stdin_writeln(self._build_latex_header())
# read all lines until our 'pgf_backend_query_start' token appears
self._expect("*pgf_backend_query_start")
self._expect_prompt()
# cache for strings already processed
self.str_cache = {}
def _cleanup(self):
if not self._os_path.isdir(self.tmpdir):
return
try:
self.latex.communicate()
self.latex_stdin_utf8.close()
self.latex.stdout.close()
except:
pass
try:
self._shutil.rmtree(self.tmpdir)
LatexManager._unclean_instances.discard(self)
except:
sys.stderr.write("error deleting tmp directory %s\n" % self.tmpdir)
def __del__(self):
if self._debug:
print("deleting LatexManager")
self._cleanup()
def get_width_height_descent(self, text, prop):
"""
Get the width, total height and descent for a text typesetted by the
current LaTeX environment.
"""
# apply font properties and define textbox
prop_cmds = _font_properties_str(prop)
textbox = "\\sbox0{%s %s}" % (prop_cmds, text)
# check cache
if textbox in self.str_cache:
return self.str_cache[textbox]
# send textbox to LaTeX and wait for prompt
self._stdin_writeln(textbox)
try:
self._expect_prompt()
except LatexError as e:
raise ValueError("Error processing '{}'\nLaTeX Output:\n{}"
.format(text, e.latex_output))
# typeout width, height and text offset of the last textbox
self._stdin_writeln(r"\typeout{\the\wd0,\the\ht0,\the\dp0}")
# read answer from latex and advance to the next prompt
try:
answer = self._expect_prompt()
except LatexError as e:
raise ValueError("Error processing '{}'\nLaTeX Output:\n{}"
.format(text, e.latex_output))
# parse metrics from the answer string
try:
width, height, offset = answer.splitlines()[0].split(",")
except:
raise ValueError("Error processing '{}'\nLaTeX Output:\n{}"
.format(text, answer))
w, h, o = float(width[:-2]), float(height[:-2]), float(offset[:-2])
# the height returned from LaTeX goes from base to top.
# the height matplotlib expects goes from bottom to top.
self.str_cache[textbox] = (w, h + o, o)
return w, h + o, o
class RendererPgf(RendererBase):
def __init__(self, figure, fh, dummy=False):
"""
Creates a new PGF renderer that translates any drawing instruction
into text commands to be interpreted in a latex pgfpicture environment.
Attributes
----------
figure : `matplotlib.figure.Figure`
Matplotlib figure to initialize height, width and dpi from.
fh : file-like
File handle for the output of the drawing commands.
"""
RendererBase.__init__(self)
self.dpi = figure.dpi
self.fh = fh
self.figure = figure
self.image_counter = 0
# get LatexManager instance
self.latexManager = LatexManagerFactory.get_latex_manager()
if dummy:
# dummy==True deactivate all methods
nop = lambda *args, **kwargs: None
for m in RendererPgf.__dict__:
if m.startswith("draw_"):
self.__dict__[m] = nop
else:
# if fh does not belong to a filename, deactivate draw_image
if not hasattr(fh, 'name') or not os.path.exists(fh.name):
warnings.warn("streamed pgf-code does not support raster "
"graphics, consider using the pgf-to-pdf option",
UserWarning)
self.__dict__["draw_image"] = lambda *args, **kwargs: None
def draw_markers(self, gc, marker_path, marker_trans, path, trans,
rgbFace=None):
writeln(self.fh, r"\begin{pgfscope}")
# convert from display units to in
f = 1. / self.dpi
# set style and clip
self._print_pgf_clip(gc)
self._print_pgf_path_styles(gc, rgbFace)
# build marker definition
bl, tr = marker_path.get_extents(marker_trans).get_points()
coords = bl[0] * f, bl[1] * f, tr[0] * f, tr[1] * f
writeln(self.fh,
r"\pgfsys@defobject{currentmarker}"
r"{\pgfqpoint{%fin}{%fin}}{\pgfqpoint{%fin}{%fin}}{" % coords)
self._print_pgf_path(None, marker_path, marker_trans)
self._pgf_path_draw(stroke=gc.get_linewidth() != 0.0,
fill=rgbFace is not None)
writeln(self.fh, r"}")
# draw marker for each vertex
for point, code in path.iter_segments(trans, simplify=False):
x, y = point[0] * f, point[1] * f
writeln(self.fh, r"\begin{pgfscope}")
writeln(self.fh, r"\pgfsys@transformshift{%fin}{%fin}" % (x, y))
writeln(self.fh, r"\pgfsys@useobject{currentmarker}{}")
writeln(self.fh, r"\end{pgfscope}")
writeln(self.fh, r"\end{pgfscope}")
def draw_path(self, gc, path, transform, rgbFace=None):
writeln(self.fh, r"\begin{pgfscope}")
# draw the path
self._print_pgf_clip(gc)
self._print_pgf_path_styles(gc, rgbFace)
self._print_pgf_path(gc, path, transform, rgbFace)
self._pgf_path_draw(stroke=gc.get_linewidth() != 0.0,
fill=rgbFace is not None)
writeln(self.fh, r"\end{pgfscope}")
# if present, draw pattern on top
if gc.get_hatch():
writeln(self.fh, r"\begin{pgfscope}")
self._print_pgf_path_styles(gc, rgbFace)
# combine clip and path for clipping
self._print_pgf_clip(gc)
self._print_pgf_path(gc, path, transform, rgbFace)
writeln(self.fh, r"\pgfusepath{clip}")
# build pattern definition
writeln(self.fh,
r"\pgfsys@defobject{currentpattern}"
r"{\pgfqpoint{0in}{0in}}{\pgfqpoint{1in}{1in}}{")
writeln(self.fh, r"\begin{pgfscope}")
writeln(self.fh,
r"\pgfpathrectangle"
r"{\pgfqpoint{0in}{0in}}{\pgfqpoint{1in}{1in}}")
writeln(self.fh, r"\pgfusepath{clip}")
scale = mpl.transforms.Affine2D().scale(self.dpi)
self._print_pgf_path(None, gc.get_hatch_path(), scale)
self._pgf_path_draw(stroke=True)
writeln(self.fh, r"\end{pgfscope}")
writeln(self.fh, r"}")
# repeat pattern, filling the bounding rect of the path
f = 1. / self.dpi
(xmin, ymin), (xmax, ymax) = \
path.get_extents(transform).get_points()
xmin, xmax = f * xmin, f * xmax
ymin, ymax = f * ymin, f * ymax
repx, repy = int(math.ceil(xmax-xmin)), int(math.ceil(ymax-ymin))
writeln(self.fh,
r"\pgfsys@transformshift{%fin}{%fin}" % (xmin, ymin))
for iy in range(repy):
for ix in range(repx):
writeln(self.fh, r"\pgfsys@useobject{currentpattern}{}")
writeln(self.fh, r"\pgfsys@transformshift{1in}{0in}")
writeln(self.fh, r"\pgfsys@transformshift{-%din}{0in}" % repx)
writeln(self.fh, r"\pgfsys@transformshift{0in}{1in}")
writeln(self.fh, r"\end{pgfscope}")
def _print_pgf_clip(self, gc):
f = 1. / self.dpi
# check for clip box
bbox = gc.get_clip_rectangle()
if bbox:
p1, p2 = bbox.get_points()
w, h = p2 - p1
coords = p1[0] * f, p1[1] * f, w * f, h * f
writeln(self.fh,
r"\pgfpathrectangle"
r"{\pgfqpoint{%fin}{%fin}}{\pgfqpoint{%fin}{%fin}}"
% coords)
writeln(self.fh, r"\pgfusepath{clip}")
# check for clip path
clippath, clippath_trans = gc.get_clip_path()
if clippath is not None:
self._print_pgf_path(gc, clippath, clippath_trans)
writeln(self.fh, r"\pgfusepath{clip}")
def _print_pgf_path_styles(self, gc, rgbFace):
# cap style
capstyles = {"butt": r"\pgfsetbuttcap",
"round": r"\pgfsetroundcap",
"projecting": r"\pgfsetrectcap"}
writeln(self.fh, capstyles[gc.get_capstyle()])
# join style
joinstyles = {"miter": r"\pgfsetmiterjoin",
"round": r"\pgfsetroundjoin",
"bevel": r"\pgfsetbeveljoin"}
writeln(self.fh, joinstyles[gc.get_joinstyle()])
# filling
has_fill = rgbFace is not None
if gc.get_forced_alpha():
fillopacity = strokeopacity = gc.get_alpha()
else:
strokeopacity = gc.get_rgb()[3]
fillopacity = rgbFace[3] if has_fill and len(rgbFace) > 3 else 1.0
if has_fill:
writeln(self.fh,
r"\definecolor{currentfill}{rgb}{%f,%f,%f}"
% tuple(rgbFace[:3]))
writeln(self.fh, r"\pgfsetfillcolor{currentfill}")
if has_fill and fillopacity != 1.0:
writeln(self.fh, r"\pgfsetfillopacity{%f}" % fillopacity)
# linewidth and color
lw = gc.get_linewidth() * mpl_pt_to_in * latex_in_to_pt
stroke_rgba = gc.get_rgb()
writeln(self.fh, r"\pgfsetlinewidth{%fpt}" % lw)
writeln(self.fh,
r"\definecolor{currentstroke}{rgb}{%f,%f,%f}"
% stroke_rgba[:3])
writeln(self.fh, r"\pgfsetstrokecolor{currentstroke}")
if strokeopacity != 1.0:
writeln(self.fh, r"\pgfsetstrokeopacity{%f}" % strokeopacity)
# line style
dash_offset, dash_list = gc.get_dashes()
if dash_list is None:
writeln(self.fh, r"\pgfsetdash{}{0pt}")
else:
writeln(self.fh,
r"\pgfsetdash{%s}{%fpt}"
% ("".join(r"{%fpt}" % dash for dash in dash_list),
dash_offset))
def _print_pgf_path(self, gc, path, transform, rgbFace=None):
f = 1. / self.dpi
# check for clip box / ignore clip for filled paths
bbox = gc.get_clip_rectangle() if gc else None
if bbox and (rgbFace is None):
p1, p2 = bbox.get_points()
clip = (p1[0], p1[1], p2[0], p2[1])
else:
clip = None
# build path
for points, code in path.iter_segments(transform, clip=clip):
if code == Path.MOVETO:
x, y = tuple(points)
writeln(self.fh,
r"\pgfpathmoveto{\pgfqpoint{%fin}{%fin}}" %
(f * x, f * y))
elif code == Path.CLOSEPOLY:
writeln(self.fh, r"\pgfpathclose")
elif code == Path.LINETO:
x, y = tuple(points)
writeln(self.fh,
r"\pgfpathlineto{\pgfqpoint{%fin}{%fin}}" %
(f * x, f * y))
elif code == Path.CURVE3:
cx, cy, px, py = tuple(points)
coords = cx * f, cy * f, px * f, py * f
writeln(self.fh,
r"\pgfpathquadraticcurveto"
r"{\pgfqpoint{%fin}{%fin}}{\pgfqpoint{%fin}{%fin}}"
% coords)
elif code == Path.CURVE4:
c1x, c1y, c2x, c2y, px, py = tuple(points)
coords = c1x * f, c1y * f, c2x * f, c2y * f, px * f, py * f
writeln(self.fh,
r"\pgfpathcurveto"
r"{\pgfqpoint{%fin}{%fin}}"
r"{\pgfqpoint{%fin}{%fin}}"
r"{\pgfqpoint{%fin}{%fin}}"
% coords)
def _pgf_path_draw(self, stroke=True, fill=False):
actions = []
if stroke:
actions.append("stroke")
if fill:
actions.append("fill")
writeln(self.fh, r"\pgfusepath{%s}" % ",".join(actions))
def option_scale_image(self):
"""
pgf backend supports affine transform of image.
"""
return True
def option_image_nocomposite(self):
"""
return whether to generate a composite image from multiple images on
a set of axes
"""
return not rcParams['image.composite_image']
def draw_image(self, gc, x, y, im, transform=None):
h, w = im.shape[:2]
if w == 0 or h == 0:
return
# save the images to png files
path = os.path.dirname(self.fh.name)
fname = os.path.splitext(os.path.basename(self.fh.name))[0]
fname_img = "%s-img%d.png" % (fname, self.image_counter)
self.image_counter += 1
_png.write_png(im[::-1], os.path.join(path, fname_img))
# reference the image in the pgf picture
writeln(self.fh, r"\begin{pgfscope}")
self._print_pgf_clip(gc)
f = 1. / self.dpi # from display coords to inch
if transform is None:
writeln(self.fh,
r"\pgfsys@transformshift{%fin}{%fin}" % (x * f, y * f))
w, h = w * f, h * f
else:
tr1, tr2, tr3, tr4, tr5, tr6 = transform.frozen().to_values()
writeln(self.fh,
r"\pgfsys@transformcm{%f}{%f}{%f}{%f}{%fin}{%fin}" %
(tr1 * f, tr2 * f, tr3 * f, tr4 * f,
(tr5 + x) * f, (tr6 + y) * f))
w = h = 1 # scale is already included in the transform
interp = str(transform is None).lower() # interpolation in PDF reader
writeln(self.fh,
r"\pgftext[left,bottom]"
r"{\pgfimage[interpolate=%s,width=%fin,height=%fin]{%s}}" %
(interp, w, h, fname_img))
writeln(self.fh, r"\end{pgfscope}")
def draw_tex(self, gc, x, y, s, prop, angle, ismath="TeX!", mtext=None):
self.draw_text(gc, x, y, s, prop, angle, ismath, mtext)
def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
# prepare string for tex
s = common_texification(s)
prop_cmds = _font_properties_str(prop)
s = r"%s %s" % (prop_cmds, s)
writeln(self.fh, r"\begin{pgfscope}")
alpha = gc.get_alpha()
if alpha != 1.0:
writeln(self.fh, r"\pgfsetfillopacity{%f}" % alpha)
writeln(self.fh, r"\pgfsetstrokeopacity{%f}" % alpha)
rgb = tuple(gc.get_rgb())[:3]
if rgb != (0, 0, 0):
writeln(self.fh, r"\definecolor{textcolor}{rgb}{%f,%f,%f}" % rgb)
writeln(self.fh, r"\pgfsetstrokecolor{textcolor}")
writeln(self.fh, r"\pgfsetfillcolor{textcolor}")
s = r"\color{textcolor}" + s
f = 1.0 / self.figure.dpi
text_args = []
if mtext and (
(angle == 0 or
mtext.get_rotation_mode() == "anchor") and
mtext.get_va() != "center_baseline"):
# if text anchoring can be supported, get the original coordinates
# and add alignment information
x, y = mtext.get_transform().transform_point(mtext.get_position())
text_args.append("x=%fin" % (x * f))
text_args.append("y=%fin" % (y * f))
halign = {"left": "left", "right": "right", "center": ""}
valign = {"top": "top", "bottom": "bottom",
"baseline": "base", "center": ""}
text_args.append(halign[mtext.get_ha()])
text_args.append(valign[mtext.get_va()])
else:
# if not, use the text layout provided by matplotlib
text_args.append("x=%fin" % (x * f))
text_args.append("y=%fin" % (y * f))
text_args.append("left")
text_args.append("base")
if angle != 0:
text_args.append("rotate=%f" % angle)
writeln(self.fh, r"\pgftext[%s]{%s}" % (",".join(text_args), s))
writeln(self.fh, r"\end{pgfscope}")
def get_text_width_height_descent(self, s, prop, ismath):
# check if the math is supposed to be displaystyled
s = common_texification(s)
# get text metrics in units of latex pt, convert to display units
w, h, d = self.latexManager.get_width_height_descent(s, prop)
# TODO: this should be latex_pt_to_in instead of mpl_pt_to_in
# but having a little bit more space around the text looks better,
# plus the bounding box reported by LaTeX is VERY narrow
f = mpl_pt_to_in * self.dpi
return w * f, h * f, d * f
def flipy(self):
return False
def get_canvas_width_height(self):
return self.figure.get_figwidth(), self.figure.get_figheight()
def points_to_pixels(self, points):
return points * mpl_pt_to_in * self.dpi
def new_gc(self):
return GraphicsContextPgf()
class GraphicsContextPgf(GraphicsContextBase):
pass
########################################################################
class TmpDirCleaner(object):
remaining_tmpdirs = set()
@staticmethod
def add(tmpdir):
TmpDirCleaner.remaining_tmpdirs.add(tmpdir)
@staticmethod
def cleanup_remaining_tmpdirs():
for tmpdir in TmpDirCleaner.remaining_tmpdirs:
try:
shutil.rmtree(tmpdir)
except:
sys.stderr.write("error deleting tmp directory %s\n" % tmpdir)
class FigureCanvasPgf(FigureCanvasBase):
filetypes = {"pgf": "LaTeX PGF picture",
"pdf": "LaTeX compiled PGF picture",
"png": "Portable Network Graphics", }
def get_default_filetype(self):
return 'pdf'
def _print_pgf_to_fh(self, fh, *args, **kwargs):
if kwargs.get("dryrun", False):
renderer = RendererPgf(self.figure, None, dummy=True)
self.figure.draw(renderer)
return
header_text = """%% Creator: Matplotlib, PGF backend
%%
%% To include the figure in your LaTeX document, write
%% \\input{<filename>.pgf}
%%
%% Make sure the required packages are loaded in your preamble
%% \\usepackage{pgf}
%%
%% Figures using additional raster images can only be included by \\input if
%% they are in the same directory as the main LaTeX file. For loading figures
%% from other directories you can use the `import` package
%% \\usepackage{import}
%% and then include the figures with
%% \\import{<path to file>}{<filename>.pgf}
%%
"""
# append the preamble used by the backend as a comment for debugging
header_info_preamble = ["%% Matplotlib used the following preamble"]
for line in get_preamble().splitlines():
header_info_preamble.append("%% " + line)
for line in get_fontspec().splitlines():
header_info_preamble.append("%% " + line)
header_info_preamble.append("%%")
header_info_preamble = "\n".join(header_info_preamble)
# get figure size in inch
w, h = self.figure.get_figwidth(), self.figure.get_figheight()
dpi = self.figure.get_dpi()
# create pgfpicture environment and write the pgf code
fh.write(header_text)
fh.write(header_info_preamble)
fh.write("\n")
writeln(fh, r"\begingroup")
writeln(fh, r"\makeatletter")
writeln(fh, r"\begin{pgfpicture}")
writeln(fh,
r"\pgfpathrectangle{\pgfpointorigin}{\pgfqpoint{%fin}{%fin}}"
% (w, h))
writeln(fh, r"\pgfusepath{use as bounding box, clip}")
_bbox_inches_restore = kwargs.pop("bbox_inches_restore", None)
renderer = MixedModeRenderer(self.figure, w, h, dpi,
RendererPgf(self.figure, fh),
bbox_inches_restore=_bbox_inches_restore)
self.figure.draw(renderer)
# end the pgfpicture environment
writeln(fh, r"\end{pgfpicture}")
writeln(fh, r"\makeatother")
writeln(fh, r"\endgroup")
def print_pgf(self, fname_or_fh, *args, **kwargs):
"""
Output pgf commands for drawing the figure so it can be included and
rendered in latex documents.
"""
if kwargs.get("dryrun", False):
self._print_pgf_to_fh(None, *args, **kwargs)
return
# figure out where the pgf is to be written to
if isinstance(fname_or_fh, six.string_types):
with codecs.open(fname_or_fh, "w", encoding="utf-8") as fh:
self._print_pgf_to_fh(fh, *args, **kwargs)
elif is_writable_file_like(fname_or_fh):
fh = codecs.getwriter("utf-8")(fname_or_fh)
self._print_pgf_to_fh(fh, *args, **kwargs)
else:
raise ValueError("filename must be a path")
def _print_pdf_to_fh(self, fh, *args, **kwargs):
w, h = self.figure.get_figwidth(), self.figure.get_figheight()
try:
# create temporary directory for compiling the figure
tmpdir = tempfile.mkdtemp(prefix="mpl_pgf_")
fname_pgf = os.path.join(tmpdir, "figure.pgf")
fname_tex = os.path.join(tmpdir, "figure.tex")
fname_pdf = os.path.join(tmpdir, "figure.pdf")
# print figure to pgf and compile it with latex
self.print_pgf(fname_pgf, *args, **kwargs)
latex_preamble = get_preamble()
latex_fontspec = get_fontspec()
latexcode = """
\\documentclass[12pt]{minimal}
\\usepackage[paperwidth=%fin, paperheight=%fin, margin=0in]{geometry}
%s
%s
\\usepackage{pgf}
\\begin{document}
\\centering
\\input{figure.pgf}
\\end{document}""" % (w, h, latex_preamble, latex_fontspec)
with codecs.open(fname_tex, "w", "utf-8") as fh_tex:
fh_tex.write(latexcode)
texcommand = get_texcommand()
cmdargs = [str(texcommand), "-interaction=nonstopmode",
"-halt-on-error", "figure.tex"]
try:
check_output(cmdargs, stderr=subprocess.STDOUT, cwd=tmpdir)
except subprocess.CalledProcessError as e:
raise RuntimeError(
"%s was not able to process your file.\n\nFull log:\n%s"
% (texcommand, e.output))
# copy file contents to target
with open(fname_pdf, "rb") as fh_src:
shutil.copyfileobj(fh_src, fh)
finally:
try:
shutil.rmtree(tmpdir)
except:
TmpDirCleaner.add(tmpdir)
def print_pdf(self, fname_or_fh, *args, **kwargs):
"""
Use LaTeX to compile a Pgf generated figure to PDF.
"""
if kwargs.get("dryrun", False):
self._print_pgf_to_fh(None, *args, **kwargs)
return
# figure out where the pdf is to be written to
if isinstance(fname_or_fh, six.string_types):
with open(fname_or_fh, "wb") as fh:
self._print_pdf_to_fh(fh, *args, **kwargs)
elif is_writable_file_like(fname_or_fh):
self._print_pdf_to_fh(fname_or_fh, *args, **kwargs)
else:
raise ValueError("filename must be a path or a file-like object")
def _print_png_to_fh(self, fh, *args, **kwargs):
converter = make_pdf_to_png_converter()
try:
# create temporary directory for pdf creation and png conversion
tmpdir = tempfile.mkdtemp(prefix="mpl_pgf_")
fname_pdf = os.path.join(tmpdir, "figure.pdf")
fname_png = os.path.join(tmpdir, "figure.png")
# create pdf and try to convert it to png
self.print_pdf(fname_pdf, *args, **kwargs)
converter(fname_pdf, fname_png, dpi=self.figure.dpi)
# copy file contents to target
with open(fname_png, "rb") as fh_src:
shutil.copyfileobj(fh_src, fh)
finally:
try:
shutil.rmtree(tmpdir)
except:
TmpDirCleaner.add(tmpdir)
def print_png(self, fname_or_fh, *args, **kwargs):
"""
Use LaTeX to compile a pgf figure to pdf and convert it to png.
"""
if kwargs.get("dryrun", False):
self._print_pgf_to_fh(None, *args, **kwargs)
return
if isinstance(fname_or_fh, six.string_types):
with open(fname_or_fh, "wb") as fh:
self._print_png_to_fh(fh, *args, **kwargs)
elif is_writable_file_like(fname_or_fh):
self._print_png_to_fh(fname_or_fh, *args, **kwargs)
else:
raise ValueError("filename must be a path or a file-like object")
def get_renderer(self):
return RendererPgf(self.figure, None, dummy=True)
class FigureManagerPgf(FigureManagerBase):
def __init__(self, *args):
FigureManagerBase.__init__(self, *args)
@_Backend.export
class _BackendPgf(_Backend):
FigureCanvas = FigureCanvasPgf
FigureManager = FigureManagerPgf
def _cleanup_all():
LatexManager._cleanup_remaining_instances()
TmpDirCleaner.cleanup_remaining_tmpdirs()
atexit.register(_cleanup_all)
| 37,119 | 36.457114 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/qt_editor/figureoptions.py | # -*- coding: utf-8 -*-
#
# Copyright © 2009 Pierre Raybaut
# Licensed under the terms of the MIT License
# see the mpl licenses directory for a copy of the license
"""Module that provides a GUI-based editor for matplotlib's figure options"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import os.path as osp
import re
import matplotlib
from matplotlib import cm, colors as mcolors, markers, image as mimage
import matplotlib.backends.qt_editor.formlayout as formlayout
from matplotlib.backends.qt_compat import QtGui
def get_icon(name):
basedir = osp.join(matplotlib.rcParams['datapath'], 'images')
return QtGui.QIcon(osp.join(basedir, name))
LINESTYLES = {'-': 'Solid',
'--': 'Dashed',
'-.': 'DashDot',
':': 'Dotted',
'None': 'None',
}
DRAWSTYLES = {
'default': 'Default',
'steps-pre': 'Steps (Pre)', 'steps': 'Steps (Pre)',
'steps-mid': 'Steps (Mid)',
'steps-post': 'Steps (Post)'}
MARKERS = markers.MarkerStyle.markers
def figure_edit(axes, parent=None):
"""Edit matplotlib figure options"""
sep = (None, None) # separator
# Get / General
# Cast to builtin floats as they have nicer reprs.
xmin, xmax = map(float, axes.get_xlim())
ymin, ymax = map(float, axes.get_ylim())
general = [('Title', axes.get_title()),
sep,
(None, "<b>X-Axis</b>"),
('Left', xmin), ('Right', xmax),
('Label', axes.get_xlabel()),
('Scale', [axes.get_xscale(), 'linear', 'log', 'logit']),
sep,
(None, "<b>Y-Axis</b>"),
('Bottom', ymin), ('Top', ymax),
('Label', axes.get_ylabel()),
('Scale', [axes.get_yscale(), 'linear', 'log', 'logit']),
sep,
('(Re-)Generate automatic legend', False),
]
# Save the unit data
xconverter = axes.xaxis.converter
yconverter = axes.yaxis.converter
xunits = axes.xaxis.get_units()
yunits = axes.yaxis.get_units()
# Sorting for default labels (_lineXXX, _imageXXX).
def cmp_key(label):
match = re.match(r"(_line|_image)(\d+)", label)
if match:
return match.group(1), int(match.group(2))
else:
return label, 0
# Get / Curves
linedict = {}
for line in axes.get_lines():
label = line.get_label()
if label == '_nolegend_':
continue
linedict[label] = line
curves = []
def prepare_data(d, init):
"""Prepare entry for FormLayout.
`d` is a mapping of shorthands to style names (a single style may
have multiple shorthands, in particular the shorthands `None`,
`"None"`, `"none"` and `""` are synonyms); `init` is one shorthand
of the initial style.
This function returns an list suitable for initializing a
FormLayout combobox, namely `[initial_name, (shorthand,
style_name), (shorthand, style_name), ...]`.
"""
# Drop duplicate shorthands from dict (by overwriting them during
# the dict comprehension).
name2short = {name: short for short, name in d.items()}
# Convert back to {shorthand: name}.
short2name = {short: name for name, short in name2short.items()}
# Find the kept shorthand for the style specified by init.
canonical_init = name2short[d[init]]
# Sort by representation and prepend the initial value.
return ([canonical_init] +
sorted(short2name.items(),
key=lambda short_and_name: short_and_name[1]))
curvelabels = sorted(linedict, key=cmp_key)
for label in curvelabels:
line = linedict[label]
color = mcolors.to_hex(
mcolors.to_rgba(line.get_color(), line.get_alpha()),
keep_alpha=True)
ec = mcolors.to_hex(
mcolors.to_rgba(line.get_markeredgecolor(), line.get_alpha()),
keep_alpha=True)
fc = mcolors.to_hex(
mcolors.to_rgba(line.get_markerfacecolor(), line.get_alpha()),
keep_alpha=True)
curvedata = [
('Label', label),
sep,
(None, '<b>Line</b>'),
('Line style', prepare_data(LINESTYLES, line.get_linestyle())),
('Draw style', prepare_data(DRAWSTYLES, line.get_drawstyle())),
('Width', line.get_linewidth()),
('Color (RGBA)', color),
sep,
(None, '<b>Marker</b>'),
('Style', prepare_data(MARKERS, line.get_marker())),
('Size', line.get_markersize()),
('Face color (RGBA)', fc),
('Edge color (RGBA)', ec)]
curves.append([curvedata, label, ""])
# Is there a curve displayed?
has_curve = bool(curves)
# Get / Images
imagedict = {}
for image in axes.get_images():
label = image.get_label()
if label == '_nolegend_':
continue
imagedict[label] = image
imagelabels = sorted(imagedict, key=cmp_key)
images = []
cmaps = [(cmap, name) for name, cmap in sorted(cm.cmap_d.items())]
for label in imagelabels:
image = imagedict[label]
cmap = image.get_cmap()
if cmap not in cm.cmap_d.values():
cmaps = [(cmap, cmap.name)] + cmaps
low, high = image.get_clim()
imagedata = [
('Label', label),
('Colormap', [cmap.name] + cmaps),
('Min. value', low),
('Max. value', high),
('Interpolation',
[image.get_interpolation()]
+ [(name, name) for name in sorted(mimage.interpolations_names)])]
images.append([imagedata, label, ""])
# Is there an image displayed?
has_image = bool(images)
datalist = [(general, "Axes", "")]
if curves:
datalist.append((curves, "Curves", ""))
if images:
datalist.append((images, "Images", ""))
def apply_callback(data):
"""This function will be called to apply changes"""
orig_xlim = axes.get_xlim()
orig_ylim = axes.get_ylim()
general = data.pop(0)
curves = data.pop(0) if has_curve else []
images = data.pop(0) if has_image else []
if data:
raise ValueError("Unexpected field")
# Set / General
(title, xmin, xmax, xlabel, xscale, ymin, ymax, ylabel, yscale,
generate_legend) = general
if axes.get_xscale() != xscale:
axes.set_xscale(xscale)
if axes.get_yscale() != yscale:
axes.set_yscale(yscale)
axes.set_title(title)
axes.set_xlim(xmin, xmax)
axes.set_xlabel(xlabel)
axes.set_ylim(ymin, ymax)
axes.set_ylabel(ylabel)
# Restore the unit data
axes.xaxis.converter = xconverter
axes.yaxis.converter = yconverter
axes.xaxis.set_units(xunits)
axes.yaxis.set_units(yunits)
axes.xaxis._update_axisinfo()
axes.yaxis._update_axisinfo()
# Set / Curves
for index, curve in enumerate(curves):
line = linedict[curvelabels[index]]
(label, linestyle, drawstyle, linewidth, color, marker, markersize,
markerfacecolor, markeredgecolor) = curve
line.set_label(label)
line.set_linestyle(linestyle)
line.set_drawstyle(drawstyle)
line.set_linewidth(linewidth)
rgba = mcolors.to_rgba(color)
line.set_alpha(None)
line.set_color(rgba)
if marker is not 'none':
line.set_marker(marker)
line.set_markersize(markersize)
line.set_markerfacecolor(markerfacecolor)
line.set_markeredgecolor(markeredgecolor)
# Set / Images
for index, image_settings in enumerate(images):
image = imagedict[imagelabels[index]]
label, cmap, low, high, interpolation = image_settings
image.set_label(label)
image.set_cmap(cm.get_cmap(cmap))
image.set_clim(*sorted([low, high]))
image.set_interpolation(interpolation)
# re-generate legend, if checkbox is checked
if generate_legend:
draggable = None
ncol = 1
if axes.legend_ is not None:
old_legend = axes.get_legend()
draggable = old_legend._draggable is not None
ncol = old_legend._ncol
new_legend = axes.legend(ncol=ncol)
if new_legend:
new_legend.draggable(draggable)
# Redraw
figure = axes.get_figure()
figure.canvas.draw()
if not (axes.get_xlim() == orig_xlim and axes.get_ylim() == orig_ylim):
figure.canvas.toolbar.push_current()
data = formlayout.fedit(datalist, title="Figure options", parent=parent,
icon=get_icon('qt4_editor_options.svg'),
apply=apply_callback)
if data is not None:
apply_callback(data)
| 9,209 | 34.019011 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/qt_editor/formsubplottool.py | from matplotlib.backends.qt_compat import QtWidgets
class UiSubplotTool(QtWidgets.QDialog):
def __init__(self, *args, **kwargs):
super(UiSubplotTool, self).__init__(*args, **kwargs)
self.setObjectName("SubplotTool")
self._widgets = {}
layout = QtWidgets.QHBoxLayout()
self.setLayout(layout)
left = QtWidgets.QVBoxLayout()
layout.addLayout(left)
right = QtWidgets.QVBoxLayout()
layout.addLayout(right)
box = QtWidgets.QGroupBox("Borders")
left.addWidget(box)
inner = QtWidgets.QFormLayout(box)
for side in ["top", "bottom", "left", "right"]:
self._widgets[side] = widget = QtWidgets.QDoubleSpinBox()
widget.setMinimum(0)
widget.setMaximum(1)
widget.setDecimals(3)
widget.setSingleStep(.005)
widget.setKeyboardTracking(False)
inner.addRow(side, widget)
left.addStretch(1)
box = QtWidgets.QGroupBox("Spacings")
right.addWidget(box)
inner = QtWidgets.QFormLayout(box)
for side in ["hspace", "wspace"]:
self._widgets[side] = widget = QtWidgets.QDoubleSpinBox()
widget.setMinimum(0)
widget.setMaximum(1)
widget.setDecimals(3)
widget.setSingleStep(.005)
widget.setKeyboardTracking(False)
inner.addRow(side, widget)
right.addStretch(1)
widget = QtWidgets.QPushButton("Export values")
self._widgets["Export values"] = widget
# Don't trigger on <enter>, which is used to input values.
widget.setAutoDefault(False)
left.addWidget(widget)
for action in ["Tight layout", "Reset", "Close"]:
self._widgets[action] = widget = QtWidgets.QPushButton(action)
widget.setAutoDefault(False)
right.addWidget(widget)
self._widgets["Close"].setFocus()
| 1,953 | 33.280702 | 74 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/qt_editor/__init__.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
| 109 | 35.666667 | 66 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/qt_editor/formlayout.py | # -*- coding: utf-8 -*-
"""
formlayout
==========
Module creating Qt form dialogs/layouts to edit various type of parameters
formlayout License Agreement (MIT License)
------------------------------------------
Copyright (c) 2009 Pierre Raybaut
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
"""
# History:
# 1.0.10: added float validator (disable "Ok" and "Apply" button when not valid)
# 1.0.7: added support for "Apply" button
# 1.0.6: code cleaning
from __future__ import (absolute_import, division, print_function,
unicode_literals)
__version__ = '1.0.10'
__license__ = __doc__
import copy
import datetime
import warnings
import six
from matplotlib import colors as mcolors
from matplotlib.backends.qt_compat import QtGui, QtWidgets, QtCore
BLACKLIST = {"title", "label"}
class ColorButton(QtWidgets.QPushButton):
"""
Color choosing push button
"""
colorChanged = QtCore.Signal(QtGui.QColor)
def __init__(self, parent=None):
QtWidgets.QPushButton.__init__(self, parent)
self.setFixedSize(20, 20)
self.setIconSize(QtCore.QSize(12, 12))
self.clicked.connect(self.choose_color)
self._color = QtGui.QColor()
def choose_color(self):
color = QtWidgets.QColorDialog.getColor(
self._color, self.parentWidget(), "",
QtWidgets.QColorDialog.ShowAlphaChannel)
if color.isValid():
self.set_color(color)
def get_color(self):
return self._color
@QtCore.Slot(QtGui.QColor)
def set_color(self, color):
if color != self._color:
self._color = color
self.colorChanged.emit(self._color)
pixmap = QtGui.QPixmap(self.iconSize())
pixmap.fill(color)
self.setIcon(QtGui.QIcon(pixmap))
color = QtCore.Property(QtGui.QColor, get_color, set_color)
def to_qcolor(color):
"""Create a QColor from a matplotlib color"""
qcolor = QtGui.QColor()
try:
rgba = mcolors.to_rgba(color)
except ValueError:
warnings.warn('Ignoring invalid color %r' % color)
return qcolor # return invalid QColor
qcolor.setRgbF(*rgba)
return qcolor
class ColorLayout(QtWidgets.QHBoxLayout):
"""Color-specialized QLineEdit layout"""
def __init__(self, color, parent=None):
QtWidgets.QHBoxLayout.__init__(self)
assert isinstance(color, QtGui.QColor)
self.lineedit = QtWidgets.QLineEdit(
mcolors.to_hex(color.getRgbF(), keep_alpha=True), parent)
self.lineedit.editingFinished.connect(self.update_color)
self.addWidget(self.lineedit)
self.colorbtn = ColorButton(parent)
self.colorbtn.color = color
self.colorbtn.colorChanged.connect(self.update_text)
self.addWidget(self.colorbtn)
def update_color(self):
color = self.text()
qcolor = to_qcolor(color)
self.colorbtn.color = qcolor # defaults to black if not qcolor.isValid()
def update_text(self, color):
self.lineedit.setText(mcolors.to_hex(color.getRgbF(), keep_alpha=True))
def text(self):
return self.lineedit.text()
def font_is_installed(font):
"""Check if font is installed"""
return [fam for fam in QtGui.QFontDatabase().families()
if six.text_type(fam) == font]
def tuple_to_qfont(tup):
"""
Create a QFont from tuple:
(family [string], size [int], italic [bool], bold [bool])
"""
if not (isinstance(tup, tuple) and len(tup) == 4
and font_is_installed(tup[0])
and isinstance(tup[1], int)
and isinstance(tup[2], bool)
and isinstance(tup[3], bool)):
return None
font = QtGui.QFont()
family, size, italic, bold = tup
font.setFamily(family)
font.setPointSize(size)
font.setItalic(italic)
font.setBold(bold)
return font
def qfont_to_tuple(font):
return (six.text_type(font.family()), int(font.pointSize()),
font.italic(), font.bold())
class FontLayout(QtWidgets.QGridLayout):
"""Font selection"""
def __init__(self, value, parent=None):
QtWidgets.QGridLayout.__init__(self)
font = tuple_to_qfont(value)
assert font is not None
# Font family
self.family = QtWidgets.QFontComboBox(parent)
self.family.setCurrentFont(font)
self.addWidget(self.family, 0, 0, 1, -1)
# Font size
self.size = QtWidgets.QComboBox(parent)
self.size.setEditable(True)
sizelist = list(range(6, 12)) + list(range(12, 30, 2)) + [36, 48, 72]
size = font.pointSize()
if size not in sizelist:
sizelist.append(size)
sizelist.sort()
self.size.addItems([str(s) for s in sizelist])
self.size.setCurrentIndex(sizelist.index(size))
self.addWidget(self.size, 1, 0)
# Italic or not
self.italic = QtWidgets.QCheckBox(self.tr("Italic"), parent)
self.italic.setChecked(font.italic())
self.addWidget(self.italic, 1, 1)
# Bold or not
self.bold = QtWidgets.QCheckBox(self.tr("Bold"), parent)
self.bold.setChecked(font.bold())
self.addWidget(self.bold, 1, 2)
def get_font(self):
font = self.family.currentFont()
font.setItalic(self.italic.isChecked())
font.setBold(self.bold.isChecked())
font.setPointSize(int(self.size.currentText()))
return qfont_to_tuple(font)
def is_edit_valid(edit):
text = edit.text()
state = edit.validator().validate(text, 0)[0]
return state == QtGui.QDoubleValidator.Acceptable
class FormWidget(QtWidgets.QWidget):
update_buttons = QtCore.Signal()
def __init__(self, data, comment="", parent=None):
QtWidgets.QWidget.__init__(self, parent)
self.data = copy.deepcopy(data)
self.widgets = []
self.formlayout = QtWidgets.QFormLayout(self)
if comment:
self.formlayout.addRow(QtWidgets.QLabel(comment))
self.formlayout.addRow(QtWidgets.QLabel(" "))
def get_dialog(self):
"""Return FormDialog instance"""
dialog = self.parent()
while not isinstance(dialog, QtWidgets.QDialog):
dialog = dialog.parent()
return dialog
def setup(self):
for label, value in self.data:
if label is None and value is None:
# Separator: (None, None)
self.formlayout.addRow(QtWidgets.QLabel(" "), QtWidgets.QLabel(" "))
self.widgets.append(None)
continue
elif label is None:
# Comment
self.formlayout.addRow(QtWidgets.QLabel(value))
self.widgets.append(None)
continue
elif tuple_to_qfont(value) is not None:
field = FontLayout(value, self)
elif (label.lower() not in BLACKLIST
and mcolors.is_color_like(value)):
field = ColorLayout(to_qcolor(value), self)
elif isinstance(value, six.string_types):
field = QtWidgets.QLineEdit(value, self)
elif isinstance(value, (list, tuple)):
if isinstance(value, tuple):
value = list(value)
selindex = value.pop(0)
field = QtWidgets.QComboBox(self)
if isinstance(value[0], (list, tuple)):
keys = [key for key, _val in value]
value = [val for _key, val in value]
else:
keys = value
field.addItems(value)
if selindex in value:
selindex = value.index(selindex)
elif selindex in keys:
selindex = keys.index(selindex)
elif not isinstance(selindex, int):
warnings.warn(
"index '%s' is invalid (label: %s, value: %s)" %
(selindex, label, value))
selindex = 0
field.setCurrentIndex(selindex)
elif isinstance(value, bool):
field = QtWidgets.QCheckBox(self)
if value:
field.setCheckState(QtCore.Qt.Checked)
else:
field.setCheckState(QtCore.Qt.Unchecked)
elif isinstance(value, float):
field = QtWidgets.QLineEdit(repr(value), self)
field.setCursorPosition(0)
field.setValidator(QtGui.QDoubleValidator(field))
field.validator().setLocale(QtCore.QLocale("C"))
dialog = self.get_dialog()
dialog.register_float_field(field)
field.textChanged.connect(lambda text: dialog.update_buttons())
elif isinstance(value, int):
field = QtWidgets.QSpinBox(self)
field.setRange(-1e9, 1e9)
field.setValue(value)
elif isinstance(value, datetime.datetime):
field = QtWidgets.QDateTimeEdit(self)
field.setDateTime(value)
elif isinstance(value, datetime.date):
field = QtWidgets.QDateEdit(self)
field.setDate(value)
else:
field = QtWidgets.QLineEdit(repr(value), self)
self.formlayout.addRow(label, field)
self.widgets.append(field)
def get(self):
valuelist = []
for index, (label, value) in enumerate(self.data):
field = self.widgets[index]
if label is None:
# Separator / Comment
continue
elif tuple_to_qfont(value) is not None:
value = field.get_font()
elif (isinstance(value, six.string_types)
or mcolors.is_color_like(value)):
value = six.text_type(field.text())
elif isinstance(value, (list, tuple)):
index = int(field.currentIndex())
if isinstance(value[0], (list, tuple)):
value = value[index][0]
else:
value = value[index]
elif isinstance(value, bool):
value = field.checkState() == QtCore.Qt.Checked
elif isinstance(value, float):
value = float(str(field.text()))
elif isinstance(value, int):
value = int(field.value())
elif isinstance(value, datetime.datetime):
value = field.dateTime().toPyDateTime()
elif isinstance(value, datetime.date):
value = field.date().toPyDate()
else:
value = eval(str(field.text()))
valuelist.append(value)
return valuelist
class FormComboWidget(QtWidgets.QWidget):
update_buttons = QtCore.Signal()
def __init__(self, datalist, comment="", parent=None):
QtWidgets.QWidget.__init__(self, parent)
layout = QtWidgets.QVBoxLayout()
self.setLayout(layout)
self.combobox = QtWidgets.QComboBox()
layout.addWidget(self.combobox)
self.stackwidget = QtWidgets.QStackedWidget(self)
layout.addWidget(self.stackwidget)
self.combobox.currentIndexChanged.connect(self.stackwidget.setCurrentIndex)
self.widgetlist = []
for data, title, comment in datalist:
self.combobox.addItem(title)
widget = FormWidget(data, comment=comment, parent=self)
self.stackwidget.addWidget(widget)
self.widgetlist.append(widget)
def setup(self):
for widget in self.widgetlist:
widget.setup()
def get(self):
return [widget.get() for widget in self.widgetlist]
class FormTabWidget(QtWidgets.QWidget):
update_buttons = QtCore.Signal()
def __init__(self, datalist, comment="", parent=None):
QtWidgets.QWidget.__init__(self, parent)
layout = QtWidgets.QVBoxLayout()
self.tabwidget = QtWidgets.QTabWidget()
layout.addWidget(self.tabwidget)
self.setLayout(layout)
self.widgetlist = []
for data, title, comment in datalist:
if len(data[0]) == 3:
widget = FormComboWidget(data, comment=comment, parent=self)
else:
widget = FormWidget(data, comment=comment, parent=self)
index = self.tabwidget.addTab(widget, title)
self.tabwidget.setTabToolTip(index, comment)
self.widgetlist.append(widget)
def setup(self):
for widget in self.widgetlist:
widget.setup()
def get(self):
return [widget.get() for widget in self.widgetlist]
class FormDialog(QtWidgets.QDialog):
"""Form Dialog"""
def __init__(self, data, title="", comment="",
icon=None, parent=None, apply=None):
QtWidgets.QDialog.__init__(self, parent)
self.apply_callback = apply
# Form
if isinstance(data[0][0], (list, tuple)):
self.formwidget = FormTabWidget(data, comment=comment,
parent=self)
elif len(data[0]) == 3:
self.formwidget = FormComboWidget(data, comment=comment,
parent=self)
else:
self.formwidget = FormWidget(data, comment=comment,
parent=self)
layout = QtWidgets.QVBoxLayout()
layout.addWidget(self.formwidget)
self.float_fields = []
self.formwidget.setup()
# Button box
self.bbox = bbox = QtWidgets.QDialogButtonBox(
QtWidgets.QDialogButtonBox.Ok | QtWidgets.QDialogButtonBox.Cancel)
self.formwidget.update_buttons.connect(self.update_buttons)
if self.apply_callback is not None:
apply_btn = bbox.addButton(QtWidgets.QDialogButtonBox.Apply)
apply_btn.clicked.connect(self.apply)
bbox.accepted.connect(self.accept)
bbox.rejected.connect(self.reject)
layout.addWidget(bbox)
self.setLayout(layout)
self.setWindowTitle(title)
if not isinstance(icon, QtGui.QIcon):
icon = QtWidgets.QWidget().style().standardIcon(QtWidgets.QStyle.SP_MessageBoxQuestion)
self.setWindowIcon(icon)
def register_float_field(self, field):
self.float_fields.append(field)
def update_buttons(self):
valid = True
for field in self.float_fields:
if not is_edit_valid(field):
valid = False
for btn_type in (QtWidgets.QDialogButtonBox.Ok,
QtWidgets.QDialogButtonBox.Apply):
btn = self.bbox.button(btn_type)
if btn is not None:
btn.setEnabled(valid)
def accept(self):
self.data = self.formwidget.get()
QtWidgets.QDialog.accept(self)
def reject(self):
self.data = None
QtWidgets.QDialog.reject(self)
def apply(self):
self.apply_callback(self.formwidget.get())
def get(self):
"""Return form result"""
return self.data
def fedit(data, title="", comment="", icon=None, parent=None, apply=None):
"""
Create form dialog and return result
(if Cancel button is pressed, return None)
data: datalist, datagroup
title: string
comment: string
icon: QIcon instance
parent: parent QWidget
apply: apply callback (function)
datalist: list/tuple of (field_name, field_value)
datagroup: list/tuple of (datalist *or* datagroup, title, comment)
-> one field for each member of a datalist
-> one tab for each member of a top-level datagroup
-> one page (of a multipage widget, each page can be selected with a combo
box) for each member of a datagroup inside a datagroup
Supported types for field_value:
- int, float, str, unicode, bool
- colors: in Qt-compatible text form, i.e. in hex format or name (red,...)
(automatically detected from a string)
- list/tuple:
* the first element will be the selected index (or value)
* the other elements can be couples (key, value) or only values
"""
# Create a QApplication instance if no instance currently exists
# (e.g., if the module is used directly from the interpreter)
if QtWidgets.QApplication.startingUp():
_app = QtWidgets.QApplication([])
dialog = FormDialog(data, title, comment, icon, parent, apply)
if dialog.exec_():
return dialog.get()
if __name__ == "__main__":
def create_datalist_example():
return [('str', 'this is a string'),
('list', [0, '1', '3', '4']),
('list2', ['--', ('none', 'None'), ('--', 'Dashed'),
('-.', 'DashDot'), ('-', 'Solid'),
('steps', 'Steps'), (':', 'Dotted')]),
('float', 1.2),
(None, 'Other:'),
('int', 12),
('font', ('Arial', 10, False, True)),
('color', '#123409'),
('bool', True),
('date', datetime.date(2010, 10, 10)),
('datetime', datetime.datetime(2010, 10, 10)),
]
def create_datagroup_example():
datalist = create_datalist_example()
return ((datalist, "Category 1", "Category 1 comment"),
(datalist, "Category 2", "Category 2 comment"),
(datalist, "Category 3", "Category 3 comment"))
#--------- datalist example
datalist = create_datalist_example()
def apply_test(data):
print("data:", data)
print("result:", fedit(datalist, title="Example",
comment="This is just an <b>example</b>.",
apply=apply_test))
#--------- datagroup example
datagroup = create_datagroup_example()
print("result:", fedit(datagroup, "Global title"))
#--------- datagroup inside a datagroup example
datalist = create_datalist_example()
datagroup = create_datagroup_example()
print("result:", fedit(((datagroup, "Title 1", "Tab 1 comment"),
(datalist, "Title 2", "Tab 2 comment"),
(datalist, "Title 3", "Tab 3 comment")),
"Global title"))
| 19,420 | 34.634862 | 99 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/ipython_inline_figure.html | <!-- Within the kernel, we don't know the address of the matplotlib
websocket server, so we have to get in client-side and fetch our
resources that way. -->
<script>
// We can't proceed until these Javascript files are fetched, so
// we fetch them synchronously
$.ajaxSetup({async: false});
$.getScript("http://" + window.location.hostname + ":{{ port }}{{prefix}}/_static/js/mpl_tornado.js");
$.getScript("http://" + window.location.hostname + ":{{ port }}{{prefix}}/js/mpl.js");
$.ajaxSetup({async: true});
function init_figure{{ fig_id }}(e) {
$('div.output').off('resize');
var output_div = $(e.target).find('div.output_subarea');
var websocket_type = mpl.get_websocket_type();
var websocket = new websocket_type(
"ws://" + window.location.hostname + ":{{ port }}{{ prefix}}/" +
{{ repr(str(fig_id)) }} + "/ws");
var fig = new mpl.figure(
{{repr(str(fig_id))}}, websocket, mpl_ondownload, output_div);
// Fetch the first image
fig.context.drawImage(fig.imageObj, 0, 0);
fig.focus_on_mouseover = true;
}
// We can't initialize the figure contents until our content
// has been added to the DOM. This is a bit of hack to get an
// event for that.
$('div.output').resize(init_figure{{ fig_id }});
</script>
| 1,305 | 36.314286 | 104 | html |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/single_figure.html | <html>
<head>
<link rel="stylesheet" href="{{ prefix }}/_static/css/page.css" type="text/css">
<link rel="stylesheet" href="{{ prefix }}/_static/css/boilerplate.css" type="text/css" />
<link rel="stylesheet" href="{{ prefix }}/_static/css/fbm.css" type="text/css" />
<link rel="stylesheet" href="{{ prefix }}/_static/jquery/css/themes/base/jquery-ui.min.css" >
<script src="{{ prefix }}/_static/jquery/js/jquery-1.11.3.min.js"></script>
<script src="{{ prefix }}/_static/jquery/js/jquery-ui.min.js"></script>
<script src="{{ prefix }}/_static/js/mpl_tornado.js"></script>
<script src="{{ prefix }}/js/mpl.js"></script>
<script>
$(document).ready(
function() {
var websocket_type = mpl.get_websocket_type();
var websocket = new websocket_type(
"{{ ws_uri }}" + {{ repr(str(fig_id)) }} + "/ws");
var fig = new mpl.figure(
{{repr(str(fig_id))}}, websocket, mpl_ondownload, $('div#figure'));
}
);
</script>
<title>matplotlib</title>
</head>
<body>
<div id="mpl-warnings" class="mpl-warnings"></div>
<div id="figure" style="margin: 10px 10px;"></div>
</body>
</html>
| 1,203 | 37.83871 | 97 | html |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/all_figures.html | <html>
<head>
<link rel="stylesheet" href="{{ prefix }}/_static/css/page.css" type="text/css">
<link rel="stylesheet" href="{{ prefix }}/_static/css/boilerplate.css" type="text/css" />
<link rel="stylesheet" href="{{ prefix }}/_static/css/fbm.css" type="text/css" />
<link rel="stylesheet" href="{{ prefix }}/_static/jquery/css/themes/base/jquery-ui.min.css" >
<script src="{{ prefix }}/_static/jquery/js/jquery-1.11.3.min.js"></script>
<script src="{{ prefix }}/_static/jquery/js/jquery-ui.min.js"></script>
<script src="{{ prefix }}/_static/js/mpl_tornado.js"></script>
<script src="{{ prefix }}/js/mpl.js"></script>
<script>
{% for (fig_id, fig_manager) in figures %}
$(document).ready(
function() {
var main_div = $('div#figures');
var figure_div = $('<div id="figure-div"/>')
main_div.append(figure_div);
var websocket_type = mpl.get_websocket_type();
var websocket = new websocket_type(
"{{ ws_uri }}" + "{{ fig_id }}" + "/ws");
var fig = new mpl.figure(
"{{ fig_id }}", websocket, mpl_ondownload, figure_div);
fig.focus_on_mouseover = true;
$(fig.canvas).attr('tabindex', {{ fig_id }});
}
);
{% end %}
</script>
<title>MPL | WebAgg current figures</title>
</head>
<body>
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cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/jquery/css/themes/base/jquery-ui.min.css | /*! jQuery UI - v1.11.4 - 2015-03-11
* http://jqueryui.com
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.ui-state-error-text{color:#fff}.ui-priority-primary,.ui-widget-content .ui-priority-primary,.ui-widget-header .ui-priority-primary{font-weight:bold}.ui-priority-secondary,.ui-widget-content .ui-priority-secondary,.ui-widget-header .ui-priority-secondary{opacity:.7;filter:Alpha(Opacity=70);font-weight:normal}.ui-state-disabled,.ui-widget-content .ui-state-disabled,.ui-widget-header .ui-state-disabled{opacity:.35;filter:Alpha(Opacity=35);background-image:none}.ui-state-disabled .ui-icon{filter:Alpha(Opacity=35)}.ui-icon{width:16px;height:16px}.ui-icon,.ui-widget-content .ui-icon{background-image:url("images/ui-icons_222222_256x240.png")}.ui-widget-header .ui-icon{background-image:url("images/ui-icons_ffffff_256x240.png")}.ui-state-default .ui-icon{background-image:url("images/ui-icons_ef8c08_256x240.png")}.ui-state-hover .ui-icon,.ui-state-focus .ui-icon{background-image:url("images/ui-icons_ef8c08_256x240.png")}.ui-state-active .ui-icon{background-image:url("images/ui-icons_ef8c08_256x240.png")}.ui-state-highlight .ui-icon{background-image:url("images/ui-icons_228ef1_256x240.png")}.ui-state-error .ui-icon,.ui-state-error-text .ui-icon{background-image:url("images/ui-icons_ffd27a_256x240.png")}.ui-icon-blank{background-position:16px 16px}.ui-icon-carat-1-n{background-position:0 0}.ui-icon-carat-1-ne{background-position:-16px 0}.ui-icon-carat-1-e{background-position:-32px 0}.ui-icon-carat-1-se{background-position:-48px 0}.ui-icon-carat-1-s{background-position:-64px 0}.ui-icon-carat-1-sw{background-position:-80px 0}.ui-icon-carat-1-w{background-position:-96px 0}.ui-icon-carat-1-nw{background-position:-112px 0}.ui-icon-carat-2-n-s{background-position:-128px 0}.ui-icon-carat-2-e-w{background-position:-144px 0}.ui-icon-triangle-1-n{background-position:0 -16px}.ui-icon-triangle-1-ne{background-position:-16px -16px}.ui-icon-triangle-1-e{background-position:-32px -16px}.ui-icon-triangle-1-se{background-position:-48px 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-48px}.ui-icon-arrowthickstop-1-e{background-position:-208px -48px}.ui-icon-arrowthickstop-1-s{background-position:-224px -48px}.ui-icon-arrowthickstop-1-w{background-position:-240px -48px}.ui-icon-arrowreturnthick-1-w{background-position:0 -64px}.ui-icon-arrowreturnthick-1-n{background-position:-16px -64px}.ui-icon-arrowreturnthick-1-e{background-position:-32px -64px}.ui-icon-arrowreturnthick-1-s{background-position:-48px -64px}.ui-icon-arrowreturn-1-w{background-position:-64px -64px}.ui-icon-arrowreturn-1-n{background-position:-80px -64px}.ui-icon-arrowreturn-1-e{background-position:-96px -64px}.ui-icon-arrowreturn-1-s{background-position:-112px -64px}.ui-icon-arrowrefresh-1-w{background-position:-128px -64px}.ui-icon-arrowrefresh-1-n{background-position:-144px -64px}.ui-icon-arrowrefresh-1-e{background-position:-160px -64px}.ui-icon-arrowrefresh-1-s{background-position:-176px -64px}.ui-icon-arrow-4{background-position:0 -80px}.ui-icon-arrow-4-diag{background-position:-16px 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-176px}.ui-icon-battery-0{background-position:-48px -176px}.ui-icon-battery-1{background-position:-64px -176px}.ui-icon-battery-2{background-position:-80px -176px}.ui-icon-battery-3{background-position:-96px -176px}.ui-icon-circle-plus{background-position:0 -192px}.ui-icon-circle-minus{background-position:-16px -192px}.ui-icon-circle-close{background-position:-32px -192px}.ui-icon-circle-triangle-e{background-position:-48px -192px}.ui-icon-circle-triangle-s{background-position:-64px -192px}.ui-icon-circle-triangle-w{background-position:-80px -192px}.ui-icon-circle-triangle-n{background-position:-96px -192px}.ui-icon-circle-arrow-e{background-position:-112px -192px}.ui-icon-circle-arrow-s{background-position:-128px -192px}.ui-icon-circle-arrow-w{background-position:-144px -192px}.ui-icon-circle-arrow-n{background-position:-160px -192px}.ui-icon-circle-zoomin{background-position:-176px -192px}.ui-icon-circle-zoomout{background-position:-192px -192px}.ui-icon-circle-check{background-position:-208px -192px}.ui-icon-circlesmall-plus{background-position:0 -208px}.ui-icon-circlesmall-minus{background-position:-16px -208px}.ui-icon-circlesmall-close{background-position:-32px -208px}.ui-icon-squaresmall-plus{background-position:-48px -208px}.ui-icon-squaresmall-minus{background-position:-64px -208px}.ui-icon-squaresmall-close{background-position:-80px -208px}.ui-icon-grip-dotted-vertical{background-position:0 -224px}.ui-icon-grip-dotted-horizontal{background-position:-16px -224px}.ui-icon-grip-solid-vertical{background-position:-32px -224px}.ui-icon-grip-solid-horizontal{background-position:-48px -224px}.ui-icon-gripsmall-diagonal-se{background-position:-64px -224px}.ui-icon-grip-diagonal-se{background-position:-80px -224px}.ui-corner-all,.ui-corner-top,.ui-corner-left,.ui-corner-tl{border-top-left-radius:4px}.ui-corner-all,.ui-corner-top,.ui-corner-right,.ui-corner-tr{border-top-right-radius:4px}.ui-corner-all,.ui-corner-bottom,.ui-corner-left,.ui-corner-bl{border-bottom-left-radius:4px}.ui-corner-all,.ui-corner-bottom,.ui-corner-right,.ui-corner-br{border-bottom-right-radius:4px}.ui-widget-overlay{background:#666 url("images/ui-bg_diagonals-thick_20_666666_40x40.png") 50% 50% repeat;opacity:.5;filter:Alpha(Opacity=50)}.ui-widget-shadow{margin:-5px 0 0 -5px;padding:5px;background:#000 url("images/ui-bg_flat_10_000000_40x100.png") 50% 50% repeat-x;opacity:.2;filter:Alpha(Opacity=20);border-radius:5px} | 30,163 | 4,308.142857 | 28,367 | css |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/css/page.css | /**
* Primary styles
*
* Author: IPython Development Team
*/
body {
background-color: white;
/* This makes sure that the body covers the entire window and needs to
be in a different element than the display: box in wrapper below */
position: absolute;
left: 0px;
right: 0px;
top: 0px;
bottom: 0px;
overflow: visible;
}
div#header {
/* Initially hidden to prevent FLOUC */
display: none;
position: relative;
height: 40px;
padding: 5px;
margin: 0px;
width: 100%;
}
span#ipython_notebook {
position: absolute;
padding: 2px 2px 2px 5px;
}
span#ipython_notebook img {
font-family: Verdana, "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;
height: 24px;
text-decoration:none;
display: inline;
color: black;
}
#site {
width: 100%;
display: none;
}
/* We set the fonts by hand here to override the values in the theme */
.ui-widget {
font-family: "Lucinda Grande", "Lucinda Sans Unicode", Helvetica, Arial, Verdana, sans-serif;
}
.ui-widget input, .ui-widget select, .ui-widget textarea, .ui-widget button {
font-family: "Lucinda Grande", "Lucinda Sans Unicode", Helvetica, Arial, Verdana, sans-serif;
}
/* Smaller buttons */
.ui-button .ui-button-text {
padding: 0.2em 0.8em;
font-size: 77%;
}
input.ui-button {
padding: 0.3em 0.9em;
}
span#login_widget {
float: right;
}
.border-box-sizing {
box-sizing: border-box;
-moz-box-sizing: border-box;
-webkit-box-sizing: border-box;
}
#figure-div {
display: inline-block;
margin: 10px;
}
| 1,599 | 18.277108 | 97 | css |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/css/fbm.css |
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
.hbox {
display: -webkit-box;
-webkit-box-orient: horizontal;
-webkit-box-align: stretch;
display: -moz-box;
-moz-box-orient: horizontal;
-moz-box-align: stretch;
display: box;
box-orient: horizontal;
box-align: stretch;
}
.hbox > * {
-webkit-box-flex: 0;
-moz-box-flex: 0;
box-flex: 0;
}
.vbox {
display: -webkit-box;
-webkit-box-orient: vertical;
-webkit-box-align: stretch;
display: -moz-box;
-moz-box-orient: vertical;
-moz-box-align: stretch;
display: box;
box-orient: vertical;
box-align: stretch;
}
.vbox > * {
-webkit-box-flex: 0;
-moz-box-flex: 0;
box-flex: 0;
}
.reverse {
-webkit-box-direction: reverse;
-moz-box-direction: reverse;
box-direction: reverse;
}
.box-flex0 {
-webkit-box-flex: 0;
-moz-box-flex: 0;
box-flex: 0;
}
.box-flex1, .box-flex {
-webkit-box-flex: 1;
-moz-box-flex: 1;
box-flex: 1;
}
.box-flex2 {
-webkit-box-flex: 2;
-moz-box-flex: 2;
box-flex: 2;
}
.box-group1 {
-webkit-box-flex-group: 1;
-moz-box-flex-group: 1;
box-flex-group: 1;
}
.box-group2 {
-webkit-box-flex-group: 2;
-moz-box-flex-group: 2;
box-flex-group: 2;
}
.start {
-webkit-box-pack: start;
-moz-box-pack: start;
box-pack: start;
}
.end {
-webkit-box-pack: end;
-moz-box-pack: end;
box-pack: end;
}
.center {
-webkit-box-pack: center;
-moz-box-pack: center;
box-pack: center;
}
| 1,473 | 14.040816 | 77 | css |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/backends/web_backend/css/boilerplate.css | /**
* HTML5 ✰ Boilerplate
*
* style.css contains a reset, font normalization and some base styles.
*
* Credit is left where credit is due.
* Much inspiration was taken from these projects:
* - yui.yahooapis.com/2.8.1/build/base/base.css
* - camendesign.com/design/
* - praegnanz.de/weblog/htmlcssjs-kickstart
*/
/**
* html5doctor.com Reset Stylesheet (Eric Meyer's Reset Reloaded + HTML5 baseline)
* v1.6.1 2010-09-17 | Authors: Eric Meyer & Richard Clark
* html5doctor.com/html-5-reset-stylesheet/
*/
html, body, div, span, object, iframe,
h1, h2, h3, h4, h5, h6, p, blockquote, pre,
abbr, address, cite, code, del, dfn, em, img, ins, kbd, q, samp,
small, strong, sub, sup, var, b, i, dl, dt, dd, ol, ul, li,
fieldset, form, label, legend,
table, caption, tbody, tfoot, thead, tr, th, td,
article, aside, canvas, details, figcaption, figure,
footer, header, hgroup, menu, nav, section, summary,
time, mark, audio, video {
margin: 0;
padding: 0;
border: 0;
font-size: 100%;
font: inherit;
vertical-align: baseline;
}
sup { vertical-align: super; }
sub { vertical-align: sub; }
article, aside, details, figcaption, figure,
footer, header, hgroup, menu, nav, section {
display: block;
}
blockquote, q { quotes: none; }
blockquote:before, blockquote:after,
q:before, q:after { content: ""; content: none; }
ins { background-color: #ff9; color: #000; text-decoration: none; }
mark { background-color: #ff9; color: #000; font-style: italic; font-weight: bold; }
del { text-decoration: line-through; }
abbr[title], dfn[title] { border-bottom: 1px dotted; cursor: help; }
table { border-collapse: collapse; border-spacing: 0; }
hr { display: block; height: 1px; border: 0; border-top: 1px solid #ccc; margin: 1em 0; padding: 0; }
input, select { vertical-align: middle; }
/**
* Font normalization inspired by YUI Library's fonts.css: developer.yahoo.com/yui/
*/
body { font:13px/1.231 sans-serif; *font-size:small; } /* Hack retained to preserve specificity */
select, input, textarea, button { font:99% sans-serif; }
/* Normalize monospace sizing:
en.wikipedia.org/wiki/MediaWiki_talk:Common.css/Archive_11#Teletype_style_fix_for_Chrome */
pre, code, kbd, samp { font-family: monospace, sans-serif; }
em,i { font-style: italic; }
b,strong { font-weight: bold; }
| 2,308 | 28.602564 | 101 | css |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/projections/polar.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from collections import OrderedDict
import numpy as np
from matplotlib.axes import Axes
import matplotlib.axis as maxis
from matplotlib import cbook
from matplotlib import docstring
import matplotlib.markers as mmarkers
import matplotlib.patches as mpatches
import matplotlib.path as mpath
from matplotlib import rcParams
import matplotlib.ticker as mticker
import matplotlib.transforms as mtransforms
import matplotlib.spines as mspines
class PolarTransform(mtransforms.Transform):
"""
The base polar transform. This handles projection *theta* and
*r* into Cartesian coordinate space *x* and *y*, but does not
perform the ultimate affine transformation into the correct
position.
"""
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, axis=None, use_rmin=True,
_apply_theta_transforms=True):
mtransforms.Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
self._apply_theta_transforms = _apply_theta_transforms
def __str__(self):
return ("{}(\n"
"{},\n"
" use_rmin={},\n"
" _apply_theta_transforms={})"
.format(type(self).__name__,
mtransforms._indent_str(self._axis),
self._use_rmin,
self._apply_theta_transforms))
def transform_non_affine(self, tr):
xy = np.empty(tr.shape, float)
t = tr[:, 0:1]
r = tr[:, 1:2]
x = xy[:, 0:1]
y = xy[:, 1:2]
# PolarAxes does not use the theta transforms here, but apply them for
# backwards-compatibility if not being used by it.
if self._apply_theta_transforms and self._axis is not None:
t *= self._axis.get_theta_direction()
t += self._axis.get_theta_offset()
if self._use_rmin and self._axis is not None:
r = r - self._axis.get_rorigin()
mask = r < 0
x[:] = np.where(mask, np.nan, r * np.cos(t))
y[:] = np.where(mask, np.nan, r * np.sin(t))
return xy
transform_non_affine.__doc__ = \
mtransforms.Transform.transform_non_affine.__doc__
def transform_path_non_affine(self, path):
vertices = path.vertices
if len(vertices) == 2 and vertices[0, 0] == vertices[1, 0]:
return mpath.Path(self.transform(vertices), path.codes)
ipath = path.interpolated(path._interpolation_steps)
return mpath.Path(self.transform(ipath.vertices), ipath.codes)
transform_path_non_affine.__doc__ = \
mtransforms.Transform.transform_path_non_affine.__doc__
def inverted(self):
return PolarAxes.InvertedPolarTransform(self._axis, self._use_rmin,
self._apply_theta_transforms)
inverted.__doc__ = mtransforms.Transform.inverted.__doc__
class PolarAffine(mtransforms.Affine2DBase):
"""
The affine part of the polar projection. Scales the output so
that maximum radius rests on the edge of the axes circle.
"""
def __init__(self, scale_transform, limits):
"""
*limits* is the view limit of the data. The only part of
its bounds that is used is the y limits (for the radius limits).
The theta range is handled by the non-affine transform.
"""
mtransforms.Affine2DBase.__init__(self)
self._scale_transform = scale_transform
self._limits = limits
self.set_children(scale_transform, limits)
self._mtx = None
def __str__(self):
return ("{}(\n"
"{},\n"
"{})"
.format(type(self).__name__,
mtransforms._indent_str(self._scale_transform),
mtransforms._indent_str(self._limits)))
def get_matrix(self):
if self._invalid:
limits_scaled = self._limits.transformed(self._scale_transform)
yscale = limits_scaled.ymax - limits_scaled.ymin
affine = mtransforms.Affine2D() \
.scale(0.5 / yscale) \
.translate(0.5, 0.5)
self._mtx = affine.get_matrix()
self._inverted = None
self._invalid = 0
return self._mtx
get_matrix.__doc__ = mtransforms.Affine2DBase.get_matrix.__doc__
class InvertedPolarTransform(mtransforms.Transform):
"""
The inverse of the polar transform, mapping Cartesian
coordinate space *x* and *y* back to *theta* and *r*.
"""
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, axis=None, use_rmin=True,
_apply_theta_transforms=True):
mtransforms.Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
self._apply_theta_transforms = _apply_theta_transforms
def __str__(self):
return ("{}(\n"
"{},\n"
" use_rmin={},\n"
" _apply_theta_transforms={})"
.format(type(self).__name__,
mtransforms._indent_str(self._axis),
self._use_rmin,
self._apply_theta_transforms))
def transform_non_affine(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:]
r = np.sqrt(x*x + y*y)
with np.errstate(invalid='ignore'):
# At x=y=r=0 this will raise an
# invalid value warning when doing 0/0
# Divide by zero warnings are only raised when
# the numerator is different from 0. That
# should not happen here.
theta = np.arccos(x / r)
theta = np.where(y < 0, 2 * np.pi - theta, theta)
# PolarAxes does not use the theta transforms here, but apply them for
# backwards-compatibility if not being used by it.
if self._apply_theta_transforms and self._axis is not None:
theta -= self._axis.get_theta_offset()
theta *= self._axis.get_theta_direction()
theta %= 2 * np.pi
if self._use_rmin and self._axis is not None:
r += self._axis.get_rorigin()
return np.concatenate((theta, r), 1)
transform_non_affine.__doc__ = \
mtransforms.Transform.transform_non_affine.__doc__
def inverted(self):
return PolarAxes.PolarTransform(self._axis, self._use_rmin,
self._apply_theta_transforms)
inverted.__doc__ = mtransforms.Transform.inverted.__doc__
class ThetaFormatter(mticker.Formatter):
"""
Used to format the *theta* tick labels. Converts the native
unit of radians into degrees and adds a degree symbol.
"""
def __call__(self, x, pos=None):
vmin, vmax = self.axis.get_view_interval()
d = np.rad2deg(abs(vmax - vmin))
digits = max(-int(np.log10(d) - 1.5), 0)
if rcParams['text.usetex'] and not rcParams['text.latex.unicode']:
format_str = r"${value:0.{digits:d}f}^\circ$"
return format_str.format(value=np.rad2deg(x), digits=digits)
else:
# we use unicode, rather than mathtext with \circ, so
# that it will work correctly with any arbitrary font
# (assuming it has a degree sign), whereas $5\circ$
# will only work correctly with one of the supported
# math fonts (Computer Modern and STIX)
format_str = "{value:0.{digits:d}f}\N{DEGREE SIGN}"
return format_str.format(value=np.rad2deg(x), digits=digits)
class _AxisWrapper(object):
def __init__(self, axis):
self._axis = axis
def get_view_interval(self):
return np.rad2deg(self._axis.get_view_interval())
def set_view_interval(self, vmin, vmax):
self._axis.set_view_interval(*np.deg2rad((vmin, vmax)))
def get_minpos(self):
return np.rad2deg(self._axis.get_minpos())
def get_data_interval(self):
return np.rad2deg(self._axis.get_data_interval())
def set_data_interval(self, vmin, vmax):
self._axis.set_data_interval(*np.deg2rad((vmin, vmax)))
def get_tick_space(self):
return self._axis.get_tick_space()
class ThetaLocator(mticker.Locator):
"""
Used to locate theta ticks.
This will work the same as the base locator except in the case that the
view spans the entire circle. In such cases, the previously used default
locations of every 45 degrees are returned.
"""
def __init__(self, base):
self.base = base
self.axis = self.base.axis = _AxisWrapper(self.base.axis)
def set_axis(self, axis):
self.axis = _AxisWrapper(axis)
self.base.set_axis(self.axis)
def __call__(self):
lim = self.axis.get_view_interval()
if _is_full_circle_deg(lim[0], lim[1]):
return np.arange(8) * 2 * np.pi / 8
else:
return np.deg2rad(self.base())
def autoscale(self):
return self.base.autoscale()
def pan(self, numsteps):
return self.base.pan(numsteps)
def refresh(self):
return self.base.refresh()
def view_limits(self, vmin, vmax):
vmin, vmax = np.rad2deg((vmin, vmax))
return np.deg2rad(self.base.view_limits(vmin, vmax))
def zoom(self, direction):
return self.base.zoom(direction)
class ThetaTick(maxis.XTick):
"""
A theta-axis tick.
This subclass of `XTick` provides angular ticks with some small
modification to their re-positioning such that ticks are rotated based on
tick location. This results in ticks that are correctly perpendicular to
the arc spine.
When 'auto' rotation is enabled, labels are also rotated to be parallel to
the spine. The label padding is also applied here since it's not possible
to use a generic axes transform to produce tick-specific padding.
"""
def __init__(self, axes, *args, **kwargs):
self._text1_translate = mtransforms.ScaledTranslation(
0, 0,
axes.figure.dpi_scale_trans)
self._text2_translate = mtransforms.ScaledTranslation(
0, 0,
axes.figure.dpi_scale_trans)
super(ThetaTick, self).__init__(axes, *args, **kwargs)
def _get_text1(self):
t = super(ThetaTick, self)._get_text1()
t.set_rotation_mode('anchor')
t.set_transform(t.get_transform() + self._text1_translate)
return t
def _get_text2(self):
t = super(ThetaTick, self)._get_text2()
t.set_rotation_mode('anchor')
t.set_transform(t.get_transform() + self._text2_translate)
return t
def _apply_params(self, **kw):
super(ThetaTick, self)._apply_params(**kw)
# Ensure transform is correct; sometimes this gets reset.
trans = self.label1.get_transform()
if not trans.contains_branch(self._text1_translate):
self.label1.set_transform(trans + self._text1_translate)
trans = self.label2.get_transform()
if not trans.contains_branch(self._text2_translate):
self.label2.set_transform(trans + self._text2_translate)
def _update_padding(self, pad, angle):
padx = pad * np.cos(angle) / 72
pady = pad * np.sin(angle) / 72
self._text1_translate._t = (padx, pady)
self._text1_translate.invalidate()
self._text2_translate._t = (-padx, -pady)
self._text2_translate.invalidate()
def update_position(self, loc):
super(ThetaTick, self).update_position(loc)
axes = self.axes
angle = loc * axes.get_theta_direction() + axes.get_theta_offset()
text_angle = np.rad2deg(angle) % 360 - 90
angle -= np.pi / 2
if self.tick1On:
marker = self.tick1line.get_marker()
if marker in (mmarkers.TICKUP, '|'):
trans = mtransforms.Affine2D().scale(1.0, 1.0).rotate(angle)
elif marker == mmarkers.TICKDOWN:
trans = mtransforms.Affine2D().scale(1.0, -1.0).rotate(angle)
else:
# Don't modify custom tick line markers.
trans = self.tick1line._marker._transform
self.tick1line._marker._transform = trans
if self.tick2On:
marker = self.tick2line.get_marker()
if marker in (mmarkers.TICKUP, '|'):
trans = mtransforms.Affine2D().scale(1.0, 1.0).rotate(angle)
elif marker == mmarkers.TICKDOWN:
trans = mtransforms.Affine2D().scale(1.0, -1.0).rotate(angle)
else:
# Don't modify custom tick line markers.
trans = self.tick2line._marker._transform
self.tick2line._marker._transform = trans
mode, user_angle = self._labelrotation
if mode == 'default':
text_angle = user_angle
else:
if text_angle > 90:
text_angle -= 180
elif text_angle < -90:
text_angle += 180
text_angle += user_angle
if self.label1On:
self.label1.set_rotation(text_angle)
if self.label2On:
self.label2.set_rotation(text_angle)
# This extra padding helps preserve the look from previous releases but
# is also needed because labels are anchored to their center.
pad = self._pad + 7
self._update_padding(pad,
self._loc * axes.get_theta_direction() +
axes.get_theta_offset())
class ThetaAxis(maxis.XAxis):
"""
A theta Axis.
This overrides certain properties of an `XAxis` to provide special-casing
for an angular axis.
"""
__name__ = 'thetaaxis'
axis_name = 'theta'
def _get_tick(self, major):
if major:
tick_kw = self._major_tick_kw
else:
tick_kw = self._minor_tick_kw
return ThetaTick(self.axes, 0, '', major=major, **tick_kw)
def _wrap_locator_formatter(self):
self.set_major_locator(ThetaLocator(self.get_major_locator()))
self.set_major_formatter(ThetaFormatter())
self.isDefault_majloc = True
self.isDefault_majfmt = True
def cla(self):
super(ThetaAxis, self).cla()
self.set_ticks_position('none')
self._wrap_locator_formatter()
def _set_scale(self, value, **kwargs):
super(ThetaAxis, self)._set_scale(value, **kwargs)
self._wrap_locator_formatter()
def _copy_tick_props(self, src, dest):
'Copy the props from src tick to dest tick'
if src is None or dest is None:
return
super(ThetaAxis, self)._copy_tick_props(src, dest)
# Ensure that tick transforms are independent so that padding works.
trans = dest._get_text1_transform()[0]
dest.label1.set_transform(trans + dest._text1_translate)
trans = dest._get_text2_transform()[0]
dest.label2.set_transform(trans + dest._text2_translate)
class RadialLocator(mticker.Locator):
"""
Used to locate radius ticks.
Ensures that all ticks are strictly positive. For all other
tasks, it delegates to the base
:class:`~matplotlib.ticker.Locator` (which may be different
depending on the scale of the *r*-axis.
"""
def __init__(self, base, axes=None):
self.base = base
self._axes = axes
def __call__(self):
show_all = True
# Ensure previous behaviour with full circle non-annular views.
if self._axes:
if _is_full_circle_rad(*self._axes.viewLim.intervalx):
rorigin = self._axes.get_rorigin()
if self._axes.get_rmin() <= rorigin:
show_all = False
if show_all:
return self.base()
else:
return [tick for tick in self.base() if tick > rorigin]
def autoscale(self):
return self.base.autoscale()
def pan(self, numsteps):
return self.base.pan(numsteps)
def zoom(self, direction):
return self.base.zoom(direction)
def refresh(self):
return self.base.refresh()
def view_limits(self, vmin, vmax):
vmin, vmax = self.base.view_limits(vmin, vmax)
return mtransforms.nonsingular(min(0, vmin), vmax)
class _ThetaShift(mtransforms.ScaledTranslation):
"""
Apply a padding shift based on axes theta limits.
This is used to create padding for radial ticks.
Parameters
----------
axes : matplotlib.axes.Axes
The owning axes; used to determine limits.
pad : float
The padding to apply, in points.
start : str, {'min', 'max', 'rlabel'}
Whether to shift away from the start (``'min'``) or the end (``'max'``)
of the axes, or using the rlabel position (``'rlabel'``).
"""
def __init__(self, axes, pad, mode):
mtransforms.ScaledTranslation.__init__(self, pad, pad,
axes.figure.dpi_scale_trans)
self.set_children(axes._realViewLim)
self.axes = axes
self.mode = mode
self.pad = pad
def __str__(self):
return ("{}(\n"
"{},\n"
"{},\n"
"{})"
.format(type(self).__name__,
mtransforms._indent_str(self.axes),
mtransforms._indent_str(self.pad),
mtransforms._indent_str(repr(self.mode))))
def get_matrix(self):
if self._invalid:
if self.mode == 'rlabel':
angle = (
np.deg2rad(self.axes.get_rlabel_position()) *
self.axes.get_theta_direction() +
self.axes.get_theta_offset()
)
else:
if self.mode == 'min':
angle = self.axes._realViewLim.xmin
elif self.mode == 'max':
angle = self.axes._realViewLim.xmax
if self.mode in ('rlabel', 'min'):
padx = np.cos(angle - np.pi / 2)
pady = np.sin(angle - np.pi / 2)
else:
padx = np.cos(angle + np.pi / 2)
pady = np.sin(angle + np.pi / 2)
self._t = (self.pad * padx / 72, self.pad * pady / 72)
return mtransforms.ScaledTranslation.get_matrix(self)
class RadialTick(maxis.YTick):
"""
A radial-axis tick.
This subclass of `YTick` provides radial ticks with some small modification
to their re-positioning such that ticks are rotated based on axes limits.
This results in ticks that are correctly perpendicular to the spine. Labels
are also rotated to be perpendicular to the spine, when 'auto' rotation is
enabled.
"""
def _get_text1(self):
t = super(RadialTick, self)._get_text1()
t.set_rotation_mode('anchor')
return t
def _get_text2(self):
t = super(RadialTick, self)._get_text2()
t.set_rotation_mode('anchor')
return t
def _determine_anchor(self, mode, angle, start):
# Note: angle is the (spine angle - 90) because it's used for the tick
# & text setup, so all numbers below are -90 from (normed) spine angle.
if mode == 'auto':
if start:
if -90 <= angle <= 90:
return 'left', 'center'
else:
return 'right', 'center'
else:
if -90 <= angle <= 90:
return 'right', 'center'
else:
return 'left', 'center'
else:
if start:
if angle < -68.5:
return 'center', 'top'
elif angle < -23.5:
return 'left', 'top'
elif angle < 22.5:
return 'left', 'center'
elif angle < 67.5:
return 'left', 'bottom'
elif angle < 112.5:
return 'center', 'bottom'
elif angle < 157.5:
return 'right', 'bottom'
elif angle < 202.5:
return 'right', 'center'
elif angle < 247.5:
return 'right', 'top'
else:
return 'center', 'top'
else:
if angle < -68.5:
return 'center', 'bottom'
elif angle < -23.5:
return 'right', 'bottom'
elif angle < 22.5:
return 'right', 'center'
elif angle < 67.5:
return 'right', 'top'
elif angle < 112.5:
return 'center', 'top'
elif angle < 157.5:
return 'left', 'top'
elif angle < 202.5:
return 'left', 'center'
elif angle < 247.5:
return 'left', 'bottom'
else:
return 'center', 'bottom'
def update_position(self, loc):
super(RadialTick, self).update_position(loc)
axes = self.axes
thetamin = axes.get_thetamin()
thetamax = axes.get_thetamax()
direction = axes.get_theta_direction()
offset_rad = axes.get_theta_offset()
offset = np.rad2deg(offset_rad)
full = _is_full_circle_deg(thetamin, thetamax)
if full:
angle = (axes.get_rlabel_position() * direction +
offset) % 360 - 90
tick_angle = 0
if angle > 90:
text_angle = angle - 180
elif angle < -90:
text_angle = angle + 180
else:
text_angle = angle
else:
angle = (thetamin * direction + offset) % 360 - 90
if direction > 0:
tick_angle = np.deg2rad(angle)
else:
tick_angle = np.deg2rad(angle + 180)
if angle > 90:
text_angle = angle - 180
elif angle < -90:
text_angle = angle + 180
else:
text_angle = angle
mode, user_angle = self._labelrotation
if mode == 'auto':
text_angle += user_angle
else:
text_angle = user_angle
if self.label1On:
if full:
ha = 'left'
va = 'bottom'
else:
ha, va = self._determine_anchor(mode, angle, direction > 0)
self.label1.set_ha(ha)
self.label1.set_va(va)
self.label1.set_rotation(text_angle)
if self.tick1On:
marker = self.tick1line.get_marker()
if marker == mmarkers.TICKLEFT:
trans = (mtransforms.Affine2D()
.scale(1.0, 1.0)
.rotate(tick_angle))
elif marker == '_':
trans = (mtransforms.Affine2D()
.scale(1.0, 1.0)
.rotate(tick_angle + np.pi / 2))
elif marker == mmarkers.TICKRIGHT:
trans = (mtransforms.Affine2D()
.scale(-1.0, 1.0)
.rotate(tick_angle))
else:
# Don't modify custom tick line markers.
trans = self.tick1line._marker._transform
self.tick1line._marker._transform = trans
if full:
self.label2On = False
self.tick2On = False
else:
angle = (thetamax * direction + offset) % 360 - 90
if direction > 0:
tick_angle = np.deg2rad(angle)
else:
tick_angle = np.deg2rad(angle + 180)
if angle > 90:
text_angle = angle - 180
elif angle < -90:
text_angle = angle + 180
else:
text_angle = angle
mode, user_angle = self._labelrotation
if mode == 'auto':
text_angle += user_angle
else:
text_angle = user_angle
if self.label2On:
ha, va = self._determine_anchor(mode, angle, direction < 0)
self.label2.set_ha(ha)
self.label2.set_va(va)
self.label2.set_rotation(text_angle)
if self.tick2On:
marker = self.tick2line.get_marker()
if marker == mmarkers.TICKLEFT:
trans = (mtransforms.Affine2D()
.scale(1.0, 1.0)
.rotate(tick_angle))
elif marker == '_':
trans = (mtransforms.Affine2D()
.scale(1.0, 1.0)
.rotate(tick_angle + np.pi / 2))
elif marker == mmarkers.TICKRIGHT:
trans = (mtransforms.Affine2D()
.scale(-1.0, 1.0)
.rotate(tick_angle))
else:
# Don't modify custom tick line markers.
trans = self.tick2line._marker._transform
self.tick2line._marker._transform = trans
class RadialAxis(maxis.YAxis):
"""
A radial Axis.
This overrides certain properties of a `YAxis` to provide special-casing
for a radial axis.
"""
__name__ = 'radialaxis'
axis_name = 'radius'
def __init__(self, *args, **kwargs):
super(RadialAxis, self).__init__(*args, **kwargs)
self.sticky_edges.y.append(0)
def _get_tick(self, major):
if major:
tick_kw = self._major_tick_kw
else:
tick_kw = self._minor_tick_kw
return RadialTick(self.axes, 0, '', major=major, **tick_kw)
def _wrap_locator_formatter(self):
self.set_major_locator(RadialLocator(self.get_major_locator(),
self.axes))
self.isDefault_majloc = True
def cla(self):
super(RadialAxis, self).cla()
self.set_ticks_position('none')
self._wrap_locator_formatter()
def _set_scale(self, value, **kwargs):
super(RadialAxis, self)._set_scale(value, **kwargs)
self._wrap_locator_formatter()
def _is_full_circle_deg(thetamin, thetamax):
"""
Determine if a wedge (in degrees) spans the full circle.
The condition is derived from :class:`~matplotlib.patches.Wedge`.
"""
return abs(abs(thetamax - thetamin) - 360.0) < 1e-12
def _is_full_circle_rad(thetamin, thetamax):
"""
Determine if a wedge (in radians) spans the full circle.
The condition is derived from :class:`~matplotlib.patches.Wedge`.
"""
return abs(abs(thetamax - thetamin) - 2 * np.pi) < 1.74e-14
class _WedgeBbox(mtransforms.Bbox):
"""
Transform (theta,r) wedge Bbox into axes bounding box.
Parameters
----------
center : tuple of float
Center of the wedge
viewLim : `~matplotlib.transforms.Bbox`
Bbox determining the boundaries of the wedge
originLim : `~matplotlib.transforms.Bbox`
Bbox determining the origin for the wedge, if different from *viewLim*
"""
def __init__(self, center, viewLim, originLim, **kwargs):
mtransforms.Bbox.__init__(self,
np.array([[0.0, 0.0], [1.0, 1.0]], np.float),
**kwargs)
self._center = center
self._viewLim = viewLim
self._originLim = originLim
self.set_children(viewLim, originLim)
def __str__(self):
return ("{}(\n"
"{},\n"
"{},\n"
"{})"
.format(type(self).__name__,
mtransforms._indent_str(self._center),
mtransforms._indent_str(self._viewLim),
mtransforms._indent_str(self._originLim)))
def get_points(self):
if self._invalid:
points = self._viewLim.get_points().copy()
# Scale angular limits to work with Wedge.
points[:, 0] *= 180 / np.pi
if points[0, 0] > points[1, 0]:
points[:, 0] = points[::-1, 0]
# Scale radial limits based on origin radius.
points[:, 1] -= self._originLim.y0
# Scale radial limits to match axes limits.
rscale = 0.5 / points[1, 1]
points[:, 1] *= rscale
width = min(points[1, 1] - points[0, 1], 0.5)
# Generate bounding box for wedge.
wedge = mpatches.Wedge(self._center, points[1, 1],
points[0, 0], points[1, 0],
width=width)
self.update_from_path(wedge.get_path())
# Ensure equal aspect ratio.
w, h = self._points[1] - self._points[0]
if h < w:
deltah = (w - h) / 2.0
deltaw = 0.0
elif w < h:
deltah = 0.0
deltaw = (h - w) / 2.0
else:
deltah = 0.0
deltaw = 0.0
self._points += np.array([[-deltaw, -deltah], [deltaw, deltah]])
self._invalid = 0
return self._points
get_points.__doc__ = mtransforms.Bbox.get_points.__doc__
class PolarAxes(Axes):
"""
A polar graph projection, where the input dimensions are *theta*, *r*.
Theta starts pointing east and goes anti-clockwise.
"""
name = 'polar'
def __init__(self, *args, **kwargs):
"""
Create a new Polar Axes for a polar plot.
"""
self._default_theta_offset = kwargs.pop('theta_offset', 0)
self._default_theta_direction = kwargs.pop('theta_direction', 1)
self._default_rlabel_position = np.deg2rad(
kwargs.pop('rlabel_position', 22.5))
Axes.__init__(self, *args, **kwargs)
self.use_sticky_edges = True
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
__init__.__doc__ = Axes.__init__.__doc__
def cla(self):
Axes.cla(self)
self.title.set_y(1.05)
start = self.spines.get('start', None)
if start:
start.set_visible(False)
end = self.spines.get('end', None)
if end:
end.set_visible(False)
self.set_xlim(0.0, 2 * np.pi)
self.grid(rcParams['polaraxes.grid'])
inner = self.spines.get('inner', None)
if inner:
inner.set_visible(False)
self.set_rorigin(None)
self.set_theta_offset(self._default_theta_offset)
self.set_theta_direction(self._default_theta_direction)
def _init_axis(self):
"move this out of __init__ because non-separable axes don't use it"
self.xaxis = ThetaAxis(self)
self.yaxis = RadialAxis(self)
# Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
# results in weird artifacts. Therefore we disable this for
# now.
# self.spines['polar'].register_axis(self.yaxis)
self._update_transScale()
def _set_lim_and_transforms(self):
# A view limit where the minimum radius can be locked if the user
# specifies an alternate origin.
self._originViewLim = mtransforms.LockableBbox(self.viewLim)
# Handle angular offset and direction.
self._direction = mtransforms.Affine2D() \
.scale(self._default_theta_direction, 1.0)
self._theta_offset = mtransforms.Affine2D() \
.translate(self._default_theta_offset, 0.0)
self.transShift = mtransforms.composite_transform_factory(
self._direction,
self._theta_offset)
# A view limit shifted to the correct location after accounting for
# orientation and offset.
self._realViewLim = mtransforms.TransformedBbox(self.viewLim,
self.transShift)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = mtransforms.TransformWrapper(
mtransforms.IdentityTransform())
# Scale view limit into a bbox around the selected wedge. This may be
# smaller than the usual unit axes rectangle if not plotting the full
# circle.
self.axesLim = _WedgeBbox((0.5, 0.5),
self._realViewLim, self._originViewLim)
# Scale the wedge to fill the axes.
self.transWedge = mtransforms.BboxTransformFrom(self.axesLim)
# Scale the axes to fill the figure.
self.transAxes = mtransforms.BboxTransformTo(self.bbox)
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(
self,
_apply_theta_transforms=False)
# Add dependency on rorigin.
self.transProjection.set_children(self._originViewLim)
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale,
self._originViewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = (
self.transScale + self.transShift + self.transProjection +
(self.transProjectionAffine + self.transWedge + self.transAxes))
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 0.0 and r == 1.0
# at the edge of the axis circles.
self._xaxis_transform = (
mtransforms.blended_transform_factory(
mtransforms.IdentityTransform(),
mtransforms.BboxTransformTo(self.viewLim)) +
self.transData)
# The theta labels are flipped along the radius, so that text 1 is on
# the outside by default. This should work the same as before.
flipr_transform = mtransforms.Affine2D() \
.translate(0.0, -0.5) \
.scale(1.0, -1.0) \
.translate(0.0, 0.5)
self._xaxis_text_transform = flipr_transform + self._xaxis_transform
# This is the transform for r-axis ticks. It scales the theta
# axis so the gridlines from 0.0 to 1.0, now go from thetamin to
# thetamax.
self._yaxis_transform = (
mtransforms.blended_transform_factory(
mtransforms.BboxTransformTo(self.viewLim),
mtransforms.IdentityTransform()) +
self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label_position = mtransforms.Affine2D() \
.translate(self._default_rlabel_position, 0.0)
self._yaxis_text_transform = mtransforms.TransformWrapper(
self._r_label_position + self.transData)
def get_xaxis_transform(self, which='grid'):
if which not in ['tick1', 'tick2', 'grid']:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text_transform, 'center', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text_transform, 'center', 'center'
def get_yaxis_transform(self, which='grid'):
if which in ('tick1', 'tick2'):
return self._yaxis_text_transform
elif which == 'grid':
return self._yaxis_transform
else:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
def get_yaxis_text1_transform(self, pad):
thetamin, thetamax = self._realViewLim.intervalx
if _is_full_circle_rad(thetamin, thetamax):
return self._yaxis_text_transform, 'bottom', 'left'
elif self.get_theta_direction() > 0:
halign = 'left'
pad_shift = _ThetaShift(self, pad, 'min')
else:
halign = 'right'
pad_shift = _ThetaShift(self, pad, 'max')
return self._yaxis_text_transform + pad_shift, 'center', halign
def get_yaxis_text2_transform(self, pad):
if self.get_theta_direction() > 0:
halign = 'right'
pad_shift = _ThetaShift(self, pad, 'max')
else:
halign = 'left'
pad_shift = _ThetaShift(self, pad, 'min')
return self._yaxis_text_transform + pad_shift, 'center', halign
def draw(self, *args, **kwargs):
thetamin, thetamax = np.rad2deg(self._realViewLim.intervalx)
if thetamin > thetamax:
thetamin, thetamax = thetamax, thetamin
rmin, rmax = self._realViewLim.intervaly - self.get_rorigin()
if isinstance(self.patch, mpatches.Wedge):
# Backwards-compatibility: Any subclassed Axes might override the
# patch to not be the Wedge that PolarAxes uses.
center = self.transWedge.transform_point((0.5, 0.5))
self.patch.set_center(center)
self.patch.set_theta1(thetamin)
self.patch.set_theta2(thetamax)
edge, _ = self.transWedge.transform_point((1, 0))
radius = edge - center[0]
width = min(radius * (rmax - rmin) / rmax, radius)
self.patch.set_radius(radius)
self.patch.set_width(width)
inner_width = radius - width
inner = self.spines.get('inner', None)
if inner:
inner.set_visible(inner_width != 0.0)
visible = not _is_full_circle_deg(thetamin, thetamax)
# For backwards compatibility, any subclassed Axes might override the
# spines to not include start/end that PolarAxes uses.
start = self.spines.get('start', None)
end = self.spines.get('end', None)
if start:
start.set_visible(visible)
if end:
end.set_visible(visible)
if visible:
yaxis_text_transform = self._yaxis_transform
else:
yaxis_text_transform = self._r_label_position + self.transData
if self._yaxis_text_transform != yaxis_text_transform:
self._yaxis_text_transform.set(yaxis_text_transform)
self.yaxis.reset_ticks()
self.yaxis.set_clip_path(self.patch)
Axes.draw(self, *args, **kwargs)
def _gen_axes_patch(self):
return mpatches.Wedge((0.5, 0.5), 0.5, 0.0, 360.0)
def _gen_axes_spines(self):
spines = OrderedDict([
('polar', mspines.Spine.arc_spine(self, 'top',
(0.5, 0.5), 0.5, 0.0, 360.0)),
('start', mspines.Spine.linear_spine(self, 'left')),
('end', mspines.Spine.linear_spine(self, 'right')),
('inner', mspines.Spine.arc_spine(self, 'bottom',
(0.5, 0.5), 0.0, 0.0, 360.0))
])
spines['polar'].set_transform(self.transWedge + self.transAxes)
spines['inner'].set_transform(self.transWedge + self.transAxes)
spines['start'].set_transform(self._yaxis_transform)
spines['end'].set_transform(self._yaxis_transform)
return spines
def set_thetamax(self, thetamax):
self.viewLim.x1 = np.deg2rad(thetamax)
def get_thetamax(self):
return np.rad2deg(self.viewLim.xmax)
def set_thetamin(self, thetamin):
self.viewLim.x0 = np.deg2rad(thetamin)
def get_thetamin(self):
return np.rad2deg(self.viewLim.xmin)
def set_thetalim(self, *args, **kwargs):
if 'thetamin' in kwargs:
kwargs['xmin'] = np.deg2rad(kwargs.pop('thetamin'))
if 'thetamax' in kwargs:
kwargs['xmax'] = np.deg2rad(kwargs.pop('thetamax'))
return tuple(np.rad2deg(self.set_xlim(*args, **kwargs)))
def set_theta_offset(self, offset):
"""
Set the offset for the location of 0 in radians.
"""
mtx = self._theta_offset.get_matrix()
mtx[0, 2] = offset
self._theta_offset.invalidate()
def get_theta_offset(self):
"""
Get the offset for the location of 0 in radians.
"""
return self._theta_offset.get_matrix()[0, 2]
def set_theta_zero_location(self, loc, offset=0.0):
"""
Sets the location of theta's zero. (Calls set_theta_offset
with the correct value in radians under the hood.)
loc : str
May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".
offset : float, optional
An offset in degrees to apply from the specified `loc`. **Note:**
this offset is *always* applied counter-clockwise regardless of
the direction setting.
"""
mapping = {
'N': np.pi * 0.5,
'NW': np.pi * 0.75,
'W': np.pi,
'SW': np.pi * 1.25,
'S': np.pi * 1.5,
'SE': np.pi * 1.75,
'E': 0,
'NE': np.pi * 0.25}
return self.set_theta_offset(mapping[loc] + np.deg2rad(offset))
def set_theta_direction(self, direction):
"""
Set the direction in which theta increases.
clockwise, -1:
Theta increases in the clockwise direction
counterclockwise, anticlockwise, 1:
Theta increases in the counterclockwise direction
"""
mtx = self._direction.get_matrix()
if direction in ('clockwise',):
mtx[0, 0] = -1
elif direction in ('counterclockwise', 'anticlockwise'):
mtx[0, 0] = 1
elif direction in (1, -1):
mtx[0, 0] = direction
else:
raise ValueError(
"direction must be 1, -1, clockwise or counterclockwise")
self._direction.invalidate()
def get_theta_direction(self):
"""
Get the direction in which theta increases.
-1:
Theta increases in the clockwise direction
1:
Theta increases in the counterclockwise direction
"""
return self._direction.get_matrix()[0, 0]
def set_rmax(self, rmax):
self.viewLim.y1 = rmax
def get_rmax(self):
return self.viewLim.ymax
def set_rmin(self, rmin):
self.viewLim.y0 = rmin
def get_rmin(self):
return self.viewLim.ymin
def set_rorigin(self, rorigin):
self._originViewLim.locked_y0 = rorigin
def get_rorigin(self):
return self._originViewLim.y0
def set_rlim(self, *args, **kwargs):
if 'rmin' in kwargs:
kwargs['ymin'] = kwargs.pop('rmin')
if 'rmax' in kwargs:
kwargs['ymax'] = kwargs.pop('rmax')
return self.set_ylim(*args, **kwargs)
def get_rlabel_position(self):
"""
Returns
-------
float
The theta position of the radius labels in degrees.
"""
return np.rad2deg(self._r_label_position.get_matrix()[0, 2])
def set_rlabel_position(self, value):
"""Updates the theta position of the radius labels.
Parameters
----------
value : number
The angular position of the radius labels in degrees.
"""
self._r_label_position.clear().translate(np.deg2rad(value), 0.0)
def set_yscale(self, *args, **kwargs):
Axes.set_yscale(self, *args, **kwargs)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator(), self))
def set_rscale(self, *args, **kwargs):
return Axes.set_yscale(self, *args, **kwargs)
def set_rticks(self, *args, **kwargs):
return Axes.set_yticks(self, *args, **kwargs)
@docstring.dedent_interpd
def set_thetagrids(self, angles, labels=None, frac=None, fmt=None,
**kwargs):
"""
Set the angles at which to place the theta grids (these
gridlines are equal along the theta dimension). *angles* is in
degrees.
*labels*, if not None, is a ``len(angles)`` list of strings of
the labels to use at each angle.
If *labels* is None, the labels will be ``fmt %% angle``
*frac* is the fraction of the polar axes radius at which to
place the label (1 is the edge). e.g., 1.05 is outside the axes
and 0.95 is inside the axes.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
if frac is not None:
cbook.warn_deprecated('2.1', name='frac', obj_type='parameter',
alternative='tick padding via '
'Axes.tick_params')
# Make sure we take into account unitized data
angles = self.convert_yunits(angles)
angles = np.deg2rad(angles)
self.set_xticks(angles)
if labels is not None:
self.set_xticklabels(labels)
elif fmt is not None:
self.xaxis.set_major_formatter(mticker.FormatStrFormatter(fmt))
for t in self.xaxis.get_ticklabels():
t.update(kwargs)
return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
@docstring.dedent_interpd
def set_rgrids(self, radii, labels=None, angle=None, fmt=None,
**kwargs):
"""
Set the radial locations and labels of the *r* grids.
