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/LASExplanation-0.0.1.tar.gz/LASExplanation-0.0.1/README.md | # LAS
This package is a brief wrap-up toolkit built based on 2 explanation packages: LIME and SHAP. The package contains 2 explainers: LIMEBAG and SHAP. It takes data and fitted models as input and returns explanations about feature importance ranks and/or weights. (etc. what attributes matter most within the prediction model).
## rq1.py
The demo runs LIMEBAG on a default dataset. It generates and presents explanations about feature importance ranks and weights for all testing data points. Can be called by LIMEBAG.demo1()
## rq2.py
The demo uses the explanations returned from LIMEBAG to run an effect size test. A summary of feature importance ranks and weights will be generated and presented as output. Can be called by LIMEBAG.demo2()
| PypiClean |
/Mesa-Geo-0.5.0.tar.gz/Mesa-Geo-0.5.0/mesa_geo/visualization/templates/js/MapModule.js | const MapModule = function (view, zoom, map_width, map_height, tiles, scale_options) {
// Create the map tag
const map_tag = document.createElement("div");
map_tag.style.width = map_width + "px";
map_tag.style.height = map_height + "px";
map_tag.style.border = "1px dotted";
map_tag.id = "mapid"
const customView = (view !== null && zoom !== null)
// Append it to #elements
const elements = document.getElementById("elements");
elements.appendChild(map_tag);
// Create Leaflet map and Agent layers
const Lmap = L.map('mapid', {zoomSnap: 0.1})
if (customView) {
Lmap.setView(view, zoom)
}
if (scale_options !== null) {
L.control.scale(scale_options).addTo(Lmap)
}
let agentLayer = L.geoJSON().addTo(Lmap)
// create tile layer
if (tiles !== null) {
if (tiles.kind === "raster_web_tile") {
L.tileLayer(tiles.url, tiles.options).addTo(Lmap)
} else if (tiles.kind === "wms_web_tile") {
L.tileLayer.wms(tiles.url, tiles.options).addTo(Lmap)
} else {
throw new Error("Unknown tile type: " + tiles.kind)
}
}
let hasFitBounds = false
this.renderLayers = function (layers) {
layers.rasters.forEach(function (layer) {
L.imageOverlay(layer, layers.total_bounds).addTo(Lmap)
})
layers.vectors.forEach(function (layer) {
L.geoJSON(layer).addTo(Lmap)
})
if (!hasFitBounds && !customView && layers.total_bounds.length !== 0) {
Lmap.fitBounds(layers.total_bounds)
hasFitBounds = true
}
}
this.renderAgents = function (agents) {
agentLayer.remove()
agentLayer = L.geoJSON(agents, {
onEachFeature: PopUpProperties,
style: function (feature) {
return feature.properties.style
},
pointToLayer: function (feature, latlang) {
return L.circleMarker(latlang, feature.properties.pointToLayer);
}
}).addTo(Lmap)
}
this.render = function (data) {
this.renderLayers(data.layers)
this.renderAgents(data.agents)
}
this.reset = function () {
agentLayer.remove()
}
}
function PopUpProperties(feature, layer) {
let popupContent = '<table>'
if (feature.properties.popupProperties) {
for (const p in feature.properties.popupProperties) {
popupContent += '<tr><td>' + p + '</td><td>' + feature.properties.popupProperties[p] + '</td></tr>'
}
}
popupContent += '</table>'
layer.bindPopup(popupContent)
} | PypiClean |
/Jalapeno-Lite-0.1.3.tar.gz/Jalapeno-Lite-0.1.3/Jalapeno/lib/siteMgr.py | import os
import pickle
from Jalapeno.lib.pardir import *
APP_DIR = no_dot(par_dir())
SITES_FOLDER = APP_DIR+os.sep+'Jalapeno_data'+os.sep+'Sites'
class Site():
def __init__(self,sitename):
self.sitename = sitename
@staticmethod
def site_create(sitename):
base_dir = SITES_FOLDER
sitefolder = os.path.join(base_dir,sitename)
subdir = {'Pages':None,
'build':None,
'_config':['_config.yaml','flask_settings.py','profile.yaml'],
'source':['image','extension']}
if not os.path.exists(sitefolder):
print("creating \'%s\' site folder"%sitename)
os.mkdir(sitefolder)
os.mkdir(sitefolder+os.sep+'Pages')
os.mkdir(sitefolder+os.sep+'Pages'+os.sep+'Draft')
os.mkdir(sitefolder+os.sep+'build')
os.mkdir(sitefolder+os.sep+'source')
os.mkdir(sitefolder+os.sep+'source'+os.sep+'image')
os.mkdir(sitefolder+os.sep+'source'+os.sep+'extension')
os.mkdir(sitefolder+os.sep+'_config')
config_folder = sitefolder+os.sep+'_config'+os.sep
for each in subdir['_config']:
f = open(config_folder+each,'w')
f.close()
f = open(config_folder+'flask_settings.py','w')
f.write(temp())
f.close()
else:
pass
@staticmethod
def site_switch(sitename):
g=open(SITES_FOLDER+os.sep+'.siterc','rb')
sitelist,site = pickle.load(g)
if sitename not in sitelist:
print('Site not exist')
return False
f = open(SITES_FOLDER+os.sep+'.siterc','wb')
pickle.dump((sitelist,sitename),f)
f.close()
print("Current site is '%s'"%sitename)
return True
@staticmethod
def site_list_add(sitename):
try:
g=open(SITES_FOLDER+os.sep+'.siterc','rb')
sitelist,site = pickle.load(g)
g.close()
sitelist.append(sitename)
f=open(SITES_FOLDER+os.sep+'.siterc','wb')
pickle.dump((sitelist,site),f)
f.close()
except:
print('site_list_add Wrong')
@staticmethod
def get_site():
g=open(SITES_FOLDER+os.sep+'.siterc','rb')
sitelist,sitename = pickle.load(g)
if sitename not in sitelist:
print('Site not exist')
return
return sitename
SITE_DIR=SITES_FOLDER+os.sep+Site.get_site()
def temp():
temp = '''
import os
from Jalapeno.path import SITE_DIR
from Jalapeno.lib.jalop_markdown import Jalop_markdown
DEBUG = True
THREADED = True
IMAGE_DIR = SITE_DIR+os.sep+'source'+os.sep+'image'
JS_EXTENSION_DIR = SITE_DIR+os.sep+'source'+os.sep+'extension'
def parent_dir(path):
return os.path.abspath(os.path.join(path,os.pardir))
PROJECT_ROOT = SITE_DIR+os.sep+'build'
FREEZER_DESTINATION = PROJECT_ROOT
FREEZER_REMOVE_EXTRA_FILES = False
'''
return temp | PypiClean |
/Azimuth-2.0.tar.gz/Azimuth-2.0/azimuth/corrstats.py | from __future__ import division
__author__ = 'psinger'
import numpy as np
from scipy.stats import t, norm
from math import atanh, pow
from numpy import tanh
def rz_ci(r, n, conf_level = 0.95):
zr_se = pow(1/(n - 3), .5)
moe = norm.ppf(1 - (1 - conf_level)/float(2)) * zr_se
zu = atanh(r) + moe
zl = atanh(r) - moe
return tanh((zl, zu))
def rho_rxy_rxz(rxy, rxz, ryz):
num = (ryz-1/2.*rxy*rxz)*(1-pow(rxy,2)-pow(rxz,2)-pow(ryz,2))+pow(ryz,3)
den = (1 - pow(rxy,2)) * (1 - pow(rxz,2))
return num/float(den)
def dependent_corr(xy, xz, yz, n, twotailed=True, conf_level=0.95, method='steiger'):
"""
Calculates the statistic significance between two dependent correlation coefficients
@param xy: correlation coefficient between x and y
@param xz: correlation coefficient between x and z
@param yz: correlation coefficient between y and z
@param n: number of elements in x, y and z
@param twotailed: whether to calculate a one or two tailed test, only works for 'steiger' method
@param conf_level: confidence level, only works for 'zou' method
@param method: defines the method uses, 'steiger' or 'zou'
@return: t and p-val
"""
if method == 'steiger':
d = xy - xz
determin = 1 - xy * xy - xz * xz - yz * yz + 2 * xy * xz * yz
av = (xy + xz)/2
cube = (1 - yz) * (1 - yz) * (1 - yz)
t2 = d * np.sqrt((n - 1) * (1 + yz)/(((2 * (n - 1)/(n - 3)) * determin + av * av * cube)))
p = 1 - t.cdf(abs(t2), n - 2)
if twotailed:
p *= 2
return t2, p
elif method == 'zou':
L1 = rz_ci(xy, n, conf_level=conf_level)[0]
U1 = rz_ci(xy, n, conf_level=conf_level)[1]
L2 = rz_ci(xz, n, conf_level=conf_level)[0]
U2 = rz_ci(xz, n, conf_level=conf_level)[1]
rho_r12_r13 = rho_rxy_rxz(xy, xz, yz)
lower = xy - xz - pow((pow((xy - L1), 2) + pow((U2 - xz), 2) - 2 * rho_r12_r13 * (xy - L1) * (U2 - xz)), 0.5)
upper = xy - xz + pow((pow((U1 - xy), 2) + pow((xz - L2), 2) - 2 * rho_r12_r13 * (U1 - xy) * (xz - L2)), 0.5)
return lower, upper
else:
raise Exception('Wrong method!')
def independent_corr(xy, ab, n, n2 = None, twotailed=True, conf_level=0.95, method='fisher'):
"""
Calculates the statistic significance between two independent correlation coefficients
@param xy: correlation coefficient between x and y
@param xz: correlation coefficient between a and b
@param n: number of elements in xy
@param n2: number of elements in ab (if distinct from n)
@param twotailed: whether to calculate a one or two tailed test, only works for 'fisher' method
@param conf_level: confidence level, only works for 'zou' method
@param method: defines the method uses, 'fisher' or 'zou'
@return: z and p-val
"""
if method == 'fisher':
xy_z = 0.5 * np.log((1 + xy)/(1 - xy))
xz_z = 0.5 * np.log((1 + ab)/(1 - ab))
if n2 is None:
n2 = n
se_diff_r = np.sqrt(1/(n - 3) + 1/(n2 - 3))
diff = xy_z - xz_z
z = abs(diff / se_diff_r)
p = (1 - norm.cdf(z))
if twotailed:
p *= 2
return z, p
elif method == 'zou':
L1 = rz_ci(xy, n, conf_level=conf_level)[0]
U1 = rz_ci(xy, n, conf_level=conf_level)[1]
L2 = rz_ci(ab, n2, conf_level=conf_level)[0]
U2 = rz_ci(ab, n2, conf_level=conf_level)[1]
lower = xy - ab - pow((pow((xy - L1), 2) + pow((U2 - ab), 2)), 0.5)
upper = xy - ab + pow((pow((U1 - xy), 2) + pow((ab - L2), 2)), 0.5)
return lower, upper
else:
raise Exception('Wrong method!')
#print dependent_corr(.396, .179, .088, 200, method='steiger')
#print independent_corr(.560, .588, 100, 353, method='fisher')
#print dependent_corr(.396, .179, .088, 200, method='zou')
#print independent_corr(.560, .588, 100, 353, method='zou') | PypiClean |
/AyiinXd-0.0.8-cp311-cp311-macosx_10_9_universal2.whl/fipper/storage/sqlite_storage.py |
import inspect
import sqlite3
import time
from threading import Lock
from typing import List, Tuple, Any
from fipper import raw
from .storage import Storage
from .. import utils
# language=SQLite
SCHEMA = """
CREATE TABLE sessions
(
dc_id INTEGER PRIMARY KEY,
api_id INTEGER,
test_mode INTEGER,
auth_key BLOB,
date INTEGER NOT NULL,
user_id INTEGER,
is_bot INTEGER
);
CREATE TABLE peers
(
id INTEGER PRIMARY KEY,
access_hash INTEGER,
type INTEGER NOT NULL,
username TEXT,
phone_number TEXT,
last_update_on INTEGER NOT NULL DEFAULT (CAST(STRFTIME('%s', 'now') AS INTEGER))
);
CREATE TABLE version
(
number INTEGER PRIMARY KEY
);
CREATE INDEX idx_peers_id ON peers (id);
CREATE INDEX idx_peers_username ON peers (username);
CREATE INDEX idx_peers_phone_number ON peers (phone_number);
CREATE TRIGGER trg_peers_last_update_on
AFTER UPDATE
ON peers
BEGIN
UPDATE peers
SET last_update_on = CAST(STRFTIME('%s', 'now') AS INTEGER)
WHERE id = NEW.id;
END;
"""
def get_input_peer(peer_id: int, access_hash: int, peer_type: str):
if peer_type in ["user", "bot"]:
return raw.types.InputPeerUser(
user_id=peer_id,
access_hash=access_hash
)
if peer_type == "group":
return raw.types.InputPeerChat(
chat_id=-peer_id
)
if peer_type in ["channel", "supergroup"]:
return raw.types.InputPeerChannel(
channel_id=utils.get_channel_id(peer_id),
access_hash=access_hash
)
raise ValueError(f"Invalid peer type: {peer_type}")
class SQLiteStorage(Storage):
VERSION = 3
USERNAME_TTL = 8 * 60 * 60
def __init__(self, name: str):
super().__init__(name)
self.conn = None # type: sqlite3.Connection
self.lock = Lock()
def create(self):
with self.lock, self.conn:
self.conn.executescript(SCHEMA)
self.conn.execute(
"INSERT INTO version VALUES (?)",
(self.VERSION,)
)
self.conn.execute(
"INSERT INTO sessions VALUES (?, ?, ?, ?, ?, ?, ?)",
(2, None, None, None, 0, None, None)
)
async def open(self):
raise NotImplementedError
async def save(self):
await self.date(int(time.time()))
with self.lock:
self.conn.commit()
async def close(self):
with self.lock:
self.conn.close()
async def delete(self):
raise NotImplementedError
async def update_peers(self, peers: List[Tuple[int, int, str, str, str]]):
with self.lock:
self.conn.executemany(
"REPLACE INTO peers (id, access_hash, type, username, phone_number)"
"VALUES (?, ?, ?, ?, ?)",
peers
)
async def get_peer_by_id(self, peer_id: int):
r = self.conn.execute(
"SELECT id, access_hash, type FROM peers WHERE id = ?",
(peer_id,)
).fetchone()
if r is None:
raise KeyError(f"ID not found: {peer_id}")
return get_input_peer(*r)
async def get_peer_by_username(self, username: str):
r = self.conn.execute(
"SELECT id, access_hash, type, last_update_on FROM peers WHERE username = ?"
"ORDER BY last_update_on DESC",
(username,)
).fetchone()
if r is None:
raise KeyError(f"Username not found: {username}")
if abs(time.time() - r[3]) > self.USERNAME_TTL:
raise KeyError(f"Username expired: {username}")
return get_input_peer(*r[:3])
async def get_peer_by_phone_number(self, phone_number: str):
r = self.conn.execute(
"SELECT id, access_hash, type FROM peers WHERE phone_number = ?",
(phone_number,)
).fetchone()
if r is None:
raise KeyError(f"Phone number not found: {phone_number}")
return get_input_peer(*r)
def _get(self):
attr = inspect.stack()[2].function
return self.conn.execute(
f"SELECT {attr} FROM sessions"
).fetchone()[0]
def _set(self, value: Any):
attr = inspect.stack()[2].function
with self.lock, self.conn:
self.conn.execute(
f"UPDATE sessions SET {attr} = ?",
(value,)
)
def _accessor(self, value: Any = object):
return self._get() if value == object else self._set(value)
async def dc_id(self, value: int = object):
return self._accessor(value)
async def api_id(self, value: int = object):
return self._accessor(value)
async def test_mode(self, value: bool = object):
return self._accessor(value)
async def auth_key(self, value: bytes = object):
return self._accessor(value)
async def date(self, value: int = object):
return self._accessor(value)
async def user_id(self, value: int = object):
return self._accessor(value)
async def is_bot(self, value: bool = object):
return self._accessor(value)
def version(self, value: int = object):
if value == object:
return self.conn.execute(
"SELECT number FROM version"
).fetchone()[0]
else:
with self.lock, self.conn:
self.conn.execute(
"UPDATE version SET number = ?",
(value,)
) | PypiClean |
/Friendly-Iter-0.0.1.tar.gz/Friendly-Iter-0.0.1/friendly_iter/iters.py | from multiprocessing import Process, Queue
from multiprocessing.queues import Empty
from .iterator_modifiers import flatten, skip, step, take
DEFAULT_NUMBER_OF_WORKERS = 4
class Iterator:
"""The friendly convenience wrapper over Python iterators."""
def __init__(self, iterable):
self.iter = iter(iterable)
def fork(self, n_jobs=DEFAULT_NUMBER_OF_WORKERS):
return ParallelIterator(self.iter, n_jobs=n_jobs)
def map(self, func):
"""Replace each item with the result of func(item)."""
self.iter = map(func, self.iter)
return self
def filter(self, func):
"""Keep only items for which func(item) is true."""
self.iter = filter(func, self.iter)
return self
def flatten(self):
self.iter = flatten(self.iter)
return self
def enumerate(self, start: int = 0):
self.iter = enumerate(self.iter, start)
def take(self, n: int):
"""Stop the iterator after the first `n` items."""
self.iter = take(n, self.iter)
return self
def skip(self, n: int):
"""Skip the first `n` items."""
self.iter = skip(n, self.iter)
return self
def step(self, n: int):
"""Yield every `n`th item, starting with the first."""
self.iter = step(n, self.iter)
return self
def __iter__(self):
return self.iter
class UnorderedIterator:
"""Like `Iterator` but does not make any guarantees about the order of
items.
The main difference to the normal `Iterator` is that this class does
not expose any methods that depend on the particular order of elements,
like `enumerate`, `skip`, or `step`.
"""
def __init__(self, iterable):
self.iter = iter(iterable)
def fork(self, n_jobs=DEFAULT_NUMBER_OF_WORKERS):
return ParallelIterator(self.iter, n_jobs=n_jobs)
def map(self, func):
"""Replace each item with the result of func(item)."""
self.iter = map(func, self.iter)
return self
def filter(self, func):
"""Keep only items for which func(item) is true."""
self.iter = filter(func, self.iter)
return self
def flatten(self):
self.iter = flatten(self.iter)
return self
def take(self, n: int):
"""Stop the iterator after `n` items.
Note that these don't have to be the *first* `n` items because the
unordered iterator does not guarantee any order.
"""
self.iter = take(n, self.iter)
return self
def __iter__(self):
return self.iter
class ParallelIterator:
"""Like `UnorderedIterator` but distributes work over several parallel
processes.
Does not expose any of the iterator methods that cannot be meaningfully
parallelized (like `take` for example).
"""
def __init__(self, iterable, n_jobs=DEFAULT_NUMBER_OF_WORKERS):
self.n_jobs = n_jobs
self.input_iter = iter(iterable)
self.pipeline = IteratorPipeline()
def map(self, func):
"""Replace each item with the result of func(item)."""
self.pipeline.add_transform(map, func)
return self
def filter(self, func):
"""Keep only items for which func(item) is true."""
self.pipeline.add_transform(filter, func)
return self
def flatten(self):
self.pipeline.add_transform(flatten)
return self
def join(self):
wc = WorkCoordinator(n_workers=self.n_jobs)
output_iter = wc.run(self.input_iter, self.pipeline)
return UnorderedIterator(output_iter)
class WorkCoordinator:
def __init__(self, n_workers, input_buffer_size=None, result_poll_interval=0.1):
self.distributor = Queue()
self.collector = Queue()
self.n_workers = n_workers
self.input_buffer_size = input_buffer_size or n_workers * 2
self.poll_interval = result_poll_interval
self.workers = []
self.active_workers = 0
def run(self, input_iter, pipeline):
self.start_workers(pipeline)
yield from self.balance_inputs_and_outputs(input_iter)
self.stop_workers()
yield from self.remaining_results()
def start_workers(self, pipeline):
self.active_workers = self.n_workers
self.workers = [Process(target=worker, args=(pipeline, self.distributor, self.collector, i)) for i in
range(self.n_workers)]
for w in self.workers:
w.start()
def stop_workers(self):
for _ in self.workers:
self.distributor.put(STOP_WORKER)
for w in self.workers:
w.join()
def balance_inputs_and_outputs(self, input_iter):
for x in input_iter:
while self.input_queue_is_full():
yield from self.try_get_result()
self.distributor.put(x)
def input_queue_is_full(self):
return self.distributor.qsize() >= self.input_buffer_size
def try_get_result(self):
try:
y = self.collector.get(timeout=self.poll_interval)
yield y
except Empty:
pass
def remaining_results(self):
while self.active_workers > 0:
y = self.collector.get()
if y == DONE_WORKER:
self.active_workers -= 1
else:
yield y
def worker(pipeline, distributor, collector, i):
def get():
while True:
x = distributor.get()
if x == STOP_WORKER:
return
yield x
for x in pipeline.apply(get()):
collector.put(x)
collector.put(DONE_WORKER)
STOP_WORKER = b'STOP'
DONE_WORKER = b'DONE'
class IteratorPipeline:
def __init__(self):
self.transformers = []
def add_transform(self, func, *args):
self.transformers.append((func, args))
def apply(self, input_iter):
it = input_iter
for func, args in self.transformers:
it = func(*args, it)
return it | PypiClean |
/fangnao-0.1.0.tar.gz/FangNao-0.1.0/docs/apis/core.rst | npbrain.core package
====================
.. currentmodule:: npbrain.core
.. automodule:: npbrain.core
.. contents::
:local:
:depth: 2
Numerical integration methods
-----------------------------
The most commonly used function is `integrate`:
.. autosummary::
:toctree: _autosummary
integrate
Methods for ordinary differential equations.
.. autosummary::
:toctree: _autosummary
ode_euler
ode_rk2
midpoint
ode_heun
ode_rk3
ode_rk4
ode_rk4_alternative
ode_backward_euler
trapezoidal_rule
ode_exponential_euler
Methods for stochastic differential equations.
.. autosummary::
:toctree: _autosummary
sde_euler
Milstein_dfree_Ito
sde_heun
Milstein_dfree_Stra
sde_exponential_euler
Neurons
-------
.. autosummary::
:toctree: _autosummary
judge_spike
initial_neu_state
format_geometry
format_refractory
generate_fake_neuron
.. autoclass:: Neurons
:members:
Synapses
--------
.. autosummary::
:toctree: _autosummary
format_delay
initial_syn_state
.. autoclass:: Synapses
:members:
Monitors
--------
.. autoclass:: Monitor
:members:
.. autoclass:: SpikeMonitor
:members:
.. autoclass:: StateMonitor
:members:
.. autosummary::
:toctree: _autosummary
raster_plot
firing_rate
Network
-------
.. autoclass:: Network
:members: add, run, run_time
| PypiClean |
/HiCAssembler-1.1.1.tar.gz/HiCAssembler-1.1.1/hicassembler/HiCAssembler.py | import numpy as np
import networkx as nx
import time
import os.path
import copy
import sys
import hicexplorer.HiCMatrix as HiCMatrix
import hicexplorer.hicMergeMatrixBins
import hicexplorer.hicFindTADs as hicFindTADs
from functools import wraps
from hicassembler.Scaffolds import Scaffolds
import logging
log = logging.getLogger("HiCAssembler")
log.setLevel(logging.DEBUG)
POWER_LAW_DECAY = 2**(-1.08) # expected exponential decay at 2*distance
MIN_LENGTH = 400000 # minimum contig or PE_scaffold length to consider
ZSCORE_THRESHOLD = -1 # zscore threshold to declare a boundary a misassembly
MIN_MAD = -0.5 # minimum zscore row contacts to filter low scoring bins
MAX_MAD = 50 # maximum zscore row contacts
def timeit(fn):
@wraps(fn)
def with_profiling(*args, **kwargs):
start_time = time.time()
ret = fn(*args, **kwargs)
elapsed_time = time.time() - start_time
log.info("{} took {}".format(fn.__name__, elapsed_time))
return ret
return with_profiling
class HiCAssembler:
def __init__(self, hic_file_name, fasta_file, out_folder,
min_mad=MIN_MAD, max_mad=MAX_MAD, split_misassemblies=True,
split_positions_file=None,
min_scaffold_length=MIN_LENGTH, matrix_bin_size=25000, use_log=False,
num_processors=5, misassembly_zscore_threshold=ZSCORE_THRESHOLD,
num_iterations=2, scaffolds_to_ignore=None):
"""
Prepares a hic matrix for assembly.
It is expected that initial contigs or scaffolds contain bins
of restriction fragment size.
Parameters
----------
hic_file_name : hic file name or a HiCMatrix object
min_mad : minimum MAD score value per bin
max_mad : maximum MAD score value per bin
Returns
-------
"""
# The list is modified with each iteration replacing its members
# by lists. After two iterations a scaffold
# list could look like: [[0],[1,2,3]]
# which means that there are two scaffolds
# one of those is composed of the contigs 1, 2 and 3
# replace the diagonal from the matrix by zeros
# hic.diagflat(0)
self.fasta_file = fasta_file
self.out_folder = out_folder
self.min_mad = min_mad
self.max_mad = max_mad
self.min_scaffold_length = min_scaffold_length
self.num_processors = num_processors
self.misassembly_threshold = misassembly_zscore_threshold
self.merged_paths = None
self.num_iterations = num_iterations
self.iteration = 0
if not isinstance(hic_file_name, str):
# assume that the hic given is already a HiCMatrix object
# this is normally used for testing
self.hic = hic_file_name
else:
log.info("Loading Hi-C matrix ... ")
# check if a lower resolution matrix is available
self.load_hic_matrix(hic_file_name, split_misassemblies, split_positions_file, matrix_bin_size)
if use_log:
self.hic.matrix.data = np.log1p(self.hic.matrix.data)
# build scaffolds graph. Bins on the same contig are
# put together into a path (a type of graph with max degree = 2)
self.scaffolds_graph = Scaffolds(copy.deepcopy(self.hic), self.out_folder)
if scaffolds_to_ignore is not None:
for scaffold in scaffolds_to_ignore:
log.info("Removing scaffold {} from assembly".format(scaffold))
if scaffold in self.scaffolds_graph.scaffold.node:
self.scaffolds_graph._remove_bin_path(self.scaffolds_graph.scaffold.node[scaffold]['path'],
split_scaffolds=True)
else:
log.warn("Scaffold {} is not part of the assembly".format(scaffold))
self.plot_matrix(self.out_folder + "/before_assembly.pdf",
title="After split mis-assemblies assembly", add_vlines=True)
mat_size = self.hic.matrix.shape[:]
# remove contigs that are too small
self.scaffolds_graph.remove_small_paths(self.min_scaffold_length, split_scaffolds=True)
assert mat_size == self.scaffolds_graph.hic.matrix.shape
self.N50 = []
def load_hic_matrix(self, hic_file_name, split_misassemblies, split_positions_file, matrix_bin_size):
"""
Checks if a already processed matrix is present and loads it. If not
the high resolution matrix is loaded, the misasemblies are
split and the lower resolution matrix is saved.
Parameters
----------
hic_file_name name of a hic file or a HiCMatrix object
split_misassemblies bool If true, the TAD calling algorithm is used to identify misassemblies
split_positions_file file containing manual split positions in bed format
matrix_bin_size bin size of matrix
Returns
-------
"""
merged_bins_matrix_file = self.out_folder + "/hic_merged_bins_matrix.h5"
if os.path.isfile(merged_bins_matrix_file):
log.info("Found reduced matrix file {}".format(merged_bins_matrix_file))
self.hic = HiCMatrix.hiCMatrix(merged_bins_matrix_file)
else:
self.hic = HiCMatrix.hiCMatrix(hic_file_name)
if split_misassemblies:
# try to find contigs that probably should be separated
self.split_misassemblies(hic_file_name, split_positions_file)
log.info("Merging bins of file to reduce resolution")
binsize = self.hic.getBinSize()
if binsize < matrix_bin_size:
# make an smaller matrix having bins of around 25.000 bp
num_bins = matrix_bin_size / binsize
log.info("Reducing matrix size to {:,} bp (number of bins merged: {})".format(binsize, num_bins))
self.hic = HiCAssembler.merge_bins(self.hic, num_bins)
self.hic.save(merged_bins_matrix_file)
self.hic = HiCMatrix.hiCMatrix(merged_bins_matrix_file)
def assemble_contigs(self):
"""
Returns
-------
"""
log.debug("Size of matrix is {}".format(self.scaffolds_graph.hic.matrix.shape[0]))
for iteration in range(self.num_iterations):
self.iteration = iteration
self.scaffolds_graph.iteration = iteration
n50 = self.scaffolds_graph.compute_N50()
self.scaffolds_graph.get_paths_stats()
log.debug("iteration: {}\tN50: {:,}".format(iteration, n50))
self.N50.append(n50)
# the first iteration is is more stringent
if iteration < 3:
target_size = int(min(2e6, self.scaffolds_graph.paths_min * (iteration + 1)))
log.debug("Merging small bins in larger bins of size {} bp".format(target_size))
self.scaffolds_graph.split_and_merge_contigs(num_splits=3,
target_size=target_size,
normalize_method='ice')
stats = self.scaffolds_graph.get_stats_per_split()
try:
# stats[2] contains the mean, median, max, min and len(number of samples)
# for bins whose start position is about the distance of two
# bins or in other words that are separated by one bin
conf_score = stats[2]['median'] * 0.9
# if the scaffolds are all very small, the get_stats_per_split
# many not have enough information to compute, thus a second
# method to identify confidence score is used
except KeyError:
conf_score = np.percentile(self.scaffolds_graph.matrix.data, 5)
log.debug("Confidence score set to {}".format(conf_score))
else:
# self.scaffolds_graph.split_and_merge_contigs(num_splits=1, target_size=int(1e6),
# normalize_method='ice')
self.scaffolds_graph.split_and_merge_contigs(num_splits=1, normalize_method='ice')
conf_score = np.percentile(self.scaffolds_graph.matrix.data, 30)
log.info("Confidence score set to: {}".format(conf_score))
self.scaffolds_graph.join_paths_max_span_tree(conf_score, node_degree_threshold=2e3,
hub_solving_method='remove weakest')
if iteration == 0:
self.scaffolds_graph.remove_small_paths(self.min_scaffold_length, split_scaffolds=True)
self.plot_matrix(self.out_folder + "/after_assembly_{}.pdf".format(iteration),
title="Assembly iteration {}".format(iteration), add_vlines=True)
before_assembly_length, before_num_paths = self.scaffolds_graph.get_assembly_length()
self.put_back_small_scaffolds()
after_assembly_length, after_num_paths = self.scaffolds_graph.get_assembly_length()
diff = after_assembly_length - before_assembly_length
log.info('{:,} bp ({:.2%}) were added back to the assembly'.
format(diff, float(diff) / self.scaffolds_graph.total_length))
log.info('Total assembly length: {:,} bp ({:.2%})'.
format(after_assembly_length, float(after_assembly_length) / self.scaffolds_graph.total_length))
self.plot_matrix(self.out_folder + "/after_put_scaff_back.pdf".
format(iteration), title="After assembly", add_vlines=True)
hic = self.reorder_matrix(max_num_bins=int(1e6), rename_scaffolds=True)
hic.save(self.out_folder + "/final_matrix.h5")
print self.N50
return self.get_contig_order()
def make_scaffold_network(self, orig_scaff, confidence_score=None):
"""
Parameters
----------
orig_scaff
confidence_score minimum value in the matrix
Returns
-------
Examples
--------
>>> import tempfile
>>> dirpath = tempfile.mkdtemp(prefix="hicassembler_test_")
>>> from hicassembler.Scaffolds import get_test_matrix as get_test_matrix
>>> cut_intervals = [('c-0', 0, 10, 1), ('c-0', 10, 30, 2), ('c-1', 0, 10, 1),
... ('c-1', 10, 20, 1), ('c-2', 0, 10, 1), ('c-2', 10, 30, 1)]
>>> hic = get_test_matrix(cut_intervals=cut_intervals)
>>> H = HiCAssembler(hic, "", dirpath, split_misassemblies=False,
... min_scaffold_length=20, use_log=False)
>>> H.scaffolds_graph.split_and_merge_contigs(num_splits=1, normalize_method='none')
>>> H.scaffolds_graph.add_edge(0, 1)
>>> list(H.scaffolds_graph.matrix_bins.get_all_paths())
[[0, 1, 5, 4]]
>>> orig_scaff = Scaffolds(H.hic)
>>> orig_scaff.split_and_merge_contigs(num_splits=1, normalize_method='none')
In orig_scaff only the scaffold paths are represented. It contains all scaffolds
including deleted ones in self.scaffold_graph. No connections between scaffolds
are present
>>> list(orig_scaff.matrix_bins.get_all_paths())
[[0, 1], [2, 3], [4, 5]]
>>> G = H.make_scaffold_network(orig_scaff)
>>> list(G.edges(data=True))
[('c-2', 'c-1', {'weight': 16.0}), ('c-2', 'c-0', {'weight': 42.0}), \
('c-1', 'c-0', {'weight': 28.0})]
>>> import shutil
>>> shutil.rmtree(dirpath)
"""
nxG = nx.Graph()
for node_id, node in orig_scaff.scaffold.node.iteritems():
nn = node.copy()
for attr, value in nn.iteritems():
if isinstance(value, np.int64):
nn[attr] = int(value)
elif isinstance(value, np.float64):
nn[attr] = float(value)
elif isinstance(value, list):
nn[attr] = ", ".join([str(x) for x in value])
elif isinstance(value, np.string_):
nn[attr] = str(value)
if node_id in self.scaffolds_graph.scaffold.node:
nn['is_backbone'] = 1
nxG.add_node(node_id, **nn)
matrix = orig_scaff.matrix.tocoo()
matrix.setdiag(0)
max_weight = float(orig_scaff.matrix.max() * 1.5)
for u, v, weight in zip(matrix.row, matrix.col, matrix.data):
if u == v:
continue
if weight < confidence_score:
continue
scaff_u = orig_scaff.pg_base.node[u]['name']
scaff_v = orig_scaff.pg_base.node[v]['name']
nxG.add_edge(scaff_u, scaff_v, weight=float(weight))
if scaff_u in self.scaffolds_graph.scaffold.node and \
scaff_v in self.scaffolds_graph.scaffold.node and \
scaff_u in self.scaffolds_graph.scaffold.adj[scaff_v]:
# u and v are directly joined
nxG.add_edge(scaff_u, scaff_v, weight=float(max_weight))
# add all contacts between assembled nodes that may not have been
# present in the graph
for path in self.scaffolds_graph.scaffold.get_all_paths():
for scaff_u, scaff_v in zip(path[:-1], path[1:]):
nxG.add_edge(scaff_u, scaff_v, weight=float(max_weight))
return nxG
@staticmethod
def _remove_weakest(G, exclude=[]):
"""
Based on the maximum spanning tree graph hubs are resolved by removing the
weakest links until only two edges are left
For a maximum spanning tree like this:
o---o---o---o---o---o--o
\
--o--o
The algorithm works as follows:
1. Sort the node degree in decreasing order
2. For each node with degree > 0 leave only the two edges with the highest
weight
Parameters
----------
G : maximum spanning tree networkx graph
exclude : list of nodes to exclude from removing links.
Returns
-------
G
"""
node_degree_mst = dict(G.degree(G.node.keys()))
for node, degree in sorted(node_degree_mst.iteritems(), key=lambda (k, v): v, reverse=True):
if degree > 2 and node not in exclude:
adj = sorted(G.adj[node].iteritems(), key=lambda (k, v): v['weight'])
# remove the weakest edges but only if either of the nodes is not a hub
for adj_node, attr in adj[:-2]:
log.debug("Removing weak edge {}-{} weight: {}".format(node, adj_node, attr['weight']))
G.remove_edge(node, adj_node)
if degree <= 2:
break
return G
@staticmethod
def _find_backbone_node(graph):
"""
Given a networkx graph, identifies the node (or nodes that are backgbone) that is labeled as backbone.
This function is called as part of put_back_small_scaffolds
Parameters
----------
graph : networkX graph.
Returns
-------
set of backbone nodes
"""
backbones = set()
for node_id, attr in graph.node.iteritems():
if 'is_backbone' in attr:
backbones.add(node_id)
return backbones
@staticmethod
def _get_subgraph_containing_node(graph, target_node):
"""
Returns the subgraph of `graph` containing the given node
Parameters
----------
graph : NetworkX graph
target_node : node id
Returns
-------
Networkx graph or None if the node is not in the graph
"""
for sub_graph in nx.connected_component_subgraphs(graph):
if target_node in sub_graph:
return sub_graph
return None
@staticmethod
def _get_paths_from_backbone(graph, backbone_node):
"""
Returns all paths that contain the backbone
The graph used should not contain nodes with degree > 2 except for the
backbone node: eg.
o--*--o--o
|
o
but not:
o--o--*--o
|
o
Parameters
----------
graph : Networkx graph
backbone_node: node id
Returns
-------
path list, where each path has the backbone as the first element
Examples
--------
>>> G = nx.Graph()
>>> G.add_edge('backbone', 1, weight=10)
>>> G.add_edge(1, 2, weight=5)
>>> G.add_edge(2, 3, weight=6)
>>> G.add_edge('backbone', 4, weight=5)
>>> G.add_edge(4, 5, weight=10)
>>> HiCAssembler._get_paths_from_backbone(G, 'backbone')
[['backbone', 1, 2, 3], ['backbone', 4, 5]]
"""
# get backbone_id neighbors
path_list = []
seen = set([backbone_node])
for adj, weight in sorted(graph.adj[backbone_node].iteritems(), key=lambda (k, v): v['weight'])[::-1]:
path = [backbone_node]
while True:
path.append(adj)
seen.add(adj)
adj_list = [x for x in graph.adj[adj].keys() if x not in seen]
if len(adj_list) == 0:
break
adj = adj_list[0]
path_list.append(path)
return path_list
def put_back_small_scaffolds(self, normalize_method='ice'):
"""
Identifies scaffolds that were removed from the Hi-C assembly and
tries to find their correct location.
Returns
-------
Examples
--------
>>> from hicassembler.Scaffolds import get_test_matrix as get_test_matrix
>>> cut_intervals = [('c-0', 0, 10, 1), ('c-0', 10, 30, 2), ('c-1', 0, 10, 1),
... ('c-1', 10, 20, 1), ('c-2', 0, 10, 1), ('c-2', 10, 30, 1)]
>>> hic = get_test_matrix(cut_intervals=cut_intervals)
>>> import tempfile
>>> dirpath = tempfile.mkdtemp()
>>> H = HiCAssembler(hic, "", dirpath, split_misassemblies=False, min_scaffold_length=20, use_log=False)
>>> H.scaffolds_graph.split_and_merge_contigs(num_splits=1, normalize_method='none')
>>> H.scaffolds_graph.add_edge(0, 1)
>>> list(H.scaffolds_graph.matrix_bins.get_all_paths())
[[0, 1, 5, 4]]
>>> H.put_back_small_scaffolds()
>>> list(H.scaffolds_graph.matrix_bins.get_all_paths())
[[0, 1, 2, 3, 5, 4]]
>>> import shutil
>>> shutil.rmtree(dirpath)
# larger test
>>> from hicassembler.Scaffolds import get_test_matrix as get_test_matrix
>>> cut_intervals = [('c-0', 0, 20, 1), ('c-0', 20, 40, 2),
... ('c-1', 10, 20, 1), ('c-1', 20, 30, 1),
... ('c-2', 0, 10, 1), ('c-2', 10, 20, 1),
... ('c-3', 0, 10, 1), ('c-3', 10, 20, 1),
... ('c-4', 0, 20, 1), ('c-4', 20, 40, 1)]
>>> from scipy.sparse import csr_matrix
>>> A = csr_matrix(np.array(
... [[50, 19, 9, 8, 5, 3, 2, 1, 0, 0],
... [ 0, 50, 20, 9, 8, 5, 3, 2, 1, 0],
... [ 0, 0, 50, 19, 9, 8, 5, 3, 2, 1],
... [ 0, 0, 0, 50, 19, 9, 8, 5, 3, 2],
... [ 0, 0, 0, 0, 50, 19, 9, 8, 5, 3],
... [ 0, 0, 0, 0, 0, 50, 19, 9, 8, 5],
... [ 0, 0, 0, 0, 0, 0, 50, 19, 9, 8],
... [ 0, 0, 0, 0, 0, 0, 0, 50, 19, 9],
... [ 0, 0, 0, 0, 0, 0, 0, 0, 50, 19],
... [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 50]]))
>>> hic = get_test_matrix(cut_intervals=cut_intervals, matrix=A)
# scramble matrix
# the scrambled order is [c-3 (inv), c-1(inv), c-0, c-4, c-2]
>>> scrambled_bins = [7,6, 3,2, 0,1, 8,9, 5,4]
>>> matrix = hic.matrix[scrambled_bins, :][:, scrambled_bins]
# the intervals are shuffled but not the direction
>>> scrambled_intervals = [6,7, 2,3, 0,1, 8,9, 5,4]
>>> cut_intervals = [cut_intervals[x] for x in scrambled_intervals]
>>> hic.setMatrix(matrix, cut_intervals)
>>> hic.matrix.todense()
matrix([[100, 19, 5, 3, 1, 2, 19, 9, 9, 8],
[ 19, 100, 8, 5, 2, 3, 9, 8, 19, 9],
[ 5, 8, 100, 19, 8, 9, 3, 2, 9, 19],
[ 3, 5, 19, 100, 9, 20, 2, 1, 8, 9],
[ 1, 2, 8, 9, 100, 19, 0, 0, 3, 5],
[ 2, 3, 9, 20, 19, 100, 1, 0, 5, 8],
[ 19, 9, 3, 2, 0, 1, 100, 19, 8, 5],
[ 9, 8, 2, 1, 0, 0, 19, 100, 5, 3],
[ 9, 19, 9, 8, 3, 5, 8, 5, 100, 19],
[ 8, 9, 19, 9, 5, 8, 5, 3, 19, 100]])
>>> dirpath = tempfile.mkdtemp()
>>> H = HiCAssembler(hic, "", dirpath, split_misassemblies=False, min_scaffold_length=20, use_log=False)
>>> H.scaffolds_graph.split_and_merge_contigs(num_splits=1, normalize_method='none')
the shorter scaffolds are removed: c-1, c-2, and c-4.
add edge between remaining scaffolds
>>> H.scaffolds_graph.add_edge(0, 1)
After adding the edge the network looks like
c-0 c-4
o---o
c-1, c-2, c-3 removed
>>> list(H.scaffolds_graph.scaffold.get_all_paths())
[['c-0', 'c-4']]
>>> H.put_back_small_scaffolds(normalize_method='none')
The intermediate maximum spanning tree that is created
looks like:
c-0 c-4
o===o
/ \
c-1 o o c-3
\
o c-2
(==) denotes `backbone` edge, i.e, a edge that was established using the larger scaffolds
In the algorithm, the backbone edges are removed as well as all backbone nodes not attached to a removed
scaffold. After this step, the previous network now looks like:
c-0 c-4
o o
/ \
c-1 o o c-3
\
o c-2
Next, each branch is considered independently (e.g. [c-0, c-1]). The orientation of the scaffolds is
determined pairwise using the find_best_permutation method on the scaffold path. E.g. for c-0 the matrix
nodes path is [4, 5]. Once the orientation is known, the edge of the scaffold backbone is deleted to
allow the insertion of the branch at that position.
>>> list(H.scaffolds_graph.scaffold.get_all_paths())
[['c-0', 'c-1', 'c-2', 'c-3', 'c-4']]
# The resulting matrix should be ordered
>>> hic = H.reorder_matrix()
>>> hic.matrix.todense()
matrix([[100, 19, 9, 8, 5, 3, 2, 1, 0, 0],
[ 19, 100, 20, 9, 8, 5, 3, 2, 1, 0],
[ 9, 20, 100, 19, 9, 8, 5, 3, 2, 1],
[ 8, 9, 19, 100, 19, 9, 8, 5, 3, 2],
[ 5, 8, 9, 19, 100, 19, 9, 8, 5, 3],
[ 3, 5, 8, 9, 19, 100, 19, 9, 8, 5],
[ 2, 3, 5, 8, 9, 19, 100, 19, 9, 8],
[ 1, 2, 3, 5, 8, 9, 19, 100, 19, 9],
[ 0, 1, 2, 3, 5, 8, 9, 19, 100, 19],
[ 0, 0, 1, 2, 3, 5, 8, 9, 19, 100]])
>>> shutil.rmtree(dirpath)
"""
log.info("Total assembly length before adding scaffolds back: {:,}".
format(self.scaffolds_graph.get_assembly_length()[0]))
# create orig_scaff once using a min_scaffold length as size target to
# compute confidence scores
orig_scaff = Scaffolds(self.hic)
orig_scaff.split_and_merge_contigs(num_splits=1, target_size=self.min_scaffold_length, normalize_method=normalize_method)
orig_stats = orig_scaff.get_stats_per_split()
conf_score = orig_stats[1]['median']
# re make orig_scaff a second time without splitting the scaffolds
# as this is the structure needed for rest of the program
orig_scaff = Scaffolds(self.hic)
orig_scaff.split_and_merge_contigs(num_splits=1, normalize_method=normalize_method)
# reset pb_base
self.scaffolds_graph.pg_base = copy.deepcopy(self.scaffolds_graph.matrix_bins)
nxG = self.make_scaffold_network(orig_scaff, confidence_score=conf_score)
nxG = nx.maximum_spanning_tree(nxG, weight='weight')
nx.write_graphml(nxG, self.out_folder + "/mst_for_small_Scaff_integration.graphml".format())
# 1. Identify branches
# delete backbone nodes that are not adjacent to a removed scaffold (removed scaffolds are those
# small contig/scaffolds removed at the beginning that are stored in the self.scaffolds_graph.remove_scaffolds.
# Basically, all so called backbone nodes that are not connected to the scaffolds that we want to put back
# are deleted.
for node_id in self.scaffolds_graph.scaffold.node.keys():
# check that the backbone node is not adjacent to a removed node.
if len(set(nxG.adj[node_id].keys()).intersection(self.scaffolds_graph.removed_scaffolds.node.keys())) == 0:
nxG.remove_node(node_id)
# remove backbone edges. That is, if there is some edge between two backbone nodes, this is removed (see
# example on the docstring).
for u, v in list(nxG.edges()):
if 'is_backbone' in nxG.node[u] and 'is_backbone' in nxG.node[v]:
nxG.remove_edge(u, v)
nx.write_graphml(nxG, "{}/backbone_put_back_scaffolds.graphml".format(self.out_folder))
# now each connected component should only have a backbone node
# and all the connected scaffolds that belong to that node.
for branch in list(nx.connected_component_subgraphs(nxG)):
branch_len = sum([branch.node[x]['length'] for x in branch])
branch_nodes = [x for x in branch]
log.debug("Checking branch for insertion in assembly.\nLength:{}\nScaffolds:{}".
format(branch_len, branch_nodes))
if len(branch) > 20:
log.info("Skipping the insertion of a branch that is too long. "
"The length of the branch is: {} (threshold is 20)".format(len(branch)))
continue
# after removing the hubs the branch may contain several connected components. Only the component
# that contains a backbone node is used.
backbone_list = HiCAssembler._find_backbone_node(branch)
if len(backbone_list) == 0:
if len(branch_nodes) == 1:
continue
# this is a branch without a backbone and is inserted as a separated
# hic-scaffold
branch = HiCAssembler._remove_weakest(branch)
path = Scaffolds._return_paths_from_graph(branch)[0]
for scaff_name in path:
# restore all scaffolds except for path[0] which is the backbone node (and was not removed)
self.scaffolds_graph.restore_scaffold(scaff_name)
# get the matrix bin paths for each scaffold
bins_path = [self.scaffolds_graph.scaffold.node[x]['path'] for x in path]
# a. find the best orientation of the scaffold paths with respect to each other
# the best path contains the bins_path in the best computed orientations
# best_path[0] is the backbone scaffold path
best_path = Scaffolds.find_best_permutation(orig_scaff.hic.matrix, bins_path,
only_expand_but_not_permute=True)
# b. add edges in the path
for path_u, path_v in zip(best_path[:-1], best_path[1:]):
self.scaffolds_graph.add_edge_matrix_bins(path_u[-1], path_v[0])
log.debug("No backbone found for branch with nodes: {}".format(branch.node.keys()))
log.info("Scaffolds without a backbone node were added: {}".format(path))
continue
# each branch should contain at most two backbone node
if len(backbone_list) > 2:
log.info("Branch contains more than one backbone. Backbones in branch: {}".format(backbone_list))
log.info("Skipping this branch of length: {}".format(len(branch)))
continue
# if the branch contains two backbone nodes and is a path
# that means that the path is connecting two different
# hic-scaffolds. The solution is to break the path by the
# weakest link instead of letting the path to join the
# two different hic-scaffolds
elif len(backbone_list) == 2:
# check if the branch forms a path with the backbones at the two ends
path = HiCAssembler._get_paths_from_backbone(branch, list(backbone_list)[0])
if len(path) > 1:
continue
path = path[0]
if backbone_list.intersection([path[0], path[-1]]) != backbone_list:
# the two backbones are not on the sides of the path.
continue
# check if the backbone nodes are adjacent in
# the hic-scaffolds. That means the removed path
# should be inserted between them.
if path[0] in self.scaffolds_graph.scaffold.adj[path[-1]]:
# remove one of the back bones of the graph and continue
log.debug("Removing one backbone scaffold from branch with two backbones")
branch.remove_node(path[-1])
self.insert_path(path[:-1], orig_scaff)
continue
else:
# the backbones belong to different hic-scaffolds
# the path is split by the weakest edge.
min_weight = np.Inf
for u, v, attr in branch.edges(data=True):
if attr['weight'] < min_weight:
min_edge = (u, v)
min_weight = attr['weight']
log.debug("Removing weak edge in path connecting two hic-scaffolds: "
"edge: {}, weight: {}".format(min_edge, min_weight))
idx_u = path.index(min_edge[0])
idx_v = path.index(min_edge[1])
if idx_u > idx_v:
idx_u, idx_v = idx_v, idx_u
assert idx_u + 1 == idx_v
path_a = path[:idx_v]
path_b = path[idx_v:]
if len(path_a) > 0:
self.insert_path(path_a, orig_scaff)
if len(path_b) > 0:
# path b must be inverted such that path[0]
# corresponds to the backbone node
self.insert_path(path_b[::-1], orig_scaff)
continue
else:
backbone_node = list(backbone_list)[0]
# A this point a branch may look like this
# o
# /
# o--*--o--o
# \
# o--o--o
# \
# o
#
# where `*` is the backbone node.
branch = HiCAssembler._remove_weakest(branch, exclude=[backbone_node])
# after removing the weakest edges parts of the graph are no longer connected to the backbone
# thus, the subgraph containing the backbone is selected
branch = HiCAssembler._get_subgraph_containing_node(branch, backbone_node)
if branch is None:
log.debug("Graph is emtpy")
continue
for path in HiCAssembler._get_paths_from_backbone(branch, backbone_node):
self.insert_path(path, orig_scaff)
log.info("Total assembly length after adding scaffolds back: {:,}".format(self.scaffolds_graph.get_assembly_length()[0]))
return
def insert_path(self, path, orig_scaff):
"""
Parameters
----------
path
Returns
-------
"""
# in path, path[0] is always the backbone node.
for scaff_name in path[1:]:
# restore all scaffolds except for path[0] which is the backbone node (and was not removed)
self.scaffolds_graph.restore_scaffold(scaff_name)
# get the matrix bin paths for each scaffold
bins_path = [self.scaffolds_graph.scaffold.node[x]['path'] for x in path]
# a. find the best orientation of the scaffold paths with respect to each other
# the best path contains the bins_path in the best computed orientations
# best_path[0] is the backbone scaffold path
best_path = Scaffolds.find_best_permutation(orig_scaff.hic.matrix, bins_path,
only_expand_but_not_permute=True)
# the backbone bin id that should be joined with the removed scaffold
# corresponds to the the last bin_id in the first best_path, which is the backbone path
backbone_bin = best_path[0][-1]
# identify the neighbor bin of the backbone scaffold in adjacent scaffold (if any).
# To insert the removed scaffolds an edge in the assembled scaffolds has to be removed. This
# edge is the edge containing the backbone_bin.
adjacent_backbone_bin = None
for adj in self.scaffolds_graph.matrix_bins.adj[backbone_bin].keys():
if self.scaffolds_graph.matrix_bins.node[adj]['name'] != self.scaffolds_graph.matrix_bins.node[backbone_bin]['name']:
adjacent_backbone_bin = adj
break
if adjacent_backbone_bin is not None:
# delete edge between backbone and adjacent scaffold
self.scaffolds_graph.delete_edge_from_matrix_bins(backbone_bin, adjacent_backbone_bin)
# add edge between last bin in best path and adjacent scaffold
self.scaffolds_graph.add_edge_matrix_bins(best_path[-1][-1], adjacent_backbone_bin)
# b. add the other edges in the path
for path_u, path_v in zip(best_path[:-1], best_path[1:]):
self.scaffolds_graph.add_edge_matrix_bins(path_u[-1], path_v[0])
integrated_paths = [(x, self.scaffolds_graph.scaffold.node[x]['length']) for x in path[1:]]
log.info("Scaffolds {} successfully integrated into the network".format(integrated_paths))
def split_misassemblies(self, hic_file_name, split_positions_file=None):
"""
Mis assemblies are commonly found in the data. To remove them, we use
a simple metric to identify empty contacts.
Parameters
----------
hic_file_name : Name of the file
Returns
-------
"""
log.info("Detecting misassemblies")
tad_score_file = self.out_folder + "/misassembly_score.txt"
zscore_matrix_file = self.out_folder + "/zscore_matrix.h5"
# check if the computation for the misassembly score was already done
if not os.path.isfile(tad_score_file) or not os.path.isfile(zscore_matrix_file):
ft = hicFindTADs.HicFindTads(hic_file_name, num_processors=self.num_processors, use_zscore=False)
# adjust window sizes to compute misassembly score (aka tad-score)
ft.max_depth = max(800000, ft.binsize * 500)
ft.min_depth = min(200000, ft.binsize * 200)
ft.step = ft.binsize * 50
log.debug("zscore window sizes set by hicassembler: ")
log.debug("max depth:\t{}".format(ft.max_depth))
log.debug("min depth:\t{}".format(ft.min_depth))
log.debug("step:\t{}".format(ft.step))
log.debug("bin size:\t{}".format(ft.binsize))
ft.hic_ma.matrix.data = np.log1p(ft.hic_ma.matrix.data)
ft.hic_ma.matrix = ft.hic_ma.convert_to_obs_exp_matrix(perchr=True)
ft.hic_ma.matrix.data = np.log2(ft.hic_ma.matrix.data)
ft.compute_spectra_matrix(perchr=True)
ft.save_bedgraph_matrix(tad_score_file)
ft.hic_ma.save(zscore_matrix_file)
log.info("Using previously computed scores: {}\t{}".format(tad_score_file, zscore_matrix_file))
# TODO here the hic_file is loaded unnecessarily. A way to remove this step would be good
ft = hicFindTADs.HicFindTads(hic_file_name, num_processors=self.num_processors, use_zscore=False)
ft.hic_ma = HiCMatrix.hiCMatrix(zscore_matrix_file)
ft.load_bedgraph_matrix(tad_score_file)
ft.find_boundaries()
tuple_ = []
# find the tad score and position of boundaries with significant pvalues
for idx, pval in ft.boundaries['pvalues'].iteritems():
tuple_.append((ft.bedgraph_matrix['chrom'][idx],
ft.bedgraph_matrix['chr_start'][idx],
ft.bedgraph_matrix['chr_end'][idx],
np.mean(ft.bedgraph_matrix['matrix'][idx])))
scaffold, start, end, tad_score = zip(*tuple_)
tad_score = np.array(tad_score)
# compute a zscore of the tad_score to select the lowest ranking boundaries.
zscore = (tad_score - np.mean(tad_score)) / np.std(tad_score)
# select as misassemblies all boundaries that have a zscore lower than 1.64 (p-value 0.05)
bin_ids = {}
bins_to_remove = []
log.info("Splitting scaffolds using threshold = {}".format(self.misassembly_threshold))
for idx in np.flatnonzero(zscore < self.misassembly_threshold):
# find the bins that overlap with the misassembly
if scaffold[idx] not in self.hic.interval_trees:
# the scaffold[idx] key may not be present
# in the self.hic because of the reduction of the matrix, which removes some scaffolds
continue
if scaffold[idx] not in bin_ids:
bin_ids[scaffold[idx]] = []
to_split_intervals = sorted(self.hic.interval_trees[scaffold[idx]][start[idx]:end[idx]])
bin_ids[scaffold[idx]].extend(sorted([interval_bin.data for interval_bin in to_split_intervals]))
# split scaffolds based on input file from user
if split_positions_file is not None:
log.debug("loading positions to split from {}".format(split_positions_file))
from hicexplorer import readBed
bed_file_h = readBed.ReadBed(open(split_positions_file, 'r'))
for bed in bed_file_h:
# find the bins that overlap with the misassembly
if bed.chromosome not in self.hic.interval_trees:
log.info("split position {} not found in hic matrix".format(bed))
continue
if bed.chromosome not in bin_ids:
bin_ids[bed.chromosome] = []
to_split_intervals = sorted(self.hic.interval_trees[bed.chromosome][bed.start:bed.end])
if len(to_split_intervals) == 0:
# it could be that there is not bin nearby so the nearest bin is taken
log.info('split position from split list {} does not match any bin. Using nearest bin'.format(bed))
to_split_intervals = [sorted(self.hic.interval_trees[bed.chromosome][0:bed.end])[-1]]
log.info('split position used is {}.'.format(to_split_intervals[0]))
to_split_intervals = sorted([interval_bin.data for interval_bin in to_split_intervals])
if len(to_split_intervals) > 1:
# if the split contains several bins, the region should be removed from the matrix.
# All the bins, except the last one, are marked for deletion. The last one is marked
# for split.
bins_to_remove.extend(to_split_intervals[:-1])
to_split_intervals = [to_split_intervals[-1]]
bin_ids[bed.chromosome].extend(to_split_intervals)
# rename cut intervals
num_removed_misassemblies = 0
new_cut_intervals = self.hic.cut_intervals[:]
for scaff_name in bin_ids:
scaff_bins = self.hic.getChrBinRange(scaff_name)
# remove splits at the start or end of chromosome as they are most likely
# false positives
id_list = set(sorted([x for x in bin_ids[scaff_name] if x not in [scaff_bins[0], scaff_bins[1] - 1]]))
part_number = 1
if len(id_list) > 0:
log.info("Removing {} misassemblies for {} ".format(len(id_list), scaff_name))
for matrix_bin in range(scaff_bins[0], scaff_bins[1]):
name, cut_start, cut_end, extra = new_cut_intervals[matrix_bin]
new_name = "{}/{}".format(name, part_number)
new_cut_intervals[matrix_bin] = (new_name, cut_start, cut_end, extra)
if matrix_bin in id_list:
part_number += 1
num_removed_misassemblies += 1
self.hic.setCutIntervals(new_cut_intervals)
log.info("{} misassemblies were removed".format(num_removed_misassemblies))
if len(bins_to_remove) > 0:
log.info("{} bins will be removed from the matrix because they are contained within the split regions.".
format(len(bins_to_remove)))
self.hic.removeBins(bins_to_remove)
def plot_matrix(self, filename, title='Assembly results',
cmap='RdYlBu_r', log1p=True, add_vlines=False, vmax=None, vmin=None):
"""
Plots the resolved paths on a matrix
Parameters
----------
filename
title
cmap
log1p
add_vlines
vmax
vmin
Returns
-------
None
"""
log.debug("plotting matrix")
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
fig = plt.figure(figsize=(10, 10))
hic = self.reorder_matrix()
axHeat2 = fig.add_subplot(111)
axHeat2.set_title(title)
chrbin_boundaries = hic.chrBinBoundaries
ma = hic.matrix.todense()
norm = None
if log1p:
ma += 1
norm = LogNorm()
img3 = axHeat2.imshow(ma, interpolation='nearest', vmax=vmax, vmin=vmin, cmap=cmap, norm=norm)
img3.set_rasterized(True)
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(axHeat2)
cax = divider.append_axes("right", size="2.5%", pad=0.09)
cbar = fig.colorbar(img3, cax=cax)
cbar.solids.set_edgecolor("face") # to avoid white lines in the color bar in pdf plots
ticks = [pos[0] for pos in chrbin_boundaries.values()]
labels = chrbin_boundaries.keys()
axHeat2.set_xticks(ticks)
if len(labels) < 40:
axHeat2.set_xticklabels(labels, size=3, rotation=90)
else:
axHeat2.set_xticklabels(labels, size=1, rotation=90)
if add_vlines:
# add lines to demarcate 'super scaffolds'
vlines = [x[0] for x in hic.chromosomeBinBoundaries.values()]
axHeat2.vlines(vlines, 1, ma.shape[0], linewidth=0.1)
axHeat2.set_ylim(ma.shape[0], 0)
axHeat2.get_yaxis().set_visible(False)
log.debug("saving matrix {}".format(filename))
plt.savefig(filename, dpi=300)
plt.close()
def remove_noise_from_matrix(self):
"""
set noise level at the value found in up to 70% of the sparse matrix data.
The noise is removed from the hic matrix.
Returns
-------
None
"""
noise_level = np.percentile(self.hic.matrix.data, 70)
log.debug("noise level set to {}".format(noise_level))
self.hic.matrix.data = self.hic.matrix.data - noise_level
self.hic.matrix.data[self.hic.matrix.data < 0] = 0
self.hic.matrix.eliminate_zeros()
def get_contig_order(self, add_split_contig_name=False):
"""
Parameters
----------
add_split_contig_name
Returns
-------
Examples
--------
>>> import tempfile
>>> dirpath = tempfile.mkdtemp(prefix="hicassembler_test_")
>>> from hicassembler.Scaffolds import get_test_matrix as get_test_matrix
>>> cut_intervals = [('c-0', 0, 10, 1), ('c-0', 10, 30, 2), ('c-1', 0, 10, 1),
... ('c-1', 10, 20, 1), ('c-2/1', 0, 10, 1), ('c-2/2', 10, 30, 1)]
>>> hic = get_test_matrix(cut_intervals=cut_intervals)
>>> H = HiCAssembler(hic, "", dirpath, split_misassemblies=False, min_scaffold_length=0)
>>> H.scaffolds_graph.add_edge_matrix_bins(1,3)
>>> H.get_contig_order(add_split_contig_name=False)
[[('c-0', 0, 30, '+'), ('c-1', 0, 20, '-')], [('c-2', 0, 10, '+')], [('c-2', 10, 30, '+')]]
>>> H.get_contig_order(add_split_contig_name=True)
[[('c-0', 0, 30, '+'), ('c-1', 0, 20, '-')], [('c-2/1', 0, 10, '+')], [('c-2/2', 10, 30, '+')]]
>>> import shutil
>>> shutil.rmtree(dirpath)
"""
import re
super_scaffolds = []
for path in self.scaffolds_graph.scaffold.get_all_paths():
scaffold = []
for scaff_name in path:
scaff_data = self.scaffolds_graph.scaffold.node[scaff_name]
if add_split_contig_name is False:
# check if node name has an indication that it was split (by ending in '/n')
res = re.search("(.*?)/(\d+)$", scaff_name)
if res is not None:
scaff_name = res.group(1)
scaffold.append((scaff_name, scaff_data['start'],
scaff_data['end'], scaff_data['direction']))
super_scaffolds.append(scaffold)
# sanity check
def get_start_end_direction(_scaff_name, _bin_list, _start_list, _end_list):
# check that the path in the scaffold is the same the bin_list
assert self.scaffolds_graph.scaffold.node[_scaff_name]['path'] == _bin_list
# check direction of scaffold. If the bin id's are decreasing
# then the direction is "-"
_scaff_start = _scaff_end = _direction = None
if len(_bin_list) == 1:
_direction = "+"
_scaff_start = _start_list[0]
_scaff_end = _end_list[0]
elif all(y - x == -1 for x, y in zip(_bin_list, _bin_list[1:])):
_direction = "-"
_scaff_start = min(_start_list)
_scaff_end = max(_end_list)
assert _scaff_start == _start_list[-1]
assert _scaff_end == _end_list[0]
elif all(y - x == 1 for x, y in zip(_bin_list, _bin_list[1:])):
_direction = "+"
_scaff_start = min(_start_list)
_scaff_end = max(_end_list)
assert _scaff_start == _start_list[0]
assert _scaff_end == _end_list[-1]
else:
# in this case the bins are not continuous. How did that happen?
sys.stderr.write('Bins are not continuous. How did that happened?')
return _scaff_start, _scaff_end, _direction
scaff_order = {}
gaps = {}
for idx, matrix_bin_path in enumerate(self.scaffolds_graph.matrix_bins.get_all_paths()):
scaff_order[idx] = []
prev_scaff_name = None
gaps[idx] = []
start_list = []
end_list = []
bin_list = []
# matrix_bin path is as list, containing all the bins that form a path
# those bins are part of scaffolds
for bin_id in matrix_bin_path:
# get the scaffold name
scaff_name, start, end, extra = self.hic.getBinPos(bin_id)
bin_data = self.scaffolds_graph.matrix_bins.node[bin_id]
assert bin_data['name'] == scaff_name
assert bin_data['start'] == start
assert bin_data['end'] == end
if scaff_name != prev_scaff_name and prev_scaff_name is not None:
scaff_start, scaff_end, direction = get_start_end_direction(prev_scaff_name,
bin_list, start_list, end_list)
scaff_order[idx].append((prev_scaff_name, scaff_start, scaff_end, direction))
start_list = []
end_list = []
bin_list = []
start_list.append(start)
end_list.append(end)
bin_list.append(bin_id)
prev_scaff_name = scaff_name
scaff_start, scaff_end, direction = get_start_end_direction(scaff_name, bin_list, start_list, end_list)
scaff_order[idx].append((scaff_name, scaff_start, scaff_end, direction))
# scaffolds that were removed and could not be put back need to be returned as well
for scaff in self.scaffolds_graph.removed_scaffolds.node.values():
idx += 1
scaff_order[idx] = [(scaff['name'], scaff['start'], scaff['end'], '+')]
if add_split_contig_name is False:
scaff_order_renamed = {}
for idx, scaff_path in scaff_order.iteritems():
scaff_order_renamed[idx] = []
for scaff_name, scaff_start, scaff_end, scaff_direction in scaff_path:
# check if node name has an indication that it was split (by ending in '/n')
res = re.search("(.*?)/(\d+)$", scaff_name)
if res is not None:
scaff_name = res.group(1)
scaff_order_renamed[idx].append((scaff_name, scaff_start, scaff_end, scaff_direction))
scaff_order = scaff_order_renamed
# brute force comparison
not_found_list = {}
for idx, hic_scaff_order in scaff_order.iteritems():
not_found_list[idx] = []
for super_scaff in super_scaffolds:
match = False
if hic_scaff_order == super_scaff:
match = True
break
if match is False:
not_found_list[idx].append(hic_scaff_order)
log.debug(not_found_list)
return scaff_order.values()
def reorder_matrix(self, max_num_bins=4000, rename_scaffolds=False):
"""
Reorders the matrix using the assembled paths
max_num_bins: since reorder is used mostly for plotting, it is required that the matrices are not too large
thus, a maximum number of bins can be set.
rename_scaffolds: Set to true if the original scaffold names that are already merged should be renamed as
hic_scaffold_{n} where n is a counter
Returns
-------
"""
import re
def sorted_nicely(list_to_order):
""" Sort the given iterable in the way that humans expect."""
convert = lambda text: int(text) if text.isdigit() else text
alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)]
return sorted(list_to_order, key=alphanum_key)
log.debug("reordering matrix")
hic = copy.deepcopy(self.scaffolds_graph.hic)
order_list = []
from collections import OrderedDict
scaff_boundaries = OrderedDict()
start_bin = 0
end_bin = 0
num_bins_to_merge = hic.matrix.shape[0] / max_num_bins
# reduce the density of the matrix if this one is too big
if hic.matrix.shape[0] > max_num_bins and num_bins_to_merge > 1:
# compute number of bins required to reduce resolution to desired
# goal
num_bins_to_merge = hic.matrix.shape[0] / max_num_bins
log.debug("Matrix size is too large for printing. Reducing the matrix by merging {} bins".
format(num_bins_to_merge))
hic, map_old_to_merged = HiCAssembler.merge_bins(hic, num_bins_to_merge, skip_small=False,
return_bin_id_mapping=True)
else:
map_old_to_merged = None
# check if scaffolds are already merged, and if not
# sort the names alphanumerically.
if self.scaffolds_graph.scaffold.path == {}:
scaffold_order = sorted_nicely(list([x for x in self.scaffolds_graph.scaffold]))
# after merging, small scaffolds will be removed from the matrix. They need
# to be removed from scaffold_order before reordering the chromosomes to avoid an error
scaffold_order = [x for x in scaffold_order if x in hic.chrBinBoundaries.keys()]
hic.reorderChromosomes(scaffold_order)
hic.chromosomeBinBoundaries = hic.chrBinBoundaries
else:
path_list_test = {}
for idx, scaff_path in enumerate(self.scaffolds_graph.scaffold.get_all_paths()):
# scaff_path looks like:
# ['scaffold_12970/3', 'scaffold_12472/3', 'scaffold_12932/3', 'scaffold_12726/3', 'scaffold_12726/1']
path_list_test[idx] = []
for scaffold_name in scaff_path:
bin_path = self.scaffolds_graph.scaffold.node[scaffold_name]['path']
if map_old_to_merged is not None:
new_bin_path = []
seen = set()
for bin_id in bin_path:
map_old_to_merged[bin_id]
if map_old_to_merged[bin_id] not in seen:
new_bin_path.append(map_old_to_merged[bin_id])
seen.add(map_old_to_merged[bin_id])
else:
new_bin_path = bin_path
order_list.extend(new_bin_path)
path_list_test[idx].extend(new_bin_path)
end_bin += len(new_bin_path)
# assert path_list_test[idx] == self.scaffolds_graph.matrix_bins[path_list_test[idx][0]]
scaff_boundaries["scaff_{}".format(idx)] = (start_bin, end_bin)
start_bin = end_bin
hic.reorderBins(order_list)
hic.chromosomeBinBoundaries = scaff_boundaries
if rename_scaffolds is True:
new_intervals = []
start_list = []
for idx, scaff_id in enumerate(hic.chromosomeBinBoundaries):
start_bin, end_bin = hic.chromosomeBinBoundaries[scaff_id]
start = 0
for interval in hic.cut_intervals[start_bin:end_bin]:
scaff_name, int_start, int_end, cov = interval
end = start + (int_end - int_start)
new_intervals.append(("hic_scaffold_{}".format(idx + 1), start, end, cov))
start_list.append((start, end, int_start, int_end, int_end - int_start))
start = end
hic.setCutIntervals(new_intervals)
return hic
@staticmethod
def merge_bins(hic, num_bins, skip_small=True, return_bin_id_mapping=False):
"""
Merge the bins using the specified number of bins. This
functions takes care to make new intervals
Parameters
----------
hic : HiCMatrix object
num_bins : number of consecutive bins to merge.
Returns
-------
A sparse matrix.
Set up a Hi-C test matrix
>>> from scipy.sparse import csr_matrix
>>> row, col = np.triu_indices(5)
>>> cut_intervals = [('a', 0, 10, 0.5), ('a', 10, 20, 1),
... ('a', 20, 30, 1), ('a', 30, 40, 0.1), ('b', 40, 50, 1)]
>>> hic = HiCMatrix.hiCMatrix()
>>> hic.nan_bins = []
>>> matrix = np.array([
... [ 50, 10, 5, 3, 0],
... [ 0, 60, 15, 5, 1],
... [ 0, 0, 80, 7, 3],
... [ 0, 0, 0, 90, 1],
... [ 0, 0, 0, 0, 100]], dtype=np.int32)
make the matrix symmetric:
>>> from scipy.sparse import dia_matrix
>>> dia = dia_matrix(([matrix.diagonal()], [0]), shape=matrix.shape)
>>> hic.matrix = csr_matrix(matrix + matrix.T - dia)
>>> hic.setMatrix(hic.matrix, cut_intervals)
run merge_matrix
>>> merge_matrix, map_id = HiCAssembler.merge_bins(hic, 2, return_bin_id_mapping=True)
>>> merge_matrix.cut_intervals
[('a', 0, 20, 0.75), ('a', 20, 40, 0.55000000000000004), ('b', 40, 50, 1.0)]
>>> merge_matrix.matrix.todense()
matrix([[120, 28, 1],
[ 28, 177, 4],
[ 1, 4, 100]], dtype=int32)
>>> map_id
{0: 0, 1: 0, 2: 1, 3: 1, 4: 2}
"""
hic = hicexplorer.hicMergeMatrixBins.remove_nans_if_needed(hic)
# get the bins to merge
ref_name_list, start_list, end_list, coverage_list = zip(*hic.cut_intervals)
new_bins = []
bins_to_merge = []
prev_ref = ref_name_list[0]
# prepare new intervals
idx_start = 0
new_start = start_list[0]
count = 0
merge_bin_id = 0
mapping_old_to_merged_bin_ids = {}
for idx, ref in enumerate(ref_name_list):
if (count > 0 and count % num_bins == 0) or ref != prev_ref:
if skip_small is True and count < num_bins / 2:
sys.stderr.write("{} has few bins ({}). Skipping it\n".format(prev_ref, count))
else:
coverage = np.mean(coverage_list[idx_start:idx])
new_end = end_list[idx - 1]
if new_start > new_end:
sys.stderr.write("end of new merged bin is smaller than start")
new_bins.append((ref_name_list[idx_start], new_start, end_list[idx - 1], coverage))
bins_to_merge.append(list(range(idx_start, idx)))
for old_bin_id in list(range(idx_start, idx)):
mapping_old_to_merged_bin_ids[old_bin_id] = merge_bin_id
merge_bin_id += 1
idx_start = idx
new_start = start_list[idx]
count = 0
prev_ref = ref
count += 1
if skip_small is True and count < num_bins / 2:
sys.stderr.write("{} has few bins ({}). Skipping it\n".format(prev_ref, count))
else:
coverage = np.mean(coverage_list[idx_start:])
new_end = end_list[idx - 1]
if new_start > new_end:
sys.stderr.write("end of new merged bin is smaller than start")
new_bins.append((ref, new_start, end_list[idx], coverage))
bins_to_merge.append(list(range(idx_start, idx + 1)))
for old_bin_id in list(range(idx_start, idx + 1)):
mapping_old_to_merged_bin_ids[old_bin_id] = merge_bin_id
merge_bin_id += 1
hic.matrix = hicexplorer.hicMergeMatrixBins.reduce_matrix(hic.matrix, bins_to_merge, diagonal=True)
hic.matrix.eliminate_zeros()
hic.setCutIntervals(new_bins)
hic.nan_bins = np.flatnonzero(hic.matrix.sum(0).A == 0)
if return_bin_id_mapping is True:
return hic, mapping_old_to_merged_bin_ids
else:
return hic
class HiCAssemblerException(Exception):
"""Base class for exceptions in HiCAssembler.""" | PypiClean |
/Django_Verify_Email-2.0.3-py3-none-any.whl/verify_email/app_configurations.py | from django.conf import settings
class GetFieldFromSettings:
"""
This class fetches the attributes that are defined in settings.py of your project by user OR Django itself.
self.default_configs : is a dict with keys as the names used in this app and values being a tuple of
attributes defined in settings.py and their corresponding default values if not found.