The labels will appear at radial distances *radii* at the
given *angle* in degrees.
*labels*, if not None, is a ``len(radii)`` list of strings of the
labels to use at each radius.
If *labels* is None, the built-in formatter will be used.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
radii = self.convert_xunits(radii)
radii = np.asarray(radii)
self.set_yticks(radii)
if labels is not None:
self.set_yticklabels(labels)
elif fmt is not None:
self.yaxis.set_major_formatter(mticker.FormatStrFormatter(fmt))
if angle is None:
angle = self.get_rlabel_position()
self.set_rlabel_position(angle)
for t in self.yaxis.get_ticklabels():
t.update(kwargs)
return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels()
def set_xscale(self, scale, *args, **kwargs):
if scale != 'linear':
raise NotImplementedError(
"You can not set the xscale on a polar plot.")
def format_coord(self, theta, r):
"""
Return a format string formatting the coordinate using Unicode
characters.
"""
if theta < 0:
theta += 2 * np.pi
theta /= np.pi
return ('\N{GREEK SMALL LETTER THETA}=%0.3f\N{GREEK SMALL LETTER PI} '
'(%0.3f\N{DEGREE SIGN}), r=%0.3f') % (theta, theta * 180.0, r)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself. For a polar plot,
this should always be 1.0
'''
return 1.0
# # # Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
Polar axes do not support zoom boxes.
"""
return False
def can_pan(self):
"""
Return *True* if this axes supports the pan/zoom button functionality.
For polar axes, this is slightly misleading. Both panning and
zooming are performed by the same button. Panning is performed
in azimuth while zooming is done along the radial.
"""
return True
def start_pan(self, x, y, button):
angle = np.deg2rad(self.get_rlabel_position())
mode = ''
if button == 1:
epsilon = np.pi / 45.0
t, r = self.transData.inverted().transform_point((x, y))
if t >= angle - epsilon and t <= angle + epsilon:
mode = 'drag_r_labels'
elif button == 3:
mode = 'zoom'
self._pan_start = cbook.Bunch(
rmax=self.get_rmax(),
trans=self.transData.frozen(),
trans_inverse=self.transData.inverted().frozen(),
r_label_angle=self.get_rlabel_position(),
x=x,
y=y,
mode=mode)
def end_pan(self):
del self._pan_start
def drag_pan(self, button, key, x, y):
p = self._pan_start
if p.mode == 'drag_r_labels':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with theta
dt0 = t - startt
dt1 = startt - t
if abs(dt1) < abs(dt0):
dt = abs(dt1) * np.sign(dt0) * -1.0
else:
dt = dt0 * -1.0
dt = (dt / np.pi) * 180.0
self.set_rlabel_position(p.r_label_angle - dt)
trans, vert1, horiz1 = self.get_yaxis_text1_transform(0.0)
trans, vert2, horiz2 = self.get_yaxis_text2_transform(0.0)
for t in self.yaxis.majorTicks + self.yaxis.minorTicks:
t.label1.set_va(vert1)
t.label1.set_ha(horiz1)
t.label2.set_va(vert2)
t.label2.set_ha(horiz2)
elif p.mode == 'zoom':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with r
scale = r / startr
self.set_rmax(p.rmax / scale)
# to keep things all self contained, we can put aliases to the Polar classes
# defined above. This isn't strictly necessary, but it makes some of the
# code more readable (and provides a backwards compatible Polar API)
PolarAxes.PolarTransform = PolarTransform
PolarAxes.PolarAffine = PolarAffine
PolarAxes.InvertedPolarTransform = InvertedPolarTransform
PolarAxes.ThetaFormatter = ThetaFormatter
PolarAxes.RadialLocator = RadialLocator
PolarAxes.ThetaLocator = ThetaLocator
# These are a couple of aborted attempts to project a polar plot using
# cubic bezier curves.
# def transform_path(self, path):
# twopi = 2.0 * np.pi
# halfpi = 0.5 * np.pi
# vertices = path.vertices
# t0 = vertices[0:-1, 0]
# t1 = vertices[1: , 0]
# td = np.where(t1 > t0, t1 - t0, twopi - (t0 - t1))
# maxtd = td.max()
# interpolate = np.ceil(maxtd / halfpi)
# if interpolate > 1.0:
# vertices = self.interpolate(vertices, interpolate)
# vertices = self.transform(vertices)
# result = np.zeros((len(vertices) * 3 - 2, 2), float)
# codes = mpath.Path.CURVE4 * np.ones((len(vertices) * 3 - 2, ),
# mpath.Path.code_type)
# result[0] = vertices[0]
# codes[0] = mpath.Path.MOVETO
# kappa = 4.0 * ((np.sqrt(2.0) - 1.0) / 3.0)
# kappa = 0.5
# p0 = vertices[0:-1]
# p1 = vertices[1: ]
# x0 = p0[:, 0:1]
# y0 = p0[:, 1: ]
# b0 = ((y0 - x0) - y0) / ((x0 + y0) - x0)
# a0 = y0 - b0*x0
# x1 = p1[:, 0:1]
# y1 = p1[:, 1: ]
# b1 = ((y1 - x1) - y1) / ((x1 + y1) - x1)
# a1 = y1 - b1*x1
# x = -(a0-a1) / (b0-b1)
# y = a0 + b0*x
# xk = (x - x0) * kappa + x0
# yk = (y - y0) * kappa + y0
# result[1::3, 0:1] = xk
# result[1::3, 1: ] = yk
# xk = (x - x1) * kappa + x1
# yk = (y - y1) * kappa + y1
# result[2::3, 0:1] = xk
# result[2::3, 1: ] = yk
# result[3::3] = p1
# print(vertices[-2:])
# print(result[-2:])
# return mpath.Path(result, codes)
# twopi = 2.0 * np.pi
# halfpi = 0.5 * np.pi
# vertices = path.vertices
# t0 = vertices[0:-1, 0]
# t1 = vertices[1: , 0]
# td = np.where(t1 > t0, t1 - t0, twopi - (t0 - t1))
# maxtd = td.max()
# interpolate = np.ceil(maxtd / halfpi)
# print("interpolate", interpolate)
# if interpolate > 1.0:
# vertices = self.interpolate(vertices, interpolate)
# result = np.zeros((len(vertices) * 3 - 2, 2), float)
# codes = mpath.Path.CURVE4 * np.ones((len(vertices) * 3 - 2, ),
# mpath.Path.code_type)
# result[0] = vertices[0]
# codes[0] = mpath.Path.MOVETO
# kappa = 4.0 * ((np.sqrt(2.0) - 1.0) / 3.0)
# tkappa = np.arctan(kappa)
# hyp_kappa = np.sqrt(kappa*kappa + 1.0)
# t0 = vertices[0:-1, 0]
# t1 = vertices[1: , 0]
# r0 = vertices[0:-1, 1]
# r1 = vertices[1: , 1]
# td = np.where(t1 > t0, t1 - t0, twopi - (t0 - t1))
# td_scaled = td / (np.pi * 0.5)
# rd = r1 - r0
# r0kappa = r0 * kappa * td_scaled
# r1kappa = r1 * kappa * td_scaled
# ravg_kappa = ((r1 + r0) / 2.0) * kappa * td_scaled
# result[1::3, 0] = t0 + (tkappa * td_scaled)
# result[1::3, 1] = r0*hyp_kappa
# # result[1::3, 1] = r0 / np.cos(tkappa * td_scaled)
# # np.sqrt(r0*r0 + ravg_kappa*ravg_kappa)
# result[2::3, 0] = t1 - (tkappa * td_scaled)
# result[2::3, 1] = r1*hyp_kappa
# # result[2::3, 1] = r1 / np.cos(tkappa * td_scaled)
# # np.sqrt(r1*r1 + ravg_kappa*ravg_kappa)
# result[3::3, 0] = t1
# result[3::3, 1] = r1
# print(vertices[:6], result[:6], t0[:6], t1[:6], td[:6],
# td_scaled[:6], tkappa)
# result = self.transform(result)
# return mpath.Path(result, codes)
# transform_path_non_affine = transform_path
| 55,098 | 34.825098 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/projections/geo.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import matplotlib
from matplotlib import rcParams
from matplotlib.axes import Axes
import matplotlib.axis as maxis
from matplotlib.patches import Circle
from matplotlib.path import Path
import matplotlib.spines as mspines
from matplotlib.ticker import (
Formatter, NullLocator, FixedLocator, NullFormatter)
from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
class GeoAxes(Axes):
"""An abstract base class for geographic projections."""
class ThetaFormatter(Formatter):
"""
Used to format the theta tick labels. Converts the native
unit of radians into degrees and adds a degree symbol.
"""
def __init__(self, round_to=1.0):
self._round_to = round_to
def __call__(self, x, pos=None):
degrees = (x / np.pi) * 180.0
degrees = np.round(degrees / self._round_to) * self._round_to
if rcParams['text.usetex'] and not rcParams['text.latex.unicode']:
return r"$%0.0f^\circ$" % degrees
else:
return "%0.0f\N{DEGREE SIGN}" % degrees
RESOLUTION = 75
def _init_axis(self):
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Do not register xaxis or yaxis with spines -- as done in
# Axes._init_axis() -- until GeoAxes.xaxis.cla() works.
# self.spines['geo'].register_axis(self.yaxis)
self._update_transScale()
def cla(self):
Axes.cla(self)
self.set_longitude_grid(30)
self.set_latitude_grid(15)
self.set_longitude_grid_ends(75)
self.xaxis.set_minor_locator(NullLocator())
self.yaxis.set_minor_locator(NullLocator())
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
self.grid(rcParams['axes.grid'])
Axes.set_xlim(self, -np.pi, np.pi)
Axes.set_ylim(self, -np.pi / 2.0, np.pi / 2.0)
def _set_lim_and_transforms(self):
# A (possibly non-linear) projection on the (already scaled) data
self.transProjection = self._get_core_transform(self.RESOLUTION)
self.transAffine = self._get_affine_transform()
self.transAxes = BboxTransformTo(self.bbox)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = \
self.transProjection + \
self.transAffine + \
self.transAxes
# This is the transform for longitude ticks.
self._xaxis_pretransform = \
Affine2D() \
.scale(1, self._longitude_cap * 2) \
.translate(0, -self._longitude_cap)
self._xaxis_transform = \
self._xaxis_pretransform + \
self.transData
self._xaxis_text1_transform = \
Affine2D().scale(1, 0) + \
self.transData + \
Affine2D().translate(0, 4)
self._xaxis_text2_transform = \
Affine2D().scale(1, 0) + \
self.transData + \
Affine2D().translate(0, -4)
# This is the transform for latitude ticks.
yaxis_stretch = Affine2D().scale(np.pi * 2, 1).translate(-np.pi, 0)
yaxis_space = Affine2D().scale(1, 1.1)
self._yaxis_transform = \
yaxis_stretch + \
self.transData
yaxis_text_base = \
yaxis_stretch + \
self.transProjection + \
(yaxis_space + \
self.transAffine + \
self.transAxes)
self._yaxis_text1_transform = \
yaxis_text_base + \
Affine2D().translate(-8, 0)
self._yaxis_text2_transform = \
yaxis_text_base + \
Affine2D().translate(8, 0)
def _get_affine_transform(self):
transform = self._get_core_transform(1)
xscale, _ = transform.transform_point((np.pi, 0))
_, yscale = transform.transform_point((0, np.pi / 2))
return Affine2D() \
.scale(0.5 / xscale, 0.5 / yscale) \
.translate(0.5, 0.5)
def get_xaxis_transform(self,which='grid'):
if which not in ['tick1', 'tick2', 'grid']:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'bottom', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'top', 'center'
def get_yaxis_transform(self,which='grid'):
if which not in ['tick1', 'tick2', 'grid']:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
return self._yaxis_text1_transform, 'center', 'right'
def get_yaxis_text2_transform(self, pad):
return self._yaxis_text2_transform, 'center', 'left'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'geo':mspines.Spine.circular_spine(self,
(0.5, 0.5), 0.5)}
def set_yscale(self, *args, **kwargs):
if args[0] != 'linear':
raise NotImplementedError
set_xscale = set_yscale
def set_xlim(self, *args, **kwargs):
raise TypeError("It is not possible to change axes limits "
"for geographic projections. Please consider "
"using Basemap or Cartopy.")
set_ylim = set_xlim
def format_coord(self, lon, lat):
'return a format string formatting the coordinate'
lon, lat = np.rad2deg([lon, lat])
if lat >= 0.0:
ns = 'N'
else:
ns = 'S'
if lon >= 0.0:
ew = 'E'
else:
ew = 'W'
return ('%f\N{DEGREE SIGN}%s, %f\N{DEGREE SIGN}%s'
% (abs(lat), ns, abs(lon), ew))
def set_longitude_grid(self, degrees):
"""
Set the number of degrees between each longitude grid.
"""
# Skip -180 and 180, which are the fixed limits.
grid = np.arange(-180 + degrees, 180, degrees)
self.xaxis.set_major_locator(FixedLocator(np.deg2rad(grid)))
self.xaxis.set_major_formatter(self.ThetaFormatter(degrees))
def set_latitude_grid(self, degrees):
"""
Set the number of degrees between each latitude grid.
"""
# Skip -90 and 90, which are the fixed limits.
grid = np.arange(-90 + degrees, 90, degrees)
self.yaxis.set_major_locator(FixedLocator(np.deg2rad(grid)))
self.yaxis.set_major_formatter(self.ThetaFormatter(degrees))
def set_longitude_grid_ends(self, degrees):
"""
Set the latitude(s) at which to stop drawing the longitude grids.
"""
self._longitude_cap = np.deg2rad(degrees)
self._xaxis_pretransform \
.clear() \
.scale(1.0, self._longitude_cap * 2.0) \
.translate(0.0, -self._longitude_cap)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself.
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
This axes object does not support interactive zoom box.
"""
return False
def can_pan(self) :
"""
Return *True* if this axes supports the pan/zoom button functionality.
This axes object does not support interactive pan/zoom.
"""
return False
def start_pan(self, x, y, button):
pass
def end_pan(self):
pass
def drag_pan(self, button, key, x, y):
pass
class _GeoTransform(Transform):
# Factoring out some common functionality.
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, resolution):
"""
Create a new geographical transform.
Resolution is the number of steps to interpolate between each input
line segment to approximate its path in curved space.
"""
Transform.__init__(self)
self._resolution = resolution
def __str__(self):
return "{}({})".format(type(self).__name__, self._resolution)
def transform_path_non_affine(self, path):
vertices = path.vertices
ipath = path.interpolated(self._resolution)
return Path(self.transform(ipath.vertices), ipath.codes)
transform_path_non_affine.__doc__ = \
Transform.transform_path_non_affine.__doc__
class AitoffAxes(GeoAxes):
name = 'aitoff'
class AitoffTransform(_GeoTransform):
"""The base Aitoff transform."""
def transform_non_affine(self, ll):
longitude = ll[:, 0]
latitude = ll[:, 1]
# Pre-compute some values
half_long = longitude / 2.0
cos_latitude = np.cos(latitude)
alpha = np.arccos(cos_latitude * np.cos(half_long))
# Avoid divide-by-zero errors using same method as NumPy.
alpha[alpha == 0.0] = 1e-20
# We want unnormalized sinc. numpy.sinc gives us normalized
sinc_alpha = np.sin(alpha) / alpha
xy = np.empty_like(ll, float)
xy[:, 0] = (cos_latitude * np.sin(half_long)) / sinc_alpha
xy[:, 1] = np.sin(latitude) / sinc_alpha
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return AitoffAxes.InvertedAitoffTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedAitoffTransform(_GeoTransform):
def transform_non_affine(self, xy):
# MGDTODO: Math is hard ;(
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return AitoffAxes.AitoffTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.AitoffTransform(resolution)
class HammerAxes(GeoAxes):
name = 'hammer'
class HammerTransform(_GeoTransform):
"""The base Hammer transform."""
def transform_non_affine(self, ll):
longitude = ll[:, 0:1]
latitude = ll[:, 1:2]
# Pre-compute some values
half_long = longitude / 2.0
cos_latitude = np.cos(latitude)
sqrt2 = np.sqrt(2.0)
alpha = np.sqrt(1.0 + cos_latitude * np.cos(half_long))
x = (2.0 * sqrt2) * (cos_latitude * np.sin(half_long)) / alpha
y = (sqrt2 * np.sin(latitude)) / alpha
return np.concatenate((x, y), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return HammerAxes.InvertedHammerTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedHammerTransform(_GeoTransform):
def transform_non_affine(self, xy):
x, y = xy.T
z = np.sqrt(1 - (x / 4) ** 2 - (y / 2) ** 2)
longitude = 2 * np.arctan((z * x) / (2 * (2 * z ** 2 - 1)))
latitude = np.arcsin(y*z)
return np.column_stack([longitude, latitude])
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return HammerAxes.HammerTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.HammerTransform(resolution)
class MollweideAxes(GeoAxes):
name = 'mollweide'
class MollweideTransform(_GeoTransform):
"""The base Mollweide transform."""
def transform_non_affine(self, ll):
def d(theta):
delta = (-(theta + np.sin(theta) - pi_sin_l)
/ (1 + np.cos(theta)))
return delta, np.abs(delta) > 0.001
longitude = ll[:, 0]
latitude = ll[:, 1]
clat = np.pi/2 - np.abs(latitude)
ihigh = clat < 0.087 # within 5 degrees of the poles
ilow = ~ihigh
aux = np.empty(latitude.shape, dtype=float)
if ilow.any(): # Newton-Raphson iteration
pi_sin_l = np.pi * np.sin(latitude[ilow])
theta = 2.0 * latitude[ilow]
delta, large_delta = d(theta)
while np.any(large_delta):
theta[large_delta] += delta[large_delta]
delta, large_delta = d(theta)
aux[ilow] = theta / 2
if ihigh.any(): # Taylor series-based approx. solution
e = clat[ihigh]
d = 0.5 * (3 * np.pi * e**2) ** (1.0/3)
aux[ihigh] = (np.pi/2 - d) * np.sign(latitude[ihigh])
xy = np.empty(ll.shape, dtype=float)
xy[:,0] = (2.0 * np.sqrt(2.0) / np.pi) * longitude * np.cos(aux)
xy[:,1] = np.sqrt(2.0) * np.sin(aux)
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return MollweideAxes.InvertedMollweideTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedMollweideTransform(_GeoTransform):
def transform_non_affine(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:2]
# from Equations (7, 8) of
# http://mathworld.wolfram.com/MollweideProjection.html
theta = np.arcsin(y / np.sqrt(2))
lon = (np.pi / (2 * np.sqrt(2))) * x / np.cos(theta)
lat = np.arcsin((2 * theta + np.sin(2 * theta)) / np.pi)
return np.concatenate((lon, lat), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return MollweideAxes.MollweideTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.MollweideTransform(resolution)
class LambertAxes(GeoAxes):
name = 'lambert'
class LambertTransform(_GeoTransform):
"""The base Lambert transform."""
def __init__(self, center_longitude, center_latitude, resolution):
"""
Create a new Lambert transform. Resolution is the number of steps
to interpolate between each input line segment to approximate its
path in curved Lambert space.
"""
_GeoTransform.__init__(self, resolution)
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def transform_non_affine(self, ll):
longitude = ll[:, 0:1]
latitude = ll[:, 1:2]
clong = self._center_longitude
clat = self._center_latitude
cos_lat = np.cos(latitude)
sin_lat = np.sin(latitude)
diff_long = longitude - clong
cos_diff_long = np.cos(diff_long)
inner_k = (1.0 +
np.sin(clat)*sin_lat +
np.cos(clat)*cos_lat*cos_diff_long)
# Prevent divide-by-zero problems
inner_k = np.where(inner_k == 0.0, 1e-15, inner_k)
k = np.sqrt(2.0 / inner_k)
x = k*cos_lat*np.sin(diff_long)
y = k*(np.cos(clat)*sin_lat -
np.sin(clat)*cos_lat*cos_diff_long)
return np.concatenate((x, y), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return LambertAxes.InvertedLambertTransform(
self._center_longitude,
self._center_latitude,
self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedLambertTransform(_GeoTransform):
def __init__(self, center_longitude, center_latitude, resolution):
_GeoTransform.__init__(self, resolution)
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def transform_non_affine(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:2]
clong = self._center_longitude
clat = self._center_latitude
p = np.sqrt(x*x + y*y)
p = np.where(p == 0.0, 1e-9, p)
c = 2.0 * np.arcsin(0.5 * p)
sin_c = np.sin(c)
cos_c = np.cos(c)
lat = np.arcsin(cos_c*np.sin(clat) +
((y*sin_c*np.cos(clat)) / p))
lon = clong + np.arctan(
(x*sin_c) / (p*np.cos(clat)*cos_c - y*np.sin(clat)*sin_c))
return np.concatenate((lon, lat), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return LambertAxes.LambertTransform(
self._center_longitude,
self._center_latitude,
self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
self._center_longitude = kwargs.pop("center_longitude", 0.0)
self._center_latitude = kwargs.pop("center_latitude", 0.0)
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
def cla(self):
GeoAxes.cla(self)
self.yaxis.set_major_formatter(NullFormatter())
def _get_core_transform(self, resolution):
return self.LambertTransform(
self._center_longitude,
self._center_latitude,
resolution)
def _get_affine_transform(self):
return Affine2D() \
.scale(0.25) \
.translate(0.5, 0.5)
| 19,032 | 33.731752 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/projections/__init__.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from .geo import AitoffAxes, HammerAxes, LambertAxes, MollweideAxes
from .polar import PolarAxes
from matplotlib import axes
class ProjectionRegistry(object):
"""
Manages the set of projections available to the system.
"""
def __init__(self):
self._all_projection_types = {}
def register(self, *projections):
"""
Register a new set of projection(s).
"""
for projection in projections:
name = projection.name
self._all_projection_types[name] = projection
def get_projection_class(self, name):
"""
Get a projection class from its *name*.
"""
return self._all_projection_types[name]
def get_projection_names(self):
"""
Get a list of the names of all projections currently
registered.
"""
return sorted(self._all_projection_types)
projection_registry = ProjectionRegistry()
projection_registry.register(
axes.Axes,
PolarAxes,
AitoffAxes,
HammerAxes,
LambertAxes,
MollweideAxes)
def register_projection(cls):
projection_registry.register(cls)
def get_projection_class(projection=None):
"""
Get a projection class from its name.
If *projection* is None, a standard rectilinear projection is
returned.
"""
if projection is None:
projection = 'rectilinear'
try:
return projection_registry.get_projection_class(projection)
except KeyError:
raise ValueError("Unknown projection '%s'" % projection)
def process_projection_requirements(figure, *args, **kwargs):
"""
Handle the args/kwargs to for add_axes/add_subplot/gca,
returning::
(axes_proj_class, proj_class_kwargs, proj_stack_key)
Which can be used for new axes initialization/identification.
.. note:: **kwargs** is modified in place.
"""
ispolar = kwargs.pop('polar', False)
projection = kwargs.pop('projection', None)
if ispolar:
if projection is not None and projection != 'polar':
raise ValueError(
"polar=True, yet projection=%r. "
"Only one of these arguments should be supplied." %
projection)
projection = 'polar'
if isinstance(projection, six.string_types) or projection is None:
projection_class = get_projection_class(projection)
elif hasattr(projection, '_as_mpl_axes'):
projection_class, extra_kwargs = projection._as_mpl_axes()
kwargs.update(**extra_kwargs)
else:
raise TypeError('projection must be a string, None or implement a '
'_as_mpl_axes method. Got %r' % projection)
# Make the key without projection kwargs, this is used as a unique
# lookup for axes instances
key = figure._make_key(*args, **kwargs)
return projection_class, kwargs, key
def get_projection_names():
"""
Get a list of acceptable projection names.
"""
return projection_registry.get_projection_names()
| 3,152 | 27.405405 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_ticker.py | from __future__ import absolute_import, division, print_function
from numpy.testing import assert_almost_equal
import numpy as np
import pytest
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import warnings
class TestMaxNLocator(object):
basic_data = [
(20, 100, np.array([20., 40., 60., 80., 100.])),
(0.001, 0.0001, np.array([0., 0.0002, 0.0004, 0.0006, 0.0008, 0.001])),
(-1e15, 1e15, np.array([-1.0e+15, -5.0e+14, 0e+00, 5e+14, 1.0e+15])),
]
integer_data = [
(-0.1, 1.1, None, np.array([-1, 0, 1, 2])),
(-0.1, 0.95, None, np.array([-0.25, 0, 0.25, 0.5, 0.75, 1.0])),
(1, 55, [1, 1.5, 5, 6, 10], np.array([0, 15, 30, 45, 60])),
]
@pytest.mark.parametrize('vmin, vmax, expected', basic_data)
def test_basic(self, vmin, vmax, expected):
loc = mticker.MaxNLocator(nbins=5)
assert_almost_equal(loc.tick_values(vmin, vmax), expected)
@pytest.mark.parametrize('vmin, vmax, steps, expected', integer_data)
def test_integer(self, vmin, vmax, steps, expected):
loc = mticker.MaxNLocator(nbins=5, integer=True, steps=steps)
assert_almost_equal(loc.tick_values(vmin, vmax), expected)
class TestLinearLocator(object):
def test_basic(self):
loc = mticker.LinearLocator(numticks=3)
test_value = np.array([-0.8, -0.3, 0.2])
assert_almost_equal(loc.tick_values(-0.8, 0.2), test_value)
def test_set_params(self):
"""
Create linear locator with presets={}, numticks=2 and change it to
something else. See if change was successful. Should not exception.
"""
loc = mticker.LinearLocator(numticks=2)
loc.set_params(numticks=8, presets={(0, 1): []})
assert loc.numticks == 8
assert loc.presets == {(0, 1): []}
class TestMultipleLocator(object):
def test_basic(self):
loc = mticker.MultipleLocator(base=3.147)
test_value = np.array([-9.441, -6.294, -3.147, 0., 3.147, 6.294,
9.441, 12.588])
assert_almost_equal(loc.tick_values(-7, 10), test_value)
def test_set_params(self):
"""
Create multiple locator with 0.7 base, and change it to something else.
See if change was successful.
"""
mult = mticker.MultipleLocator(base=0.7)
mult.set_params(base=1.7)
assert mult._base == 1.7
class TestAutoMinorLocator(object):
def test_basic(self):
fig, ax = plt.subplots()
ax.set_xlim(0, 1.39)
ax.minorticks_on()
test_value = np.array([0.05, 0.1, 0.15, 0.25, 0.3, 0.35, 0.45,
0.5, 0.55, 0.65, 0.7, 0.75, 0.85, 0.9,
0.95, 1, 1.05, 1.1, 1.15, 1.25, 1.3, 1.35])
assert_almost_equal(ax.xaxis.get_ticklocs(minor=True), test_value)
# NB: the following values are assuming that *xlim* is [0, 5]
params = [
(0, 0), # no major tick => no minor tick either
(1, 0), # a single major tick => no minor tick
(2, 4), # 1 "nice" major step => 1*5 minor **divisions**
(3, 6) # 2 "not nice" major steps => 2*4 minor **divisions**
]
@pytest.mark.parametrize('nb_majorticks, expected_nb_minorticks', params)
def test_low_number_of_majorticks(
self, nb_majorticks, expected_nb_minorticks):
# This test is related to issue #8804
fig, ax = plt.subplots()
xlims = (0, 5) # easier to test the different code paths
ax.set_xlim(*xlims)
ax.set_xticks(np.linspace(xlims[0], xlims[1], nb_majorticks))
ax.minorticks_on()
ax.xaxis.set_minor_locator(mticker.AutoMinorLocator())
assert len(ax.xaxis.get_minorticklocs()) == expected_nb_minorticks
class TestLogLocator(object):
def test_basic(self):
loc = mticker.LogLocator(numticks=5)
with pytest.raises(ValueError):
loc.tick_values(0, 1000)
test_value = np.array([1.00000000e-05, 1.00000000e-03, 1.00000000e-01,
1.00000000e+01, 1.00000000e+03, 1.00000000e+05,
1.00000000e+07, 1.000000000e+09])
assert_almost_equal(loc.tick_values(0.001, 1.1e5), test_value)
loc = mticker.LogLocator(base=2)
test_value = np.array([0.5, 1., 2., 4., 8., 16., 32., 64., 128., 256.])
assert_almost_equal(loc.tick_values(1, 100), test_value)
def test_set_params(self):
"""
Create log locator with default value, base=10.0, subs=[1.0],
numdecs=4, numticks=15 and change it to something else.
See if change was successful. Should not raise exception.
"""
loc = mticker.LogLocator()
loc.set_params(numticks=7, numdecs=8, subs=[2.0], base=4)
assert loc.numticks == 7
assert loc.numdecs == 8
assert loc._base == 4
assert list(loc._subs) == [2.0]
class TestNullLocator(object):
def test_set_params(self):
"""
Create null locator, and attempt to call set_params() on it.
Should not exception, and should raise a warning.
"""
loc = mticker.NullLocator()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
loc.set_params()
assert len(w) == 1
class TestLogitLocator(object):
def test_set_params(self):
"""
Create logit locator with default minor=False, and change it to
something else. See if change was successful. Should not exception.
"""
loc = mticker.LogitLocator() # Defaults to false.
loc.set_params(minor=True)
assert loc.minor
class TestFixedLocator(object):
def test_set_params(self):
"""
Create fixed locator with 5 nbins, and change it to something else.
See if change was successful.
Should not exception.
"""
fixed = mticker.FixedLocator(range(0, 24), nbins=5)
fixed.set_params(nbins=7)
assert fixed.nbins == 7
class TestIndexLocator(object):
def test_set_params(self):
"""
Create index locator with 3 base, 4 offset. and change it to something
else. See if change was successful.
Should not exception.
"""
index = mticker.IndexLocator(base=3, offset=4)
index.set_params(base=7, offset=7)
assert index._base == 7
assert index.offset == 7
class TestSymmetricalLogLocator(object):
def test_set_params(self):
"""
Create symmetrical log locator with default subs =[1.0] numticks = 15,
and change it to something else.
See if change was successful.
Should not exception.
"""
sym = mticker.SymmetricalLogLocator(base=10, linthresh=1)
sym.set_params(subs=[2.0], numticks=8)
assert sym._subs == [2.0]
assert sym.numticks == 8
class TestScalarFormatter(object):
offset_data = [
(123, 189, 0),
(-189, -123, 0),
(12341, 12349, 12340),
(-12349, -12341, -12340),
(99999.5, 100010.5, 100000),
(-100010.5, -99999.5, -100000),
(99990.5, 100000.5, 100000),
(-100000.5, -99990.5, -100000),
(1233999, 1234001, 1234000),
(-1234001, -1233999, -1234000),
(1, 1, 1),
(123, 123, 120),
# Test cases courtesy of @WeatherGod
(.4538, .4578, .45),
(3789.12, 3783.1, 3780),
(45124.3, 45831.75, 45000),
(0.000721, 0.0007243, 0.00072),
(12592.82, 12591.43, 12590),
(9., 12., 0),
(900., 1200., 0),
(1900., 1200., 0),
(0.99, 1.01, 1),
(9.99, 10.01, 10),
(99.99, 100.01, 100),
(5.99, 6.01, 6),
(15.99, 16.01, 16),
(-0.452, 0.492, 0),
(-0.492, 0.492, 0),
(12331.4, 12350.5, 12300),
(-12335.3, 12335.3, 0),
]
use_offset_data = [True, False]
@pytest.mark.parametrize('left, right, offset', offset_data)
def test_offset_value(self, left, right, offset):
fig, ax = plt.subplots()
formatter = ax.get_xaxis().get_major_formatter()
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', 'Attempting to set identical',
UserWarning)
ax.set_xlim(left, right)
assert len(w) == (1 if left == right else 0)
# Update ticks.
next(ax.get_xaxis().iter_ticks())
assert formatter.offset == offset
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', 'Attempting to set identical',
UserWarning)
ax.set_xlim(right, left)
assert len(w) == (1 if left == right else 0)
# Update ticks.
next(ax.get_xaxis().iter_ticks())
assert formatter.offset == offset
@pytest.mark.parametrize('use_offset', use_offset_data)
def test_use_offset(self, use_offset):
with matplotlib.rc_context({'axes.formatter.useoffset': use_offset}):
tmp_form = mticker.ScalarFormatter()
assert use_offset == tmp_form.get_useOffset()
class FakeAxis(object):
"""Allow Formatter to be called without having a "full" plot set up."""
def __init__(self, vmin=1, vmax=10):
self.vmin = vmin
self.vmax = vmax
def get_view_interval(self):
return self.vmin, self.vmax
class TestLogFormatterExponent(object):
param_data = [
(True, 4, np.arange(-3, 4.0), np.arange(-3, 4.0),
['-3', '-2', '-1', '0', '1', '2', '3']),
# With labelOnlyBase=False, non-integer powers should be nicely
# formatted.
(False, 10, np.array([0.1, 0.00001, np.pi, 0.2, -0.2, -0.00001]),
range(6), ['0.1', '1e-05', '3.14', '0.2', '-0.2', '-1e-05']),
(False, 50, np.array([3, 5, 12, 42], dtype='float'), range(6),
['3', '5', '12', '42']),
]
base_data = [2.0, 5.0, 10.0, np.pi, np.e]
@pytest.mark.parametrize(
'labelOnlyBase, exponent, locs, positions, expected', param_data)
@pytest.mark.parametrize('base', base_data)
def test_basic(self, labelOnlyBase, base, exponent, locs, positions,
expected):
formatter = mticker.LogFormatterExponent(base=base,
labelOnlyBase=labelOnlyBase)
formatter.axis = FakeAxis(1, base**exponent)
vals = base**locs
labels = [formatter(x, pos) for (x, pos) in zip(vals, positions)]
assert labels == expected
def test_blank(self):
# Should be a blank string for non-integer powers if labelOnlyBase=True
formatter = mticker.LogFormatterExponent(base=10, labelOnlyBase=True)
formatter.axis = FakeAxis()
assert formatter(10**0.1) == ''
class TestLogFormatterMathtext():
fmt = mticker.LogFormatterMathtext()
test_data = [
(0, 1, '$\\mathdefault{10^{0}}$'),
(0, 1e-2, '$\\mathdefault{10^{-2}}$'),
(0, 1e2, '$\\mathdefault{10^{2}}$'),
(3, 1, '$\\mathdefault{1}$'),
(3, 1e-2, '$\\mathdefault{0.01}$'),
(3, 1e2, '$\\mathdefault{100}$'),
(3, 1e-3, '$\\mathdefault{10^{-3}}$'),
(3, 1e3, '$\\mathdefault{10^{3}}$'),
]
@pytest.mark.parametrize('min_exponent, value, expected', test_data)
def test_min_exponent(self, min_exponent, value, expected):
with matplotlib.rc_context({'axes.formatter.min_exponent':
min_exponent}):
assert self.fmt(value) == expected
class TestLogFormatterSciNotation(object):
test_data = [
(2, 0.03125, '$\\mathdefault{2^{-5}}$'),
(2, 1, '$\\mathdefault{2^{0}}$'),
(2, 32, '$\\mathdefault{2^{5}}$'),
(2, 0.0375, '$\\mathdefault{1.2\\times2^{-5}}$'),
(2, 1.2, '$\\mathdefault{1.2\\times2^{0}}$'),
(2, 38.4, '$\\mathdefault{1.2\\times2^{5}}$'),
(10, -1, '$\\mathdefault{-10^{0}}$'),
(10, 1e-05, '$\\mathdefault{10^{-5}}$'),
(10, 1, '$\\mathdefault{10^{0}}$'),
(10, 100000, '$\\mathdefault{10^{5}}$'),
(10, 2e-05, '$\\mathdefault{2\\times10^{-5}}$'),
(10, 2, '$\\mathdefault{2\\times10^{0}}$'),
(10, 200000, '$\\mathdefault{2\\times10^{5}}$'),
(10, 5e-05, '$\\mathdefault{5\\times10^{-5}}$'),
(10, 5, '$\\mathdefault{5\\times10^{0}}$'),
(10, 500000, '$\\mathdefault{5\\times10^{5}}$'),
]
@pytest.mark.style('default')
@pytest.mark.parametrize('base, value, expected', test_data)
def test_basic(self, base, value, expected):
formatter = mticker.LogFormatterSciNotation(base=base)
formatter.sublabel = {1, 2, 5, 1.2}
with matplotlib.rc_context({'text.usetex': False}):
assert formatter(value) == expected
class TestLogFormatter(object):
pprint_data = [
(3.141592654e-05, 0.001, '3.142e-5'),
(0.0003141592654, 0.001, '3.142e-4'),
(0.003141592654, 0.001, '3.142e-3'),
(0.03141592654, 0.001, '3.142e-2'),
(0.3141592654, 0.001, '3.142e-1'),
(3.141592654, 0.001, '3.142'),
(31.41592654, 0.001, '3.142e1'),
(314.1592654, 0.001, '3.142e2'),
(3141.592654, 0.001, '3.142e3'),
(31415.92654, 0.001, '3.142e4'),
(314159.2654, 0.001, '3.142e5'),
(1e-05, 0.001, '1e-5'),
(0.0001, 0.001, '1e-4'),
(0.001, 0.001, '1e-3'),
(0.01, 0.001, '1e-2'),
(0.1, 0.001, '1e-1'),
(1, 0.001, '1'),
(10, 0.001, '10'),
(100, 0.001, '100'),
(1000, 0.001, '1000'),
(10000, 0.001, '1e4'),
(100000, 0.001, '1e5'),
(3.141592654e-05, 0.015, '0'),
(0.0003141592654, 0.015, '0'),
(0.003141592654, 0.015, '0.003'),
(0.03141592654, 0.015, '0.031'),
(0.3141592654, 0.015, '0.314'),
(3.141592654, 0.015, '3.142'),
(31.41592654, 0.015, '31.416'),
(314.1592654, 0.015, '314.159'),
(3141.592654, 0.015, '3141.593'),
(31415.92654, 0.015, '31415.927'),
(314159.2654, 0.015, '314159.265'),
(1e-05, 0.015, '0'),
(0.0001, 0.015, '0'),
(0.001, 0.015, '0.001'),
(0.01, 0.015, '0.01'),
(0.1, 0.015, '0.1'),
(1, 0.015, '1'),
(10, 0.015, '10'),
(100, 0.015, '100'),
(1000, 0.015, '1000'),
(10000, 0.015, '10000'),
(100000, 0.015, '100000'),
(3.141592654e-05, 0.5, '0'),
(0.0003141592654, 0.5, '0'),
(0.003141592654, 0.5, '0.003'),
(0.03141592654, 0.5, '0.031'),
(0.3141592654, 0.5, '0.314'),
(3.141592654, 0.5, '3.142'),
(31.41592654, 0.5, '31.416'),
(314.1592654, 0.5, '314.159'),
(3141.592654, 0.5, '3141.593'),
(31415.92654, 0.5, '31415.927'),
(314159.2654, 0.5, '314159.265'),
(1e-05, 0.5, '0'),
(0.0001, 0.5, '0'),
(0.001, 0.5, '0.001'),
(0.01, 0.5, '0.01'),
(0.1, 0.5, '0.1'),
(1, 0.5, '1'),
(10, 0.5, '10'),
(100, 0.5, '100'),
(1000, 0.5, '1000'),
(10000, 0.5, '10000'),
(100000, 0.5, '100000'),
(3.141592654e-05, 5, '0'),
(0.0003141592654, 5, '0'),
(0.003141592654, 5, '0'),
(0.03141592654, 5, '0.03'),
(0.3141592654, 5, '0.31'),
(3.141592654, 5, '3.14'),
(31.41592654, 5, '31.42'),
(314.1592654, 5, '314.16'),
(3141.592654, 5, '3141.59'),
(31415.92654, 5, '31415.93'),
(314159.2654, 5, '314159.27'),
(1e-05, 5, '0'),
(0.0001, 5, '0'),
(0.001, 5, '0'),
(0.01, 5, '0.01'),
(0.1, 5, '0.1'),
(1, 5, '1'),
(10, 5, '10'),
(100, 5, '100'),
(1000, 5, '1000'),
(10000, 5, '10000'),
(100000, 5, '100000'),
(3.141592654e-05, 100, '0'),
(0.0003141592654, 100, '0'),
(0.003141592654, 100, '0'),
(0.03141592654, 100, '0'),
(0.3141592654, 100, '0.3'),
(3.141592654, 100, '3.1'),
(31.41592654, 100, '31.4'),
(314.1592654, 100, '314.2'),
(3141.592654, 100, '3141.6'),
(31415.92654, 100, '31415.9'),
(314159.2654, 100, '314159.3'),
(1e-05, 100, '0'),
(0.0001, 100, '0'),
(0.001, 100, '0'),
(0.01, 100, '0'),
(0.1, 100, '0.1'),
(1, 100, '1'),
(10, 100, '10'),
(100, 100, '100'),
(1000, 100, '1000'),
(10000, 100, '10000'),
(100000, 100, '100000'),
(3.141592654e-05, 1000000.0, '3.1e-5'),
(0.0003141592654, 1000000.0, '3.1e-4'),
(0.003141592654, 1000000.0, '3.1e-3'),
(0.03141592654, 1000000.0, '3.1e-2'),
(0.3141592654, 1000000.0, '3.1e-1'),
(3.141592654, 1000000.0, '3.1'),
(31.41592654, 1000000.0, '3.1e1'),
(314.1592654, 1000000.0, '3.1e2'),
(3141.592654, 1000000.0, '3.1e3'),
(31415.92654, 1000000.0, '3.1e4'),
(314159.2654, 1000000.0, '3.1e5'),
(1e-05, 1000000.0, '1e-5'),
(0.0001, 1000000.0, '1e-4'),
(0.001, 1000000.0, '1e-3'),
(0.01, 1000000.0, '1e-2'),
(0.1, 1000000.0, '1e-1'),
(1, 1000000.0, '1'),
(10, 1000000.0, '10'),
(100, 1000000.0, '100'),
(1000, 1000000.0, '1000'),
(10000, 1000000.0, '1e4'),
(100000, 1000000.0, '1e5'),
]
@pytest.mark.parametrize('value, domain, expected', pprint_data)
def test_pprint(self, value, domain, expected):
fmt = mticker.LogFormatter()
label = fmt.pprint_val(value, domain)
assert label == expected
def _sub_labels(self, axis, subs=()):
"Test whether locator marks subs to be labeled"
fmt = axis.get_minor_formatter()
minor_tlocs = axis.get_minorticklocs()
fmt.set_locs(minor_tlocs)
coefs = minor_tlocs / 10**(np.floor(np.log10(minor_tlocs)))
label_expected = [np.round(c) in subs for c in coefs]
label_test = [fmt(x) != '' for x in minor_tlocs]
assert label_test == label_expected
@pytest.mark.style('default')
def test_sublabel(self):
# test label locator
fig, ax = plt.subplots()
ax.set_xscale('log')
ax.xaxis.set_major_locator(mticker.LogLocator(base=10, subs=[]))
ax.xaxis.set_minor_locator(mticker.LogLocator(base=10,
subs=np.arange(2, 10)))
ax.xaxis.set_major_formatter(mticker.LogFormatter(labelOnlyBase=True))
ax.xaxis.set_minor_formatter(mticker.LogFormatter(labelOnlyBase=False))
# axis range above 3 decades, only bases are labeled
ax.set_xlim(1, 1e4)
fmt = ax.xaxis.get_major_formatter()
fmt.set_locs(ax.xaxis.get_majorticklocs())
show_major_labels = [fmt(x) != ''
for x in ax.xaxis.get_majorticklocs()]
assert np.all(show_major_labels)
self._sub_labels(ax.xaxis, subs=[])
# For the next two, if the numdec threshold in LogFormatter.set_locs
# were 3, then the label sub would be 3 for 2-3 decades and (2,5)
# for 1-2 decades. With a threshold of 1, subs are not labeled.
# axis range at 2 to 3 decades
ax.set_xlim(1, 800)
self._sub_labels(ax.xaxis, subs=[])
# axis range at 1 to 2 decades
ax.set_xlim(1, 80)
self._sub_labels(ax.xaxis, subs=[])
# axis range at 0.4 to 1 decades, label subs 2, 3, 4, 6
ax.set_xlim(1, 8)
self._sub_labels(ax.xaxis, subs=[2, 3, 4, 6])
# axis range at 0 to 0.4 decades, label all
ax.set_xlim(0.5, 0.9)
self._sub_labels(ax.xaxis, subs=np.arange(2, 10, dtype=int))
@pytest.mark.parametrize('val', [1, 10, 100, 1000])
def test_LogFormatter_call(self, val):
# test _num_to_string method used in __call__
temp_lf = mticker.LogFormatter()
temp_lf.axis = FakeAxis()
assert temp_lf(val) == str(val)
class TestFormatStrFormatter(object):
def test_basic(self):
# test % style formatter
tmp_form = mticker.FormatStrFormatter('%05d')
assert '00002' == tmp_form(2)
class TestStrMethodFormatter(object):
test_data = [
('{x:05d}', (2,), '00002'),
('{x:03d}-{pos:02d}', (2, 1), '002-01'),
]
@pytest.mark.parametrize('format, input, expected', test_data)
def test_basic(self, format, input, expected):
fmt = mticker.StrMethodFormatter(format)
assert fmt(*input) == expected
class TestEngFormatter(object):
# (input, expected) where ''expected'' corresponds to the outputs
# respectively returned when (places=None, places=0, places=2)
raw_format_data = [
(-1234.56789, ('-1.23457 k', '-1 k', '-1.23 k')),
(-1.23456789, ('-1.23457', '-1', '-1.23')),
(-0.123456789, ('-123.457 m', '-123 m', '-123.46 m')),
(-0.00123456789, ('-1.23457 m', '-1 m', '-1.23 m')),
(-0.0, ('0', '0', '0.00')),
(-0, ('0', '0', '0.00')),
(0, ('0', '0', '0.00')),
(1.23456789e-6, (u'1.23457 \u03bc', u'1 \u03bc', u'1.23 \u03bc')),
(0.123456789, ('123.457 m', '123 m', '123.46 m')),
(0.1, ('100 m', '100 m', '100.00 m')),
(1, ('1', '1', '1.00')),
(1.23456789, ('1.23457', '1', '1.23')),
(999.9, ('999.9', '1 k', '999.90')), # places=0: corner-case rounding
(999.9999, ('1 k', '1 k', '1.00 k')), # corner-case roudning for all
(1000, ('1 k', '1 k', '1.00 k')),
(1001, ('1.001 k', '1 k', '1.00 k')),
(100001, ('100.001 k', '100 k', '100.00 k')),
(987654.321, ('987.654 k', '988 k', '987.65 k')),
(1.23e27, ('1230 Y', '1230 Y', '1230.00 Y')) # OoR value (> 1000 Y)
]
@pytest.mark.parametrize('input, expected', raw_format_data)
def test_params(self, input, expected):
"""
Test the formatting of EngFormatter for various values of the 'places'
argument, in several cases:
0. without a unit symbol but with a (default) space separator;
1. with both a unit symbol and a (default) space separator;
2. with both a unit symbol and some non default separators;
3. without a unit symbol but with some non default separators.
Note that cases 2. and 3. are looped over several separator strings.
"""
UNIT = 's' # seconds
DIGITS = '0123456789' # %timeit showed 10-20% faster search than set
# Case 0: unit='' (default) and sep=' ' (default).
# 'expected' already corresponds to this reference case.
exp_outputs = expected
formatters = (
mticker.EngFormatter(), # places=None (default)
mticker.EngFormatter(places=0),
mticker.EngFormatter(places=2)
)
for _formatter, _exp_output in zip(formatters, exp_outputs):
assert _formatter(input) == _exp_output
# Case 1: unit=UNIT and sep=' ' (default).
# Append a unit symbol to the reference case.
# Beware of the values in [1, 1000), where there is no prefix!
exp_outputs = (_s + " " + UNIT if _s[-1] in DIGITS # case w/o prefix
else _s + UNIT for _s in expected)
formatters = (
mticker.EngFormatter(unit=UNIT), # places=None (default)
mticker.EngFormatter(unit=UNIT, places=0),
mticker.EngFormatter(unit=UNIT, places=2)
)
for _formatter, _exp_output in zip(formatters, exp_outputs):
assert _formatter(input) == _exp_output
# Test several non default separators: no separator, a narrow
# no-break space (unicode character) and an extravagant string.
for _sep in ("", "\N{NARROW NO-BREAK SPACE}", "@_@"):
# Case 2: unit=UNIT and sep=_sep.
# Replace the default space separator from the reference case
# with the tested one `_sep` and append a unit symbol to it.
exp_outputs = (_s + _sep + UNIT if _s[-1] in DIGITS # no prefix
else _s.replace(" ", _sep) + UNIT
for _s in expected)
formatters = (
mticker.EngFormatter(unit=UNIT, sep=_sep), # places=None
mticker.EngFormatter(unit=UNIT, places=0, sep=_sep),
mticker.EngFormatter(unit=UNIT, places=2, sep=_sep)
)
for _formatter, _exp_output in zip(formatters, exp_outputs):
assert _formatter(input) == _exp_output
# Case 3: unit='' (default) and sep=_sep.
# Replace the default space separator from the reference case
# with the tested one `_sep`. Reference case is already unitless.
exp_outputs = (_s.replace(" ", _sep) for _s in expected)
formatters = (
mticker.EngFormatter(sep=_sep), # places=None (default)
mticker.EngFormatter(places=0, sep=_sep),
mticker.EngFormatter(places=2, sep=_sep)
)
for _formatter, _exp_output in zip(formatters, exp_outputs):
assert _formatter(input) == _exp_output
class TestPercentFormatter(object):
percent_data = [
# Check explicitly set decimals over different intervals and values
(100, 0, '%', 120, 100, '120%'),
(100, 0, '%', 100, 90, '100%'),
(100, 0, '%', 90, 50, '90%'),
(100, 0, '%', -1.7, 40, '-2%'),
(100, 1, '%', 90.0, 100, '90.0%'),
(100, 1, '%', 80.1, 90, '80.1%'),
(100, 1, '%', 70.23, 50, '70.2%'),
# 60.554 instead of 60.55: see https://bugs.python.org/issue5118
(100, 1, '%', -60.554, 40, '-60.6%'),
# Check auto decimals over different intervals and values
(100, None, '%', 95, 1, '95.00%'),
(1.0, None, '%', 3, 6, '300%'),
(17.0, None, '%', 1, 8.5, '6%'),
(17.0, None, '%', 1, 8.4, '5.9%'),
(5, None, '%', -100, 0.000001, '-2000.00000%'),
# Check percent symbol
(1.0, 2, None, 1.2, 100, '120.00'),
(75, 3, '', 50, 100, '66.667'),
(42, None, '^^Foobar$$', 21, 12, '50.0^^Foobar$$'),
]
percent_ids = [
# Check explicitly set decimals over different intervals and values
'decimals=0, x>100%',
'decimals=0, x=100%',
'decimals=0, x<100%',
'decimals=0, x<0%',
'decimals=1, x>100%',
'decimals=1, x=100%',
'decimals=1, x<100%',
'decimals=1, x<0%',
# Check auto decimals over different intervals and values
'autodecimal, x<100%, display_range=1',
'autodecimal, x>100%, display_range=6 (custom xmax test)',
'autodecimal, x<100%, display_range=8.5 (autodecimal test 1)',
'autodecimal, x<100%, display_range=8.4 (autodecimal test 2)',
'autodecimal, x<-100%, display_range=1e-6 (tiny display range)',
# Check percent symbol
'None as percent symbol',
'Empty percent symbol',
'Custom percent symbol',
]
latex_data = [
(False, False, r'50\{t}%'),
(False, True, r'50\\\{t\}\%'),
(True, False, r'50\{t}%'),
(True, True, r'50\{t}%'),
]
@pytest.mark.parametrize(
'xmax, decimals, symbol, x, display_range, expected',
percent_data, ids=percent_ids)
def test_basic(self, xmax, decimals, symbol,
x, display_range, expected):
formatter = mticker.PercentFormatter(xmax, decimals, symbol)
with matplotlib.rc_context(rc={'text.usetex': False}):
assert formatter.format_pct(x, display_range) == expected
@pytest.mark.parametrize('is_latex, usetex, expected', latex_data)
def test_latex(self, is_latex, usetex, expected):
fmt = mticker.PercentFormatter(symbol='\\{t}%', is_latex=is_latex)
with matplotlib.rc_context(rc={'text.usetex': usetex}):
assert fmt.format_pct(50, 100) == expected
| 28,203 | 37.582763 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_category.py | # -*- coding: utf-8 -*-
"""Catch all for categorical functions"""
from __future__ import absolute_import, division, print_function
import pytest
import numpy as np
from matplotlib.axes import Axes
import matplotlib.pyplot as plt
import matplotlib.category as cat
# Python2/3 text handling
_to_str = cat.StrCategoryFormatter._text
class TestUnitData(object):
test_cases = [('single', (["hello world"], [0])),
('unicode', (["Здравствуйте мир"], [0])),
('mixed', (['A', "np.nan", 'B', "3.14", "мир"],
[0, 1, 2, 3, 4]))]
ids, data = zip(*test_cases)
@pytest.mark.parametrize("data, locs", data, ids=ids)
def test_unit(self, data, locs):
unit = cat.UnitData(data)
assert list(unit._mapping.keys()) == data
assert list(unit._mapping.values()) == locs
def test_update(self):
data = ['a', 'd']
locs = [0, 1]
data_update = ['b', 'd', 'e']
unique_data = ['a', 'd', 'b', 'e']
updated_locs = [0, 1, 2, 3]
unit = cat.UnitData(data)
assert list(unit._mapping.keys()) == data
assert list(unit._mapping.values()) == locs
unit.update(data_update)
assert list(unit._mapping.keys()) == unique_data
assert list(unit._mapping.values()) == updated_locs
failing_test_cases = [("number", 3.14), ("nan", np.nan),
("list", [3.14, 12]), ("mixed type", ["A", 2])]
fids, fdata = zip(*test_cases)
@pytest.mark.parametrize("fdata", fdata, ids=fids)
def test_non_string_fails(self, fdata):
with pytest.raises(TypeError):
cat.UnitData(fdata)
@pytest.mark.parametrize("fdata", fdata, ids=fids)
def test_non_string_update_fails(self, fdata):
unitdata = cat.UnitData()
with pytest.raises(TypeError):
unitdata.update(fdata)
class FakeAxis(object):
def __init__(self, units):
self.units = units
class TestStrCategoryConverter(object):
"""Based on the pandas conversion and factorization tests:
ref: /pandas/tseries/tests/test_converter.py
/pandas/tests/test_algos.py:TestFactorize
"""
test_cases = [("unicode", ["Здравствуйте мир"]),
("ascii", ["hello world"]),
("single", ['a', 'b', 'c']),
("integer string", ["1", "2"]),
("single + values>10", ["A", "B", "C", "D", "E", "F", "G",
"H", "I", "J", "K", "L", "M", "N",
"O", "P", "Q", "R", "S", "T", "U",
"V", "W", "X", "Y", "Z"])]
ids, values = zip(*test_cases)
failing_test_cases = [("mixed", [3.14, 'A', np.inf]),
("string integer", ['42', 42])]
fids, fvalues = zip(*failing_test_cases)
@pytest.fixture(autouse=True)
def mock_axis(self, request):
self.cc = cat.StrCategoryConverter()
# self.unit should be probably be replaced with real mock unit
self.unit = cat.UnitData()
self.ax = FakeAxis(self.unit)
@pytest.mark.parametrize("vals", values, ids=ids)
def test_convert(self, vals):
np.testing.assert_allclose(self.cc.convert(vals, self.ax.units,
self.ax),
range(len(vals)))
@pytest.mark.parametrize("value", ["hi", "мир"], ids=["ascii", "unicode"])
def test_convert_one_string(self, value):
assert self.cc.convert(value, self.unit, self.ax) == 0
def test_convert_one_number(self):
actual = self.cc.convert(0.0, self.unit, self.ax)
np.testing.assert_allclose(actual, np.array([0.]))
def test_convert_float_array(self):
data = np.array([1, 2, 3], dtype=float)
actual = self.cc.convert(data, self.unit, self.ax)
np.testing.assert_allclose(actual, np.array([1., 2., 3.]))
@pytest.mark.parametrize("fvals", fvalues, ids=fids)
def test_convert_fail(self, fvals):
with pytest.raises(TypeError):
self.cc.convert(fvals, self.unit, self.ax)
def test_axisinfo(self):
axis = self.cc.axisinfo(self.unit, self.ax)
assert isinstance(axis.majloc, cat.StrCategoryLocator)
assert isinstance(axis.majfmt, cat.StrCategoryFormatter)
def test_default_units(self):
assert isinstance(self.cc.default_units(["a"], self.ax), cat.UnitData)
@pytest.fixture
def ax():
return plt.figure().subplots()
PLOT_LIST = [Axes.scatter, Axes.plot, Axes.bar]
PLOT_IDS = ["scatter", "plot", "bar"]
class TestStrCategoryLocator(object):
def test_StrCategoryLocator(self):
locs = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
unit = cat.UnitData([str(j) for j in locs])
ticks = cat.StrCategoryLocator(unit._mapping)
np.testing.assert_array_equal(ticks.tick_values(None, None), locs)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_StrCategoryLocatorPlot(self, ax, plotter):
ax.plot(["a", "b", "c"])
np.testing.assert_array_equal(ax.yaxis.major.locator(), range(3))
class TestStrCategoryFormatter(object):
test_cases = [("ascii", ["hello", "world", "hi"]),
("unicode", ["Здравствуйте", "привет"])]
ids, cases = zip(*test_cases)
@pytest.mark.parametrize("ydata", cases, ids=ids)
def test_StrCategoryFormatter(self, ax, ydata):
unit = cat.UnitData(ydata)
labels = cat.StrCategoryFormatter(unit._mapping)
for i, d in enumerate(ydata):
assert labels(i, i) == _to_str(d)
@pytest.mark.parametrize("ydata", cases, ids=ids)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_StrCategoryFormatterPlot(self, ax, ydata, plotter):
plotter(ax, range(len(ydata)), ydata)
for i, d in enumerate(ydata):
assert ax.yaxis.major.formatter(i, i) == _to_str(d)
assert ax.yaxis.major.formatter(i+1, i+1) == ""
assert ax.yaxis.major.formatter(0, None) == ""
def axis_test(axis, labels):
ticks = list(range(len(labels)))
np.testing.assert_array_equal(axis.get_majorticklocs(), ticks)
graph_labels = [axis.major.formatter(i, i) for i in ticks]
assert graph_labels == [_to_str(l) for l in labels]
assert list(axis.units._mapping.keys()) == [l for l in labels]
assert list(axis.units._mapping.values()) == ticks
class TestPlotBytes(object):
bytes_cases = [('string list', ['a', 'b', 'c']),
('bytes list', [b'a', b'b', b'c']),
('bytes ndarray', np.array([b'a', b'b', b'c']))]
bytes_ids, bytes_data = zip(*bytes_cases)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
@pytest.mark.parametrize("bdata", bytes_data, ids=bytes_ids)
def test_plot_bytes(self, ax, plotter, bdata):
counts = np.array([4, 6, 5])
plotter(ax, bdata, counts)
axis_test(ax.xaxis, bdata)
class TestPlotNumlike(object):
numlike_cases = [('string list', ['1', '11', '3']),
('string ndarray', np.array(['1', '11', '3'])),
('bytes list', [b'1', b'11', b'3']),
('bytes ndarray', np.array([b'1', b'11', b'3']))]
numlike_ids, numlike_data = zip(*numlike_cases)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
@pytest.mark.parametrize("ndata", numlike_data, ids=numlike_ids)
def test_plot_numlike(self, ax, plotter, ndata):
counts = np.array([4, 6, 5])
plotter(ax, ndata, counts)
axis_test(ax.xaxis, ndata)
class TestPlotTypes(object):
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_unicode(self, ax, plotter):
words = ['Здравствуйте', 'привет']
plotter(ax, words, [0, 1])
axis_test(ax.xaxis, words)
@pytest.fixture
def test_data(self):
self.x = ["hello", "happy", "world"]
self.xy = [2, 6, 3]
self.y = ["Python", "is", "fun"]
self.yx = [3, 4, 5]
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_xaxis(self, ax, test_data, plotter):
plotter(ax, self.x, self.xy)
axis_test(ax.xaxis, self.x)
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_yaxis(self, ax, test_data, plotter):
plotter(ax, self.yx, self.y)
axis_test(ax.yaxis, self.y)
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_xyaxis(self, ax, test_data, plotter):
plotter(ax, self.x, self.y)
axis_test(ax.xaxis, self.x)
axis_test(ax.yaxis, self.y)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_update_plot(self, ax, plotter):
plotter(ax, ['a', 'b'], ['e', 'g'])
plotter(ax, ['a', 'b', 'd'], ['f', 'a', 'b'])
plotter(ax, ['b', 'c', 'd'], ['g', 'e', 'd'])
axis_test(ax.xaxis, ['a', 'b', 'd', 'c'])
axis_test(ax.yaxis, ['e', 'g', 'f', 'a', 'b', 'd'])
failing_test_cases = [("mixed", ['A', 3.14]),
("number integer", ['1', 1]),
("string integer", ['42', 42]),
("missing", ['12', np.nan])]
fids, fvalues = zip(*failing_test_cases)
PLOT_BROKEN_LIST = [Axes.scatter,
pytest.param(Axes.plot, marks=pytest.mark.xfail),
pytest.param(Axes.bar, marks=pytest.mark.xfail)]
PLOT_BROKEN_IDS = ["scatter", "plot", "bar"]
@pytest.mark.parametrize("plotter", PLOT_BROKEN_LIST, ids=PLOT_BROKEN_IDS)
@pytest.mark.parametrize("xdata", fvalues, ids=fids)
def test_mixed_type_exception(self, ax, plotter, xdata):
with pytest.raises(TypeError):
plotter(ax, xdata, [1, 2])
@pytest.mark.parametrize("plotter", PLOT_BROKEN_LIST, ids=PLOT_BROKEN_IDS)
@pytest.mark.parametrize("xdata", fvalues, ids=fids)
def test_mixed_type_update_exception(self, ax, plotter, xdata):
with pytest.raises(TypeError):
plotter(ax, [0, 3], [1, 3])
plotter(ax, xdata, [1, 2])
| 10,321 | 35.996416 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_quiver.py | from __future__ import print_function
import warnings
import numpy as np
import pytest
import sys
from matplotlib import pyplot as plt
from matplotlib.testing.decorators import image_comparison
def draw_quiver(ax, **kw):
X, Y = np.meshgrid(np.arange(0, 2 * np.pi, 1),
np.arange(0, 2 * np.pi, 1))
U = np.cos(X)
V = np.sin(Y)
Q = ax.quiver(U, V, **kw)
return Q
def test_quiver_memory_leak():
fig, ax = plt.subplots()
Q = draw_quiver(ax)
ttX = Q.X
Q.remove()
del Q
assert sys.getrefcount(ttX) == 2
def test_quiver_key_memory_leak():
fig, ax = plt.subplots()
Q = draw_quiver(ax)
qk = ax.quiverkey(Q, 0.5, 0.92, 2, r'$2 \frac{m}{s}$',
labelpos='W',
fontproperties={'weight': 'bold'})
assert sys.getrefcount(qk) == 3
qk.remove()
assert sys.getrefcount(qk) == 2
def test_no_warnings():
fig, ax = plt.subplots()
X, Y = np.meshgrid(np.arange(15), np.arange(10))
U = V = np.ones_like(X)
phi = (np.random.rand(15, 10) - .5) * 150
with warnings.catch_warnings(record=True) as w:
ax.quiver(X, Y, U, V, angles=phi)
fig.canvas.draw()
assert len(w) == 0
def test_zero_headlength():
# Based on report by Doug McNeil:
# http://matplotlib.1069221.n5.nabble.com/quiver-warnings-td28107.html
fig, ax = plt.subplots()
X, Y = np.meshgrid(np.arange(10), np.arange(10))
U, V = np.cos(X), np.sin(Y)
with warnings.catch_warnings(record=True) as w:
ax.quiver(U, V, headlength=0, headaxislength=0)
fig.canvas.draw()
assert len(w) == 0
@image_comparison(baseline_images=['quiver_animated_test_image'],
extensions=['png'])
def test_quiver_animate():
# Tests fix for #2616
fig, ax = plt.subplots()
Q = draw_quiver(ax, animated=True)
qk = ax.quiverkey(Q, 0.5, 0.92, 2, r'$2 \frac{m}{s}$',
labelpos='W',
fontproperties={'weight': 'bold'})
@image_comparison(baseline_images=['quiver_with_key_test_image'],
extensions=['png'])
def test_quiver_with_key():
fig, ax = plt.subplots()
ax.margins(0.1)
Q = draw_quiver(ax)
qk = ax.quiverkey(Q, 0.5, 0.95, 2,
r'$2\, \mathrm{m}\, \mathrm{s}^{-1}$',
angle=-10,
coordinates='figure',
labelpos='W',
fontproperties={'weight': 'bold',
'size': 'large'})
@image_comparison(baseline_images=['quiver_single_test_image'],
extensions=['png'], remove_text=True)
def test_quiver_single():
fig, ax = plt.subplots()
ax.margins(0.1)
ax.quiver([1], [1], [2], [2])
def test_quiver_copy():
fig, ax = plt.subplots()
uv = dict(u=np.array([1.1]), v=np.array([2.0]))
q0 = ax.quiver([1], [1], uv['u'], uv['v'])
uv['v'][0] = 0
assert q0.V[0] == 2.0
@image_comparison(baseline_images=['quiver_key_pivot'],
extensions=['png'], remove_text=True)
def test_quiver_key_pivot():
fig, ax = plt.subplots()
u, v = np.mgrid[0:2*np.pi:10j, 0:2*np.pi:10j]
q = ax.quiver(np.sin(u), np.cos(v))
ax.set_xlim(-2, 11)
ax.set_ylim(-2, 11)
ax.quiverkey(q, 0.5, 1, 1, 'N', labelpos='N')
ax.quiverkey(q, 1, 0.5, 1, 'E', labelpos='E')
ax.quiverkey(q, 0.5, 0, 1, 'S', labelpos='S')
ax.quiverkey(q, 0, 0.5, 1, 'W', labelpos='W')
@image_comparison(baseline_images=['barbs_test_image'],
extensions=['png'], remove_text=True)
def test_barbs():
x = np.linspace(-5, 5, 5)
X, Y = np.meshgrid(x, x)
U, V = 12*X, 12*Y
fig, ax = plt.subplots()
ax.barbs(X, Y, U, V, np.sqrt(U*U + V*V), fill_empty=True, rounding=False,
sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3),
cmap='viridis')
@image_comparison(baseline_images=['barbs_pivot_test_image'],
extensions=['png'], remove_text=True)
def test_barbs_pivot():
x = np.linspace(-5, 5, 5)
X, Y = np.meshgrid(x, x)
U, V = 12*X, 12*Y
fig, ax = plt.subplots()
ax.barbs(X, Y, U, V, fill_empty=True, rounding=False, pivot=1.7,
sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))
ax.scatter(X, Y, s=49, c='black')
def test_bad_masked_sizes():
'Test error handling when given differing sized masked arrays'
x = np.arange(3)
y = np.arange(3)
u = np.ma.array(15. * np.ones((4,)))
v = np.ma.array(15. * np.ones_like(u))
u[1] = np.ma.masked
v[1] = np.ma.masked
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.barbs(x, y, u, v)
def test_angles_and_scale():
# angles array + scale_units kwarg
fig, ax = plt.subplots()
X, Y = np.meshgrid(np.arange(15), np.arange(10))
U = V = np.ones_like(X)
phi = (np.random.rand(15, 10) - .5) * 150
ax.quiver(X, Y, U, V, angles=phi, scale_units='xy')
@image_comparison(baseline_images=['quiver_xy'],
extensions=['png'], remove_text=True)
def test_quiver_xy():
# simple arrow pointing from SW to NE
fig, ax = plt.subplots(subplot_kw=dict(aspect='equal'))
ax.quiver(0, 0, 1, 1, angles='xy', scale_units='xy', scale=1)
ax.set_xlim(0, 1.1)
ax.set_ylim(0, 1.1)
ax.grid()
def test_quiverkey_angles():
# Check that only a single arrow is plotted for a quiverkey when an array
# of angles is given to the original quiver plot
fig, ax = plt.subplots()
X, Y = np.meshgrid(np.arange(2), np.arange(2))
U = V = angles = np.ones_like(X)
q = ax.quiver(X, Y, U, V, angles=angles)
qk = ax.quiverkey(q, 1, 1, 2, 'Label')
# The arrows are only created when the key is drawn
fig.canvas.draw()
assert len(qk.verts) == 1
| 5,827 | 27.70936 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_spines.py | from __future__ import absolute_import, division, print_function
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
@image_comparison(baseline_images=['spines_axes_positions'])
def test_spines_axes_positions():
# SF bug 2852168
fig = plt.figure()
x = np.linspace(0, 2*np.pi, 100)
y = 2*np.sin(x)
ax = fig.add_subplot(1, 1, 1)
ax.set_title('centered spines')
ax.plot(x, y)
ax.spines['right'].set_position(('axes', 0.1))
ax.yaxis.set_ticks_position('right')
ax.spines['top'].set_position(('axes', 0.25))
ax.xaxis.set_ticks_position('top')
ax.spines['left'].set_color('none')
ax.spines['bottom'].set_color('none')
@image_comparison(baseline_images=['spines_data_positions'])
def test_spines_data_positions():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.spines['left'].set_position(('data', -1.5))
ax.spines['top'].set_position(('data', 0.5))
ax.spines['right'].set_position(('data', -0.5))
ax.spines['bottom'].set_position('zero')
ax.set_xlim([-2, 2])
ax.set_ylim([-2, 2])
@image_comparison(baseline_images=['spines_capstyle'])
def test_spines_capstyle():
# issue 2542
plt.rc('axes', linewidth=20)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_xticks([])
ax.set_yticks([])
def test_label_without_ticks():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
plt.subplots_adjust(left=0.3, bottom=0.3)
ax.plot(np.arange(10))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('outward', 30))
ax.spines['right'].set_visible(False)
ax.set_ylabel('y label')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('outward', 30))
ax.spines['top'].set_visible(False)
ax.set_xlabel('x label')
ax.xaxis.set_ticks([])
ax.yaxis.set_ticks([])
plt.draw()
spine = ax.spines['left']
spinebbox = spine.get_transform().transform_path(
spine.get_path()).get_extents()
assert ax.yaxis.label.get_position()[0] < spinebbox.xmin, \
"Y-Axis label not left of the spine"
spine = ax.spines['bottom']
spinebbox = spine.get_transform().transform_path(
spine.get_path()).get_extents()
assert ax.xaxis.label.get_position()[1] < spinebbox.ymin, \
"X-Axis label not below the spine"
| 2,392 | 30.486842 | 64 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_image.py | from __future__ import absolute_import, division, print_function
import six
from copy import copy
import io
import os
import sys
import warnings
import numpy as np
from numpy import ma
from numpy.testing import assert_array_equal
from matplotlib import (
colors, image as mimage, patches, pyplot as plt,
rc_context, rcParams)
from matplotlib.image import (AxesImage, BboxImage, FigureImage,
NonUniformImage, PcolorImage)
from matplotlib.testing.decorators import image_comparison
from matplotlib.transforms import Bbox, Affine2D, TransformedBbox
import pytest
try:
from PIL import Image
HAS_PIL = True
except ImportError:
HAS_PIL = False
needs_pillow = pytest.mark.xfail(not HAS_PIL, reason='Test requires Pillow')
@image_comparison(baseline_images=['image_interps'], style='mpl20')
def test_image_interps():
'make the basic nearest, bilinear and bicubic interps'
X = np.arange(100)
X = X.reshape(5, 20)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.imshow(X, interpolation='nearest')
ax1.set_title('three interpolations')
ax1.set_ylabel('nearest')
ax2 = fig.add_subplot(312)
ax2.imshow(X, interpolation='bilinear')
ax2.set_ylabel('bilinear')
ax3 = fig.add_subplot(313)
ax3.imshow(X, interpolation='bicubic')
ax3.set_ylabel('bicubic')
@image_comparison(baseline_images=['interp_nearest_vs_none'],
extensions=['pdf', 'svg'], remove_text=True)
def test_interp_nearest_vs_none():
'Test the effect of "nearest" and "none" interpolation'
# Setting dpi to something really small makes the difference very
# visible. This works fine with pdf, since the dpi setting doesn't
# affect anything but images, but the agg output becomes unusably
# small.
rcParams['savefig.dpi'] = 3
X = np.array([[[218, 165, 32], [122, 103, 238]],
[[127, 255, 0], [255, 99, 71]]], dtype=np.uint8)
fig = plt.figure()
ax1 = fig.add_subplot(121)
ax1.imshow(X, interpolation='none')
ax1.set_title('interpolation none')
ax2 = fig.add_subplot(122)
ax2.imshow(X, interpolation='nearest')
ax2.set_title('interpolation nearest')
def do_figimage(suppressComposite):
""" Helper for the next two tests """
fig = plt.figure(figsize=(2,2), dpi=100)
fig.suppressComposite = suppressComposite
x,y = np.ix_(np.arange(100.0)/100.0, np.arange(100.0)/100.0)
z = np.sin(x**2 + y**2 - x*y)
c = np.sin(20*x**2 + 50*y**2)
img = z + c/5
fig.figimage(img, xo=0, yo=0, origin='lower')
fig.figimage(img[::-1,:], xo=0, yo=100, origin='lower')
fig.figimage(img[:,::-1], xo=100, yo=0, origin='lower')
fig.figimage(img[::-1,::-1], xo=100, yo=100, origin='lower')
@image_comparison(baseline_images=['figimage-0'],
extensions=['png','pdf'])
def test_figimage0():
'test the figimage method'
suppressComposite = False
do_figimage(suppressComposite)
@image_comparison(baseline_images=['figimage-1'],
extensions=['png','pdf'])
def test_figimage1():
'test the figimage method'
suppressComposite = True
do_figimage(suppressComposite)
def test_image_python_io():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1,2,3])
buffer = io.BytesIO()
fig.savefig(buffer)
buffer.seek(0)
plt.imread(buffer)
@needs_pillow
def test_imread_pil_uint16():
img = plt.imread(os.path.join(os.path.dirname(__file__),
'baseline_images', 'test_image', 'uint16.tif'))
assert (img.dtype == np.uint16)
assert np.sum(img) == 134184960
@pytest.mark.skipif(sys.version_info < (3, 6), reason="requires Python 3.6+")
@needs_pillow
def test_imread_fspath():
from pathlib import Path
img = plt.imread(
Path(__file__).parent / 'baseline_images/test_image/uint16.tif')
assert img.dtype == np.uint16
assert np.sum(img) == 134184960
def test_imsave():
# The goal here is that the user can specify an output logical DPI
# for the image, but this will not actually add any extra pixels
# to the image, it will merely be used for metadata purposes.
# So we do the traditional case (dpi == 1), and the new case (dpi
# == 100) and read the resulting PNG files back in and make sure
# the data is 100% identical.
np.random.seed(1)
data = np.random.rand(256, 128)
buff_dpi1 = io.BytesIO()
plt.imsave(buff_dpi1, data, dpi=1)
buff_dpi100 = io.BytesIO()
plt.imsave(buff_dpi100, data, dpi=100)
buff_dpi1.seek(0)
arr_dpi1 = plt.imread(buff_dpi1)
buff_dpi100.seek(0)
arr_dpi100 = plt.imread(buff_dpi100)
assert arr_dpi1.shape == (256, 128, 4)
assert arr_dpi100.shape == (256, 128, 4)
assert_array_equal(arr_dpi1, arr_dpi100)
@pytest.mark.skipif(sys.version_info < (3, 6), reason="requires Python 3.6+")
@pytest.mark.parametrize("fmt", ["png", "pdf", "ps", "eps", "svg"])
def test_imsave_fspath(fmt):
Path = pytest.importorskip("pathlib").Path
plt.imsave(Path(os.devnull), np.array([[0, 1]]), format=fmt)
def test_imsave_color_alpha():
# Test that imsave accept arrays with ndim=3 where the third dimension is
# color and alpha without raising any exceptions, and that the data is
# acceptably preserved through a save/read roundtrip.
np.random.seed(1)
for origin in ['lower', 'upper']:
data = np.random.rand(16, 16, 4)
buff = io.BytesIO()
plt.imsave(buff, data, origin=origin, format="png")
buff.seek(0)
arr_buf = plt.imread(buff)
# Recreate the float -> uint8 conversion of the data
# We can only expect to be the same with 8 bits of precision,
# since that's what the PNG file used.
data = (255*data).astype('uint8')
if origin == 'lower':
data = data[::-1]
arr_buf = (255*arr_buf).astype('uint8')
assert_array_equal(data, arr_buf)
@image_comparison(baseline_images=['image_alpha'], remove_text=True)
def test_image_alpha():
plt.figure()
np.random.seed(0)
Z = np.random.rand(6, 6)
plt.subplot(131)
plt.imshow(Z, alpha=1.0, interpolation='none')
plt.subplot(132)
plt.imshow(Z, alpha=0.5, interpolation='none')
plt.subplot(133)
plt.imshow(Z, alpha=0.5, interpolation='nearest')
def test_cursor_data():
from matplotlib.backend_bases import MouseEvent
fig, ax = plt.subplots()
im = ax.imshow(np.arange(100).reshape(10, 10), origin='upper')
x, y = 4, 4
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) == 44
# Now try for a point outside the image
# Tests issue #4957
x, y = 10.1, 4
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) is None
# Hmm, something is wrong here... I get 0, not None...
# But, this works further down in the tests with extents flipped
#x, y = 0.1, -0.1
#xdisp, ydisp = ax.transData.transform_point([x, y])
#event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
#z = im.get_cursor_data(event)
#assert z is None, "Did not get None, got %d" % z
ax.clear()
# Now try with the extents flipped.
im = ax.imshow(np.arange(100).reshape(10, 10), origin='lower')
x, y = 4, 4
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) == 44
fig, ax = plt.subplots()
im = ax.imshow(np.arange(100).reshape(10, 10), extent=[0, 0.5, 0, 0.5])
x, y = 0.25, 0.25
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) == 55
# Now try for a point outside the image
# Tests issue #4957
x, y = 0.75, 0.25
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) is None
x, y = 0.01, -0.01
xdisp, ydisp = ax.transData.transform_point([x, y])
event = MouseEvent('motion_notify_event', fig.canvas, xdisp, ydisp)
assert im.get_cursor_data(event) is None
@image_comparison(baseline_images=['image_clip'], style='mpl20')
def test_image_clip():
d = [[1, 2], [3, 4]]
fig, ax = plt.subplots()
im = ax.imshow(d)
patch = patches.Circle((0, 0), radius=1, transform=ax.transData)
im.set_clip_path(patch)
@image_comparison(baseline_images=['image_cliprect'], style='mpl20')
def test_image_cliprect():
import matplotlib.patches as patches
fig = plt.figure()
ax = fig.add_subplot(111)
d = [[1,2],[3,4]]
im = ax.imshow(d, extent=(0,5,0,5))
rect = patches.Rectangle(xy=(1,1), width=2, height=2, transform=im.axes.transData)
im.set_clip_path(rect)
@image_comparison(baseline_images=['imshow'], remove_text=True, style='mpl20')
def test_imshow():
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
arr = np.arange(100).reshape((10, 10))
ax = fig.add_subplot(111)
ax.imshow(arr, interpolation="bilinear", extent=(1,2,1,2))
ax.set_xlim(0,3)
ax.set_ylim(0,3)
@image_comparison(baseline_images=['no_interpolation_origin'],
remove_text=True)
def test_no_interpolation_origin():
fig = plt.figure()
ax = fig.add_subplot(211)
ax.imshow(np.arange(100).reshape((2, 50)), origin="lower",
interpolation='none')
ax = fig.add_subplot(212)
ax.imshow(np.arange(100).reshape((2, 50)), interpolation='none')
@image_comparison(baseline_images=['image_shift'], remove_text=True,
extensions=['pdf', 'svg'])
def test_image_shift():
from matplotlib.colors import LogNorm
imgData = [[1.0/(x) + 1.0/(y) for x in range(1,100)] for y in range(1,100)]
tMin=734717.945208
tMax=734717.946366
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(imgData, norm=LogNorm(), interpolation='none',
extent=(tMin, tMax, 1, 100))
ax.set_aspect('auto')
def test_image_edges():
f = plt.figure(figsize=[1, 1])
ax = f.add_axes([0, 0, 1, 1], frameon=False)
data = np.tile(np.arange(12), 15).reshape(20, 9)
im = ax.imshow(data, origin='upper', extent=[-10, 10, -10, 10],
interpolation='none', cmap='gray')
x = y = 2
ax.set_xlim([-x, x])
ax.set_ylim([-y, y])
ax.set_xticks([])
ax.set_yticks([])
buf = io.BytesIO()
f.savefig(buf, facecolor=(0, 1, 0))
buf.seek(0)
im = plt.imread(buf)
r, g, b, a = sum(im[:, 0])
r, g, b, a = sum(im[:, -1])
assert g != 100, 'Expected a non-green edge - but sadly, it was.'
@image_comparison(baseline_images=['image_composite_background'],
remove_text=True,
style='mpl20')
def test_image_composite_background():
fig = plt.figure()
ax = fig.add_subplot(111)
arr = np.arange(12).reshape(4, 3)
ax.imshow(arr, extent=[0, 2, 15, 0])
ax.imshow(arr, extent=[4, 6, 15, 0])
ax.set_facecolor((1, 0, 0, 0.5))
ax.set_xlim([0, 12])
@image_comparison(baseline_images=['image_composite_alpha'],
remove_text=True)
def test_image_composite_alpha():
"""
Tests that the alpha value is recognized and correctly applied in the
process of compositing images together.
"""
fig = plt.figure()
ax = fig.add_subplot(111)
arr = np.zeros((11, 21, 4))
arr[:, :, 0] = 1
arr[:, :, 3] = np.concatenate((np.arange(0, 1.1, 0.1), np.arange(0, 1, 0.1)[::-1]))
arr2 = np.zeros((21, 11, 4))
arr2[:, :, 0] = 1
arr2[:, :, 1] = 1
arr2[:, :, 3] = np.concatenate((np.arange(0, 1.1, 0.1), np.arange(0, 1, 0.1)[::-1]))[:, np.newaxis]
ax.imshow(arr, extent=[1, 2, 5, 0], alpha=0.3)
ax.imshow(arr, extent=[2, 3, 5, 0], alpha=0.6)
ax.imshow(arr, extent=[3, 4, 5, 0])
ax.imshow(arr2, extent=[0, 5, 1, 2])
ax.imshow(arr2, extent=[0, 5, 2, 3], alpha=0.6)
ax.imshow(arr2, extent=[0, 5, 3, 4], alpha=0.3)
ax.set_facecolor((0, 0.5, 0, 1))
ax.set_xlim([0, 5])
ax.set_ylim([5, 0])
@image_comparison(baseline_images=['rasterize_10dpi'],
extensions=['pdf', 'svg'],
remove_text=True, style='mpl20')
def test_rasterize_dpi():
# This test should check rasterized rendering with high output resolution.
# It plots a rasterized line and a normal image with implot. So it will catch
# when images end up in the wrong place in case of non-standard dpi setting.
# Instead of high-res rasterization i use low-res. Therefore the fact that the
# resolution is non-standard is easily checked by image_comparison.
import numpy as np
import matplotlib.pyplot as plt
img = np.asarray([[1, 2], [3, 4]])
fig, axes = plt.subplots(1, 3, figsize = (3, 1))
axes[0].imshow(img)
axes[1].plot([0,1],[0,1], linewidth=20., rasterized=True)
axes[1].set(xlim = (0,1), ylim = (-1, 2))
axes[2].plot([0,1],[0,1], linewidth=20.)
axes[2].set(xlim = (0,1), ylim = (-1, 2))
# Low-dpi PDF rasterization errors prevent proper image comparison tests.
# Hide detailed structures like the axes spines.
for ax in axes:
ax.set_xticks([])
ax.set_yticks([])
for spine in ax.spines.values():
spine.set_visible(False)
rcParams['savefig.dpi'] = 10
@image_comparison(baseline_images=['bbox_image_inverted'], remove_text=True,
style='mpl20')
def test_bbox_image_inverted():
# This is just used to produce an image to feed to BboxImage
image = np.arange(100).reshape((10, 10))
ax = plt.subplot(111)
bbox_im = BboxImage(
TransformedBbox(Bbox([[100, 100], [0, 0]]), ax.transData))
bbox_im.set_data(image)
bbox_im.set_clip_on(False)
ax.set_xlim(0, 100)
ax.set_ylim(0, 100)
ax.add_artist(bbox_im)
image = np.identity(10)
bbox_im = BboxImage(
TransformedBbox(Bbox([[0.1, 0.2], [0.3, 0.25]]), ax.figure.transFigure))
bbox_im.set_data(image)
bbox_im.set_clip_on(False)
ax.add_artist(bbox_im)
def test_get_window_extent_for_AxisImage():
# Create a figure of known size (1000x1000 pixels), place an image
# object at a given location and check that get_window_extent()
# returns the correct bounding box values (in pixels).
im = np.array([[0.25, 0.75, 1.0, 0.75], [0.1, 0.65, 0.5, 0.4],
[0.6, 0.3, 0.0, 0.2], [0.7, 0.9, 0.4, 0.6]])
fig = plt.figure(figsize=(10, 10), dpi=100)
ax = plt.subplot()
ax.set_position([0, 0, 1, 1])
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
im_obj = ax.imshow(im, extent=[0.4, 0.7, 0.2, 0.9], interpolation='nearest')
fig.canvas.draw()
renderer = fig.canvas.renderer
im_bbox = im_obj.get_window_extent(renderer)
assert_array_equal(im_bbox.get_points(), [[400, 200], [700, 900]])
@image_comparison(baseline_images=['zoom_and_clip_upper_origin'],
remove_text=True,
extensions=['png'],
style='mpl20')
def test_zoom_and_clip_upper_origin():
image = np.arange(100)
image = image.reshape((10, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(image)
ax.set_ylim(2.0, -0.5)
ax.set_xlim(-0.5, 2.0)
def test_nonuniformimage_setcmap():
ax = plt.gca()
im = NonUniformImage(ax)
im.set_cmap('Blues')
def test_nonuniformimage_setnorm():
ax = plt.gca()
im = NonUniformImage(ax)
im.set_norm(plt.Normalize())
@needs_pillow
def test_jpeg_2d():
# smoke test that mode-L pillow images work.
imd = np.ones((10, 10), dtype='uint8')
for i in range(10):
imd[i, :] = np.linspace(0.0, 1.0, 10) * 255
im = Image.new('L', (10, 10))
im.putdata(imd.flatten())
fig, ax = plt.subplots()
ax.imshow(im)
@needs_pillow
def test_jpeg_alpha():
plt.figure(figsize=(1, 1), dpi=300)
# Create an image that is all black, with a gradient from 0-1 in
# the alpha channel from left to right.
im = np.zeros((300, 300, 4), dtype=float)
im[..., 3] = np.linspace(0.0, 1.0, 300)
plt.figimage(im)
buff = io.BytesIO()
with rc_context({'savefig.facecolor': 'red'}):
plt.savefig(buff, transparent=True, format='jpg', dpi=300)
buff.seek(0)
image = Image.open(buff)
# If this fails, there will be only one color (all black). If this
# is working, we should have all 256 shades of grey represented.
num_colors = len(image.getcolors(256))
assert 175 <= num_colors <= 185
# The fully transparent part should be red.
corner_pixel = image.getpixel((0, 0))
assert corner_pixel == (254, 0, 0)
def test_nonuniformimage_setdata():
ax = plt.gca()
im = NonUniformImage(ax)
x = np.arange(3, dtype=float)
y = np.arange(4, dtype=float)
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(x, y, z)
x[0] = y[0] = z[0, 0] = 9.9
assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'
def test_axesimage_setdata():
ax = plt.gca()
im = AxesImage(ax)
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(z)
z[0, 0] = 9.9
assert im._A[0, 0] == 0, 'value changed'
def test_figureimage_setdata():
fig = plt.gcf()
im = FigureImage(fig)
z = np.arange(12, dtype=float).reshape((4, 3))
im.set_data(z)
z[0, 0] = 9.9
assert im._A[0, 0] == 0, 'value changed'
def test_pcolorimage_setdata():
ax = plt.gca()
im = PcolorImage(ax)
x = np.arange(3, dtype=float)
y = np.arange(4, dtype=float)
z = np.arange(6, dtype=float).reshape((3, 2))
im.set_data(x, y, z)
x[0] = y[0] = z[0, 0] = 9.9
assert im._A[0, 0] == im._Ax[0] == im._Ay[0] == 0, 'value changed'
def test_pcolorimage_extent():
im = plt.hist2d([1, 2, 3], [3, 5, 6],
bins=[[0, 3, 7], [1, 2, 3]])[-1]
assert im.get_extent() == (0, 7, 1, 3)
def test_minimized_rasterized():
# This ensures that the rasterized content in the colorbars is
# only as thick as the colorbar, and doesn't extend to other parts
# of the image. See #5814. While the original bug exists only
# in Postscript, the best way to detect it is to generate SVG
# and then parse the output to make sure the two colorbar images
# are the same size.
from xml.etree import ElementTree
np.random.seed(0)
data = np.random.rand(10, 10)
fig, ax = plt.subplots(1, 2)
p1 = ax[0].pcolormesh(data)
p2 = ax[1].pcolormesh(data)
plt.colorbar(p1, ax=ax[0])
plt.colorbar(p2, ax=ax[1])
buff = io.BytesIO()
plt.savefig(buff, format='svg')
buff = io.BytesIO(buff.getvalue())
tree = ElementTree.parse(buff)
width = None
for image in tree.iter('image'):
if width is None:
width = image['width']
else:
if image['width'] != width:
assert False
@pytest.mark.network
def test_load_from_url():
req = six.moves.urllib.request.urlopen(
"http://matplotlib.org/_static/logo_sidebar_horiz.png")
plt.imread(req)
@image_comparison(baseline_images=['log_scale_image'],
remove_text=True)
# The recwarn fixture captures a warning in image_comparison.
def test_log_scale_image(recwarn):
Z = np.zeros((10, 10))
Z[::2] = 1
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(Z, extent=[1, 100, 1, 100], cmap='viridis',
vmax=1, vmin=-1)
ax.set_yscale('log')
@image_comparison(baseline_images=['rotate_image'],
remove_text=True)
def test_rotate_image():
delta = 0.25
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))
Z = Z2 - Z1 # difference of Gaussians
fig, ax1 = plt.subplots(1, 1)
im1 = ax1.imshow(Z, interpolation='none', cmap='viridis',
origin='lower',
extent=[-2, 4, -3, 2], clip_on=True)
trans_data2 = Affine2D().rotate_deg(30) + ax1.transData
im1.set_transform(trans_data2)
# display intended extent of the image
x1, x2, y1, y2 = im1.get_extent()
ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "r--", lw=3,
transform=trans_data2)
ax1.set_xlim(2, 5)
ax1.set_ylim(0, 4)
def test_image_preserve_size():
buff = io.BytesIO()
im = np.zeros((481, 321))
plt.imsave(buff, im, format="png")
buff.seek(0)
img = plt.imread(buff)
assert img.shape[:2] == im.shape
def test_image_preserve_size2():
n = 7
data = np.identity(n, float)
fig = plt.figure(figsize=(n, n), frameon=False)
ax = plt.Axes(fig, [0.0, 0.0, 1.0, 1.0])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(data, interpolation='nearest', origin='lower',aspect='auto')
buff = io.BytesIO()
fig.savefig(buff, dpi=1)
buff.seek(0)
img = plt.imread(buff)
assert img.shape == (7, 7, 4)
assert_array_equal(np.asarray(img[:, :, 0], bool),
np.identity(n, bool)[::-1])
@image_comparison(baseline_images=['mask_image_over_under'],
remove_text=True, extensions=['png'])
def test_mask_image_over_under():
delta = 0.025
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))
Z = 10*(Z2 - Z1) # difference of Gaussians
palette = copy(plt.cm.gray)
palette.set_over('r', 1.0)
palette.set_under('g', 1.0)
palette.set_bad('b', 1.0)
Zm = ma.masked_where(Z > 1.2, Z)
fig, (ax1, ax2) = plt.subplots(1, 2)
im = ax1.imshow(Zm, interpolation='bilinear',
cmap=palette,
norm=colors.Normalize(vmin=-1.0, vmax=1.0, clip=False),
origin='lower', extent=[-3, 3, -3, 3])
ax1.set_title('Green=low, Red=high, Blue=bad')
fig.colorbar(im, extend='both', orientation='horizontal',
ax=ax1, aspect=10)
im = ax2.imshow(Zm, interpolation='nearest',
cmap=palette,
norm=colors.BoundaryNorm([-1, -0.5, -0.2, 0, 0.2, 0.5, 1],
ncolors=256, clip=False),
origin='lower', extent=[-3, 3, -3, 3])
ax2.set_title('With BoundaryNorm')
fig.colorbar(im, extend='both', spacing='proportional',
orientation='horizontal', ax=ax2, aspect=10)
@image_comparison(baseline_images=['mask_image'],
remove_text=True)
def test_mask_image():
# Test mask image two ways: Using nans and using a masked array.
fig, (ax1, ax2) = plt.subplots(1, 2)
A = np.ones((5, 5))
A[1:2, 1:2] = np.nan
ax1.imshow(A, interpolation='nearest')
A = np.zeros((5, 5), dtype=bool)
A[1:2, 1:2] = True
A = np.ma.masked_array(np.ones((5, 5), dtype=np.uint16), A)
ax2.imshow(A, interpolation='nearest')
@image_comparison(baseline_images=['imshow_endianess'],
remove_text=True, extensions=['png'])
def test_imshow_endianess():
x = np.arange(10)
X, Y = np.meshgrid(x, x)
Z = ((X-5)**2 + (Y-5)**2)**0.5
fig, (ax1, ax2) = plt.subplots(1, 2)
kwargs = dict(origin="lower", interpolation='nearest',
cmap='viridis')
ax1.imshow(Z.astype('<f8'), **kwargs)
ax2.imshow(Z.astype('>f8'), **kwargs)
@image_comparison(baseline_images=['imshow_masked_interpolation'],
remove_text=True, style='mpl20')
def test_imshow_masked_interpolation():
cm = copy(plt.get_cmap('viridis'))
cm.set_over('r')
cm.set_under('b')
cm.set_bad('k')
N = 20
n = colors.Normalize(vmin=0, vmax=N*N-1)
# data = np.random.random((N, N))*N*N
data = np.arange(N*N, dtype='float').reshape(N, N)
data[5, 5] = -1
# This will cause crazy ringing for the higher-order
# interpolations
data[15, 5] = 1e5
# data[3, 3] = np.nan
data[15, 15] = np.inf
mask = np.zeros_like(data).astype('bool')
mask[5, 15] = True
data = np.ma.masked_array(data, mask)
fig, ax_grid = plt.subplots(3, 6)
for interp, ax in zip(sorted(mimage._interpd_), ax_grid.ravel()):
ax.set_title(interp)
ax.imshow(data, norm=n, cmap=cm, interpolation=interp)
ax.axis('off')
def test_imshow_no_warn_invalid():
with warnings.catch_warnings(record=True) as warns:
warnings.simplefilter("always")
plt.imshow([[1, 2], [3, np.nan]])
assert len(warns) == 0
@pytest.mark.parametrize(
'dtype', [np.dtype(s) for s in 'u2 u4 i2 i4 i8 f4 f8'.split()])
def test_imshow_clips_rgb_to_valid_range(dtype):
arr = np.arange(300, dtype=dtype).reshape((10, 10, 3))
if dtype.kind != 'u':
arr -= 10
too_low = arr < 0
too_high = arr > 255
if dtype.kind == 'f':
arr = arr / 255
_, ax = plt.subplots()
out = ax.imshow(arr).get_array()
assert (out[too_low] == 0).all()
if dtype.kind == 'f':
assert (out[too_high] == 1).all()
assert out.dtype.kind == 'f'
else:
assert (out[too_high] == 255).all()
assert out.dtype == np.uint8
@image_comparison(baseline_images=['imshow_flatfield'],
remove_text=True, style='mpl20',
extensions=['png'])
def test_imshow_flatfield():
fig, ax = plt.subplots()
im = ax.imshow(np.ones((5, 5)))
im.set_clim(.5, 1.5)
@image_comparison(baseline_images=['imshow_bignumbers'],
remove_text=True, style='mpl20',
extensions=['png'])
def test_imshow_bignumbers():
# putting a big number in an array of integers shouldn't
# ruin the dynamic range of the resolved bits.
fig, ax = plt.subplots()
img = np.array([[1, 2, 1e12],[3, 1, 4]], dtype=np.uint64)
pc = ax.imshow(img)
pc.set_clim(0, 5)
@image_comparison(baseline_images=['imshow_bignumbers_real'],
remove_text=True, style='mpl20',
extensions=['png'])
def test_imshow_bignumbers_real():
# putting a big number in an array of integers shouldn't
# ruin the dynamic range of the resolved bits.
fig, ax = plt.subplots()
img = np.array([[2., 1., 1.e22],[4., 1., 3.]])
pc = ax.imshow(img)
pc.set_clim(0, 5)
@pytest.mark.parametrize(
"make_norm",
[colors.Normalize,
colors.LogNorm,
lambda: colors.SymLogNorm(1),
lambda: colors.PowerNorm(1)])
def test_empty_imshow(make_norm):
fig, ax = plt.subplots()
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore", "Attempting to set identical left==right")
im = ax.imshow([[]], norm=make_norm())
im.set_extent([-5, 5, -5, 5])
fig.canvas.draw()
with pytest.raises(RuntimeError):
im.make_image(fig._cachedRenderer)
def test_imshow_float128():
fig, ax = plt.subplots()
ax.imshow(np.zeros((3, 3), dtype=np.longdouble))
def test_imshow_bool():
fig, ax = plt.subplots()
ax.imshow(np.array([[True, False], [False, True]], dtype=bool))
def test_imshow_deprecated_interd_warn():
im = plt.imshow([[1, 2], [3, np.nan]])
for k in ('_interpd', '_interpdr', 'iterpnames'):
with warnings.catch_warnings(record=True) as warns:
getattr(im, k)
assert len(warns) == 1
def test_full_invalid():
x = np.ones((10, 10))
x[:] = np.nan
f, ax = plt.subplots()
ax.imshow(x)
f.canvas.draw()
@pytest.mark.parametrize("fmt,counted",
[("ps", b" colorimage"), ("svg", b"<image")])
@pytest.mark.parametrize("composite_image,count", [(True, 1), (False, 2)])
def test_composite(fmt, counted, composite_image, count):
# Test that figures can be saved with and without combining multiple images
# (on a single set of axes) into a single composite image.
X, Y = np.meshgrid(np.arange(-5, 5, 1), np.arange(-5, 5, 1))
Z = np.sin(Y ** 2)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_xlim(0, 3)
ax.imshow(Z, extent=[0, 1, 0, 1])
ax.imshow(Z[::-1], extent=[2, 3, 0, 1])
plt.rcParams['image.composite_image'] = composite_image
buf = io.BytesIO()
fig.savefig(buf, format=fmt)
assert buf.getvalue().count(counted) == count
def test_relim():
fig, ax = plt.subplots()
ax.imshow([[0]], extent=(0, 1, 0, 1))
ax.relim()
ax.autoscale()
assert ax.get_xlim() == ax.get_ylim() == (0, 1)
| 28,875 | 29.205021 | 103 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_pickle.py | from __future__ import absolute_import, division, print_function
from six.moves import cPickle as pickle
from six.moves import range
from io import BytesIO
import numpy as np
from matplotlib.testing.decorators import image_comparison
from matplotlib.dates import rrulewrapper
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
def test_simple():
fig = plt.figure()
pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL)
ax = plt.subplot(121)
pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL)
ax = plt.axes(projection='polar')
plt.plot(np.arange(10), label='foobar')
plt.legend()
pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL)
# ax = plt.subplot(121, projection='hammer')
# pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL)
plt.figure()
plt.bar(x=np.arange(10), height=np.arange(10))
pickle.dump(plt.gca(), BytesIO(), pickle.HIGHEST_PROTOCOL)
fig = plt.figure()
ax = plt.axes()
plt.plot(np.arange(10))
ax.set_yscale('log')
pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL)
@image_comparison(baseline_images=['multi_pickle'],
extensions=['png'], remove_text=True,
style='mpl20')
def test_complete():
fig = plt.figure('Figure with a label?', figsize=(10, 6))
plt.suptitle('Can you fit any more in a figure?')
# make some arbitrary data
x, y = np.arange(8), np.arange(10)
data = u = v = np.linspace(0, 10, 80).reshape(10, 8)
v = np.sin(v * -0.6)
# Ensure lists also pickle correctly.
plt.subplot(3, 3, 1)
plt.plot(list(range(10)))
plt.subplot(3, 3, 2)
plt.contourf(data, hatches=['//', 'ooo'])
plt.colorbar()
plt.subplot(3, 3, 3)
plt.pcolormesh(data)
plt.subplot(3, 3, 4)
plt.imshow(data)
plt.subplot(3, 3, 5)
plt.pcolor(data)
ax = plt.subplot(3, 3, 6)
ax.set_xlim(0, 7)
ax.set_ylim(0, 9)
plt.streamplot(x, y, u, v)
ax = plt.subplot(3, 3, 7)
ax.set_xlim(0, 7)
ax.set_ylim(0, 9)
plt.quiver(x, y, u, v)
plt.subplot(3, 3, 8)
plt.scatter(x, x**2, label='$x^2$')
plt.legend(loc='upper left')
plt.subplot(3, 3, 9)
plt.errorbar(x, x * -0.5, xerr=0.2, yerr=0.4)
#
# plotting is done, now test its pickle-ability
#
result_fh = BytesIO()
pickle.dump(fig, result_fh, pickle.HIGHEST_PROTOCOL)
plt.close('all')
# make doubly sure that there are no figures left
assert plt._pylab_helpers.Gcf.figs == {}
# wind back the fh and load in the figure
result_fh.seek(0)
fig = pickle.load(result_fh)
# make sure there is now a figure manager
assert plt._pylab_helpers.Gcf.figs != {}
assert fig.get_label() == 'Figure with a label?'
def test_no_pyplot():
# tests pickle-ability of a figure not created with pyplot
from matplotlib.backends.backend_pdf import FigureCanvasPdf as fc
from matplotlib.figure import Figure
fig = Figure()
_ = fc(fig)
ax = fig.add_subplot(1, 1, 1)
ax.plot([1, 2, 3], [1, 2, 3])
pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL)
def test_renderer():
from matplotlib.backends.backend_agg import RendererAgg
renderer = RendererAgg(10, 20, 30)
pickle.dump(renderer, BytesIO())
def test_image():
# Prior to v1.4.0 the Image would cache data which was not picklable
# once it had been drawn.
from matplotlib.backends.backend_agg import new_figure_manager
manager = new_figure_manager(1000)
fig = manager.canvas.figure
ax = fig.add_subplot(1, 1, 1)
ax.imshow(np.arange(12).reshape(3, 4))
manager.canvas.draw()
pickle.dump(fig, BytesIO())
def test_polar():
ax = plt.subplot(111, polar=True)
fig = plt.gcf()
pf = pickle.dumps(fig)
pickle.loads(pf)
plt.draw()
class TransformBlob(object):
def __init__(self):
self.identity = mtransforms.IdentityTransform()
self.identity2 = mtransforms.IdentityTransform()
# Force use of the more complex composition.
self.composite = mtransforms.CompositeGenericTransform(
self.identity,
self.identity2)
# Check parent -> child links of TransformWrapper.
self.wrapper = mtransforms.TransformWrapper(self.composite)
# Check child -> parent links of TransformWrapper.
self.composite2 = mtransforms.CompositeGenericTransform(
self.wrapper,
self.identity)
def test_transform():
obj = TransformBlob()
pf = pickle.dumps(obj)
del obj
obj = pickle.loads(pf)
# Check parent -> child links of TransformWrapper.
assert obj.wrapper._child == obj.composite
# Check child -> parent links of TransformWrapper.
assert [v() for v in obj.wrapper._parents.values()] == [obj.composite2]
# Check input and output dimensions are set as expected.
assert obj.wrapper.input_dims == obj.composite.input_dims
assert obj.wrapper.output_dims == obj.composite.output_dims
def test_rrulewrapper():
r = rrulewrapper(2)
try:
pickle.loads(pickle.dumps(r))
except RecursionError:
print('rrulewrapper pickling test failed')
raise
| 5,184 | 26.727273 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/conftest.py | from __future__ import absolute_import, division, print_function
from matplotlib.testing.conftest import (mpl_test_settings,
mpl_image_comparison_parameters,
pytest_configure, pytest_unconfigure,
pd)
| 324 | 45.428571 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_ps.py | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import io
import re
import numpy as np
import pytest
import six
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import patheffects
from matplotlib.testing.decorators import image_comparison
from matplotlib.testing.determinism import (_determinism_source_date_epoch,
_determinism_check)
needs_ghostscript = pytest.mark.xfail(
matplotlib.checkdep_ghostscript()[0] is None,
reason="This test needs a ghostscript installation")
needs_usetex = pytest.mark.xfail(
not matplotlib.checkdep_usetex(True),
reason="This test needs a TeX installation")
# This tests tends to hit a TeX cache lock on AppVeyor.
@pytest.mark.flaky(reruns=3)
@pytest.mark.parametrize('format, use_log, rcParams', [
('ps', False, {}),
needs_ghostscript(('ps', False, {'ps.usedistiller': 'ghostscript'})),
needs_usetex(needs_ghostscript(('ps', False, {'text.latex.unicode': True,
'text.usetex': True}))),
('eps', False, {}),
('eps', True, {'ps.useafm': True}),
needs_usetex(needs_ghostscript(('eps', False, {'text.latex.unicode': True,
'text.usetex': True}))),
], ids=[
'ps',
'ps with distiller',
'ps with usetex',
'eps',
'eps afm',
'eps with usetex'
])
def test_savefig_to_stringio(format, use_log, rcParams):
matplotlib.rcParams.update(rcParams)
fig, ax = plt.subplots()
buffers = [
six.moves.StringIO(),
io.StringIO(),
io.BytesIO()]
if use_log:
ax.set_yscale('log')
ax.plot([1, 2], [1, 2])
ax.set_title(u"Déjà vu")
for buffer in buffers:
fig.savefig(buffer, format=format)
values = [x.getvalue() for x in buffers]
if six.PY3:
values = [
values[0].encode('ascii'),
values[1].encode('ascii'),
values[2]]
# Remove comments from the output. This includes things that
# could change from run to run, such as the time.
values = [re.sub(b'%%.*?\n', b'', x) for x in values]
assert values[0] == values[1]
assert values[1] == values[2].replace(b'\r\n', b'\n')
for buffer in buffers:
buffer.close()
def test_patheffects():
with matplotlib.rc_context():
matplotlib.rcParams['path.effects'] = [
patheffects.withStroke(linewidth=4, foreground='w')]
fig, ax = plt.subplots()
ax.plot([1, 2, 3])
with io.BytesIO() as ps:
fig.savefig(ps, format='ps')
@needs_usetex
@needs_ghostscript
def test_tilde_in_tempfilename():
# Tilde ~ in the tempdir path (e.g. TMPDIR, TMP or TEMP on windows
# when the username is very long and windows uses a short name) breaks
# latex before https://github.com/matplotlib/matplotlib/pull/5928
import tempfile
import shutil
import os
import os.path
tempdir = None
old_tempdir = tempfile.tempdir
try:
# change the path for new tempdirs, which is used
# internally by the ps backend to write a file
tempdir = tempfile.mkdtemp()
base_tempdir = os.path.join(tempdir, "short~1")
os.makedirs(base_tempdir)
tempfile.tempdir = base_tempdir
# usetex results in the latex call, which does not like the ~
plt.rc('text', usetex=True)
plt.plot([1, 2, 3, 4])
plt.xlabel(r'\textbf{time} (s)')
output_eps = os.path.join(base_tempdir, 'tex_demo.eps')
# use the PS backend to write the file...
plt.savefig(output_eps, format="ps")
finally:
tempfile.tempdir = old_tempdir
if tempdir:
try:
shutil.rmtree(tempdir)
except Exception as e:
# do not break if this is not removable...
print(e)
def test_source_date_epoch():
"""Test SOURCE_DATE_EPOCH support for PS output"""
# SOURCE_DATE_EPOCH support is not tested with text.usetex,
# because the produced timestamp comes from ghostscript:
# %%CreationDate: D:20000101000000Z00\'00\', and this could change
# with another ghostscript version.
_determinism_source_date_epoch(
"ps", b"%%CreationDate: Sat Jan 01 00:00:00 2000")
def test_determinism_all():
"""Test for reproducible PS output"""
_determinism_check(format="ps")
@needs_usetex
@needs_ghostscript
def test_determinism_all_tex():
"""Test for reproducible PS/tex output"""
_determinism_check(format="ps", usetex=True)
@image_comparison(baseline_images=["empty"], extensions=["eps"])
def test_transparency():
fig, ax = plt.subplots()
ax.set_axis_off()
ax.plot([0, 1], color="r", alpha=0)
ax.text(.5, .5, "foo", color="r", alpha=0)
@needs_usetex
def test_failing_latex(tmpdir):
"""Test failing latex subprocess call"""
path = str(tmpdir.join("tmpoutput.ps"))
matplotlib.rcParams['text.usetex'] = True
# This fails with "Double subscript"
plt.xlabel("$22_2_2$")
with pytest.raises(RuntimeError):
plt.savefig(path)
| 5,170 | 28.890173 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_offsetbox.py | from __future__ import absolute_import, division, print_function
import pytest
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.lines as mlines
from matplotlib.offsetbox import (
AnchoredOffsetbox, DrawingArea, _get_packed_offsets)
@image_comparison(baseline_images=['offsetbox_clipping'], remove_text=True)
def test_offsetbox_clipping():
# - create a plot
# - put an AnchoredOffsetbox with a child DrawingArea
# at the center of the axes
# - give the DrawingArea a gray background
# - put a black line across the bounds of the DrawingArea
# - see that the black line is clipped to the edges of
# the DrawingArea.
fig, ax = plt.subplots()
size = 100
da = DrawingArea(size, size, clip=True)
bg = mpatches.Rectangle((0, 0), size, size,
facecolor='#CCCCCC',
edgecolor='None',
linewidth=0)
line = mlines.Line2D([-size*.5, size*1.5], [size/2, size/2],
color='black',
linewidth=10)
anchored_box = AnchoredOffsetbox(
loc=10,
child=da,
pad=0.,
frameon=False,
bbox_to_anchor=(.5, .5),
bbox_transform=ax.transAxes,
borderpad=0.)
da.add_artist(bg)
da.add_artist(line)
ax.add_artist(anchored_box)
ax.set_xlim((0, 1))
ax.set_ylim((0, 1))
def test_offsetbox_clip_children():
# - create a plot
# - put an AnchoredOffsetbox with a child DrawingArea
# at the center of the axes
# - give the DrawingArea a gray background
# - put a black line across the bounds of the DrawingArea
# - see that the black line is clipped to the edges of
# the DrawingArea.
fig, ax = plt.subplots()
size = 100
da = DrawingArea(size, size, clip=True)
bg = mpatches.Rectangle((0, 0), size, size,
facecolor='#CCCCCC',
edgecolor='None',
linewidth=0)
line = mlines.Line2D([-size*.5, size*1.5], [size/2, size/2],
color='black',
linewidth=10)
anchored_box = AnchoredOffsetbox(
loc=10,
child=da,
pad=0.,
frameon=False,
bbox_to_anchor=(.5, .5),
bbox_transform=ax.transAxes,
borderpad=0.)
da.add_artist(bg)
da.add_artist(line)
ax.add_artist(anchored_box)
fig.canvas.draw()
assert not fig.stale
da.clip_children = True
assert fig.stale
def test_offsetbox_loc_codes():
# Check that valid string location codes all work with an AnchoredOffsetbox
codes = {'upper right': 1,
'upper left': 2,
'lower left': 3,
'lower right': 4,
'right': 5,
'center left': 6,
'center right': 7,
'lower center': 8,
'upper center': 9,
'center': 10,
}
fig, ax = plt.subplots()
da = DrawingArea(100, 100)
for code in codes:
anchored_box = AnchoredOffsetbox(loc=code, child=da)
ax.add_artist(anchored_box)
fig.canvas.draw()
def test_expand_with_tight_layout():
# Check issue reported in #10476, and updated due to #10784
fig, ax = plt.subplots()
d1 = [1, 2]
d2 = [2, 1]
ax.plot(d1, label='series 1')
ax.plot(d2, label='series 2')
ax.legend(ncol=2, mode='expand')
fig.tight_layout() # where the crash used to happen
@pytest.mark.parametrize('wd_list',
([(150, 1)], [(150, 1)]*3, [(0.1, 1)], [(0.1, 1)]*2))
@pytest.mark.parametrize('total', (250, 100, 0, -1, None))
@pytest.mark.parametrize('sep', (250, 1, 0, -1))
@pytest.mark.parametrize('mode', ("expand", "fixed", "equal"))
def test_get_packed_offsets(wd_list, total, sep, mode):
# Check a (rather arbitrary) set of parameters due to successive similar
# issue tickets (at least #10476 and #10784) related to corner cases
# triggered inside this function when calling higher-level functions
# (e.g. `Axes.legend`).
_get_packed_offsets(wd_list, total, sep, mode=mode)
| 4,252 | 31.968992 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_ttconv.py | from __future__ import absolute_import, division, print_function
import six
import matplotlib
from matplotlib.font_manager import FontProperties
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import os.path
@image_comparison(baseline_images=["truetype-conversion"],
extensions=["pdf"])
def test_truetype_conversion():
fontname = os.path.join(os.path.dirname(__file__), 'mpltest.ttf')
fontname = os.path.abspath(fontname)
fontprop = FontProperties(fname=fontname, size=80)
matplotlib.rcParams['pdf.fonttype'] = 3
fig = plt.figure()
ax = fig.add_subplot(111)
ax.text(0, 0, "ABCDE", fontproperties=fontprop)
ax.set_xticks([])
ax.set_yticks([])
| 743 | 30 | 69 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_animation.py | from __future__ import absolute_import, division, print_function
import six
import sys
import tempfile
import numpy as np
import pytest
import matplotlib as mpl
from matplotlib import pyplot as plt
from matplotlib import animation
class NullMovieWriter(animation.AbstractMovieWriter):
"""
A minimal MovieWriter. It doesn't actually write anything.
It just saves the arguments that were given to the setup() and
grab_frame() methods as attributes, and counts how many times
grab_frame() is called.
This class doesn't have an __init__ method with the appropriate
signature, and it doesn't define an isAvailable() method, so
it cannot be added to the 'writers' registry.
"""
frame_size_can_vary = True
def setup(self, fig, outfile, dpi, *args):
self.fig = fig
self.outfile = outfile
self.dpi = dpi
self.args = args
self._count = 0
def grab_frame(self, **savefig_kwargs):
self.savefig_kwargs = savefig_kwargs
self._count += 1
def finish(self):
pass
def test_null_movie_writer():
# Test running an animation with NullMovieWriter.
fig = plt.figure()
def init():
pass
def animate(i):
pass
num_frames = 5
filename = "unused.null"
dpi = 50
savefig_kwargs = dict(foo=0)
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=num_frames)
writer = NullMovieWriter()
anim.save(filename, dpi=dpi, writer=writer,
savefig_kwargs=savefig_kwargs)
assert writer.fig == fig
assert writer.outfile == filename
assert writer.dpi == dpi
assert writer.args == ()
assert writer.savefig_kwargs == savefig_kwargs
assert writer._count == num_frames
def test_movie_writer_dpi_default():
# Test setting up movie writer with figure.dpi default.
fig = plt.figure()
filename = "unused.null"
fps = 5
codec = "unused"
bitrate = 1
extra_args = ["unused"]
def run():
pass
writer = animation.MovieWriter(fps, codec, bitrate, extra_args)
writer._run = run
writer.setup(fig, filename)
assert writer.dpi == fig.dpi
@animation.writers.register('null')
class RegisteredNullMovieWriter(NullMovieWriter):
# To be able to add NullMovieWriter to the 'writers' registry,
# we must define an __init__ method with a specific signature,
# and we must define the class method isAvailable().
# (These methods are not actually required to use an instance
# of this class as the 'writer' argument of Animation.save().)
def __init__(self, fps=None, codec=None, bitrate=None,
extra_args=None, metadata=None):
pass
@classmethod
def isAvailable(self):
return True
WRITER_OUTPUT = [
('ffmpeg', 'movie.mp4'),
('ffmpeg_file', 'movie.mp4'),
('avconv', 'movie.mp4'),
('avconv_file', 'movie.mp4'),
('imagemagick', 'movie.gif'),
('imagemagick_file', 'movie.gif'),
('pillow', 'movie.gif'),
('html', 'movie.html'),
('null', 'movie.null')
]
if sys.version_info >= (3, 6):
from pathlib import Path
WRITER_OUTPUT += [
(writer, Path(output)) for writer, output in WRITER_OUTPUT]
# Smoke test for saving animations. In the future, we should probably
# design more sophisticated tests which compare resulting frames a-la
# matplotlib.testing.image_comparison
@pytest.mark.parametrize('writer, output', WRITER_OUTPUT)
def test_save_animation_smoketest(tmpdir, writer, output):
try:
# for ImageMagick the rcparams must be patched to account for
# 'convert' being a built in MS tool, not the imagemagick
# tool.
writer._init_from_registry()
except AttributeError:
pass
if not animation.writers.is_available(writer):
pytest.skip("writer '%s' not available on this system" % writer)
fig, ax = plt.subplots()
line, = ax.plot([], [])
ax.set_xlim(0, 10)
ax.set_ylim(-1, 1)
dpi = None
codec = None
if writer == 'ffmpeg':
# Issue #8253
fig.set_size_inches((10.85, 9.21))
dpi = 100.
codec = 'h264'
def init():
line.set_data([], [])
return line,
def animate(i):
x = np.linspace(0, 10, 100)
y = np.sin(x + i)
line.set_data(x, y)
return line,
# Use temporary directory for the file-based writers, which produce a file
# per frame with known names.
with tmpdir.as_cwd():
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=5)
try:
anim.save(output, fps=30, writer=writer, bitrate=500, dpi=dpi,
codec=codec)
except UnicodeDecodeError:
pytest.xfail("There can be errors in the numpy import stack, "
"see issues #1891 and #2679")
def test_no_length_frames():
fig, ax = plt.subplots()
line, = ax.plot([], [])
def init():
line.set_data([], [])
return line,
def animate(i):
x = np.linspace(0, 10, 100)
y = np.sin(x + i)
line.set_data(x, y)
return line,
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=iter(range(5)))
writer = NullMovieWriter()
anim.save('unused.null', writer=writer)
def test_movie_writer_registry():
ffmpeg_path = mpl.rcParams['animation.ffmpeg_path']
# Not sure about the first state as there could be some writer
# which set rcparams
# assert not animation.writers._dirty
assert len(animation.writers._registered) > 0
animation.writers.list() # resets dirty state
assert not animation.writers._dirty
mpl.rcParams['animation.ffmpeg_path'] = u"not_available_ever_xxxx"
assert animation.writers._dirty
animation.writers.list() # resets
assert not animation.writers._dirty
assert not animation.writers.is_available("ffmpeg")
# something which is guaranteed to be available in path
# and exits immediately
bin = u"true" if sys.platform != 'win32' else u"where"
mpl.rcParams['animation.ffmpeg_path'] = bin
assert animation.writers._dirty
animation.writers.list() # resets
assert not animation.writers._dirty
assert animation.writers.is_available("ffmpeg")
mpl.rcParams['animation.ffmpeg_path'] = ffmpeg_path
| 6,426 | 27.95045 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_font_manager.py | from __future__ import absolute_import, division, print_function
import six
import os
import tempfile
import warnings
import numpy as np
import pytest
from matplotlib.font_manager import (
findfont, FontProperties, fontManager, json_dump, json_load, get_font,
get_fontconfig_fonts, is_opentype_cff_font, fontManager as fm)
from matplotlib import rc_context
if six.PY2:
from distutils.spawn import find_executable
has_fclist = find_executable('fc-list') is not None
else:
# py >= 3.3
from shutil import which
has_fclist = which('fc-list') is not None
def test_font_priority():
with rc_context(rc={
'font.sans-serif':
['cmmi10', 'Bitstream Vera Sans']}):
font = findfont(
FontProperties(family=["sans-serif"]))
assert os.path.basename(font) == 'cmmi10.ttf'
# Smoketest get_charmap, which isn't used internally anymore
font = get_font(font)
cmap = font.get_charmap()
assert len(cmap) == 131
assert cmap[8729] == 30
def test_score_weight():
assert 0 == fontManager.score_weight("regular", "regular")
assert 0 == fontManager.score_weight("bold", "bold")
assert (0 < fontManager.score_weight(400, 400) <
fontManager.score_weight("normal", "bold"))
assert (0 < fontManager.score_weight("normal", "regular") <
fontManager.score_weight("normal", "bold"))
assert (fontManager.score_weight("normal", "regular") ==
fontManager.score_weight(400, 400))
def test_json_serialization():
# on windows, we can't open a file twice, so save the name and unlink
# manually...
try:
name = None
with tempfile.NamedTemporaryFile(delete=False) as temp:
name = temp.name
json_dump(fontManager, name)
copy = json_load(name)
finally:
if name and os.path.exists(name):
os.remove(name)
with warnings.catch_warnings():
warnings.filterwarnings('ignore', 'findfont: Font family.*not found')
for prop in ({'family': 'STIXGeneral'},
{'family': 'Bitstream Vera Sans', 'weight': 700},
{'family': 'no such font family'}):
fp = FontProperties(**prop)
assert (fontManager.findfont(fp, rebuild_if_missing=False) ==
copy.findfont(fp, rebuild_if_missing=False))
def test_otf():
fname = '/usr/share/fonts/opentype/freefont/FreeMono.otf'
if os.path.exists(fname):
assert is_opentype_cff_font(fname)
otf_files = [f for f in fm.ttffiles if 'otf' in f]
for f in otf_files:
with open(f, 'rb') as fd:
res = fd.read(4) == b'OTTO'
assert res == is_opentype_cff_font(f)
@pytest.mark.skipif(not has_fclist, reason='no fontconfig installed')
def test_get_fontconfig_fonts():
assert len(get_fontconfig_fonts()) > 1
@pytest.mark.parametrize('factor', [2, 4, 6, 8])
def test_hinting_factor(factor):
font = findfont(FontProperties(family=["sans-serif"]))
font1 = get_font(font, hinting_factor=1)
font1.clear()
font1.set_size(12, 100)
font1.set_text('abc')
expected = font1.get_width_height()
hinted_font = get_font(font, hinting_factor=factor)
hinted_font.clear()
hinted_font.set_size(12, 100)
hinted_font.set_text('abc')
# Check that hinting only changes text layout by a small (10%) amount.
np.testing.assert_allclose(hinted_font.get_width_height(), expected,
rtol=0.1)
| 3,510 | 31.509259 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_artist.py | from __future__ import absolute_import, division, print_function
import io
import warnings
from itertools import chain
import numpy as np
import pytest
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.lines as mlines
import matplotlib.path as mpath
import matplotlib.transforms as mtransforms
import matplotlib.collections as mcollections
import matplotlib.artist as martist
from matplotlib.testing.decorators import image_comparison
def test_patch_transform_of_none():
# tests the behaviour of patches added to an Axes with various transform
# specifications
ax = plt.axes()
ax.set_xlim([1, 3])
ax.set_ylim([1, 3])
# Draw an ellipse over data coord (2,2) by specifying device coords.
xy_data = (2, 2)
xy_pix = ax.transData.transform_point(xy_data)
# Not providing a transform of None puts the ellipse in data coordinates .
e = mpatches.Ellipse(xy_data, width=1, height=1, fc='yellow', alpha=0.5)
ax.add_patch(e)
assert e._transform == ax.transData
# Providing a transform of None puts the ellipse in device coordinates.
e = mpatches.Ellipse(xy_pix, width=120, height=120, fc='coral',
transform=None, alpha=0.5)
assert e.is_transform_set() is True
ax.add_patch(e)
assert isinstance(e._transform, mtransforms.IdentityTransform)
# Providing an IdentityTransform puts the ellipse in device coordinates.
e = mpatches.Ellipse(xy_pix, width=100, height=100,
transform=mtransforms.IdentityTransform(), alpha=0.5)
ax.add_patch(e)
assert isinstance(e._transform, mtransforms.IdentityTransform)
# Not providing a transform, and then subsequently "get_transform" should
# not mean that "is_transform_set".
e = mpatches.Ellipse(xy_pix, width=120, height=120, fc='coral',
alpha=0.5)
intermediate_transform = e.get_transform()
assert e.is_transform_set() is False
ax.add_patch(e)
assert e.get_transform() != intermediate_transform
assert e.is_transform_set() is True
assert e._transform == ax.transData
def test_collection_transform_of_none():
# tests the behaviour of collections added to an Axes with various
# transform specifications
ax = plt.axes()
ax.set_xlim([1, 3])
ax.set_ylim([1, 3])
# draw an ellipse over data coord (2,2) by specifying device coords
xy_data = (2, 2)
xy_pix = ax.transData.transform_point(xy_data)
# not providing a transform of None puts the ellipse in data coordinates
e = mpatches.Ellipse(xy_data, width=1, height=1)
c = mcollections.PatchCollection([e], facecolor='yellow', alpha=0.5)
ax.add_collection(c)
# the collection should be in data coordinates
assert c.get_offset_transform() + c.get_transform() == ax.transData
# providing a transform of None puts the ellipse in device coordinates
e = mpatches.Ellipse(xy_pix, width=120, height=120)
c = mcollections.PatchCollection([e], facecolor='coral',
alpha=0.5)
c.set_transform(None)
ax.add_collection(c)
assert isinstance(c.get_transform(), mtransforms.IdentityTransform)
# providing an IdentityTransform puts the ellipse in device coordinates
e = mpatches.Ellipse(xy_pix, width=100, height=100)
c = mcollections.PatchCollection([e],
transform=mtransforms.IdentityTransform(),
alpha=0.5)
ax.add_collection(c)
assert isinstance(c._transOffset, mtransforms.IdentityTransform)
@image_comparison(baseline_images=["clip_path_clipping"], remove_text=True)
def test_clipping():
exterior = mpath.Path.unit_rectangle().deepcopy()
exterior.vertices *= 4
exterior.vertices -= 2
interior = mpath.Path.unit_circle().deepcopy()
interior.vertices = interior.vertices[::-1]
clip_path = mpath.Path(vertices=np.concatenate([exterior.vertices,
interior.vertices]),
codes=np.concatenate([exterior.codes,
interior.codes]))
star = mpath.Path.unit_regular_star(6).deepcopy()
star.vertices *= 2.6
ax1 = plt.subplot(121)
col = mcollections.PathCollection([star], lw=5, edgecolor='blue',
facecolor='red', alpha=0.7, hatch='*')
col.set_clip_path(clip_path, ax1.transData)
ax1.add_collection(col)
ax2 = plt.subplot(122, sharex=ax1, sharey=ax1)
patch = mpatches.PathPatch(star, lw=5, edgecolor='blue', facecolor='red',
alpha=0.7, hatch='*')
patch.set_clip_path(clip_path, ax2.transData)
ax2.add_patch(patch)
ax1.set_xlim([-3, 3])
ax1.set_ylim([-3, 3])
def test_cull_markers():
x = np.random.random(20000)
y = np.random.random(20000)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y, 'k.')
ax.set_xlim(2, 3)
pdf = io.BytesIO()
fig.savefig(pdf, format="pdf")
assert len(pdf.getvalue()) < 8000
svg = io.BytesIO()
fig.savefig(svg, format="svg")
assert len(svg.getvalue()) < 20000
@image_comparison(baseline_images=['hatching'], remove_text=True,
style='default')
def test_hatching():
fig, ax = plt.subplots(1, 1)
# Default hatch color.
rect1 = mpatches.Rectangle((0, 0), 3, 4, hatch='/')
ax.add_patch(rect1)
rect2 = mcollections.RegularPolyCollection(4, sizes=[16000],
offsets=[(1.5, 6.5)],
transOffset=ax.transData,
hatch='/')
ax.add_collection(rect2)
# Ensure edge color is not applied to hatching.
rect3 = mpatches.Rectangle((4, 0), 3, 4, hatch='/', edgecolor='C1')
ax.add_patch(rect3)
rect4 = mcollections.RegularPolyCollection(4, sizes=[16000],
offsets=[(5.5, 6.5)],
transOffset=ax.transData,
hatch='/', edgecolor='C1')
ax.add_collection(rect4)
ax.set_xlim(0, 7)
ax.set_ylim(0, 9)
def test_remove():
fig, ax = plt.subplots()
im = ax.imshow(np.arange(36).reshape(6, 6))
ln, = ax.plot(range(5))
assert fig.stale
assert ax.stale
fig.canvas.draw()
assert not fig.stale
assert not ax.stale
assert not ln.stale
assert im in ax.mouseover_set
assert ln not in ax.mouseover_set
assert im.axes is ax
im.remove()
ln.remove()
for art in [im, ln]:
assert art.axes is None
assert art.figure is None
assert im not in ax.mouseover_set
assert fig.stale
assert ax.stale
@image_comparison(baseline_images=["default_edges"], remove_text=True,
extensions=['png'], style='default')
def test_default_edges():
fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2)
ax1.plot(np.arange(10), np.arange(10), 'x',
np.arange(10) + 1, np.arange(10), 'o')
ax2.bar(np.arange(10), np.arange(10), align='edge')
ax3.text(0, 0, "BOX", size=24, bbox=dict(boxstyle='sawtooth'))
ax3.set_xlim((-1, 1))
ax3.set_ylim((-1, 1))
pp1 = mpatches.PathPatch(
mpath.Path([(0, 0), (1, 0), (1, 1), (0, 0)],
[mpath.Path.MOVETO, mpath.Path.CURVE3,
mpath.Path.CURVE3, mpath.Path.CLOSEPOLY]),
fc="none", transform=ax4.transData)
ax4.add_patch(pp1)
def test_properties():
ln = mlines.Line2D([], [])
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
ln.properties()
assert len(w) == 0
def test_setp():
# Check empty list
plt.setp([])
plt.setp([[]])
# Check arbitrary iterables
fig, axes = plt.subplots()
lines1 = axes.plot(range(3))
lines2 = axes.plot(range(3))
martist.setp(chain(lines1, lines2), 'lw', 5)
plt.setp(axes.spines.values(), color='green')
# Check `file` argument
sio = io.StringIO()
plt.setp(lines1, 'zorder', file=sio)
assert sio.getvalue() == ' zorder: float \n'
def test_None_zorder():
fig, ax = plt.subplots()
ln, = ax.plot(range(5), zorder=None)
assert ln.get_zorder() == mlines.Line2D.zorder
ln.set_zorder(123456)
assert ln.get_zorder() == 123456
ln.set_zorder(None)
assert ln.get_zorder() == mlines.Line2D.zorder
@pytest.mark.parametrize('accept_clause, expected', [
('', 'unknown'),
("ACCEPTS: [ '-' | '--' | '-.' ]", "[ '-' | '--' | '-.' ] "),
('ACCEPTS: Some description.', 'Some description. '),
('.. ACCEPTS: Some description.', 'Some description. '),
])
def test_artist_inspector_get_valid_values(accept_clause, expected):
class TestArtist(martist.Artist):
def set_f(self):
pass
func = TestArtist.set_f
if hasattr(func, '__func__'):
func = func.__func__ # python 2 must write via __func__.__doc__
func.__doc__ = """
Some text.
%s
""" % accept_clause
valid_values = martist.ArtistInspector(TestArtist).get_valid_values('f')
assert valid_values == expected
| 9,318 | 31.929329 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_rcparams.py | from __future__ import absolute_import, division, print_function
import six
import os
import warnings
from collections import OrderedDict
from cycler import cycler, Cycler
import pytest
try:
from unittest import mock
except ImportError:
import mock
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from itertools import chain
import numpy as np
from matplotlib.rcsetup import (validate_bool_maybe_none,
validate_stringlist,
validate_colorlist,
validate_color,
validate_bool,
validate_nseq_int,
validate_nseq_float,
validate_cycler,
validate_hatch,
validate_hist_bins,
_validate_linestyle)
mpl.rc('text', usetex=False)
mpl.rc('lines', linewidth=22)
fname = os.path.join(os.path.dirname(__file__), 'test_rcparams.rc')
def test_rcparams():
usetex = mpl.rcParams['text.usetex']
linewidth = mpl.rcParams['lines.linewidth']
# test context given dictionary
with mpl.rc_context(rc={'text.usetex': not usetex}):
assert mpl.rcParams['text.usetex'] == (not usetex)
assert mpl.rcParams['text.usetex'] == usetex
# test context given filename (mpl.rc sets linewdith to 33)
with mpl.rc_context(fname=fname):
assert mpl.rcParams['lines.linewidth'] == 33
assert mpl.rcParams['lines.linewidth'] == linewidth
# test context given filename and dictionary
with mpl.rc_context(fname=fname, rc={'lines.linewidth': 44}):
assert mpl.rcParams['lines.linewidth'] == 44
assert mpl.rcParams['lines.linewidth'] == linewidth
# test rc_file
try:
mpl.rc_file(fname)
assert mpl.rcParams['lines.linewidth'] == 33
finally:
mpl.rcParams['lines.linewidth'] = linewidth
def test_RcParams_class():
rc = mpl.RcParams({'font.cursive': ['Apple Chancery',
'Textile',
'Zapf Chancery',
'cursive'],
'font.family': 'sans-serif',
'font.weight': 'normal',
'font.size': 12})
expected_repr = """
RcParams({'font.cursive': ['Apple Chancery',
'Textile',
'Zapf Chancery',
'cursive'],
'font.family': ['sans-serif'],
'font.size': 12.0,
'font.weight': 'normal'})""".lstrip()
assert expected_repr == repr(rc)
expected_str = """
font.cursive: ['Apple Chancery', 'Textile', 'Zapf Chancery', 'cursive']
font.family: ['sans-serif']
font.size: 12.0
font.weight: normal""".lstrip()
assert expected_str == str(rc)
# test the find_all functionality
assert ['font.cursive', 'font.size'] == sorted(rc.find_all('i[vz]'))
assert ['font.family'] == list(rc.find_all('family'))
def test_rcparams_update():
rc = mpl.RcParams({'figure.figsize': (3.5, 42)})
bad_dict = {'figure.figsize': (3.5, 42, 1)}
# make sure validation happens on input
with pytest.raises(ValueError):
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
message='.*(validate)',
category=UserWarning)
rc.update(bad_dict)
def test_rcparams_init():
with pytest.raises(ValueError):
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
message='.*(validate)',
category=UserWarning)
mpl.RcParams({'figure.figsize': (3.5, 42, 1)})
def test_Bug_2543():
# Test that it possible to add all values to itself / deepcopy
# This was not possible because validate_bool_maybe_none did not
# accept None as an argument.
# https://github.com/matplotlib/matplotlib/issues/2543
# We filter warnings at this stage since a number of them are raised
# for deprecated rcparams as they should. We don't want these in the
# printed in the test suite.
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
message='.*(deprecated|obsolete)',
category=UserWarning)
with mpl.rc_context():
_copy = mpl.rcParams.copy()
for key in _copy:
mpl.rcParams[key] = _copy[key]
mpl.rcParams['text.dvipnghack'] = None
with mpl.rc_context():
from copy import deepcopy
_deep_copy = deepcopy(mpl.rcParams)
# real test is that this does not raise
assert validate_bool_maybe_none(None) is None
assert validate_bool_maybe_none("none") is None
with pytest.raises(ValueError):
validate_bool_maybe_none("blah")
with pytest.raises(ValueError):
validate_bool(None)
with pytest.raises(ValueError):
with mpl.rc_context():
mpl.rcParams['svg.fonttype'] = True
legend_color_tests = [
('face', {'color': 'r'}, mcolors.to_rgba('r')),
('face', {'color': 'inherit', 'axes.facecolor': 'r'},
mcolors.to_rgba('r')),
('face', {'color': 'g', 'axes.facecolor': 'r'}, mcolors.to_rgba('g')),
('edge', {'color': 'r'}, mcolors.to_rgba('r')),
('edge', {'color': 'inherit', 'axes.edgecolor': 'r'},
mcolors.to_rgba('r')),
('edge', {'color': 'g', 'axes.facecolor': 'r'}, mcolors.to_rgba('g'))
]
legend_color_test_ids = [
'same facecolor',
'inherited facecolor',
'different facecolor',
'same edgecolor',
'inherited edgecolor',
'different facecolor',
]
@pytest.mark.parametrize('color_type, param_dict, target', legend_color_tests,
ids=legend_color_test_ids)
def test_legend_colors(color_type, param_dict, target):
param_dict['legend.%scolor' % (color_type, )] = param_dict.pop('color')
get_func = 'get_%scolor' % (color_type, )
with mpl.rc_context(param_dict):
_, ax = plt.subplots()
ax.plot(range(3), label='test')
leg = ax.legend()
assert getattr(leg.legendPatch, get_func)() == target
def test_Issue_1713():
utf32_be = os.path.join(os.path.dirname(__file__),
'test_utf32_be_rcparams.rc')
import locale
with mock.patch('locale.getpreferredencoding', return_value='UTF-32-BE'):
rc = mpl.rc_params_from_file(utf32_be, True, False)
assert rc.get('timezone') == 'UTC'
def generate_validator_testcases(valid):
validation_tests = (
{'validator': validate_bool,
'success': chain(((_, True) for _ in
('t', 'y', 'yes', 'on', 'true', '1', 1, True)),
((_, False) for _ in
('f', 'n', 'no', 'off', 'false', '0', 0, False))),
'fail': ((_, ValueError)
for _ in ('aardvark', 2, -1, [], ))},
{'validator': validate_stringlist,
'success': (('', []),
('a,b', ['a', 'b']),
('aardvark', ['aardvark']),
('aardvark, ', ['aardvark']),
('aardvark, ,', ['aardvark']),
(['a', 'b'], ['a', 'b']),
(('a', 'b'), ['a', 'b']),
(iter(['a', 'b']), ['a', 'b']),
(np.array(['a', 'b']), ['a', 'b']),
((1, 2), ['1', '2']),
(np.array([1, 2]), ['1', '2']),
),
'fail': ((dict(), ValueError),
(1, ValueError),
)
},
{'validator': validate_nseq_int(2),
'success': ((_, [1, 2])
for _ in ('1, 2', [1.5, 2.5], [1, 2],
(1, 2), np.array((1, 2)))),
'fail': ((_, ValueError)
for _ in ('aardvark', ('a', 1),
(1, 2, 3)
))
},
{'validator': validate_nseq_float(2),
'success': ((_, [1.5, 2.5])
for _ in ('1.5, 2.5', [1.5, 2.5], [1.5, 2.5],
(1.5, 2.5), np.array((1.5, 2.5)))),
'fail': ((_, ValueError)
for _ in ('aardvark', ('a', 1),
(1, 2, 3)
))
},
{'validator': validate_cycler,
'success': (('cycler("color", "rgb")',
cycler("color", 'rgb')),
(cycler('linestyle', ['-', '--']),
cycler('linestyle', ['-', '--'])),
("""(cycler("color", ["r", "g", "b"]) +
cycler("mew", [2, 3, 5]))""",
(cycler("color", 'rgb') +
cycler("markeredgewidth", [2, 3, 5]))),
("cycler(c='rgb', lw=[1, 2, 3])",
cycler('color', 'rgb') + cycler('linewidth', [1, 2, 3])),
("cycler('c', 'rgb') * cycler('linestyle', ['-', '--'])",
(cycler('color', 'rgb') *
cycler('linestyle', ['-', '--']))),
(cycler('ls', ['-', '--']),
cycler('linestyle', ['-', '--'])),
(cycler(mew=[2, 5]),
cycler('markeredgewidth', [2, 5])),
),
# This is *so* incredibly important: validate_cycler() eval's
# an arbitrary string! I think I have it locked down enough,
# and that is what this is testing.
# TODO: Note that these tests are actually insufficient, as it may
# be that they raised errors, but still did an action prior to
# raising the exception. We should devise some additional tests
# for that...
'fail': ((4, ValueError), # Gotta be a string or Cycler object
('cycler("bleh, [])', ValueError), # syntax error
('Cycler("linewidth", [1, 2, 3])',
ValueError), # only 'cycler()' function is allowed
('1 + 2', ValueError), # doesn't produce a Cycler object
('os.system("echo Gotcha")', ValueError), # os not available
('import os', ValueError), # should not be able to import
('def badjuju(a): return a; badjuju(cycler("color", "rgb"))',
ValueError), # Should not be able to define anything
# even if it does return a cycler
('cycler("waka", [1, 2, 3])', ValueError), # not a property
('cycler(c=[1, 2, 3])', ValueError), # invalid values
("cycler(lw=['a', 'b', 'c'])", ValueError), # invalid values
(cycler('waka', [1, 3, 5]), ValueError), # not a property
(cycler('color', ['C1', 'r', 'g']), ValueError) # no CN
)
},
{'validator': validate_hatch,
'success': (('--|', '--|'), ('\\oO', '\\oO'),
('/+*/.x', '/+*/.x'), ('', '')),
'fail': (('--_', ValueError),
(8, ValueError),
('X', ValueError)),
},
{'validator': validate_colorlist,
'success': (('r,g,b', ['r', 'g', 'b']),
(['r', 'g', 'b'], ['r', 'g', 'b']),
('r, ,', ['r']),
(['', 'g', 'blue'], ['g', 'blue']),
([np.array([1, 0, 0]), np.array([0, 1, 0])],
np.array([[1, 0, 0], [0, 1, 0]])),
(np.array([[1, 0, 0], [0, 1, 0]]),
np.array([[1, 0, 0], [0, 1, 0]])),
),
'fail': (('fish', ValueError),
),
},
{'validator': validate_color,
'success': (('None', 'none'),
('none', 'none'),
('AABBCC', '#AABBCC'), # RGB hex code
('AABBCC00', '#AABBCC00'), # RGBA hex code
('tab:blue', 'tab:blue'), # named color
('C0', 'C0'), # color from cycle
('(0, 1, 0)', [0.0, 1.0, 0.0]), # RGB tuple
((0, 1, 0), (0, 1, 0)), # non-string version
('(0, 1, 0, 1)', [0.0, 1.0, 0.0, 1.0]), # RGBA tuple
((0, 1, 0, 1), (0, 1, 0, 1)), # non-string version
('(0, 1, "0.5")', [0.0, 1.0, 0.5]), # unusual but valid
),
'fail': (('tab:veryblue', ValueError), # invalid name
('C123', ValueError), # invalid RGB(A) code and cycle index
('(0, 1)', ValueError), # tuple with length < 3
('(0, 1, 0, 1, 0)', ValueError), # tuple with length > 4
('(0, 1, none)', ValueError), # cannot cast none to float
),
},
{'validator': validate_hist_bins,
'success': (('auto', 'auto'),
('10', 10),
('1, 2, 3', [1, 2, 3]),
([1, 2, 3], [1, 2, 3]),
(np.arange(15), np.arange(15))
),
'fail': (('aardvark', ValueError),
)
}
)
# The behavior of _validate_linestyle depends on the version of Python.
# ASCII-compliant bytes arguments should pass on Python 2 because of the
# automatic conversion between bytes and strings. Python 3 does not
# perform such a conversion, so the same cases should raise an exception.
#
# Common cases:
ls_test = {'validator': _validate_linestyle,
'success': (('-', '-'), ('solid', 'solid'),
('--', '--'), ('dashed', 'dashed'),
('-.', '-.'), ('dashdot', 'dashdot'),
(':', ':'), ('dotted', 'dotted'),
('', ''), (' ', ' '),
('None', 'none'), ('none', 'none'),
('DoTtEd', 'dotted'), # case-insensitive
(['1.23', '4.56'], (None, [1.23, 4.56])),
([1.23, 456], (None, [1.23, 456.0])),
([1, 2, 3, 4], (None, [1.0, 2.0, 3.0, 4.0])),
),
'fail': (('aardvark', ValueError), # not a valid string
('dotted'.encode('utf-16'), ValueError), # even on PY2
((None, [1, 2]), ValueError), # (offset, dashes) != OK
((0, [1, 2]), ValueError), # idem
((-1, [1, 2]), ValueError), # idem
([1, 2, 3], ValueError), # sequence with odd length
(1.23, ValueError), # not a sequence
)
}
# Add some cases of bytes arguments that Python 2 can convert silently:
ls_bytes_args = (b'dotted', 'dotted'.encode('ascii'))
if six.PY3:
ls_test['fail'] += tuple((arg, ValueError) for arg in ls_bytes_args)
else:
ls_test['success'] += tuple((arg, 'dotted') for arg in ls_bytes_args)
# Update the validation test sequence.
validation_tests += (ls_test,)
for validator_dict in validation_tests:
validator = validator_dict['validator']
if valid:
for arg, target in validator_dict['success']:
yield validator, arg, target
else:
for arg, error_type in validator_dict['fail']:
yield validator, arg, error_type
@pytest.mark.parametrize('validator, arg, target',
generate_validator_testcases(True))
def test_validator_valid(validator, arg, target):
res = validator(arg)
if isinstance(target, np.ndarray):
assert np.all(res == target)
elif not isinstance(target, Cycler):
assert res == target
else:
# Cyclers can't simply be asserted equal. They don't implement __eq__
assert list(res) == list(target)
@pytest.mark.parametrize('validator, arg, exception_type',
generate_validator_testcases(False))
def test_validator_invalid(validator, arg, exception_type):
with pytest.raises(exception_type):
validator(arg)
def test_keymaps():
key_list = [k for k in mpl.rcParams if 'keymap' in k]
for k in key_list:
assert isinstance(mpl.rcParams[k], list)
def test_rcparams_reset_after_fail():
# There was previously a bug that meant that if rc_context failed and
# raised an exception due to issues in the supplied rc parameters, the
# global rc parameters were left in a modified state.
with mpl.rc_context(rc={'text.usetex': False}):
assert mpl.rcParams['text.usetex'] is False
with pytest.raises(KeyError):
with mpl.rc_context(rc=OrderedDict([('text.usetex', True),
('test.blah', True)])):
pass
assert mpl.rcParams['text.usetex'] is False
def test_if_rctemplate_is_up_to_date():
# This tests if the matplotlibrc.template file
# contains all valid rcParams.
dep1 = mpl._all_deprecated
dep2 = mpl._deprecated_set
deprecated = list(dep1.union(dep2))
#print(deprecated)
path_to_rc = mpl.matplotlib_fname()
with open(path_to_rc, "r") as f:
rclines = f.readlines()
missing = {}
for k,v in mpl.defaultParams.items():
if k[0] == "_":
continue
if k in deprecated:
continue
if "verbose" in k:
continue
found = False
for line in rclines:
if k in line:
found = True
if not found:
missing.update({k:v})
if missing:
raise ValueError("The following params are missing " +
"in the matplotlibrc.template file: {}"
.format(missing.items()))
def test_if_rctemplate_would_be_valid(tmpdir):
# This tests if the matplotlibrc.template file would result in a valid
# rc file if all lines are uncommented.
path_to_rc = mpl.matplotlib_fname()
with open(path_to_rc, "r") as f:
rclines = f.readlines()
newlines = []
for line in rclines:
if line[0] == "#":
newline = line[1:]
else:
newline = line
if "$TEMPLATE_BACKEND" in newline:
newline = "backend : Agg"
if "datapath" in newline:
newline = ""
newlines.append(newline)
d = tmpdir.mkdir('test1')
fname = str(d.join('testrcvalid.temp'))
with open(fname, "w") as f:
f.writelines(newlines)
with pytest.warns(None) as record:
dic = mpl.rc_params_from_file(fname,
fail_on_error=True,
use_default_template=False)
assert len(record) == 0
#d1 = set(dic.keys())
#d2 = set(matplotlib.defaultParams.keys())
#print(d2-d1)
| 19,307 | 38.728395 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_basic.py | from __future__ import absolute_import, division, print_function
import six
import sys
import matplotlib
def test_simple():
assert 1 + 1 == 2
def test_override_builtins():
import pylab
ok_to_override = {
'__name__',
'__doc__',
'__package__',
'__loader__',
'__spec__',
'any',
'all',
'sum',
'divmod'
}
# We could use six.moves.builtins here, but that seems
# to do a little more than just this.
if six.PY3:
builtins = sys.modules['builtins']
else:
builtins = sys.modules['__builtin__']
overridden = False
for key in dir(pylab):
if key in dir(builtins):
if (getattr(pylab, key) != getattr(builtins, key) and
key not in ok_to_override):
print("'%s' was overridden in globals()." % key)
overridden = True
assert not overridden
def test_verbose():
assert isinstance(matplotlib.verbose, matplotlib.Verbose)
| 1,020 | 20.270833 | 65 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_constrainedlayout.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import warnings
import numpy as np
import pytest
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnchoredOffsetbox, DrawingArea
from matplotlib.patches import Rectangle
import matplotlib.gridspec as gridspec
from matplotlib import ticker, rcParams
def example_plot(ax, fontsize=12, nodec=False):
ax.plot([1, 2])
ax.locator_params(nbins=3)
if not nodec:
ax.set_xlabel('x-label', fontsize=fontsize)
ax.set_ylabel('y-label', fontsize=fontsize)
ax.set_title('Title', fontsize=fontsize)
else:
ax.set_xticklabels('')
ax.set_yticklabels('')
def example_pcolor(ax, fontsize=12):
dx, dy = 0.6, 0.6
y, x = np.mgrid[slice(-3, 3 + dy, dy),
slice(-3, 3 + dx, dx)]
z = (1 - x / 2. + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
pcm = ax.pcolormesh(x, y, z, cmap='RdBu_r', vmin=-1., vmax=1.,
rasterized=True)
# ax.locator_params(nbins=3)
ax.set_xlabel('x-label', fontsize=fontsize)
ax.set_ylabel('y-label', fontsize=fontsize)
ax.set_title('Title', fontsize=fontsize)
return pcm
@image_comparison(baseline_images=['constrained_layout1'],
extensions=['png'])
def test_constrained_layout1():
'Test constrained_layout for a single subplot'
fig = plt.figure(constrained_layout=True)
ax = fig.add_subplot(111)
example_plot(ax, fontsize=24)
@image_comparison(baseline_images=['constrained_layout2'],
extensions=['png'])
def test_constrained_layout2():
'Test constrained_layout for 2x2 subplots'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
example_plot(ax, fontsize=24)
@image_comparison(baseline_images=['constrained_layout3'],
extensions=['png'])
def test_constrained_layout3():
'Test constrained_layout for colorbars with subplots'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for nn, ax in enumerate(axs.flatten()):
pcm = example_pcolor(ax, fontsize=24)
if nn == 3:
pad = 0.08
else:
pad = 0.02 # default
fig.colorbar(pcm, ax=ax, pad=pad)
@image_comparison(baseline_images=['constrained_layout4'])
def test_constrained_layout4():
'Test constrained_layout for a single colorbar with subplots'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
pcm = example_pcolor(ax, fontsize=24)
fig.colorbar(pcm, ax=axs, pad=0.01, shrink=0.6)
@image_comparison(baseline_images=['constrained_layout5'],
tol=5.e-2, extensions=['png'])
def test_constrained_layout5():
'''
Test constrained_layout for a single colorbar with subplots,
colorbar bottom
'''
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
pcm = example_pcolor(ax, fontsize=24)
fig.colorbar(pcm, ax=axs,
use_gridspec=False, pad=0.01, shrink=0.6,
location='bottom')
@image_comparison(baseline_images=['constrained_layout6'],
extensions=['png'])
def test_constrained_layout6():
'Test constrained_layout for nested gridspecs'
fig = plt.figure(constrained_layout=True)
gs = gridspec.GridSpec(1, 2, figure=fig)
gsl = gridspec.GridSpecFromSubplotSpec(2, 2, gs[0])
gsr = gridspec.GridSpecFromSubplotSpec(1, 2, gs[1])
axsl = []
for gs in gsl:
ax = fig.add_subplot(gs)
axsl += [ax]
example_plot(ax, fontsize=12)
ax.set_xlabel('x-label\nMultiLine')
axsr = []
for gs in gsr:
ax = fig.add_subplot(gs)
axsr += [ax]
pcm = example_pcolor(ax, fontsize=12)
fig.colorbar(pcm, ax=axsr,
pad=0.01, shrink=0.99, location='bottom',
ticks=ticker.MaxNLocator(nbins=5))
@image_comparison(baseline_images=['constrained_layout8'],
extensions=['png'])
def test_constrained_layout8():
'Test for gridspecs that are not completely full'
fig = plt.figure(figsize=(7, 4), constrained_layout=True)
gs = gridspec.GridSpec(3, 5, figure=fig)
axs = []
j = 1
for i in [0, 1]:
ax = fig.add_subplot(gs[j, i])
axs += [ax]
pcm = example_pcolor(ax, fontsize=10)
if i > 0:
ax.set_ylabel('')
if j < 1:
ax.set_xlabel('')
ax.set_title('')
j = 0
for i in [2, 4]:
ax = fig.add_subplot(gs[j, i])
axs += [ax]
pcm = example_pcolor(ax, fontsize=10)
if i > 0:
ax.set_ylabel('')
if j < 1:
ax.set_xlabel('')
ax.set_title('')
ax = fig.add_subplot(gs[2, :])
axs += [ax]
pcm = example_pcolor(ax, fontsize=10)
fig.colorbar(pcm, ax=axs, pad=0.01, shrink=0.6)
def test_constrained_layout7():
'Test for proper warning if fig not set in GridSpec'
with pytest.warns(UserWarning, match='Calling figure.constrained_layout, '
'but figure not setup to do constrained layout'):
fig = plt.figure(constrained_layout=True)
gs = gridspec.GridSpec(1, 2)
gsl = gridspec.GridSpecFromSubplotSpec(2, 2, gs[0])
gsr = gridspec.GridSpecFromSubplotSpec(1, 2, gs[1])
axsl = []
for gs in gsl:
ax = fig.add_subplot(gs)
# need to trigger a draw to get warning
fig.draw(fig.canvas.get_renderer())
@image_comparison(baseline_images=['constrained_layout8'],
extensions=['png'])
def test_constrained_layout8():
'Test for gridspecs that are not completely full'
fig = plt.figure(figsize=(10, 5), constrained_layout=True)
gs = gridspec.GridSpec(3, 5, figure=fig)
axs = []
j = 1
for i in [0, 4]:
ax = fig.add_subplot(gs[j, i])
axs += [ax]
pcm = example_pcolor(ax, fontsize=9)
if i > 0:
ax.set_ylabel('')
if j < 1:
ax.set_xlabel('')
ax.set_title('')
j = 0
for i in [1]:
ax = fig.add_subplot(gs[j, i])
axs += [ax]
pcm = example_pcolor(ax, fontsize=9)
if i > 0:
ax.set_ylabel('')
if j < 1:
ax.set_xlabel('')
ax.set_title('')
ax = fig.add_subplot(gs[2, :])
axs += [ax]
pcm = example_pcolor(ax, fontsize=9)
fig.colorbar(pcm, ax=axs, pad=0.01, shrink=0.6)
@image_comparison(baseline_images=['constrained_layout9'],
extensions=['png'])
def test_constrained_layout9():
'Test for handling suptitle and for sharex and sharey'
fig, axs = plt.subplots(2, 2, constrained_layout=True,
sharex=False, sharey=False)
# ax = fig.add_subplot(111)
for ax in axs.flatten():
pcm = example_pcolor(ax, fontsize=24)
ax.set_xlabel('')
ax.set_ylabel('')
ax.set_aspect(2.)
fig.colorbar(pcm, ax=axs, pad=0.01, shrink=0.6)
fig.suptitle('Test Suptitle', fontsize=28)
@image_comparison(baseline_images=['constrained_layout10'],
extensions=['png'])
def test_constrained_layout10():
'Test for handling legend outside axis'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
ax.plot(np.arange(12), label='This is a label')
ax.legend(loc='center left', bbox_to_anchor=(0.8, 0.5))
@image_comparison(baseline_images=['constrained_layout11'],
extensions=['png'])
def test_constrained_layout11():
'Test for multiple nested gridspecs '
fig = plt.figure(constrained_layout=True, figsize=(10, 3))
gs0 = gridspec.GridSpec(1, 2, figure=fig)
gsl = gridspec.GridSpecFromSubplotSpec(1, 2, gs0[0])
gsl0 = gridspec.GridSpecFromSubplotSpec(2, 2, gsl[1])
ax = fig.add_subplot(gs0[1])
example_plot(ax, fontsize=9)
axs = []
for gs in gsl0:
ax = fig.add_subplot(gs)
axs += [ax]
pcm = example_pcolor(ax, fontsize=9)
fig.colorbar(pcm, ax=axs, shrink=0.6, aspect=70.)
ax = fig.add_subplot(gsl[0])
example_plot(ax, fontsize=9)
@image_comparison(baseline_images=['constrained_layout11rat'],
extensions=['png'])
def test_constrained_layout11rat():
'Test for multiple nested gridspecs with width_ratios'
fig = plt.figure(constrained_layout=True, figsize=(10, 3))
gs0 = gridspec.GridSpec(1, 2, figure=fig, width_ratios=[6., 1.])
gsl = gridspec.GridSpecFromSubplotSpec(1, 2, gs0[0])
gsl0 = gridspec.GridSpecFromSubplotSpec(2, 2, gsl[1],
height_ratios=[2., 1.])
ax = fig.add_subplot(gs0[1])
example_plot(ax, fontsize=9)
axs = []
for gs in gsl0:
ax = fig.add_subplot(gs)
axs += [ax]
pcm = example_pcolor(ax, fontsize=9)
fig.colorbar(pcm, ax=axs, shrink=0.6, aspect=70.)
ax = fig.add_subplot(gsl[0])
example_plot(ax, fontsize=9)
@image_comparison(baseline_images=['constrained_layout12'],
extensions=['png'])
def test_constrained_layout12():
'Test that very unbalanced labeling still works.'
fig = plt.figure(constrained_layout=True)
gs0 = gridspec.GridSpec(6, 2, figure=fig)
ax1 = fig.add_subplot(gs0[:3, 1])
ax2 = fig.add_subplot(gs0[3:, 1])
example_plot(ax1, fontsize=24)
example_plot(ax2, fontsize=24)
ax = fig.add_subplot(gs0[0:2, 0])
example_plot(ax, nodec=True)
ax = fig.add_subplot(gs0[2:4, 0])
example_plot(ax, nodec=True)
ax = fig.add_subplot(gs0[4:, 0])
example_plot(ax, nodec=True)
ax.set_xlabel('x-label')
@image_comparison(baseline_images=['constrained_layout13'], tol=2.e-2,
extensions=['png'])
def test_constrained_layout13():
'Test that padding works.'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
pcm = example_pcolor(ax, fontsize=12)
fig.colorbar(pcm, ax=ax, shrink=0.6, aspect=20., pad=0.02)
fig.set_constrained_layout_pads(w_pad=24./72., h_pad=24./72.)
@image_comparison(baseline_images=['constrained_layout14'],
extensions=['png'])
def test_constrained_layout14():
'Test that padding works.'
fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flatten():
pcm = example_pcolor(ax, fontsize=12)
fig.colorbar(pcm, ax=ax, shrink=0.6, aspect=20., pad=0.02)
fig.set_constrained_layout_pads(
w_pad=3./72., h_pad=3./72.,
hspace=0.2, wspace=0.2)
@image_comparison(baseline_images=['constrained_layout15'],
extensions=['png'])
def test_constrained_layout15():
'Test that rcparams work.'
rcParams['figure.constrained_layout.use'] = True
fig, axs = plt.subplots(2, 2)
for ax in axs.flatten():
example_plot(ax, fontsize=12)
@image_comparison(baseline_images=['constrained_layout16'],
extensions=['png'])
def test_constrained_layout16():
'Test ax.set_position.'
fig, ax = plt.subplots(constrained_layout=True)
example_plot(ax, fontsize=12)
ax2 = fig.add_axes([0.2, 0.2, 0.4, 0.4])
@image_comparison(baseline_images=['constrained_layout17'],
extensions=['png'])
def test_constrained_layout17():
'Test uneven gridspecs'
fig = plt.figure(constrained_layout=True)
gs = gridspec.GridSpec(3, 3, figure=fig)
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1:])
ax3 = fig.add_subplot(gs[1:, 0:2])
ax4 = fig.add_subplot(gs[1:, -1])
example_plot(ax1)
example_plot(ax2)
example_plot(ax3)
example_plot(ax4)
def test_constrained_layout18():
'Test twinx'
fig, ax = plt.subplots(constrained_layout=True)
ax2 = ax.twinx()
example_plot(ax)
example_plot(ax2, fontsize=24)
fig.canvas.draw()
assert all(ax.get_position().extents == ax2.get_position().extents)
def test_constrained_layout19():
'Test twiny'
fig, ax = plt.subplots(constrained_layout=True)
ax2 = ax.twiny()
example_plot(ax)
example_plot(ax2, fontsize=24)
ax2.set_title('')
ax.set_title('')
fig.canvas.draw()
assert all(ax.get_position().extents == ax2.get_position().extents)
def test_constrained_layout20():
'Smoke test cl does not mess up added axes'
gx = np.linspace(-5, 5, 4)
img = np.hypot(gx, gx[:, None])
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1])
mesh = ax.pcolormesh(gx, gx, img)
fig.colorbar(mesh)
| 12,468 | 30.890026 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_axes.py | from __future__ import absolute_import, division, print_function
import six
from six.moves import xrange
from itertools import chain, product
from distutils.version import LooseVersion
import io
import datetime
import pytz
import numpy as np
from numpy import ma
from cycler import cycler
import pytest
import warnings
import matplotlib
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.markers as mmarkers
import matplotlib.patches as mpatches
import matplotlib.colors as mcolors
from numpy.testing import assert_allclose, assert_array_equal
from matplotlib.cbook import (
IgnoredKeywordWarning, MatplotlibDeprecationWarning)
from matplotlib.cbook._backports import broadcast_to
# Note: Some test cases are run twice: once normally and once with labeled data
# These two must be defined in the same test function or need to have
# different baseline images to prevent race conditions when pytest runs
# the tests with multiple threads.
def test_get_labels():
fig, ax = plt.subplots()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
assert ax.get_xlabel() == 'x label'
assert ax.get_ylabel() == 'y label'
@image_comparison(baseline_images=['acorr'], extensions=['png'], style='mpl20')
def test_acorr():
np.random.seed(19680801)
n = 512
x = np.random.normal(0, 1, n).cumsum()
fig, ax = plt.subplots()
ax.acorr(x, maxlags=n - 1, label='acorr')
ax.legend()
@image_comparison(baseline_images=['spy'], extensions=['png'], style='mpl20')
def test_spy():
np.random.seed(19680801)
a = np.ones(32 * 32)
a[:16 * 32] = 0
np.random.shuffle(a)
a = np.reshape(a, (32, 32))
fig, ax = plt.subplots()
ax.spy(a)
@image_comparison(baseline_images=['matshow'],
extensions=['png'], style='mpl20')
def test_matshow():
np.random.seed(19680801)
a = np.random.rand(32, 32)
fig, ax = plt.subplots()
ax.matshow(a)
@image_comparison(baseline_images=['formatter_ticker_001',
'formatter_ticker_002',
'formatter_ticker_003',
'formatter_ticker_004',
'formatter_ticker_005',
])
def test_formatter_ticker():
import matplotlib.testing.jpl_units as units
units.register()
# This should affect the tick size. (Tests issue #543)
matplotlib.rcParams['lines.markeredgewidth'] = 30
# This essentially test to see if user specified labels get overwritten
# by the auto labeler functionality of the axes.
xdata = [x*units.sec for x in range(10)]
ydata1 = [(1.5*y - 0.5)*units.km for y in range(10)]
ydata2 = [(1.75*y - 1.0)*units.km for y in range(10)]
fig = plt.figure()
ax = plt.subplot(111)
ax.set_xlabel("x-label 001")
fig = plt.figure()
ax = plt.subplot(111)
ax.set_xlabel("x-label 001")
ax.plot(xdata, ydata1, color='blue', xunits="sec")
fig = plt.figure()
ax = plt.subplot(111)
ax.set_xlabel("x-label 001")
ax.plot(xdata, ydata1, color='blue', xunits="sec")
ax.set_xlabel("x-label 003")
fig = plt.figure()
ax = plt.subplot(111)
ax.plot(xdata, ydata1, color='blue', xunits="sec")
ax.plot(xdata, ydata2, color='green', xunits="hour")
ax.set_xlabel("x-label 004")
# See SF bug 2846058
# https://sourceforge.net/tracker/?func=detail&aid=2846058&group_id=80706&atid=560720
fig = plt.figure()
ax = plt.subplot(111)
ax.plot(xdata, ydata1, color='blue', xunits="sec")
ax.plot(xdata, ydata2, color='green', xunits="hour")
ax.set_xlabel("x-label 005")
ax.autoscale_view()
@image_comparison(baseline_images=["formatter_large_small"])
def test_formatter_large_small():
# github issue #617, pull #619
if LooseVersion(np.__version__) >= LooseVersion('1.11.0'):
pytest.skip("Fall out from a fixed numpy bug")
fig, ax = plt.subplots(1)
x = [0.500000001, 0.500000002]
y = [1e64, 1.1e64]
ax.plot(x, y)
@image_comparison(baseline_images=["twin_axis_locaters_formatters"])
def test_twin_axis_locaters_formatters():
vals = np.linspace(0, 1, num=5, endpoint=True)
locs = np.sin(np.pi * vals / 2.0)
majl = plt.FixedLocator(locs)
minl = plt.FixedLocator([0.1, 0.2, 0.3])
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
ax1.plot([0.1, 100], [0, 1])
ax1.yaxis.set_major_locator(majl)
ax1.yaxis.set_minor_locator(minl)
ax1.yaxis.set_major_formatter(plt.FormatStrFormatter('%08.2lf'))
ax1.yaxis.set_minor_formatter(plt.FixedFormatter(['tricks', 'mind',
'jedi']))
ax1.xaxis.set_major_locator(plt.LinearLocator())
ax1.xaxis.set_minor_locator(plt.FixedLocator([15, 35, 55, 75]))
ax1.xaxis.set_major_formatter(plt.FormatStrFormatter('%05.2lf'))
ax1.xaxis.set_minor_formatter(plt.FixedFormatter(['c', '3', 'p', 'o']))
ax2 = ax1.twiny()
ax3 = ax1.twinx()
def test_twinx_cla():
fig, ax = plt.subplots()
ax2 = ax.twinx()
ax3 = ax2.twiny()
plt.draw()
assert not ax2.xaxis.get_visible()
assert not ax2.patch.get_visible()
ax2.cla()
ax3.cla()
assert not ax2.xaxis.get_visible()
assert not ax2.patch.get_visible()
assert ax2.yaxis.get_visible()
assert ax3.xaxis.get_visible()
assert not ax3.patch.get_visible()
assert not ax3.yaxis.get_visible()
assert ax.xaxis.get_visible()
assert ax.patch.get_visible()
assert ax.yaxis.get_visible()
@image_comparison(baseline_images=['twin_autoscale'], extensions=['png'])
def test_twinx_axis_scales():
x = np.array([0, 0.5, 1])
y = 0.5 * x
x2 = np.array([0, 1, 2])
y2 = 2 * x2
fig = plt.figure()
ax = fig.add_axes((0, 0, 1, 1), autoscalex_on=False, autoscaley_on=False)
ax.plot(x, y, color='blue', lw=10)
ax2 = plt.twinx(ax)
ax2.plot(x2, y2, 'r--', lw=5)
ax.margins(0, 0)
ax2.margins(0, 0)
def test_twin_inherit_autoscale_setting():
fig, ax = plt.subplots()
ax_x_on = ax.twinx()
ax.set_autoscalex_on(False)
ax_x_off = ax.twinx()
assert ax_x_on.get_autoscalex_on()
assert not ax_x_off.get_autoscalex_on()
ax_y_on = ax.twiny()
ax.set_autoscaley_on(False)
ax_y_off = ax.twiny()
assert ax_y_on.get_autoscaley_on()
assert not ax_y_off.get_autoscaley_on()
def test_inverted_cla():
# Github PR #5450. Setting autoscale should reset
# axes to be non-inverted.
# plotting an image, then 1d graph, axis is now down
fig = plt.figure(0)
ax = fig.gca()
# 1. test that a new axis is not inverted per default
assert not ax.xaxis_inverted()
assert not ax.yaxis_inverted()
img = np.random.random((100, 100))
ax.imshow(img)
# 2. test that a image axis is inverted
assert not ax.xaxis_inverted()
assert ax.yaxis_inverted()
# 3. test that clearing and plotting a line, axes are
# not inverted
ax.cla()
x = np.linspace(0, 2*np.pi, 100)
ax.plot(x, np.cos(x))
assert not ax.xaxis_inverted()
assert not ax.yaxis_inverted()
# 4. autoscaling should not bring back axes to normal
ax.cla()
ax.imshow(img)
plt.autoscale()
assert not(ax.xaxis_inverted())
assert ax.yaxis_inverted()
# 5. two shared axes. Clearing the master axis should bring axes in shared
# axes back to normal
ax0 = plt.subplot(211)
ax1 = plt.subplot(212, sharey=ax0)
ax0.imshow(img)
ax1.plot(x, np.cos(x))
ax0.cla()
assert not(ax1.yaxis_inverted())
ax1.cla()
# 6. clearing the nonmaster should not touch limits
ax0.imshow(img)
ax1.plot(x, np.cos(x))
ax1.cla()
assert ax.yaxis_inverted()
# clean up
plt.close(fig)
@image_comparison(baseline_images=["minorticks_on_rcParams_both"],
extensions=['png'])
def test_minorticks_on_rcParams_both():
fig = plt.figure()
matplotlib.rcParams['xtick.minor.visible'] = True
matplotlib.rcParams['ytick.minor.visible'] = True
plt.plot([0, 1], [0, 1])
plt.axis([0, 1, 0, 1])
@image_comparison(baseline_images=["autoscale_tiny_range"], remove_text=True)
def test_autoscale_tiny_range():
# github pull #904
fig, ax = plt.subplots(2, 2)
ax = ax.flatten()
for i in xrange(4):
y1 = 10**(-11 - i)
ax[i].plot([0, 1], [1, 1 + y1])
@pytest.mark.style('default')
def test_autoscale_tight():
fig, ax = plt.subplots(1, 1)
ax.plot([1, 2, 3, 4])
ax.autoscale(enable=True, axis='x', tight=False)
ax.autoscale(enable=True, axis='y', tight=True)
assert_allclose(ax.get_xlim(), (-0.15, 3.15))
assert_allclose(ax.get_ylim(), (1.0, 4.0))
@pytest.mark.style('default')
def test_autoscale_log_shared():
# related to github #7587
# array starts at zero to trigger _minpos handling
x = np.arange(100, dtype=float)
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)
ax1.loglog(x, x)
ax2.semilogx(x, x)
ax1.autoscale(tight=True)
ax2.autoscale(tight=True)
plt.draw()
lims = (x[1], x[-1])
assert_allclose(ax1.get_xlim(), lims)
assert_allclose(ax1.get_ylim(), lims)
assert_allclose(ax2.get_xlim(), lims)
assert_allclose(ax2.get_ylim(), (x[0], x[-1]))
@pytest.mark.style('default')
def test_use_sticky_edges():
fig, ax = plt.subplots()
ax.imshow([[0, 1], [2, 3]], origin='lower')
assert_allclose(ax.get_xlim(), (-0.5, 1.5))
assert_allclose(ax.get_ylim(), (-0.5, 1.5))
ax.use_sticky_edges = False
ax.autoscale()
xlim = (-0.5 - 2 * ax._xmargin, 1.5 + 2 * ax._xmargin)
ylim = (-0.5 - 2 * ax._ymargin, 1.5 + 2 * ax._ymargin)
assert_allclose(ax.get_xlim(), xlim)
assert_allclose(ax.get_ylim(), ylim)
# Make sure it is reversible:
ax.use_sticky_edges = True
ax.autoscale()
assert_allclose(ax.get_xlim(), (-0.5, 1.5))
assert_allclose(ax.get_ylim(), (-0.5, 1.5))
@image_comparison(baseline_images=['offset_points'],
remove_text=True)
def test_basic_annotate():
# Setup some data
t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2.0*np.pi * t)
# Offset Points
fig = plt.figure()
ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1, 5), ylim=(-3, 5))
line, = ax.plot(t, s, lw=3, color='purple')
ax.annotate('local max', xy=(3, 1), xycoords='data',
xytext=(3, 3), textcoords='offset points')
@image_comparison(baseline_images=['arrow_simple'],
extensions=['png'], remove_text=True)
def test_arrow_simple():
# Simple image test for ax.arrow
# kwargs that take discrete values
length_includes_head = (True, False)
shape = ('full', 'left', 'right')
head_starts_at_zero = (True, False)
# Create outer product of values
kwargs = list(product(length_includes_head, shape, head_starts_at_zero))
fig, axs = plt.subplots(3, 4)
for i, (ax, kwarg) in enumerate(zip(axs.flatten(), kwargs)):
ax.set_xlim(-2, 2)
ax.set_ylim(-2, 2)
# Unpack kwargs
(length_includes_head, shape, head_starts_at_zero) = kwarg
theta = 2 * np.pi * i / 12
# Draw arrow
ax.arrow(0, 0, np.sin(theta), np.cos(theta),
width=theta/100,
length_includes_head=length_includes_head,
shape=shape,
head_starts_at_zero=head_starts_at_zero,
head_width=theta / 10,
head_length=theta / 10)
def test_annotate_default_arrow():
# Check that we can make an annotation arrow with only default properties.
fig, ax = plt.subplots()
ann = ax.annotate("foo", (0, 1), xytext=(2, 3))
assert ann.arrow_patch is None
ann = ax.annotate("foo", (0, 1), xytext=(2, 3), arrowprops={})
assert ann.arrow_patch is not None
@image_comparison(baseline_images=['polar_axes'], style='default')
def test_polar_annotations():
# you can specify the xypoint and the xytext in different
# positions and coordinate systems, and optionally turn on a
# connecting line and mark the point with a marker. Annotations
# work on polar axes too. In the example below, the xy point is
# in native coordinates (xycoords defaults to 'data'). For a
# polar axes, this is in (theta, radius) space. The text in this
# example is placed in the fractional figure coordinate system.
# Text keyword args like horizontal and vertical alignment are
# respected
# Setup some data
r = np.arange(0.0, 1.0, 0.001)
theta = 2.0 * 2.0 * np.pi * r
fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
line, = ax.plot(theta, r, color='#ee8d18', lw=3)
line, = ax.plot((0, 0), (0, 1), color="#0000ff", lw=1)
ind = 800
thisr, thistheta = r[ind], theta[ind]
ax.plot([thistheta], [thisr], 'o')
ax.annotate('a polar annotation',
xy=(thistheta, thisr), # theta, radius
xytext=(0.05, 0.05), # fraction, fraction
textcoords='figure fraction',
arrowprops=dict(facecolor='black', shrink=0.05),
horizontalalignment='left',
verticalalignment='baseline',
)
ax.tick_params(axis='x', tick1On=True, tick2On=True, direction='out')
@image_comparison(baseline_images=['polar_coords'], style='default',
remove_text=True)
def test_polar_coord_annotations():
# You can also use polar notation on a catesian axes. Here the
# native coordinate system ('data') is cartesian, so you need to
# specify the xycoords and textcoords as 'polar' if you want to
# use (theta, radius)
from matplotlib.patches import Ellipse
el = Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5)
fig = plt.figure()
ax = fig.add_subplot(111, aspect='equal')
ax.add_artist(el)
el.set_clip_box(ax.bbox)
ax.annotate('the top',
xy=(np.pi/2., 10.), # theta, radius
xytext=(np.pi/3, 20.), # theta, radius
xycoords='polar',
textcoords='polar',
arrowprops=dict(facecolor='black', shrink=0.05),
horizontalalignment='left',
verticalalignment='baseline',
clip_on=True, # clip to the axes bounding box
)
ax.set_xlim(-20, 20)
ax.set_ylim(-20, 20)
@image_comparison(baseline_images=['fill_units'], extensions=['png'],
savefig_kwarg={'dpi': 60})
def test_fill_units():
from datetime import datetime
import matplotlib.testing.jpl_units as units
units.register()
# generate some data
t = units.Epoch("ET", dt=datetime(2009, 4, 27))
value = 10.0 * units.deg
day = units.Duration("ET", 24.0 * 60.0 * 60.0)
fig = plt.figure()
# Top-Left
ax1 = fig.add_subplot(221)
ax1.plot([t], [value], yunits='deg', color='red')
ax1.fill([733525.0, 733525.0, 733526.0, 733526.0],
[0.0, 0.0, 90.0, 0.0], 'b')
# Top-Right
ax2 = fig.add_subplot(222)
ax2.plot([t], [value], yunits='deg', color='red')
ax2.fill([t, t, t + day, t + day],
[0.0, 0.0, 90.0, 0.0], 'b')
# Bottom-Left
ax3 = fig.add_subplot(223)
ax3.plot([t], [value], yunits='deg', color='red')
ax3.fill([733525.0, 733525.0, 733526.0, 733526.0],
[0 * units.deg, 0 * units.deg, 90 * units.deg, 0 * units.deg],
'b')
# Bottom-Right
ax4 = fig.add_subplot(224)
ax4.plot([t], [value], yunits='deg', color='red')
ax4.fill([t, t, t + day, t + day],
[0 * units.deg, 0 * units.deg, 90 * units.deg, 0 * units.deg],
facecolor="blue")
fig.autofmt_xdate()
@image_comparison(baseline_images=['single_point', 'single_point'])
def test_single_point():
# Issue #1796: don't let lines.marker affect the grid
matplotlib.rcParams['lines.marker'] = 'o'
matplotlib.rcParams['axes.grid'] = True
fig = plt.figure()
plt.subplot(211)
plt.plot([0], [0], 'o')
plt.subplot(212)
plt.plot([1], [1], 'o')
# Reuse testcase from above for a labeled data test
data = {'a': [0], 'b': [1]}
fig = plt.figure()
plt.subplot(211)
plt.plot('a', 'a', 'o', data=data)
plt.subplot(212)
plt.plot('b', 'b', 'o', data=data)
@image_comparison(baseline_images=['single_date'])
def test_single_date():
time1 = [721964.0]
data1 = [-65.54]
fig = plt.figure()
plt.subplot(211)
plt.plot_date(time1, data1, 'o', color='r')
plt.subplot(212)
plt.plot(time1, data1, 'o', color='r')
@image_comparison(baseline_images=['shaped_data'])
def test_shaped_data():
xdata = np.array([[0.53295185, 0.23052951, 0.19057629, 0.66724975,
0.96577916, 0.73136095, 0.60823287, 0.01792100,
0.29744742, 0.27164665],
[0.27980120, 0.25814229, 0.02818193, 0.12966456,
0.57446277, 0.58167607, 0.71028245, 0.69112737,
0.89923072, 0.99072476],
[0.81218578, 0.80464528, 0.76071809, 0.85616314,
0.12757994, 0.94324936, 0.73078663, 0.09658102,
0.60703967, 0.77664978],
[0.28332265, 0.81479711, 0.86985333, 0.43797066,
0.32540082, 0.43819229, 0.92230363, 0.49414252,
0.68168256, 0.05922372],
[0.10721335, 0.93904142, 0.79163075, 0.73232848,
0.90283839, 0.68408046, 0.25502302, 0.95976614,
0.59214115, 0.13663711],
[0.28087456, 0.33127607, 0.15530412, 0.76558121,
0.83389773, 0.03735974, 0.98717738, 0.71432229,
0.54881366, 0.86893953],
[0.77995937, 0.99555600, 0.29688434, 0.15646162,
0.05184800, 0.37161935, 0.12998491, 0.09377296,
0.36882507, 0.36583435],
[0.37851836, 0.05315792, 0.63144617, 0.25003433,
0.69586032, 0.11393988, 0.92362096, 0.88045438,
0.93530252, 0.68275072],
[0.86486596, 0.83236675, 0.82960664, 0.57796630,
0.25724233, 0.84841095, 0.90862812, 0.64414887,
0.35652720, 0.71026066],
[0.01383268, 0.34060930, 0.76084285, 0.70800694,
0.87634056, 0.08213693, 0.54655021, 0.98123181,
0.44080053, 0.86815815]])
y1 = np.arange(10).reshape((1, -1))
y2 = np.arange(10).reshape((-1, 1))
fig = plt.figure()
plt.subplot(411)
plt.plot(y1)
plt.subplot(412)
plt.plot(y2)
plt.subplot(413)
with pytest.raises(ValueError):
plt.plot((y1, y2))
plt.subplot(414)
plt.plot(xdata[:, 1], xdata[1, :], 'o')
@image_comparison(baseline_images=['const_xy'])
def test_const_xy():
fig = plt.figure()
plt.subplot(311)
plt.plot(np.arange(10), np.ones((10,)))
plt.subplot(312)
plt.plot(np.ones((10,)), np.arange(10))
plt.subplot(313)
plt.plot(np.ones((10,)), np.ones((10,)), 'o')
@image_comparison(baseline_images=['polar_wrap_180', 'polar_wrap_360'],
style='default')
def test_polar_wrap():
fig = plt.figure()
plt.subplot(111, polar=True)
plt.polar(np.deg2rad([179, -179]), [0.2, 0.1], "b.-")
plt.polar(np.deg2rad([179, 181]), [0.2, 0.1], "g.-")
plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
assert len(fig.axes) == 1, 'More than one polar axes created.'
fig = plt.figure()
plt.subplot(111, polar=True)
plt.polar(np.deg2rad([2, -2]), [0.2, 0.1], "b.-")
plt.polar(np.deg2rad([2, 358]), [0.2, 0.1], "g.-")
plt.polar(np.deg2rad([358, 2]), [0.2, 0.1], "r.-")
plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
@image_comparison(baseline_images=['polar_units', 'polar_units_2'],
style='default')
def test_polar_units():
import matplotlib.testing.jpl_units as units
units.register()
pi = np.pi
deg = units.deg
km = units.km
x1 = [pi/6.0, pi/4.0, pi/3.0, pi/2.0]
x2 = [30.0*deg, 45.0*deg, 60.0*deg, 90.0*deg]
y1 = [1.0, 2.0, 3.0, 4.0]
y2 = [4.0, 3.0, 2.0, 1.0]
fig = plt.figure()
plt.polar(x2, y1, color="blue")
# polar(x2, y1, color = "red", xunits="rad")
# polar(x2, y2, color = "green")
fig = plt.figure()
# make sure runits and theta units work
y1 = [y*km for y in y1]
plt.polar(x2, y1, color="blue", thetaunits="rad", runits="km")
assert isinstance(plt.gca().get_xaxis().get_major_formatter(),
units.UnitDblFormatter)
@image_comparison(baseline_images=['polar_rmin'], style='default')
def test_polar_rmin():
r = np.arange(0, 3.0, 0.01)
theta = 2*np.pi*r
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True)
ax.plot(theta, r)
ax.set_rmax(2.0)
ax.set_rmin(0.5)
@image_comparison(baseline_images=['polar_negative_rmin'], style='default')
def test_polar_negative_rmin():
r = np.arange(-3.0, 0.0, 0.01)
theta = 2*np.pi*r
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True)
ax.plot(theta, r)
ax.set_rmax(0.0)
ax.set_rmin(-3.0)
@image_comparison(baseline_images=['polar_rorigin'], style='default')
def test_polar_rorigin():
r = np.arange(0, 3.0, 0.01)
theta = 2*np.pi*r
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True)
ax.plot(theta, r)
ax.set_rmax(2.0)
ax.set_rmin(0.5)
ax.set_rorigin(0.0)
@image_comparison(baseline_images=['polar_theta_position'], style='default')
def test_polar_theta_position():
r = np.arange(0, 3.0, 0.01)
theta = 2*np.pi*r
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True)
ax.plot(theta, r)
ax.set_theta_zero_location("NW", 30)
ax.set_theta_direction('clockwise')
@image_comparison(baseline_images=['polar_rlabel_position'], style='default')
def test_polar_rlabel_position():
fig = plt.figure()
ax = fig.add_subplot(111, projection='polar')
ax.set_rlabel_position(315)
ax.tick_params(rotation='auto')
@image_comparison(baseline_images=['polar_theta_wedge'], style='default',
tol=0.01 if six.PY2 else 0)
def test_polar_theta_limits():
r = np.arange(0, 3.0, 0.01)
theta = 2*np.pi*r
theta_mins = np.arange(15.0, 361.0, 90.0)
theta_maxs = np.arange(50.0, 361.0, 90.0)
DIRECTIONS = ('out', 'in', 'inout')
fig, axes = plt.subplots(len(theta_mins), len(theta_maxs),
subplot_kw={'polar': True},
figsize=(8, 6))
for i, start in enumerate(theta_mins):
for j, end in enumerate(theta_maxs):
ax = axes[i, j]
ax.plot(theta, r)
if start < end:
ax.set_thetamin(start)
ax.set_thetamax(end)
else:
# Plot with clockwise orientation instead.
ax.set_thetamin(end)
ax.set_thetamax(start)
ax.set_theta_direction('clockwise')
ax.tick_params(tick1On=True, tick2On=True,
direction=DIRECTIONS[i % len(DIRECTIONS)],
rotation='auto')
ax.yaxis.set_tick_params(label2On=True, rotation='auto')
@image_comparison(baseline_images=['axvspan_epoch'])
def test_axvspan_epoch():
from datetime import datetime
import matplotlib.testing.jpl_units as units
units.register()
# generate some data
t0 = units.Epoch("ET", dt=datetime(2009, 1, 20))
tf = units.Epoch("ET", dt=datetime(2009, 1, 21))
dt = units.Duration("ET", units.day.convert("sec"))
fig = plt.figure()
plt.axvspan(t0, tf, facecolor="blue", alpha=0.25)
ax = plt.gca()
ax.set_xlim(t0 - 5.0*dt, tf + 5.0*dt)
@image_comparison(baseline_images=['axhspan_epoch'])
def test_axhspan_epoch():
from datetime import datetime
import matplotlib.testing.jpl_units as units
units.register()
# generate some data
t0 = units.Epoch("ET", dt=datetime(2009, 1, 20))
tf = units.Epoch("ET", dt=datetime(2009, 1, 21))
dt = units.Duration("ET", units.day.convert("sec"))
fig = plt.figure()
plt.axhspan(t0, tf, facecolor="blue", alpha=0.25)
ax = plt.gca()
ax.set_ylim(t0 - 5.0*dt, tf + 5.0*dt)
@image_comparison(baseline_images=['hexbin_extent', 'hexbin_extent'],
remove_text=True, extensions=['png'])
def test_hexbin_extent():
# this test exposes sf bug 2856228
fig = plt.figure()
ax = fig.add_subplot(111)
data = (np.arange(2000) / 2000).reshape((2, 1000))
x, y = data
ax.hexbin(x, y, extent=[.1, .3, .6, .7])
# Reuse testcase from above for a labeled data test
data = {"x": x, "y": y}
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hexbin("x", "y", extent=[.1, .3, .6, .7], data=data)
@image_comparison(baseline_images=['hexbin_empty'], remove_text=True,
extensions=['png'])
def test_hexbin_empty():
# From #3886: creating hexbin from empty dataset raises ValueError
ax = plt.gca()
ax.hexbin([], [])
def test_hexbin_pickable():
# From #1973: Test that picking a hexbin collection works
class FauxMouseEvent:
def __init__(self, x, y):
self.x = x
self.y = y
fig = plt.figure()
ax = fig.add_subplot(111)
data = (np.arange(200) / 200).reshape((2, 100))
x, y = data
hb = ax.hexbin(x, y, extent=[.1, .3, .6, .7], picker=-1)
assert hb.contains(FauxMouseEvent(400, 300))[0]
@image_comparison(baseline_images=['hexbin_log'],
remove_text=True,
extensions=['png'])
def test_hexbin_log():
# Issue #1636
fig = plt.figure()
np.random.seed(0)
n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
y = np.power(2, y * 0.5)
ax = fig.add_subplot(111)
ax.hexbin(x, y, yscale='log')
def test_inverted_limits():
# Test gh:1553
# Calling invert_xaxis prior to plotting should not disable autoscaling
# while still maintaining the inverted direction
fig = plt.figure()
ax = fig.gca()
ax.invert_xaxis()
ax.plot([-5, -3, 2, 4], [1, 2, -3, 5])
assert ax.get_xlim() == (4, -5)
assert ax.get_ylim() == (-3, 5)
plt.close()
fig = plt.figure()
ax = fig.gca()
ax.invert_yaxis()
ax.plot([-5, -3, 2, 4], [1, 2, -3, 5])
assert ax.get_xlim() == (-5, 4)
assert ax.get_ylim() == (5, -3)
plt.close()
@image_comparison(baseline_images=['nonfinite_limits'])
def test_nonfinite_limits():
x = np.arange(0., np.e, 0.01)
# silence divide by zero warning from log(0)
olderr = np.seterr(divide='ignore')
try:
y = np.log(x)
finally:
np.seterr(**olderr)
x[len(x)//2] = np.nan
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y)
@image_comparison(baseline_images=['imshow', 'imshow'],
remove_text=True, style='mpl20')
def test_imshow():
# Create a NxN image
N = 100
(x, y) = np.indices((N, N))
x -= N//2
y -= N//2
r = np.sqrt(x**2+y**2-x*y)
# Create a contour plot at N/4 and extract both the clip path and transform
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(r)
# Reuse testcase from above for a labeled data test
data = {"r": r}
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow("r", data=data)
@image_comparison(baseline_images=['imshow_clip'], style='mpl20')
def test_imshow_clip():
# As originally reported by Gellule Xg <[email protected]>
# Create a NxN image
N = 100
(x, y) = np.indices((N, N))
x -= N//2
y -= N//2
r = np.sqrt(x**2+y**2-x*y)
# Create a contour plot at N/4 and extract both the clip path and transform
fig = plt.figure()
ax = fig.add_subplot(111)
c = ax.contour(r, [N/4])
x = c.collections[0]
clipPath = x.get_paths()[0]
clipTransform = x.get_transform()
from matplotlib.transforms import TransformedPath
clip_path = TransformedPath(clipPath, clipTransform)
# Plot the image clipped by the contour
ax.imshow(r, clip_path=clip_path)
@image_comparison(baseline_images=['polycollection_joinstyle'],
remove_text=True)
def test_polycollection_joinstyle():
# Bug #2890979 reported by Matthew West
from matplotlib import collections as mcoll
fig = plt.figure()
ax = fig.add_subplot(111)
verts = np.array([[1, 1], [1, 2], [2, 2], [2, 1]])
c = mcoll.PolyCollection([verts], linewidths=40)
ax.add_collection(c)
ax.set_xbound(0, 3)
ax.set_ybound(0, 3)
@pytest.mark.parametrize(
'x, y1, y2', [
(np.zeros((2, 2)), 3, 3),
(np.arange(0.0, 2, 0.02), np.zeros((2, 2)), 3),
(np.arange(0.0, 2, 0.02), 3, np.zeros((2, 2)))
], ids=[
'2d_x_input',
'2d_y1_input',
'2d_y2_input'
]
)
def test_fill_between_input(x, y1, y2):
fig = plt.figure()
ax = fig.add_subplot(211)
with pytest.raises(ValueError):
ax.fill_between(x, y1, y2)
@pytest.mark.parametrize(
'y, x1, x2', [
(np.zeros((2, 2)), 3, 3),
(np.arange(0.0, 2, 0.02), np.zeros((2, 2)), 3),
(np.arange(0.0, 2, 0.02), 3, np.zeros((2, 2)))
], ids=[
'2d_y_input',
'2d_x1_input',
'2d_x2_input'
]
)
def test_fill_betweenx_input(y, x1, x2):
fig = plt.figure()
ax = fig.add_subplot(211)
with pytest.raises(ValueError):
ax.fill_betweenx(y, x1, x2)
@image_comparison(baseline_images=['fill_between_interpolate'],
remove_text=True)
def test_fill_between_interpolate():
x = np.arange(0.0, 2, 0.02)
y1 = np.sin(2*np.pi*x)
y2 = 1.2*np.sin(4*np.pi*x)
fig = plt.figure()
ax = fig.add_subplot(211)
ax.plot(x, y1, x, y2, color='black')
ax.fill_between(x, y1, y2, where=y2 >= y1, facecolor='white', hatch='/',
interpolate=True)
ax.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red',
interpolate=True)
# Test support for masked arrays.
y2 = np.ma.masked_greater(y2, 1.0)
# Test that plotting works for masked arrays with the first element masked
y2[0] = np.ma.masked
ax1 = fig.add_subplot(212, sharex=ax)
ax1.plot(x, y1, x, y2, color='black')
ax1.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green',
interpolate=True)
ax1.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red',
interpolate=True)
@image_comparison(baseline_images=['fill_between_interpolate_decreasing'],
style='mpl20', remove_text=True)
def test_fill_between_interpolate_decreasing():
p = np.array([724.3, 700, 655])
t = np.array([9.4, 7, 2.2])
prof = np.array([7.9, 6.6, 3.8])
fig = plt.figure(figsize=(9, 9))
ax = fig.add_subplot(1, 1, 1)
ax.plot(t, p, 'tab:red')
ax.plot(prof, p, 'k')
ax.fill_betweenx(p, t, prof, where=prof < t,
facecolor='blue', interpolate=True, alpha=0.4)
ax.fill_betweenx(p, t, prof, where=prof > t,
facecolor='red', interpolate=True, alpha=0.4)
ax.set_xlim(0, 30)
ax.set_ylim(800, 600)
@image_comparison(baseline_images=['symlog'])
def test_symlog():
x = np.array([0, 1, 2, 4, 6, 9, 12, 24])
y = np.array([1000000, 500000, 100000, 100, 5, 0, 0, 0])
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y)
ax.set_yscale('symlog')
ax.set_xscale('linear')
ax.set_ylim(-1, 10000000)
@image_comparison(baseline_images=['symlog2'],
remove_text=True)
def test_symlog2():
# Numbers from -50 to 50, with 0.1 as step
x = np.arange(-50, 50, 0.001)
fig = plt.figure()
ax = fig.add_subplot(511)
# Plots a simple linear function 'f(x) = x'
ax.plot(x, x)
ax.set_xscale('symlog', linthreshx=20.0)
ax.grid(True)
ax = fig.add_subplot(512)
# Plots a simple linear function 'f(x) = x'
ax.plot(x, x)
ax.set_xscale('symlog', linthreshx=2.0)
ax.grid(True)
ax = fig.add_subplot(513)
# Plots a simple linear function 'f(x) = x'
ax.plot(x, x)
ax.set_xscale('symlog', linthreshx=1.0)
ax.grid(True)
ax = fig.add_subplot(514)
# Plots a simple linear function 'f(x) = x'
ax.plot(x, x)
ax.set_xscale('symlog', linthreshx=0.1)
ax.grid(True)
ax = fig.add_subplot(515)
# Plots a simple linear function 'f(x) = x'
ax.plot(x, x)
ax.set_xscale('symlog', linthreshx=0.01)
ax.grid(True)
ax.set_ylim(-0.1, 0.1)
def test_pcolorargs_5205():
# Smoketest to catch issue found in gh:5205
x = [-1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5]
y = [-1.5, -1.25, -1.0, -0.75, -0.5, -0.25, 0,
0.25, 0.5, 0.75, 1.0, 1.25, 1.5]
X, Y = np.meshgrid(x, y)
Z = np.hypot(X, Y)
plt.pcolor(Z)
plt.pcolor(list(Z))
plt.pcolor(x, y, Z)
plt.pcolor(X, Y, list(Z))
@image_comparison(baseline_images=['pcolormesh'], remove_text=True)
def test_pcolormesh():
n = 12
x = np.linspace(-1.5, 1.5, n)
y = np.linspace(-1.5, 1.5, n*2)
X, Y = np.meshgrid(x, y)
Qx = np.cos(Y) - np.cos(X)
Qz = np.sin(Y) + np.sin(X)
Qx = (Qx + 1.1)
Z = np.hypot(X, Y) / 5
Z = (Z - Z.min()) / Z.ptp()
# The color array can include masked values:
Zm = ma.masked_where(np.abs(Qz) < 0.5 * np.max(Qz), Z)
fig = plt.figure()
ax = fig.add_subplot(131)
ax.pcolormesh(Qx, Qz, Z, lw=0.5, edgecolors='k')
ax = fig.add_subplot(132)
ax.pcolormesh(Qx, Qz, Z, lw=2, edgecolors=['b', 'w'])
ax = fig.add_subplot(133)
ax.pcolormesh(Qx, Qz, Z, shading="gouraud")
@image_comparison(baseline_images=['pcolormesh_datetime_axis'],
extensions=['png'], remove_text=False)
def test_pcolormesh_datetime_axis():
fig = plt.figure()
fig.subplots_adjust(hspace=0.4, top=0.98, bottom=.15)
base = datetime.datetime(2013, 1, 1)
x = np.array([base + datetime.timedelta(days=d) for d in range(21)])
y = np.arange(21)
z1, z2 = np.meshgrid(np.arange(20), np.arange(20))
z = z1 * z2
plt.subplot(221)
plt.pcolormesh(x[:-1], y[:-1], z)
plt.subplot(222)
plt.pcolormesh(x, y, z)
x = np.repeat(x[np.newaxis], 21, axis=0)
y = np.repeat(y[:, np.newaxis], 21, axis=1)
plt.subplot(223)
plt.pcolormesh(x[:-1, :-1], y[:-1, :-1], z)
plt.subplot(224)
plt.pcolormesh(x, y, z)
for ax in fig.get_axes():
for label in ax.get_xticklabels():
label.set_ha('right')
label.set_rotation(30)
@image_comparison(baseline_images=['pcolor_datetime_axis'],
extensions=['png'], remove_text=False)
def test_pcolor_datetime_axis():
fig = plt.figure()
fig.subplots_adjust(hspace=0.4, top=0.98, bottom=.15)
base = datetime.datetime(2013, 1, 1)
x = np.array([base + datetime.timedelta(days=d) for d in range(21)])
y = np.arange(21)
z1, z2 = np.meshgrid(np.arange(20), np.arange(20))
z = z1 * z2
plt.subplot(221)
plt.pcolor(x[:-1], y[:-1], z)
plt.subplot(222)
plt.pcolor(x, y, z)
x = np.repeat(x[np.newaxis], 21, axis=0)
y = np.repeat(y[:, np.newaxis], 21, axis=1)
plt.subplot(223)
plt.pcolor(x[:-1, :-1], y[:-1, :-1], z)
plt.subplot(224)
plt.pcolor(x, y, z)
for ax in fig.get_axes():
for label in ax.get_xticklabels():
label.set_ha('right')
label.set_rotation(30)
def test_pcolorargs():
n = 12
x = np.linspace(-1.5, 1.5, n)
y = np.linspace(-1.5, 1.5, n*2)
X, Y = np.meshgrid(x, y)
Z = np.sqrt(X**2 + Y**2)/5
_, ax = plt.subplots()
with pytest.raises(TypeError):
ax.pcolormesh(y, x, Z)
with pytest.raises(TypeError):
ax.pcolormesh(X, Y, Z.T)
with pytest.raises(TypeError):
ax.pcolormesh(x, y, Z[:-1, :-1], shading="gouraud")
with pytest.raises(TypeError):
ax.pcolormesh(X, Y, Z[:-1, :-1], shading="gouraud")
x[0] = np.NaN
with pytest.raises(ValueError):
ax.pcolormesh(x, y, Z[:-1, :-1])
with np.errstate(invalid='ignore'):
x = np.ma.array(x, mask=(x < 0))
with pytest.raises(ValueError):
ax.pcolormesh(x, y, Z[:-1, :-1])
@image_comparison(baseline_images=['canonical'])
def test_canonical():
fig, ax = plt.subplots()
ax.plot([1, 2, 3])
@image_comparison(baseline_images=['arc_angles'], remove_text=True,
style='default', extensions=['png'])
def test_arc_angles():
from matplotlib import patches
# Ellipse parameters
w = 2
h = 1
centre = (0.2, 0.5)
scale = 2
fig, axs = plt.subplots(3, 3)
for i, ax in enumerate(axs.flat):
theta2 = i * 360 / 9
theta1 = theta2 - 45
ax.add_patch(patches.Ellipse(centre, w, h, alpha=0.3))
ax.add_patch(patches.Arc(centre, w, h, theta1=theta1, theta2=theta2))
# Straight lines intersecting start and end of arc
ax.plot([scale * np.cos(np.deg2rad(theta1)) + centre[0],
centre[0],
scale * np.cos(np.deg2rad(theta2)) + centre[0]],
[scale * np.sin(np.deg2rad(theta1)) + centre[1],
centre[1],
scale * np.sin(np.deg2rad(theta2)) + centre[1]])
ax.set_xlim(-scale, scale)
ax.set_ylim(-scale, scale)