There is a special case in "get" method, if you set "VERIFICATION_SUCCESS_TEMPLATE" as None is settings.py, it
will skip the intermediate page where success information is displayed. (This is better explained in docs.)
The "get" method takes the name of the attributes as input, checks for it in settings.py,
if found:
returns the corresponding value.
else:
returns the default value from "self.defaults_configs".
"""
def __init__(self):
self.defaults_configs = {
'debug_settings': (
'DEBUG',
False
),
'subject': (
"SUBJECT",
"Email Verification Mail"
),
'email_field_name': (
"EMAIL_FIELD_NAME",
"email",
),
'html_message_template': (
"HTML_MESSAGE_TEMPLATE",
'verify_email/email_verification_msg.html'
),
'from_alias': (
"DEFAULT_FROM_EMAIL",
'noreply<[email protected]>',
),
'login_page': (
'LOGIN_URL',
'accounts_login'
),
'verification_success_template': (
'VERIFICATION_SUCCESS_TEMPLATE',
'verify_email/email_verification_successful.html'
),
'verification_success_msg': (
'VERIFICATION_SUCCESS_MSG',
"Your Email is verified successfully and account has been activated. "
"You can login with the credentials now..."
),
'verification_failed_template': (
'VERIFICATION_FAILED_TEMPLATE',
'verify_email/email_verification_failed.html'
),
'link_expired_template': (
'LINK_EXPIRED_TEMPLATE',
'verify_email/link_expired.html'
),
'verification_failed_msg': (
'VERIFICATION_FAILED_MSG',
"There is something wrong with this link, can't verify the user..."
),
'request_new_email_template': (
'REQUEST_NEW_EMAIL_TEMPLATE',
'verify_email/request_new_email.html'
),
'new_email_sent_template': (
'NEW_EMAIL_SENT_TEMPLATE',
'verify_email/new_email_sent.html'
),
'salt': (
'HASH_SALT',
None
),
'sep': (
'SEPARATOR',
':'
),
'key': (
'HASHING_KEY',
None
),
'max_age': (
'EXPIRE_AFTER',
None
),
'max_retries': (
'MAX_RETRIES',
2
)
}
def get(self, field_name, raise_exception=True, default_type=str):
attr = getattr(
settings,
self.defaults_configs[field_name][0], # get field from settings
self.defaults_configs[field_name][1] # get default value if field not defined
)
if (attr == '' or attr is None or not isinstance(field_name, default_type)) and raise_exception:
if field_name == 'verification_success_template' and attr is None:
return None
raise AttributeError
return attr | PypiClean |
/AdjectorClient-1.0b1.tar.gz/AdjectorClient-1.0b1/adjector/model/entities.py | import logging
from datetime import datetime
from elixir import using_options, using_table_options, BLOB, Boolean, ColumnProperty, \
DateTime, Entity, EntityMeta, Field, Float, Integer, ManyToMany, ManyToOne, \
OneToMany, OneToOne, SmallInteger, String, UnicodeText
from genshi import Markup
from sqlalchemy import func, UniqueConstraint
from adjector.core.conf import conf
from adjector.core.tracking import add_tracking, remove_tracking
log = logging.getLogger(__name__)
max_int = 2147483647
tz_now = lambda : datetime.now(conf.timezone)
UnicodeText = UnicodeText(assert_unicode=False)
class CircularDependencyException(Exception):
pass
class GenericEntity(object):
def __init__(self, data):
self._updated = self.set(data)
def set(self, data):
for field in data.keys():
if hasattr(self, field):
if field == 'title':
data[field] = data[field][:80]
self.__setattr__(field, data[field])
else:
log.warning('No field: %s' % field)
def value(self):
return self.__dict__
class GenericListEntity(GenericEntity):
def set(self, data):
GenericEntity.set(self, data)
# Detect cycles in parenting - Brent's algorithm http://www.siafoo.net/algorithm/11
turtle = self
rabbit = self
steps_taken = 0
step_limit = 2
while True:
if not rabbit.parent_id:
break #no loop
rabbit = rabbit.query.get(rabbit.parent_id)
steps_taken += 1
if rabbit == turtle:
# loop!
raise CircularDependencyException
if steps_taken == step_limit:
steps_taken = 0
step_limit *=2
turtle = rabbit
class CJIgnoredLink(Entity):
cj_advertiser_id = Field(Integer, required=True)
cj_link_id = Field(Integer, required=True)
using_options(tablename=conf.table_prefix + 'cj_ignored_links')
using_table_options(UniqueConstraint('cj_link_id'))
def __init__(self, link_id, advertiser_id):
self.cj_advertiser_id = advertiser_id
self.cj_link_id = link_id
class Click(Entity):
time = Field(DateTime(timezone=True), required=True, default=tz_now)
creative = ManyToOne('Creative', ondelete='set null')
zone = ManyToOne('Zone', ondelete='set null')
using_options(tablename=conf.table_prefix + 'clicks')
def __init__(self, creative_id, zone_id):
self.creative_id = creative_id
self.zone_id = zone_id
class Creative(GenericEntity, Entity):
parent = ManyToOne('Set', required=False, ondelete='set null')
#zones = ManyToMany('Zone', tablename='creatives_to_zones')
creative_zone_pairs = OneToMany('CreativeZonePair', cascade='delete')
title = Field(String(80, convert_unicode=True), required=True)
html = Field(UnicodeText, required=True, default='')
is_text = Field(Boolean, required=True, default=False)
width = Field(Integer, required=True, default=0)
height = Field(Integer, required=True, default=0)
start_date = Field(DateTime(timezone=True))
end_date = Field(DateTime(timezone=True))
weight = Field(Float, required=True, default=1.0)
add_tracking = Field(Boolean, required=True, default=True)
disabled = Field(Boolean, required=True, default=False)
create_date = Field(DateTime(timezone=True), required=True, default=tz_now)
cj_link_id = Field(Integer)
cj_advertiser_id = Field(Integer)
cj_site_id = Field(Integer)
views = OneToMany('View')
clicks = OneToMany('Click')
# Cached Values
html_tracked = Field(UnicodeText) #will be overwritten on set
parent_weight = Field(Float, required=True, default=1.0) # overwritten on any parent weight change
using_options(tablename=conf.table_prefix + 'creatives', order_by='title')
using_table_options(UniqueConstraint('cj_link_id'))
def __init__(self, data):
GenericEntity.__init__(self, data)
if self.parent_id:
self.parent_weight = Set.get(self.parent_id).weight
def get_clicks(self, start=None, end=None):
query = Click.query.filter_by(creative_id = self.id)
if start:
query = query.filter(Click.time > start)
if end:
query = query.filter(Click.time < end)
return query.count()
def get_views(self, start=None, end=None):
query = View.query.filter_by(creative_id = self.id)
if start:
query = query.filter(View.time > start)
if end:
query = query.filter(View.time < end)
return query.count()
@staticmethod
def possible_parents(this=None):
return [[set.id, set.title] for set in Set.query()]
def set(self, data):
old_parent_id = self.parent_id
old_html = self.html
old_add_tracking = self.add_tracking
GenericEntity.set(self, data)
if self.parent_id != old_parent_id:
self.parent_weight = Set.get(self.parent_id).weight
# TODO: Handle Block / Text bullshit
# Parse html
if self.html != old_html or self.add_tracking != old_add_tracking:
if self.add_tracking is not False:
self.html_tracked = add_tracking(self.html)
else:
self.html_tracked = None
return [self]
def value(self):
value = GenericEntity.value(self)
value['preview'] = Markup(remove_tracking(self.html, self.cj_site_id))
value['total_weight'] = self.weight * self.parent_weight
value['html_tracked'] = value['html_tracked'] or value['html']
return value
def view(self):
return '%s/creative/%i' % (conf.admin_base_url, self.id)
class CreativeZonePair(GenericEntity, Entity):
creative = ManyToOne('Creative', ondelete='cascade', use_alter=True)
zone = ManyToOne('Zone', ondelete='cascade', use_alter=True)
is_text = Field(Boolean, required=True)
lower_bound = Field(Float, required=True)
upper_bound = Field(Float, required=True)
using_options(tablename=conf.table_prefix + 'creative_zone_pairs')
using_table_options(UniqueConstraint('creative_id', 'zone_id'))
class Location(GenericListEntity, Entity):
''' A container for locations or zones '''
parent = ManyToOne('Location', required=False, ondelete='set null')
sublocations = OneToMany('Location')
zones = OneToMany('Zone')
title = Field(String(80, convert_unicode=True), required=True)
description = Field(UnicodeText)
create_date = Field(DateTime(timezone=True), required=True, default=tz_now)
cj_site_id = Field(Integer)
parent_cj_site_id = Field(Integer)
using_options(tablename=conf.table_prefix + 'locations', order_by='title')
def __init__(self, data):
GenericEntity.__init__(self, data)
if self.parent_id:
self.parent_cj_site_id = Location.get(self.parent_id).cj_site_id
def delete(self, data):
updated = []
for subloc in self.sublocations:
updated.extend(subloc.set(dict(parent_cj_site_id = None)))
for zone in self.zones:
updated.extend(zone.set(dict(parent_cj_site_id = None)))
Entity.delete(self)
return updated
@staticmethod
def possible_parents(this = None):
filter = None
if this:
filter = Location.id != this.id
return [[location.id, location.title] for location in Location.query.filter(filter)]
def set(self, data):
updated = [self]
old_parent_id = self.parent_id
old_cj_site_id = self.cj_site_id
old_parent_cj_site_id = self.parent_cj_site_id
GenericEntity.set(self, data)
if self.parent_id != old_parent_id:
self.parent_cj_site_id = Location.get(self.parent_id).cj_site_id
if self.cj_site_id != old_cj_site_id or self.parent_cj_site_id != old_parent_cj_site_id:
# Only pass parent- down if we don't have our own
for subloc in self.sublocations:
updated.extend(subloc.set(dict(parent_cj_site_id = self.cj_site_id or self.parent_cj_site_id)))
for zone in self.zones:
updated.extend(zone.set(dict(parent_cj_site_id = self.cj_site_id or self.parent_cj_site_id)))
return updated
def view(self):
return '%s/location/%i' % (conf.admin_base_url, self.id)
class Set(GenericListEntity, Entity):
parent = ManyToOne('Set', required=False, ondelete='set null')
subsets = OneToMany('Set')
creatives = OneToMany('Creative')
title = Field(String(80, convert_unicode=True), required=True)
description = Field(UnicodeText)
weight = Field(Float, required=True, default=1.0)
parent_weight = Field(Float, required=True, default=1.0) # overwritten on any parent weight change
create_date = Field(DateTime(timezone=True), required=True, default=tz_now)
cj_advertiser_id = Field(Integer)
using_options(tablename=conf.table_prefix + 'sets', order_by='title')
using_table_options(UniqueConstraint('cj_advertiser_id'))
def __init__(self, data):
GenericEntity.__init__(self, data)
if self.parent_id:
self.parent_weight = Set.get(self.parent_id).weight
def delete(self, data):
updated = []
for subset in self.subsets:
updated.extend(subset.set(dict(parent_weight = 1.0)))
for creative in self.creatives:
updated.extend(creative.set(dict(parent_weight = 1.0)))
Entity.delete(self)
return updated
@staticmethod
def possible_parents(this = None):
filter = None
if this:
filter = Set.id != this.id
return [[set.id, set.title] for set in Set.query.filter(filter)]
def set(self, data):
updated = [self]
old_parent_id = self.parent_id
old_weight = self.weight
old_parent_weight = self.parent_weight
GenericEntity.set(self, data)
if self.parent_id != old_parent_id:
self.parent_weight = Set.get(self.parent_id).weight
if self.weight != old_weight or self.parent_weight != old_parent_weight:
for subset in self.subsets:
updated.extend(subset.set(dict(parent_weight = self.parent_weight * self.weight)))
for creative in self.creatives:
updated.extend(creative.set(dict(parent_weight = self.parent_weight * self.weight)))
return updated
def value(self):
value = GenericEntity.value(self)
value['total_weight'] = self.weight * self.parent_weight
return value
def view(self):
return '%s/set/%i' % (conf.admin_base_url, self.id)
class View(GenericEntity, Entity):
time = Field(DateTime(timezone=True), required=True, default=tz_now)
creative = ManyToOne('Creative', ondelete='set null')
zone = ManyToOne('Zone', ondelete='set null')
using_options(tablename=conf.table_prefix + 'views')
def __init__(self, creative_id, zone_id):
self.creative_id = creative_id
self.zone_id = zone_id
class Zone(GenericEntity, Entity):
parent = ManyToOne('Location', required=False, ondelete='set null')
creative_zone_pairs = OneToMany('CreativeZonePair', cascade='delete')
name = Field(String(80, convert_unicode=True), required=False)
title = Field(String(80, convert_unicode=True), required=True)
description = Field(UnicodeText)
#creatives = ManyToMany('Creative', tablename='creatives_to_zones')
normalize_by_container = Field(Boolean, required=True, default=False)
creative_types = Field(SmallInteger, required=True, default=0) #0: Both, 1: Text, 2: Blocks
# These only matter if blocks allowed
min_width = Field(Integer, required=True, default=0)
max_width = Field(Integer, required=True, default=max_int)
min_height = Field(Integer, required=True, default=0)
max_height = Field(Integer, required=True, default=max_int)
# These only matter if text allowed
num_texts = Field(SmallInteger, required=True, default=1)
weight_texts = Field(Float, required=True, default=1.0)
before_all_text = Field(UnicodeText)
after_all_text = Field(UnicodeText)
before_each_text = Field(UnicodeText)
after_each_text = Field(UnicodeText)
create_date = Field(DateTime(timezone=True), required=True, default=tz_now)
# Cached from parent
parent_cj_site_id = Field(Integer)
# Cached from creatives
total_text_weight = Field(Float) # i dunno, some default? should be updated quick.
views = OneToMany('View')
clicks = OneToMany('Click')
using_options(tablename=conf.table_prefix + 'zones', order_by='title')
def __init__(self, data):
GenericEntity.__init__(self, data)
if self.parent_id:
self.parent_cj_site_id = Location.get(self.parent_id).cj_site_id
def get_clicks(self, start=None, end=None):
query = Click.query.filter_by(zone_id = self.id)
if start:
query = query.filter(Click.time > start)
if end:
query = query.filter(Click.time < end)
return query.count()
def get_views(self, start=None, end=None):
query = View.query.filter_by(zone_id = self.id)
if start:
query = query.filter(View.time > start)
if end:
query = query.filter(View.time < end)
return query.count()
@staticmethod
def possible_parents(this=None):
return [[location.id, location.title] for location in Location.query()]
def set(self, data):
if data.has_key('previous_name'):
del data['previous_name']
old_parent_id = self.parent_id
GenericEntity.set(self, data)
if self.parent_id != old_parent_id:
self.parent_cj_site_id = Location.get(self.parent_id).cj_site_id
return [self]
def value(self):
val = self.__dict__.copy()
val['previous_name'] = self.name
return val
def view(self):
return '%s/zone/%i' % (conf.admin_base_url, self.id) | PypiClean |
/NeodroidVision-0.3.0-py36-none-any.whl/neodroidvision/data/detection/coco/coco_evaluation.py |
__author__ = "Christian Heider Nielsen"
__doc__ = r"""
Created on 22/03/2020
"""
import copy
import json
import logging
from collections import defaultdict, namedtuple
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, Dict, List, Sequence, Tuple
import numpy
import pycocotools.mask
import torch
import torch._six
import torchvision
from pycocotools.coco import COCO # Version 2.0 REQUIRES numpy 1.17
from pycocotools.cocoeval import COCOeval
from warg import IncompatiblePackageVersions
if pycocotools.coco.__version__ == "2.0" and "1.18" in numpy.__version__:
print("Hint: downgrade numpy to 1.17.x")
raise IncompatiblePackageVersions(
numpy, "pycocotools", pycocotools=pycocotools.coco.__version__
)
from draugr.torch_utilities import minmax_to_xywh_torch
from neodroidvision.utilities.torch_utilities.distributing.distributing_utilities import (
all_gather_cuda,
)
__all__ = [
"CocoEvaluator",
"merge",
"create_common_coco_eval",
"create_index",
"load_results",
"coco_evaluation",
"get_iou_types",
]
BboxPredTuple = namedtuple("BboxPredTuple", ("boxes", "scores", "labels"))
SegmPredTuple = namedtuple("SegmPredTuple", ("masks", "scores", "labels"))
KeypointsPredTuple = namedtuple("KeypointsPredTuple", ("keypoints", "scores", "labels"))
class IouType(Enum):
BoundingBox = "bbox"
Segmentation = "segm"
Keypoints = "keypoints"
class CocoEvaluator(object):
"""description"""
def __init__(self, coco_api: COCO, iou_types: Sequence[IouType]):
assert isinstance(iou_types, (list, tuple))
self.coco_api = copy.deepcopy(coco_api)
self.iou_types = iou_types
self.coco_eval = {}
for iou_type in iou_types:
assert iou_type in IouType
self.coco_eval[iou_type] = COCOeval(self.coco_api, iouType=iou_type.value)
self.img_ids = []
self.eval_imgs = {k: [] for k in iou_types}
def update(self, predictions: Dict) -> None:
"""
:param predictions:
:type predictions:"""
img_ids = list(numpy.unique(list(predictions.keys())))
self.img_ids.extend(img_ids)
for iou_type in self.iou_types:
results = self.prepare_data(predictions, iou_type)
coco_dt = load_results(self.coco_api, results) if results else COCO()
coco_eval = self.coco_eval[iou_type]
coco_eval.cocoDt = coco_dt
coco_eval.params.imgIds = list(img_ids)
img_ids, eval_imgs = evaluate(coco_eval)
self.eval_imgs[iou_type].append(eval_imgs)
def synchronize_between_processes(self):
"""description"""
for iou_type in self.iou_types:
self.eval_imgs[iou_type] = numpy.concatenate(self.eval_imgs[iou_type], 2)
create_common_coco_eval(
self.coco_eval[iou_type], self.img_ids, self.eval_imgs[iou_type]
)
def accumulate(self):
"""description"""
for coco_eval in self.coco_eval.values():
coco_eval.accumulate()
def summarize(self):
"""description"""
for iou_type, coco_eval in self.coco_eval.items():
print(f"IoU metric: {iou_type}")
coco_eval.summarize()
def prepare_data(
self, predictions: Sequence, iou_type: IouType
) -> List[Dict[str, Any]]:
"""
:param predictions:
:type predictions:
:param iou_type:
:type iou_type:
:return:
:rtype:"""
if iou_type == iou_type.BoundingBox:
return self.prepare_for_coco_detection(predictions)
elif iou_type == iou_type.Segmentation:
return self.prepare_for_coco_segmentation(predictions)
elif iou_type == iou_type.Keypoints:
return self.prepare_for_coco_keypoint(predictions)
else:
raise ValueError(f"Unknown iou type {iou_type}")
def prepare_for_coco_detection(self, predictions: Sequence[BboxPredTuple]):
"""
:param predictions:
:type predictions:
:return:
:rtype:"""
coco_results = []
for original_id, prediction in predictions.items():
if len(prediction) == 0:
continue
boxes = prediction["boxes"]
boxes = minmax_to_xywh_torch(boxes).tolist()
scores = prediction["scores"].tolist()
labels = prediction["labels"].tolist()
coco_results.extend(
[
{
"image_id": original_id,
"category_id": labels[k],
"bbox": box,
"score": scores[k],
}
for k, box in enumerate(boxes)
]
)
return coco_results
def prepare_for_coco_segmentation(self, predictions: Sequence[SegmPredTuple]):
"""
:param predictions:
:type predictions:
:return:
:rtype:"""
coco_results = []
for original_id, prediction in predictions.items():
if len(prediction) == 0:
continue
scores = prediction["scores"]
labels = prediction["labels"]
masks = prediction["masks"]
masks = masks > 0.5
scores = prediction["scores"].tolist()
labels = prediction["labels"].tolist()
rles = [
pycocotools.mask.encode(
numpy.array(mask[0, :, :, numpy.newaxis], order="F")
)[0]
for mask in masks
]
for rle in rles:
rle["counts"] = rle["counts"].decode("utf-8")
coco_results.extend(
[
{
"image_id": original_id,
"category_id": labels[k],
"segmentation": rle,
"score": scores[k],
}
for k, rle in enumerate(rles)
]
)
return coco_results
def prepare_for_coco_keypoint(self, predictions: Sequence[KeypointsPredTuple]):
"""
:param predictions:
:type predictions:
:return:
:rtype:"""
coco_results = []
for original_id, prediction in predictions.items():
if len(prediction) == 0:
continue
scores = prediction["scores"].tolist()
labels = prediction["labels"].tolist()
keypoints = prediction["keypoints"]
keypoints = keypoints.flatten(start_dim=1).tolist()
coco_results.extend(
[
{
"image_id": original_id,
"category_id": labels[k],
"keypoints": keypoint,
"score": scores[k],
}
for k, keypoint in enumerate(keypoints)
]
)
return coco_results
def evaluate(iou_type_evaluator: COCOeval) -> Tuple:
"""
Run per image evaluation on given images and store results (a list of dict) in self.evalImgs
:return: None"""
p = iou_type_evaluator.params
# add backward compatibility if useSegm is specified in params
if p.useSegm is not None:
p.iouType = "segm" if p.useSegm == 1 else "bbox"
print(f"useSegm (deprecated) is not None. Running {p.iouType} evaluation")
# print('Evaluate annotation type *{}*'.format(p.iouType))
p.imgIds = list(numpy.unique(p.imgIds))
if p.useCats:
p.catIds = list(numpy.unique(p.catIds))
p.maxDets = sorted(p.maxDets)
iou_type_evaluator.params = p
iou_type_evaluator._prepare()
# loop through images, area range, max detection number
cat_ids = p.catIds if p.useCats else [-1]
compute_iou = None
if p.iouType == "segm" or p.iouType == "bbox":
compute_iou = iou_type_evaluator.computeIoU
elif p.iouType == "keypoints":
compute_iou = iou_type_evaluator.computeOks
iou_type_evaluator.ious = {
(imgId, catId): compute_iou(imgId, catId)
for imgId in p.imgIds
for catId in cat_ids
}
evaluate_img = iou_type_evaluator.evaluateImg
max_det = p.maxDets[-1]
eval_imgs = [
evaluate_img(img_id, cat_id, area_rng, max_det)
for cat_id in cat_ids
for area_rng in p.areaRng
for img_id in p.imgIds
]
eval_imgs = numpy.asarray(
eval_imgs
).reshape( # this is NOT in the pycocotools code, but could be done outside
len(cat_ids), len(p.areaRng), len(p.imgIds)
)
iou_type_evaluator._paramsEval = copy.deepcopy(iou_type_evaluator.params)
return p.imgIds, eval_imgs
def merge(img_ids, eval_imgs):
"""
:param img_ids:
:type img_ids:
:param eval_imgs:
:type eval_imgs:
:return:
:rtype:"""
all_img_ids = all_gather_cuda(img_ids)
all_eval_imgs = all_gather_cuda(eval_imgs)
merged_img_ids = []
for p in all_img_ids:
merged_img_ids.extend(p)
merged_eval_imgs = []
for p in all_eval_imgs:
merged_eval_imgs.append(p)
merged_img_ids = numpy.array(merged_img_ids)
merged_eval_imgs = numpy.concatenate(merged_eval_imgs, 2)
# keep only unique (and in sorted order) images
merged_img_ids, idx = numpy.unique(merged_img_ids, return_index=True)
merged_eval_imgs = merged_eval_imgs[..., idx]
return merged_img_ids, merged_eval_imgs
def create_common_coco_eval(coco_eval, img_ids, eval_imgs):
"""
:param coco_eval:
:type coco_eval:
:param img_ids:
:type img_ids:
:param eval_imgs:
:type eval_imgs:"""
img_ids, eval_imgs = merge(img_ids, eval_imgs)
img_ids = list(img_ids)
eval_imgs = list(eval_imgs.flatten())
coco_eval.evalImgs = eval_imgs
coco_eval.params.img_ids = img_ids
coco_eval._paramsEval = copy.deepcopy(coco_eval.params)
#################################################################
# From pycocotools, just removed the prints and fixed
# a Python3 bug about unicode not defined
#################################################################
# Ideally, pycocotools wouldn't have hard-coded prints
# so that we could avoid copy-pasting those two functions
def create_index(self):
"""
:param self:
:type self:"""
# create index
# print('creating index...')
anns, cats, imgs = {}, {}, {}
imgToAnns, catToImgs = defaultdict(list), defaultdict(list)
if "annotations" in self.dataset:
for ann in self.dataset["annotations"]:
imgToAnns[ann["image_id"]].append(ann)
anns[ann["id"]] = ann
if "images" in self.dataset:
for img in self.dataset["images"]:
imgs[img["id"]] = img
if "categories" in self.dataset:
for cat in self.dataset["categories"]:
cats[cat["id"]] = cat
if "annotations" in self.dataset and "categories" in self.dataset:
for ann in self.dataset["annotations"]:
catToImgs[ann["category_id"]].append(ann["image_id"])
# print('index created!')
# create class members
self.anns = anns
self.imgToAnns = imgToAnns
self.catToImgs = catToImgs
self.imgs = imgs
self.cats = cats
def load_results(self, resFile) -> COCO:
"""
Load result file and return a result api object.
:param self:
:type self:
:param resFile:
:type resFile:
:return: res (obj) : result api object"""
res = COCO()
res.dataset["images"] = [img for img in self.dataset["images"]]
# print('Loading and preparing results...')
# tic = time.time()
if isinstance(resFile, torch._six.string_classes):
anns = json.load(open(resFile))
elif type(resFile) == numpy.ndarray:
anns = self.loadNumpyAnnotations(resFile)
else:
anns = resFile
assert type(anns) == list, "results in not an array of objects"
annsImgIds = [ann["image_id"] for ann in anns]
assert set(annsImgIds) == (
set(annsImgIds) & set(self.getImgIds())
), "Results do not correspond to current coco set"
if "caption" in anns[0]:
imgIds = set([img["id"] for img in res.dataset["images"]]) & set(
[ann["image_id"] for ann in anns]
)
res.dataset["images"] = [
img for img in res.dataset["images"] if img["id"] in imgIds
]
for id, ann in enumerate(anns):
ann["id"] = id + 1
elif "bbox" in anns[0] and not anns[0]["bbox"] == []:
res.dataset["categories"] = copy.deepcopy(self.dataset["categories"])
for id, ann in enumerate(anns):
bb = ann["bbox"]
x1, x2, y1, y2 = [bb[0], bb[0] + bb[2], bb[1], bb[1] + bb[3]]
if "segmentation" not in ann:
ann["segmentation"] = [[x1, y1, x1, y2, x2, y2, x2, y1]]
ann["area"] = bb[2] * bb[3]
ann["id"] = id + 1
ann["iscrowd"] = 0
elif "segmentation" in anns[0]:
res.dataset["categories"] = copy.deepcopy(self.dataset["categories"])
for id, ann in enumerate(anns):
# now only support compressed RLE format as segmentation results
ann["area"] = pycocotools.mask.area(ann["segmentation"])
if "bbox" not in ann:
ann["bbox"] = pycocotools.mask.toBbox(ann["segmentation"])
ann["id"] = id + 1
ann["iscrowd"] = 0
elif "keypoints" in anns[0]:
res.dataset["categories"] = copy.deepcopy(self.dataset["categories"])
for id, ann in enumerate(anns):
s = ann["keypoints"]
x = s[0::3]
y = s[1::3]
x0, x1, y0, y1 = numpy.min(x), numpy.max(x), numpy.min(y), numpy.max(y)
ann["area"] = (x1 - x0) * (y1 - y0)
ann["id"] = id + 1
ann["bbox"] = [x0, y0, x1 - x0, y1 - y0]
# print('DONE (t={:0.2f}s)'.format(time.time()- tic))
res.dataset["annotations"] = anns
create_index(res)
return res
#################################################################
# end of straight copy from pycocotools, just removing the prints
#################################################################
def coco_evaluation(dataset, predictions, output_dir: Path, iteration=None):
"""
:param dataset:
:type dataset:
:param predictions:
:type predictions:
:param output_dir:
:type output_dir:
:param iteration:
:type iteration:
:return:
:rtype:"""
coco_results = []
for i, prediction in enumerate(predictions):
img_info = dataset.get_img_info(i)
prediction = prediction.resize((img_info["width"], img_info["height"])).numpy()
boxes, labels, scores = (
prediction["boxes"],
prediction["labels"],
prediction["scores"],
)
image_id, annotation = dataset.get_annotation(i)
class_mapper = dataset.contiguous_id_to_coco_id
if labels.shape[0] == 0:
continue
boxes = boxes.tolist()
labels = labels.tolist()
scores = scores.tolist()
coco_results.extend(
[
{
"image_id": image_id,
"category_id": class_mapper[labels[k]],
"bbox": [
box[0],
box[1],
box[2] - box[0],
box[3] - box[1],
], # to xywh format
"score": scores[k],
}
for k, box in enumerate(boxes)
]
)
iou_type = "bbox"
json_result_file = str(output_dir / f"{iou_type}.json")
logger = logging.getLogger("SSD.inference")
logger.info(f"Writing results to {json_result_file}...")
with open(json_result_file, "w") as f:
json.dump(coco_results, f)
coco_gt = dataset.coco
coco_dt = coco_gt.load_results(json_result_file)
coco_eval = COCOeval(coco_gt, coco_dt, iou_type)
coco_eval.evaluate()
coco_eval.accumulate()
coco_eval.summarize()
result_strings = []
keys = ["AP", "AP50", "AP75", "APs", "APm", "APl"]
metrics = {}
for i, key in enumerate(keys):
metrics[key] = coco_eval.stats[i]
logger.info(f"{key:<10}: {round(coco_eval.stats[i], 3)}")
result_strings.append(f"{key:<10}: {round(coco_eval.stats[i], 3)}")
if iteration is not None:
result_path = str(output_dir / f"result_{iteration:07d}.txt")
else:
result_path = str(
output_dir / f"result_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.txt"
)
with open(result_path, "w") as f:
f.write("\n".join(result_strings))
return dict(metrics=metrics)
def get_iou_types(model) -> Sequence[IouType]:
"""
:param model:
:type model:
:return:
:rtype:"""
model_without_ddp = model
if isinstance(model, torch.nn.parallel.DistributedDataParallel):
model_without_ddp = model.module
iou_types = [IouType.BoundingBox]
if isinstance(model_without_ddp, torchvision.models.detection.MaskRCNN):
iou_types.append(IouType.Segmentation)
if isinstance(model_without_ddp, torchvision.models.detection.KeypointRCNN):
iou_types.append(IouType.Keypoints)
return iou_types | PypiClean |
/KailWeb-0.5.tar.gz/KailWeb-0.5/README.md | Module and HTML Template Renderer Classes
This Python module contains two classes: Start and Renderer.
The Start class is used to start the default web browser and load a specified HTML file. The constructor takes an optional page parameter, which specifies the path to the HTML file to load. The open_page() method opens the default web browser and loads the specified HTML file. If an error occurs while loading the page, an error message is printed to the console.
The Renderer class is used to render HTML templates with dynamic data. The constructor takes a required template_file parameter, which specifies the path to the HTML template file. The render() method takes a dictionary of key-value pairs representing the data to include in the template. The method reads the contents of the HTML template file, replaces placeholders in the template with values from the context, and returns the rendered HTML code as a string.
Example usage:
``python
from kailweb import Start, Renderer
# Open the default web browser and load index.html
start = Start('/index.html')
start.open_page()
# Render a template with dynamic data
renderer = Renderer('template.html')
context = {'name': 'John', 'age': 30}
html = renderer.render(context)
print(html)
`` | PypiClean |
/Flask-User-AWS-1.0.1.7.tar.gz/Flask-User-AWS-1.0.1.7/flask_user/email_adapters/sendgrid_email_adapter.py |
from __future__ import print_function
# Non-system imports are moved into the methods to make them an optional requirement
from flask_user import current_app, ConfigError
from flask_user.email_adapters import EmailAdapterInterface
SENDGRID_IMPORT_ERROR_MESSAGE = 'The sendgrid package is missing. Install sendgrid with "pip install sendgrid".'
class SendgridEmailAdapter(EmailAdapterInterface):
""" Implements the EmailAdapter interface to send emails with SendGrid Web API v3 using sendgrid-python."""
def __init__(self, app):
"""Check config settings and setup SendGrid Web API v3.
Args:
app(Flask): The Flask application instance.
"""
super(SendgridEmailAdapter, self).__init__(app)
sendgrid_api_key = app.config.get('SENDGRID_API_KEY')
if not sendgrid_api_key:
raise ConfigError(
"The SENDGRID_API_KEY setting is missing. Set SENDGRID_API_KEY in your app config.")
# Setup sendgrid-python
try:
from sendgrid import SendGridAPIClient
self.sg = SendGridAPIClient(apikey=sendgrid_api_key)
except ImportError:
raise ConfigError(SENDGRID_IMPORT_ERROR_MESSAGE)
def send_email_message(self, recipient, subject, html_message, text_message, sender_email, sender_name):
""" Send email message via sendgrid-python.
Args:
recipient: Email address or tuple of (Name, Email-address).
subject: Subject line.
html_message: The message body in HTML.
text_message: The message body in plain text.
"""
if not current_app.testing: # pragma: no cover
try:
# Prepare Sendgrid helper objects
from sendgrid.helpers.mail import Email, Content, Substitution, Mail
from_email = Email(sender_email, sender_name)
to_email = Email(recipient)
text_content = Content('text/plain', text_message)
html_content = Content('text/html', html_message)
# Prepare Sendgrid Mail object
# Note: RFC 1341: text must be first, followed by html
mail = Mail(from_email, subject, to_email, text_content)
mail.add_content(html_content)
# Send mail via the Sendgrid API
response = self.sg.client.mail.send.post(request_body=mail.get())
print(response.status_code)
print(response.body)
print(response.headers)
except ImportError:
raise ConfigError(SENDGRID_IMPORT_ERROR_MESSAGE)
except Exception as e:
print(e)
print(e.body)
raise | PypiClean |
/MirrorX-6.0.13-py3-none-any.whl/bot/helper/ext_utils/fs_utils.py | import sys
from bot import aria2, LOGGER, DOWNLOAD_DIR, ARIA_CHILD_PROC, MEGA_CHILD_PROC
import shutil
import os
import pathlib
import magic
import tarfile
from .exceptions import NotSupportedExtractionArchive
def clean_download(path: str):
if os.path.exists(path):
LOGGER.info(f"Cleaning download: {path}")
shutil.rmtree(path)
def start_cleanup():
try:
shutil.rmtree(DOWNLOAD_DIR)
except FileNotFoundError:
pass
def clean_all():
aria2.remove_all(True)
try:
shutil.rmtree(DOWNLOAD_DIR)
except FileNotFoundError:
pass
def exit_clean_up(signal, frame):
try:
LOGGER.info("Please wait, while we clean up the downloads and stop running downloads")
clean_all()
ARIA_CHILD_PROC.kill()
MEGA_CHILD_PROC.kill()
sys.exit(0)
except KeyboardInterrupt:
LOGGER.warning("Force Exiting before the cleanup finishes!")
ARIA_CHILD_PROC.kill()
MEGA_CHILD_PROC.kill()
sys.exit(1)
def get_path_size(path):
if os.path.isfile(path):
return os.path.getsize(path)
total_size = 0
for root, dirs, files in os.walk(path):
for f in files:
abs_path = os.path.join(root, f)
total_size += os.path.getsize(abs_path)
return total_size
def tar(org_path):
tar_path = org_path + ".tar"
path = pathlib.PurePath(org_path)
LOGGER.info(f'Tar: orig_path: {org_path}, tar_path: {tar_path}')
tar = tarfile.open(tar_path, "w")
tar.add(org_path, arcname=path.name)
tar.close()
return tar_path
def get_base_name(orig_path: str):
if orig_path.endswith(".tar.bz2"):
return orig_path.replace(".tar.bz2", "")
elif orig_path.endswith(".tar.gz"):
return orig_path.replace(".tar.gz", "")
elif orig_path.endswith(".bz2"):
return orig_path.replace(".bz2", "")
elif orig_path.endswith(".gz"):
return orig_path.replace(".gz", "")
elif orig_path.endswith(".tar"):
return orig_path.replace(".tar", "")
elif orig_path.endswith(".tbz2"):
return orig_path.replace("tbz2", "")
elif orig_path.endswith(".tgz"):
return orig_path.replace(".tgz", "")
elif orig_path.endswith(".zip"):
return orig_path.replace(".zip", "")
elif orig_path.endswith(".7z"):
return orig_path.replace(".7z", "")
elif orig_path.endswith(".Z"):
return orig_path.replace(".Z", "")
elif orig_path.endswith(".rar"):
return orig_path.replace(".rar", "")
elif orig_path.endswith(".iso"):
return orig_path.replace(".iso", "")
elif orig_path.endswith(".wim"):
return orig_path.replace(".wim", "")
elif orig_path.endswith(".cab"):
return orig_path.replace(".cab", "")
elif orig_path.endswith(".apm"):
return orig_path.replace(".apm", "")
elif orig_path.endswith(".arj"):
return orig_path.replace(".arj", "")
elif orig_path.endswith(".chm"):
return orig_path.replace(".chm", "")
elif orig_path.endswith(".cpio"):
return orig_path.replace(".cpio", "")
elif orig_path.endswith(".cramfs"):
return orig_path.replace(".cramfs", "")
elif orig_path.endswith(".deb"):
return orig_path.replace(".deb", "")
elif orig_path.endswith(".dmg"):
return orig_path.replace(".dmg", "")
elif orig_path.endswith(".fat"):
return orig_path.replace(".fat", "")
elif orig_path.endswith(".hfs"):
return orig_path.replace(".hfs", "")
elif orig_path.endswith(".lzh"):
return orig_path.replace(".lzh", "")
elif orig_path.endswith(".lzma"):
return orig_path.replace(".lzma", "")
elif orig_path.endswith(".lzma2"):
return orig_path.replace(".lzma2", "")
elif orig_path.endswith(".mbr"):
return orig_path.replace(".mbr", "")
elif orig_path.endswith(".msi"):
return orig_path.replace(".msi", "")
elif orig_path.endswith(".mslz"):
return orig_path.replace(".mslz", "")
elif orig_path.endswith(".nsis"):
return orig_path.replace(".nsis", "")
elif orig_path.endswith(".ntfs"):
return orig_path.replace(".ntfs", "")
elif orig_path.endswith(".rpm"):
return orig_path.replace(".rpm", "")
elif orig_path.endswith(".squashfs"):
return orig_path.replace(".squashfs", "")
elif orig_path.endswith(".udf"):
return orig_path.replace(".udf", "")
elif orig_path.endswith(".vhd"):
return orig_path.replace(".vhd", "")
elif orig_path.endswith(".xar"):
return orig_path.replace(".xar", "")
else:
raise NotSupportedExtractionArchive('File format not supported for extraction')
def get_mime_type(file_path):
mime = magic.Magic(mime=True)
mime_type = mime.from_file(file_path)
mime_type = mime_type if mime_type else "text/plain"
return mime_type | PypiClean |
/Inukshuk-0.1.2.tar.gz/Inukshuk-0.1.2/inukshuk/nodes/expression.py | from ..lexer import (
TOKEN_ID_WHITESPACE,
TOKEN_ID_IDENTIFIER, TOKEN_ID_INTEGER, TOKEN_ID_FLOAT,
TOKEN_ID_STRING_SINGLE_QUOTES, TOKEN_ID_STRING_DOUBLE_QUOTES,
TOKEN_ID_SYMBOL)
from .base import (
ParserError, ParserNode, MultiChildrenParserNode)
from .const import (
StringNode, FloatNode, IntegerNode, ListNode, const_identifiers)
from .filters import FilterNode
from .operators import (
NotOperatorNode, binary_operator_nodes, misc_operator_nodes)
class InvalidOperatorError(Exception):
def __init__(self, value_node, op_name):
super().__init__("Invalid operator: %s" % op_name)
self.value_node = value_node
self.op_name = op_name
class ExpressionNode(ParserNode):
def __init__(self, with_tail=True):
super().__init__()
self.child = None
self.with_tail = with_tail
def iterChildren(self):
yield self.child
def add(self, node):
if self.child is None:
self.child = node
else:
raise Exception("This node already has a child: %s" % self.child)
def parse(self, parser):
parser_read = parser.read
parser_peek = parser.peek
parser_expect = parser.expect
parser_skip = parser.skip
_, token_id, value = parser_peek()
if token_id == TOKEN_ID_SYMBOL and value == '(':
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
self.recurseInto(parser, ExpressionNode())
parser_skip(TOKEN_ID_WHITESPACE)
parser_expect(TOKEN_ID_SYMBOL, ')')
parser_skip(TOKEN_ID_WHITESPACE)
if self.with_tail:
self._parseTail(parser)
return
if token_id == TOKEN_ID_SYMBOL and value == '[':
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
self.recurseInto(parser, ListNode())
parser_skip(TOKEN_ID_WHITESPACE)
parser_expect(TOKEN_ID_SYMBOL, ']')
parser_skip(TOKEN_ID_WHITESPACE)
if self.with_tail:
self._parseTail(parser)
return
if token_id == TOKEN_ID_IDENTIFIER and value == 'not':
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
self.recurseInto(parser, NotOperatorNode())
parser_skip(TOKEN_ID_WHITESPACE)
if self.with_tail:
self._parseTail(parser)
return
self.child = self._parseValueWithFilter(parser)
parser_skip(TOKEN_ID_WHITESPACE)
if self.with_tail:
self._parseTail(parser)
def _parseValueWithFilter(self, parser):
parser_read = parser.read
parser_skip = parser.skip
parser_isNext = parser.isNext
# Start with the value, a context query or a string.
value_node = self._parseValue(parser)
# Now see if there are any filters.
expr_root_node = value_node
parser_skip(TOKEN_ID_WHITESPACE)
while parser_isNext(TOKEN_ID_SYMBOL, '|'):
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
flt_node = FilterNode()
flt_node.add(expr_root_node)
flt_node.parse(parser)
expr_root_node = flt_node
parser_skip(TOKEN_ID_WHITESPACE)
return expr_root_node
def _parseValue(self, parser):
parser_readValue = parser.readValue
parser_isNext = parser.isNext
parser_peek = parser.peek
# A context query, a string, a number, a list, a dictionary,
# a tuple, or true/false.
value_node = None
if parser_isNext(TOKEN_ID_IDENTIFIER):
_, _, idval = parser_peek()
value_node = const_identifiers.get(idval)
if value_node is None:
value_node = ContextQueryNode()
value_node.parse(parser)
else:
parser.read()
elif (parser_isNext(TOKEN_ID_STRING_SINGLE_QUOTES) or
parser_isNext(TOKEN_ID_STRING_DOUBLE_QUOTES)):
value_node = StringNode(parser_readValue())
elif parser_isNext(TOKEN_ID_FLOAT):
value_node = FloatNode(float(parser_readValue()))
elif parser_isNext(TOKEN_ID_INTEGER):
value_node = IntegerNode(int(parser_readValue()))
elif parser_isNext(TOKEN_ID_SYMBOL, '-'):
parser_readValue()
if parser_isNext(TOKEN_ID_FLOAT):
value_node = FloatNode(-float(parser_readValue()))
elif parser_isNext(TOKEN_ID_INTEGER):
value_node = IntegerNode(-int(parser_readValue()))
else:
line_num, _, value = parser.peek()
raise ParserError(line_num, "unexpected token '%s'." % value)
else:
line_num, _, value = parser_peek()
raise ParserError(line_num, "unexpected token '%s'." % value)
return value_node
def _parseTail(self, parser):
# See if the expression continue... in which case we wrap
# our current child into a bigger expression.
parser_read = parser.read
parser_peek = parser.peek
parser_skip = parser.skip
child_op_prec = getattr(self.child, '__op_precedence__', None)
child_is_binary_op = getattr(self.child, '__op_type__', 0) == 2
line_num, token_id, value = parser_peek()
if token_id == TOKEN_ID_IDENTIFIER:
op_node_cls = misc_operator_nodes.get(value)
if op_node_cls is not None:
# Test or boolean operator.
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
if op_node_cls.__op_type__ != 2:
raise Exception("Unexpected unary operator: %s" %
op_node_cls)
as_tail = False
if child_is_binary_op:
as_tail = (
child_op_prec < op_node_cls.__op_precedence__)
op_node = op_node_cls()
if as_tail:
op_node.add(self.child.child2)
self.child.child2 = op_node
op_node.parse(parser)
else:
op_node.add(self.child)
self.child = op_node
op_node.parse(parser)
parser_skip(TOKEN_ID_WHITESPACE)
self._parseTail(parser)
return
elif token_id == TOKEN_ID_SYMBOL:
op_name = None
# Binary operators are 1 or 2 characters... see if any operator
# matches this first character.
for k in binary_operator_nodes.keys():
if k[0] == value:
op_name = value
break
if op_name:
# Yep, it matched. Now see if there's a 2nd character too.
parser_read()
_, token_id, value = parser_peek()
if token_id == TOKEN_ID_SYMBOL:
# Try matching a 2-character operator. If nothing matches,
# go back to the one character operator.
#
# This can happen for instance with:
# {{ a /(2 + b) }}
# ^^
# 2-chars!
#
if (op_name + value) in binary_operator_nodes:
op_name += value
parser_read()
op_node_cls = binary_operator_nodes.get(op_name)
if op_node_cls is not None:
# Binary operator.
parser_skip(TOKEN_ID_WHITESPACE)
as_tail = False
if child_is_binary_op:
as_tail = (
child_op_prec < op_node_cls.__op_precedence__)
op_node = op_node_cls()
if as_tail:
op_node.add(self.child.child2)
self.child.child2 = op_node
op_node.parse(parser)
else:
op_node.add(self.child)
self.child = op_node
op_node.parse(parser)
parser_skip(TOKEN_ID_WHITESPACE)
self._parseTail(parser)
return
else:
# Raise an exception because at this point we can't
# give back what we consumed.
raise InvalidOperatorError(self.child, op_name)
def render(self, ctx, data, out):
return self.child.render(ctx, data, out)
def compile(self, ctx, out):
self.child.compile(ctx, out)
class ExpressionWrapperNode(ExpressionNode):
def render(self, ctx, data, out):
# This is where we make sure things are converted to strings for
# rendering the output.
val = self.child.render(ctx, data, out)
out(ctx.engine.escape(val))
def compile(self, ctx, out):
self.child.compile(ctx, out)
val = ctx.popvar()
out.indent().write('out_write_escaped(%s)\n' % val)
class ContextQueryNode(MultiChildrenParserNode):
TYPE_PROPERTY = 0
TYPE_ARRAY_ITEM = 1
TYPE_DICT_ITEM = 2
TYPE_FUNC_CALL = 3
def __init__(self, name=None):
super().__init__()
self.name = name
self.query_type = ContextQueryNode.TYPE_PROPERTY
self.array_item_query = None
self.is_head = True
self.has_tail = False
self.force_cache_query = False
def parse(self, parser):
parser_expect = parser.expect
parser_isNext = parser.isNext
parser_skip = parser.skip
parser_read = parser.read
self.name = parser_expect(TOKEN_ID_IDENTIFIER)
# See if we have either a dictionary access or a function call.
if parser_isNext(TOKEN_ID_SYMBOL, '['):
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
if parser_isNext(TOKEN_ID_INTEGER):
# Index or full slice or first-half-slice (array[i:]).
is_slice = False
index1 = int(parser_read()[2])
index2 = None
parser_skip(TOKEN_ID_WHITESPACE)
if parser_isNext(TOKEN_ID_SYMBOL, ':'):
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
is_slice = True
if parser_isNext(TOKEN_ID_INTEGER):
index2 = int(parser_read()[2])
self.array_item_query = (is_slice, index1, index2)
self.query_type = ContextQueryNode.TYPE_ARRAY_ITEM
elif parser_isNext(TOKEN_ID_SYMBOL, ':'):
# Second-half-slice (array[:i]).
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
index2 = parser_expect(TOKEN_ID_INTEGER)
self.array_item_query = (True, None, int(index2))
self.query_type = ContextQueryNode.TYPE_ARRAY_ITEM
else:
self.recurseInto(parser, ExpressionNode())
self.query_type = ContextQueryNode.TYPE_DICT_ITEM
parser_skip(TOKEN_ID_WHITESPACE)
parser_expect(TOKEN_ID_SYMBOL, ']')
elif parser_isNext(TOKEN_ID_SYMBOL, '('):
self.query_type = ContextQueryNode.TYPE_FUNC_CALL
parser_read()
parser_skip(TOKEN_ID_WHITESPACE)
needs_comma = False
while not parser_isNext(TOKEN_ID_SYMBOL, ')'):
if needs_comma:
parser_skip(TOKEN_ID_WHITESPACE)
parser_expect(TOKEN_ID_SYMBOL, ',')
parser_skip(TOKEN_ID_WHITESPACE)
self.recurseInto(parser, ExpressionNode())
needs_comma = True
parser_expect(TOKEN_ID_SYMBOL, ')')
# See if the context query continues.
if parser_isNext(TOKEN_ID_SYMBOL, '.'):
parser_read()
self.has_tail = True
tail = ContextQueryNode()
tail.is_head = False
self.recurseInto(parser, tail)
def render(self, ctx, data, out):
children = self.children
if self.has_tail:
children = self.children[:-1]
if self.is_head:
val = ctx.queryRoot(data, self.name)
else:
val = ctx.query(data, self.name)
if self.query_type == ContextQueryNode.TYPE_ARRAY_ITEM:
is_slice, index1, index2 = self.array_item_query
if is_slice:
valid_index1 = index1 is not None
valid_index2 = index2 is not None
if valid_index1 and valid_index2:
val = val[index1:index2]
elif valid_index1:
val = val[index1:]
elif valid_index2:
val = val[:index2]
else:
raise Exception("Got slicing notation without indices!")
else:
val = val[index1]
elif self.query_type == ContextQueryNode.TYPE_DICT_ITEM:
key = children[0].render(ctx, data, out)
val = val[key]
elif self.query_type == ContextQueryNode.TYPE_FUNC_CALL:
params = list(self._renderTheseChildren(children, ctx, data, out))
if getattr(val, 'needs_context', False):
val = val(ctx, data, out, *params)
else:
val = val(*params)
elif self.query_type != ContextQueryNode.TYPE_PROPERTY:
raise Exception("Unexpected query type: %s" % self.query_type)
if self.has_tail:
return self.children[-1].render(ctx, val, out)
else:
return val
def _renderTheseChildren(self, children, ctx, data, out):
for c in children:
yield c.render(ctx, data, out)
def compile(self, ctx, out):
children = self.children
if self.has_tail:
children = self.children[:-1]
data_name = 'data'
if not self.is_head:
data_name = ctx.popvar()
if self.query_type == ContextQueryNode.TYPE_PROPERTY:
val = self._cachedQueryVar(ctx, self.name)
if val is None:
val = self._newQuery(data_name, self.name)
if self.force_cache_query:
cached_val = ctx.varname('cached_query')
out.indent().write('%s = %s\n' % (cached_val, val))
val = cached_val
ctx.cacheQuery(self.name, val)
ctx.pushvar(val)
elif self.query_type == ContextQueryNode.TYPE_ARRAY_ITEM:
val = self._cachedQueryVar(ctx, self.name)
if val is None:
val = self._newQuery(data_name, self.name)
if self.force_cache_query:
cached_val = ctx.varname('cached_query')
out.indent().write('%s = %s\n' % (cached_val, val))
val = cached_val
ctx.cacheQuery(self.name, val)
is_slice, index1, index2 = self.array_item_query
if is_slice:
valid_index1 = index1 is not None
valid_index2 = index2 is not None
if valid_index1 and valid_index2:
expr = '%s[%s:%s]' % (val, index1, index2)
elif valid_index1:
expr = '%s[%s:]' % (val, index1)
elif valid_index2:
expr = '%s[:%s]' % (val, index2)
else:
raise Exception("Got slicing notation without indices!")
else:
expr = '%s[%s]' % (val, index1)
ctx.pushvar(expr)
elif self.query_type == ContextQueryNode.TYPE_DICT_ITEM:
dname = self._cachedQueryVar(ctx, self.name)
if dname is None:
dname = self._newQuery(data_name, self.name)
if self.force_cache_query:
cached_dname = ctx.varname('cached_query')
out.indent().write('%s = %s\n' % (cached_dname, dname))
dname = cached_dname
ctx.cacheQuery(self.name, dname)
children[0].compile(ctx, out)
expr = '%s[%s]' % (dname, ctx.popvar())
ctx.pushvar(expr)
elif self.query_type == ContextQueryNode.TYPE_FUNC_CALL:
fname = self._cachedQueryVar(ctx, self.name)
if fname is None:
fname = self._newQuery(data_name, self.name)
if self.force_cache_query:
cached_fname = ctx.varname('cached_query')
out.indent().write('%s = %s\n' % (cached_fname, fname))
fname = cached_fname
ctx.cacheQuery(self.name, fname)
param_names = []
for c in children:
c.compile(ctx, out)
param_names.append(ctx.popvar())
if param_names:
val = ('ctx_invoke(data, out_write, %s, %s)' %
(fname, ', '.join(param_names)))
else:
val = 'ctx_invoke(data, out_write, %s)' % fname
ctx.pushvar(val)
else:
raise Exception("Unexpected query type: %s" % self.query_type)
if self.has_tail:
self.children[-1].compile(ctx, out)
def _cachedQueryVar(self, ctx, query):
if self.is_head:
return ctx.getCachedQuery(query)
return None
def _newQuery(self, dataname, query):
if self.is_head:
return 'ctx_queryRoot(%s, %s)' % (dataname, repr(query))
else:
return 'ctx_query(%s, %s)' % (dataname, repr(query)) | PypiClean |
/Discohook-1.0.0.tar.gz/Discohook-1.0.0/discohook/client.py | import logging
import json
import time
import datetime
import requests
logger = logging.getLogger(__name__)
__all__ = ["Discohook", "DiscohookEmbed", "DiscohookException"]
class Discohook:
"""
Webhook for Discord
"""
def __init__(self, url, **kwargs):
"""
Init Discohook
- param url : Discohook webhook url
- type url : str, list
- keyword content : the message contents
- keyword username : override the default username of the webhook
- keyword avatar_url : override the default avatar of the webhook
- keyword tts : true if this is a TTS message
- keyword file : file contents
- keyword filename : file name
- keyword embeds : list of embedded rich content
- keyword allowed_mentions : allowed mentions for the message
- keyword proxies : dict of proxies
- keyword timeout : (optional) amount of seconds to wait for a response from Discord
"""
self.url = url
self.content = kwargs.get("content")
self.username = kwargs.get("username")
self.avatar_url = kwargs.get("avatar_url")
self.tts = kwargs.get("tts", False)
self.files = kwargs.get("files", dict())
self.embeds = kwargs.get("embeds", [])
self.proxies = kwargs.get("proxies")
self.allowed_mentions = kwargs.get("allowed_mentions")
self.timeout = kwargs.get("timeout")
self.rate_limit_retry = kwargs.get("rate_limit_retry")
def add_file(self, file, filename):
"""
Adds a file to the webhook
- param file : `file content`
- param filename : `filename`
- return :
"""
self.files["_{}".format(filename)] = (filename, file)
def add_embed(self, embed):
"""
Adds an embedded rich content
- param embed : embed object or dict
"""
self.embeds.append(embed.__dict__ if isinstance(embed, DiscohookEmbed) else embed)
def remove_embed(self, index):
"""
Removes embedded rich content from `self.embeds`
- param index : index of embed in `self.embeds`
"""
self.embeds.pop(index)
def remove_file(self, filename):
"""
Removes file from `self.files` using specified `filename` if it exists
- param filename : `filename`
"""
filename = "_{}".format(filename)
if filename in self.files:
del self.files[filename]
def get_embeds(self):
"""
Gets all `self.embeds` as list
- return : `self.embeds`
"""
return self.embeds
def set_proxies(self, proxies):
"""
Sets Proxies
- param proxies : `dict of proxies`
- type proxies : `dict`
"""
self.proxies = proxies
def set_content(self, content):
"""
Sets Content
- param content : `content string`
- type content : `string`
"""
self.content = content
@property
def json(self):
"""
Convert webhook data to json
- return webhook data as json
"""
data = dict()
embeds = self.embeds
self.embeds = list()
# convert DiscohookEmbed to dict
for embed in embeds:
self.add_embed(embed)
for key, value in self.__dict__.items():
if value and key not in ["url", "files", "filename"]:
data[key] = value
embeds_empty = (
all(not embed for embed in data["embeds"]) if "embeds" in data else True
)
if embeds_empty and "content" not in data and bool(self.files) is False:
logger.error("Webhook message is empty! set content or embed data")
return data
def remove_embeds(self):
"""
Sets `self.embeds` to empty `list`.
"""
self.embeds = []
def remove_files(self):
"""
Sets `self.files` to empty `dict`.
"""
self.files = {}
def api_post_request(self, url):
if bool(self.files) is False:
response = requests.post(url, json=self.json, proxies=self.proxies,
params={'wait': True},
timeout=self.timeout)
else:
self.files["payload_json"] = (None, json.dumps(self.json))
response = requests.post(url, files=self.files,
proxies=self.proxies,
timeout=self.timeout)
return response
def execute(self, remove_embeds=False, remove_files=False):
"""
Executes the Webhook
- param remove_embeds : if set to True, calls `self.remove_embeds()` to empty `self.embeds` after webhook is executed
- param remove_files : if set to True, calls `self.remove_files()` to empty `self.files` after webhook is executed
- return : Webhook response
"""
webhook_urls = self.url if isinstance(self.url, list) else [self.url]
urls_len = len(webhook_urls)
responses = []
for i, url in enumerate(webhook_urls):
response = self.api_post_request(url)
if response.status_code in [200, 204]:
logger.debug(
"[{index}/{length}] Webhook executed".format(
index=i+1, length=urls_len
)
)
elif response.status_code == 429 and self.rate_limit_retry:
while response.status_code == 429:
errors = json.loads(
response.content.decode('utf-8'))
wh_sleep = (int(errors['retry_after']) / 1000) + 0.15
time.sleep(wh_sleep)
logger.error(
"Webhook rate limited: sleeping for {wh_sleep} "
"seconds...".format(
wh_sleep=wh_sleep
)
)
response = self.api_post_request(url)
if response.status_code in [200, 204]:
logger.debug(
"[{index}/{length}] Webhook executed".format(
index=i + 1, length=urls_len
)
)
break
else:
logger.error(
"[{index}/{length}] Webhook status code {status_code}: {content}".format(
index=i+1,
length=urls_len,
status_code=response.status_code,
content=response.content.decode("utf-8"),
)
)
responses.append(response)
if remove_embeds:
self.remove_embeds()
if remove_files:
self.remove_files()
return responses[0] if len(responses) == 1 else responses
def edit(self, sent_webhook):
"""
Edits the webhook passed as a response
- param sent_webhook : webhook.execute() response
- return : Another webhook response
"""
sent_webhook = sent_webhook if isinstance(sent_webhook, list) else [sent_webhook]
webhook_len = len(sent_webhook)
responses = []
for i, webhook in enumerate(sent_webhook):
url = webhook.url.split('?')[0] # removes any query params
previous_sent_message_id = json.loads(webhook.content.decode('utf-8'))['id']
if bool(self.files) is False:
response = requests.patch(url+'/messages/'+str(previous_sent_message_id), json=self.json, proxies=self.proxies, params={'wait': True}, timeout=self.timeout)
else:
self.files["payload_json"] = (None, json.dumps(self.json))
response = requests.patch(url+'/messages/'+str(previous_sent_message_id), files=self.files, proxies=self.proxies, timeout=self.timeout)
if response.status_code in [200, 204]:
logger.debug(
"[{index}/{length}] Webhook edited".format(
index=i + 1,
length=webhook_len,
)
)
else:
logger.error(
"[{index}/{length}] Webhook status code {status_code}: {content}".format(
index=i + 1,
length=webhook_len,
status_code=response.status_code,
content=response.content.decode("utf-8"),
)
)
responses.append(response)
return responses[0] if len(responses) == 1 else responses
def delete(self, sent_webhook):
"""
Deletes the webhook passed as a response
- param sent_webhook : webhook.execute() response
- return : Response
"""
sent_webhook = sent_webhook if isinstance(sent_webhook, list) else [sent_webhook]
webhook_len = len(sent_webhook)
responses = []
for i, webhook in enumerate(sent_webhook):
url = webhook.url.split('?')[0] # removes any query params
previous_sent_message_id = json.loads(webhook.content.decode('utf-8'))['id']
response = requests.delete(url+'/messages/'+str(previous_sent_message_id), proxies=self.proxies, timeout=self.timeout)
if response.status_code in [200, 204]:
logger.debug(
"[{index}/{length}] Webhook deleted".format(
index=i + 1,
length=webhook_len,
)
)
else:
logger.error(
"[{index}/{length}] Webhook status code {status_code}: {content}".format(
index=i + 1,
length=webhook_len,
status_code=response.status_code,
content=response.content.decode("utf-8"),
)
)
responses.append(response)
return responses[0] if len(responses) == 1 else responses
class DiscohookEmbed:
"""
Discord Embed
"""
def __init__(self, **kwargs):
"""
Init Discord Embed
- keyword title : title of embed
- keyword description : description of embed
- keyword url : url of embed
- keyword timestamp : timestamp of embed content
- keyword color : color code of the embed as int
- keyword hex_color : color code of the embed as a hex string
- keyword footer : footer information
- keyword image : image information
- keyword thumbnail : thumbnail information
- keyword video : video information
- keyword provider : provider information
- keyword author : author information
- keyword fields : fields information
"""
self.title = kwargs.get("title")
self.description = kwargs.get("description")
self.url = kwargs.get("url")
self.timestamp = kwargs.get("timestamp")
self.color = kwargs.get("color")
if self.color:
self.set_color(self.color)
self.hex_color = kwargs.get("hex_color")
self.footer = kwargs.get("footer")
self.image = kwargs.get("image")
self.thumbnail = kwargs.get("thumbnail")
self.video = kwargs.get("video")
self.provider = kwargs.get("provider")
self.author = kwargs.get("author")
self.fields = kwargs.get("fields", [])
def set_title(self, title):
"""
Set title of embed
- param title : title of embed
"""
self.title = title
def set_description(self, description):
"""
Set description of embed
- param description : description of embed
"""
self.description = description
def set_url(self, url):
"""
Set url of embed
- param url : url of embed
"""
self.url = url
def set_timestamp(self, timestamp=None):
"""
Set timestamp of embed content
- param timestamp : (optional) timestamp of embed content
"""
if timestamp is None:
timestamp = time.time()
self.timestamp = str(datetime.datetime.utcfromtimestamp(timestamp))
def set_color(self, color):
"""
Set color code of the embed as decimal(int) or hex(string)
- param color : color code of the embed as decimal(int) or hex(string)
"""
if isinstance(color, str):
self.color = int(color, 16)
else:
self.color = color
def set_footer(self, **kwargs):
"""
Set footer information of embed
- keyword text : footer text
- keyword icon_url : url of footer icon (only supports http(s) and attachments)
- keyword proxy_icon_url : a proxied url of footer icon
"""
self.footer = {
"text": kwargs.get("text"),
"icon_url": kwargs.get("icon_url"),
"proxy_icon_url": kwargs.get("proxy_icon_url"),
}
def set_image(self, **kwargs):
"""
Set image of embed
- keyword url : source url of image (only supports http(s) and attachments)
- keyword proxy_url : a proxied url of the image
- keyword height : height of image
- keyword width : width of image
"""
self.image = {
"url": kwargs.get("url"),
"proxy_url": kwargs.get("proxy_url"),
"height": kwargs.get("height"),
"width": kwargs.get("width"),
}
def set_thumbnail(self, **kwargs):
"""
Set thumbnail of embed
- keyword url : source url of thumbnail (only supports http(s) and attachments)
- keyword proxy_url : a proxied thumbnail of the image
- keyword height : height of thumbnail
- keyword width : width of thumbnail
"""
self.thumbnail = {
"url": kwargs.get("url"),
"proxy_url": kwargs.get("proxy_url"),
"height": kwargs.get("height"),
"width": kwargs.get("width"),
}
def set_video(self, **kwargs):
"""
Set video of embed
- keyword url : source url of video
- keyword height : height of video
- keyword width : width of video
"""
self.video = {
"url": kwargs.get("url"),
"height": kwargs.get("height"),
"width": kwargs.get("width"),
}
def set_provider(self, **kwargs):
"""
set provider of embed
- keyword name : name of provider
- keyword url : url of provider
"""
self.provider = {
"name": kwargs.get("name"),
"url": kwargs.get("url"),
}
def set_author(self, **kwargs):
"""
Set author of embed
- keyword name : name of author
- keyword url : url of author
- keyword icon_url : url of author icon (only supports http(s) and attachments)
- keyword proxy_icon_url : a proxied url of author icon
"""
self.author = {
"name": kwargs.get("name"),
"url": kwargs.get("url"),
"icon_url": kwargs.get("icon_url"),
"proxy_icon_url": kwargs.get("proxy_icon_url"),
}
def add_embed_field(self, **kwargs):
"""
Set field of embed
- keyword name : name of the field
- keyword value : value of the field
- keyword inline : (optional) whether or not this field should display inline
"""
self.fields.append(
{
"name": kwargs.get("name"),
"value": kwargs.get("value"),
"inline": kwargs.get("inline", True),
}
)
def del_embed_field(self, index):
"""
Remove field from `self.fields`
- param index : index of field in `self.fields`
"""
self.fields.pop(index)
def get_embed_fields(self):
"""
Get all `self.fields` as list
- return : `self.fields`
"""
return self.fields | PypiClean |
/Axelrod-4.13.0.tar.gz/Axelrod-4.13.0/axelrod/moran.py |
from collections import Counter
from typing import Callable, List, Optional, Set, Tuple
import matplotlib.pyplot as plt
import numpy as np
from axelrod import DEFAULT_TURNS, EvolvablePlayer, Game, Player
from axelrod.deterministic_cache import DeterministicCache
from axelrod.graph import Graph, complete_graph
from axelrod.match import Match
from axelrod.random_ import BulkRandomGenerator, RandomGenerator
class MoranProcess(object):
def __init__(
self,
players: List[Player],
turns: int = DEFAULT_TURNS,
prob_end: float = None,
noise: float = 0,
game: Game = None,
deterministic_cache: DeterministicCache = None,
mutation_rate: float = 0.0,
mode: str = "bd",
interaction_graph: Graph = None,
reproduction_graph: Graph = None,
fitness_transformation: Callable = None,
mutation_method="transition",
stop_on_fixation=True,
seed=None,
match_class=Match,
) -> None:
"""
An agent based Moran process class. In each round, each player plays a
Match with each other player. Players are assigned a fitness score by
their total score from all matches in the round. A player is chosen to
reproduce proportionally to fitness, possibly mutated, and is cloned.
The clone replaces a randomly chosen player.
If the mutation_rate is 0, the population will eventually fixate on
exactly one player type. In this case a StopIteration exception is
raised and the play stops. If the mutation_rate is not zero, then the
process will iterate indefinitely, so mp.play() will never exit, and
you should use the class as an iterator instead.
When a player mutates it chooses a random player type from the initial
population. This is not the only method yet emulates the common method
in the literature.
It is possible to pass interaction graphs and reproduction graphs to the
Moran process. In this case, in each round, each player plays a
Match with each neighboring player according to the interaction graph.
Players are assigned a fitness score by their total score from all
matches in the round. A player is chosen to reproduce proportionally to
fitness, possibly mutated, and is cloned. The clone replaces a randomly
chosen neighboring player according to the reproduction graph.
Parameters
----------
players
turns:
The number of turns in each pairwise interaction
prob_end :
The probability of a given turn ending a match
noise:
The background noise, if any. Randomly flips plays with probability
`noise`.
game: axelrod.Game
The game object used to score matches.
deterministic_cache:
A optional prebuilt deterministic cache
mutation_rate:
The rate of mutation. Replicating players are mutated with
probability `mutation_rate`
mode:
Birth-Death (bd) or Death-Birth (db)
interaction_graph: Axelrod.graph.Graph
The graph in which the replicators are arranged
reproduction_graph: Axelrod.graph.Graph
The reproduction graph, set equal to the interaction graph if not
given
fitness_transformation:
A function mapping a score to a (non-negative) float
mutation_method:
A string indicating if the mutation method should be between original types ("transition")
or based on the player's mutation method, if present ("atomic").
stop_on_fixation:
A bool indicating if the process should stop on fixation
seed: int
A random seed for reproducibility
"""
m = mutation_method.lower()
if m in ["atomic", "transition"]:
self.mutation_method = m
else:
raise ValueError(
"Invalid mutation method {}".format(mutation_method)
)
assert (mutation_rate >= 0) and (mutation_rate <= 1)
assert (noise >= 0) and (noise <= 1)
mode = mode.lower()
assert mode in ["bd", "db"]
self.mode = mode
if deterministic_cache is not None:
self.deterministic_cache = deterministic_cache
else:
self.deterministic_cache = DeterministicCache()
self.turns = turns
self.match_class = match_class
self.prob_end = prob_end
self.game = game
self.noise = noise
self.initial_players = players # save initial population
self.players = [] # type: List
self.populations = [] # type: List
self.score_history = [] # type: List
self.winning_strategy_name = None # type: Optional[str]
self.mutation_rate = mutation_rate
self.stop_on_fixation = stop_on_fixation
self._random = RandomGenerator(seed=seed)
self._bulk_random = BulkRandomGenerator(self._random.random_seed_int())
self.set_players()
# Build the set of mutation targets
# Determine the number of unique types (players)
keys = set([str(p) for p in players])
# Create a dictionary mapping each type to a set of representatives
# of the other types
d = dict()
for p in players:
d[str(p)] = p
mutation_targets = dict()
for key in sorted(keys):
mutation_targets[key] = [
v for (k, v) in sorted(d.items()) if k != key
]
self.mutation_targets = mutation_targets
if interaction_graph is None:
interaction_graph = complete_graph(len(players), loops=False)
if reproduction_graph is None:
reproduction_graph = Graph(
interaction_graph.edges, directed=interaction_graph.directed
)
reproduction_graph.add_loops()
# Check equal vertices
v1 = interaction_graph.vertices
v2 = reproduction_graph.vertices
assert list(v1) == list(v2)
self.interaction_graph = interaction_graph
self.reproduction_graph = reproduction_graph
self.fitness_transformation = fitness_transformation
# Map players to graph vertices
self.locations = sorted(interaction_graph.vertices)
self.index = dict(
zip(sorted(interaction_graph.vertices), range(len(players)))
)
self.fixated = self.fixation_check()
def set_players(self) -> None:
"""Copy the initial players into the first population, setting seeds as needed."""
self.players = []
for player in self.initial_players:
if (self.mutation_method == "atomic") and issubclass(
player.__class__, EvolvablePlayer
):
# For reproducibility, we generate random seeds for evolvable players.
seed = next(self._bulk_random)
new_player = player.create_new(seed=seed)
self.players.append(new_player)
else:
player.reset()
self.players.append(player)
self.populations = [self.population_distribution()]
def fitness_proportionate_selection(
self, scores: List, fitness_transformation: Callable = None
) -> int:
"""Randomly selects an individual proportionally to score.
Parameters
----------
scores: Any sequence of real numbers
fitness_transformation: A function mapping a score to a (non-negative) float
Returns
-------
An index of the above list selected at random proportionally to the list
element divided by the total.
"""
if fitness_transformation is None:
csums = np.cumsum(scores)
else:
csums = np.cumsum([fitness_transformation(s) for s in scores])
total = csums[-1]
r = self._random.random() * total
for i, x in enumerate(csums):
if x >= r:
break
return i
def mutate(self, index: int) -> Player:
"""Mutate the player at index.
Parameters
----------
index:
The index of the player to be mutated
"""
if self.mutation_method == "atomic":
if not issubclass(self.players[index].__class__, EvolvablePlayer):
raise TypeError(
"Player is not evolvable. Use a subclass of EvolvablePlayer."
)
return self.players[index].mutate()
# Assuming mutation_method == "transition"
if self.mutation_rate > 0:
# Choose another strategy at random from the initial population
r = self._random.random()
if r < self.mutation_rate:
s = str(self.players[index])
j = self._random.randrange(0, len(self.mutation_targets[s]))
p = self.mutation_targets[s][j]
return p.clone()
# Just clone the player
return self.players[index].clone()
def death(self, index: int = None) -> int:
"""
Selects the player to be removed.
Note that the in the birth-death case, the player that is reproducing
may also be replaced. However in the death-birth case, this player will
be excluded from the choices.
Parameters
----------
index:
The index of the player to be removed
"""
if index is None:
# Select a player to be replaced globally
i = self._random.randrange(0, len(self.players))
# Record internally for use in _matchup_indices
self.dead = i
else:
# Select locally
# index is not None in this case
vertex = self._random.choice(
sorted(
self.reproduction_graph.out_vertices(self.locations[index])
)
)
i = self.index[vertex]
return i
def birth(self, index: int = None) -> int:
"""The birth event.