# This looks the same, but it triggers a different code path when it
# gets large enough.
w *= 10
h *= 10
centre = (centre[0] * 10, centre[1] * 10)
scale *= 10
@image_comparison(baseline_images=['arc_ellipse'],
remove_text=True)
def test_arc_ellipse():
from matplotlib import patches
xcenter, ycenter = 0.38, 0.52
width, height = 1e-1, 3e-1
angle = -30
theta = np.deg2rad(np.arange(360))
x = width / 2. * np.cos(theta)
y = height / 2. * np.sin(theta)
rtheta = np.deg2rad(angle)
R = np.array([
[np.cos(rtheta), -np.sin(rtheta)],
[np.sin(rtheta), np.cos(rtheta)]])
x, y = np.dot(R, np.array([x, y]))
x += xcenter
y += ycenter
fig = plt.figure()
ax = fig.add_subplot(211, aspect='auto')
ax.fill(x, y, alpha=0.2, facecolor='yellow', edgecolor='yellow',
linewidth=1, zorder=1)
e1 = patches.Arc((xcenter, ycenter), width, height,
angle=angle, linewidth=2, fill=False, zorder=2)
ax.add_patch(e1)
ax = fig.add_subplot(212, aspect='equal')
ax.fill(x, y, alpha=0.2, facecolor='green', edgecolor='green', zorder=1)
e2 = patches.Arc((xcenter, ycenter), width, height,
angle=angle, linewidth=2, fill=False, zorder=2)
ax.add_patch(e2)
@image_comparison(baseline_images=['markevery'],
remove_text=True)
def test_markevery():
x = np.linspace(0, 10, 100)
y = np.sin(x) * np.sqrt(x/10 + 0.5)
# check marker only plot
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y, 'o', label='default')
ax.plot(x, y, 'd', markevery=None, label='mark all')
ax.plot(x, y, 's', markevery=10, label='mark every 10')
ax.plot(x, y, '+', markevery=(5, 20), label='mark every 5 starting at 10')
ax.legend()
@image_comparison(baseline_images=['markevery_line'],
remove_text=True)
def test_markevery_line():
x = np.linspace(0, 10, 100)
y = np.sin(x) * np.sqrt(x/10 + 0.5)
# check line/marker combos
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y, '-o', label='default')
ax.plot(x, y, '-d', markevery=None, label='mark all')
ax.plot(x, y, '-s', markevery=10, label='mark every 10')
ax.plot(x, y, '-+', markevery=(5, 20), label='mark every 5 starting at 10')
ax.legend()
@image_comparison(baseline_images=['markevery_linear_scales'],
remove_text=True)
def test_markevery_linear_scales():
cases = [None,
8,
(30, 8),
[16, 24, 30], [0, -1],
slice(100, 200, 3),
0.1, 0.3, 1.5,
(0.0, 0.1), (0.45, 0.1)]
cols = 3
gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)
delta = 0.11
x = np.linspace(0, 10 - 2 * delta, 200) + delta
y = np.sin(x) + 1.0 + delta
for i, case in enumerate(cases):
row = (i // cols)
col = i % cols
plt.subplot(gs[row, col])
plt.title('markevery=%s' % str(case))
plt.plot(x, y, 'o', ls='-', ms=4, markevery=case)
@image_comparison(baseline_images=['markevery_linear_scales_zoomed'],
remove_text=True)
def test_markevery_linear_scales_zoomed():
cases = [None,
8,
(30, 8),
[16, 24, 30], [0, -1],
slice(100, 200, 3),
0.1, 0.3, 1.5,
(0.0, 0.1), (0.45, 0.1)]
cols = 3
gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)
delta = 0.11
x = np.linspace(0, 10 - 2 * delta, 200) + delta
y = np.sin(x) + 1.0 + delta
for i, case in enumerate(cases):
row = (i // cols)
col = i % cols
plt.subplot(gs[row, col])
plt.title('markevery=%s' % str(case))
plt.plot(x, y, 'o', ls='-', ms=4, markevery=case)
plt.xlim((6, 6.7))
plt.ylim((1.1, 1.7))
@image_comparison(baseline_images=['markevery_log_scales'],
remove_text=True)
def test_markevery_log_scales():
cases = [None,
8,
(30, 8),
[16, 24, 30], [0, -1],
slice(100, 200, 3),
0.1, 0.3, 1.5,
(0.0, 0.1), (0.45, 0.1)]
cols = 3
gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)
delta = 0.11
x = np.linspace(0, 10 - 2 * delta, 200) + delta
y = np.sin(x) + 1.0 + delta
for i, case in enumerate(cases):
row = (i // cols)
col = i % cols
plt.subplot(gs[row, col])
plt.title('markevery=%s' % str(case))
plt.xscale('log')
plt.yscale('log')
plt.plot(x, y, 'o', ls='-', ms=4, markevery=case)
@image_comparison(baseline_images=['markevery_polar'], style='default',
remove_text=True)
def test_markevery_polar():
cases = [None,
8,
(30, 8),
[16, 24, 30], [0, -1],
slice(100, 200, 3),
0.1, 0.3, 1.5,
(0.0, 0.1), (0.45, 0.1)]
cols = 3
gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)
r = np.linspace(0, 3.0, 200)
theta = 2 * np.pi * r
for i, case in enumerate(cases):
row = (i // cols)
col = i % cols
plt.subplot(gs[row, col], polar=True)
plt.title('markevery=%s' % str(case))
plt.plot(theta, r, 'o', ls='-', ms=4, markevery=case)
@image_comparison(baseline_images=['marker_edges'],
remove_text=True)
def test_marker_edges():
x = np.linspace(0, 1, 10)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, np.sin(x), 'y.', ms=30.0, mew=0, mec='r')
ax.plot(x+0.1, np.sin(x), 'y.', ms=30.0, mew=1, mec='r')
ax.plot(x+0.2, np.sin(x), 'y.', ms=30.0, mew=2, mec='b')
@image_comparison(baseline_images=['bar_tick_label_single',
'bar_tick_label_single'],
extensions=['png'])
def test_bar_tick_label_single():
# From 2516: plot bar with array of string labels for x axis
ax = plt.gca()
ax.bar(0, 1, tick_label='0')
# Reuse testcase from above for a labeled data test
data = {"a": 0, "b": 1}
fig = plt.figure()
ax = fig.add_subplot(111)
ax = plt.gca()
ax.bar("a", "b", tick_label='0', data=data)
def test_bar_ticklabel_fail():
fig, ax = plt.subplots()
ax.bar([], [])
@image_comparison(baseline_images=['bar_tick_label_multiple'],
extensions=['png'])
def test_bar_tick_label_multiple():
# From 2516: plot bar with array of string labels for x axis
ax = plt.gca()
ax.bar([1, 2.5], [1, 2], width=[0.2, 0.5], tick_label=['a', 'b'],
align='center')
@image_comparison(
baseline_images=['bar_tick_label_multiple_old_label_alignment'],
extensions=['png'])
def test_bar_tick_label_multiple_old_alignment():
# Test that the algnment for class is backward compatible
matplotlib.rcParams["ytick.alignment"] = "center"
ax = plt.gca()
ax.bar([1, 2.5], [1, 2], width=[0.2, 0.5], tick_label=['a', 'b'],
align='center')
@image_comparison(baseline_images=['barh_tick_label'],
extensions=['png'])
def test_barh_tick_label():
# From 2516: plot barh with array of string labels for y axis
ax = plt.gca()
ax.barh([1, 2.5], [1, 2], height=[0.2, 0.5], tick_label=['a', 'b'],
align='center')
@image_comparison(baseline_images=['hist_log'],
remove_text=True)
def test_hist_log():
data0 = np.linspace(0, 1, 200)**3
data = np.r_[1-data0, 1+data0]
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist(data, fill=False, log=True)
@image_comparison(baseline_images=['hist_bar_empty'], remove_text=True,
extensions=['png'])
def test_hist_bar_empty():
# From #3886: creating hist from empty dataset raises ValueError
ax = plt.gca()
ax.hist([], histtype='bar')
@image_comparison(baseline_images=['hist_step_empty'], remove_text=True,
extensions=['png'])
def test_hist_step_empty():
# From #3886: creating hist from empty dataset raises ValueError
ax = plt.gca()
ax.hist([], histtype='step')
@image_comparison(baseline_images=['hist_steplog'], remove_text=True, tol=0.1)
def test_hist_steplog():
np.random.seed(0)
data = np.random.standard_normal(2000)
data += -2.0 - np.min(data)
data_pos = data + 2.1
data_big = data_pos + 30
weights = np.ones_like(data) * 1.e-5
ax = plt.subplot(4, 1, 1)
plt.hist(data, 100, histtype='stepfilled', log=True)
ax = plt.subplot(4, 1, 2)
plt.hist(data_pos, 100, histtype='stepfilled', log=True)
ax = plt.subplot(4, 1, 3)
plt.hist(data, 100, weights=weights, histtype='stepfilled', log=True)
ax = plt.subplot(4, 1, 4)
plt.hist(data_big, 100, histtype='stepfilled', log=True,
orientation='horizontal')
@image_comparison(baseline_images=['hist_step_filled'], remove_text=True,
extensions=['png'])
def test_hist_step_filled():
np.random.seed(0)
x = np.random.randn(1000, 3)
n_bins = 10
kwargs = [{'fill': True}, {'fill': False}, {'fill': None}, {}]*2
types = ['step']*4+['stepfilled']*4
fig, axes = plt.subplots(nrows=2, ncols=4)
axes = axes.flatten()
for kg, _type, ax in zip(kwargs, types, axes):
ax.hist(x, n_bins, histtype=_type, stacked=True, **kg)
ax.set_title('%s/%s' % (kg, _type))
ax.set_ylim(ymin=-50)
patches = axes[0].patches
assert all([p.get_facecolor() == p.get_edgecolor() for p in patches])
@image_comparison(baseline_images=['hist_density'], extensions=['png'])
def test_hist_density():
np.random.seed(19680801)
data = np.random.standard_normal(2000)
fig, ax = plt.subplots()
ax.hist(data, density=True)
@image_comparison(baseline_images=['hist_step_log_bottom'],
remove_text=True, extensions=['png'])
def test_hist_step_log_bottom():
# check that bottom doesn't get overwritten by the 'minimum' on a
# log scale histogram (https://github.com/matplotlib/matplotlib/pull/4608)
np.random.seed(0)
data = np.random.standard_normal(2000)
fig = plt.figure()
ax = fig.add_subplot(111)
# normal hist (should clip minimum to 1/base)
ax.hist(data, bins=10, log=True, histtype='stepfilled',
alpha=0.5, color='b')
# manual bottom < 1/base (previously buggy, see #4608)
ax.hist(data, bins=10, log=True, histtype='stepfilled',
alpha=0.5, color='g', bottom=1e-2)
# manual bottom > 1/base
ax.hist(data, bins=10, log=True, histtype='stepfilled',
alpha=0.5, color='r', bottom=0.5)
# array bottom with some less than 1/base (should clip to 1/base)
ax.hist(data, bins=10, log=True, histtype='stepfilled',
alpha=0.5, color='y', bottom=np.arange(10))
ax.set_ylim(9e-3, 1e3)
def test_hist_unequal_bins_density():
# Test correct behavior of normalized histogram with unequal bins
# https://github.com/matplotlib/matplotlib/issues/9557
rng = np.random.RandomState(57483)
t = rng.randn(100)
bins = [-3, -1, -0.5, 0, 1, 5]
mpl_heights, _, _ = plt.hist(t, bins=bins, density=True)
np_heights, _ = np.histogram(t, bins=bins, density=True)
assert_allclose(mpl_heights, np_heights)
def test_hist_datetime_datasets():
data = [[datetime.datetime(2017, 1, 1), datetime.datetime(2017, 1, 1)],
[datetime.datetime(2017, 1, 1), datetime.datetime(2017, 1, 2)]]
fig, ax = plt.subplots()
ax.hist(data, stacked=True)
ax.hist(data, stacked=False)
def contour_dat():
x = np.linspace(-3, 5, 150)
y = np.linspace(-3, 5, 120)
z = np.cos(x) + np.sin(y[:, np.newaxis])
return x, y, z
@image_comparison(baseline_images=['contour_hatching'])
def test_contour_hatching():
x, y, z = contour_dat()
fig = plt.figure()
ax = fig.add_subplot(111)
cs = ax.contourf(x, y, z, hatches=['-', '/', '\\', '//'],
cmap=plt.get_cmap('gray'),
extend='both', alpha=0.5)
@image_comparison(baseline_images=['contour_colorbar'])
def test_contour_colorbar():
x, y, z = contour_dat()
fig = plt.figure()
ax = fig.add_subplot(111)
cs = ax.contourf(x, y, z, levels=np.arange(-1.8, 1.801, 0.2),
cmap=plt.get_cmap('RdBu'),
vmin=-0.6,
vmax=0.6,
extend='both')
cs1 = ax.contour(x, y, z, levels=np.arange(-2.2, -0.599, 0.2),
colors=['y'],
linestyles='solid',
linewidths=2)
cs2 = ax.contour(x, y, z, levels=np.arange(0.6, 2.2, 0.2),
colors=['c'],
linewidths=2)
cbar = fig.colorbar(cs, ax=ax)
cbar.add_lines(cs1)
cbar.add_lines(cs2, erase=False)
@image_comparison(baseline_images=['hist2d', 'hist2d'])
def test_hist2d():
np.random.seed(0)
# make it not symmetric in case we switch x and y axis
x = np.random.randn(100)*2+5
y = np.random.randn(100)-2
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d(x, y, bins=10)
# Reuse testcase from above for a labeled data test
data = {"x": x, "y": y}
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d("x", "y", bins=10, data=data)
@image_comparison(baseline_images=['hist2d_transpose'])
def test_hist2d_transpose():
np.random.seed(0)
# make sure the output from np.histogram is transposed before
# passing to pcolorfast
x = np.array([5]*100)
y = np.random.randn(100)-2
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist2d(x, y, bins=10)
@image_comparison(baseline_images=['scatter', 'scatter'])
def test_scatter_plot():
fig, ax = plt.subplots()
data = {"x": [3, 4, 2, 6], "y": [2, 5, 2, 3], "c": ['r', 'y', 'b', 'lime'],
"s": [24, 15, 19, 29]}
ax.scatter(data["x"], data["y"], c=data["c"], s=data["s"])
# Reuse testcase from above for a labeled data test
fig, ax = plt.subplots()
ax.scatter("x", "y", c="c", s="s", data=data)
@image_comparison(baseline_images=['scatter_marker'], remove_text=True,
extensions=['png'])
def test_scatter_marker():
fig, (ax0, ax1, ax2) = plt.subplots(ncols=3)
ax0.scatter([3, 4, 2, 6], [2, 5, 2, 3],
c=[(1, 0, 0), 'y', 'b', 'lime'],
s=[60, 50, 40, 30],
edgecolors=['k', 'r', 'g', 'b'],
marker='s')
ax1.scatter([3, 4, 2, 6], [2, 5, 2, 3],
c=[(1, 0, 0), 'y', 'b', 'lime'],
s=[60, 50, 40, 30],
edgecolors=['k', 'r', 'g', 'b'],
marker=mmarkers.MarkerStyle('o', fillstyle='top'))
# unit area ellipse
rx, ry = 3, 1
area = rx * ry * np.pi
theta = np.linspace(0, 2 * np.pi, 21)
verts = np.column_stack([np.cos(theta) * rx / area,
np.sin(theta) * ry / area])
ax2.scatter([3, 4, 2, 6], [2, 5, 2, 3],
c=[(1, 0, 0), 'y', 'b', 'lime'],
s=[60, 50, 40, 30],
edgecolors=['k', 'r', 'g', 'b'],
verts=verts)
@image_comparison(baseline_images=['scatter_2D'], remove_text=True,
extensions=['png'])
def test_scatter_2D():
x = np.arange(3)
y = np.arange(2)
x, y = np.meshgrid(x, y)
z = x + y
fig, ax = plt.subplots()
ax.scatter(x, y, c=z, s=200, edgecolors='face')
def test_scatter_color():
# Try to catch cases where 'c' kwarg should have been used.
with pytest.raises(ValueError):
plt.scatter([1, 2], [1, 2], color=[0.1, 0.2])
with pytest.raises(ValueError):
plt.scatter([1, 2, 3], [1, 2, 3], color=[1, 2, 3])
def test_as_mpl_axes_api():
# tests the _as_mpl_axes api
from matplotlib.projections.polar import PolarAxes
import matplotlib.axes as maxes
class Polar(object):
def __init__(self):
self.theta_offset = 0
def _as_mpl_axes(self):
# implement the matplotlib axes interface
return PolarAxes, {'theta_offset': self.theta_offset}
prj = Polar()
prj2 = Polar()
prj2.theta_offset = np.pi
prj3 = Polar()
# testing axes creation with plt.axes
ax = plt.axes([0, 0, 1, 1], projection=prj)
assert type(ax) == PolarAxes
ax_via_gca = plt.gca(projection=prj)
assert ax_via_gca is ax
plt.close()
# testing axes creation with gca
ax = plt.gca(projection=prj)
assert type(ax) == maxes._subplots._subplot_classes[PolarAxes]
ax_via_gca = plt.gca(projection=prj)
assert ax_via_gca is ax
# try getting the axes given a different polar projection
with pytest.warns(UserWarning) as rec:
ax_via_gca = plt.gca(projection=prj2)
assert len(rec) == 1
assert 'Requested projection is different' in str(rec[0].message)
assert ax_via_gca is not ax
assert ax.get_theta_offset() == 0
assert ax_via_gca.get_theta_offset() == np.pi
# try getting the axes given an == (not is) polar projection
with pytest.warns(UserWarning):
ax_via_gca = plt.gca(projection=prj3)
assert len(rec) == 1
assert 'Requested projection is different' in str(rec[0].message)
assert ax_via_gca is ax
plt.close()
# testing axes creation with subplot
ax = plt.subplot(121, projection=prj)
assert type(ax) == maxes._subplots._subplot_classes[PolarAxes]
plt.close()
def test_pyplot_axes():
# test focusing of Axes in other Figure
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
assert ax1 is plt.axes(ax1)
assert ax1 is plt.gca()
assert fig1 is plt.gcf()
plt.close(fig1)
plt.close(fig2)
@image_comparison(baseline_images=['log_scales'])
def test_log_scales():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(np.log(np.linspace(0.1, 100)))
ax.set_yscale('log', basey=5.5)
ax.invert_yaxis()
ax.set_xscale('log', basex=9.0)
@image_comparison(baseline_images=['stackplot_test_image',
'stackplot_test_image'])
def test_stackplot():
fig = plt.figure()
x = np.linspace(0, 10, 10)
y1 = 1.0 * x
y2 = 2.0 * x + 1
y3 = 3.0 * x + 2
ax = fig.add_subplot(1, 1, 1)
ax.stackplot(x, y1, y2, y3)
ax.set_xlim((0, 10))
ax.set_ylim((0, 70))
# Reuse testcase from above for a labeled data test
data = {"x": x, "y1": y1, "y2": y2, "y3": y3}
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.stackplot("x", "y1", "y2", "y3", data=data)
ax.set_xlim((0, 10))
ax.set_ylim((0, 70))
@image_comparison(baseline_images=['stackplot_test_baseline'],
remove_text=True)
def test_stackplot_baseline():
np.random.seed(0)
def layers(n, m):
a = np.zeros((m, n))
for i in range(n):
for j in range(5):
x = 1 / (.1 + np.random.random())
y = 2 * np.random.random() - .5
z = 10 / (.1 + np.random.random())
a[:, i] += x * np.exp(-((np.arange(m) / m - y) * z) ** 2)
return a
d = layers(3, 100)
d[50, :] = 0 # test for fixed weighted wiggle (issue #6313)
fig, axs = plt.subplots(2, 2)
axs[0, 0].stackplot(range(100), d.T, baseline='zero')
axs[0, 1].stackplot(range(100), d.T, baseline='sym')
axs[1, 0].stackplot(range(100), d.T, baseline='wiggle')
axs[1, 1].stackplot(range(100), d.T, baseline='weighted_wiggle')
@image_comparison(baseline_images=['bxp_baseline'],
extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_baseline():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats)
@image_comparison(baseline_images=['bxp_rangewhis'],
extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_rangewhis():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4)),
whis='range'
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats)
@image_comparison(baseline_images=['bxp_precentilewhis'],
extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_precentilewhis():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4)),
whis=[5, 95]
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats)
@image_comparison(baseline_images=['bxp_with_xlabels'],
extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_with_xlabels():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
for stats, label in zip(logstats, list('ABCD')):
stats['label'] = label
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats)
@image_comparison(baseline_images=['bxp_horizontal'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default',
tol=0.1)
def test_bxp_horizontal():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_xscale('log')
ax.bxp(logstats, vert=False)
@image_comparison(baseline_images=['bxp_with_ylabels'],
extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default',
tol=0.1,)
def test_bxp_with_ylabels():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
for stats, label in zip(logstats, list('ABCD')):
stats['label'] = label
fig, ax = plt.subplots()
ax.set_xscale('log')
ax.bxp(logstats, vert=False)
@image_comparison(baseline_images=['bxp_patchartist'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_patchartist():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, patch_artist=True)
@image_comparison(baseline_images=['bxp_custompatchartist'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 100},
style='default')
def test_bxp_custompatchartist():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
boxprops = dict(facecolor='yellow', edgecolor='green', linestyle='dotted')
ax.bxp(logstats, patch_artist=True, boxprops=boxprops)
@image_comparison(baseline_images=['bxp_customoutlier'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_customoutlier():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
flierprops = dict(linestyle='none', marker='d', markerfacecolor='g')
ax.bxp(logstats, flierprops=flierprops)
@image_comparison(baseline_images=['bxp_withmean_custompoint'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_showcustommean():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
meanprops = dict(linestyle='none', marker='d', markerfacecolor='green')
ax.bxp(logstats, showmeans=True, meanprops=meanprops)
@image_comparison(baseline_images=['bxp_custombox'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_custombox():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
boxprops = dict(linestyle='--', color='b', linewidth=3)
ax.bxp(logstats, boxprops=boxprops)
@image_comparison(baseline_images=['bxp_custommedian'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_custommedian():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
medianprops = dict(linestyle='--', color='b', linewidth=3)
ax.bxp(logstats, medianprops=medianprops)
@image_comparison(baseline_images=['bxp_customcap'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_customcap():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
capprops = dict(linestyle='--', color='g', linewidth=3)
ax.bxp(logstats, capprops=capprops)
@image_comparison(baseline_images=['bxp_customwhisker'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_customwhisker():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
whiskerprops = dict(linestyle='-', color='m', linewidth=3)
ax.bxp(logstats, whiskerprops=whiskerprops)
@image_comparison(baseline_images=['bxp_withnotch'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_shownotches():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, shownotches=True)
@image_comparison(baseline_images=['bxp_nocaps'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_nocaps():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, showcaps=False)
@image_comparison(baseline_images=['bxp_nobox'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_nobox():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, showbox=False)
@image_comparison(baseline_images=['bxp_no_flier_stats'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_no_flier_stats():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
for ls in logstats:
ls.pop('fliers', None)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, showfliers=False)
@image_comparison(baseline_images=['bxp_withmean_point'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_showmean():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, showmeans=True, meanline=False)
@image_comparison(baseline_images=['bxp_withmean_line'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_showmeanasline():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, showmeans=True, meanline=True)
@image_comparison(baseline_images=['bxp_scalarwidth'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_scalarwidth():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, widths=0.25)
@image_comparison(baseline_images=['bxp_customwidths'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_customwidths():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, widths=[0.10, 0.25, 0.65, 0.85])
@image_comparison(baseline_images=['bxp_custompositions'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_bxp_custompositions():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.bxp(logstats, positions=[1, 5, 6, 7])
def test_bxp_bad_widths():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
with pytest.raises(ValueError):
ax.bxp(logstats, widths=[1])
def test_bxp_bad_positions():
np.random.seed(937)
logstats = matplotlib.cbook.boxplot_stats(
np.random.lognormal(mean=1.25, sigma=1., size=(37, 4))
)
fig, ax = plt.subplots()
ax.set_yscale('log')
with pytest.raises(ValueError):
ax.bxp(logstats, positions=[2, 3])
@image_comparison(baseline_images=['boxplot', 'boxplot'],
tol=1,
style='default')
def test_boxplot():
# Randomness used for bootstrapping.
np.random.seed(937)
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
ax.boxplot([x, x], bootstrap=10000, notch=1)
ax.set_ylim((-30, 30))
# Reuse testcase from above for a labeled data test
data = {"x": [x, x]}
fig, ax = plt.subplots()
ax.boxplot("x", bootstrap=10000, notch=1, data=data)
ax.set_ylim((-30, 30))
@image_comparison(baseline_images=['boxplot_sym2'],
remove_text=True, extensions=['png'],
style='default')
def test_boxplot_sym2():
# Randomness used for bootstrapping.
np.random.seed(937)
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.boxplot([x, x], bootstrap=10000, sym='^')
ax1.set_ylim((-30, 30))
ax2.boxplot([x, x], bootstrap=10000, sym='g')
ax2.set_ylim((-30, 30))
@image_comparison(baseline_images=['boxplot_sym'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40},
style='default')
def test_boxplot_sym():
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
ax.boxplot([x, x], sym='gs')
ax.set_ylim((-30, 30))
@image_comparison(
baseline_images=['boxplot_autorange_false_whiskers',
'boxplot_autorange_true_whiskers'],
extensions=['png'],
style='default'
)
def test_boxplot_autorange_whiskers():
# Randomness used for bootstrapping.
np.random.seed(937)
x = np.ones(140)
x = np.hstack([0, x, 2])
fig1, ax1 = plt.subplots()
ax1.boxplot([x, x], bootstrap=10000, notch=1)
ax1.set_ylim((-5, 5))
fig2, ax2 = plt.subplots()
ax2.boxplot([x, x], bootstrap=10000, notch=1, autorange=True)
ax2.set_ylim((-5, 5))
def _rc_test_bxp_helper(ax, rc_dict):
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
with matplotlib.rc_context(rc_dict):
ax.boxplot([x, x])
return ax
@image_comparison(baseline_images=['boxplot_rc_parameters'],
savefig_kwarg={'dpi': 100}, remove_text=True,
tol=1, style='default')
def test_boxplot_rc_parameters():
# Randomness used for bootstrapping.
np.random.seed(937)
fig, ax = plt.subplots(3)
rc_axis0 = {
'boxplot.notch': True,
'boxplot.whiskers': [5, 95],
'boxplot.bootstrap': 10000,
'boxplot.flierprops.color': 'b',
'boxplot.flierprops.marker': 'o',
'boxplot.flierprops.markerfacecolor': 'g',
'boxplot.flierprops.markeredgecolor': 'b',
'boxplot.flierprops.markersize': 5,
'boxplot.flierprops.linestyle': '--',
'boxplot.flierprops.linewidth': 2.0,
'boxplot.boxprops.color': 'r',
'boxplot.boxprops.linewidth': 2.0,
'boxplot.boxprops.linestyle': '--',
'boxplot.capprops.color': 'c',
'boxplot.capprops.linewidth': 2.0,
'boxplot.capprops.linestyle': '--',
'boxplot.medianprops.color': 'k',
'boxplot.medianprops.linewidth': 2.0,
'boxplot.medianprops.linestyle': '--',
}
rc_axis1 = {
'boxplot.vertical': False,
'boxplot.whiskers': 'range',
'boxplot.patchartist': True,
}
rc_axis2 = {
'boxplot.whiskers': 2.0,
'boxplot.showcaps': False,
'boxplot.showbox': False,
'boxplot.showfliers': False,
'boxplot.showmeans': True,
'boxplot.meanline': True,
'boxplot.meanprops.color': 'c',
'boxplot.meanprops.linewidth': 2.0,
'boxplot.meanprops.linestyle': '--',
'boxplot.whiskerprops.color': 'r',
'boxplot.whiskerprops.linewidth': 2.0,
'boxplot.whiskerprops.linestyle': '-.',
}
dict_list = [rc_axis0, rc_axis1, rc_axis2]
for axis, rc_axis in zip(ax, dict_list):
_rc_test_bxp_helper(axis, rc_axis)
assert (matplotlib.patches.PathPatch in
[type(t) for t in ax[1].get_children()])
@image_comparison(baseline_images=['boxplot_with_CIarray'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40}, style='default')
def test_boxplot_with_CIarray():
# Randomness used for bootstrapping.
np.random.seed(937)
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig = plt.figure()
ax = fig.add_subplot(111)
CIs = np.array([[-1.5, 3.], [-1., 3.5]])
# show 1 boxplot with mpl medians/conf. interfals, 1 with manual values
ax.boxplot([x, x], bootstrap=10000, usermedians=[None, 1.0],
conf_intervals=CIs, notch=1)
ax.set_ylim((-30, 30))
@image_comparison(baseline_images=['boxplot_no_inverted_whisker'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40}, style='default')
def test_boxplot_no_weird_whisker():
x = np.array([3, 9000, 150, 88, 350, 200000, 1400, 960],
dtype=np.float64)
ax1 = plt.axes()
ax1.boxplot(x)
ax1.set_yscale('log')
ax1.yaxis.grid(False, which='minor')
ax1.xaxis.grid(False)
def test_boxplot_bad_medians_1():
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.boxplot(x, usermedians=[1, 2])
def test_boxplot_bad_medians_2():
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.boxplot([x, x], usermedians=[[1, 2], [1, 2]])
def test_boxplot_bad_ci_1():
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.boxplot([x, x], conf_intervals=[[1, 2]])
def test_boxplot_zorder():
x = np.arange(10)
fix, ax = plt.subplots()
assert ax.boxplot(x)['boxes'][0].get_zorder() == 2
assert ax.boxplot(x, zorder=10)['boxes'][0].get_zorder() == 10
def test_boxplot_bad_ci_2():
x = np.linspace(-7, 7, 140)
x = np.hstack([-25, x, 25])
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.boxplot([x, x], conf_intervals=[[1, 2], [1]])
@image_comparison(baseline_images=['boxplot_mod_artists_after_plotting'],
remove_text=True, extensions=['png'],
savefig_kwarg={'dpi': 40}, style='default')
def test_boxplot_mod_artist_after_plotting():
x = [0.15, 0.11, 0.06, 0.06, 0.12, 0.56, -0.56]
fig, ax = plt.subplots()
bp = ax.boxplot(x, sym="o")
for key in bp:
for obj in bp[key]:
obj.set_color('green')
@image_comparison(baseline_images=['violinplot_vert_baseline',
'violinplot_vert_baseline'],
extensions=['png'])
def test_vert_violinplot_baseline():
# First 9 digits of frac(sqrt(2))
np.random.seed(414213562)
data = [np.random.normal(size=100) for i in range(4)]
ax = plt.axes()
ax.violinplot(data, positions=range(4), showmeans=0, showextrema=0,
showmedians=0)
# Reuse testcase from above for a labeled data test
data = {"d": data}
fig, ax = plt.subplots()
ax = plt.axes()
ax.violinplot("d", positions=range(4), showmeans=0, showextrema=0,
showmedians=0, data=data)
@image_comparison(baseline_images=['violinplot_vert_showmeans'],
extensions=['png'])
def test_vert_violinplot_showmeans():
ax = plt.axes()
# First 9 digits of frac(sqrt(3))
np.random.seed(732050807)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=1, showextrema=0,
showmedians=0)
@image_comparison(baseline_images=['violinplot_vert_showextrema'],
extensions=['png'])
def test_vert_violinplot_showextrema():
ax = plt.axes()
# First 9 digits of frac(sqrt(5))
np.random.seed(236067977)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=0, showextrema=1,
showmedians=0)
@image_comparison(baseline_images=['violinplot_vert_showmedians'],
extensions=['png'])
def test_vert_violinplot_showmedians():
ax = plt.axes()
# First 9 digits of frac(sqrt(7))
np.random.seed(645751311)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=0, showextrema=0,
showmedians=1)
@image_comparison(baseline_images=['violinplot_vert_showall'],
extensions=['png'])
def test_vert_violinplot_showall():
ax = plt.axes()
# First 9 digits of frac(sqrt(11))
np.random.seed(316624790)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=1, showextrema=1,
showmedians=1)
@image_comparison(baseline_images=['violinplot_vert_custompoints_10'],
extensions=['png'])
def test_vert_violinplot_custompoints_10():
ax = plt.axes()
# First 9 digits of frac(sqrt(13))
np.random.seed(605551275)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=0, showextrema=0,
showmedians=0, points=10)
@image_comparison(baseline_images=['violinplot_vert_custompoints_200'],
extensions=['png'])
def test_vert_violinplot_custompoints_200():
ax = plt.axes()
# First 9 digits of frac(sqrt(17))
np.random.seed(123105625)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), showmeans=0, showextrema=0,
showmedians=0, points=200)
@image_comparison(baseline_images=['violinplot_horiz_baseline'],
extensions=['png'])
def test_horiz_violinplot_baseline():
ax = plt.axes()
# First 9 digits of frac(sqrt(19))
np.random.seed(358898943)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=0,
showextrema=0, showmedians=0)
@image_comparison(baseline_images=['violinplot_horiz_showmedians'],
extensions=['png'])
def test_horiz_violinplot_showmedians():
ax = plt.axes()
# First 9 digits of frac(sqrt(23))
np.random.seed(795831523)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=0,
showextrema=0, showmedians=1)
@image_comparison(baseline_images=['violinplot_horiz_showmeans'],
extensions=['png'])
def test_horiz_violinplot_showmeans():
ax = plt.axes()
# First 9 digits of frac(sqrt(29))
np.random.seed(385164807)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=1,
showextrema=0, showmedians=0)
@image_comparison(baseline_images=['violinplot_horiz_showextrema'],
extensions=['png'])
def test_horiz_violinplot_showextrema():
ax = plt.axes()
# First 9 digits of frac(sqrt(31))
np.random.seed(567764362)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=0,
showextrema=1, showmedians=0)
@image_comparison(baseline_images=['violinplot_horiz_showall'],
extensions=['png'])
def test_horiz_violinplot_showall():
ax = plt.axes()
# First 9 digits of frac(sqrt(37))
np.random.seed(82762530)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=1,
showextrema=1, showmedians=1)
@image_comparison(baseline_images=['violinplot_horiz_custompoints_10'],
extensions=['png'])
def test_horiz_violinplot_custompoints_10():
ax = plt.axes()
# First 9 digits of frac(sqrt(41))
np.random.seed(403124237)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=0,
showextrema=0, showmedians=0, points=10)
@image_comparison(baseline_images=['violinplot_horiz_custompoints_200'],
extensions=['png'])
def test_horiz_violinplot_custompoints_200():
ax = plt.axes()
# First 9 digits of frac(sqrt(43))
np.random.seed(557438524)
data = [np.random.normal(size=100) for i in range(4)]
ax.violinplot(data, positions=range(4), vert=False, showmeans=0,
showextrema=0, showmedians=0, points=200)
def test_violinplot_bad_positions():
ax = plt.axes()
# First 9 digits of frac(sqrt(47))
np.random.seed(855654600)
data = [np.random.normal(size=100) for i in range(4)]
with pytest.raises(ValueError):
ax.violinplot(data, positions=range(5))
def test_violinplot_bad_widths():
ax = plt.axes()
# First 9 digits of frac(sqrt(53))
np.random.seed(280109889)
data = [np.random.normal(size=100) for i in range(4)]
with pytest.raises(ValueError):
ax.violinplot(data, positions=range(4), widths=[1, 2, 3])
def test_manage_xticks():
_, ax = plt.subplots()
ax.set_xlim(0, 4)
old_xlim = ax.get_xlim()
np.random.seed(0)
y1 = np.random.normal(10, 3, 20)
y2 = np.random.normal(3, 1, 20)
ax.boxplot([y1, y2], positions=[1, 2],
manage_xticks=False)
new_xlim = ax.get_xlim()
assert_array_equal(old_xlim, new_xlim)
def test_tick_space_size_0():
# allow font size to be zero, which affects ticks when there is
# no other text in the figure.
plt.plot([0, 1], [0, 1])
matplotlib.rcParams.update({'font.size': 0})
b = io.BytesIO()
plt.savefig(b, dpi=80, format='raw')
@image_comparison(baseline_images=['errorbar_basic', 'errorbar_mixed',
'errorbar_basic'])
def test_errorbar():
x = np.arange(0.1, 4, 0.5)
y = np.exp(-x)
yerr = 0.1 + 0.2*np.sqrt(x)
xerr = 0.1 + yerr
# First illustrate basic pyplot interface, using defaults where possible.
fig = plt.figure()
ax = fig.gca()
ax.errorbar(x, y, xerr=0.2, yerr=0.4)
ax.set_title("Simplest errorbars, 0.2 in x, 0.4 in y")
# Now switch to a more OO interface to exercise more features.
fig, axs = plt.subplots(nrows=2, ncols=2, sharex=True)
ax = axs[0, 0]
# Try a Nx1 shaped error just to check
ax.errorbar(x, y, yerr=np.reshape(yerr, (len(y), 1)), fmt='o')
ax.set_title('Vert. symmetric')
# With 4 subplots, reduce the number of axis ticks to avoid crowding.
ax.locator_params(nbins=4)
ax = axs[0, 1]
ax.errorbar(x, y, xerr=xerr, fmt='o', alpha=0.4)
ax.set_title('Hor. symmetric w/ alpha')
ax = axs[1, 0]
ax.errorbar(x, y, yerr=[yerr, 2*yerr], xerr=[xerr, 2*xerr], fmt='--o')
ax.set_title('H, V asymmetric')
ax = axs[1, 1]
ax.set_yscale('log')
# Here we have to be careful to keep all y values positive:
ylower = np.maximum(1e-2, y - yerr)
yerr_lower = y - ylower
ax.errorbar(x, y, yerr=[yerr_lower, 2*yerr], xerr=xerr,
fmt='o', ecolor='g', capthick=2)
ax.set_title('Mixed sym., log y')
fig.suptitle('Variable errorbars')
# Reuse the first testcase from above for a labeled data test
data = {"x": x, "y": y}
fig = plt.figure()
ax = fig.gca()
ax.errorbar("x", "y", xerr=0.2, yerr=0.4, data=data)
ax.set_title("Simplest errorbars, 0.2 in x, 0.4 in y")
def test_errorbar_colorcycle():
f, ax = plt.subplots()
x = np.arange(10)
y = 2*x
e1, _, _ = ax.errorbar(x, y, c=None)
e2, _, _ = ax.errorbar(x, 2*y, c=None)
ln1, = ax.plot(x, 4*y)
assert mcolors.to_rgba(e1.get_color()) == mcolors.to_rgba('C0')
assert mcolors.to_rgba(e2.get_color()) == mcolors.to_rgba('C1')
assert mcolors.to_rgba(ln1.get_color()) == mcolors.to_rgba('C2')
def test_errorbar_shape():
fig = plt.figure()
ax = fig.gca()
x = np.arange(0.1, 4, 0.5)
y = np.exp(-x)
yerr1 = 0.1 + 0.2*np.sqrt(x)
yerr = np.vstack((yerr1, 2*yerr1)).T
xerr = 0.1 + yerr
with pytest.raises(ValueError):
ax.errorbar(x, y, yerr=yerr, fmt='o')
with pytest.raises(ValueError):
ax.errorbar(x, y, xerr=xerr, fmt='o')
with pytest.raises(ValueError):
ax.errorbar(x, y, yerr=yerr, xerr=xerr, fmt='o')
@image_comparison(baseline_images=['errorbar_limits'])
def test_errorbar_limits():
x = np.arange(0.5, 5.5, 0.5)
y = np.exp(-x)
xerr = 0.1
yerr = 0.2
ls = 'dotted'
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# standard error bars
plt.errorbar(x, y, xerr=xerr, yerr=yerr, ls=ls, color='blue')
# including upper limits
uplims = np.zeros_like(x)
uplims[[1, 5, 9]] = True
plt.errorbar(x, y+0.5, xerr=xerr, yerr=yerr, uplims=uplims, ls=ls,
color='green')
# including lower limits
lolims = np.zeros_like(x)
lolims[[2, 4, 8]] = True
plt.errorbar(x, y+1.0, xerr=xerr, yerr=yerr, lolims=lolims, ls=ls,
color='red')
# including upper and lower limits
plt.errorbar(x, y+1.5, marker='o', ms=8, xerr=xerr, yerr=yerr,
lolims=lolims, uplims=uplims, ls=ls, color='magenta')
# including xlower and xupper limits
xerr = 0.2
yerr = np.zeros_like(x) + 0.2
yerr[[3, 6]] = 0.3
xlolims = lolims
xuplims = uplims
lolims = np.zeros_like(x)
uplims = np.zeros_like(x)
lolims[[6]] = True
uplims[[3]] = True
plt.errorbar(x, y+2.1, marker='o', ms=8, xerr=xerr, yerr=yerr,
xlolims=xlolims, xuplims=xuplims, uplims=uplims,
lolims=lolims, ls='none', mec='blue', capsize=0,
color='cyan')
ax.set_xlim((0, 5.5))
ax.set_title('Errorbar upper and lower limits')
def test_errobar_nonefmt():
# Check that passing 'none' as a format still plots errorbars
x = np.arange(5)
y = np.arange(5)
plotline, _, barlines = plt.errorbar(x, y, xerr=1, yerr=1, fmt='none')
assert plotline is None
for errbar in barlines:
assert np.all(errbar.get_color() == mcolors.to_rgba('C0'))
@image_comparison(baseline_images=['errorbar_with_prop_cycle'],
extensions=['png'], style='mpl20', remove_text=True)
def test_errorbar_with_prop_cycle():
_cycle = cycler(ls=['--', ':'], marker=['s', 's'], mfc=['k', 'w'])
plt.rc("axes", prop_cycle=_cycle)
fig, ax = plt.subplots()
ax.errorbar(x=[2, 4, 10], y=[3, 2, 4], yerr=0.5)
ax.errorbar(x=[2, 4, 10], y=[6, 4, 2], yerr=0.5)
@image_comparison(baseline_images=['hist_stacked_stepfilled',
'hist_stacked_stepfilled'])
def test_hist_stacked_stepfilled():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist((d1, d2), histtype="stepfilled", stacked=True)
# Reuse testcase from above for a labeled data test
data = {"x": (d1, d2)}
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist("x", histtype="stepfilled", stacked=True, data=data)
@image_comparison(baseline_images=['hist_offset'])
def test_hist_offset():
# make some data
d1 = np.linspace(0, 10, 50)
d2 = np.linspace(1, 3, 20)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist(d1, bottom=5)
ax.hist(d2, bottom=15)
@image_comparison(baseline_images=['hist_step'], extensions=['png'],
remove_text=True)
def test_hist_step():
# make some data
d1 = np.linspace(1, 3, 20)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist(d1, histtype="step")
ax.set_ylim(0, 10)
ax.set_xlim(-1, 5)
@image_comparison(baseline_images=['hist_step_horiz'], extensions=['png'])
def test_hist_step_horiz():
# make some data
d1 = np.linspace(0, 10, 50)
d2 = np.linspace(1, 3, 20)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist((d1, d2), histtype="step", orientation="horizontal")
@image_comparison(baseline_images=['hist_stacked_weights'])
def test_hist_stacked_weighted():
# make some data
d1 = np.linspace(0, 10, 50)
d2 = np.linspace(1, 3, 20)
w1 = np.linspace(0.01, 3.5, 50)
w2 = np.linspace(0.05, 2., 20)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist((d1, d2), weights=(w1, w2), histtype="stepfilled", stacked=True)
def test_stem_args():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
x = list(xrange(10))
y = list(xrange(10))
# Test the call signatures
ax.stem(y)
ax.stem(x, y)
ax.stem(x, y, 'r--')
ax.stem(x, y, 'r--', basefmt='b--')
def test_stem_dates():
fig, ax = plt.subplots(1, 1)
from dateutil import parser
x = parser.parse("2013-9-28 11:00:00")
y = 100
x1 = parser.parse("2013-9-28 12:00:00")
y1 = 200
ax.stem([x, x1], [y, y1], "*-")
@image_comparison(baseline_images=['hist_stacked_stepfilled_alpha'])
def test_hist_stacked_stepfilled_alpha():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist((d1, d2), histtype="stepfilled", stacked=True, alpha=0.5)
@image_comparison(baseline_images=['hist_stacked_step'])
def test_hist_stacked_step():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist((d1, d2), histtype="step", stacked=True)
@image_comparison(baseline_images=['hist_stacked_normed'])
def test_hist_stacked_normed():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig, ax = plt.subplots()
with pytest.warns(UserWarning):
ax.hist((d1, d2), stacked=True, normed=True)
@image_comparison(baseline_images=['hist_stacked_normed'], extensions=['png'])
def test_hist_stacked_density():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig, ax = plt.subplots()
ax.hist((d1, d2), stacked=True, density=True)
@pytest.mark.parametrize('normed', [False, True])
@pytest.mark.parametrize('density', [False, True])
def test_hist_normed_density(normed, density):
# Normed and density should not be used simultaneously
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig, ax = plt.subplots()
# test that kwargs normed and density cannot be set both.
with pytest.raises(Exception):
ax.hist((d1, d2), stacked=True, normed=normed, density=density)
@image_comparison(baseline_images=['hist_step_bottom'], extensions=['png'],
remove_text=True)
def test_hist_step_bottom():
# make some data
d1 = np.linspace(1, 3, 20)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist(d1, bottom=np.arange(10), histtype="stepfilled")
@image_comparison(baseline_images=['hist_stacked_bar'])
def test_hist_stacked_bar():
# make some data
d = [[100, 100, 100, 100, 200, 320, 450, 80, 20, 600, 310, 800],
[20, 23, 50, 11, 100, 420], [120, 120, 120, 140, 140, 150, 180],
[60, 60, 60, 60, 300, 300, 5, 5, 5, 5, 10, 300],
[555, 555, 555, 30, 30, 30, 30, 30, 100, 100, 100, 100, 30, 30],
[30, 30, 30, 30, 400, 400, 400, 400, 400, 400, 400, 400]]
colors = [(0.5759849696758961, 1.0, 0.0), (0.0, 1.0, 0.350624650815206),
(0.0, 1.0, 0.6549834156005998), (0.0, 0.6569064625276622, 1.0),
(0.28302699607823545, 0.0, 1.0), (0.6849123462299822, 0.0, 1.0)]
labels = ['green', 'orange', ' yellow', 'magenta', 'black']
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist(d, bins=10, histtype='barstacked', align='mid', color=colors,
label=labels)
ax.legend(loc='upper right', bbox_to_anchor=(1.0, 1.0), ncol=1)
def test_hist_emptydata():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist([[], range(10), range(10)], histtype="step")
@image_comparison(baseline_images=['transparent_markers'], remove_text=True)
def test_transparent_markers():
np.random.seed(0)
data = np.random.random(50)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(data, 'D', mfc='none', markersize=100)
@image_comparison(baseline_images=['rgba_markers'], remove_text=True)
def test_rgba_markers():
fig, axs = plt.subplots(ncols=2)
rcolors = [(1, 0, 0, 1), (1, 0, 0, 0.5)]
bcolors = [(0, 0, 1, 1), (0, 0, 1, 0.5)]
alphas = [None, 0.2]
kw = dict(ms=100, mew=20)
for i, alpha in enumerate(alphas):
for j, rcolor in enumerate(rcolors):
for k, bcolor in enumerate(bcolors):
axs[i].plot(j+1, k+1, 'o', mfc=bcolor, mec=rcolor,
alpha=alpha, **kw)
axs[i].plot(j+1, k+3, 'x', mec=rcolor, alpha=alpha, **kw)
for ax in axs:
ax.axis([-1, 4, 0, 5])
@image_comparison(baseline_images=['mollweide_grid'], remove_text=True)
def test_mollweide_grid():
# test that both horizontal and vertical gridlines appear on the Mollweide
# projection
fig = plt.figure()
ax = fig.add_subplot(111, projection='mollweide')
ax.grid()
def test_mollweide_forward_inverse_closure():
# test that the round-trip Mollweide forward->inverse transformation is an
# approximate identity
fig = plt.figure()
ax = fig.add_subplot(111, projection='mollweide')
# set up 1-degree grid in longitude, latitude
lon = np.linspace(-np.pi, np.pi, 360)
lat = np.linspace(-np.pi / 2.0, np.pi / 2.0, 180)
lon, lat = np.meshgrid(lon, lat)
ll = np.vstack((lon.flatten(), lat.flatten())).T
# perform forward transform
xy = ax.transProjection.transform(ll)
# perform inverse transform
ll2 = ax.transProjection.inverted().transform(xy)
# compare
np.testing.assert_array_almost_equal(ll, ll2, 3)
def test_mollweide_inverse_forward_closure():
# test that the round-trip Mollweide inverse->forward transformation is an
# approximate identity
fig = plt.figure()
ax = fig.add_subplot(111, projection='mollweide')
# set up grid in x, y
x = np.linspace(0, 1, 500)
x, y = np.meshgrid(x, x)
xy = np.vstack((x.flatten(), y.flatten())).T
# perform inverse transform
ll = ax.transProjection.inverted().transform(xy)
# perform forward transform
xy2 = ax.transProjection.transform(ll)
# compare
np.testing.assert_array_almost_equal(xy, xy2, 3)
@image_comparison(baseline_images=['test_alpha'], remove_text=True)
def test_alpha():
np.random.seed(0)
data = np.random.random(50)
fig = plt.figure()
ax = fig.add_subplot(111)
# alpha=.5 markers, solid line
ax.plot(data, '-D', color=[1, 0, 0], mfc=[1, 0, 0, .5],
markersize=20, lw=10)
# everything solid by kwarg
ax.plot(data + 2, '-D', color=[1, 0, 0, .5], mfc=[1, 0, 0, .5],
markersize=20, lw=10,
alpha=1)
# everything alpha=.5 by kwarg
ax.plot(data + 4, '-D', color=[1, 0, 0], mfc=[1, 0, 0],
markersize=20, lw=10,
alpha=.5)
# everything alpha=.5 by colors
ax.plot(data + 6, '-D', color=[1, 0, 0, .5], mfc=[1, 0, 0, .5],
markersize=20, lw=10)
# alpha=.5 line, solid markers
ax.plot(data + 8, '-D', color=[1, 0, 0, .5], mfc=[1, 0, 0],
markersize=20, lw=10)
@image_comparison(baseline_images=['eventplot', 'eventplot'], remove_text=True)
def test_eventplot():
'''
test that eventplot produces the correct output
'''
np.random.seed(0)
data1 = np.random.random([32, 20]).tolist()
data2 = np.random.random([6, 20]).tolist()
data = data1 + data2
num_datasets = len(data)
colors1 = [[0, 1, .7]] * len(data1)
colors2 = [[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[1, .75, 0],
[1, 0, 1],
[0, 1, 1]]
colors = colors1 + colors2
lineoffsets1 = 12 + np.arange(0, len(data1)) * .33
lineoffsets2 = [-15, -3, 1, 1.5, 6, 10]
lineoffsets = lineoffsets1.tolist() + lineoffsets2
linelengths1 = [.33] * len(data1)
linelengths2 = [5, 2, 1, 1, 3, 1.5]
linelengths = linelengths1 + linelengths2
fig = plt.figure()
axobj = fig.add_subplot(111)
colls = axobj.eventplot(data, colors=colors, lineoffsets=lineoffsets,
linelengths=linelengths)
num_collections = len(colls)
assert num_collections == num_datasets
# Reuse testcase from above for a labeled data test
data = {"pos": data, "c": colors, "lo": lineoffsets, "ll": linelengths}
fig = plt.figure()
axobj = fig.add_subplot(111)
colls = axobj.eventplot("pos", colors="c", lineoffsets="lo",
linelengths="ll", data=data)
num_collections = len(colls)
assert num_collections == num_datasets
@image_comparison(baseline_images=['test_eventplot_defaults'],
extensions=['png'], remove_text=True)
def test_eventplot_defaults():
'''
test that eventplot produces the correct output given the default params
(see bug #3728)
'''
np.random.seed(0)
data1 = np.random.random([32, 20]).tolist()
data2 = np.random.random([6, 20]).tolist()
data = data1 + data2
fig = plt.figure()
axobj = fig.add_subplot(111)
colls = axobj.eventplot(data)
@pytest.mark.parametrize(('colors'), [
('0.5',), # string color with multiple characters: not OK before #8193 fix
('tab:orange', 'tab:pink', 'tab:cyan', 'bLacK'), # case-insensitive
('red', (0, 1, 0), None, (1, 0, 1, 0.5)), # a tricky case mixing types
('rgbk',) # len('rgbk') == len(data) and each character is a valid color
])
def test_eventplot_colors(colors):
'''Test the *colors* parameter of eventplot. Inspired by the issue #8193.
'''
data = [[i] for i in range(4)] # 4 successive events of different nature
# Build the list of the expected colors
expected = [c if c is not None else 'C0' for c in colors]
# Convert the list into an array of RGBA values
# NB: ['rgbk'] is not a valid argument for to_rgba_array, while 'rgbk' is.
if len(expected) == 1:
expected = expected[0]
expected = broadcast_to(mcolors.to_rgba_array(expected), (len(data), 4))
fig, ax = plt.subplots()
if len(colors) == 1: # tuple with a single string (like '0.5' or 'rgbk')
colors = colors[0]
collections = ax.eventplot(data, colors=colors)
for coll, color in zip(collections, expected):
assert_allclose(coll.get_color(), color)
@image_comparison(baseline_images=['test_eventplot_problem_kwargs'],
extensions=['png'], remove_text=True)
def test_eventplot_problem_kwargs():
'''
test that 'singular' versions of LineCollection props raise an
IgnoredKeywordWarning rather than overriding the 'plural' versions (e.g.
to prevent 'color' from overriding 'colors', see issue #4297)
'''
np.random.seed(0)
data1 = np.random.random([20]).tolist()
data2 = np.random.random([10]).tolist()
data = [data1, data2]
fig = plt.figure()
axobj = fig.add_subplot(111)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
colls = axobj.eventplot(data,
colors=['r', 'b'],
color=['c', 'm'],
linewidths=[2, 1],
linewidth=[1, 2],
linestyles=['solid', 'dashed'],
linestyle=['dashdot', 'dotted'])
# check that three IgnoredKeywordWarnings were raised
assert len(w) == 3
assert all(issubclass(wi.category, IgnoredKeywordWarning) for wi in w)
def test_empty_eventplot():
fig, ax = plt.subplots(1, 1)
ax.eventplot([[]], colors=[(0.0, 0.0, 0.0, 0.0)])
plt.draw()
@pytest.mark.parametrize('data, orientation', product(
([[]], [[], [0, 1]], [[0, 1], []]),
('_empty', 'vertical', 'horizontal', None, 'none')))
def test_eventplot_orientation(data, orientation):
"""Introduced when fixing issue #6412. """
opts = {} if orientation == "_empty" else {'orientation': orientation}
fig, ax = plt.subplots(1, 1)
ax.eventplot(data, **opts)
plt.draw()
@image_comparison(baseline_images=['marker_styles'], extensions=['png'],
remove_text=True)
def test_marker_styles():
fig = plt.figure()
ax = fig.add_subplot(111)
for y, marker in enumerate(sorted(matplotlib.markers.MarkerStyle.markers,
key=lambda x: str(type(x))+str(x))):
ax.plot((y % 2)*5 + np.arange(10)*10, np.ones(10)*10*y, linestyle='',
marker=marker, markersize=10+y/5, label=marker)
@image_comparison(baseline_images=['rc_markerfill'], extensions=['png'])
def test_markers_fillstyle_rcparams():
fig, ax = plt.subplots()
x = np.arange(7)
for idx, (style, marker) in enumerate(
[('top', 's'), ('bottom', 'o'), ('none', '^')]):
matplotlib.rcParams['markers.fillstyle'] = style
ax.plot(x+idx, marker=marker)
@image_comparison(baseline_images=['vertex_markers'], extensions=['png'],
remove_text=True)
def test_vertex_markers():
data = list(xrange(10))
marker_as_tuple = ((-1, -1), (1, -1), (1, 1), (-1, 1))
marker_as_list = [(-1, -1), (1, -1), (1, 1), (-1, 1)]
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(data, linestyle='', marker=marker_as_tuple, mfc='k')
ax.plot(data[::-1], linestyle='', marker=marker_as_list, mfc='b')
ax.set_xlim([-1, 10])
ax.set_ylim([-1, 10])
@image_comparison(baseline_images=['vline_hline_zorder',
'errorbar_zorder'])
def test_eb_line_zorder():
x = list(xrange(10))
# First illustrate basic pyplot interface, using defaults where possible.
fig = plt.figure()
ax = fig.gca()
ax.plot(x, lw=10, zorder=5)
ax.axhline(1, color='red', lw=10, zorder=1)
ax.axhline(5, color='green', lw=10, zorder=10)
ax.axvline(7, color='m', lw=10, zorder=7)
ax.axvline(2, color='k', lw=10, zorder=3)
ax.set_title("axvline and axhline zorder test")
# Now switch to a more OO interface to exercise more features.
fig = plt.figure()
ax = fig.gca()
x = list(xrange(10))
y = np.zeros(10)
yerr = list(xrange(10))
ax.errorbar(x, y, yerr=yerr, zorder=5, lw=5, color='r')
for j in range(10):
ax.axhline(j, lw=5, color='k', zorder=j)
ax.axhline(-j, lw=5, color='k', zorder=j)
ax.set_title("errorbar zorder test")
@image_comparison(
baseline_images=['vlines_basic', 'vlines_with_nan', 'vlines_masked'],
extensions=['png']
)
def test_vlines():
# normal
x1 = [2, 3, 4, 5, 7]
y1 = [2, -6, 3, 8, 2]
fig1, ax1 = plt.subplots()
ax1.vlines(x1, 0, y1, colors='g', linewidth=5)
# GH #7406
x2 = [2, 3, 4, 5, 6, 7]
y2 = [2, -6, 3, 8, np.nan, 2]
fig2, (ax2, ax3, ax4) = plt.subplots(nrows=3, figsize=(4, 8))
ax2.vlines(x2, 0, y2, colors='g', linewidth=5)
x3 = [2, 3, 4, 5, 6, 7]
y3 = [np.nan, 2, -6, 3, 8, 2]
ax3.vlines(x3, 0, y3, colors='r', linewidth=3, linestyle='--')
x4 = [2, 3, 4, 5, 6, 7]
y4 = [np.nan, 2, -6, 3, 8, np.nan]
ax4.vlines(x4, 0, y4, colors='k', linewidth=2)
# tweak the x-axis so we can see the lines better
for ax in [ax1, ax2, ax3, ax4]:
ax.set_xlim(0, 10)
# check that the y-lims are all automatically the same
assert ax1.get_ylim() == ax2.get_ylim()
assert ax1.get_ylim() == ax3.get_ylim()
assert ax1.get_ylim() == ax4.get_ylim()
fig3, ax5 = plt.subplots()
x5 = np.ma.masked_equal([2, 4, 6, 8, 10, 12], 8)
ymin5 = np.ma.masked_equal([0, 1, -1, 0, 2, 1], 2)
ymax5 = np.ma.masked_equal([13, 14, 15, 16, 17, 18], 18)
ax5.vlines(x5, ymin5, ymax5, colors='k', linewidth=2)
ax5.set_xlim(0, 15)
@image_comparison(
baseline_images=['hlines_basic', 'hlines_with_nan', 'hlines_masked'],
extensions=['png']
)
def test_hlines():
# normal
y1 = [2, 3, 4, 5, 7]
x1 = [2, -6, 3, 8, 2]
fig1, ax1 = plt.subplots()
ax1.hlines(y1, 0, x1, colors='g', linewidth=5)
# GH #7406
y2 = [2, 3, 4, 5, 6, 7]
x2 = [2, -6, 3, 8, np.nan, 2]
fig2, (ax2, ax3, ax4) = plt.subplots(nrows=3, figsize=(4, 8))
ax2.hlines(y2, 0, x2, colors='g', linewidth=5)
y3 = [2, 3, 4, 5, 6, 7]
x3 = [np.nan, 2, -6, 3, 8, 2]
ax3.hlines(y3, 0, x3, colors='r', linewidth=3, linestyle='--')
y4 = [2, 3, 4, 5, 6, 7]
x4 = [np.nan, 2, -6, 3, 8, np.nan]
ax4.hlines(y4, 0, x4, colors='k', linewidth=2)
# tweak the y-axis so we can see the lines better
for ax in [ax1, ax2, ax3, ax4]:
ax.set_ylim(0, 10)
# check that the x-lims are all automatically the same
assert ax1.get_xlim() == ax2.get_xlim()
assert ax1.get_xlim() == ax3.get_xlim()
assert ax1.get_xlim() == ax4.get_xlim()
fig3, ax5 = plt.subplots()
y5 = np.ma.masked_equal([2, 4, 6, 8, 10, 12], 8)
xmin5 = np.ma.masked_equal([0, 1, -1, 0, 2, 1], 2)
xmax5 = np.ma.masked_equal([13, 14, 15, 16, 17, 18], 18)
ax5.hlines(y5, xmin5, xmax5, colors='k', linewidth=2)
ax5.set_ylim(0, 15)
@image_comparison(baseline_images=['step_linestyle', 'step_linestyle'],
remove_text=True)
def test_step_linestyle():
x = y = np.arange(10)
# First illustrate basic pyplot interface, using defaults where possible.
fig, ax_lst = plt.subplots(2, 2)
ax_lst = ax_lst.flatten()
ln_styles = ['-', '--', '-.', ':']
for ax, ls in zip(ax_lst, ln_styles):
ax.step(x, y, lw=5, linestyle=ls, where='pre')
ax.step(x, y + 1, lw=5, linestyle=ls, where='mid')
ax.step(x, y + 2, lw=5, linestyle=ls, where='post')
ax.set_xlim([-1, 5])
ax.set_ylim([-1, 7])
# Reuse testcase from above for a labeled data test
data = {"x": x, "y": y, "y1": y+1, "y2": y+2}
fig, ax_lst = plt.subplots(2, 2)
ax_lst = ax_lst.flatten()
ln_styles = ['-', '--', '-.', ':']
for ax, ls in zip(ax_lst, ln_styles):
ax.step("x", "y", lw=5, linestyle=ls, where='pre', data=data)
ax.step("x", "y1", lw=5, linestyle=ls, where='mid', data=data)
ax.step("x", "y2", lw=5, linestyle=ls, where='post', data=data)
ax.set_xlim([-1, 5])
ax.set_ylim([-1, 7])
@image_comparison(baseline_images=['mixed_collection'], remove_text=True)
def test_mixed_collection():
from matplotlib import patches
from matplotlib import collections
x = list(xrange(10))
# First illustrate basic pyplot interface, using defaults where possible.
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
c = patches.Circle((8, 8), radius=4, facecolor='none', edgecolor='green')
# PDF can optimize this one
p1 = collections.PatchCollection([c], match_original=True)
p1.set_offsets([[0, 0], [24, 24]])
p1.set_linewidths([1, 5])
# PDF can't optimize this one, because the alpha of the edge changes
p2 = collections.PatchCollection([c], match_original=True)
p2.set_offsets([[48, 0], [-32, -16]])
p2.set_linewidths([1, 5])
p2.set_edgecolors([[0, 0, 0.1, 1.0], [0, 0, 0.1, 0.5]])
ax.patch.set_color('0.5')
ax.add_collection(p1)
ax.add_collection(p2)
ax.set_xlim(0, 16)
ax.set_ylim(0, 16)
def test_subplot_key_hash():
ax = plt.subplot(np.float64(5.5), np.int64(1), np.float64(1.2))
ax.twinx()
assert ax.get_subplotspec().get_geometry() == (5, 1, 0, 0)
@image_comparison(baseline_images=['specgram_freqs',
'specgram_freqs_linear'],
remove_text=True, extensions=['png'], tol=0.07,
style='default')
def test_specgram_freqs():
'''test axes.specgram in default (psd) mode with sinusoidal stimuli'''
n = 1000
Fs = 10.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(10 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for fstim1, fstim2 in zip(fstims1, fstims2):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
y = np.hstack([y1, y2])
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided')
spec21 = ax21.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default',
scale='linear', norm=matplotlib.colors.LogNorm())
spec22 = ax22.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
scale='linear', norm=matplotlib.colors.LogNorm())
spec23 = ax23.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
scale='linear', norm=matplotlib.colors.LogNorm())
@image_comparison(baseline_images=['specgram_noise',
'specgram_noise_linear'],
remove_text=True, extensions=['png'], tol=0.01,
style='default')
def test_specgram_noise():
'''test axes.specgram in default (psd) mode with noise stimuli'''
np.random.seed(0)
n = 1000
Fs = 10.
NFFT = int(10 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2])
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided')
spec21 = ax21.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default',
scale='linear', norm=matplotlib.colors.LogNorm())
spec22 = ax22.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
scale='linear', norm=matplotlib.colors.LogNorm())
spec23 = ax23.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
scale='linear', norm=matplotlib.colors.LogNorm())
@image_comparison(baseline_images=['specgram_magnitude_freqs',
'specgram_magnitude_freqs_linear'],
remove_text=True, extensions=['png'], tol=0.07,
style='default')
def test_specgram_magnitude_freqs():
'''test axes.specgram in magnitude mode with sinusoidal stimuli'''
n = 1000
Fs = 10.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(100 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for i, (fstim1, fstim2) in enumerate(zip(fstims1, fstims2)):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
y1[-1] = y1[-1]/y1[-1]
y2[-1] = y2[-1]/y2[-1]
y = np.hstack([y1, y2])
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='magnitude')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='magnitude')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='magnitude')
spec21 = ax21.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
spec22 = ax22.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
spec23 = ax23.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
@image_comparison(baseline_images=['specgram_magnitude_noise',
'specgram_magnitude_noise_linear'],
remove_text=True, extensions=['png'],
style='default')
def test_specgram_magnitude_noise():
'''test axes.specgram in magnitude mode with noise stimuli'''
np.random.seed(0)
n = 1000
Fs = 10.
NFFT = int(10 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2])
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='magnitude')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='magnitude')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='magnitude')
spec21 = ax21.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
spec22 = ax22.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
spec23 = ax23.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='magnitude',
scale='linear', norm=matplotlib.colors.LogNorm())
@image_comparison(baseline_images=['specgram_angle_freqs'],
remove_text=True, extensions=['png'], tol=0.007,
style='default')
def test_specgram_angle_freqs():
'''test axes.specgram in angle mode with sinusoidal stimuli'''
n = 1000
Fs = 10.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(10 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for i, (fstim1, fstim2) in enumerate(zip(fstims1, fstims2)):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
y1[-1] = y1[-1]/y1[-1]
y2[-1] = y2[-1]/y2[-1]
y = np.hstack([y1, y2])
fig1 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='angle')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='angle')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='angle')
with pytest.raises(ValueError):
ax11.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='default',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax12.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='onesided',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax13.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='twosided',
mode='phase', scale='dB')
@image_comparison(baseline_images=['specgram_angle_noise'],
remove_text=True, extensions=['png'],
style='default')
def test_specgram_noise_angle():
'''test axes.specgram in angle mode with noise stimuli'''
np.random.seed(0)
n = 1000
Fs = 10.
NFFT = int(10 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2])
fig1 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='angle')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='angle')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='angle')
with pytest.raises(ValueError):
ax11.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='default',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax12.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='onesided',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax13.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='twosided',
mode='phase', scale='dB')
@image_comparison(baseline_images=['specgram_phase_freqs'],
remove_text=True, extensions=['png'],
style='default')
def test_specgram_freqs_phase():
'''test axes.specgram in phase mode with sinusoidal stimuli'''
n = 1000
Fs = 10.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(10 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for i, (fstim1, fstim2) in enumerate(zip(fstims1, fstims2)):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
y1[-1] = y1[-1]/y1[-1]
y2[-1] = y2[-1]/y2[-1]
y = np.hstack([y1, y2])
fig1 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default', mode='phase')
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided', mode='phase')
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided', mode='phase')
with pytest.raises(ValueError):
ax11.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='default',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax12.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='onesided',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax13.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='twosided',
mode='phase', scale='dB')
@image_comparison(baseline_images=['specgram_phase_noise'],
remove_text=True, extensions=['png'],
style='default')
def test_specgram_noise_phase():
'''test axes.specgram in phase mode with noise stimuli'''
np.random.seed(0)
n = 1000
Fs = 10.
NFFT = int(10 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2])
fig1 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
spec11 = ax11.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default',
mode='phase', )
spec12 = ax12.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
mode='phase', )
spec13 = ax13.specgram(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
mode='phase', )
with pytest.raises(ValueError):
ax11.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='default',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax12.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='onesided',
mode='phase', scale='dB')
with pytest.raises(ValueError):
ax13.specgram(y, NFFT=NFFT, Fs=Fs,
noverlap=noverlap, pad_to=pad_to, sides='twosided',
mode='phase', scale='dB')
@image_comparison(baseline_images=['psd_freqs'], remove_text=True,
extensions=['png'])
def test_psd_freqs():
'''test axes.psd with sinusoidal stimuli'''
n = 10000
Fs = 100.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(1000 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for fstim1, fstim2 in zip(fstims1, fstims2):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
y = np.hstack([y1, y2])
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
psd1, freqs1 = ax1.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
psd2, freqs2 = ax2.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
return_line=False)
psd3, freqs3, line3 = ax3.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
return_line=True)
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['psd_noise'], remove_text=True,
extensions=['png'])
def test_psd_noise():
'''test axes.psd with noise stimuli'''
np.random.seed(0)
n = 10000
Fs = 100.
NFFT = int(1000 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2])
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
psd1, freqs1 = ax1.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
psd2, freqs2 = ax2.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
return_line=False)
psd3, freqs3, line3 = ax3.psd(y, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
return_line=True)
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['csd_freqs'], remove_text=True,
extensions=['png'])
def test_csd_freqs():
'''test axes.csd with sinusoidal stimuli'''
n = 10000
Fs = 100.
fstims1 = [Fs/4, Fs/5, Fs/11]
fstims2 = [Fs/4.7, Fs/5.6, Fs/11.9]
NFFT = int(1000 * Fs / min(fstims1 + fstims2))
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y1 = np.zeros(x.size)
y2 = np.zeros(x.size)
for fstim1, fstim2 in zip(fstims1, fstims2):
y1 += np.sin(fstim1 * x * np.pi * 2)
y2 += np.sin(fstim2 * x * np.pi * 2)
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
csd1, freqs1 = ax1.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
csd2, freqs2 = ax2.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
return_line=False)
csd3, freqs3, line3 = ax3.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
return_line=True)
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['csd_noise'], remove_text=True,
extensions=['png'])
def test_csd_noise():
'''test axes.csd with noise stimuli'''
np.random.seed(0)
n = 10000
Fs = 100.
NFFT = int(1000 * Fs / 11)
noverlap = int(NFFT / 2)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
csd1, freqs1 = ax1.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='default')
csd2, freqs2 = ax2.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='onesided',
return_line=False)
csd3, freqs3, line3 = ax3.csd(y1, y2, NFFT=NFFT, Fs=Fs, noverlap=noverlap,
pad_to=pad_to, sides='twosided',
return_line=True)
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['magnitude_spectrum_freqs_linear',
'magnitude_spectrum_freqs_dB'],
remove_text=True,
extensions=['png'])
def test_magnitude_spectrum_freqs():
'''test axes.magnitude_spectrum with sinusoidal stimuli'''
n = 10000
Fs = 100.
fstims1 = [Fs/4, Fs/5, Fs/11]
NFFT = int(1000 * Fs / min(fstims1))
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y = np.zeros(x.size)
for i, fstim1 in enumerate(fstims1):
y += np.sin(fstim1 * x * np.pi * 2) * 10**i
y = y
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11, freqs11, line11 = ax11.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec12, freqs12, line12 = ax12.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec13, freqs13, line13 = ax13.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
spec21, freqs21, line21 = ax21.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default',
scale='dB')
spec22, freqs22, line22 = ax22.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided',
scale='dB')
spec23, freqs23, line23 = ax23.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided',
scale='dB')
ax11.set_xlabel('')
ax12.set_xlabel('')
ax13.set_xlabel('')
ax11.set_ylabel('')
ax12.set_ylabel('')
ax13.set_ylabel('')
ax21.set_xlabel('')
ax22.set_xlabel('')
ax23.set_xlabel('')
ax21.set_ylabel('')
ax22.set_ylabel('')
ax23.set_ylabel('')
@image_comparison(baseline_images=['magnitude_spectrum_noise_linear',
'magnitude_spectrum_noise_dB'],
remove_text=True,
extensions=['png'])
def test_magnitude_spectrum_noise():
'''test axes.magnitude_spectrum with noise stimuli'''
np.random.seed(0)
n = 10000
Fs = 100.
NFFT = int(1000 * Fs / 11)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2]) - .5
fig1 = plt.figure()
fig2 = plt.figure()
ax11 = fig1.add_subplot(3, 1, 1)
ax12 = fig1.add_subplot(3, 1, 2)
ax13 = fig1.add_subplot(3, 1, 3)
ax21 = fig2.add_subplot(3, 1, 1)
ax22 = fig2.add_subplot(3, 1, 2)
ax23 = fig2.add_subplot(3, 1, 3)
spec11, freqs11, line11 = ax11.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec12, freqs12, line12 = ax12.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec13, freqs13, line13 = ax13.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
spec21, freqs21, line21 = ax21.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default',
scale='dB')
spec22, freqs22, line22 = ax22.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided',
scale='dB')
spec23, freqs23, line23 = ax23.magnitude_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided',
scale='dB')
ax11.set_xlabel('')
ax12.set_xlabel('')
ax13.set_xlabel('')
ax11.set_ylabel('')
ax12.set_ylabel('')
ax13.set_ylabel('')
ax21.set_xlabel('')
ax22.set_xlabel('')
ax23.set_xlabel('')
ax21.set_ylabel('')
ax22.set_ylabel('')
ax23.set_ylabel('')
@image_comparison(baseline_images=['angle_spectrum_freqs'],
remove_text=True,
extensions=['png'])
def test_angle_spectrum_freqs():
'''test axes.angle_spectrum with sinusoidal stimuli'''
n = 10000
Fs = 100.
fstims1 = [Fs/4, Fs/5, Fs/11]
NFFT = int(1000 * Fs / min(fstims1))
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y = np.zeros(x.size)
for i, fstim1 in enumerate(fstims1):
y += np.sin(fstim1 * x * np.pi * 2) * 10**i
y = y
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
spec1, freqs1, line1 = ax1.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec2, freqs2, line2 = ax2.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec3, freqs3, line3 = ax3.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['angle_spectrum_noise'],
remove_text=True,
extensions=['png'])
def test_angle_spectrum_noise():
'''test axes.angle_spectrum with noise stimuli'''
np.random.seed(0)
n = 10000
Fs = 100.
NFFT = int(1000 * Fs / 11)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2]) - .5
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
spec1, freqs1, line1 = ax1.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec2, freqs2, line2 = ax2.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec3, freqs3, line3 = ax3.angle_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['phase_spectrum_freqs'],
remove_text=True,
extensions=['png'])
def test_phase_spectrum_freqs():
'''test axes.phase_spectrum with sinusoidal stimuli'''
n = 10000
Fs = 100.
fstims1 = [Fs/4, Fs/5, Fs/11]
NFFT = int(1000 * Fs / min(fstims1))
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
x = np.arange(0, n, 1/Fs)
y = np.zeros(x.size)
for i, fstim1 in enumerate(fstims1):
y += np.sin(fstim1 * x * np.pi * 2) * 10**i
y = y
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
spec1, freqs1, line1 = ax1.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec2, freqs2, line2 = ax2.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec3, freqs3, line3 = ax3.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['phase_spectrum_noise'],
remove_text=True,
extensions=['png'])
def test_phase_spectrum_noise():
'''test axes.phase_spectrum with noise stimuli'''
np.random.seed(0)
n = 10000
Fs = 100.
NFFT = int(1000 * Fs / 11)
pad_to = int(2 ** np.ceil(np.log2(NFFT)))
y1 = np.random.standard_normal(n)
y2 = np.random.rand(n)
y = np.hstack([y1, y2]) - .5
fig = plt.figure()
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
spec1, freqs1, line1 = ax1.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='default')
spec2, freqs2, line2 = ax2.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='onesided')
spec3, freqs3, line3 = ax3.phase_spectrum(y, Fs=Fs, pad_to=pad_to,
sides='twosided')
ax1.set_xlabel('')
ax2.set_xlabel('')
ax3.set_xlabel('')
ax1.set_ylabel('')
ax2.set_ylabel('')
ax3.set_ylabel('')
@image_comparison(baseline_images=['twin_spines'], remove_text=True,
extensions=['png'])
def test_twin_spines():
def make_patch_spines_invisible(ax):
ax.set_frame_on(True)
ax.patch.set_visible(False)
for sp in six.itervalues(ax.spines):
sp.set_visible(False)
fig = plt.figure(figsize=(4, 3))
fig.subplots_adjust(right=0.75)
host = fig.add_subplot(111)
par1 = host.twinx()
par2 = host.twinx()
# Offset the right spine of par2. The ticks and label have already been
# placed on the right by twinx above.
par2.spines["right"].set_position(("axes", 1.2))
# Having been created by twinx, par2 has its frame off, so the line of
# its detached spine is invisible. First, activate the frame but make
# the patch and spines invisible.
make_patch_spines_invisible(par2)
# Second, show the right spine.
par2.spines["right"].set_visible(True)
p1, = host.plot([0, 1, 2], [0, 1, 2], "b-")
p2, = par1.plot([0, 1, 2], [0, 3, 2], "r-")
p3, = par2.plot([0, 1, 2], [50, 30, 15], "g-")
host.set_xlim(0, 2)
host.set_ylim(0, 2)
par1.set_ylim(0, 4)
par2.set_ylim(1, 65)
host.yaxis.label.set_color(p1.get_color())
par1.yaxis.label.set_color(p2.get_color())
par2.yaxis.label.set_color(p3.get_color())
tkw = dict(size=4, width=1.5)
host.tick_params(axis='y', colors=p1.get_color(), **tkw)
par1.tick_params(axis='y', colors=p2.get_color(), **tkw)
par2.tick_params(axis='y', colors=p3.get_color(), **tkw)
host.tick_params(axis='x', **tkw)
@image_comparison(baseline_images=['twin_spines_on_top', 'twin_spines_on_top'],
extensions=['png'], remove_text=True)
def test_twin_spines_on_top():
matplotlib.rcParams['axes.linewidth'] = 48.0
matplotlib.rcParams['lines.linewidth'] = 48.0
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
data = np.array([[1000, 1100, 1200, 1250],
[310, 301, 360, 400]])
ax2 = ax1.twinx()
ax1.plot(data[0], data[1]/1E3, color='#BEAED4')
ax1.fill_between(data[0], data[1]/1E3, color='#BEAED4', alpha=.8)
ax2.plot(data[0], data[1]/1E3, color='#7FC97F')
ax2.fill_between(data[0], data[1]/1E3, color='#7FC97F', alpha=.5)
# Reuse testcase from above for a labeled data test
data = {"i": data[0], "j": data[1]/1E3}
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
ax2 = ax1.twinx()
ax1.plot("i", "j", color='#BEAED4', data=data)
ax1.fill_between("i", "j", color='#BEAED4', alpha=.8, data=data)
ax2.plot("i", "j", color='#7FC97F', data=data)
ax2.fill_between("i", "j", color='#7FC97F', alpha=.5, data=data)
def test_rcparam_grid_minor():
orig_grid = matplotlib.rcParams['axes.grid']
orig_locator = matplotlib.rcParams['axes.grid.which']
matplotlib.rcParams['axes.grid'] = True
values = (
(('both'), (True, True)),
(('major'), (True, False)),
(('minor'), (False, True))
)
for locator, result in values:
matplotlib.rcParams['axes.grid.which'] = locator
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
assert (ax.xaxis._gridOnMajor, ax.xaxis._gridOnMinor) == result
matplotlib.rcParams['axes.grid'] = orig_grid
matplotlib.rcParams['axes.grid.which'] = orig_locator
def test_vline_limit():
fig = plt.figure()
ax = fig.gca()
ax.axvline(0.5)
ax.plot([-0.1, 0, 0.2, 0.1])
(ymin, ymax) = ax.get_ylim()
assert_allclose(ax.get_ylim(), (-.1, .2))
def test_empty_shared_subplots():
# empty plots with shared axes inherit limits from populated plots
fig, axes = plt.subplots(nrows=1, ncols=2, sharex=True, sharey=True)
axes[0].plot([1, 2, 3], [2, 4, 6])
x0, x1 = axes[1].get_xlim()
y0, y1 = axes[1].get_ylim()
assert x0 <= 1
assert x1 >= 3
assert y0 <= 2
assert y1 >= 6
def test_shared_with_aspect_1():
# allow sharing one axis
for adjustable in ['box', 'datalim']:
fig, axes = plt.subplots(nrows=2, sharex=True)
axes[0].set_aspect(2, adjustable=adjustable, share=True)
assert axes[1].get_aspect() == 2
assert axes[1].get_adjustable() == adjustable
fig, axes = plt.subplots(nrows=2, sharex=True)
axes[0].set_aspect(2, adjustable=adjustable)
assert axes[1].get_aspect() == 'auto'
def test_shared_with_aspect_2():
# Share 2 axes only with 'box':
fig, axes = plt.subplots(nrows=2, sharex=True, sharey=True)
axes[0].set_aspect(2, share=True)
axes[0].plot([1, 2], [3, 4])
axes[1].plot([3, 4], [1, 2])
plt.draw() # Trigger apply_aspect().
assert axes[0].get_xlim() == axes[1].get_xlim()
assert axes[0].get_ylim() == axes[1].get_ylim()
def test_shared_with_aspect_3():
# Different aspect ratios:
for adjustable in ['box', 'datalim']:
fig, axes = plt.subplots(nrows=2, sharey=True)
axes[0].set_aspect(2, adjustable=adjustable)
axes[1].set_aspect(0.5, adjustable=adjustable)
axes[0].plot([1, 2], [3, 4])
axes[1].plot([3, 4], [1, 2])
plt.draw() # Trigger apply_aspect().
assert axes[0].get_xlim() != axes[1].get_xlim()
assert axes[0].get_ylim() == axes[1].get_ylim()
fig_aspect = fig.bbox_inches.height / fig.bbox_inches.width
for ax in axes:
p = ax.get_position()
box_aspect = p.height / p.width
lim_aspect = ax.viewLim.height / ax.viewLim.width
expected = fig_aspect * box_aspect / lim_aspect
assert round(expected, 4) == round(ax.get_aspect(), 4)
@pytest.mark.parametrize('twin', ('x', 'y'))
def test_twin_with_aspect(twin):
fig, ax = plt.subplots()
# test twinx or twiny
ax_twin = getattr(ax, 'twin{}'.format(twin))()
ax.set_aspect(5)
ax_twin.set_aspect(2)
assert_array_equal(ax.bbox.extents,
ax_twin.bbox.extents)
def test_relim_visible_only():
x1 = (0., 10.)
y1 = (0., 10.)
x2 = (-10., 20.)
y2 = (-10., 30.)
fig = matplotlib.figure.Figure()
ax = fig.add_subplot(111)
ax.plot(x1, y1)
assert ax.get_xlim() == x1
assert ax.get_ylim() == y1
l = ax.plot(x2, y2)
assert ax.get_xlim() == x2
assert ax.get_ylim() == y2
l[0].set_visible(False)
assert ax.get_xlim() == x2
assert ax.get_ylim() == y2
ax.relim(visible_only=True)
ax.autoscale_view()
assert ax.get_xlim() == x1
assert ax.get_ylim() == y1
def test_text_labelsize():
"""
tests for issue #1172
"""
fig = plt.figure()
ax = fig.gca()
ax.tick_params(labelsize='large')
ax.tick_params(direction='out')
@image_comparison(baseline_images=['pie_linewidth_0', 'pie_linewidth_0',
'pie_linewidth_0'],
extensions=['png'])
def test_pie_linewidth_0():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0})
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
# Reuse testcase from above for a labeled data test
data = {"l": labels, "s": sizes, "c": colors, "ex": explode}
fig = plt.figure()
ax = fig.gca()
ax.pie("s", explode="ex", labels="l", colors="c",
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0}, data=data)
ax.axis('equal')
# And again to test the pyplot functions which should also be able to be
# called with a data kwarg
plt.figure()
plt.pie("s", explode="ex", labels="l", colors="c",
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0}, data=data)
plt.axis('equal')
@image_comparison(baseline_images=['pie_center_radius'], extensions=['png'])
def test_pie_center_radius():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0}, center=(1, 2), radius=1.5)
plt.annotate("Center point", xy=(1, 2), xytext=(1, 1.5),
arrowprops=dict(arrowstyle="->",
connectionstyle="arc3"))
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
@image_comparison(baseline_images=['pie_linewidth_2'], extensions=['png'])
def test_pie_linewidth_2():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 2})
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
@image_comparison(baseline_images=['pie_ccw_true'], extensions=['png'])
def test_pie_ccw_true():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
counterclock=True)
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
@image_comparison(baseline_images=['pie_frame_grid'], extensions=['png'])
def test_pie_frame_grid():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
# only "explode" the 2nd slice (i.e. 'Hogs')
explode = (0, 0.1, 0, 0)
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0},
frame=True, center=(2, 2))
plt.pie(sizes[::-1], explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0},
frame=True, center=(5, 2))
plt.pie(sizes, explode=explode[::-1], labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
wedgeprops={'linewidth': 0},
frame=True, center=(3, 5))
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
@image_comparison(baseline_images=['pie_rotatelabels_true'],
extensions=['png'])
def test_pie_rotatelabels_true():
# The slices will be ordered and plotted counter-clockwise.
labels = 'Hogwarts', 'Frogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct='%1.1f%%', shadow=True, startangle=90,
rotatelabels=True)
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')
@image_comparison(baseline_images=['set_get_ticklabels'], extensions=['png'])
def test_set_get_ticklabels():
# test issue 2246
fig, ax = plt.subplots(2)
ha = ['normal', 'set_x/yticklabels']
ax[0].plot(np.arange(10))
ax[0].set_title(ha[0])
ax[1].plot(np.arange(10))
ax[1].set_title(ha[1])
# set ticklabel to 1 plot in normal way
ax[0].set_xticklabels(('a', 'b', 'c', 'd'))
ax[0].set_yticklabels(('11', '12', '13', '14'))
# set ticklabel to the other plot, expect the 2 plots have same label
# setting pass get_ticklabels return value as ticklabels argument
ax[1].set_xticklabels(ax[0].get_xticklabels())
ax[1].set_yticklabels(ax[0].get_yticklabels())
def test_tick_label_update():
# test issue 9397
fig, ax = plt.subplots()
# Set up a dummy formatter
def formatter_func(x, pos):
return "unit value" if x == 1 else ""
ax.xaxis.set_major_formatter(plt.FuncFormatter(formatter_func))
# Force some of the x-axis ticks to be outside of the drawn range
ax.set_xticks([-1, 0, 1, 2, 3])
ax.set_xlim(-0.5, 2.5)
ax.figure.canvas.draw()
tick_texts = [tick.get_text() for tick in ax.xaxis.get_ticklabels()]
assert tick_texts == ["", "", "unit value", "", ""]
@image_comparison(baseline_images=['o_marker_path_snap'], extensions=['png'],
savefig_kwarg={'dpi': 72})
def test_o_marker_path_snap():
fig, ax = plt.subplots()
ax.margins(.1)
for ms in range(1, 15):
ax.plot([1, 2, ], np.ones(2) + ms, 'o', ms=ms)
for ms in np.linspace(1, 10, 25):
ax.plot([3, 4, ], np.ones(2) + ms, 'o', ms=ms)
def test_margins():
# test all ways margins can be called
data = [1, 10]
xmin = 0.0
xmax = len(data) - 1.0
ymin = min(data)
ymax = max(data)
fig1, ax1 = plt.subplots(1, 1)
ax1.plot(data)
ax1.margins(1)
assert ax1.margins() == (1, 1)
assert ax1.get_xlim() == (xmin - (xmax - xmin) * 1,
xmax + (xmax - xmin) * 1)
assert ax1.get_ylim() == (ymin - (ymax - ymin) * 1,
ymax + (ymax - ymin) * 1)
fig2, ax2 = plt.subplots(1, 1)
ax2.plot(data)
ax2.margins(0.5, 2)
assert ax2.margins() == (0.5, 2)
assert ax2.get_xlim() == (xmin - (xmax - xmin) * 0.5,
xmax + (xmax - xmin) * 0.5)
assert ax2.get_ylim() == (ymin - (ymax - ymin) * 2,
ymax + (ymax - ymin) * 2)
fig3, ax3 = plt.subplots(1, 1)
ax3.plot(data)
ax3.margins(x=-0.2, y=0.5)
assert ax3.margins() == (-0.2, 0.5)
assert ax3.get_xlim() == (xmin - (xmax - xmin) * -0.2,
xmax + (xmax - xmin) * -0.2)
assert ax3.get_ylim() == (ymin - (ymax - ymin) * 0.5,
ymax + (ymax - ymin) * 0.5)
def test_length_one_hist():
fig, ax = plt.subplots()
ax.hist(1)
ax.hist([1])
def test_pathological_hexbin():
# issue #2863
out = io.BytesIO()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
mylist = [10] * 100
fig, ax = plt.subplots(1, 1)
ax.hexbin(mylist, mylist)
fig.savefig(out)
assert len(w) == 0
def test_color_None():
# issue 3855
fig, ax = plt.subplots()
ax.plot([1, 2], [1, 2], color=None)
def test_color_alias():
# issues 4157 and 4162
fig, ax = plt.subplots()
line = ax.plot([0, 1], c='lime')[0]
assert 'lime' == line.get_color()
def test_numerical_hist_label():
fig, ax = plt.subplots()
ax.hist([range(15)] * 5, label=range(5))
ax.legend()
def test_unicode_hist_label():
fig, ax = plt.subplots()
a = (b'\xe5\xbe\x88\xe6\xbc\x82\xe4\xba\xae, ' +
b'r\xc3\xb6m\xc3\xa4n ch\xc3\xa4r\xc3\xa1ct\xc3\xa8rs')
b = b'\xd7\xa9\xd7\x9c\xd7\x95\xd7\x9d'
labels = [a.decode('utf-8'),
'hi aardvark',
b.decode('utf-8'),
]
ax.hist([range(15)] * 3, label=labels)
ax.legend()
def test_move_offsetlabel():
data = np.random.random(10) * 1e-22
fig, ax = plt.subplots()
ax.plot(data)
ax.yaxis.tick_right()
assert (1, 0.5) == ax.yaxis.offsetText.get_position()
@image_comparison(baseline_images=['rc_spines'], extensions=['png'],
savefig_kwarg={'dpi': 40})
def test_rc_spines():
rc_dict = {
'axes.spines.left': False,
'axes.spines.right': False,
'axes.spines.top': False,
'axes.spines.bottom': False}
with matplotlib.rc_context(rc_dict):
fig, ax = plt.subplots()
@image_comparison(baseline_images=['rc_grid'], extensions=['png'],
savefig_kwarg={'dpi': 40})
def test_rc_grid():
fig = plt.figure()
rc_dict0 = {
'axes.grid': True,
'axes.grid.axis': 'both'
}
rc_dict1 = {
'axes.grid': True,
'axes.grid.axis': 'x'
}
rc_dict2 = {
'axes.grid': True,
'axes.grid.axis': 'y'
}
dict_list = [rc_dict0, rc_dict1, rc_dict2]
i = 1
for rc_dict in dict_list:
with matplotlib.rc_context(rc_dict):
fig.add_subplot(3, 1, i)
i += 1
def test_rc_tick():
d = {'xtick.bottom': False, 'xtick.top': True,
'ytick.left': True, 'ytick.right': False}
with plt.rc_context(rc=d):
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
xax = ax1.xaxis
yax = ax1.yaxis
# tick1On bottom/left
assert not xax._major_tick_kw['tick1On']
assert xax._major_tick_kw['tick2On']
assert not xax._minor_tick_kw['tick1On']
assert xax._minor_tick_kw['tick2On']
assert yax._major_tick_kw['tick1On']
assert not yax._major_tick_kw['tick2On']
assert yax._minor_tick_kw['tick1On']
assert not yax._minor_tick_kw['tick2On']
def test_rc_major_minor_tick():
d = {'xtick.top': True, 'ytick.right': True, # Enable all ticks
'xtick.bottom': True, 'ytick.left': True,
# Selectively disable
'xtick.minor.bottom': False, 'xtick.major.bottom': False,
'ytick.major.left': False, 'ytick.minor.left': False}
with plt.rc_context(rc=d):
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
xax = ax1.xaxis
yax = ax1.yaxis
# tick1On bottom/left
assert not xax._major_tick_kw['tick1On']
assert xax._major_tick_kw['tick2On']
assert not xax._minor_tick_kw['tick1On']
assert xax._minor_tick_kw['tick2On']
assert not yax._major_tick_kw['tick1On']
assert yax._major_tick_kw['tick2On']
assert not yax._minor_tick_kw['tick1On']
assert yax._minor_tick_kw['tick2On']
def test_square_plot():
x = np.arange(4)
y = np.array([1., 3., 5., 7.])
fig, ax = plt.subplots()
ax.plot(x, y, 'mo')
ax.axis('square')
xlim, ylim = ax.get_xlim(), ax.get_ylim()
assert np.diff(xlim) == np.diff(ylim)
assert ax.get_aspect() == 'equal'
def test_no_None():
fig, ax = plt.subplots()
with pytest.raises(ValueError):
plt.plot(None)
with pytest.raises(ValueError):
plt.plot(None, None)
def test_pcolor_fast_non_uniform():
Z = np.arange(6).reshape((3, 2))
X = np.array([0, 1, 2, 10])
Y = np.array([0, 1, 2])
plt.figure()
ax = plt.subplot(111)
ax.pcolorfast(X, Y, Z.T)
def test_shared_scale():
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True)
axs[0, 0].set_xscale("log")
axs[0, 0].set_yscale("log")
for ax in axs.flat:
assert ax.get_yscale() == 'log'
assert ax.get_xscale() == 'log'
axs[1, 1].set_xscale("linear")
axs[1, 1].set_yscale("linear")
for ax in axs.flat:
assert ax.get_yscale() == 'linear'
assert ax.get_xscale() == 'linear'
def test_violin_point_mass():
"""Violin plot should handle point mass pdf gracefully."""
plt.violinplot(np.array([0, 0]))
def generate_errorbar_inputs():
base_xy = cycler('x', [np.arange(5)]) + cycler('y', [np.ones((5, ))])
err_cycler = cycler('err', [1,
[1, 1, 1, 1, 1],
[[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1]],
[[1]] * 5,
np.ones(5),
np.ones((2, 5)),
np.ones((5, 1)),
None
])
xerr_cy = cycler('xerr', err_cycler)
yerr_cy = cycler('yerr', err_cycler)
empty = ((cycler('x', [[]]) + cycler('y', [[]])) *
cycler('xerr', [[], None]) * cycler('yerr', [[], None]))
xerr_only = base_xy * xerr_cy
yerr_only = base_xy * yerr_cy
both_err = base_xy * yerr_cy * xerr_cy
test_cyclers = chain(xerr_only, yerr_only, both_err, empty)
return test_cyclers
@pytest.mark.parametrize('kwargs', generate_errorbar_inputs())
def test_errorbar_inputs_shotgun(kwargs):
ax = plt.gca()
eb = ax.errorbar(**kwargs)
eb.remove()
@image_comparison(baseline_images=["dash_offset"], remove_text=True)
def test_dash_offset():
fig, ax = plt.subplots()
x = np.linspace(0, 10)
y = np.ones_like(x)
for j in range(0, 100, 2):
ax.plot(x, j*y, ls=(j, (10, 10)), lw=5, color='k')
def test_title_pad():
# check that title padding puts the title in the right
# place...
fig, ax = plt.subplots()
ax.set_title('aardvark', pad=30.)
m = ax.titleOffsetTrans.get_matrix()
assert m[1, -1] == (30. / 72. * fig.dpi)
ax.set_title('aardvark', pad=0.)
m = ax.titleOffsetTrans.get_matrix()
assert m[1, -1] == 0.
# check that it is reverted...
ax.set_title('aardvark', pad=None)
m = ax.titleOffsetTrans.get_matrix()
assert m[1, -1] == (matplotlib.rcParams['axes.titlepad'] / 72. * fig.dpi)
def test_title_location_roundtrip():
fig, ax = plt.subplots()
ax.set_title('aardvark')
ax.set_title('left', loc='left')
ax.set_title('right', loc='right')
assert 'left' == ax.get_title(loc='left')
assert 'right' == ax.get_title(loc='right')
assert 'aardvark' == ax.get_title()
with pytest.raises(ValueError):
ax.get_title(loc='foo')
with pytest.raises(ValueError):
ax.set_title('fail', loc='foo')
@image_comparison(baseline_images=["loglog"], remove_text=True,
extensions=['png'])
def test_loglog():
fig, ax = plt.subplots()
x = np.arange(1, 11)
ax.loglog(x, x**3, lw=5)
ax.tick_params(length=25, width=2)
ax.tick_params(length=15, width=2, which='minor')
@image_comparison(baseline_images=["test_loglog_nonpos"],
remove_text=True, extensions=['png'], style='mpl20')
def test_loglog_nonpos():
fig, ax = plt.subplots(3, 3)
x = np.arange(1, 11)
y = x**3
y[7] = -3.
x[4] = -10
for nn, mcx in enumerate(['mask', 'clip', '']):
for mm, mcy in enumerate(['mask', 'clip', '']):
kws = {}
if mcx:
kws['nonposx'] = mcx
if mcy:
kws['nonposy'] = mcy
ax[mm, nn].loglog(x, y**3, lw=2, **kws)
@pytest.mark.style('default')
def test_axes_margins():
fig, ax = plt.subplots()
ax.plot([0, 1, 2, 3])
assert ax.get_ybound()[0] != 0
fig, ax = plt.subplots()
ax.bar([0, 1, 2, 3], [1, 1, 1, 1])
assert ax.get_ybound()[0] == 0
fig, ax = plt.subplots()
ax.barh([0, 1, 2, 3], [1, 1, 1, 1])
assert ax.get_xbound()[0] == 0
fig, ax = plt.subplots()
ax.pcolor(np.zeros((10, 10)))
assert ax.get_xbound() == (0, 10)
assert ax.get_ybound() == (0, 10)
fig, ax = plt.subplots()
ax.pcolorfast(np.zeros((10, 10)))
assert ax.get_xbound() == (0, 10)
assert ax.get_ybound() == (0, 10)
fig, ax = plt.subplots()
ax.hist(np.arange(10))
assert ax.get_ybound()[0] == 0
fig, ax = plt.subplots()
ax.imshow(np.zeros((10, 10)))
assert ax.get_xbound() == (-0.5, 9.5)
assert ax.get_ybound() == (-0.5, 9.5)
@pytest.fixture(params=['x', 'y'])
def shared_axis_remover(request):
def _helper_x(ax):
ax2 = ax.twinx()
ax2.remove()
ax.set_xlim(0, 15)
r = ax.xaxis.get_major_locator()()
assert r[-1] > 14
def _helper_y(ax):
ax2 = ax.twiny()
ax2.remove()
ax.set_ylim(0, 15)
r = ax.yaxis.get_major_locator()()
assert r[-1] > 14
return {"x": _helper_x, "y": _helper_y}[request.param]
@pytest.fixture(params=['gca', 'subplots', 'subplots_shared', 'add_axes'])
def shared_axes_generator(request):
# test all of the ways to get fig/ax sets
if request.param == 'gca':
fig = plt.figure()
ax = fig.gca()
elif request.param == 'subplots':
fig, ax = plt.subplots()
elif request.param == 'subplots_shared':
fig, ax_lst = plt.subplots(2, 2, sharex='all', sharey='all')
ax = ax_lst[0][0]
elif request.param == 'add_axes':
fig = plt.figure()
ax = fig.add_axes([.1, .1, .8, .8])
return fig, ax
def test_remove_shared_axes(shared_axes_generator, shared_axis_remover):
# test all of the ways to get fig/ax sets
fig, ax = shared_axes_generator
shared_axis_remover(ax)
def test_remove_shared_axes_relim():
fig, ax_lst = plt.subplots(2, 2, sharex='all', sharey='all')
ax = ax_lst[0][0]
orig_xlim = ax_lst[0][1].get_xlim()
ax.remove()
ax.set_xlim(0, 5)
assert_array_equal(ax_lst[0][1].get_xlim(), orig_xlim)
def test_adjust_numtick_aspect():
fig, ax = plt.subplots()
ax.yaxis.get_major_locator().set_params(nbins='auto')
ax.set_xlim(0, 1000)
ax.set_aspect('equal')
fig.canvas.draw()
assert len(ax.yaxis.get_major_locator()()) == 2
ax.set_ylim(0, 1000)
fig.canvas.draw()
assert len(ax.yaxis.get_major_locator()()) > 2
@image_comparison(baseline_images=["auto_numticks"], style='default',
extensions=['png'])
def test_auto_numticks():
# Make tiny, empty subplots, verify that there are only 3 ticks.
fig, axes = plt.subplots(4, 4)
@image_comparison(baseline_images=["auto_numticks_log"], style='default',
extensions=['png'])
def test_auto_numticks_log():
# Verify that there are not too many ticks with a large log range.
fig, ax = plt.subplots()
matplotlib.rcParams['axes.autolimit_mode'] = 'round_numbers'
ax.loglog([1e-20, 1e5], [1e-16, 10])
def test_broken_barh_empty():
fig, ax = plt.subplots()
ax.broken_barh([], (.1, .5))
def test_pandas_pcolormesh(pd):
time = pd.date_range('2000-01-01', periods=10)
depth = np.arange(20)
data = np.random.rand(20, 10)
fig, ax = plt.subplots()
ax.pcolormesh(time, depth, data)
def test_pandas_indexing_dates(pd):
dates = np.arange('2005-02', '2005-03', dtype='datetime64[D]')
values = np.sin(np.array(range(len(dates))))
df = pd.DataFrame({'dates': dates, 'values': values})
ax = plt.gca()
without_zero_index = df[np.array(df.index) % 2 == 1].copy()
ax.plot('dates', 'values', data=without_zero_index)
def test_pandas_errorbar_indexing(pd):
df = pd.DataFrame(np.random.uniform(size=(5, 4)),
columns=['x', 'y', 'xe', 'ye'],
index=[1, 2, 3, 4, 5])
fig, ax = plt.subplots()
ax.errorbar('x', 'y', xerr='xe', yerr='ye', data=df)
def test_pandas_indexing_hist(pd):
ser_1 = pd.Series(data=[1, 2, 2, 3, 3, 4, 4, 4, 4, 5])
ser_2 = ser_1.iloc[1:]
fig, axes = plt.subplots()
axes.hist(ser_2)
def test_pandas_bar_align_center(pd):
# Tests fix for issue 8767
df = pd.DataFrame({'a': range(2), 'b': range(2)})
fig, ax = plt.subplots(1)
ax.bar(df.loc[df['a'] == 1, 'b'],
df.loc[df['a'] == 1, 'b'],
align='center')
fig.canvas.draw()
def test_axis_set_tick_params_labelsize_labelcolor():
# Tests fix for issue 4346
axis_1 = plt.subplot()
axis_1.yaxis.set_tick_params(labelsize=30, labelcolor='red',
direction='out')
# Expected values after setting the ticks
assert axis_1.yaxis.majorTicks[0]._size == 4.0
assert axis_1.yaxis.majorTicks[0]._color == 'k'
assert axis_1.yaxis.majorTicks[0]._labelsize == 30.0
assert axis_1.yaxis.majorTicks[0]._labelcolor == 'red'
def test_axes_tick_params_gridlines():
# Now treating grid params like other Tick params
ax = plt.subplot()
ax.tick_params(grid_color='b', grid_linewidth=5, grid_alpha=0.5,
grid_linestyle='dashdot')
for axis in ax.xaxis, ax.yaxis:
assert axis.majorTicks[0]._grid_color == 'b'
assert axis.majorTicks[0]._grid_linewidth == 5
assert axis.majorTicks[0]._grid_alpha == 0.5
assert axis.majorTicks[0]._grid_linestyle == 'dashdot'
def test_axes_tick_params_ylabelside():
# Tests fix for issue 10267
ax = plt.subplot()
ax.tick_params(labelleft=False, labelright=True,
which='major')
ax.tick_params(labelleft=False, labelright=True,
which='minor')
# expects left false, right true
assert ax.yaxis.majorTicks[0].label1On is False
assert ax.yaxis.majorTicks[0].label2On is True
assert ax.yaxis.minorTicks[0].label1On is False
assert ax.yaxis.minorTicks[0].label2On is True
def test_axes_tick_params_xlabelside():
# Tests fix for issue 10267
ax = plt.subplot()
ax.tick_params(labeltop=True, labelbottom=False,
which='major')
ax.tick_params(labeltop=True, labelbottom=False,
which='minor')
# expects top True, bottom False
# label1On mapped to labelbottom
# label2On mapped to labeltop
assert ax.xaxis.majorTicks[0].label1On is False
assert ax.xaxis.majorTicks[0].label2On is True
assert ax.xaxis.minorTicks[0].label1On is False
assert ax.xaxis.minorTicks[0].label2On is True
def test_none_kwargs():
fig, ax = plt.subplots()
ln, = ax.plot(range(32), linestyle=None)
assert ln.get_linestyle() == '-'
def test_ls_ds_conflict():
with pytest.raises(ValueError):
plt.plot(range(32), linestyle='steps-pre:', drawstyle='steps-post')
def test_bar_uint8():
xs = [0, 1, 2, 3]
b = plt.bar(np.array(xs, dtype=np.uint8), [2, 3, 4, 5])
for (patch, x) in zip(b.patches, xs):
assert patch.xy[0] == x
@image_comparison(baseline_images=['date_timezone_x'], extensions=['png'])
def test_date_timezone_x():
# Tests issue 5575
time_index = [pytz.timezone('Canada/Eastern').localize(datetime.datetime(
year=2016, month=2, day=22, hour=x)) for x in range(3)]
# Same Timezone
fig = plt.figure(figsize=(20, 12))
plt.subplot(2, 1, 1)
plt.plot_date(time_index, [3] * 3, tz='Canada/Eastern')
# Different Timezone
plt.subplot(2, 1, 2)
plt.plot_date(time_index, [3] * 3, tz='UTC')
@image_comparison(baseline_images=['date_timezone_y'],
extensions=['png'])
def test_date_timezone_y():
# Tests issue 5575
time_index = [pytz.timezone('Canada/Eastern').localize(datetime.datetime(
year=2016, month=2, day=22, hour=x)) for x in range(3)]
# Same Timezone
fig = plt.figure(figsize=(20, 12))
plt.subplot(2, 1, 1)
plt.plot_date([3] * 3,
time_index, tz='Canada/Eastern', xdate=False, ydate=True)
# Different Timezone
plt.subplot(2, 1, 2)
plt.plot_date([3] * 3, time_index, tz='UTC', xdate=False, ydate=True)
@image_comparison(baseline_images=['date_timezone_x_and_y'],
extensions=['png'])
def test_date_timezone_x_and_y():
# Tests issue 5575
time_index = [pytz.timezone('UTC').localize(datetime.datetime(
year=2016, month=2, day=22, hour=x)) for x in range(3)]
# Same Timezone
fig = plt.figure(figsize=(20, 12))
plt.subplot(2, 1, 1)
plt.plot_date(time_index, time_index, tz='UTC', ydate=True)
# Different Timezone
plt.subplot(2, 1, 2)
plt.plot_date(time_index, time_index, tz='US/Eastern', ydate=True)
@image_comparison(baseline_images=['axisbelow'],
extensions=['png'], remove_text=True)
def test_axisbelow():
# Test 'line' setting added in 6287.
# Show only grids, not frame or ticks, to make this test
# independent of future change to drawing order of those elements.
fig, axs = plt.subplots(ncols=3, sharex=True, sharey=True)
settings = (False, 'line', True)
for ax, setting in zip(axs, settings):
ax.plot((0, 10), (0, 10), lw=10, color='m')
circ = mpatches.Circle((3, 3), color='r')
ax.add_patch(circ)
ax.grid(color='c', linestyle='-', linewidth=3)
ax.tick_params(top=False, bottom=False,
left=False, right=False)
for spine in ax.spines.values():
spine.set_visible(False)
ax.set_axisbelow(setting)
def test_offset_label_color():
# Tests issue 6440
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot([1.01e9, 1.02e9, 1.03e9])
ax.yaxis.set_tick_params(labelcolor='red')
assert ax.yaxis.get_offset_text().get_color() == 'red'
def test_large_offset():
fig, ax = plt.subplots()
ax.plot((1 + np.array([0, 1.e-12])) * 1.e27)
fig.canvas.draw()
def test_barb_units():
fig, ax = plt.subplots()
dates = [datetime.datetime(2017, 7, 15, 18, i) for i in range(0, 60, 10)]
y = np.linspace(0, 5, len(dates))
u = v = np.linspace(0, 50, len(dates))
ax.barbs(dates, y, u, v)
def test_quiver_units():
fig, ax = plt.subplots()
dates = [datetime.datetime(2017, 7, 15, 18, i) for i in range(0, 60, 10)]
y = np.linspace(0, 5, len(dates))
u = v = np.linspace(0, 50, len(dates))
ax.quiver(dates, y, u, v)
def test_bar_color_cycle():
ccov = mcolors.colorConverter.to_rgb
fig, ax = plt.subplots()
for j in range(5):
ln, = ax.plot(range(3))
brs = ax.bar(range(3), range(3))
for br in brs:
assert ccov(ln.get_color()) == ccov(br.get_facecolor())
def test_tick_param_label_rotation():
fix, (ax, ax2) = plt.subplots(1, 2)
ax.plot([0, 1], [0, 1])
ax2.plot([0, 1], [0, 1])
ax.xaxis.set_tick_params(which='both', rotation=75)
ax.yaxis.set_tick_params(which='both', rotation=90)
for text in ax.get_xticklabels(which='both'):
assert text.get_rotation() == 75
for text in ax.get_yticklabels(which='both'):
assert text.get_rotation() == 90
ax2.tick_params(axis='x', labelrotation=53)
ax2.tick_params(axis='y', rotation=35)
for text in ax2.get_xticklabels(which='major'):
assert text.get_rotation() == 53
for text in ax2.get_yticklabels(which='major'):
assert text.get_rotation() == 35
@pytest.mark.style('default')
def test_fillbetween_cycle():
fig, ax = plt.subplots()
for j in range(3):
cc = ax.fill_between(range(3), range(3))
target = mcolors.to_rgba('C{}'.format(j))
assert tuple(cc.get_facecolors().squeeze()) == tuple(target)
for j in range(3, 6):
cc = ax.fill_betweenx(range(3), range(3))
target = mcolors.to_rgba('C{}'.format(j))
assert tuple(cc.get_facecolors().squeeze()) == tuple(target)
target = mcolors.to_rgba('k')
for al in ['facecolor', 'facecolors', 'color']:
cc = ax.fill_between(range(3), range(3), **{al: 'k'})
assert tuple(cc.get_facecolors().squeeze()) == tuple(target)
edge_target = mcolors.to_rgba('k')
for j, el in enumerate(['edgecolor', 'edgecolors'], start=6):
cc = ax.fill_between(range(3), range(3), **{el: 'k'})
face_target = mcolors.to_rgba('C{}'.format(j))
assert tuple(cc.get_facecolors().squeeze()) == tuple(face_target)
assert tuple(cc.get_edgecolors().squeeze()) == tuple(edge_target)
def test_log_margins():
plt.rcParams['axes.autolimit_mode'] = 'data'
fig, ax = plt.subplots()
margin = 0.05
ax.set_xmargin(margin)
ax.semilogx([10, 100], [10, 100])
xlim0, xlim1 = ax.get_xlim()
transform = ax.xaxis.get_transform()
xlim0t, xlim1t = transform.transform([xlim0, xlim1])
x0t, x1t = transform.transform([10, 100])
delta = (x1t - x0t) * margin
assert_allclose([xlim0t + delta, xlim1t - delta], [x0t, x1t])
def test_color_length_mismatch():
N = 5
x, y = np.arange(N), np.arange(N)
colors = np.arange(N+1)
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.scatter(x, y, c=colors)
c_rgb = (0.5, 0.5, 0.5)
ax.scatter(x, y, c=c_rgb)
ax.scatter(x, y, c=[c_rgb] * N)
def test_scatter_color_masking():
x = np.array([1, 2, 3])
y = np.array([1, np.nan, 3])
colors = np.array(['k', 'w', 'k'])
linewidths = np.array([1, 2, 3])
s = plt.scatter(x, y, color=colors, linewidths=linewidths)
facecolors = s.get_facecolors()
linecolors = s.get_edgecolors()
linewidths = s.get_linewidths()
assert_array_equal(facecolors[1], np.array([0, 0, 0, 1]))
assert_array_equal(linecolors[1], np.array([0, 0, 0, 1]))
assert linewidths[1] == 3
def test_eventplot_legend():
plt.eventplot([1.0], label='Label')
plt.legend()
def test_bar_broadcast_args():
fig, ax = plt.subplots()
# Check that a bar chart with a single height for all bars works.
ax.bar(range(4), 1)
# Check that a horizontal chart with one width works.
ax.bar(0, 1, bottom=range(4), width=1, orientation='horizontal')
# Check that edgecolor gets broadcasted.
rect1, rect2 = ax.bar([0, 1], [0, 1], edgecolor=(.1, .2, .3, .4))
assert rect1.get_edgecolor() == rect2.get_edgecolor() == (.1, .2, .3, .4)
def test_invalid_axis_limits():
plt.plot([0, 1], [0, 1])
with pytest.raises(ValueError):
plt.xlim(np.nan)
with pytest.raises(ValueError):
plt.xlim(np.inf)
with pytest.raises(ValueError):
plt.ylim(np.nan)
with pytest.raises(ValueError):
plt.ylim(np.inf)
# Test all 4 combinations of logs/symlogs for minorticks_on()
@pytest.mark.parametrize('xscale', ['symlog', 'log'])
@pytest.mark.parametrize('yscale', ['symlog', 'log'])
def test_minorticks_on(xscale, yscale):
ax = plt.subplot(111)
ax.plot([1, 2, 3, 4])
ax.set_xscale(xscale)
ax.set_yscale(yscale)
ax.minorticks_on()
def test_twinx_knows_limits():
fig, ax = plt.subplots()
ax.axvspan(1, 2)
xtwin = ax.twinx()
xtwin.plot([0, 0.5], [1, 2])
# control axis
fig2, ax2 = plt.subplots()
ax2.axvspan(1, 2)
ax2.plot([0, 0.5], [1, 2])
assert_array_equal(xtwin.viewLim.intervalx, ax2.viewLim.intervalx)
@pytest.mark.style('mpl20')
@pytest.mark.parametrize('args, kwargs, warning_count',
[((1, 1), {'width': 1, 'bottom': 1}, 0),
((1, ), {'height': 1, 'bottom': 1}, 0),
((), {'x': 1, 'height': 1}, 0),
((), {'left': 1, 'height': 1}, 1)])
def test_bar_signature(args, kwargs, warning_count):
fig, ax = plt.subplots()
with warnings.catch_warnings(record=True) as w:
r, = ax.bar(*args, **kwargs)
assert r.get_width() == kwargs.get('width', 0.8)
assert r.get_y() == kwargs.get('bottom', 0)
assert len(w) == warning_count
@pytest.mark.style('mpl20')
@pytest.mark.parametrize('args, kwargs, warning_count',
[((1, 1), {'height': 1, 'left': 1}, 0),
((1, ), {'width': 1, 'left': 1}, 0),
((), {'y': 1, 'width': 1}, 0),
((), {'bottom': 1, 'width': 1}, 1)])
def test_barh_signature(args, kwargs, warning_count):
fig, ax = plt.subplots()
with warnings.catch_warnings(record=True) as w:
r, = ax.barh(*args, **kwargs)
assert r.get_height() == kwargs.get('height', 0.8)
assert r.get_x() == kwargs.get('left', 0)
assert len(w) == warning_count
def test_zero_linewidth():
# Check that setting a zero linewidth doesn't error
plt.plot([0, 1], [0, 1], ls='--', lw=0)
def test_patch_deprecations():
fig, ax = plt.subplots()
with warnings.catch_warnings(record=True) as w:
assert ax.patch == ax.axesPatch
assert fig.patch == fig.figurePatch
assert len(w) == 2
def test_polar_gridlines():
fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
# make all major grid lines lighter, only x grid lines set in 2.1.0
ax.grid(alpha=0.2)
# hide y tick labels, no effect in 2.1.0
plt.setp(ax.yaxis.get_ticklabels(), visible=False)
fig.canvas.draw()
assert ax.xaxis.majorTicks[0].gridline.get_alpha() == .2
assert ax.yaxis.majorTicks[0].gridline.get_alpha() == .2
def test_empty_errorbar_legend():
fig, ax = plt.subplots()
ax.errorbar([], [], xerr=[], label='empty y')
ax.errorbar([], [], yerr=[], label='empty x')
ax.legend()
def test_plot_columns_cycle_deprecation():
with pytest.warns(MatplotlibDeprecationWarning):
plt.plot(np.zeros((2, 2)), np.zeros((2, 3)))
| 180,002 | 31.068947 | 89 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_scale.py | from __future__ import print_function, unicode_literals
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib.scale import Log10Transform, InvertedLog10Transform
import numpy as np
import io
import pytest
@image_comparison(baseline_images=['log_scales'], remove_text=True)
def test_log_scales():
ax = plt.figure().add_subplot(122, yscale='log', xscale='symlog')
ax.axvline(24.1)
ax.axhline(24.1)
@image_comparison(baseline_images=['logit_scales'], remove_text=True,
extensions=['png'])
def test_logit_scales():
ax = plt.figure().add_subplot(111, xscale='logit')
# Typical extinction curve for logit
x = np.array([0.001, 0.003, 0.01, 0.03, 0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, 0.97, 0.99, 0.997, 0.999])
y = 1.0 / x
ax.plot(x, y)
ax.grid(True)
def test_log_scatter():
"""Issue #1799"""
fig, ax = plt.subplots(1)
x = np.arange(10)
y = np.arange(10) - 1
ax.scatter(x, y)
buf = io.BytesIO()
fig.savefig(buf, format='pdf')
buf = io.BytesIO()
fig.savefig(buf, format='eps')
buf = io.BytesIO()
fig.savefig(buf, format='svg')
def test_logscale_subs():
fig, ax = plt.subplots()
ax.set_yscale('log', subsy=np.array([2, 3, 4]))
# force draw
fig.canvas.draw()
@image_comparison(baseline_images=['logscale_mask'], remove_text=True,
extensions=['png'])
def test_logscale_mask():
# Check that zero values are masked correctly on log scales.
# See github issue 8045
xs = np.linspace(0, 50, 1001)
fig, ax = plt.subplots()
ax.plot(np.exp(-xs**2))
fig.canvas.draw()
ax.set(yscale="log")
def test_extra_kwargs_raise():
fig, ax = plt.subplots()
with pytest.raises(ValueError):
ax.set_yscale('log', nonpos='mask')
def test_logscale_invert_transform():
fig, ax = plt.subplots()
ax.set_yscale('log')
# get transformation from data to axes
tform = (ax.transAxes + ax.transData.inverted()).inverted()
# direct test of log transform inversion
assert isinstance(Log10Transform().inverted(), InvertedLog10Transform)
def test_logscale_transform_repr():
# check that repr of log transform succeeds
fig, ax = plt.subplots()
ax.set_yscale('log')
s = repr(ax.transData)
# check that repr of log transform returns correct string
s = repr(Log10Transform(nonpos='clip'))
assert s == "Log10Transform({!r})".format('clip')
@image_comparison(baseline_images=['logscale_nonpos_values'], remove_text=True,
extensions=['png'], style='mpl20')
def test_logscale_nonpos_values():
np.random.seed(19680801)
xs = np.random.normal(size=int(1e3))
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
ax1.hist(xs, range=(-5, 5), bins=10)
ax1.set_yscale('log')
ax2.hist(xs, range=(-5, 5), bins=10)
ax2.set_yscale('log', nonposy='mask')
xdata = np.arange(0, 10, 0.01)
ydata = np.exp(-xdata)
edata = 0.2*(10-xdata)*np.cos(5*xdata)*np.exp(-xdata)
ax3.fill_between(xdata, ydata - edata, ydata + edata)
ax3.set_yscale('log')
x = np.logspace(-1, 1)
y = x ** 3
yerr = x**2
ax4.errorbar(x, y, yerr=yerr)
ax4.set_yscale('log')
ax4.set_xscale('log')
| 3,316 | 25.75 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_dviread.py | from __future__ import absolute_import, division, print_function
import six
from matplotlib.testing.decorators import skip_if_command_unavailable
import matplotlib.dviread as dr
import os.path
import json
import pytest
def test_PsfontsMap(monkeypatch):
monkeypatch.setattr(dr, 'find_tex_file', lambda x: x)
filename = os.path.join(
os.path.dirname(__file__),
'baseline_images', 'dviread', 'test.map')
fontmap = dr.PsfontsMap(filename)
# Check all properties of a few fonts
for n in [1, 2, 3, 4, 5]:
key = ('TeXfont%d' % n).encode('ascii')
entry = fontmap[key]
assert entry.texname == key
assert entry.psname == ('PSfont%d' % n).encode('ascii')
if n not in [3, 5]:
assert entry.encoding == ('font%d.enc' % n).encode('ascii')
elif n == 3:
assert entry.encoding == b'enc3.foo'
# We don't care about the encoding of TeXfont5, which specifies
# multiple encodings.
if n not in [1, 5]:
assert entry.filename == ('font%d.pfa' % n).encode('ascii')
else:
assert entry.filename == ('font%d.pfb' % n).encode('ascii')
if n == 4:
assert entry.effects == {'slant': -0.1, 'extend': 2.2}
else:
assert entry.effects == {}
# Some special cases
entry = fontmap[b'TeXfont6']
assert entry.filename is None
assert entry.encoding is None
entry = fontmap[b'TeXfont7']
assert entry.filename is None
assert entry.encoding == b'font7.enc'
entry = fontmap[b'TeXfont8']
assert entry.filename == b'font8.pfb'
assert entry.encoding is None
entry = fontmap[b'TeXfont9']
assert entry.filename == b'/absolute/font9.pfb'
# Missing font
with pytest.raises(KeyError) as exc:
fontmap[b'no-such-font']
assert 'no-such-font' in str(exc.value)
@skip_if_command_unavailable(["kpsewhich", "-version"])
def test_dviread():
dir = os.path.join(os.path.dirname(__file__), 'baseline_images', 'dviread')
with open(os.path.join(dir, 'test.json')) as f:
correct = json.load(f)
for entry in correct:
entry['text'] = [[a, b, c, d.encode('ascii'), e]
for [a, b, c, d, e] in entry['text']]
with dr.Dvi(os.path.join(dir, 'test.dvi'), None) as dvi:
data = [{'text': [[t.x, t.y,
six.unichr(t.glyph),
t.font.texname,
round(t.font.size, 2)]
for t in page.text],
'boxes': [[b.x, b.y, b.height, b.width] for b in page.boxes]}
for page in dvi]
assert data == correct
| 2,704 | 35.554054 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_table.py | from __future__ import absolute_import, division, print_function
import six
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.testing.decorators import image_comparison
from matplotlib.table import CustomCell, Table
from matplotlib.path import Path
def test_non_square():
# Check that creating a non-square table works
cellcolors = ['b', 'r']
plt.table(cellColours=cellcolors)
@image_comparison(baseline_images=['table_zorder'],
extensions=['png'],
remove_text=True)
def test_zorder():
data = [[66386, 174296],
[58230, 381139]]
colLabels = ('Freeze', 'Wind')
rowLabels = ['%d year' % x for x in (100, 50)]
cellText = []
yoff = np.zeros(len(colLabels))
for row in reversed(data):
yoff += row
cellText.append(['%1.1f' % (x/1000.0) for x in yoff])
t = np.linspace(0, 2*np.pi, 100)
plt.plot(t, np.cos(t), lw=4, zorder=2)
plt.table(cellText=cellText,
rowLabels=rowLabels,
colLabels=colLabels,
loc='center',
zorder=-2,
)
plt.table(cellText=cellText,
rowLabels=rowLabels,
colLabels=colLabels,
loc='upper center',
zorder=4,
)
plt.yticks([])
@image_comparison(baseline_images=['table_labels'],
extensions=['png'])
def test_label_colours():
dim = 3
c = np.linspace(0, 1, dim)
colours = plt.cm.RdYlGn(c)
cellText = [['1'] * dim] * dim
fig = plt.figure()
ax1 = fig.add_subplot(4, 1, 1)
ax1.axis('off')
ax1.table(cellText=cellText,
rowColours=colours,
loc='best')
ax2 = fig.add_subplot(4, 1, 2)
ax2.axis('off')
ax2.table(cellText=cellText,
rowColours=colours,
rowLabels=['Header'] * dim,
loc='best')
ax3 = fig.add_subplot(4, 1, 3)
ax3.axis('off')
ax3.table(cellText=cellText,
colColours=colours,
loc='best')
ax4 = fig.add_subplot(4, 1, 4)
ax4.axis('off')
ax4.table(cellText=cellText,
colColours=colours,
colLabels=['Header'] * dim,
loc='best')
@image_comparison(baseline_images=['table_cell_manipulation'],
extensions=['png'], remove_text=True)
def test_diff_cell_table():
cells = ('horizontal', 'vertical', 'open', 'closed', 'T', 'R', 'B', 'L')
cellText = [['1'] * len(cells)] * 2
colWidths = [0.1] * len(cells)
_, axes = plt.subplots(nrows=len(cells), figsize=(4, len(cells)+1))
for ax, cell in zip(axes, cells):
ax.table(
colWidths=colWidths,
cellText=cellText,
loc='center',
edges=cell,
)
ax.axis('off')
plt.tight_layout()
def test_customcell():
types = ('horizontal', 'vertical', 'open', 'closed', 'T', 'R', 'B', 'L')
codes = (
(Path.MOVETO, Path.LINETO, Path.MOVETO, Path.LINETO, Path.MOVETO),
(Path.MOVETO, Path.MOVETO, Path.LINETO, Path.MOVETO, Path.LINETO),
(Path.MOVETO, Path.MOVETO, Path.MOVETO, Path.MOVETO, Path.MOVETO),
(Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY),
(Path.MOVETO, Path.MOVETO, Path.MOVETO, Path.LINETO, Path.MOVETO),
(Path.MOVETO, Path.MOVETO, Path.LINETO, Path.MOVETO, Path.MOVETO),
(Path.MOVETO, Path.LINETO, Path.MOVETO, Path.MOVETO, Path.MOVETO),
(Path.MOVETO, Path.MOVETO, Path.MOVETO, Path.MOVETO, Path.LINETO),
)
for t, c in zip(types, codes):
cell = CustomCell((0, 0), visible_edges=t, width=1, height=1)
code = tuple(s for _, s in cell.get_path().iter_segments())
assert c == code
@image_comparison(baseline_images=['table_auto_column'],
extensions=['png'])
def test_auto_column():
fig = plt.figure()
# iterable list input
ax1 = fig.add_subplot(4, 1, 1)
ax1.axis('off')
tb1 = ax1.table(cellText=[['Fit Text', 2],
['very long long text, Longer text than default', 1]],
rowLabels=["A", "B"],
colLabels=["Col1", "Col2"],
loc="center")
tb1.auto_set_font_size(False)
tb1.set_fontsize(12)
tb1.auto_set_column_width([-1, 0, 1])
# iterable tuple input
ax2 = fig.add_subplot(4, 1, 2)
ax2.axis('off')
tb2 = ax2.table(cellText=[['Fit Text', 2],
['very long long text, Longer text than default', 1]],
rowLabels=["A", "B"],
colLabels=["Col1", "Col2"],
loc="center")
tb2.auto_set_font_size(False)
tb2.set_fontsize(12)
tb2.auto_set_column_width((-1, 0, 1))
#3 single inputs
ax3 = fig.add_subplot(4, 1, 3)
ax3.axis('off')
tb3 = ax3.table(cellText=[['Fit Text', 2],
['very long long text, Longer text than default', 1]],
rowLabels=["A", "B"],
colLabels=["Col1", "Col2"],
loc="center")
tb3.auto_set_font_size(False)
tb3.set_fontsize(12)
tb3.auto_set_column_width(-1)
tb3.auto_set_column_width(0)
tb3.auto_set_column_width(1)
#4 non integer interable input
ax4 = fig.add_subplot(4, 1, 4)
ax4.axis('off')
tb4 = ax4.table(cellText=[['Fit Text', 2],
['very long long text, Longer text than default', 1]],
rowLabels=["A", "B"],
colLabels=["Col1", "Col2"],
loc="center")
tb4.auto_set_font_size(False)
tb4.set_fontsize(12)
tb4.auto_set_column_width("-101")
def test_table_cells():
fig, ax = plt.subplots()
table = Table(ax)
cell = table.add_cell(1, 2, 1, 1)
assert isinstance(cell, CustomCell)
assert cell is table[1, 2]
cell2 = CustomCell((0, 0), 1, 2, visible_edges=None)
table[2, 1] = cell2
assert table[2, 1] is cell2
# make sure gettitem support has not broken
# properties and setp
table.properties()
plt.setp(table)
| 5,984 | 28.628713 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_compare_images.py | from __future__ import absolute_import, division, print_function
import six
import io
import os
import shutil
import warnings
from numpy.testing import assert_almost_equal
import pytest
from pytest import approx
from matplotlib.testing.compare import compare_images
from matplotlib.testing.decorators import _image_directories, image_comparison
from matplotlib.testing.exceptions import ImageComparisonFailure
baseline_dir, result_dir = _image_directories(lambda: 'dummy func')
# Tests of the image comparison algorithm.
@pytest.mark.parametrize(
'im1, im2, tol, expect_rms',
[
# Comparison of an image and the same image with minor differences.
# This expects the images to compare equal under normal tolerance, and
# have a small RMS.
('basn3p02.png', 'basn3p02-minorchange.png', 10, None),
# Now test with no tolerance.
('basn3p02.png', 'basn3p02-minorchange.png', 0, 6.50646),
# Comparison with an image that is shifted by 1px in the X axis.
('basn3p02.png', 'basn3p02-1px-offset.png', 0, 90.15611),
# Comparison with an image with half the pixels shifted by 1px in the X
# axis.
('basn3p02.png', 'basn3p02-half-1px-offset.png', 0, 63.75),
# Comparison of an image and the same image scrambled.
# This expects the images to compare completely different, with a very
# large RMS.
# Note: The image has been scrambled in a specific way, by having
# each color component of each pixel randomly placed somewhere in the
# image. It contains exactly the same number of pixels of each color
# value of R, G and B, but in a totally different position.
# Test with no tolerance to make sure that we pick up even a very small
# RMS error.
('basn3p02.png', 'basn3p02-scrambled.png', 0, 172.63582),
# Comparison of an image and a slightly brighter image.
# The two images are solid color, with the second image being exactly 1
# color value brighter.
# This expects the images to compare equal under normal tolerance, and
# have an RMS of exactly 1.
('all127.png', 'all128.png', 0, 1),
# Now test the reverse comparison.
('all128.png', 'all127.png', 0, 1),
])
def test_image_comparison_expect_rms(im1, im2, tol, expect_rms):
"""Compare two images, expecting a particular RMS error.
im1 and im2 are filenames relative to the baseline_dir directory.
tol is the tolerance to pass to compare_images.
expect_rms is the expected RMS value, or None. If None, the test will
succeed if compare_images succeeds. Otherwise, the test will succeed if
compare_images fails and returns an RMS error almost equal to this value.
"""
im1 = os.path.join(baseline_dir, im1)
im2_src = os.path.join(baseline_dir, im2)
im2 = os.path.join(result_dir, im2)
# Move im2 from baseline_dir to result_dir. This will ensure that
# compare_images writes the diff file to result_dir, instead of trying to
# write to the (possibly read-only) baseline_dir.
shutil.copyfile(im2_src, im2)
results = compare_images(im1, im2, tol=tol, in_decorator=True)
if expect_rms is None:
assert results is None
else:
assert results is not None
assert results['rms'] == approx(expect_rms, abs=1e-4)
# The following tests are used by test_nose_image_comparison to ensure that the
# image_comparison decorator continues to work with nose. They should not be
# prefixed by test_ so they don't run with pytest.
def nosetest_empty():
pass
def nosetest_simple_figure():
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(6.4, 4), dpi=100)
ax.plot([1, 2, 3], [3, 4, 5])
return fig
def nosetest_manual_text_removal():
from matplotlib.testing.decorators import ImageComparisonTest
fig = nosetest_simple_figure()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
# Make sure this removes text like it should.
ImageComparisonTest.remove_text(fig)
assert len(w) == 1
assert 'remove_text function was deprecated in version 2.1.' in str(w[0])
@pytest.mark.parametrize(
'func, kwargs, errors, failures, dots',
[
(nosetest_empty, {'baseline_images': []}, [], [], ''),
(nosetest_empty, {'baseline_images': ['foo']},
[(AssertionError,
'Test generated 0 images but there are 1 baseline images')],
[],
'E'),
(nosetest_simple_figure,
{'baseline_images': ['basn3p02'], 'extensions': ['png'],
'remove_text': True},
[],
[(ImageComparisonFailure, 'Image sizes do not match expected size:')],
'F'),
(nosetest_simple_figure,
{'baseline_images': ['simple']},
[],
[(ImageComparisonFailure, 'images not close')] * 3,
'FFF'),
(nosetest_simple_figure,
{'baseline_images': ['simple'], 'remove_text': True},
[],
[],
'...'),
(nosetest_manual_text_removal,
{'baseline_images': ['simple']},
[],
[],
'...'),
],
ids=[
'empty',
'extra baselines',
'incorrect shape',
'failing figure',
'passing figure',
'manual text removal',
])
def test_nose_image_comparison(func, kwargs, errors, failures, dots,
monkeypatch):
nose = pytest.importorskip('nose')
monkeypatch.setattr('matplotlib._called_from_pytest', False)
class TestResultVerifier(nose.result.TextTestResult):
def __init__(self, *args, **kwargs):
super(TestResultVerifier, self).__init__(*args, **kwargs)
self.error_count = 0
self.failure_count = 0
def addError(self, test, err):
super(TestResultVerifier, self).addError(test, err)
if self.error_count < len(errors):
assert err[0] is errors[self.error_count][0]
assert errors[self.error_count][1] in str(err[1])
else:
raise err[1]
self.error_count += 1
def addFailure(self, test, err):
super(TestResultVerifier, self).addFailure(test, err)
assert self.failure_count < len(failures), err[1]
assert err[0] is failures[self.failure_count][0]
assert failures[self.failure_count][1] in str(err[1])
self.failure_count += 1
# Make sure that multiple extensions work, but don't require LaTeX or
# Inkscape to do so.
kwargs.setdefault('extensions', ['png', 'png', 'png'])
func = image_comparison(**kwargs)(func)
loader = nose.loader.TestLoader()
suite = loader.loadTestsFromGenerator(
func,
'matplotlib.tests.test_compare_images')
if six.PY2:
output = io.BytesIO()
else:
output = io.StringIO()
result = TestResultVerifier(stream=output, descriptions=True, verbosity=1)
with warnings.catch_warnings():
# Nose uses deprecated stuff; we don't care about it.
warnings.simplefilter('ignore', DeprecationWarning)
suite.run(result=result)
assert output.getvalue() == dots
assert result.error_count == len(errors)
assert result.failure_count == len(failures)
| 7,394 | 35.608911 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_simplification.py | from __future__ import absolute_import, division, print_function
import io
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
import pytest
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib import patches, transforms
from matplotlib.path import Path
# NOTE: All of these tests assume that path.simplify is set to True
# (the default)
@image_comparison(baseline_images=['clipping'], remove_text=True)
def test_clipping():
t = np.arange(0.0, 2.0, 0.01)
s = np.sin(2*np.pi*t)
fig, ax = plt.subplots()
ax.plot(t, s, linewidth=1.0)
ax.set_ylim((-0.20, -0.28))
@image_comparison(baseline_images=['overflow'], remove_text=True)
def test_overflow():
x = np.array([1.0, 2.0, 3.0, 2.0e5])
y = np.arange(len(x))
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(xmin=2, xmax=6)
@image_comparison(baseline_images=['clipping_diamond'], remove_text=True)
def test_diamond():
x = np.array([0.0, 1.0, 0.0, -1.0, 0.0])
y = np.array([1.0, 0.0, -1.0, 0.0, 1.0])
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(xmin=-0.6, xmax=0.6)
ax.set_ylim(ymin=-0.6, ymax=0.6)
def test_noise():
np.random.seed(0)
x = np.random.uniform(size=(50000,)) * 50
fig, ax = plt.subplots()
p1 = ax.plot(x, solid_joinstyle='round', linewidth=2.0)
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 25512
def test_antiparallel_simplification():
def _get_simplified(x, y):
fig, ax = plt.subplots()
p1 = ax.plot(x, y)
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
simplified = transform.inverted().transform_path(simplified)
return simplified
# test ending on a maximum
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, 2, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., -1.],
[0., 2.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test ending on a minimum
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, -2, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 1.],
[0., -2.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test ending in between
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, 0, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 1.],
[0., -1.],
[0., 0.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test no anti-parallel ending at max
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, 2, 1, 3, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 3.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test no anti-parallel ending in middle
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, 2, 1, 1, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 2.],
[0., 1.],
[1., 0.5]],
simplified.vertices[:-2, :])
# Only consider angles in 0 <= angle <= pi/2, otherwise
# using min/max will get the expected results out of order:
# min/max for simplification code depends on original vector,
# and if angle is outside above range then simplification
# min/max will be opposite from actual min/max.
@pytest.mark.parametrize('angle', [0, np.pi/4, np.pi/3, np.pi/2])
@pytest.mark.parametrize('offset', [0, .5])
def test_angled_antiparallel(angle, offset):
scale = 5
np.random.seed(19680801)
# get 15 random offsets
# TODO: guarantee offset > 0 results in some offsets < 0
vert_offsets = (np.random.rand(15) - offset) * scale
# always start at 0 so rotation makes sense
vert_offsets[0] = 0
# always take the first step the same direction
vert_offsets[1] = 1
# compute points along a diagonal line
x = np.sin(angle) * vert_offsets
y = np.cos(angle) * vert_offsets
# will check these later
x_max = x[1:].max()
x_min = x[1:].min()
y_max = y[1:].max()
y_min = y[1:].min()
if offset > 0:
p_expected = Path([[0, 0],
[x_max, y_max],
[x_min, y_min],
[x[-1], y[-1]],
[0, 0]],
codes=[1, 2, 2, 2, 0])
else:
p_expected = Path([[0, 0],
[x_max, y_max],
[x[-1], y[-1]],
[0, 0]],
codes=[1, 2, 2, 0])
p = Path(np.vstack([x, y]).T)
p2 = p.cleaned(simplify=True)
assert_array_almost_equal(p_expected.vertices,
p2.vertices)
assert_array_equal(p_expected.codes, p2.codes)
def test_sine_plus_noise():
np.random.seed(0)
x = (np.sin(np.linspace(0, np.pi * 2.0, 50000)) +
np.random.uniform(size=(50000,)) * 0.01)
fig, ax = plt.subplots()
p1 = ax.plot(x, solid_joinstyle='round', linewidth=2.0)
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 25240
@image_comparison(baseline_images=['simplify_curve'], remove_text=True)
def test_simplify_curve():
pp1 = patches.PathPatch(
Path([(0, 0), (1, 0), (1, 1), (np.nan, 1), (0, 0), (2, 0), (2, 2),
(0, 0)],
[Path.MOVETO, Path.CURVE3, Path.CURVE3, Path.CURVE3, Path.CURVE3,
Path.CURVE3, Path.CURVE3, Path.CLOSEPOLY]),
fc="none")
fig, ax = plt.subplots()
ax.add_patch(pp1)
ax.set_xlim((0, 2))
ax.set_ylim((0, 2))
@image_comparison(baseline_images=['hatch_simplify'], remove_text=True)
def test_hatch():
fig, ax = plt.subplots()
ax.add_patch(plt.Rectangle((0, 0), 1, 1, fill=False, hatch="/"))
ax.set_xlim((0.45, 0.55))
ax.set_ylim((0.45, 0.55))
@image_comparison(baseline_images=['fft_peaks'], remove_text=True)
def test_fft_peaks():
fig, ax = plt.subplots()
t = np.arange(65536)
p1 = ax.plot(abs(np.fft.fft(np.sin(2*np.pi*.01*t)*np.blackman(len(t)))))
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 36
def test_start_with_moveto():
# Should be entirely clipped away to a single MOVETO
data = b"""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"""
import base64
if hasattr(base64, 'encodebytes'):
# Python 3 case
decodebytes = base64.decodebytes
else:
# Python 2 case
decodebytes = base64.decodestring
verts = np.fromstring(decodebytes(data), dtype='<i4')
verts = verts.reshape((len(verts) // 2, 2))
path = Path(verts)
segs = path.iter_segments(transforms.IdentityTransform(),
clip=(0.0, 0.0, 100.0, 100.0))
segs = list(segs)
assert len(segs) == 1
assert segs[0][1] == Path.MOVETO
def test_throw_rendering_complexity_exceeded():
plt.rcParams['path.simplify'] = False
xx = np.arange(200000)
yy = np.random.rand(200000)
yy[1000] = np.nan
fig, ax = plt.subplots()
ax.plot(xx, yy)
with pytest.raises(OverflowError):
fig.savefig(io.BytesIO())
@image_comparison(baseline_images=['clipper_edge'], remove_text=True)
def test_clipper():
dat = (0, 1, 0, 2, 0, 3, 0, 4, 0, 5)
fig = plt.figure(figsize=(2, 1))
fig.subplots_adjust(left=0, bottom=0, wspace=0, hspace=0)
ax = fig.add_axes((0, 0, 1.0, 1.0), ylim=(0, 5), autoscale_on=False)
ax.plot(dat)
ax.xaxis.set_major_locator(plt.MultipleLocator(1))
ax.yaxis.set_major_locator(plt.MultipleLocator(1))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_xlim(5, 9)
@image_comparison(baseline_images=['para_equal_perp'], remove_text=True)
def test_para_equal_perp():
x = np.array([0, 1, 2, 1, 0, -1, 0, 1] + [1] * 128)
y = np.array([1, 1, 2, 1, 0, -1, 0, 0] + [0] * 128)
fig, ax = plt.subplots()
ax.plot(x + 1, y + 1)
ax.plot(x + 1, y + 1, 'ro')
@image_comparison(baseline_images=['clipping_with_nans'])
def test_clipping_with_nans():
x = np.linspace(0, 3.14 * 2, 3000)
y = np.sin(x)
x[::100] = np.nan
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_ylim(-0.25, 0.25)
def test_clipping_full():
p = Path([[1e30, 1e30]] * 5)
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert simplified == []
p = Path([[50, 40], [75, 65]], [1, 2])
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert ([(list(x), y) for x, y in simplified] ==
[([50, 40], 1), ([75, 65], 2)])
p = Path([[50, 40]], [1])
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert ([(list(x), y) for x, y in simplified] ==
[([50, 40], 1)])
| 11,169 | 31.005731 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backends_interactive.py | import importlib
import os
import sys
from matplotlib.compat.subprocess import Popen
import pytest
# Minimal smoke-testing of the backends for which the dependencies are
# PyPI-installable on Travis. They are not available for all tested Python
# versions so we don't fail on missing backends.
#
# We also don't test on Py2 because its subprocess module doesn't support
# timeouts, and it would require a separate code path to check for module
# existence without actually trying to import the module (which may install
# an undesirable input hook).
def _get_testable_interactive_backends():
backends = []
for deps, backend in [(["cairocffi", "pgi"], "gtk3agg"),
(["cairocffi", "pgi"], "gtk3cairo"),
(["PyQt5"], "qt5agg"),
(["cairocffi", "PyQt5"], "qt5cairo"),
(["tkinter"], "tkagg"),
(["wx"], "wxagg")]:
reason = None
if sys.version_info < (3,):
reason = "Py3-only test"
elif not os.environ.get("DISPLAY"):
reason = "No $DISPLAY"
elif any(importlib.util.find_spec(dep) is None for dep in deps):
reason = "Missing dependency"
backends.append(pytest.mark.skip(reason=reason)(backend) if reason
else backend)
return backends
_test_script = """\
import sys
from matplotlib import pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1,2,3], [1,3,1])
fig.canvas.mpl_connect("draw_event", lambda event: sys.exit())
plt.show()
"""
@pytest.mark.parametrize("backend", _get_testable_interactive_backends())
@pytest.mark.flaky(reruns=3)
def test_backend(backend):
environ = os.environ.copy()
environ["MPLBACKEND"] = backend
proc = Popen([sys.executable, "-c", _test_script], env=environ)
# Empirically, 1s is not enough on Travis.
assert proc.wait(timeout=10) == 0
| 1,944 | 31.966102 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_contour.py | from __future__ import absolute_import, division, print_function
import datetime
import numpy as np
from matplotlib.testing.decorators import image_comparison
from matplotlib import pyplot as plt
from numpy.testing import assert_array_almost_equal
import pytest
import warnings
def test_contour_shape_1d_valid():
x = np.arange(10)
y = np.arange(9)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contour(x, y, z)
def test_contour_shape_2d_valid():
x = np.arange(10)
y = np.arange(9)
xg, yg = np.meshgrid(x, y)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contour(xg, yg, z)
def test_contour_shape_mismatch_1():
x = np.arange(9)
y = np.arange(9)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Length of x must be number of columns in z.')
def test_contour_shape_mismatch_2():
x = np.arange(10)
y = np.arange(10)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Length of y must be number of rows in z.')
def test_contour_shape_mismatch_3():
x = np.arange(10)
y = np.arange(10)
xg, yg = np.meshgrid(x, y)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(xg, y, z)
excinfo.match(r'Number of dimensions of x and y should match.')
with pytest.raises(TypeError) as excinfo:
ax.contour(x, yg, z)
excinfo.match(r'Number of dimensions of x and y should match.')
def test_contour_shape_mismatch_4():
g = np.random.random((9, 10))
b = np.random.random((9, 9))
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(b, g, z)
excinfo.match(r'Shape of x does not match that of z: found \(9L?, 9L?\) ' +
r'instead of \(9L?, 10L?\)')
with pytest.raises(TypeError) as excinfo:
ax.contour(g, b, z)
excinfo.match(r'Shape of y does not match that of z: found \(9L?, 9L?\) ' +
r'instead of \(9L?, 10L?\)')
def test_contour_shape_invalid_1():
x = np.random.random((3, 3, 3))
y = np.random.random((3, 3, 3))
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Inputs x and y must be 1D or 2D.')
def test_contour_shape_invalid_2():
x = np.random.random((3, 3, 3))
y = np.random.random((3, 3, 3))
z = np.random.random((3, 3, 3))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Input z must be a 2D array.')
def test_contour_empty_levels():
x = np.arange(9)
z = np.random.random((9, 9))
fig, ax = plt.subplots()
with pytest.warns(UserWarning) as record:
ax.contour(x, x, z, levels=[])
assert len(record) == 1
def test_contour_badlevel_fmt():
# test funny edge case from
# https://github.com/matplotlib/matplotlib/issues/9742
# User supplied fmt for each level as a dictionary, but
# MPL changed the level to the minimum data value because
# no contours possible.
# This would error out pre
# https://github.com/matplotlib/matplotlib/pull/9743
x = np.arange(9)
z = np.zeros((9, 9))
fig, ax = plt.subplots()
fmt = {1.: '%1.2f'}
with pytest.warns(UserWarning) as record:
cs = ax.contour(x, x, z, levels=[1.])
ax.clabel(cs, fmt=fmt)
assert len(record) == 1
def test_contour_uniform_z():
x = np.arange(9)
z = np.ones((9, 9))
fig, ax = plt.subplots()
with pytest.warns(UserWarning) as record:
ax.contour(x, x, z)
assert len(record) == 1
@image_comparison(baseline_images=['contour_manual_labels'],
savefig_kwarg={'dpi': 200}, remove_text=True, style='mpl20')
def test_contour_manual_labels():
x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))
z = np.max(np.dstack([abs(x), abs(y)]), 2)
plt.figure(figsize=(6, 2), dpi=200)
cs = plt.contour(x, y, z)
pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])
plt.clabel(cs, manual=pts)
@image_comparison(baseline_images=['contour_labels_size_color'],
extensions=['png'], remove_text=True, style='mpl20')
def test_contour_labels_size_color():
x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))
z = np.max(np.dstack([abs(x), abs(y)]), 2)
plt.figure(figsize=(6, 2))
cs = plt.contour(x, y, z)
pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])
plt.clabel(cs, manual=pts, fontsize='small', colors=('r', 'g'))
@image_comparison(baseline_images=['contour_manual_colors_and_levels'],
extensions=['png'], remove_text=True)
def test_given_colors_levels_and_extends():
_, axes = plt.subplots(2, 4)
data = np.arange(12).reshape(3, 4)
colors = ['red', 'yellow', 'pink', 'blue', 'black']
levels = [2, 4, 8, 10]
for i, ax in enumerate(axes.flatten()):
filled = i % 2 == 0.
extend = ['neither', 'min', 'max', 'both'][i // 2]
if filled:
# If filled, we have 3 colors with no extension,
# 4 colors with one extension, and 5 colors with both extensions
first_color = 1 if extend in ['max', 'neither'] else None
last_color = -1 if extend in ['min', 'neither'] else None
c = ax.contourf(data, colors=colors[first_color:last_color],
levels=levels, extend=extend)
else:
# If not filled, we have 4 levels and 4 colors
c = ax.contour(data, colors=colors[:-1],
levels=levels, extend=extend)
plt.colorbar(c, ax=ax)
@image_comparison(baseline_images=['contour_datetime_axis'],
extensions=['png'], remove_text=False)
def test_contour_datetime_axis():
fig = plt.figure()
fig.subplots_adjust(hspace=0.4, top=0.98, bottom=.15)
base = datetime.datetime(2013, 1, 1)
x = np.array([base + datetime.timedelta(days=d) for d in range(20)])
y = np.arange(20)
z1, z2 = np.meshgrid(np.arange(20), np.arange(20))
z = z1 * z2
plt.subplot(221)
plt.contour(x, y, z)
plt.subplot(222)
plt.contourf(x, y, z)
x = np.repeat(x[np.newaxis], 20, axis=0)
y = np.repeat(y[:, np.newaxis], 20, axis=1)
plt.subplot(223)
plt.contour(x, y, z)
plt.subplot(224)
plt.contourf(x, y, z)
for ax in fig.get_axes():
for label in ax.get_xticklabels():
label.set_ha('right')
label.set_rotation(30)
@image_comparison(baseline_images=['contour_test_label_transforms'],
extensions=['png'], remove_text=True)
def test_labels():
# Adapted from pylab_examples example code: contour_demo.py
# see issues #2475, #2843, and #2818 for explanation
delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-(X**2 + Y**2) / 2) / (2 * np.pi)
Z2 = (np.exp(-(((X - 1) / 1.5)**2 + ((Y - 1) / 0.5)**2) / 2) /
(2 * np.pi * 0.5 * 1.5))
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)
fig, ax = plt.subplots(1, 1)
CS = ax.contour(X, Y, Z)
disp_units = [(216, 177), (359, 290), (521, 406)]
data_units = [(-2, .5), (0, -1.5), (2.8, 1)]
CS.clabel()
for x, y in data_units:
CS.add_label_near(x, y, inline=True, transform=None)
for x, y in disp_units:
CS.add_label_near(x, y, inline=True, transform=False)
@image_comparison(baseline_images=['contour_corner_mask_False',
'contour_corner_mask_True'],
extensions=['png'], remove_text=True)
def test_corner_mask():
n = 60
mask_level = 0.95
noise_amp = 1.0
np.random.seed([1])
x, y = np.meshgrid(np.linspace(0, 2.0, n), np.linspace(0, 2.0, n))
z = np.cos(7*x)*np.sin(8*y) + noise_amp*np.random.rand(n, n)
mask = np.where(np.random.rand(n, n) >= mask_level, True, False)
z = np.ma.array(z, mask=mask)
for corner_mask in [False, True]:
fig = plt.figure()
plt.contourf(z, corner_mask=corner_mask)
def test_contourf_decreasing_levels():
# github issue 5477.
z = [[0.1, 0.3], [0.5, 0.7]]
plt.figure()
with pytest.raises(ValueError):
plt.contourf(z, [1.0, 0.0])
def test_contourf_symmetric_locator():
# github issue 7271
z = np.arange(12).reshape((3, 4))
locator = plt.MaxNLocator(nbins=4, symmetric=True)
cs = plt.contourf(z, locator=locator)
assert_array_almost_equal(cs.levels, np.linspace(-12, 12, 5))
def test_contour_1x1_array():
# github issue 8197
with pytest.raises(TypeError) as excinfo:
plt.contour([[0]])
excinfo.match(r'Input z must be at least a 2x2 array.')
with pytest.raises(TypeError) as excinfo:
plt.contour([0], [0], [[0]])
excinfo.match(r'Input z must be at least a 2x2 array.')
def test_internal_cpp_api():
# Following github issue 8197.
import matplotlib._contour as _contour
with pytest.raises(TypeError) as excinfo:
qcg = _contour.QuadContourGenerator()
excinfo.match(r'function takes exactly 6 arguments \(0 given\)')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator(1, 2, 3, 4, 5, 6)
excinfo.match(r'Expected 2-dimensional array, got 0')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator([[0]], [[0]], [[]], None, True, 0)
excinfo.match(r'x, y and z must all be 2D arrays with the same dimensions')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator([[0]], [[0]], [[0]], None, True, 0)
excinfo.match(r'x, y and z must all be at least 2x2 arrays')
arr = [[0, 1], [2, 3]]
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator(arr, arr, arr, [[0]], True, 0)
excinfo.match(r'If mask is set it must be a 2D array with the same ' +
r'dimensions as x.')
qcg = _contour.QuadContourGenerator(arr, arr, arr, None, True, 0)
with pytest.raises(ValueError) as excinfo:
qcg.create_filled_contour(1, 0)
excinfo.match(r'filled contour levels must be increasing')
def test_circular_contour_warning():
# Check that almost circular contours don't throw a warning
with pytest.warns(None) as record:
x, y = np.meshgrid(np.linspace(-2, 2, 4), np.linspace(-2, 2, 4))
r = np.sqrt(x ** 2 + y ** 2)
plt.figure()
cs = plt.contour(x, y, r)
plt.clabel(cs)
assert len(record) == 0
| 11,061 | 28.897297 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_bbox_tight.py | from __future__ import absolute_import, division, print_function
import numpy as np
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import matplotlib.patches as mpatches
from matplotlib.ticker import FuncFormatter
@image_comparison(baseline_images=['bbox_inches_tight'], remove_text=True,
savefig_kwarg=dict(bbox_inches='tight'))
def test_bbox_inches_tight():
#: Test that a figure saved using bbox_inches='tight' is clipped correctly
data = [[66386, 174296, 75131, 577908, 32015],
[58230, 381139, 78045, 99308, 160454],
[89135, 80552, 152558, 497981, 603535],
[78415, 81858, 150656, 193263, 69638],
[139361, 331509, 343164, 781380, 52269]]
colLabels = rowLabels = [''] * 5
rows = len(data)
ind = np.arange(len(colLabels)) + 0.3 # the x locations for the groups
cellText = []
width = 0.4 # the width of the bars
yoff = np.zeros(len(colLabels))
# the bottom values for stacked bar chart
fig, ax = plt.subplots(1, 1)
for row in range(rows):
ax.bar(ind, data[row], width, bottom=yoff, color='b')
yoff = yoff + data[row]
cellText.append([''])
plt.xticks([])
plt.legend([''] * 5, loc=(1.2, 0.2))
# Add a table at the bottom of the axes
cellText.reverse()
the_table = plt.table(cellText=cellText,
rowLabels=rowLabels,
colLabels=colLabels, loc='bottom')
@image_comparison(baseline_images=['bbox_inches_tight_suptile_legend'],
remove_text=False, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_suptile_legend():
plt.plot(np.arange(10), label='a straight line')
plt.legend(bbox_to_anchor=(0.9, 1), loc=2, )
plt.title('Axis title')
plt.suptitle('Figure title')
# put an extra long y tick on to see that the bbox is accounted for
def y_formatter(y, pos):
if int(y) == 4:
return 'The number 4'
else:
return str(y)
plt.gca().yaxis.set_major_formatter(FuncFormatter(y_formatter))
plt.xlabel('X axis')
@image_comparison(baseline_images=['bbox_inches_tight_clipping'],
remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_clipping():
# tests bbox clipping on scatter points, and path clipping on a patch
# to generate an appropriately tight bbox
plt.scatter(np.arange(10), np.arange(10))
ax = plt.gca()
ax.set_xlim([0, 5])
ax.set_ylim([0, 5])
# make a massive rectangle and clip it with a path
patch = mpatches.Rectangle([-50, -50], 100, 100,
transform=ax.transData,
facecolor='blue', alpha=0.5)
path = mpath.Path.unit_regular_star(5).deepcopy()
path.vertices *= 0.25
patch.set_clip_path(path, transform=ax.transAxes)
plt.gcf().artists.append(patch)
@image_comparison(baseline_images=['bbox_inches_tight_raster'],
remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_raster():
"""Test rasterization with tight_layout"""
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1.0, 2.0], rasterized=True)
| 3,323 | 35.527473 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_pgf.py | # -*- encoding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import os
import shutil
import numpy as np
import pytest
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.compat import subprocess
from matplotlib.testing.compare import compare_images, ImageComparisonFailure
from matplotlib.testing.decorators import image_comparison, _image_directories
baseline_dir, result_dir = _image_directories(lambda: 'dummy func')
def check_for(texsystem):
header = """
\\documentclass{minimal}
\\usepackage{pgf}
\\begin{document}
\\typeout{pgfversion=\\pgfversion}
\\makeatletter
\\@@end
"""
try:
latex = subprocess.Popen([str(texsystem), "-halt-on-error"],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE)
stdout, stderr = latex.communicate(header.encode("utf8"))
except OSError:
return False
return latex.returncode == 0
needs_xelatex = pytest.mark.skipif(not check_for('xelatex'),
reason='xelatex + pgf is required')
needs_pdflatex = pytest.mark.skipif(not check_for('pdflatex'),
reason='pdflatex + pgf is required')
def compare_figure(fname, savefig_kwargs={}, tol=0):
actual = os.path.join(result_dir, fname)
plt.savefig(actual, **savefig_kwargs)
expected = os.path.join(result_dir, "expected_%s" % fname)
shutil.copyfile(os.path.join(baseline_dir, fname), expected)
err = compare_images(expected, actual, tol=tol)
if err:
raise ImageComparisonFailure(err)
def create_figure():
plt.figure()
x = np.linspace(0, 1, 15)
# line plot
plt.plot(x, x ** 2, "b-")
# marker
plt.plot(x, 1 - x**2, "g>")
# filled paths and patterns
plt.fill_between([0., .4], [.4, 0.], hatch='//', facecolor="lightgray",
edgecolor="red")
plt.fill([3, 3, .8, .8, 3], [2, -2, -2, 0, 2], "b")
# text and typesetting
plt.plot([0.9], [0.5], "ro", markersize=3)
plt.text(0.9, 0.5, u'unicode (ü, °, µ) and math ($\\mu_i = x_i^2$)',
ha='right', fontsize=20)
plt.ylabel('sans-serif, blue, $\\frac{\\sqrt{x}}{y^2}$..',
family='sans-serif', color='blue')
plt.xlim(0, 1)
plt.ylim(0, 1)
# test compiling a figure to pdf with xelatex
@needs_xelatex
@pytest.mark.backend('pgf')
@image_comparison(baseline_images=['pgf_xelatex'], extensions=['pdf'],
style='default')
def test_xelatex():
rc_xelatex = {'font.family': 'serif',
'pgf.rcfonts': False}
mpl.rcParams.update(rc_xelatex)
create_figure()
# test compiling a figure to pdf with pdflatex
@needs_pdflatex
@pytest.mark.backend('pgf')
@image_comparison(baseline_images=['pgf_pdflatex'], extensions=['pdf'],
style='default')
def test_pdflatex():
import os
if os.environ.get('APPVEYOR', False):
pytest.xfail("pdflatex test does not work on appveyor due to missing "
"LaTeX fonts")
rc_pdflatex = {'font.family': 'serif',
'pgf.rcfonts': False,
'pgf.texsystem': 'pdflatex',
'pgf.preamble': ['\\usepackage[utf8x]{inputenc}',
'\\usepackage[T1]{fontenc}']}
mpl.rcParams.update(rc_pdflatex)
create_figure()
# test updating the rc parameters for each figure
@needs_xelatex
@needs_pdflatex
@pytest.mark.style('default')
@pytest.mark.backend('pgf')
def test_rcupdate():
rc_sets = []
rc_sets.append({'font.family': 'sans-serif',
'font.size': 30,
'figure.subplot.left': .2,
'lines.markersize': 10,
'pgf.rcfonts': False,
'pgf.texsystem': 'xelatex'})
rc_sets.append({'font.family': 'monospace',
'font.size': 10,
'figure.subplot.left': .1,
'lines.markersize': 20,
'pgf.rcfonts': False,
'pgf.texsystem': 'pdflatex',
'pgf.preamble': ['\\usepackage[utf8x]{inputenc}',
'\\usepackage[T1]{fontenc}',
'\\usepackage{sfmath}']})
tol = (6, 0)
original_params = mpl.rcParams.copy()
for i, rc_set in enumerate(rc_sets):
mpl.rcParams.clear()
mpl.rcParams.update(original_params)
mpl.rcParams.update(rc_set)
create_figure()
compare_figure('pgf_rcupdate%d.pdf' % (i + 1), tol=tol[i])
# test backend-side clipping, since large numbers are not supported by TeX
@needs_xelatex
@pytest.mark.style('default')
@pytest.mark.backend('pgf')
def test_pathclip():
rc_xelatex = {'font.family': 'serif',
'pgf.rcfonts': False}
mpl.rcParams.update(rc_xelatex)
plt.figure()
plt.plot([0., 1e100], [0., 1e100])
plt.xlim(0, 1)
plt.ylim(0, 1)
# this test passes if compiling/saving to pdf works (no image comparison)
plt.savefig(os.path.join(result_dir, "pgf_pathclip.pdf"))
# test mixed mode rendering
@needs_xelatex
@pytest.mark.backend('pgf')
@image_comparison(baseline_images=['pgf_mixedmode'], extensions=['pdf'],
style='default')
def test_mixedmode():
rc_xelatex = {'font.family': 'serif',
'pgf.rcfonts': False}
mpl.rcParams.update(rc_xelatex)
Y, X = np.ogrid[-1:1:40j, -1:1:40j]
plt.figure()
plt.pcolor(X**2 + Y**2).set_rasterized(True)
# test bbox_inches clipping
@needs_xelatex
@pytest.mark.style('default')
@pytest.mark.backend('pgf')
def test_bbox_inches():
rc_xelatex = {'font.family': 'serif',
'pgf.rcfonts': False}
mpl.rcParams.update(rc_xelatex)
Y, X = np.ogrid[-1:1:40j, -1:1:40j]
fig = plt.figure()
ax1 = fig.add_subplot(121)
ax1.plot(range(5))
ax2 = fig.add_subplot(122)
ax2.plot(range(5))
plt.tight_layout()
bbox = ax1.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
compare_figure('pgf_bbox_inches.pdf', savefig_kwargs={'bbox_inches': bbox},
tol=0)
| 6,218 | 30.409091 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_afm.py | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
from six import BytesIO
import matplotlib.afm as afm
AFM_TEST_DATA = b"""StartFontMetrics 2.0
Comment Comments are ignored.
Comment Creation Date:Mon Nov 13 12:34:11 GMT 2017
FontName MyFont-Bold
EncodingScheme FontSpecific
FullName My Font Bold
FamilyName Test Fonts
Weight Bold
ItalicAngle 0.0
IsFixedPitch false
UnderlinePosition -100
UnderlineThickness 50
Version 001.000
Notice Copyright (c) 2017 No one.
FontBBox 0 -321 1234 369
StartCharMetrics 3
C 0 ; WX 250 ; N space ; B 0 0 0 0 ;
C 42 ; WX 1141 ; N foo ; B 40 60 800 360 ;
C 99 ; WX 583 ; N bar ; B 40 -10 543 210 ;
EndCharMetrics
EndFontMetrics
"""
def test_nonascii_str():
# This tests that we also decode bytes as utf-8 properly.
# Else, font files with non ascii characters fail to load.
inp_str = u"привет"
byte_str = inp_str.encode("utf8")
ret = afm._to_str(byte_str)
assert ret == inp_str
def test_parse_header():
fh = BytesIO(AFM_TEST_DATA)
header = afm._parse_header(fh)
assert header == {
b'StartFontMetrics': 2.0,
b'FontName': 'MyFont-Bold',
b'EncodingScheme': 'FontSpecific',
b'FullName': 'My Font Bold',
b'FamilyName': 'Test Fonts',
b'Weight': 'Bold',
b'ItalicAngle': 0.0,
b'IsFixedPitch': False,
b'UnderlinePosition': -100,
b'UnderlineThickness': 50,
b'Version': '001.000',
b'Notice': 'Copyright (c) 2017 No one.',
b'FontBBox': [0, -321, 1234, 369],
b'StartCharMetrics': 3,
}
def test_parse_char_metrics():
fh = BytesIO(AFM_TEST_DATA)
afm._parse_header(fh) # position
metrics = afm._parse_char_metrics(fh)
assert metrics == (
{0: (250.0, 'space', [0, 0, 0, 0]),
42: (1141.0, 'foo', [40, 60, 800, 360]),
99: (583.0, 'bar', [40, -10, 543, 210]),
},
{'space': (250.0, [0, 0, 0, 0]),
'foo': (1141.0, [40, 60, 800, 360]),
'bar': (583.0, [40, -10, 543, 210]),
})
def test_get_familyname_guessed():
fh = BytesIO(AFM_TEST_DATA)
fm = afm.AFM(fh)
del fm._header[b'FamilyName'] # remove FamilyName, so we have to guess
assert fm.get_familyname() == 'My Font'
| 2,281 | 26.166667 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_type1font.py | from __future__ import absolute_import, division, print_function
import six
import matplotlib.type1font as t1f
import os.path
import difflib
def test_Type1Font():
filename = os.path.join(os.path.dirname(__file__), 'cmr10.pfb')
font = t1f.Type1Font(filename)
slanted = font.transform({'slant': 1})
condensed = font.transform({'extend': 0.5})
with open(filename, 'rb') as fd:
rawdata = fd.read()
assert font.parts[0] == rawdata[0x0006:0x10c5]
assert font.parts[1] == rawdata[0x10cb:0x897f]
assert font.parts[2] == rawdata[0x8985:0x8ba6]
assert font.parts[1:] == slanted.parts[1:]
assert font.parts[1:] == condensed.parts[1:]
differ = difflib.Differ()
diff = list(differ.compare(
font.parts[0].decode('latin-1').splitlines(),
slanted.parts[0].decode('latin-1').splitlines()))
for line in (
# Removes UniqueID
'- FontDirectory/CMR10 known{/CMR10 findfont dup/UniqueID known{dup',
'+ FontDirectory/CMR10 known{/CMR10 findfont dup',
# Changes the font name
'- /FontName /CMR10 def',
'+ /FontName /CMR10_Slant_1000 def',
# Alters FontMatrix
'- /FontMatrix [0.001 0 0 0.001 0 0 ]readonly def',
'+ /FontMatrix [0.001 0.0 0.001 0.001 0.0 0.0]readonly def',
# Alters ItalicAngle
'- /ItalicAngle 0 def',
'+ /ItalicAngle -45.0 def'):
assert line in diff, 'diff to slanted font must contain %s' % line
diff = list(differ.compare(font.parts[0].decode('latin-1').splitlines(),
condensed.parts[0].decode('latin-1').splitlines()))
for line in (
# Removes UniqueID
'- FontDirectory/CMR10 known{/CMR10 findfont dup/UniqueID known{dup',
'+ FontDirectory/CMR10 known{/CMR10 findfont dup',
# Changes the font name
'- /FontName /CMR10 def',
'+ /FontName /CMR10_Extend_500 def',
# Alters FontMatrix
'- /FontMatrix [0.001 0 0 0.001 0 0 ]readonly def',
'+ /FontMatrix [0.0005 0.0 0.0 0.001 0.0 0.0]readonly def'):
assert line in diff, 'diff to condensed font must contain %s' % line
| 2,175 | 38.563636 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_agg.py | from __future__ import absolute_import, division, print_function
import io
import numpy as np
from numpy.testing import assert_array_almost_equal
import pytest
from matplotlib import (
collections, path, pyplot as plt, transforms as mtransforms, rcParams)
from matplotlib.image import imread
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib.testing.decorators import image_comparison
def test_repeated_save_with_alpha():
# We want an image which has a background color of bluish green, with an
# alpha of 0.25.
fig = Figure([1, 0.4])
canvas = FigureCanvas(fig)
fig.set_facecolor((0, 1, 0.4))
fig.patch.set_alpha(0.25)
# The target color is fig.patch.get_facecolor()
buf = io.BytesIO()
fig.savefig(buf,
facecolor=fig.get_facecolor(),
edgecolor='none')
# Save the figure again to check that the
# colors don't bleed from the previous renderer.
buf.seek(0)
fig.savefig(buf,
facecolor=fig.get_facecolor(),
edgecolor='none')
# Check the first pixel has the desired color & alpha
# (approx: 0, 1.0, 0.4, 0.25)
buf.seek(0)
assert_array_almost_equal(tuple(imread(buf)[0, 0]),
(0.0, 1.0, 0.4, 0.250),
decimal=3)
def test_large_single_path_collection():
buff = io.BytesIO()
# Generates a too-large single path in a path collection that
# would cause a segfault if the draw_markers optimization is
# applied.
f, ax = plt.subplots()
collection = collections.PathCollection(
[path.Path([[-10, 5], [10, 5], [10, -5], [-10, -5], [-10, 5]])])
ax.add_artist(collection)
ax.set_xlim(10**-3, 1)
plt.savefig(buff)
def test_marker_with_nan():
# This creates a marker with nans in it, which was segfaulting the
# Agg backend (see #3722)
fig, ax = plt.subplots(1)
steps = 1000
data = np.arange(steps)
ax.semilogx(data)
ax.fill_between(data, data*0.8, data*1.2)
buf = io.BytesIO()
fig.savefig(buf, format='png')
def test_long_path():
buff = io.BytesIO()
fig, ax = plt.subplots()
np.random.seed(0)
points = np.random.rand(70000)
ax.plot(points)
fig.savefig(buff, format='png')
@image_comparison(baseline_images=['agg_filter'],
extensions=['png'], remove_text=True)
def test_agg_filter():
def smooth1d(x, window_len):
s = np.r_[2*x[0] - x[window_len:1:-1],
x,
2*x[-1] - x[-1:-window_len:-1]]
w = np.hanning(window_len)
y = np.convolve(w/w.sum(), s, mode='same')
return y[window_len-1:-window_len+1]
def smooth2d(A, sigma=3):
window_len = max(int(sigma), 3)*2 + 1
A1 = np.array([smooth1d(x, window_len) for x in np.asarray(A)])
A2 = np.transpose(A1)
A3 = np.array([smooth1d(x, window_len) for x in A2])
A4 = np.transpose(A3)
return A4
class BaseFilter(object):
def prepare_image(self, src_image, dpi, pad):
ny, nx, depth = src_image.shape
padded_src = np.zeros([pad*2 + ny, pad*2 + nx, depth], dtype="d")
padded_src[pad:-pad, pad:-pad, :] = src_image[:, :, :]
return padded_src # , tgt_image
def get_pad(self, dpi):
return 0
def __call__(self, im, dpi):
pad = self.get_pad(dpi)
padded_src = self.prepare_image(im, dpi, pad)
tgt_image = self.process_image(padded_src, dpi)
return tgt_image, -pad, -pad
class OffsetFilter(BaseFilter):
def __init__(self, offsets=None):
if offsets is None:
self.offsets = (0, 0)
else:
self.offsets = offsets
def get_pad(self, dpi):
return int(max(*self.offsets)/72.*dpi)
def process_image(self, padded_src, dpi):
ox, oy = self.offsets
a1 = np.roll(padded_src, int(ox/72.*dpi), axis=1)
a2 = np.roll(a1, -int(oy/72.*dpi), axis=0)
return a2
class GaussianFilter(BaseFilter):
"simple gauss filter"
def __init__(self, sigma, alpha=0.5, color=None):
self.sigma = sigma
self.alpha = alpha
if color is None:
self.color = (0, 0, 0)
else:
self.color = color
def get_pad(self, dpi):
return int(self.sigma*3/72.*dpi)
def process_image(self, padded_src, dpi):
tgt_image = np.zeros_like(padded_src)
aa = smooth2d(padded_src[:, :, -1]*self.alpha,
self.sigma/72.*dpi)
tgt_image[:, :, -1] = aa
tgt_image[:, :, :-1] = self.color
return tgt_image
class DropShadowFilter(BaseFilter):
def __init__(self, sigma, alpha=0.3, color=None, offsets=None):
self.gauss_filter = GaussianFilter(sigma, alpha, color)
self.offset_filter = OffsetFilter(offsets)
def get_pad(self, dpi):
return max(self.gauss_filter.get_pad(dpi),
self.offset_filter.get_pad(dpi))
def process_image(self, padded_src, dpi):
t1 = self.gauss_filter.process_image(padded_src, dpi)
t2 = self.offset_filter.process_image(t1, dpi)
return t2
fig = plt.figure()
ax = fig.add_subplot(111)
# draw lines
l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",
mec="b", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-",
mec="r", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
gauss = DropShadowFilter(4)
for l in [l1, l2]:
# draw shadows with same lines with slight offset.
xx = l.get_xdata()
yy = l.get_ydata()
shadow, = ax.plot(xx, yy)
shadow.update_from(l)
# offset transform
ot = mtransforms.offset_copy(l.get_transform(), ax.figure,
x=4.0, y=-6.0, units='points')
shadow.set_transform(ot)
# adjust zorder of the shadow lines so that it is drawn below the
# original lines
shadow.set_zorder(l.get_zorder() - 0.5)
shadow.set_agg_filter(gauss)
shadow.set_rasterized(True) # to support mixed-mode renderers
ax.set_xlim(0., 1.)
ax.set_ylim(0., 1.)
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
def test_too_large_image():
fig = plt.figure(figsize=(300, 1000))
buff = io.BytesIO()
with pytest.raises(ValueError):
fig.savefig(buff)
def test_chunksize():
x = range(200)
# Test without chunksize
fig, ax = plt.subplots()
ax.plot(x, np.sin(x))
fig.canvas.draw()
# Test with chunksize
fig, ax = plt.subplots()
rcParams['agg.path.chunksize'] = 105
ax.plot(x, np.sin(x))
fig.canvas.draw()
@pytest.mark.backend('Agg')
def test_jpeg_dpi():
Image = pytest.importorskip("PIL.Image")
# Check that dpi is set correctly in jpg files.
plt.plot([0, 1, 2], [0, 1, 0])
buf = io.BytesIO()
plt.savefig(buf, format="jpg", dpi=200)
im = Image.open(buf)
assert im.info['dpi'] == (200, 200)
| 7,365 | 29.188525 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_colorbar.py | from __future__ import absolute_import, division, print_function
import numpy as np
import pytest
from matplotlib import rc_context
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm, LogNorm
from matplotlib.cm import get_cmap
from matplotlib.colorbar import ColorbarBase
def _get_cmap_norms():
"""
Define a colormap and appropriate norms for each of the four
possible settings of the extend keyword.
Helper function for _colorbar_extension_shape and
colorbar_extension_length.
"""
# Create a color map and specify the levels it represents.
cmap = get_cmap("RdBu", lut=5)
clevs = [-5., -2.5, -.5, .5, 1.5, 3.5]
# Define norms for the color maps.
norms = dict()
norms['neither'] = BoundaryNorm(clevs, len(clevs) - 1)
norms['min'] = BoundaryNorm([-10] + clevs[1:], len(clevs) - 1)
norms['max'] = BoundaryNorm(clevs[:-1] + [10], len(clevs) - 1)
norms['both'] = BoundaryNorm([-10] + clevs[1:-1] + [10], len(clevs) - 1)
return cmap, norms
def _colorbar_extension_shape(spacing):
'''
Produce 4 colorbars with rectangular extensions for either uniform
or proportional spacing.
Helper function for test_colorbar_extension_shape.
'''
# Get a colormap and appropriate norms for each extension type.
cmap, norms = _get_cmap_norms()
# Create a figure and adjust whitespace for subplots.
fig = plt.figure()
fig.subplots_adjust(hspace=4)
for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
# Get the appropriate norm and use it to get colorbar boundaries.
norm = norms[extension_type]
boundaries = values = norm.boundaries
# Create a subplot.
cax = fig.add_subplot(4, 1, i + 1)
# Generate the colorbar.
cb = ColorbarBase(cax, cmap=cmap, norm=norm,
boundaries=boundaries, values=values,
extend=extension_type, extendrect=True,
orientation='horizontal', spacing=spacing)
# Turn off text and ticks.
cax.tick_params(left=False, labelleft=False,
bottom=False, labelbottom=False)
# Return the figure to the caller.
return fig
def _colorbar_extension_length(spacing):
'''
Produce 12 colorbars with variable length extensions for either
uniform or proportional spacing.
Helper function for test_colorbar_extension_length.
'''
# Get a colormap and appropriate norms for each extension type.
cmap, norms = _get_cmap_norms()
# Create a figure and adjust whitespace for subplots.
fig = plt.figure()
fig.subplots_adjust(hspace=.6)
for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
# Get the appropriate norm and use it to get colorbar boundaries.
norm = norms[extension_type]
boundaries = values = norm.boundaries
for j, extendfrac in enumerate((None, 'auto', 0.1)):
# Create a subplot.
cax = fig.add_subplot(12, 1, i*3 + j + 1)
# Generate the colorbar.
ColorbarBase(cax, cmap=cmap, norm=norm,
boundaries=boundaries, values=values,
extend=extension_type, extendfrac=extendfrac,
orientation='horizontal', spacing=spacing)
# Turn off text and ticks.
cax.tick_params(left=False, labelleft=False,
bottom=False, labelbottom=False)
# Return the figure to the caller.
return fig
@image_comparison(
baseline_images=['colorbar_extensions_shape_uniform',
'colorbar_extensions_shape_proportional'],
extensions=['png'])
def test_colorbar_extension_shape():
'''Test rectangular colorbar extensions.'''
# Create figures for uniform and proportionally spaced colorbars.
_colorbar_extension_shape('uniform')
_colorbar_extension_shape('proportional')
@image_comparison(baseline_images=['colorbar_extensions_uniform',
'colorbar_extensions_proportional'],
extensions=['png'])
def test_colorbar_extension_length():
'''Test variable length colorbar extensions.'''
# Create figures for uniform and proportionally spaced colorbars.
_colorbar_extension_length('uniform')
_colorbar_extension_length('proportional')
@image_comparison(baseline_images=['cbar_with_orientation',
'cbar_locationing',
'double_cbar',
'cbar_sharing',
],
extensions=['png'], remove_text=True,
savefig_kwarg={'dpi': 40})
def test_colorbar_positioning():
data = np.arange(1200).reshape(30, 40)
levels = [0, 200, 400, 600, 800, 1000, 1200]
# -------------------
plt.figure()
plt.contourf(data, levels=levels)
plt.colorbar(orientation='horizontal', use_gridspec=False)
locations = ['left', 'right', 'top', 'bottom']
plt.figure()
for i, location in enumerate(locations):
plt.subplot(2, 2, i + 1)
plt.contourf(data, levels=levels)
plt.colorbar(location=location, use_gridspec=False)
# -------------------
plt.figure()
# make some other data (random integers)
data_2nd = np.array([[2, 3, 2, 3], [1.5, 2, 2, 3], [2, 3, 3, 4]])
# make the random data expand to the shape of the main data
data_2nd = np.repeat(np.repeat(data_2nd, 10, axis=1), 10, axis=0)
color_mappable = plt.contourf(data, levels=levels, extend='both')
# test extend frac here
hatch_mappable = plt.contourf(data_2nd, levels=[1, 2, 3], colors='none',
hatches=['/', 'o', '+'], extend='max')
plt.contour(hatch_mappable, colors='black')
plt.colorbar(color_mappable, location='left', label='variable 1',
use_gridspec=False)
plt.colorbar(hatch_mappable, location='right', label='variable 2',
use_gridspec=False)
# -------------------
plt.figure()
ax1 = plt.subplot(211, anchor='NE', aspect='equal')
plt.contourf(data, levels=levels)
ax2 = plt.subplot(223)
plt.contourf(data, levels=levels)
ax3 = plt.subplot(224)
plt.contourf(data, levels=levels)
plt.colorbar(ax=[ax2, ax3, ax1], location='right', pad=0.0, shrink=0.5,
panchor=False, use_gridspec=False)
plt.colorbar(ax=[ax2, ax3, ax1], location='left', shrink=0.5,
panchor=False, use_gridspec=False)
plt.colorbar(ax=[ax1], location='bottom', panchor=False,
anchor=(0.8, 0.5), shrink=0.6, use_gridspec=False)
@image_comparison(baseline_images=['cbar_with_subplots_adjust'],
extensions=['png'], remove_text=True,
savefig_kwarg={'dpi': 40})
def test_gridspec_make_colorbar():
plt.figure()
data = np.arange(1200).reshape(30, 40)
levels = [0, 200, 400, 600, 800, 1000, 1200]
plt.subplot(121)
plt.contourf(data, levels=levels)
plt.colorbar(use_gridspec=True, orientation='vertical')
plt.subplot(122)
plt.contourf(data, levels=levels)
plt.colorbar(use_gridspec=True, orientation='horizontal')
plt.subplots_adjust(top=0.95, right=0.95, bottom=0.2, hspace=0.25)
@image_comparison(baseline_images=['colorbar_single_scatter'],
extensions=['png'], remove_text=True,
savefig_kwarg={'dpi': 40})
def test_colorbar_single_scatter():
# Issue #2642: if a path collection has only one entry,
# the norm scaling within the colorbar must ensure a
# finite range, otherwise a zero denominator will occur in _locate.
plt.figure()
x = np.arange(4)
y = x.copy()
z = np.ma.masked_greater(np.arange(50, 54), 50)
cmap = plt.get_cmap('jet', 16)
cs = plt.scatter(x, y, z, c=z, cmap=cmap)
plt.colorbar(cs)
@pytest.mark.parametrize('use_gridspec', [False, True],
ids=['no gridspec', 'with gridspec'])
def test_remove_from_figure(use_gridspec):
"""
Test `remove_from_figure` with the specified ``use_gridspec`` setting
"""
fig = plt.figure()
ax = fig.add_subplot(111)
sc = ax.scatter([1, 2], [3, 4], cmap="spring")
sc.set_array(np.array([5, 6]))
pre_figbox = np.array(ax.figbox)
cb = fig.colorbar(sc, use_gridspec=use_gridspec)
fig.subplots_adjust()
cb.remove()
fig.subplots_adjust()
post_figbox = np.array(ax.figbox)
assert (pre_figbox == post_figbox).all()
def test_colorbarbase():
# smoke test from #3805
ax = plt.gca()
ColorbarBase(ax, plt.cm.bone)
@image_comparison(
baseline_images=['colorbar_closed_patch'],
remove_text=True)
def test_colorbar_closed_patch():
fig = plt.figure(figsize=(8, 6))
ax1 = fig.add_axes([0.05, 0.85, 0.9, 0.1])
ax2 = fig.add_axes([0.1, 0.65, 0.75, 0.1])
ax3 = fig.add_axes([0.05, 0.45, 0.9, 0.1])
ax4 = fig.add_axes([0.05, 0.25, 0.9, 0.1])
ax5 = fig.add_axes([0.05, 0.05, 0.9, 0.1])
cmap = get_cmap("RdBu", lut=5)
im = ax1.pcolormesh(np.linspace(0, 10, 16).reshape((4, 4)), cmap=cmap)
values = np.linspace(0, 10, 5)
with rc_context({'axes.linewidth': 16}):
plt.colorbar(im, cax=ax2, cmap=cmap, orientation='horizontal',
extend='both', extendfrac=0.5, values=values)
plt.colorbar(im, cax=ax3, cmap=cmap, orientation='horizontal',
extend='both', values=values)
plt.colorbar(im, cax=ax4, cmap=cmap, orientation='horizontal',
extend='both', extendrect=True, values=values)
plt.colorbar(im, cax=ax5, cmap=cmap, orientation='horizontal',
extend='neither', values=values)
def test_colorbar_ticks():
# test fix for #5673
fig, ax = plt.subplots()
x = np.arange(-3.0, 4.001)
y = np.arange(-4.0, 3.001)
X, Y = np.meshgrid(x, y)
Z = X * Y
clevs = np.array([-12, -5, 0, 5, 12], dtype=float)
colors = ['r', 'g', 'b', 'c']
cs = ax.contourf(X, Y, Z, clevs, colors=colors)
cbar = fig.colorbar(cs, ax=ax, extend='neither',
orientation='horizontal', ticks=clevs)
assert len(cbar.ax.xaxis.get_ticklocs()) == len(clevs)
def test_colorbar_get_ticks():
# test feature for #5792
plt.figure()
data = np.arange(1200).reshape(30, 40)
levels = [0, 200, 400, 600, 800, 1000, 1200]
plt.subplot()
plt.contourf(data, levels=levels)
# testing getter for user set ticks
userTicks = plt.colorbar(ticks=[0, 600, 1200])
assert userTicks.get_ticks().tolist() == [0, 600, 1200]
# testing for getter after calling set_ticks
userTicks.set_ticks([600, 700, 800])
assert userTicks.get_ticks().tolist() == [600, 700, 800]
# testing for getter after calling set_ticks with some ticks out of bounds
userTicks.set_ticks([600, 1300, 1400, 1500])
assert userTicks.get_ticks().tolist() == [600]
# testing getter when no ticks are assigned
defTicks = plt.colorbar(orientation='horizontal')
assert defTicks.get_ticks().tolist() == levels
def test_colorbar_lognorm_extension():
# Test that colorbar with lognorm is extended correctly
f, ax = plt.subplots()
cb = ColorbarBase(ax, norm=LogNorm(vmin=0.1, vmax=1000.0),
orientation='vertical', extend='both')
assert cb._values[0] >= 0.0
def test_colorbar_axes_kw():
# test fix for #8493: This does only test, that axes-related keywords pass
# and do not raise an exception.
plt.figure()
plt.imshow(([[1, 2], [3, 4]]))
plt.colorbar(orientation='horizontal', fraction=0.2, pad=0.2, shrink=0.5,
aspect=10, anchor=(0., 0.), panchor=(0., 1.))
| 11,847 | 36.375394 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_subplots.py | from __future__ import absolute_import, division, print_function
import warnings
import numpy
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
import pytest
def check_shared(axs, x_shared, y_shared):
"""
x_shared and y_shared are n x n boolean matrices; entry (i, j) indicates
whether the x (or y) axes of subplots i and j should be shared.
"""
shared = [axs[0]._shared_x_axes, axs[0]._shared_y_axes]
for (i1, ax1), (i2, ax2), (i3, (name, shared)) in zip(
enumerate(axs),
enumerate(axs),
enumerate(zip("xy", [x_shared, y_shared]))):
if i2 <= i1:
continue
assert shared[i3].joined(ax1, ax2) == shared[i1, i2], \
"axes %i and %i incorrectly %ssharing %s axis" % (
i1, i2, "not " if shared[i1, i2] else "", name)
def check_visible(axs, x_visible, y_visible):
def tostr(v):
return "invisible" if v else "visible"
for (ax, vx, vy) in zip(axs, x_visible, y_visible):
for l in ax.get_xticklabels() + [ax.get_xaxis().offsetText]:
assert l.get_visible() == vx, \
"X axis was incorrectly %s" % (tostr(vx))
for l in ax.get_yticklabels() + [ax.get_yaxis().offsetText]:
assert l.get_visible() == vy, \
"Y axis was incorrectly %s" % (tostr(vy))
def test_shared():
rdim = (4, 4, 2)
share = {
'all': numpy.ones(rdim[:2], dtype=bool),
'none': numpy.zeros(rdim[:2], dtype=bool),
'row': numpy.array([
[False, True, False, False],
[True, False, False, False],
[False, False, False, True],
[False, False, True, False]]),
'col': numpy.array([
[False, False, True, False],
[False, False, False, True],
[True, False, False, False],
[False, True, False, False]]),
}
visible = {
'x': {
'all': [False, False, True, True],
'col': [False, False, True, True],
'row': [True] * 4,
'none': [True] * 4,
False: [True] * 4,
True: [False, False, True, True],
},
'y': {
'all': [True, False, True, False],
'col': [True] * 4,
'row': [True, False, True, False],
'none': [True] * 4,
False: [True] * 4,
True: [True, False, True, False],
},
}
share[False] = share['none']
share[True] = share['all']
# test default
f, ((a1, a2), (a3, a4)) = plt.subplots(2, 2)
axs = [a1, a2, a3, a4]
check_shared(axs, share['none'], share['none'])
plt.close(f)
# test all option combinations
ops = [False, True, 'all', 'none', 'row', 'col']
for xo in ops:
for yo in ops:
f, ((a1, a2), (a3, a4)) = plt.subplots(2, 2, sharex=xo, sharey=yo)
axs = [a1, a2, a3, a4]
check_shared(axs, share[xo], share[yo])
check_visible(axs, visible['x'][xo], visible['y'][yo])
plt.close(f)
# test label_outer
f, ((a1, a2), (a3, a4)) = plt.subplots(2, 2, sharex=True, sharey=True)
axs = [a1, a2, a3, a4]
for ax in axs:
ax.label_outer()
check_visible(axs, [False, False, True, True], [True, False, True, False])
def test_shared_and_moved():
# test if sharey is on, but then tick_left is called that labels don't
# re-appear. Seaborn does this just to be sure yaxis is on left...
f, (a1, a2) = plt.subplots(1, 2, sharey=True)
check_visible([a2], [True], [False])
a2.yaxis.tick_left()
check_visible([a2], [True], [False])
f, (a1, a2) = plt.subplots(2, 1, sharex=True)
check_visible([a1], [False], [True])
a2.xaxis.tick_bottom()
check_visible([a1], [False], [True])
def test_exceptions():
# TODO should this test more options?
with pytest.raises(ValueError):
plt.subplots(2, 2, sharex='blah')
with pytest.raises(ValueError):
plt.subplots(2, 2, sharey='blah')
# We filter warnings in this test which are genuine since
# the point of this test is to ensure that this raises.
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
message='.*sharex argument to subplots',
category=UserWarning)
with pytest.raises(ValueError):
plt.subplots(2, 2, -1)
with pytest.raises(ValueError):
plt.subplots(2, 2, 0)
with pytest.raises(ValueError):
plt.subplots(2, 2, 5)
@image_comparison(baseline_images=['subplots_offset_text'], remove_text=False)
def test_subplots_offsettext():
x = numpy.arange(0, 1e10, 1e9)
y = numpy.arange(0, 100, 10)+1e4
fig, axes = plt.subplots(2, 2, sharex='col', sharey='all')
axes[0, 0].plot(x, x)
axes[1, 0].plot(x, x)
axes[0, 1].plot(y, x)
axes[1, 1].plot(y, x)
| 5,110 | 34.006849 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_streamplot.py | from __future__ import absolute_import, division, print_function
import sys
import numpy as np
from numpy.testing import assert_array_almost_equal
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
import matplotlib.transforms as mtransforms
on_win = (sys.platform == 'win32')
def velocity_field():
Y, X = np.mgrid[-3:3:100j, -3:3:100j]
U = -1 - X**2 + Y
V = 1 + X - Y**2
return X, Y, U, V
def swirl_velocity_field():
x = np.linspace(-3., 3., 100)
y = np.linspace(-3., 3., 100)
X, Y = np.meshgrid(x, y)
a = 0.1
U = np.cos(a) * (-Y) - np.sin(a) * X
V = np.sin(a) * (-Y) + np.cos(a) * X
return x, y, U, V
@image_comparison(baseline_images=['streamplot_startpoints'])
def test_startpoints():
X, Y, U, V = velocity_field()
start_x = np.linspace(X.min(), X.max(), 10)
start_y = np.linspace(Y.min(), Y.max(), 10)
start_points = np.column_stack([start_x, start_y])
plt.streamplot(X, Y, U, V, start_points=start_points)
plt.plot(start_x, start_y, 'ok')
@image_comparison(baseline_images=['streamplot_colormap'],
tol=.02)
def test_colormap():
X, Y, U, V = velocity_field()
plt.streamplot(X, Y, U, V, color=U, density=0.6, linewidth=2,
cmap=plt.cm.autumn)
plt.colorbar()
@image_comparison(baseline_images=['streamplot_linewidth'])
def test_linewidth():
X, Y, U, V = velocity_field()
speed = np.sqrt(U*U + V*V)
lw = 5*speed/speed.max()
df = 25. / 30. # Compatibility factor for old test image
plt.streamplot(X, Y, U, V, density=[0.5 * df, 1. * df], color='k',
linewidth=lw)
@image_comparison(baseline_images=['streamplot_masks_and_nans'],
tol=0.04 if on_win else 0)
def test_masks_and_nans():
X, Y, U, V = velocity_field()
mask = np.zeros(U.shape, dtype=bool)
mask[40:60, 40:60] = 1
U[:20, :20] = np.nan
U = np.ma.array(U, mask=mask)
with np.errstate(invalid='ignore'):
plt.streamplot(X, Y, U, V, color=U, cmap=plt.cm.Blues)
@image_comparison(baseline_images=['streamplot_maxlength'],
extensions=['png'])
def test_maxlength():
x, y, U, V = swirl_velocity_field()
plt.streamplot(x, y, U, V, maxlength=10., start_points=[[0., 1.5]],
linewidth=2, density=2)
@image_comparison(baseline_images=['streamplot_direction'],
extensions=['png'])
def test_direction():
x, y, U, V = swirl_velocity_field()
plt.streamplot(x, y, U, V, integration_direction='backward',
maxlength=1.5, start_points=[[1.5, 0.]],
linewidth=2, density=2)
def test_streamplot_limits():
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
# The calculated bounds are approximately the bounds of the original data,
# this is because the entire path is taken into account when updating the
# datalim.
assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
decimal=1)
| 3,235 | 30.72549 | 78 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_cycles.py | import warnings
from matplotlib.testing.decorators import image_comparison
from matplotlib.cbook import MatplotlibDeprecationWarning
import matplotlib.pyplot as plt
import numpy as np
import pytest
from cycler import cycler
@image_comparison(baseline_images=['color_cycle_basic'], remove_text=True,
extensions=['png'])
def test_colorcycle_basic():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle(cycler('color', ['r', 'g', 'y']))
xs = np.arange(10)
ys = 0.25 * xs + 2
ax.plot(xs, ys, label='red', lw=4)
ys = 0.45 * xs + 3
ax.plot(xs, ys, label='green', lw=4)
ys = 0.65 * xs + 4
ax.plot(xs, ys, label='yellow', lw=4)
ys = 0.85 * xs + 5
ax.plot(xs, ys, label='red2', lw=4)
ax.legend(loc='upper left')
@image_comparison(baseline_images=['marker_cycle', 'marker_cycle'],
remove_text=True, extensions=['png'])
def test_marker_cycle():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle(cycler('c', ['r', 'g', 'y']) +
cycler('marker', ['.', '*', 'x']))
xs = np.arange(10)
ys = 0.25 * xs + 2
ax.plot(xs, ys, label='red dot', lw=4, ms=16)
ys = 0.45 * xs + 3
ax.plot(xs, ys, label='green star', lw=4, ms=16)
ys = 0.65 * xs + 4
ax.plot(xs, ys, label='yellow x', lw=4, ms=16)
ys = 0.85 * xs + 5
ax.plot(xs, ys, label='red2 dot', lw=4, ms=16)
ax.legend(loc='upper left')
fig = plt.figure()
ax = fig.add_subplot(111)
# Test keyword arguments, numpy arrays, and generic iterators
ax.set_prop_cycle(c=np.array(['r', 'g', 'y']),
marker=iter(['.', '*', 'x']))
xs = np.arange(10)
ys = 0.25 * xs + 2
ax.plot(xs, ys, label='red dot', lw=4, ms=16)
ys = 0.45 * xs + 3
ax.plot(xs, ys, label='green star', lw=4, ms=16)
ys = 0.65 * xs + 4
ax.plot(xs, ys, label='yellow x', lw=4, ms=16)
ys = 0.85 * xs + 5
ax.plot(xs, ys, label='red2 dot', lw=4, ms=16)
ax.legend(loc='upper left')
@image_comparison(baseline_images=['lineprop_cycle_basic'], remove_text=True,
extensions=['png'])
def test_linestylecycle_basic():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle(cycler('ls', ['-', '--', ':']))
xs = np.arange(10)
ys = 0.25 * xs + 2
ax.plot(xs, ys, label='solid', lw=4, color='k')
ys = 0.45 * xs + 3
ax.plot(xs, ys, label='dashed', lw=4, color='k')
ys = 0.65 * xs + 4
ax.plot(xs, ys, label='dotted', lw=4, color='k')
ys = 0.85 * xs + 5
ax.plot(xs, ys, label='solid2', lw=4, color='k')
ax.legend(loc='upper left')
@image_comparison(baseline_images=['fill_cycle_basic'], remove_text=True,
extensions=['png'])
def test_fillcycle_basic():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle(cycler('c', ['r', 'g', 'y']) +
cycler('hatch', ['xx', 'O', '|-']) +
cycler('linestyle', ['-', '--', ':']))
xs = np.arange(10)
ys = 0.25 * xs**.5 + 2
ax.fill(xs, ys, label='red, xx', linewidth=3)
ys = 0.45 * xs**.5 + 3
ax.fill(xs, ys, label='green, circle', linewidth=3)
ys = 0.65 * xs**.5 + 4
ax.fill(xs, ys, label='yellow, cross', linewidth=3)
ys = 0.85 * xs**.5 + 5
ax.fill(xs, ys, label='red2, xx', linewidth=3)
ax.legend(loc='upper left')
@image_comparison(baseline_images=['fill_cycle_ignore'], remove_text=True,
extensions=['png'])
def test_fillcycle_ignore():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle(cycler('color', ['r', 'g', 'y']) +
cycler('hatch', ['xx', 'O', '|-']) +
cycler('marker', ['.', '*', 'D']))
xs = np.arange(10)
ys = 0.25 * xs**.5 + 2
# Should not advance the cycler, even though there is an
# unspecified property in the cycler "marker".
# "marker" is not a Polygon property, and should be ignored.
ax.fill(xs, ys, 'r', hatch='xx', label='red, xx')
ys = 0.45 * xs**.5 + 3
# Allow the cycler to advance, but specify some properties
ax.fill(xs, ys, hatch='O', label='red, circle')
ys = 0.65 * xs**.5 + 4
ax.fill(xs, ys, label='green, circle')
ys = 0.85 * xs**.5 + 5
ax.fill(xs, ys, label='yellow, cross')
ax.legend(loc='upper left')
@image_comparison(baseline_images=['property_collision_plot'],
remove_text=True, extensions=['png'])
def test_property_collision_plot():
fig, ax = plt.subplots()
ax.set_prop_cycle('linewidth', [2, 4])
for c in range(1, 4):
ax.plot(np.arange(10), c * np.arange(10), lw=0.1, color='k')
ax.plot(np.arange(10), 4 * np.arange(10), color='k')
ax.plot(np.arange(10), 5 * np.arange(10), color='k')
@image_comparison(baseline_images=['property_collision_fill'],
remove_text=True, extensions=['png'])
def test_property_collision_fill():
fig, ax = plt.subplots()
xs = np.arange(10)
ys = 0.25 * xs**.5 + 2
ax.set_prop_cycle(linewidth=[2, 3, 4, 5, 6], facecolor='bgcmy')
for c in range(1, 4):
ax.fill(xs, c * ys, lw=0.1)
ax.fill(xs, 4 * ys)
ax.fill(xs, 5 * ys)
def test_valid_input_forms():
fig, ax = plt.subplots()
# These should not raise an error.
ax.set_prop_cycle(None)
ax.set_prop_cycle(cycler('linewidth', [1, 2]))
ax.set_prop_cycle('color', 'rgywkbcm')
ax.set_prop_cycle('lw', (1, 2))
ax.set_prop_cycle('linewidth', [1, 2])
ax.set_prop_cycle('linewidth', iter([1, 2]))
ax.set_prop_cycle('linewidth', np.array([1, 2]))
ax.set_prop_cycle('color', np.array([[1, 0, 0],
[0, 1, 0],
[0, 0, 1]]))
ax.set_prop_cycle('dashes', [[], [13, 2], [8, 3, 1, 3], [None, None]])
ax.set_prop_cycle(lw=[1, 2], color=['k', 'w'], ls=['-', '--'])
ax.set_prop_cycle(lw=np.array([1, 2]),
color=np.array(['k', 'w']),
ls=np.array(['-', '--']))
assert True
def test_cycle_reset():
fig, ax = plt.subplots()
# Can't really test a reset because only a cycle object is stored
# but we can test the first item of the cycle.
prop = next(ax._get_lines.prop_cycler)
ax.set_prop_cycle(linewidth=[10, 9, 4])
assert prop != next(ax._get_lines.prop_cycler)
ax.set_prop_cycle(None)
got = next(ax._get_lines.prop_cycler)
assert prop == got
fig, ax = plt.subplots()
# Need to double-check the old set/get_color_cycle(), too
with warnings.catch_warnings():
warnings.simplefilter("ignore", MatplotlibDeprecationWarning)
prop = next(ax._get_lines.prop_cycler)
ax.set_color_cycle(['c', 'm', 'y', 'k'])
assert prop != next(ax._get_lines.prop_cycler)
ax.set_color_cycle(None)
got = next(ax._get_lines.prop_cycler)
assert prop == got
def test_invalid_input_forms():
fig, ax = plt.subplots()
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle(1)
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle([1, 2])
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle('color', 'fish')
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle('linewidth', 1)
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle('linewidth', {'1': 1, '2': 2})
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle(linewidth=1, color='r')
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle('foobar', [1, 2])
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle(foobar=[1, 2])
with pytest.raises((TypeError, ValueError)):
ax.set_prop_cycle(cycler(foobar=[1, 2]))
with pytest.raises(ValueError):
ax.set_prop_cycle(cycler(color='rgb', c='cmy'))
| 7,921 | 34.524664 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_tightlayout.py | from __future__ import absolute_import, division, print_function
import six
import warnings
import numpy as np
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnchoredOffsetbox, DrawingArea
from matplotlib.patches import Rectangle
def example_plot(ax, fontsize=12):
ax.plot([1, 2])
ax.locator_params(nbins=3)
ax.set_xlabel('x-label', fontsize=fontsize)
ax.set_ylabel('y-label', fontsize=fontsize)
ax.set_title('Title', fontsize=fontsize)
@image_comparison(baseline_images=['tight_layout1'])
def test_tight_layout1():
'Test tight_layout for a single subplot'
fig = plt.figure()
ax = fig.add_subplot(111)
example_plot(ax, fontsize=24)
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout2'])
def test_tight_layout2():
'Test tight_layout for multiple subplots'
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)
example_plot(ax1)
example_plot(ax2)
example_plot(ax3)
example_plot(ax4)
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout3'])
def test_tight_layout3():
'Test tight_layout for multiple subplots'
fig = plt.figure()
ax1 = plt.subplot(221)
ax2 = plt.subplot(223)
ax3 = plt.subplot(122)
example_plot(ax1)
example_plot(ax2)
example_plot(ax3)
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout4'],
freetype_version=('2.5.5', '2.6.1'))
def test_tight_layout4():
'Test tight_layout for subplot2grid'
fig = plt.figure()
ax1 = plt.subplot2grid((3, 3), (0, 0))
ax2 = plt.subplot2grid((3, 3), (0, 1), colspan=2)
ax3 = plt.subplot2grid((3, 3), (1, 0), colspan=2, rowspan=2)
ax4 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)
example_plot(ax1)
example_plot(ax2)
example_plot(ax3)
example_plot(ax4)
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout5'])
def test_tight_layout5():
'Test tight_layout for image'
fig = plt.figure()
ax = plt.subplot(111)
arr = np.arange(100).reshape((10, 10))
ax.imshow(arr, interpolation="none")
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout6'])
def test_tight_layout6():
'Test tight_layout for gridspec'
# This raises warnings since tight layout cannot
# do this fully automatically. But the test is
# correct since the layout is manually edited
with warnings.catch_warnings():
warnings.simplefilter("ignore", UserWarning)
fig = plt.figure()
import matplotlib.gridspec as gridspec
gs1 = gridspec.GridSpec(2, 1)
ax1 = fig.add_subplot(gs1[0])
ax2 = fig.add_subplot(gs1[1])
example_plot(ax1)
example_plot(ax2)
gs1.tight_layout(fig, rect=[0, 0, 0.5, 1])
gs2 = gridspec.GridSpec(3, 1)
for ss in gs2:
ax = fig.add_subplot(ss)
example_plot(ax)
ax.set_title("")
ax.set_xlabel("")
ax.set_xlabel("x-label", fontsize=12)
gs2.tight_layout(fig, rect=[0.5, 0, 1, 1], h_pad=0.45)
top = min(gs1.top, gs2.top)
bottom = max(gs1.bottom, gs2.bottom)
gs1.tight_layout(fig, rect=[None, 0 + (bottom-gs1.bottom),
0.5, 1 - (gs1.top-top)])
gs2.tight_layout(fig, rect=[0.5, 0 + (bottom-gs2.bottom),
None, 1 - (gs2.top-top)],
h_pad=0.45)
@image_comparison(baseline_images=['tight_layout7'])
def test_tight_layout7():
# tight layout with left and right titles
fig = plt.figure()
fontsize = 24
ax = fig.add_subplot(111)
ax.plot([1, 2])
ax.locator_params(nbins=3)
ax.set_xlabel('x-label', fontsize=fontsize)
ax.set_ylabel('y-label', fontsize=fontsize)
ax.set_title('Left Title', loc='left', fontsize=fontsize)
ax.set_title('Right Title', loc='right', fontsize=fontsize)
plt.tight_layout()
@image_comparison(baseline_images=['tight_layout8'])
def test_tight_layout8():
'Test automatic use of tight_layout'
fig = plt.figure()
fig.set_tight_layout({'pad': .1})
ax = fig.add_subplot(111)
example_plot(ax, fontsize=24)
@image_comparison(baseline_images=['tight_layout9'])
def test_tight_layout9():
# Test tight_layout for non-visible suplots
# GH 8244
f, axarr = plt.subplots(2, 2)
axarr[1][1].set_visible(False)
plt.tight_layout()
# The following test is misleading when the text is removed.
@image_comparison(baseline_images=['outward_ticks'], remove_text=False)
def test_outward_ticks():
'Test automatic use of tight_layout'
fig = plt.figure()
ax = fig.add_subplot(221)
ax.xaxis.set_tick_params(tickdir='out', length=16, width=3)
ax.yaxis.set_tick_params(tickdir='out', length=16, width=3)
ax.xaxis.set_tick_params(
tickdir='out', length=32, width=3, tick1On=True, which='minor')
ax.yaxis.set_tick_params(
tickdir='out', length=32, width=3, tick1On=True, which='minor')
# The following minor ticks are not labelled, and they
# are drawn over the major ticks and labels--ugly!
ax.xaxis.set_ticks([0], minor=True)
ax.yaxis.set_ticks([0], minor=True)
ax = fig.add_subplot(222)
ax.xaxis.set_tick_params(tickdir='in', length=32, width=3)
ax.yaxis.set_tick_params(tickdir='in', length=32, width=3)
ax = fig.add_subplot(223)
ax.xaxis.set_tick_params(tickdir='inout', length=32, width=3)
ax.yaxis.set_tick_params(tickdir='inout', length=32, width=3)
ax = fig.add_subplot(224)
ax.xaxis.set_tick_params(tickdir='out', length=32, width=3)
ax.yaxis.set_tick_params(tickdir='out', length=32, width=3)
plt.tight_layout()
def add_offsetboxes(ax, size=10, margin=.1, color='black'):
"""
Surround ax with OffsetBoxes
"""
m, mp = margin, 1+margin
anchor_points = [(-m, -m), (-m, .5), (-m, mp),
(mp, .5), (.5, mp), (mp, mp),
(.5, -m), (mp, -m), (.5, -m)]
for point in anchor_points:
da = DrawingArea(size, size)
background = Rectangle((0, 0), width=size,
height=size,
facecolor=color,
edgecolor='None',
linewidth=0,
antialiased=False)
da.add_artist(background)
anchored_box = AnchoredOffsetbox(
loc=10,
child=da,
pad=0.,
frameon=False,
bbox_to_anchor=point,
bbox_transform=ax.transAxes,
borderpad=0.)
ax.add_artist(anchored_box)
return anchored_box
@image_comparison(baseline_images=['tight_layout_offsetboxes1',
'tight_layout_offsetboxes2'])
def test_tight_layout_offsetboxes():
# 1.
# - Create 4 subplots
# - Plot a diagonal line on them
# - Surround each plot with 7 boxes
# - Use tight_layout
# - See that the squares are included in the tight_layout
# and that the squares in the middle do not overlap
#
# 2.
# - Make the squares around the right side axes invisible
# - See that the invisible squares do not affect the
# tight_layout
rows = cols = 2
colors = ['red', 'blue', 'green', 'yellow']
x = y = [0, 1]
def _subplots():
_, axs = plt.subplots(rows, cols)
axs = axs.flat
for ax, color in zip(axs, colors):
ax.plot(x, y, color=color)
add_offsetboxes(ax, 20, color=color)
return axs
# 1.
axs = _subplots()
plt.tight_layout()
# 2.
axs = _subplots()
for ax in (axs[cols-1::rows]):
for child in ax.get_children():
if isinstance(child, AnchoredOffsetbox):
child.set_visible(False)
plt.tight_layout()
def test_empty_layout():
"""Tests that tight layout doesn't cause an error when there are
no axes.