Parameters
----------
index:
The index of the player to be copied
"""
# Compute necessary fitnesses.
scores = self.score_all()
if index is not None:
# Death has already occurred, so remove the dead player from the
# possible choices
scores.pop(index)
# Make sure to get the correct index post-pop
j = self.fitness_proportionate_selection(
scores, fitness_transformation=self.fitness_transformation
)
if j >= index:
j += 1
else:
j = self.fitness_proportionate_selection(
scores, fitness_transformation=self.fitness_transformation
)
return j
def fixation_check(self) -> bool:
"""
Checks if the population is all of a single type
Returns
-------
Boolean:
True if fixation has occurred (population all of a single type)
"""
classes = set(str(p) for p in self.players)
self.fixated = False
if len(classes) == 1:
# Set the winning strategy name variable
self.winning_strategy_name = str(self.players[0])
self.fixated = True
return self.fixated
def __next__(self) -> object:
"""
Iterate the population:
- play the round's matches
- chooses a player proportionally to fitness (total score) to reproduce
- mutate, if appropriate
- choose a player to be replaced
- update the population
Returns
-------
MoranProcess:
Returns itself with a new population
"""
# Check the exit condition, that all players are of the same type.
if self.stop_on_fixation and self.fixation_check():
raise StopIteration
if self.mode == "bd":
# Birth then death
j = self.birth()
i = self.death(j)
elif self.mode == "db":
# Death then birth
i = self.death()
self.players[i] = None
j = self.birth(i)
# Mutate and/or replace player i with clone of player j
self.players[i] = self.mutate(j)
# Record population.
self.populations.append(self.population_distribution())
return self
def _matchup_indices(self) -> Set[Tuple[int, int]]:
"""
Generate the matchup pairs.
Returns
-------
indices:
A set of 2 tuples of matchup pairs: the collection of all players
who play each other.
"""
indices = set() # type: Set
# For death-birth we only want the neighbors of the dead node
# The other calculations are unnecessary
if self.mode == "db":
source = self.index[self.dead]
self.dead = None
sources = sorted(self.interaction_graph.out_vertices(source))
else:
# birth-death is global
sources = sorted(self.locations)
for i, source in enumerate(sources):
for target in sorted(self.interaction_graph.out_vertices(source)):
j = self.index[target]
if (self.players[i] is None) or (self.players[j] is None):
continue
# Don't duplicate matches
if ((i, j) in indices) or ((j, i) in indices):
continue
indices.add((i, j))
return indices
def score_all(self) -> List:
"""Plays the next round of the process. Every player is paired up
against every other player and the total scores are recorded.
Returns
-------
scores:
List of scores for each player
"""
N = len(self.players)
scores = [0] * N
for i, j in self._matchup_indices():
player1 = self.players[i]
player2 = self.players[j]
match = self.match_class(
(player1, player2),
turns=self.turns,
prob_end=self.prob_end,
noise=self.noise,
game=self.game,
deterministic_cache=self.deterministic_cache,
seed=next(self._bulk_random),
)
match.play()
match_scores = match.final_score_per_turn()
scores[i] += match_scores[0]
scores[j] += match_scores[1]
self.score_history.append(scores)
return scores
def population_distribution(self) -> Counter:
"""Returns the population distribution of the last iteration.
Returns
-------
counter:
The counts of each strategy in the population of the last iteration
"""
player_names = [str(player) for player in self.players]
counter = Counter(player_names)
return counter
def __iter__(self) -> object:
"""
Returns
-------
self
"""
return self
def reset(self) -> None:
"""Reset the process to replay."""
self.winning_strategy_name = None
self.score_history = []
# Reset all the players
self.set_players()
def play(self) -> List[Counter]:
"""
Play the process out to completion. If played with mutation this will
not terminate.
Returns
-------
populations:
Returns a list of all the populations
"""
if not self.stop_on_fixation or self.mutation_rate != 0:
raise ValueError(
"MoranProcess.play() will never exit if mutation_rate is"
"nonzero or stop_on_fixation is False. Use iteration instead."
)
while True:
try:
self.__next__()
except StopIteration:
break
return self.populations
def __len__(self) -> int:
"""
Returns
-------
The length of the Moran process: the number of populations
"""
return len(self.populations)
def populations_plot(self, ax=None):
"""
Create a stackplot of the population distributions at each iteration of
the Moran process.
Parameters
----------------
ax: matplotlib axis
Allows the plot to be written to a given matplotlib axis.
Default is None.
Returns
-----------
A matplotlib axis object
"""
player_names = self.populations[0].keys()
if ax is None:
_, ax = plt.subplots()
else:
ax = ax
plot_data = []
labels = []
for name in player_names:
labels.append(name)
values = [counter[name] for counter in self.populations]
plot_data.append(values)
domain = range(len(values))
ax.stackplot(domain, plot_data, labels=labels)
ax.set_title("Moran Process Population by Iteration")
ax.set_xlabel("Iteration")
ax.set_ylabel("Number of Individuals")
ax.legend()
return ax
class ApproximateMoranProcess(MoranProcess):
"""
A class to approximate a Moran process based
on a distribution of potential Match outcomes.
Instead of playing the matches, the result is sampled
from a dictionary of player tuples to distribution of match outcomes
"""
def __init__(
self,
players: List[Player],
cached_outcomes: dict,
mutation_rate: float = 0,
seed: Optional[int] = None,
) -> None:
"""
Parameters
----------
players:
cached_outcomes:
Mapping tuples of players to instances of the moran.Pdf class.
mutation_rate:
The rate of mutation. Replicating players are mutated with
probability `mutation_rate`
"""
super(ApproximateMoranProcess, self).__init__(
players,
turns=0,
noise=0,
deterministic_cache=None,
mutation_rate=mutation_rate,
seed=seed,
)
self.cached_outcomes = cached_outcomes
def set_players(self) -> None:
"""Copy the initial players into the first population."""
self.players = []
for player in self.initial_players:
player.reset()
self.players.append(player)
self.populations = [self.population_distribution()]
def score_all(self) -> List:
"""Plays the next round of the process. Every player is paired up
against every other player and the total scores are obtained from the
cached outcomes.
Returns
-------
scores:
List of scores for each player
"""
N = len(self.players)
scores = [0] * N
for i in range(N):
for j in range(i + 1, N):
player_names = tuple(
[str(self.players[i]), str(self.players[j])]
)
cached_score = self._get_scores_from_cache(player_names)
scores[i] += cached_score[0]
scores[j] += cached_score[1]
self.score_history.append(scores)
return scores
def _get_scores_from_cache(self, player_names: Tuple) -> Tuple:
"""
Retrieve the scores from the players in the cache
Parameters
----------
player_names:
The names of the players
Returns
-------
scores:
The scores of the players in that particular match
"""
try:
match_scores = self.cached_outcomes[player_names].sample()
return match_scores
except KeyError: # If players are stored in opposite order
match_scores = self.cached_outcomes[player_names[::-1]].sample()
return match_scores[::-1] | PypiClean |
/2Keys-0.5.1.tar.gz/2Keys-0.5.1/twokeys/add_keyboard/add_keyboard.py | import asyncio
from os import path, listdir, getcwd, system
import colorful
from ..util.constants import KEYBOARDS_PATH_BASE, KEYBOARD_EVENT_FORMAT, KEYBOARD_EVENT_SIZE, SCRIPTS_ROOT, MODULE_NAME
from ..util.logger import Logger
from ..util.config import load_config
from ..watcher import AsyncKeyboard as AsyncKeyboardWatcher
logger = Logger("detect")
# Function to add keyboards (s is emphasised) from config
def add_keyboards(config):
for key, value in config["keyboards"].items():
logger.info("Running script to add keyboard for keyboard " + colorful.cyan(key) + "...")
print("") # Padding
system("cd " + getcwd() + " && python3 -m " + MODULE_NAME + " add " + key)
print("") # Padding
def add_keyboard(name, gen_handler, inputs_path):
# Check if paths not given
config = load_config()
if name == "" or name not in config["keyboards"]:
logger.warn("No keyboard supplied.")
logger.warn("Detection will be ran on all keyboards.")
logger.warn("To just generate daemons, use the 'daemon-gen' command")
logger.info("Running detection on all keyboards...")
return add_keyboards(config)
logger.info("Mapping keyboard " + name)
logger.info("Scanning for keyboards...")
if not path.isdir(inputs_path): # Make sure there's something to detect
logger.err("Couldn't scan for keyboards")
logger.err("Verify you have at least one keyboard plugged in")
logger.err("and the dir " + inputs_path + " exists")
logger.err("You can specify a custom path with the --inputs-path option")
exit()
# Scan
# From https://stackoverflow.com/questions/3207219/how-do-i-list-all-files-of-a-directory
keyboards = listdir(inputs_path)
logger.debug("Keyboards:")
logger.debug(keyboards)
logger.info("Press a button on the keyboard you want to map to register it.")
# Then watch all keyboards and ask for one to be pressed
keyboards_events = [AsyncKeyboardWatcher(keyboard_path, inputs_path) for keyboard_path in keyboards] # Keyboard watch classes for each input
handler = gen_handler(keyboards_events, name) # The handler needs access to keyboards_events, which it won't on exe in the watcher, as well as keyboard name
# Run
jobs = [keyboards_events[i].keyboard_watcher(handler) for i in range(0, len(keyboards))] # Create jobs list
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(jobs)) | PypiClean |
/KoreaTrain-0.0.1.tar.gz/KoreaTrain-0.0.1/koreatrain/koreatrain.py | from SRT import *
from korail2 import *
from .tools import get_time
from .constants import Platform
from .dataclass import Parameter, SRParameter, KorailParameter
from .errors import KoreaTrainError, KoreaTrainLoginError, KoreaTrainNotLoginError
class KoreaTrain:
def __init__(
self,
platform: Platform,
parameter: Parameter | None = None,
username: str | None = None,
password: str | None = None,
auto_login: bool = True,
feedback: bool = False
) -> None:
self.platform = platform
self.parameter = parameter
self.username = username
self.password = password
self.logged_in = False
self.service = None
if parameter is not None and not isinstance(parameter, Parameter):
raise TypeError('Invalid type: `parameter` must be a Parameter instance.')
if username is None and password is None:
auto_login = False
match platform:
case Platform.SR:
self.service = SRT(username, password, False, feedback)
case Platform.KORAIL:
self.service = Korail(username, password, False, feedback)
case _:
raise ValueError(f'Invalid value: invalid platform value ({platform}) has been received.')
if auto_login: self.login()
def __repr__(self) -> str:
return f'[{type(self).__name__}] platform: {self.platform}, parameter: {self.parameter}, logged_in: {self.logged_in}.'
def login(self, username: str | None = None, password: str | None = None) -> bool:
if username is None: username = self.username
if password is None: password = self.password
if username is None or password is None:
raise TypeError('Invalid type: the username or password cannot be None.')
self.logged_in = self.service.login(username, password)
return self.logged_in
def logout(self) -> bool:
self.service.logout()
return True
def set_parameter(self, parameter: Parameter):
if isinstance(parameter, Parameter): # Check if the base class of the parameter is the Parameter.
self.parameter = parameter
else:
raise TypeError('Invalid type: `parameter` must be a Parameter instance.')
def search_train(self, parameter: Parameter | None = None, available_only: bool = True) -> list:
if parameter is None:
parameter = self.parameter
if parameter is None or not isinstance(parameter, Parameter):
raise TypeError('Invalid type: `parameter` must be a Parameter instance.')
match self.platform:
case Platform.SR:
if type(parameter) is not SRParameter:
raise TypeError('Invalid type: only SRParameter can be used when the platform is specified as SR.')
return self.service.search_train(
dep=parameter.dep,
arr=parameter.arr,
date=parameter.date,
time=parameter.time,
time_limit=parameter.time_limit,
available_only=available_only
)
case Platform.KORAIL:
if type(parameter) is not KorailParameter:
raise TypeError('Invalid type: only KorailParameter can be used when the platform is specified as KORAIL.')
# TODO: Optimize this by calling multiple search_train instead of calling the search_train_allday.
trains = self.service.search_train_allday(
dep=parameter.dep,
arr=parameter.arr,
date=parameter.date,
time=parameter.time,
train_type=parameter.train_type,
passengers=parameter.passengers,
include_no_seats=(not available_only)
)
if parameter.time is None: parameter.time = get_time()
if parameter.time_limit is None:
return trains
else:
return [train for train in trains if int(parameter.time) <= int(train.dep_time) <= int(parameter.time_limit)]
def reserve(self, train, parameter: Parameter | None = None):
if not self.logged_in:
raise KoreaTrainNotLoginError()
if parameter is None:
parameter = self.parameter
if parameter is None or not isinstance(parameter, Parameter):
raise TypeError('Invalid type: `parameter` must be a Parameter instance.')
match self.platform:
case Platform.SR:
if type(parameter) is not SRParameter:
raise ValueError('Invalid parameter.')
return self.service.reserve(
train=train,
passengers=parameter.passengers,
special_seat=parameter.reserve_option,
window_seat=parameter.window
)
case Platform.KORAIL:
if type(parameter) is not KorailParameter:
raise ValueError('Invalid parameter.')
return self.service.reserve(
train=train,
passengers=parameter.passengers,
option=parameter.reserve_option
)
def get_reservations(self, paid_only: bool = False) -> list:
if not self.logged_in:
raise KoreaTrainNotLoginError()
match self.platform:
case Platform.SR:
return self.service.get_reservations(paid_only)
case Platform.KORAIL:
# TODO: paid_only option only works for SR. Implement one for Korail.
return self.service.reservations()
# def get_tickets(self):
# pass
def cancel(self, reservation) -> bool:
if not self.logged_in:
raise KoreaTrainNotLoginError()
return self.service.cancel(reservation) | PypiClean |
/FamcyDev-0.3.71-py3-none-any.whl/Famcy/node_modules/jquery/src/css/showHide.js | define( [
"../core",
"../data/var/dataPriv",
"../css/var/isHiddenWithinTree"
], function( jQuery, dataPriv, isHiddenWithinTree ) {
"use strict";
var defaultDisplayMap = {};
function getDefaultDisplay( elem ) {
var temp,
doc = elem.ownerDocument,
nodeName = elem.nodeName,
display = defaultDisplayMap[ nodeName ];
if ( display ) {
return display;
}
temp = doc.body.appendChild( doc.createElement( nodeName ) );
display = jQuery.css( temp, "display" );
temp.parentNode.removeChild( temp );
if ( display === "none" ) {
display = "block";
}
defaultDisplayMap[ nodeName ] = display;
return display;
}
function showHide( elements, show ) {
var display, elem,
values = [],
index = 0,
length = elements.length;
// Determine new display value for elements that need to change
for ( ; index < length; index++ ) {
elem = elements[ index ];
if ( !elem.style ) {
continue;
}
display = elem.style.display;
if ( show ) {
// Since we force visibility upon cascade-hidden elements, an immediate (and slow)
// check is required in this first loop unless we have a nonempty display value (either
// inline or about-to-be-restored)
if ( display === "none" ) {
values[ index ] = dataPriv.get( elem, "display" ) || null;
if ( !values[ index ] ) {
elem.style.display = "";
}
}
if ( elem.style.display === "" && isHiddenWithinTree( elem ) ) {
values[ index ] = getDefaultDisplay( elem );
}
} else {
if ( display !== "none" ) {
values[ index ] = "none";
// Remember what we're overwriting
dataPriv.set( elem, "display", display );
}
}
}
// Set the display of the elements in a second loop to avoid constant reflow
for ( index = 0; index < length; index++ ) {
if ( values[ index ] != null ) {
elements[ index ].style.display = values[ index ];
}
}
return elements;
}
jQuery.fn.extend( {
show: function() {
return showHide( this, true );
},
hide: function() {
return showHide( this );
},
toggle: function( state ) {
if ( typeof state === "boolean" ) {
return state ? this.show() : this.hide();
}
return this.each( function() {
if ( isHiddenWithinTree( this ) ) {
jQuery( this ).show();
} else {
jQuery( this ).hide();
}
} );
}
} );
return showHide;
} ); | PypiClean |
/Eureqa-1.76.0.tar.gz/Eureqa-1.76.0/eureqa/analysis/components/modal.py |
import os.path
from eureqa.analysis.analysis_file import AnalysisFile
from eureqa.analysis.components.modal_link import ModalLink
from eureqa.analysis.components.base import _Component
class Modal(_Component):
"""Represents a popup window (modal) which can contain other components.
Example:
# create a modal which is activated if a link is clicked
text_block = TextBlock("This text is inside the modal")
modal = Modal(title="This is the modal title", size='medium', icon_file_path='path/to/icon', component=text_block)
h = HtmlBlock('Click this link to open a modal: {0}'.format(analysis.html_ref(modal.link('link text'))))
layout.add_component(h)
:param str title: The title of the modal
:param str size: (optional) modal size. Options are 'small', 'medium' or 'large'
:param str icon_file_path: (optional) path to an icon file to display in the corner of the modal
:param Component component: The component to display in the modal
"""
_component_type_str = 'MODAL'
def __init__(self, title=None, size=None, icon_file_path=None, component=None,
_analysis=None, _component_id=None, _component_type=None):
self._title = title or ''
self._size = size or 'small'
if icon_file_path is not None:
self._icon_file_path = icon_file_path
if component is not None:
self._content_component = component
super(Modal, self).__init__(_analysis=_analysis, _component_id=_component_id,
_component_type=_component_type)
# call to self._associate may have been triggered by super.__init__ above
# so we set up the content component after that call, to get the component id if there is one
if hasattr(self, '_content_component') and hasattr(component, '_component_id'):
self._content_component_id = component._component_id
@property
def content_component_id(self):
"""The id of the component to be displayed in the modal
:rtype: str
"""
return getattr(self, "_content_component_id", None)
@property
def title(self):
"""The title of the modal
:rtype: str
"""
return getattr(self, "_title", None)
@property
def size(self):
"""The size of the modal
:rtype: str
"""
return getattr(self, "_size", None)
@property
def icon_file_url(self):
"""The url of an icon file to be displayed in the corner of the modal
:rtype: str
"""
return getattr(self, "_icon_file_url", None)
@property
def icon_file_id(self):
"""The id of an icon file to be displayed in the corner of the modal
:rtype: str
"""
return getattr(self, "_icon_file_id", None)
def _walk_children(self):
if hasattr(self, "_content_component"):
yield self._content_component
def _register(self, analysis):
updated_content = False
if hasattr(self, '_content_component'):
self._content_component_id = self._content_component._component_id
updated_content = True
if hasattr(self, '_icon_file_path') and not hasattr(self, "_icon_file_url"):
icon_file_name = os.path.basename(self._icon_file_path)
icon_file = open(self._icon_file_path, 'rb')
self._icon_file = AnalysisFile.create(analysis, icon_file, filename=icon_file_name)
self._icon_file_url = ("/api/%s/analysis/%s/files/%s" % (analysis._organization, analysis._id, self._icon_file._file_id))
self._icon_file_id = self._icon_file._file_id
updated_content = True
super(Modal, self)._register(analysis)
def _associate_with_table(self, analysis):
content_json = []
if hasattr(self, '_content_component'):
content_json += self._content_component._associate_with_table(analysis)
self._content_component_id = self._content_component._component_id
if hasattr(self, '_icon_file_path'):
icon_file_name = os.path.basename(self._icon_file_path)
icon_file = open(self._icon_file_path, 'rb')
self._icon_file = AnalysisFile.create(analysis, icon_file, filename=icon_file_name)
self._icon_file_url = ("/api/%s/analysis/%s/files/%s" % (analysis._organization, analysis._id, self._icon_file._file_id))
self._icon_file_id = self._icon_file._file_id
return super(Modal, self)._associate_with_table(analysis) + content_json
def _fields(self):
return super(Modal, self)._fields() + [ 'content_component_id', 'title', 'size', 'icon_file_url', 'icon_file_id' ]
def link(self, link_text=None):
"""
Returns a ModalLink component which represents a link to this modal
:param str link_text: (optional) link text to use in the ModalLink instead of default text
:rtype: eureqa.analysis.components.modal_link.ModalLink
"""
return ModalLink(modal=self, link_text=link_text) | PypiClean |
/Flask_AdminLTE3-1.0.9-py3-none-any.whl/flask_adminlte3/static/plugins/moment/locale/de-ch.js |
;(function (global, factory) {
typeof exports === 'object' && typeof module !== 'undefined'
&& typeof require === 'function' ? factory(require('../moment')) :
typeof define === 'function' && define.amd ? define(['../moment'], factory) :
factory(global.moment)
}(this, (function (moment) { 'use strict';
//! moment.js locale configuration
function processRelativeTime(number, withoutSuffix, key, isFuture) {
var format = {
m: ['eine Minute', 'einer Minute'],
h: ['eine Stunde', 'einer Stunde'],
d: ['ein Tag', 'einem Tag'],
dd: [number + ' Tage', number + ' Tagen'],
w: ['eine Woche', 'einer Woche'],
M: ['ein Monat', 'einem Monat'],
MM: [number + ' Monate', number + ' Monaten'],
y: ['ein Jahr', 'einem Jahr'],
yy: [number + ' Jahre', number + ' Jahren'],
};
return withoutSuffix ? format[key][0] : format[key][1];
}
var deCh = moment.defineLocale('de-ch', {
months: 'Januar_Februar_März_April_Mai_Juni_Juli_August_September_Oktober_November_Dezember'.split(
'_'
),
monthsShort: 'Jan._Feb._März_Apr._Mai_Juni_Juli_Aug._Sep._Okt._Nov._Dez.'.split(
'_'
),
monthsParseExact: true,
weekdays: 'Sonntag_Montag_Dienstag_Mittwoch_Donnerstag_Freitag_Samstag'.split(
'_'
),
weekdaysShort: 'So_Mo_Di_Mi_Do_Fr_Sa'.split('_'),
weekdaysMin: 'So_Mo_Di_Mi_Do_Fr_Sa'.split('_'),
weekdaysParseExact: true,
longDateFormat: {
LT: 'HH:mm',
LTS: 'HH:mm:ss',
L: 'DD.MM.YYYY',
LL: 'D. MMMM YYYY',
LLL: 'D. MMMM YYYY HH:mm',
LLLL: 'dddd, D. MMMM YYYY HH:mm',
},
calendar: {
sameDay: '[heute um] LT [Uhr]',
sameElse: 'L',
nextDay: '[morgen um] LT [Uhr]',
nextWeek: 'dddd [um] LT [Uhr]',
lastDay: '[gestern um] LT [Uhr]',
lastWeek: '[letzten] dddd [um] LT [Uhr]',
},
relativeTime: {
future: 'in %s',
past: 'vor %s',
s: 'ein paar Sekunden',
ss: '%d Sekunden',
m: processRelativeTime,
mm: '%d Minuten',
h: processRelativeTime,
hh: '%d Stunden',
d: processRelativeTime,
dd: processRelativeTime,
w: processRelativeTime,
ww: '%d Wochen',
M: processRelativeTime,
MM: processRelativeTime,
y: processRelativeTime,
yy: processRelativeTime,
},
dayOfMonthOrdinalParse: /\d{1,2}\./,
ordinal: '%d.',
week: {
dow: 1, // Monday is the first day of the week.
doy: 4, // The week that contains Jan 4th is the first week of the year.
},
});
return deCh;
}))); | PypiClean |
/Argonaut-0.3.4.tar.gz/Argonaut-0.3.4/argonaut/public/ckeditor/_source/plugins/smiley/plugin.js | /*
Copyright (c) 2003-2010, CKSource - Frederico Knabben. All rights reserved.
For licensing, see LICENSE.html or http://ckeditor.com/license
*/
CKEDITOR.plugins.add( 'smiley',
{
requires : [ 'dialog' ],
init : function( editor )
{
editor.config.smiley_path = editor.config.smiley_path || ( this.path + 'images/' );
editor.addCommand( 'smiley', new CKEDITOR.dialogCommand( 'smiley' ) );
editor.ui.addButton( 'Smiley',
{
label : editor.lang.smiley.toolbar,
command : 'smiley'
});
CKEDITOR.dialog.add( 'smiley', this.path + 'dialogs/smiley.js' );
}
} );
/**
* The base path used to build the URL for the smiley images. It must end with
* a slash.
* @name CKEDITOR.config.smiley_path
* @type String
* @default {@link CKEDITOR.basePath} + 'plugins/smiley/images/'
* @example
* config.smiley_path = 'http://www.example.com/images/smileys/';
* @example
* config.smiley_path = '/images/smileys/';
*/
/**
* The file names for the smileys to be displayed. These files must be
* contained inside the URL path defined with the
* {@link CKEDITOR.config.smiley_path} setting.
* @type Array
* @default (see example)
* @example
* // This is actually the default value.
* config.smiley_images = [
* 'regular_smile.gif','sad_smile.gif','wink_smile.gif','teeth_smile.gif','confused_smile.gif','tounge_smile.gif',
* 'embaressed_smile.gif','omg_smile.gif','whatchutalkingabout_smile.gif','angry_smile.gif','angel_smile.gif','shades_smile.gif',
* 'devil_smile.gif','cry_smile.gif','lightbulb.gif','thumbs_down.gif','thumbs_up.gif','heart.gif',
* 'broken_heart.gif','kiss.gif','envelope.gif'];
*/
CKEDITOR.config.smiley_images = [
'regular_smile.gif','sad_smile.gif','wink_smile.gif','teeth_smile.gif','confused_smile.gif','tounge_smile.gif',
'embaressed_smile.gif','omg_smile.gif','whatchutalkingabout_smile.gif','angry_smile.gif','angel_smile.gif','shades_smile.gif',
'devil_smile.gif','cry_smile.gif','lightbulb.gif','thumbs_down.gif','thumbs_up.gif','heart.gif',
'broken_heart.gif','kiss.gif','envelope.gif'];
/**
* The description to be used for each of the smileys defined in the
* {@link CKEDITOR.config.smiley_images} setting. Each entry in this array list
* must match its relative pair in the {@link CKEDITOR.config.smiley_images}
* setting.
* @type Array
* @default The textual descriptions of smiley.
* @example
* // Default settings.
* config.smiley_descriptions =
* [
* 'smiley', 'sad', 'wink', 'laugh', 'frown', 'cheeky', 'blush', 'surprise',
* 'indecision', 'angry', 'angel', 'cool', 'devil', 'crying', 'enlightened', 'no',
* 'yes', 'heart', 'broken heart', 'kiss', 'mail'
* ];
* @example
* // Use textual emoticons as description.
* config.smiley_descriptions =
* [
* ':)', ':(', ';)', ':D', ':/', ':P', ':*)', ':-o',
* ':|', '>:(', 'o:)', '8-)', '>:-)', ';(', '', '', '',
* '', '', ':-*', ''
* ];
*/
CKEDITOR.config.smiley_descriptions =
[
'smiley', 'sad', 'wink', 'laugh', 'frown', 'cheeky', 'blush', 'surprise',
'indecision', 'angry', 'angel', 'cool', 'devil', 'crying', 'enlightened', 'no',
'yes', 'heart', 'broken heart', 'kiss', 'mail'
];
/**
* The number of columns to be generated by the smilies matrix.
* @name CKEDITOR.config.smiley_columns
* @type Number
* @default 8
* @since 3.3.2
* @example
* config.smiley_columns = 6;
*/ | PypiClean |
/Flask-Mix-0.0.2.tar.gz/Flask-Mix-0.0.2/flask_mix.py | import json
import os
from flask import current_app
class Mix:
"""
Mix extends a Flask app by adding a `mix` template helper for including
static files managed by Laravel Mix.
See https://laravel-mix.com for more information on Laravel Mix.
"""
def __init__(self, app=None):
self.app = app
self.assets = ''
self.assets_url = ''
if app is not None:
self.init_app(app)
def init_app(self, app):
"""
Initializes the extension. The assets and optional asset URL are loaded
from disk when the app starts. In debug mode, the assets and asset url
are reloaded from disk before each request.
"""
app.config.setdefault('MIX_ASSETS_BASE_URL', '')
app.config.setdefault('MIX_MANIFEST_PATH',
os.path.join(app.static_folder,
'mix-manifest.json'))
app.config.setdefault('MIX_HOT_PATH',
os.path.join(app.static_folder, 'hot'))
self.get_assets(app)
self.get_assets_base_url(app)
if app.config.get('DEBUG'):
app.before_request(self.reload)
app.add_template_global(self.mix)
def reload(self):
"""
Reloads the assets and assets URL from disk. Should only be used in
DEBUG mode.
"""
self.get_assets(current_app)
self.get_assets_base_url(current_app)
def get_assets(self, app):
"""
Loads the asset map from the mix manifest file on disk.
"""
manifest_path = app.config.get('MIX_MANIFEST_PATH')
try:
with app.open_resource(manifest_path, 'r') as manifest:
self.assets = json.load(manifest)
except IOError:
raise RuntimeError(
"MIX_MANIFEST_PATH requires a valid mix-manifest.json file"
)
def get_assets_base_url(self, app):
"""
Loads the assets url from the mix hot file on disk or from the
MIX_ASSETS_BASE_URL environment variable.
"""
hot_path = app.config.get('MIX_HOT_PATH')
try:
with app.open_resource(hot_path, 'r') as hot_file:
base_url = hot_file.read().strip()
if base_url.endswith('/'):
base_url = base_url[:-1]
self.assets_base_url = base_url
except:
self.assets_base_url = app.config.get('MIX_ASSETS_BASE_URL')
def mix(self, file):
"""
Method exposed to templates that can be given the path to a source
asset and will return the path to built static asset.
"""
if not self.assets:
return ''
return self.assets_base_url + self.assets.get(file) | PypiClean |
/ClueMapperSecure-0.6.3.tar.gz/ClueMapperSecure-0.6.3/src/clue/secure/htpasswd.py |
# Adapted from:
# http://svn.edgewall.org/repos/trac/trunk/contrib/htpasswd.py
import crypt
import os
import random
class HtpasswdFile:
"""A class for manipulating htpasswd files.
>>> import tempfile
>>> h, t = tempfile.mkstemp()
>>> passwd = HtpasswdFile(t, True)
>>> passwd.update('abc', 'def')
>>> passwd.update('foo', 'bar')
>>> passwd.update('abc', 'xyz')
>>> passwd.delete('abc')
>>> passwd.save()
>>> passwd = HtpasswdFile(t, False)
>>> os.remove(t)
>>> passwd = HtpasswdFile(t, False)
Traceback (most recent call last):
Exception: ... does not exist
"""
SALT_CHARS = 'abcdefghijklmnopqrstuvwxyz' \
'ABCDEFGHIJKLMNOPQRSTUVWXYZ' \
'0123456789/.'
def __init__(self, filename, create=False):
self.entries = []
self.filename = filename
if not create:
if os.path.exists(self.filename):
self.load()
else:
raise Exception("%s does not exist" % self.filename)
def gen_salt(self):
return random.choice(self.SALT_CHARS) + random.choice(self.SALT_CHARS)
def load(self):
"""Read the htpasswd file into memory."""
lines = open(self.filename, 'r').readlines()
self.entries = []
for line in lines:
username, pwhash = line.split(':')
entry = [username, pwhash.rstrip()]
self.entries.append(entry)
def save(self):
"""Write the htpasswd file to disk"""
open(self.filename, 'w').writelines(["%s:%s\n" % (entry[0], entry[1])
for entry in self.entries])
def update(self, username, password):
"""Replace the entry for the given user, or add it if new."""
pwhash = crypt.crypt(password, self.gen_salt())
matching_entries = [entry for entry in self.entries
if entry[0] == username]
if matching_entries:
matching_entries[0][1] = pwhash
else:
self.entries.append([username, pwhash])
def delete(self, username):
"""Remove the entry for the given user."""
self.entries = [entry for entry in self.entries
if entry[0] != username] | PypiClean |
/GloboNetworkAPI-0.9.6.tar.gz/GloboNetworkAPI-0.9.6/networkapiclient/ApiVipRequest.py | import urllib
from networkapiclient.ApiGenericClient import ApiGenericClient
from networkapiclient.utils import build_uri_with_ids
class ApiVipRequest(ApiGenericClient):
def __init__(self, networkapi_url, user, password, user_ldap=None, log_level='INFO'):
"""Class constructor receives parameters to connect to the networkAPI.
:param networkapi_url: URL to access the network API.
:param user: User for authentication.
:param password: Password for authentication.
"""
super(ApiVipRequest, self).__init__(
networkapi_url,
user,
password,
user_ldap,
log_level
)
def list_environment_by_environmet_vip(self, environment_vip_id):
"""
"""
uri = 'api/vip/list/environment/by/environment/vip/%s/' % (
environment_vip_id)
return super(ApiVipRequest, self).get(uri)
#######################
# API V3
#######################
def option_vip_by_environmentvip(self, environment_vip_id):
"""
List Option Vip by Environment Vip
param environment_vip_id: Id of Environment Vip
"""
uri = 'api/v3/option-vip/environment-vip/%s/' % environment_vip_id
return super(ApiVipRequest, self).get(uri)
def get_vip_request_details(self, vip_request_id):
"""
Method to get details of vip request
param vip_request_id: vip_request id
"""
uri = 'api/v3/vip-request/details/%s/' % vip_request_id
return super(ApiVipRequest, self).get(uri)
def search_vip_request_details(self, search):
"""
Method to list vip request
param search: search
"""
uri = 'api/v3/vip-request/details/?%s' % urllib.urlencode(
{'search': search})
return super(ApiVipRequest, self).get(uri)
def get_vip_request(self, vip_request_id):
"""
Method to get vip request
param vip_request_id: vip_request id
"""
uri = 'api/v3/vip-request/%s/' % vip_request_id
return super(ApiVipRequest, self).get(uri)
def search_vip_request(self, search):
"""
Method to list vip request
param search: search
"""
uri = 'api/v3/vip-request/?%s' % urllib.urlencode({'search': search})
return super(ApiVipRequest, self).get(uri)
def save_vip_request(self, vip_request):
"""
Method to save vip request
param vip_request: vip_request object
"""
uri = 'api/v3/vip-request/'
data = dict()
data['vips'] = list()
data['vips'].append(vip_request)
return super(ApiVipRequest, self).post(uri, data)
def update_vip_request(self, vip_request, vip_request_id):
"""
Method to update vip request
param vip_request: vip_request object
param vip_request_id: vip_request id
"""
uri = 'api/v3/vip-request/%s/' % vip_request_id
data = dict()
data['vips'] = list()
data['vips'].append(vip_request)
return super(ApiVipRequest, self).put(uri, data)
def delete_vip_request(self, vip_request_ids):
"""
Method to delete vip request
param vip_request_ids: vip_request ids
"""
uri = 'api/v3/vip-request/%s/' % vip_request_ids
return super(ApiVipRequest, self).delete(uri)
def create_vip(self, vip_request_ids):
"""
Method to create vip request
param vip_request_ids: vip_request ids
"""
uri = 'api/v3/vip-request/deploy/%s/' % vip_request_ids
return super(ApiVipRequest, self).post(uri)
def update_vip(self, vip_request, vip_request_id):
"""
Method to update vip request
param vip_request: vip_request object
param vip_request_id: vip_request id
"""
uri = 'api/v3/vip-request/deploy/%s/' % vip_request_id
data = dict()
data['vips'] = list()
data['vips'].append(vip_request)
return super(ApiVipRequest, self).put(uri, data)
def remove_vip(self, vip_request_ids):
"""
Method to delete vip request
param vip_request_ids: vip_request ids
"""
uri = 'api/v3/vip-request/deploy/%s/' % vip_request_ids
return super(ApiVipRequest, self).delete(uri)
def search(self, **kwargs):
"""
Method to search vip's based on extends search.
:param search: Dict containing QuerySets to find vip's.
:param include: Array containing fields to include on response.
:param exclude: Array containing fields to exclude on response.
:param fields: Array containing fields to override default fields.
:param kind: Determine if result will be detailed ('detail') or basic ('basic').
:return: Dict containing vip's
"""
return super(ApiVipRequest, self).get(self.prepare_url('api/v3/vip-request/',
kwargs))
def get(self, ids, **kwargs):
"""
Method to get vips by their id's
:param ids: List containing identifiers of vip's
:param include: Array containing fields to include on response.
:param exclude: Array containing fields to exclude on response.
:param fields: Array containing fields to override default fields.
:param kind: Determine if result will be detailed ('detail') or basic ('basic').
:return: Dict containing vip's
"""
url = build_uri_with_ids('api/v3/vip-request/%s/', ids)
return super(ApiVipRequest, self).get(self.prepare_url(url, kwargs))
def delete(self, ids):
"""
Method to delete vip's by their id's
:param ids: Identifiers of vip's
:return: None
"""
url = build_uri_with_ids('api/v3/vip-request/%s/', ids)
return super(ApiVipRequest, self).delete(url)
def update(self, vips):
"""
Method to update vip's
:param vips: List containing vip's desired to updated
:return: None
"""
data = {'vips': vips}
vips_ids = [str(vip.get('id')) for vip in vips]
return super(ApiVipRequest, self).put('api/v3/vip-request/%s/' %
';'.join(vips_ids), data)
def create(self, vips):
"""
Method to create vip's
:param vips: List containing vip's desired to be created on database
:return: None
"""
data = {'vips': vips}
return super(ApiVipRequest, self).post('api/v3/vip-request/', data)
def deploy(self, ids):
"""
Method to deploy vip's
:param vips: List containing vip's desired to be deployed on equipment
:return: None
"""
url = build_uri_with_ids('api/v3/vip-request/deploy/%s/', ids)
return super(ApiVipRequest, self).post(url)
def undeploy(self, ids, clean_up=0):
"""
Method to undeploy vip's
:param vips: List containing vip's desired to be undeployed on equipment
:return: None
"""
url = build_uri_with_ids('api/v3/vip-request/deploy/%s/?cleanup=%s', ids, clean_up)
return super(ApiVipRequest, self).delete(url)
def redeploy(self, vips):
"""
Method to redeploy vip's
:param vips: List containing vip's desired to updated on equipment
:return: None
"""
data = {'vips': vips}
vips_ids = [str(vip.get('id')) for vip in vips]
return super(ApiVipRequest, self).put('api/v3/vip-request/deploy/%s/' %
';'.join(vips_ids), data) | PypiClean |
/MaterialDjango-0.2.5.tar.gz/MaterialDjango-0.2.5/bower_components/prism/components/prism-rest.js | Prism.languages.rest = {
'table': [
{
pattern: /(\s*)(?:\+[=-]+)+\+(?:\r?\n|\r)(?:\1(?:[+|].+)+[+|](?:\r?\n|\r))+\1(?:\+[=-]+)+\+/,
lookbehind: true,
inside: {
'punctuation': /\||(?:\+[=-]+)+\+/
}
},
{
pattern: /(\s*)(?:=+ +)+=+(?:(?:\r?\n|\r)\1.+)+(?:\r?\n|\r)\1(?:=+ +)+=+(?=(?:\r?\n|\r){2}|\s*$)/,
lookbehind: true,
inside: {
'punctuation': /[=-]+/
}
}
],
// Directive-like patterns
'substitution-def': {
pattern: /(^\s*\.\. )\|(?:[^|\s](?:[^|]*[^|\s])?)\| [^:]+::/m,
lookbehind: true,
inside: {
'substitution': {
pattern: /^\|(?:[^|\s]|[^|\s][^|]*[^|\s])\|/,
alias: 'attr-value',
inside: {
'punctuation': /^\||\|$/
}
},
'directive': {
pattern: /( +)[^:]+::/,
lookbehind: true,
alias: 'function',
inside: {
'punctuation': /::$/
}
}
}
},
'link-target': [
{
pattern: /(^\s*\.\. )\[[^\]]+\]/m,
lookbehind: true,
alias: 'string',
inside: {
'punctuation': /^\[|\]$/
}
},
{
pattern: /(^\s*\.\. )_(?:`[^`]+`|(?:[^:\\]|\\.)+):/m,
lookbehind: true,
alias: 'string',
inside: {
'punctuation': /^_|:$/
}
}
],
'directive': {
pattern: /(^\s*\.\. )[^:]+::/m,
lookbehind: true,
alias: 'function',
inside: {
'punctuation': /::$/
}
},
'comment': {
// The two alternatives try to prevent highlighting of blank comments
pattern: /(^\s*\.\.)(?:(?: .+)?(?:(?:\r?\n|\r).+)+| .+)(?=(?:\r?\n|\r){2}|$)/m,
lookbehind: true
},
'title': [
// Overlined and underlined
{
pattern: /^(([!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~])\2+)(?:\r?\n|\r).+(?:\r?\n|\r)\1$/m,
inside: {
'punctuation': /^[!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~]+|[!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~]+$/,
'important': /.+/
}
},
// Underlined only
{
pattern: /(^|(?:\r?\n|\r){2}).+(?:\r?\n|\r)([!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~])\2+(?=\r?\n|\r|$)/,
lookbehind: true,
inside: {
'punctuation': /[!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~]+$/,
'important': /.+/
}
}
],
'hr': {
pattern: /((?:\r?\n|\r){2})([!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~])\2{3,}(?=(?:\r?\n|\r){2})/,
lookbehind: true,
alias: 'punctuation'
},
'field': {
pattern: /(^\s*):[^:\r\n]+:(?= )/m,
lookbehind: true,
alias: 'attr-name'
},
'command-line-option': {
pattern: /(^\s*)(?:[+-][a-z\d]|(?:--|\/)[a-z\d-]+)(?:[ =](?:[a-z][\w-]*|<[^<>]+>))?(?:, (?:[+-][a-z\d]|(?:--|\/)[a-z\d-]+)(?:[ =](?:[a-z][\w-]*|<[^<>]+>))?)*(?=(?:\r?\n|\r)? {2,}\S)/im,
lookbehind: true,
alias: 'symbol'
},
'literal-block': {
pattern: /::(?:\r?\n|\r){2}([ \t]+).+(?:(?:\r?\n|\r)\1.+)*/,
inside: {
'literal-block-punctuation': {
pattern: /^::/,
alias: 'punctuation'
}
}
},
'quoted-literal-block': {
pattern: /::(?:\r?\n|\r){2}([!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~]).*(?:(?:\r?\n|\r)\1.*)*/,
inside: {
'literal-block-punctuation': {
pattern: /^(?:::|([!"#$%&'()*+,\-.\/:;<=>?@\[\\\]^_`{|}~])\1*)/m,
alias: 'punctuation'
}
}
},
'list-bullet': {
pattern: /(^\s*)(?:[*+\-•‣⁃]|\(?(?:\d+|[a-z]|[ivxdclm]+)\)|(?:\d+|[a-z]|[ivxdclm]+)\.)(?= )/im,
lookbehind: true,
alias: 'punctuation'
},
'doctest-block': {
pattern: /(^\s*)>>> .+(?:(?:\r?\n|\r).+)*/m,
lookbehind: true,
inside: {
'punctuation': /^>>>/
}
},
'inline': [
{
pattern: /(^|[\s\-:\/'"<(\[{])(?::[^:]+:`.*?`|`.*?`:[^:]+:|(\*\*?|``?|\|)(?!\s).*?[^\s]\2(?=[\s\-.,:;!?\\\/'")\]}]|$))/m,
lookbehind: true,
inside: {
'bold': {
pattern: /(^\*\*).+(?=\*\*$)/,
lookbehind: true
},
'italic': {
pattern: /(^\*).+(?=\*$)/,
lookbehind: true
},
'inline-literal': {
pattern: /(^``).+(?=``$)/,
lookbehind: true,
alias: 'symbol'
},
'role': {
pattern: /^:[^:]+:|:[^:]+:$/,
alias: 'function',
inside: {
'punctuation': /^:|:$/
}
},
'interpreted-text': {
pattern: /(^`).+(?=`$)/,
lookbehind: true,
alias: 'attr-value'
},
'substitution': {
pattern: /(^\|).+(?=\|$)/,
lookbehind: true,
alias: 'attr-value'
},
'punctuation': /\*\*?|``?|\|/
}
}
],
'link': [
{
pattern: /\[[^\]]+\]_(?=[\s\-.,:;!?\\\/'")\]}]|$)/,
alias: 'string',
inside: {
'punctuation': /^\[|\]_$/
}
},
{
pattern: /(?:\b[a-z\d](?:[_.:+]?[a-z\d]+)*_?_|`[^`]+`_?_|_`[^`]+`)(?=[\s\-.,:;!?\\\/'")\]}]|$)/i,
alias: 'string',
inside: {
'punctuation': /^_?`|`$|`?_?_$/
}
}
],
// Line block start,
// quote attribution,
// explicit markup start,
// and anonymous hyperlink target shortcut (__)
'punctuation': {
pattern: /(^\s*)(?:\|(?= |$)|(?:---?|—|\.\.|__)(?= )|\.\.$)/m,
lookbehind: true
}
}; | PypiClean |
/Flask-Migrate-4.0.4.tar.gz/Flask-Migrate-4.0.4/src/flask_migrate/templates/aioflask-multidb/env.py | import asyncio
import logging
from logging.config import fileConfig
from sqlalchemy import MetaData
from flask import current_app
from alembic import context
USE_TWOPHASE = False
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.
config = context.config
# Interpret the config file for Python logging.
# This line sets up loggers basically.
fileConfig(config.config_file_name)
logger = logging.getLogger('alembic.env')
def get_engine(bind_key=None):
try:
# this works with Flask-SQLAlchemy<3 and Alchemical
return current_app.extensions['migrate'].db.get_engine(bind=bind_key)
except TypeError:
# this works with Flask-SQLAlchemy>=3
return current_app.extensions['migrate'].db.engines.get(bind_key)
def get_engine_url(bind_key=None):
try:
return get_engine(bind_key).url.render_as_string(
hide_password=False).replace('%', '%%')
except AttributeError:
return str(get_engine(bind_key).url).replace('%', '%%')
# add your model's MetaData object here
# for 'autogenerate' support
# from myapp import mymodel
# target_metadata = mymodel.Base.metadata
config.set_main_option('sqlalchemy.url', get_engine_url())
bind_names = []
if current_app.config.get('SQLALCHEMY_BINDS') is not None:
bind_names = list(current_app.config['SQLALCHEMY_BINDS'].keys())
else:
get_bind_names = getattr(current_app.extensions['migrate'].db,
'bind_names', None)
if get_bind_names:
bind_names = get_bind_names()
for bind in bind_names:
context.config.set_section_option(
bind, "sqlalchemy.url", get_engine_url(bind_key=bind))
target_db = current_app.extensions['migrate'].db
# other values from the config, defined by the needs of env.py,
# can be acquired:
# my_important_option = config.get_main_option("my_important_option")
# ... etc.
def get_metadata(bind):
"""Return the metadata for a bind."""
if bind == '':
bind = None
if hasattr(target_db, 'metadatas'):
return target_db.metadatas[bind]
# legacy, less flexible implementation
m = MetaData()
for t in target_db.metadata.tables.values():
if t.info.get('bind_key') == bind:
t.tometadata(m)
return m
def run_migrations_offline():
"""Run migrations in 'offline' mode.
This configures the context with just a URL
and not an Engine, though an Engine is acceptable
here as well. By skipping the Engine creation
we don't even need a DBAPI to be available.
Calls to context.execute() here emit the given string to the
script output.
"""
# for the --sql use case, run migrations for each URL into
# individual files.
engines = {
'': {
'url': context.config.get_main_option('sqlalchemy.url')
}
}
for name in bind_names:
engines[name] = rec = {}
rec['url'] = context.config.get_section_option(name, "sqlalchemy.url")
for name, rec in engines.items():
logger.info("Migrating database %s" % (name or '<default>'))
file_ = "%s.sql" % name
logger.info("Writing output to %s" % file_)
with open(file_, 'w') as buffer:
context.configure(
url=rec['url'],
output_buffer=buffer,
target_metadata=get_metadata(name),
literal_binds=True,
)
with context.begin_transaction():
context.run_migrations(engine_name=name)
def do_run_migrations(_, engines):
# this callback is used to prevent an auto-migration from being generated
# when there are no changes to the schema
# reference: http://alembic.zzzcomputing.com/en/latest/cookbook.html
def process_revision_directives(context, revision, directives):
if getattr(config.cmd_opts, 'autogenerate', False):
script = directives[0]
if len(script.upgrade_ops_list) >= len(bind_names) + 1:
empty = True
for upgrade_ops in script.upgrade_ops_list:
if not upgrade_ops.is_empty():
empty = False
if empty:
directives[:] = []
logger.info('No changes in schema detected.')
for name, rec in engines.items():
rec['sync_connection'] = conn = rec['connection']._sync_connection()
if USE_TWOPHASE:
rec['transaction'] = conn.begin_twophase()
else:
rec['transaction'] = conn.begin()
try:
for name, rec in engines.items():
logger.info("Migrating database %s" % (name or '<default>'))
context.configure(
connection=rec['sync_connection'],
upgrade_token="%s_upgrades" % name,
downgrade_token="%s_downgrades" % name,
target_metadata=get_metadata(name),
process_revision_directives=process_revision_directives,
**current_app.extensions['migrate'].configure_args
)
context.run_migrations(engine_name=name)
if USE_TWOPHASE:
for rec in engines.values():
rec['transaction'].prepare()
for rec in engines.values():
rec['transaction'].commit()
except: # noqa: E722
for rec in engines.values():
rec['transaction'].rollback()
raise
finally:
for rec in engines.values():
rec['sync_connection'].close()
async def run_migrations_online():
"""Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
"""
# for the direct-to-DB use case, start a transaction on all
# engines, then run all migrations, then commit all transactions.
engines = {
'': {'engine': get_engine()}
}
for name in bind_names:
engines[name] = rec = {}
rec['engine'] = get_engine(bind_key=name)
for name, rec in engines.items():
engine = rec['engine']
rec['connection'] = await engine.connect().start()
await engines['']['connection'].run_sync(do_run_migrations, engines)
for rec in engines.values():
await rec['connection'].close()
if context.is_offline_mode():
run_migrations_offline()
else:
asyncio.get_event_loop().run_until_complete(run_migrations_online()) | PypiClean |
/FreeGS-0.8.0-py3-none-any.whl/freegs/_divgeo.py | import numpy as np
from freeqdsk._fileutils import ChunkOutput, write_1d, write_2d
def write(data, fh, label=None):
"""
Write a DivGeo file, given a dictionary of data
data - dictionary
nx, ny Number of points in R (x), Z (y)
rcentr Reference value of R
bcentr Vacuum toroidal magnetic field at rcentr
sibdry Poloidal flux psi at plasma boundary
either:
r[nx] 1D array of R values
or
rdim Size of the R dimension
rleft Innermost R point
either:
z[ny] 1D array of Z values
or
zdim Size of the Z dimension
zmid Middle of the Z dimension
"""
# Write header
fh.write(
""" jm := no. of grid points in radial direction;
km := no. of grid points in vertical direction;
r := radial coordinates of grid points [m];
z := vertical coordinates of grid points [m];
psi := flux per radiant at grid points [Wb/rad];
psib := psi at plasma boundary [Wb/rad];
btf := toroidal magnetic field [t];
rtf := major radius at which btf is specified [m];
jm = {nx:d} ;
km = {ny:d} ;
psib = {sibdry:1.15E} Wb/rad;
btf = {bcentr:1.14f} t;
rtf = {rcentr:1.14f} m;
""".format(
**data
)
)
try:
r = data["r"]
except KeyError:
# No "r" in the dictionary
# use rdim, rleft and nx (from eqdsk)
Rmin = data["rleft"]
Rmax = data["rleft"] + data["rdim"]
nx = data["nx"]
dR = (Rmax - Rmin) / (nx - 1)
r = np.arange(nx) * dR + Rmin
try:
z = data["z"]
except KeyError:
# No "z" in the dictionary
# use zdim, zmid and ny (from eqdsk)
Zmin = data["zmid"] - 0.5 * data["zdim"]
Zmax = data["zmid"] + 0.5 * data["zdim"]
ny = data["ny"]
dZ = (Zmax - Zmin) / (ny - 1)
z = np.arange(ny) * dZ + Zmin
# Now write r and z
fh.write(" r(1:jm);\n")
co = ChunkOutput(fh, chunksize=5, extraspaces=3)
write_1d(r, co)
co.newline()
fh.write(" \n z(1:km);\n")
write_1d(z, co)
co.newline()
fh.write(" \n ((psi(j,k)-psib,j=1,jm),k=1,km)\n")
write_2d(data["psi"] - data["sibdry"], co)
co.newline() | PypiClean |
/LARRY_dataset-0.0.2rc0-py3-none-any.whl/larry/_datasets/klein_lab_pp_recipe/_remove_cell_cycle_correlated_genes.py | from tqdm.notebook import tqdm
import numpy as np
import scipy
# -- import local dependencies: --------------------------------------------------
from ._cell_cycle_genes import cell_cycle_genes
from ..._utils import sparse_zscore
def remove_cell_cycle_correlated_genes(adata, min_corr=0.1, key_added = "use_genes"):
"""
Remove signature-correlated genes from a list of test genes
Arguments:
----------
E: scipy.sparse.csc_matrix, shape (n_cells, n_genes)
- full counts matrix
gene_list: numpy array, shape (n_genes,)
- full gene list
exclude_corr_genes_list: list of list(s)
- Each sublist is used to build a signature. Test genes correlated
with this signature will be removed
test_gene_idx: 1-D numpy array
- indices of genes to test for correlation with the
gene signatures from exclude_corr_genes_list
min_corr: float (default=0.1)
- Test genes with a Pearson correlation of min_corr or higher
with any of the gene sets from exclude_corr_genes_list will
be excluded
Returns:
--------
numpy array of gene indices (subset of test_gene_idx) that
are not correlated with any of the gene signatures
Source:
https://github.com/AllonKleinLab/SPRING_dev/blob/aa52c405b6f15efd53c66f6856799dfe46e72d01/data_prep/spring_helper.py#L307-L328
"""
E = adata.X.tocsc()
gene_list = adata.var["gene_ids"].tolist()
test_gene_idx = adata.var.loc[adata.var["hv_genes"]].index.astype(int).tolist()
exclude_corr_genes_list = cell_cycle_genes()
seed_ix_list = []
for l in exclude_corr_genes_list:
seed_ix_list.append(
np.array([i for i in range(len(gene_list)) if gene_list[i] in l], dtype=int)
)
exclude_ix = []
for iSet in tqdm(range(len(seed_ix_list))):
seed_ix = seed_ix_list[iSet][
E[:, seed_ix_list[iSet]].sum(axis=0).A.squeeze() > 0
]
tmp = sparse_zscore(E[:, seed_ix.flatten()])
tmp = tmp.sum(1).A.squeeze()
c = np.zeros(len(test_gene_idx))
for iG in range(len(c)):
c[iG], _ = scipy.stats.pearsonr(tmp, E[:, test_gene_idx[iG]].A.squeeze())
exclude_ix.extend(
[test_gene_idx[i] for i in range(len(test_gene_idx)) if (c[i]) >= min_corr]
)
exclude_ix = np.array(exclude_ix)
filtered_idx = np.array(
[g for g in test_gene_idx if g not in exclude_ix], dtype=int
)
adata.var[key_added] = adata.var.index.astype(int).isin(filtered_idx) | PypiClean |
/AyiinXd-0.0.8-cp311-cp311-macosx_10_9_universal2.whl/fipper/methods/mongo/manage/warn.py |
# ========================×========================
# Jangan Hapus Credit Ngentod
# ========================×========================
from typing import Optional, Tuple
import fipper
class Warn:
async def get_warn_action(self: "fipper.Client", chat_id: int) -> Tuple[Optional[str], bool]:
warndb = self.mongo_async.warn
res = await warndb.find_one({"chat_id": chat_id})
if res:
try:
aksi = res['action']
return aksi
except KeyError:
return "mute"
else:
return "mute"
async def set_warn_action(self: "fipper.Client", chat_id: int, action: Optional[str]):
warndb = self.mongo_async.warn
cek = await warndb.find_one({"chat_id": chat_id, "action": action})
if cek:
await warndb.update_one(
{"chat_id": chat_id},
{
"$set": {
"action": action,
},
}
)
else:
await warndb.insert_one(
{
"chat_id": chat_id,
"action": action,
}
)
async def get_warns(self: "fipper.Client", chat_id, user_id):
warndb = self.mongo_async.warn
r = await warndb.find_one({"chat_id": chat_id, "user_id": user_id})
if r:
try:
num = r['number']
return num
except KeyError:
return 0
else:
return 0
async def add_warns(self: "fipper.Client", chat_id, user_id, number):
warndb = self.mongo_async.warn
cek = await warndb.find_one({"chat_id": chat_id, "user_id": user_id})
if cek:
await warndb.update_one(
{"chat_id": chat_id},
{
"$set": {
"user_id": user_id,
"number": number,
},
}
)
else:
await warndb.insert_one(
{
"chat_id": chat_id,
"user_id": user_id,
"number": number,
}
)
async def reset_warns(self: "fipper.Client", chat_id, user_id):
warndb = self.mongo_async.warn
res = await warndb.find_one({"chat_id": chat_id, "user_id": user_id})
if res:
await warndb.delete_one({"user_id": user_id})
async def get_warns_limit(self: "fipper.Client", chat_id):
warndb = self.mongo_async.warn
res = await warndb.find_one({"chat_id": chat_id})
if res:
try:
limit = res['warns_limit']
return limit
except KeyError:
return 3
else:
return 3
async def set_warns_limit(self: "fipper.Client", chat_id, warns_limit):
warndb = self.mongo_async.warn
cek = await warndb.find_one({"chat_id": chat_id, "warns_limit": warns_limit})
if cek:
await warndb.update_one(
{"chat_id": chat_id},
{
"$set": {
"warns_limit": warns_limit,
},
}
)
else:
await warndb.insert_one(
{
"chat_id": chat_id,
"warns_limit": warns_limit,
}
)
async def all_warns(self: "fipper.Client", chat_id):
warndb = self.mongo_async.warn
r = [jo async for jo in warndb.find({"chat_id": chat_id})]
if r:
return r
else:
return [] | PypiClean |
/ACNLogger2-1.1.0-py3-none-any.whl/ACNLogger/__init__.py |
import logging
import time
import os
import sys
import inspect
from html import escape
class ACNLogger:
def check(self, message):
if self.ENV == "DEV":
return message
else:
newstr = message.replace("./", "")
newstr = newstr.replace("..", "")
return escape(newstr)
def debug(self, message):
self.logger.debug("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(message))
def info(self, message):
self.logger.info("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(message))
def warning(self, message):
self.logger.warning("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(message))
def error(self, e):
self.logger.error("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(str(e)))
def critical(self, e):
self.logger.critical("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(str(e)))
def exception(self, e):
if self.ENV != "PRO":
self.logger.exception("["+os.path.basename(inspect.stack()[1].filename)+"] ["+self.ENV+"] ["+self.oid+"] ["+self.session+"] ["+self.correlationId+"] " + self.check(str(e)))
else:
self.error(e)
def setSession(self, session):
self.session = session
def setCorrelationId(self, correlationId):
self.correlationId = correlationId
def setOId(self, oid):
self.oid = oid
def __init__(self,name,file=None,console_level="debug",logfile_level="debug"):
#file = file or name+".log"
_logLevelMap = {
"debug": logging.DEBUG,
"info": logging.INFO,
"warning": logging.WARNING,
"error": logging.ERROR,
"critical":logging.CRITICAL
}
acn_logger=logging.getLogger(name) # Creating the new logger
acn_logger.setLevel(logging.DEBUG) # Setting new logger level to INFO or above
acn_logger.propagate = False
console_handler=logging.StreamHandler()
console_handler.setLevel(_logLevelMap[console_level])
#file_handler=logging.FileHandler(file)
#file_handler.setLevel(_logLevelMap[logfile_level])
#acn_logger.addHandler(file_handler) #Adding file handler to the new logger
acn_logger.addHandler(console_handler)
formatter=logging.Formatter('[%(asctime)s] [%(levelname)s] [%(process)d] %(message)s') #Creating a formatter
#file_handler.setFormatter(formatter) #Setting handler format
console_handler.setFormatter(formatter)
self.session = "UNDEFINED"
self.correlationId = "UNDEFINED"
self.oid = "UNDEFINED"
self.logger=acn_logger
try:
self.ENV = os.environ["ENV"]
except:
self.ENV = "ENV NOT SET"
self.warning("Environment variable ENV not set")
self.info("STARTING MICROSERVICE") | PypiClean |
/Newcalls-0.0.1-cp37-cp37m-win_amd64.whl/newcalls/node_modules/@types/node/zlib.d.ts | declare module 'zlib' {
import * as stream from 'node:stream';
interface ZlibOptions {
/**
* @default constants.Z_NO_FLUSH
*/
flush?: number | undefined;
/**
* @default constants.Z_FINISH
*/
finishFlush?: number | undefined;
/**
* @default 16*1024
*/
chunkSize?: number | undefined;
windowBits?: number | undefined;
level?: number | undefined; // compression only
memLevel?: number | undefined; // compression only
strategy?: number | undefined; // compression only
dictionary?: NodeJS.ArrayBufferView | ArrayBuffer | undefined; // deflate/inflate only, empty dictionary by default
info?: boolean | undefined;
maxOutputLength?: number | undefined;
}
interface BrotliOptions {
/**
* @default constants.BROTLI_OPERATION_PROCESS
*/
flush?: number | undefined;
/**
* @default constants.BROTLI_OPERATION_FINISH
*/
finishFlush?: number | undefined;
/**
* @default 16*1024
*/
chunkSize?: number | undefined;
params?:
| {
/**
* Each key is a `constants.BROTLI_*` constant.
*/
[key: number]: boolean | number;
}
| undefined;
maxOutputLength?: number | undefined;
}
interface Zlib {
/** @deprecated Use bytesWritten instead. */
readonly bytesRead: number;
readonly bytesWritten: number;
shell?: boolean | string | undefined;
close(callback?: () => void): void;
flush(kind?: number, callback?: () => void): void;
flush(callback?: () => void): void;
}
interface ZlibParams {
params(level: number, strategy: number, callback: () => void): void;
}
interface ZlibReset {
reset(): void;
}
interface BrotliCompress extends stream.Transform, Zlib {}
interface BrotliDecompress extends stream.Transform, Zlib {}
interface Gzip extends stream.Transform, Zlib {}
interface Gunzip extends stream.Transform, Zlib {}
interface Deflate extends stream.Transform, Zlib, ZlibReset, ZlibParams {}
interface Inflate extends stream.Transform, Zlib, ZlibReset {}
interface DeflateRaw extends stream.Transform, Zlib, ZlibReset, ZlibParams {}
interface InflateRaw extends stream.Transform, Zlib, ZlibReset {}
interface Unzip extends stream.Transform, Zlib {}
/**
* Creates and returns a new `BrotliCompress` object.
* @since v11.7.0, v10.16.0
*/
function createBrotliCompress(options?: BrotliOptions): BrotliCompress;
/**
* Creates and returns a new `BrotliDecompress` object.
* @since v11.7.0, v10.16.0
*/
function createBrotliDecompress(options?: BrotliOptions): BrotliDecompress;
/**
* Creates and returns a new `Gzip` object.
* See `example`.
* @since v0.5.8
*/
function createGzip(options?: ZlibOptions): Gzip;
/**
* Creates and returns a new `Gunzip` object.
* @since v0.5.8
*/
function createGunzip(options?: ZlibOptions): Gunzip;
/**
* Creates and returns a new `Deflate` object.
* @since v0.5.8
*/
function createDeflate(options?: ZlibOptions): Deflate;
/**
* Creates and returns a new `Inflate` object.
* @since v0.5.8
*/
function createInflate(options?: ZlibOptions): Inflate;
/**
* Creates and returns a new `DeflateRaw` object.
*
* An upgrade of zlib from 1.2.8 to 1.2.11 changed behavior when `windowBits`is set to 8 for raw deflate streams. zlib would automatically set `windowBits`to 9 if was initially set to 8\. Newer
* versions of zlib will throw an exception,
* so Node.js restored the original behavior of upgrading a value of 8 to 9,
* since passing `windowBits = 9` to zlib actually results in a compressed stream
* that effectively uses an 8-bit window only.
* @since v0.5.8
*/
function createDeflateRaw(options?: ZlibOptions): DeflateRaw;
/**
* Creates and returns a new `InflateRaw` object.
* @since v0.5.8
*/
function createInflateRaw(options?: ZlibOptions): InflateRaw;
/**
* Creates and returns a new `Unzip` object.
* @since v0.5.8
*/
function createUnzip(options?: ZlibOptions): Unzip;
type InputType = string | ArrayBuffer | NodeJS.ArrayBufferView;
type CompressCallback = (error: Error | null, result: Buffer) => void;
/**
* @since v11.7.0, v10.16.0
*/
function brotliCompress(buf: InputType, options: BrotliOptions, callback: CompressCallback): void;
function brotliCompress(buf: InputType, callback: CompressCallback): void;
namespace brotliCompress {
function __promisify__(buffer: InputType, options?: BrotliOptions): Promise<Buffer>;
}
/**
* Compress a chunk of data with `BrotliCompress`.
* @since v11.7.0, v10.16.0
*/
function brotliCompressSync(buf: InputType, options?: BrotliOptions): Buffer;
/**
* @since v11.7.0, v10.16.0
*/
function brotliDecompress(buf: InputType, options: BrotliOptions, callback: CompressCallback): void;
function brotliDecompress(buf: InputType, callback: CompressCallback): void;
namespace brotliDecompress {
function __promisify__(buffer: InputType, options?: BrotliOptions): Promise<Buffer>;
}
/**
* Decompress a chunk of data with `BrotliDecompress`.
* @since v11.7.0, v10.16.0
*/
function brotliDecompressSync(buf: InputType, options?: BrotliOptions): Buffer;
/**
* @since v0.6.0
*/
function deflate(buf: InputType, callback: CompressCallback): void;
function deflate(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace deflate {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Compress a chunk of data with `Deflate`.
* @since v0.11.12
*/
function deflateSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function deflateRaw(buf: InputType, callback: CompressCallback): void;
function deflateRaw(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace deflateRaw {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Compress a chunk of data with `DeflateRaw`.
* @since v0.11.12
*/
function deflateRawSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function gzip(buf: InputType, callback: CompressCallback): void;
function gzip(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace gzip {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Compress a chunk of data with `Gzip`.
* @since v0.11.12
*/
function gzipSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function gunzip(buf: InputType, callback: CompressCallback): void;
function gunzip(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace gunzip {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Decompress a chunk of data with `Gunzip`.
* @since v0.11.12
*/
function gunzipSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function inflate(buf: InputType, callback: CompressCallback): void;
function inflate(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace inflate {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Decompress a chunk of data with `Inflate`.
* @since v0.11.12
*/
function inflateSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function inflateRaw(buf: InputType, callback: CompressCallback): void;
function inflateRaw(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace inflateRaw {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Decompress a chunk of data with `InflateRaw`.
* @since v0.11.12
*/
function inflateRawSync(buf: InputType, options?: ZlibOptions): Buffer;
/**
* @since v0.6.0
*/
function unzip(buf: InputType, callback: CompressCallback): void;
function unzip(buf: InputType, options: ZlibOptions, callback: CompressCallback): void;
namespace unzip {
function __promisify__(buffer: InputType, options?: ZlibOptions): Promise<Buffer>;
}
/**
* Decompress a chunk of data with `Unzip`.
* @since v0.11.12
*/
function unzipSync(buf: InputType, options?: ZlibOptions): Buffer;
namespace constants {
const BROTLI_DECODE: number;
const BROTLI_DECODER_ERROR_ALLOC_BLOCK_TYPE_TREES: number;
const BROTLI_DECODER_ERROR_ALLOC_CONTEXT_MAP: number;
const BROTLI_DECODER_ERROR_ALLOC_CONTEXT_MODES: number;
const BROTLI_DECODER_ERROR_ALLOC_RING_BUFFER_1: number;
const BROTLI_DECODER_ERROR_ALLOC_RING_BUFFER_2: number;
const BROTLI_DECODER_ERROR_ALLOC_TREE_GROUPS: number;
const BROTLI_DECODER_ERROR_DICTIONARY_NOT_SET: number;
const BROTLI_DECODER_ERROR_FORMAT_BLOCK_LENGTH_1: number;
const BROTLI_DECODER_ERROR_FORMAT_BLOCK_LENGTH_2: number;
const BROTLI_DECODER_ERROR_FORMAT_CL_SPACE: number;
const BROTLI_DECODER_ERROR_FORMAT_CONTEXT_MAP_REPEAT: number;
const BROTLI_DECODER_ERROR_FORMAT_DICTIONARY: number;
const BROTLI_DECODER_ERROR_FORMAT_DISTANCE: number;
const BROTLI_DECODER_ERROR_FORMAT_EXUBERANT_META_NIBBLE: number;
const BROTLI_DECODER_ERROR_FORMAT_EXUBERANT_NIBBLE: number;
const BROTLI_DECODER_ERROR_FORMAT_HUFFMAN_SPACE: number;
const BROTLI_DECODER_ERROR_FORMAT_PADDING_1: number;
const BROTLI_DECODER_ERROR_FORMAT_PADDING_2: number;
const BROTLI_DECODER_ERROR_FORMAT_RESERVED: number;
const BROTLI_DECODER_ERROR_FORMAT_SIMPLE_HUFFMAN_ALPHABET: number;
const BROTLI_DECODER_ERROR_FORMAT_SIMPLE_HUFFMAN_SAME: number;
const BROTLI_DECODER_ERROR_FORMAT_TRANSFORM: number;
const BROTLI_DECODER_ERROR_FORMAT_WINDOW_BITS: number;
const BROTLI_DECODER_ERROR_INVALID_ARGUMENTS: number;
const BROTLI_DECODER_ERROR_UNREACHABLE: number;
const BROTLI_DECODER_NEEDS_MORE_INPUT: number;
const BROTLI_DECODER_NEEDS_MORE_OUTPUT: number;
const BROTLI_DECODER_NO_ERROR: number;
const BROTLI_DECODER_PARAM_DISABLE_RING_BUFFER_REALLOCATION: number;
const BROTLI_DECODER_PARAM_LARGE_WINDOW: number;
const BROTLI_DECODER_RESULT_ERROR: number;
const BROTLI_DECODER_RESULT_NEEDS_MORE_INPUT: number;
const BROTLI_DECODER_RESULT_NEEDS_MORE_OUTPUT: number;
const BROTLI_DECODER_RESULT_SUCCESS: number;
const BROTLI_DECODER_SUCCESS: number;
const BROTLI_DEFAULT_MODE: number;
const BROTLI_DEFAULT_QUALITY: number;
const BROTLI_DEFAULT_WINDOW: number;
const BROTLI_ENCODE: number;
const BROTLI_LARGE_MAX_WINDOW_BITS: number;
const BROTLI_MAX_INPUT_BLOCK_BITS: number;
const BROTLI_MAX_QUALITY: number;
const BROTLI_MAX_WINDOW_BITS: number;
const BROTLI_MIN_INPUT_BLOCK_BITS: number;
const BROTLI_MIN_QUALITY: number;
const BROTLI_MIN_WINDOW_BITS: number;
const BROTLI_MODE_FONT: number;
const BROTLI_MODE_GENERIC: number;
const BROTLI_MODE_TEXT: number;
const BROTLI_OPERATION_EMIT_METADATA: number;
const BROTLI_OPERATION_FINISH: number;
const BROTLI_OPERATION_FLUSH: number;
const BROTLI_OPERATION_PROCESS: number;
const BROTLI_PARAM_DISABLE_LITERAL_CONTEXT_MODELING: number;
const BROTLI_PARAM_LARGE_WINDOW: number;
const BROTLI_PARAM_LGBLOCK: number;
const BROTLI_PARAM_LGWIN: number;
const BROTLI_PARAM_MODE: number;
const BROTLI_PARAM_NDIRECT: number;
const BROTLI_PARAM_NPOSTFIX: number;
const BROTLI_PARAM_QUALITY: number;
const BROTLI_PARAM_SIZE_HINT: number;
const DEFLATE: number;
const DEFLATERAW: number;
const GUNZIP: number;
const GZIP: number;
const INFLATE: number;
const INFLATERAW: number;
const UNZIP: number;
// Allowed flush values.
const Z_NO_FLUSH: number;
const Z_PARTIAL_FLUSH: number;
const Z_SYNC_FLUSH: number;
const Z_FULL_FLUSH: number;
const Z_FINISH: number;
const Z_BLOCK: number;
const Z_TREES: number;
// Return codes for the compression/decompression functions.
// Negative values are errors, positive values are used for special but normal events.
const Z_OK: number;
const Z_STREAM_END: number;
const Z_NEED_DICT: number;
const Z_ERRNO: number;
const Z_STREAM_ERROR: number;
const Z_DATA_ERROR: number;
const Z_MEM_ERROR: number;
const Z_BUF_ERROR: number;
const Z_VERSION_ERROR: number;
// Compression levels.
const Z_NO_COMPRESSION: number;
const Z_BEST_SPEED: number;
const Z_BEST_COMPRESSION: number;
const Z_DEFAULT_COMPRESSION: number;
// Compression strategy.
const Z_FILTERED: number;
const Z_HUFFMAN_ONLY: number;
const Z_RLE: number;
const Z_FIXED: number;
const Z_DEFAULT_STRATEGY: number;
const Z_DEFAULT_WINDOWBITS: number;
const Z_MIN_WINDOWBITS: number;
const Z_MAX_WINDOWBITS: number;
const Z_MIN_CHUNK: number;
const Z_MAX_CHUNK: number;
const Z_DEFAULT_CHUNK: number;
const Z_MIN_MEMLEVEL: number;
const Z_MAX_MEMLEVEL: number;
const Z_DEFAULT_MEMLEVEL: number;
const Z_MIN_LEVEL: number;
const Z_MAX_LEVEL: number;
const Z_DEFAULT_LEVEL: number;
const ZLIB_VERNUM: number;
}
// Allowed flush values.
/** @deprecated Use `constants.Z_NO_FLUSH` */
const Z_NO_FLUSH: number;
/** @deprecated Use `constants.Z_PARTIAL_FLUSH` */
const Z_PARTIAL_FLUSH: number;
/** @deprecated Use `constants.Z_SYNC_FLUSH` */
const Z_SYNC_FLUSH: number;
/** @deprecated Use `constants.Z_FULL_FLUSH` */
const Z_FULL_FLUSH: number;
/** @deprecated Use `constants.Z_FINISH` */
const Z_FINISH: number;
/** @deprecated Use `constants.Z_BLOCK` */
const Z_BLOCK: number;
/** @deprecated Use `constants.Z_TREES` */
const Z_TREES: number;
// Return codes for the compression/decompression functions.
// Negative values are errors, positive values are used for special but normal events.