"""
fig = plt.gcf()
fig.tight_layout()
| 8,117 | 28.52 | 71 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_patches.py | """
Tests specific to the patches module.
"""
from __future__ import absolute_import, division, print_function
import six
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_equal
import pytest
from matplotlib.patches import Polygon
from matplotlib.patches import Rectangle
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.collections as mcollections
from matplotlib import path as mpath
from matplotlib import transforms as mtransforms
import matplotlib.style as mstyle
import sys
on_win = (sys.platform == 'win32')
def test_Polygon_close():
#: Github issue #1018 identified a bug in the Polygon handling
#: of the closed attribute; the path was not getting closed
#: when set_xy was used to set the vertices.
# open set of vertices:
xy = [[0, 0], [0, 1], [1, 1]]
# closed set:
xyclosed = xy + [[0, 0]]
# start with open path and close it:
p = Polygon(xy, closed=True)
assert_array_equal(p.get_xy(), xyclosed)
p.set_xy(xy)
assert_array_equal(p.get_xy(), xyclosed)
# start with closed path and open it:
p = Polygon(xyclosed, closed=False)
assert_array_equal(p.get_xy(), xy)
p.set_xy(xyclosed)
assert_array_equal(p.get_xy(), xy)
# start with open path and leave it open:
p = Polygon(xy, closed=False)
assert_array_equal(p.get_xy(), xy)
p.set_xy(xy)
assert_array_equal(p.get_xy(), xy)
# start with closed path and leave it closed:
p = Polygon(xyclosed, closed=True)
assert_array_equal(p.get_xy(), xyclosed)
p.set_xy(xyclosed)
assert_array_equal(p.get_xy(), xyclosed)
def test_rotate_rect():
loc = np.asarray([1.0, 2.0])
width = 2
height = 3
angle = 30.0
# A rotated rectangle
rect1 = Rectangle(loc, width, height, angle=angle)
# A non-rotated rectangle
rect2 = Rectangle(loc, width, height)
# Set up an explicit rotation matrix (in radians)
angle_rad = np.pi * angle / 180.0
rotation_matrix = np.array([[np.cos(angle_rad), -np.sin(angle_rad)],
[np.sin(angle_rad), np.cos(angle_rad)]])
# Translate to origin, rotate each vertex, and then translate back
new_verts = np.inner(rotation_matrix, rect2.get_verts() - loc).T + loc
# They should be the same
assert_almost_equal(rect1.get_verts(), new_verts)
def test_negative_rect():
# These two rectangles have the same vertices, but starting from a
# different point. (We also drop the last vertex, which is a duplicate.)
pos_vertices = Rectangle((-3, -2), 3, 2).get_verts()[:-1]
neg_vertices = Rectangle((0, 0), -3, -2).get_verts()[:-1]
assert_array_equal(np.roll(neg_vertices, 2, 0), pos_vertices)
@image_comparison(baseline_images=['clip_to_bbox'])
def test_clip_to_bbox():
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_xlim([-18, 20])
ax.set_ylim([-150, 100])
path = mpath.Path.unit_regular_star(8).deepcopy()
path.vertices *= [10, 100]
path.vertices -= [5, 25]
path2 = mpath.Path.unit_circle().deepcopy()
path2.vertices *= [10, 100]
path2.vertices += [10, -25]
combined = mpath.Path.make_compound_path(path, path2)
patch = mpatches.PathPatch(
combined, alpha=0.5, facecolor='coral', edgecolor='none')
ax.add_patch(patch)
bbox = mtransforms.Bbox([[-12, -77.5], [50, -110]])
result_path = combined.clip_to_bbox(bbox)
result_patch = mpatches.PathPatch(
result_path, alpha=0.5, facecolor='green', lw=4, edgecolor='black')
ax.add_patch(result_patch)
@image_comparison(baseline_images=['patch_alpha_coloring'], remove_text=True)
def test_patch_alpha_coloring():
"""
Test checks that the patch and collection are rendered with the specified
alpha values in their facecolor and edgecolor.
"""
star = mpath.Path.unit_regular_star(6)
circle = mpath.Path.unit_circle()
# concatenate the star with an internal cutout of the circle
verts = np.concatenate([circle.vertices, star.vertices[::-1]])
codes = np.concatenate([circle.codes, star.codes])
cut_star1 = mpath.Path(verts, codes)
cut_star2 = mpath.Path(verts + 1, codes)
ax = plt.axes()
patch = mpatches.PathPatch(cut_star1,
linewidth=5, linestyle='dashdot',
facecolor=(1, 0, 0, 0.5),
edgecolor=(0, 0, 1, 0.75))
ax.add_patch(patch)
col = mcollections.PathCollection([cut_star2],
linewidth=5, linestyles='dashdot',
facecolor=(1, 0, 0, 0.5),
edgecolor=(0, 0, 1, 0.75))
ax.add_collection(col)
ax.set_xlim([-1, 2])
ax.set_ylim([-1, 2])
@image_comparison(baseline_images=['patch_alpha_override'], remove_text=True)
def test_patch_alpha_override():
#: Test checks that specifying an alpha attribute for a patch or
#: collection will override any alpha component of the facecolor
#: or edgecolor.
star = mpath.Path.unit_regular_star(6)
circle = mpath.Path.unit_circle()
# concatenate the star with an internal cutout of the circle
verts = np.concatenate([circle.vertices, star.vertices[::-1]])
codes = np.concatenate([circle.codes, star.codes])
cut_star1 = mpath.Path(verts, codes)
cut_star2 = mpath.Path(verts + 1, codes)
ax = plt.axes()
patch = mpatches.PathPatch(cut_star1,
linewidth=5, linestyle='dashdot',
alpha=0.25,
facecolor=(1, 0, 0, 0.5),
edgecolor=(0, 0, 1, 0.75))
ax.add_patch(patch)
col = mcollections.PathCollection([cut_star2],
linewidth=5, linestyles='dashdot',
alpha=0.25,
facecolor=(1, 0, 0, 0.5),
edgecolor=(0, 0, 1, 0.75))
ax.add_collection(col)
ax.set_xlim([-1, 2])
ax.set_ylim([-1, 2])
@pytest.mark.style('default')
def test_patch_color_none():
# Make sure the alpha kwarg does not override 'none' facecolor.
# Addresses issue #7478.
c = plt.Circle((0, 0), 1, facecolor='none', alpha=1)
assert c.get_facecolor()[0] == 0
@image_comparison(baseline_images=['patch_custom_linestyle'],
remove_text=True)
def test_patch_custom_linestyle():
#: A test to check that patches and collections accept custom dash
#: patterns as linestyle and that they display correctly.
star = mpath.Path.unit_regular_star(6)
circle = mpath.Path.unit_circle()
# concatenate the star with an internal cutout of the circle
verts = np.concatenate([circle.vertices, star.vertices[::-1]])
codes = np.concatenate([circle.codes, star.codes])
cut_star1 = mpath.Path(verts, codes)
cut_star2 = mpath.Path(verts + 1, codes)
ax = plt.axes()
patch = mpatches.PathPatch(cut_star1,
linewidth=5, linestyle=(0.0, (5.0, 7.0, 10.0, 7.0)),
facecolor=(1, 0, 0),
edgecolor=(0, 0, 1))
ax.add_patch(patch)
col = mcollections.PathCollection([cut_star2],
linewidth=5, linestyles=[(0.0, (5.0, 7.0, 10.0, 7.0))],
facecolor=(1, 0, 0),
edgecolor=(0, 0, 1))
ax.add_collection(col)
ax.set_xlim([-1, 2])
ax.set_ylim([-1, 2])
def test_patch_linestyle_accents():
#: Test if linestyle can also be specified with short menoics
#: like "--"
#: c.f. Gihub issue #2136
star = mpath.Path.unit_regular_star(6)
circle = mpath.Path.unit_circle()
# concatenate the star with an internal cutout of the circle
verts = np.concatenate([circle.vertices, star.vertices[::-1]])
codes = np.concatenate([circle.codes, star.codes])
linestyles = ["-", "--", "-.", ":",
"solid", "dashed", "dashdot", "dotted"]
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
for i, ls in enumerate(linestyles):
star = mpath.Path(verts + i, codes)
patch = mpatches.PathPatch(star,
linewidth=3, linestyle=ls,
facecolor=(1, 0, 0),
edgecolor=(0, 0, 1))
ax.add_patch(patch)
ax.set_xlim([-1, i + 1])
ax.set_ylim([-1, i + 1])
fig.canvas.draw()
assert True
def test_wedge_movement():
param_dict = {'center': ((0, 0), (1, 1), 'set_center'),
'r': (5, 8, 'set_radius'),
'width': (2, 3, 'set_width'),
'theta1': (0, 30, 'set_theta1'),
'theta2': (45, 50, 'set_theta2')}
init_args = dict((k, v[0]) for (k, v) in six.iteritems(param_dict))
w = mpatches.Wedge(**init_args)
for attr, (old_v, new_v, func) in six.iteritems(param_dict):
assert getattr(w, attr) == old_v
getattr(w, func)(new_v)
assert getattr(w, attr) == new_v
# png needs tol>=0.06, pdf tol>=1.617
@image_comparison(baseline_images=['wedge_range'],
remove_text=True, tol=1.65 if on_win else 0)
def test_wedge_range():
ax = plt.axes()
t1 = 2.313869244286224
args = [[52.31386924, 232.31386924],
[52.313869244286224, 232.31386924428622],
[t1, t1 + 180.0],
[0, 360],
[90, 90 + 360],
[-180, 180],
[0, 380],
[45, 46],
[46, 45]]
for i, (theta1, theta2) in enumerate(args):
x = i % 3
y = i // 3
wedge = mpatches.Wedge((x * 3, y * 3), 1, theta1, theta2,
facecolor='none', edgecolor='k', lw=3)
ax.add_artist(wedge)
ax.set_xlim([-2, 8])
ax.set_ylim([-2, 9])
def test_patch_str():
"""
Check that patches have nice and working `str` representation.
Note that the logic is that `__str__` is defined such that:
str(eval(str(p))) == str(p)
"""
p = mpatches.Circle(xy=(1, 2), radius=3)
assert str(p) == 'Circle(xy=(1, 2), radius=3)'
p = mpatches.Ellipse(xy=(1, 2), width=3, height=4, angle=5)
assert str(p) == 'Ellipse(xy=(1, 2), width=3, height=4, angle=5)'
p = mpatches.Rectangle(xy=(1, 2), width=3, height=4, angle=5)
assert str(p) == 'Rectangle(xy=(1, 2), width=3, height=4, angle=5)'
p = mpatches.Wedge(center=(1, 2), r=3, theta1=4, theta2=5, width=6)
assert str(p) == 'Wedge(center=(1, 2), r=3, theta1=4, theta2=5, width=6)'
p = mpatches.Arc(xy=(1, 2), width=3, height=4, angle=5, theta1=6, theta2=7)
expected = 'Arc(xy=(1, 2), width=3, height=4, angle=5, theta1=6, theta2=7)'
assert str(p) == expected
@image_comparison(baseline_images=['multi_color_hatch'],
remove_text=True, style='default')
def test_multi_color_hatch():
fig, ax = plt.subplots()
rects = ax.bar(range(5), range(1, 6))
for i, rect in enumerate(rects):
rect.set_facecolor('none')
rect.set_edgecolor('C{}'.format(i))
rect.set_hatch('/')
for i in range(5):
with mstyle.context({'hatch.color': 'C{}'.format(i)}):
r = Rectangle((i - .8 / 2, 5), .8, 1, hatch='//', fc='none')
ax.add_patch(r)
@image_comparison(baseline_images=['units_rectangle'], extensions=['png'])
def test_units_rectangle():
import matplotlib.testing.jpl_units as U
U.register()
p = mpatches.Rectangle((5*U.km, 6*U.km), 1*U.km, 2*U.km)
fig, ax = plt.subplots()
ax.add_patch(p)
ax.set_xlim([4*U.km, 7*U.km])
ax.set_ylim([5*U.km, 9*U.km])
@image_comparison(baseline_images=['connection_patch'], extensions=['png'],
style='mpl20', remove_text=True)
def test_connection_patch():
fig, (ax1, ax2) = plt.subplots(1, 2)
con = mpatches.ConnectionPatch(xyA=(0.1, 0.1), xyB=(0.9, 0.9),
coordsA='data', coordsB='data',
axesA=ax2, axesB=ax1,
arrowstyle="->")
ax2.add_artist(con)
def test_datetime_rectangle():
# Check that creating a rectangle with timedeltas doesn't fail
from datetime import datetime, timedelta
start = datetime(2017, 1, 1, 0, 0, 0)
delta = timedelta(seconds=16)
patch = mpatches.Rectangle((start, 0), delta, 1)
fig, ax = plt.subplots()
ax.add_patch(patch)
def test_datetime_datetime_fails():
from datetime import datetime
start = datetime(2017, 1, 1, 0, 0, 0)
dt_delta = datetime(1970, 1, 5) # Will be 5 days if units are done wrong
with pytest.raises(TypeError):
mpatches.Rectangle((start, 0), dt_delta, 1)
with pytest.raises(TypeError):
mpatches.Rectangle((0, start), 1, dt_delta)
def test_contains_point():
ell = mpatches.Ellipse((0.5, 0.5), 0.5, 1.0, 0)
points = [(0.0, 0.5), (0.2, 0.5), (0.25, 0.5), (0.5, 0.5)]
path = ell.get_path()
transform = ell.get_transform()
radius = ell._process_radius(None)
expected = np.array([path.contains_point(point,
transform,
radius) for point in points])
result = np.array([ell.contains_point(point) for point in points])
assert np.all(result == expected)
def test_contains_points():
ell = mpatches.Ellipse((0.5, 0.5), 0.5, 1.0, 0)
points = [(0.0, 0.5), (0.2, 0.5), (0.25, 0.5), (0.5, 0.5)]
path = ell.get_path()
transform = ell.get_transform()
radius = ell._process_radius(None)
expected = path.contains_points(points, transform, radius)
result = ell.contains_points(points)
assert np.all(result == expected)
| 13,849 | 32.535109 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_usetex.py | from __future__ import absolute_import, division, print_function
import pytest
import matplotlib
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
@pytest.mark.skipif(not matplotlib.checkdep_usetex(True),
reason='Missing TeX or Ghostscript or dvipng')
@image_comparison(baseline_images=['test_usetex'],
extensions=['pdf', 'png'],
tol=0.3)
def test_usetex():
matplotlib.rcParams['text.usetex'] = True
fig = plt.figure()
ax = fig.add_subplot(111)
ax.text(0.1, 0.2,
# the \LaTeX macro exercises character sizing and placement,
# \left[ ... \right\} draw some variable-height characters,
# \sqrt and \frac draw horizontal rules, \mathrm changes the font
r'\LaTeX\ $\left[\int\limits_e^{2e}'
r'\sqrt\frac{\log^3 x}{x}\,\mathrm{d}x \right\}$',
fontsize=24)
ax.set_xticks([])
ax.set_yticks([])
| 984 | 34.178571 | 77 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_mathtext.py | from __future__ import absolute_import, division, print_function
import six
import io
import re
import numpy as np
import pytest
import matplotlib
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
from matplotlib import mathtext
math_tests = [
r'$a+b+\dot s+\dot{s}+\ldots$',
r'$x \doteq y$',
r'\$100.00 $\alpha \_$',
r'$\frac{\$100.00}{y}$',
r'$x y$',
r'$x+y\ x=y\ x<y\ x:y\ x,y\ x@y$',
r'$100\%y\ x*y\ x/y x\$y$',
r'$x\leftarrow y\ x\forall y\ x-y$',
r'$x \sf x \bf x {\cal X} \rm x$',
r'$x\ x\,x\;x\quad x\qquad x\!x\hspace{ 0.5 }y$',
r'$\{ \rm braces \}$',
r'$\left[\left\lfloor\frac{5}{\frac{\left(3\right)}{4}} y\right)\right]$',
r'$\left(x\right)$',
r'$\sin(x)$',
r'$x_2$',
r'$x^2$',
r'$x^2_y$',
r'$x_y^2$',
r'$\prod_{i=\alpha_{i+1}}^\infty$',
r'$x = \frac{x+\frac{5}{2}}{\frac{y+3}{8}}$',
r'$dz/dt = \gamma x^2 + {\rm sin}(2\pi y+\phi)$',
r'Foo: $\alpha_{i+1}^j = {\rm sin}(2\pi f_j t_i) e^{-5 t_i/\tau}$',
r'$\mathcal{R}\prod_{i=\alpha_{i+1}}^\infty a_i \sin(2 \pi f x_i)$',
r'Variable $i$ is good',
r'$\Delta_i^j$',
r'$\Delta^j_{i+1}$',
r'$\ddot{o}\acute{e}\grave{e}\hat{O}\breve{\imath}\tilde{n}\vec{q}$',
r"$\arccos((x^i))$",
r"$\gamma = \frac{x=\frac{6}{8}}{y} \delta$",
r'$\limsup_{x\to\infty}$',
r'$\oint^\infty_0$',
r"$f'\quad f'''(x)\quad ''/\mathrm{yr}$",
r'$\frac{x_2888}{y}$',
r"$\sqrt[3]{\frac{X_2}{Y}}=5$",
r"$\sqrt[5]{\prod^\frac{x}{2\pi^2}_\infty}$",
r"$\sqrt[3]{x}=5$",
r'$\frac{X}{\frac{X}{Y}}$',
r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]$",
r'$\mathcal{H} = \int d \tau \left(\epsilon E^2 + \mu H^2\right)$',
r'$\widehat{abc}\widetilde{def}$',
'$\\Gamma \\Delta \\Theta \\Lambda \\Xi \\Pi \\Sigma \\Upsilon \\Phi \\Psi \\Omega$',
'$\\alpha \\beta \\gamma \\delta \\epsilon \\zeta \\eta \\theta \\iota \\lambda \\mu \\nu \\xi \\pi \\kappa \\rho \\sigma \\tau \\upsilon \\phi \\chi \\psi$',
# The examples prefixed by 'mmltt' are from the MathML torture test here:
# http://www.mozilla.org/projects/mathml/demo/texvsmml.xhtml
r'${x}^{2}{y}^{2}$',
r'${}_{2}F_{3}$',
r'$\frac{x+{y}^{2}}{k+1}$',
r'$x+{y}^{\frac{2}{k+1}}$',
r'$\frac{a}{b/2}$',
r'${a}_{0}+\frac{1}{{a}_{1}+\frac{1}{{a}_{2}+\frac{1}{{a}_{3}+\frac{1}{{a}_{4}}}}}$',
r'${a}_{0}+\frac{1}{{a}_{1}+\frac{1}{{a}_{2}+\frac{1}{{a}_{3}+\frac{1}{{a}_{4}}}}}$',
r'$\binom{n}{k/2}$',
r'$\binom{p}{2}{x}^{2}{y}^{p-2}-\frac{1}{1-x}\frac{1}{1-{x}^{2}}$',
r'${x}^{2y}$',
r'$\sum _{i=1}^{p}\sum _{j=1}^{q}\sum _{k=1}^{r}{a}_{ij}{b}_{jk}{c}_{ki}$',
r'$\sqrt{1+\sqrt{1+\sqrt{1+\sqrt{1+\sqrt{1+\sqrt{1+\sqrt{1+x}}}}}}}$',
r'$\left(\frac{{\partial }^{2}}{\partial {x}^{2}}+\frac{{\partial }^{2}}{\partial {y}^{2}}\right){|\varphi \left(x+iy\right)|}^{2}=0$',
r'${2}^{{2}^{{2}^{x}}}$',
r'${\int }_{1}^{x}\frac{\mathrm{dt}}{t}$',
r'$\int {\int }_{D}\mathrm{dx} \mathrm{dy}$',
# mathtex doesn't support array
# 'mmltt18' : r'$f\left(x\right)=\left\{\begin{array}{cc}\hfill 1/3\hfill & \text{if_}0\le x\le 1;\hfill \\ \hfill 2/3\hfill & \hfill \text{if_}3\le x\le 4;\hfill \\ \hfill 0\hfill & \text{elsewhere.}\hfill \end{array}$',
# mathtex doesn't support stackrel
# 'mmltt19' : ur'$\stackrel{\stackrel{k\text{times}}{\ufe37}}{x+...+x}$',
r'${y}_{{x}^{2}}$',
# mathtex doesn't support the "\text" command
# 'mmltt21' : r'$\sum _{p\text{\prime}}f\left(p\right)={\int }_{t>1}f\left(t\right) d\pi \left(t\right)$',
# mathtex doesn't support array
# 'mmltt23' : r'$\left(\begin{array}{cc}\hfill \left(\begin{array}{cc}\hfill a\hfill & \hfill b\hfill \\ \hfill c\hfill & \hfill d\hfill \end{array}\right)\hfill & \hfill \left(\begin{array}{cc}\hfill e\hfill & \hfill f\hfill \\ \hfill g\hfill & \hfill h\hfill \end{array}\right)\hfill \\ \hfill 0\hfill & \hfill \left(\begin{array}{cc}\hfill i\hfill & \hfill j\hfill \\ \hfill k\hfill & \hfill l\hfill \end{array}\right)\hfill \end{array}\right)$',
# mathtex doesn't support array
# 'mmltt24' : u'$det|\\begin{array}{ccccc}\\hfill {c}_{0}\\hfill & \\hfill {c}_{1}\\hfill & \\hfill {c}_{2}\\hfill & \\hfill \\dots \\hfill & \\hfill {c}_{n}\\hfill \\\\ \\hfill {c}_{1}\\hfill & \\hfill {c}_{2}\\hfill & \\hfill {c}_{3}\\hfill & \\hfill \\dots \\hfill & \\hfill {c}_{n+1}\\hfill \\\\ \\hfill {c}_{2}\\hfill & \\hfill {c}_{3}\\hfill & \\hfill {c}_{4}\\hfill & \\hfill \\dots \\hfill & \\hfill {c}_{n+2}\\hfill \\\\ \\hfill \\u22ee\\hfill & \\hfill \\u22ee\\hfill & \\hfill \\u22ee\\hfill & \\hfill \\hfill & \\hfill \\u22ee\\hfill \\\\ \\hfill {c}_{n}\\hfill & \\hfill {c}_{n+1}\\hfill & \\hfill {c}_{n+2}\\hfill & \\hfill \\dots \\hfill & \\hfill {c}_{2n}\\hfill \\end{array}|>0$',
r'${y}_{{x}_{2}}$',
r'${x}_{92}^{31415}+\pi $',
r'${x}_{{y}_{b}^{a}}^{{z}_{c}^{d}}$',
r'${y}_{3}^{\prime \prime \prime }$',
r"$\left( \xi \left( 1 - \xi \right) \right)$", # Bug 2969451
r"$\left(2 \, a=b\right)$", # Sage bug #8125
r"$? ! &$", # github issue #466
r'$\operatorname{cos} x$', # github issue #553
r'$\sum _{\genfrac{}{}{0}{}{0\leq i\leq m}{0<j<n}}P\left(i,j\right)$',
r"$\left\Vert a \right\Vert \left\vert b \right\vert \left| a \right| \left\| b\right\| \Vert a \Vert \vert b \vert$",
r'$\mathring{A} \stackrel{\circ}{A} \AA$',
r'$M \, M \thinspace M \/ M \> M \: M \; M \ M \enspace M \quad M \qquad M \! M$',
r'$\Cup$ $\Cap$ $\leftharpoonup$ $\barwedge$ $\rightharpoonup$',
r'$\dotplus$ $\doteq$ $\doteqdot$ $\ddots$',
r'$xyz^kx_kx^py^{p-2} d_i^jb_jc_kd x^j_i E^0 E^0_u$', # github issue #4873
r'${xyz}^k{x}_{k}{x}^{p}{y}^{p-2} {d}_{i}^{j}{b}_{j}{c}_{k}{d} {x}^{j}_{i}{E}^{0}{E}^0_u$',
r'${\int}_x^x x\oint_x^x x\int_{X}^{X}x\int_x x \int^x x \int_{x} x\int^{x}{\int}_{x} x{\int}^{x}_{x}x$',
r'testing$^{123}$',
' '.join('$\\' + p + '$' for p in sorted(mathtext.Parser._snowflake)),
r'$6-2$; $-2$; $ -2$; ${-2}$; ${ -2}$; $20^{+3}_{-2}$',
r'$\overline{\omega}^x \frac{1}{2}_0^x$', # github issue #5444
r'$,$ $.$ $1{,}234{, }567{ , }890$ and $1,234,567,890$', # github issue 5799
r'$\left(X\right)_{a}^{b}$', # github issue 7615
r'$\dfrac{\$100.00}{y}$', # github issue #1888
]
digits = "0123456789"
uppercase = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
lowercase = "abcdefghijklmnopqrstuvwxyz"
uppergreek = ("\\Gamma \\Delta \\Theta \\Lambda \\Xi \\Pi \\Sigma \\Upsilon \\Phi \\Psi "
"\\Omega")
lowergreek = ("\\alpha \\beta \\gamma \\delta \\epsilon \\zeta \\eta \\theta \\iota "
"\\lambda \\mu \\nu \\xi \\pi \\kappa \\rho \\sigma \\tau \\upsilon "
"\\phi \\chi \\psi")
all = [digits, uppercase, lowercase, uppergreek, lowergreek]
font_test_specs = [
([], all),
(['mathrm'], all),
(['mathbf'], all),
(['mathit'], all),
(['mathtt'], [digits, uppercase, lowercase]),
(['mathcircled'], [digits, uppercase, lowercase]),
(['mathrm', 'mathcircled'], [digits, uppercase, lowercase]),
(['mathbf', 'mathcircled'], [digits, uppercase, lowercase]),
(['mathbb'], [digits, uppercase, lowercase,
r'\Gamma \Pi \Sigma \gamma \pi']),
(['mathrm', 'mathbb'], [digits, uppercase, lowercase,
r'\Gamma \Pi \Sigma \gamma \pi']),
(['mathbf', 'mathbb'], [digits, uppercase, lowercase,
r'\Gamma \Pi \Sigma \gamma \pi']),
(['mathcal'], [uppercase]),
(['mathfrak'], [uppercase, lowercase]),
(['mathbf', 'mathfrak'], [uppercase, lowercase]),
(['mathscr'], [uppercase, lowercase]),
(['mathsf'], [digits, uppercase, lowercase]),
(['mathrm', 'mathsf'], [digits, uppercase, lowercase]),
(['mathbf', 'mathsf'], [digits, uppercase, lowercase])
]
font_tests = []
for fonts, chars in font_test_specs:
wrapper = [' '.join(fonts), ' $']
for font in fonts:
wrapper.append(r'\%s{' % font)
wrapper.append('%s')
for font in fonts:
wrapper.append('}')
wrapper.append('$')
wrapper = ''.join(wrapper)
for set in chars:
font_tests.append(wrapper % set)
@pytest.fixture
def baseline_images(request, fontset, index):
return ['%s_%s_%02d' % (request.param, fontset, index)]
@pytest.mark.parametrize('index, test', enumerate(math_tests),
ids=[str(index) for index in range(len(math_tests))])
@pytest.mark.parametrize('fontset',
['cm', 'stix', 'stixsans', 'dejavusans',
'dejavuserif'])
@pytest.mark.parametrize('baseline_images', ['mathtext'], indirect=True)
@image_comparison(baseline_images=None)
def test_mathtext_rendering(baseline_images, fontset, index, test):
matplotlib.rcParams['mathtext.fontset'] = fontset
fig = plt.figure(figsize=(5.25, 0.75))
fig.text(0.5, 0.5, test,
horizontalalignment='center', verticalalignment='center')
@pytest.mark.parametrize('index, test', enumerate(font_tests),
ids=[str(index) for index in range(len(font_tests))])
@pytest.mark.parametrize('fontset',
['cm', 'stix', 'stixsans', 'dejavusans',
'dejavuserif'])
@pytest.mark.parametrize('baseline_images', ['mathfont'], indirect=True)
@image_comparison(baseline_images=None, extensions=['png'])
def test_mathfont_rendering(baseline_images, fontset, index, test):
matplotlib.rcParams['mathtext.fontset'] = fontset
fig = plt.figure(figsize=(5.25, 0.75))
fig.text(0.5, 0.5, test,
horizontalalignment='center', verticalalignment='center')
def test_fontinfo():
import matplotlib.font_manager as font_manager
import matplotlib.ft2font as ft2font
fontpath = font_manager.findfont("DejaVu Sans")
font = ft2font.FT2Font(fontpath)
table = font.get_sfnt_table("head")
assert table['version'] == (1, 0)
@pytest.mark.parametrize(
'math, msg',
[
(r'$\hspace{}$', r'Expected \hspace{n}'),
(r'$\hspace{foo}$', r'Expected \hspace{n}'),
(r'$\frac$', r'Expected \frac{num}{den}'),
(r'$\frac{}{}$', r'Expected \frac{num}{den}'),
(r'$\stackrel$', r'Expected \stackrel{num}{den}'),
(r'$\stackrel{}{}$', r'Expected \stackrel{num}{den}'),
(r'$\binom$', r'Expected \binom{num}{den}'),
(r'$\binom{}{}$', r'Expected \binom{num}{den}'),
(r'$\genfrac$',
r'Expected \genfrac{ldelim}{rdelim}{rulesize}{style}{num}{den}'),
(r'$\genfrac{}{}{}{}{}{}$',
r'Expected \genfrac{ldelim}{rdelim}{rulesize}{style}{num}{den}'),
(r'$\sqrt$', r'Expected \sqrt{value}'),
(r'$\sqrt f$', r'Expected \sqrt{value}'),
(r'$\overline$', r'Expected \overline{value}'),
(r'$\overline{}$', r'Expected \overline{value}'),
(r'$\leftF$', r'Expected a delimiter'),
(r'$\rightF$', r'Unknown symbol: \rightF'),
(r'$\left(\right$', r'Expected a delimiter'),
(r'$\left($', r'Expected "\right"'),
(r'$\dfrac$', r'Expected \dfrac{num}{den}'),
(r'$\dfrac{}{}$', r'Expected \dfrac{num}{den}'),
],
ids=[
'hspace without value',
'hspace with invalid value',
'frac without parameters',
'frac with empty parameters',
'stackrel without parameters',
'stackrel with empty parameters',
'binom without parameters',
'binom with empty parameters',
'genfrac without parameters',
'genfrac with empty parameters',
'sqrt without parameters',
'sqrt with invalid value',
'overline without parameters',
'overline with empty parameter',
'left with invalid delimiter',
'right with invalid delimiter',
'unclosed parentheses with sizing',
'unclosed parentheses without sizing',
'dfrac without parameters',
'dfrac with empty parameters',
]
)
def test_mathtext_exceptions(math, msg):
parser = mathtext.MathTextParser('agg')
with pytest.raises(ValueError) as excinfo:
parser.parse(math)
excinfo.match(re.escape(msg))
def test_single_minus_sign():
plt.figure(figsize=(0.3, 0.3))
plt.text(0.5, 0.5, '$-$')
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.gca().set_xticks([])
plt.gca().set_yticks([])
buff = io.BytesIO()
plt.savefig(buff, format="rgba", dpi=1000)
array = np.fromstring(buff.getvalue(), dtype=np.uint8)
# If this fails, it would be all white
assert not np.all(array == 0xff)
| 12,837 | 45.179856 | 703 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_pdf.py | # -*- encoding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import six
import io
import os
import sys
import tempfile
import numpy as np
import pytest
from matplotlib import dviread, pyplot as plt, checkdep_usetex, rcParams
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.testing.compare import compare_images
from matplotlib.testing.decorators import image_comparison
from matplotlib.testing.determinism import (_determinism_source_date_epoch,
_determinism_check)
needs_usetex = pytest.mark.xfail(
not checkdep_usetex(True),
reason="This test needs a TeX installation")
@image_comparison(baseline_images=['pdf_use14corefonts'],
extensions=['pdf'])
def test_use14corefonts():
rcParams['pdf.use14corefonts'] = True
rcParams['font.family'] = 'sans-serif'
rcParams['font.size'] = 8
rcParams['font.sans-serif'] = ['Helvetica']
rcParams['pdf.compression'] = 0
text = u'''A three-line text positioned just above a blue line
and containing some French characters and the euro symbol:
"Merci pépé pour les 10 €"'''
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_title('Test PDF backend with option use14corefonts=True')
ax.text(0.5, 0.5, text, horizontalalignment='center',
verticalalignment='bottom',
fontsize=14)
ax.axhline(0.5, linewidth=0.5)
def test_type42():
rcParams['pdf.fonttype'] = 42
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1, 2, 3])
fig.savefig(io.BytesIO())
def test_multipage_pagecount():
with PdfPages(io.BytesIO()) as pdf:
assert pdf.get_pagecount() == 0
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1, 2, 3])
fig.savefig(pdf, format="pdf")
assert pdf.get_pagecount() == 1
pdf.savefig()
assert pdf.get_pagecount() == 2
def test_multipage_properfinalize():
pdfio = io.BytesIO()
with PdfPages(pdfio) as pdf:
for i in range(10):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_title('This is a long title')
fig.savefig(pdf, format="pdf")
pdfio.seek(0)
assert sum(b'startxref' in line for line in pdfio) == 1
assert sys.getsizeof(pdfio) < 40000
def test_multipage_keep_empty():
from matplotlib.backends.backend_pdf import PdfPages
from tempfile import NamedTemporaryFile
# test empty pdf files
# test that an empty pdf is left behind with keep_empty=True (default)
with NamedTemporaryFile(delete=False) as tmp:
with PdfPages(tmp) as pdf:
filename = pdf._file.fh.name
assert os.path.exists(filename)
os.remove(filename)
# test if an empty pdf is deleting itself afterwards with keep_empty=False
with PdfPages(filename, keep_empty=False) as pdf:
pass
assert not os.path.exists(filename)
# test pdf files with content, they should never be deleted
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([1, 2, 3])
# test that a non-empty pdf is left behind with keep_empty=True (default)
with NamedTemporaryFile(delete=False) as tmp:
with PdfPages(tmp) as pdf:
filename = pdf._file.fh.name
pdf.savefig()
assert os.path.exists(filename)
os.remove(filename)
# test that a non-empty pdf is left behind with keep_empty=False
with NamedTemporaryFile(delete=False) as tmp:
with PdfPages(tmp, keep_empty=False) as pdf:
filename = pdf._file.fh.name
pdf.savefig()
assert os.path.exists(filename)
os.remove(filename)
def test_composite_image():
# Test that figures can be saved with and without combining multiple images
# (on a single set of axes) into a single composite image.
X, Y = np.meshgrid(np.arange(-5, 5, 1), np.arange(-5, 5, 1))
Z = np.sin(Y ** 2)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_xlim(0, 3)
ax.imshow(Z, extent=[0, 1, 0, 1])
ax.imshow(Z[::-1], extent=[2, 3, 0, 1])
plt.rcParams['image.composite_image'] = True
with PdfPages(io.BytesIO()) as pdf:
fig.savefig(pdf, format="pdf")
assert len(pdf._file._images) == 1
plt.rcParams['image.composite_image'] = False
with PdfPages(io.BytesIO()) as pdf:
fig.savefig(pdf, format="pdf")
assert len(pdf._file._images) == 2
@pytest.mark.skipif(sys.version_info < (3, 6), reason="requires Python 3.6+")
def test_pdfpages_fspath():
from pathlib import Path
with PdfPages(Path(os.devnull)) as pdf:
pdf.savefig(plt.figure())
def test_source_date_epoch():
"""Test SOURCE_DATE_EPOCH support for PDF output"""
_determinism_source_date_epoch("pdf", b"/CreationDate (D:20000101000000Z)")
def test_determinism_plain():
"""Test for reproducible PDF output: simple figure"""
_determinism_check('', format="pdf")
def test_determinism_images():
"""Test for reproducible PDF output: figure with different images"""
_determinism_check('i', format="pdf")
def test_determinism_hatches():
"""Test for reproducible PDF output: figure with different hatches"""
_determinism_check('h', format="pdf")
def test_determinism_markers():
"""Test for reproducible PDF output: figure with different markers"""
_determinism_check('m', format="pdf")
def test_determinism_all():
"""Test for reproducible PDF output"""
_determinism_check(format="pdf")
@image_comparison(baseline_images=['hatching_legend'],
extensions=['pdf'])
def test_hatching_legend():
"""Test for correct hatching on patches in legend"""
fig = plt.figure(figsize=(1, 2))
a = plt.Rectangle([0, 0], 0, 0, facecolor="green", hatch="XXXX")
b = plt.Rectangle([0, 0], 0, 0, facecolor="blue", hatch="XXXX")
fig.legend([a, b, a, b], ["", "", "", ""])
@image_comparison(baseline_images=['grayscale_alpha'],
extensions=['pdf'])
def test_grayscale_alpha():
"""Masking images with NaN did not work for grayscale images"""
x, y = np.ogrid[-2:2:.1, -2:2:.1]
dd = np.exp(-(x**2 + y**2))
dd[dd < .1] = np.nan
fig, ax = plt.subplots()
ax.imshow(dd, interpolation='none', cmap='gray_r')
ax.set_xticks([])
ax.set_yticks([])
# This tests tends to hit a TeX cache lock on AppVeyor.
@pytest.mark.flaky(reruns=3)
@needs_usetex
def test_missing_psfont(monkeypatch):
"""An error is raised if a TeX font lacks a Type-1 equivalent"""
def psfont(*args, **kwargs):
return dviread.PsFont(texname='texfont', psname='Some Font',
effects=None, encoding=None, filename=None)
monkeypatch.setattr(dviread.PsfontsMap, '__getitem__', psfont)
rcParams['text.usetex'] = True
fig, ax = plt.subplots()
ax.text(0.5, 0.5, 'hello')
with tempfile.TemporaryFile() as tmpfile, pytest.raises(ValueError):
fig.savefig(tmpfile, format='pdf')
@pytest.mark.style('default')
def test_pdf_savefig_when_color_is_none(tmpdir):
fig, ax = plt.subplots()
plt.axis('off')
ax.plot(np.sin(np.linspace(-5, 5, 100)), 'v', c='none')
actual_image = tmpdir.join('figure.pdf')
expected_image = tmpdir.join('figure.eps')
fig.savefig(str(actual_image), format='pdf')
fig.savefig(str(expected_image), format='eps')
result = compare_images(str(actual_image), str(expected_image), 0)
assert result is None
@needs_usetex
def test_failing_latex(tmpdir):
"""Test failing latex subprocess call"""
path = str(tmpdir.join("tmpoutput.pdf"))
rcParams['text.usetex'] = True
# This fails with "Double subscript"
plt.xlabel("$22_2_2$")
with pytest.raises(RuntimeError):
plt.savefig(path)
| 7,811 | 31.414938 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_bases.py | from matplotlib.backend_bases import FigureCanvasBase
from matplotlib.backend_bases import RendererBase
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import matplotlib.path as path
import numpy as np
import os
import shutil
import tempfile
def test_uses_per_path():
id = transforms.Affine2D()
paths = [path.Path.unit_regular_polygon(i) for i in range(3, 7)]
tforms = [id.rotate(i) for i in range(1, 5)]
offsets = np.arange(20).reshape((10, 2))
facecolors = ['red', 'green']
edgecolors = ['red', 'green']
def check(master_transform, paths, all_transforms,
offsets, facecolors, edgecolors):
rb = RendererBase()
raw_paths = list(rb._iter_collection_raw_paths(
master_transform, paths, all_transforms))
gc = rb.new_gc()
ids = [path_id for xo, yo, path_id, gc0, rgbFace in
rb._iter_collection(gc, master_transform, all_transforms,
range(len(raw_paths)), offsets,
transforms.IdentityTransform(),
facecolors, edgecolors, [], [], [False],
[], 'data')]
uses = rb._iter_collection_uses_per_path(
paths, all_transforms, offsets, facecolors, edgecolors)
if raw_paths:
seen = np.bincount(ids, minlength=len(raw_paths))
assert set(seen).issubset([uses - 1, uses])
check(id, paths, tforms, offsets, facecolors, edgecolors)
check(id, paths[0:1], tforms, offsets, facecolors, edgecolors)
check(id, [], tforms, offsets, facecolors, edgecolors)
check(id, paths, tforms[0:1], offsets, facecolors, edgecolors)
check(id, paths, [], offsets, facecolors, edgecolors)
for n in range(0, offsets.shape[0]):
check(id, paths, tforms, offsets[0:n, :], facecolors, edgecolors)
check(id, paths, tforms, offsets, [], edgecolors)
check(id, paths, tforms, offsets, facecolors, [])
check(id, paths, tforms, offsets, [], [])
check(id, paths, tforms, offsets, facecolors[0:1], edgecolors)
def test_get_default_filename():
try:
test_dir = tempfile.mkdtemp()
plt.rcParams['savefig.directory'] = test_dir
fig = plt.figure()
canvas = FigureCanvasBase(fig)
filename = canvas.get_default_filename()
assert filename == 'image.png'
finally:
shutil.rmtree(test_dir)
def test_get_default_filename_already_exists():
# From #3068: Suggest non-existing default filename
try:
test_dir = tempfile.mkdtemp()
plt.rcParams['savefig.directory'] = test_dir
fig = plt.figure()
canvas = FigureCanvasBase(fig)
# create 'image.png' in figure's save dir
open(os.path.join(test_dir, 'image.png'), 'w').close()
filename = canvas.get_default_filename()
assert filename == 'image-1.png'
finally:
shutil.rmtree(test_dir)
| 2,983 | 36.3 | 75 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_triangulation.py | from __future__ import absolute_import, division, print_function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
import pytest
from numpy.testing import assert_array_equal, assert_array_almost_equal,\
assert_array_less
import numpy.ma.testutils as matest
from matplotlib.testing.decorators import image_comparison
import matplotlib.cm as cm
from matplotlib.path import Path
import sys
on_win = (sys.platform == 'win32')
def test_delaunay():
# No duplicate points, regular grid.
nx = 5
ny = 4
x, y = np.meshgrid(np.linspace(0.0, 1.0, nx), np.linspace(0.0, 1.0, ny))
x = x.ravel()
y = y.ravel()
npoints = nx*ny
ntriangles = 2 * (nx-1) * (ny-1)
nedges = 3*nx*ny - 2*nx - 2*ny + 1
# Create delaunay triangulation.
triang = mtri.Triangulation(x, y)
# The tests in the remainder of this function should be passed by any
# triangulation that does not contain duplicate points.
# Points - floating point.
assert_array_almost_equal(triang.x, x)
assert_array_almost_equal(triang.y, y)
# Triangles - integers.
assert len(triang.triangles) == ntriangles
assert np.min(triang.triangles) == 0
assert np.max(triang.triangles) == npoints-1
# Edges - integers.
assert len(triang.edges) == nedges
assert np.min(triang.edges) == 0
assert np.max(triang.edges) == npoints-1
# Neighbors - integers.
# Check that neighbors calculated by C++ triangulation class are the same
# as those returned from delaunay routine.
neighbors = triang.neighbors
triang._neighbors = None
assert_array_equal(triang.neighbors, neighbors)
# Is each point used in at least one triangle?
assert_array_equal(np.unique(triang.triangles), np.arange(npoints))
def test_delaunay_duplicate_points():
# x[duplicate] == x[duplicate_of]
# y[duplicate] == y[duplicate_of]
npoints = 10
duplicate = 7
duplicate_of = 3
np.random.seed(23)
x = np.random.random((npoints))
y = np.random.random((npoints))
x[duplicate] = x[duplicate_of]
y[duplicate] = y[duplicate_of]
# Create delaunay triangulation.
triang = mtri.Triangulation(x, y)
# Duplicate points should be ignored, so the index of the duplicate points
# should not appear in any triangle.
assert_array_equal(np.unique(triang.triangles),
np.delete(np.arange(npoints), duplicate))
def test_delaunay_points_in_line():
# Cannot triangulate points that are all in a straight line, but check
# that delaunay code fails gracefully.
x = np.linspace(0.0, 10.0, 11)
y = np.linspace(0.0, 10.0, 11)
with pytest.raises(RuntimeError):
mtri.Triangulation(x, y)
# Add an extra point not on the line and the triangulation is OK.
x = np.append(x, 2.0)
y = np.append(y, 8.0)
triang = mtri.Triangulation(x, y)
@pytest.mark.parametrize('x, y', [
# Triangulation should raise a ValueError if passed less than 3 points.
([], []),
([1], [5]),
([1, 2], [5, 6]),
# Triangulation should also raise a ValueError if passed duplicate points
# such that there are less than 3 unique points.
([1, 2, 1], [5, 6, 5]),
([1, 2, 2], [5, 6, 6]),
([1, 1, 1, 2, 1, 2], [5, 5, 5, 6, 5, 6]),
])
def test_delaunay_insufficient_points(x, y):
with pytest.raises(ValueError):
mtri.Triangulation(x, y)
def test_delaunay_robust():
# Fails when mtri.Triangulation uses matplotlib.delaunay, works when using
# qhull.
tri_points = np.array([
[0.8660254037844384, -0.5000000000000004],
[0.7577722283113836, -0.5000000000000004],
[0.6495190528383288, -0.5000000000000003],
[0.5412658773652739, -0.5000000000000003],
[0.811898816047911, -0.40625000000000044],
[0.7036456405748561, -0.4062500000000004],
[0.5953924651018013, -0.40625000000000033]])
test_points = np.asarray([
[0.58, -0.46],
[0.65, -0.46],
[0.65, -0.42],
[0.7, -0.48],
[0.7, -0.44],
[0.75, -0.44],
[0.8, -0.48]])
# Utility function that indicates if a triangle defined by 3 points
# (xtri, ytri) contains the test point xy. Avoid calling with a point that
# lies on or very near to an edge of the triangle.
def tri_contains_point(xtri, ytri, xy):
tri_points = np.vstack((xtri, ytri)).T
return Path(tri_points).contains_point(xy)
# Utility function that returns how many triangles of the specified
# triangulation contain the test point xy. Avoid calling with a point that
# lies on or very near to an edge of any triangle in the triangulation.
def tris_contain_point(triang, xy):
count = 0
for tri in triang.triangles:
if tri_contains_point(triang.x[tri], triang.y[tri], xy):
count += 1
return count
# Using matplotlib.delaunay, an invalid triangulation is created with
# overlapping triangles; qhull is OK.
triang = mtri.Triangulation(tri_points[:, 0], tri_points[:, 1])
for test_point in test_points:
assert tris_contain_point(triang, test_point) == 1
# If ignore the first point of tri_points, matplotlib.delaunay throws a
# KeyError when calculating the convex hull; qhull is OK.
triang = mtri.Triangulation(tri_points[1:, 0], tri_points[1:, 1])
@image_comparison(baseline_images=['tripcolor1'], extensions=['png'])
def test_tripcolor():
x = np.asarray([0, 0.5, 1, 0, 0.5, 1, 0, 0.5, 1, 0.75])
y = np.asarray([0, 0, 0, 0.5, 0.5, 0.5, 1, 1, 1, 0.75])
triangles = np.asarray([
[0, 1, 3], [1, 4, 3],
[1, 2, 4], [2, 5, 4],
[3, 4, 6], [4, 7, 6],
[4, 5, 9], [7, 4, 9], [8, 7, 9], [5, 8, 9]])
# Triangulation with same number of points and triangles.
triang = mtri.Triangulation(x, y, triangles)
Cpoints = x + 0.5*y
xmid = x[triang.triangles].mean(axis=1)
ymid = y[triang.triangles].mean(axis=1)
Cfaces = 0.5*xmid + ymid
plt.subplot(121)
plt.tripcolor(triang, Cpoints, edgecolors='k')
plt.title('point colors')
plt.subplot(122)
plt.tripcolor(triang, facecolors=Cfaces, edgecolors='k')
plt.title('facecolors')
def test_no_modify():
# Test that Triangulation does not modify triangles array passed to it.
triangles = np.array([[3, 2, 0], [3, 1, 0]], dtype=np.int32)
points = np.array([(0, 0), (0, 1.1), (1, 0), (1, 1)])
old_triangles = triangles.copy()
tri = mtri.Triangulation(points[:, 0], points[:, 1], triangles)
edges = tri.edges
assert_array_equal(old_triangles, triangles)
def test_trifinder():
# Test points within triangles of masked triangulation.
x, y = np.meshgrid(np.arange(4), np.arange(4))
x = x.ravel()
y = y.ravel()
triangles = [[0, 1, 4], [1, 5, 4], [1, 2, 5], [2, 6, 5], [2, 3, 6],
[3, 7, 6], [4, 5, 8], [5, 9, 8], [5, 6, 9], [6, 10, 9],
[6, 7, 10], [7, 11, 10], [8, 9, 12], [9, 13, 12], [9, 10, 13],
[10, 14, 13], [10, 11, 14], [11, 15, 14]]
mask = np.zeros(len(triangles))
mask[8:10] = 1
triang = mtri.Triangulation(x, y, triangles, mask)
trifinder = triang.get_trifinder()
xs = [0.25, 1.25, 2.25, 3.25]
ys = [0.25, 1.25, 2.25, 3.25]
xs, ys = np.meshgrid(xs, ys)
xs = xs.ravel()
ys = ys.ravel()
tris = trifinder(xs, ys)
assert_array_equal(tris, [0, 2, 4, -1, 6, -1, 10, -1,
12, 14, 16, -1, -1, -1, -1, -1])
tris = trifinder(xs-0.5, ys-0.5)
assert_array_equal(tris, [-1, -1, -1, -1, -1, 1, 3, 5,
-1, 7, -1, 11, -1, 13, 15, 17])
# Test points exactly on boundary edges of masked triangulation.
xs = [0.5, 1.5, 2.5, 0.5, 1.5, 2.5, 1.5, 1.5, 0.0, 1.0, 2.0, 3.0]
ys = [0.0, 0.0, 0.0, 3.0, 3.0, 3.0, 1.0, 2.0, 1.5, 1.5, 1.5, 1.5]
tris = trifinder(xs, ys)
assert_array_equal(tris, [0, 2, 4, 13, 15, 17, 3, 14, 6, 7, 10, 11])
# Test points exactly on boundary corners of masked triangulation.
xs = [0.0, 3.0]
ys = [0.0, 3.0]
tris = trifinder(xs, ys)
assert_array_equal(tris, [0, 17])
#
# Test triangles with horizontal colinear points. These are not valid
# triangulations, but we try to deal with the simplest violations.
#
# If +ve, triangulation is OK, if -ve triangulation invalid,
# if zero have colinear points but should pass tests anyway.
delta = 0.0
x = [1.5, 0, 1, 2, 3, 1.5, 1.5]
y = [-1, 0, 0, 0, 0, delta, 1]
triangles = [[0, 2, 1], [0, 3, 2], [0, 4, 3], [1, 2, 5], [2, 3, 5],
[3, 4, 5], [1, 5, 6], [4, 6, 5]]
triang = mtri.Triangulation(x, y, triangles)
trifinder = triang.get_trifinder()
xs = [-0.1, 0.4, 0.9, 1.4, 1.9, 2.4, 2.9]
ys = [-0.1, 0.1]
xs, ys = np.meshgrid(xs, ys)
tris = trifinder(xs, ys)
assert_array_equal(tris, [[-1, 0, 0, 1, 1, 2, -1],
[-1, 6, 6, 6, 7, 7, -1]])
#
# Test triangles with vertical colinear points. These are not valid
# triangulations, but we try to deal with the simplest violations.
#
# If +ve, triangulation is OK, if -ve triangulation invalid,
# if zero have colinear points but should pass tests anyway.
delta = 0.0
x = [-1, -delta, 0, 0, 0, 0, 1]
y = [1.5, 1.5, 0, 1, 2, 3, 1.5]
triangles = [[0, 1, 2], [0, 1, 5], [1, 2, 3], [1, 3, 4], [1, 4, 5],
[2, 6, 3], [3, 6, 4], [4, 6, 5]]
triang = mtri.Triangulation(x, y, triangles)
trifinder = triang.get_trifinder()
xs = [-0.1, 0.1]
ys = [-0.1, 0.4, 0.9, 1.4, 1.9, 2.4, 2.9]
xs, ys = np.meshgrid(xs, ys)
tris = trifinder(xs, ys)
assert_array_equal(tris, [[-1, -1], [0, 5], [0, 5], [0, 6], [1, 6], [1, 7],
[-1, -1]])
# Test that changing triangulation by setting a mask causes the trifinder
# to be reinitialised.
x = [0, 1, 0, 1]
y = [0, 0, 1, 1]
triangles = [[0, 1, 2], [1, 3, 2]]
triang = mtri.Triangulation(x, y, triangles)
trifinder = triang.get_trifinder()
xs = [-0.2, 0.2, 0.8, 1.2]
ys = [0.5, 0.5, 0.5, 0.5]
tris = trifinder(xs, ys)
assert_array_equal(tris, [-1, 0, 1, -1])
triang.set_mask([1, 0])
assert trifinder == triang.get_trifinder()
tris = trifinder(xs, ys)
assert_array_equal(tris, [-1, -1, 1, -1])
def test_triinterp():
# Test points within triangles of masked triangulation.
x, y = np.meshgrid(np.arange(4), np.arange(4))
x = x.ravel()
y = y.ravel()
z = 1.23*x - 4.79*y
triangles = [[0, 1, 4], [1, 5, 4], [1, 2, 5], [2, 6, 5], [2, 3, 6],
[3, 7, 6], [4, 5, 8], [5, 9, 8], [5, 6, 9], [6, 10, 9],
[6, 7, 10], [7, 11, 10], [8, 9, 12], [9, 13, 12], [9, 10, 13],
[10, 14, 13], [10, 11, 14], [11, 15, 14]]
mask = np.zeros(len(triangles))
mask[8:10] = 1
triang = mtri.Triangulation(x, y, triangles, mask)
linear_interp = mtri.LinearTriInterpolator(triang, z)
cubic_min_E = mtri.CubicTriInterpolator(triang, z)
cubic_geom = mtri.CubicTriInterpolator(triang, z, kind='geom')
xs = np.linspace(0.25, 2.75, 6)
ys = [0.25, 0.75, 2.25, 2.75]
xs, ys = np.meshgrid(xs, ys) # Testing arrays with array.ndim = 2
for interp in (linear_interp, cubic_min_E, cubic_geom):
zs = interp(xs, ys)
assert_array_almost_equal(zs, (1.23*xs - 4.79*ys))
# Test points outside triangulation.
xs = [-0.25, 1.25, 1.75, 3.25]
ys = xs
xs, ys = np.meshgrid(xs, ys)
for interp in (linear_interp, cubic_min_E, cubic_geom):
zs = linear_interp(xs, ys)
assert_array_equal(zs.mask, [[True]*4]*4)
# Test mixed configuration (outside / inside).
xs = np.linspace(0.25, 1.75, 6)
ys = [0.25, 0.75, 1.25, 1.75]
xs, ys = np.meshgrid(xs, ys)
for interp in (linear_interp, cubic_min_E, cubic_geom):
zs = interp(xs, ys)
matest.assert_array_almost_equal(zs, (1.23*xs - 4.79*ys))
mask = (xs >= 1) * (xs <= 2) * (ys >= 1) * (ys <= 2)
assert_array_equal(zs.mask, mask)
# 2nd order patch test: on a grid with an 'arbitrary shaped' triangle,
# patch test shall be exact for quadratic functions and cubic
# interpolator if *kind* = user
(a, b, c) = (1.23, -4.79, 0.6)
def quad(x, y):
return a*(x-0.5)**2 + b*(y-0.5)**2 + c*x*y
def gradient_quad(x, y):
return (2*a*(x-0.5) + c*y, 2*b*(y-0.5) + c*x)
x = np.array([0.2, 0.33367, 0.669, 0., 1., 1., 0.])
y = np.array([0.3, 0.80755, 0.4335, 0., 0., 1., 1.])
triangles = np.array([[0, 1, 2], [3, 0, 4], [4, 0, 2], [4, 2, 5],
[1, 5, 2], [6, 5, 1], [6, 1, 0], [6, 0, 3]])
triang = mtri.Triangulation(x, y, triangles)
z = quad(x, y)
dz = gradient_quad(x, y)
# test points for 2nd order patch test
xs = np.linspace(0., 1., 5)
ys = np.linspace(0., 1., 5)
xs, ys = np.meshgrid(xs, ys)
cubic_user = mtri.CubicTriInterpolator(triang, z, kind='user', dz=dz)
interp_zs = cubic_user(xs, ys)
assert_array_almost_equal(interp_zs, quad(xs, ys))
(interp_dzsdx, interp_dzsdy) = cubic_user.gradient(x, y)
(dzsdx, dzsdy) = gradient_quad(x, y)
assert_array_almost_equal(interp_dzsdx, dzsdx)
assert_array_almost_equal(interp_dzsdy, dzsdy)
# Cubic improvement: cubic interpolation shall perform better than linear
# on a sufficiently dense mesh for a quadratic function.
n = 11
x, y = np.meshgrid(np.linspace(0., 1., n+1), np.linspace(0., 1., n+1))
x = x.ravel()
y = y.ravel()
z = quad(x, y)
triang = mtri.Triangulation(x, y, triangles=meshgrid_triangles(n+1))
xs, ys = np.meshgrid(np.linspace(0.1, 0.9, 5), np.linspace(0.1, 0.9, 5))
xs = xs.ravel()
ys = ys.ravel()
linear_interp = mtri.LinearTriInterpolator(triang, z)
cubic_min_E = mtri.CubicTriInterpolator(triang, z)
cubic_geom = mtri.CubicTriInterpolator(triang, z, kind='geom')
zs = quad(xs, ys)
diff_lin = np.abs(linear_interp(xs, ys) - zs)
for interp in (cubic_min_E, cubic_geom):
diff_cubic = np.abs(interp(xs, ys) - zs)
assert np.max(diff_lin) >= 10 * np.max(diff_cubic)
assert (np.dot(diff_lin, diff_lin) >=
100 * np.dot(diff_cubic, diff_cubic))
def test_triinterpcubic_C1_continuity():
# Below the 4 tests which demonstrate C1 continuity of the
# TriCubicInterpolator (testing the cubic shape functions on arbitrary
# triangle):
#
# 1) Testing continuity of function & derivatives at corner for all 9
# shape functions. Testing also function values at same location.
# 2) Testing C1 continuity along each edge (as gradient is polynomial of
# 2nd order, it is sufficient to test at the middle).
# 3) Testing C1 continuity at triangle barycenter (where the 3 subtriangles
# meet)
# 4) Testing C1 continuity at median 1/3 points (midside between 2
# subtriangles)
# Utility test function check_continuity
def check_continuity(interpolator, loc, values=None):
"""
Checks the continuity of interpolator (and its derivatives) near
location loc. Can check the value at loc itself if *values* is
provided.
*interpolator* TriInterpolator
*loc* location to test (x0, y0)
*values* (optional) array [z0, dzx0, dzy0] to check the value at *loc*
"""
n_star = 24 # Number of continuity points in a boundary of loc
epsilon = 1.e-10 # Distance for loc boundary
k = 100. # Continuity coefficient
(loc_x, loc_y) = loc
star_x = loc_x + epsilon*np.cos(np.linspace(0., 2*np.pi, n_star))
star_y = loc_y + epsilon*np.sin(np.linspace(0., 2*np.pi, n_star))
z = interpolator([loc_x], [loc_y])[0]
(dzx, dzy) = interpolator.gradient([loc_x], [loc_y])
if values is not None:
assert_array_almost_equal(z, values[0])
assert_array_almost_equal(dzx[0], values[1])
assert_array_almost_equal(dzy[0], values[2])
diff_z = interpolator(star_x, star_y) - z
(tab_dzx, tab_dzy) = interpolator.gradient(star_x, star_y)
diff_dzx = tab_dzx - dzx
diff_dzy = tab_dzy - dzy
assert_array_less(diff_z, epsilon*k)
assert_array_less(diff_dzx, epsilon*k)
assert_array_less(diff_dzy, epsilon*k)
# Drawing arbitrary triangle (a, b, c) inside a unit square.
(ax, ay) = (0.2, 0.3)
(bx, by) = (0.33367, 0.80755)
(cx, cy) = (0.669, 0.4335)
x = np.array([ax, bx, cx, 0., 1., 1., 0.])
y = np.array([ay, by, cy, 0., 0., 1., 1.])
triangles = np.array([[0, 1, 2], [3, 0, 4], [4, 0, 2], [4, 2, 5],
[1, 5, 2], [6, 5, 1], [6, 1, 0], [6, 0, 3]])
triang = mtri.Triangulation(x, y, triangles)
for idof in range(9):
z = np.zeros(7, dtype=np.float64)
dzx = np.zeros(7, dtype=np.float64)
dzy = np.zeros(7, dtype=np.float64)
values = np.zeros([3, 3], dtype=np.float64)
case = idof//3
values[case, idof % 3] = 1.0
if case == 0:
z[idof] = 1.0
elif case == 1:
dzx[idof % 3] = 1.0
elif case == 2:
dzy[idof % 3] = 1.0
interp = mtri.CubicTriInterpolator(triang, z, kind='user',
dz=(dzx, dzy))
# Test 1) Checking values and continuity at nodes
check_continuity(interp, (ax, ay), values[:, 0])
check_continuity(interp, (bx, by), values[:, 1])
check_continuity(interp, (cx, cy), values[:, 2])
# Test 2) Checking continuity at midside nodes
check_continuity(interp, ((ax+bx)*0.5, (ay+by)*0.5))
check_continuity(interp, ((ax+cx)*0.5, (ay+cy)*0.5))
check_continuity(interp, ((cx+bx)*0.5, (cy+by)*0.5))
# Test 3) Checking continuity at barycenter
check_continuity(interp, ((ax+bx+cx)/3., (ay+by+cy)/3.))
# Test 4) Checking continuity at median 1/3-point
check_continuity(interp, ((4.*ax+bx+cx)/6., (4.*ay+by+cy)/6.))
check_continuity(interp, ((ax+4.*bx+cx)/6., (ay+4.*by+cy)/6.))
check_continuity(interp, ((ax+bx+4.*cx)/6., (ay+by+4.*cy)/6.))
def test_triinterpcubic_cg_solver():
# Now 3 basic tests of the Sparse CG solver, used for
# TriCubicInterpolator with *kind* = 'min_E'
# 1) A commonly used test involves a 2d Poisson matrix.
def poisson_sparse_matrix(n, m):
"""
Sparse Poisson matrix.
Returns the sparse matrix in coo format resulting from the
discretisation of the 2-dimensional Poisson equation according to a
finite difference numerical scheme on a uniform (n, m) grid.
Size of the matrix: (n*m, n*m)
"""
l = m*n
rows = np.concatenate([
np.arange(l, dtype=np.int32),
np.arange(l-1, dtype=np.int32), np.arange(1, l, dtype=np.int32),
np.arange(l-n, dtype=np.int32), np.arange(n, l, dtype=np.int32)])
cols = np.concatenate([
np.arange(l, dtype=np.int32),
np.arange(1, l, dtype=np.int32), np.arange(l-1, dtype=np.int32),
np.arange(n, l, dtype=np.int32), np.arange(l-n, dtype=np.int32)])
vals = np.concatenate([
4*np.ones(l, dtype=np.float64),
-np.ones(l-1, dtype=np.float64), -np.ones(l-1, dtype=np.float64),
-np.ones(l-n, dtype=np.float64), -np.ones(l-n, dtype=np.float64)])
# In fact +1 and -1 diags have some zeros
vals[l:2*l-1][m-1::m] = 0.
vals[2*l-1:3*l-2][m-1::m] = 0.
return vals, rows, cols, (n*m, n*m)
# Instantiating a sparse Poisson matrix of size 48 x 48:
(n, m) = (12, 4)
mat = mtri.triinterpolate._Sparse_Matrix_coo(*poisson_sparse_matrix(n, m))
mat.compress_csc()
mat_dense = mat.to_dense()
# Testing a sparse solve for all 48 basis vector
for itest in range(n*m):
b = np.zeros(n*m, dtype=np.float64)
b[itest] = 1.
x, _ = mtri.triinterpolate._cg(A=mat, b=b, x0=np.zeros(n*m),
tol=1.e-10)
assert_array_almost_equal(np.dot(mat_dense, x), b)
# 2) Same matrix with inserting 2 rows - cols with null diag terms
# (but still linked with the rest of the matrix by extra-diag terms)
(i_zero, j_zero) = (12, 49)
vals, rows, cols, _ = poisson_sparse_matrix(n, m)
rows = rows + 1*(rows >= i_zero) + 1*(rows >= j_zero)
cols = cols + 1*(cols >= i_zero) + 1*(cols >= j_zero)
# adding extra-diag terms
rows = np.concatenate([rows, [i_zero, i_zero-1, j_zero, j_zero-1]])
cols = np.concatenate([cols, [i_zero-1, i_zero, j_zero-1, j_zero]])
vals = np.concatenate([vals, [1., 1., 1., 1.]])
mat = mtri.triinterpolate._Sparse_Matrix_coo(vals, rows, cols,
(n*m + 2, n*m + 2))
mat.compress_csc()
mat_dense = mat.to_dense()
# Testing a sparse solve for all 50 basis vec
for itest in range(n*m + 2):
b = np.zeros(n*m + 2, dtype=np.float64)
b[itest] = 1.
x, _ = mtri.triinterpolate._cg(A=mat, b=b, x0=np.ones(n*m + 2),
tol=1.e-10)
assert_array_almost_equal(np.dot(mat_dense, x), b)
# 3) Now a simple test that summation of duplicate (i.e. with same rows,
# same cols) entries occurs when compressed.
vals = np.ones(17, dtype=np.float64)
rows = np.array([0, 1, 2, 0, 0, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1],
dtype=np.int32)
cols = np.array([0, 1, 2, 1, 1, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2],
dtype=np.int32)
dim = (3, 3)
mat = mtri.triinterpolate._Sparse_Matrix_coo(vals, rows, cols, dim)
mat.compress_csc()
mat_dense = mat.to_dense()
assert_array_almost_equal(mat_dense, np.array([
[1., 2., 0.], [2., 1., 5.], [0., 5., 1.]], dtype=np.float64))
def test_triinterpcubic_geom_weights():
# Tests to check computation of weights for _DOF_estimator_geom:
# The weight sum per triangle can be 1. (in case all angles < 90 degrees)
# or (2*w_i) where w_i = 1-alpha_i/np.pi is the weight of apex i ; alpha_i
# is the apex angle > 90 degrees.
(ax, ay) = (0., 1.687)
x = np.array([ax, 0.5*ax, 0., 1.])
y = np.array([ay, -ay, 0., 0.])
z = np.zeros(4, dtype=np.float64)
triangles = [[0, 2, 3], [1, 3, 2]]
sum_w = np.zeros([4, 2]) # 4 possibilities ; 2 triangles
for theta in np.linspace(0., 2*np.pi, 14): # rotating the figure...
x_rot = np.cos(theta)*x + np.sin(theta)*y
y_rot = -np.sin(theta)*x + np.cos(theta)*y
triang = mtri.Triangulation(x_rot, y_rot, triangles)
cubic_geom = mtri.CubicTriInterpolator(triang, z, kind='geom')
dof_estimator = mtri.triinterpolate._DOF_estimator_geom(cubic_geom)
weights = dof_estimator.compute_geom_weights()
# Testing for the 4 possibilities...
sum_w[0, :] = np.sum(weights, 1) - 1
for itri in range(3):
sum_w[itri+1, :] = np.sum(weights, 1) - 2*weights[:, itri]
assert_array_almost_equal(np.min(np.abs(sum_w), axis=0),
np.array([0., 0.], dtype=np.float64))
def test_triinterp_colinear():
# Tests interpolating inside a triangulation with horizontal colinear
# points (refer also to the tests :func:`test_trifinder` ).
#
# These are not valid triangulations, but we try to deal with the
# simplest violations (i. e. those handled by default TriFinder).
#
# Note that the LinearTriInterpolator and the CubicTriInterpolator with
# kind='min_E' or 'geom' still pass a linear patch test.
# We also test interpolation inside a flat triangle, by forcing
# *tri_index* in a call to :meth:`_interpolate_multikeys`.
# If +ve, triangulation is OK, if -ve triangulation invalid,
# if zero have colinear points but should pass tests anyway.
delta = 0.
x0 = np.array([1.5, 0, 1, 2, 3, 1.5, 1.5])
y0 = np.array([-1, 0, 0, 0, 0, delta, 1])
# We test different affine transformations of the initial figure ; to
# avoid issues related to round-off errors we only use integer
# coefficients (otherwise the Triangulation might become invalid even with
# delta == 0).
transformations = [[1, 0], [0, 1], [1, 1], [1, 2], [-2, -1], [-2, 1]]
for transformation in transformations:
x_rot = transformation[0]*x0 + transformation[1]*y0
y_rot = -transformation[1]*x0 + transformation[0]*y0
(x, y) = (x_rot, y_rot)
z = 1.23*x - 4.79*y
triangles = [[0, 2, 1], [0, 3, 2], [0, 4, 3], [1, 2, 5], [2, 3, 5],
[3, 4, 5], [1, 5, 6], [4, 6, 5]]
triang = mtri.Triangulation(x, y, triangles)
xs = np.linspace(np.min(triang.x), np.max(triang.x), 20)
ys = np.linspace(np.min(triang.y), np.max(triang.y), 20)
xs, ys = np.meshgrid(xs, ys)
xs = xs.ravel()
ys = ys.ravel()
mask_out = (triang.get_trifinder()(xs, ys) == -1)
zs_target = np.ma.array(1.23*xs - 4.79*ys, mask=mask_out)
linear_interp = mtri.LinearTriInterpolator(triang, z)
cubic_min_E = mtri.CubicTriInterpolator(triang, z)
cubic_geom = mtri.CubicTriInterpolator(triang, z, kind='geom')
for interp in (linear_interp, cubic_min_E, cubic_geom):
zs = interp(xs, ys)
assert_array_almost_equal(zs_target, zs)
# Testing interpolation inside the flat triangle number 4: [2, 3, 5]
# by imposing *tri_index* in a call to :meth:`_interpolate_multikeys`
itri = 4
pt1 = triang.triangles[itri, 0]
pt2 = triang.triangles[itri, 1]
xs = np.linspace(triang.x[pt1], triang.x[pt2], 10)
ys = np.linspace(triang.y[pt1], triang.y[pt2], 10)
zs_target = 1.23*xs - 4.79*ys
for interp in (linear_interp, cubic_min_E, cubic_geom):
zs, = interp._interpolate_multikeys(
xs, ys, tri_index=itri*np.ones(10, dtype=np.int32))
assert_array_almost_equal(zs_target, zs)
def test_triinterp_transformations():
# 1) Testing that the interpolation scheme is invariant by rotation of the
# whole figure.
# Note: This test is non-trivial for a CubicTriInterpolator with
# kind='min_E'. It does fail for a non-isotropic stiffness matrix E of
# :class:`_ReducedHCT_Element` (tested with E=np.diag([1., 1., 1.])), and
# provides a good test for :meth:`get_Kff_and_Ff`of the same class.
#
# 2) Also testing that the interpolation scheme is invariant by expansion
# of the whole figure along one axis.
n_angles = 20
n_radii = 10
min_radius = 0.15
def z(x, y):
r1 = np.sqrt((0.5-x)**2 + (0.5-y)**2)
theta1 = np.arctan2(0.5-x, 0.5-y)
r2 = np.sqrt((-x-0.2)**2 + (-y-0.2)**2)
theta2 = np.arctan2(-x-0.2, -y-0.2)
z = -(2*(np.exp((r1/10)**2)-1)*30. * np.cos(7.*theta1) +
(np.exp((r2/10)**2)-1)*30. * np.cos(11.*theta2) +
0.7*(x**2 + y**2))
return (np.max(z)-z)/(np.max(z)-np.min(z))
# First create the x and y coordinates of the points.
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0 + n_angles, 2*np.pi + n_angles,
n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi/n_angles
x0 = (radii*np.cos(angles)).flatten()
y0 = (radii*np.sin(angles)).flatten()
triang0 = mtri.Triangulation(x0, y0) # Delaunay triangulation
z0 = z(x0, y0)
# Then create the test points
xs0 = np.linspace(-1., 1., 23)
ys0 = np.linspace(-1., 1., 23)
xs0, ys0 = np.meshgrid(xs0, ys0)
xs0 = xs0.ravel()
ys0 = ys0.ravel()
interp_z0 = {}
for i_angle in range(2):
# Rotating everything
theta = 2*np.pi / n_angles * i_angle
x = np.cos(theta)*x0 + np.sin(theta)*y0
y = -np.sin(theta)*x0 + np.cos(theta)*y0
xs = np.cos(theta)*xs0 + np.sin(theta)*ys0
ys = -np.sin(theta)*xs0 + np.cos(theta)*ys0
triang = mtri.Triangulation(x, y, triang0.triangles)
linear_interp = mtri.LinearTriInterpolator(triang, z0)
cubic_min_E = mtri.CubicTriInterpolator(triang, z0)
cubic_geom = mtri.CubicTriInterpolator(triang, z0, kind='geom')
dic_interp = {'lin': linear_interp,
'min_E': cubic_min_E,
'geom': cubic_geom}
# Testing that the interpolation is invariant by rotation...
for interp_key in ['lin', 'min_E', 'geom']:
interp = dic_interp[interp_key]
if i_angle == 0:
interp_z0[interp_key] = interp(xs0, ys0) # storage
else:
interpz = interp(xs, ys)
matest.assert_array_almost_equal(interpz,
interp_z0[interp_key])
scale_factor = 987654.3210
for scaled_axis in ('x', 'y'):
# Scaling everything (expansion along scaled_axis)
if scaled_axis == 'x':
x = scale_factor * x0
y = y0
xs = scale_factor * xs0
ys = ys0
else:
x = x0
y = scale_factor * y0
xs = xs0
ys = scale_factor * ys0
triang = mtri.Triangulation(x, y, triang0.triangles)
linear_interp = mtri.LinearTriInterpolator(triang, z0)
cubic_min_E = mtri.CubicTriInterpolator(triang, z0)
cubic_geom = mtri.CubicTriInterpolator(triang, z0, kind='geom')
dic_interp = {'lin': linear_interp,
'min_E': cubic_min_E,
'geom': cubic_geom}
# Testing that the interpolation is invariant by expansion along
# 1 axis...
for interp_key in ['lin', 'min_E', 'geom']:
interpz = dic_interp[interp_key](xs, ys)
matest.assert_array_almost_equal(interpz, interp_z0[interp_key])
@image_comparison(baseline_images=['tri_smooth_contouring'],
extensions=['png'], remove_text=True, tol=0.07)
def test_tri_smooth_contouring():
# Image comparison based on example tricontour_smooth_user.
n_angles = 20
n_radii = 10
min_radius = 0.15
def z(x, y):
r1 = np.sqrt((0.5-x)**2 + (0.5-y)**2)
theta1 = np.arctan2(0.5-x, 0.5-y)
r2 = np.sqrt((-x-0.2)**2 + (-y-0.2)**2)
theta2 = np.arctan2(-x-0.2, -y-0.2)
z = -(2*(np.exp((r1/10)**2)-1)*30. * np.cos(7.*theta1) +
(np.exp((r2/10)**2)-1)*30. * np.cos(11.*theta2) +
0.7*(x**2 + y**2))
return (np.max(z)-z)/(np.max(z)-np.min(z))
# First create the x and y coordinates of the points.
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0 + n_angles, 2*np.pi + n_angles,
n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi/n_angles
x0 = (radii*np.cos(angles)).flatten()
y0 = (radii*np.sin(angles)).flatten()
triang0 = mtri.Triangulation(x0, y0) # Delaunay triangulation
z0 = z(x0, y0)
triang0.set_mask(np.hypot(x0[triang0.triangles].mean(axis=1),
y0[triang0.triangles].mean(axis=1))
< min_radius)
# Then the plot
refiner = mtri.UniformTriRefiner(triang0)
tri_refi, z_test_refi = refiner.refine_field(z0, subdiv=4)
levels = np.arange(0., 1., 0.025)
plt.triplot(triang0, lw=0.5, color='0.5')
plt.tricontour(tri_refi, z_test_refi, levels=levels, colors="black")
@image_comparison(baseline_images=['tri_smooth_gradient'],
extensions=['png'], remove_text=True, tol=0.092)
def test_tri_smooth_gradient():
# Image comparison based on example trigradient_demo.
def dipole_potential(x, y):
""" An electric dipole potential V """
r_sq = x**2 + y**2
theta = np.arctan2(y, x)
z = np.cos(theta)/r_sq
return (np.max(z)-z) / (np.max(z)-np.min(z))
# Creating a Triangulation
n_angles = 30
n_radii = 10
min_radius = 0.2
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi/n_angles
x = (radii*np.cos(angles)).flatten()
y = (radii*np.sin(angles)).flatten()
V = dipole_potential(x, y)
triang = mtri.Triangulation(x, y)
triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1),
y[triang.triangles].mean(axis=1))
< min_radius)
# Refine data - interpolates the electrical potential V
refiner = mtri.UniformTriRefiner(triang)
tri_refi, z_test_refi = refiner.refine_field(V, subdiv=3)
# Computes the electrical field (Ex, Ey) as gradient of -V
tci = mtri.CubicTriInterpolator(triang, -V)
(Ex, Ey) = tci.gradient(triang.x, triang.y)
E_norm = np.sqrt(Ex**2 + Ey**2)
# Plot the triangulation, the potential iso-contours and the vector field
plt.figure()
plt.gca().set_aspect('equal')
plt.triplot(triang, color='0.8')
levels = np.arange(0., 1., 0.01)
cmap = cm.get_cmap(name='hot', lut=None)
plt.tricontour(tri_refi, z_test_refi, levels=levels, cmap=cmap,
linewidths=[2.0, 1.0, 1.0, 1.0])
# Plots direction of the electrical vector field
plt.quiver(triang.x, triang.y, Ex/E_norm, Ey/E_norm,
units='xy', scale=10., zorder=3, color='blue',
width=0.007, headwidth=3., headlength=4.)
# We are leaving ax.use_sticky_margins as True, so the
# view limits are the contour data limits.
def test_tritools():
# Tests TriAnalyzer.scale_factors on masked triangulation
# Tests circle_ratios on equilateral and right-angled triangle.
x = np.array([0., 1., 0.5, 0., 2.])
y = np.array([0., 0., 0.5*np.sqrt(3.), -1., 1.])
triangles = np.array([[0, 1, 2], [0, 1, 3], [1, 2, 4]], dtype=np.int32)
mask = np.array([False, False, True], dtype=bool)
triang = mtri.Triangulation(x, y, triangles, mask=mask)
analyser = mtri.TriAnalyzer(triang)
assert_array_almost_equal(analyser.scale_factors,
np.array([1., 1./(1.+0.5*np.sqrt(3.))]))
assert_array_almost_equal(
analyser.circle_ratios(rescale=False),
np.ma.masked_array([0.5, 1./(1.+np.sqrt(2.)), np.nan], mask))
# Tests circle ratio of a flat triangle
x = np.array([0., 1., 2.])
y = np.array([1., 1.+3., 1.+6.])
triangles = np.array([[0, 1, 2]], dtype=np.int32)
triang = mtri.Triangulation(x, y, triangles)
analyser = mtri.TriAnalyzer(triang)
assert_array_almost_equal(analyser.circle_ratios(), np.array([0.]))
# Tests TriAnalyzer.get_flat_tri_mask
# Creates a triangulation of [-1, 1] x [-1, 1] with contiguous groups of
# 'flat' triangles at the 4 corners and at the center. Checks that only
# those at the borders are eliminated by TriAnalyzer.get_flat_tri_mask
n = 9
def power(x, a):
return np.abs(x)**a*np.sign(x)
x = np.linspace(-1., 1., n+1)
x, y = np.meshgrid(power(x, 2.), power(x, 0.25))
x = x.ravel()
y = y.ravel()
triang = mtri.Triangulation(x, y, triangles=meshgrid_triangles(n+1))
analyser = mtri.TriAnalyzer(triang)
mask_flat = analyser.get_flat_tri_mask(0.2)
verif_mask = np.zeros(162, dtype=bool)
corners_index = [0, 1, 2, 3, 14, 15, 16, 17, 18, 19, 34, 35, 126, 127,
142, 143, 144, 145, 146, 147, 158, 159, 160, 161]
verif_mask[corners_index] = True
assert_array_equal(mask_flat, verif_mask)
# Now including a hole (masked triangle) at the center. The center also
# shall be eliminated by get_flat_tri_mask.
mask = np.zeros(162, dtype=bool)
mask[80] = True
triang.set_mask(mask)
mask_flat = analyser.get_flat_tri_mask(0.2)
center_index = [44, 45, 62, 63, 78, 79, 80, 81, 82, 83, 98, 99, 116, 117]
verif_mask[center_index] = True
assert_array_equal(mask_flat, verif_mask)
def test_trirefine():
# Testing subdiv=2 refinement
n = 3
subdiv = 2
x = np.linspace(-1., 1., n+1)
x, y = np.meshgrid(x, x)
x = x.ravel()
y = y.ravel()
mask = np.zeros(2*n**2, dtype=bool)
mask[n**2:] = True
triang = mtri.Triangulation(x, y, triangles=meshgrid_triangles(n+1),
mask=mask)
refiner = mtri.UniformTriRefiner(triang)
refi_triang = refiner.refine_triangulation(subdiv=subdiv)
x_refi = refi_triang.x
y_refi = refi_triang.y
n_refi = n * subdiv**2
x_verif = np.linspace(-1., 1., n_refi+1)
x_verif, y_verif = np.meshgrid(x_verif, x_verif)
x_verif = x_verif.ravel()
y_verif = y_verif.ravel()
ind1d = np.in1d(np.around(x_verif*(2.5+y_verif), 8),
np.around(x_refi*(2.5+y_refi), 8))
assert_array_equal(ind1d, True)
# Testing the mask of the refined triangulation
refi_mask = refi_triang.mask
refi_tri_barycenter_x = np.sum(refi_triang.x[refi_triang.triangles],
axis=1) / 3.
refi_tri_barycenter_y = np.sum(refi_triang.y[refi_triang.triangles],
axis=1) / 3.
tri_finder = triang.get_trifinder()
refi_tri_indices = tri_finder(refi_tri_barycenter_x,
refi_tri_barycenter_y)
refi_tri_mask = triang.mask[refi_tri_indices]
assert_array_equal(refi_mask, refi_tri_mask)
# Testing that the numbering of triangles does not change the
# interpolation result.
x = np.asarray([0.0, 1.0, 0.0, 1.0])
y = np.asarray([0.0, 0.0, 1.0, 1.0])
triang = [mtri.Triangulation(x, y, [[0, 1, 3], [3, 2, 0]]),
mtri.Triangulation(x, y, [[0, 1, 3], [2, 0, 3]])]
z = np.sqrt((x-0.3)*(x-0.3) + (y-0.4)*(y-0.4))
# Refining the 2 triangulations and reordering the points
xyz_data = []
for i in range(2):
refiner = mtri.UniformTriRefiner(triang[i])
refined_triang, refined_z = refiner.refine_field(z, subdiv=1)
xyz = np.dstack((refined_triang.x, refined_triang.y, refined_z))[0]
xyz = xyz[np.lexsort((xyz[:, 1], xyz[:, 0]))]
xyz_data += [xyz]
assert_array_almost_equal(xyz_data[0], xyz_data[1])
def meshgrid_triangles(n):
"""
Utility function.
Returns triangles to mesh a np.meshgrid of n x n points
"""
tri = []
for i in range(n-1):
for j in range(n-1):
a = i + j*(n)
b = (i+1) + j*n
c = i + (j+1)*n
d = (i+1) + (j+1)*n
tri += [[a, b, d], [a, d, c]]
return np.array(tri, dtype=np.int32)
def test_triplot_return():
# Check that triplot returns the artists it adds
from matplotlib.figure import Figure
ax = Figure().add_axes([0.1, 0.1, 0.7, 0.7])
triang = mtri.Triangulation(
[0.0, 1.0, 0.0, 1.0], [0.0, 0.0, 1.0, 1.0],
triangles=[[0, 1, 3], [3, 2, 0]])
assert ax.triplot(triang, "b-") is not None, \
'triplot should return the artist it adds'
def test_trirefiner_fortran_contiguous_triangles():
# github issue 4180. Test requires two arrays of triangles that are
# identical except that one is C-contiguous and one is fortran-contiguous.
triangles1 = np.array([[2, 0, 3], [2, 1, 0]])
assert not np.isfortran(triangles1)
triangles2 = np.array(triangles1, copy=True, order='F')
assert np.isfortran(triangles2)
x = np.array([0.39, 0.59, 0.43, 0.32])
y = np.array([33.99, 34.01, 34.19, 34.18])
triang1 = mtri.Triangulation(x, y, triangles1)
triang2 = mtri.Triangulation(x, y, triangles2)
refiner1 = mtri.UniformTriRefiner(triang1)
refiner2 = mtri.UniformTriRefiner(triang2)
fine_triang1 = refiner1.refine_triangulation(subdiv=1)
fine_triang2 = refiner2.refine_triangulation(subdiv=1)
assert_array_equal(fine_triang1.triangles, fine_triang2.triangles)
def test_qhull_triangle_orientation():
# github issue 4437.
xi = np.linspace(-2, 2, 100)
x, y = map(np.ravel, np.meshgrid(xi, xi))
w = np.logical_and(x > y - 1, np.logical_and(x < -1.95, y > -1.2))
x, y = x[w], y[w]
theta = np.radians(25)
x1 = x*np.cos(theta) - y*np.sin(theta)
y1 = x*np.sin(theta) + y*np.cos(theta)
# Calculate Delaunay triangulation using Qhull.
triang = mtri.Triangulation(x1, y1)
# Neighbors returned by Qhull.
qhull_neighbors = triang.neighbors
# Obtain neighbors using own C++ calculation.
triang._neighbors = None
own_neighbors = triang.neighbors
assert_array_equal(qhull_neighbors, own_neighbors)
def test_trianalyzer_mismatched_indices():
# github issue 4999.
x = np.array([0., 1., 0.5, 0., 2.])
y = np.array([0., 0., 0.5*np.sqrt(3.), -1., 1.])
triangles = np.array([[0, 1, 2], [0, 1, 3], [1, 2, 4]], dtype=np.int32)
mask = np.array([False, False, True], dtype=bool)
triang = mtri.Triangulation(x, y, triangles, mask=mask)
analyser = mtri.TriAnalyzer(triang)
# numpy >= 1.10 raises a VisibleDeprecationWarning in the following line
# prior to the fix.
triang2 = analyser._get_compressed_triangulation()
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0])
def test_internal_cpp_api():
# Following github issue 8197.
import matplotlib._tri as _tri
# C++ Triangulation.
with pytest.raises(TypeError) as excinfo:
triang = _tri.Triangulation()
excinfo.match(r'function takes exactly 7 arguments \(0 given\)')
with pytest.raises(ValueError) as excinfo:
triang = _tri.Triangulation([], [1], [[]], None, None, None, False)
excinfo.match(r'x and y must be 1D arrays of the same length')
x = [0, 1, 1]
y = [0, 0, 1]
with pytest.raises(ValueError) as excinfo:
triang = _tri.Triangulation(x, y, [[0, 1]], None, None, None, False)
excinfo.match(r'triangles must be a 2D array of shape \(\?,3\)')
tris = [[0, 1, 2]]
with pytest.raises(ValueError) as excinfo:
triang = _tri.Triangulation(x, y, tris, [0, 1], None, None, False)
excinfo.match(r'mask must be a 1D array with the same length as the ' +
r'triangles array')
with pytest.raises(ValueError) as excinfo:
triang = _tri.Triangulation(x, y, tris, None, [[1]], None, False)
excinfo.match(r'edges must be a 2D array with shape \(\?,2\)')
with pytest.raises(ValueError) as excinfo:
triang = _tri.Triangulation(x, y, tris, None, None, [[-1]], False)
excinfo.match(r'neighbors must be a 2D array with the same shape as the ' +
r'triangles array')
triang = _tri.Triangulation(x, y, tris, None, None, None, False)
with pytest.raises(ValueError) as excinfo:
triang.calculate_plane_coefficients([])
excinfo.match(r'z array must have same length as triangulation x and y ' +
r'arrays')
with pytest.raises(ValueError) as excinfo:
triang.set_mask([0, 1])
excinfo.match(r'mask must be a 1D array with the same length as the ' +
r'triangles array')
# C++ TriContourGenerator.
with pytest.raises(TypeError) as excinfo:
tcg = _tri.TriContourGenerator()
excinfo.match(r'function takes exactly 2 arguments \(0 given\)')
with pytest.raises(ValueError) as excinfo:
tcg = _tri.TriContourGenerator(triang, [1])
excinfo.match(r'z must be a 1D array with the same length as the x and ' +
r'y arrays')
z = [0, 1, 2]
tcg = _tri.TriContourGenerator(triang, z)
with pytest.raises(ValueError) as excinfo:
tcg.create_filled_contour(1, 0)
excinfo.match(r'filled contour levels must be increasing')
# C++ TrapezoidMapTriFinder.
with pytest.raises(TypeError) as excinfo:
trifinder = _tri.TrapezoidMapTriFinder()
excinfo.match(r'function takes exactly 1 argument \(0 given\)')
trifinder = _tri.TrapezoidMapTriFinder(triang)
with pytest.raises(ValueError) as excinfo:
trifinder.find_many([0], [0, 1])
excinfo.match(r'x and y must be array_like with same shape')
def test_qhull_large_offset():
# github issue 8682.
x = np.asarray([0, 1, 0, 1, 0.5])
y = np.asarray([0, 0, 1, 1, 0.5])
offset = 1e10
triang = mtri.Triangulation(x, y)
triang_offset = mtri.Triangulation(x + offset, y + offset)
assert len(triang.triangles) == len(triang_offset.triangles)
| 44,908 | 38.637246 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_texmanager.py | from __future__ import absolute_import, division, print_function
import matplotlib.pyplot as plt
from matplotlib.texmanager import TexManager
def test_fontconfig_preamble():
"""
Test that the preamble is included in _fontconfig
"""
plt.rcParams['text.usetex'] = True
tm1 = TexManager()
font_config1 = tm1.get_font_config()
plt.rcParams['text.latex.preamble'] = ['\\usepackage{txfonts}']
tm2 = TexManager()
font_config2 = tm2.get_font_config()
assert font_config1 != font_config2
| 525 | 24.047619 | 67 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_preprocess_data.py | from __future__ import (absolute_import, division, print_function)
import re
import numpy as np
import pytest
from matplotlib import _preprocess_data
# Notes on testing the plotting functions itself
# * the individual decorated plotting functions are tested in 'test_axes.py'
# * that pyplot functions accept a data kwarg is only tested in
# test_axes.test_pie_linewidth_0
# these two get used in multiple tests, so define them here
@_preprocess_data(replace_names=["x", "y"], label_namer="y")
def plot_func(ax, x, y, ls="x", label=None, w="xyz"):
return ("x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label))
@_preprocess_data(replace_names=["x", "y"], label_namer="y",
positional_parameter_names=["x", "y", "ls", "label", "w"])
def plot_func_varargs(ax, *args, **kwargs):
all_args = [None, None, "x", None, "xyz"]
for i, v in enumerate(args):
all_args[i] = v
for i, k in enumerate(["x", "y", "ls", "label", "w"]):
if k in kwargs:
all_args[i] = kwargs[k]
x, y, ls, label, w = all_args
return ("x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label))
all_funcs = [plot_func, plot_func_varargs]
all_func_ids = ['plot_func', 'plot_func_varargs']
def test_compiletime_checks():
"""test decorator invocations -> no replacements"""
def func(ax, x, y): pass
def func_args(ax, x, y, *args): pass
def func_kwargs(ax, x, y, **kwargs): pass
def func_no_ax_args(*args, **kwargs): pass
# this is ok
_preprocess_data(replace_names=["x", "y"])(func)
_preprocess_data(replace_names=["x", "y"])(func_kwargs)
# this has "enough" information to do all the replaces
_preprocess_data(replace_names=["x", "y"])(func_args)
# no positional_parameter_names but needed due to replaces
with pytest.raises(AssertionError):
# z is unknown
_preprocess_data(replace_names=["x", "y", "z"])(func_args)
with pytest.raises(AssertionError):
_preprocess_data(replace_names=["x", "y"])(func_no_ax_args)
# no replacements at all -> all ok...
_preprocess_data(replace_names=[], label_namer=None)(func)
_preprocess_data(replace_names=[], label_namer=None)(func_args)
_preprocess_data(replace_names=[], label_namer=None)(func_kwargs)
_preprocess_data(replace_names=[], label_namer=None)(func_no_ax_args)
# label namer is unknown
with pytest.raises(AssertionError):
_preprocess_data(label_namer="z")(func)
with pytest.raises(AssertionError):
_preprocess_data(label_namer="z")(func_args)
# but "ok-ish", if func has kwargs -> will show up at runtime :-(
_preprocess_data(label_namer="z")(func_kwargs)
_preprocess_data(label_namer="z")(func_no_ax_args)
def test_label_problems_at_runtime():
"""Tests for behaviour which would actually be nice to get rid of."""
@_preprocess_data(label_namer="z")
def func(*args, **kwargs):
pass
# This is a programming mistake: the parameter which should add the
# label is not present in the function call. Unfortunately this was masked
# due to the **kwargs usage
# This would be nice to handle as a compiletime check (see above...)
with pytest.warns(RuntimeWarning):
func(None, x="a", y="b")
def real_func(x, y):
pass
@_preprocess_data(label_namer="x")
def func(*args, **kwargs):
real_func(**kwargs)
# This sets a label although the function can't handle it.
with pytest.raises(TypeError):
func(None, x="a", y="b")
@pytest.mark.parametrize('func', all_funcs, ids=all_func_ids)
def test_function_call_without_data(func):
"""test without data -> no replacements"""
assert (func(None, "x", "y") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: None")
assert (func(None, x="x", y="y") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: None")
assert (func(None, "x", "y", label="") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: ")
assert (func(None, "x", "y", label="text") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: text")
assert (func(None, x="x", y="y", label="") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: ")
assert (func(None, x="x", y="y", label="text") ==
"x: ['x'], y: ['y'], ls: x, w: xyz, label: text")
@pytest.mark.parametrize('func', all_funcs, ids=all_func_ids)
def test_function_call_with_dict_data(func):
"""Test with dict data -> label comes from the value of 'x' parameter """
data = {"a": [1, 2], "b": [8, 9], "w": "NOT"}
assert (func(None, "a", "b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func(None, x="a", y="b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func(None, "a", "b", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func(None, "a", "b", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
assert (func(None, x="a", y="b", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func(None, x="a", y="b", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
@pytest.mark.parametrize('func', all_funcs, ids=all_func_ids)
def test_function_call_with_dict_data_not_in_data(func):
"test for the case that one var is not in data -> half replaces, half kept"
data = {"a": [1, 2], "w": "NOT"}
assert (func(None, "a", "b", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: b")
assert (func(None, x="a", y="b", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: b")
assert (func(None, "a", "b", label="", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: ")
assert (func(None, "a", "b", label="text", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: text")
assert (func(None, x="a", y="b", label="", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: ")
assert (func(None, x="a", y="b", label="text", data=data) ==
"x: [1, 2], y: ['b'], ls: x, w: xyz, label: text")
@pytest.mark.parametrize('func', all_funcs, ids=all_func_ids)
def test_function_call_with_pandas_data(func, pd):
"""test with pandas dataframe -> label comes from data["col"].name """
data = pd.DataFrame({"a": np.array([1, 2], dtype=np.int32),
"b": np.array([8, 9], dtype=np.int32),
"w": ["NOT", "NOT"]})
assert (func(None, "a", "b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func(None, x="a", y="b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func(None, "a", "b", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func(None, "a", "b", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
assert (func(None, x="a", y="b", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func(None, x="a", y="b", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
def test_function_call_replace_all():
"""Test without a "replace_names" argument, all vars should be replaced"""
data = {"a": [1, 2], "b": [8, 9], "x": "xyz"}
@_preprocess_data(label_namer="y")
def func_replace_all(ax, x, y, ls="x", label=None, w="NOT"):
return "x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label)
assert (func_replace_all(None, "a", "b", w="x", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func_replace_all(None, x="a", y="b", w="x", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func_replace_all(None, "a", "b", w="x", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (
func_replace_all(None, "a", "b", w="x", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
assert (
func_replace_all(None, x="a", y="b", w="x", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (
func_replace_all(None, x="a", y="b", w="x", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
@_preprocess_data(label_namer="y")
def func_varags_replace_all(ax, *args, **kwargs):
all_args = [None, None, "x", None, "xyz"]
for i, v in enumerate(args):
all_args[i] = v
for i, k in enumerate(["x", "y", "ls", "label", "w"]):
if k in kwargs:
all_args[i] = kwargs[k]
x, y, ls, label, w = all_args
return "x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label)
# in the first case, we can't get a "y" argument,
# as we don't know the names of the *args
assert (func_varags_replace_all(None, x="a", y="b", w="x", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (
func_varags_replace_all(None, "a", "b", w="x", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (
func_varags_replace_all(None, "a", "b", w="x", label="text",
data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
assert (
func_varags_replace_all(None, x="a", y="b", w="x", label="",
data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (
func_varags_replace_all(None, x="a", y="b", w="x", label="text",
data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
with pytest.warns(RuntimeWarning):
assert (func_varags_replace_all(None, "a", "b", w="x", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: None")
def test_no_label_replacements():
"""Test with "label_namer=None" -> no label replacement at all"""
@_preprocess_data(replace_names=["x", "y"], label_namer=None)
def func_no_label(ax, x, y, ls="x", label=None, w="xyz"):
return "x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label)
data = {"a": [1, 2], "b": [8, 9], "w": "NOT"}
assert (func_no_label(None, "a", "b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: None")
assert (func_no_label(None, x="a", y="b", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: None")
assert (func_no_label(None, "a", "b", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func_no_label(None, "a", "b", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
def test_more_args_than_pos_parameter():
@_preprocess_data(replace_names=["x", "y"], label_namer="y")
def func(ax, x, y, z=1):
pass
data = {"a": [1, 2], "b": [8, 9], "w": "NOT"}
with pytest.raises(RuntimeError):
func(None, "a", "b", "z", "z", data=data)
def test_function_call_with_replace_all_args():
"""Test with a "replace_all_args" argument, all *args should be replaced"""
data = {"a": [1, 2], "b": [8, 9], "x": "xyz"}
def funcy(ax, *args, **kwargs):
all_args = [None, None, "x", None, "NOT"]
for i, v in enumerate(args):
all_args[i] = v
for i, k in enumerate(["x", "y", "ls", "label", "w"]):
if k in kwargs:
all_args[i] = kwargs[k]
x, y, ls, label, w = all_args
return "x: %s, y: %s, ls: %s, w: %s, label: %s" % (
list(x), list(y), ls, w, label)
func = _preprocess_data(replace_all_args=True, replace_names=["w"],
label_namer="y")(funcy)
assert (func(None, "a", "b", w="x", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func(None, "a", "b", w="x", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
func2 = _preprocess_data(replace_all_args=True, replace_names=["w"],
label_namer="y",
positional_parameter_names=["x", "y", "ls",
"label", "w"])(funcy)
assert (func2(None, "a", "b", w="x", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: b")
assert (func2(None, "a", "b", w="x", label="", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: ")
assert (func2(None, "a", "b", w="x", label="text", data=data) ==
"x: [1, 2], y: [8, 9], ls: x, w: xyz, label: text")
def test_docstring_addition():
@_preprocess_data()
def funcy(ax, *args, **kwargs):
"""Funcy does nothing"""
pass
assert re.search(r".*All positional and all keyword arguments\.",
funcy.__doc__)
assert not re.search(r".*All positional arguments\.", funcy.__doc__)
assert not re.search(r".*All arguments with the following names: .*",
funcy.__doc__)
@_preprocess_data(replace_all_args=True, replace_names=[])
def funcy(ax, x, y, z, bar=None):
"""Funcy does nothing"""
pass
assert re.search(r".*All positional arguments\.",
funcy.__doc__)
assert not re.search(r".*All positional and all keyword arguments\.",
funcy.__doc__)
assert not re.search(r".*All arguments with the following names: .*",
funcy.__doc__)
@_preprocess_data(replace_all_args=True, replace_names=["bar"])
def funcy(ax, x, y, z, bar=None):
"""Funcy does nothing"""
pass
assert re.search(r".*All positional arguments\.", funcy.__doc__)
assert re.search(r".*All arguments with the following names: 'bar'\.",
funcy.__doc__)
assert not re.search(r".*All positional and all keyword arguments\.",
funcy.__doc__)
@_preprocess_data(replace_names=["x", "bar"])
def funcy(ax, x, y, z, bar=None):
"""Funcy does nothing"""
pass
# lists can print in any order, so test for both x,bar and bar,x
assert re.search(r".*All arguments with the following names: '.*', '.*'\.",
funcy.__doc__)
assert re.search(r".*'x'.*", funcy.__doc__)
assert re.search(r".*'bar'.*", funcy.__doc__)
assert not re.search(r".*All positional and all keyword arguments\.",
funcy.__doc__)
assert not re.search(r".*All positional arguments\.",
funcy.__doc__)
def test_positional_parameter_names_as_function():
# Also test the _plot_arg_replacer for plot...
from matplotlib.axes._axes import _plot_args_replacer
@_preprocess_data(replace_names=["x", "y"],
positional_parameter_names=_plot_args_replacer)
def funcy(ax, *args, **kwargs):
return "{args} | {kwargs}".format(args=args, kwargs=kwargs)
# the normal case...
data = {"x": "X", "hy1": "Y"}
assert funcy(None, "x", "hy1", data=data) == "('X', 'Y') | {}"
assert funcy(None, "x", "hy1", "c", data=data) == "('X', 'Y', 'c') | {}"
# no arbitrary long args with data
with pytest.raises(ValueError):
assert (funcy(None, "x", "y", "c", "x", "y", "x", "y", data=data) ==
"('X', 'Y', 'c', 'X', 'Y', 'X', 'Y') | {}")
# In the two arg case, if a valid color spec is in data, we warn but use
# it as data...
data = {"x": "X", "y": "Y", "ro": "!!"}
with pytest.warns(RuntimeWarning):
assert funcy(None, "y", "ro", data=data) == "('Y', '!!') | {}"
| 16,058 | 40.496124 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_dates.py | from __future__ import absolute_import, division, print_function
from six.moves import map
import datetime
import dateutil
import tempfile
import numpy as np
import pytest
import pytz
try:
# mock in python 3.3+
from unittest import mock
except ImportError:
import mock
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
def test_date_numpyx():
# test that numpy dates work properly...
base = datetime.datetime(2017, 1, 1)
time = [base + datetime.timedelta(days=x) for x in range(0, 3)]
timenp = np.array(time, dtype='datetime64[ns]')
data = np.array([0., 2., 1.])
fig = plt.figure(figsize=(10, 2))
ax = fig.add_subplot(1, 1, 1)
h, = ax.plot(time, data)
hnp, = ax.plot(timenp, data)
assert np.array_equal(h.get_xdata(orig=False), hnp.get_xdata(orig=False))
fig = plt.figure(figsize=(10, 2))
ax = fig.add_subplot(1, 1, 1)
h, = ax.plot(data, time)
hnp, = ax.plot(data, timenp)
assert np.array_equal(h.get_ydata(orig=False), hnp.get_ydata(orig=False))
@pytest.mark.parametrize('t0', [datetime.datetime(2017, 1, 1, 0, 1, 1),
[datetime.datetime(2017, 1, 1, 0, 1, 1),
datetime.datetime(2017, 1, 1, 1, 1, 1)],
[[datetime.datetime(2017, 1, 1, 0, 1, 1),
datetime.datetime(2017, 1, 1, 1, 1, 1)],
[datetime.datetime(2017, 1, 1, 2, 1, 1),
datetime.datetime(2017, 1, 1, 3, 1, 1)]]])
@pytest.mark.parametrize('dtype', ['datetime64[s]',
'datetime64[us]',
'datetime64[ms]',
'datetime64[ns]'])
def test_date_date2num_numpy(t0, dtype):
time = mdates.date2num(t0)
tnp = np.array(t0, dtype=dtype)
nptime = mdates.date2num(tnp)
assert np.array_equal(time, nptime)
@pytest.mark.parametrize('dtype', ['datetime64[s]',
'datetime64[us]',
'datetime64[ms]',
'datetime64[ns]'])
def test_date2num_NaT(dtype):
t0 = datetime.datetime(2017, 1, 1, 0, 1, 1)
tmpl = [mdates.date2num(t0), np.nan]
tnp = np.array([t0, 'NaT'], dtype=dtype)
nptime = mdates.date2num(tnp)
np.testing.assert_array_equal(tmpl, nptime)
@pytest.mark.parametrize('units', ['s', 'ms', 'us', 'ns'])
def test_date2num_NaT_scalar(units):
tmpl = mdates.date2num(np.datetime64('NaT', units))
assert np.isnan(tmpl)
@image_comparison(baseline_images=['date_empty'], extensions=['png'])
def test_date_empty():
# make sure mpl does the right thing when told to plot dates even
# if no date data has been presented, cf
# http://sourceforge.net/tracker/?func=detail&aid=2850075&group_id=80706&atid=560720
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.xaxis_date()
@image_comparison(baseline_images=['date_axhspan'], extensions=['png'])
def test_date_axhspan():
# test ax hspan with date inputs
t0 = datetime.datetime(2009, 1, 20)
tf = datetime.datetime(2009, 1, 21)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.axhspan(t0, tf, facecolor="blue", alpha=0.25)
ax.set_ylim(t0 - datetime.timedelta(days=5),
tf + datetime.timedelta(days=5))
fig.subplots_adjust(left=0.25)
@image_comparison(baseline_images=['date_axvspan'], extensions=['png'])
def test_date_axvspan():
# test ax hspan with date inputs
t0 = datetime.datetime(2000, 1, 20)
tf = datetime.datetime(2010, 1, 21)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.axvspan(t0, tf, facecolor="blue", alpha=0.25)
ax.set_xlim(t0 - datetime.timedelta(days=720),
tf + datetime.timedelta(days=720))
fig.autofmt_xdate()
@image_comparison(baseline_images=['date_axhline'],
extensions=['png'])
def test_date_axhline():
# test ax hline with date inputs
t0 = datetime.datetime(2009, 1, 20)
tf = datetime.datetime(2009, 1, 31)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.axhline(t0, color="blue", lw=3)
ax.set_ylim(t0 - datetime.timedelta(days=5),
tf + datetime.timedelta(days=5))
fig.subplots_adjust(left=0.25)
@image_comparison(baseline_images=['date_axvline'],
extensions=['png'])
def test_date_axvline():
# test ax hline with date inputs
t0 = datetime.datetime(2000, 1, 20)
tf = datetime.datetime(2000, 1, 21)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.axvline(t0, color="red", lw=3)
ax.set_xlim(t0 - datetime.timedelta(days=5),
tf + datetime.timedelta(days=5))
fig.autofmt_xdate()
def test_too_many_date_ticks():
# Attempt to test SF 2715172, see
# https://sourceforge.net/tracker/?func=detail&aid=2715172&group_id=80706&atid=560720
# setting equal datetimes triggers and expander call in
# transforms.nonsingular which results in too many ticks in the
# DayLocator. This should trigger a Locator.MAXTICKS RuntimeError
t0 = datetime.datetime(2000, 1, 20)
tf = datetime.datetime(2000, 1, 20)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
with pytest.warns(UserWarning) as rec:
ax.set_xlim((t0, tf), auto=True)
assert len(rec) == 1
assert 'Attempting to set identical left==right' in str(rec[0].message)
ax.plot([], [])
ax.xaxis.set_major_locator(mdates.DayLocator())
with pytest.raises(RuntimeError):
fig.savefig('junk.png')
@image_comparison(baseline_images=['RRuleLocator_bounds'], extensions=['png'])
def test_RRuleLocator():
import matplotlib.testing.jpl_units as units
units.register()
# This will cause the RRuleLocator to go out of bounds when it tries
# to add padding to the limits, so we make sure it caps at the correct
# boundary values.
t0 = datetime.datetime(1000, 1, 1)
tf = datetime.datetime(6000, 1, 1)
fig = plt.figure()
ax = plt.subplot(111)
ax.set_autoscale_on(True)
ax.plot([t0, tf], [0.0, 1.0], marker='o')
rrule = mdates.rrulewrapper(dateutil.rrule.YEARLY, interval=500)
locator = mdates.RRuleLocator(rrule)
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))
ax.autoscale_view()
fig.autofmt_xdate()
def test_RRuleLocator_dayrange():
loc = mdates.DayLocator()
x1 = datetime.datetime(year=1, month=1, day=1, tzinfo=pytz.UTC)
y1 = datetime.datetime(year=1, month=1, day=16, tzinfo=pytz.UTC)
loc.tick_values(x1, y1)
# On success, no overflow error shall be thrown
@image_comparison(baseline_images=['DateFormatter_fractionalSeconds'],
extensions=['png'])
def test_DateFormatter():
import matplotlib.testing.jpl_units as units
units.register()
# Lets make sure that DateFormatter will allow us to have tick marks
# at intervals of fractional seconds.
t0 = datetime.datetime(2001, 1, 1, 0, 0, 0)
tf = datetime.datetime(2001, 1, 1, 0, 0, 1)
fig = plt.figure()
ax = plt.subplot(111)
ax.set_autoscale_on(True)
ax.plot([t0, tf], [0.0, 1.0], marker='o')
# rrule = mpldates.rrulewrapper( dateutil.rrule.YEARLY, interval=500 )
# locator = mpldates.RRuleLocator( rrule )
# ax.xaxis.set_major_locator( locator )
# ax.xaxis.set_major_formatter( mpldates.AutoDateFormatter(locator) )
ax.autoscale_view()
fig.autofmt_xdate()
def test_date_formatter_strftime():
"""
Tests that DateFormatter matches datetime.strftime,
check microseconds for years before 1900 for bug #3179
as well as a few related issues for years before 1900.