/** @deprecated Use `constants.Z_OK` */
const Z_OK: number;
/** @deprecated Use `constants.Z_STREAM_END` */
const Z_STREAM_END: number;
/** @deprecated Use `constants.Z_NEED_DICT` */
const Z_NEED_DICT: number;
/** @deprecated Use `constants.Z_ERRNO` */
const Z_ERRNO: number;
/** @deprecated Use `constants.Z_STREAM_ERROR` */
const Z_STREAM_ERROR: number;
/** @deprecated Use `constants.Z_DATA_ERROR` */
const Z_DATA_ERROR: number;
/** @deprecated Use `constants.Z_MEM_ERROR` */
const Z_MEM_ERROR: number;
/** @deprecated Use `constants.Z_BUF_ERROR` */
const Z_BUF_ERROR: number;
/** @deprecated Use `constants.Z_VERSION_ERROR` */
const Z_VERSION_ERROR: number;
// Compression levels.
/** @deprecated Use `constants.Z_NO_COMPRESSION` */
const Z_NO_COMPRESSION: number;
/** @deprecated Use `constants.Z_BEST_SPEED` */
const Z_BEST_SPEED: number;
/** @deprecated Use `constants.Z_BEST_COMPRESSION` */
const Z_BEST_COMPRESSION: number;
/** @deprecated Use `constants.Z_DEFAULT_COMPRESSION` */
const Z_DEFAULT_COMPRESSION: number;
// Compression strategy.
/** @deprecated Use `constants.Z_FILTERED` */
const Z_FILTERED: number;
/** @deprecated Use `constants.Z_HUFFMAN_ONLY` */
const Z_HUFFMAN_ONLY: number;
/** @deprecated Use `constants.Z_RLE` */
const Z_RLE: number;
/** @deprecated Use `constants.Z_FIXED` */
const Z_FIXED: number;
/** @deprecated Use `constants.Z_DEFAULT_STRATEGY` */
const Z_DEFAULT_STRATEGY: number;
/** @deprecated */
const Z_BINARY: number;
/** @deprecated */
const Z_TEXT: number;
/** @deprecated */
const Z_ASCII: number;
/** @deprecated */
const Z_UNKNOWN: number;
/** @deprecated */
const Z_DEFLATED: number;
}
declare module 'node:zlib' {
export * from 'zlib';
} | PypiClean |
/CustomPipeline-0.0.3-py3-none-any.whl/rpcore/rpobject.py |
from __future__ import print_function
import sys
# Load and init colorama, used to color the output
from rplibs.colorama import init as init_colorama
from rplibs.colorama import Fore, Style
init_colorama()
class RPObject(object):
""" This is the base class for every object in the render pipeline. It
provides the functions debug, warn, error and fatal for classes which
inherit from this object, including the name of the class when printing out
the message. """
_OUTPUT_LEVEL = 0
_OUTPUT_LEVELS = ["debug", "warning", "error", "fatal"]
@classmethod
def set_output_level(cls, level):
""" Sets the output level, messages with a level below will not be
printed. E.g. if you set the output level to "error", only error and
fatal messages will be shown. """
assert level in RPObject._OUTPUT_LEVELS
RPObject._OUTPUT_LEVEL = RPObject._OUTPUT_LEVELS.index(level)
@staticmethod
def global_debug(context, *args, **kwargs):
""" This method can be used from a static context to print a debug
message. The first argument should be the name of the object / context,
all other arguments should be the message. """
if RPObject._OUTPUT_LEVEL > 0:
return
print(kwargs.get("color", Fore.GREEN) + "[>] " +
context.ljust(25) + " " + Style.RESET_ALL + Fore.WHITE +
' '.join([str(i) for i in args]), Fore.RESET + Style.RESET_ALL)
@staticmethod
def global_warn(context, *args):
""" This method can be used from a static context to print a warning.
The first argument should be the name of the object / context, all
other arguments should be the message. """
if RPObject._OUTPUT_LEVEL > 1:
return
print(Fore.YELLOW + Style.BRIGHT + "[!] " + context.ljust(25) +
Fore.YELLOW + Style.BRIGHT + " " + ' '.join([str(i) for i in args]) +
Fore.RESET + Style.RESET_ALL)
@staticmethod
def global_error(context, *args):
""" This method can be used from a static context to print an error.
The first argument should be the name of the object / context, all
other arguments should be the message. """
if RPObject._OUTPUT_LEVEL > 2:
return
print(Fore.RED + Style.BRIGHT + "\n[!!!] " +
context.ljust(23) + " " + ' '.join([str(i) for i in args]) +
"\n" + Fore.RESET + Style.RESET_ALL)
def __init__(self, name=None):
""" Initiates the RPObject with a given name. The name should be
representative about the class. If no name is given, the classname
is used """
if name is None:
name = self.__class__.__name__
self._debug_name = name
self._debug_color = Fore.GREEN
def _set_debug_color(self, color, style=None):
""" Sets the color used to output debug messages """
self._debug_color = getattr(Fore, color.upper())
if style:
self._debug_color += getattr(Style, style.upper())
@property
def debug_name(self):
""" Returns the name of the debug object """
return self._debug_name
@debug_name.setter
def debug_name(self, name):
""" Renames this object """
self._debug_name = name
def debug(self, *args):
""" Outputs a debug message, something that is not necessarry
but provides useful information for the developer """
self.global_debug(self._debug_name, *args, color=self._debug_color)
def warn(self, *args):
""" Outputs a warning message, something that failed or does
not work, but does not prevent the program from running """
self.global_warn(self._debug_name, *args)
def error(self, *args):
""" Outputs an error message, something really serious.
Hopefully this never get's called! """
self.global_error(self._debug_name, *args)
def fatal(self, *args):
""" Outputs a fatal error message, printing out the errors and then
calling sys.exit to terminate the program. This method should be called
when something failed so hard that the pipeline has to exit. """
# We have to set output level to 0 here, so we can print out errors
RPObject._OUTPUT_LEVEL = 0
self.error(*args)
sys.exit(0)
def __repr__(self):
""" Represents this object. Subclasses can override this """
return self._debug_name | PypiClean |
/Flask-Scaffold-0.5.1.tar.gz/Flask-Scaffold-0.5.1/app/templates/static/node_modules/angular-grid/src/ts/virtualDom/vHtmlElement.ts |
module awk.vdom {
var _ = awk.grid.Utils;
export class VHtmlElement extends VElement {
private type: string;
private classes: string[];
private eventListeners: VEventListener[];
private attributes: {[key: string]: string};
private children: VElement[];
private innerHtml: string;
private style = <any>{};
private bound: boolean;
private element: HTMLElement;
constructor(type: string) {
super();
this.type = type;
}
public getElement(): HTMLElement {
return this.element;
}
public setInnerHtml(innerHtml: string): void {
if (this.bound) {
this.element.innerHTML = innerHtml;
} else {
this.innerHtml = innerHtml;
}
}
public addStyles(styles: any): void {
if (!styles) {
return;
}
if (!this.bound && !this.style) {
this.style = {};
}
_.iterateObject(styles, (key: string, value: string)=> {
if (this.bound) {
var style = <any> this.element.style;
style[key] = value;
} else {
this.style[key] = value;
}
});
}
private attachEventListeners(node: Node): void {
if (!this.eventListeners) {
return;
}
for (var i = 0; i<this.eventListeners.length; i++) {
var listener = this.eventListeners[i];
node.addEventListener(listener.event, listener.listener);
}
}
public addClass(newClass: string): void {
if (this.bound) {
_.addCssClass(this.element, newClass);
} else {
if (!this.classes) {
this.classes = [];
}
this.classes.push(newClass);
}
}
public removeClass(oldClass: string): void {
if (this.bound) {
_.removeCssClass(this.element, oldClass);
} else {
if (!this.classes) {
return;
}
while (this.classes.indexOf(oldClass)>=0) {
_.removeFromArray(this.classes, oldClass);
}
}
}
public addClasses(classes: string[]): void {
if (!classes || classes.length <= 0) {
return;
}
if (this.bound) {
for (var i = 0; i<classes.length; i++) {
_.addCssClass(this.element, classes[i])
}
} else {
if (!this.classes) {
this.classes = [];
}
for (var j = 0; j<classes.length; j++) {
this.classes.push(classes[j]);
}
}
}
public toHtmlString(): string {
var buff = '';
// opening element
buff += '<' + this.type + ' v_element_id="'+this.getId()+'" ';
buff += this.toHtmlStringClasses();
buff += this.toHtmlStringAttributes();
buff += this.toHtmlStringStyles();
buff += '>';
// contents
if (this.innerHtml) {
buff += this.innerHtml;
}
buff += this.toHtmlStringChildren();
// closing element
buff += '</' + this.type + '>';
return buff;
}
private toHtmlStringChildren(): string {
if (!this.children) {
return '';
}
var result = '';
for (var i = 0; i<this.children.length; i++) {
result += this.children[i].toHtmlString();
}
return result;
}
private toHtmlStringAttributes(): string {
if (!this.attributes) {
return '';
}
var result = '';
_.iterateObject(this.attributes, (key: string, value: string)=> {
result += ' ' + key + '="'+value+'"';
});
return result;
}
private toHtmlStringClasses(): string {
if (!this.classes) {
return '';
}
return ' class="'+this.classes.join(' ')+'"';
}
private toHtmlStringStyles(): string {
var result = ' style="';
var atLeastOne = false;
_.iterateObject(this.style, (key: string, value: string)=> {
result += ' ' + key + ': '+value+';';
atLeastOne = true;
});
result += '"';
if (atLeastOne) {
return result;
} else {
return '';
}
}
public appendChild(child: any) {
if (this.bound) {
if (_.isNodeOrElement(child)){
this.element.appendChild(child);
} else {
console.error('cannot appendChild with virtual child to already bound VHTMLElement');
}
} else {
if (!this.children) {
this.children = [];
}
if (_.isNodeOrElement(child)) {
this.children.push(new VWrapperElement(child));
} else {
this.children.push(child);
}
}
}
public setAttribute(key: string, value: string) {
if (this.bound) {
console.error('cannot setAttribute to already bound VHTMLElement');
}
if (!this.attributes) {
this.attributes = {};
}
this.attributes[key] = value;
}
public addEventListener(event: string, listener: EventListener) {
if (this.bound) {
console.error('cannot addEventListener to already bound VHTMLElement');
}
if (!this.eventListeners) {
this.eventListeners = [];
}
var entry = new VEventListener(event, listener);
this.eventListeners.push(entry);
}
public elementAttached(element: Element): void {
super.elementAttached(element);
this.element = <HTMLElement> element;
this.attachEventListeners(element);
this.fireElementAttachedToChildren(element);
this.bound = true;
}
public fireElementAttachedToChildren(element: Element) {
if (!this.children) {
return;
}
for (var i = 0; i<this.children.length; i++) {
var child = this.children[i];
var childElement = element.querySelector('[v_element_id="'+child.getId()+'"]');
child.elementAttached(childElement);
}
}
}
class VEventListener {
constructor(public event: string, public listener: EventListener) {}
}
} | PypiClean |
/FireWorks-2.0.3.tar.gz/FireWorks-2.0.3/fireworks/user_objects/firetasks/dataflow_tasks.py |
__author__ = "Ivan Kondov"
__email__ = "[email protected]"
__copyright__ = "Copyright 2016, Karlsruhe Institute of Technology"
import sys
from fireworks import Firework
from fireworks.core.firework import FiretaskBase, FWAction
from fireworks.utilities.fw_serializers import load_object
if sys.version_info[0] > 2:
basestring = str
class CommandLineTask(FiretaskBase):
"""
A Firetask to execute external commands in a shell
Required params:
- command_spec (dict): a dictionary specification of the command
(see below for details)
Optional params:
- inputs ([str]): list of labels, one for each input argument
- outputs ([str]): list of labels, one for each output argument
- chunk_number (int): the serial number of the firetask
when it is part of a series generated by a ForeachTask
command_spec = {
'command': [str], # mandatory
label_1: dict_1, # optional
label_2: dict_2, # optional
...
}
The 'command' is a representation of the command as to be used with
subprocess package. The optional keys label_1, label_2, etc. are
the actual labels used in the inputs and outputs. The dictionaries dict_1,
dict_2, etc. have the following schema:
{
'binding': {
prefix: str or None,
separator: str or None
},
'source': {
'type': 'path' or 'data' or 'identifier'
or 'stdin' or 'stdout' or 'stderr' or None,
'value': str or int or float
},
'target': {
'type': 'path' or 'data' or 'identifier'
or 'stdin' or 'stdout' or 'stderr' or None,
'value': str
}
}
Remarks
-------
* If the 'type' in the 'source' field is 'data' the 'value' can be of
types 'str', 'int' and 'float'.
* When a *str* is found instead of *dict* for some 'source', for example
'source': 'string', 'string' is replaced with spec['string'] which must be
available and of the schema of the 'source'.
* When a *str* is found instead of *dict* for some label, for example
label: 'string', 'string' is replaced with spec['string'] which can be a
dictionary with this schema or a list of such dictionaries.
"""
_fw_name = "CommandLineTask"
required_params = ["command_spec"]
optional_params = ["inputs", "outputs", "chunk_number"]
def run_task(self, fw_spec):
cmd_spec = self["command_spec"]
ilabels = self.get("inputs")
olabels = self.get("outputs")
if ilabels is None:
ilabels = []
else:
assert isinstance(ilabels, list), '"inputs" must be a list'
if olabels is None:
olabels = []
else:
assert isinstance(olabels, list), '"outputs" must be a list'
inputs = []
outputs = []
for ios, labels in zip([inputs, outputs], [ilabels, olabels]):
# cmd_spec: {label: {{binding: {}}, {source: {}}, {target: {}}}}
for label in labels:
if isinstance(cmd_spec[label], basestring):
inp = []
for item in fw_spec[cmd_spec[label]]:
if "source" in item:
inp.append(item)
else:
inp.append({"source": item})
else:
inp = {}
for key in ["binding", "source", "target"]:
if key in cmd_spec[label]:
item = cmd_spec[label][key]
if isinstance(item, basestring):
inp[key] = fw_spec[item]
elif isinstance(item, dict):
inp[key] = item
else:
raise ValueError
ios.append(inp)
command = cmd_spec["command"]
outlist = self.command_line_tool(command, inputs, outputs)
if len(outlist) > 0:
if self.get("chunk_number") is not None:
mod_spec = []
if len(olabels) > 1:
assert len(olabels) == len(outlist)
for olab, out in zip(olabels, outlist):
for item in out:
mod_spec.append({"_push": {olab: item}})
else:
for out in outlist:
mod_spec.append({"_push": {olabels[0]: out}})
return FWAction(mod_spec=mod_spec)
else:
output_dict = {}
for olab, out in zip(olabels, outlist):
output_dict[olab] = out
return FWAction(update_spec=output_dict)
else:
return FWAction()
@staticmethod
def command_line_tool(command, inputs=None, outputs=None):
"""
This function composes and executes a command from provided
specifications.
Required parameters:
- command ([str]): the command as to be passed to subprocess.Popen
Optional parameters:
- inputs ([dict, [dict]]): list of the specifications for inputs;
multiple inputs may be passed in one list of dictionaries
- outputs ([dict]): list of the specifications for outputs
Returns:
- list of target dictionaries for each output:
'target': {
'type': 'path' or 'data' or 'identifier'
or 'stdin' or 'stdout' or 'stderr' or None
'value': str
}
If outputs is None then an empty list is returned.
"""
import os
import uuid
from shutil import copyfile
from subprocess import PIPE, Popen
def set_binding(arg):
argstr = ""
if "binding" in arg:
if "prefix" in arg["binding"]:
argstr += arg["binding"]["prefix"]
if "separator" in arg["binding"]:
argstr += arg["binding"]["separator"]
return argstr
arglist = command
stdin = None
stdout = None
stderr = PIPE
stdininp = None
if inputs is not None:
for inp in inputs:
argl = inp if isinstance(inp, list) else [inp]
for arg in argl:
argstr = set_binding(arg)
assert "source" in arg, 'input has no key "source"'
assert arg["source"]["type"] is not None and arg["source"]["value"] is not None
if "target" in arg:
assert arg["target"] is not None
assert arg["target"]["type"] == "stdin"
if arg["source"]["type"] == "path":
stdin = open(arg["source"]["value"])
elif arg["source"]["type"] == "data":
stdin = PIPE
stdininp = str(arg["source"]["value"]).encode()
else:
# filepad
raise NotImplementedError()
else:
if arg["source"]["type"] == "path":
argstr += arg["source"]["value"]
elif arg["source"]["type"] == "data":
argstr += str(arg["source"]["value"])
else:
# filepad
raise NotImplementedError()
if len(argstr) > 0:
arglist.append(argstr)
if outputs is not None:
for arg in outputs:
if isinstance(arg, list):
arg = arg[0]
argstr = set_binding(arg)
assert "target" in arg
assert arg["target"] is not None
if arg["target"]["type"] == "path":
assert "value" in arg["target"]
assert len(arg["target"]["value"]) > 0
path = arg["target"]["value"]
if os.path.isdir(path):
path = os.path.join(path, str(uuid.uuid4()))
arg["target"]["value"] = path
if "source" in arg:
assert arg["source"] is not None
assert "type" in arg["source"]
if arg["source"]["type"] == "stdout":
stdout = open(path, "w")
elif arg["source"]["type"] == "stderr":
stderr = open(path, "w")
elif arg["source"]["type"] == "path":
pass
else:
argstr += path
else:
argstr += path
elif arg["target"]["type"] == "data":
stdout = PIPE
else:
# filepad
raise NotImplementedError()
if len(argstr) > 0:
arglist.append(argstr)
proc = Popen(arglist, stdin=stdin, stderr=stderr, stdout=stdout)
res = proc.communicate(input=stdininp)
if proc.returncode != 0:
err = res[1] if len(res) > 1 else ""
raise RuntimeError(err)
retlist = []
if outputs is not None:
for output in outputs:
if "source" in output and output["source"]["type"] == "path":
copyfile(output["source"]["value"], output["target"]["value"])
if output["target"]["type"] == "data":
output["target"]["value"] = res[0].decode().strip()
retlist.append(output["target"])
return retlist
class ForeachTask(FiretaskBase):
"""
This firetask branches the workflow creating parallel fireworks
using FWAction: one firework for each element or each chunk from the
*split* list. Each firework in this generated list contains the firetask
specified in the *task* dictionary. If the number of chunks is specified
the *split* list will be divided into this number of chunks and each
chunk will be processed by one of the generated child fireworks.
Required params:
- task (dict): a dictionary version of the firetask
- split (str): a label of an input list; it must be available both in
the *inputs* list of the specified task and in the spec.
Optional params:
- number of chunks (int): if provided the *split* input list will be
divided into this number of sublists and each will be processed by
a separate child firework
"""
_fw_name = "ForeachTask"
required_params = ["task", "split"]
optional_params = ["number of chunks"]
def run_task(self, fw_spec):
assert isinstance(self["split"], basestring), self["split"]
assert isinstance(fw_spec[self["split"]], list)
if isinstance(self["task"]["inputs"], list):
assert self["split"] in self["task"]["inputs"]
else:
assert self["split"] == self["task"]["inputs"]
split_field = fw_spec[self["split"]]
lensplit = len(split_field)
assert lensplit != 0, ("input to split is empty:", self["split"])
nchunks = self.get("number of chunks")
if not nchunks:
nchunks = lensplit
chunklen = lensplit // nchunks
if lensplit % nchunks > 0:
chunklen = chunklen + 1
chunks = [split_field[i : i + chunklen] for i in range(0, lensplit, chunklen)]
fireworks = []
for index, chunk in enumerate(chunks):
spec = fw_spec.copy()
spec[self["split"]] = chunk
task = load_object(self["task"])
task["chunk_number"] = index
name = f"{self._fw_name} {index}"
fireworks.append(Firework(task, spec=spec, name=name))
return FWAction(detours=fireworks)
class JoinDictTask(FiretaskBase):
"""combines specified spec fields into a dictionary"""
_fw_name = "JoinDictTask"
required_params = ["inputs", "output"]
optional_params = ["rename"]
def run_task(self, fw_spec):
assert isinstance(self["output"], basestring)
assert isinstance(self["inputs"], list)
if self["output"] not in fw_spec:
output = {}
else:
assert isinstance(fw_spec[self["output"]], dict)
output = fw_spec[self["output"]]
if self.get("rename"):
assert isinstance(self.get("rename"), dict)
rename = self.get("rename")
else:
rename = {}
for item in self["inputs"]:
if item in rename:
output[self["rename"][item]] = fw_spec[item]
else:
output[item] = fw_spec[item]
return FWAction(update_spec={self["output"]: output})
class JoinListTask(FiretaskBase):
"""combines specified spec fields into a list."""
_fw_name = "JoinListTask"
required_params = ["inputs", "output"]
def run_task(self, fw_spec):
assert isinstance(self["output"], basestring)
assert isinstance(self["inputs"], list)
if self["output"] not in fw_spec:
output = []
else:
assert isinstance(fw_spec[self["output"]], list)
output = fw_spec[self["output"]]
for item in self["inputs"]:
output.append(fw_spec[item])
return FWAction(update_spec={self["output"]: output})
class ImportDataTask(FiretaskBase):
"""
Update the spec with data from file in a nested dictionary at a position
specified by a mapstring = maplist[0]/maplist[1]/...
i.e. spec[maplist[0]][maplist[1]]... = data
"""
_fw_name = "ImportDataTask"
required_params = ["filename", "mapstring"]
optional_params = []
def run_task(self, fw_spec):
import json
import operator
from functools import reduce
import ruamel.yaml as yaml
filename = self["filename"]
mapstring = self["mapstring"]
assert isinstance(filename, basestring)
assert isinstance(mapstring, basestring)
maplist = mapstring.split("/")
fmt = filename.split(".")[-1]
assert fmt in ["json", "yaml"]
with open(filename) as inp:
data = json.load(inp) if fmt == "json" else yaml.safe_load(inp)
leaf = reduce(operator.getitem, maplist[:-1], fw_spec)
if isinstance(data, dict):
if maplist[-1] not in leaf:
leaf[maplist[-1]] = data
else:
leaf[maplist[-1]].update(data)
else:
leaf[maplist[-1]] = data
return FWAction(update_spec={maplist[0]: fw_spec[maplist[0]]}) | PypiClean |
/LaptopControlPanel-0.1.0.tar.gz/LaptopControlPanel-0.1.0/setup_data.py |
####################################################################################################
import os
####################################################################################################
def merge_include(src_lines, doc_path, included_rst_files=None):
if included_rst_files is None:
included_rst_files = {}
text = ''
for line in src_lines:
if line.startswith('.. include::'):
include_file_name = line.split('::')[-1].strip()
if include_file_name not in included_rst_files:
# print "include", include_file_name
with open(os.path.join(doc_path, include_file_name)) as f:
included_rst_files[include_file_name] = True
text += merge_include(f.readlines(), doc_path, included_rst_files)
else:
text += line
return text
####################################################################################################
# Utility function to read the README file.
# Used for the long_description.
def read(file_name):
source_path = os.path.dirname(os.path.realpath(__file__))
if os.path.basename(source_path) == 'tools':
source_path = os.path.dirname(source_path)
elif 'build/bdist' in source_path:
source_path = source_path[:source_path.find('build/bdist')]
absolut_file_name = os.path.join(source_path, file_name)
doc_path = os.path.join(source_path, 'doc', 'sphinx', 'source')
# Read and merge includes
with open(absolut_file_name) as f:
lines = f.readlines()
text = merge_include(lines, doc_path)
return text
####################################################################################################
long_description = read('README.txt')
####################################################################################################
setup_dict = dict(
name='LaptopControlPanel',
version='0.1.0',
author='Fabrice Salvaire',
author_email='[email protected]',
description='A Control Panel for Lenovo Thinkpad Laptop',
license = "GPLv3",
keywords = "laptop control panel",
url='https://github.com/FabriceSalvaire/LaptopControlPanel',
scripts=[
'bin/battery-control',
'bin/battery-monitoring',
'bin/laptop-control-panel',
'bin/fan-calibration',
'bin/round-robin-monitoring',
],
packages=['LaptopControlPanel',
'LaptopControlPanel.GUI',
'LaptopControlPanel.GUI.Widgets',
'LaptopControlPanel.GUI.Pages',
'LaptopControlPanel.GUI.Pages.ui',
'LaptopControlPanel.GUI.ui',
'LaptopControlPanel.Monitoring',
'LaptopControlPanel.Config',
'LaptopControlPanel.Acpi',
'LaptopControlPanel.System',
'LaptopControlPanel.Kernel',
'LaptopControlPanel.DataBase',
'LaptopControlPanel.Logging',
'LaptopControlPanel.Tools',
'LaptopControlPanel.Application',
],
data_files = [('share/LaptopControlPanel/icons',['share/icons']),
],
long_description=long_description,
# cf. http://pypi.python.org/pypi?%3Aaction=list_classifiers
classifiers=[
"Topic :: Scientific/Engineering",
"Intended Audience :: Education",
"Development Status :: 5 - Production/Stable",
"License :: OSI Approved :: GNU General Public License (GPL)",
"Operating System :: OS Independent",
"Programming Language :: Python :: 2.7",
],
# install_requires=[
# # pip install => Could not find any downloads that satisfy the requirement PyQt4>=4.9
# # 'PyQt4>=4.9',
# ],
)
####################################################################################################
#
# End
#
#################################################################################################### | PypiClean |
/GaitAnalysisToolKit-0.2.0.tar.gz/GaitAnalysisToolKit-0.2.0/docs/gait.rst | ===========
Gait Module
===========
The :py:mod:`gaitanalysis.gait` module provides tools to process and analyze
with typical data collected during the measurement of human locomotion (gait).
In general, the three dimensional coordinates throughout time of a set of
markers which are attached to anatomical features on the human are tracked.
Secondly, various analog signals are recorded. In particular, voltages which
are proportional to the applied forces and moments on one or two force plates,
voltages from electromyography (EMG) measurements, and/or accelerometers, etc.
All of these measurements are stored as discrete samples in time.
| PypiClean |
/11l-2021.3-py3-none-any.whl/python_to_11l/tokenizer.py | from typing import List, Tuple
Char = str
from enum import IntEnum
keywords = [ # https://docs.python.org/3/reference/lexical_analysis.html#keywords
'False', 'await', 'else', 'import', 'pass',
'None', 'break', 'except', 'in', 'raise',
'True', 'class', 'finally', 'is', 'return',
'and', 'continue', 'for', 'lambda', 'try',
'as', 'def', 'from', 'nonlocal', 'while',
'assert', 'del', 'global', 'not', 'with',
'async', 'elif', 'if', 'or', 'yield',]
operators = [ # https://docs.python.org/3/reference/lexical_analysis.html#operators
'+', '-', '*', '**', '/', '//', '%', '@',
'<<', '>>', '&', '|', '^', '~',
'<', '>', '<=', '>=', '==', '!=',]
#operators.sort(key = lambda x: len(x), reverse = True)
delimiters = [ # https://docs.python.org/3/reference/lexical_analysis.html#delimiters
'(', ')', '[', ']', '{', '}',
',', ':', '.', ';', '@', '=', '->',
'+=', '-=', '*=', '/=', '//=', '%=', '@=',
'&=', '|=', '^=', '>>=', '<<=', '**=',]
#delimiters.sort(key = lambda x: len(x), reverse = True)
operators_and_delimiters = sorted(operators + delimiters, key = lambda x: len(x), reverse = True)
class Error(Exception):
message : str
pos : int
end : int
def __init__(self, message, pos):
self.message = message
self.pos = pos
self.end = pos
class Token:
class Category(IntEnum): # why ‘Category’: >[https://docs.python.org/3/reference/lexical_analysis.html#other-tokens]:‘the following categories of tokens exist’
NAME = 0 # or IDENTIFIER
KEYWORD = 1
CONSTANT = 2
OPERATOR_OR_DELIMITER = 3
NUMERIC_LITERAL = 4
STRING_LITERAL = 5
INDENT = 6 # [https://docs.python.org/3/reference/lexical_analysis.html#indentation][-1]
DEDENT = 7
STATEMENT_SEPARATOR = 8
start : int
end : int
category : Category
def __init__(self, start, end, category):
self.start = start
self.end = end
self.category = category
def __repr__(self):
return str(self.start)
def value(self, source):
return source[self.start:self.end]
def to_str(self, source):
return 'Token('+str(self.category)+', "'+self.value(source)+'")'
def tokenize(source, newline_chars : List[int] = None, comments : List[Tuple[int, int]] = None):
tokens : List[Token] = []
indentation_levels : List[int] = []
nesting_elements : List[Tuple[Char, int]] = [] # parentheses, square brackets or curly braces
begin_of_line = True
expected_an_indented_block = False
i = 0
while i < len(source):
if begin_of_line: # at the beginning of each line, the line's indentation level is compared to the last of the indentation_levels [:1]
begin_of_line = False
linestart = i
indentation_level = 0
while i < len(source):
if source[i] == ' ':
indentation_level += 1
elif source[i] == "\t":
indentation_level += 8 # consider tab as just 8 spaces (I know that Python 3 use different rules, but I disagree with Python 3 approach ([-1]:‘Tabs are replaced (from left to right) by one to eight spaces’), so I decided to use this simpler solution)
else:
break
i += 1
if i == len(source): # end of source
break
if source[i] in "\r\n#": # lines with only whitespace and/or comments do not affect the indentation
continue
prev_indentation_level = indentation_levels[-1] if len(indentation_levels) else 0
if expected_an_indented_block:
if not indentation_level > prev_indentation_level:
raise Error('expected an indented block', i)
if indentation_level == prev_indentation_level: # [1:] [-1]:‘If it is equal, nothing happens.’ [:2]
if len(tokens):
tokens.append(Token(linestart-1, linestart, Token.Category.STATEMENT_SEPARATOR))
elif indentation_level > prev_indentation_level: # [2:] [-1]:‘If it is larger, it is pushed on the stack, and one INDENT token is generated.’ [:3]
if not expected_an_indented_block:
raise Error('unexpected indent', i)
expected_an_indented_block = False
indentation_levels.append(indentation_level)
tokens.append(Token(linestart, i, Token.Category.INDENT))
else: # [3:] [-1]:‘If it is smaller, it ~‘must’ be one of the numbers occurring on the stack; all numbers on the stack that are larger are popped off, and for each number popped off a DEDENT token is generated.’ [:4]
while True:
indentation_levels.pop()
tokens.append(Token(i, i, Token.Category.DEDENT))
level = indentation_levels[-1] if len(indentation_levels) else 0
if level == indentation_level:
break
if level < indentation_level:
raise Error('unindent does not match any outer indentation level', i)
ch = source[i]
if ch in " \t":
i += 1 # just skip whitespace characters
elif ch in "\r\n":
if newline_chars is not None:
newline_chars.append(i)
i += 1
if ch == "\r" and source[i:i+1] == "\n":
i += 1
if len(nesting_elements) == 0: # [https://docs.python.org/3/reference/lexical_analysis.html#implicit-line-joining ‘Implicit line joining’]:‘Expressions in parentheses, square brackets or curly braces can be split over more than one physical line without using backslashes.’
begin_of_line = True
elif ch == '#':
comment_start = i
i += 1
while i < len(source) and source[i] not in "\r\n":
i += 1
if comments is not None:
comments.append((comment_start, i))
else:
expected_an_indented_block = ch == ':'
operator_or_delimiter = ''
for op in operators_and_delimiters:
if source[i:i+len(op)] == op:
operator_or_delimiter = op
break
lexem_start = i
i += 1
category : Token.Category
if operator_or_delimiter != '':
i = lexem_start + len(operator_or_delimiter)
category = Token.Category.OPERATOR_OR_DELIMITER
if ch in '([{':
nesting_elements.append((ch, lexem_start))
elif ch in ')]}': # ([{
if len(nesting_elements) == 0 or nesting_elements[-1][0] != {')':'(', ']':'[', '}':'{'}[ch]: # }])
raise Error('there is no corresponding opening parenthesis/bracket/brace for `' + ch + '`', lexem_start)
nesting_elements.pop()
elif ch == ';':
category = Token.Category.STATEMENT_SEPARATOR
elif ch in ('"', "'") or (ch in 'rRbB' and source[i:i+1] in ('"', "'")):
ends : str
if ch in 'rRbB':
ends = source[i:i+3] if source[i:i+3] in ('"""', "'''") else source[i]
else:
i -= 1
ends = source[i:i+3] if source[i:i+3] in ('"""', "'''") else ch
i += len(ends)
while True:
if i == len(source):
raise Error('unclosed string literal', lexem_start)
if source[i] == '\\':
i += 1
if i == len(source):
continue
elif source[i:i+len(ends)] == ends:
i += len(ends)
break
i += 1
category = Token.Category.STRING_LITERAL
elif ch.isalpha() or ch == '_': # this is NAME/IDENTIFIER or KEYWORD
while i < len(source):
ch = source[i]
if not (ch.isalpha() or ch == '_' or '0' <= ch <= '9' or ch == '?'):
break
i += 1
if source[lexem_start:i] in keywords:
if source[lexem_start:i] in ('None', 'False', 'True'):
category = Token.Category.CONSTANT
else:
category = Token.Category.KEYWORD
else:
category = Token.Category.NAME
elif (ch in '-+' and '0' <= source[i:i+1] <= '9') or '0' <= ch <= '9': # this is NUMERIC_LITERAL
if ch in '-+':
assert(False) # considering sign as a part of numeric literal is a bad idea — expressions like `j-3` are cease to parse correctly
#sign = ch
ch = source[i+1]
else:
i -= 1
is_hex = ch == '0' and source[i+1:i+2] in ('x', 'X')
is_oct = ch == '0' and source[i+1:i+2] in ('o', 'O')
is_bin = ch == '0' and source[i+1:i+2] in ('b', 'B')
if is_hex or is_oct or is_bin:
i += 2
# if not '0' <= source[i:i+1] <= '9':
# raise Error('expected digit', i)
start = i
i += 1
if is_hex:
while i < len(source) and ('0' <= source[i] <= '9' or 'a' <= source[i] <= 'z' or 'A' <= source[i] <= 'Z' or source[i] == '_'):
i += 1
elif is_oct:
while i < len(source) and ('0' <= source[i] <= '7' or source[i] == '_'):
i += 1
elif is_bin:
while i < len(source) and source[i] in '01_':
i += 1
else:
while i < len(source) and ('0' <= source[i] <= '9' or source[i] in '_.eE'):
if source[i] in 'eE':
if source[i+1:i+2] in '-+':
i += 1
i += 1
if source[i:i+1] in ('j', 'J'):
i += 1
if '_' in source[start:i] and not '.' in source[start:i]: # float numbers do not checked for a while
number = source[start:i].replace('_', '')
number_with_separators = ''
j = len(number)
while j > 3:
number_with_separators = '_' + number[j-3:j] + number_with_separators
j -= 3
number_with_separators = number[0:j] + number_with_separators
if source[start:i] != number_with_separators:
raise Error('digit separator in this number is located in the wrong place (should be: '+ number_with_separators +')', start)
category = Token.Category.NUMERIC_LITERAL
elif ch == '\\':
if source[i] not in "\r\n":
raise Error('only new line character allowed after backslash', i)
if source[i] == "\r":
i += 1
if source[i] == "\n":
i += 1
continue
else:
raise Error('unexpected character ' + ch, lexem_start)
tokens.append(Token(lexem_start, i, category))
if len(nesting_elements):
raise Error('there is no corresponding closing parenthesis/bracket/brace for `' + nesting_elements[-1][0] + '`', nesting_elements[-1][1])
if expected_an_indented_block:
raise Error('expected an indented block', i)
while len(indentation_levels): # [4:] [-1]:‘At the end of the file, a DEDENT token is generated for each number remaining on the stack that is larger than zero.’
tokens.append(Token(i, i, Token.Category.DEDENT))
indentation_levels.pop()
return tokens | PypiClean |
/CalimaPython-2.2.0-py3-none-any.whl/pycalima/cmdline.py |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from pycalima.Calima import Calima,FindCalimas
import sys, getopt, time
def printHelp():
print("\nCommand control and monitoring tool for PAX Calima fan. Let the air flow!\n")
print("-h\tshow this help list")
print("-l\tScan and list all found Calimas")
print("-m MAC\tSpecify Calima MAC address")
print("-p PIN\tSpecify Calima Pincode")
print("-s\tScan all characteristics")
print("-b SEC\tEnable Boost mode for SEC seconds")
print("-t SPD\tSet trickle speed to SPD in all modes. Use max 2000.")
print("\tWarning: this will make fan run at at this speed all the time")
def main():
# Define vars
action = ""
mac_address = ""
pincode = ""
boostsecs = 0
tricklespeed = 950
try:
opts, args = getopt.getopt(sys.argv[1:], "hb:lsm:p:t:")
except getopt.GetoptError:
printHelp()
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
printHelp()
sys.exit()
elif opt == '-l':
print(FindCalimas())
sys.exit()
elif opt in ("-m"):
mac_address = arg
elif opt in ("-p"):
pincode = arg
elif opt in ("-s"):
action = "scan"
elif opt == '-b':
action = "startboost"
boostsecs= int(arg)
elif opt == '-t':
action = "settrickle"
tricklespeed= int(arg)
else:
usage()
sys.exit(2)
if pincode == "" or mac_address == "":
print("You need to set both mac address and pincode to connect\n")
print("Run me with -h to get some help\n")
sys.exit(2)
fan = Calima(mac_address, pincode)
if action == "startboost":
print("Setting Boost mode for {} seconds".format(boostsecs))
fan.setBoostMode(1,2250,boostsecs)
time.sleep(2)
print(fan.getBoostMode())
fan.disconnect()
elif action == "scan":
fan.scanCharacteristics()
#currentState = fan.getStateShort()
#for item in currentState._fields:
# print("{}={} ".format(item,getattr(currentState, item)),end='')
fan.disconnect()
elif action == "settrickle":
print("Setting tricklespeed to {} ".format(tricklespeed))
fan.setFanSpeedSettings(2250,975,tricklespeed)
time.sleep(2)
print(fan.getFanSpeedSettings())
fan.disconnect()
else:
print("Device Name: ", fan.getDeviceName())
print("Model Number: ", fan.getModelNumber())
print("Serial Number: ", fan.getSerialNumber())
print("Hardware Revision: ", fan.getHardwareRevision())
print("Firmware Revision: ", fan.getFirmwareRevision())
print("Software Revision: ", fan.getSoftwareRevision())
print("Manufacturer: ", fan.getManufacturer())
print("Alias: ", fan.getAlias())
print("Factory Settings Changed: ", fan.getFactorySettingsChanged())
print("Mode: ", fan.getMode())
print("Fan Speed Settings: ", fan.getFanSpeedSettings())
print("Sensors Sensitivity: ", fan.getSensorsSensitivity())
print("Light Sensor Settings: ", fan.getLightSensorSettings())
print("Heat Distributor: ", fan.getHeatDistributor())
print("Boost Mode: ", fan.getBoostMode())
print("Led: ", fan.getLed())
print("Automatic Cycles: ", fan.getAutomaticCycles())
print("Time: ", fan.getTime())
print("Silent Hours: ", fan.getSilentHours())
print("Trickle Days: ", fan.getTrickleDays())
while True:
try:
print(fan.getState())
time.sleep(2)
except Exception as e:
print(e)
fan.disconnect()
break
if __name__ == '__main__':
main() | PypiClean |
/BuilT-0.0.4-py3-none-any.whl/built/registry.py | from __future__ import print_function
import logging
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader
from easydict import EasyDict as edict
from collections import defaultdict
from torchvision import datasets, transforms
from built.singleton_decorator import SingletonDecorator
from built.forward_hook import DefaultPostForwardHook
from built.metric import DefaultMetric
from built.logger import DefaultLogger
from built.models.mnist import Mnist
class Category:
"""Category class to save a category name and its name of classes"""
def __init__(self, name):
self._name = name
self._class_dict = dict()
def __repr__(self):
format_str = self.__class__.__name__
format_str += f'(name={self._name}, items={list(self._class_dict.keys())})'
return format_str
@property
def name(self):
return self._name
@property
def class_dict(self):
return self._class_dict
def get(self, key: str):
return self._class_dict.get(key, None)
def add(self, klass):
"""add a callable class.
Args:
klass: callable class to be registered
"""
if not callable(klass):
raise ValueError(f'object must be callable')
class_name = klass.__name__
if class_name in self._class_dict:
print(f'{class_name} is already registered in {self.name}')
else:
self._class_dict[class_name] = klass
return klass
class Registry:
"""Registry class to regist classes with categories"""
categories = dict()
# def __repr__(self):
# format_str = self.__class__.__name__
# for k, v in self.categories.items():
# format_str += f'(category[{k}]: {v})'
# return format_str
@classmethod
def clear(cls):
cls.categories.clear()
@classmethod
def add(cls, category, klass=None):
if category not in cls.categories:
cls.categories[category] = Category(category)
if klass is not None:
cls.categories[category].add(klass)
@classmethod
def register(cls, category=''):
def _register(klass):
return cls.add(category, klass)
return _register
@classmethod
def build_from_config(cls, category, config, default_args=None):
"""Build a callable object from configuation dict.
Args:
category: The name of category to search the name from.
config (dict): Configuration dict. It should contain the key "name".
default_args (dict, optional): Default initialization argments.
"""
assert isinstance(config, dict) and 'name' in config
assert isinstance(default_args, dict) or default_args is None
name = config['name']
name = name.replace('-', '_')
cls.add(category)
klass = cls.categories[category].get(name)
if klass is None:
raise KeyError(f'{name} is not in the {category} registry')
args = dict()
if default_args is not None:
args.update(default_args)
if 'params' in config:
args.update(config['params'])
return klass(**args) | PypiClean |
/HIRISEimgs-1.0.0.tar.gz/HIRISEimgs-1.0.0/HIRISE_api/hirise/utils.py | import requests
from bs4 import BeautifulSoup
def file_parameters_list():
"""
Function that returns file parameters list
"""
return [
"FILE_NAME",
"REQUIRED_STORAGE_BYTES",
"MISSION_PHASE_NAME",
"ORBIT_NUMBER",
]
def image_map_parameters_list():
"""
Function that returns image mapping parameters list
"""
return [
"CENTER_LATITUDE",
"CENTER_LONGITUDE",
"MAXIMUM_LATITUDE",
"MINIMUM_LATITUDE",
"EASTERNMOST_LONGITUDE",
"WESTERNMOST_LONGITUDE",
]
def viewing_parameters_list():
"""
Function that returns viewing parameters list
"""
return [
"INCIDENCE_ANGLE",
"EMISSION_ANGLE",
"PHASE_ANGLE",
"LOCAL_TIME",
"SOLAR_LONGITUDE",
"SUB_SOLAR_AZIMUTH",
"NORTH_AZIMUTH",
]
def timing_parameters_list():
"""
Function that returns timing parameters list
"""
return [
"MRO:OBSERVATION_START_TIME",
"START_TIME",
"SPACECRAFT_CLOCK_START_COUNT",
"STOP_TIME",
"SPACECRAFT_CLOCK_STOP_COUNT",
"PRODUCT_CREATION_TIME",
]
def other_parameters_list():
"""
Function that returns scaling factor, offset, center filter wavelength
parameters list
"""
return ["SCALING_FACTOR", "OFFSET", "CENTER_FILTER_WAVELENGTH"]
def LBL_parser(label_url):
"""
Function that parses the .LBL file in NASA's Planetary Data System
"""
# Get the data from the url
req = requests.get(label_url, stream=True)
lbl_file = req.text
lbl_dict = {
"file_parameters": {},
"image_map_parameters": {},
"viewing_parameters": {},
"timing_parameters": {},
"other_parameters": {},
}
# Select the parameters to save
file_parameters = file_parameters_list()
image_map_parameters = image_map_parameters_list()
viewing_parameters = viewing_parameters_list()
timing_parameters = timing_parameters_list()
other_parameters = other_parameters_list()
file_dict = dict.fromkeys(file_parameters, "")
image_dict = dict.fromkeys(image_map_parameters, "")
view_dict = dict.fromkeys(viewing_parameters, "")
time_dict = dict.fromkeys(timing_parameters, "")
other_dict = dict.fromkeys(other_parameters, "")
for line in lbl_file.split("\n"):
# Split the label data
if "=" in line:
line_array = line.split("=")
line_key = line_array[0].strip()
line_value = line_array[1].strip()
# Append required values in the respective df formats
if line_key in file_parameters:
file_dict[line_key] = line_value
elif line_key in viewing_parameters:
view_dict[line_key] = line_value
elif line_key in timing_parameters:
time_dict[line_key] = line_value
elif line_key in other_parameters:
other_dict[line_key] = line_value
elif line_key in image_map_parameters:
image_dict[line_key] = line_value
lbl_dict["file_parameters"] = file_dict
lbl_dict["image_map_parameters"] = image_dict
lbl_dict["viewing_parameters"] = view_dict
lbl_dict["timing_parameters"] = time_dict
lbl_dict["other_parameters"] = other_dict
return lbl_dict
def get_website_data(base_url, page_key, sub_key=None):
"""
Function that assistes in wescaping the NASA website
"""
if sub_key:
page_url = base_url + str(page_key) + "/" + sub_key
else:
page_url = base_url + str(page_key)
# Get the data from the url
req = requests.get(page_url)
# Use soup to create an HTML parser
soup = BeautifulSoup(req.text, "html.parser")
# Find all the labels with the correct tag - "a"
labels = soup.find_all("a")
# List to save orbital labels
page_labels = []
# Loop through all the orbital ranges
for i in range(1, len(labels)):
# Save orbital labels into a list
page_labels.append(labels[i]["href"])
return page_labels, len(page_labels)
def validate_append_float_data(param, list_of_params):
"""
Function that validates floating point data
"""
if param:
list_of_params.append(float(param.split("<")[0]))
else:
list_of_params.append(None)
def append_float_data_without_strip(param, list_of_params):
"""
Function that validates floating point data without stripping the last
characters
"""
if param:
list_of_params.append(float(param))
else:
list_of_params.append(None)
def downloadRange(start_range, end, step):
i = start_range
while i < end:
yield i
i += step
yield end | PypiClean |
/CocoRPy27-1.4.1.zip/CocoRPy27-1.4.1/pimaker/piBuilder.py | from fileTools import *
class Rule( object ):
def __init__( self, target, dependancies, action, description=None ):
global TARGET, NEEDS
self._target = target
self._description = description
self._dependancies = { } # dependency to rule
self._action = None
TARGET = self._target
NEEDS = [ ]
for dependancy in dependancies:
NEEDS.append( self.expandMacros(dependancy) )
for dependancy in NEEDS:
self._dependancies[ dependancy ] = None
self._action = self.expandMacros( action )
def getDependancies( self ):
return self._dependancies.keys( )
def getDescription( self ):
return self._description
def defineDependencyRule( self, dependencyName, Rule ):
self._dependancies[ dependencyName ] = Rule
def build( self ):
target = os.path.normpath( self._target )
# Handle subrules
if len( self._dependancies ) == 0:
needToRebuildTarget = True
else:
needToRebuildTarget = not os.path.exists( target )
for dependency, subrule in self._dependancies.iteritems( ):
dependency = os.path.normpath( dependency )
if not os.path.exists( dependency ):
if subrule:
subrule.build( )
print '-----------------------------------'
else:
raise Exception( 'No rule to build target %s' % dependency )
if os.path.exists( target ):
targetTime = os.stat( target ).st_mtime
dependencyTime = os.stat( dependency ).st_mtime
if dependencyTime > targetTime:
needToRebuildTarget = True
if needToRebuildTarget:
print 'Building: %s' % target
execActionCode( self._action )
def expandMacros( self, aString ):
macroStart = aString.find( '${' )
while macroStart != -1:
macroEnd = aString.find( '}', macroStart+2 )
macroSeq = aString[ macroStart+2 : macroEnd ].split( ',' )
if '.' in macroSeq[0]:
var,op = macroSeq[0].split('.')
else:
var = macroSeq[0]
op = None
value = globals( )[ var ]
if isinstance( value, (str,unicode) ):
if op == 'dir':
value = os.path.dirname( value )
elif op == 'name':
value = os.path.basename( value )
elif op == 'base':
value = os.path.splitext( os.path.basename( value ) )[0]
elif op == 'ext':
value = os.path.splitext( os.path.basename( value ) )[1]
if len(macroSeq) > 1:
mark = macroSeq[1].find( '=' )
if mark == -1:
raise Exception( 'Error in macro' )
old = macroSeq[1][ : mark ]
new = macroSeq[1][ mark+1 : ]
value = value.replace( old, new )
aString = aString[ :macroStart ] + value + aString[ macroEnd+1: ]
macroStart = aString.find( '${' )
elif isinstance( value, (list,tuple) ):
pass
return aString
class Builder( object ):
def __init__( self, projectName='' ):
self._rules = { }
self._topLevelTargets = [ ]
self._allTargets = [ ]
self._leaves = [ ]
self._projectName = projectName
self._menuOrder = [ ]
def addTarget( self, targets, *args ):
if isinstance( targets, str ):
targets = [ targets ]
numArgs = len( args )
if numArgs == 3:
# We have a description
description = args[0]
dependencies = args[1]
actions = args[2]
elif numArgs == 2:
# No description
description = None
dependencies = args[0]
actions = args[1]
else:
raise TypeError( 'addTarget() takes 3 or 4 arguments (%d given)' % numArgs )
for target in targets:
depend = [ ]
self._rules[ target ] = Rule( target, dependencies, actions, description )
self._menuOrder.append( target )
def finalize( self ):
# Assemble the Rules into a Tree
for target, rule in self._rules.iteritems( ):
for dependencyName in rule.getDependancies( ):
if dependencyName in self._rules:
rule.defineDependencyRule( dependencyName, self._rules[ dependencyName ] )
else:
if dependencyName not in self._leaves:
self._leaves.append( dependencyName )
# Determine the top-level targets
targets = self._rules.keys( )
for name in self._rules.keys( ):
for rule in self._rules.values( ):
if name in rule.getDependancies( ):
if name in targets:
targets.remove( name )
targets.sort()
self._topLevelTargets = [ ]
for targetName in self._menuOrder:
if targetName in targets:
self._topLevelTargets.append( ( targetName, self._rules[ targetName ].getDescription() ) )
# Create the allTargets list
self._allTargets = [ ]
for targetName in self._menuOrder:
descr = self._rules[ targetName ].getDescription()
if descr is not None:
self._allTargets.append( ( targetName, descr ) )
else:
self._allTargets.append( ( targetName, '' ) )
def targets( self ):
return self._rules.keys( )
def build( self, target ):
print '********** Building Target: %s...' % target
try:
theRule = self._rules[ target ]
theRule.build( )
print '********** Build completed.'
except:
type,value,trace = sys.exc_info( )
print 'BUILD FAILED!!!'
print traceback.print_exc( )
def topTargets( self ):
return self._topLevelTargets
def allTargets( self ):
return self._rules.keys( )
def initializationCode( self, code ):
execActionCode( code )
def goInteractive( self ):
print
print 'Entering Interactive Builder'
response = ''
self._buildMenu( self._topLevelTargets )
while response != 'exit':
target = raw_input( '\nbuild> ' )
if target == 'showall':
self._buildMenu( self._allTargets )
continue
elif target == 'exit':
break
elif target in self.allTargets( ):
print
print
self.build( target )
self._buildMenu( self._topLevelTargets )
else:
print ' !!! Unknown Target !!!'
def _buildMenu( self, targetList ):
print
print 'Targets:'
for targetName, targetDescription in targetList:
if targetDescription:
print ' %-20s %s' % ( targetName, targetDescription )
else:
print ' %-20s' % ( targetName )
print
print ' %-20s %s' % ( 'showall', 'Show the full list of targets.' )
print ' %-20s %s' % ( 'exit', 'Exit the interactive builder.' )
bld = Builder( )
def buildTarget( aTargetName ):
bld.build( aTargetName )
def execActionCode( code ):
exec code in globals( ) | PypiClean |
/Eve-SQLAlchemy-0.7.1.tar.gz/Eve-SQLAlchemy-0.7.1/eve_sqlalchemy/config/domainconfig.py | from __future__ import unicode_literals
from eve.utils import config
class DomainConfig(object):
"""Create an Eve `DOMAIN` dict out of :class:`ResourceConfig`s.
Upon rendering the `DOMAIN` dictionary, we will first collect all given
:class:`ResourceConfig` objects and pass them as `related_resource_configs`
to their `render` methods. This way each :class:`ResourceConfig` knows
about all existent endpoints in `DOMAIN` and can properly set up relations.
A special case occurs if one model is referenced for more than one
endpoint, e.g.:
DomainConfig({
'users': ResourceConfig(User),
'admins': ResourceConfig(User),
'groups': ResourceConfig(Group)
})
Here, we cannot reliably determine which resource should be used for
relations to `User`. In this case you have to specify the target resource
for all such relations:
DomainConfig({
'users': ResourceConfig(User),
'admins': ResourceConfig(User),
'groups': ResourceConfig(Group)
}, related_resources={
(Group, 'members'): 'users',
(Group, 'admins'): 'admins'
})
"""
def __init__(self, resource_configs, related_resources={}):
"""Initializes the :class:`DomainConfig` object.
:param resource_configs: mapping of endpoint names to
:class:`ResourceConfig` objects
:param related_resources: mapping of (model, field name) to a resource
"""
self.resource_configs = resource_configs
self.related_resources = related_resources
def render(self, date_created=config.DATE_CREATED,
last_updated=config.LAST_UPDATED, etag=config.ETAG):
"""Renders the Eve `DOMAIN` dictionary.
If you change any of `DATE_CREATED`, `LAST_UPDATED` or `ETAG`, make
sure you pass your new value.
:param date_created: value of `DATE_CREATED`
:param last_updated: value of `LAST_UPDATED`
:param etag: value of `ETAG`
"""
domain_def = {}
related_resource_configs = self._create_related_resource_configs()
for endpoint, resource_config in self.resource_configs.items():
domain_def[endpoint] = resource_config.render(
date_created, last_updated, etag, related_resource_configs)
return domain_def
def _create_related_resource_configs(self):
"""Creates a mapping from model to (resource, :class:`ResourceConfig`).
This mapping will be passed to all :class:`ResourceConfig` objects'
`render` methods.
If there is more than one resource using the same model, relations for
this model cannot be set up automatically. In this case you will have
to manually set `related_resources` when creating the
:class:`DomainConfig` object.
"""
result = {}
keys_to_remove = set()
for resource, resource_config in self.resource_configs.items():
model = resource_config.model
if model in result:
keys_to_remove.add(model)
result[model] = (resource, resource_config)
for key in keys_to_remove:
del result[key]
for field, resource in self.related_resources.items():
result[field] = (resource, self.resource_configs[resource])
return result | PypiClean |
/FaceChannelV1/Model.py | import numpy
from keras.models import load_model, Model, Input
from keras.models import Input
from keras.layers import Dense, Dropout, Flatten, Lambda
from keras.layers.convolutional import Conv2D, MaxPooling2D, AveragePooling2D
from keras.layers.core import Activation
from keras.layers.normalization import BatchNormalization
import os
import keras
"""Load Trained Models"""
"""Models from Scratch"""
def getDimensionalModel():
backbone = buildFaceChannel()
dense = Dense(200, activation="relu", name="denseLayer")(backbone)
arousal_output = Dense(units=1, activation='tanh', name='arousal_output')(dense)
valence_output = Dense(units=1, activation='tanh', name='valence_output')(dense)
return Model(inputs=backbone.input, outputs=[arousal_output, valence_output])
def getCategoricalModel(numberClasses):
backbone = buildFaceChannel()
dense = Dense(200, activation="relu", name="denseLayer")(backbone)
categoricalOutput = Dense(units=numberClasses, activation='tanh', name='categoricalOutput')(dense)
return Model(inputs=backbone.input, outputs=categoricalOutput)
def buildFaceChannel():
def shuntingInhibition(inputs):
inhibitionDecay = 0.5
v_c, v_c_inhibit = inputs
output = (v_c / (inhibitionDecay
+ v_c_inhibit))
return output
keras.backend.set_image_data_format("channels_first")
nch = 256
inputShape = numpy.array((1, 64, 64)).astype(numpy.int32)
inputLayer = Input(shape=inputShape, name="Vision_Network_Input")
# Conv1 and 2
conv1 = Conv2D(nch / 4, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv1")(
inputLayer)
bn1 = BatchNormalization(axis=1)(conv1)
actv1 = Activation("relu")(bn1)
conv2 = Conv2D(nch / 4, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv2")(actv1)
bn2 = BatchNormalization(axis=1)(conv2)
actv2 = Activation("relu")(bn2)
mp1 = MaxPooling2D(pool_size=(2, 2))(actv2)
drop1 = Dropout(0.25)(mp1)
# Conv 3 and 4
conv3 = Conv2D(nch / 2, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv3")(drop1)
bn3 = BatchNormalization(axis=1)(conv3)
actv3 = Activation("relu")(bn3)
conv4 = Conv2D(nch / 2, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv4")(actv3)
bn4 = BatchNormalization(axis=1)(conv4)
actv4 = Activation("relu")(bn4)
mp2 = MaxPooling2D(pool_size=(2, 2))(actv4)
drop2 = Dropout(0.25)(mp2)
# Conv 5 and 6 and 7
conv5 = Conv2D(nch / 2, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv5")(drop2)
bn5 = BatchNormalization(axis=1)(conv5)
actv5 = Activation("relu")(bn5)
conv6 = Conv2D(nch / 2, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv6")(actv5)
bn6 = BatchNormalization(axis=1)(conv6)
actv6 = Activation("relu")(bn6)
conv7 = Conv2D(nch / 2, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv7")(actv6)
bn7 = BatchNormalization(axis=1)(conv7)
actv7 = Activation("relu")(bn7)
mp3 = MaxPooling2D(pool_size=(2, 2))(actv7)
drop3 = Dropout(0.25)(mp3)
# Conv 8 and 9 and 10
conv8 = Conv2D(nch, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="Vision_conv8")(drop3)
bn8 = BatchNormalization(axis=1)(conv8)
actv8 = Activation("relu")(bn8)
conv9 = Conv2D(nch, (3, 3), padding="same", kernel_initializer="glorot_uniform", name="conv9")(actv8)
bn9 = BatchNormalization(axis=1)(conv9)
actv9 = Activation("relu")(bn9)
conv10 = Conv2D(nch, (3, 3), padding="same", kernel_initializer="glorot_uniform", activation="relu",
name="conv10")(actv9)
conv10_inhibition = Conv2D(nch, (3, 3), padding="same", kernel_initializer="glorot_uniform", activation="relu",
name="conv10_inhibition")(actv9)
v_conv_inhibitted = Lambda(function=shuntingInhibition)([conv10, conv10_inhibition])
mp4 = MaxPooling2D(pool_size=(2, 2))(v_conv_inhibitted)
drop4 = Dropout(0.25)(mp4)
flatten = Flatten()(drop4)
return flatten | PypiClean |
/EpyNN-1.2.11.tar.gz/EpyNN-1.2.11/epynn/convolution/parameters.py | import math
# Related third party imports
import numpy as np
def convolution_compute_shapes(layer, A):
"""Compute forward shapes and dimensions for layer.
"""
X = A # Input of current layer
layer.fs['X'] = X.shape # (m, h, w, d)
layer.d['m'] = layer.fs['X'][0] # Number of samples (m)
layer.d['h'] = layer.fs['X'][1] # Height of features (h)
layer.d['w'] = layer.fs['X'][2] # Width of features (w)
layer.d['d'] = layer.fs['X'][3] # Depth of features (d)
# Output height (oh) and width (ow)
layer.d['oh'] = math.floor((layer.d['h']-layer.d['fh']) / layer.d['sh']) + 1
layer.d['ow'] = math.floor((layer.d['w']-layer.d['fw']) / layer.d['sw']) + 1
# Shapes for trainable parameters
# filter_height (fh), filter_width (fw), features_depth (d), unit_filters (u)
layer.fs['W'] = (layer.d['fh'], layer.d['fw'], layer.d['d'], layer.d['u'])
layer.fs['b'] = (layer.d['u'], )
return None
def convolution_initialize_parameters(layer):
"""Initialize parameters for layer.
"""
# For linear activation of inputs (Z)
layer.p['W'] = layer.initialization(layer.fs['W'], rng=layer.np_rng)
layer.p['b'] = np.zeros(layer.fs['b']) # Z = X * W + b
return None
def convolution_compute_gradients(layer):
"""Compute gradients with respect to weight and bias for layer.
"""
# Gradients initialization with respect to parameters
for parameter in layer.p.keys():
gradient = 'd' + parameter
layer.g[gradient] = np.zeros_like(layer.p[parameter])
Xb = layer.fc['Xb'] # Input blocks of forward propagation
dZ = layer.bc['dZ'] # Gradient of the loss with respect to Z
# Expand dZ dimensions with respect to Xb
dZb = dZ
dZb = np.expand_dims(dZb, axis=3) # (m, oh, ow, 1, u)
dZb = np.expand_dims(dZb, axis=3) # (m, oh, ow, 1, 1, u)
dZb = np.expand_dims(dZb, axis=3) # (m, oh, ow, 1, 1, 1, u)
# (1) Gradient of the loss with respect to W, b
dW = layer.g['dW'] = np.sum(dZb * Xb, axis=(2, 1, 0)) # (1.1) dL/dW
db = layer.g['db'] = np.sum(dZb, axis=(2, 1, 0)) # (1.2) dL/db
layer.g['db'] = db.squeeze() if layer.use_bias else 0.
return None
def convolution_update_parameters(layer):
"""Update parameters for layer.
"""
for gradient in layer.g.keys():
parameter = gradient[1:]
# Update is driven by learning rate and gradients
layer.p[parameter] -= layer.lrate[layer.e] * layer.g[gradient]
return None | PypiClean |
/mynewspaper-4.0.tar.gz/mynewspaper-4.0/tools/migrate_db_from_v3_to_v4.py |
# CAUTION: this script migrates a MyNewspaper database from
# v3.x to v4.x format
# Copyright (C) 2013 Iñigo Serna
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
__author__ = 'Iñigo Serna'
__revision__ = '1.0'
import os
import os.path
import sys
import sqlite3
import datetime
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
sys.path.append(os.path.join(os.path.dirname(__file__), '../src'))
from utils import get_feed_icon
######################################################################
##### Variables
STMT_CREATE_DB = """
CREATE TABLE groups (
gid INTEGER PRIMARY KEY,
name VARCHAR(100) UNIQUE NOT NULL,
sort_idx INT,
num_total INT,
num_unread INT,
num_starred INT,
num_later INT,
num_archived INT
);
CREATE TABLE feeds (
fid INTEGER PRIMARY KEY,
name VARCHAR(100) UNIQUE NOT NULL,
url VARCHAR(255) NOT NULL,
link VARCHAR(255),
icon VARCHAR(255),
state INT, -- 0:archive, 1:enabled, 2:disabled, 3:broken
sort_idx INT,
gid INT,
etag VARCHAR(255),
lastupdate VARCHAR(100), -- feed sent timestamp, as string
artsperhour INT,
num_total INT,
num_unread INT,
num_starred INT,
num_later INT,
num_archived INT
);
CREATE INDEX idx_feeds_group ON feeds (gid);
CREATE TABLE articles (
aid INTEGER PRIMARY KEY,
uid VARCHAR(255) UNIQUE NOT NULL,
title VARCHAR(255),
url VARCHAR(255),
contents TEXT,
timestamp TIMESTAMP,
state INT, -- 0:total/delete, 1:unread, 2:starred, 3:later, 4:archived
fid INT
);
CREATE INDEX idx_articles_uid ON articles (uid);
CREATE INDEX idx_articles_state ON articles (state);
CREATE INDEX idx_articles_feed ON articles (fid);
INSERT INTO groups VALUES (0, 'Uncategorized', 0, 0, 0, 0, 0, 0);
INSERT INTO feeds VALUES (0, 'Archive', '', '', '', 0, 0, -1, '', '', 0, 0, 0, 0, 0, 0);
"""
######################################################################
##### Functions
class Feed:
def __init__(self, fid, name, link):
self.fid = fid
self.name = name
self.link = link
def __repr__(self):
return '<Feed {0.fid}: {0.name}>'.format(self)
def migrate_db(db_old, db_new, add_icons=True):
db0 = sqlite3.connect(db_old)
db0.row_factory = sqlite3.Row
c0 = db0.cursor()
print('Creating new DB')
db1 = sqlite3.connect(db_new)
db1.row_factory = sqlite3.Row
c1 = db1.cursor()
c1.executescript(STMT_CREATE_DB)
print('Migrating Folders')
c0.execute('SELECT * FROM rss_group')
for r in c0.fetchall():
c1.execute('INSERT INTO groups VALUES (?, ?, ?, 0, 0, 0, 0, 0)', (r['id'], r['name'], r['sort_idx']))
print('Migrating Feeds')
c0.execute('SELECT * FROM feed')
for r in c0.fetchall():
lastupdate = '' # datetime.datetime.strptime(r['lastupdate'], '%Y-%m-%d %H:%M:%S')
state = 2 if r['disabled'] else 1
c1.execute('INSERT INTO feeds VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, -1, 0, 0, 0, 0, 0)',
(r['id'], r['name'], r['url'], r['link'], '', state, r['sort_idx'],
r['rss_group_id'], r['etag'], lastupdate))
print('Migrating Articles')
c0.execute('SELECT * FROM article')
for r in c0.fetchall():
timestamp = r['timestamp'] + '+00:00'
if r['state'] == 2: state = 4 # archived
elif r['state'] == 3: state = 2 # starred
elif r['state'] == 4: state = 3 # later
else: state = r['state']
c1.execute('INSERT INTO articles VALUES (?, ?, ?, ?, ?, ?, ?, ?)',
(r['id'], r['aid'], r['title'], r['url'], r['contents'],
timestamp, state, r['feed_id']))
print('Fixing numbers')
ST = ('num_total', 'num_unread', 'num_starred', 'num_later', 'num_archived')
c1.execute('SELECT fid FROM feeds')
for r in c1.fetchall():
for st, it in enumerate(ST):
if st == 0: continue # num_total
stmt = 'UPDATE feeds SET %s=(SELECT COUNT(*) FROM articles WHERE fid=? AND state=%d) WHERE fid=?' % (it, st)
c1.execute(stmt, (r[0], r[0]))
c1.execute('UPDATE feeds SET num_total=num_unread+num_starred+num_later+num_archived WHERE fid=?', (r[0], ))
c1.execute('SELECT gid FROM groups')
for r in c1.fetchall():
for it in ST:
stmt = 'UPDATE groups SET %s=(SELECT COALESCE(SUM(%s), 0) FROM feeds WHERE gid=?) WHERE gid=?' % (it, it)
c1.execute(stmt, (r[0], r[0]))
if add_icons:
print('Adding feed icons... be patience, this will take some time')
c1.execute('SELECT fid, name, link FROM feeds')
feeds = [Feed(r['fid'], r['name'], r['link']) for r in c1.fetchall()]
with ThreadPoolExecutor(max_workers=10) as e:
futures_favicon = {e.submit(get_feed_icon, f): f for f in feeds}
for future in as_completed(futures_favicon):
try:
feed = futures_favicon[future]
icon_url = future.result()
except Exception as exc:
print('Error adding favicon for %s: %s' % (feed, exc))
else:
if icon_url is not None:
c1.execute('UPDATE feeds SET icon=? WHERE fid=?', (icon_url, feed.fid))
else:
print('Won\'t add feed icons')
db1.commit()
c0.close()
db0.close()
c1.close()
db1.close()
def main(db_old, db_new, add_icons=True):
t0 = time.time()
print('MyNewspaper DB migration tool v3 -> v4')
print('---------------------------------------')
print('Old DB: %s' % db_old)
print('New DB: %s' % db_new)
print
if not os.path.exists(db_old):
print('Old db file <%s> does not exist' % db_old)
sys.exit(-1)
if os.path.exists(db_new):
os.unlink(db_new)
migrate_db(db_old, db_new, add_icons)
tot = time.time() - t0
if tot > 60:
print('Migration finished in %d\'%2.2d"' % divmod(tot, 60))
else:
print('Migration finished in %d sec' % tot)
######################################################################
##### Main
if __name__ == '__main__':
if len(sys.argv) == 3 and sys.argv[1] != sys.argv[2]:
main(sys.argv[1], sys.argv[2])
elif len(sys.argv) == 4 and sys.argv[1] != sys.argv[2] and sys.argv[3] == '--no-favicons':
main(sys.argv[1], sys.argv[2], False)
else:
print('%s <old.db> <new.db> [--no-favicons]' % sys.argv[0])
sys.exit(-1)
###################################################################### | PypiClean |
/MagnetiCalc-1.15.2.tar.gz/MagnetiCalc-1.15.2/magneticalc/QtWidgets2/QLayouted.py |
# ISC License
#
# Copyright (c) 2020–2022, Paul Wilhelm, M. Sc. <[email protected]>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
from typing import Dict, Tuple, Callable, Union, Optional
from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import QVBoxLayout, QHBoxLayout, QLayout, QWidget, QPushButton
from magneticalc.QtWidgets2.QButtons import QButtons
class QLayouted:
""" QLayouted class. """
def __init__(self, direction: str = "vertical") -> None:
"""
Initializes the QLayouted class.
This adds a layout and several related functions like addWidget() to the parent class.
@param direction: Sets "vertical" or "horizontal" layout
"""
self._layout = QVBoxLayout() if direction == "vertical" else QHBoxLayout()
def install_layout(self, parent: QWidget) -> None:
"""
Installs this layout in the parent.
"""
parent.setLayout(self._layout)
# noinspection PyPep8Naming
def addWidget(self, widget, alignment: Optional[Union[Qt.Alignment, Qt.AlignmentFlag]] = None) -> None:
"""
Adds widget.
@param widget: QWidget
@param alignment: Alignment
"""
if alignment:
self._layout.addWidget(widget)
else:
self._layout.addWidget(widget)
# noinspection PyPep8Naming
def addLayout(self, layout: QLayout) -> None:
"""
Adds layout.
@param layout: QLayout
"""
self._layout.addLayout(layout)
# noinspection PyPep8Naming
def addSpacing(self, spacing: int) -> None:
"""
Adds spacing.
@param spacing: Spacing value
"""
self._layout.addSpacing(spacing)
# noinspection PyPep8Naming
def addButtons(self, data: Dict[str, Tuple[str, Callable]]) -> Dict[int, QPushButton]:
"""
Adds buttons.
@param data: Dictionary {text: (icon, callback), …}
@return: Dictionary {index: QPushButton, …}
"""
buttons = QButtons(data)
self.addLayout(buttons)
return buttons.dictionary | PypiClean |
/NeurIPS22-CellSeg-0.0.1.tar.gz/NeurIPS22-CellSeg-0.0.1/README.md | # NeurIPS-CellSeg
A naive baseline and submission demo for the [microscopy image segmentation challenge in NeurIPS 2022](https://neurips22-cellseg.grand-challenge.org/)
## Requirements
```python
MONAI version: 0.9
Numpy version: 1.21.2
Pytorch version: 1.10.1
Nibabel version: 3.2.1
scikit-image version: 0.19.2
Pillow version: 9.0.1
Tensorboard version: 2.8.0
gdown version: 4.2.0
TorchVision version: 0.11.2
tqdm version: 4.63.0
psutil version: 5.8.0
pandas version: 1.4.1
einops version: 0.3.2
```
## Preprocessing
Download training data to the `data` folder
Run `python pre_process_3class.py`
## Training
`cd baseline`
Run `python model_training_3class.py --data_path 'path to training data' --batch_size 8`
## Inference
Run
`python predict.py -i input_path -o output_path`
> Your prediction file should have at least the two arguments: `input_path` and `output_path`. The two arguments are important to establish connections between local folders and docker folders.
## Build Docker
We recommend this great tutorial: https://nbviewer.org/github/ericspod/ContainersForCollaboration/blob/master/ContainersForCollaboration.ipynb
### 1) Preparation
The docker is built on [MONAI](https://hub.docker.com/r/projectmonai/monai)
> docker pull projectmonai/monai
Prepare `Dockerfile`
```dockerfile
FROM projectmonai/monai:latest
WORKDIR /workspace
COPY ./ /workspace
```
Put the inference command in the `predict.sh`
```bash
# !/bin/bash -e
python predict.py -i "/workspace/inputs/" -o "/workspace/outputs/"
```
> The `input_path` and `output_path` augments should specify the corresponding docker workspace folders rather than local folders, because we will map the local folders to the docker workspace folders when running the docker container.
### 2) Build Docker and make sanity test
The submitted docker will be evaluated by the following command:
```bash
docker container run --gpus "device=0" --name teamname --rm -v $PWD/CellSeg_Test/:/workspace/inputs/ -v $PWD/teamname_outputs/:/workspace/outputs/ teamname:latest /bin/bash -c "sh predict.sh"
```
- `--name`: container name during running
- `--rm`: remove the container after running
- `-v $PWD/CellSeg_Test/:/workspace/inputs/`: map local image data folder to Docker `workspace/inputs` folder.
- `-v $PWD/teamname_outputs/:/workspace/outputs/ `: map Docker `workspace/outputs` folder to local folder. The segmentation results will be in `$PWD/teamname_outputs`
- `teamname:latest`: docker image name (should be `teamname`) and its version tag. **The version tag should be `latest`**. Please do not use `v0`, `v1`... as the version tag
- `/bin/bash -c "sh predict.sh"`: start the prediction command. It will load testing images from `workspace/inputs` and save the segmentation results to `workspace/outputs`
Assuming the team name is `baseline`, the Docker build command is
`docker build -t baseline . `
Test the docker to make sure it works. There should be segmentation results in the `baseline_outputs` folder.
```bash
docker container run --gpus "device=0" --name baseline --rm -v $PWD/CellSeg_Test/:/workspace/inputs/ -v $PWD/baseline_outputs/:/workspace/outputs/ baseline:latest /bin/bash -c "sh predict.sh"
```
> During the inference, please monitor the GPU memory consumption using `watch nvidia-smi`. The GPU memory consumption should be less than 1500MB. Otherwise, it will run into an OOM error on the official evaluation server. We impose this hard constraint on GPU memory consumption to ensure ease of use, because biologists may not have powerful GPUs in practice. Thus, the model should be low-resource.
### 3) Save Docker
`docker save baseline | gzip -c > baseline.tar.gz`
Upload the docker to Google drive or Baidu net disk and send the download link to `[email protected]`.
> Please **do not** upload the Docker to dockerhub!
## Limitations and potential improvements
The naive baseline's primary aim is to give participants out-of-the-box scripts that can generate successful submisions. Thus, there are many ways to surpass this baseline:
- New cell representation methods. In the baseline, we separated touching cells by simply removing their boundaries. More advanced cell representation could be used to address this issue, such as [stardist](https://github.com/stardist/stardist), [cellpose](https://github.com/MouseLand/cellpose), [omnipose](https://github.com/kevinjohncutler/omnipose), [deepcell](https://github.com/vanvalenlab/deepcell-tf), and so on.