"""
def test_strftime_fields(dt):
"""For datetime object dt, check DateFormatter fields"""
# Note: the last couple of %%s are to check multiple %s are handled
# properly; %% should get replaced by %.
formatter = mdates.DateFormatter("%w %d %m %y %Y %H %I %M %S %%%f %%x")
# Compute date fields without using datetime.strftime,
# since datetime.strftime does not work before year 1900
formatted_date_str = (
"{weekday} {day:02d} {month:02d} {year:02d} {full_year:04d} "
"{hour24:02d} {hour12:02d} {minute:02d} {second:02d} "
"%{microsecond:06d} %x"
.format(
weekday=str((dt.weekday() + 1) % 7),
day=dt.day,
month=dt.month,
year=dt.year % 100,
full_year=dt.year,
hour24=dt.hour,
hour12=((dt.hour-1) % 12) + 1,
minute=dt.minute,
second=dt.second,
microsecond=dt.microsecond))
assert formatter.strftime(dt) == formatted_date_str
try:
# Test strftime("%x") with the current locale.
import locale # Might not exist on some platforms, such as Windows
locale_formatter = mdates.DateFormatter("%x")
locale_d_fmt = locale.nl_langinfo(locale.D_FMT)
expanded_formatter = mdates.DateFormatter(locale_d_fmt)
assert locale_formatter.strftime(dt) == \
expanded_formatter.strftime(dt)
except (ImportError, AttributeError):
pass
for year in range(1, 3000, 71):
# Iterate through random set of years
test_strftime_fields(datetime.datetime(year, 1, 1))
test_strftime_fields(datetime.datetime(year, 2, 3, 4, 5, 6, 12345))
def test_date_formatter_callable():
scale = -11
locator = mock.Mock(_get_unit=mock.Mock(return_value=scale))
callable_formatting_function = (lambda dates, _:
[dt.strftime('%d-%m//%Y') for dt in dates])
formatter = mdates.AutoDateFormatter(locator)
formatter.scaled[-10] = callable_formatting_function
assert formatter([datetime.datetime(2014, 12, 25)]) == ['25-12//2014']
def test_drange():
"""
This test should check if drange works as expected, and if all the
rounding errors are fixed
"""
start = datetime.datetime(2011, 1, 1, tzinfo=mdates.UTC)
end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC)
delta = datetime.timedelta(hours=1)
# We expect 24 values in drange(start, end, delta), because drange returns
# dates from an half open interval [start, end)
assert len(mdates.drange(start, end, delta)) == 24
# if end is a little bit later, we expect the range to contain one element
# more
end = end + datetime.timedelta(microseconds=1)
assert len(mdates.drange(start, end, delta)) == 25
# reset end
end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC)
# and tst drange with "complicated" floats:
# 4 hours = 1/6 day, this is an "dangerous" float
delta = datetime.timedelta(hours=4)
daterange = mdates.drange(start, end, delta)
assert len(daterange) == 6
assert mdates.num2date(daterange[-1]) == (end - delta)
def test_empty_date_with_year_formatter():
# exposes sf bug 2861426:
# https://sourceforge.net/tracker/?func=detail&aid=2861426&group_id=80706&atid=560720
# update: I am no longer believe this is a bug, as I commented on
# the tracker. The question is now: what to do with this test
import matplotlib.dates as dates
fig = plt.figure()
ax = fig.add_subplot(111)
yearFmt = dates.DateFormatter('%Y')
ax.xaxis.set_major_formatter(yearFmt)
with tempfile.TemporaryFile() as fh:
with pytest.raises(ValueError):
fig.savefig(fh)
def test_auto_date_locator():
def _create_auto_date_locator(date1, date2):
locator = mdates.AutoDateLocator()
locator.create_dummy_axis()
locator.set_view_interval(mdates.date2num(date1),
mdates.date2num(date2))
return locator
d1 = datetime.datetime(1990, 1, 1)
results = ([datetime.timedelta(weeks=52 * 200),
['1990-01-01 00:00:00+00:00', '2010-01-01 00:00:00+00:00',
'2030-01-01 00:00:00+00:00', '2050-01-01 00:00:00+00:00',
'2070-01-01 00:00:00+00:00', '2090-01-01 00:00:00+00:00',
'2110-01-01 00:00:00+00:00', '2130-01-01 00:00:00+00:00',
'2150-01-01 00:00:00+00:00', '2170-01-01 00:00:00+00:00']
],
[datetime.timedelta(weeks=52),
['1990-01-01 00:00:00+00:00', '1990-02-01 00:00:00+00:00',
'1990-03-01 00:00:00+00:00', '1990-04-01 00:00:00+00:00',
'1990-05-01 00:00:00+00:00', '1990-06-01 00:00:00+00:00',
'1990-07-01 00:00:00+00:00', '1990-08-01 00:00:00+00:00',
'1990-09-01 00:00:00+00:00', '1990-10-01 00:00:00+00:00',
'1990-11-01 00:00:00+00:00', '1990-12-01 00:00:00+00:00']
],
[datetime.timedelta(days=141),
['1990-01-05 00:00:00+00:00', '1990-01-26 00:00:00+00:00',
'1990-02-16 00:00:00+00:00', '1990-03-09 00:00:00+00:00',
'1990-03-30 00:00:00+00:00', '1990-04-20 00:00:00+00:00',
'1990-05-11 00:00:00+00:00']
],
[datetime.timedelta(days=40),
['1990-01-03 00:00:00+00:00', '1990-01-10 00:00:00+00:00',
'1990-01-17 00:00:00+00:00', '1990-01-24 00:00:00+00:00',
'1990-01-31 00:00:00+00:00', '1990-02-07 00:00:00+00:00']
],
[datetime.timedelta(hours=40),
['1990-01-01 00:00:00+00:00', '1990-01-01 04:00:00+00:00',
'1990-01-01 08:00:00+00:00', '1990-01-01 12:00:00+00:00',
'1990-01-01 16:00:00+00:00', '1990-01-01 20:00:00+00:00',
'1990-01-02 00:00:00+00:00', '1990-01-02 04:00:00+00:00',
'1990-01-02 08:00:00+00:00', '1990-01-02 12:00:00+00:00',
'1990-01-02 16:00:00+00:00']
],
[datetime.timedelta(minutes=20),
['1990-01-01 00:00:00+00:00', '1990-01-01 00:05:00+00:00',
'1990-01-01 00:10:00+00:00', '1990-01-01 00:15:00+00:00',
'1990-01-01 00:20:00+00:00']
],
[datetime.timedelta(seconds=40),
['1990-01-01 00:00:00+00:00', '1990-01-01 00:00:05+00:00',
'1990-01-01 00:00:10+00:00', '1990-01-01 00:00:15+00:00',
'1990-01-01 00:00:20+00:00', '1990-01-01 00:00:25+00:00',
'1990-01-01 00:00:30+00:00', '1990-01-01 00:00:35+00:00',
'1990-01-01 00:00:40+00:00']
],
[datetime.timedelta(microseconds=1500),
['1989-12-31 23:59:59.999500+00:00',
'1990-01-01 00:00:00+00:00',
'1990-01-01 00:00:00.000500+00:00',
'1990-01-01 00:00:00.001000+00:00',
'1990-01-01 00:00:00.001500+00:00']
],
)
for t_delta, expected in results:
d2 = d1 + t_delta
locator = _create_auto_date_locator(d1, d2)
assert list(map(str, mdates.num2date(locator()))) == expected
def test_auto_date_locator_intmult():
def _create_auto_date_locator(date1, date2):
locator = mdates.AutoDateLocator(interval_multiples=True)
locator.create_dummy_axis()
locator.set_view_interval(mdates.date2num(date1),
mdates.date2num(date2))
return locator
d1 = datetime.datetime(1997, 1, 1)
results = ([datetime.timedelta(weeks=52 * 200),
['1980-01-01 00:00:00+00:00', '2000-01-01 00:00:00+00:00',
'2020-01-01 00:00:00+00:00', '2040-01-01 00:00:00+00:00',
'2060-01-01 00:00:00+00:00', '2080-01-01 00:00:00+00:00',
'2100-01-01 00:00:00+00:00', '2120-01-01 00:00:00+00:00',
'2140-01-01 00:00:00+00:00', '2160-01-01 00:00:00+00:00',
'2180-01-01 00:00:00+00:00', '2200-01-01 00:00:00+00:00']
],
[datetime.timedelta(weeks=52),
['1997-01-01 00:00:00+00:00', '1997-02-01 00:00:00+00:00',
'1997-03-01 00:00:00+00:00', '1997-04-01 00:00:00+00:00',
'1997-05-01 00:00:00+00:00', '1997-06-01 00:00:00+00:00',
'1997-07-01 00:00:00+00:00', '1997-08-01 00:00:00+00:00',
'1997-09-01 00:00:00+00:00', '1997-10-01 00:00:00+00:00',
'1997-11-01 00:00:00+00:00', '1997-12-01 00:00:00+00:00']
],
[datetime.timedelta(days=141),
['1997-01-01 00:00:00+00:00', '1997-01-22 00:00:00+00:00',
'1997-02-01 00:00:00+00:00', '1997-02-22 00:00:00+00:00',
'1997-03-01 00:00:00+00:00', '1997-03-22 00:00:00+00:00',
'1997-04-01 00:00:00+00:00', '1997-04-22 00:00:00+00:00',
'1997-05-01 00:00:00+00:00', '1997-05-22 00:00:00+00:00']
],
[datetime.timedelta(days=40),
['1997-01-01 00:00:00+00:00', '1997-01-08 00:00:00+00:00',
'1997-01-15 00:00:00+00:00', '1997-01-22 00:00:00+00:00',
'1997-01-29 00:00:00+00:00', '1997-02-01 00:00:00+00:00',
'1997-02-08 00:00:00+00:00']
],
[datetime.timedelta(hours=40),
['1997-01-01 00:00:00+00:00', '1997-01-01 04:00:00+00:00',
'1997-01-01 08:00:00+00:00', '1997-01-01 12:00:00+00:00',
'1997-01-01 16:00:00+00:00', '1997-01-01 20:00:00+00:00',
'1997-01-02 00:00:00+00:00', '1997-01-02 04:00:00+00:00',
'1997-01-02 08:00:00+00:00', '1997-01-02 12:00:00+00:00',
'1997-01-02 16:00:00+00:00']
],
[datetime.timedelta(minutes=20),
['1997-01-01 00:00:00+00:00', '1997-01-01 00:05:00+00:00',
'1997-01-01 00:10:00+00:00', '1997-01-01 00:15:00+00:00',
'1997-01-01 00:20:00+00:00']
],
[datetime.timedelta(seconds=40),
['1997-01-01 00:00:00+00:00', '1997-01-01 00:00:05+00:00',
'1997-01-01 00:00:10+00:00', '1997-01-01 00:00:15+00:00',
'1997-01-01 00:00:20+00:00', '1997-01-01 00:00:25+00:00',
'1997-01-01 00:00:30+00:00', '1997-01-01 00:00:35+00:00',
'1997-01-01 00:00:40+00:00']
],
[datetime.timedelta(microseconds=1500),
['1996-12-31 23:59:59.999500+00:00',
'1997-01-01 00:00:00+00:00',
'1997-01-01 00:00:00.000500+00:00',
'1997-01-01 00:00:00.001000+00:00',
'1997-01-01 00:00:00.001500+00:00']
],
)
for t_delta, expected in results:
d2 = d1 + t_delta
locator = _create_auto_date_locator(d1, d2)
assert list(map(str, mdates.num2date(locator()))) == expected
@image_comparison(baseline_images=['date_inverted_limit'],
extensions=['png'])
def test_date_inverted_limit():
# test ax hline with date inputs
t0 = datetime.datetime(2009, 1, 20)
tf = datetime.datetime(2009, 1, 31)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.axhline(t0, color="blue", lw=3)
ax.set_ylim(t0 - datetime.timedelta(days=5),
tf + datetime.timedelta(days=5))
ax.invert_yaxis()
fig.subplots_adjust(left=0.25)
def _test_date2num_dst(date_range, tz_convert):
# Timezones
BRUSSELS = pytz.timezone('Europe/Brussels')
UTC = pytz.UTC
# Create a list of timezone-aware datetime objects in UTC
# Interval is 0b0.0000011 days, to prevent float rounding issues
dtstart = datetime.datetime(2014, 3, 30, 0, 0, tzinfo=UTC)
interval = datetime.timedelta(minutes=33, seconds=45)
interval_days = 0.0234375 # 2025 / 86400 seconds
N = 8
dt_utc = date_range(start=dtstart, freq=interval, periods=N)
dt_bxl = tz_convert(dt_utc, BRUSSELS)
expected_ordinalf = [735322.0 + (i * interval_days) for i in range(N)]
actual_ordinalf = list(mdates.date2num(dt_bxl))
assert actual_ordinalf == expected_ordinalf
def test_date2num_dst():
# Test for github issue #3896, but in date2num around DST transitions
# with a timezone-aware pandas date_range object.
class dt_tzaware(datetime.datetime):
"""
This bug specifically occurs because of the normalization behavior of
pandas Timestamp objects, so in order to replicate it, we need a
datetime-like object that applies timezone normalization after
subtraction.
"""
def __sub__(self, other):
r = super(dt_tzaware, self).__sub__(other)
tzinfo = getattr(r, 'tzinfo', None)
if tzinfo is not None:
localizer = getattr(tzinfo, 'normalize', None)
if localizer is not None:
r = tzinfo.normalize(r)
if isinstance(r, datetime.datetime):
r = self.mk_tzaware(r)
return r
def __add__(self, other):
return self.mk_tzaware(super(dt_tzaware, self).__add__(other))
def astimezone(self, tzinfo):
dt = super(dt_tzaware, self).astimezone(tzinfo)
return self.mk_tzaware(dt)
@classmethod
def mk_tzaware(cls, datetime_obj):
kwargs = {}
attrs = ('year',
'month',
'day',
'hour',
'minute',
'second',
'microsecond',
'tzinfo')
for attr in attrs:
val = getattr(datetime_obj, attr, None)
if val is not None:
kwargs[attr] = val
return cls(**kwargs)
# Define a date_range function similar to pandas.date_range
def date_range(start, freq, periods):
dtstart = dt_tzaware.mk_tzaware(start)
return [dtstart + (i * freq) for i in range(periods)]
# Define a tz_convert function that converts a list to a new time zone.
def tz_convert(dt_list, tzinfo):
return [d.astimezone(tzinfo) for d in dt_list]
_test_date2num_dst(date_range, tz_convert)
def test_date2num_dst_pandas(pd):
# Test for github issue #3896, but in date2num around DST transitions
# with a timezone-aware pandas date_range object.
def tz_convert(*args):
return pd.DatetimeIndex.tz_convert(*args).astype(object)
_test_date2num_dst(pd.date_range, tz_convert)
@pytest.mark.parametrize("attach_tz, get_tz", [
(lambda dt, zi: zi.localize(dt), lambda n: pytz.timezone(n)),
(lambda dt, zi: dt.replace(tzinfo=zi), lambda n: dateutil.tz.gettz(n))])
def test_rrulewrapper(attach_tz, get_tz):
SYD = get_tz('Australia/Sydney')
dtstart = attach_tz(datetime.datetime(2017, 4, 1, 0), SYD)
dtend = attach_tz(datetime.datetime(2017, 4, 4, 0), SYD)
rule = mdates.rrulewrapper(freq=dateutil.rrule.DAILY, dtstart=dtstart)
act = rule.between(dtstart, dtend)
exp = [datetime.datetime(2017, 4, 1, 13, tzinfo=dateutil.tz.tzutc()),
datetime.datetime(2017, 4, 2, 14, tzinfo=dateutil.tz.tzutc())]
assert act == exp
def test_DayLocator():
with pytest.raises(ValueError):
mdates.DayLocator(interval=-1)
with pytest.raises(ValueError):
mdates.DayLocator(interval=-1.5)
with pytest.raises(ValueError):
mdates.DayLocator(interval=0)
with pytest.raises(ValueError):
mdates.DayLocator(interval=1.3)
mdates.DayLocator(interval=1.0)
def test_tz_utc():
dt = datetime.datetime(1970, 1, 1, tzinfo=mdates.UTC)
dt.tzname()
@pytest.mark.parametrize("x, tdelta",
[(1, datetime.timedelta(days=1)),
([1, 1.5], [datetime.timedelta(days=1),
datetime.timedelta(days=1.5)])])
def test_num2timedelta(x, tdelta):
dt = mdates.num2timedelta(x)
assert dt == tdelta
| 24,373 | 37.9984 | 89 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_lines.py | """
Tests specific to the lines module.
"""
from __future__ import absolute_import, division, print_function
import itertools
import matplotlib.lines as mlines
import pytest
from timeit import repeat
import numpy as np
from cycler import cycler
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
# Runtimes on a loaded system are inherently flaky. Not so much that a rerun
# won't help, hopefully.
@pytest.mark.flaky(reruns=3)
def test_invisible_Line_rendering():
"""
Github issue #1256 identified a bug in Line.draw method
Despite visibility attribute set to False, the draw method was not
returning early enough and some pre-rendering code was executed
though not necessary.
Consequence was an excessive draw time for invisible Line instances
holding a large number of points (Npts> 10**6)
"""
# Creates big x and y data:
N = 10**7
x = np.linspace(0,1,N)
y = np.random.normal(size=N)
# Create a plot figure:
fig = plt.figure()
ax = plt.subplot(111)
# Create a "big" Line instance:
l = mlines.Line2D(x,y)
l.set_visible(False)
# but don't add it to the Axis instance `ax`
# [here Interactive panning and zooming is pretty responsive]
# Time the canvas drawing:
t_no_line = min(repeat(fig.canvas.draw, number=1, repeat=3))
# (gives about 25 ms)
# Add the big invisible Line:
ax.add_line(l)
# [Now interactive panning and zooming is very slow]
# Time the canvas drawing:
t_unvisible_line = min(repeat(fig.canvas.draw, number=1, repeat=3))
# gives about 290 ms for N = 10**7 pts
slowdown_factor = (t_unvisible_line/t_no_line)
slowdown_threshold = 2 # trying to avoid false positive failures
assert slowdown_factor < slowdown_threshold
def test_set_line_coll_dash():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
np.random.seed(0)
# Testing setting linestyles for line collections.
# This should not produce an error.
cs = ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
assert True
@image_comparison(baseline_images=['line_dashes'], remove_text=True)
def test_line_dashes():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(range(10), linestyle=(0, (3, 3)), lw=5)
def test_line_colors():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(range(10), color='none')
ax.plot(range(10), color='r')
ax.plot(range(10), color='.3')
ax.plot(range(10), color=(1, 0, 0, 1))
ax.plot(range(10), color=(1, 0, 0))
fig.canvas.draw()
assert True
def test_linestyle_variants():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
for ls in ["-", "solid", "--", "dashed",
"-.", "dashdot", ":", "dotted"]:
ax.plot(range(10), linestyle=ls)
fig.canvas.draw()
assert True
def test_valid_linestyles():
line = mlines.Line2D([], [])
with pytest.raises(ValueError):
line.set_linestyle('aardvark')
@image_comparison(baseline_images=['drawstyle_variants'], remove_text=True,
extensions=["png"])
def test_drawstyle_variants():
fig, axs = plt.subplots(6)
dss = ["default", "steps-mid", "steps-pre", "steps-post", "steps", None]
# We want to check that drawstyles are properly handled even for very long
# lines (for which the subslice optimization is on); however, we need
# to zoom in so that the difference between the drawstyles is actually
# visible.
for ax, ds in zip(axs.flat, dss):
ax.plot(range(2000), drawstyle=ds)
ax.set(xlim=(0, 2), ylim=(0, 2))
def test_valid_drawstyles():
line = mlines.Line2D([], [])
with pytest.raises(ValueError):
line.set_drawstyle('foobar')
def test_set_drawstyle():
x = np.linspace(0, 2*np.pi, 10)
y = np.sin(x)
fig, ax = plt.subplots()
line, = ax.plot(x, y)
line.set_drawstyle("steps-pre")
assert len(line.get_path().vertices) == 2*len(x)-1
line.set_drawstyle("default")
assert len(line.get_path().vertices) == len(x)
@image_comparison(baseline_images=['line_collection_dashes'], remove_text=True)
def test_set_line_coll_dash_image():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
np.random.seed(0)
cs = ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
@image_comparison(baseline_images=['marker_fill_styles'], remove_text=True,
extensions=['png'])
def test_marker_fill_styles():
colors = itertools.cycle([[0, 0, 1], 'g', '#ff0000', 'c', 'm', 'y',
np.array([0, 0, 0])])
altcolor = 'lightgreen'
y = np.array([1, 1])
x = np.array([0, 9])
fig, ax = plt.subplots()
for j, marker in enumerate(mlines.Line2D.filled_markers):
for i, fs in enumerate(mlines.Line2D.fillStyles):
color = next(colors)
ax.plot(j * 10 + x, y + i + .5 * (j % 2),
marker=marker,
markersize=20,
markerfacecoloralt=altcolor,
fillstyle=fs,
label=fs,
linewidth=5,
color=color,
markeredgecolor=color,
markeredgewidth=2)
ax.set_ylim([0, 7.5])
ax.set_xlim([-5, 155])
@image_comparison(baseline_images=['scaled_lines'], style='default')
def test_lw_scaling():
th = np.linspace(0, 32)
fig, ax = plt.subplots()
lins_styles = ['dashed', 'dotted', 'dashdot']
cy = cycler(matplotlib.rcParams['axes.prop_cycle'])
for j, (ls, sty) in enumerate(zip(lins_styles, cy)):
for lw in np.linspace(.5, 10, 10):
ax.plot(th, j*np.ones(50) + .1 * lw, linestyle=ls, lw=lw, **sty)
def test_nan_is_sorted():
line = mlines.Line2D([], [])
assert line._is_sorted(np.array([1, 2, 3]))
assert line._is_sorted(np.array([1, np.nan, 3]))
assert not line._is_sorted([3, 5] + [np.nan] * 100 + [0, 2])
| 6,018 | 29.095 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_colors.py | from __future__ import absolute_import, division, print_function
import copy
import six
import itertools
import warnings
from distutils.version import LooseVersion as V
import numpy as np
import pytest
from numpy.testing.utils import assert_array_equal, assert_array_almost_equal
from matplotlib import cycler
import matplotlib
import matplotlib.colors as mcolors
import matplotlib.cm as cm
import matplotlib.colorbar as mcolorbar
import matplotlib.cbook as cbook
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
def test_resample():
"""
Github issue #6025 pointed to incorrect ListedColormap._resample;
here we test the method for LinearSegmentedColormap as well.
"""
n = 101
colorlist = np.empty((n, 4), float)
colorlist[:, 0] = np.linspace(0, 1, n)
colorlist[:, 1] = 0.2
colorlist[:, 2] = np.linspace(1, 0, n)
colorlist[:, 3] = 0.7
lsc = mcolors.LinearSegmentedColormap.from_list('lsc', colorlist)
lc = mcolors.ListedColormap(colorlist)
lsc3 = lsc._resample(3)
lc3 = lc._resample(3)
expected = np.array([[0.0, 0.2, 1.0, 0.7],
[0.5, 0.2, 0.5, 0.7],
[1.0, 0.2, 0.0, 0.7]], float)
assert_array_almost_equal(lsc3([0, 0.5, 1]), expected)
assert_array_almost_equal(lc3([0, 0.5, 1]), expected)
def test_colormap_copy():
cm = plt.cm.Reds
cm_copy = copy.copy(cm)
with np.errstate(invalid='ignore'):
ret1 = cm_copy([-1, 0, .5, 1, np.nan, np.inf])
cm2 = copy.copy(cm_copy)
cm2.set_bad('g')
with np.errstate(invalid='ignore'):
ret2 = cm_copy([-1, 0, .5, 1, np.nan, np.inf])
assert_array_equal(ret1, ret2)
def test_colormap_endian():
"""
Github issue #1005: a bug in putmask caused erroneous
mapping of 1.0 when input from a non-native-byteorder
array.
"""
cmap = cm.get_cmap("jet")
# Test under, over, and invalid along with values 0 and 1.
a = [-0.5, 0, 0.5, 1, 1.5, np.nan]
for dt in ["f2", "f4", "f8"]:
anative = np.ma.masked_invalid(np.array(a, dtype=dt))
aforeign = anative.byteswap().newbyteorder()
assert_array_equal(cmap(anative), cmap(aforeign))
def test_BoundaryNorm():
"""
Github issue #1258: interpolation was failing with numpy
1.7 pre-release.
"""
boundaries = [0, 1.1, 2.2]
vals = [-1, 0, 1, 2, 2.2, 4]
# Without interpolation
expected = [-1, 0, 0, 1, 2, 2]
ncolors = len(boundaries) - 1
bn = mcolors.BoundaryNorm(boundaries, ncolors)
assert_array_equal(bn(vals), expected)
# ncolors != len(boundaries) - 1 triggers interpolation
expected = [-1, 0, 0, 2, 3, 3]
ncolors = len(boundaries)
bn = mcolors.BoundaryNorm(boundaries, ncolors)
assert_array_equal(bn(vals), expected)
# more boundaries for a third color
boundaries = [0, 1, 2, 3]
vals = [-1, 0.1, 1.1, 2.2, 4]
ncolors = 5
expected = [-1, 0, 2, 4, 5]
bn = mcolors.BoundaryNorm(boundaries, ncolors)
assert_array_equal(bn(vals), expected)
# a scalar as input should not trigger an error and should return a scalar
boundaries = [0, 1, 2]
vals = [-1, 0.1, 1.1, 2.2]
bn = mcolors.BoundaryNorm(boundaries, 2)
expected = [-1, 0, 1, 2]
for v, ex in zip(vals, expected):
ret = bn(v)
assert isinstance(ret, six.integer_types)
assert_array_equal(ret, ex)
assert_array_equal(bn([v]), ex)
# same with interp
bn = mcolors.BoundaryNorm(boundaries, 3)
expected = [-1, 0, 2, 3]
for v, ex in zip(vals, expected):
ret = bn(v)
assert isinstance(ret, six.integer_types)
assert_array_equal(ret, ex)
assert_array_equal(bn([v]), ex)
# Clipping
bn = mcolors.BoundaryNorm(boundaries, 3, clip=True)
expected = [0, 0, 2, 2]
for v, ex in zip(vals, expected):
ret = bn(v)
assert isinstance(ret, six.integer_types)
assert_array_equal(ret, ex)
assert_array_equal(bn([v]), ex)
# Masked arrays
boundaries = [0, 1.1, 2.2]
vals = np.ma.masked_invalid([-1., np.NaN, 0, 1.4, 9])
# Without interpolation
ncolors = len(boundaries) - 1
bn = mcolors.BoundaryNorm(boundaries, ncolors)
expected = np.ma.masked_array([-1, -99, 0, 1, 2], mask=[0, 1, 0, 0, 0])
assert_array_equal(bn(vals), expected)
# With interpolation
bn = mcolors.BoundaryNorm(boundaries, len(boundaries))
expected = np.ma.masked_array([-1, -99, 0, 2, 3], mask=[0, 1, 0, 0, 0])
assert_array_equal(bn(vals), expected)
# Non-trivial masked arrays
vals = np.ma.masked_invalid([np.Inf, np.NaN])
assert np.all(bn(vals).mask)
vals = np.ma.masked_invalid([np.Inf])
assert np.all(bn(vals).mask)
def test_LogNorm():
"""
LogNorm ignored clip, now it has the same
behavior as Normalize, e.g., values > vmax are bigger than 1
without clip, with clip they are 1.
"""
ln = mcolors.LogNorm(clip=True, vmax=5)
assert_array_equal(ln([1, 6]), [0, 1.0])
def test_PowerNorm():
a = np.array([0, 0.5, 1, 1.5], dtype=float)
pnorm = mcolors.PowerNorm(1)
norm = mcolors.Normalize()
assert_array_almost_equal(norm(a), pnorm(a))
a = np.array([-0.5, 0, 2, 4, 8], dtype=float)
expected = [0, 0, 1/16, 1/4, 1]
pnorm = mcolors.PowerNorm(2, vmin=0, vmax=8)
assert_array_almost_equal(pnorm(a), expected)
assert pnorm(a[0]) == expected[0]
assert pnorm(a[2]) == expected[2]
assert_array_almost_equal(a[1:], pnorm.inverse(pnorm(a))[1:])
# Clip = True
a = np.array([-0.5, 0, 1, 8, 16], dtype=float)
expected = [0, 0, 0, 1, 1]
pnorm = mcolors.PowerNorm(2, vmin=2, vmax=8, clip=True)
assert_array_almost_equal(pnorm(a), expected)
assert pnorm(a[0]) == expected[0]
assert pnorm(a[-1]) == expected[-1]
# Clip = True at call time
a = np.array([-0.5, 0, 1, 8, 16], dtype=float)
expected = [0, 0, 0, 1, 1]
pnorm = mcolors.PowerNorm(2, vmin=2, vmax=8, clip=False)
assert_array_almost_equal(pnorm(a, clip=True), expected)
assert pnorm(a[0], clip=True) == expected[0]
assert pnorm(a[-1], clip=True) == expected[-1]
def test_Normalize():
norm = mcolors.Normalize()
vals = np.arange(-10, 10, 1, dtype=float)
_inverse_tester(norm, vals)
_scalar_tester(norm, vals)
_mask_tester(norm, vals)
# Handle integer input correctly (don't overflow when computing max-min,
# i.e. 127-(-128) here).
vals = np.array([-128, 127], dtype=np.int8)
norm = mcolors.Normalize(vals.min(), vals.max())
assert_array_equal(np.asarray(norm(vals)), [0, 1])
# Don't lose precision on longdoubles (float128 on Linux):
# for array inputs...
vals = np.array([1.2345678901, 9.8765432109], dtype=np.longdouble)
norm = mcolors.Normalize(vals.min(), vals.max())
assert_array_equal(np.asarray(norm(vals)), [0, 1])
# and for scalar ones.
eps = np.finfo(np.longdouble).resolution
norm = plt.Normalize(1, 1 + 100 * eps)
# This returns exactly 0.5 when longdouble is extended precision (80-bit),
# but only a value close to it when it is quadruple precision (128-bit).
assert 0 < norm(1 + 50 * eps) < 1
def test_SymLogNorm():
"""
Test SymLogNorm behavior
"""
norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2)
vals = np.array([-30, -1, 2, 6], dtype=float)
normed_vals = norm(vals)
expected = [0., 0.53980074, 0.826991, 1.02758204]
assert_array_almost_equal(normed_vals, expected)
_inverse_tester(norm, vals)
_scalar_tester(norm, vals)
_mask_tester(norm, vals)
# Ensure that specifying vmin returns the same result as above
norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2)
normed_vals = norm(vals)
assert_array_almost_equal(normed_vals, expected)
def test_SymLogNorm_colorbar():
"""
Test un-called SymLogNorm in a colorbar.
"""
norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
fig = plt.figure()
cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
plt.close(fig)
def test_SymLogNorm_single_zero():
"""
Test SymLogNorm to ensure it is not adding sub-ticks to zero label
"""
fig = plt.figure()
norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
ticks = cbar.get_ticks()
assert sum(ticks == 0) == 1
plt.close(fig)
def _inverse_tester(norm_instance, vals):
"""
Checks if the inverse of the given normalization is working.
"""
assert_array_almost_equal(norm_instance.inverse(norm_instance(vals)), vals)
def _scalar_tester(norm_instance, vals):
"""
Checks if scalars and arrays are handled the same way.
Tests only for float.
"""
scalar_result = [norm_instance(float(v)) for v in vals]
assert_array_almost_equal(scalar_result, norm_instance(vals))
def _mask_tester(norm_instance, vals):
"""
Checks mask handling
"""
masked_array = np.ma.array(vals)
masked_array[0] = np.ma.masked
assert_array_equal(masked_array.mask, norm_instance(masked_array).mask)
@image_comparison(baseline_images=['levels_and_colors'],
extensions=['png'])
def test_cmap_and_norm_from_levels_and_colors():
data = np.linspace(-2, 4, 49).reshape(7, 7)
levels = [-1, 2, 2.5, 3]
colors = ['red', 'green', 'blue', 'yellow', 'black']
extend = 'both'
cmap, norm = mcolors.from_levels_and_colors(levels, colors, extend=extend)
ax = plt.axes()
m = plt.pcolormesh(data, cmap=cmap, norm=norm)
plt.colorbar(m)
# Hide the axes labels (but not the colorbar ones, as they are useful)
ax.tick_params(labelleft=False, labelbottom=False)
def test_cmap_and_norm_from_levels_and_colors2():
levels = [-1, 2, 2.5, 3]
colors = ['red', (0, 1, 0), 'blue', (0.5, 0.5, 0.5), (0.0, 0.0, 0.0, 1.0)]
clr = mcolors.to_rgba_array(colors)
bad = (0.1, 0.1, 0.1, 0.1)
no_color = (0.0, 0.0, 0.0, 0.0)
masked_value = 'masked_value'
# Define the test values which are of interest.
# Note: levels are lev[i] <= v < lev[i+1]
tests = [('both', None, {-2: clr[0],
-1: clr[1],
2: clr[2],
2.25: clr[2],
3: clr[4],
3.5: clr[4],
masked_value: bad}),
('min', -1, {-2: clr[0],
-1: clr[1],
2: clr[2],
2.25: clr[2],
3: no_color,
3.5: no_color,
masked_value: bad}),
('max', -1, {-2: no_color,
-1: clr[0],
2: clr[1],
2.25: clr[1],
3: clr[3],
3.5: clr[3],
masked_value: bad}),
('neither', -2, {-2: no_color,
-1: clr[0],
2: clr[1],
2.25: clr[1],
3: no_color,
3.5: no_color,
masked_value: bad}),
]
for extend, i1, cases in tests:
cmap, norm = mcolors.from_levels_and_colors(levels, colors[0:i1],
extend=extend)
cmap.set_bad(bad)
for d_val, expected_color in cases.items():
if d_val == masked_value:
d_val = np.ma.array([1], mask=True)
else:
d_val = [d_val]
assert_array_equal(expected_color, cmap(norm(d_val))[0],
'Wih extend={0!r} and data '
'value={1!r}'.format(extend, d_val))
with pytest.raises(ValueError):
mcolors.from_levels_and_colors(levels, colors)
def test_rgb_hsv_round_trip():
for a_shape in [(500, 500, 3), (500, 3), (1, 3), (3,)]:
np.random.seed(0)
tt = np.random.random(a_shape)
assert_array_almost_equal(tt,
mcolors.hsv_to_rgb(mcolors.rgb_to_hsv(tt)))
assert_array_almost_equal(tt,
mcolors.rgb_to_hsv(mcolors.hsv_to_rgb(tt)))
def test_autoscale_masked():
# Test for #2336. Previously fully masked data would trigger a ValueError.
data = np.ma.masked_all((12, 20))
plt.pcolor(data)
plt.draw()
def test_colors_no_float():
# Gray must be a string to distinguish 3-4 grays from RGB or RGBA.
with pytest.raises(ValueError):
mcolors.to_rgba(0.4)
@image_comparison(baseline_images=['light_source_shading_topo'],
extensions=['png'])
def test_light_source_topo_surface():
"""Shades a DEM using different v.e.'s and blend modes."""
fname = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
dem = np.load(fname)
elev = dem['elevation']
# Get the true cellsize in meters for accurate vertical exaggeration
# Convert from decimal degrees to meters
dx, dy = dem['dx'], dem['dy']
dx = 111320.0 * dx * np.cos(dem['ymin'])
dy = 111320.0 * dy
dem.close()
ls = mcolors.LightSource(315, 45)
cmap = cm.gist_earth
fig, axes = plt.subplots(nrows=3, ncols=3)
for row, mode in zip(axes, ['hsv', 'overlay', 'soft']):
for ax, ve in zip(row, [0.1, 1, 10]):
rgb = ls.shade(elev, cmap, vert_exag=ve, dx=dx, dy=dy,
blend_mode=mode)
ax.imshow(rgb)
ax.set(xticks=[], yticks=[])
def test_light_source_shading_default():
"""Array comparison test for the default "hsv" blend mode. Ensure the
default result doesn't change without warning."""
y, x = np.mgrid[-1.2:1.2:8j, -1.2:1.2:8j]
z = 10 * np.cos(x**2 + y**2)
cmap = plt.cm.copper
ls = mcolors.LightSource(315, 45)
rgb = ls.shade(z, cmap)
# Result stored transposed and rounded for more compact display...
expect = np.array(
[[[0.00, 0.45, 0.90, 0.90, 0.82, 0.62, 0.28, 0.00],
[0.45, 0.94, 0.99, 1.00, 1.00, 0.96, 0.65, 0.17],
[0.90, 0.99, 1.00, 1.00, 1.00, 1.00, 0.94, 0.35],
[0.90, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.49],
[0.82, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.41],
[0.62, 0.96, 1.00, 1.00, 1.00, 1.00, 0.90, 0.07],
[0.28, 0.65, 0.94, 1.00, 1.00, 0.90, 0.35, 0.01],
[0.00, 0.17, 0.35, 0.49, 0.41, 0.07, 0.01, 0.00]],
[[0.00, 0.28, 0.59, 0.72, 0.62, 0.40, 0.18, 0.00],
[0.28, 0.78, 0.93, 0.92, 0.83, 0.66, 0.39, 0.11],
[0.59, 0.93, 0.99, 1.00, 0.92, 0.75, 0.50, 0.21],
[0.72, 0.92, 1.00, 0.99, 0.93, 0.76, 0.51, 0.18],
[0.62, 0.83, 0.92, 0.93, 0.87, 0.68, 0.42, 0.08],
[0.40, 0.66, 0.75, 0.76, 0.68, 0.52, 0.23, 0.02],
[0.18, 0.39, 0.50, 0.51, 0.42, 0.23, 0.00, 0.00],
[0.00, 0.11, 0.21, 0.18, 0.08, 0.02, 0.00, 0.00]],
[[0.00, 0.18, 0.38, 0.46, 0.39, 0.26, 0.11, 0.00],
[0.18, 0.50, 0.70, 0.75, 0.64, 0.44, 0.25, 0.07],
[0.38, 0.70, 0.91, 0.98, 0.81, 0.51, 0.29, 0.13],
[0.46, 0.75, 0.98, 0.96, 0.84, 0.48, 0.22, 0.12],
[0.39, 0.64, 0.81, 0.84, 0.71, 0.31, 0.11, 0.05],
[0.26, 0.44, 0.51, 0.48, 0.31, 0.10, 0.03, 0.01],
[0.11, 0.25, 0.29, 0.22, 0.11, 0.03, 0.00, 0.00],
[0.00, 0.07, 0.13, 0.12, 0.05, 0.01, 0.00, 0.00]],
[[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]]
]).T
if (V(np.__version__) == V('1.9.0')):
# Numpy 1.9.0 uses a 2. order algorithm on the edges by default
# This was changed back again in 1.9.1
expect = expect[1:-1, 1:-1, :]
rgb = rgb[1:-1, 1:-1, :]
assert_array_almost_equal(rgb, expect, decimal=2)
@pytest.mark.xfail(V('1.7.0') <= V(np.__version__) <= V('1.9.0'),
reason='NumPy version is not buggy')
# Numpy 1.9.1 fixed a bug in masked arrays which resulted in
# additional elements being masked when calculating the gradient thus
# the output is different with earlier numpy versions.
def test_light_source_masked_shading():
"""Array comparison test for a surface with a masked portion. Ensures that
we don't wind up with "fringes" of odd colors around masked regions."""
y, x = np.mgrid[-1.2:1.2:8j, -1.2:1.2:8j]
z = 10 * np.cos(x**2 + y**2)
z = np.ma.masked_greater(z, 9.9)
cmap = plt.cm.copper
ls = mcolors.LightSource(315, 45)
rgb = ls.shade(z, cmap)
# Result stored transposed and rounded for more compact display...
expect = np.array(
[[[0.00, 0.46, 0.91, 0.91, 0.84, 0.64, 0.29, 0.00],
[0.46, 0.96, 1.00, 1.00, 1.00, 0.97, 0.67, 0.18],
[0.91, 1.00, 1.00, 1.00, 1.00, 1.00, 0.96, 0.36],
[0.91, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 0.51],
[0.84, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 0.44],
[0.64, 0.97, 1.00, 1.00, 1.00, 1.00, 0.94, 0.09],
[0.29, 0.67, 0.96, 1.00, 1.00, 0.94, 0.38, 0.01],
[0.00, 0.18, 0.36, 0.51, 0.44, 0.09, 0.01, 0.00]],
[[0.00, 0.29, 0.61, 0.75, 0.64, 0.41, 0.18, 0.00],
[0.29, 0.81, 0.95, 0.93, 0.85, 0.68, 0.40, 0.11],
[0.61, 0.95, 1.00, 0.78, 0.78, 0.77, 0.52, 0.22],
[0.75, 0.93, 0.78, 0.00, 0.00, 0.78, 0.54, 0.19],
[0.64, 0.85, 0.78, 0.00, 0.00, 0.78, 0.45, 0.08],
[0.41, 0.68, 0.77, 0.78, 0.78, 0.55, 0.25, 0.02],
[0.18, 0.40, 0.52, 0.54, 0.45, 0.25, 0.00, 0.00],
[0.00, 0.11, 0.22, 0.19, 0.08, 0.02, 0.00, 0.00]],
[[0.00, 0.19, 0.39, 0.48, 0.41, 0.26, 0.12, 0.00],
[0.19, 0.52, 0.73, 0.78, 0.66, 0.46, 0.26, 0.07],
[0.39, 0.73, 0.95, 0.50, 0.50, 0.53, 0.30, 0.14],
[0.48, 0.78, 0.50, 0.00, 0.00, 0.50, 0.23, 0.12],
[0.41, 0.66, 0.50, 0.00, 0.00, 0.50, 0.11, 0.05],
[0.26, 0.46, 0.53, 0.50, 0.50, 0.11, 0.03, 0.01],
[0.12, 0.26, 0.30, 0.23, 0.11, 0.03, 0.00, 0.00],
[0.00, 0.07, 0.14, 0.12, 0.05, 0.01, 0.00, 0.00]],
[[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]],
]).T
assert_array_almost_equal(rgb, expect, decimal=2)
def test_light_source_hillshading():
"""Compare the current hillshading method against one that should be
mathematically equivalent. Illuminates a cone from a range of angles."""
def alternative_hillshade(azimuth, elev, z):
illum = _sph2cart(*_azimuth2math(azimuth, elev))
illum = np.array(illum)
dy, dx = np.gradient(-z)
dy = -dy
dz = np.ones_like(dy)
normals = np.dstack([dx, dy, dz])
dividers = np.zeros_like(z)[..., None]
for i, mat in enumerate(normals):
for j, vec in enumerate(mat):
dividers[i, j, 0] = np.linalg.norm(vec)
normals /= dividers
# once we drop support for numpy 1.7.x the above can be written as
# normals /= np.linalg.norm(normals, axis=2)[..., None]
# aviding the double loop.
intensity = np.tensordot(normals, illum, axes=(2, 0))
intensity -= intensity.min()
intensity /= intensity.ptp()
return intensity
y, x = np.mgrid[5:0:-1, :5]
z = -np.hypot(x - x.mean(), y - y.mean())
for az, elev in itertools.product(range(0, 390, 30), range(0, 105, 15)):
ls = mcolors.LightSource(az, elev)
h1 = ls.hillshade(z)
h2 = alternative_hillshade(az, elev, z)
assert_array_almost_equal(h1, h2)
def test_light_source_planar_hillshading():
"""Ensure that the illumination intensity is correct for planar
surfaces."""
def plane(azimuth, elevation, x, y):
"""Create a plane whose normal vector is at the given azimuth and
elevation."""
theta, phi = _azimuth2math(azimuth, elevation)
a, b, c = _sph2cart(theta, phi)
z = -(a*x + b*y) / c
return z
def angled_plane(azimuth, elevation, angle, x, y):
"""Create a plane whose normal vector is at an angle from the given
azimuth and elevation."""
elevation = elevation + angle
if elevation > 90:
azimuth = (azimuth + 180) % 360
elevation = (90 - elevation) % 90
return plane(azimuth, elevation, x, y)
y, x = np.mgrid[5:0:-1, :5]
for az, elev in itertools.product(range(0, 390, 30), range(0, 105, 15)):
ls = mcolors.LightSource(az, elev)
# Make a plane at a range of angles to the illumination
for angle in range(0, 105, 15):
z = angled_plane(az, elev, angle, x, y)
h = ls.hillshade(z)
assert_array_almost_equal(h, np.cos(np.radians(angle)))
def test_color_names():
assert mcolors.to_hex("blue") == "#0000ff"
assert mcolors.to_hex("xkcd:blue") == "#0343df"
assert mcolors.to_hex("tab:blue") == "#1f77b4"
def _sph2cart(theta, phi):
x = np.cos(theta) * np.sin(phi)
y = np.sin(theta) * np.sin(phi)
z = np.cos(phi)
return x, y, z
def _azimuth2math(azimuth, elevation):
"""Converts from clockwise-from-north and up-from-horizontal to
mathematical conventions."""
theta = np.radians((90 - azimuth) % 360)
phi = np.radians(90 - elevation)
return theta, phi
def test_pandas_iterable(pd):
# Using a list or series yields equivalent
# color maps, i.e the series isn't seen as
# a single color
lst = ['red', 'blue', 'green']
s = pd.Series(lst)
cm1 = mcolors.ListedColormap(lst, N=5)
cm2 = mcolors.ListedColormap(s, N=5)
assert_array_equal(cm1.colors, cm2.colors)
@pytest.mark.parametrize('name', sorted(cm.cmap_d))
def test_colormap_reversing(name):
"""Check the generated _lut data of a colormap and corresponding
reversed colormap if they are almost the same."""
cmap = plt.get_cmap(name)
cmap_r = cmap.reversed()
if not cmap_r._isinit:
cmap._init()
cmap_r._init()
assert_array_almost_equal(cmap._lut[:-3], cmap_r._lut[-4::-1])
def test_cn():
matplotlib.rcParams['axes.prop_cycle'] = cycler('color',
['blue', 'r'])
assert mcolors.to_hex("C0") == '#0000ff'
assert mcolors.to_hex("C1") == '#ff0000'
matplotlib.rcParams['axes.prop_cycle'] = cycler('color',
['xkcd:blue', 'r'])
assert mcolors.to_hex("C0") == '#0343df'
assert mcolors.to_hex("C1") == '#ff0000'
matplotlib.rcParams['axes.prop_cycle'] = cycler('color', ['8e4585', 'r'])
assert mcolors.to_hex("C0") == '#8e4585'
# if '8e4585' gets parsed as a float before it gets detected as a hex
# colour it will be interpreted as a very large number.
# this mustn't happen.
assert mcolors.to_rgb("C0")[0] != np.inf
def test_conversions():
# to_rgba_array("none") returns a (0, 4) array.
assert_array_equal(mcolors.to_rgba_array("none"), np.zeros((0, 4)))
# a list of grayscale levels, not a single color.
assert_array_equal(
mcolors.to_rgba_array([".2", ".5", ".8"]),
np.vstack([mcolors.to_rgba(c) for c in [".2", ".5", ".8"]]))
# alpha is properly set.
assert mcolors.to_rgba((1, 1, 1), .5) == (1, 1, 1, .5)
assert mcolors.to_rgba(".1", .5) == (.1, .1, .1, .5)
# builtin round differs between py2 and py3.
assert mcolors.to_hex((.7, .7, .7)) == "#b2b2b2"
# hex roundtrip.
hex_color = "#1234abcd"
assert mcolors.to_hex(mcolors.to_rgba(hex_color), keep_alpha=True) == \
hex_color
def test_grey_gray():
color_mapping = mcolors._colors_full_map
for k in color_mapping.keys():
if 'grey' in k:
assert color_mapping[k] == color_mapping[k.replace('grey', 'gray')]
if 'gray' in k:
assert color_mapping[k] == color_mapping[k.replace('gray', 'grey')]
def test_tableau_order():
dflt_cycle = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728',
'#9467bd', '#8c564b', '#e377c2', '#7f7f7f',
'#bcbd22', '#17becf']
assert list(mcolors.TABLEAU_COLORS.values()) == dflt_cycle
def test_ndarray_subclass_norm(recwarn):
# Emulate an ndarray subclass that handles units
# which objects when adding or subtracting with other
# arrays. See #6622 and #8696
class MyArray(np.ndarray):
def __isub__(self, other):
raise RuntimeError
def __add__(self, other):
raise RuntimeError
data = np.arange(-10, 10, 1, dtype=float)
data.shape = (10, 2)
mydata = data.view(MyArray)
for norm in [mcolors.Normalize(), mcolors.LogNorm(),
mcolors.SymLogNorm(3, vmax=5, linscale=1),
mcolors.Normalize(vmin=mydata.min(), vmax=mydata.max()),
mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max()),
mcolors.PowerNorm(1)]:
assert_array_equal(norm(mydata), norm(data))
fig, ax = plt.subplots()
ax.imshow(mydata, norm=norm)
fig.canvas.draw()
if isinstance(norm, mcolors.PowerNorm):
assert len(recwarn) == 1
warn = recwarn.pop(UserWarning)
assert ('Power-law scaling on negative values is ill-defined'
in str(warn.message))
else:
assert len(recwarn) == 0
recwarn.clear()
def test_same_color():
assert mcolors.same_color('k', (0, 0, 0))
assert not mcolors.same_color('w', (1, 1, 0))
| 26,431 | 35.060027 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_mlab.py | from __future__ import absolute_import, division, print_function
import six
import tempfile
import warnings
from numpy.testing import (assert_allclose, assert_almost_equal,
assert_array_equal, assert_array_almost_equal_nulp)
import numpy.ma.testutils as matest
import numpy as np
import datetime as datetime
import pytest
import matplotlib.mlab as mlab
import matplotlib.cbook as cbook
from matplotlib.cbook.deprecation import MatplotlibDeprecationWarning
try:
from mpl_toolkits.natgrid import _natgrid
HAS_NATGRID = True
except ImportError:
HAS_NATGRID = False
'''
A lot of mlab.py has been deprecated in Matplotlib 2.2 and is scheduled for
removal in the future. The tests that use deprecated methods have a block
to catch the deprecation warning, and can be removed with the mlab code is
removed.
'''
def test_colinear_pca():
with pytest.warns(MatplotlibDeprecationWarning):
a = mlab.PCA._get_colinear()
pca = mlab.PCA(a)
assert_allclose(pca.fracs[2:], 0., atol=1e-8)
assert_allclose(pca.Y[:, 2:], 0., atol=1e-8)
@pytest.mark.parametrize('input', [
# test odd lengths
[1, 2, 3],
# test even lengths
[1, 2, 3, 4],
# derived from email sent by jason-sage to MPL-user on 20090914
[1, 1, 2, 2, 1, 2, 4, 3, 2, 2, 2, 3, 4, 5, 6, 7, 8, 9, 7, 6, 4, 5, 5],
],
ids=[
'odd length',
'even length',
'custom data',
])
@pytest.mark.parametrize('percentile', [
0,
50,
75,
100,
[0, 75, 100],
])
def test_prctile(input, percentile):
with pytest.warns(MatplotlibDeprecationWarning):
assert_allclose(mlab.prctile(input, percentile),
np.percentile(input, percentile))
@pytest.mark.parametrize('xmin, xmax, N', [
(.01, 1000., 6),
(.03, 1313., 7),
(.03, 1313., 0),
(.03, 1313., 1),
], ids=[
'tens',
'primes',
'none',
'single',
])
def test_logspace(xmin, xmax, N):
with pytest.warns(MatplotlibDeprecationWarning):
res = mlab.logspace(xmin, xmax, N)
targ = np.logspace(np.log10(xmin), np.log10(xmax), N)
assert_allclose(targ, res)
assert res.size == N
class TestStride(object):
def get_base(self, x):
y = x
while y.base is not None:
y = y.base
return y
def calc_window_target(self, x, NFFT, noverlap=0, axis=0):
'''This is an adaptation of the original window extraction
algorithm. This is here to test to make sure the new implementation
has the same result'''
step = NFFT - noverlap
ind = np.arange(0, len(x) - NFFT + 1, step)
n = len(ind)
result = np.zeros((NFFT, n))
# do the ffts of the slices
for i in range(n):
result[:, i] = x[ind[i]:ind[i]+NFFT]
if axis == 1:
result = result.T
return result
@pytest.mark.parametrize('shape', [(), (10, 1)], ids=['0D', '2D'])
def test_stride_windows_invalid_input_shape(self, shape):
x = np.arange(np.prod(shape)).reshape(shape)
with pytest.raises(ValueError):
mlab.stride_windows(x, 5)
@pytest.mark.parametrize('n, noverlap',
[(0, None), (11, None), (2, 2), (2, 3)],
ids=['n less than 1', 'n greater than input',
'noverlap greater than n',
'noverlap equal to n'])
def test_stride_windows_invalid_params(self, n, noverlap):
x = np.arange(10)
with pytest.raises(ValueError):
mlab.stride_windows(x, n, noverlap)
@pytest.mark.parametrize('shape', [(), (10, 1)], ids=['0D', '2D'])
def test_stride_repeat_invalid_input_shape(self, shape):
x = np.arange(np.prod(shape)).reshape(shape)
with pytest.raises(ValueError):
mlab.stride_repeat(x, 5)
@pytest.mark.parametrize('axis', [-1, 2],
ids=['axis less than 0',
'axis greater than input shape'])
def test_stride_repeat_invalid_axis(self, axis):
x = np.array(0)
with pytest.raises(ValueError):
mlab.stride_repeat(x, 5, axis=axis)
def test_stride_repeat_n_lt_1_ValueError(self):
x = np.arange(10)
with pytest.raises(ValueError):
mlab.stride_repeat(x, 0)
@pytest.mark.parametrize('axis', [0, 1], ids=['axis0', 'axis1'])
@pytest.mark.parametrize('n', [1, 5], ids=['n1', 'n5'])
def test_stride_repeat(self, n, axis):
x = np.arange(10)
y = mlab.stride_repeat(x, n, axis=axis)
expected_shape = [10, 10]
expected_shape[axis] = n
yr = np.repeat(np.expand_dims(x, axis), n, axis=axis)
assert yr.shape == y.shape
assert_array_equal(yr, y)
assert tuple(expected_shape) == y.shape
assert self.get_base(y) is x
@pytest.mark.parametrize('axis', [0, 1], ids=['axis0', 'axis1'])
@pytest.mark.parametrize('n, noverlap',
[(1, 0), (5, 0), (15, 2), (13, -3)],
ids=['n1-noverlap0', 'n5-noverlap0',
'n15-noverlap2', 'n13-noverlapn3'])
def test_stride_windows(self, n, noverlap, axis):
x = np.arange(100)
y = mlab.stride_windows(x, n, noverlap=noverlap, axis=axis)
expected_shape = [0, 0]
expected_shape[axis] = n
expected_shape[1 - axis] = 100 // (n - noverlap)
yt = self.calc_window_target(x, n, noverlap=noverlap, axis=axis)
assert yt.shape == y.shape
assert_array_equal(yt, y)
assert tuple(expected_shape) == y.shape
assert self.get_base(y) is x
@pytest.mark.parametrize('axis', [0, 1], ids=['axis0', 'axis1'])
def test_stride_windows_n32_noverlap0_unflatten(self, axis):
n = 32
x = np.arange(n)[np.newaxis]
x1 = np.tile(x, (21, 1))
x2 = x1.flatten()
y = mlab.stride_windows(x2, n, axis=axis)
if axis == 0:
x1 = x1.T
assert y.shape == x1.shape
assert_array_equal(y, x1)
def test_stride_ensure_integer_type(self):
N = 100
x = np.empty(N + 20, dtype='>f4')
x.fill(np.NaN)
y = x[10:-10]
y.fill(0.3)
# previous to #3845 lead to corrupt access
y_strided = mlab.stride_windows(y, n=33, noverlap=0.6)
assert_array_equal(y_strided, 0.3)
# previous to #3845 lead to corrupt access
y_strided = mlab.stride_windows(y, n=33.3, noverlap=0)
assert_array_equal(y_strided, 0.3)
# even previous to #3845 could not find any problematic
# configuration however, let's be sure it's not accidentally
# introduced
y_strided = mlab.stride_repeat(y, n=33.815)
assert_array_equal(y_strided, 0.3)
@pytest.fixture
def tempcsv():
if six.PY2:
fd = tempfile.TemporaryFile(suffix='csv', mode="wb+")
else:
fd = tempfile.TemporaryFile(suffix='csv', mode="w+", newline='')
with fd:
yield fd
def test_recarray_csv_roundtrip(tempcsv):
expected = np.recarray((99,),
[(str('x'), float),
(str('y'), float),
(str('t'), float)])
# initialising all values: uninitialised memory sometimes produces
# floats that do not round-trip to string and back.
expected['x'][:] = np.linspace(-1e9, -1, 99)
expected['y'][:] = np.linspace(1, 1e9, 99)
expected['t'][:] = np.linspace(0, 0.01, 99)
with pytest.warns(MatplotlibDeprecationWarning):
mlab.rec2csv(expected, tempcsv)
tempcsv.seek(0)
actual = mlab.csv2rec(tempcsv)
assert_allclose(expected['x'], actual['x'])
assert_allclose(expected['y'], actual['y'])
assert_allclose(expected['t'], actual['t'])
def test_rec2csv_bad_shape_ValueError(tempcsv):
bad = np.recarray((99, 4), [(str('x'), float),
(str('y'), float)])
# the bad recarray should trigger a ValueError for having ndim > 1.
with pytest.warns(MatplotlibDeprecationWarning):
with pytest.raises(ValueError):
mlab.rec2csv(bad, tempcsv)
def test_csv2rec_names_with_comments(tempcsv):
tempcsv.write('# comment\n1,2,3\n4,5,6\n')
tempcsv.seek(0)
with pytest.warns(MatplotlibDeprecationWarning):
array = mlab.csv2rec(tempcsv, names='a,b,c')
assert len(array) == 2
assert len(array.dtype) == 3
@pytest.mark.parametrize('input, kwargs', [
('01/11/14\n'
'03/05/76 12:00:01 AM\n'
'07/09/83 5:17:34 PM\n'
'06/20/2054 2:31:45 PM\n'
'10/31/00 11:50:23 AM\n',
{}),
('11/01/14\n'
'05/03/76 12:00:01 AM\n'
'09/07/83 5:17:34 PM\n'
'20/06/2054 2:31:45 PM\n'
'31/10/00 11:50:23 AM\n',
{'dayfirst': True}),
('14/01/11\n'
'76/03/05 12:00:01 AM\n'
'83/07/09 5:17:34 PM\n'
'2054/06/20 2:31:45 PM\n'
'00/10/31 11:50:23 AM\n',
{'yearfirst': True}),
], ids=['usdate', 'dayfirst', 'yearfirst'])
def test_csv2rec_dates(tempcsv, input, kwargs):
tempcsv.write(input)
expected = [datetime.datetime(2014, 1, 11, 0, 0),
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
tempcsv.seek(0)
with pytest.warns(MatplotlibDeprecationWarning):
array = mlab.csv2rec(tempcsv, names='a', **kwargs)
assert_array_equal(array['a'].tolist(), expected)
def test_rec2txt_basic():
# str() calls around field names necessary b/c as of numpy 1.11
# dtype doesn't like unicode names (caused by unicode_literals import)
a = np.array([(1.0, 2, 'foo', 'bing'),
(2.0, 3, 'bar', 'blah')],
dtype=np.dtype([(str('x'), np.float32),
(str('y'), np.int8),
(str('s'), str, 3),
(str('s2'), str, 4)]))
truth = (' x y s s2\n'
' 1.000 2 foo bing \n'
' 2.000 3 bar blah ').splitlines()
with pytest.warns(MatplotlibDeprecationWarning):
assert mlab.rec2txt(a).splitlines() == truth
class TestWindow(object):
def setup(self):
np.random.seed(0)
n = 1000
self.sig_rand = np.random.standard_normal(n) + 100.
self.sig_ones = np.ones(n)
def check_window_apply_repeat(self, x, window, NFFT, noverlap):
'''This is an adaptation of the original window application
algorithm. This is here to test to make sure the new implementation
has the same result'''
step = NFFT - noverlap
ind = np.arange(0, len(x) - NFFT + 1, step)
n = len(ind)
result = np.zeros((NFFT, n))
if cbook.iterable(window):
windowVals = window
else:
windowVals = window(np.ones((NFFT,), x.dtype))
# do the ffts of the slices
for i in range(n):
result[:, i] = windowVals * x[ind[i]:ind[i]+NFFT]
return result
def test_window_none_rand(self):
res = mlab.window_none(self.sig_ones)
assert_array_equal(res, self.sig_ones)
def test_window_none_ones(self):
res = mlab.window_none(self.sig_rand)
assert_array_equal(res, self.sig_rand)
def test_window_hanning_rand(self):
targ = np.hanning(len(self.sig_rand)) * self.sig_rand
res = mlab.window_hanning(self.sig_rand)
assert_allclose(targ, res, atol=1e-06)
def test_window_hanning_ones(self):
targ = np.hanning(len(self.sig_ones))
res = mlab.window_hanning(self.sig_ones)
assert_allclose(targ, res, atol=1e-06)
def test_apply_window_1D_axis1_ValueError(self):
x = self.sig_rand
window = mlab.window_hanning
with pytest.raises(ValueError):
mlab.apply_window(x, window, axis=1, return_window=False)
def test_apply_window_1D_els_wrongsize_ValueError(self):
x = self.sig_rand
window = mlab.window_hanning(np.ones(x.shape[0]-1))
with pytest.raises(ValueError):
mlab.apply_window(x, window)
def test_apply_window_0D_ValueError(self):
x = np.array(0)
window = mlab.window_hanning
with pytest.raises(ValueError):
mlab.apply_window(x, window, axis=1, return_window=False)
def test_apply_window_3D_ValueError(self):
x = self.sig_rand[np.newaxis][np.newaxis]
window = mlab.window_hanning
with pytest.raises(ValueError):
mlab.apply_window(x, window, axis=1, return_window=False)
def test_apply_window_hanning_1D(self):
x = self.sig_rand
window = mlab.window_hanning
window1 = mlab.window_hanning(np.ones(x.shape[0]))
y, window2 = mlab.apply_window(x, window, return_window=True)
yt = window(x)
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
assert_array_equal(window1, window2)
def test_apply_window_hanning_1D_axis0(self):
x = self.sig_rand
window = mlab.window_hanning
y = mlab.apply_window(x, window, axis=0, return_window=False)
yt = window(x)
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_els_1D_axis0(self):
x = self.sig_rand
window = mlab.window_hanning(np.ones(x.shape[0]))
window1 = mlab.window_hanning
y = mlab.apply_window(x, window, axis=0, return_window=False)
yt = window1(x)
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_2D_axis0(self):
x = np.random.standard_normal([1000, 10]) + 100.
window = mlab.window_hanning
y = mlab.apply_window(x, window, axis=0, return_window=False)
yt = np.zeros_like(x)
for i in range(x.shape[1]):
yt[:, i] = window(x[:, i])
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_els1_2D_axis0(self):
x = np.random.standard_normal([1000, 10]) + 100.
window = mlab.window_hanning(np.ones(x.shape[0]))
window1 = mlab.window_hanning
y = mlab.apply_window(x, window, axis=0, return_window=False)
yt = np.zeros_like(x)
for i in range(x.shape[1]):
yt[:, i] = window1(x[:, i])
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_els2_2D_axis0(self):
x = np.random.standard_normal([1000, 10]) + 100.
window = mlab.window_hanning
window1 = mlab.window_hanning(np.ones(x.shape[0]))
y, window2 = mlab.apply_window(x, window, axis=0, return_window=True)
yt = np.zeros_like(x)
for i in range(x.shape[1]):
yt[:, i] = window1*x[:, i]
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
assert_array_equal(window1, window2)
def test_apply_window_hanning_els3_2D_axis0(self):
x = np.random.standard_normal([1000, 10]) + 100.
window = mlab.window_hanning
window1 = mlab.window_hanning(np.ones(x.shape[0]))
y, window2 = mlab.apply_window(x, window, axis=0, return_window=True)
yt = mlab.apply_window(x, window1, axis=0, return_window=False)
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
assert_array_equal(window1, window2)
def test_apply_window_hanning_2D_axis1(self):
x = np.random.standard_normal([10, 1000]) + 100.
window = mlab.window_hanning
y = mlab.apply_window(x, window, axis=1, return_window=False)
yt = np.zeros_like(x)
for i in range(x.shape[0]):
yt[i, :] = window(x[i, :])
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_2D__els1_axis1(self):
x = np.random.standard_normal([10, 1000]) + 100.
window = mlab.window_hanning(np.ones(x.shape[1]))
window1 = mlab.window_hanning
y = mlab.apply_window(x, window, axis=1, return_window=False)
yt = np.zeros_like(x)
for i in range(x.shape[0]):
yt[i, :] = window1(x[i, :])
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_2D_els2_axis1(self):
x = np.random.standard_normal([10, 1000]) + 100.
window = mlab.window_hanning
window1 = mlab.window_hanning(np.ones(x.shape[1]))
y, window2 = mlab.apply_window(x, window, axis=1, return_window=True)
yt = np.zeros_like(x)
for i in range(x.shape[0]):
yt[i, :] = window1 * x[i, :]
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
assert_array_equal(window1, window2)
def test_apply_window_hanning_2D_els3_axis1(self):
x = np.random.standard_normal([10, 1000]) + 100.
window = mlab.window_hanning
window1 = mlab.window_hanning(np.ones(x.shape[1]))
y = mlab.apply_window(x, window, axis=1, return_window=False)
yt = mlab.apply_window(x, window1, axis=1, return_window=False)
assert yt.shape == y.shape
assert x.shape == y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_stride_windows_hanning_2D_n13_noverlapn3_axis0(self):
x = self.sig_rand
window = mlab.window_hanning
yi = mlab.stride_windows(x, n=13, noverlap=2, axis=0)
y = mlab.apply_window(yi, window, axis=0, return_window=False)
yt = self.check_window_apply_repeat(x, window, 13, 2)
assert yt.shape == y.shape
assert x.shape != y.shape
assert_allclose(yt, y, atol=1e-06)
def test_apply_window_hanning_2D_stack_axis1(self):
ydata = np.arange(32)
ydata1 = ydata+5
ydata2 = ydata+3.3
ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
ycontrol2 = mlab.window_hanning(ydata2)
ydata = np.vstack([ydata1, ydata2])
ycontrol = np.vstack([ycontrol1, ycontrol2])
ydata = np.tile(ydata, (20, 1))
ycontrol = np.tile(ycontrol, (20, 1))
result = mlab.apply_window(ydata, mlab.window_hanning, axis=1,
return_window=False)
assert_allclose(ycontrol, result, atol=1e-08)
def test_apply_window_hanning_2D_stack_windows_axis1(self):
ydata = np.arange(32)
ydata1 = ydata+5
ydata2 = ydata+3.3
ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
ycontrol2 = mlab.window_hanning(ydata2)
ydata = np.vstack([ydata1, ydata2])
ycontrol = np.vstack([ycontrol1, ycontrol2])
ydata = np.tile(ydata, (20, 1))
ycontrol = np.tile(ycontrol, (20, 1))
result = mlab.apply_window(ydata, mlab.window_hanning, axis=1,
return_window=False)
assert_allclose(ycontrol, result, atol=1e-08)
def test_apply_window_hanning_2D_stack_windows_axis1_unflatten(self):
n = 32
ydata = np.arange(n)
ydata1 = ydata+5
ydata2 = ydata+3.3
ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
ycontrol2 = mlab.window_hanning(ydata2)
ydata = np.vstack([ydata1, ydata2])
ycontrol = np.vstack([ycontrol1, ycontrol2])
ydata = np.tile(ydata, (20, 1))
ycontrol = np.tile(ycontrol, (20, 1))
ydata = ydata.flatten()
ydata1 = mlab.stride_windows(ydata, 32, noverlap=0, axis=0)
result = mlab.apply_window(ydata1, mlab.window_hanning, axis=0,
return_window=False)
assert_allclose(ycontrol.T, result, atol=1e-08)
class TestDetrend(object):
def setup(self):
np.random.seed(0)
n = 1000
x = np.linspace(0., 100, n)
self.sig_zeros = np.zeros(n)
self.sig_off = self.sig_zeros + 100.
self.sig_slope = np.linspace(-10., 90., n)
self.sig_slope_mean = x - x.mean()
sig_rand = np.random.standard_normal(n)
sig_sin = np.sin(x*2*np.pi/(n/100))
sig_rand -= sig_rand.mean()
sig_sin -= sig_sin.mean()
self.sig_base = sig_rand + sig_sin
self.atol = 1e-08
def test_detrend_none_0D_zeros(self):
input = 0.
targ = input
res = mlab.detrend_none(input)
assert input == targ
def test_detrend_none_0D_zeros_axis1(self):
input = 0.
targ = input
res = mlab.detrend_none(input, axis=1)
assert input == targ
def test_detrend_str_none_0D_zeros(self):
input = 0.
targ = input
res = mlab.detrend(input, key='none')
assert input == targ
def test_detrend_detrend_none_0D_zeros(self):
input = 0.
targ = input
res = mlab.detrend(input, key=mlab.detrend_none)
assert input == targ
def test_detrend_none_0D_off(self):
input = 5.5
targ = input
res = mlab.detrend_none(input)
assert input == targ
def test_detrend_none_1D_off(self):
input = self.sig_off
targ = input
res = mlab.detrend_none(input)
assert_array_equal(res, targ)
def test_detrend_none_1D_slope(self):
input = self.sig_slope
targ = input
res = mlab.detrend_none(input)
assert_array_equal(res, targ)
def test_detrend_none_1D_base(self):
input = self.sig_base
targ = input
res = mlab.detrend_none(input)
assert_array_equal(res, targ)
def test_detrend_none_1D_base_slope_off_list(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = input.tolist()
res = mlab.detrend_none(input.tolist())
assert res == targ
def test_detrend_none_2D(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
input = np.vstack(arri)
targ = input
res = mlab.detrend_none(input)
assert_array_equal(res, targ)
def test_detrend_none_2D_T(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
input = np.vstack(arri)
targ = input
res = mlab.detrend_none(input.T)
assert_array_equal(res.T, targ)
def test_detrend_mean_0D_zeros(self):
input = 0.
targ = 0.
res = mlab.detrend_mean(input)
assert_almost_equal(res, targ)
def test_detrend_str_mean_0D_zeros(self):
input = 0.
targ = 0.
res = mlab.detrend(input, key='mean')
assert_almost_equal(res, targ)
def test_detrend_detrend_mean_0D_zeros(self):
input = 0.
targ = 0.
res = mlab.detrend(input, key=mlab.detrend_mean)
assert_almost_equal(res, targ)
def test_detrend_mean_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend_mean(input)
assert_almost_equal(res, targ)
def test_detrend_str_mean_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend(input, key='mean')
assert_almost_equal(res, targ)
def test_detrend_detrend_mean_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend(input, key=mlab.detrend_mean)
assert_almost_equal(res, targ)
def test_detrend_mean_1D_zeros(self):
input = self.sig_zeros
targ = self.sig_zeros
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_mean_1D_base(self):
input = self.sig_base
targ = self.sig_base
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_mean_1D_base_off(self):
input = self.sig_base + self.sig_off
targ = self.sig_base
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_mean_1D_base_slope(self):
input = self.sig_base + self.sig_slope
targ = self.sig_base + self.sig_slope_mean
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_mean_1D_base_slope_off(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=1e-08)
def test_detrend_mean_1D_base_slope_off_axis0(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.detrend_mean(input, axis=0)
assert_allclose(res, targ, atol=1e-08)
def test_detrend_mean_1D_base_slope_off_list(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.detrend_mean(input.tolist())
assert_allclose(res, targ, atol=1e-08)
def test_detrend_mean_1D_base_slope_off_list_axis0(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.detrend_mean(input.tolist(), axis=0)
assert_allclose(res, targ, atol=1e-08)
def test_demean_0D_off(self):
input = 5.5
targ = 0.
res = mlab.demean(input, axis=None)
assert_almost_equal(res, targ)
def test_demean_1D_base_slope_off(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.demean(input)
assert_allclose(res, targ, atol=1e-08)
def test_demean_1D_base_slope_off_axis0(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.demean(input, axis=0)
assert_allclose(res, targ, atol=1e-08)
def test_demean_1D_base_slope_off_list(self):
input = self.sig_base + self.sig_slope + self.sig_off
targ = self.sig_base + self.sig_slope_mean
res = mlab.demean(input.tolist())
assert_allclose(res, targ, atol=1e-08)
def test_detrend_mean_2D_default(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend_mean(input)
assert_allclose(res, targ, atol=1e-08)
def test_detrend_mean_2D_none(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend_mean(input, axis=None)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_mean_2D_none_T(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri).T
targ = np.vstack(arrt)
res = mlab.detrend_mean(input, axis=None)
assert_allclose(res.T, targ,
atol=1e-08)
def test_detrend_mean_2D_axis0(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.detrend_mean(input, axis=0)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_mean_2D_axis1(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend_mean(input, axis=1)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_mean_2D_axism1(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend_mean(input, axis=-1)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_2D_default(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend(input)
assert_allclose(res, targ, atol=1e-08)
def test_detrend_2D_none(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend(input, axis=None)
assert_allclose(res, targ, atol=1e-08)
def test_detrend_str_mean_2D_axis0(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.detrend(input, key='mean', axis=0)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_str_constant_2D_none_T(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri).T
targ = np.vstack(arrt)
res = mlab.detrend(input, key='constant', axis=None)
assert_allclose(res.T, targ,
atol=1e-08)
def test_detrend_str_default_2D_axis1(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend(input, key='default', axis=1)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_detrend_mean_2D_axis0(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.detrend(input, key=mlab.detrend_mean, axis=0)
assert_allclose(res, targ,
atol=1e-08)
def test_demean_2D_default(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.demean(input)
assert_allclose(res, targ,
atol=1e-08)
def test_demean_2D_none(self):
arri = [self.sig_off,
self.sig_base + self.sig_off]
arrt = [self.sig_zeros,
self.sig_base]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.demean(input, axis=None)
assert_allclose(res, targ,
atol=1e-08)
def test_demean_2D_axis0(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.demean(input, axis=0)
assert_allclose(res, targ,
atol=1e-08)
def test_demean_2D_axis1(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.demean(input, axis=1)
assert_allclose(res, targ,
atol=1e-08)
def test_demean_2D_axism1(self):
arri = [self.sig_base,
self.sig_base + self.sig_off,
self.sig_base + self.sig_slope,
self.sig_base + self.sig_off + self.sig_slope]
arrt = [self.sig_base,
self.sig_base,
self.sig_base + self.sig_slope_mean,
self.sig_base + self.sig_slope_mean]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.demean(input, axis=-1)
assert_allclose(res, targ,
atol=1e-08)
def test_detrend_bad_key_str_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.detrend(input, key='spam')
def test_detrend_bad_key_var_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.detrend(input, key=5)
def test_detrend_mean_0D_d0_ValueError(self):
input = 5.5
with pytest.raises(ValueError):
mlab.detrend_mean(input, axis=0)
def test_detrend_0D_d0_ValueError(self):
input = 5.5
with pytest.raises(ValueError):
mlab.detrend(input, axis=0)
def test_detrend_mean_1D_d1_ValueError(self):
input = self.sig_slope
with pytest.raises(ValueError):
mlab.detrend_mean(input, axis=1)
def test_detrend_1D_d1_ValueError(self):
input = self.sig_slope
with pytest.raises(ValueError):
mlab.detrend(input, axis=1)
def test_demean_1D_d1_ValueError(self):
input = self.sig_slope
with pytest.raises(ValueError):
mlab.demean(input, axis=1)
def test_detrend_mean_2D_d2_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.detrend_mean(input, axis=2)
def test_detrend_2D_d2_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.detrend(input, axis=2)
def test_demean_2D_d2_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.demean(input, axis=2)
def test_detrend_linear_0D_zeros(self):
input = 0.
targ = 0.
res = mlab.detrend_linear(input)
assert_almost_equal(res, targ)
def test_detrend_linear_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend_linear(input)
assert_almost_equal(res, targ)
def test_detrend_str_linear_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend(input, key='linear')
assert_almost_equal(res, targ)
def test_detrend_detrend_linear_0D_off(self):
input = 5.5
targ = 0.
res = mlab.detrend(input, key=mlab.detrend_linear)
assert_almost_equal(res, targ)
def test_detrend_linear_1d_off(self):
input = self.sig_off
targ = self.sig_zeros
res = mlab.detrend_linear(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_linear_1d_slope(self):
input = self.sig_slope
targ = self.sig_zeros
res = mlab.detrend_linear(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_linear_1d_slope_off(self):
input = self.sig_slope + self.sig_off
targ = self.sig_zeros
res = mlab.detrend_linear(input)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_str_linear_1d_slope_off(self):
input = self.sig_slope + self.sig_off
targ = self.sig_zeros
res = mlab.detrend(input, key='linear')
assert_allclose(res, targ, atol=self.atol)
def test_detrend_detrend_linear_1d_slope_off(self):
input = self.sig_slope + self.sig_off
targ = self.sig_zeros
res = mlab.detrend(input, key=mlab.detrend_linear)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_linear_1d_slope_off_list(self):
input = self.sig_slope + self.sig_off
targ = self.sig_zeros
res = mlab.detrend_linear(input.tolist())
assert_allclose(res, targ, atol=self.atol)
def test_detrend_linear_2D_ValueError(self):
input = self.sig_slope[np.newaxis]
with pytest.raises(ValueError):
mlab.detrend_linear(input)
def test_detrend_str_linear_2d_slope_off_axis0(self):
arri = [self.sig_off,
self.sig_slope,
self.sig_slope + self.sig_off]
arrt = [self.sig_zeros,
self.sig_zeros,
self.sig_zeros]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.detrend(input, key='linear', axis=0)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_detrend_linear_1d_slope_off_axis1(self):
arri = [self.sig_off,
self.sig_slope,
self.sig_slope + self.sig_off]
arrt = [self.sig_zeros,
self.sig_zeros,
self.sig_zeros]
input = np.vstack(arri).T
targ = np.vstack(arrt).T
res = mlab.detrend(input, key=mlab.detrend_linear, axis=0)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_str_linear_2d_slope_off_axis0(self):
arri = [self.sig_off,
self.sig_slope,
self.sig_slope + self.sig_off]
arrt = [self.sig_zeros,
self.sig_zeros,
self.sig_zeros]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend(input, key='linear', axis=1)
assert_allclose(res, targ, atol=self.atol)
def test_detrend_detrend_linear_1d_slope_off_axis1(self):
arri = [self.sig_off,
self.sig_slope,
self.sig_slope + self.sig_off]
arrt = [self.sig_zeros,
self.sig_zeros,
self.sig_zeros]
input = np.vstack(arri)
targ = np.vstack(arrt)
res = mlab.detrend(input, key=mlab.detrend_linear, axis=1)
assert_allclose(res, targ, atol=self.atol)
@pytest.mark.parametrize('iscomplex', [False, True],
ids=['real', 'complex'], scope='class')
@pytest.mark.parametrize('sides', ['onesided', 'twosided', 'default'],
scope='class')
@pytest.mark.parametrize(
'fstims,len_x,NFFT_density,nover_density,pad_to_density,pad_to_spectrum',
[
([], None, -1, -1, -1, -1),
([4], None, -1, -1, -1, -1),
([4, 5, 10], None, -1, -1, -1, -1),
([], None, None, -1, -1, None),
([], None, -1, -1, None, None),
([], None, None, -1, None, None),
([], 1024, 512, -1, -1, 128),
([], 256, -1, -1, 33, 257),
([], 255, 33, -1, -1, None),
([], 256, 128, -1, 256, 256),
([], None, -1, 32, -1, -1),
],
ids=[
'nosig',
'Fs4',
'FsAll',
'nosig_noNFFT',
'nosig_nopad_to',
'nosig_noNFFT_no_pad_to',
'nosig_trim',
'nosig_odd',
'nosig_oddlen',
'nosig_stretch',
'nosig_overlap',
],
scope='class')
class TestSpectral(object):
@pytest.fixture(scope='class', autouse=True)
def stim(self, request, fstims, iscomplex, sides, len_x, NFFT_density,
nover_density, pad_to_density, pad_to_spectrum):
Fs = 100.
x = np.arange(0, 10, 1 / Fs)
if len_x is not None:
x = x[:len_x]
# get the stimulus frequencies, defaulting to None
fstims = [Fs / fstim for fstim in fstims]
# get the constants, default to calculated values
if NFFT_density is None:
NFFT_density_real = 256
elif NFFT_density < 0:
NFFT_density_real = NFFT_density = 100
else:
NFFT_density_real = NFFT_density
if nover_density is None:
nover_density_real = 0
elif nover_density < 0:
nover_density_real = nover_density = NFFT_density_real // 2
else:
nover_density_real = nover_density
if pad_to_density is None:
pad_to_density_real = NFFT_density_real
elif pad_to_density < 0:
pad_to_density = int(2**np.ceil(np.log2(NFFT_density_real)))
pad_to_density_real = pad_to_density
else:
pad_to_density_real = pad_to_density
if pad_to_spectrum is None:
pad_to_spectrum_real = len(x)
elif pad_to_spectrum < 0:
pad_to_spectrum_real = pad_to_spectrum = len(x)
else:
pad_to_spectrum_real = pad_to_spectrum
if pad_to_spectrum is None:
NFFT_spectrum_real = NFFT_spectrum = pad_to_spectrum_real
else:
NFFT_spectrum_real = NFFT_spectrum = len(x)
nover_spectrum_real = nover_spectrum = 0
NFFT_specgram = NFFT_density
nover_specgram = nover_density
pad_to_specgram = pad_to_density
NFFT_specgram_real = NFFT_density_real
nover_specgram_real = nover_density_real
if sides == 'onesided' or (sides == 'default' and not iscomplex):
# frequencies for specgram, psd, and csd
# need to handle even and odd differently
if pad_to_density_real % 2:
freqs_density = np.linspace(0, Fs / 2,
num=pad_to_density_real,
endpoint=False)[::2]
else:
freqs_density = np.linspace(0, Fs / 2,
num=pad_to_density_real // 2 + 1)
# frequencies for complex, magnitude, angle, and phase spectrums
# need to handle even and odd differently
if pad_to_spectrum_real % 2:
freqs_spectrum = np.linspace(0, Fs / 2,
num=pad_to_spectrum_real,
endpoint=False)[::2]
else:
freqs_spectrum = np.linspace(0, Fs / 2,
num=pad_to_spectrum_real // 2 + 1)
else:
# frequencies for specgram, psd, and csd
# need to handle even and odd differentl
if pad_to_density_real % 2:
freqs_density = np.linspace(-Fs / 2, Fs / 2,
num=2 * pad_to_density_real,
endpoint=False)[1::2]
else:
freqs_density = np.linspace(-Fs / 2, Fs / 2,
num=pad_to_density_real,
endpoint=False)
# frequencies for complex, magnitude, angle, and phase spectrums
# need to handle even and odd differently
if pad_to_spectrum_real % 2:
freqs_spectrum = np.linspace(-Fs / 2, Fs / 2,
num=2 * pad_to_spectrum_real,
endpoint=False)[1::2]
else:
freqs_spectrum = np.linspace(-Fs / 2, Fs / 2,
num=pad_to_spectrum_real,
endpoint=False)
freqs_specgram = freqs_density
# time points for specgram
t_start = NFFT_specgram_real // 2
t_stop = len(x) - NFFT_specgram_real // 2 + 1
t_step = NFFT_specgram_real - nover_specgram_real
t_specgram = x[t_start:t_stop:t_step]
if NFFT_specgram_real % 2:
t_specgram += 1 / Fs / 2
if len(t_specgram) == 0:
t_specgram = np.array([NFFT_specgram_real / (2 * Fs)])
t_spectrum = np.array([NFFT_spectrum_real / (2 * Fs)])
t_density = t_specgram
y = np.zeros_like(x)
for i, fstim in enumerate(fstims):
y += np.sin(fstim * x * np.pi * 2) * 10**i
if iscomplex:
y = y.astype('complex')
# Interestingly, the instance on which this fixture is called is not
# the same as the one on which a test is run. So we need to modify the
# class itself when using a class-scoped fixture.
cls = request.cls
cls.Fs = Fs
cls.sides = sides
cls.fstims = fstims
cls.NFFT_density = NFFT_density
cls.nover_density = nover_density
cls.pad_to_density = pad_to_density
cls.NFFT_spectrum = NFFT_spectrum
cls.nover_spectrum = nover_spectrum
cls.pad_to_spectrum = pad_to_spectrum
cls.NFFT_specgram = NFFT_specgram
cls.nover_specgram = nover_specgram
cls.pad_to_specgram = pad_to_specgram
cls.t_specgram = t_specgram
cls.t_density = t_density
cls.t_spectrum = t_spectrum
cls.y = y
cls.freqs_density = freqs_density
cls.freqs_spectrum = freqs_spectrum
cls.freqs_specgram = freqs_specgram
cls.NFFT_density_real = NFFT_density_real
def check_freqs(self, vals, targfreqs, resfreqs, fstims):
assert resfreqs.argmin() == 0
assert resfreqs.argmax() == len(resfreqs)-1
assert_allclose(resfreqs, targfreqs, atol=1e-06)
for fstim in fstims:
i = np.abs(resfreqs - fstim).argmin()
assert vals[i] > vals[i+2]
assert vals[i] > vals[i-2]
def check_maxfreq(self, spec, fsp, fstims):
# skip the test if there are no frequencies
if len(fstims) == 0:
return
# if twosided, do the test for each side
if fsp.min() < 0:
fspa = np.abs(fsp)
zeroind = fspa.argmin()
self.check_maxfreq(spec[:zeroind], fspa[:zeroind], fstims)
self.check_maxfreq(spec[zeroind:], fspa[zeroind:], fstims)
return
fstimst = fstims[:]
spect = spec.copy()
# go through each peak and make sure it is correctly the maximum peak
while fstimst:
maxind = spect.argmax()
maxfreq = fsp[maxind]
assert_almost_equal(maxfreq, fstimst[-1])
del fstimst[-1]
spect[maxind-5:maxind+5] = 0
def test_spectral_helper_raises_complex_same_data(self):
# test that mode 'complex' cannot be used if x is not y
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y+1, mode='complex')
def test_spectral_helper_raises_magnitude_same_data(self):
# test that mode 'magnitude' cannot be used if x is not y
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y+1, mode='magnitude')
def test_spectral_helper_raises_angle_same_data(self):
# test that mode 'angle' cannot be used if x is not y
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y+1, mode='angle')
def test_spectral_helper_raises_phase_same_data(self):
# test that mode 'phase' cannot be used if x is not y
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y+1, mode='phase')
def test_spectral_helper_raises_unknown_mode(self):
# test that unknown value for mode cannot be used
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, mode='spam')
def test_spectral_helper_raises_unknown_sides(self):
# test that unknown value for sides cannot be used
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y, sides='eggs')
def test_spectral_helper_raises_noverlap_gt_NFFT(self):
# test that noverlap cannot be larger than NFFT
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y, NFFT=10, noverlap=20)
def test_spectral_helper_raises_noverlap_eq_NFFT(self):
# test that noverlap cannot be equal to NFFT
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, NFFT=10, noverlap=10)
def test_spectral_helper_raises_winlen_ne_NFFT(self):
# test that the window length cannot be different from NFFT
with pytest.raises(ValueError):
mlab._spectral_helper(x=self.y, y=self.y, NFFT=10,
window=np.ones(9))
def test_single_spectrum_helper_raises_mode_default(self):
# test that mode 'default' cannot be used with _single_spectrum_helper
with pytest.raises(ValueError):
mlab._single_spectrum_helper(x=self.y, mode='default')
def test_single_spectrum_helper_raises_mode_psd(self):
# test that mode 'psd' cannot be used with _single_spectrum_helper
with pytest.raises(ValueError):
mlab._single_spectrum_helper(x=self.y, mode='psd')
def test_spectral_helper_psd(self):
freqs = self.freqs_density
spec, fsp, t = mlab._spectral_helper(x=self.y, y=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
mode='psd')
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_density, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
def test_spectral_helper_magnitude_specgram(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab._spectral_helper(x=self.y, y=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='magnitude')
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
def test_spectral_helper_magnitude_magnitude_spectrum(self):
freqs = self.freqs_spectrum
spec, fsp, t = mlab._spectral_helper(x=self.y, y=self.y,
NFFT=self.NFFT_spectrum,
Fs=self.Fs,
noverlap=self.nover_spectrum,
pad_to=self.pad_to_spectrum,
sides=self.sides,
mode='magnitude')
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_spectrum, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == 1
def test_csd(self):
freqs = self.freqs_density
spec, fsp = mlab.csd(x=self.y, y=self.y+1,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides)
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape
def test_csd_padding(self):
"""Test zero padding of csd(). """
if self.NFFT_density is None: # for derived classes
return
sargs = dict(x=self.y, y=self.y+1, Fs=self.Fs, window=mlab.window_none,
sides=self.sides)
spec0, _ = mlab.csd(NFFT=self.NFFT_density, **sargs)
spec1, _ = mlab.csd(NFFT=self.NFFT_density*2, **sargs)
assert_almost_equal(np.sum(np.conjugate(spec0)*spec0).real,
np.sum(np.conjugate(spec1/2)*spec1/2).real)
def test_psd(self):
freqs = self.freqs_density
spec, fsp = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides)
assert spec.shape == freqs.shape
self.check_freqs(spec, freqs, fsp, self.fstims)
def test_psd_detrend_mean_func_offset(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.zeros(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ydata = np.vstack([ydata1, ydata2])
ydata = np.tile(ydata, (20, 1))
ydatab = ydata.T.flatten()
ydata = ydata.flatten()
ycontrol = np.zeros_like(ydata)
spec_g, fsp_g = mlab.psd(x=ydata,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_mean)
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_mean)
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides)
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_detrend_mean_str_offset(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.zeros(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ydata = np.vstack([ydata1, ydata2])
ydata = np.tile(ydata, (20, 1))
ydatab = ydata.T.flatten()
ydata = ydata.flatten()
ycontrol = np.zeros_like(ydata)
spec_g, fsp_g = mlab.psd(x=ydata,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend='mean')
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend='mean')
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides)
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_detrend_linear_func_trend(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.arange(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ydata = np.vstack([ydata1, ydata2])
ydata = np.tile(ydata, (20, 1))
ydatab = ydata.T.flatten()
ydata = ydata.flatten()
ycontrol = np.zeros_like(ydata)
spec_g, fsp_g = mlab.psd(x=ydata,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_linear)
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_linear)
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides)
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_detrend_linear_str_trend(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.arange(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ydata = np.vstack([ydata1, ydata2])
ydata = np.tile(ydata, (20, 1))
ydatab = ydata.T.flatten()
ydata = ydata.flatten()
ycontrol = np.zeros_like(ydata)
spec_g, fsp_g = mlab.psd(x=ydata,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend='linear')
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend='linear')
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides)
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_window_hanning(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.arange(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ycontrol1, windowVals = mlab.apply_window(ydata1,
mlab.window_hanning,
return_window=True)
ycontrol2 = mlab.window_hanning(ydata2)
ydata = np.vstack([ydata1, ydata2])
ycontrol = np.vstack([ycontrol1, ycontrol2])
ydata = np.tile(ydata, (20, 1))
ycontrol = np.tile(ycontrol, (20, 1))
ydatab = ydata.T.flatten()
ydataf = ydata.flatten()
ycontrol = ycontrol.flatten()
spec_g, fsp_g = mlab.psd(x=ydataf,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
window=mlab.window_hanning)
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
window=mlab.window_hanning)
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
window=mlab.window_none)
spec_c *= len(ycontrol1)/(np.abs(windowVals)**2).sum()
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_window_hanning_detrend_linear(self):
if self.NFFT_density is None:
return
freqs = self.freqs_density
ydata = np.arange(self.NFFT_density)
ycontrol = np.zeros(self.NFFT_density)
ydata1 = ydata+5
ydata2 = ydata+3.3
ycontrol1 = ycontrol
ycontrol2 = ycontrol
ycontrol1, windowVals = mlab.apply_window(ycontrol1,
mlab.window_hanning,
return_window=True)
ycontrol2 = mlab.window_hanning(ycontrol2)
ydata = np.vstack([ydata1, ydata2])
ycontrol = np.vstack([ycontrol1, ycontrol2])
ydata = np.tile(ydata, (20, 1))
ycontrol = np.tile(ycontrol, (20, 1))
ydatab = ydata.T.flatten()
ydataf = ydata.flatten()
ycontrol = ycontrol.flatten()
spec_g, fsp_g = mlab.psd(x=ydataf,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_linear,
window=mlab.window_hanning)
spec_b, fsp_b = mlab.psd(x=ydatab,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
detrend=mlab.detrend_linear,
window=mlab.window_hanning)
spec_c, fsp_c = mlab.psd(x=ycontrol,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=0,
sides=self.sides,
window=mlab.window_none)
spec_c *= len(ycontrol1)/(np.abs(windowVals)**2).sum()
assert_array_equal(fsp_g, fsp_c)
assert_array_equal(fsp_b, fsp_c)
assert_allclose(spec_g, spec_c, atol=1e-08)
# these should not be almost equal
with pytest.raises(AssertionError):
assert_allclose(spec_b, spec_c, atol=1e-08)
def test_psd_windowarray(self):
freqs = self.freqs_density
spec, fsp = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
window=np.ones(self.NFFT_density_real))
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape
def test_psd_windowarray_scale_by_freq(self):
freqs = self.freqs_density
win = mlab.window_hanning(np.ones(self.NFFT_density_real))
spec, fsp = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
window=mlab.window_hanning)
spec_s, fsp_s = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
window=mlab.window_hanning,
scale_by_freq=True)
spec_n, fsp_n = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
window=mlab.window_hanning,
scale_by_freq=False)
assert_array_equal(fsp, fsp_s)
assert_array_equal(fsp, fsp_n)
assert_array_equal(spec, spec_s)
assert_allclose(spec_s*(win**2).sum(),
spec_n/self.Fs*win.sum()**2,
atol=1e-08)
def test_complex_spectrum(self):
freqs = self.freqs_spectrum
spec, fsp = mlab.complex_spectrum(x=self.y,
Fs=self.Fs,
sides=self.sides,
pad_to=self.pad_to_spectrum)
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape
def test_magnitude_spectrum(self):
freqs = self.freqs_spectrum
spec, fsp = mlab.magnitude_spectrum(x=self.y,
Fs=self.Fs,
sides=self.sides,
pad_to=self.pad_to_spectrum)
assert spec.shape == freqs.shape
self.check_maxfreq(spec, fsp, self.fstims)
self.check_freqs(spec, freqs, fsp, self.fstims)
def test_angle_spectrum(self):
freqs = self.freqs_spectrum
spec, fsp = mlab.angle_spectrum(x=self.y,
Fs=self.Fs,
sides=self.sides,
pad_to=self.pad_to_spectrum)
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape
def test_phase_spectrum(self):
freqs = self.freqs_spectrum
spec, fsp = mlab.phase_spectrum(x=self.y,
Fs=self.Fs,
sides=self.sides,
pad_to=self.pad_to_spectrum)
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape
def test_specgram_auto(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides)
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
# since we are using a single freq, all time slices
# should be about the same
if np.abs(spec.max()) != 0:
assert_allclose(np.diff(spec, axis=1).max()/np.abs(spec.max()), 0,
atol=1e-02)
self.check_freqs(specm, freqs, fsp, self.fstims)
def test_specgram_default(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='default')
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
# since we are using a single freq, all time slices
# should be about the same
if np.abs(spec.max()) != 0:
assert_allclose(np.diff(spec, axis=1).max()/np.abs(spec.max()), 0,
atol=1e-02)
self.check_freqs(specm, freqs, fsp, self.fstims)
def test_specgram_psd(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='psd')
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
# since we are using a single freq, all time slices
# should be about the same
if np.abs(spec.max()) != 0:
assert_allclose(np.diff(spec, axis=1).max()/np.abs(spec.max()), 0,
atol=1e-02)
self.check_freqs(specm, freqs, fsp, self.fstims)
def test_specgram_complex(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='complex')
specm = np.mean(np.abs(spec), axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
self.check_freqs(specm, freqs, fsp, self.fstims)
def test_specgram_magnitude(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='magnitude')
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
# since we are using a single freq, all time slices
# should be about the same
if np.abs(spec.max()) != 0:
assert_allclose(np.diff(spec, axis=1).max()/np.abs(spec.max()), 0,
atol=1e-02)
self.check_freqs(specm, freqs, fsp, self.fstims)
def test_specgram_angle(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='angle')
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
def test_specgram_phase(self):
freqs = self.freqs_specgram
spec, fsp, t = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='phase')
specm = np.mean(spec, axis=1)
assert_allclose(fsp, freqs, atol=1e-06)
assert_allclose(t, self.t_specgram, atol=1e-06)
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]
def test_specgram_warn_only1seg(self):
"""Warning should be raised if len(x) <= NFFT. """
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", category=UserWarning)
mlab.specgram(x=self.y, NFFT=len(self.y), Fs=self.Fs)
assert len(w) == 1
assert issubclass(w[0].category, UserWarning)
assert str(w[0].message).startswith("Only one segment is calculated")
def test_psd_csd_equal(self):
freqs = self.freqs_density
Pxx, freqsxx = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides)
Pxy, freqsxy = mlab.csd(x=self.y, y=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides)
assert_array_almost_equal_nulp(Pxx, Pxy)
assert_array_equal(freqsxx, freqsxy)
def test_specgram_auto_default_equal(self):
'''test that mlab.specgram without mode and with mode 'default' and
'psd' are all the same'''
freqs = self.freqs_specgram
speca, freqspeca, ta = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides)
specb, freqspecb, tb = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='default')
assert_array_equal(speca, specb)
assert_array_equal(freqspeca, freqspecb)
assert_array_equal(ta, tb)
def test_specgram_auto_psd_equal(self):
'''test that mlab.specgram without mode and with mode 'default' and
'psd' are all the same'''
freqs = self.freqs_specgram
speca, freqspeca, ta = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides)
specc, freqspecc, tc = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='psd')
assert_array_equal(speca, specc)
assert_array_equal(freqspeca, freqspecc)
assert_array_equal(ta, tc)
def test_specgram_complex_mag_equivalent(self):
freqs = self.freqs_specgram
specc, freqspecc, tc = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='complex')
specm, freqspecm, tm = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='magnitude')
assert_array_equal(freqspecc, freqspecm)
assert_array_equal(tc, tm)
assert_allclose(np.abs(specc), specm, atol=1e-06)
def test_specgram_complex_angle_equivalent(self):
freqs = self.freqs_specgram
specc, freqspecc, tc = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='complex')
speca, freqspeca, ta = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='angle')
assert_array_equal(freqspecc, freqspeca)
assert_array_equal(tc, ta)
assert_allclose(np.angle(specc), speca, atol=1e-06)
def test_specgram_complex_phase_equivalent(self):
freqs = self.freqs_specgram
specc, freqspecc, tc = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='complex')
specp, freqspecp, tp = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='phase')
assert_array_equal(freqspecc, freqspecp)
assert_array_equal(tc, tp)
assert_allclose(np.unwrap(np.angle(specc), axis=0), specp,
atol=1e-06)
def test_specgram_angle_phase_equivalent(self):
freqs = self.freqs_specgram
speca, freqspeca, ta = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='angle')
specp, freqspecp, tp = mlab.specgram(x=self.y,
NFFT=self.NFFT_specgram,
Fs=self.Fs,
noverlap=self.nover_specgram,
pad_to=self.pad_to_specgram,
sides=self.sides,
mode='phase')
assert_array_equal(freqspeca, freqspecp)
assert_array_equal(ta, tp)
assert_allclose(np.unwrap(speca, axis=0), specp,
atol=1e-06)
def test_psd_windowarray_equal(self):
freqs = self.freqs_density
win = mlab.window_hanning(np.ones(self.NFFT_density_real))
speca, fspa = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides,
window=win)
specb, fspb = mlab.psd(x=self.y,
NFFT=self.NFFT_density,
Fs=self.Fs,
noverlap=self.nover_density,
pad_to=self.pad_to_density,
sides=self.sides)
assert_array_equal(fspa, fspb)
assert_allclose(speca, specb, atol=1e-08)
# extra test for cohere...
def test_cohere():
N = 1024
np.random.seed(19680801)
x = np.random.randn(N)
# phase offset
y = np.roll(x, 20)
# high-freq roll-off
y = np.convolve(y, np.ones(20) / 20., mode='same')
cohsq, f = mlab.cohere(x, y, NFFT=256, Fs=2, noverlap=128)
assert_allclose(np.mean(cohsq), 0.837, atol=1.e-3)
assert np.isreal(np.mean(cohsq))
def test_griddata_linear():
# z is a linear function of x and y.
def get_z(x, y):
return 3.0*x - y
# Passing 1D xi and yi arrays to griddata.
x = np.asarray([0.0, 1.0, 0.0, 1.0, 0.5])
y = np.asarray([0.0, 0.0, 1.0, 1.0, 0.5])
z = get_z(x, y)
xi = [0.2, 0.4, 0.6, 0.8]
yi = [0.1, 0.3, 0.7, 0.9]
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z, xi, yi, interp='linear')
xi, yi = np.meshgrid(xi, yi)
np.testing.assert_array_almost_equal(zi, get_z(xi, yi))
# Passing 2D xi and yi arrays to griddata.
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z, xi, yi, interp='linear')
np.testing.assert_array_almost_equal(zi, get_z(xi, yi))
# Masking z array.
z_masked = np.ma.array(z, mask=[False, False, False, True, False])
correct_zi_masked = np.ma.masked_where(xi + yi > 1.0, get_z(xi, yi))
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z_masked, xi, yi, interp='linear')
matest.assert_array_almost_equal(zi, correct_zi_masked)
np.testing.assert_array_equal(np.ma.getmask(zi),
np.ma.getmask(correct_zi_masked))
@pytest.mark.xfail(not HAS_NATGRID, reason='natgrid not installed')
def test_griddata_nn():
# z is a linear function of x and y.
def get_z(x, y):
return 3.0*x - y
# Passing 1D xi and yi arrays to griddata.
x = np.asarray([0.0, 1.0, 0.0, 1.0, 0.5])
y = np.asarray([0.0, 0.0, 1.0, 1.0, 0.5])
z = get_z(x, y)
xi = [0.2, 0.4, 0.6, 0.8]
yi = [0.1, 0.3, 0.7, 0.9]
correct_zi = [[0.49999252, 1.0999978, 1.7000030, 2.3000080],
[0.29999208, 0.8999978, 1.5000029, 2.1000059],
[-0.1000099, 0.4999943, 1.0999964, 1.6999979],
[-0.3000128, 0.2999894, 0.8999913, 1.4999933]]
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z, xi, yi, interp='nn')
np.testing.assert_array_almost_equal(zi, correct_zi, 5)
with pytest.warns(MatplotlibDeprecationWarning):
# Decreasing xi or yi should raise ValueError.
with pytest.raises(ValueError):
mlab.griddata(x, y, z, xi[::-1], yi, interp='nn')
with pytest.raises(ValueError):
mlab.griddata(x, y, z, xi, yi[::-1], interp='nn')
# Passing 2D xi and yi arrays to griddata.
xi, yi = np.meshgrid(xi, yi)
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z, xi, yi, interp='nn')
np.testing.assert_array_almost_equal(zi, correct_zi, 5)
# Masking z array.
z_masked = np.ma.array(z, mask=[False, False, False, True, False])
correct_zi_masked = np.ma.masked_where(xi + yi > 1.0, correct_zi)
with pytest.warns(MatplotlibDeprecationWarning):
zi = mlab.griddata(x, y, z_masked, xi, yi, interp='nn')
np.testing.assert_array_almost_equal(zi, correct_zi_masked, 5)
np.testing.assert_array_equal(np.ma.getmask(zi),
np.ma.getmask(correct_zi_masked))
#*****************************************************************
# These Tests where taken from SCIPY with some minor modifications
# this can be retrieved from:
# https://github.com/scipy/scipy/blob/master/scipy/stats/tests/test_kdeoth.py
#*****************************************************************
class TestGaussianKDE(object):
def test_kde_integer_input(self):
"""Regression test for #1181."""
x1 = np.arange(5)
kde = mlab.GaussianKDE(x1)
y_expected = [0.13480721, 0.18222869, 0.19514935, 0.18222869,
0.13480721]
np.testing.assert_array_almost_equal(kde(x1), y_expected, decimal=6)
def test_gaussian_kde_covariance_caching(self):
x1 = np.array([-7, -5, 1, 4, 5], dtype=float)
xs = np.linspace(-10, 10, num=5)
# These expected values are from scipy 0.10, before some changes to
# gaussian_kde. They were not compared with any external reference.
y_expected = [0.02463386, 0.04689208, 0.05395444, 0.05337754,
0.01664475]
# set it to the default bandwidth.
kde2 = mlab.GaussianKDE(x1, 'scott')
y2 = kde2(xs)
np.testing.assert_array_almost_equal(y_expected, y2, decimal=7)
def test_kde_bandwidth_method(self):
np.random.seed(8765678)
n_basesample = 50
xn = np.random.randn(n_basesample)
# Default
gkde = mlab.GaussianKDE(xn)
# Supply a callable
gkde2 = mlab.GaussianKDE(xn, 'scott')
# Supply a scalar
gkde3 = mlab.GaussianKDE(xn, bw_method=gkde.factor)
xs = np.linspace(-7, 7, 51)
kdepdf = gkde.evaluate(xs)
kdepdf2 = gkde2.evaluate(xs)
assert kdepdf.all() == kdepdf2.all()
kdepdf3 = gkde3.evaluate(xs)
assert kdepdf.all() == kdepdf3.all()
class TestGaussianKDECustom(object):
def test_no_data(self):
"""Pass no data into the GaussianKDE class."""
with pytest.raises(ValueError):
mlab.GaussianKDE([])
def test_single_dataset_element(self):
"""Pass a single dataset element into the GaussianKDE class."""
with pytest.raises(ValueError):
mlab.GaussianKDE([42])
def test_silverman_multidim_dataset(self):
"""Use a multi-dimensional array as the dataset and test silverman's
output"""
x1 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
with pytest.raises(np.linalg.LinAlgError):
mlab.GaussianKDE(x1, "silverman")
def test_silverman_singledim_dataset(self):
"""Use a single dimension list as the dataset and test silverman's
output."""
x1 = np.array([-7, -5, 1, 4, 5])
mygauss = mlab.GaussianKDE(x1, "silverman")
y_expected = 0.76770389927475502
assert_almost_equal(mygauss.covariance_factor(), y_expected, 7)
def test_scott_multidim_dataset(self):
"""Use a multi-dimensional array as the dataset and test scott's output
"""
x1 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
with pytest.raises(np.linalg.LinAlgError):
mlab.GaussianKDE(x1, "scott")
def test_scott_singledim_dataset(self):
"""Use a single-dimensional array as the dataset and test scott's
output"""
x1 = np.array([-7, -5, 1, 4, 5])
mygauss = mlab.GaussianKDE(x1, "scott")
y_expected = 0.72477966367769553
assert_almost_equal(mygauss.covariance_factor(), y_expected, 7)
def test_scalar_empty_dataset(self):
"""Use an empty array as the dataset and test the scalar's cov factor
"""
with pytest.raises(ValueError):
mlab.GaussianKDE([], bw_method=5)
def test_scalar_covariance_dataset(self):
"""Use a dataset and test a scalar's cov factor
"""
np.random.seed(8765678)
n_basesample = 50
multidim_data = [np.random.randn(n_basesample) for i in range(5)]
kde = mlab.GaussianKDE(multidim_data, bw_method=0.5)
assert kde.covariance_factor() == 0.5
def test_callable_covariance_dataset(self):
"""Use a multi-dimensional array as the dataset and test the callable's
cov factor"""
np.random.seed(8765678)
n_basesample = 50
multidim_data = [np.random.randn(n_basesample) for i in range(5)]
def callable_fun(x):
return 0.55
kde = mlab.GaussianKDE(multidim_data, bw_method=callable_fun)
assert kde.covariance_factor() == 0.55
def test_callable_singledim_dataset(self):
"""Use a single-dimensional array as the dataset and test the
callable's cov factor"""
np.random.seed(8765678)
n_basesample = 50
multidim_data = np.random.randn(n_basesample)
kde = mlab.GaussianKDE(multidim_data, bw_method='silverman')
y_expected = 0.48438841363348911
assert_almost_equal(kde.covariance_factor(), y_expected, 7)
def test_wrong_bw_method(self):
"""Test the error message that should be called when bw is invalid."""
np.random.seed(8765678)
n_basesample = 50
data = np.random.randn(n_basesample)
with pytest.raises(ValueError):
mlab.GaussianKDE(data, bw_method="invalid")
class TestGaussianKDEEvaluate(object):
def test_evaluate_diff_dim(self):
"""Test the evaluate method when the dim's of dataset and points are
different dimensions"""
x1 = np.arange(3, 10, 2)
kde = mlab.GaussianKDE(x1)
x2 = np.arange(3, 12, 2)
y_expected = [
0.08797252, 0.11774109, 0.11774109, 0.08797252, 0.0370153
]
y = kde.evaluate(x2)
np.testing.assert_array_almost_equal(y, y_expected, 7)
def test_evaluate_inv_dim(self):
""" Invert the dimensions. i.e., Give the dataset a dimension of
1 [3,2,4], and the points will have a dimension of 3 [[3],[2],[4]].