- New architectures
- More data augmentations and the use of additional [public datasets](https://grand-challenge.org/forums/forum/weakly-supervised-cell-segmentation-in-multi-modality-microscopy-673/topic/official-external-datasets-thread-720/) or the set of unlabeled data provided.
- Well-designed training protocols
- Postprocessing
Nevertheless, please always keep in mind that many end users do not have powerful computation resources. It's important to consider the trade-off between resource consumption and accuracy.
| PypiClean |
/observations-0.1.4.tar.gz/observations-0.1.4/observations/r/beav2.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def beav2(path):
"""Body Temperature Series of Beaver 2
Reynolds (1994) describes a small part of a study of the long-term
temperature dynamics of beaver *Castor canadensis* in north-central
Wisconsin. Body temperature was measured by telemetry every 10 minutes
for four females, but data from a one period of less than a day for each
of two animals is used there.
The `beav2` data frame has 100 rows and 4 columns. This data frame
contains the following columns:
`day`
Day of observation (in days since the beginning of 1990), November
3–4.
`time`
Time of observation, in the form `0330` for 3.30am.
`temp`
Measured body temperature in degrees Celsius.
`activ`
Indicator of activity outside the retreat.
P. S. Reynolds (1994) Time-series analyses of beaver body temperatures.
Chapter 11 of Lange, N., Ryan, L., Billard, L., Brillinger, D.,
Conquest, L. and Greenhouse, J. eds (1994) *Case Studies in Biometry.*
New York: John Wiley and Sons.
Args:
path: str.
Path to directory which either stores file or otherwise file will
be downloaded and extracted there.
Filename is `beav2.csv`.
Returns:
Tuple of np.ndarray `x_train` with 100 rows and 4 columns and
dictionary `metadata` of column headers (feature names).
"""
import pandas as pd
path = os.path.expanduser(path)
filename = 'beav2.csv'
if not os.path.exists(os.path.join(path, filename)):
url = 'http://dustintran.com/data/r/MASS/beav2.csv'
maybe_download_and_extract(path, url,
save_file_name='beav2.csv',
resume=False)
data = pd.read_csv(os.path.join(path, filename), index_col=0,
parse_dates=True)
x_train = data.values
metadata = {'columns': data.columns}
return x_train, metadata | PypiClean |
/Flask-User-AWS-1.0.1.7.tar.gz/Flask-User-AWS-1.0.1.7/flask_user/password_manager.py |
from __future__ import print_function
from flask import current_app
from passlib.context import CryptContext
class PasswordManager(object):
"""Hash and verify user passwords using passlib """
def __init__(self, app):
"""
Create a passlib CryptContext.
Args:
password_hash(str): The name of a valid passlib password hash.
Examples: ``'bcrypt', 'pbkdf2_sha512', 'sha512_crypt' or 'argon2'``.
Example:
``password_manager = PasswordManager('bcrypt')``
"""
self.app = app
self.user_manager = app.user_manager
# Create a passlib CryptContext
self.password_crypt_context = CryptContext(
schemes=self.user_manager.USER_PASSLIB_CRYPTCONTEXT_SCHEMES,
**self.user_manager.USER_PASSLIB_CRYPTCONTEXT_KEYWORDS)
def hash_password(self, password):
"""Hash plaintext ``password`` using the ``password_hash`` specified in the constructor.
Args:
password(str): Plaintext password that the user types in.
Returns:
hashed password.
Example:
``user.password = hash_password('mypassword')``
"""
# Use passlib's CryptContext to hash a password
password_hash = self.password_crypt_context.encrypt(password)
return password_hash
def verify_password(self, password, password_hash):
"""Verify plaintext ``password`` against ``hashed password``.
Args:
password(str): Plaintext password that the user types in.
password_hash(str): Password hash generated by a previous call to ``hash_password()``.
Returns:
| True when ``password`` matches ``password_hash``.
| False otherwise.
Example:
::
if verify_password('mypassword', user.password):
login_user(user)
"""
# Print deprecation warning if called with (password, user) instead of (password, user.password)
if isinstance(password_hash, self.user_manager.db_manager.UserClass):
print(
'Deprecation warning: verify_password(password, user) has been changed'\
' to: verify_password(password, password_hash). The user param will be deprecated.'\
' Please change your call with verify_password(password, user) into'\
' a call with verify_password(password, user.password)'
' as soon as possible.')
password_hash = password_hash.password # effectively user.password
# Use passlib's CryptContext to verify a password
return self.password_crypt_context.verify(password, password_hash) | PypiClean |
/Lagranto-0.3.1.tar.gz/Lagranto-0.3.1/docs/tutorial_lagranto.rst | Tutorial
--------
The goal of this section is show how to calculate trajectories, analyzed them and plot them using the :ref:`lagranto-package`.
* `Calculation`_
* `Analyze`_
* `Plotting`_
* `Writing`_
Calculation
^^^^^^^^^^^
The :ref:`lagranto-package` provide a class, :class:`lagranto.LagrantoRun`, to wrap the Lagranto programs in python. It allow to calculate trajectories in parallel. You can take a look at the docstring to get familiar with the class.
Let's say that we want to calculate Warm Conveyor Belt trajectories for a 5 day period in June 2013.
Using Era-Interim we can start trajectories every 6 hour and we will calculate them for 48 hours forward in time. Since :class:`lagranto.LagrantoRun` needs a list of (startdate, enddate), we can build the dates as follow:
.. code-block:: python
from datetime import datetime, timedelta
from dypy.small_tools import interval
startdate = datetime(2013, 6, 1, 0)
enddate = startdate + timedelta(days=5)
dates = [(d, d + timedelta(hours=48)) for d in
interval(startdate, enddate, timedelta(hours=6))]
If the Era-interim data are in the `erainterim` folder and if the output files should be written in the `output` folder, then the :class:`lagranto.LagrantoRun` can be initialized as follow:
.. code-block:: python
from lagranto import LagrantoRun
lrun = LagrantoRun(dates, workingdir='erainterim',
outputdir='output', version='ecmwf')
We want to start the trajectories every 20km in the box [5E, 40E, 30N, 60N], so let's create a starting file:
.. code-block:: python
specifier = "'box.eqd(5,20,40,50,20)@profile(850,500,10)@hPa'"
out_create_startf = lrun.create_startf(startdate, specifier, tolist=True)
The `tolist` argument is needed if we want to use the same staring file for all starting time of the trajectories.
We can now calculate the trajectories, but first starting for a single date to test our setup:
.. code-block:: python
out_caltra = lrun.caltra(*dates[1])
We can also test tracing Q along a trajectories:
.. code-block:: python
out_trace = lrun.trace(dates[1][0], field='Q 1.')
We can now calculate and trace the trajectories in parallel, but for this we will use a tracevars file:
.. code-block:: python
tracevars = """Q 1. 0 P
U 1. 0 P
"""
out = lrun.run_parallel(trace_kw={'tracevars_content': tracevars}, type='both')
The `tracevars_content` keyword argument will be passed to trace to create a tracevars file with Q and U.
The `type` keyword argument determine what is run in parallel, currently both, trace, and caltra are available.
Analyze
^^^^^^^
Now that we have calculated trajectories let's read them and analyze them. By default the name of the files are formatted as `lsl_{:%Y%m%d%H}.4`.
So if we want to read the trajectories started at 00 UTC 01 June 2013 we can do as follow:
.. code-block:: python
from lagranto import Tra
filename_template = 'output/lsl_{:%Y%m%d%H}.4'
filename = filename_template.format(date=dates[-1][0])
trajs = Tra()
trajs.load_netcdf(filename)
print(trajs)
We can now test if the trajectories fulfill the standard criteria for WCB, an ascent greater than 500 hPa in 48 hours.
To make it clear, the goal of this exmple is not to replace the fortran routines of the LAGRANTO package but to illustrate the possibilities that python provides to analyze trajectories using a simple example.
.. code-block:: python
wcb_index = np.where((trajs['p'][:, :1] - trajs['p']) > 500)
wcb_trajs = Tra()
wcb_trajs.set_array(trajs[wcb_index[0], :])
print(wcb_trajs)
Plotting
^^^^^^^^
Now that we have WCB trajectories, let's plot them on a map. We will use cartopy for this.
.. code-block:: python
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from lagranto.plotting import plot_trajs
import matplotlib.pyplot as plt
crs = ccrs.Stereographic(central_longitude=180 - 170,
central_latitude=90 - 43,
true_scale_latitude=90 - 43)
fig = plt.figure()
ax = plt.axes(projection=crs)
land_50m = cfeature.NaturalEarthFeature('cultural', 'admin_0_countries',
'50m', edgecolor='gray',
facecolor='none', linewidth=0)
ax.add_feature(land_50m)
ax.set_extent([-10, 28, 30, 60])
plot_trajs(ax, wcb_trajs, 'p')
# fig.savefig('wcb_trajs_{date:%Y%m%d_%H}.pdf'.format(date=dates[-1][0]), bbox_inches='tight')
.. image :: images/wcb_trajs_20130529_18.png
Writing
^^^^^^^
The WCB trajectories can also be written to disk as follow:
.. code-block:: python
wcb_trajs.write_netcdf('output/wcb_trajs.nc')
| PypiClean |
/BIT_framework-0.0.2-py3-none-any.whl/BIT_DL/pytorch/modules/encoders/xlnet_encoder.py | import sys
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import functional as F
from BIT_DL.pytorch.modules.encoders.encoder_base import EncoderBase
from BIT_DL.pytorch.modules.pretrained.xlnet import PretrainedXLNetMixin
from BIT_DL.pytorch.modules.pretrained.xlnet_utils import (
PositionWiseFF, RelativeMultiheadAttention, RelativePositionalEncoding,
params_except_in)
from BIT_DL.pytorch.utils.utils import dict_fetch, sum_tensors
__all__ = [
"XLNetEncoder",
]
class XLNetEncoder(EncoderBase, PretrainedXLNetMixin):
r"""Raw XLNet module for encoding sequences. Please see
:class:`~BIT_DL.pytorch.modules.PretrainedXLNetMixin` for a brief description
of XLNet.
Args:
pretrained_model_name (optional): a `str`, the name
of pre-trained model (e.g., ``xlnet-based-cased``). Please refer to
:class:`~BIT_DL.pytorch.modules.PretrainedXLNetMixin` for
all supported models.
If `None`, the model name in :attr:`hparams` is used.
cache_dir (optional): the path to a folder in which the
pre-trained models will be cached. If `None` (default),
a default directory (``texar_data`` folder under user's home
directory) will be used.
hparams (dict or HParams, optional): Hyperparameters. Missing
hyperparameter will be set to default values. See
:meth:`default_hparams` for the hyperparameter structure
and default values.
"""
_IS_DECODE = False
def __init__(self,
pretrained_model_name: Optional[str] = None,
cache_dir: Optional[str] = None,
hparams=None):
super().__init__(hparams=hparams)
self.load_pretrained_config(pretrained_model_name, cache_dir)
num_layers = self._hparams.num_layers
num_heads = self._hparams.num_heads
head_dim = self._hparams.head_dim
self.word_embed = nn.Embedding(self._hparams.vocab_size,
self._hparams.hidden_dim)
self.pos_embed = RelativePositionalEncoding(
hparams={
"dim": self._hparams.hidden_dim,
"max_seq_len": self._hparams.max_seq_length,
})
self.dropout = nn.Dropout(self._hparams.dropout)
self.r_r_bias = None
self.r_w_bias = None
self.r_s_bias = None
if not self._hparams.untie_r:
self.r_r_bias = nn.Parameter(torch.Tensor(num_heads, head_dim))
self.r_w_bias = nn.Parameter(torch.Tensor(num_heads, head_dim))
self.r_s_bias = (nn.Parameter(torch.Tensor(num_heads, head_dim))
if self._hparams.use_segments else None)
self.attn_layers = nn.ModuleList()
self.ff_layers = nn.ModuleList()
rel_attn_hparams = dict_fetch(
self._hparams, RelativeMultiheadAttention.default_hparams())
ff_hparams = dict_fetch(
self._hparams, PositionWiseFF.default_hparams())
for _ in range(num_layers):
self.attn_layers.append(RelativeMultiheadAttention(
self.r_r_bias, self.r_w_bias, self.r_s_bias,
hparams=rel_attn_hparams))
self.ff_layers.append(PositionWiseFF(hparams=ff_hparams))
self.mask_emb = nn.Parameter(
torch.Tensor(1, 1, self._hparams.hidden_dim))
if self._IS_DECODE:
self.lm_bias = nn.Parameter(torch.zeros(self._hparams.vocab_size))
self.init_pretrained_weights()
@staticmethod
def default_hparams() -> Dict[str, Any]:
r"""Returns a dictionary of hyperparameters with default values.
* The encoder arch is determined by the constructor argument
:attr:`pretrained_model_name` if it's specified. In this case,
`hparams` are ignored.
* Otherwise, the encoder arch is determined by
`hparams['pretrained_model_name']` if it's specified. All other
configurations in `hparams` are ignored.
* If the above two are `None`, the encoder arch is defined by the
configurations in `hparams` and weights are randomly initialized.
.. code-block:: python
{
"pretrained_model_name": "xlnet-base-cased",
"untie_r": True,
"num_layers": 12,
"mem_len": 0,
"reuse_len": 0,
"num_heads": 12,
"hidden_dim": 768,
"head_dim": 64,
"dropout": 0.1,
"attention_dropout": 0.1,
"use_segments": True,
"ffn_inner_dim": 3072,
"activation": 'gelu',
"vocab_size": 32000,
"max_seq_length": 512,
"initializer": None,
"name": "xlnet_encoder",
}
Here:
The default parameters are values for cased XLNet-Base model.
`"pretrained_model_name"`: str or None
The name of the pre-trained XLNet model. If None, the model
will be randomly initialized.
`"untie_r"`: bool
Whether to untie the biases in attention.
`"num_layers"`: int
The number of stacked layers.
`"mem_len"`: int
The number of tokens to cache.
`"reuse_len"`: int
The number of tokens in the current batch to be cached and reused
in the future.
`"num_heads"`: int
The number of attention heads.
`"hidden_dim"`: int
The hidden size.
`"head_dim"`: int
The dimension size of each attention head.
`"dropout"`: float
Dropout rate.
`"attention_dropout"`: float
Dropout rate on attention probabilities.
`"use_segments"`: bool
Whether to use segment embedding.
`"ffn_inner_dim"`: int
The hidden size in feed-forward layers.
`"activation"`: str
`relu` or `gelu`.
`"vocab_size"`: int
The vocabulary size.
`"max_seq_length"`: int
The maximum sequence length for `RelativePositionalEncoding`.
`"initializer"`: dict, optional
Hyperparameters of the default initializer that initializes
variables created in this module.
See :func:`~BIT_DL.pytorch.core.get_initializer` for details.
`"name"`: str
Name of the module.
"""
return {
'pretrained_model_name': 'xlnet-base-cased',
'untie_r': True,
'num_layers': 12,
'mem_len': 0,
'reuse_len': 0,
# layer
'num_heads': 12,
'hidden_dim': 768,
'head_dim': 64,
'dropout': 0.1,
'attention_dropout': 0.1,
'use_segments': True,
# ffn
'ffn_inner_dim': 3072,
'activation': 'gelu',
# embedding
'vocab_size': 32000,
'max_seq_length': 512,
'initializer': None,
'name': "xlnet_encoder",
'@no_typecheck': ['pretrained_model_name'],
}
def param_groups(self,
lr: Optional[float] = None,
lr_layer_scale: float = 1.0,
decay_base_params: bool = False):
r"""Create parameter groups for optimizers. When
:attr:`lr_layer_decay_rate` is not 1.0, parameters from each layer form
separate groups with different base learning rates.
The return value of this method can be used in the constructor of
optimizers, for example:
.. code-block:: python
model = XLNetEncoder(...)
param_groups = model.param_groups(lr=2e-5, lr_layer_scale=0.8)
optim = torch.optim.Adam(param_groups)
Args:
lr (float): The learning rate. Can be omitted if
:attr:`lr_layer_decay_rate` is 1.0.
lr_layer_scale (float): Per-layer LR scaling rate. The `i`-th layer
will be scaled by `lr_layer_scale ^ (num_layers - i - 1)`.
decay_base_params (bool): If `True`, treat non-layer parameters
(e.g. embeddings) as if they're in layer 0. If `False`, these
parameters are not scaled.
Returns:
The parameter groups, used as the first argument for optimizers.
"""
if lr_layer_scale != 1.0:
if lr is None:
raise ValueError(
"lr must be specified when lr_layer_decay_rate is not 1.0")
num_layers = self._hparams.num_layers
base_group = {
"params": params_except_in(
self, ['attn_layers', 'ff_layers']),
"lr": lr * (lr_layer_scale ** num_layers
if decay_base_params else 1.0)
}
param_groups = [base_group]
for idx in range(num_layers):
decay_rate = lr_layer_scale ** (num_layers - idx - 1)
param_group = {
"params": [*self.attn_layers[idx].parameters(),
*self.ff_layers[idx].parameters()],
"lr": lr * decay_rate,
}
param_groups.append(param_group)
return param_groups
return self.parameters()
@property
def output_size(self):
r"""The feature size of :meth:`forward` output.
"""
return self._hparams.hidden_dim
@staticmethod
def _cache_mem(output: torch.Tensor,
prev_mem: Optional[torch.Tensor],
mem_len: int,
reuse_len: int = 0) -> torch.Tensor:
r"""Cache hidden states into memory."""
assert mem_len > 0
if reuse_len is not None and reuse_len > 0:
output = output[:reuse_len]
if prev_mem is None:
new_mem = output[-mem_len:]
else:
new_mem = torch.cat([prev_mem, output], dim=0)[-mem_len:]
return new_mem.detach()
def _create_causal_attn_mask(self,
seq_len: int,
mem_len: int,
same_length: bool = False) -> torch.Tensor:
r"""Create causal attention mask of shape
`(seq_len, mem_len + seq_len)`.
"""
assert self.r_w_bias is not None
device = self.r_w_bias.device
attn_mask = torch.ones(seq_len, seq_len, device=device)
mask_u = torch.triu(attn_mask, diagonal=1)
attn_mask_pad = torch.zeros(seq_len, mem_len, device=device)
ret = torch.cat([attn_mask_pad, mask_u], dim=1)
if same_length:
mask_l = torch.tril(attn_mask, diagonal=-1)
ret = torch.cat([ret[:, :seq_len] + mask_l, ret[:, seq_len:]], 1)
return ret
def forward(self, # type: ignore
inputs: Union[torch.Tensor, torch.LongTensor],
segment_ids: Optional[torch.LongTensor] = None,
input_mask: Optional[torch.Tensor] = None,
memory: Optional[List[torch.Tensor]] = None,
permute_mask: Optional[torch.Tensor] = None,
target_mapping: Optional[torch.Tensor] = None,
bi_data: bool = False,
clamp_len: Optional[int] = None,
cache_len: int = 0,
same_length: bool = False,
attn_type: str = 'bi',
two_stream: bool = False) \
-> Tuple[torch.Tensor, Optional[List[torch.Tensor]]]:
r"""Compute XLNet representations for the input.
Args:
inputs: Either a **2D Tensor** of shape `[batch_size, max_time]`,
containing the ids of tokens in input sequences, or
a **3D Tensor** of shape `[batch_size, max_time, vocab_size]`,
containing soft token ids (i.e., weights or probabilities)
used to mix the embedding vectors.
segment_ids: Shape `[batch_size, max_time]`.
input_mask: Float tensor of shape `[batch_size, max_time]`. Note
that positions with value 1 are masked out.
memory: Memory from previous batches. A list of length `num_layers`,
each tensor of shape `[batch_size, mem_len, hidden_dim]`.
permute_mask: The permutation mask. Float tensor of shape
`[batch_size, max_time, max_time]`.
A value of 0 for ``permute_mask[i, j, k]`` indicates that
position `i` attends to position `j` in batch `k`.
target_mapping: The target token mapping. Float tensor of shape
`[batch_size, num_targets, max_time]`.
A value of 1 for ``target_mapping[i, j, k]`` indicates that
the `i`-th target token (in order of permutation) in batch `k`
is the token at position `j`.
Each row ``target_mapping[i, :, k]`` can have no more than one
value of 1.
bi_data (bool): Whether to use bidirectional data input pipeline.
clamp_len (int): Clamp all relative distances larger than
:attr:`clamp_len`. A value of -1 means no clamping.
cache_len (int): Length of memory (number of tokens) to cache.
same_length (bool): Whether to use the same attention length for
each token.
attn_type (str): Attention type. Supported values are `"uni"`
and `"bi"`.
two_stream (bool): Whether to use two-stream attention. Only set to
`True` when pre-training or generating text. Defaults to
`False`.
:returns: A tuple of `(output, new_memory)`:
- **`output`**: The final layer output representations. Shape
`[batch_size, max_time, hidden_dim]`.
- **`new_memory`**: The memory of the current batch.
If `cache_len` is 0, then `new_memory` is `None`. Otherwise, it is
a list of length `num_layers`, each tensor of shape
`[batch_size, cache_len, hidden_dim]`.
This can be used as the :attr:`memory` argument in the next batch.
"""
if inputs.dim() == 2:
word_embeds = self.word_embed(inputs)
elif inputs.dim() == 3:
word_embeds = torch.tensordot(inputs, self.word_embed.weight,
dims=([-1], [0]))
else:
raise ValueError("'inputs' should be a 2D or 3D tensor.")
return self._forward(word_embed=word_embeds,
segment_ids=segment_ids,
input_mask=input_mask,
memory=memory,
permute_mask=permute_mask,
target_mapping=target_mapping,
bi_data=bi_data,
clamp_len=clamp_len,
cache_len=cache_len,
same_length=same_length,
attn_type=attn_type,
two_stream=two_stream)
def _forward(self,
word_embed: torch.Tensor,
segment_ids: Optional[torch.LongTensor] = None,
input_mask: Optional[torch.Tensor] = None,
memory: Optional[List[torch.Tensor]] = None,
permute_mask: Optional[torch.Tensor] = None,
target_mapping: Optional[torch.Tensor] = None,
bi_data: bool = False,
clamp_len: Optional[int] = None,
cache_len: int = 0,
same_length: bool = False,
attn_type: str = 'bi',
two_stream: bool = False) \
-> Tuple[torch.Tensor, Optional[List[torch.Tensor]]]:
r"""Compute XLNet representations for the input. This layer exists
because :class:`XLNetDecoder` compute embeddings in the decoder helper.
`word_embed` has shape `[batch_size, max_time, word_embed_dim]`.
Please refer to :meth:`forward` for the detailed information of other
arguments.
"""
# seq_len == max_time
# word_embed: [seq_len, batch_size, word_embed_dim]
word_embed = word_embed.permute(1, 0, 2)
# segment_ids: [seq_len, batch_size]
if segment_ids is not None:
segment_ids = segment_ids.permute(1, 0)
# input_mask: [seq_len, batch_size]
if input_mask is not None:
input_mask = input_mask.permute(1, 0)
# memory: A list of length num_layers
# each tensor of shape [mem_len, batch_size, hidden_dim]
if memory is not None:
memory = [m.permute(1, 0, 2) for m in memory]
# permute_mask: [seq_len, seq_len, batch_size]
if permute_mask is not None:
permute_mask = permute_mask.permute(1, 2, 0)
# target_mapping: [num_targets, seq_len, batch_size]
if target_mapping is not None:
target_mapping = target_mapping.permute(1, 2, 0)
seq_len, batch_size = word_embed.size()[:2]
mem_len = memory[0].size(0) if memory is not None else 0
tot_len = seq_len + mem_len
reuse_len = self._hparams.reuse_len
# Construct masks.
masks: List[Optional[torch.Tensor]] = []
# Causal attention mask.
if attn_type == 'uni':
causal_mask = self._create_causal_attn_mask(
seq_len, mem_len, same_length)
# attn_mask: (seq_len, tot_len, 1, 1)
causal_mask = causal_mask.unsqueeze(2).unsqueeze(3)
masks.append(causal_mask)
elif attn_type == 'bi':
pass
else:
raise ValueError(f"Unsupported attention type: {attn_type}")
# Data mask: input mask & permutation mask.
if input_mask is not None:
input_mask = input_mask.expand(seq_len, -1, -1)
data_mask = sum_tensors([input_mask, permute_mask])
if data_mask is not None:
# All positions in memory can be attended to.
memory_mask = data_mask.new_zeros(seq_len, mem_len, batch_size)
# data_mask: (seq_len, tot_len, batch_size, 1)
data_mask = torch.cat([memory_mask, data_mask], dim=1).unsqueeze(3)
masks.append(data_mask)
# Exclude the main diagonal (target tokens) from the mask.
attn_mask = sum_tensors(masks)
if attn_mask is None:
final_mask = None
else:
attn_mask = (attn_mask > 0)
final_mask = -torch.eye(seq_len, device=attn_mask.device)
final_mask = torch.cat([
final_mask.new_zeros(seq_len, mem_len), final_mask], dim=-1)
final_mask = final_mask.unsqueeze(2).unsqueeze(3)
# final_mask: (seq_len, tot_len, batch_size, 1)
final_mask = ((attn_mask.float() + final_mask) > 0)
# Construct segment embedding.
if segment_ids is not None:
concat_segment_ids = torch.cat([
segment_ids.new_zeros(mem_len, batch_size), segment_ids])
segment_matrix = (segment_ids.unsqueeze(1) !=
concat_segment_ids.unsqueeze(0)).long()
segment_matrix = F.one_hot(segment_matrix, num_classes=2).float()
else:
segment_matrix = None
pos_embed = self.pos_embed(
batch_size, seq_len, tot_len, clamp_len, attn_type, bi_data)
pos_embed = self.dropout(pos_embed)
states_h = self.dropout(word_embed)
states_g = None
if two_stream:
if target_mapping is not None:
word_embed_q = self.mask_emb.expand(
target_mapping.size(0), batch_size, -1)
else:
word_embed_q = word_embed
states_g = self.dropout(word_embed_q)
new_memory = []
for idx in range(self._hparams.num_layers):
cur_memory = memory[idx] if memory is not None else None
if cache_len > 0:
new_memory.append(self._cache_mem(
states_h, cur_memory, cache_len, reuse_len))
attn_layer: RelativeMultiheadAttention
attn_layer = self.attn_layers[idx] # type: ignore
states_h, states_g = attn_layer(
states_h=states_h, states_g=states_g,
pos_embed=pos_embed, segment_mat=segment_matrix,
attn_mask_h=final_mask, attn_mask_g=attn_mask,
target_mapping=target_mapping, memory=cur_memory)
states_h = self.ff_layers[idx](states_h)
if states_g is not None:
states_g = self.ff_layers[idx](states_g)
output = self.dropout(states_h if states_g is None else states_g)
# Now output: [seq_len, batch_size, hidden_dim]
# new_memory: None or A list of length num_layers,
# each tensor of shape [cache_len, batch_size, hidden_dim]
output = output.permute(1, 0, 2)
if new_memory is not None:
new_memory = [m.permute(1, 0, 2) for m in new_memory]
if cache_len == 0:
return output, None
return output, new_memory | PypiClean |
/CI_CloudConnector-0.60.zip/CI_CloudConnector-0.60/README.txt | Cloud Connector Python
-----------------------------
Created by Idop - 21.6.2016
reads Modbuc TCP \ EtherNetIP \ Simulation tags and send to web service using OAuth authentication
Runs on Python 2.7.9 and tested on raspberi Pi3 - debian Jesi OS
How to Operate:
------------------------------
After installing correctly all componenets you can run
sudo python CI_CloudConnector.py help
This will show all operating options
after testing is done you can operate application in production mode using
sudo python CI_CloudConnector.py MainLoop
Install Instructions
------------------------------
Project is uploaded to Open source directory "PIP"
run the next command to download and install the module
sudo pip install CI_CloudConnector
Trouble shotting
------------------------
ERROR: if pyhot.h missing run
Soultion: sudo apt-get install python-dev
ERROR: : error message when upgrading 'module object has no attribute _handlerList'
Soultion: run 'sudo pip uninstall logging'
running the application
-------------------------------
run the module from where it was deployed with help option to see instructions
importent: in the first run a config file will be created in /CI_LC/config.ini you must edit this file with server defenitions
sudo python CI_LocalConnector.py help
* dependencies should be installed automaticly (required modules : pip , pymodbus , cpppo
running the apllication at startup (linux)
------------------------------------------------
edit startupscript
sudo nano /etc/init.d/idopStartUp.sh
sudo chmod 755 /etc/init.d/idopStartUp.sh
sudo update-rc.d idopStartUp.sh defaults
to remove from startup
sudo update-rc.d -f idopStartUp.sh remove
inside this file we just call another shell
idopStartUp.sh
examples
-------------
#! /bin/sh
# /etc/init.d/idopStartUp.sh
bash /home/pi/CI_Projects/launcher.sh &
#!/bin/sh
# launcher.sh
#navigate home than to this directory then back home
cd /
cd /home/pi/CI_Projects
export PATH="$PATH:/usr/lib/python2.7:/usr/lib/python2.7/plat-arm-linux-gnueabihf:/usr/lib/python2.7/lib-tk:/usr/lib/python2.7/lib-old:/usr/lib/python2.7/lib-dynload:/home/pi/.local/lib/python2.7/site-packages:/usr/local/lib/python2.7/dist-packages:/usr/lib/python2.7/dist-packages:/usr/lib/python2.7/dist-packages/PILcompat:/usr/lib/python2.7/dist-packages/gtk-2.0:/usr/lib/pymodules/python2.7"
sudo python CI_LocalConnector.py MainLoop
cd / | PypiClean |
/564bff00ff_strawberry_graphql-0.168.2-py3-none-any.whl/strawberry/extensions/tracing/datadog.py | from __future__ import annotations
import hashlib
from inspect import isawaitable
from typing import TYPE_CHECKING, Any, Generator, Iterator, Optional
from ddtrace import tracer
from strawberry.extensions import SchemaExtension
from strawberry.extensions.tracing.utils import should_skip_tracing
from strawberry.utils.cached_property import cached_property
if TYPE_CHECKING:
from strawberry.types.execution import ExecutionContext
class DatadogTracingExtension(SchemaExtension):
def __init__(
self,
*,
execution_context: Optional[ExecutionContext] = None,
):
if execution_context:
self.execution_context = execution_context
@cached_property
def _resource_name(self):
assert self.execution_context.query
query_hash = self.hash_query(self.execution_context.query)
if self.execution_context.operation_name:
return f"{self.execution_context.operation_name}:{query_hash}"
return query_hash
def hash_query(self, query: str) -> str:
return hashlib.md5(query.encode("utf-8")).hexdigest()
def on_operation(self) -> Iterator[None]:
self._operation_name = self.execution_context.operation_name
span_name = (
f"{self._operation_name}" if self._operation_name else "Anonymous Query"
)
self.request_span = tracer.trace(
span_name,
resource=self._resource_name,
span_type="graphql",
service="strawberry",
)
self.request_span.set_tag("graphql.operation_name", self._operation_name)
operation_type = "query"
assert self.execution_context.query
if self.execution_context.query.strip().startswith("mutation"):
operation_type = "mutation"
if self.execution_context.query.strip().startswith("subscription"):
operation_type = "subscription"
self.request_span.set_tag("graphql.operation_type", operation_type)
yield
self.request_span.finish()
def on_validate(self) -> Generator[None, None, None]:
self.validation_span = tracer.trace("Validation", span_type="graphql")
yield
self.validation_span.finish()
def on_parse(self) -> Generator[None, None, None]:
self.parsing_span = tracer.trace("Parsing", span_type="graphql")
yield
self.parsing_span.finish()
async def resolve(self, _next, root, info, *args, **kwargs) -> Any:
if should_skip_tracing(_next, info):
result = _next(root, info, *args, **kwargs)
if isawaitable(result): # pragma: no cover
result = await result
return result
field_path = f"{info.parent_type}.{info.field_name}"
with tracer.trace(f"Resolving: {field_path}", span_type="graphql") as span:
span.set_tag("graphql.field_name", info.field_name)
span.set_tag("graphql.parent_type", info.parent_type.name)
span.set_tag("graphql.field_path", field_path)
span.set_tag("graphql.path", ".".join(map(str, info.path.as_list())))
result = _next(root, info, *args, **kwargs)
if isawaitable(result):
result = await result
return result
class DatadogTracingExtensionSync(DatadogTracingExtension):
def resolve(self, _next, root, info, *args, **kwargs) -> Any:
if should_skip_tracing(_next, info):
return _next(root, info, *args, **kwargs)
field_path = f"{info.parent_type}.{info.field_name}"
with tracer.trace(f"Resolving: {field_path}", span_type="graphql") as span:
span.set_tag("graphql.field_name", info.field_name)
span.set_tag("graphql.parent_type", info.parent_type.name)
span.set_tag("graphql.field_path", field_path)
span.set_tag("graphql.path", ".".join(map(str, info.path.as_list())))
return _next(root, info, *args, **kwargs) | PypiClean |
/Arachne-0.5.0.tar.gz/Arachne-0.5.0/CHANGES.md | Changelog
=========
Here you will find the full list of changes between each Arachne release
Version 0.5.0 (Nov 20th 2016)
---------------------
- Add support for Scrapy 1.0 ([#4](https://github.com/kirankoduru/arachne/issues/4))
Version 0.4.0 (Mar 17th 2016)
-----------------------------
- Renamed the endpoints `/spiders` as `/` for more intuitive purposes - ([#8](https://github.com/kirankoduru/arachne/issues/8))
- The `/run-spider` endpoint returns the name of spider and the status of the spider as running
Version 0.3.1 (Nov 25th 2015)
-----------------------------
- [BUG FIX] Whoops! Forgot to test if there were individual spider `scrapy_settings` available
Version 0.3.0 (Nov 23rd 2015)
-----------------------------
- Add individual spider settings to the `scrapy_settings` variable
- Add global spider settings to the `SCRAPY_SETTINGS` variable
Version 0.2.0 (Nov 15th 2015)
-----------------------------
- Export to CSV and JSON pipeline now available
Version 0.1.0 (Nov 14th 2015)
-----------------------------
- First public preview release
| PypiClean |
/Bis-Miner-3.11.1.tar.gz/Bis-Miner-3.11.0/Orange/widgets/data/owsql.py | import sys
from collections import OrderedDict
from AnyQt.QtWidgets import (
QLineEdit, QComboBox, QTextEdit, QMessageBox, QSizePolicy, QApplication)
from AnyQt.QtGui import QCursor
from AnyQt.QtCore import Qt, QTimer
from Orange.canvas import report
from Orange.data import Table
from Orange.data.sql.backend import Backend
from Orange.data.sql.backend.base import BackendError
from Orange.data.sql.table import SqlTable, LARGE_TABLE, AUTO_DL_LIMIT
from Orange.widgets import gui
from Orange.widgets.credentials import CredentialManager
from Orange.widgets.settings import Setting
from Orange.widgets.utils.itemmodels import PyListModel
from Orange.widgets.widget import OWWidget, Output, Msg
MAX_DL_LIMIT = 1000000
class TableModel(PyListModel):
def data(self, index, role=Qt.DisplayRole):
row = index.row()
if role == Qt.DisplayRole:
return str(self[row])
return super().data(index, role)
class BackendModel(PyListModel):
def data(self, index, role=Qt.DisplayRole):
row = index.row()
if role == Qt.DisplayRole:
return self[row].display_name
return super().data(index, role)
class OWSql(OWWidget):
name = "SQL表格"
id = "orange.widgets.data.sql"
description = "从SQL加载数据集"
icon = "icons/SQLTable.svg"
priority = 30
category = "Data"
keywords = ["data", "file", "load", "read", "SQL"]
class Outputs:
data = Output("数据", Table, doc="Attribute-valued dataset read from the input file.")
settings_version = 2
want_main_area = False
resizing_enabled = False
host = Setting(None)
port = Setting(None)
database = Setting(None)
schema = Setting(None)
username = ""
password = ""
table = Setting(None)
sql = Setting("")
guess_values = Setting(True)
download = Setting(False)
materialize = Setting(False)
materialize_table_name = Setting("")
class Information(OWWidget.Information):
data_sampled = Msg("Data description was generated from a sample.")
class Error(OWWidget.Error):
connection = Msg("{}")
no_backends = Msg("Please install a backend to use this widget")
missing_extension = Msg("Database is missing extension{}: {}")
def __init__(self):
super().__init__()
self.backend = None
self.data_desc_table = None
self.database_desc = None
vbox = gui.vBox(self.controlArea, "Server", addSpace=True)
box = gui.vBox(vbox)
self.backends = BackendModel(Backend.available_backends())
self.backendcombo = QComboBox(box)
if len(self.backends):
self.backendcombo.setModel(self.backends)
else:
self.Error.no_backends()
box.setEnabled(False)
box.layout().addWidget(self.backendcombo)
self.servertext = QLineEdit(box)
self.servertext.setPlaceholderText('Server')
self.servertext.setToolTip('Server')
self.servertext.editingFinished.connect(self._load_credentials)
if self.host:
self.servertext.setText(self.host if not self.port else
'{}:{}'.format(self.host, self.port))
box.layout().addWidget(self.servertext)
self.databasetext = QLineEdit(box)
self.databasetext.setPlaceholderText('Database[/Schema]')
self.databasetext.setToolTip('Database or optionally Database/Schema')
if self.database:
self.databasetext.setText(
self.database if not self.schema else
'{}/{}'.format(self.database, self.schema))
box.layout().addWidget(self.databasetext)
self.usernametext = QLineEdit(box)
self.usernametext.setPlaceholderText('Username')
self.usernametext.setToolTip('Username')
box.layout().addWidget(self.usernametext)
self.passwordtext = QLineEdit(box)
self.passwordtext.setPlaceholderText('Password')
self.passwordtext.setToolTip('Password')
self.passwordtext.setEchoMode(QLineEdit.Password)
box.layout().addWidget(self.passwordtext)
self._load_credentials()
self.tables = TableModel()
tables = gui.hBox(box)
self.tablecombo = QComboBox(
minimumContentsLength=35,
sizeAdjustPolicy=QComboBox.AdjustToMinimumContentsLength
)
self.tablecombo.setModel(self.tables)
self.tablecombo.setToolTip('table')
tables.layout().addWidget(self.tablecombo)
self.connect()
index = self.tablecombo.findText(str(self.table))
if index != -1:
self.tablecombo.setCurrentIndex(index)
# set up the callback to select_table in case of selection change
self.tablecombo.activated[int].connect(self.select_table)
self.connectbutton = gui.button(
tables, self, '↻', callback=self.connect)
self.connectbutton.setSizePolicy(
QSizePolicy.Fixed, QSizePolicy.Fixed)
tables.layout().addWidget(self.connectbutton)
self.custom_sql = gui.vBox(box)
self.custom_sql.setVisible(False)
self.sqltext = QTextEdit(self.custom_sql)
self.sqltext.setPlainText(self.sql)
self.custom_sql.layout().addWidget(self.sqltext)
mt = gui.hBox(self.custom_sql)
cb = gui.checkBox(mt, self, 'materialize', 'Materialize to table ')
cb.setToolTip('Save results of the query in a table')
le = gui.lineEdit(mt, self, 'materialize_table_name')
le.setToolTip('Save results of the query in a table')
self.executebtn = gui.button(
self.custom_sql, self, 'Execute', callback=self.open_table)
box.layout().addWidget(self.custom_sql)
gui.checkBox(box, self, "guess_values",
"Auto-discover categorical variables",
callback=self.open_table)
gui.checkBox(box, self, "download",
"Download data to local memory",
callback=self.open_table)
gui.rubber(self.buttonsArea)
QTimer.singleShot(0, self.select_table)
def _load_credentials(self):
self._parse_host_port()
cm = self._credential_manager(self.host, self.port)
self.username = cm.username
self.password = cm.password
if self.username:
self.usernametext.setText(self.username)
if self.password:
self.passwordtext.setText(self.password)
def _save_credentials(self):
cm = self._credential_manager(self.host, self.port)
cm.username = self.username or ''
cm.password = self.password or ''
def _credential_manager(self, host, port):
return CredentialManager("SQL Table: {}:{}".format(host, port))
def error(self, id=0, text=""):
super().error(id, text)
err_style = 'QLineEdit {border: 2px solid red;}'
if 'server' in text or 'host' in text:
self.servertext.setStyleSheet(err_style)
else:
self.servertext.setStyleSheet('')
if 'role' in text:
self.usernametext.setStyleSheet(err_style)
else:
self.usernametext.setStyleSheet('')
if 'database' in text:
self.databasetext.setStyleSheet(err_style)
else:
self.databasetext.setStyleSheet('')
def _parse_host_port(self):
hostport = self.servertext.text().split(':')
self.host = hostport[0]
self.port = hostport[1] if len(hostport) == 2 else None
def connect(self):
self._parse_host_port()
self.database, _, self.schema = self.databasetext.text().partition('/')
self.username = self.usernametext.text() or None
self.password = self.passwordtext.text() or None
try:
if self.backendcombo.currentIndex() < 0:
return
backend = self.backends[self.backendcombo.currentIndex()]
self.backend = backend(dict(
host=self.host,
port=self.port,
database=self.database,
user=self.username,
password=self.password
))
self.Error.connection.clear()
self._save_credentials()
self.database_desc = OrderedDict((
("Host", self.host), ("Port", self.port),
("Database", self.database), ("User name", self.username)
))
self.refresh_tables()
except BackendError as err:
error = str(err).split('\n')[0]
self.Error.connection(error)
self.database_desc = self.data_desc_table = None
self.tablecombo.clear()
def refresh_tables(self):
self.tables.clear()
self.Error.missing_extension.clear()
if self.backend is None:
self.data_desc_table = None
return
self.tables.append("Select a table")
self.tables.append("Custom SQL")
self.tables.extend(self.backend.list_tables(self.schema))
# Called on tablecombo selection change:
def select_table(self):
curIdx = self.tablecombo.currentIndex()
if self.tablecombo.itemText(curIdx) != "Custom SQL":
self.custom_sql.setVisible(False)
return self.open_table()
else:
self.custom_sql.setVisible(True)
self.data_desc_table = None
self.database_desc["Table"] = "(None)"
self.table = None
if len(str(self.sql)) > 14:
return self.open_table()
#self.Error.missing_extension(
# 's' if len(missing) > 1 else '',
# ', '.join(missing),
# shown=missing)
def open_table(self):
table = self.get_table()
self.data_desc_table = table
self.Outputs.data.send(table)
def get_table(self):
curIdx = self.tablecombo.currentIndex()
if curIdx <= 0:
if self.database_desc:
self.database_desc["Table"] = "(None)"
self.data_desc_table = None
return
if self.tablecombo.itemText(curIdx) != "Custom SQL":
self.table = self.tables[self.tablecombo.currentIndex()]
self.database_desc["Table"] = self.table
if "Query" in self.database_desc:
del self.database_desc["Query"]
what = self.table
else:
what = self.sql = self.sqltext.toPlainText()
self.table = "Custom SQL"
if self.materialize:
import psycopg2
if not self.materialize_table_name:
self.Error.connection(
"Specify a table name to materialize the query")
return
try:
with self.backend.execute_sql_query("DROP TABLE IF EXISTS " +
self.materialize_table_name):
pass
with self.backend.execute_sql_query("CREATE TABLE " +
self.materialize_table_name +
" AS " + self.sql):
pass
with self.backend.execute_sql_query("ANALYZE " + self.materialize_table_name):
pass
except (psycopg2.ProgrammingError, BackendError) as ex:
self.Error.connection(str(ex))
return
try:
table = SqlTable(dict(host=self.host,
port=self.port,
database=self.database,
user=self.username,
password=self.password),
what,
backend=type(self.backend),
inspect_values=False)
except BackendError as ex:
self.Error.connection(str(ex))
return
self.Error.connection.clear()
sample = False
if table.approx_len() > LARGE_TABLE and self.guess_values:
confirm = QMessageBox(self)
confirm.setIcon(QMessageBox.Warning)
confirm.setText("Attribute discovery might take "
"a long time on large tables.\n"
"Do you want to auto discover attributes?")
confirm.addButton("Yes", QMessageBox.YesRole)
no_button = confirm.addButton("No", QMessageBox.NoRole)
sample_button = confirm.addButton("Yes, on a sample",
QMessageBox.YesRole)
confirm.exec()
if confirm.clickedButton() == no_button:
self.guess_values = False
elif confirm.clickedButton() == sample_button:
sample = True
self.Information.clear()
if self.guess_values:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
if sample:
s = table.sample_time(1)
domain = s.get_domain(inspect_values=True)
self.Information.data_sampled()
else:
domain = table.get_domain(inspect_values=True)
QApplication.restoreOverrideCursor()
table.domain = domain
if self.download:
if table.approx_len() > MAX_DL_LIMIT:
QMessageBox.warning(
self, 'Warning', "Data is too big to download.\n"
"Consider using the Data Sampler widget to download "
"a sample instead.")
self.download = False
elif table.approx_len() > AUTO_DL_LIMIT:
confirm = QMessageBox.question(
self, 'Question', "Data appears to be big. Do you really "
"want to download it to local memory?",
QMessageBox.Yes | QMessageBox.No, QMessageBox.No)
if confirm == QMessageBox.No:
self.download = False
if self.download:
table.download_data(MAX_DL_LIMIT)
table = Table(table)
return table
def send_report(self):
if not self.database_desc:
self.report_paragraph("No database connection.")
return
self.report_items("Database", self.database_desc)
if self.data_desc_table:
self.report_items("Data",
report.describe_data(self.data_desc_table))
@classmethod
def migrate_settings(cls, settings, version):
if version < 2:
# Until Orange version 3.4.4 username and password had been stored
# in Settings.
cm = cls._credential_manager(settings["host"], settings["port"])
cm.username = settings["username"]
cm.password = settings["password"]
if __name__ == "__main__":
a = QApplication(sys.argv)
ow = OWSql()
ow.show()
a.exec_()
ow.saveSettings() | PypiClean |
/MTGA-0.9.5-py3-none-any.whl/mtga/set_data/eld.py | import sys
from mtga.models.card import Card
from mtga.models.card_set import Set
import inspect
AllThatGlitters = Card(name="all_that_glitters", pretty_name="All That Glitters", cost=['1', 'W'],
color_identity=['W'], card_type="Enchantment", sub_types="Aura",
abilities=[1027, 136335], set_id="ELD", rarity="Uncommon", collectible=True, set_number=2,
mtga_id=70149)
ShiningArmor = Card(name="shining_armor", pretty_name="Shining Armor", cost=['1', 'W'],
color_identity=['W'], card_type="Artifact", sub_types="Equipment",
abilities=[7, 136241, 7610, 1156], set_id="ELD", rarity="Common", collectible=True, set_number=29,
mtga_id=70176)
VenerableKnight = Card(name="venerable_knight", pretty_name="Venerable Knight", cost=['W'],
color_identity=['W'], card_type="Creature", sub_types="Human Knight",
abilities=[136079], set_id="ELD", rarity="Uncommon", collectible=True, set_number=35,
mtga_id=70182)
AnimatingFaerie = Card(name="animating_faerie", pretty_name="Animating Faerie", cost=['2', 'U'],
color_identity=['U'], card_type="Creature", sub_types="Faerie",
abilities=[8], set_id="ELD", rarity="Uncommon", collectible=True, set_number=38,
mtga_id=70185)
CorridorMonitor = Card(name="corridor_monitor", pretty_name="Corridor Monitor", cost=['1', 'U'],
color_identity=['U'], card_type="Artifact Creature", sub_types="Construct",
abilities=[136084], set_id="ELD", rarity="Common", collectible=True, set_number=41,
mtga_id=70188)
FaerieVandal = Card(name="faerie_vandal", pretty_name="Faerie Vandal", cost=['1', 'U'],
color_identity=['U'], card_type="Creature", sub_types="Faerie Rogue",
abilities=[7, 8, 136108], set_id="ELD", rarity="Uncommon", collectible=True, set_number=45,
mtga_id=70192)
Frogify = Card(name="frogify", pretty_name="Frogify", cost=['1', 'U'],
color_identity=['U'], card_type="Enchantment", sub_types="Aura",
abilities=[1027, 136125], set_id="ELD", rarity="Uncommon", collectible=True, set_number=47,
mtga_id=70194)
RunAwayTogether = Card(name="run_away_together", pretty_name="Run Away Together", cost=['1', 'U'],
color_identity=['U'], card_type="Instant", sub_types="",
abilities=[136218], set_id="ELD", rarity="Common", collectible=True, set_number=62,
mtga_id=70209)
WitchingWell = Card(name="witching_well", pretty_name="Witching Well", cost=['U'],
color_identity=['U'], card_type="Artifact", sub_types="",
abilities=[100685, 136240], set_id="ELD", rarity="Common", collectible=True, set_number=74,
mtga_id=70221)
BakeintoaPie = Card(name="bake_into_a_pie", pretty_name="Bake into a Pie", cost=['2', 'B', 'B'],
color_identity=['B'], card_type="Instant", sub_types="",
abilities=[136246], set_id="ELD", rarity="Common", collectible=True, set_number=76,
mtga_id=70223)
BelleoftheBrawl = Card(name="belle_of_the_brawl", pretty_name="Belle of the Brawl", cost=['2', 'B'],
color_identity=['B'], card_type="Creature", sub_types="Human Knight",
abilities=[142, 136248], set_id="ELD", rarity="Uncommon", collectible=True, set_number=78,
mtga_id=70225)
FoulmireKnight = Card(name="foulmire_knight", pretty_name="Foulmire Knight", cost=['B'],
color_identity=['B'], card_type="Creature", sub_types="Zombie Knight",
abilities=[1], set_id="ELD", rarity="Uncommon", collectible=True, set_number=90,
mtga_id=70237)
OrderofMidnight = Card(name="order_of_midnight", pretty_name="Order of Midnight", cost=['1', 'B'],
color_identity=['B'], card_type="Creature", sub_types="Human Knight",
abilities=[8, 86476], set_id="ELD", rarity="Uncommon", collectible=True, set_number=99,
mtga_id=70246)
SmittenSwordmaster = Card(name="smitten_swordmaster", pretty_name="Smitten Swordmaster", cost=['1', 'B'],
color_identity=['B'], card_type="Creature", sub_types="Human Knight",
abilities=[12], set_id="ELD", rarity="Common", collectible=True, set_number=105,
mtga_id=70252)
SyrKonradtheGrim = Card(name="syr_konrad_the_grim", pretty_name="Syr Konrad, the Grim", cost=['3', 'B', 'B'],
color_identity=['B'], card_type="Creature", sub_types="Human Knight",
abilities=[136076, 136077], set_id="ELD", rarity="Uncommon", collectible=True, set_number=107,
mtga_id=70254)
CrystalSlipper = Card(name="crystal_slipper", pretty_name="Crystal Slipper", cost=['1', 'R'],
color_identity=['R'], card_type="Artifact", sub_types="Equipment",
abilities=[136299, 1268], set_id="ELD", rarity="Common", collectible=True, set_number=119,
mtga_id=70266)
EmberethShieldbreaker = Card(name="embereth_shieldbreaker", pretty_name="Embereth Shieldbreaker", cost=['1', 'R'],
color_identity=['R'], card_type="Creature", sub_types="Human Knight",
abilities=[], set_id="ELD", rarity="Uncommon", collectible=True, set_number=122,
mtga_id=70269)
BeanstalkGiant = Card(name="beanstalk_giant", pretty_name="Beanstalk Giant", cost=['6', 'G'],
color_identity=['G'], card_type="Creature", sub_types="Giant",
abilities=[88259], set_id="ELD", rarity="Uncommon", collectible=True, set_number=149,
mtga_id=70296)
KeeperofFables = Card(name="keeper_of_fables", pretty_name="Keeper of Fables", cost=['3', 'G', 'G'],
color_identity=['G'], card_type="Creature", sub_types="Cat",
abilities=[136258], set_id="ELD", rarity="Uncommon", collectible=True, set_number=163,
mtga_id=70310)
RosethornAcolyte = Card(name="rosethorn_acolyte", pretty_name="Rosethorn Acolyte", cost=['2', 'G'],
color_identity=['G'], card_type="Creature", sub_types="Elf Druid",
abilities=[1055], set_id="ELD", rarity="Common", collectible=True, set_number=174,
mtga_id=70321)
GarrukCursedHuntsman = Card(name="garruk_cursed_huntsman", pretty_name="Garruk, Cursed Huntsman", cost=['4', 'B', 'G'],
color_identity=['B', 'G'], card_type="Planeswalker", sub_types="Garruk",
abilities=[136126, 104880, 136128], set_id="ELD", rarity="Mythic Rare", collectible=True, set_number=191,
mtga_id=70338)
InspiringVeteran = Card(name="inspiring_veteran", pretty_name="Inspiring Veteran", cost=['R', 'W'],
color_identity=['R', 'W'], card_type="Creature", sub_types="Human Knight",
abilities=[119104], set_id="ELD", rarity="Uncommon", collectible=True, set_number=194,
mtga_id=70341)
MaraleafPixie = Card(name="maraleaf_pixie", pretty_name="Maraleaf Pixie", cost=['G', 'U'],
color_identity=['G', 'U'], card_type="Creature", sub_types="Faerie",
abilities=[8, 18504], set_id="ELD", rarity="Uncommon", collectible=True, set_number=196,
mtga_id=70343)
SavvyHunter = Card(name="savvy_hunter", pretty_name="Savvy Hunter", cost=['1', 'B', 'G'],
color_identity=['B', 'G'], card_type="Creature", sub_types="Human Warrior",
abilities=[136251, 136147], set_id="ELD", rarity="Uncommon", collectible=True, set_number=200,
mtga_id=70347)
Shinechaser = Card(name="shinechaser", pretty_name="Shinechaser", cost=['1', 'W', 'U'],
color_identity=['W', 'U'], card_type="Creature", sub_types="Faerie",
abilities=[8, 15, 103355, 136148], set_id="ELD", rarity="Uncommon", collectible=True, set_number=201,
mtga_id=70348)
SteelclawLance = Card(name="steelclaw_lance", pretty_name="Steelclaw Lance", cost=['B', 'R'],
color_identity=['B', 'R'], card_type="Artifact", sub_types="Equipment",
abilities=[2512, 136149, 1156], set_id="ELD", rarity="Uncommon", collectible=True, set_number=202,
mtga_id=70349)
WintermoorCommander = Card(name="wintermoor_commander", pretty_name="Wintermoor Commander", cost=['W', 'B'],
color_identity=['W', 'B'], card_type="Creature", sub_types="Human Knight",
abilities=[1, 136151, 136152], set_id="ELD", rarity="Uncommon", collectible=True, set_number=205,
mtga_id=70352)
ArcanistsOwl = Card(name="arcanists_owl", pretty_name="Arcanist's Owl", cost=['(W/U)', '(W/U)', '(W/U)', '(W/U)'],
color_identity=['W', 'U'], card_type="Artifact Creature", sub_types="Bird",
abilities=[8, 136153], set_id="ELD", rarity="Uncommon", collectible=True, set_number=206,
mtga_id=70353)
FirebornKnight = Card(name="fireborn_knight", pretty_name="Fireborn Knight", cost=['(R/W)', '(R/W)', '(R/W)', '(R/W)'],
color_identity=['R', 'W'], card_type="Creature", sub_types="Human Knight",
abilities=[3, 136269], set_id="ELD", rarity="Uncommon", collectible=True, set_number=210,
mtga_id=70357)
GoldenEgg = Card(name="golden_egg", pretty_name="Golden Egg", cost=['2'],
color_identity=[], card_type="Artifact", sub_types="Food",
abilities=[86788, 88207, 136278], set_id="ELD", rarity="Common", collectible=True, set_number=220,
mtga_id=70367)
HeraldicBanner = Card(name="heraldic_banner", pretty_name="Heraldic Banner", cost=['3'],
color_identity=[], card_type="Artifact", sub_types="",
abilities=[88237, 136279, 2374], set_id="ELD", rarity="Uncommon", collectible=True, set_number=222,
mtga_id=70369)
ShamblingSuit = Card(name="shambling_suit", pretty_name="Shambling Suit", cost=['3'],
color_identity=[], card_type="Artifact Creature", sub_types="Construct",
abilities=[1316], set_id="ELD", rarity="Uncommon", collectible=True, set_number=230,
mtga_id=70377)
WitchsOven = Card(name="witchs_oven", pretty_name="Witch's Oven", cost=['1'],
color_identity=[], card_type="Artifact", sub_types="",
abilities=[136178], set_id="ELD", rarity="Uncommon", collectible=True, set_number=237,
mtga_id=70384)
TournamentGrounds = Card(name="tournament_grounds", pretty_name="Tournament Grounds", cost=[],
color_identity=['W', 'B', 'R'], card_type="Land", sub_types="",
abilities=[1152, 136198], set_id="ELD", rarity="Uncommon", collectible=True, set_number=248,
mtga_id=70395)
Plains = Card(name="plains", pretty_name="Plains", cost=[],
color_identity=['W'], card_type="Land", sub_types="Plains",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=250,
mtga_id=70397)
Plains2 = Card(name="plains", pretty_name="Plains", cost=[],
color_identity=['W'], card_type="Land", sub_types="Plains",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=251,
mtga_id=70398)
Plains3 = Card(name="plains", pretty_name="Plains", cost=[],
color_identity=['W'], card_type="Land", sub_types="Plains",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=252,
mtga_id=70399)
Plains4 = Card(name="plains", pretty_name="Plains", cost=[],
color_identity=['W'], card_type="Land", sub_types="Plains",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=253,
mtga_id=70400)
Island = Card(name="island", pretty_name="Island", cost=[],
color_identity=['U'], card_type="Land", sub_types="Island",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=254,
mtga_id=70401)
Island2 = Card(name="island", pretty_name="Island", cost=[],
color_identity=['U'], card_type="Land", sub_types="Island",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=255,
mtga_id=70402)
Island3 = Card(name="island", pretty_name="Island", cost=[],
color_identity=['U'], card_type="Land", sub_types="Island",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=256,
mtga_id=70403)
Island4 = Card(name="island", pretty_name="Island", cost=[],
color_identity=['U'], card_type="Land", sub_types="Island",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=257,
mtga_id=70404)
Swamp = Card(name="swamp", pretty_name="Swamp", cost=[],
color_identity=['B'], card_type="Land", sub_types="Swamp",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=258,
mtga_id=70405)
Swamp2 = Card(name="swamp", pretty_name="Swamp", cost=[],
color_identity=['B'], card_type="Land", sub_types="Swamp",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=259,
mtga_id=70406)
Swamp3 = Card(name="swamp", pretty_name="Swamp", cost=[],
color_identity=['B'], card_type="Land", sub_types="Swamp",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=260,
mtga_id=70407)
Swamp4 = Card(name="swamp", pretty_name="Swamp", cost=[],
color_identity=['B'], card_type="Land", sub_types="Swamp",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=261,
mtga_id=70408)
Mountain = Card(name="mountain", pretty_name="Mountain", cost=[],
color_identity=['R'], card_type="Land", sub_types="Mountain",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=262,
mtga_id=70409)
Mountain2 = Card(name="mountain", pretty_name="Mountain", cost=[],
color_identity=['R'], card_type="Land", sub_types="Mountain",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=263,
mtga_id=70410)
Mountain3 = Card(name="mountain", pretty_name="Mountain", cost=[],
color_identity=['R'], card_type="Land", sub_types="Mountain",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=264,
mtga_id=70411)
Mountain4 = Card(name="mountain", pretty_name="Mountain", cost=[],
color_identity=['R'], card_type="Land", sub_types="Mountain",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=265,
mtga_id=70412)
Forest = Card(name="forest", pretty_name="Forest", cost=[],
color_identity=['G'], card_type="Land", sub_types="Forest",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=266,
mtga_id=70413)
Forest2 = Card(name="forest", pretty_name="Forest", cost=[],
color_identity=['G'], card_type="Land", sub_types="Forest",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=267,
mtga_id=70414)
Forest3 = Card(name="forest", pretty_name="Forest", cost=[],
color_identity=['G'], card_type="Land", sub_types="Forest",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=268,
mtga_id=70415)
Forest4 = Card(name="forest", pretty_name="Forest", cost=[],
color_identity=['G'], card_type="Land", sub_types="Forest",
abilities=[], set_id="ELD", rarity="Basic", collectible=True, set_number=269,
mtga_id=70416)
WindScarredCrag = Card(name="windscarred_crag", pretty_name="Wind-Scarred Crag", cost=[],
color_identity=['R', 'W'], card_type="Land", sub_types="",
abilities=[76735, 90050, 4247], set_id="ELD", rarity="Common", collectible=True, set_number=308,
mtga_id=70421)
ThornwoodFalls = Card(name="thornwood_falls", pretty_name="Thornwood Falls", cost=[],
color_identity=['G', 'U'], card_type="Land", sub_types="",
abilities=[76735, 90050, 18504], set_id="ELD", rarity="Common", collectible=True, set_number=313,
mtga_id=70426)
Goat = Card(name="goat", pretty_name="Goat", cost=[],
color_identity=[], card_type="Creature", sub_types="Goat",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10001,
mtga_id=70427)
Human = Card(name="human", pretty_name="Human", cost=[],
color_identity=[], card_type="Creature", sub_types="Human",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10002,
mtga_id=70428)
Knight = Card(name="knight", pretty_name="Knight", cost=[],
color_identity=[], card_type="Creature", sub_types="Knight",
abilities=[15], set_id="ELD", rarity="Token", collectible=False, set_number=10003,
mtga_id=70429)
Mouse = Card(name="mouse", pretty_name="Mouse", cost=[],
color_identity=[], card_type="Creature", sub_types="PlaceholderSubType2",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10004,
mtga_id=70430)
Faerie = Card(name="faerie", pretty_name="Faerie", cost=[],
color_identity=[], card_type="Creature", sub_types="Faerie",
abilities=[8], set_id="ELD", rarity="Token", collectible=False, set_number=10005,
mtga_id=70431)
Rat = Card(name="rat", pretty_name="Rat", cost=[],
color_identity=[], card_type="Creature", sub_types="Rat",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10006,
mtga_id=70432)
Dwarf = Card(name="dwarf", pretty_name="Dwarf", cost=[],
color_identity=[], card_type="Creature", sub_types="Dwarf",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10007,
mtga_id=70433)
Bear = Card(name="bear", pretty_name="Bear", cost=[],
color_identity=[], card_type="Creature", sub_types="Bear",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10008,
mtga_id=70434)
Boar = Card(name="boar", pretty_name="Boar", cost=[],
color_identity=[], card_type="Creature", sub_types="Boar",
abilities=[136165], set_id="ELD", rarity="Token", collectible=False, set_number=10009,
mtga_id=70435)
Giant = Card(name="giant", pretty_name="Giant", cost=[],
color_identity=[], card_type="Creature", sub_types="Giant",
abilities=[], set_id="ELD", rarity="Token", collectible=False, set_number=10010,
mtga_id=70436)
HumanCleric = Card(name="human_cleric", pretty_name="Human Cleric", cost=[],
color_identity=[], card_type="Creature", sub_types="Human Cleric",
abilities=[12, 9], set_id="ELD", rarity="Token", collectible=False, set_number=10011,
mtga_id=70437)
HumanRogue = Card(name="human_rogue", pretty_name="Human Rogue", cost=[],
color_identity=[], card_type="Creature", sub_types="Human Rogue",
abilities=[9, 136242], set_id="ELD", rarity="Token", collectible=False, set_number=10012,
mtga_id=70438)
HumanWarrior = Card(name="human_warrior", pretty_name="Human Warrior", cost=[],
color_identity=[], card_type="Creature", sub_types="Human Warrior",
abilities=[14, 9], set_id="ELD", rarity="Token", collectible=False, set_number=10013,
mtga_id=70439)
Wolf = Card(name="wolf", pretty_name="Wolf", cost=[],
color_identity=[], card_type="Creature", sub_types="Wolf",
abilities=[136216], set_id="ELD", rarity="Token", collectible=False, set_number=10014,
mtga_id=70440)
Food = Card(name="food", pretty_name="Food", cost=[],
color_identity=[], card_type="Artifact", sub_types="Food",
abilities=[197], set_id="ELD", rarity="Token", collectible=False, set_number=10015,
mtga_id=70441)
Food2 = Card(name="food", pretty_name="Food", cost=[],
color_identity=[], card_type="Artifact", sub_types="Food",
abilities=[197], set_id="ELD", rarity="Token", collectible=False, set_number=10016,
mtga_id=70442)
Food3 = Card(name="food", pretty_name="Food", cost=[],
color_identity=[], card_type="Artifact", sub_types="Food",
abilities=[197], set_id="ELD", rarity="Token", collectible=False, set_number=10017,
mtga_id=70443)
Food4 = Card(name="food", pretty_name="Food", cost=[],
color_identity=[], card_type="Artifact", sub_types="Food",
abilities=[197], set_id="ELD", rarity="Token", collectible=False, set_number=10018,
mtga_id=70444)
MaceoftheValiant = Card(name="mace_of_the_valiant", pretty_name="Mace of the Valiant", cost=['2', 'W'],
color_identity=['W'], card_type="Artifact", sub_types="Equipment",
abilities=[136349, 136350, 1156], set_id="ELD", rarity="Rare", collectible=True, set_number=314,
mtga_id=70447)
FaerieFormation = Card(name="faerie_formation", pretty_name="Faerie Formation", cost=['4', 'U'],
color_identity=['U'], card_type="Creature", sub_types="Faerie",
abilities=[8, 136368], set_id="ELD", rarity="Rare", collectible=True, set_number=316,
mtga_id=70449)
ShimmerDragon = Card(name="shimmer_dragon", pretty_name="Shimmer Dragon", cost=['4', 'U', 'U'],
color_identity=['U'], card_type="Creature", sub_types="Dragon",
abilities=[8, 136352, 136364], set_id="ELD", rarity="Rare", collectible=True, set_number=317,
mtga_id=70450)
WorkshopElders = Card(name="workshop_elders", pretty_name="Workshop Elders", cost=['6', 'U'],
color_identity=['U'], card_type="Creature", sub_types="Human Artificer",
abilities=[136353, 136366], set_id="ELD", rarity="Rare", collectible=True, set_number=318,
mtga_id=70451)
TasteofDeath = Card(name="taste_of_death", pretty_name="Taste of Death", cost=['4', 'B', 'B'],
color_identity=['B'], card_type="Sorcery", sub_types="",
abilities=[136355], set_id="ELD", rarity="Rare", collectible=True, set_number=320,
mtga_id=70453)
SteelbaneHydra = Card(name="steelbane_hydra", pretty_name="Steelbane Hydra", cost=['X', 'G', 'G'],
color_identity=['G'], card_type="Creature", sub_types="Turtle Hydra",
abilities=[76885, 136369], set_id="ELD", rarity="Rare", collectible=True, set_number=322,
mtga_id=70455)
ThornMammoth = Card(name="thorn_mammoth", pretty_name="Thorn Mammoth", cost=['5', 'G', 'G'],
color_identity=['G'], card_type="Creature", sub_types="Elephant",
abilities=[14, 136357], set_id="ELD", rarity="Rare", collectible=True, set_number=323,
mtga_id=70456)
AlelaArtfulProvocateur = Card(name="alela_artful_provocateur", pretty_name="Alela, Artful Provocateur", cost=['1', 'W', 'U', 'B'],
color_identity=['W', 'U', 'B'], card_type="Creature", sub_types="Faerie Warlock",
abilities=[8, 1, 12, 121999, 136371], set_id="ELD", rarity="Mythic Rare", collectible=True, set_number=324,
mtga_id=70457)
BanishintoFable = Card(name="banish_into_fable", pretty_name="Banish into Fable", cost=['4', 'W', 'U'],
color_identity=['W', 'U'], card_type="Instant", sub_types="",
abilities=[1389, 136359], set_id="ELD", rarity="Rare", collectible=True, set_number=325,
mtga_id=70458)
ChulaneTellerofTales = Card(name="chulane_teller_of_tales", pretty_name="Chulane, Teller of Tales", cost=['2', 'G', 'W', 'U'],
color_identity=['W', 'U', 'G'], card_type="Creature", sub_types="Human Druid",
abilities=[15, 136373, 1392], set_id="ELD", rarity="Mythic Rare", collectible=True, set_number=326,
mtga_id=70459)
KnightsCharge = Card(name="knights_charge", pretty_name="Knights' Charge", cost=['1', 'W', 'B'],
color_identity=['W', 'B'], card_type="Enchantment", sub_types="",
abilities=[1395, 136361], set_id="ELD", rarity="Rare", collectible=True, set_number=328,
mtga_id=70461)
KorvoldFaeCursedKing = Card(name="korvold_faecursed_king", pretty_name="Korvold, Fae-Cursed King", cost=['2', 'B', 'R', 'G'],
color_identity=['B', 'R', 'G'], card_type="Creature", sub_types="Dragon Noble",
abilities=[8, 136365, 1398], set_id="ELD", rarity="Mythic Rare", collectible=True, set_number=329,
mtga_id=70462)
SyrGwynHeroofAshvale = Card(name="syr_gwyn_hero_of_ashvale", pretty_name="Syr Gwyn, Hero of Ashvale", cost=['3', 'R', 'W', 'B'],
color_identity=['W', 'B', 'R'], card_type="Creature", sub_types="Human Knight",
abilities=[15, 142, 1399, 1400], set_id="ELD", rarity="Mythic Rare", collectible=True, set_number=330,
mtga_id=70463)
ArcaneSignet = Card(name="arcane_signet", pretty_name="Arcane Signet", cost=['2'],
color_identity=[], card_type="Artifact", sub_types="",
abilities=[90126], set_id="ELD", rarity="Common", collectible=True, set_number=331,
mtga_id=70464)
TomeofLegends = Card(name="tome_of_legends", pretty_name="Tome of Legends", cost=['2'],
color_identity=[], card_type="Artifact", sub_types="",
abilities=[136362, 136372, 136363], set_id="ELD", rarity="Rare", collectible=True, set_number=332,
mtga_id=70465)
CommandTower = Card(name="command_tower", pretty_name="Command Tower", cost=[],
color_identity=[], card_type="Land", sub_types="",
abilities=[90126], set_id="ELD", rarity="Common", collectible=True, set_number=333,
mtga_id=70466)
BringtoLife = Card(name="bring_to_life", pretty_name="Bring to Life", cost=['2', 'U'],
color_identity=['U'], card_type="Sorcery", sub_types="Adventure",
abilities=[136488], set_id="ELD", rarity="Uncommon", collectible=False, set_number=38,
mtga_id=70477)
ProfaneInsight = Card(name="profane_insight", pretty_name="Profane Insight", cost=['2', 'B'],
color_identity=['B'], card_type="Instant", sub_types="Adventure",
abilities=[1416], set_id="ELD", rarity="Uncommon", collectible=False, set_number=90,
mtga_id=70483)
AlterFate = Card(name="alter_fate", pretty_name="Alter Fate", cost=['1', 'B'],
color_identity=['B'], card_type="Sorcery", sub_types="Adventure",
abilities=[24122], set_id="ELD", rarity="Uncommon", collectible=False, set_number=99,
mtga_id=70485)
CurryFavor = Card(name="curry_favor", pretty_name="Curry Favor", cost=['B'],
color_identity=['B'], card_type="Sorcery", sub_types="Adventure",
abilities=[136490], set_id="ELD", rarity="Common", collectible=False, set_number=105,
mtga_id=70487)
BattleDisplay = Card(name="battle_display", pretty_name="Battle Display", cost=['R'],
color_identity=['R'], card_type="Sorcery", sub_types="Adventure",
abilities=[22564], set_id="ELD", rarity="Uncommon", collectible=False, set_number=122,
mtga_id=70489)
FertileFootsteps = Card(name="fertile_footsteps", pretty_name="Fertile Footsteps", cost=['2', 'G'],
color_identity=['G'], card_type="Sorcery", sub_types="Adventure",
abilities=[5296], set_id="ELD", rarity="Uncommon", collectible=False, set_number=149,
mtga_id=70492)
SeasonalRitual = Card(name="seasonal_ritual", pretty_name="Seasonal Ritual", cost=['G'],
color_identity=['G'], card_type="Sorcery", sub_types="Adventure",
abilities=[1429], set_id="ELD", rarity="Common", collectible=False, set_number=174,
mtga_id=70497)
clsmembers = [card for name, card in inspect.getmembers(sys.modules[__name__]) if isinstance(card, Card)]
ThroneOfEldraine = Set("ThroneOfEldraine", cards=clsmembers)
set_ability_map = {1: 'Deathtouch',
3: 'Double strike',
7: 'Flash',
8: 'Flying',
9: 'Haste',
12: 'Lifelink',
14: 'Trample',
15: 'Vigilance',
142: 'Menace',
197: '{o2}, {oT}, Sacrifice this artifact: You gain 3 life.',
1027: 'Enchant creature',
1055: '{oT}: Add one mana of any color.',
1152: '{oT}: Add {oC}.',
1156: 'Equip {o3}',
1268: 'Equip {o1}',
1316: "Shambling Suit's power is equal to the number of artifacts and/or "
'enchantments you control.',
1389: 'When you cast this spell from your hand, copy it if you control an '
'artifact, then copy it if you control an enchantment. You may choose '
'new targets for the copies.',
1392: "{o3}, {oT}: Return target creature you control to its owner's hand.",
1395: 'Whenever a Knight you control attacks, each opponent loses 1 life and '
'you gain 1 life.',
1398: 'Whenever you sacrifice a permanent, put a +1/+1 counter on Korvold and '
'draw a card.',
1399: 'Whenever an equipped creature you control attacks, you draw a card and '
'you lose 1 life.',
1400: 'Equipment you control have equip Knight {o0}.',
1416: 'You draw a card and you lose 1 life.',
1429: 'Add one mana of any color.',
2374: '{oT}: Add one mana of the chosen color.',
2512: 'Equipped creature gets +2/+2.',
4247: '{oT}: Add {oR} or {oW}.',
5296: 'Search your library for a basic land card, put it onto the '
'battlefield, then shuffle your library.',
7610: 'Equipped creature gets +0/+2 and has vigilance.',
18504: '{oT}: Add {oG} or {oU}.',
22564: 'Destroy target artifact.',
24122: 'Return target creature card from your graveyard to your hand.',
76735: 'Thornwood Falls enters the battlefield tapped.',
76885: 'Steelbane Hydra enters the battlefield with X +1/+1 counters on it.',
86476: "Order of Midnight can't block.",
86788: 'When Golden Egg enters the battlefield, draw a card.',
88207: '{o1}, {oT}, Sacrifice Golden Egg: Add one mana of any color.',
88237: 'As Heraldic Banner enters the battlefield, choose a color.',
88259: "Beanstalk Giant's power and toughness are each equal to the number of "
'lands you control.',
90050: 'When Thornwood Falls enters the battlefield, you gain 1 life.',
90126: "{oT}: Add one mana of any color in your commander's color identity.",
100685: 'When Witching Well enters the battlefield, scry 2.',
103355: 'Shinechaser gets +1/+1 as long as you control an artifact.',
104880: '-3: Destroy target creature. Draw a card.',
119104: 'Other Knights you control get +1/+1.',
121999: 'Other creatures you control with flying get +1/+0.',
136076: 'Whenever another creature dies, or a creature card is put into a '
'graveyard from anywhere other than the battlefield, or a creature '
'card leaves your graveyard, Syr Konrad, the Grim deals 1 damage to '
'each opponent.',
136077: '{o1oB}: Each player puts the top card of their library into their '
'graveyard.',
136079: 'When Venerable Knight dies, put a +1/+1 counter on target Knight you '
'control.',
136084: 'When Corridor Monitor enters the battlefield, untap target artifact '
'or creature you control.',
136108: 'Whenever you draw your second card each turn, put a +1/+1 counter on '
'Faerie Vandal.',
136125: 'Enchanted creature loses all abilities and is a blue Frog creature '
'with base power and toughness 1/1. \n'
'<i>(It loses all other card types and creature types.)</i>',
136126: '0: Create two 2/2 black and green Wolf creature tokens with "When '
'this creature dies, put a loyalty counter on each Garruk you '
'control."',
136128: '-6: You get an emblem with "Creatures you control get +3/+3 and have '
'trample."',
136147: 'Sacrifice two Foods: Draw a card.',