ValueError should be raised"""
np.random.seed(8765678)
n_basesample = 50
multidim_data = np.random.randn(n_basesample)
kde = mlab.GaussianKDE(multidim_data)
x2 = [[1], [2], [3]]
with pytest.raises(ValueError):
kde.evaluate(x2)
def test_evaluate_dim_and_num(self):
""" Tests if evaluated against a one by one array"""
x1 = np.arange(3, 10, 2)
x2 = np.array([3])
kde = mlab.GaussianKDE(x1)
y_expected = [0.08797252]
y = kde.evaluate(x2)
np.testing.assert_array_almost_equal(y, y_expected, 7)
def test_evaluate_point_dim_not_one(self):
"""Test"""
x1 = np.arange(3, 10, 2)
x2 = [np.arange(3, 10, 2), np.arange(3, 10, 2)]
kde = mlab.GaussianKDE(x1)
with pytest.raises(ValueError):
kde.evaluate(x2)
def test_evaluate_equal_dim_and_num_lt(self):
"""Test when line 3810 fails"""
x1 = np.arange(3, 10, 2)
x2 = np.arange(3, 8, 2)
kde = mlab.GaussianKDE(x1)
y_expected = [0.08797252, 0.11774109, 0.11774109]
y = kde.evaluate(x2)
np.testing.assert_array_almost_equal(y, y_expected, 7)
def test_contiguous_regions():
a, b, c = 3, 4, 5
# Starts and ends with True
mask = [True]*a + [False]*b + [True]*c
expected = [(0, a), (a+b, a+b+c)]
with pytest.warns(MatplotlibDeprecationWarning):
assert mlab.contiguous_regions(mask) == expected
d, e = 6, 7
# Starts with True ends with False
mask = mask + [False]*e
with pytest.warns(MatplotlibDeprecationWarning):
assert mlab.contiguous_regions(mask) == expected
# Starts with False ends with True
mask = [False]*d + mask[:-e]
expected = [(d, d+a), (d+a+b, d+a+b+c)]
with pytest.warns(MatplotlibDeprecationWarning):
assert mlab.contiguous_regions(mask) == expected
# Starts and ends with False
mask = mask + [False]*e
with pytest.warns(MatplotlibDeprecationWarning):
assert mlab.contiguous_regions(mask) == expected
# No True in mask
assert mlab.contiguous_regions([False]*5) == []
# Empty mask
assert mlab.contiguous_regions([]) == []
def test_psd_onesided_norm():
u = np.array([0, 1, 2, 3, 1, 2, 1])
dt = 1.0
Su = np.abs(np.fft.fft(u) * dt)**2 / (dt * u.size)
P, f = mlab.psd(u, NFFT=u.size, Fs=1/dt, window=mlab.window_none,
detrend=mlab.detrend_none, noverlap=0, pad_to=None,
scale_by_freq=None,
sides='onesided')
Su_1side = np.append([Su[0]], Su[1:4] + Su[4:][::-1])
assert_allclose(P, Su_1side, atol=1e-06)
def test_psd_oversampling():
"""Test the case len(x) < NFFT for psd()."""
u = np.array([0, 1, 2, 3, 1, 2, 1])
dt = 1.0
Su = np.abs(np.fft.fft(u) * dt)**2 / (dt * u.size)
P, f = mlab.psd(u, NFFT=u.size*2, Fs=1/dt, window=mlab.window_none,
detrend=mlab.detrend_none, noverlap=0, pad_to=None,
scale_by_freq=None,
sides='onesided')
Su_1side = np.append([Su[0]], Su[1:4] + Su[4:][::-1])
assert_almost_equal(np.sum(P), np.sum(Su_1side)) # same energy
| 97,575 | 38.392814 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_svg.py | from __future__ import absolute_import, division, print_function
import six
import numpy as np
from io import BytesIO
import os
import tempfile
import xml.parsers.expat
import pytest
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
import matplotlib
from matplotlib import dviread
needs_usetex = pytest.mark.xfail(
not matplotlib.checkdep_usetex(True),
reason="This test needs a TeX installation")
def test_visibility():
fig = plt.figure()
ax = fig.add_subplot(111)
x = np.linspace(0, 4 * np.pi, 50)
y = np.sin(x)
yerr = np.ones_like(y)
a, b, c = ax.errorbar(x, y, yerr=yerr, fmt='ko')
for artist in b:
artist.set_visible(False)
fd = BytesIO()
fig.savefig(fd, format='svg')
fd.seek(0)
buf = fd.read()
fd.close()
parser = xml.parsers.expat.ParserCreate()
parser.Parse(buf) # this will raise ExpatError if the svg is invalid
@image_comparison(baseline_images=['fill_black_with_alpha'], remove_text=True,
extensions=['svg'])
def test_fill_black_with_alpha():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(x=[0, 0.1, 1], y=[0, 0, 0], c='k', alpha=0.1, s=10000)
@image_comparison(baseline_images=['noscale'], remove_text=True)
def test_noscale():
X, Y = np.meshgrid(np.arange(-5, 5, 1), np.arange(-5, 5, 1))
Z = np.sin(Y ** 2)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.imshow(Z, cmap='gray', interpolation='none')
def test_text_urls():
fig = plt.figure()
test_url = "http://test_text_urls.matplotlib.org"
fig.suptitle("test_text_urls", url=test_url)
fd = BytesIO()
fig.savefig(fd, format='svg')
fd.seek(0)
buf = fd.read().decode()
fd.close()
expected = '<a xlink:href="{0}">'.format(test_url)
assert expected in buf
@image_comparison(baseline_images=['bold_font_output'], extensions=['svg'])
def test_bold_font_output():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(np.arange(10), np.arange(10))
ax.set_xlabel('nonbold-xlabel')
ax.set_ylabel('bold-ylabel', fontweight='bold')
ax.set_title('bold-title', fontweight='bold')
@image_comparison(baseline_images=['bold_font_output_with_none_fonttype'],
extensions=['svg'])
def test_bold_font_output_with_none_fonttype():
plt.rcParams['svg.fonttype'] = 'none'
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(np.arange(10), np.arange(10))
ax.set_xlabel('nonbold-xlabel')
ax.set_ylabel('bold-ylabel', fontweight='bold')
ax.set_title('bold-title', fontweight='bold')
def _test_determinism_save(filename, usetex):
# This function is mostly copy&paste from "def test_visibility"
# To require no GUI, we use Figure and FigureCanvasSVG
# instead of plt.figure and fig.savefig
from matplotlib.figure import Figure
from matplotlib.backends.backend_svg import FigureCanvasSVG
from matplotlib import rc
rc('svg', hashsalt='asdf')
rc('text', usetex=usetex)
fig = Figure()
ax = fig.add_subplot(111)
x = np.linspace(0, 4 * np.pi, 50)
y = np.sin(x)
yerr = np.ones_like(y)
a, b, c = ax.errorbar(x, y, yerr=yerr, fmt='ko')
for artist in b:
artist.set_visible(False)
ax.set_title('A string $1+2+\\sigma$')
ax.set_xlabel('A string $1+2+\\sigma$')
ax.set_ylabel('A string $1+2+\\sigma$')
FigureCanvasSVG(fig).print_svg(filename)
@pytest.mark.parametrize(
"filename, usetex",
# unique filenames to allow for parallel testing
[("determinism_notex.svg", False),
needs_usetex(("determinism_tex.svg", True))])
def test_determinism(filename, usetex):
import sys
from subprocess import check_output, STDOUT, CalledProcessError
plots = []
for i in range(3):
# Using check_output and setting stderr to STDOUT will capture the real
# problem in the output property of the exception
try:
check_output(
[sys.executable, '-R', '-c',
'import matplotlib; '
'matplotlib._called_from_pytest = True; '
'matplotlib.use("svg"); '
'from matplotlib.tests.test_backend_svg '
'import _test_determinism_save;'
'_test_determinism_save(%r, %r)' % (filename, usetex)],
stderr=STDOUT)
except CalledProcessError as e:
# it's easier to use utf8 and ask for forgiveness than try
# to figure out what the current console has as an
# encoding :-/
print(e.output.decode(encoding="utf-8", errors="ignore"))
raise e
else:
with open(filename, 'rb') as fd:
plots.append(fd.read())
finally:
os.unlink(filename)
for p in plots[1:]:
assert p == plots[0]
@needs_usetex
def test_missing_psfont(monkeypatch):
"""An error is raised if a TeX font lacks a Type-1 equivalent"""
from matplotlib import rc
def psfont(*args, **kwargs):
return dviread.PsFont(texname='texfont', psname='Some Font',
effects=None, encoding=None, filename=None)
monkeypatch.setattr(dviread.PsfontsMap, '__getitem__', psfont)
rc('text', usetex=True)
fig, ax = plt.subplots()
ax.text(0.5, 0.5, 'hello')
with tempfile.TemporaryFile() as tmpfile, pytest.raises(ValueError):
fig.savefig(tmpfile, format='svg')
| 5,510 | 29.28022 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_backend_qt5.py | from __future__ import absolute_import, division, print_function
import copy
import matplotlib
from matplotlib import pyplot as plt
from matplotlib._pylab_helpers import Gcf
from numpy.testing import assert_equal
import pytest
try:
# mock in python 3.3+
from unittest import mock
except ImportError:
import mock
with matplotlib.rc_context(rc={'backend': 'Qt5Agg'}):
qt_compat = pytest.importorskip('matplotlib.backends.qt_compat',
minversion='5')
from matplotlib.backends.backend_qt5 import (
MODIFIER_KEYS, SUPER, ALT, CTRL, SHIFT) # noqa
QtCore = qt_compat.QtCore
_, ControlModifier, ControlKey = MODIFIER_KEYS[CTRL]
_, AltModifier, AltKey = MODIFIER_KEYS[ALT]
_, SuperModifier, SuperKey = MODIFIER_KEYS[SUPER]
_, ShiftModifier, ShiftKey = MODIFIER_KEYS[SHIFT]
@pytest.mark.backend('Qt5Agg')
def test_fig_close():
# save the state of Gcf.figs
init_figs = copy.copy(Gcf.figs)
# make a figure using pyplot interface
fig = plt.figure()
# simulate user clicking the close button by reaching in
# and calling close on the underlying Qt object
fig.canvas.manager.window.close()
# assert that we have removed the reference to the FigureManager
# that got added by plt.figure()
assert init_figs == Gcf.figs
@pytest.mark.parametrize(
'qt_key, qt_mods, answer',
[
(QtCore.Qt.Key_A, ShiftModifier, 'A'),
(QtCore.Qt.Key_A, QtCore.Qt.NoModifier, 'a'),
(QtCore.Qt.Key_A, ControlModifier, 'ctrl+a'),
(QtCore.Qt.Key_Aacute, ShiftModifier,
'\N{LATIN CAPITAL LETTER A WITH ACUTE}'),
(QtCore.Qt.Key_Aacute, QtCore.Qt.NoModifier,
'\N{LATIN SMALL LETTER A WITH ACUTE}'),
(ControlKey, AltModifier, 'alt+control'),
(AltKey, ControlModifier, 'ctrl+alt'),
(QtCore.Qt.Key_Aacute, (ControlModifier | AltModifier | SuperModifier),
'ctrl+alt+super+\N{LATIN SMALL LETTER A WITH ACUTE}'),
(QtCore.Qt.Key_Backspace, QtCore.Qt.NoModifier, 'backspace'),
(QtCore.Qt.Key_Backspace, ControlModifier, 'ctrl+backspace'),
(QtCore.Qt.Key_Play, QtCore.Qt.NoModifier, None),
],
ids=[
'shift',
'lower',
'control',
'unicode_upper',
'unicode_lower',
'alt_control',
'control_alt',
'modifier_order',
'backspace',
'backspace_mod',
'non_unicode_key',
]
)
@pytest.mark.backend('Qt5Agg')
def test_correct_key(qt_key, qt_mods, answer):
"""
Make a figure
Send a key_press_event event (using non-public, qt5 backend specific api)
Catch the event
Assert sent and caught keys are the same
"""
qt_canvas = plt.figure().canvas
event = mock.Mock()
event.isAutoRepeat.return_value = False
event.key.return_value = qt_key
event.modifiers.return_value = qt_mods
def receive(event):
assert event.key == answer
qt_canvas.mpl_connect('key_press_event', receive)
qt_canvas.keyPressEvent(event)
@pytest.mark.backend('Qt5Agg')
def test_dpi_ratio_change():
"""
Make sure that if _dpi_ratio changes, the figure dpi changes but the
widget remains the same physical size.
"""
prop = 'matplotlib.backends.backend_qt5.FigureCanvasQT._dpi_ratio'
with mock.patch(prop, new_callable=mock.PropertyMock) as p:
p.return_value = 3
fig = plt.figure(figsize=(5, 2), dpi=120)
qt_canvas = fig.canvas
qt_canvas.show()
from matplotlib.backends.backend_qt5 import qApp
# Make sure the mocking worked
assert qt_canvas._dpi_ratio == 3
size = qt_canvas.size()
qt_canvas.manager.show()
qt_canvas.draw()
qApp.processEvents()
# The DPI and the renderer width/height change
assert fig.dpi == 360
assert qt_canvas.renderer.width == 1800
assert qt_canvas.renderer.height == 720
# The actual widget size and figure physical size don't change
assert size.width() == 600
assert size.height() == 240
assert_equal(qt_canvas.get_width_height(), (600, 240))
assert_equal(fig.get_size_inches(), (5, 2))
p.return_value = 2
assert qt_canvas._dpi_ratio == 2
qt_canvas.draw()
qApp.processEvents()
# this second processEvents is required to fully run the draw.
# On `update` we notice the DPI has changed and trigger a
# resize event to refresh, the second processEvents is
# required to process that and fully update the window sizes.
qApp.processEvents()
# The DPI and the renderer width/height change
assert fig.dpi == 240
assert qt_canvas.renderer.width == 1200
assert qt_canvas.renderer.height == 480
# The actual widget size and figure physical size don't change
assert size.width() == 600
assert size.height() == 240
assert_equal(qt_canvas.get_width_height(), (600, 240))
assert_equal(fig.get_size_inches(), (5, 2))
@pytest.mark.backend('Qt5Agg')
def test_subplottool():
fig, ax = plt.subplots()
with mock.patch(
"matplotlib.backends.backend_qt5.SubplotToolQt.exec_",
lambda self: None):
fig.canvas.manager.toolbar.configure_subplots()
@pytest.mark.backend('Qt5Agg')
def test_figureoptions():
fig, ax = plt.subplots()
ax.plot([1, 2])
ax.imshow([[1]])
with mock.patch(
"matplotlib.backends.qt_editor.formlayout.FormDialog.exec_",
lambda self: None):
fig.canvas.manager.toolbar.edit_parameters()
| 5,629 | 29.765027 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_legend.py | from __future__ import absolute_import, division, print_function
try:
# mock in python 3.3+
from unittest import mock
except ImportError:
import mock
import collections
import numpy as np
import pytest
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.transforms as mtransforms
import matplotlib.collections as mcollections
from matplotlib.legend_handler import HandlerTuple
import matplotlib.legend as mlegend
import inspect
# test that docstrigs are the same
def get_docstring_section(func, section):
""" extract a section from the docstring of a function """
ll = inspect.getdoc(func)
lines = ll.splitlines()
insec = False
st = ''
for ind in range(len(lines)):
if lines[ind][:len(section)] == section and lines[ind+1][:3] == '---':
insec = True
ind = ind+1
if insec:
if len(lines[ind + 1]) > 3 and lines[ind + 1][0:3] == '---':
insec = False
break
else:
st += lines[ind] + '\n'
return st
def test_legend_kwdocstrings():
stax = get_docstring_section(mpl.axes.Axes.legend, 'Parameters')
stfig = get_docstring_section(mpl.figure.Figure.legend, 'Parameters')
assert stfig == stax
stleg = get_docstring_section(mpl.legend.Legend.__init__,
'Other Parameters')
stax = get_docstring_section(mpl.axes.Axes.legend, 'Other Parameters')
stfig = get_docstring_section(mpl.figure.Figure.legend, 'Other Parameters')
assert stleg == stax
assert stfig == stax
assert stleg == stfig
def test_legend_ordereddict():
# smoketest that ordereddict inputs work...
X = np.random.randn(10)
Y = np.random.randn(10)
labels = ['a'] * 5 + ['b'] * 5
colors = ['r'] * 5 + ['g'] * 5
fig, ax = plt.subplots()
for x, y, label, color in zip(X, Y, labels, colors):
ax.scatter(x, y, label=label, c=color)
handles, labels = ax.get_legend_handles_labels()
legend = collections.OrderedDict(zip(labels, handles))
ax.legend(legend.values(), legend.keys(), loc=6, bbox_to_anchor=(1, .5))
@image_comparison(baseline_images=['legend_auto1'], remove_text=True)
def test_legend_auto1():
'Test automatic legend placement'
fig = plt.figure()
ax = fig.add_subplot(111)
x = np.arange(100)
ax.plot(x, 50 - x, 'o', label='y=1')
ax.plot(x, x - 50, 'o', label='y=-1')
ax.legend(loc=0)
@image_comparison(baseline_images=['legend_auto2'], remove_text=True)
def test_legend_auto2():
'Test automatic legend placement'
fig = plt.figure()
ax = fig.add_subplot(111)
x = np.arange(100)
b1 = ax.bar(x, x, color='m')
b2 = ax.bar(x, x[::-1], color='g')
ax.legend([b1[0], b2[0]], ['up', 'down'], loc=0)
@image_comparison(baseline_images=['legend_auto3'])
def test_legend_auto3():
'Test automatic legend placement'
fig = plt.figure()
ax = fig.add_subplot(111)
x = [0.9, 0.1, 0.1, 0.9, 0.9, 0.5]
y = [0.95, 0.95, 0.05, 0.05, 0.5, 0.5]
ax.plot(x, y, 'o-', label='line')
ax.set_xlim(0.0, 1.0)
ax.set_ylim(0.0, 1.0)
ax.legend(loc=0)
@image_comparison(baseline_images=['legend_various_labels'], remove_text=True)
def test_various_labels():
# tests all sorts of label types
fig = plt.figure()
ax = fig.add_subplot(121)
ax.plot(np.arange(4), 'o', label=1)
ax.plot(np.linspace(4, 4.1), 'o', label=u'D\xe9velopp\xe9s')
ax.plot(np.arange(4, 1, -1), 'o', label='__nolegend__')
ax.legend(numpoints=1, loc=0)
@image_comparison(baseline_images=['legend_labels_first'], extensions=['png'],
remove_text=True)
def test_labels_first():
# test labels to left of markers
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(np.arange(10), '-o', label=1)
ax.plot(np.ones(10)*5, ':x', label="x")
ax.plot(np.arange(20, 10, -1), 'd', label="diamond")
ax.legend(loc=0, markerfirst=False)
@image_comparison(baseline_images=['legend_multiple_keys'], extensions=['png'],
remove_text=True)
def test_multiple_keys():
# test legend entries with multiple keys
fig = plt.figure()
ax = fig.add_subplot(111)
p1, = ax.plot([1, 2, 3], '-o')
p2, = ax.plot([2, 3, 4], '-x')
p3, = ax.plot([3, 4, 5], '-d')
ax.legend([(p1, p2), (p2, p1), p3], ['two keys', 'pad=0', 'one key'],
numpoints=1,
handler_map={(p1, p2): HandlerTuple(ndivide=None),
(p2, p1): HandlerTuple(ndivide=None, pad=0)})
@image_comparison(baseline_images=['rgba_alpha'],
extensions=['png'], remove_text=True)
def test_alpha_rgba():
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
ax.plot(range(10), lw=5)
leg = plt.legend(['Longlabel that will go away'], loc=10)
leg.legendPatch.set_facecolor([1, 0, 0, 0.5])
@image_comparison(baseline_images=['rcparam_alpha'],
extensions=['png'], remove_text=True)
def test_alpha_rcparam():
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
ax.plot(range(10), lw=5)
with mpl.rc_context(rc={'legend.framealpha': .75}):
leg = plt.legend(['Longlabel that will go away'], loc=10)
# this alpha is going to be over-ridden by the rcparam with
# sets the alpha of the patch to be non-None which causes the alpha
# value of the face color to be discarded. This behavior may not be
# ideal, but it is what it is and we should keep track of it changing
leg.legendPatch.set_facecolor([1, 0, 0, 0.5])
@image_comparison(baseline_images=['fancy'], remove_text=True)
def test_fancy():
# using subplot triggers some offsetbox functionality untested elsewhere
plt.subplot(121)
plt.scatter(np.arange(10), np.arange(10, 0, -1), label='XX\nXX')
plt.plot([5] * 10, 'o--', label='XX')
plt.errorbar(np.arange(10), np.arange(10), xerr=0.5,
yerr=0.5, label='XX')
plt.legend(loc="center left", bbox_to_anchor=[1.0, 0.5],
ncol=2, shadow=True, title="My legend", numpoints=1)
@image_comparison(baseline_images=['framealpha'], remove_text=True)
def test_framealpha():
x = np.linspace(1, 100, 100)
y = x
plt.plot(x, y, label='mylabel', lw=10)
plt.legend(framealpha=0.5)
@image_comparison(baseline_images=['scatter_rc3', 'scatter_rc1'],
remove_text=True)
def test_rc():
# using subplot triggers some offsetbox functionality untested elsewhere
plt.figure()
ax = plt.subplot(121)
ax.scatter(np.arange(10), np.arange(10, 0, -1), label='three')
ax.legend(loc="center left", bbox_to_anchor=[1.0, 0.5],
title="My legend")
mpl.rcParams['legend.scatterpoints'] = 1
plt.figure()
ax = plt.subplot(121)
ax.scatter(np.arange(10), np.arange(10, 0, -1), label='one')
ax.legend(loc="center left", bbox_to_anchor=[1.0, 0.5],
title="My legend")
@image_comparison(baseline_images=['legend_expand'], remove_text=True)
def test_legend_expand():
'Test expand mode'
legend_modes = [None, "expand"]
fig, axes_list = plt.subplots(len(legend_modes), 1)
x = np.arange(100)
for ax, mode in zip(axes_list, legend_modes):
ax.plot(x, 50 - x, 'o', label='y=1')
l1 = ax.legend(loc=2, mode=mode)
ax.add_artist(l1)
ax.plot(x, x - 50, 'o', label='y=-1')
l2 = ax.legend(loc=5, mode=mode)
ax.add_artist(l2)
ax.legend(loc=3, mode=mode, ncol=2)
@image_comparison(baseline_images=['hatching'], remove_text=True,
style='default')
def test_hatching():
fig, ax = plt.subplots()
# Patches
patch = plt.Rectangle((0, 0), 0.3, 0.3, hatch='xx',
label='Patch\ndefault color\nfilled')
ax.add_patch(patch)
patch = plt.Rectangle((0.33, 0), 0.3, 0.3, hatch='||', edgecolor='C1',
label='Patch\nexplicit color\nfilled')
ax.add_patch(patch)
patch = plt.Rectangle((0, 0.4), 0.3, 0.3, hatch='xx', fill=False,
label='Patch\ndefault color\nunfilled')
ax.add_patch(patch)
patch = plt.Rectangle((0.33, 0.4), 0.3, 0.3, hatch='||', fill=False,
edgecolor='C1',
label='Patch\nexplicit color\nunfilled')
ax.add_patch(patch)
# Paths
ax.fill_between([0, .15, .3], [.8, .8, .8], [.9, 1.0, .9],
hatch='+', label='Path\ndefault color')
ax.fill_between([.33, .48, .63], [.8, .8, .8], [.9, 1.0, .9],
hatch='+', edgecolor='C2', label='Path\nexplicit color')
ax.set_xlim(-0.01, 1.1)
ax.set_ylim(-0.01, 1.1)
ax.legend(handlelength=4, handleheight=4)
def test_legend_remove():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
lines = ax.plot(range(10))
leg = fig.legend(lines, "test")
leg.remove()
assert fig.legends == []
leg = ax.legend("test")
leg.remove()
assert ax.get_legend() is None
class TestLegendFunction(object):
# Tests the legend function on the Axes and pyplot.
def test_legend_handle_label(self):
lines = plt.plot(range(10))
with mock.patch('matplotlib.legend.Legend') as Legend:
plt.legend(lines, ['hello world'])
Legend.assert_called_with(plt.gca(), lines, ['hello world'])
def test_legend_no_args(self):
lines = plt.plot(range(10), label='hello world')
with mock.patch('matplotlib.legend.Legend') as Legend:
plt.legend()
Legend.assert_called_with(plt.gca(), lines, ['hello world'])
def test_legend_label_args(self):
lines = plt.plot(range(10), label='hello world')
with mock.patch('matplotlib.legend.Legend') as Legend:
plt.legend(['foobar'])
Legend.assert_called_with(plt.gca(), lines, ['foobar'])
def test_legend_three_args(self):
lines = plt.plot(range(10), label='hello world')
with mock.patch('matplotlib.legend.Legend') as Legend:
plt.legend(lines, ['foobar'], loc='right')
Legend.assert_called_with(plt.gca(), lines, ['foobar'], loc='right')
def test_legend_handler_map(self):
lines = plt.plot(range(10), label='hello world')
with mock.patch('matplotlib.legend.'
'_get_legend_handles_labels') as handles_labels:
handles_labels.return_value = lines, ['hello world']
plt.legend(handler_map={'1': 2})
handles_labels.assert_called_with([plt.gca()], {'1': 2})
def test_kwargs(self):
fig, ax = plt.subplots(1, 1)
th = np.linspace(0, 2*np.pi, 1024)
lns, = ax.plot(th, np.sin(th), label='sin', lw=5)
lnc, = ax.plot(th, np.cos(th), label='cos', lw=5)
with mock.patch('matplotlib.legend.Legend') as Legend:
ax.legend(labels=('a', 'b'), handles=(lnc, lns))
Legend.assert_called_with(ax, (lnc, lns), ('a', 'b'))
def test_warn_args_kwargs(self):
fig, ax = plt.subplots(1, 1)
th = np.linspace(0, 2*np.pi, 1024)
lns, = ax.plot(th, np.sin(th), label='sin', lw=5)
lnc, = ax.plot(th, np.cos(th), label='cos', lw=5)
with mock.patch('warnings.warn') as warn:
ax.legend((lnc, lns), labels=('a', 'b'))
warn.assert_called_with("You have mixed positional and keyword "
"arguments, some input may be "
"discarded.")
def test_parasite(self):
from mpl_toolkits.axes_grid1 import host_subplot
host = host_subplot(111)
par = host.twinx()
p1, = host.plot([0, 1, 2], [0, 1, 2], label="Density")
p2, = par.plot([0, 1, 2], [0, 3, 2], label="Temperature")
with mock.patch('matplotlib.legend.Legend') as Legend:
leg = plt.legend()
Legend.assert_called_with(host, [p1, p2],
['Density', 'Temperature'])
class TestLegendFigureFunction(object):
# Tests the legend function for figure
def test_legend_handle_label(self):
fig, ax = plt.subplots()
lines = ax.plot(range(10))
with mock.patch('matplotlib.legend.Legend') as Legend:
fig.legend(lines, ['hello world'])
Legend.assert_called_with(fig, lines, ['hello world'])
def test_legend_no_args(self):
fig, ax = plt.subplots()
lines = ax.plot(range(10), label='hello world')
with mock.patch('matplotlib.legend.Legend') as Legend:
fig.legend()
Legend.assert_called_with(fig, lines, ['hello world'])
def test_legend_label_arg(self):
fig, ax = plt.subplots()
lines = ax.plot(range(10))
with mock.patch('matplotlib.legend.Legend') as Legend:
fig.legend(['foobar'])
Legend.assert_called_with(fig, lines, ['foobar'])
def test_legend_label_three_args(self):
fig, ax = plt.subplots()
lines = ax.plot(range(10))
with mock.patch('matplotlib.legend.Legend') as Legend:
fig.legend(lines, ['foobar'], 'right')
Legend.assert_called_with(fig, lines, ['foobar'], 'right')
def test_legend_label_three_args_pluskw(self):
# test that third argument and loc= called together give
# Exception
fig, ax = plt.subplots()
lines = ax.plot(range(10))
with pytest.raises(Exception):
fig.legend(lines, ['foobar'], 'right', loc='left')
def test_legend_kw_args(self):
fig, axs = plt.subplots(1, 2)
lines = axs[0].plot(range(10))
lines2 = axs[1].plot(np.arange(10) * 2.)
with mock.patch('matplotlib.legend.Legend') as Legend:
fig.legend(loc='right', labels=('a', 'b'),
handles=(lines, lines2))
Legend.assert_called_with(fig, (lines, lines2), ('a', 'b'),
loc='right')
def test_warn_args_kwargs(self):
fig, axs = plt.subplots(1, 2)
lines = axs[0].plot(range(10))
lines2 = axs[1].plot(np.arange(10) * 2.)
with mock.patch('warnings.warn') as warn:
fig.legend((lines, lines2), labels=('a', 'b'))
warn.assert_called_with("You have mixed positional and keyword "
"arguments, some input may be "
"discarded.")
@image_comparison(baseline_images=['legend_stackplot'], extensions=['png'])
def test_legend_stackplot():
'''test legend for PolyCollection using stackplot'''
# related to #1341, #1943, and PR #3303
fig = plt.figure()
ax = fig.add_subplot(111)
x = np.linspace(0, 10, 10)
y1 = 1.0 * x
y2 = 2.0 * x + 1
y3 = 3.0 * x + 2
ax.stackplot(x, y1, y2, y3, labels=['y1', 'y2', 'y3'])
ax.set_xlim((0, 10))
ax.set_ylim((0, 70))
ax.legend(loc=0)
def test_cross_figure_patch_legend():
fig, ax = plt.subplots()
fig2, ax2 = plt.subplots()
brs = ax.bar(range(3), range(3))
fig2.legend(brs, 'foo')
def test_nanscatter():
fig, ax = plt.subplots()
h = ax.scatter([np.nan], [np.nan], marker="o",
facecolor="r", edgecolor="r", s=3)
ax.legend([h], ["scatter"])
fig, ax = plt.subplots()
for color in ['red', 'green', 'blue']:
n = 750
x, y = np.random.rand(2, n)
scale = 200.0 * np.random.rand(n)
ax.scatter(x, y, c=color, s=scale, label=color,
alpha=0.3, edgecolors='none')
ax.legend()
ax.grid(True)
def test_legend_repeatcheckok():
fig, ax = plt.subplots()
ax.scatter(0.0, 1.0, color='k', marker='o', label='test')
ax.scatter(0.5, 0.0, color='r', marker='v', label='test')
hl = ax.legend()
hand, lab = mlegend._get_legend_handles_labels([ax])
assert len(lab) == 2
fig, ax = plt.subplots()
ax.scatter(0.0, 1.0, color='k', marker='o', label='test')
ax.scatter(0.5, 0.0, color='k', marker='v', label='test')
hl = ax.legend()
hand, lab = mlegend._get_legend_handles_labels([ax])
assert len(lab) == 2
@image_comparison(baseline_images=['not_covering_scatter'], extensions=['png'])
def test_not_covering_scatter():
colors = ['b', 'g', 'r']
for n in range(3):
plt.scatter([n], [n], color=colors[n])
plt.legend(['foo', 'foo', 'foo'], loc='best')
plt.gca().set_xlim(-0.5, 2.2)
plt.gca().set_ylim(-0.5, 2.2)
@image_comparison(baseline_images=['not_covering_scatter_transform'],
extensions=['png'])
def test_not_covering_scatter_transform():
# Offsets point to top left, the default auto position
offset = mtransforms.Affine2D().translate(-20, 20)
x = np.linspace(0, 30, 1000)
plt.plot(x, x)
plt.scatter([20], [10], transform=offset + plt.gca().transData)
plt.legend(['foo', 'bar'], loc='best')
def test_linecollection_scaled_dashes():
lines1 = [[(0, .5), (.5, 1)], [(.3, .6), (.2, .2)]]
lines2 = [[[0.7, .2], [.8, .4]], [[.5, .7], [.6, .1]]]
lines3 = [[[0.6, .2], [.8, .4]], [[.5, .7], [.1, .1]]]
lc1 = mcollections.LineCollection(lines1, linestyles="--", lw=3)
lc2 = mcollections.LineCollection(lines2, linestyles="-.")
lc3 = mcollections.LineCollection(lines3, linestyles=":", lw=.5)
fig, ax = plt.subplots()
ax.add_collection(lc1)
ax.add_collection(lc2)
ax.add_collection(lc3)
leg = ax.legend([lc1, lc2, lc3], ["line1", "line2", 'line 3'])
h1, h2, h3 = leg.legendHandles
for oh, lh in zip((lc1, lc2, lc3), (h1, h2, h3)):
assert oh.get_linestyles()[0][1] == lh._dashSeq
assert oh.get_linestyles()[0][0] == lh._dashOffset
def test_handler_numpoints():
'''test legend handler with numponts less than or equal to 1'''
# related to #6921 and PR #8478
fig, ax = plt.subplots()
ax.plot(range(5), label='test')
ax.legend(numpoints=0.5)
def test_shadow_framealpha():
# Test if framealpha is activated when shadow is True
# and framealpha is not explicitly passed'''
fig, ax = plt.subplots()
ax.plot(range(100), label="test")
leg = ax.legend(shadow=True, facecolor='w')
assert leg.get_frame().get_alpha() == 1
| 18,218 | 34.036538 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_skew.py | """
Testing that skewed axes properly work
"""
from __future__ import absolute_import, division, print_function
import itertools
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
from matplotlib.axes import Axes
import matplotlib.transforms as transforms
import matplotlib.axis as maxis
import matplotlib.spines as mspines
import matplotlib.patches as mpatch
from matplotlib.projections import register_projection
# The sole purpose of this class is to look at the upper, lower, or total
# interval as appropriate and see what parts of the tick to draw, if any.
class SkewXTick(maxis.XTick):
def update_position(self, loc):
# This ensures that the new value of the location is set before
# any other updates take place
self._loc = loc
super(SkewXTick, self).update_position(loc)
def _has_default_loc(self):
return self.get_loc() is None
def _need_lower(self):
return (self._has_default_loc() or
transforms.interval_contains(self.axes.lower_xlim,
self.get_loc()))
def _need_upper(self):
return (self._has_default_loc() or
transforms.interval_contains(self.axes.upper_xlim,
self.get_loc()))
@property
def gridOn(self):
return (self._gridOn and (self._has_default_loc() or
transforms.interval_contains(self.get_view_interval(),
self.get_loc())))
@gridOn.setter
def gridOn(self, value):
self._gridOn = value
@property
def tick1On(self):
return self._tick1On and self._need_lower()
@tick1On.setter
def tick1On(self, value):
self._tick1On = value
@property
def label1On(self):
return self._label1On and self._need_lower()
@label1On.setter
def label1On(self, value):
self._label1On = value
@property
def tick2On(self):
return self._tick2On and self._need_upper()
@tick2On.setter
def tick2On(self, value):
self._tick2On = value
@property
def label2On(self):
return self._label2On and self._need_upper()
@label2On.setter
def label2On(self, value):
self._label2On = value
def get_view_interval(self):
return self.axes.xaxis.get_view_interval()
# This class exists to provide two separate sets of intervals to the tick,
# as well as create instances of the custom tick
class SkewXAxis(maxis.XAxis):
def _get_tick(self, major):
return SkewXTick(self.axes, None, '', major=major)
def get_view_interval(self):
return self.axes.upper_xlim[0], self.axes.lower_xlim[1]
# This class exists to calculate the separate data range of the
# upper X-axis and draw the spine there. It also provides this range
# to the X-axis artist for ticking and gridlines
class SkewSpine(mspines.Spine):
def _adjust_location(self):
pts = self._path.vertices
if self.spine_type == 'top':
pts[:, 0] = self.axes.upper_xlim
else:
pts[:, 0] = self.axes.lower_xlim
# This class handles registration of the skew-xaxes as a projection as well
# as setting up the appropriate transformations. It also overrides standard
# spines and axes instances as appropriate.
class SkewXAxes(Axes):
# The projection must specify a name. This will be used be the
# user to select the projection, i.e. ``subplot(111,
# projection='skewx')``.
name = 'skewx'
def _init_axis(self):
# Taken from Axes and modified to use our modified X-axis
self.xaxis = SkewXAxis(self)
self.spines['top'].register_axis(self.xaxis)
self.spines['bottom'].register_axis(self.xaxis)
self.yaxis = maxis.YAxis(self)
self.spines['left'].register_axis(self.yaxis)
self.spines['right'].register_axis(self.yaxis)
def _gen_axes_spines(self):
spines = {'top': SkewSpine.linear_spine(self, 'top'),
'bottom': mspines.Spine.linear_spine(self, 'bottom'),
'left': mspines.Spine.linear_spine(self, 'left'),
'right': mspines.Spine.linear_spine(self, 'right')}
return spines
def _set_lim_and_transforms(self):
"""
This is called once when the plot is created to set up all the
transforms for the data, text and grids.
"""
rot = 30
# Get the standard transform setup from the Axes base class
Axes._set_lim_and_transforms(self)
# Need to put the skew in the middle, after the scale and limits,
# but before the transAxes. This way, the skew is done in Axes
# coordinates thus performing the transform around the proper origin
# We keep the pre-transAxes transform around for other users, like the
# spines for finding bounds
self.transDataToAxes = (self.transScale +
(self.transLimits +
transforms.Affine2D().skew_deg(rot, 0)))
# Create the full transform from Data to Pixels
self.transData = self.transDataToAxes + self.transAxes
# Blended transforms like this need to have the skewing applied using
# both axes, in axes coords like before.
self._xaxis_transform = (transforms.blended_transform_factory(
self.transScale + self.transLimits,
transforms.IdentityTransform()) +
transforms.Affine2D().skew_deg(rot, 0)) + self.transAxes
@property
def lower_xlim(self):
return self.axes.viewLim.intervalx
@property
def upper_xlim(self):
pts = [[0., 1.], [1., 1.]]
return self.transDataToAxes.inverted().transform(pts)[:, 0]
# Now register the projection with matplotlib so the user can select
# it.
register_projection(SkewXAxes)
@image_comparison(baseline_images=['skew_axes'], remove_text=True)
def test_set_line_coll_dash_image():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='skewx')
ax.set_xlim(-50, 50)
ax.set_ylim(50, -50)
ax.grid(True)
# An example of a slanted line at constant X
ax.axvline(0, color='b')
@image_comparison(baseline_images=['skew_rects'], remove_text=True)
def test_skew_rectangle():
fix, axes = plt.subplots(5, 5, sharex=True, sharey=True, figsize=(8, 8))
axes = axes.flat
rotations = list(itertools.product([-3, -1, 0, 1, 3], repeat=2))
axes[0].set_xlim([-3, 3])
axes[0].set_ylim([-3, 3])
axes[0].set_aspect('equal', share=True)
for ax, (xrots, yrots) in zip(axes, rotations):
xdeg, ydeg = 45 * xrots, 45 * yrots
t = transforms.Affine2D().skew_deg(xdeg, ydeg)
ax.set_title('Skew of {0} in X and {1} in Y'.format(xdeg, ydeg))
ax.add_patch(mpatch.Rectangle([-1, -1], 2, 2,
transform=t + ax.transData,
alpha=0.5, facecolor='coral'))
plt.subplots_adjust(wspace=0, left=0.01, right=0.99, bottom=0.01, top=0.99)
| 7,139 | 32.679245 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_arrow_patches.py | from __future__ import absolute_import, division, print_function
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
import matplotlib.patches as mpatches
def draw_arrow(ax, t, r):
ax.annotate('', xy=(0.5, 0.5 + r), xytext=(0.5, 0.5), size=30,
arrowprops=dict(arrowstyle=t,
fc="b", ec='k'))
@image_comparison(baseline_images=['fancyarrow_test_image'])
def test_fancyarrow():
# Added 0 to test division by zero error described in issue 3930
r = [0.4, 0.3, 0.2, 0.1, 0]
t = ["fancy", "simple", mpatches.ArrowStyle.Fancy()]
fig, axes = plt.subplots(len(t), len(r), squeeze=False,
subplot_kw=dict(aspect=True),
figsize=(8, 4.5))
for i_r, r1 in enumerate(r):
for i_t, t1 in enumerate(t):
ax = axes[i_t, i_r]
draw_arrow(ax, t1, r1)
ax.tick_params(labelleft=False, labelbottom=False)
@image_comparison(baseline_images=['boxarrow_test_image'], extensions=['png'])
def test_boxarrow():
styles = mpatches.BoxStyle.get_styles()
n = len(styles)
spacing = 1.2
figheight = (n * spacing + .5)
fig1 = plt.figure(1, figsize=(4 / 1.5, figheight / 1.5))
fontsize = 0.3 * 72
for i, stylename in enumerate(sorted(styles)):
fig1.text(0.5, ((n - i) * spacing - 0.5)/figheight, stylename,
ha="center",
size=fontsize,
transform=fig1.transFigure,
bbox=dict(boxstyle=stylename, fc="w", ec="k"))
def __prepare_fancyarrow_dpi_cor_test():
"""
Convenience function that prepares and returns a FancyArrowPatch. It aims
at being used to test that the size of the arrow head does not depend on
the DPI value of the exported picture.
NB: this function *is not* a test in itself!
"""
fig2 = plt.figure("fancyarrow_dpi_cor_test", figsize=(4, 3), dpi=50)
ax = fig2.add_subplot(111)
ax.set_xlim([0, 1])
ax.set_ylim([0, 1])
ax.add_patch(mpatches.FancyArrowPatch(posA=(0.3, 0.4), posB=(0.8, 0.6),
lw=3, arrowstyle=u'->',
mutation_scale=100))
return fig2
@image_comparison(baseline_images=['fancyarrow_dpi_cor_100dpi'],
remove_text=True, extensions=['png'],
savefig_kwarg=dict(dpi=100))
def test_fancyarrow_dpi_cor_100dpi():
"""
Check the export of a FancyArrowPatch @ 100 DPI. FancyArrowPatch is
instantiated through a dedicated function because another similar test
checks a similar export but with a different DPI value.
Remark: test only a rasterized format.
"""
__prepare_fancyarrow_dpi_cor_test()
@image_comparison(baseline_images=['fancyarrow_dpi_cor_200dpi'],
remove_text=True, extensions=['png'],
savefig_kwarg=dict(dpi=200))
def test_fancyarrow_dpi_cor_200dpi():
"""
As test_fancyarrow_dpi_cor_100dpi, but exports @ 200 DPI. The relative size
of the arrow head should be the same.
"""
__prepare_fancyarrow_dpi_cor_test()
@image_comparison(baseline_images=['fancyarrow_dash'],
remove_text=True, extensions=['png'],
style='default')
def test_fancyarrow_dash():
from matplotlib.patches import FancyArrowPatch
fig, ax = plt.subplots()
e = FancyArrowPatch((0, 0), (0.5, 0.5),
arrowstyle='-|>',
connectionstyle='angle3,angleA=0,angleB=90',
mutation_scale=10.0,
linewidth=2,
linestyle='dashed',
color='k')
e2 = FancyArrowPatch((0, 0), (0.5, 0.5),
arrowstyle='-|>',
connectionstyle='angle3',
mutation_scale=10.0,
linewidth=2,
linestyle='dotted',
color='k')
ax.add_patch(e)
ax.add_patch(e2)
@image_comparison(baseline_images=['arrow_styles'], extensions=['png'],
style='mpl20', remove_text=True)
def test_arrow_styles():
styles = mpatches.ArrowStyle.get_styles()
n = len(styles)
fig, ax = plt.subplots(figsize=(6, 10))
ax.set_xlim(0, 1)
ax.set_ylim(-1, n)
for i, stylename in enumerate(sorted(styles)):
patch = mpatches.FancyArrowPatch((0.1, i), (0.8, i),
arrowstyle=stylename,
mutation_scale=25)
ax.add_patch(patch)
| 4,675 | 32.884058 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_collections.py | """
Tests specific to the collections module.
"""
from __future__ import absolute_import, division, print_function
import io
import numpy as np
from numpy.testing import (
assert_array_equal, assert_array_almost_equal, assert_equal)
import pytest
import matplotlib.pyplot as plt
import matplotlib.collections as mcollections
import matplotlib.transforms as mtransforms
from matplotlib.collections import Collection, LineCollection, EventCollection
from matplotlib.testing.decorators import image_comparison
def generate_EventCollection_plot():
'''
generate the initial collection and plot it
'''
positions = np.array([0., 1., 2., 3., 5., 8., 13., 21.])
extra_positions = np.array([34., 55., 89.])
orientation = 'horizontal'
lineoffset = 1
linelength = .5
linewidth = 2
color = [1, 0, 0, 1]
linestyle = 'solid'
antialiased = True
coll = EventCollection(positions,
orientation=orientation,
lineoffset=lineoffset,
linelength=linelength,
linewidth=linewidth,
color=color,
linestyle=linestyle,
antialiased=antialiased
)
fig = plt.figure()
splt = fig.add_subplot(1, 1, 1)
splt.add_collection(coll)
splt.set_title('EventCollection: default')
props = {'positions': positions,
'extra_positions': extra_positions,
'orientation': orientation,
'lineoffset': lineoffset,
'linelength': linelength,
'linewidth': linewidth,
'color': color,
'linestyle': linestyle,
'antialiased': antialiased
}
splt.set_xlim(-1, 22)
splt.set_ylim(0, 2)
return splt, coll, props
@image_comparison(baseline_images=['EventCollection_plot__default'])
def test__EventCollection__get_segments():
'''
check to make sure the default segments have the correct coordinates
'''
_, coll, props = generate_EventCollection_plot()
check_segments(coll,
props['positions'],
props['linelength'],
props['lineoffset'],
props['orientation'])
def test__EventCollection__get_positions():
'''
check to make sure the default positions match the input positions
'''
_, coll, props = generate_EventCollection_plot()
np.testing.assert_array_equal(props['positions'], coll.get_positions())
def test__EventCollection__get_orientation():
'''
check to make sure the default orientation matches the input
orientation
'''
_, coll, props = generate_EventCollection_plot()
assert_equal(props['orientation'], coll.get_orientation())
def test__EventCollection__is_horizontal():
'''
check to make sure the default orientation matches the input
orientation
'''
_, coll, _ = generate_EventCollection_plot()
assert_equal(True, coll.is_horizontal())
def test__EventCollection__get_linelength():
'''
check to make sure the default linelength matches the input linelength
'''
_, coll, props = generate_EventCollection_plot()
assert_equal(props['linelength'], coll.get_linelength())
def test__EventCollection__get_lineoffset():
'''
check to make sure the default lineoffset matches the input lineoffset
'''
_, coll, props = generate_EventCollection_plot()
assert_equal(props['lineoffset'], coll.get_lineoffset())
def test__EventCollection__get_linestyle():
'''
check to make sure the default linestyle matches the input linestyle
'''
_, coll, _ = generate_EventCollection_plot()
assert_equal(coll.get_linestyle(), [(None, None)])
def test__EventCollection__get_color():
'''
check to make sure the default color matches the input color
'''
_, coll, props = generate_EventCollection_plot()
np.testing.assert_array_equal(props['color'], coll.get_color())
check_allprop_array(coll.get_colors(), props['color'])
@image_comparison(baseline_images=['EventCollection_plot__set_positions'])
def test__EventCollection__set_positions():
'''
check to make sure set_positions works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'], props['extra_positions']])
coll.set_positions(new_positions)
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll, new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: set_positions')
splt.set_xlim(-1, 90)
@image_comparison(baseline_images=['EventCollection_plot__add_positions'])
def test__EventCollection__add_positions():
'''
check to make sure add_positions works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][0]])
coll.add_positions(props['extra_positions'][0])
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: add_positions')
splt.set_xlim(-1, 35)
@image_comparison(baseline_images=['EventCollection_plot__append_positions'])
def test__EventCollection__append_positions():
'''
check to make sure append_positions works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][2]])
coll.append_positions(props['extra_positions'][2])
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: append_positions')
splt.set_xlim(-1, 90)
@image_comparison(baseline_images=['EventCollection_plot__extend_positions'])
def test__EventCollection__extend_positions():
'''
check to make sure extend_positions works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][1:]])
coll.extend_positions(props['extra_positions'][1:])
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: extend_positions')
splt.set_xlim(-1, 90)
@image_comparison(baseline_images=['EventCollection_plot__switch_orientation'])
def test__EventCollection__switch_orientation():
'''
check to make sure switch_orientation works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_orientation = 'vertical'
coll.switch_orientation()
assert_equal(new_orientation, coll.get_orientation())
assert_equal(False, coll.is_horizontal())
new_positions = coll.get_positions()
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'], new_orientation)
splt.set_title('EventCollection: switch_orientation')
splt.set_ylim(-1, 22)
splt.set_xlim(0, 2)
@image_comparison(
baseline_images=['EventCollection_plot__switch_orientation__2x'])
def test__EventCollection__switch_orientation_2x():
'''
check to make sure calling switch_orientation twice sets the
orientation back to the default
'''
splt, coll, props = generate_EventCollection_plot()
coll.switch_orientation()
coll.switch_orientation()
new_positions = coll.get_positions()
assert_equal(props['orientation'], coll.get_orientation())
assert_equal(True, coll.is_horizontal())
np.testing.assert_array_equal(props['positions'], new_positions)
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: switch_orientation 2x')
@image_comparison(baseline_images=['EventCollection_plot__set_orientation'])
def test__EventCollection__set_orientation():
'''
check to make sure set_orientation works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_orientation = 'vertical'
coll.set_orientation(new_orientation)
assert_equal(new_orientation, coll.get_orientation())
assert_equal(False, coll.is_horizontal())
check_segments(coll,
props['positions'],
props['linelength'],
props['lineoffset'],
new_orientation)
splt.set_title('EventCollection: set_orientation')
splt.set_ylim(-1, 22)
splt.set_xlim(0, 2)
@image_comparison(baseline_images=['EventCollection_plot__set_linelength'])
def test__EventCollection__set_linelength():
'''
check to make sure set_linelength works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_linelength = 15
coll.set_linelength(new_linelength)
assert_equal(new_linelength, coll.get_linelength())
check_segments(coll,
props['positions'],
new_linelength,
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: set_linelength')
splt.set_ylim(-20, 20)
@image_comparison(baseline_images=['EventCollection_plot__set_lineoffset'])
def test__EventCollection__set_lineoffset():
'''
check to make sure set_lineoffset works properly
'''
splt, coll, props = generate_EventCollection_plot()
new_lineoffset = -5.
coll.set_lineoffset(new_lineoffset)
assert_equal(new_lineoffset, coll.get_lineoffset())
check_segments(coll,
props['positions'],
props['linelength'],
new_lineoffset,
props['orientation'])
splt.set_title('EventCollection: set_lineoffset')
splt.set_ylim(-6, -4)
@image_comparison(baseline_images=['EventCollection_plot__set_linestyle'])
def test__EventCollection__set_linestyle():
'''
check to make sure set_linestyle works properly
'''
splt, coll, _ = generate_EventCollection_plot()
new_linestyle = 'dashed'
coll.set_linestyle(new_linestyle)
assert_equal(coll.get_linestyle(), [(0, (6.0, 6.0))])
splt.set_title('EventCollection: set_linestyle')
@image_comparison(baseline_images=['EventCollection_plot__set_ls_dash'],
remove_text=True)
def test__EventCollection__set_linestyle_single_dash():
'''
check to make sure set_linestyle accepts a single dash pattern
'''
splt, coll, _ = generate_EventCollection_plot()
new_linestyle = (0, (6., 6.))
coll.set_linestyle(new_linestyle)
assert_equal(coll.get_linestyle(), [(0, (6.0, 6.0))])
splt.set_title('EventCollection: set_linestyle')
@image_comparison(baseline_images=['EventCollection_plot__set_linewidth'])
def test__EventCollection__set_linewidth():
'''
check to make sure set_linestyle works properly
'''
splt, coll, _ = generate_EventCollection_plot()
new_linewidth = 5
coll.set_linewidth(new_linewidth)
assert_equal(coll.get_linewidth(), new_linewidth)
splt.set_title('EventCollection: set_linewidth')
@image_comparison(baseline_images=['EventCollection_plot__set_color'])
def test__EventCollection__set_color():
'''
check to make sure set_color works properly
'''
splt, coll, _ = generate_EventCollection_plot()
new_color = np.array([0, 1, 1, 1])
coll.set_color(new_color)
np.testing.assert_array_equal(new_color, coll.get_color())
check_allprop_array(coll.get_colors(), new_color)
splt.set_title('EventCollection: set_color')
def check_segments(coll, positions, linelength, lineoffset, orientation):
'''
check to make sure all values in the segment are correct, given a
particular set of inputs
note: this is not a test, it is used by tests
'''
segments = coll.get_segments()
if (orientation.lower() == 'horizontal'
or orientation.lower() == 'none' or orientation is None):
# if horizontal, the position in is in the y-axis
pos1 = 1
pos2 = 0
elif orientation.lower() == 'vertical':
# if vertical, the position in is in the x-axis
pos1 = 0
pos2 = 1
else:
raise ValueError("orientation must be 'horizontal' or 'vertical'")
# test to make sure each segment is correct
for i, segment in enumerate(segments):
assert_equal(segment[0, pos1], lineoffset + linelength / 2.)
assert_equal(segment[1, pos1], lineoffset - linelength / 2.)
assert_equal(segment[0, pos2], positions[i])
assert_equal(segment[1, pos2], positions[i])
def check_allprop_array(values, target):
'''
check to make sure all values match the given target if arrays
note: this is not a test, it is used by tests
'''
for value in values:
np.testing.assert_array_equal(value, target)
def test_null_collection_datalim():
col = mcollections.PathCollection([])
col_data_lim = col.get_datalim(mtransforms.IdentityTransform())
assert_array_equal(col_data_lim.get_points(),
mtransforms.Bbox.null().get_points())
def test_add_collection():
# Test if data limits are unchanged by adding an empty collection.
# Github issue #1490, pull #1497.
plt.figure()
ax = plt.axes()
coll = ax.scatter([0, 1], [0, 1])
ax.add_collection(coll)
bounds = ax.dataLim.bounds
coll = ax.scatter([], [])
assert_equal(ax.dataLim.bounds, bounds)
def test_quiver_limits():
ax = plt.axes()
x, y = np.arange(8), np.arange(10)
u = v = np.linspace(0, 10, 80).reshape(10, 8)
q = plt.quiver(x, y, u, v)
assert_equal(q.get_datalim(ax.transData).bounds, (0., 0., 7., 9.))
plt.figure()
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.quiver(x, y, np.sin(x), np.cos(y), transform=trans)
assert_equal(ax.dataLim.bounds, (20.0, 30.0, 15.0, 6.0))
def test_barb_limits():
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
# The calculated bounds are approximately the bounds of the original data,
# this is because the entire path is taken into account when updating the
# datalim.
assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
decimal=1)
@image_comparison(baseline_images=['EllipseCollection_test_image'],
extensions=['png'],
remove_text=True)
def test_EllipseCollection():
# Test basic functionality
fig, ax = plt.subplots()
x = np.arange(4)
y = np.arange(3)
X, Y = np.meshgrid(x, y)
XY = np.vstack((X.ravel(), Y.ravel())).T
ww = X / x[-1]
hh = Y / y[-1]
aa = np.ones_like(ww) * 20 # first axis is 20 degrees CCW from x axis
ec = mcollections.EllipseCollection(ww, hh, aa,
units='x',
offsets=XY,
transOffset=ax.transData,
facecolors='none')
ax.add_collection(ec)
ax.autoscale_view()
@image_comparison(baseline_images=['polycollection_close'],
extensions=['png'], remove_text=True)
def test_polycollection_close():
from mpl_toolkits.mplot3d import Axes3D
vertsQuad = [
[[0., 0.], [0., 1.], [1., 1.], [1., 0.]],
[[0., 1.], [2., 3.], [2., 2.], [1., 1.]],
[[2., 2.], [2., 3.], [4., 1.], [3., 1.]],
[[3., 0.], [3., 1.], [4., 1.], [4., 0.]]]
fig = plt.figure()
ax = Axes3D(fig)
colors = ['r', 'g', 'b', 'y', 'k']
zpos = list(range(5))
poly = mcollections.PolyCollection(
vertsQuad * len(zpos), linewidth=0.25)
poly.set_alpha(0.7)
# need to have a z-value for *each* polygon = element!
zs = []
cs = []
for z, c in zip(zpos, colors):
zs.extend([z] * len(vertsQuad))
cs.extend([c] * len(vertsQuad))
poly.set_color(cs)
ax.add_collection3d(poly, zs=zs, zdir='y')
# axis limit settings:
ax.set_xlim3d(0, 4)
ax.set_zlim3d(0, 3)
ax.set_ylim3d(0, 4)
@image_comparison(baseline_images=['regularpolycollection_rotate'],
extensions=['png'], remove_text=True)
def test_regularpolycollection_rotate():
xx, yy = np.mgrid[:10, :10]
xy_points = np.transpose([xx.flatten(), yy.flatten()])
rotations = np.linspace(0, 2*np.pi, len(xy_points))
fig, ax = plt.subplots()
for xy, alpha in zip(xy_points, rotations):
col = mcollections.RegularPolyCollection(
4, sizes=(100,), rotation=alpha,
offsets=[xy], transOffset=ax.transData)
ax.add_collection(col, autolim=True)
ax.autoscale_view()
@image_comparison(baseline_images=['regularpolycollection_scale'],
extensions=['png'], remove_text=True)
def test_regularpolycollection_scale():
# See issue #3860
class SquareCollection(mcollections.RegularPolyCollection):
def __init__(self, **kwargs):
super(SquareCollection, self).__init__(
4, rotation=np.pi/4., **kwargs)
def get_transform(self):
"""Return transform scaling circle areas to data space."""
ax = self.axes
pts2pixels = 72.0 / ax.figure.dpi
scale_x = pts2pixels * ax.bbox.width / ax.viewLim.width
scale_y = pts2pixels * ax.bbox.height / ax.viewLim.height
return mtransforms.Affine2D().scale(scale_x, scale_y)
fig, ax = plt.subplots()
xy = [(0, 0)]
# Unit square has a half-diagonal of `1 / sqrt(2)`, so `pi * r**2`
# equals...
circle_areas = [np.pi / 2]
squares = SquareCollection(sizes=circle_areas, offsets=xy,
transOffset=ax.transData)
ax.add_collection(squares, autolim=True)
ax.axis([-1, 1, -1, 1])
def test_picking():
fig, ax = plt.subplots()
col = ax.scatter([0], [0], [1000], picker=True)
fig.savefig(io.BytesIO(), dpi=fig.dpi)
class MouseEvent(object):
pass
event = MouseEvent()
event.x = 325
event.y = 240
found, indices = col.contains(event)
assert found
assert_array_equal(indices['ind'], [0])
def test_linestyle_single_dashes():
plt.scatter([0, 1, 2], [0, 1, 2], linestyle=(0., [2., 2.]))
plt.draw()
@image_comparison(baseline_images=['size_in_xy'], remove_text=True,
extensions=['png'])
def test_size_in_xy():
fig, ax = plt.subplots()
widths, heights, angles = (10, 10), 10, 0
widths = 10, 10
coords = [(10, 10), (15, 15)]
e = mcollections.EllipseCollection(
widths, heights, angles,
units='xy',
offsets=coords,
transOffset=ax.transData)
ax.add_collection(e)
ax.set_xlim(0, 30)
ax.set_ylim(0, 30)
def test_pandas_indexing(pd):
# Should not fail break when faced with a
# non-zero indexed series
index = [11, 12, 13]
ec = fc = pd.Series(['red', 'blue', 'green'], index=index)
lw = pd.Series([1, 2, 3], index=index)
ls = pd.Series(['solid', 'dashed', 'dashdot'], index=index)
aa = pd.Series([True, False, True], index=index)
Collection(edgecolors=ec)
Collection(facecolors=fc)
Collection(linewidths=lw)
Collection(linestyles=ls)
Collection(antialiaseds=aa)
@pytest.mark.style('default')
def test_lslw_bcast():
col = mcollections.PathCollection([])
col.set_linestyles(['-', '-'])
col.set_linewidths([1, 2, 3])
assert_equal(col.get_linestyles(), [(None, None)] * 6)
assert_equal(col.get_linewidths(), [1, 2, 3] * 2)
col.set_linestyles(['-', '-', '-'])
assert_equal(col.get_linestyles(), [(None, None)] * 3)
assert_equal(col.get_linewidths(), [1, 2, 3])
@pytest.mark.style('default')
def test_capstyle():
col = mcollections.PathCollection([], capstyle='round')
assert_equal(col.get_capstyle(), 'round')
col.set_capstyle('butt')
assert_equal(col.get_capstyle(), 'butt')
@pytest.mark.style('default')
def test_joinstyle():
col = mcollections.PathCollection([], joinstyle='round')
assert_equal(col.get_joinstyle(), 'round')
col.set_joinstyle('miter')
assert_equal(col.get_joinstyle(), 'miter')
@image_comparison(baseline_images=['cap_and_joinstyle'],
extensions=['png'])
def test_cap_and_joinstyle_image():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_xlim([-0.5, 1.5])
ax.set_ylim([-0.5, 2.5])
x = np.array([0.0, 1.0, 0.5])
ys = np.array([[0.0], [0.5], [1.0]]) + np.array([[0.0, 0.0, 1.0]])
segs = np.zeros((3, 3, 2))
segs[:, :, 0] = x
segs[:, :, 1] = ys
line_segments = LineCollection(segs, linewidth=[10, 15, 20])
line_segments.set_capstyle("round")
line_segments.set_joinstyle("miter")
ax.add_collection(line_segments)
ax.set_title('Line collection with customized caps and joinstyle')
@image_comparison(baseline_images=['scatter_post_alpha'],
extensions=['png'], remove_text=True,
style='default')
def test_scatter_post_alpha():
fig, ax = plt.subplots()
sc = ax.scatter(range(5), range(5), c=range(5))
# this needs to be here to update internal state
fig.canvas.draw()
sc.set_alpha(.1)
| 22,315 | 32.109792 | 79 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_container.py | from __future__ import absolute_import, division, print_function
import six
import matplotlib.pyplot as plt
def test_stem_remove():
ax = plt.gca()
st = ax.stem([1, 2], [1, 2])
st.remove()
def test_errorbar_remove():
# Regression test for a bug that caused remove to fail when using
# fmt='none'
ax = plt.gca()
eb = ax.errorbar([1], [1])
eb.remove()
eb = ax.errorbar([1], [1], xerr=1)
eb.remove()
eb = ax.errorbar([1], [1], yerr=2)
eb.remove()
eb = ax.errorbar([1], [1], xerr=[2], yerr=2)
eb.remove()
eb = ax.errorbar([1], [1], fmt='none')
eb.remove()
| 627 | 17.470588 | 69 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/__init__.py | from __future__ import absolute_import, division, print_function
import six
import difflib
import os
from matplotlib import cbook
from matplotlib.testing import setup
# Check that the test directories exist
if not os.path.exists(os.path.join(
os.path.dirname(__file__), 'baseline_images')):
raise IOError(
'The baseline image directory does not exist. '
'This is most likely because the test data is not installed. '
'You may need to install matplotlib from source to get the '
'test data.')
@cbook.deprecated("2.1")
def assert_str_equal(reference_str, test_str,
format_str=('String {str1} and {str2} do not '
'match:\n{differences}')):
"""
Assert the two strings are equal. If not, fail and print their
diffs using difflib.
"""
if reference_str != test_str:
diff = difflib.unified_diff(reference_str.splitlines(1),
test_str.splitlines(1),
'Reference', 'Test result',
'', '', 0)
raise ValueError(format_str.format(str1=reference_str,
str2=test_str,
differences=''.join(diff)))
| 1,313 | 32.692308 | 70 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_png.py | from __future__ import absolute_import, division, print_function
import six
from six import BytesIO
import glob
import os
import numpy as np
import pytest
from matplotlib.testing.decorators import image_comparison
from matplotlib import pyplot as plt
import matplotlib.cm as cm
import sys
on_win = (sys.platform == 'win32')
@image_comparison(baseline_images=['pngsuite'], extensions=['png'],
tol=0.03)
def test_pngsuite():
dirname = os.path.join(
os.path.dirname(__file__),
'baseline_images',
'pngsuite')
files = sorted(glob.iglob(os.path.join(dirname, 'basn*.png')))
fig = plt.figure(figsize=(len(files), 2))
for i, fname in enumerate(files):
data = plt.imread(fname)
cmap = None # use default colormap
if data.ndim == 2:
# keep grayscale images gray
cmap = cm.gray
plt.imshow(data, extent=[i, i + 1, 0, 1], cmap=cmap)
plt.gca().patch.set_facecolor("#ddffff")
plt.gca().set_xlim(0, len(files))
def test_imread_png_uint16():
from matplotlib import _png
img = _png.read_png_int(os.path.join(os.path.dirname(__file__),
'baseline_images/test_png/uint16.png'))
assert (img.dtype == np.uint16)
assert np.sum(img.flatten()) == 134184960
def test_truncated_file(tmpdir):
d = tmpdir.mkdir('test')
fname = str(d.join('test.png'))
fname_t = str(d.join('test_truncated.png'))
plt.savefig(fname)
with open(fname, 'rb') as fin:
buf = fin.read()
with open(fname_t, 'wb') as fout:
fout.write(buf[:20])
with pytest.raises(Exception):
plt.imread(fname_t)
def test_truncated_buffer():
b = BytesIO()
plt.savefig(b)
b.seek(0)
b2 = BytesIO(b.read(20))
b2.seek(0)
with pytest.raises(Exception):
plt.imread(b2)
| 1,864 | 24.902778 | 76 | py |
cba-pipeline-public | cba-pipeline-public-master/containernet/ndn-containers/ndn_headless-player/bandits/venv/lib/python3.6/site-packages/matplotlib/tests/test_transforms.py | from __future__ import absolute_import, division, print_function
from six.moves import zip
import unittest
import numpy as np
from numpy.testing import (assert_allclose, assert_almost_equal,
assert_array_equal, assert_array_almost_equal)
import pytest
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.transforms as mtransforms
from matplotlib.path import Path
from matplotlib.scale import LogScale
from matplotlib.testing.decorators import image_comparison
def test_non_affine_caching():
class AssertingNonAffineTransform(mtransforms.Transform):
"""
This transform raises an assertion error when called when it
shouldn't be and self.raise_on_transform is True.
"""
input_dims = output_dims = 2
is_affine = False
def __init__(self, *args, **kwargs):
mtransforms.Transform.__init__(self, *args, **kwargs)
self.raise_on_transform = False
self.underlying_transform = mtransforms.Affine2D().scale(10, 10)
def transform_path_non_affine(self, path):
assert not self.raise_on_transform, \
'Invalidated affine part of transform unnecessarily.'
return self.underlying_transform.transform_path(path)
transform_path = transform_path_non_affine
def transform_non_affine(self, path):
assert not self.raise_on_transform, \
'Invalidated affine part of transform unnecessarily.'
return self.underlying_transform.transform(path)
transform = transform_non_affine
my_trans = AssertingNonAffineTransform()
ax = plt.axes()
plt.plot(np.arange(10), transform=my_trans + ax.transData)
plt.draw()
# enable the transform to raise an exception if it's non-affine transform
# method is triggered again.
my_trans.raise_on_transform = True
ax.transAxes.invalidate()
plt.draw()
def test_external_transform_api():
class ScaledBy(object):
def __init__(self, scale_factor):
self._scale_factor = scale_factor
def _as_mpl_transform(self, axes):
return (mtransforms.Affine2D().scale(self._scale_factor)
+ axes.transData)
ax = plt.axes()
line, = plt.plot(np.arange(10), transform=ScaledBy(10))
ax.set_xlim(0, 100)
ax.set_ylim(0, 100)
# assert that the top transform of the line is the scale transform.
assert_allclose(line.get_transform()._a.get_matrix(),
mtransforms.Affine2D().scale(10).get_matrix())
@image_comparison(baseline_images=['pre_transform_data'],
tol=0.08)
def test_pre_transform_plotting():
# a catch-all for as many as possible plot layouts which handle
# pre-transforming the data NOTE: The axis range is important in this
# plot. It should be x10 what the data suggests it should be
ax = plt.axes()
times10 = mtransforms.Affine2D().scale(10)
ax.contourf(np.arange(48).reshape(6, 8), transform=times10 + ax.transData)
ax.pcolormesh(np.linspace(0, 4, 7),
np.linspace(5.5, 8, 9),
np.arange(48).reshape(8, 6),
transform=times10 + ax.transData)
ax.scatter(np.linspace(0, 10), np.linspace(10, 0),
transform=times10 + ax.transData)
x = np.linspace(8, 10, 20)
y = np.linspace(1, 5, 20)
u = 2*np.sin(x) + np.cos(y[:, np.newaxis])
v = np.sin(x) - np.cos(y[:, np.newaxis])
df = 25. / 30. # Compatibility factor for old test image
ax.streamplot(x, y, u, v, transform=times10 + ax.transData,
density=(df, df), linewidth=u**2 + v**2)
# reduce the vector data down a bit for barb and quiver plotting
x, y = x[::3], y[::3]
u, v = u[::3, ::3], v[::3, ::3]
ax.quiver(x, y + 5, u, v, transform=times10 + ax.transData)
ax.barbs(x - 3, y + 5, u**2, v**2, transform=times10 + ax.transData)
def test_contour_pre_transform_limits():
ax = plt.axes()
xs, ys = np.meshgrid(np.linspace(15, 20, 15), np.linspace(12.4, 12.5, 20))
ax.contourf(xs, ys, np.log(xs * ys),
transform=mtransforms.Affine2D().scale(0.1) + ax.transData)
expected = np.array([[1.5, 1.24],
[2., 1.25]])
assert_almost_equal(expected, ax.dataLim.get_points())
def test_pcolor_pre_transform_limits():
# Based on test_contour_pre_transform_limits()
ax = plt.axes()
xs, ys = np.meshgrid(np.linspace(15, 20, 15), np.linspace(12.4, 12.5, 20))
ax.pcolor(xs, ys, np.log(xs * ys),
transform=mtransforms.Affine2D().scale(0.1) + ax.transData)
expected = np.array([[1.5, 1.24],
[2., 1.25]])
assert_almost_equal(expected, ax.dataLim.get_points())
def test_pcolormesh_pre_transform_limits():
# Based on test_contour_pre_transform_limits()
ax = plt.axes()
xs, ys = np.meshgrid(np.linspace(15, 20, 15), np.linspace(12.4, 12.5, 20))
ax.pcolormesh(xs, ys, np.log(xs * ys),
transform=mtransforms.Affine2D().scale(0.1) + ax.transData)
expected = np.array([[1.5, 1.24],
[2., 1.25]])
assert_almost_equal(expected, ax.dataLim.get_points())
def test_Affine2D_from_values():
points = np.array([[0, 0],
[10, 20],
[-1, 0],
])
t = mtransforms.Affine2D.from_values(1, 0, 0, 0, 0, 0)
actual = t.transform(points)
expected = np.array([[0, 0], [10, 0], [-1, 0]])
assert_almost_equal(actual, expected)
t = mtransforms.Affine2D.from_values(0, 2, 0, 0, 0, 0)
actual = t.transform(points)
expected = np.array([[0, 0], [0, 20], [0, -2]])
assert_almost_equal(actual, expected)
t = mtransforms.Affine2D.from_values(0, 0, 3, 0, 0, 0)
actual = t.transform(points)
expected = np.array([[0, 0], [60, 0], [0, 0]])
assert_almost_equal(actual, expected)
t = mtransforms.Affine2D.from_values(0, 0, 0, 4, 0, 0)
actual = t.transform(points)
expected = np.array([[0, 0], [0, 80], [0, 0]])
assert_almost_equal(actual, expected)
t = mtransforms.Affine2D.from_values(0, 0, 0, 0, 5, 0)
actual = t.transform(points)
expected = np.array([[5, 0], [5, 0], [5, 0]])
assert_almost_equal(actual, expected)
t = mtransforms.Affine2D.from_values(0, 0, 0, 0, 0, 6)
actual = t.transform(points)
expected = np.array([[0, 6], [0, 6], [0, 6]])
assert_almost_equal(actual, expected)
def test_clipping_of_log():
# issue 804
M, L, C = Path.MOVETO, Path.LINETO, Path.CLOSEPOLY
points = [(0.2, -99), (0.4, -99), (0.4, 20), (0.2, 20), (0.2, -99)]
codes = [M, L, L, L, C]
path = Path(points, codes)
# something like this happens in plotting logarithmic histograms
trans = mtransforms.BlendedGenericTransform(mtransforms.Affine2D(),
LogScale.Log10Transform('clip'))
tpath = trans.transform_path_non_affine(path)
result = tpath.iter_segments(trans.get_affine(),
clip=(0, 0, 100, 100),
simplify=False)
tpoints, tcodes = zip(*result)
assert_allclose(tcodes, [M, L, L, L, C])
class NonAffineForTest(mtransforms.Transform):
"""
A class which looks like a non affine transform, but does whatever
the given transform does (even if it is affine). This is very useful
for testing NonAffine behaviour with a simple Affine transform.
"""
is_affine = False
output_dims = 2
input_dims = 2
def __init__(self, real_trans, *args, **kwargs):
self.real_trans = real_trans
mtransforms.Transform.__init__(self, *args, **kwargs)
def transform_non_affine(self, values):
return self.real_trans.transform(values)
def transform_path_non_affine(self, path):
return self.real_trans.transform_path(path)
class BasicTransformTests(unittest.TestCase):
def setUp(self):
self.ta1 = mtransforms.Affine2D(shorthand_name='ta1').rotate(np.pi / 2)
self.ta2 = mtransforms.Affine2D(shorthand_name='ta2').translate(10, 0)
self.ta3 = mtransforms.Affine2D(shorthand_name='ta3').scale(1, 2)
self.tn1 = NonAffineForTest(mtransforms.Affine2D().translate(1, 2),
shorthand_name='tn1')
self.tn2 = NonAffineForTest(mtransforms.Affine2D().translate(1, 2),
shorthand_name='tn2')
self.tn3 = NonAffineForTest(mtransforms.Affine2D().translate(1, 2),
shorthand_name='tn3')
# creates a transform stack which looks like ((A, (N, A)), A)
self.stack1 = (self.ta1 + (self.tn1 + self.ta2)) + self.ta3
# creates a transform stack which looks like (((A, N), A), A)
self.stack2 = self.ta1 + self.tn1 + self.ta2 + self.ta3
# creates a transform stack which is a subset of stack2
self.stack2_subset = self.tn1 + self.ta2 + self.ta3
# when in debug, the transform stacks can produce dot images:
# self.stack1.write_graphviz(file('stack1.dot', 'w'))
# self.stack2.write_graphviz(file('stack2.dot', 'w'))
# self.stack2_subset.write_graphviz(file('stack2_subset.dot', 'w'))
def test_transform_depth(self):
assert self.stack1.depth == 4
assert self.stack2.depth == 4
assert self.stack2_subset.depth == 3
def test_left_to_right_iteration(self):
stack3 = (self.ta1 + (self.tn1 + (self.ta2 + self.tn2))) + self.ta3
# stack3.write_graphviz(file('stack3.dot', 'w'))
target_transforms = [stack3,
(self.tn1 + (self.ta2 + self.tn2)) + self.ta3,
(self.ta2 + self.tn2) + self.ta3,
self.tn2 + self.ta3,
self.ta3,
]
r = [rh for _, rh in stack3._iter_break_from_left_to_right()]
assert len(r) == len(target_transforms)
for target_stack, stack in zip(target_transforms, r):
assert target_stack == stack
def test_transform_shortcuts(self):
assert self.stack1 - self.stack2_subset == self.ta1
assert self.stack2 - self.stack2_subset == self.ta1
assert self.stack2_subset - self.stack2 == self.ta1.inverted()
assert (self.stack2_subset - self.stack2).depth == 1
with pytest.raises(ValueError):
self.stack1 - self.stack2
aff1 = self.ta1 + (self.ta2 + self.ta3)
aff2 = self.ta2 + self.ta3
assert aff1 - aff2 == self.ta1
assert aff1 - self.ta2 == aff1 + self.ta2.inverted()
assert self.stack1 - self.ta3 == self.ta1 + (self.tn1 + self.ta2)
assert self.stack2 - self.ta3 == self.ta1 + self.tn1 + self.ta2
assert ((self.ta2 + self.ta3) - self.ta3 + self.ta3 ==
self.ta2 + self.ta3)
def test_contains_branch(self):
r1 = (self.ta2 + self.ta1)
r2 = (self.ta2 + self.ta1)
assert r1 == r2
assert r1 != self.ta1
assert r1.contains_branch(r2)
assert r1.contains_branch(self.ta1)
assert not r1.contains_branch(self.ta2)
assert not r1.contains_branch((self.ta2 + self.ta2))
assert r1 == r2
assert self.stack1.contains_branch(self.ta3)
assert self.stack2.contains_branch(self.ta3)
assert self.stack1.contains_branch(self.stack2_subset)
assert self.stack2.contains_branch(self.stack2_subset)
assert not self.stack2_subset.contains_branch(self.stack1)
assert not self.stack2_subset.contains_branch(self.stack2)
assert self.stack1.contains_branch((self.ta2 + self.ta3))
assert self.stack2.contains_branch((self.ta2 + self.ta3))
assert not self.stack1.contains_branch((self.tn1 + self.ta2))
def test_affine_simplification(self):
# tests that a transform stack only calls as much is absolutely
# necessary "non-affine" allowing the best possible optimization with
# complex transformation stacks.
points = np.array([[0, 0], [10, 20], [np.nan, 1], [-1, 0]],
dtype=np.float64)
na_pts = self.stack1.transform_non_affine(points)
all_pts = self.stack1.transform(points)
na_expected = np.array([[1., 2.], [-19., 12.],
[np.nan, np.nan], [1., 1.]], dtype=np.float64)
all_expected = np.array([[11., 4.], [-9., 24.],
[np.nan, np.nan], [11., 2.]],
dtype=np.float64)
# check we have the expected results from doing the affine part only
assert_array_almost_equal(na_pts, na_expected)
# check we have the expected results from a full transformation
assert_array_almost_equal(all_pts, all_expected)
# check we have the expected results from doing the transformation in
# two steps
assert_array_almost_equal(self.stack1.transform_affine(na_pts),
all_expected)
# check that getting the affine transformation first, then fully
# transforming using that yields the same result as before.
assert_array_almost_equal(self.stack1.get_affine().transform(na_pts),
all_expected)
# check that the affine part of stack1 & stack2 are equivalent
# (i.e. the optimization is working)
expected_result = (self.ta2 + self.ta3).get_matrix()
result = self.stack1.get_affine().get_matrix()
assert_array_equal(expected_result, result)
result = self.stack2.get_affine().get_matrix()
assert_array_equal(expected_result, result)
class TestTransformPlotInterface(unittest.TestCase):
def tearDown(self):
plt.close()
def test_line_extent_axes_coords(self):
# a simple line in axes coordinates
ax = plt.axes()
ax.plot([0.1, 1.2, 0.8], [0.9, 0.5, 0.8], transform=ax.transAxes)
assert_array_equal(ax.dataLim.get_points(),
np.array([[np.inf, np.inf],
[-np.inf, -np.inf]]))
def test_line_extent_data_coords(self):
# a simple line in data coordinates
ax = plt.axes()
ax.plot([0.1, 1.2, 0.8], [0.9, 0.5, 0.8], transform=ax.transData)
assert_array_equal(ax.dataLim.get_points(),
np.array([[0.1, 0.5], [1.2, 0.9]]))
def test_line_extent_compound_coords1(self):
# a simple line in data coordinates in the y component, and in axes
# coordinates in the x
ax = plt.axes()
trans = mtransforms.blended_transform_factory(ax.transAxes,
ax.transData)
ax.plot([0.1, 1.2, 0.8], [35, -5, 18], transform=trans)
assert_array_equal(ax.dataLim.get_points(),
np.array([[np.inf, -5.],
[-np.inf, 35.]]))
plt.close()
def test_line_extent_predata_transform_coords(self):
# a simple line in (offset + data) coordinates
ax = plt.axes()
trans = mtransforms.Affine2D().scale(10) + ax.transData
ax.plot([0.1, 1.2, 0.8], [35, -5, 18], transform=trans)
assert_array_equal(ax.dataLim.get_points(),
np.array([[1., -50.], [12., 350.]]))
plt.close()
def test_line_extent_compound_coords2(self):
# a simple line in (offset + data) coordinates in the y component, and
# in axes coordinates in the x
ax = plt.axes()
trans = mtransforms.blended_transform_factory(ax.transAxes,
mtransforms.Affine2D().scale(10) + ax.transData)
ax.plot([0.1, 1.2, 0.8], [35, -5, 18], transform=trans)
assert_array_equal(ax.dataLim.get_points(),
np.array([[np.inf, -50.], [-np.inf, 350.]]))
plt.close()
def test_line_extents_affine(self):
ax = plt.axes()
offset = mtransforms.Affine2D().translate(10, 10)
plt.plot(np.arange(10), transform=offset + ax.transData)
expected_data_lim = np.array([[0., 0.], [9., 9.]]) + 10
assert_array_almost_equal(ax.dataLim.get_points(), expected_data_lim)
def test_line_extents_non_affine(self):
ax = plt.axes()
offset = mtransforms.Affine2D().translate(10, 10)
na_offset = NonAffineForTest(mtransforms.Affine2D().translate(10, 10))
plt.plot(np.arange(10), transform=offset + na_offset + ax.transData)
expected_data_lim = np.array([[0., 0.], [9., 9.]]) + 20
assert_array_almost_equal(ax.dataLim.get_points(), expected_data_lim)
def test_pathc_extents_non_affine(self):
ax = plt.axes()
offset = mtransforms.Affine2D().translate(10, 10)
na_offset = NonAffineForTest(mtransforms.Affine2D().translate(10, 10))
pth = Path(np.array([[0, 0], [0, 10], [10, 10], [10, 0]]))
patch = mpatches.PathPatch(pth,
transform=offset + na_offset + ax.transData)
ax.add_patch(patch)
expected_data_lim = np.array([[0., 0.], [10., 10.]]) + 20
assert_array_almost_equal(ax.dataLim.get_points(), expected_data_lim)
def test_pathc_extents_affine(self):
ax = plt.axes()
offset = mtransforms.Affine2D().translate(10, 10)
pth = Path(np.array([[0, 0], [0, 10], [10, 10], [10, 0]]))
patch = mpatches.PathPatch(pth, transform=offset + ax.transData)
ax.add_patch(patch)
expected_data_lim = np.array([[0., 0.], [10., 10.]]) + 10
assert_array_almost_equal(ax.dataLim.get_points(), expected_data_lim)
def test_line_extents_for_non_affine_transData(self):
ax = plt.axes(projection='polar')
# add 10 to the radius of the data
offset = mtransforms.Affine2D().translate(0, 10)
plt.plot(np.arange(10), transform=offset + ax.transData)
# the data lim of a polar plot is stored in coordinates
# before a transData transformation, hence the data limits
# are not what is being shown on the actual plot.
expected_data_lim = np.array([[0., 0.], [9., 9.]]) + [0, 10]
assert_array_almost_equal(ax.dataLim.get_points(), expected_data_lim)
def assert_bbox_eq(bbox1, bbox2):
assert_array_equal(bbox1.bounds, bbox2.bounds)
def test_bbox_intersection():
bbox_from_ext = mtransforms.Bbox.from_extents
inter = mtransforms.Bbox.intersection
r1 = bbox_from_ext(0, 0, 1, 1)
r2 = bbox_from_ext(0.5, 0.5, 1.5, 1.5)
r3 = bbox_from_ext(0.5, 0, 0.75, 0.75)
r4 = bbox_from_ext(0.5, 1.5, 1, 2.5)
r5 = bbox_from_ext(1, 1, 2, 2)
# self intersection -> no change
assert_bbox_eq(inter(r1, r1), r1)
# simple intersection
assert_bbox_eq(inter(r1, r2), bbox_from_ext(0.5, 0.5, 1, 1))
# r3 contains r2
assert_bbox_eq(inter(r1, r3), r3)
# no intersection
assert inter(r1, r4) is None
# single point
assert_bbox_eq(inter(r1, r5), bbox_from_ext(1, 1, 1, 1))
def test_bbox_as_strings():
b = mtransforms.Bbox([[.5, 0], [.75, .75]])
assert_bbox_eq(b, eval(repr(b), {'Bbox': mtransforms.Bbox}))
asdict = eval(str(b), {'Bbox': dict})
for k, v in asdict.items():
assert getattr(b, k) == v
fmt = '.1f'
asdict = eval(format(b, fmt), {'Bbox': dict})
for k, v in asdict.items():
assert eval(format(getattr(b, k), fmt)) == v
def test_transform_single_point():
t = mtransforms.Affine2D()
r = t.transform_affine((1, 1))
assert r.shape == (2,)
def test_log_transform():
# Tests that the last line runs without exception (previously the
# transform would fail if one of the axes was logarithmic).
fig, ax = plt.subplots()
ax.set_yscale('log')
ax.transData.transform((1, 1))
def test_nan_overlap():
a = mtransforms.Bbox([[0, 0], [1, 1]])
b = mtransforms.Bbox([[0, 0], [1, np.nan]])
assert not a.overlaps(b)
def test_transform_angles():
t = mtransforms.Affine2D() # Identity transform
angles = np.array([20, 45, 60])
points = np.array([[0, 0], [1, 1], [2, 2]])
# Identity transform does not change angles
new_angles = t.transform_angles(angles, points)
assert_array_almost_equal(angles, new_angles)
# points missing a 2nd dimension
with pytest.raises(ValueError):
t.transform_angles(angles, points[0:2, 0:1])
# Number of angles != Number of points
with pytest.raises(ValueError):
t.transform_angles(angles, points[0:2, :])
def test_nonsingular():
# test for zero-expansion type cases; other cases may be added later
zero_expansion = np.array([-0.001, 0.001])
cases = [(0, np.nan), (0, 0), (0, 7.9e-317)]
for args in cases:
out = np.array(mtransforms.nonsingular(*args))
assert_array_equal(out, zero_expansion)
def test_invalid_arguments():
t = mtransforms.Affine2D()
# There are two different exceptions, since the wrong number of
# dimensions is caught when constructing an array_view, and that
# raises a ValueError, and a wrong shape with a possible number
# of dimensions is caught by our CALL_CPP macro, which always
# raises the less precise RuntimeError.
with pytest.raises(ValueError):
t.transform(1)
with pytest.raises(ValueError):
t.transform([[[1]]])
with pytest.raises(RuntimeError):
t.transform([])
with pytest.raises(RuntimeError):
t.transform([1])
with pytest.raises(RuntimeError):
t.transform([[1]])
with pytest.raises(RuntimeError):
t.transform([[1, 2, 3]])
def test_transformed_path():
points = [(0, 0), (1, 0), (1, 1), (0, 1)]
codes = [Path.MOVETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY]
path = Path(points, codes)
trans = mtransforms.Affine2D()
trans_path = mtransforms.TransformedPath(path, trans)
assert_allclose(trans_path.get_fully_transformed_path().vertices, points)
# Changing the transform should change the result.
r2 = 1 / np.sqrt(2)
trans.rotate(np.pi / 4)
assert_allclose(trans_path.get_fully_transformed_path().vertices,
[(0, 0), (r2, r2), (0, 2 * r2), (-r2, r2)],
atol=1e-15)
# Changing the path does not change the result (it's cached).
path.points = [(0, 0)] * 4
assert_allclose(trans_path.get_fully_transformed_path().vertices,
[(0, 0), (r2, r2), (0, 2 * r2), (-r2, r2)],
atol=1e-15)
def test_transformed_patch_path():
trans = mtransforms.Affine2D()
patch = mpatches.Wedge((0, 0), 1, 45, 135, transform=trans)
tpatch = mtransforms.TransformedPatchPath(patch)
points = tpatch.get_fully_transformed_path().vertices
# Changing the transform should change the result.
trans.scale(2)
assert_allclose(tpatch.get_fully_transformed_path().vertices, points * 2)
# Changing the path should change the result (and cancel out the scaling
# from the transform).
patch.set_radius(0.5)
assert_allclose(tpatch.get_fully_transformed_path().vertices, points)
@pytest.mark.parametrize('locked_element', ['x0', 'y0', 'x1', 'y1'])
def test_lockable_bbox(locked_element):
other_elements = ['x0', 'y0', 'x1', 'y1']
other_elements.remove(locked_element)
orig = mtransforms.Bbox.unit()
locked = mtransforms.LockableBbox(orig, **{locked_element: 2})
# LockableBbox should keep its locked element as specified in __init__.
assert getattr(locked, locked_element) == 2
assert getattr(locked, 'locked_' + locked_element) == 2
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
# Changing underlying Bbox should update everything but locked element.
orig.set_points(orig.get_points() + 10)
assert getattr(locked, locked_element) == 2
assert getattr(locked, 'locked_' + locked_element) == 2
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
# Unlocking element should revert values back to the underlying Bbox.
setattr(locked, 'locked_' + locked_element, None)
assert getattr(locked, 'locked_' + locked_element) is None
assert np.all(orig.get_points() == locked.get_points())
# Relocking an element should change its value, but not others.
setattr(locked, 'locked_' + locked_element, 3)
assert getattr(locked, locked_element) == 3
assert getattr(locked, 'locked_' + locked_element) == 3
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
| 24,773 | 37.95283 | 79 | py |
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