136148: 'Shinechaser gets +1/+1 as long as you control an enchantment.',
136149: 'Equip Knight {o1}',
136151: "Wintermoor Commander's toughness is equal to the number of Knights "
'you control.',
136152: 'Whenever Wintermoor Commander attacks, another target Knight you '
'control gains indestructible until end of turn.',
136153: "When Arcanist's Owl enters the battlefield, look at the top four "
'cards of your library. You may reveal an artifact or enchantment '
'card from among them and put it into your hand. Put the rest on the '
'bottom of your library in a random order.',
136165: 'When this creature dies, create a Food token.',
136178: '{oT}, Sacrifice a creature: Create a Food token. If the sacrificed '
"creature's toughness was 4 or greater, create two Food tokens "
'instead.',
136198: '{oT}: Add {oR}, {oW}, or {oB}. Spend this mana only to cast a Knight '
'or Equipment spell.',
136216: 'When this creature dies, put a loyalty counter on each Garruk you '
'control.',
136218: 'Choose two target creatures controlled by different players. Return '
"those creatures to their owners' hands.",
136240: '{o3oU}, Sacrifice Witching Well: Draw two cards.',
136241: 'When Shining Armor enters the battlefield, attach it to target '
'Knight you control.',
136242: 'When this creature enters the battlefield, it deals 1 damage to any '
'target.',
136246: 'Destroy target creature. Create a Food token.',
136248: 'Whenever Belle of the Brawl attacks, other Knights you control get '
'+1/+0 until end of turn.',
136251: 'Whenever Savvy Hunter attacks or blocks, create a Food token.',
136258: 'Whenever one or more non-Human creatures you control deal combat '
'damage to a player, draw a card.',
136269: '{o(R/W)o(R/W)o(R/W)o(R/W)}: Fireborn Knight gets +1/+1 until end of '
'turn.',
136278: '{o2}, {oT}, Sacrifice Golden Egg: You gain 3 life.',
136279: 'Creatures you control of the chosen color get +1/+0.',
136299: 'Equipped creature gets +1/+0 and has haste.',
136335: 'Enchanted creature gets +1/+1 for each artifact and/or enchantment '
'you control.',
136349: 'Equipped creature gets +1/+1 for each charge counter on Mace of the '
'Valiant and has vigilance.',
136350: 'Whenever a creature enters the battlefield under your control, put a '
'charge counter on Mace of the Valiant.',
136352: 'As long as you control four or more artifacts, Shimmer Dragon has '
'hexproof.',
136353: 'Artifact creatures you control have flying.',
136355: 'Each player sacrifices three creatures. You create three Food '
'tokens.',
136357: 'Whenever Thorn Mammoth or another creature enters the battlefield '
'under your control, Thorn Mammoth fights up to one target creature '
"you don't control.",
136359: "Return target nonland permanent to its owner's hand. You create a "
'2/2 white Knight creature token with vigilance.',
136361: "{o6oWoB}, Sacrifice Knights' Charge: Return all Knight creature "
'cards from your graveyard to the battlefield.',
136362: 'Tome of Legends enters the battlefield with a page counter on it.',
136363: '{o1}, {oT}, Remove a page counter from Tome of Legends: Draw a card.',
136364: 'Tap two untapped artifacts you control: Draw a card.',
136365: 'Whenever Korvold, Fae-Cursed King enters the battlefield or attacks, '
'sacrifice another permanent.',
136366: 'At the beginning of combat on your turn, you may have target '
'noncreature artifact you control become a 0/0 artifact creature. If '
'you do, put four +1/+1 counters on it.',
136368: '{o3oU}: Create a 1/1 blue Faerie creature token with flying. Draw a '
'card.',
136369: '{o2oG}, Remove a +1/+1 counter from Steelbane Hydra: Destroy target '
'artifact or enchantment.',
136371: 'Whenever you cast an artifact or enchantment spell, create a 1/1 '
'blue Faerie creature token with flying.',
136372: 'Whenever your commander enters the battlefield or attacks, put a '
'page counter on Tome of Legends.',
136373: 'Whenever you cast a creature spell, draw a card, then you may put a '
'land card from your hand onto the battlefield.',
136488: 'Target noncreature artifact you control becomes a 0/0 artifact '
'creature. Put four +1/+1 counters on it.',
136490: 'You gain X life and each opponent loses X life, where X is the '
'number of Knights you control.'} | PypiClean |
/15five-django-ajax-selects-1.5.2.155.tar.gz/15five-django-ajax-selects-1.5.2.155/CHANGELOG.md | # Change Log
## [1.5.2](https://github.com/crucialfelix/django-ajax-selects/tree/1.5.2) (2016-10-19)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.5.1...1.5.2)
**Fixed bugs:**
- Occasionally: $.ui.autocomplete is undefined [\#188](https://github.com/crucialfelix/django-ajax-selects/issues/188)
**Closed issues:**
- No cache management headers in HTTP response [\#187](https://github.com/crucialfelix/django-ajax-selects/issues/187)
## [1.5.1](https://github.com/crucialfelix/django-ajax-selects/tree/1.5.1) (2016-10-13)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.5.0...1.5.1)
**Implemented enhancements:**
- Prefer document.createElement to document.write [\#182](https://github.com/crucialfelix/django-ajax-selects/issues/182)
**Fixed bugs:**
- fix: add related for multiple select [\#184](https://github.com/crucialfelix/django-ajax-selects/pull/184) ([crucialfelix](https://github.com/crucialfelix))
## [1.5.0](https://github.com/crucialfelix/django-ajax-selects/tree/1.5.0) (2016-09-05)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.4.3...1.5.0)
- Added Support for Django 1.10
- Dropped Django 1.5
**Fixed bugs:**
- Initial fields are duplicated when new row added. [\#94](https://github.com/crucialfelix/django-ajax-selects/issues/94)
**Closed issues:**
- ValueError in Django 1.10 [\#177](https://github.com/crucialfelix/django-ajax-selects/issues/177)
- Django 1.10 did add popup [\#174](https://github.com/crucialfelix/django-ajax-selects/issues/174)
- Example not Working [\#161](https://github.com/crucialfelix/django-ajax-selects/issues/161)
**Merged pull requests:**
- Fix documentation to format code properly [\#165](https://github.com/crucialfelix/django-ajax-selects/pull/165) ([joshblum](https://github.com/joshblum))
- install.sh not working [\#162](https://github.com/crucialfelix/django-ajax-selects/pull/162) ([hdzierz](https://github.com/hdzierz))
## [1.4.3](https://github.com/crucialfelix/django-ajax-selects/tree/1.4.3) (2016-03-13)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.4.2...1.4.3)
**Closed issues:**
- Additional stacked inlines clear un-saved autocomplete fields [\#156](https://github.com/crucialfelix/django-ajax-selects/issues/156)
- support request: ManyToOneRel doesn't have expected attributes [\#154](https://github.com/crucialfelix/django-ajax-selects/issues/154)
**Merged pull requests:**
- Stop using deprecated \_meta api. [\#160](https://github.com/crucialfelix/django-ajax-selects/pull/160) ([kramarz](https://github.com/kramarz))
- Fixed file name in documentation for custom templates. [\#158](https://github.com/crucialfelix/django-ajax-selects/pull/158) ([sebslomski](https://github.com/sebslomski))
- Fixes re-initialization upon adding inlines [\#157](https://github.com/crucialfelix/django-ajax-selects/pull/157) ([funkyfuture](https://github.com/funkyfuture))
## [1.4.2](https://github.com/crucialfelix/django-ajax-selects/tree/1.4.2) (2016-01-18)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.4.1...1.4.2)
**Fixed bugs:**
- Selected data lost when adding new rows via ajax [\#145](https://github.com/crucialfelix/django-ajax-selects/issues/145)
- Inline forms raise TypeError when not filled in [\#142](https://github.com/crucialfelix/django-ajax-selects/issues/142)
**Merged pull requests:**
- Fix incorrect has\_changed result for AutoCompleteSelectField that has not been filled in. [\#152](https://github.com/crucialfelix/django-ajax-selects/pull/152) ([unklphil](https://github.com/unklphil))
- Only trigger reset\(\) initially if data hasn't changed. [\#146](https://github.com/crucialfelix/django-ajax-selects/pull/146) ([jmfederico](https://github.com/jmfederico))
## [1.4.1](https://github.com/crucialfelix/django-ajax-selects/tree/1.4.1) (2015-11-18)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.4.0...1.4.1)
**Closed issues:**
- Templates not included in pypi1.4.0 package [\#141](https://github.com/crucialfelix/django-ajax-selects/issues/141)
- Documentation seems to be broken on RTD [\#140](https://github.com/crucialfelix/django-ajax-selects/issues/140)
## [1.4.0](https://github.com/crucialfelix/django-ajax-selects/tree/1.4.0) (2015-11-07)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.6...1.4.0)
**Implemented enhancements:**
- Pass `request` to `LookupChannel` methods, make overriding easier [\#40](https://github.com/crucialfelix/django-ajax-selects/issues/40)
**Fixed bugs:**
- AttributeError on invalid form data [\#135](https://github.com/crucialfelix/django-ajax-selects/issues/135)
- Doesn't work with readonly\_fields [\#120](https://github.com/crucialfelix/django-ajax-selects/issues/120)
- Add another popup doesn't add `?\_popup=1` to url in Django 1.8 [\#118](https://github.com/crucialfelix/django-ajax-selects/issues/118)
- Field appers duplicated when marked as readonly in admin [\#84](https://github.com/crucialfelix/django-ajax-selects/issues/84)
**Closed issues:**
- can't import register module [\#139](https://github.com/crucialfelix/django-ajax-selects/issues/139)
- How to fire lookup for value in text field using javascript [\#137](https://github.com/crucialfelix/django-ajax-selects/issues/137)
- tests not included in MANIFEST.in [\#136](https://github.com/crucialfelix/django-ajax-selects/issues/136)
- Content of input not included in field, only dropdown choices for make\_ajax\_field [\#134](https://github.com/crucialfelix/django-ajax-selects/issues/134)
- documentation for add link on ajax fields for django admin inlines [\#127](https://github.com/crucialfelix/django-ajax-selects/issues/127)
- Can't specify widget for AutoCompleteSelectMultipleField [\#126](https://github.com/crucialfelix/django-ajax-selects/issues/126)
- RemovedInDjango19Warning in ajax\_select [\#125](https://github.com/crucialfelix/django-ajax-selects/issues/125)
- Django's form change\_data always include autocomplete fields [\#123](https://github.com/crucialfelix/django-ajax-selects/issues/123)
- AttributeError: 'int' object has no attribute 'isnumeric' [\#117](https://github.com/crucialfelix/django-ajax-selects/issues/117)
- Error with TheForm in Django 1.8 [\#115](https://github.com/crucialfelix/django-ajax-selects/issues/115)
- Not Secure. invalid literal for long\(\) with base 10 [\#114](https://github.com/crucialfelix/django-ajax-selects/issues/114)
- ImportError: No module named ajax\_select [\#112](https://github.com/crucialfelix/django-ajax-selects/issues/112)
- 'AutoCompleteSelectWidget' object has no attribute 'choices' [\#111](https://github.com/crucialfelix/django-ajax-selects/issues/111)
- "Uncaught TypeError: Cannot read property 'autocomplete' of undefined" [\#107](https://github.com/crucialfelix/django-ajax-selects/issues/107)
- Regression? Or UUID PK not supported [\#103](https://github.com/crucialfelix/django-ajax-selects/issues/103)
- Support lookup channels from third-party apps [\#98](https://github.com/crucialfelix/django-ajax-selects/issues/98)
- callbacks for select doesn't work [\#97](https://github.com/crucialfelix/django-ajax-selects/issues/97)
- DeprecationWarning: Creating a ModelForm without either the 'fields' attribute or the 'exclude' attribute is deprecated [\#96](https://github.com/crucialfelix/django-ajax-selects/issues/96)
- AutoCompleteSelectField has no attribute 'limit\_choices\_to' in Django 1.7 [\#83](https://github.com/crucialfelix/django-ajax-selects/issues/83)
- Custom form [\#81](https://github.com/crucialfelix/django-ajax-selects/issues/81)
- avoid warning when installing via pip [\#53](https://github.com/crucialfelix/django-ajax-selects/issues/53)
- search\_fields like in ModelAdmin [\#21](https://github.com/crucialfelix/django-ajax-selects/issues/21)
- Issues when using django-admin-sortable [\#12](https://github.com/crucialfelix/django-ajax-selects/issues/12)
**Merged pull requests:**
- Get rid of terrible `\_as\_pk` function \(fixes \#117, \#120, and \#135\) [\#138](https://github.com/crucialfelix/django-ajax-selects/pull/138) ([hwkns](https://github.com/hwkns))
- Reset button handling [\#132](https://github.com/crucialfelix/django-ajax-selects/pull/132) ([jmerdich](https://github.com/jmerdich))
- Remove unnecessary backquotes in README.md [\#131](https://github.com/crucialfelix/django-ajax-selects/pull/131) ([zablotski](https://github.com/zablotski))
- Feature autodiscover [\#129](https://github.com/crucialfelix/django-ajax-selects/pull/129) ([morr0350](https://github.com/morr0350))
- Example for get\_formset on inline admin [\#128](https://github.com/crucialfelix/django-ajax-selects/pull/128) ([rlskoeser](https://github.com/rlskoeser))
- ajax\_lookup should respond with content type `application/json` [\#119](https://github.com/crucialfelix/django-ajax-selects/pull/119) ([unklphil](https://github.com/unklphil))
- Add AjaxSelectAdminStackedInline to work similarly to AjaxSelectAdminTabularInline [\#89](https://github.com/crucialfelix/django-ajax-selects/pull/89) ([unklphil](https://github.com/unklphil))
## [1.3.6](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.6) (2015-04-06)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.5...1.3.6)
**Closed issues:**
- 'AutoCompleteSelectWidget' object has no attribute 'choices' [\#110](https://github.com/crucialfelix/django-ajax-selects/issues/110)
- \_\_init\_\_\(\) got an unexpected keyword argument 'mimetype' [\#108](https://github.com/crucialfelix/django-ajax-selects/issues/108)
- Limit number of results returned by lookup and auto load additional results when user scrolls to bottom of list [\#105](https://github.com/crucialfelix/django-ajax-selects/issues/105)
- Support reverse relationships [\#99](https://github.com/crucialfelix/django-ajax-selects/issues/99)
- 'set' object does not support indexing [\#93](https://github.com/crucialfelix/django-ajax-selects/issues/93)
- deck area [\#92](https://github.com/crucialfelix/django-ajax-selects/issues/92)
- Inline won't work with new lines \(SOLVED\) [\#87](https://github.com/crucialfelix/django-ajax-selects/issues/87)
- Bug in ajax\_selects.js \(addKiller function call\) [\#79](https://github.com/crucialfelix/django-ajax-selects/issues/79)
- AutoCompleteSelectField breaks when using localization and long ids [\#68](https://github.com/crucialfelix/django-ajax-selects/issues/68)
- format\_match did not work with django-ajax-select 1.3.3 [\#58](https://github.com/crucialfelix/django-ajax-selects/issues/58)
- Support Non-integer Primary Keys \(mongodb etc\) [\#34](https://github.com/crucialfelix/django-ajax-selects/issues/34)
- non operation with mongodb [\#3](https://github.com/crucialfelix/django-ajax-selects/issues/3)
**Merged pull requests:**
- Change order for running script by .sh \#112 \(NOTICE\) [\#113](https://github.com/crucialfelix/django-ajax-selects/pull/113) ([skrzypek](https://github.com/skrzypek))
- Update README.md [\#101](https://github.com/crucialfelix/django-ajax-selects/pull/101) ([cormier](https://github.com/cormier))
- Added option for fields in TheForm superclass [\#91](https://github.com/crucialfelix/django-ajax-selects/pull/91) ([onyekaa](https://github.com/onyekaa))
## [1.3.5](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.5) (2014-08-02)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.4...1.3.5)
**Closed issues:**
- ajax-selects/fields.py simplejson is deprecated [\#74](https://github.com/crucialfelix/django-ajax-selects/issues/74)
- Document the use in template for 'quick installation' [\#71](https://github.com/crucialfelix/django-ajax-selects/issues/71)
- Document how to use an ajax field in a ListFilter in admin [\#70](https://github.com/crucialfelix/django-ajax-selects/issues/70)
- Issue with Ajax-Search on Media-Fields [\#60](https://github.com/crucialfelix/django-ajax-selects/issues/60)
- Set width of jquery autocomplete widget [\#30](https://github.com/crucialfelix/django-ajax-selects/issues/30)
**Merged pull requests:**
- Fix issue 58 and pull request 76 [\#85](https://github.com/crucialfelix/django-ajax-selects/pull/85) ([camillobruni](https://github.com/camillobruni))
- Django's HttpResponse object has deprecated the mimetype kwarg in 1.7 [\#82](https://github.com/crucialfelix/django-ajax-selects/pull/82) ([squidsoup](https://github.com/squidsoup))
- Support non-int primary keys [\#78](https://github.com/crucialfelix/django-ajax-selects/pull/78) ([AlexHill](https://github.com/AlexHill))
- correct import deprecated since Django 1.4 [\#77](https://github.com/crucialfelix/django-ajax-selects/pull/77) ([gertingold](https://github.com/gertingold))
- maintain compatibility with Python 2.6 [\#75](https://github.com/crucialfelix/django-ajax-selects/pull/75) ([gertingold](https://github.com/gertingold))
## [1.3.4](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.4) (2014-03-30)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.3...1.3.4)
**Closed issues:**
- Custom validation with django-ajax-selects [\#73](https://github.com/crucialfelix/django-ajax-selects/issues/73)
- DeprecationWarning django.utils.simplejson [\#63](https://github.com/crucialfelix/django-ajax-selects/issues/63)
- When create select list always show \(in bottom list\) add new object. [\#62](https://github.com/crucialfelix/django-ajax-selects/issues/62)
**Merged pull requests:**
- Trivial typo fix \(chanel\_name\) [\#69](https://github.com/crucialfelix/django-ajax-selects/pull/69) ([gthb](https://github.com/gthb))
- Fixes \#18 - AJAX Selector and dynamic inlines [\#67](https://github.com/crucialfelix/django-ajax-selects/pull/67) ([peterfarrell](https://github.com/peterfarrell))
- Using json as opposed to simplejson \(depreciated\) [\#65](https://github.com/crucialfelix/django-ajax-selects/pull/65) ([krzysztof](https://github.com/krzysztof))
## [1.3.3](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.3) (2013-11-13)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.2...1.3.3)
**Merged pull requests:**
- Remove protocol from dynamically loaded urls. [\#54](https://github.com/crucialfelix/django-ajax-selects/pull/54) ([jellonek](https://github.com/jellonek))
## [1.3.2](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.2) (2013-11-09)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.1...1.3.2)
## [1.3.1](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.1) (2013-10-09)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.3.0...1.3.1)
**Closed issues:**
- parameters to triggers [\#43](https://github.com/crucialfelix/django-ajax-selects/issues/43)
- django.conf.urls.defaults depreciated [\#38](https://github.com/crucialfelix/django-ajax-selects/issues/38)
- How do you pass a class name for the addKiller [\#37](https://github.com/crucialfelix/django-ajax-selects/issues/37)
- AutoComplete and AutoCompleteSelect renders fine but AutoCompleteMultipleSelect isnt working [\#31](https://github.com/crucialfelix/django-ajax-selects/issues/31)
- django inline formset [\#18](https://github.com/crucialfelix/django-ajax-selects/issues/18)
## [1.3.0](https://github.com/crucialfelix/django-ajax-selects/tree/1.3.0) (2013-10-08)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.2.5...1.3.0)
**Closed issues:**
- ContentNotRenderedError [\#39](https://github.com/crucialfelix/django-ajax-selects/issues/39)
- Please add a change trigger to the target. [\#35](https://github.com/crucialfelix/django-ajax-selects/issues/35)
- can\_add isn't working in lookups [\#23](https://github.com/crucialfelix/django-ajax-selects/issues/23)
**Merged pull requests:**
- Follow the Meta definition of the original modelform [\#49](https://github.com/crucialfelix/django-ajax-selects/pull/49) ([artscoop](https://github.com/artscoop))
## [1.2.5](https://github.com/crucialfelix/django-ajax-selects/tree/1.2.5) (2012-08-22)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.2.4...1.2.5)
**Closed issues:**
- dj1.4 Error importing template source loader django.template.loaders.filesystem.load\_template\_source: [\#15](https://github.com/crucialfelix/django-ajax-selects/issues/15)
- fixed bug: AutoCompleteSelectMultipleField does not honor 'widget' parameter [\#14](https://github.com/crucialfelix/django-ajax-selects/issues/14)
- error 'this.data\("autocomplete"\) is undefined' [\#10](https://github.com/crucialfelix/django-ajax-selects/issues/10)
- Fire the change event on selection [\#8](https://github.com/crucialfelix/django-ajax-selects/issues/8)
- ValueError: translation table must be 256 characters long [\#5](https://github.com/crucialfelix/django-ajax-selects/issues/5)
- Error on Pop-Up [\#19](https://github.com/crucialfelix/django-ajax-selects/issues/19)
**Merged pull requests:**
- Small fix in CSS [\#2](https://github.com/crucialfelix/django-ajax-selects/pull/2) ([karlmoritz](https://github.com/karlmoritz))
## [1.2.4](https://github.com/crucialfelix/django-ajax-selects/tree/1.2.4) (2012-01-15)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.2.3...1.2.4)
## [1.2.3](https://github.com/crucialfelix/django-ajax-selects/tree/1.2.3) (2011-11-29)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.2.1...1.2.3)
## [1.2.1](https://github.com/crucialfelix/django-ajax-selects/tree/1.2.1) (2011-10-19)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.1.5...1.2.1)
## [1.1.5](https://github.com/crucialfelix/django-ajax-selects/tree/1.1.5) (2011-08-24)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.1.3...1.1.5)
## [1.1.3](https://github.com/crucialfelix/django-ajax-selects/tree/1.1.3) (2010-06-06)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.1.1...1.1.3)
## [1.1.1](https://github.com/crucialfelix/django-ajax-selects/tree/1.1.1) (2010-06-03)
[Full Changelog](https://github.com/crucialfelix/django-ajax-selects/compare/1.1.0...1.1.1)
## [1.1.0](https://github.com/crucialfelix/django-ajax-selects/tree/1.1.0) (2010-03-06)
\* *This Change Log was automatically generated by [github_changelog_generator](https://github.com/skywinder/Github-Changelog-Generator)*
| PypiClean |
/Flask-Multi-Redis-0.1.5.tar.gz/Flask-Multi-Redis-0.1.5/LICENSE.rst | GNU Affero General Public License
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How to Apply These Terms to Your New Programs
---------------------------------------------
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| <one line to give the program's name and a brief idea of what it does.>
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|
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| (at your option) any later version.
|
| This program is distributed in the hope that it will be useful,
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| PypiClean |
/GRImpulsiveWaves-0.3.2-py3-none-any.whl/grimpulsivewaves/plotting/dynamic.py | import numpy as np
import plotly
import plotly.graph_objects as go
from plotly.io import write_image
import random
class PlotlyDynamicPlotter:
def __init__(self, labels=["x", "y", "z"], title="", aspectratio=None, xrange=None, yrange=None, zrange=None, showSpikes=True, spikeColor="#000000", bgcolor="#fff", fontsize=10, ticks=True, tick_fontsize=12):
self.labels = labels
axis = dict(showline=True,
linewidth=4,
title=dict(font=dict(size=20)),
showticklabels=ticks,
tickfont=dict(size=tick_fontsize),
backgroundcolor=bgcolor)
layout = go.Layout(scene= dict(
xaxis_title=labels[0],
yaxis_title=labels[1],
zaxis_title=labels[2],
xaxis=axis,
yaxis=axis,
zaxis=axis),
font=dict(
size=fontsize)
)
self.fig = go.Figure(layout=layout)
if xrange:
self.fig.update_layout(scene=dict(
xaxis=dict(range=xrange, showbackground=True)
))
if yrange:
self.fig.update_layout(scene=dict(
yaxis=dict(range=yrange, showbackground=True)
))
if zrange:
self.fig.update_layout(scene=dict(
zaxis=dict(range=zrange, showbackground=True)
))
if showSpikes:
self.fig.update_layout(scene=dict(
xaxis=dict(spikecolor=spikeColor,
spikesides=False,
spikethickness=2),
yaxis=dict(spikecolor=spikeColor,
spikesides=False,
spikethickness=2),
zaxis=dict(spikecolor=spikeColor,
spikesides=False,
spikethickness=2)
))
else:
self.fig.update_layout(scene=dict(
xaxis=dict(showspikes=False),
yaxis=dict(showspikes=False),
zaxis=dict(showspikes=False)
))
self.fig.update_layout(title=dict(text=title, font=dict(size=35), x=0.5, xanchor="center", y=0.8, yanchor="top"))
if aspectratio:
self.fig.update_layout(scene_aspectmode='manual', scene_aspectratio=dict(x=aspectratio[0], y=aspectratio[1], z=aspectratio[2]))
def plotTrajectory3D(self, trajectory, color="#{:06x}".format(random.randint(0, 0xFFFFFF)).upper(), xc=1, yc=2, zc=3, name="", t=None, showlegend=False, opacity=1, linewidth=2, dash='solid'):
hinfo = "%{fullData.name}<br><br>" + self.labels[0] + ": %{x}<br>" + self.labels[1] + ": %{y}<br>" + self.labels[2] + ": %{z}<br><br>" + r"tau: %{text}<extra></extra>"
xs = np.array([x[xc] for x in trajectory]).flatten()
ys = np.array([x[yc] for x in trajectory]).flatten()
zs = np.array([x[zc] for x in trajectory]).flatten()
self.fig.add_scatter3d(x=xs, y=ys, z=zs, mode="lines", line=go.scatter3d.Line(color=color, width=linewidth, dash=dash), name=name,
hoverinfo='all', opacity=opacity)
if t is not None:
self.fig['data'][-1].update(text=t)
self.fig['data'][-1].update(hovertemplate=hinfo)
self.fig['data'][-1].update(showlegend=showlegend)
def plotHyperboloid(self, l=1, vsize=(-2,2), opacity=0.5, plot_edges=False, color="rgb(" + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + ")", drawImpulse=False, showlegend=False, drawCoords=False):
"""
Generate hyperboloid
:param l: Cosmological constant
"""
import plotly.figure_factory as ff #I hope Python is clever!
from scipy.spatial import Delaunay
eps = np.sign(l)
a = np.sqrt(3/np.abs(l))
u = np.linspace(0, 2 * np.pi, 90)
v = np.linspace(vsize[0], vsize[1], 90) #TODO: resolution should not be hard-coded
u, v = np.meshgrid(u, v)
u = u.flatten()
v = v.flatten()
if(eps > 0):
x = a * np.cosh(v/a) * np.cos(u)
y = a * np.cosh(v/a) * np.sin(u)
z = a * np.sinh(v/a)
else:
x = a * np.cosh(v/a) * np.cos(u)
z = a * np.cosh(v/a) * np.sin(u)
y = a * np.sinh(v/a)
points2D = np.vstack([u, v]).T
tri = Delaunay(points2D)
simplices = tri.simplices
_tempfig = ff.create_trisurf(x=x, y=y, z=z, simplices=simplices, show_colorbar=False, colormap=color, plot_edges=plot_edges,
aspectratio=dict(x=1, y=1, z=0.8))
_tempfig['data'][0].update(opacity=opacity)
_tempfig['data'][0].update(hoverinfo='skip')
_tempfig['data'][0].update(hoverinfo='skip')
_tempfig['data'][0].update(name="Hyperboloid")
_tempfig['data'][0].update(showlegend=showlegend)
if drawImpulse:
v = np.linspace(vsize[0], vsize[1], 10)
z = v[:-1]
y = v[:-1]
x = 10 * [-a]
x2 = 10 * [a]
_tempfig.add_scatter3d(x=x, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=4), name="U = infinity", hoverinfo='skip', showlegend=showlegend, opacity=0.4)
_tempfig.add_scatter3d(x=x2, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=8), name="U = 0", hoverinfo='skip', showlegend=showlegend, opacity=0.8)
if drawCoords:
b = a + 0.005
bm = a - 0.005
u = np.linspace(0, 2 * np.pi, 12)
ud = np.linspace(0, 2 * np.pi, 120)
v = np.linspace(vsize[0], vsize[1], 12)
vd = np.linspace(vsize[0], vsize[1], 120)
#u const
for u0 in u:
if (eps > 0):
x = b * np.cosh(vd / b) * np.cos(u0)
xm = bm * np.cosh(vd / bm) * np.cos(u0)
y = b * np.cosh(vd / b) * np.sin(u0)
ym = bm * np.cosh(vd / bm) * np.sin(u0)
z = b * np.sinh(vd / b)
zm = bm * np.sinh(vd / bm)
else:
x = b * np.cosh(vd / b) * np.cos(u0)
xm = bm * np.cosh(vd / bm) * np.cos(u0)
y = b * np.sinh(vd / b)
ym = bm * np.sinh(vd / bm)
z = b * np.cosh(vd / b) * np.sin(u0)
zm = bm * np.cosh(vd / bm) * np.sin(u0)
_tempfig.add_scatter3d(x=x, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=2),
showlegend=False, opacity=1, name="", hoverinfo='skip')
_tempfig.add_scatter3d(x=xm, y=ym, z=zm, mode="lines", line=go.scatter3d.Line(color="black", width=2),
showlegend=False, opacity=1, name="", hoverinfo='skip')
#v const
for v0 in v:
if (eps > 0):
x = b * np.cosh(v0 / b) * np.cos(ud)
y = b * np.cosh(v0 / b) * np.sin(ud)
z = b * np.sinh(v0 / b) * np.ones_like(ud)
xm = bm * np.cosh(v0 / bm) * np.cos(ud)
ym = bm * np.cosh(v0 / bm) * np.sin(ud)
zm = bm * np.sinh(v0 / bm) * np.ones_like(ud)
else:
x = b * np.cosh(v0 / b) * np.cos(ud)
y = b * np.sinh(v0 / b) * np.ones_like(ud)
z = b * np.cosh(v0 / b) * np.sin(ud)
xm = bm * np.cosh(v0 / bm) * np.cos(ud)
ym = bm * np.sinh(v0 / bm) * np.ones_like(ud)
zm = bm * np.cosh(v0 / bm) * np.sin(ud)
_tempfig.add_scatter3d(x=x, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=2),
showlegend=False, opacity=1, name="", hoverinfo='skip')
_tempfig.add_scatter3d(x=xm, y=ym, z=zm, mode="lines", line=go.scatter3d.Line(color="black", width=2),
showlegend=False, opacity=1, name="", hoverinfo='skip')
self.fig.add_traces(_tempfig.data)
def plotCutAndPasteHyperboloid(self, H, l, vsize=(-2, 2), opacity=0.5, plot_edges=False, color="rgb(" + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + ")", drawImpulse=False, showlegend=False, drawOnlyMinus=False):
from scipy.spatial import Delaunay
a = np.sqrt(3 / np.abs(l))
eps = np.sign(l)
uo = np.linspace(0, 2 * np.pi, 650)
v = np.linspace(vsize[0], vsize[1], 550) # TODO: resolution should not be hard-coded
uo, v = np.meshgrid(uo, v)
u = uo.flatten()
v = v.flatten()
#TODO: OPRAVIT, ZKUST https://stackoverflow.com/questions/25060103/determine-sum-of-numpy-array-while-excluding-certain-values
if (eps > 0):
x = a * np.cosh(v / a) * np.cos(u) # Z1
z = a * np.sinh(v / a) # Z0
y = a * np.cosh(v / a) * np.sin(u) # Z4
else:
x = a * np.cosh(v/a) * np.cos(u)
z = a * np.cosh(v / a) * np.sin(u)
y = a * np.sinh(v / a)
xm = np.array([a if c - b <= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
ym = np.array([b if c - b <= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
zm = np.array([c if c - b <= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
if not drawOnlyMinus:
xp = np.array([a if c - b >= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
yp = np.array([b - 1. / np.sqrt(2) * H if c - b >= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
zp = np.array([c + 1. / np.sqrt(2) * H if c - b >= 0 else np.nan for a, b, c in zip(x, y, z)]).reshape(uo.shape)
_tempfig = go.Figure(data=([
go.Surface(x=xm, y=ym, z=zm, colorscale=[color, color])
] if drawOnlyMinus else [
go.Surface(x=xp, y=yp, z=zp, colorscale=[color, color]),
go.Surface(x=xm, y=ym, z=zm, colorscale=[color, color])
]))
if not drawOnlyMinus:
_tempfig['data'][0].update(name="Hyperboloid +")
_tempfig['data'][1].update(name="Hyperboloid -")
else:
_tempfig['data'][0].update(name="Hyperboloid -")
_tempfig.update_traces(showscale=False, opacity=opacity, hoverinfo='skip', showlegend=showlegend)
if drawImpulse:
v = np.linspace(vsize[0], vsize[1], 10)
z = v[:-1]
y = v[:-1]
x = 10 * [-a]
x2 = 10 * [a]
_tempfig.add_scatter3d(x=x, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=4),
name="U- = infinity", hoverinfo='skip', showlegend=showlegend , opacity=0.4)
_tempfig.add_scatter3d(x=x2, y=y, z=z, mode="lines", line=go.scatter3d.Line(color="black", width=8),
name="U- = 0", hoverinfo='skip', showlegend=showlegend, opacity=0.8)
if not drawOnlyMinus:
_tempfig.add_scatter3d(x=x , y=y - 1. / np.sqrt(2) * H, z=z + 1. / np.sqrt(2) * H, mode="lines", line=go.scatter3d.Line(color="black", width=4),
name="U+ = infinity", hoverinfo='skip', showlegend=showlegend, opacity=0.4)
_tempfig.add_scatter3d(x=x2, y=y - 1. / np.sqrt(2) * H, z=z + 1. / np.sqrt(2) * H, mode="lines", line=go.scatter3d.Line(color="black", width=8),
name="U+ = 0", hoverinfo='skip', showlegend=showlegend, opacity=0.8)
self.fig.add_traces(_tempfig.data)
def plotSurface(self, f, *args, xdomain=[-1, 1], ydomain=[-1, 1], xstep=0.05, ystep=0.05, color="rgb(" + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + "," + str(random.randint(50,100)) + ")", color2=None, complexNull=False, name="Surface", showlegend=False):
x = np.arange(xdomain[0], xdomain[1], xstep)
y = np.arange(ydomain[0], ydomain[1], ystep)
#X, Y = np.meshgrid(x, y)
z = np.zeros((x.size, y.size))
for i in range(x.size):
for j in range(y.size):
if complexNull:
z[i, j] = f(x[i] + 1j * y[j], x[i] - 1j * y[j], args)
else:
z[i, j] = f(x[i], y[j], args)
if z[i, j] == np.NaN:
z[i, j] = 0
if color2 is None:
color2 = color
_tempfig = go.Figure(data=[
go.Surface(x=x, y=y, z=z, colorscale=[color, color2], name=name, surfacecolor=np.sqrt(np.abs(z)))])
_tempfig.update_traces(showscale=False, showlegend=showlegend)
self.fig.add_traces(_tempfig.data)
def show(self):
self.fig.show()
def export_html(self, path, include_plotlyjs=True, include_mathjax=False):
if include_mathjax:
include_mathjax = 'cdn'
self.fig.write_html(path, include_plotlyjs=include_plotlyjs, include_mathjax=include_mathjax)
#TODO: Do something with default camera
def export_pdf(self, path, eye=(1.25, 1.25, 1.25), up=(.0, .0, 1.0), orbit=False, title=True):
"""
This requires Kaleido, install using "pip install -U Kaleido".
:param path: Path of resulting file
:param eye: Eye of camera
:return:
"""
camera = dict(
eye=dict(x=eye[0], y=eye[1], z=eye[2]),
up=dict(x=up[0], y=up[1], z=up[2])
)
if orbit:
self.fig.update_layout(scene = dict(dragmode='orbit'))
self.fig.update_layout(scene_camera=camera, showlegend=False)
write_image(self.fig, path, format="pdf", scale=3, engine="kaleido", width=1024, height=1024)
self.fig.update_layout(scene_camera=dict(eye=dict(x=1.25, y=1.25, z=1.25), up=dict(x=.0,y=.0,z=1.0)), showlegend=True, scene=dict(dragmode='turntable')) | PypiClean |
/Flask-Perm-0.2.8.tar.gz/Flask-Perm-0.2.8/flask_perm/app.py |
import logging
from functools import wraps
from flask import session, request
from sqlalchemy.exc import IntegrityError
from werkzeug.security import generate_password_hash
from werkzeug.security import check_password_hash
from .core import db, bcrypt
class Perm(object):
class Denied(Exception):
pass
def __init__(self, app=None):
self.app = app
self.user_callback = None
self.current_user_callback = None
self.users_callback = None
self.users_count_callback = None
self._admin_logger = logging.getLogger('flask_perm.admin')
self.registered_permissions = set()
if app is not None:
self.init_app(app)
@property
def admin_logger(self):
return self._admin_logger
@admin_logger.setter
def admin_logger(self, logger):
self._admin_logger = logger
def init_app(self, app):
"""Initialize Perm object.
"""
if not hasattr(app, 'extensions'):
app.extensions = {}
app.extensions['perm'] = self
db.app = app
db.init_app(app)
bcrypt.app = app
bcrypt.init_app(app)
app.config.setdefault('PERM_ADMIN_PREFIX', '/perm-admin')
app.config.setdefault('PERM_ADMIN_ECHO', False)
from . import models
db.create_all()
from .api import bp as api_bp
app.register_blueprint(api_bp, url_prefix=app.config.get('PERM_ADMIN_PREFIX') + '/api')
from .admin import bp as admin_bp
app.register_blueprint(admin_bp, url_prefix=app.config.get('PERM_ADMIN_PREFIX'))
self.register_context_processors(app)
def log_admin_action(self, msg):
'''Log msg to `flask.admin` logger.'''
if self.app.config.get('PERM_ADMIN_ECHO'):
self.admin_logger.info(msg)
def require_perm_admin(self, f):
'''A decorator that can protect function from unauthorized request.
Used in perm admin dashboard.'''
@wraps(f)
def _(*args, **kwargs):
if not session.get('perm_admin_id'):
raise self.Denied
return f(*args, **kwargs)
return _
def create_super_admin(self, email, password):
"""Create superadmin / Reset password."""
from .services import SuperAdminService
try:
superadmin = SuperAdminService.create(email, password)
except IntegrityError:
superadmin = SuperAdminService.get_by_email(email)
superadmin = SuperAdminService.reset_password(superadmin.id, password)
return SuperAdminService.to_dict(superadmin)
def login_perm_admin(self, super_admin_id):
"""Get authorization to access perm admin dashboard."""
session['perm_admin_id'] = super_admin_id
def logout_perm_admin(self):
"""Revoke authorization from accessing perm admin dashboard."""
session.pop('perm_admin_id', None)
def get_perm_admin_id_from_session(self):
from .services import SuperAdminService
admin_id = session.get('perm_admin_id')
super_admin = admin_id and SuperAdminService.get(admin_id)
return super_admin and super_admin.id
def get_perm_admin_id_by_auth(self, email, password):
from .services import SuperAdminService
if SuperAdminService.verify_password(email, password):
super_admin = SuperAdminService.get_by_email(email)
return super_admin and super_admin.id
def get_perm_admin_id(self):
"""Get super admin id. Both basic authorization and cookie are support."""
if request.authorization:
auth = request.authorization
return self.get_perm_admin_id_by_auth(auth.username, auth.password)
return self.get_perm_admin_id_from_session()
def has_perm_admin_logined(self):
""""""
return bool(self.get_perm_admin_id())
def user_loader(self, callback):
"""Define user loader.
Required if you plan to use perm admin dashboard.
The callback will be used to render user basic information in dashboard.
Callback must take `user_id` integer parameter.
"""
self.user_callback = callback
return callback
def current_user_loader(self, callback):
"""Define current user loader.
Required if you plan to use decorator to protect your function.
The callback will be used in deciding whether current user has authority.
Callback takes no parameters.
"""
self.current_user_callback = callback
return callback
def users_loader(self, callback):
"""Define users loader.
Required if you plan to use perm admin dashboard.
The callback will be used to render whole user list in dashboard.
Callback must take 5 parameters:
* filter_by={},
* sort_field='created_at',
* sort_dir='desc',
* offset=0,
* limit=20
"""
self.users_callback = callback
return callback
def users_count_loader(self, callback):
"""Define users count loader.
Required if you plan to use perm admin dashboard.
The callback will be used in paginating user list.
Callback takes no parameters."""
self.users_count_callback = callback
return callback
def load_user(self, user_id):
if self.user_callback is None:
raise NotImplementedError('You must register user_loader!')
return self.user_callback(user_id)
def load_current_user(self):
if self.current_user_callback is None:
raise NotImplementedError('You must register current_user_loader!')
return self.current_user_callback()
def load_users(self, filter_by={}, sort_field='created_at', sort_dir='desc', offset=0, limit=20):
if self.users_callback is None:
raise NotImplementedError('You must register users_loader!')
return self.users_callback(**dict(
filter_by=filter_by,
sort_field=sort_field,
sort_dir=sort_dir,
offset=offset,
limit=limit,
))
def load_users_count(self):
if self.users_count_callback is None:
raise NotImplementedError('You must register users_count_loader')
return self.users_count_callback()
def has_permission(self, user_id, code):
"""Decide whether a user has a permission identified by `codes`.
Code is defined in perm admin dashboard."""
from .services import VerificationService, PermissionService
permission = PermissionService.get_by_code(code)
if not permission:
return False
return VerificationService.has_permission(user_id, permission.id)
def has_permissions(self, user_id, *codes):
"""Decide whether a user has permissions identified by `codes`.
Codes are defined in perm admin dashboard."""
if not codes:
return True
if '*' in codes:
return any(
self.has_permission(user_id, code)
for code in self.get_all_permission_codes()
)
else:
return any(self.has_permission(user_id, code) for code in codes)
def get_user_permissions(self, user_id):
"""Define all permission codes that authorized to a user.
Codes are defined in perm admin dashboard."""
from .services import VerificationService, PermissionService
permission_ids = VerificationService.get_user_permissions(user_id)
permissions = map(PermissionService.get, permission_ids)
permissions = filter(None, permissions)
permissions = map(PermissionService.rest, permissions)
return permissions
def get_all_permission_codes(self):
"""Get all permission codes.
WARNING: this might have performance issue."""
from .services import PermissionService
permissions = PermissionService.get_permissions()
return [permission.code for permission in permissions]
def is_user_in_groups(self, user_id, *groups):
"""Decide whether a user is in groups.
Groups are defined in perm admin dashboard."""
from .services import UserGroupService, UserGroupMemberService
if not groups:
return False
if '*' in groups:
user_group_ids = UserGroupService.get_all_user_group_ids()
else:
user_groups = UserGroupService.get_user_groups_by_codes(groups)
user_group_ids = [user_group.id for user_group in user_groups]
if not user_group_ids:
return False
return UserGroupMemberService.is_user_in_groups(user_id, user_group_ids)
def require_group(self, *groups):
"""A decorator that can decide whether current user is in listed groups.
Groups are defined in perm admin dashboard."""
from .services import UserGroupService, UserGroupMemberService
def deco(func):
@wraps(func)
def _(*args, **kwargs):
current_user = self.load_current_user()
if not current_user:
raise self.Denied
current_user_id = current_user.id
is_allowed = self.is_user_in_groups(current_user_id, *groups)
if is_allowed:
return func(*args, **kwargs)
else:
raise self.Denied
return _
return deco
def require_group_in_template(self, *groups):
"""Require group in template"""
from .services import UserGroupService, UserGroupMemberService
current_user = self.load_current_user()
if not current_user:
return False
current_user_id = current_user.id
return self.is_user_in_groups(current_user_id, *groups)
def require_permission(self, *codes):
"""A decorator that can decide whether current user has listed permission codes.
Codes are defined in perm admin dashboard."""
for code in codes:
self.registered_permissions.add(code)
def deco(func):
@wraps(func)
def _(*args, **kwargs):
current_user = self.load_current_user()
if not current_user:
raise self.Denied
is_allowed = self.has_permissions(current_user.id, *codes)
if is_allowed:
return func(*args, **kwargs)
else:
raise self.Denied
return _
return deco
def require_permission_in_template(self, *codes):
"""Require permission in template."""
for code in codes:
self.registered_permissions.add(code)
current_user = self.load_current_user()
if not current_user:
return False
return self.has_permissions(current_user.id, *codes)
def default_context_processors(self):
return {
'require_permission': self.require_permission_in_template,
'require_group': self.require_group_in_template,
}
def register_commands(self, flask_script_manager):
"""Register several convinient Flask-Script commands.
WARNING: make sure you have installed Flask-Script.
:param flask_script_manager: a flask.ext.script.Manager object.
"""
from .script import perm_manager
flask_script_manager.add_command('perm', perm_manager)
def register_context_processors(self, app):
"""Register default context processors to app.
"""
app.context_processor(self.default_context_processors) | PypiClean |
/Nuitka_fixed-1.1.2-cp310-cp310-win_amd64.whl/nuitka/build/inline_copy/lib/scons-2.3.2/SCons/Tool/msgmerge.py |
__revision__ = "src/engine/SCons/Tool/msgmerge.py 2014/07/05 09:42:21 garyo"
#############################################################################
def _update_or_init_po_files(target, source, env):
""" Action function for `POUpdate` builder """
import SCons.Action
from SCons.Tool.GettextCommon import _init_po_files
for tgt in target:
if tgt.rexists():
action = SCons.Action.Action('$MSGMERGECOM', '$MSGMERGECOMSTR')
else:
action = _init_po_files
status = action([tgt], source, env)
if status : return status
return 0
#############################################################################
#############################################################################
def _POUpdateBuilder(env, **kw):
""" Create an object of `POUpdate` builder """
import SCons.Action
from SCons.Tool.GettextCommon import _POFileBuilder
action = SCons.Action.Action(_update_or_init_po_files, None)
return _POFileBuilder(env, action=action, target_alias='$POUPDATE_ALIAS')
#############################################################################
#############################################################################
from SCons.Environment import _null
#############################################################################
def _POUpdateBuilderWrapper(env, target=None, source=_null, **kw):
""" Wrapper for `POUpdate` builder - make user's life easier """
if source is _null:
if 'POTDOMAIN' in kw:
domain = kw['POTDOMAIN']
elif env.has_key('POTDOMAIN') and env['POTDOMAIN']:
domain = env['POTDOMAIN']
else:
domain = 'messages'
source = [ domain ] # NOTE: Suffix shall be appended automatically
return env._POUpdateBuilder(target, source, **kw)
#############################################################################
#############################################################################
def generate(env,**kw):
""" Generate the `xgettext` tool """
from SCons.Tool.GettextCommon import _detect_msgmerge
try:
env['MSGMERGE'] = _detect_msgmerge(env)
except:
env['MSGMERGE'] = 'msgmerge'
env.SetDefault(
POTSUFFIX = ['.pot'],
POSUFFIX = ['.po'],
MSGMERGECOM = '$MSGMERGE $MSGMERGEFLAGS --update $TARGET $SOURCE',
MSGMERGECOMSTR = '',
MSGMERGEFLAGS = [ ],
POUPDATE_ALIAS = 'po-update'
)
env.Append(BUILDERS = { '_POUpdateBuilder':_POUpdateBuilder(env) })
env.AddMethod(_POUpdateBuilderWrapper, 'POUpdate')
env.AlwaysBuild(env.Alias('$POUPDATE_ALIAS'))
#############################################################################
#############################################################################
def exists(env):
""" Check if the tool exists """
from SCons.Tool.GettextCommon import _msgmerge_exists
try:
return _msgmerge_exists(env)
except:
return False
#############################################################################
# Local Variables:
# tab-width:4
# indent-tabs-mode:nil
# End:
# vim: set expandtab tabstop=4 shiftwidth=4: | PypiClean |
/NeodroidVision-0.3.0-py36-none-any.whl/neodroidvision/data/classification/nlet/triplet_dataset.py |
__author__ = "Christian Heider Nielsen"
__doc__ = r"""
Created on 30/06/2020
"""
import random
from pathlib import Path
from typing import Tuple
import numpy
import torch
__all__ = ["TripletDataset"]
from draugr.torch_utilities import global_pin_memory
from torch.utils.data import DataLoader
from neodroidvision.data.classification.nlet import PairDataset
class TripletDataset(
PairDataset
): # TODO: Extract image specificity of class to a subclass and move this super pair class to a
# general torch lib.
"""
# This dataset generates a triple of images. an image of a category, another of the same category and
lastly one from another category"""
def __getitem__(self, idx1: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
"""
returns torch.tensors for img triplet, first tensor being idx random category, second being the same
category with different index
and third being of a random other category(Never the same)
:param idx1:
:type idx1:
:return:
:rtype:"""
t1 = random.choice(self._dataset.category_names)
while True:
idx2 = random.randint(0, self._dataset.category_sizes[t1])
if idx1 != idx2:
break
while True:
t2 = random.choice(self._dataset.category_names)
if t1 != t2:
break
return (
self._dataset.sample(t1, idx1)[0],
self._dataset.sample(t1, idx2)[0],
self._dataset.sample(
t2, random.randint(0, self._dataset.category_sizes[t2])
)[0],
*((t1, t2, t1) if self.return_categories else ()),
)
def sample(self, horizontal_merge: bool = False) -> None:
"""description"""
dl = iter(
DataLoader(
self,
batch_size=9,
shuffle=True,
num_workers=0,
pin_memory=global_pin_memory(0),
)
)
for _ in range(3):
images1, images2, images3, *labels = next(dl)
X1 = numpy.transpose(images1.numpy(), [0, 2, 3, 1])
X2 = numpy.transpose(images2.numpy(), [0, 2, 3, 1])
X3 = numpy.transpose(images3.numpy(), [0, 2, 3, 1])
if horizontal_merge:
X = numpy.dstack((X1, X2, X3))
else:
X = numpy.hstack((X1, X2, X3))
PairDataset.plot_images(X, list(zip(*labels)))
if __name__ == "__main__":
sd = TripletDataset(Path.home() / "Data" / "mnist_png", return_categories=True)
print(sd.predictor_shape)
print(sd.response_shape)
sd.sample() | PypiClean |
/Jin-Py-1.0.31.tar.gz/Jin-Py-1.0.31/jin/composer.py | import os
import sys
pushCommandTemplate = ["rsync", "-vzaPr"]
clearCommandTemplate = ["rsync", "-vPr", "--delete", "--existing", "--ignore-existing"]
class Composer():
"""Composes an rsync command from system arguements and jinconfig file"""
def __init__(self, args, config):
self.args = args
self.config = config
self.isDryRun = False
self.isHot = False
self.minToWatch = 1
self.command = self.dispatchCommandFromType(self.args[0])
def checkConfigForRequired(self, command, config):
if command == "push":
if self.config.get("sloc") == None and self.config.get("sdir") == None:
print(".jinconfig doesn't contain source information!")
sys.exit(1)
if self.config.get("dloc") == None and self.config.get("ddir") == None:
print(".jinconfig doesn't contain destination information!")
sys.exit(1)
if self.config.get("wmin") != None:
self.minToWatch = int(self.config.get("wmin")[0])
if command == "empty":
if self.config.get("dloc") == None and self.config.get("ddir") == None:
print(".jinconfig doesn't contain destination information!")
sys.exit(1)
def dispatchCommandFromType(self, command):
if command == "push":
self.checkConfigForRequired(command, self.config)
if len(self.args) > 1:
for arg in self.args[1:]:
if arg == "dry":
pushCommandTemplate.append("--dry-run")
self.isDryRun = True
elif arg == "watch":
self.isHot = True
elif arg == "match-host":
pushCommandTemplate.append("--delete")
else:
print(f"Invalid command '{arg}'!")
sys.exit(1)
return self.generatePushCommand()
elif command == "empty":
self.checkConfigForRequired(command, self.config)
if len(self.args) > 1:
for arg in self.args:
if arg == "dry":
clearCommandTemplate.append("--dry-run")
self.isDryRun = True
return self.generateClearCommand()
else:
print(f"Invalid command '{command}'! Exiting...")
sys.exit(1)
def generateClearCommand(self):
command = clearCommandTemplate
destination = ""
if not os.path.exists("./.jin/_blank/"):
print(".jin/_blank directory doesn't exist! Run 'jin make' to fix this.")
sys.exit(1)
if self.config.get("dloc") == None:
destination = self.config.get("ddir")[0]
else:
destination = f"{self.config.get('dloc')[0]}:{self.config.get('ddir')[0]}"
# command = rsync -r --delete --existing --ignore-existing ./jin/_blank/ [destination]
command.extend((".jin/_blank/", destination))
return command
def generatePushCommand(self):
command = pushCommandTemplate
source = ""
destination = ""
ignoreSpecific = []
ignoreType = []
if self.config.get("sloc") == None:
source = self.config.get("sdir")[0]
else:
source = f"{self.config.get('sloc')[0]}:{self.config.get('sdir')[0]}"
if self.config.get("dloc") == None:
destination = self.config.get("ddir")[0]
else:
destination = f"{self.config.get('dloc')[0]}:{self.config.get('ddir')[0]}"
if self.config.get("igspec") != None:
for excludedSpecific in self.config.get("igspec"):
ignoreSpecific.append("--exclude")
ignoreSpecific.append(excludedSpecific)
if self.config.get("igtype") != None:
for excludedType in self.config.get("igtype"):
ignoreType.append("--exclude")
ignoreType.append(excludedType)
for spec in ignoreSpecific: command.append(spec)
for spec in ignoreType: command.append(spec)
# command = rsync -vzaPr --exclude [ignoreSpecific] --exclude [ignoreType] [source] [destination]
command.extend((source, destination))
print(" ".join(command), "\n")
return command | PypiClean |
/Firefly_III_API_Client-2.0.5.0-py3-none-any.whl/firefly_iii_client/paths/v1_tags_tag/put.py | from dataclasses import dataclass
import typing_extensions
import urllib3
from urllib3._collections import HTTPHeaderDict
from firefly_iii_client import api_client, exceptions
from datetime import date, datetime # noqa: F401
import decimal # noqa: F401
import functools # noqa: F401
import io # noqa: F401
import re # noqa: F401
import typing # noqa: F401
import typing_extensions # noqa: F401
import uuid # noqa: F401
import frozendict # noqa: F401
from firefly_iii_client import schemas # noqa: F401
from firefly_iii_client.model.tag_single import TagSingle
from firefly_iii_client.model.validation_error import ValidationError
from firefly_iii_client.model.unauthenticated import Unauthenticated
from firefly_iii_client.model.bad_request import BadRequest
from firefly_iii_client.model.tag_model_update import TagModelUpdate
from firefly_iii_client.model.internal_exception import InternalException
from firefly_iii_client.model.not_found import NotFound
from . import path
# Header params
XTraceIdSchema = schemas.UUIDSchema
RequestRequiredHeaderParams = typing_extensions.TypedDict(
'RequestRequiredHeaderParams',
{
}
)
RequestOptionalHeaderParams = typing_extensions.TypedDict(
'RequestOptionalHeaderParams',
{
'X-Trace-Id': typing.Union[XTraceIdSchema, str, uuid.UUID, ],
},
total=False
)
class RequestHeaderParams(RequestRequiredHeaderParams, RequestOptionalHeaderParams):
pass
request_header_x_trace_id = api_client.HeaderParameter(
name="X-Trace-Id",
style=api_client.ParameterStyle.SIMPLE,
schema=XTraceIdSchema,
)
# Path params
TagSchema = schemas.StrSchema
RequestRequiredPathParams = typing_extensions.TypedDict(
'RequestRequiredPathParams',
{
'tag': typing.Union[TagSchema, str, ],
}
)
RequestOptionalPathParams = typing_extensions.TypedDict(
'RequestOptionalPathParams',
{
},
total=False
)
class RequestPathParams(RequestRequiredPathParams, RequestOptionalPathParams):
pass
request_path_tag = api_client.PathParameter(
name="tag",
style=api_client.ParameterStyle.SIMPLE,
schema=TagSchema,
required=True,
)
# body param
SchemaForRequestBodyApplicationJson = TagModelUpdate
SchemaForRequestBodyApplicationXWwwFormUrlencoded = TagModelUpdate
request_body_tag_model_update = api_client.RequestBody(
content={
'application/json': api_client.MediaType(
schema=SchemaForRequestBodyApplicationJson),
'application/x-www-form-urlencoded': api_client.MediaType(
schema=SchemaForRequestBodyApplicationXWwwFormUrlencoded),
},
required=True,
)
_auth = [
'firefly_iii_auth',
]
SchemaFor200ResponseBodyApplicationVndApijson = TagSingle
@dataclass
class ApiResponseFor200(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor200ResponseBodyApplicationVndApijson,
]
headers: schemas.Unset = schemas.unset
_response_for_200 = api_client.OpenApiResponse(
response_cls=ApiResponseFor200,
content={
'application/vnd.api+json': api_client.MediaType(
schema=SchemaFor200ResponseBodyApplicationVndApijson),
},
)
SchemaFor400ResponseBodyApplicationJson = BadRequest
@dataclass
class ApiResponseFor400(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor400ResponseBodyApplicationJson,
]
headers: schemas.Unset = schemas.unset
_response_for_400 = api_client.OpenApiResponse(
response_cls=ApiResponseFor400,
content={
'application/json': api_client.MediaType(
schema=SchemaFor400ResponseBodyApplicationJson),
},
)
SchemaFor401ResponseBodyApplicationJson = Unauthenticated
@dataclass
class ApiResponseFor401(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor401ResponseBodyApplicationJson,
]
headers: schemas.Unset = schemas.unset
_response_for_401 = api_client.OpenApiResponse(
response_cls=ApiResponseFor401,
content={
'application/json': api_client.MediaType(
schema=SchemaFor401ResponseBodyApplicationJson),
},
)
SchemaFor404ResponseBodyApplicationJson = NotFound
@dataclass
class ApiResponseFor404(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor404ResponseBodyApplicationJson,
]
headers: schemas.Unset = schemas.unset
_response_for_404 = api_client.OpenApiResponse(
response_cls=ApiResponseFor404,
content={
'application/json': api_client.MediaType(
schema=SchemaFor404ResponseBodyApplicationJson),
},
)
SchemaFor422ResponseBodyApplicationJson = ValidationError
@dataclass
class ApiResponseFor422(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor422ResponseBodyApplicationJson,
]
headers: schemas.Unset = schemas.unset
_response_for_422 = api_client.OpenApiResponse(
response_cls=ApiResponseFor422,
content={
'application/json': api_client.MediaType(
schema=SchemaFor422ResponseBodyApplicationJson),
},
)
SchemaFor500ResponseBodyApplicationJson = InternalException
@dataclass
class ApiResponseFor500(api_client.ApiResponse):
response: urllib3.HTTPResponse
body: typing.Union[
SchemaFor500ResponseBodyApplicationJson,
]
headers: schemas.Unset = schemas.unset
_response_for_500 = api_client.OpenApiResponse(
response_cls=ApiResponseFor500,
content={
'application/json': api_client.MediaType(
schema=SchemaFor500ResponseBodyApplicationJson),
},
)
_status_code_to_response = {
'200': _response_for_200,
'400': _response_for_400,
'401': _response_for_401,
'404': _response_for_404,
'422': _response_for_422,
'500': _response_for_500,
}
_all_accept_content_types = (
'application/vnd.api+json',
'application/json',
)
class BaseApi(api_client.Api):
@typing.overload
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,],
content_type: typing_extensions.Literal["application/json"] = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: typing_extensions.Literal["application/x-www-form-urlencoded"],
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
skip_deserialization: typing_extensions.Literal[True],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
) -> api_client.ApiResponseWithoutDeserialization: ...
@typing.overload
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = ...,
) -> typing.Union[
ApiResponseFor200,
api_client.ApiResponseWithoutDeserialization,
]: ...
def _update_tag_oapg(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = 'application/json',
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = False,
):
"""
Update existing tag.
:param skip_deserialization: If true then api_response.response will be set but
api_response.body and api_response.headers will not be deserialized into schema
class instances
"""
self._verify_typed_dict_inputs_oapg(RequestHeaderParams, header_params)
self._verify_typed_dict_inputs_oapg(RequestPathParams, path_params)
used_path = path.value
_path_params = {}
for parameter in (
request_path_tag,
):
parameter_data = path_params.get(parameter.name, schemas.unset)
if parameter_data is schemas.unset:
continue
serialized_data = parameter.serialize(parameter_data)
_path_params.update(serialized_data)
for k, v in _path_params.items():
used_path = used_path.replace('{%s}' % k, v)
_headers = HTTPHeaderDict()
for parameter in (
request_header_x_trace_id,
):
parameter_data = header_params.get(parameter.name, schemas.unset)
if parameter_data is schemas.unset:
continue
serialized_data = parameter.serialize(parameter_data)
_headers.extend(serialized_data)
# TODO add cookie handling
if accept_content_types:
for accept_content_type in accept_content_types:
_headers.add('Accept', accept_content_type)
if body is schemas.unset:
raise exceptions.ApiValueError(
'The required body parameter has an invalid value of: unset. Set a valid value instead')
_fields = None
_body = None
serialized_data = request_body_tag_model_update.serialize(body, content_type)
_headers.add('Content-Type', content_type)
if 'fields' in serialized_data:
_fields = serialized_data['fields']
elif 'body' in serialized_data:
_body = serialized_data['body']
response = self.api_client.call_api(
resource_path=used_path,
method='put'.upper(),
headers=_headers,
fields=_fields,
body=_body,
auth_settings=_auth,
stream=stream,
timeout=timeout,
)
if skip_deserialization:
api_response = api_client.ApiResponseWithoutDeserialization(response=response)
else:
response_for_status = _status_code_to_response.get(str(response.status))
if response_for_status:
api_response = response_for_status.deserialize(response, self.api_client.configuration)
else:
api_response = api_client.ApiResponseWithoutDeserialization(response=response)
if not 200 <= response.status <= 299:
raise exceptions.ApiException(
status=response.status,
reason=response.reason,
api_response=api_response
)
return api_response
class UpdateTag(BaseApi):
# this class is used by api classes that refer to endpoints with operationId fn names
@typing.overload
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,],
content_type: typing_extensions.Literal["application/json"] = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: typing_extensions.Literal["application/x-www-form-urlencoded"],
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
skip_deserialization: typing_extensions.Literal[True],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
) -> api_client.ApiResponseWithoutDeserialization: ...
@typing.overload
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = ...,
) -> typing.Union[
ApiResponseFor200,
api_client.ApiResponseWithoutDeserialization,
]: ...
def update_tag(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = 'application/json',
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = False,
):
return self._update_tag_oapg(
body=body,
header_params=header_params,
path_params=path_params,
content_type=content_type,
accept_content_types=accept_content_types,
stream=stream,
timeout=timeout,
skip_deserialization=skip_deserialization
)
class ApiForput(BaseApi):
# this class is used by api classes that refer to endpoints by path and http method names
@typing.overload
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,],
content_type: typing_extensions.Literal["application/json"] = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: typing_extensions.Literal["application/x-www-form-urlencoded"],
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: typing_extensions.Literal[False] = ...,
) -> typing.Union[
ApiResponseFor200,
]: ...
@typing.overload
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
skip_deserialization: typing_extensions.Literal[True],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
) -> api_client.ApiResponseWithoutDeserialization: ...
@typing.overload
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = ...,
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = ...,
) -> typing.Union[
ApiResponseFor200,
api_client.ApiResponseWithoutDeserialization,
]: ...
def put(
self,
body: typing.Union[SchemaForRequestBodyApplicationJson,SchemaForRequestBodyApplicationXWwwFormUrlencoded,],
content_type: str = 'application/json',
header_params: RequestHeaderParams = frozendict.frozendict(),
path_params: RequestPathParams = frozendict.frozendict(),
accept_content_types: typing.Tuple[str] = _all_accept_content_types,
stream: bool = False,
timeout: typing.Optional[typing.Union[int, typing.Tuple]] = None,
skip_deserialization: bool = False,
):
return self._update_tag_oapg(
body=body,
header_params=header_params,
path_params=path_params,
content_type=content_type,
accept_content_types=accept_content_types,
stream=stream,
timeout=timeout,
skip_deserialization=skip_deserialization
) | PypiClean |
/Djblets-3.3.tar.gz/Djblets-3.3/djblets/htdocs/static/djblets/js/avatars/views/avatarSettingsFormView.js | "use strict";
(function () {
const [readyPromise, resolve] = Promise.withResolver();
/**
* A form for managing the settings of avatar services.
*
* This form lets you select the avatar service you wish to use, as well as
* configure the settings for that avatar service.
*/
Djblets.Avatars.SettingsFormView = Backbone.View.extend({
events: {
'change #id_avatar_service_id': '_onServiceChanged',
'submit': '_onSubmit'
},
/**
* Initialize the form.
*/
initialize() {
console.assert(Djblets.Avatars.SettingsFormView.instance === null);
Djblets.Avatars.SettingsFormView.instance = this;
this._configForms = new Map();
this._$config = this.$('.avatar-service-configuration');
const services = this.model.get('services');
this.listenTo(this.model, 'change:serviceID', () => this._showHideForms());
/*
* The promise continuations will only be executed once the stack is
* unwound.
*/
resolve();
},
/**
* Validate the current form upon submission.
*
* Args:
* e (Event):
* The form submission event.
*/
_onSubmit(e) {
const serviceID = this.model.get('serviceID');
const currentForm = this._configForms.get(serviceID);
if (currentForm && !currentForm.validate()) {
e.preventDefault();
}
},
/**
* Render the child forms.
*
* This will show the for the currently selected service if it has one.
*
* Returns:
* Djblets.Avatars.SettingsFormView:
* This view (for chaining).
*/
renderForms() {
for (const form of this._configForms.values()) {
form.render();
}
/*
* Ensure that if the browser sets the value of the <select> upon
* refresh that we update the model accordingly.
*/
this.$('#id_avatar_service_id').change();
this._showHideForms(true);
return this;
},
/**
* Show or hide the configuration form.
*/
_showHideForms() {
const services = this.model.get('services');
const serviceID = this.model.get('serviceID');
const currentForm = this._configForms.get(serviceID);
const previousID = this.model.previous('serviceID');
const previousForm = previousID ? this._configForms.get(previousID) : undefined;
if (previousForm && currentForm) {
previousForm.$el.hide();
currentForm.$el.show();
} else if (previousForm) {
previousForm.$el.hide();
this._$config.hide();
} else if (currentForm) {
currentForm.$el.show();
this._$config.show();
}
},
/**
* Handle the service being changed.
*
* Args:
* e (Event):
* The change event.
*/
_onServiceChanged(e) {
const $target = $(e.target);
this.model.set('serviceID', $target.val());
}
}, {
/**
* The form instance.
*/
instance: null,
/**
* Add a configuration form to the instance.
*
* Args:
* serviceID (string):
* The unique ID for the avatar service.
*
* formClass (constructor):
* The view to use for the form.
*/
addConfigForm(serviceID, formClass) {
Djblets.Avatars.SettingsFormView.instance._configForms.set(serviceID, new formClass({
el: $(`[data-avatar-service-id="${serviceID}"]`),
model: Djblets.Avatars.SettingsFormView.instance.model
}));
},
/**
* A promise that is resolved when the avatar services form has been
* initialized.
*/
ready: readyPromise
});
})();
//# sourceMappingURL=avatarSettingsFormView.js.map | PypiClean |
/MIAvisual-0.0.6-py3-none-any.whl/matplotlib/type1font.py | import binascii
import enum
import itertools
import logging
import re
import struct
import numpy as np
from matplotlib.cbook import _format_approx
from . import _api
_log = logging.getLogger(__name__)
# token types
_TokenType = enum.Enum('_TokenType',
'whitespace name string delimiter number')
class Type1Font:
"""
A class representing a Type-1 font, for use by backends.
Attributes
----------
parts : tuple
A 3-tuple of the cleartext part, the encrypted part, and the finale of
zeros.
decrypted : bytes
The decrypted form of parts[1].
prop : dict[str, Any]
A dictionary of font properties.
"""
__slots__ = ('parts', 'decrypted', 'prop')
def __init__(self, input):
"""
Initialize a Type-1 font.
Parameters
----------
input : str or 3-tuple
Either a pfb file name, or a 3-tuple of already-decoded Type-1
font `~.Type1Font.parts`.
"""
if isinstance(input, tuple) and len(input) == 3:
self.parts = input
else:
with open(input, 'rb') as file:
data = self._read(file)
self.parts = self._split(data)
self.decrypted = self._decrypt(self.parts[1], 'eexec')
self._parse()
def _read(self, file):
"""Read the font from a file, decoding into usable parts."""
rawdata = file.read()
if not rawdata.startswith(b'\x80'):
return rawdata
data = b''
while rawdata:
if not rawdata.startswith(b'\x80'):
raise RuntimeError('Broken pfb file (expected byte 128, '
'got %d)' % rawdata[0])
type = rawdata[1]
if type in (1, 2):
length, = struct.unpack('<i', rawdata[2:6])
segment = rawdata[6:6 + length]
rawdata = rawdata[6 + length:]
if type == 1: # ASCII text: include verbatim
data += segment
elif type == 2: # binary data: encode in hexadecimal
data += binascii.hexlify(segment)
elif type == 3: # end of file
break
else:
raise RuntimeError('Unknown segment type %d in pfb file' %
type)
return data
def _split(self, data):
"""
Split the Type 1 font into its three main parts.
The three parts are: (1) the cleartext part, which ends in a
eexec operator; (2) the encrypted part; (3) the fixed part,
which contains 512 ASCII zeros possibly divided on various
lines, a cleartomark operator, and possibly something else.
"""
# Cleartext part: just find the eexec and skip whitespace
idx = data.index(b'eexec')
idx += len(b'eexec')
while data[idx] in b' \t\r\n':
idx += 1
len1 = idx
# Encrypted part: find the cleartomark operator and count
# zeros backward
idx = data.rindex(b'cleartomark') - 1
zeros = 512
while zeros and data[idx] in b'0' or data[idx] in b'\r\n':
if data[idx] in b'0':
zeros -= 1
idx -= 1
if zeros:
# this may have been a problem on old implementations that
# used the zeros as necessary padding
_log.info('Insufficiently many zeros in Type 1 font')
# Convert encrypted part to binary (if we read a pfb file, we may end
# up converting binary to hexadecimal to binary again; but if we read
# a pfa file, this part is already in hex, and I am not quite sure if
# even the pfb format guarantees that it will be in binary).
idx1 = len1 + ((idx - len1 + 2) & ~1) # ensure an even number of bytes
binary = binascii.unhexlify(data[len1:idx1])
return data[:len1], binary, data[idx+1:]
_whitespace_or_comment_re = re.compile(br'[\0\t\r\014\n ]+|%[^\r\n\v]*')
_token_re = re.compile(br'/{0,2}[^]\0\t\r\v\n ()<>{}/%[]+')
_instring_re = re.compile(br'[()\\]')
@staticmethod
def _decrypt(ciphertext, key, ndiscard=4):
"""
Decrypt ciphertext using the Type-1 font algorithm
The algorithm is described in Adobe's "Adobe Type 1 Font Format".
The key argument can be an integer, or one of the strings
'eexec' and 'charstring', which map to the key specified for the
corresponding part of Type-1 fonts.
The ndiscard argument should be an integer, usually 4.
That number of bytes is discarded from the beginning of plaintext.
"""
key = _api.check_getitem({'eexec': 55665, 'charstring': 4330}, key=key)
plaintext = []
for byte in ciphertext:
plaintext.append(byte ^ (key >> 8))
key = ((key+byte) * 52845 + 22719) & 0xffff
return bytes(plaintext[ndiscard:])
@staticmethod
def _encrypt(plaintext, key, ndiscard=4):
"""
Encrypt plaintext using the Type-1 font algorithm
The algorithm is described in Adobe's "Adobe Type 1 Font Format".
The key argument can be an integer, or one of the strings
'eexec' and 'charstring', which map to the key specified for the
corresponding part of Type-1 fonts.
The ndiscard argument should be an integer, usually 4. That
number of bytes is prepended to the plaintext before encryption.
This function prepends NUL bytes for reproducibility, even though
the original algorithm uses random bytes, presumably to avoid
cryptanalysis.
"""
key = _api.check_getitem({'eexec': 55665, 'charstring': 4330}, key=key)
ciphertext = []
for byte in b'\0' * ndiscard + plaintext:
c = byte ^ (key >> 8)
ciphertext.append(c)
key = ((key + c) * 52845 + 22719) & 0xffff
return bytes(ciphertext)
@classmethod
def _tokens(cls, text):
"""
A PostScript tokenizer. Yield (token, value) pairs such as
(_TokenType.whitespace, ' ') or (_TokenType.name, '/Foobar').
"""
# Preload enum members for speed.
tok_whitespace = _TokenType.whitespace
tok_name = _TokenType.name
tok_string = _TokenType.string
tok_delimiter = _TokenType.delimiter
tok_number = _TokenType.number
pos = 0
while pos < len(text):
match = cls._whitespace_or_comment_re.match(text, pos)
if match:
yield (tok_whitespace, match.group())
pos = match.end()
elif text[pos:pos+1] == b'(':
start = pos
pos += 1
depth = 1
while depth:
match = cls._instring_re.search(text, pos)
if match is None:
return
pos = match.end()
if match.group() == b'(':
depth += 1
elif match.group() == b')':
depth -= 1
else: # a backslash - skip the next character
pos += 1
yield (tok_string, text[start:pos])
elif text[pos:pos + 2] in (b'<<', b'>>'):
yield (tok_delimiter, text[pos:pos + 2])
pos += 2
elif text[pos:pos+1] == b'<':
start = pos
pos = text.index(b'>', pos)
yield (tok_string, text[start:pos])
else:
match = cls._token_re.match(text, pos)
if match:
try:
float(match.group())
yield (tok_number, match.group())
except ValueError:
yield (tok_name, match.group())
pos = match.end()
else:
yield (tok_delimiter, text[pos:pos + 1])
pos += 1
def _parse(self):
"""
Find the values of various font properties. This limited kind
of parsing is described in Chapter 10 "Adobe Type Manager
Compatibility" of the Type-1 spec.
"""
# Preload enum members for speed.
tok_whitespace = _TokenType.whitespace
tok_name = _TokenType.name
tok_string = _TokenType.string
tok_number = _TokenType.number
# Start with reasonable defaults
prop = {'weight': 'Regular', 'ItalicAngle': 0.0, 'isFixedPitch': False,
'UnderlinePosition': -100, 'UnderlineThickness': 50}
filtered = ((token, value)
for token, value in self._tokens(self.parts[0])
if token is not tok_whitespace)
# The spec calls this an ASCII format; in Python 2.x we could
# just treat the strings and names as opaque bytes but let's
# turn them into proper Unicode, and be lenient in case of high bytes.
def convert(x): return x.decode('ascii', 'replace')
for token, value in filtered:
if token is tok_name and value.startswith(b'/'):
key = convert(value[1:])
token, value = next(filtered)
if token is tok_name:
if value in (b'true', b'false'):
value = value == b'true'
else:
value = convert(value.lstrip(b'/'))
elif token is tok_string:
value = convert(value.lstrip(b'(').rstrip(b')'))
elif token is tok_number:
if b'.' in value:
value = float(value)
else:
value = int(value)
else: # more complicated value such as an array
value = None
if key != 'FontInfo' and value is not None:
prop[key] = value
# Fill in the various *Name properties
if 'FontName' not in prop:
prop['FontName'] = (prop.get('FullName') or
prop.get('FamilyName') or
'Unknown')
if 'FullName' not in prop:
prop['FullName'] = prop['FontName']
if 'FamilyName' not in prop:
extras = ('(?i)([ -](regular|plain|italic|oblique|(semi)?bold|'
'(ultra)?light|extra|condensed))+$')
prop['FamilyName'] = re.sub(extras, '', prop['FullName'])
self.prop = prop
@classmethod
def _transformer(cls, tokens, slant, extend):
tok_whitespace = _TokenType.whitespace
tok_name = _TokenType.name
def fontname(name):
result = name
if slant:
result += b'_Slant_%d' % int(1000 * slant)
if extend != 1.0:
result += b'_Extend_%d' % int(1000 * extend)
return result
def italicangle(angle):
return b'%a' % round(
float(angle) - np.arctan(slant) / np.pi * 180,
5
)
def fontmatrix(array):
array = array.lstrip(b'[').rstrip(b']').split()
array = [float(x) for x in array]
oldmatrix = np.eye(3, 3)
oldmatrix[0:3, 0] = array[::2]
oldmatrix[0:3, 1] = array[1::2]
modifier = np.array([[extend, 0, 0],
[slant, 1, 0],
[0, 0, 1]])
newmatrix = np.dot(modifier, oldmatrix)
array[::2] = newmatrix[0:3, 0]
array[1::2] = newmatrix[0:3, 1]
return (
'[%s]' % ' '.join(_format_approx(x, 6) for x in array)
).encode('ascii')
def replace(fun):
def replacer(tokens):
token, value = next(tokens) # name, e.g., /FontMatrix
yield value
token, value = next(tokens) # possible whitespace
while token is tok_whitespace:
yield value
token, value = next(tokens)
if value != b'[': # name/number/etc.
yield fun(value)
else: # array, e.g., [1 2 3]
result = b''
while value != b']':
result += value
token, value = next(tokens)
result += value
yield fun(result)
return replacer
def suppress(tokens):
for _ in itertools.takewhile(lambda x: x[1] != b'def', tokens):
pass
yield b''
table = {b'/FontName': replace(fontname),
b'/ItalicAngle': replace(italicangle),
b'/FontMatrix': replace(fontmatrix),
b'/UniqueID': suppress}
for token, value in tokens:
if token is tok_name and value in table:
yield from table[value](
itertools.chain([(token, value)], tokens))
else:
yield value
def transform(self, effects):
"""
Return a new font that is slanted and/or extended.
Parameters
----------
effects : dict
A dict with optional entries:
- 'slant' : float, default: 0
Tangent of the angle that the font is to be slanted to the
right. Negative values slant to the left.
- 'extend' : float, default: 1
Scaling factor for the font width. Values less than 1 condense
the glyphs.
Returns
-------
`Type1Font`
"""
tokenizer = self._tokens(self.parts[0])
transformed = self._transformer(tokenizer,
slant=effects.get('slant', 0.0),
extend=effects.get('extend', 1.0))
return Type1Font((b"".join(transformed), self.parts[1], self.parts[2])) | PypiClean |
/NucDetect-0.18.3-py3-none-any.whl/core/roi/ROI.py | from __future__ import annotations
import hashlib
import math
import warnings
from typing import Union, Dict, List, Tuple, Iterable
import numpy as np
from numba.typed import List as numList
from core.roi.AreaAnalysis import get_bounding_box, get_center, get_surface, get_ellipse_radii, get_orientation_angle, \
get_orientation_vector, get_eccentricity, get_ovality
class ROI:
__slots__ = [
"main",
"ident",
"auto",
"area",
"dims",
"stats",
"ell_params", # ellipse parameters
"length",
"associated",
"id",
"marked"
]
def __init__(self, main: bool = True, channel: str = "Blue", auto: bool = True,
associated: Union[ROI, None] = None, marked: bool = False):
"""
Constructor of ROI class
:param main: Indicates that this roi is on the main channel
:param channel: Name of the channel
:param auto: Indicates if the roi was automatically generated
:param associated: The ROI this ROI is associated with
:param marked: Convenience flag for processing
"""
self.main = main
self.ident = channel
self.auto = auto
self.dims = {}
self.area = []
self.stats = {}
self.ell_params = {}
self.length = -1
self.associated = associated
self.marked = marked
self.id = None
def __add__(self, other):
if isinstance(other, ROI):
self.add_to_area(other.area)
else:
raise AttributeError("Addition only supported for ROI class!")
def __eq__(self, other: ROI):
if isinstance(other, ROI):
return set(self.area) == set(other.area)
else:
return False
def __ne__(self, other):
if not isinstance(other, ROI):
return True
else:
return not self.__eq__(other)
def __gt__(self, other):
if not isinstance(other, ROI):
return False
else:
if len(self) > len(other):
return True
return False
def __lt__(self, other):
if not isinstance(other, ROI):
return False
else:
if len(self) < len(other):
return True
return False
def __len__(self):
if self.length == -1:
self.length = np.sum([x[2] for x in self.area])
return self.length
else:
return self.length
def __hash__(self):
if not self.id:
md5 = hashlib.md5()
ident = f"{self.ident}{self.area}".encode()
md5.update(ident)
self.id = int(f"0x{md5.hexdigest()}", 0)
return self.id
def merge(self, roi: ROI) -> None:
"""
Method to merge this roi with another ROI
:param roi: The roi to merge with this
:return: None
"""
if isinstance(roi, ROI):
if roi.ident == self.ident:
self.add_to_area(roi.area)
self.id = None
self.dims.clear()
self.stats.clear()
self.ell_params.clear()
else:
warnings.warn(f"The ROI {hash(self)} and "
f"{hash(roi)} have different channel IDs!({self.ident}, {roi.ident})")
else:
raise ValueError("Not an ROI")
def reset_stored_values(self) -> None:
"""
Method to reset the calculated id, stored dimensions, statistics and ellipse parameters
:return: None
"""
self.id = None
self.dims.clear()
self.stats.clear()
self.ell_params.clear()
self.length = -1
self.calculate_dimensions()
def set_area(self, rle: Iterable) -> None:
"""
Method to define the area of this ROI
:param rle: run length encoded area
:return: None
"""
self.area.clear()
self.add_to_area(rle)
def add_to_area(self, rle):
"""
Method to extend the area of this ROI with the given area
:param rle: RL encoded area to add to this ROI
:return: None
"""
self.area.extend(rle)
self.reset_stored_values()
def calculate_ellipse_parameters(self) -> Union[Dict[str, Union[int, float, Tuple, None]]]:
"""
Method to calculate the ellipse parameters of this ROI.
:return: A dictionary containing the calculated parameters. None, if the ROI is not main
"""
# Check if the current ROI is main, else warn
if not self.main:
warnings.warn(f"Ellipse Parameter Calculation: ROI {hash(self)} is not marked as main")
return {"center": None, "major_axis": None, "minor_axis": None, "angle": None,
"orientation": None, "area": None, "shape_match": None, "eccentricity": None,
"roundness": None}
# Check if the parameters are already calculated
if not self.ell_params:
numba_area = numList(self.area)
r_maj, r_min = get_ellipse_radii(numba_area)
or_vec = get_orientation_vector(numba_area)
angle = get_orientation_angle(numba_area)
center = get_center(numba_area)
area = get_surface(numba_area)
self.ell_params["center"] = center
self.ell_params["major_axis"] = r_maj
self.ell_params["minor_axis"] = r_min
self.ell_params["angle"] = - (math.degrees(angle) - 45)
self.ell_params["orientation"] = or_vec
self.ell_params["area"] = r_min * r_maj * math.pi
self.ell_params["shape_match"] = self.ell_params["area"] / area
self.ell_params["eccentricity"] = get_eccentricity(numba_area)
self.ell_params["roundness"] = get_ovality(numba_area)
return self.ell_params
def calculate_roi_intersection(self, roi: ROI) -> float:
"""
Method to calculate the intersection ratio to another ROI
:param roi: The other ROI
:return: The degree of intersection as float
"""
max_intersection = min(len(self), len(roi))
intersection = set(self.area).intersection(set(roi.area))
return len(intersection) / max_intersection
def calculate_dimensions(self) -> Dict[str, Union[int, float]]:
"""
Method to calculate the dimension of this roi
:return: The calculated dimensions as dict
"""
if not self.dims:
if self.area:
numba_area = numList()
# Add elements to area
[numba_area.append(x) for x in self.area]
y, x, height, width = get_bounding_box(numba_area)
center = get_center(numba_area)
area = get_surface(numba_area)
self.dims["minX"] = x
self.dims["maxX"] = x + width
self.dims["minY"] = y
self.dims["maxY"] = y + height
self.dims["width"] = width
self.dims["height"] = height
self.dims["center"] = center
self.dims["area"] = area
else:
raise Exception(f"ROI {self.id} does not contain any points!")
return self.dims
def extract_area_intensity(self, channel: np.ndarray) -> List[Union[int, float]]:
"""
Method to extract the intensity values of this roi from the given channel
:param channel: The channel to extract the values from
:return: The extracted values as list
"""
vals = []
for row in self.area:
# Iterate over saved points
for x in range(row[2]):
vals.append(
channel[row[0]][row[1] + x]
)
return vals
def calculate_statistics(self, channel: np.ndarray) -> Dict[str, Union[int, float]]:
"""
Method to calculate statistics for this roi
:param channel: The channel this ROI is derived from
:return: The calculated statistics
"""
if not self.stats:
# Extract values from channel
vals = self.extract_area_intensity(channel)
self.stats = {
"area": int(np.sum([x[2] for x in self.area])),
"intensity average": float(np.average(vals)),
"intensity median": float(np.median(vals)),
"intensity maximum": int(np.amax(vals)),
"intensity minimum": int(np.amin(vals)),
"intensity std": float(np.std(vals))
}
return self.stats
def __str__(self):
return f"ROI {self.id} - Channel: {self.ident} - Main: {self.main}" | PypiClean |
/BlueWhale3_Network-1.4.2-cp38-cp38-macosx_10_9_x86_64.whl/orangecontrib/network/widgets/OWNxClustering.py | from Orange.data import Table
from Orange.data.util import get_unique_names
from Orange.widgets import gui, widget, settings
from Orange.widgets.widget import Input, Output
from orangecontrib.network import Network
from orangecontrib.network.network import community as cd
from orangewidget.settings import rename_setting
from orangecontrib.network.i18n_config import *
def __(key):
return i18n.t('network.OWNxClustering.' + key)
class OWNxClustering(widget.OWWidget):
name = __('name')
description = __('desc')
icon = "icons/NetworkClustering.svg"
priority = 6430
class Inputs:
network = Input("Network", Network, default=True, label=i18n.t("network.common.network"))
class Outputs:
network = Output("Network", Network, label=i18n.t("network.common.network"))
items = Output("Items", Table, label=i18n.t("network.common.items"))
resizing_enabled = False
want_main_area = False
settings_version = 2
attenuate = settings.Setting(False)
iterations = settings.Setting(1000)
use_random_state = settings.Setting(False)
hop_attenuation = settings.Setting(0.1)
auto_apply = settings.Setting(True)
def __init__(self):
super().__init__()
self.net = None
self.cluster_feature = None
box = gui.vBox(self.controlArea, __("box.label_pro"))
gui.spin(
box, self, "iterations", 1, 100000, 1,
label=__("label.max_iter"), callback=self.commit)
gui.doubleSpin(box, self, "hop_attenuation", 0, 1, 0.01,
label=__("label.apply"),
checked="attenuate", callback=self.commit)
self.random_state = gui.checkBox(
box, self, "use_random_state",
label=__("label.replicable"), callback=self.commit)
gui.auto_apply(self.controlArea, self)
@Inputs.network
def set_network(self, net):
self.net = net
self.commit()
def commit(self):
kwargs = {'iterations': self.iterations}
if self.attenuate:
alg = cd.label_propagation_hop_attenuation
kwargs['delta'] = self.hop_attenuation
else:
alg = cd.label_propagation
if self.net is None:
self.Outputs.items.send(None)
self.Outputs.network.send(None)
self.cluster_feature = None
return
if self.use_random_state:
kwargs['seed'] = 0
labels = alg(self.net, **kwargs)
domain = self.net.nodes.domain
# Tie a name for presenting clustering results to the widget instance
if self.cluster_feature is None:
self.cluster_feature = get_unique_names(domain, 'Cluster')
net = self.net.copy()
cd.add_results_to_items(net, labels, self.cluster_feature)
self.Outputs.items.send(net.nodes)
self.Outputs.network.send(net)
nclusters = len(set(labels.values()))
@classmethod
def migrate_settings(cls, settings, version):
if version < 2:
rename_setting(settings, "autoApply", "auto_apply")
if hasattr(settings, "method"):
rename_setting(settings, "method", "attenuate")
if __name__ == "__main__":
from Orange.widgets.utils.widgetpreview import WidgetPreview
from orangecontrib.network.network.readwrite \
import read_pajek, transform_data_to_orange_table
from os.path import join, dirname
fname = join(dirname(dirname(__file__)), 'networks', 'leu_by_genesets.net')
network = read_pajek(fname)
transform_data_to_orange_table(network)
WidgetPreview(OWNxClustering).run(set_network=network) | PypiClean |
/AnalysisProjectDependencies-0.1.tar.gz/AnalysisProjectDependencies-0.1/bower_components/cytoscape/snippets/images.js | yourDiv.style.left = 0;
yourDiv.style.top = 0;
yourDiv.style.width = "100%";
yourDiv.style.height = "100%";
yourDiv.style.position = "absolute";
var cytoscape = require("cytoscape");
var cy = cytoscape({
container: yourDiv,
style: cytoscape.stylesheet()
.selector('node')
.style({
'height': 80,
'width': 80,
'background-fit': 'cover',
'border-color': '#000',
'border-width': 3,
'border-opacity': 0.5
})
.selector('.eating')
.style({
'border-color': 'red'
})
.selector('.eater')
.style({
'border-width': 9
})
.selector('edge')
.style({
'width': 6,
'target-arrow-shape': 'triangle',
'line-color': '#ffaaaa',
'target-arrow-color': '#ffaaaa'
})
.selector('#bird')
.style({
'background-image': 'https://farm8.staticflickr.com/7272/7633179468_3e19e45a0c_b.jpg'
})
.selector('#cat')
.style({
'background-image': 'https://farm2.staticflickr.com/1261/1413379559_412a540d29_b.jpg'
})
.selector('#ladybug')
.style({
'background-image': 'https://farm4.staticflickr.com/3063/2751740612_af11fb090b_b.jpg'
})
.selector('#aphid')
.style({
'background-image': 'https://farm9.staticflickr.com/8316/8003798443_32d01257c8_b.jpg'
})
.selector('#rose')
.style({
'background-image': 'https://farm6.staticflickr.com/5109/5817854163_eaccd688f5_b.jpg'
})
.selector('#grasshopper')
.style({
'background-image': 'https://farm7.staticflickr.com/6098/6224655456_f4c3c98589_b.jpg'
})
.selector('#plant')
.style({
'background-image': 'https://farm1.staticflickr.com/231/524893064_f49a4d1d10_z.jpg'
})
.selector('#wheat')
.style({
'background-image': 'https://farm3.staticflickr.com/2660/3715569167_7e978e8319_b.jpg'
}),
elements: {
nodes: [
{ data: { id: 'cat' } },
{ data: { id: 'bird' } },
{ data: { id: 'ladybug' } },
{ data: { id: 'aphid' } },
{ data: { id: 'rose' } },
{ data: { id: 'grasshopper' } },
{ data: { id: 'plant' } },
{ data: { id: 'wheat' } }
],
edges: [
{ data: { source: 'cat', target: 'bird' } },
{ data: { source: 'bird', target: 'ladybug' } },
{ data: { source: 'bird', target: 'grasshopper' } },
{ data: { source: 'grasshopper', target: 'plant' } },
{ data: { source: 'grasshopper', target: 'wheat' } },
{ data: { source: 'ladybug', target: 'aphid' } },
{ data: { source: 'aphid', target: 'rose' } }
]
},
layout: {
name: 'breadthfirst',
directed: true,
padding: 10
}
}); // cy init
cy.on('tap', 'node', function(){
var nodes = this;
var tapped = nodes;
var food = [];
nodes.addClass('eater');
for(;;){
var connectedEdges = nodes.connectedEdges(function( edge ){
return !edge.target().anySame( nodes );
});
var connectedNodes = connectedEdges.targets();
Array.prototype.push.apply( food, connectedNodes );
nodes = connectedNodes;
if( nodes.empty() ){ break; }
}
var delay = 0;
var duration = 500;
for( var i = food.length - 1; i >= 0; i-- ){ (function(){
var thisFood = food[i];
var eater = thisFood.connectedEdges(function( edge ){
return edge.target().same(thisFood);
}).source();
thisFood.delay( delay, function(){
eater.addClass('eating');
} ).animate({
position: eater.position(),
css: {
'width': 10,
'height': 10,
'border-width': 0,
'opacity': 0
}
}, {
duration: duration,
complete: function(){
thisFood.remove();
}
});
delay += duration;
})(); } // for
}); // on tap | PypiClean |
/Beer_Advocate_API-1.1.0.tar.gz/Beer_Advocate_API-1.1.0/BA/user.py | import requests
from BA.tools import reg_sandwich, is_date, ba_parser, ba_base
class User:
"""Stores and retrieves data from Beer Advocate for a particular user
Attributes
----------
username : str
The user's username
user_id : str
The user's user_id if the user's profile page is publice
url : str
The full URL to the beer's profile page
reviews : str
Contains first page of user's reviews
info : dict
Dictionary containing user's info if profile page is public
"""
def __init__(self, username):
self.username = username
self.user_id = ''
first_review_page = ba_base + '/user/beers/?ba=' + username
self.reviews = self._get_pagereviews(first_review_page, first_call = True)
self.info = self._get_info()
def _get_info(self):
""""Returns user info if user has a profile page"""
parser = ba_parser(attributes = ['class'], vals = ['mainProfileColumn', 'secondaryContent pairsJustified'])
page_html = requests.get(self.url).text
parser.feed(page_html)
parser.clean_lines()
user_dat = parser.lines
user_info = dict()
index = 0
while index in range(len(user_dat)):
if user_dat[index] == 'Likes Received:':
user_info.update({'Likes Received': user_dat[index + 1]})
self.username = user_dat[index + 2]
break
elif user_dat[index] == ':':
key = user_dat[index - 1]
val = user_dat[index + 1]
user_info.update({key: val})
elif ':' in user_dat[index]:
key = user_dat[index][:-1]
val = user_dat[index + 1]
user_info.update({key: val})
index += 1
if user_info == {}:
self.private = True
return 'Sorry, either this user is private or does not exist'
self.private = False
return user_info
def _get_pagereviews(self, url, first_call = False):
"""
Returns all reviews on page
"""
parser = ba_parser(tags = ['div'],vals = ['ba-content'],
save_comments = True, save_urls = True)
page_html = requests.get(url).text
parser.feed(page_html)
parser.clean_lines()
review_dat = parser.lines
index = 0
reviews=[]
while index in range(len(review_dat)):
if is_date(review_dat[index], hyphened = True):
if '%' in review_dat[index + 6]:
reviews.append(review_dat[index:index + 7])
index+=7
else:
index += 1
if first_call:
self.last_page = 0
for url in parser.urls:
if 'start=' in url:
page_num = int(reg_sandwich('start=', '&', url))
if page_num > self.last_page:
self.last_page = page_num
for comment in parser.comments:
if 'user_id' in comment:
self.user_id = reg_sandwich('id=', '&', comment)
break
self.url = ba_base + '/community/members/'+ self.username + '.' \
+ self.user_id
return reviews
def get_reviews(self, n_most_recent = 0):
"""Gets reviews by users
Parameters
----------
If n_most_recent is 0 (default), all reviews are returned. Otherwise, n_most recent is rounded up to the nearest 50th and the result is the number of ratings that are returned, or the total number (whichever is smaller)
Returns
-------
list
The result is a list of slists, where each element is a review by the User
"""
parser = ba_parser(vals = ['rating_fullview'])
n_most_recent = self.last_page if n_most_recent == 0 else ((n_most_recent - 1)//50)*50
all_reviews = self.reviews[:]
for page_num in range(50,n_most_recent + 1, 50):
url = ba_base + '/user/beers/?start=' + str(page_num)\
+ '&ba=' + self.username + '&order=dateD&view=R'
all_reviews += self._get_pagereviews(url)
return all_reviews | PypiClean |
/Django-Pizza-16.10.1.tar.gz/Django-Pizza-16.10.1/pizza/kitchen_sink/static/ks/ckeditor/lang/en-ca.js | /*
Copyright (c) 2003-2013, CKSource - Frederico Knabben. All rights reserved.
For licensing, see LICENSE.html or http://ckeditor.com/license
*/
CKEDITOR.lang['en-ca']={"editor":"Rich Text Editor","editorPanel":"Rich Text Editor panel","common":{"editorHelp":"Press ALT 0 for help","browseServer":"Browse Server","url":"URL","protocol":"Protocol","upload":"Upload","uploadSubmit":"Send it to the Server","image":"Image","flash":"Flash","form":"Form","checkbox":"Checkbox","radio":"Radio Button","textField":"Text Field","textarea":"Textarea","hiddenField":"Hidden Field","button":"Button","select":"Selection Field","imageButton":"Image Button","notSet":"<not set>","id":"Id","name":"Name","langDir":"Language Direction","langDirLtr":"Left to Right (LTR)","langDirRtl":"Right to Left (RTL)","langCode":"Language Code","longDescr":"Long Description URL","cssClass":"Stylesheet Classes","advisoryTitle":"Advisory Title","cssStyle":"Style","ok":"OK","cancel":"Cancel","close":"Close","preview":"Preview","resize":"Resize","generalTab":"General","advancedTab":"Advanced","validateNumberFailed":"This value is not a number.","confirmNewPage":"Any unsaved changes to this content will be lost. Are you sure you want to load new page?","confirmCancel":"Some of the options have been changed. Are you sure to close the dialog?","options":"Options","target":"Target","targetNew":"New Window (_blank)","targetTop":"Topmost Window (_top)","targetSelf":"Same Window (_self)","targetParent":"Parent Window (_parent)","langDirLTR":"Left to Right (LTR)","langDirRTL":"Right to Left (RTL)","styles":"Style","cssClasses":"Stylesheet Classes","width":"Width","height":"Height","align":"Align","alignLeft":"Left","alignRight":"Right","alignCenter":"Centre","alignTop":"Top","alignMiddle":"Middle","alignBottom":"Bottom","invalidValue":"Invalid value.","invalidHeight":"Height must be a number.","invalidWidth":"Width must be a number.","invalidCssLength":"Value specified for the \"%1\" field must be a positive number with or without a valid CSS measurement unit (px, %, in, cm, mm, em, ex, pt, or pc).","invalidHtmlLength":"Value specified for the \"%1\" field must be a positive number with or without a valid HTML measurement unit (px or %).","invalidInlineStyle":"Value specified for the inline style must consist of one or more tuples with the format of \"name : value\", separated by semi-colons.","cssLengthTooltip":"Enter a number for a value in pixels or a number with a valid CSS unit (px, %, in, cm, mm, em, ex, pt, or pc).","unavailable":"%1<span class=\"cke_accessibility\">, unavailable</span>"},"about":{"copy":"Copyright © $1. All rights reserved.","dlgTitle":"About CKEditor","help":"Check $1 for help.","moreInfo":"For licensing information please visit our web site:","title":"About CKEditor","userGuide":"CKEditor User's Guide"},"basicstyles":{"bold":"Bold","italic":"Italic","strike":"Strike Through","subscript":"Subscript","superscript":"Superscript","underline":"Underline"},"bidi":{"ltr":"Text direction from left to right","rtl":"Text direction from right to left"},"blockquote":{"toolbar":"Block Quote"},"clipboard":{"copy":"Copy","copyError":"Your browser security settings don't permit the editor to automatically execute copying operations. Please use the keyboard for that (Ctrl/Cmd+C).","cut":"Cut","cutError":"Your browser security settings don't permit the editor to automatically execute cutting operations. Please use the keyboard for that (Ctrl/Cmd+X).","paste":"Paste","pasteArea":"Paste Area","pasteMsg":"Please paste inside the following box using the keyboard (<strong>Ctrl/Cmd+V</strong>) and hit OK","securityMsg":"Because of your browser security settings, the editor is not able to access your clipboard data directly. You are required to paste it again in this window.","title":"Paste"},"colorbutton":{"auto":"Automatic","bgColorTitle":"Background Colour","colors":{"000":"Black","800000":"Maroon","8B4513":"Saddle Brown","2F4F4F":"Dark Slate Gray","008080":"Teal","000080":"Navy","4B0082":"Indigo","696969":"Dark Gray","B22222":"Fire Brick","A52A2A":"Brown","DAA520":"Golden Rod","006400":"Dark Green","40E0D0":"Turquoise","0000CD":"Medium Blue","800080":"Purple","808080":"Gray","F00":"Red","FF8C00":"Dark Orange","FFD700":"Gold","008000":"Green","0FF":"Cyan","00F":"Blue","EE82EE":"Violet","A9A9A9":"Dim Gray","FFA07A":"Light Salmon","FFA500":"Orange","FFFF00":"Yellow","00FF00":"Lime","AFEEEE":"Pale Turquoise","ADD8E6":"Light Blue","DDA0DD":"Plum","D3D3D3":"Light Grey","FFF0F5":"Lavender Blush","FAEBD7":"Antique White","FFFFE0":"Light Yellow","F0FFF0":"Honeydew","F0FFFF":"Azure","F0F8FF":"Alice Blue","E6E6FA":"Lavender","FFF":"White"},"more":"More Colours...","panelTitle":"Colors","textColorTitle":"Text Colour"},"colordialog":{"clear":"Clear","highlight":"Highlight","options":"Color Options","selected":"Selected Color","title":"Select color"},"templates":{"button":"Templates","emptyListMsg":"(No templates defined)","insertOption":"Replace actual contents","options":"Template Options","selectPromptMsg":"Please select the template to open in the editor","title":"Content Templates"},"contextmenu":{"options":"Context Menu Options"},"div":{"IdInputLabel":"Id","advisoryTitleInputLabel":"Advisory Title","cssClassInputLabel":"Stylesheet Classes","edit":"Edit Div","inlineStyleInputLabel":"Inline Style","langDirLTRLabel":"Left to Right (LTR)","langDirLabel":"Language Direction","langDirRTLLabel":"Right to Left (RTL)","languageCodeInputLabel":" Language Code","remove":"Remove Div","styleSelectLabel":"Style","title":"Create Div Container","toolbar":"Create Div Container"},"toolbar":{"toolbarCollapse":"Collapse Toolbar","toolbarExpand":"Expand Toolbar","toolbarGroups":{"document":"Document","clipboard":"Clipboard/Undo","editing":"Editing","forms":"Forms","basicstyles":"Basic Styles","paragraph":"Paragraph","links":"Links","insert":"Insert","styles":"Styles","colors":"Colors","tools":"Tools"},"toolbars":"Editor toolbars"},"elementspath":{"eleLabel":"Elements path","eleTitle":"%1 element"},"find":{"find":"Find","findOptions":"Find Options","findWhat":"Find what:","matchCase":"Match case","matchCyclic":"Match cyclic","matchWord":"Match whole word","notFoundMsg":"The specified text was not found.","replace":"Replace","replaceAll":"Replace All","replaceSuccessMsg":"%1 occurrence(s) replaced.","replaceWith":"Replace with:","title":"Find and Replace"},"fakeobjects":{"anchor":"Anchor","flash":"Flash Animation","hiddenfield":"Hidden Field","iframe":"IFrame","unknown":"Unknown Object"},"flash":{"access":"Script Access","accessAlways":"Always","accessNever":"Never","accessSameDomain":"Same domain","alignAbsBottom":"Abs Bottom","alignAbsMiddle":"Abs Middle","alignBaseline":"Baseline","alignTextTop":"Text Top","bgcolor":"Background colour","chkFull":"Allow Fullscreen","chkLoop":"Loop","chkMenu":"Enable Flash Menu","chkPlay":"Auto Play","flashvars":"Variables for Flash","hSpace":"HSpace","properties":"Flash Properties","propertiesTab":"Properties","quality":"Quality","qualityAutoHigh":"Auto High","qualityAutoLow":"Auto Low","qualityBest":"Best","qualityHigh":"High","qualityLow":"Low","qualityMedium":"Medium","scale":"Scale","scaleAll":"Show all","scaleFit":"Exact Fit","scaleNoBorder":"No Border","title":"Flash Properties","vSpace":"VSpace","validateHSpace":"HSpace must be a number.","validateSrc":"URL must not be empty.","validateVSpace":"VSpace must be a number.","windowMode":"Window mode","windowModeOpaque":"Opaque","windowModeTransparent":"Transparent","windowModeWindow":"Window"},"font":{"fontSize":{"label":"Size","voiceLabel":"Font Size","panelTitle":"Font Size"},"label":"Font","panelTitle":"Font Name","voiceLabel":"Font"},"forms":{"button":{"title":"Button Properties","text":"Text (Value)","type":"Type","typeBtn":"Button","typeSbm":"Submit","typeRst":"Reset"},"checkboxAndRadio":{"checkboxTitle":"Checkbox Properties","radioTitle":"Radio Button Properties","value":"Value","selected":"Selected"},"form":{"title":"Form Properties","menu":"Form Properties","action":"Action","method":"Method","encoding":"Encoding"},"hidden":{"title":"Hidden Field Properties","name":"Name","value":"Value"},"select":{"title":"Selection Field Properties","selectInfo":"Select Info","opAvail":"Available Options","value":"Value","size":"Size","lines":"lines","chkMulti":"Allow multiple selections","opText":"Text","opValue":"Value","btnAdd":"Add","btnModify":"Modify","btnUp":"Up","btnDown":"Down","btnSetValue":"Set as selected value","btnDelete":"Delete"},"textarea":{"title":"Textarea Properties","cols":"Columns","rows":"Rows"},"textfield":{"title":"Text Field Properties","name":"Name","value":"Value","charWidth":"Character Width","maxChars":"Maximum Characters","type":"Type","typeText":"Text","typePass":"Password","typeEmail":"Email","typeSearch":"Search","typeTel":"Telephone Number","typeUrl":"URL"}},"format":{"label":"Format","panelTitle":"Paragraph Format","tag_address":"Address","tag_div":"Normal (DIV)","tag_h1":"Heading 1","tag_h2":"Heading 2","tag_h3":"Heading 3","tag_h4":"Heading 4","tag_h5":"Heading 5","tag_h6":"Heading 6","tag_p":"Normal","tag_pre":"Formatted"},"horizontalrule":{"toolbar":"Insert Horizontal Line"},"iframe":{"border":"Show frame border","noUrl":"Please type the iframe URL","scrolling":"Enable scrollbars","title":"IFrame Properties","toolbar":"IFrame"},"image":{"alertUrl":"Please type the image URL","alt":"Alternative Text","border":"Border","btnUpload":"Send it to the Server","button2Img":"Do you want to transform the selected image button on a simple image?","hSpace":"HSpace","img2Button":"Do you want to transform the selected image on a image button?","infoTab":"Image Info","linkTab":"Link","lockRatio":"Lock Ratio","menu":"Image Properties","resetSize":"Reset Size","title":"Image Properties","titleButton":"Image Button Properties","upload":"Upload","urlMissing":"Image source URL is missing.","vSpace":"VSpace","validateBorder":"Border must be a whole number.","validateHSpace":"HSpace must be a whole number.","validateVSpace":"VSpace must be a whole number."},"indent":{"indent":"Increase Indent","outdent":"Decrease Indent"},"smiley":{"options":"Smiley Options","title":"Insert a Smiley","toolbar":"Smiley"},"justify":{"block":"Justify","center":"Centre","left":"Align Left","right":"Align Right"},"link":{"acccessKey":"Access Key","advanced":"Advanced","advisoryContentType":"Advisory Content Type","advisoryTitle":"Advisory Title","anchor":{"toolbar":"Anchor","menu":"Edit Anchor","title":"Anchor Properties","name":"Anchor Name","errorName":"Please type the anchor name","remove":"Remove Anchor"},"anchorId":"By Element Id","anchorName":"By Anchor Name","charset":"Linked Resource Charset","cssClasses":"Stylesheet Classes","emailAddress":"E-Mail Address","emailBody":"Message Body","emailSubject":"Message Subject","id":"Id","info":"Link Info","langCode":"Language Code","langDir":"Language Direction","langDirLTR":"Left to Right (LTR)","langDirRTL":"Right to Left (RTL)","menu":"Edit Link","name":"Name","noAnchors":"(No anchors available in the document)","noEmail":"Please type the e-mail address","noUrl":"Please type the link URL","other":"<other>","popupDependent":"Dependent (Netscape)","popupFeatures":"Popup Window Features","popupFullScreen":"Full Screen (IE)","popupLeft":"Left Position","popupLocationBar":"Location Bar","popupMenuBar":"Menu Bar","popupResizable":"Resizable","popupScrollBars":"Scroll Bars","popupStatusBar":"Status Bar","popupToolbar":"Toolbar","popupTop":"Top Position","rel":"Relationship","selectAnchor":"Select an Anchor","styles":"Style","tabIndex":"Tab Index","target":"Target","targetFrame":"<frame>","targetFrameName":"Target Frame Name","targetPopup":"<popup window>","targetPopupName":"Popup Window Name","title":"Link","toAnchor":"Link to anchor in the text","toEmail":"E-mail","toUrl":"URL","toolbar":"Link","type":"Link Type","unlink":"Unlink","upload":"Upload"},"list":{"bulletedlist":"Insert/Remove Bulleted List","numberedlist":"Insert/Remove Numbered List"},"liststyle":{"armenian":"Armenian numbering","bulletedTitle":"Bulleted List Properties","circle":"Circle","decimal":"Decimal (1, 2, 3, etc.)","decimalLeadingZero":"Decimal leading zero (01, 02, 03, etc.)","disc":"Disc","georgian":"Georgian numbering (an, ban, gan, etc.)","lowerAlpha":"Lower Alpha (a, b, c, d, e, etc.)","lowerGreek":"Lower Greek (alpha, beta, gamma, etc.)","lowerRoman":"Lower Roman (i, ii, iii, iv, v, etc.)","none":"None","notset":"<not set>","numberedTitle":"Numbered List Properties","square":"Square","start":"Start","type":"Type","upperAlpha":"Upper Alpha (A, B, C, D, E, etc.)","upperRoman":"Upper Roman (I, II, III, IV, V, etc.)","validateStartNumber":"List start number must be a whole number."},"magicline":{"title":"Insert paragraph here"},"maximize":{"maximize":"Maximize","minimize":"Minimize"},"newpage":{"toolbar":"New Page"},"pagebreak":{"alt":"Page Break","toolbar":"Insert Page Break for Printing"},"pastetext":{"button":"Paste as plain text","title":"Paste as Plain Text"},"pastefromword":{"confirmCleanup":"The text you want to paste seems to be copied from Word. Do you want to clean it before pasting?","error":"It was not possible to clean up the pasted data due to an internal error","title":"Paste from Word","toolbar":"Paste from Word"},"preview":{"preview":"Preview"},"print":{"toolbar":"Print"},"removeformat":{"toolbar":"Remove Format"},"save":{"toolbar":"Save"},"selectall":{"toolbar":"Select All"},"showblocks":{"toolbar":"Show Blocks"},"sourcearea":{"toolbar":"Source"},"specialchar":{"options":"Special Character Options","title":"Select Special Character","toolbar":"Insert Special Character"},"scayt":{"about":"About SCAYT","aboutTab":"About","addWord":"Add Word","allCaps":"Ignore All-Caps Words","dic_create":"Create","dic_delete":"Delete","dic_field_name":"Dictionary name","dic_info":"Initially the User Dictionary is stored in a Cookie. However, Cookies are limited in size. When the User Dictionary grows to a point where it cannot be stored in a Cookie, then the dictionary may be stored on our server. To store your personal dictionary on our server you should specify a name for your dictionary. If you already have a stored dictionary, please type its name and click the Restore button.","dic_rename":"Rename","dic_restore":"Restore","dictionariesTab":"Dictionaries","disable":"Disable SCAYT","emptyDic":"Dictionary name should not be empty.","enable":"Enable SCAYT","ignore":"Ignore","ignoreAll":"Ignore All","ignoreDomainNames":"Ignore Domain Names","langs":"Languages","languagesTab":"Languages","mixedCase":"Ignore Words with Mixed Case","mixedWithDigits":"Ignore Words with Numbers","moreSuggestions":"More suggestions","opera_title":"Not supported by Opera","options":"Options","optionsTab":"Options","title":"Spell Check As You Type","toggle":"Toggle SCAYT","noSuggestions":"No suggestion"},"stylescombo":{"label":"Styles","panelTitle":"Formatting Styles","panelTitle1":"Block Styles","panelTitle2":"Inline Styles","panelTitle3":"Object Styles"},"table":{"border":"Border size","caption":"Caption","cell":{"menu":"Cell","insertBefore":"Insert Cell Before","insertAfter":"Insert Cell After","deleteCell":"Delete Cells","merge":"Merge Cells","mergeRight":"Merge Right","mergeDown":"Merge Down","splitHorizontal":"Split Cell Horizontally","splitVertical":"Split Cell Vertically","title":"Cell Properties","cellType":"Cell Type","rowSpan":"Rows Span","colSpan":"Columns Span","wordWrap":"Word Wrap","hAlign":"Horizontal Alignment","vAlign":"Vertical Alignment","alignBaseline":"Baseline","bgColor":"Background Color","borderColor":"Border Color","data":"Data","header":"Header","yes":"Yes","no":"No","invalidWidth":"Cell width must be a number.","invalidHeight":"Cell height must be a number.","invalidRowSpan":"Rows span must be a whole number.","invalidColSpan":"Columns span must be a whole number.","chooseColor":"Choose"},"cellPad":"Cell padding","cellSpace":"Cell spacing","column":{"menu":"Column","insertBefore":"Insert Column Before","insertAfter":"Insert Column After","deleteColumn":"Delete Columns"},"columns":"Columns","deleteTable":"Delete Table","headers":"Headers","headersBoth":"Both","headersColumn":"First column","headersNone":"None","headersRow":"First Row","invalidBorder":"Border size must be a number.","invalidCellPadding":"Cell padding must be a number.","invalidCellSpacing":"Cell spacing must be a number.","invalidCols":"Number of columns must be a number greater than 0.","invalidHeight":"Table height must be a number.","invalidRows":"Number of rows must be a number greater than 0.","invalidWidth":"Table width must be a number.","menu":"Table Properties","row":{"menu":"Row","insertBefore":"Insert Row Before","insertAfter":"Insert Row After","deleteRow":"Delete Rows"},"rows":"Rows","summary":"Summary","title":"Table Properties","toolbar":"Table","widthPc":"percent","widthPx":"pixels","widthUnit":"width unit"},"undo":{"redo":"Redo","undo":"Undo"},"wsc":{"btnIgnore":"Ignore","btnIgnoreAll":"Ignore All","btnReplace":"Replace","btnReplaceAll":"Replace All","btnUndo":"Undo","changeTo":"Change to","errorLoading":"Error loading application service host: %s.","ieSpellDownload":"Spell checker not installed. Do you want to download it now?","manyChanges":"Spell check complete: %1 words changed","noChanges":"Spell check complete: No words changed","noMispell":"Spell check complete: No misspellings found","noSuggestions":"- No suggestions -","notAvailable":"Sorry, but service is unavailable now.","notInDic":"Not in dictionary","oneChange":"Spell check complete: One word changed","progress":"Spell check in progress...","title":"Spell Check","toolbar":"Check Spelling"}}; | PypiClean |
/OSG-Gratia-Viewer-0.1.tar.gz/OSG-Gratia-Viewer-0.1/src/gratia/web/__init__.py | from graphtool.base.xml_config import XmlConfig
from gratia.database.query_handler import displayName
from graphtool.web.security import DenyAll
from Cheetah.Template import Template
from xml.dom.minidom import parse
import cherrypy, os, urllib, urllib2, re, sys
# Helper functions
class Gratia(XmlConfig):
def __init__(self, *args, **kw):
super(Gratia, self).__init__(*args, **kw)
security_obj_name = self.metadata.get('security', False)
if security_obj_name:
self.security_obj = self.globals[security_obj_name]
else:
self.security_obj = DenyAll()
self.metadata['template_dir'] = '$GRAPHTOOL_USER_ROOT/templates'
self.template_dir = os.path.expandvars(self.metadata.get('template_dir', '.'))
self.main = self.template('main.tmpl')(self.main)
self.overview = self.template('overview.tmpl')(self.overview)
self.vo_overview = self.template('vo_overview.tmpl')(self.vo_overview)
self.vo_opp = self.template('vo_opp.tmpl')(self.vo_opp)
self.vo_opp2 = self.template('vo_opp2.tmpl')(self.vo_opp2)
self.vo_exitcode = self.template('vo_exitcode.tmpl')(self.vo_exitcode)
self.site_owner = self.template('site.tmpl')(self.site_owner)
self._cp_config ={}
self.index = self.overview
def template(self, name=None):
template_file = os.path.join(self.template_dir, name)
tclass = Template.compile(file=template_file)
def template_decorator(func):
def func_wrapper(*args, **kw):
data = func(*args, **kw)
if data.get('is_authenticated', True):
base_url = self.metadata.get('base_url', '')
else:
base_url = self.metadata.get('base_url_noauth', '')
if base_url == '/':
base_url = ""
addl = {'base_url': base_url}
return str(tclass(namespaces=[data, addl]))
func_wrapper.exposed = True
return func_wrapper
return template_decorator
def generate_drilldown(self, option, url):
def drilldown(pivot, group, base_url, filter_dict):
filter_dict[option] = pivot
filter_url = urllib.urlencode(filter_dict)
return base_url + url + '?' + filter_url
return drilldown
def generate_pg_map(self, func, kw, drilldown_url, drilldown_option):
map = {}
map['kind'] = 'pivot-group'
results, metadata = func(**kw)
assert metadata['kind'] == 'pivot-group'
map['name'] = metadata['name']
column_names = str(metadata.get('column_names',''))
column_units = str(metadata.get('column_units',''))
names = [ i.strip() for i in column_names.split(',') ]
units = [ i.strip() for i in column_units.split(',') ]
map['column_names'] = names
map['column_units'] = units
map['pivot_name'] = metadata['pivot_name']
data = {}
map['data'] = data
map['drilldown'] = self.generate_drilldown(drilldown_option, drilldown_url)
coords = metadata['grapher'].get_coords(metadata['query'], metadata, **metadata['given_kw'])
for pivot, groups in results.items():
data_groups = {}
data[pivot] = data_groups
if pivot in coords:
coord_groups = coords[pivot]
for group, val in groups.items():
if group in coord_groups:
coord = str(coord_groups[group]).replace('(', '').replace(')', '')
data_groups[group] = (coord, val)
return map
def user_roles(self, data):
"""
Authenticate a user and get their roles
"""
data['is_site_owner'] = False
data['is_vo_owner'] = False
data['is_view_other_users'] = False
if not data['is_authenticated']:
data['auth_count'] = 0
return
dn = data['dn']
data['vo_ownership'] = self.security_obj.list_roles("vo_ownership", dn)
data['site_ownership'] = self.security_obj.list_roles("site_ownership", \
dn)
data['user_ownership'] = self.security_obj.list_roles("users", dn)
auth_count = 0
if len(data['vo_ownership']) > 0:
data['is_vo_owner'] = True
auth_count += 1
if len(data['user_ownership']) > 0:
data['is_view_other_users'] = True
auth_count += 1
if len(data['site_ownership']) > 0:
data['is_site_owner'] = True
auth_count += 1
data['is_super_user'] = False
data['auth_count'] = auth_count
def user_auth(self, data):
dn = cherrypy.request.headers.get('SSL-CLIENT-S-DN',None)
if dn:
assert cherrypy.request.headers.get('SSL-CLIENT-VERIFY', \
'Failure') == 'SUCCESS'
data['is_authenticated'] = True
data['dn'] = dn
data['name'] = displayName(dn)
else:
data['is_authenticated'] = False
def assign_blank(self, dict, *args):
for arg in args:
if arg not in dict:
dict[arg] = ''
def copy_if_present(self, to_dict, from_dict, *args):
for arg in args:
if arg in from_dict and from_dict[arg] != '':
to_dict[arg] = from_dict[arg]
def refine(self, data, filter_dict, facility=True, vo=True, dn=True):
relTime = data.get('relativetime', False)
data['refine_vo'] = vo
data['refine_facility'] = facility
data['refine_dn'] = dn
if relTime:
if relTime == 'absolute':
data['relTime'] = 'absolute'
starttime = data.get('starttime', None)
if starttime != None and starttime.strip() != '':
filter_dict['starttime'] = starttime
endtime = data.get('endtime', None)
if endtime != None and endtime.strip() != '':
filter_dict['endtime'] = endtime
else:
data['relTime'] = relTime
interval = int(relTime)
filter_dict['starttime'] = 'time.time()-%i' % interval
filter_dict['endtime'] = 'time.time()'
if interval < 4*86400:
filter_dict['span'] = 3600
elif interval < 30*86400:
filter_dict['span'] = 86400
else:
filter_dict['span'] = 86400*7
else:
data['relTime'] = 'absolute'
self.copy_if_present(filter_dict, data, 'facility', 'vo', \
'exclude-facility', 'exclude-vo', 'user', 'user', 'exclude-dn')
data['query_kw'] = dict(filter_dict)
data['filter_url'] = urllib.urlencode(filter_dict)
self.assign_blank(filter_dict, 'facility', 'vo', 'exclude-vo', \
'exclude-facility', 'exclude-dn', 'user')
data['filter_dict'] = filter_dict
if data['filter_url'] != '':
data['filter_url'] = '?' + data['filter_url']
data['refine'] = os.path.join(self.template_dir, 'refine.tmpl')
data['refine_error'] = None
def image_map(self, data, obj_name, func_name, drilldown_url, drilldown_option):
maps = data.get('maps', [])
data['maps'] = maps
map = self.generate_pg_map(getattr(self.globals[obj_name], func_name), data['query_kw'], \
drilldown_url, drilldown_option)
maps.append(map)
#if 'image_maps' not in data:
data['image_maps'] = os.path.join(self.template_dir, 'image_map.tmpl')
def main(self, *args, **kw):
data = dict(kw)
data['given_kw'] = dict(kw)
self.focus(kw, data, 'main', 'facility', ['facility', 'vo', 'both'])
filter_dict = {}
# Do user auth:
self.user_auth(data)
self.user_roles(data)
# Handle the refine variables
self.refine(data, filter_dict, dn=False)
# Generate image maps:
if data['focus']['value'] == 'facility' or data['focus']['value'] == 'both':
self.image_map(data, 'GratiaBarQueries', 'facility_transfer_rate', 'main', 'facility')
self.image_map(data, 'GratiaBarQueries', 'facility_quality', 'main', 'facility')
self.image_map(data, 'GratiaBarQueries', 'facility_transfer_volume', 'main', 'facility')
else:
self.image_map(data, 'GratiaBarQueries', 'vo_transfer_rate', 'main', 'vo')
self.image_map(data, 'GratiaBarQueries', 'vo_quality', 'main', 'vo')
self.image_map(data, 'GratiaBarQueries', 'vo_transfer_volume', 'main', 'vo')
if data['is_authenticated']:
data['title'] = "OSG Storage Main for %s" % data['name']
else:
data['title'] = "OSG Storage Main"
return data
def focus(self, kw, data, page, default, values):
focus_kw = dict(kw)
focus = data.get('focus', default)
def change_focus(view, base_url):
base_url = base_url + '/' + page
if view==data['focus']:
return None
focus_kw['focus'] = view
query = urllib.urlencode(focus_kw)
if len(query) > 0:
query = '?' + query
return base_url + query
data['change_focus'] = change_focus
focus = {'value': focus, 'change': change_focus}
focus['tmpl'] = os.path.join(self.template_dir, 'focus.tmpl')
focus['values'] = values
data['focus'] = focus
def site_owner(self, *args, **kw):
data = dict(kw)
data['given_kw'] = kw
filter_dict = {}
data['facility'] = data.get('facility', None)
self.focus(kw, data, 'site_owner', 'user', ['user', 'vo', 'both'])
#User auth
self.user_auth(data)
self.user_roles(data)
#Handle refine
self.refine(data, filter_dict, facility=False)
#Generate image maps
if data['focus']['value'] == 'user' or data['focus']['value'] == 'both':
#self.image_map(data, 'GratiaSiteBarQueries', 'site_user_job_quality', 'site_owner', 'user')
#self.image_map(data, 'GratiaSiteBarQueries', 'site_user_job_hours', 'site_owner', 'user')
self.image_map(data, 'GratiaSiteBarQueries', 'site_user_transfer_quality', 'site_owner', 'user')
self.image_map(data, 'GratiaSiteBarQueries', 'site_user_transfer_rate', 'site_owner', 'user')
if data['focus']['value'] == 'vo' or data['focus']['value'] == 'both':
#self.image_map(data, 'GratiaSiteBarQueries', 'site_vo_job_quality', 'site_owner', 'user')
#self.image_map(data, 'GratiaSiteBarQueries', 'site_vo_job_hours', 'site_owner', 'user')
self.image_map(data, 'GratiaSiteBarQueries', 'site_vo_transfer_quality', 'site_owner', 'user')
self.image_map(data, 'GratiaSiteBarQueries', 'site_vo_transfer_rate', 'site_owner', 'user')
#Empty transfer list for now
#transfers, metadata = self.globals['GratiaSiteBarQueries'].site_table(data['query_kw'])
transfers = []
for transfer in transfers:
transfer['name'] = displayName(transfer['name'])
transfer['transfer_rate'] = to_mb(transfer['transfer_rate']) + ' MB/s'
transfer['bytes_transferred'] = to_mb(transfer['bytes_transferred']) + ' MB'
data['transfers'] = transfers
# External data
external = {}
data['external'] = external
external['GridScan'] = self.fetch_gridscan(data.get('facility'))
external['GIP Validator'] = self.gip_validation(data['facility'])
return data
def fetch_gridscan(self, site):
doc = urllib2.urlopen('http://scan.grid.iu.edu/cgi-bin/show_results?grid=1')
in_row = False
in_font = False
link_re = re.compile('HREF="(.*?)"')
link = "#"
status = "Unknown"
for line in doc.readlines():
if line.find(site) >= 0:
in_row = True
if not in_row:
continue
if line.find('HREF') >= 0:
m = link_re.search(line)
if m:
link = m.groups()[0]
if line.startswith("<FONT"):
in_font = True
continue
if in_font:
status = line.strip()
break
return status, "http://scan.grid.iu.edu" + link
def gip_validation(self, site):
doc = urllib2.urlopen('http://gip-validate.grid.iu.edu/production')
row_re = re.compile("<td valign='middle'>%s</td>" % site)
info_re = re.compile("<td height='30' bgcolor='(.*?)'><a href='(.*?)'>")
in_row = False
result = "Unknown"
link = "#"
for line in doc.readlines():
if row_re.search(line):
in_row = True
continue
if in_row:
m = info_re.search(line)
if m:
color, link = m.groups()
if color == 'green':
result = "PASS"
elif color == 'red':
result = "FAIL"
elif color == "black":
result = "Not Reporting"
else:
result = "Unknown"
break
return result, "http://gip-validate.grid.iu.edu/production/" + link
def vo_owner(self, *args, **kw):
return "We're sorry, but the VO owner page has not been written."
vo_owner.exposed = True
def user(self, *args, **kw):
return "We're sorry, but the user details page has not been written."
user.exposed = True
def overview(self, *args, **kw):
data = dict(kw)
self.user_auth(data)
data['title'] = "OSG overview page"
data['static_url'] = self.metadata.get('static_url', '/store/gratia')
return data
def get_variable_values(self, url):
retval = []
try:
xmldoc = urllib2.urlopen(url)
except (KeyboardInterrupt, SystemExit):
raise
except Exception, e:
print >> sys.stderr, "Exception occurred while getting variable values: %s" % str(e)
return retval
dom = parse(xmldoc)
for pivot in dom.getElementsByTagName('pivot'):
pivot_str = pivot.getAttribute('name')
if len(pivot_str) > 0:
retval.append(pivot_str)
return retval
def get_vo_list(self, vos_url, registered_vos_url, keep_vos):
vos = self.get_variable_values(vos_url)
info = urllib2.urlopen(registered_vos_url)
reg_vos = []
for line in info.readlines():
line = line.strip()
if len(line) == 0:
continue
reg_vos.append(line.split('<')[0].lower())
retval = []
for vo in vos:
if vo in keep_vos or vo.lower() in reg_vos:
retval.append(vo)
for vo in keep_vos:
if vo not in retval:
retval.append(vo)
return retval
def vo_overview(self, *args, **kw):
data = dict(kw)
self.user_auth(data)
vos_url = self.metadata.get('vos_url', '/gratia/xml/vo_corrected_table')
registered_vos_url = self.metadata.get('registered_vos_url', \
'http://www.grid.iu.edu/osg-includes/vo_txt.php')
keep_vos = [i.strip() for i in self.metadata.get('keep_vos', \
'').split(',') if len(i.strip()) > 0]
if kw.get('filter', 'true').lower() == 'false':
vos = self.get_variable_values(vos_url)
else:
vos = self.get_vo_list(vos_url, registered_vos_url, keep_vos)
data['vos'] = vos
data['current_vo'] = kw.get('vo', None)
data['static_url'] = self.metadata.get('static_url', '/store/gratia')
return data
def vo_opp(self, *args, **kw):
data = dict(kw)
self.user_auth(data)
vos_url = self.metadata.get('vos_url', '/gratia/xml/vo_corrected_table')
registered_vos_url = self.metadata.get('registered_vos_url', \
'http://www.grid.iu.edu/osg-includes/vo_txt.php')
keep_vos = [i.strip() for i in self.metadata.get('keep_vos', \
'').split(',') if len(i.strip()) > 0]
if kw.get('filter', 'true').lower() == 'false':
vos = self.get_variable_values(vos_url)
else:
vos = self.get_vo_list(vos_url, registered_vos_url, keep_vos)
data['vos'] = vos
data['current_vo'] = kw.get('vo', None)
data['static_url'] = self.metadata.get('static_url', '/store/gratia')
return data
def vo_opp2(self, *args, **kw):
data = dict(kw)
self.user_auth(data)
vos_url = self.metadata.get('vos_url', '/gratia/xml/vo_corrected_table')
registered_vos_url = self.metadata.get('registered_vos_url', \
'http://www.grid.iu.edu/osg-includes/vo_txt.php')
keep_vos = [i.strip() for i in self.metadata.get('keep_vos', \
'').split(',') if len(i.strip()) > 0]
if kw.get('filter', 'true').lower() == 'false':
vos = self.get_variable_values(vos_url)
else:
vos = self.get_vo_list(vos_url, registered_vos_url, keep_vos)
data['vos'] = vos
data['current_vo'] = kw.get('vo', None)
data['static_url'] = self.metadata.get('static_url', '/store/gratia')
return data
def vo_exitcode(self, *args, **kw):
data = dict(kw)
self.user_auth(data)
vos_url = self.metadata.get('vos_url', '/gratia/xml/vo_corrected_table')
registered_vos_url = self.metadata.get('registered_vos_url', \
'http://www.grid.iu.edu/osg-includes/vo_txt.php')
keep_vos = [i.strip() for i in self.metadata.get('keep_vos', \
'').split(',') if len(i.strip()) > 0]
if kw.get('filter', 'true').lower() == 'false':
vos = self.get_variable_values(vos_url)
else:
vos = self.get_vo_list(vos_url, registered_vos_url, keep_vos)
data['vos'] = vos
data['current_vo'] = kw.get('vo', None)
data['static_url'] = self.metadata.get('static_url', '/store/gratia')
return data | PypiClean |
/Flask-AdminLTE2-1.0.0.tar.gz/Flask-AdminLTE2-1.0.0/flask_adminlte2/static/plugins/morris/morris.js | (function() {
var $, Morris, minutesSpecHelper, secondsSpecHelper,
__slice = [].slice,
__bind = function(fn, me){ return function(){ return fn.apply(me, arguments); }; },
__hasProp = {}.hasOwnProperty,
__extends = function(child, parent) { for (var key in parent) { if (__hasProp.call(parent, key)) child[key] = parent[key]; } function ctor() { this.constructor = child; } ctor.prototype = parent.prototype; child.prototype = new ctor(); child.__super__ = parent.prototype; return child; },
__indexOf = [].indexOf || function(item) { for (var i = 0, l = this.length; i < l; i++) { if (i in this && this[i] === item) return i; } return -1; };
Morris = window.Morris = {};
$ = jQuery;
Morris.EventEmitter = (function() {
function EventEmitter() {}
EventEmitter.prototype.on = function(name, handler) {
if (this.handlers == null) {
this.handlers = {};
}
if (this.handlers[name] == null) {
this.handlers[name] = [];
}
this.handlers[name].push(handler);
return this;
};
EventEmitter.prototype.fire = function() {
var args, handler, name, _i, _len, _ref, _results;
name = arguments[0], args = 2 <= arguments.length ? __slice.call(arguments, 1) : [];
if ((this.handlers != null) && (this.handlers[name] != null)) {
_ref = this.handlers[name];
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
handler = _ref[_i];
_results.push(handler.apply(null, args));
}
return _results;
}
};
return EventEmitter;
})();
Morris.commas = function(num) {
var absnum, intnum, ret, strabsnum;
if (num != null) {
ret = num < 0 ? "-" : "";
absnum = Math.abs(num);
intnum = Math.floor(absnum).toFixed(0);
ret += intnum.replace(/(?=(?:\d{3})+$)(?!^)/g, ',');
strabsnum = absnum.toString();
if (strabsnum.length > intnum.length) {
ret += strabsnum.slice(intnum.length);
}
return ret;
} else {
return '-';
}
};
Morris.pad2 = function(number) {
return (number < 10 ? '0' : '') + number;
};
Morris.Grid = (function(_super) {
__extends(Grid, _super);
function Grid(options) {
this.resizeHandler = __bind(this.resizeHandler, this);
var _this = this;
if (typeof options.element === 'string') {
this.el = $(document.getElementById(options.element));
} else {
this.el = $(options.element);
}
if ((this.el == null) || this.el.length === 0) {
throw new Error("Graph container element not found");
}
if (this.el.css('position') === 'static') {
this.el.css('position', 'relative');
}
this.options = $.extend({}, this.gridDefaults, this.defaults || {}, options);
if (typeof this.options.units === 'string') {
this.options.postUnits = options.units;
}
this.raphael = new Raphael(this.el[0]);
this.elementWidth = null;
this.elementHeight = null;
this.dirty = false;
this.selectFrom = null;
if (this.init) {
this.init();
}
this.setData(this.options.data);
this.el.bind('mousemove', function(evt) {
var left, offset, right, width, x;
offset = _this.el.offset();
x = evt.pageX - offset.left;
if (_this.selectFrom) {
left = _this.data[_this.hitTest(Math.min(x, _this.selectFrom))]._x;
right = _this.data[_this.hitTest(Math.max(x, _this.selectFrom))]._x;
width = right - left;
return _this.selectionRect.attr({
x: left,
width: width
});
} else {
return _this.fire('hovermove', x, evt.pageY - offset.top);
}
});
this.el.bind('mouseleave', function(evt) {
if (_this.selectFrom) {
_this.selectionRect.hide();
_this.selectFrom = null;
}
return _this.fire('hoverout');
});
this.el.bind('touchstart touchmove touchend', function(evt) {
var offset, touch;
touch = evt.originalEvent.touches[0] || evt.originalEvent.changedTouches[0];
offset = _this.el.offset();
return _this.fire('hovermove', touch.pageX - offset.left, touch.pageY - offset.top);
});
this.el.bind('click', function(evt) {
var offset;
offset = _this.el.offset();
return _this.fire('gridclick', evt.pageX - offset.left, evt.pageY - offset.top);
});
if (this.options.rangeSelect) {
this.selectionRect = this.raphael.rect(0, 0, 0, this.el.innerHeight()).attr({
fill: this.options.rangeSelectColor,
stroke: false
}).toBack().hide();
this.el.bind('mousedown', function(evt) {
var offset;
offset = _this.el.offset();
return _this.startRange(evt.pageX - offset.left);
});
this.el.bind('mouseup', function(evt) {
var offset;
offset = _this.el.offset();
_this.endRange(evt.pageX - offset.left);
return _this.fire('hovermove', evt.pageX - offset.left, evt.pageY - offset.top);
});
}
if (this.options.resize) {
$(window).bind('resize', function(evt) {
if (_this.timeoutId != null) {
window.clearTimeout(_this.timeoutId);
}
return _this.timeoutId = window.setTimeout(_this.resizeHandler, 100);
});
}
this.el.css('-webkit-tap-highlight-color', 'rgba(0,0,0,0)');
if (this.postInit) {
this.postInit();
}
}
Grid.prototype.gridDefaults = {
dateFormat: null,
axes: true,
grid: true,
gridLineColor: '#aaa',
gridStrokeWidth: 0.5,
gridTextColor: '#888',
gridTextSize: 12,
gridTextFamily: 'sans-serif',
gridTextWeight: 'normal',
hideHover: false,
yLabelFormat: null,
xLabelAngle: 0,
numLines: 5,
padding: 25,
parseTime: true,
postUnits: '',
preUnits: '',
ymax: 'auto',
ymin: 'auto 0',
goals: [],
goalStrokeWidth: 1.0,
goalLineColors: ['#666633', '#999966', '#cc6666', '#663333'],
events: [],
eventStrokeWidth: 1.0,
eventLineColors: ['#005a04', '#ccffbb', '#3a5f0b', '#005502'],
rangeSelect: null,
rangeSelectColor: '#eef',
resize: false
};
Grid.prototype.setData = function(data, redraw) {
var e, idx, index, maxGoal, minGoal, ret, row, step, total, y, ykey, ymax, ymin, yval, _ref;
if (redraw == null) {
redraw = true;
}
this.options.data = data;
if ((data == null) || data.length === 0) {
this.data = [];
this.raphael.clear();
if (this.hover != null) {
this.hover.hide();
}
return;
}
ymax = this.cumulative ? 0 : null;
ymin = this.cumulative ? 0 : null;
if (this.options.goals.length > 0) {
minGoal = Math.min.apply(Math, this.options.goals);
maxGoal = Math.max.apply(Math, this.options.goals);
ymin = ymin != null ? Math.min(ymin, minGoal) : minGoal;
ymax = ymax != null ? Math.max(ymax, maxGoal) : maxGoal;
}
this.data = (function() {
var _i, _len, _results;
_results = [];
for (index = _i = 0, _len = data.length; _i < _len; index = ++_i) {
row = data[index];
ret = {
src: row
};
ret.label = row[this.options.xkey];
if (this.options.parseTime) {
ret.x = Morris.parseDate(ret.label);
if (this.options.dateFormat) {
ret.label = this.options.dateFormat(ret.x);
} else if (typeof ret.label === 'number') {
ret.label = new Date(ret.label).toString();
}
} else {
ret.x = index;
if (this.options.xLabelFormat) {
ret.label = this.options.xLabelFormat(ret);
}
}
total = 0;
ret.y = (function() {
var _j, _len1, _ref, _results1;
_ref = this.options.ykeys;
_results1 = [];
for (idx = _j = 0, _len1 = _ref.length; _j < _len1; idx = ++_j) {
ykey = _ref[idx];
yval = row[ykey];
if (typeof yval === 'string') {
yval = parseFloat(yval);
}
if ((yval != null) && typeof yval !== 'number') {
yval = null;
}
if (yval != null) {
if (this.cumulative) {
total += yval;
} else {
if (ymax != null) {
ymax = Math.max(yval, ymax);
ymin = Math.min(yval, ymin);
} else {
ymax = ymin = yval;
}
}
}
if (this.cumulative && (total != null)) {
ymax = Math.max(total, ymax);
ymin = Math.min(total, ymin);
}
_results1.push(yval);
}
return _results1;
}).call(this);
_results.push(ret);
}
return _results;
}).call(this);
if (this.options.parseTime) {
this.data = this.data.sort(function(a, b) {
return (a.x > b.x) - (b.x > a.x);
});
}
this.xmin = this.data[0].x;
this.xmax = this.data[this.data.length - 1].x;
this.events = [];
if (this.options.events.length > 0) {
if (this.options.parseTime) {
this.events = (function() {
var _i, _len, _ref, _results;
_ref = this.options.events;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
e = _ref[_i];
_results.push(Morris.parseDate(e));
}
return _results;
}).call(this);
} else {
this.events = this.options.events;
}
this.xmax = Math.max(this.xmax, Math.max.apply(Math, this.events));
this.xmin = Math.min(this.xmin, Math.min.apply(Math, this.events));
}
if (this.xmin === this.xmax) {
this.xmin -= 1;
this.xmax += 1;
}
this.ymin = this.yboundary('min', ymin);
this.ymax = this.yboundary('max', ymax);
if (this.ymin === this.ymax) {
if (ymin) {
this.ymin -= 1;
}
this.ymax += 1;
}
if (((_ref = this.options.axes) === true || _ref === 'both' || _ref === 'y') || this.options.grid === true) {
if (this.options.ymax === this.gridDefaults.ymax && this.options.ymin === this.gridDefaults.ymin) {
this.grid = this.autoGridLines(this.ymin, this.ymax, this.options.numLines);
this.ymin = Math.min(this.ymin, this.grid[0]);
this.ymax = Math.max(this.ymax, this.grid[this.grid.length - 1]);
} else {
step = (this.ymax - this.ymin) / (this.options.numLines - 1);
this.grid = (function() {
var _i, _ref1, _ref2, _results;
_results = [];
for (y = _i = _ref1 = this.ymin, _ref2 = this.ymax; step > 0 ? _i <= _ref2 : _i >= _ref2; y = _i += step) {
_results.push(y);
}
return _results;
}).call(this);
}
}
this.dirty = true;
if (redraw) {
return this.redraw();
}
};
Grid.prototype.yboundary = function(boundaryType, currentValue) {
var boundaryOption, suggestedValue;
boundaryOption = this.options["y" + boundaryType];
if (typeof boundaryOption === 'string') {
if (boundaryOption.slice(0, 4) === 'auto') {
if (boundaryOption.length > 5) {
suggestedValue = parseInt(boundaryOption.slice(5), 10);
if (currentValue == null) {
return suggestedValue;
}
return Math[boundaryType](currentValue, suggestedValue);
} else {
if (currentValue != null) {
return currentValue;
} else {
return 0;
}
}
} else {
return parseInt(boundaryOption, 10);
}
} else {
return boundaryOption;
}
};
Grid.prototype.autoGridLines = function(ymin, ymax, nlines) {
var gmax, gmin, grid, smag, span, step, unit, y, ymag;
span = ymax - ymin;
ymag = Math.floor(Math.log(span) / Math.log(10));
unit = Math.pow(10, ymag);
gmin = Math.floor(ymin / unit) * unit;
gmax = Math.ceil(ymax / unit) * unit;
step = (gmax - gmin) / (nlines - 1);
if (unit === 1 && step > 1 && Math.ceil(step) !== step) {
step = Math.ceil(step);
gmax = gmin + step * (nlines - 1);
}
if (gmin < 0 && gmax > 0) {
gmin = Math.floor(ymin / step) * step;
gmax = Math.ceil(ymax / step) * step;
}
if (step < 1) {
smag = Math.floor(Math.log(step) / Math.log(10));
grid = (function() {
var _i, _results;
_results = [];
for (y = _i = gmin; step > 0 ? _i <= gmax : _i >= gmax; y = _i += step) {
_results.push(parseFloat(y.toFixed(1 - smag)));
}
return _results;
})();
} else {
grid = (function() {
var _i, _results;
_results = [];
for (y = _i = gmin; step > 0 ? _i <= gmax : _i >= gmax; y = _i += step) {
_results.push(y);
}
return _results;
})();
}
return grid;
};
Grid.prototype._calc = function() {
var bottomOffsets, gridLine, h, i, w, yLabelWidths, _ref, _ref1;
w = this.el.width();
h = this.el.height();
if (this.elementWidth !== w || this.elementHeight !== h || this.dirty) {
this.elementWidth = w;
this.elementHeight = h;
this.dirty = false;
this.left = this.options.padding;
this.right = this.elementWidth - this.options.padding;
this.top = this.options.padding;
this.bottom = this.elementHeight - this.options.padding;
if ((_ref = this.options.axes) === true || _ref === 'both' || _ref === 'y') {
yLabelWidths = (function() {
var _i, _len, _ref1, _results;
_ref1 = this.grid;
_results = [];
for (_i = 0, _len = _ref1.length; _i < _len; _i++) {
gridLine = _ref1[_i];
_results.push(this.measureText(this.yAxisFormat(gridLine)).width);
}
return _results;
}).call(this);
this.left += Math.max.apply(Math, yLabelWidths);
}
if ((_ref1 = this.options.axes) === true || _ref1 === 'both' || _ref1 === 'x') {
bottomOffsets = (function() {
var _i, _ref2, _results;
_results = [];
for (i = _i = 0, _ref2 = this.data.length; 0 <= _ref2 ? _i < _ref2 : _i > _ref2; i = 0 <= _ref2 ? ++_i : --_i) {
_results.push(this.measureText(this.data[i].text, -this.options.xLabelAngle).height);
}
return _results;
}).call(this);
this.bottom -= Math.max.apply(Math, bottomOffsets);
}
this.width = Math.max(1, this.right - this.left);
this.height = Math.max(1, this.bottom - this.top);
this.dx = this.width / (this.xmax - this.xmin);
this.dy = this.height / (this.ymax - this.ymin);
if (this.calc) {
return this.calc();
}
}
};
Grid.prototype.transY = function(y) {
return this.bottom - (y - this.ymin) * this.dy;
};
Grid.prototype.transX = function(x) {
if (this.data.length === 1) {
return (this.left + this.right) / 2;
} else {
return this.left + (x - this.xmin) * this.dx;
}
};
Grid.prototype.redraw = function() {
this.raphael.clear();
this._calc();
this.drawGrid();
this.drawGoals();
this.drawEvents();
if (this.draw) {
return this.draw();
}
};
Grid.prototype.measureText = function(text, angle) {
var ret, tt;
if (angle == null) {
angle = 0;
}
tt = this.raphael.text(100, 100, text).attr('font-size', this.options.gridTextSize).attr('font-family', this.options.gridTextFamily).attr('font-weight', this.options.gridTextWeight).rotate(angle);
ret = tt.getBBox();
tt.remove();
return ret;
};
Grid.prototype.yAxisFormat = function(label) {
return this.yLabelFormat(label);
};
Grid.prototype.yLabelFormat = function(label) {
if (typeof this.options.yLabelFormat === 'function') {
return this.options.yLabelFormat(label);
} else {
return "" + this.options.preUnits + (Morris.commas(label)) + this.options.postUnits;
}
};
Grid.prototype.drawGrid = function() {
var lineY, y, _i, _len, _ref, _ref1, _ref2, _results;
if (this.options.grid === false && ((_ref = this.options.axes) !== true && _ref !== 'both' && _ref !== 'y')) {
return;
}
_ref1 = this.grid;
_results = [];
for (_i = 0, _len = _ref1.length; _i < _len; _i++) {
lineY = _ref1[_i];
y = this.transY(lineY);
if ((_ref2 = this.options.axes) === true || _ref2 === 'both' || _ref2 === 'y') {
this.drawYAxisLabel(this.left - this.options.padding / 2, y, this.yAxisFormat(lineY));
}
if (this.options.grid) {
_results.push(this.drawGridLine("M" + this.left + "," + y + "H" + (this.left + this.width)));
} else {
_results.push(void 0);
}
}
return _results;
};
Grid.prototype.drawGoals = function() {
var color, goal, i, _i, _len, _ref, _results;
_ref = this.options.goals;
_results = [];
for (i = _i = 0, _len = _ref.length; _i < _len; i = ++_i) {
goal = _ref[i];
color = this.options.goalLineColors[i % this.options.goalLineColors.length];
_results.push(this.drawGoal(goal, color));
}
return _results;
};
Grid.prototype.drawEvents = function() {
var color, event, i, _i, _len, _ref, _results;
_ref = this.events;
_results = [];
for (i = _i = 0, _len = _ref.length; _i < _len; i = ++_i) {
event = _ref[i];
color = this.options.eventLineColors[i % this.options.eventLineColors.length];
_results.push(this.drawEvent(event, color));
}
return _results;
};
Grid.prototype.drawGoal = function(goal, color) {
return this.raphael.path("M" + this.left + "," + (this.transY(goal)) + "H" + this.right).attr('stroke', color).attr('stroke-width', this.options.goalStrokeWidth);
};
Grid.prototype.drawEvent = function(event, color) {
return this.raphael.path("M" + (this.transX(event)) + "," + this.bottom + "V" + this.top).attr('stroke', color).attr('stroke-width', this.options.eventStrokeWidth);
};
Grid.prototype.drawYAxisLabel = function(xPos, yPos, text) {
return this.raphael.text(xPos, yPos, text).attr('font-size', this.options.gridTextSize).attr('font-family', this.options.gridTextFamily).attr('font-weight', this.options.gridTextWeight).attr('fill', this.options.gridTextColor).attr('text-anchor', 'end');
};
Grid.prototype.drawGridLine = function(path) {
return this.raphael.path(path).attr('stroke', this.options.gridLineColor).attr('stroke-width', this.options.gridStrokeWidth);
};
Grid.prototype.startRange = function(x) {
this.hover.hide();
this.selectFrom = x;
return this.selectionRect.attr({
x: x,
width: 0
}).show();
};
Grid.prototype.endRange = function(x) {
var end, start;
if (this.selectFrom) {
start = Math.min(this.selectFrom, x);
end = Math.max(this.selectFrom, x);
this.options.rangeSelect.call(this.el, {
start: this.data[this.hitTest(start)].x,
end: this.data[this.hitTest(end)].x
});
return this.selectFrom = null;
}
};
Grid.prototype.resizeHandler = function() {
this.timeoutId = null;
this.raphael.setSize(this.el.width(), this.el.height());
return this.redraw();
};
return Grid;
})(Morris.EventEmitter);
Morris.parseDate = function(date) {
var isecs, m, msecs, n, o, offsetmins, p, q, r, ret, secs;
if (typeof date === 'number') {
return date;
}
m = date.match(/^(\d+) Q(\d)$/);
n = date.match(/^(\d+)-(\d+)$/);
o = date.match(/^(\d+)-(\d+)-(\d+)$/);
p = date.match(/^(\d+) W(\d+)$/);
q = date.match(/^(\d+)-(\d+)-(\d+)[ T](\d+):(\d+)(Z|([+-])(\d\d):?(\d\d))?$/);
r = date.match(/^(\d+)-(\d+)-(\d+)[ T](\d+):(\d+):(\d+(\.\d+)?)(Z|([+-])(\d\d):?(\d\d))?$/);
if (m) {
return new Date(parseInt(m[1], 10), parseInt(m[2], 10) * 3 - 1, 1).getTime();
} else if (n) {
return new Date(parseInt(n[1], 10), parseInt(n[2], 10) - 1, 1).getTime();
} else if (o) {
return new Date(parseInt(o[1], 10), parseInt(o[2], 10) - 1, parseInt(o[3], 10)).getTime();
} else if (p) {
ret = new Date(parseInt(p[1], 10), 0, 1);
if (ret.getDay() !== 4) {
ret.setMonth(0, 1 + ((4 - ret.getDay()) + 7) % 7);
}
return ret.getTime() + parseInt(p[2], 10) * 604800000;
} else if (q) {
if (!q[6]) {
return new Date(parseInt(q[1], 10), parseInt(q[2], 10) - 1, parseInt(q[3], 10), parseInt(q[4], 10), parseInt(q[5], 10)).getTime();
} else {
offsetmins = 0;
if (q[6] !== 'Z') {
offsetmins = parseInt(q[8], 10) * 60 + parseInt(q[9], 10);
if (q[7] === '+') {
offsetmins = 0 - offsetmins;
}
}
return Date.UTC(parseInt(q[1], 10), parseInt(q[2], 10) - 1, parseInt(q[3], 10), parseInt(q[4], 10), parseInt(q[5], 10) + offsetmins);
}
} else if (r) {
secs = parseFloat(r[6]);
isecs = Math.floor(secs);
msecs = Math.round((secs - isecs) * 1000);
if (!r[8]) {
return new Date(parseInt(r[1], 10), parseInt(r[2], 10) - 1, parseInt(r[3], 10), parseInt(r[4], 10), parseInt(r[5], 10), isecs, msecs).getTime();
} else {
offsetmins = 0;
if (r[8] !== 'Z') {
offsetmins = parseInt(r[10], 10) * 60 + parseInt(r[11], 10);
if (r[9] === '+') {
offsetmins = 0 - offsetmins;
}
}
return Date.UTC(parseInt(r[1], 10), parseInt(r[2], 10) - 1, parseInt(r[3], 10), parseInt(r[4], 10), parseInt(r[5], 10) + offsetmins, isecs, msecs);
}
} else {
return new Date(parseInt(date, 10), 0, 1).getTime();
}
};
Morris.Hover = (function() {
Hover.defaults = {
"class": 'morris-hover morris-default-style'
};
function Hover(options) {
if (options == null) {
options = {};
}
this.options = $.extend({}, Morris.Hover.defaults, options);
this.el = $("<div class='" + this.options["class"] + "'></div>");
this.el.hide();
this.options.parent.append(this.el);
}
Hover.prototype.update = function(html, x, y) {
if (!html) {
return this.hide();
} else {
this.html(html);
this.show();
return this.moveTo(x, y);
}
};
Hover.prototype.html = function(content) {
return this.el.html(content);
};
Hover.prototype.moveTo = function(x, y) {
var hoverHeight, hoverWidth, left, parentHeight, parentWidth, top;
parentWidth = this.options.parent.innerWidth();
parentHeight = this.options.parent.innerHeight();
hoverWidth = this.el.outerWidth();
hoverHeight = this.el.outerHeight();
left = Math.min(Math.max(0, x - hoverWidth / 2), parentWidth - hoverWidth);
if (y != null) {
top = y - hoverHeight - 10;
if (top < 0) {
top = y + 10;
if (top + hoverHeight > parentHeight) {
top = parentHeight / 2 - hoverHeight / 2;
}
}
} else {
top = parentHeight / 2 - hoverHeight / 2;
}
return this.el.css({
left: left + "px",
top: parseInt(top) + "px"
});
};
Hover.prototype.show = function() {
return this.el.show();
};
Hover.prototype.hide = function() {
return this.el.hide();
};
return Hover;
})();
Morris.Line = (function(_super) {
__extends(Line, _super);
function Line(options) {
this.hilight = __bind(this.hilight, this);
this.onHoverOut = __bind(this.onHoverOut, this);
this.onHoverMove = __bind(this.onHoverMove, this);
this.onGridClick = __bind(this.onGridClick, this);
if (!(this instanceof Morris.Line)) {
return new Morris.Line(options);
}
Line.__super__.constructor.call(this, options);
}
Line.prototype.init = function() {
if (this.options.hideHover !== 'always') {
this.hover = new Morris.Hover({
parent: this.el
});
this.on('hovermove', this.onHoverMove);
this.on('hoverout', this.onHoverOut);
return this.on('gridclick', this.onGridClick);
}
};
Line.prototype.defaults = {
lineWidth: 3,
pointSize: 4,
lineColors: ['#0b62a4', '#7A92A3', '#4da74d', '#afd8f8', '#edc240', '#cb4b4b', '#9440ed'],
pointStrokeWidths: [1],
pointStrokeColors: ['#ffffff'],
pointFillColors: [],
smooth: true,
xLabels: 'auto',
xLabelFormat: null,
xLabelMargin: 24,
hideHover: false
};
Line.prototype.calc = function() {
this.calcPoints();
return this.generatePaths();
};
Line.prototype.calcPoints = function() {
var row, y, _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
row = _ref[_i];
row._x = this.transX(row.x);
row._y = (function() {
var _j, _len1, _ref1, _results1;
_ref1 = row.y;
_results1 = [];
for (_j = 0, _len1 = _ref1.length; _j < _len1; _j++) {
y = _ref1[_j];
if (y != null) {
_results1.push(this.transY(y));
} else {
_results1.push(y);
}
}
return _results1;
}).call(this);
_results.push(row._ymax = Math.min.apply(Math, [this.bottom].concat((function() {
var _j, _len1, _ref1, _results1;
_ref1 = row._y;
_results1 = [];
for (_j = 0, _len1 = _ref1.length; _j < _len1; _j++) {
y = _ref1[_j];
if (y != null) {
_results1.push(y);
}
}
return _results1;
})())));
}
return _results;
};
Line.prototype.hitTest = function(x) {
var index, r, _i, _len, _ref;
if (this.data.length === 0) {
return null;
}
_ref = this.data.slice(1);
for (index = _i = 0, _len = _ref.length; _i < _len; index = ++_i) {
r = _ref[index];
if (x < (r._x + this.data[index]._x) / 2) {
break;
}
}
return index;
};
Line.prototype.onGridClick = function(x, y) {
var index;
index = this.hitTest(x);
return this.fire('click', index, this.data[index].src, x, y);
};
Line.prototype.onHoverMove = function(x, y) {
var index;
index = this.hitTest(x);
return this.displayHoverForRow(index);
};
Line.prototype.onHoverOut = function() {
if (this.options.hideHover !== false) {
return this.displayHoverForRow(null);
}
};
Line.prototype.displayHoverForRow = function(index) {
var _ref;
if (index != null) {
(_ref = this.hover).update.apply(_ref, this.hoverContentForRow(index));
return this.hilight(index);
} else {
this.hover.hide();
return this.hilight();
}
};
Line.prototype.hoverContentForRow = function(index) {
var content, j, row, y, _i, _len, _ref;
row = this.data[index];
content = "<div class='morris-hover-row-label'>" + row.label + "</div>";
_ref = row.y;
for (j = _i = 0, _len = _ref.length; _i < _len; j = ++_i) {
y = _ref[j];
content += "<div class='morris-hover-point' style='color: " + (this.colorFor(row, j, 'label')) + "'>\n " + this.options.labels[j] + ":\n " + (this.yLabelFormat(y)) + "\n</div>";
}
if (typeof this.options.hoverCallback === 'function') {
content = this.options.hoverCallback(index, this.options, content, row.src);
}
return [content, row._x, row._ymax];
};
Line.prototype.generatePaths = function() {
var coords, i, r, smooth;
return this.paths = (function() {
var _i, _ref, _ref1, _results;
_results = [];
for (i = _i = 0, _ref = this.options.ykeys.length; 0 <= _ref ? _i < _ref : _i > _ref; i = 0 <= _ref ? ++_i : --_i) {
smooth = typeof this.options.smooth === "boolean" ? this.options.smooth : (_ref1 = this.options.ykeys[i], __indexOf.call(this.options.smooth, _ref1) >= 0);
coords = (function() {
var _j, _len, _ref2, _results1;
_ref2 = this.data;
_results1 = [];
for (_j = 0, _len = _ref2.length; _j < _len; _j++) {
r = _ref2[_j];
if (r._y[i] !== void 0) {
_results1.push({
x: r._x,
y: r._y[i]
});
}
}
return _results1;
}).call(this);
if (coords.length > 1) {
_results.push(Morris.Line.createPath(coords, smooth, this.bottom));
} else {
_results.push(null);
}
}
return _results;
}).call(this);
};
Line.prototype.draw = function() {
var _ref;
if ((_ref = this.options.axes) === true || _ref === 'both' || _ref === 'x') {
this.drawXAxis();
}
this.drawSeries();
if (this.options.hideHover === false) {
return this.displayHoverForRow(this.data.length - 1);
}
};
Line.prototype.drawXAxis = function() {
var drawLabel, l, labels, prevAngleMargin, prevLabelMargin, row, ypos, _i, _len, _results,
_this = this;
ypos = this.bottom + this.options.padding / 2;
prevLabelMargin = null;
prevAngleMargin = null;
drawLabel = function(labelText, xpos) {
var label, labelBox, margin, offset, textBox;
label = _this.drawXAxisLabel(_this.transX(xpos), ypos, labelText);
textBox = label.getBBox();
label.transform("r" + (-_this.options.xLabelAngle));
labelBox = label.getBBox();
label.transform("t0," + (labelBox.height / 2) + "...");
if (_this.options.xLabelAngle !== 0) {
offset = -0.5 * textBox.width * Math.cos(_this.options.xLabelAngle * Math.PI / 180.0);
label.transform("t" + offset + ",0...");
}
labelBox = label.getBBox();
if (((prevLabelMargin == null) || prevLabelMargin >= labelBox.x + labelBox.width || (prevAngleMargin != null) && prevAngleMargin >= labelBox.x) && labelBox.x >= 0 && (labelBox.x + labelBox.width) < _this.el.width()) {
if (_this.options.xLabelAngle !== 0) {
margin = 1.25 * _this.options.gridTextSize / Math.sin(_this.options.xLabelAngle * Math.PI / 180.0);
prevAngleMargin = labelBox.x - margin;
}
return prevLabelMargin = labelBox.x - _this.options.xLabelMargin;
} else {
return label.remove();
}
};
if (this.options.parseTime) {
if (this.data.length === 1 && this.options.xLabels === 'auto') {
labels = [[this.data[0].label, this.data[0].x]];
} else {
labels = Morris.labelSeries(this.xmin, this.xmax, this.width, this.options.xLabels, this.options.xLabelFormat);
}
} else {
labels = (function() {
var _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
row = _ref[_i];
_results.push([row.label, row.x]);
}
return _results;
}).call(this);
}
labels.reverse();
_results = [];
for (_i = 0, _len = labels.length; _i < _len; _i++) {
l = labels[_i];
_results.push(drawLabel(l[0], l[1]));
}
return _results;
};
Line.prototype.drawSeries = function() {
var i, _i, _j, _ref, _ref1, _results;
this.seriesPoints = [];
for (i = _i = _ref = this.options.ykeys.length - 1; _ref <= 0 ? _i <= 0 : _i >= 0; i = _ref <= 0 ? ++_i : --_i) {
this._drawLineFor(i);
}
_results = [];
for (i = _j = _ref1 = this.options.ykeys.length - 1; _ref1 <= 0 ? _j <= 0 : _j >= 0; i = _ref1 <= 0 ? ++_j : --_j) {
_results.push(this._drawPointFor(i));
}
return _results;
};
Line.prototype._drawPointFor = function(index) {
var circle, row, _i, _len, _ref, _results;
this.seriesPoints[index] = [];
_ref = this.data;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
row = _ref[_i];
circle = null;
if (row._y[index] != null) {
circle = this.drawLinePoint(row._x, row._y[index], this.colorFor(row, index, 'point'), index);
}
_results.push(this.seriesPoints[index].push(circle));
}
return _results;
};
Line.prototype._drawLineFor = function(index) {
var path;
path = this.paths[index];
if (path !== null) {
return this.drawLinePath(path, this.colorFor(null, index, 'line'), index);
}
};
Line.createPath = function(coords, smooth, bottom) {
var coord, g, grads, i, ix, lg, path, prevCoord, x1, x2, y1, y2, _i, _len;
path = "";
if (smooth) {
grads = Morris.Line.gradients(coords);
}
prevCoord = {
y: null
};
for (i = _i = 0, _len = coords.length; _i < _len; i = ++_i) {
coord = coords[i];
if (coord.y != null) {
if (prevCoord.y != null) {
if (smooth) {
g = grads[i];
lg = grads[i - 1];
ix = (coord.x - prevCoord.x) / 4;
x1 = prevCoord.x + ix;
y1 = Math.min(bottom, prevCoord.y + ix * lg);
x2 = coord.x - ix;
y2 = Math.min(bottom, coord.y - ix * g);
path += "C" + x1 + "," + y1 + "," + x2 + "," + y2 + "," + coord.x + "," + coord.y;
} else {
path += "L" + coord.x + "," + coord.y;
}
} else {
if (!smooth || (grads[i] != null)) {
path += "M" + coord.x + "," + coord.y;
}
}
}
prevCoord = coord;
}
return path;
};
Line.gradients = function(coords) {
var coord, grad, i, nextCoord, prevCoord, _i, _len, _results;
grad = function(a, b) {
return (a.y - b.y) / (a.x - b.x);
};
_results = [];
for (i = _i = 0, _len = coords.length; _i < _len; i = ++_i) {
coord = coords[i];
if (coord.y != null) {
nextCoord = coords[i + 1] || {
y: null
};
prevCoord = coords[i - 1] || {
y: null
};
if ((prevCoord.y != null) && (nextCoord.y != null)) {
_results.push(grad(prevCoord, nextCoord));
} else if (prevCoord.y != null) {
_results.push(grad(prevCoord, coord));
} else if (nextCoord.y != null) {
_results.push(grad(coord, nextCoord));
} else {
_results.push(null);
}
} else {
_results.push(null);
}
}
return _results;
};
Line.prototype.hilight = function(index) {
var i, _i, _j, _ref, _ref1;
if (this.prevHilight !== null && this.prevHilight !== index) {
for (i = _i = 0, _ref = this.seriesPoints.length - 1; 0 <= _ref ? _i <= _ref : _i >= _ref; i = 0 <= _ref ? ++_i : --_i) {
if (this.seriesPoints[i][this.prevHilight]) {
this.seriesPoints[i][this.prevHilight].animate(this.pointShrinkSeries(i));
}
}
}
if (index !== null && this.prevHilight !== index) {
for (i = _j = 0, _ref1 = this.seriesPoints.length - 1; 0 <= _ref1 ? _j <= _ref1 : _j >= _ref1; i = 0 <= _ref1 ? ++_j : --_j) {
if (this.seriesPoints[i][index]) {
this.seriesPoints[i][index].animate(this.pointGrowSeries(i));
}
}
}
return this.prevHilight = index;
};
Line.prototype.colorFor = function(row, sidx, type) {
if (typeof this.options.lineColors === 'function') {
return this.options.lineColors.call(this, row, sidx, type);
} else if (type === 'point') {
return this.options.pointFillColors[sidx % this.options.pointFillColors.length] || this.options.lineColors[sidx % this.options.lineColors.length];
} else {
return this.options.lineColors[sidx % this.options.lineColors.length];
}
};
Line.prototype.drawXAxisLabel = function(xPos, yPos, text) {
return this.raphael.text(xPos, yPos, text).attr('font-size', this.options.gridTextSize).attr('font-family', this.options.gridTextFamily).attr('font-weight', this.options.gridTextWeight).attr('fill', this.options.gridTextColor);
};
Line.prototype.drawLinePath = function(path, lineColor, lineIndex) {
return this.raphael.path(path).attr('stroke', lineColor).attr('stroke-width', this.lineWidthForSeries(lineIndex));
};
Line.prototype.drawLinePoint = function(xPos, yPos, pointColor, lineIndex) {
return this.raphael.circle(xPos, yPos, this.pointSizeForSeries(lineIndex)).attr('fill', pointColor).attr('stroke-width', this.pointStrokeWidthForSeries(lineIndex)).attr('stroke', this.pointStrokeColorForSeries(lineIndex));
};
Line.prototype.pointStrokeWidthForSeries = function(index) {
return this.options.pointStrokeWidths[index % this.options.pointStrokeWidths.length];
};
Line.prototype.pointStrokeColorForSeries = function(index) {
return this.options.pointStrokeColors[index % this.options.pointStrokeColors.length];
};
Line.prototype.lineWidthForSeries = function(index) {
if (this.options.lineWidth instanceof Array) {
return this.options.lineWidth[index % this.options.lineWidth.length];
} else {
return this.options.lineWidth;
}
};
Line.prototype.pointSizeForSeries = function(index) {
if (this.options.pointSize instanceof Array) {
return this.options.pointSize[index % this.options.pointSize.length];
} else {
return this.options.pointSize;
}
};
Line.prototype.pointGrowSeries = function(index) {
return Raphael.animation({
r: this.pointSizeForSeries(index) + 3
}, 25, 'linear');
};
Line.prototype.pointShrinkSeries = function(index) {
return Raphael.animation({
r: this.pointSizeForSeries(index)
}, 25, 'linear');
};
return Line;
})(Morris.Grid);
Morris.labelSeries = function(dmin, dmax, pxwidth, specName, xLabelFormat) {
var d, d0, ddensity, name, ret, s, spec, t, _i, _len, _ref;
ddensity = 200 * (dmax - dmin) / pxwidth;
d0 = new Date(dmin);
spec = Morris.LABEL_SPECS[specName];
if (spec === void 0) {
_ref = Morris.AUTO_LABEL_ORDER;
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
name = _ref[_i];
s = Morris.LABEL_SPECS[name];
if (ddensity >= s.span) {
spec = s;
break;
}
}
}
if (spec === void 0) {
spec = Morris.LABEL_SPECS["second"];
}
if (xLabelFormat) {
spec = $.extend({}, spec, {
fmt: xLabelFormat
});
}
d = spec.start(d0);
ret = [];
while ((t = d.getTime()) <= dmax) {
if (t >= dmin) {
ret.push([spec.fmt(d), t]);
}
spec.incr(d);
}
return ret;
};
minutesSpecHelper = function(interval) {
return {
span: interval * 60 * 1000,
start: function(d) {
return new Date(d.getFullYear(), d.getMonth(), d.getDate(), d.getHours());
},
fmt: function(d) {
return "" + (Morris.pad2(d.getHours())) + ":" + (Morris.pad2(d.getMinutes()));
},
incr: function(d) {
return d.setUTCMinutes(d.getUTCMinutes() + interval);
}
};
};
secondsSpecHelper = function(interval) {
return {
span: interval * 1000,
start: function(d) {
return new Date(d.getFullYear(), d.getMonth(), d.getDate(), d.getHours(), d.getMinutes());
},
fmt: function(d) {
return "" + (Morris.pad2(d.getHours())) + ":" + (Morris.pad2(d.getMinutes())) + ":" + (Morris.pad2(d.getSeconds()));
},
incr: function(d) {
return d.setUTCSeconds(d.getUTCSeconds() + interval);
}
};
};
Morris.LABEL_SPECS = {
"decade": {
span: 172800000000,
start: function(d) {
return new Date(d.getFullYear() - d.getFullYear() % 10, 0, 1);
},
fmt: function(d) {
return "" + (d.getFullYear());
},
incr: function(d) {
return d.setFullYear(d.getFullYear() + 10);
}
},
"year": {
span: 17280000000,
start: function(d) {
return new Date(d.getFullYear(), 0, 1);
},
fmt: function(d) {
return "" + (d.getFullYear());
},
incr: function(d) {
return d.setFullYear(d.getFullYear() + 1);
}
},
"month": {
span: 2419200000,
start: function(d) {
return new Date(d.getFullYear(), d.getMonth(), 1);
},
fmt: function(d) {
return "" + (d.getFullYear()) + "-" + (Morris.pad2(d.getMonth() + 1));
},
incr: function(d) {
return d.setMonth(d.getMonth() + 1);
}
},
"week": {
span: 604800000,
start: function(d) {
return new Date(d.getFullYear(), d.getMonth(), d.getDate());
},
fmt: function(d) {
return "" + (d.getFullYear()) + "-" + (Morris.pad2(d.getMonth() + 1)) + "-" + (Morris.pad2(d.getDate()));
},
incr: function(d) {
return d.setDate(d.getDate() + 7);
}
},
"day": {
span: 86400000,
start: function(d) {
return new Date(d.getFullYear(), d.getMonth(), d.getDate());
},
fmt: function(d) {
return "" + (d.getFullYear()) + "-" + (Morris.pad2(d.getMonth() + 1)) + "-" + (Morris.pad2(d.getDate()));
},
incr: function(d) {
return d.setDate(d.getDate() + 1);
}
},
"hour": minutesSpecHelper(60),
"30min": minutesSpecHelper(30),
"15min": minutesSpecHelper(15),
"10min": minutesSpecHelper(10),
"5min": minutesSpecHelper(5),
"minute": minutesSpecHelper(1),
"30sec": secondsSpecHelper(30),
"15sec": secondsSpecHelper(15),
"10sec": secondsSpecHelper(10),
"5sec": secondsSpecHelper(5),
"second": secondsSpecHelper(1)
};
Morris.AUTO_LABEL_ORDER = ["decade", "year", "month", "week", "day", "hour", "30min", "15min", "10min", "5min", "minute", "30sec", "15sec", "10sec", "5sec", "second"];
Morris.Area = (function(_super) {
var areaDefaults;
__extends(Area, _super);
areaDefaults = {
fillOpacity: 'auto',
behaveLikeLine: false
};
function Area(options) {
var areaOptions;
if (!(this instanceof Morris.Area)) {
return new Morris.Area(options);
}
areaOptions = $.extend({}, areaDefaults, options);
this.cumulative = !areaOptions.behaveLikeLine;
if (areaOptions.fillOpacity === 'auto') {
areaOptions.fillOpacity = areaOptions.behaveLikeLine ? .8 : 1;
}
Area.__super__.constructor.call(this, areaOptions);
}
Area.prototype.calcPoints = function() {
var row, total, y, _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
row = _ref[_i];
row._x = this.transX(row.x);
total = 0;
row._y = (function() {
var _j, _len1, _ref1, _results1;
_ref1 = row.y;
_results1 = [];
for (_j = 0, _len1 = _ref1.length; _j < _len1; _j++) {
y = _ref1[_j];
if (this.options.behaveLikeLine) {
_results1.push(this.transY(y));
} else {
total += y || 0;
_results1.push(this.transY(total));
}
}
return _results1;
}).call(this);
_results.push(row._ymax = Math.max.apply(Math, row._y));
}
return _results;
};
Area.prototype.drawSeries = function() {
var i, range, _i, _j, _k, _len, _ref, _ref1, _results, _results1, _results2;
this.seriesPoints = [];
if (this.options.behaveLikeLine) {
range = (function() {
_results = [];
for (var _i = 0, _ref = this.options.ykeys.length - 1; 0 <= _ref ? _i <= _ref : _i >= _ref; 0 <= _ref ? _i++ : _i--){ _results.push(_i); }
return _results;
}).apply(this);
} else {
range = (function() {
_results1 = [];
for (var _j = _ref1 = this.options.ykeys.length - 1; _ref1 <= 0 ? _j <= 0 : _j >= 0; _ref1 <= 0 ? _j++ : _j--){ _results1.push(_j); }
return _results1;
}).apply(this);
}
_results2 = [];
for (_k = 0, _len = range.length; _k < _len; _k++) {
i = range[_k];
this._drawFillFor(i);
this._drawLineFor(i);
_results2.push(this._drawPointFor(i));
}
return _results2;
};
Area.prototype._drawFillFor = function(index) {
var path;
path = this.paths[index];
if (path !== null) {
path = path + ("L" + (this.transX(this.xmax)) + "," + this.bottom + "L" + (this.transX(this.xmin)) + "," + this.bottom + "Z");
return this.drawFilledPath(path, this.fillForSeries(index));
}
};
Area.prototype.fillForSeries = function(i) {
var color;
color = Raphael.rgb2hsl(this.colorFor(this.data[i], i, 'line'));
return Raphael.hsl(color.h, this.options.behaveLikeLine ? color.s * 0.9 : color.s * 0.75, Math.min(0.98, this.options.behaveLikeLine ? color.l * 1.2 : color.l * 1.25));
};
Area.prototype.drawFilledPath = function(path, fill) {
return this.raphael.path(path).attr('fill', fill).attr('fill-opacity', this.options.fillOpacity).attr('stroke', 'none');
};
return Area;
})(Morris.Line);
Morris.Bar = (function(_super) {
__extends(Bar, _super);
function Bar(options) {
this.onHoverOut = __bind(this.onHoverOut, this);
this.onHoverMove = __bind(this.onHoverMove, this);
this.onGridClick = __bind(this.onGridClick, this);
if (!(this instanceof Morris.Bar)) {
return new Morris.Bar(options);
}
Bar.__super__.constructor.call(this, $.extend({}, options, {
parseTime: false
}));
}
Bar.prototype.init = function() {
this.cumulative = this.options.stacked;
if (this.options.hideHover !== 'always') {
this.hover = new Morris.Hover({
parent: this.el
});
this.on('hovermove', this.onHoverMove);
this.on('hoverout', this.onHoverOut);
return this.on('gridclick', this.onGridClick);
}
};
Bar.prototype.defaults = {
barSizeRatio: 0.75,
barGap: 3,
barColors: ['#0b62a4', '#7a92a3', '#4da74d', '#afd8f8', '#edc240', '#cb4b4b', '#9440ed'],
barOpacity: 1.0,
barRadius: [0, 0, 0, 0],
xLabelMargin: 50
};
Bar.prototype.calc = function() {
var _ref;
this.calcBars();
if (this.options.hideHover === false) {
return (_ref = this.hover).update.apply(_ref, this.hoverContentForRow(this.data.length - 1));
}
};
Bar.prototype.calcBars = function() {
var idx, row, y, _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (idx = _i = 0, _len = _ref.length; _i < _len; idx = ++_i) {
row = _ref[idx];
row._x = this.left + this.width * (idx + 0.5) / this.data.length;
_results.push(row._y = (function() {
var _j, _len1, _ref1, _results1;
_ref1 = row.y;
_results1 = [];
for (_j = 0, _len1 = _ref1.length; _j < _len1; _j++) {
y = _ref1[_j];
if (y != null) {
_results1.push(this.transY(y));
} else {
_results1.push(null);
}
}
return _results1;
}).call(this));
}
return _results;
};
Bar.prototype.draw = function() {
var _ref;
if ((_ref = this.options.axes) === true || _ref === 'both' || _ref === 'x') {
this.drawXAxis();
}
return this.drawSeries();
};
Bar.prototype.drawXAxis = function() {
var i, label, labelBox, margin, offset, prevAngleMargin, prevLabelMargin, row, textBox, ypos, _i, _ref, _results;
ypos = this.bottom + (this.options.xAxisLabelTopPadding || this.options.padding / 2);
prevLabelMargin = null;
prevAngleMargin = null;
_results = [];
for (i = _i = 0, _ref = this.data.length; 0 <= _ref ? _i < _ref : _i > _ref; i = 0 <= _ref ? ++_i : --_i) {
row = this.data[this.data.length - 1 - i];
label = this.drawXAxisLabel(row._x, ypos, row.label);
textBox = label.getBBox();
label.transform("r" + (-this.options.xLabelAngle));
labelBox = label.getBBox();
label.transform("t0," + (labelBox.height / 2) + "...");
if (this.options.xLabelAngle !== 0) {
offset = -0.5 * textBox.width * Math.cos(this.options.xLabelAngle * Math.PI / 180.0);
label.transform("t" + offset + ",0...");
}
if (((prevLabelMargin == null) || prevLabelMargin >= labelBox.x + labelBox.width || (prevAngleMargin != null) && prevAngleMargin >= labelBox.x) && labelBox.x >= 0 && (labelBox.x + labelBox.width) < this.el.width()) {
if (this.options.xLabelAngle !== 0) {
margin = 1.25 * this.options.gridTextSize / Math.sin(this.options.xLabelAngle * Math.PI / 180.0);
prevAngleMargin = labelBox.x - margin;
}
_results.push(prevLabelMargin = labelBox.x - this.options.xLabelMargin);
} else {
_results.push(label.remove());
}
}
return _results;
};
Bar.prototype.drawSeries = function() {
var barWidth, bottom, groupWidth, idx, lastTop, left, leftPadding, numBars, row, sidx, size, spaceLeft, top, ypos, zeroPos;
groupWidth = this.width / this.options.data.length;
numBars = this.options.stacked ? 1 : this.options.ykeys.length;
barWidth = (groupWidth * this.options.barSizeRatio - this.options.barGap * (numBars - 1)) / numBars;
if (this.options.barSize) {
barWidth = Math.min(barWidth, this.options.barSize);
}
spaceLeft = groupWidth - barWidth * numBars - this.options.barGap * (numBars - 1);
leftPadding = spaceLeft / 2;
zeroPos = this.ymin <= 0 && this.ymax >= 0 ? this.transY(0) : null;
return this.bars = (function() {
var _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (idx = _i = 0, _len = _ref.length; _i < _len; idx = ++_i) {
row = _ref[idx];
lastTop = 0;
_results.push((function() {
var _j, _len1, _ref1, _results1;
_ref1 = row._y;
_results1 = [];
for (sidx = _j = 0, _len1 = _ref1.length; _j < _len1; sidx = ++_j) {
ypos = _ref1[sidx];
if (ypos !== null) {
if (zeroPos) {
top = Math.min(ypos, zeroPos);
bottom = Math.max(ypos, zeroPos);
} else {
top = ypos;
bottom = this.bottom;
}
left = this.left + idx * groupWidth + leftPadding;
if (!this.options.stacked) {
left += sidx * (barWidth + this.options.barGap);
}
size = bottom - top;
if (this.options.verticalGridCondition && this.options.verticalGridCondition(row.x)) {
this.drawBar(this.left + idx * groupWidth, this.top, groupWidth, Math.abs(this.top - this.bottom), this.options.verticalGridColor, this.options.verticalGridOpacity, this.options.barRadius);
}
if (this.options.stacked) {
top -= lastTop;
}
this.drawBar(left, top, barWidth, size, this.colorFor(row, sidx, 'bar'), this.options.barOpacity, this.options.barRadius);
_results1.push(lastTop += size);
} else {
_results1.push(null);
}
}
return _results1;
}).call(this));
}
return _results;
}).call(this);
};
Bar.prototype.colorFor = function(row, sidx, type) {
var r, s;
if (typeof this.options.barColors === 'function') {
r = {
x: row.x,
y: row.y[sidx],
label: row.label
};
s = {
index: sidx,
key: this.options.ykeys[sidx],
label: this.options.labels[sidx]
};
return this.options.barColors.call(this, r, s, type);
} else {
return this.options.barColors[sidx % this.options.barColors.length];
}
};
Bar.prototype.hitTest = function(x) {
if (this.data.length === 0) {
return null;
}
x = Math.max(Math.min(x, this.right), this.left);
return Math.min(this.data.length - 1, Math.floor((x - this.left) / (this.width / this.data.length)));
};
Bar.prototype.onGridClick = function(x, y) {
var index;
index = this.hitTest(x);
return this.fire('click', index, this.data[index].src, x, y);
};
Bar.prototype.onHoverMove = function(x, y) {
var index, _ref;
index = this.hitTest(x);
return (_ref = this.hover).update.apply(_ref, this.hoverContentForRow(index));
};
Bar.prototype.onHoverOut = function() {
if (this.options.hideHover !== false) {
return this.hover.hide();
}
};
Bar.prototype.hoverContentForRow = function(index) {
var content, j, row, x, y, _i, _len, _ref;
row = this.data[index];
content = "<div class='morris-hover-row-label'>" + row.label + "</div>";
_ref = row.y;
for (j = _i = 0, _len = _ref.length; _i < _len; j = ++_i) {
y = _ref[j];
content += "<div class='morris-hover-point' style='color: " + (this.colorFor(row, j, 'label')) + "'>\n " + this.options.labels[j] + ":\n " + (this.yLabelFormat(y)) + "\n</div>";
}
if (typeof this.options.hoverCallback === 'function') {
content = this.options.hoverCallback(index, this.options, content, row.src);
}
x = this.left + (index + 0.5) * this.width / this.data.length;
return [content, x];
};
Bar.prototype.drawXAxisLabel = function(xPos, yPos, text) {
var label;
return label = this.raphael.text(xPos, yPos, text).attr('font-size', this.options.gridTextSize).attr('font-family', this.options.gridTextFamily).attr('font-weight', this.options.gridTextWeight).attr('fill', this.options.gridTextColor);
};
Bar.prototype.drawBar = function(xPos, yPos, width, height, barColor, opacity, radiusArray) {
var maxRadius, path;
maxRadius = Math.max.apply(Math, radiusArray);
if (maxRadius === 0 || maxRadius > height) {
path = this.raphael.rect(xPos, yPos, width, height);
} else {
path = this.raphael.path(this.roundedRect(xPos, yPos, width, height, radiusArray));
}
return path.attr('fill', barColor).attr('fill-opacity', opacity).attr('stroke', 'none');
};
Bar.prototype.roundedRect = function(x, y, w, h, r) {
if (r == null) {
r = [0, 0, 0, 0];
}
return ["M", x, r[0] + y, "Q", x, y, x + r[0], y, "L", x + w - r[1], y, "Q", x + w, y, x + w, y + r[1], "L", x + w, y + h - r[2], "Q", x + w, y + h, x + w - r[2], y + h, "L", x + r[3], y + h, "Q", x, y + h, x, y + h - r[3], "Z"];
};
return Bar;
})(Morris.Grid);
Morris.Donut = (function(_super) {
__extends(Donut, _super);
Donut.prototype.defaults = {
colors: ['#0B62A4', '#3980B5', '#679DC6', '#95BBD7', '#B0CCE1', '#095791', '#095085', '#083E67', '#052C48', '#042135'],
backgroundColor: '#FFFFFF',
labelColor: '#000000',
formatter: Morris.commas,
resize: false
};
function Donut(options) {
this.resizeHandler = __bind(this.resizeHandler, this);
this.select = __bind(this.select, this);
this.click = __bind(this.click, this);
var _this = this;
if (!(this instanceof Morris.Donut)) {
return new Morris.Donut(options);
}
this.options = $.extend({}, this.defaults, options);
if (typeof options.element === 'string') {
this.el = $(document.getElementById(options.element));
} else {
this.el = $(options.element);
}
if (this.el === null || this.el.length === 0) {
throw new Error("Graph placeholder not found.");
}
if (options.data === void 0 || options.data.length === 0) {
return;
}
this.raphael = new Raphael(this.el[0]);
if (this.options.resize) {
$(window).bind('resize', function(evt) {
if (_this.timeoutId != null) {
window.clearTimeout(_this.timeoutId);
}
return _this.timeoutId = window.setTimeout(_this.resizeHandler, 100);
});
}
this.setData(options.data);
}
Donut.prototype.redraw = function() {
var C, cx, cy, i, idx, last, max_value, min, next, seg, total, value, w, _i, _j, _k, _len, _len1, _len2, _ref, _ref1, _ref2, _results;
this.raphael.clear();
cx = this.el.width() / 2;
cy = this.el.height() / 2;
w = (Math.min(cx, cy) - 10) / 3;
total = 0;
_ref = this.values;
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
value = _ref[_i];
total += value;
}
min = 5 / (2 * w);
C = 1.9999 * Math.PI - min * this.data.length;
last = 0;
idx = 0;
this.segments = [];
_ref1 = this.values;
for (i = _j = 0, _len1 = _ref1.length; _j < _len1; i = ++_j) {
value = _ref1[i];
next = last + min + C * (value / total);
seg = new Morris.DonutSegment(cx, cy, w * 2, w, last, next, this.data[i].color || this.options.colors[idx % this.options.colors.length], this.options.backgroundColor, idx, this.raphael);
seg.render();
this.segments.push(seg);
seg.on('hover', this.select);
seg.on('click', this.click);
last = next;
idx += 1;
}
this.text1 = this.drawEmptyDonutLabel(cx, cy - 10, this.options.labelColor, 15, 800);
this.text2 = this.drawEmptyDonutLabel(cx, cy + 10, this.options.labelColor, 14);
max_value = Math.max.apply(Math, this.values);
idx = 0;
_ref2 = this.values;
_results = [];
for (_k = 0, _len2 = _ref2.length; _k < _len2; _k++) {
value = _ref2[_k];
if (value === max_value) {
this.select(idx);
break;
}
_results.push(idx += 1);
}
return _results;
};
Donut.prototype.setData = function(data) {
var row;
this.data = data;
this.values = (function() {
var _i, _len, _ref, _results;
_ref = this.data;
_results = [];
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
row = _ref[_i];
_results.push(parseFloat(row.value));
}
return _results;
}).call(this);
return this.redraw();
};
Donut.prototype.click = function(idx) {
return this.fire('click', idx, this.data[idx]);
};
Donut.prototype.select = function(idx) {
var row, s, segment, _i, _len, _ref;
_ref = this.segments;
for (_i = 0, _len = _ref.length; _i < _len; _i++) {
s = _ref[_i];
s.deselect();
}
segment = this.segments[idx];
segment.select();
row = this.data[idx];
return this.setLabels(row.label, this.options.formatter(row.value, row));
};
Donut.prototype.setLabels = function(label1, label2) {
var inner, maxHeightBottom, maxHeightTop, maxWidth, text1bbox, text1scale, text2bbox, text2scale;
inner = (Math.min(this.el.width() / 2, this.el.height() / 2) - 10) * 2 / 3;
maxWidth = 1.8 * inner;
maxHeightTop = inner / 2;
maxHeightBottom = inner / 3;
this.text1.attr({
text: label1,
transform: ''
});
text1bbox = this.text1.getBBox();
text1scale = Math.min(maxWidth / text1bbox.width, maxHeightTop / text1bbox.height);
this.text1.attr({
transform: "S" + text1scale + "," + text1scale + "," + (text1bbox.x + text1bbox.width / 2) + "," + (text1bbox.y + text1bbox.height)
});
this.text2.attr({
text: label2,
transform: ''
});
text2bbox = this.text2.getBBox();
text2scale = Math.min(maxWidth / text2bbox.width, maxHeightBottom / text2bbox.height);
return this.text2.attr({
transform: "S" + text2scale + "," + text2scale + "," + (text2bbox.x + text2bbox.width / 2) + "," + text2bbox.y
});
};
Donut.prototype.drawEmptyDonutLabel = function(xPos, yPos, color, fontSize, fontWeight) {
var text;
text = this.raphael.text(xPos, yPos, '').attr('font-size', fontSize).attr('fill', color);
if (fontWeight != null) {
text.attr('font-weight', fontWeight);
}
return text;
};
Donut.prototype.resizeHandler = function() {
this.timeoutId = null;
this.raphael.setSize(this.el.width(), this.el.height());
return this.redraw();
};
return Donut;
})(Morris.EventEmitter);
Morris.DonutSegment = (function(_super) {
__extends(DonutSegment, _super);
function DonutSegment(cx, cy, inner, outer, p0, p1, color, backgroundColor, index, raphael) {
this.cx = cx;
this.cy = cy;
this.inner = inner;
this.outer = outer;
this.color = color;
this.backgroundColor = backgroundColor;
this.index = index;
this.raphael = raphael;
this.deselect = __bind(this.deselect, this);
this.select = __bind(this.select, this);
this.sin_p0 = Math.sin(p0);
this.cos_p0 = Math.cos(p0);
this.sin_p1 = Math.sin(p1);
this.cos_p1 = Math.cos(p1);
this.is_long = (p1 - p0) > Math.PI ? 1 : 0;
this.path = this.calcSegment(this.inner + 3, this.inner + this.outer - 5);
this.selectedPath = this.calcSegment(this.inner + 3, this.inner + this.outer);
this.hilight = this.calcArc(this.inner);
}
DonutSegment.prototype.calcArcPoints = function(r) {
return [this.cx + r * this.sin_p0, this.cy + r * this.cos_p0, this.cx + r * this.sin_p1, this.cy + r * this.cos_p1];
};
DonutSegment.prototype.calcSegment = function(r1, r2) {
var ix0, ix1, iy0, iy1, ox0, ox1, oy0, oy1, _ref, _ref1;
_ref = this.calcArcPoints(r1), ix0 = _ref[0], iy0 = _ref[1], ix1 = _ref[2], iy1 = _ref[3];
_ref1 = this.calcArcPoints(r2), ox0 = _ref1[0], oy0 = _ref1[1], ox1 = _ref1[2], oy1 = _ref1[3];
return ("M" + ix0 + "," + iy0) + ("A" + r1 + "," + r1 + ",0," + this.is_long + ",0," + ix1 + "," + iy1) + ("L" + ox1 + "," + oy1) + ("A" + r2 + "," + r2 + ",0," + this.is_long + ",1," + ox0 + "," + oy0) + "Z";
};
DonutSegment.prototype.calcArc = function(r) {
var ix0, ix1, iy0, iy1, _ref;
_ref = this.calcArcPoints(r), ix0 = _ref[0], iy0 = _ref[1], ix1 = _ref[2], iy1 = _ref[3];
return ("M" + ix0 + "," + iy0) + ("A" + r + "," + r + ",0," + this.is_long + ",0," + ix1 + "," + iy1);
};
DonutSegment.prototype.render = function() {
var _this = this;
this.arc = this.drawDonutArc(this.hilight, this.color);
return this.seg = this.drawDonutSegment(this.path, this.color, this.backgroundColor, function() {
return _this.fire('hover', _this.index);
}, function() {
return _this.fire('click', _this.index);
});
};
DonutSegment.prototype.drawDonutArc = function(path, color) {
return this.raphael.path(path).attr({
stroke: color,
'stroke-width': 2,
opacity: 0
});
};
DonutSegment.prototype.drawDonutSegment = function(path, fillColor, strokeColor, hoverFunction, clickFunction) {
return this.raphael.path(path).attr({
fill: fillColor,
stroke: strokeColor,
'stroke-width': 3
}).hover(hoverFunction).click(clickFunction);
};
DonutSegment.prototype.select = function() {
if (!this.selected) {
this.seg.animate({
path: this.selectedPath
}, 150, '<>');
this.arc.animate({
opacity: 1
}, 150, '<>');
return this.selected = true;
}
};
DonutSegment.prototype.deselect = function() {
if (this.selected) {
this.seg.animate({
path: this.path
}, 150, '<>');
this.arc.animate({
opacity: 0
}, 150, '<>');
return this.selected = false;
}
};
return DonutSegment;
})(Morris.EventEmitter);
}).call(this); | PypiClean |
/NeuroUnits-0.1.2.tar.gz/NeuroUnits-0.1.2/src/neurounits/importers/neuroml/neuroml_xml_data.py |
# -------------------------------------------------------------------------------
# Copyright (c) 2012 Michael Hull. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# - Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# - Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
# -------------------------------------------------------------------------------
import re
import xml.etree.cElementTree as etree
from .errors import NeuroUnitsImportNeuroMLNotImplementedException
def ignore(*args, **kwargs):
pass
def not_supported(*args, **kwargs):
raise NeuroUnitsImportNeuroMLNotImplementedException()
ns_regex = re.compile(r'{(?P<NS>.*)}(?P<TAG>.*)')
def strip_namespace(tag):
m = ns_regex.match(tag)
return m.groupdict()['TAG']
def recursive_strip_namespaces(xmlNode):
xmlNode.tag = strip_namespace(xmlNode.tag)
for child in xmlNode.getchildren():
recursive_strip_namespaces(child)
def dispatch_subnodes(node, dispatch_map):
for n in node.getchildren():
if n.tag in dispatch_map:
dispatch_map[n.tag](n)
else:
print ' -- ', n
assert False
class ChannelML_Q10Setting(object):
def __init__(self, gate, q10factor, experimental_temp, mode):
self.gate = gate
self.q10factor = q10factor
self.experimental_temp = experimental_temp
self.mode = mode
class ChannelML_GateEqn(object):
def __init__(self, sn):
self.name = sn.attrib['name']
self.frm = sn.attrib['from']
self.to = sn.attrib['to']
self.expr_form = sn.attrib['expr_form']
self.rate = sn.attrib.get('rate', None)
self.scale = sn.attrib.get('scale', None)
self.midpoint = sn.attrib.get('midpoint', None)
self.expr = sn.attrib.get('expr', None)
def getSubString(self, what):
LUT = {'rate': lambda : '{%f}' % float(self.rate),
'scale': lambda : '{%f}' % float(self.scale),
'midpoint': lambda : '{%f}' % float(self.midpoint)}
return LUT[what]()
def getEqn(self):
if self.expr_form == 'generic':
# A hack, so we don't need to deal with the tertiary operator:
if '?' in self.expr:
assert self.expr.count('?') == 1
(A, BC) = self.expr.split('?')
(B, C) = BC.split(':')
self.expr = '[%s]if[%s]else[%s]' % (B.strip(), A.strip().replace(' ', ''), C.strip())
return self.expr
scale = '{%f}' % float(self.scale) # self.getSubString('scale')
rate = self.getSubString('rate')
midpoint = self.getSubString('midpoint')
if self.expr_form == 'sigmoid':
return ' (1 * %s) / ( 1.0 + exp ( (V - %s)/%s ) ) ' \
% (rate, midpoint, scale)
elif self.expr_form == 'exponential':
return ' %s * exp ( 1.0 * (V- %s)/%s ) ' % (rate, midpoint, scale)
elif self.expr_form == 'exp_linear':
return '%s * ( (V - %s) / %s) / (1 - exp( -1.0 * ((V - %s)/%s) )) ' % (rate, midpoint, scale, midpoint, scale,)
else:
assert False
class ChannelML_Transition(ChannelML_GateEqn):
pass
class ChannelML_TimeCourse(ChannelML_GateEqn):
pass
class ChannelML_SteadyState(ChannelML_GateEqn):
pass
class ChannelML_Gate(object):
def load_closed_state(self, sn):
self.closedstates.append(sn.attrib['id'])
def load_open_state(self, sn):
self.openstates.append(sn.attrib['id'])
def load_time_course(self, sn):
self.time_courses.append(ChannelML_TimeCourse(sn))
def load_steady_state(self, sn):
self.steady_states.append(ChannelML_SteadyState(sn))
def load_transition(self, sn):
self.transitions.append(ChannelML_Transition(sn))
def load_initialisation(self, sn):
assert not self.initialisation
self.initialisation = sn.attrib['value']
def __init__(self, node):
self.openstates = []
self.closedstates = []
self.time_courses = []
self.steady_states = []
self.transitions = []
self.initialisation = None
self.name = node.attrib['name']
self.instances = int(node.attrib['instances'])
tag_handlers = {
'closed_state': self.load_closed_state,
'open_state': self.load_open_state,
'time_course': self.load_time_course,
'steady_state': self.load_steady_state,
'transition': self.load_transition,
'initialisation': self.load_initialisation,
}
# Load the Subnodes:
dispatch_subnodes(node, tag_handlers)
assert self.openstates
assert self.closedstates
class ChannelMLInfo(object):
def load_Q10Settings(self, node):
if 'fixed_q10' in node.attrib:
setting = ChannelML_Q10Setting( gate=node.get('gate',None),
q10factor=node.attrib['fixed_q10'],
experimental_temp=node.attrib['experimental_temp'],
mode='fixed_q10')
self.q10settings.append(setting)
else:
assert 'q10_factor' in node.attrib
setting = ChannelML_Q10Setting( gate=node.get('gate',None),
q10factor=node.attrib['q10_factor'],
experimental_temp=node.attrib['experimental_temp'],
mode='q10_factor')
self.q10settings.append(setting)
def load_parameters(self, node):
for parameter in node.iter('parameter'):
self.parameters[parameter.get('name')] = parameter.get('value')
def load_conc_factor(self,node):
self.unsupported_tags = "Unsupported NeuroML tag: 'conc_factor'"
def load_conc_dependence(self,node):
self.unsupported_tags = "Unsupported NeuroML tag: 'conc_dependence' "
self.iv_conc_dep_name = node.attrib['name']
self.iv_conc_dep_ion = node.attrib['ion']
self.iv_conc_dep_charge = int(node.attrib['charge'])
self.iv_conc_dep_variable_name = node.attrib['variable_name']
self.iv_conc_dep_min_conc = node.attrib['min_conc']
self.iv_conc_dep_max_conc = node.attrib['max_conc']
def load_gate(self, node):
self.gates.append(ChannelML_Gate(node))
def load_offset(self, n):
self.offset = float(n.attrib['value'])
def load_current_voltage_relation(self, node):
self.iv_cond_law = node.attrib.get('cond_law', None)
self.iv_ion = node.attrib.get('ion', None)
self.iv_default_gmax = node.attrib.get('default_gmax', None)
self.iv_default_erev = node.attrib.get('default_erev', None)
self.iv_charge = node.attrib.get('charge', None)
self.iv_fixed_erev = node.attrib.get('fixed_erev', None)
tag_handlers = {
'q10_settings': self.load_Q10Settings,
'offset': self.load_offset,
'conc_dependence': self.load_conc_dependence,
'ohmic': ignore,
'conc_factor': self.load_conc_factor,
'gate': self.load_gate,
}
dispatch_subnodes(node, tag_handlers)
def __init__(self, chl_type_node, units):
print 'Loading Channel Type:', chl_type_node.get('name')
self.name = chl_type_node.get('name')
self.parameters = {}
self.q10settings = []
self.offset = 0.
self.gates = []
self.units = units
# self.iv_conc_dep_name = None
# self.iv_conc_dep_ion = None
self.unsupported_tags = None
# Sanity Checks:
assert chl_type_node.get('density', 'yes') == 'yes'
tag_handlers = {
'status': ignore,
'notes': ignore,
'authorList': ignore,
'publication': ignore,
'neuronDBref': ignore,
'modelDBref': ignore,
'impl_prefs': ignore,
'current_voltage_relation': self.load_current_voltage_relation,
'parameters': self.load_parameters,
}
dispatch_subnodes(chl_type_node, tag_handlers)
def _parse_channelml_file(xmlfile):
tree = etree.parse(xmlfile)
root = tree.getroot()
recursive_strip_namespaces(root)
if root.tag != 'channelml':
return {}
# print xmlfile
chls = {}
for ch in root.iter('channel_type'):
chl = ChannelMLInfo(ch, units=root.attrib['units'])
chls[chl.name + ' (%s)' % xmlfile] = chl
return chls | PypiClean |
/Nuitka_winsvc-1.7.10-cp310-cp310-win_amd64.whl/nuitka/build/inline_copy/tqdm/tqdm/gui.py | from __future__ import absolute_import, division
import re
from warnings import warn
# to inherit from the tqdm class
from .std import TqdmExperimentalWarning
from .std import tqdm as std_tqdm
# import compatibility functions and utilities
from .utils import _range
__author__ = {"github.com/": ["casperdcl", "lrq3000"]}
__all__ = ['tqdm_gui', 'tgrange', 'tqdm', 'trange']
class tqdm_gui(std_tqdm): # pragma: no cover
"""Experimental Matplotlib GUI version of tqdm!"""
# TODO: @classmethod: write() on GUI?
def __init__(self, *args, **kwargs):
from collections import deque
import matplotlib as mpl
import matplotlib.pyplot as plt
kwargs = kwargs.copy()
kwargs['gui'] = True
colour = kwargs.pop('colour', 'g')
super(tqdm_gui, self).__init__(*args, **kwargs)
if self.disable:
return
warn("GUI is experimental/alpha", TqdmExperimentalWarning, stacklevel=2)
self.mpl = mpl
self.plt = plt
# Remember if external environment uses toolbars
self.toolbar = self.mpl.rcParams['toolbar']
self.mpl.rcParams['toolbar'] = 'None'
self.mininterval = max(self.mininterval, 0.5)
self.fig, ax = plt.subplots(figsize=(9, 2.2))
# self.fig.subplots_adjust(bottom=0.2)
total = self.__len__() # avoids TypeError on None #971
if total is not None:
self.xdata = []
self.ydata = []
self.zdata = []
else:
self.xdata = deque([])
self.ydata = deque([])
self.zdata = deque([])
self.line1, = ax.plot(self.xdata, self.ydata, color='b')
self.line2, = ax.plot(self.xdata, self.zdata, color='k')
ax.set_ylim(0, 0.001)
if total is not None:
ax.set_xlim(0, 100)
ax.set_xlabel("percent")
self.fig.legend((self.line1, self.line2), ("cur", "est"),
loc='center right')
# progressbar
self.hspan = plt.axhspan(0, 0.001, xmin=0, xmax=0, color=colour)
else:
# ax.set_xlim(-60, 0)
ax.set_xlim(0, 60)
ax.invert_xaxis()
ax.set_xlabel("seconds")
ax.legend(("cur", "est"), loc='lower left')
ax.grid()
# ax.set_xlabel('seconds')
ax.set_ylabel((self.unit if self.unit else "it") + "/s")
if self.unit_scale:
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
ax.yaxis.get_offset_text().set_x(-0.15)
# Remember if external environment is interactive
self.wasion = plt.isinteractive()
plt.ion()
self.ax = ax
def close(self):
if self.disable:
return
self.disable = True
with self.get_lock():
self._instances.remove(self)
# Restore toolbars
self.mpl.rcParams['toolbar'] = self.toolbar
# Return to non-interactive mode
if not self.wasion:
self.plt.ioff()
if self.leave:
self.display()
else:
self.plt.close(self.fig)
def clear(self, *_, **__):
pass
def display(self, *_, **__):
n = self.n
cur_t = self._time()
elapsed = cur_t - self.start_t
delta_it = n - self.last_print_n
delta_t = cur_t - self.last_print_t
# Inline due to multiple calls
total = self.total
xdata = self.xdata
ydata = self.ydata
zdata = self.zdata
ax = self.ax
line1 = self.line1
line2 = self.line2
# instantaneous rate
y = delta_it / delta_t
# overall rate
z = n / elapsed
# update line data
xdata.append(n * 100.0 / total if total else cur_t)
ydata.append(y)
zdata.append(z)
# Discard old values
# xmin, xmax = ax.get_xlim()
# if (not total) and elapsed > xmin * 1.1:
if (not total) and elapsed > 66:
xdata.popleft()
ydata.popleft()
zdata.popleft()
ymin, ymax = ax.get_ylim()
if y > ymax or z > ymax:
ymax = 1.1 * y
ax.set_ylim(ymin, ymax)
ax.figure.canvas.draw()
if total:
line1.set_data(xdata, ydata)
line2.set_data(xdata, zdata)
try:
poly_lims = self.hspan.get_xy()
except AttributeError:
self.hspan = self.plt.axhspan(0, 0.001, xmin=0, xmax=0, color='g')
poly_lims = self.hspan.get_xy()
poly_lims[0, 1] = ymin
poly_lims[1, 1] = ymax
poly_lims[2] = [n / total, ymax]
poly_lims[3] = [poly_lims[2, 0], ymin]
if len(poly_lims) > 4:
poly_lims[4, 1] = ymin
self.hspan.set_xy(poly_lims)
else:
t_ago = [cur_t - i for i in xdata]
line1.set_data(t_ago, ydata)
line2.set_data(t_ago, zdata)
d = self.format_dict
# remove {bar}
d['bar_format'] = (d['bar_format'] or "{l_bar}<bar/>{r_bar}").replace(
"{bar}", "<bar/>")
msg = self.format_meter(**d)
if '<bar/>' in msg:
msg = "".join(re.split(r'\|?<bar/>\|?', msg, 1))
ax.set_title(msg, fontname="DejaVu Sans Mono", fontsize=11)
self.plt.pause(1e-9)
def tgrange(*args, **kwargs):
"""
A shortcut for `tqdm.gui.tqdm(xrange(*args), **kwargs)`.
On Python3+, `range` is used instead of `xrange`.
"""
return tqdm_gui(_range(*args), **kwargs)
# Aliases
tqdm = tqdm_gui
trange = tgrange | PypiClean |
/AtmosphericChemistry-0.1.0.tar.gz/AtmosphericChemistry-0.1.0/README.txt | =============================
Atmospheric Chemistry Package
=============================
This collection of python classes and routines facilitates the exploration,
construction, and conversion of (gas-phase) chemical mechanisms
(the system of differential equations that are solved in numerical models
of atmospheric chemistry and transport). It consists of the following key elements:
1. The **Compound** class describing various physical and chemical properties of
individual molecules or lumped substances and defining their names in various
common chemistry schemes.
2. The **speciesTable** class which collects the compound information from all
molecules and handles reading and writing this information from or to csv
files.
3. The **Reaction** class describing gas-phase chemical reactants, products,
product yields, the rate coefficient term(s) and optional tags, comments,
and reaction labels.
4. The **Mechanism** class which contains a list of reactions and additional
variables, comments, and other information and handles in- and output from
and to various file formats (mech, csv, kpp, mozpp, racm).
Additional utilities allow computation of molecular weights based on the
elemental composition of a molecule and queries of the Pubchem and Master
Chemical Mechanism databases to obtain additional information about a compound
(e.g. SMILES code, IUPAC name, etc.). There is even a rudimentary algebra
class (mathTree) included, which allows scanning of mathematical expressions
and factorisation.
The main purpose of this package is the interconversion of chemical mechanisms
from one format to another, including the translation of species names from
the namespace of one model to that of another model. It has been developed originally
because of the author's need to perform an intercomparison of various mechanisms
with the help of a specific chemical boxmodel (CAABA/MECCA, see http://www.mecca.messy-interface.org/),
but it may also be useful for other purposes, and the author will be grateful for
feedback on various use cases as well as suggestions for improvement.
Conversion of a chemical mechanism is possible in only 4 lines of code::
from ac.gasphase.mechanism import Mechanism
m = Mechanism.from_mech(inputfilename)
m.translate_to_model('tm5')
m.write_kpp_mecca(outputfilename)
This will read a mechanism in the 'mech' format, translate all species names to the TM5
namespace and write out species and equations files for the Kinetic Preprocessor (KPP,
see http://people.cs.vt.edu/~asandu/Software/Kpp/).
It is also easily possible to test all reactions for mass conservation::
m.check_mass_balance()
or to find out which reactions involve a specific reactant, say HO2::
rlist = m.find_reactions(['HO2'])
for r in rlist:
print r.to_mech()
A number of applications of the ac package are provided in the *bin* directory of
this distribution.
Requirements
============
Most of the functionality of the AtmosphericChemistry package requires only python
standard libraries and numpy. However, if you want to use the pubchem or mcm_query
routines to access compound information from internet databases, you will also need
urllib, urllib2, lxml.html, json, time.
Author
======
Martin G. Schultz, IEK-8, Forschungszentrum Juelich, Germany
A Acknowledgements
==================
Matt Swain for providing the PubChemPy module which is included in this package
for cross-referencing compound information in the master species table.
Snehal Waychal for providing the mcm_query module and for packaging this up.
| PypiClean |
/FreePyBX-1.0-RC1.tar.gz/FreePyBX-1.0-RC1/freepybx/public/js/dojox/form/uploader/plugins/Flash.js | define("dojox/form/uploader/plugins/Flash",["dojo/dom-form","dojo/dom-style","dojo/dom-construct","dojo/dom-attr","dojo/_base/declare","dojo/_base/config","dojo/_base/connect","dojo/_base/lang","dojo/_base/array","dojox/form/uploader/plugins/HTML5","dojox/embed/Flash"],function(_1,_2,_3,_4,_5,_6,_7,_8,_9,_a,_b){
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}); | PypiClean |
/GithubStat-1.2.tar.gz/GithubStat-1.2/README.md | # GithubStat
**A Simple Github User Statistics Meter based on Github-API.**
[](https://github.com/htr-tech)
[](#)
[](https://badge.fury.io/py/GithubStat)
[](https://pypi.org/project/GithubStat)
[](https://pepy.tech/project/GithubStat)
[](https://pepy.tech/project/GithubStat/month)
### Installation :
- **Install GithubStat via Pypi :**
```
$ pip install GithubStat
```
- Now simply Type
```
$ GithubStat <github-username>
```
- **Use it via console :**
```python
>>> from GithubStat.__init__ import stats
>>> stats('htr-tech')
[-] Username : htr-tech
[-] Name : Tahmid Rayat
[-] Followers : 1969
[-] Following : 12
......
```
- **Install GithubStat via Github :**
```
$ git clone https://github.com/htr-tech/GithubStat.git
$ cd GithubStat
$ python setup.py install
$ GithubStat <github-username>
```
***Copyright (c) 2022 Tahmid Rayat Under [MIT LICENSE](https://github.com/htr-tech/GithubStat/blob/master/LICENSE#L1)***
### *📡 Get in Touch :*
[](https://github.com/htr-tech)
[](https://fb.com/tahmid.rayat.official)
[](https://www.instagram.com/tahmid.rayat)
| PypiClean |
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104 565ZM307 565Q307 580 317 593T346 610Q348 610 350 610T354 611Q355 612 367 612Q395 611 408 597T421 565T409 534T365 519H358Q336 519 322 532T307 565"]});MathJax.Ajax.loadComplete(MathJax.OutputJax.SVG.fontDir+"/Typewriter/Regular/BasicLatin.js"); | PypiClean |
/CoDocParser-0.2.49.tar.gz/CoDocParser-0.2.49/docparser/plugins/data_type_behavior.py | import re
import time
import traceback
from docparser.core.behavior_base import BehaviorBase
class DataTypeBehavior(BehaviorBase):
"""
数据类型转换处理行为
=================
配置说明：主节点下
"data_type_format": {
# table：对应表格模板中的column中的列名，
# data_type 对应执行转换方法
# format: 格式化的样式
# collect: 复杂情况使用正则表达式来处理，必须命名捕获组，且对应format的组名 例如：'{a}+{b}' '(?P<a>\\w*?,)afasdf(?P<a>\\d+)' 'hello,afasdf123123' => 'hello+123123'
# filter： 使用正则过滤当前值的干扰字符串
# default： 设置默认值的情况下，如果转换失败会使用默认值替换原值
"ESTIMATE ARRIVAL AT POD Country": {"table": "", "data_type": "time", "format": "%A, %d %b, %Y %I:%M %p", "filter": "(\\n)"},
"ESTIMATE ARRIVAL AT POD Time": {"table": "", "data_type": "time", "format": "%A, %d %b, %Y %I:%M %p", "filter": "(\\n)"},
}
"""
class_index = 1
class TypeConverter:
@classmethod
def convert_str(cls, table, error, key, conf, values, collect, val_format, val_filter, default_val, logger):
return values
@classmethod
def convert_time(cls, table, error, key, conf, values, collect, val_format, val_filter, default_val, logger):
format_list = val_format if isinstance(val_format, list) else [val_format]
for i in range(len(values)):
for f in format_list:
try:
values[i] = time.strftime("%Y-%m-%d %H:%M:%S", time.strptime(values[i], f))
break
except ValueError:
if default_val:
values[i] = default_val
logger.getLogger(cls.__name__).error(
f'时间格式转换异常,原因: [{values[i]} | {f} | {default_val}] <{traceback.format_exc()}>')
except Exception:
if default_val:
values[i] = default_val
logger.getLogger(cls.__name__).error(
f'时间格式转换异常,原因: [{values[i]} | {f} | {default_val}] <{traceback.format_exc()}>')
return values
def data_processing(self, ref_data, data: list, error: list, config: dict, logger, additional) -> dict:
"""
数据处理行为
:param ref_data: 源数据
:param data: execl解析出数据
:param error: execl解析出现的错误
:param config: 解析配置
:param logger: 日志工具
:param additional: 附加数据
"""
format_config = config.get("data_type_format")
if data and len(data) > 0 and format_config is not None:
cls = DataTypeBehavior.TypeConverter()
for key, conf in format_config.items():
table_name = conf.get("table")
data_type = conf.get("data_type")
fun_name = f"convert_{data_type.lower()}"
if hasattr(DataTypeBehavior.TypeConverter, fun_name):
callback = getattr(cls, fun_name)
else:
continue
val_format = conf.get("format")
collect = conf.get("collect")
val_filter = conf.get("filter")
default_val = conf.get("default")
values = self._find_values(key, table_name, data)
self.__filter(values, val_filter)
self.__format(values, collect, val_format)
callback(data, error, key, conf, values, collect, val_format, val_filter, default_val, logger)
self._restore_values(key, table_name, data, values)
return additional
@classmethod
def __filter(cls, values, rule):
"""
过滤指定字符
"""
regex = re.compile(rule)
for i in range(len(values)):
values[i] = regex.sub("", values[i])
@classmethod
def __format(cls, values, collect, val_format):
if collect and collect.strip() != "":
regex = re.compile(collect)
for i in range(len(values)):
if (match := regex.search(values[i])) is not None:
if (group_dict := match.groupdict()) is not None:
values[i] = val_format.format(**group_dict) | PypiClean |
/ApiMeter-1.2.8.tar.gz/ApiMeter-1.2.8/apimeter/locusts.py |
import io
import multiprocessing
import os
import sys
from locust.main import main
from apimeter.logger import color_print
from apimeter.testcase import TestcaseLoader
def parse_locustfile(file_path):
""" parse testcase file and return locustfile path.
if file_path is a Python file, assume it is a locustfile
if file_path is a YAML/JSON file, convert it to locustfile
"""
if not os.path.isfile(file_path):
color_print("file path invalid, exit.", "RED")
sys.exit(1)
file_suffix = os.path.splitext(file_path)[1]
if file_suffix == ".py":
locustfile_path = file_path
elif file_suffix in ['.yaml', '.yml', '.json']:
locustfile_path = gen_locustfile(file_path)
else:
# '' or other suffix
color_print("file type should be YAML/JSON/Python, exit.", "RED")
sys.exit(1)
return locustfile_path
def gen_locustfile(testcase_file_path):
""" generate locustfile from template.
"""
locustfile_path = 'locustfile.py'
template_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"templates",
"locustfile_template"
)
TestcaseLoader.load_test_dependencies()
testset = TestcaseLoader.load_test_file(testcase_file_path)
host = testset.get("config", {}).get("request", {}).get("base_url", "")
with io.open(template_path, encoding='utf-8') as template:
with io.open(locustfile_path, 'w', encoding='utf-8') as locustfile:
template_content = template.read()
template_content = template_content.replace("$HOST", host)
template_content = template_content.replace("$TESTCASE_FILE", testcase_file_path)
locustfile.write(template_content)
return locustfile_path
def start_master(sys_argv):
sys_argv.append("--master")
sys.argv = sys_argv
main()
def start_slave(sys_argv):
if "--slave" not in sys_argv:
sys_argv.extend(["--slave"])
sys.argv = sys_argv
main()
def run_locusts_with_processes(sys_argv, processes_count):
processes = []
manager = multiprocessing.Manager()
for _ in range(processes_count):
p_slave = multiprocessing.Process(target=start_slave, args=(sys_argv,))
p_slave.daemon = True
p_slave.start()
processes.append(p_slave)
try:
if "--slave" in sys_argv:
[process.join() for process in processes]
else:
start_master(sys_argv)
except KeyboardInterrupt:
manager.shutdown() | PypiClean |
/Miscoto-3.1.2.tar.gz/Miscoto-3.1.2/miscoto/query.py |
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
import os
import tempfile
import clyngor
from miscoto import utils
def get_scopes(instance_f, encoding):
"""Get metabolic scope of a microbiota
Args:
instance_f (str): ASP instance file
encoding (str): ASP model encoding
Returns:
TermSet: ASP model
"""
prg = [encoding, instance_f]
options = ''
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity:
best_model = model
return best_model
def get_grounded_communities_from_file(instance_f, encoding):
"""Ground the model, from a file
Args:
instance_f (str): model file
encoding (str): ASP model encoding
Returns:
bytes: grounded model
"""
prg = [encoding, instance_f]
grounding = clyngor.grounded_program(prg)
return grounding
def get_communities_from_g(grounding):
"""Get optimal community, from grounding
Args:
grounding (bytes): grounded model
Returns:
TermSet: solution
"""
options = '--configuration jumpy --opt-strategy=usc,oll'
best_model = None
models = clyngor.solve_from_grounded(grounding, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_communities(lp_instance, encoding):
"""Get optimal community, from TermSet
Args:
lp_instance (TermSet): microbiota model
encoding (str): ASP model encoding
Returns:
TermSet: solution
"""
options = '--configuration jumpy --opt-strategy=usc,5'
prg = [encoding, lp_instance]
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_intersection_communities_from_g(grounding, optimum):
"""Get intersection of solutions, from grounding
Args:
grounding (bytes): grounded model
optimum (str): optimal score
Returns:
TermSet: intersection
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode cautious --opt-mode=optN,' +str(optimum)
models = clyngor.solve_from_grounded(grounding, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_intersection_communities_from_g_noopti(grounding):
"""Get intersection of solutions, from grounding, without optimal score
Args:
grounding (bytes): grounded model
Returns:
TermSet: intersection
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode cautious --opt-mode=optN'
models = clyngor.solve_from_grounded(grounding, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_intersection_communities_opti(lp_instance, optimum, encoding):
"""Get intersection of solutions, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP model encoding
Returns:
TermSet: intersection
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode cautious --opt-mode=optN,' + str(optimum)
prg = [encoding, lp_instance]
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_intersection_communities(lp_instance, encoding):
"""Get intersection of solutions, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP model encoding
Returns:
TermSet: intersection
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode cautious --opt-mode=optN'
prg = [encoding, lp_instance]
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_all_communities_from_g(grounding, optimum, nmodels=0):
"""Get all optimal communities, from grounding
Args:
grounding (bytes): grounded model
optimum (str): optimal score
nmodels (int, optional): Defaults to 0. number of models to compute, 0 = all
Returns:
list: list of Termsets
"""
options = '--configuration handy --opt-strategy=usc,5 --opt-mode=optN,' +str(optimum)
models = clyngor.solve_from_grounded(grounding, options=options, nb_model=nmodels, use_clingo_module=False).by_arity.discard_quotes
opt_models = clyngor.opt_models_from_clyngor_answers(models)
return opt_models
def get_all_communities_from_g_noopti(grounding, nmodels=0):
"""Get all optimal communities, from grounding, without optimal score
Args:
grounding (bytes): grounded model
nmodels (int, optional): Defaults to 0. number of models, 0 = all
Returns:
list: list of TermSets
"""
options = '--configuration handy --opt-strategy=usc,5 --opt-mode=optN'
models = clyngor.solve_from_grounded(grounding, options=options, nb_model=nmodels, use_clingo_module=False).by_arity.discard_quotes
opt_models = clyngor.opt_models_from_clyngor_answers(models)
return opt_models
def get_all_communities_opti(lp_instance, optimum, encoding, nmodels=0):
"""Get all communities, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP model encoding file
nmodels (int, optional): Defaults to 0. number of models, 0 = all
Returns:
list: list of TermSets
"""
options = '--configuration handy --opt-strategy=usc,0 --opt-mode=optN,' + str(optimum)
prg = [encoding, lp_instance]
models = clyngor.solve(prg, options=options, nb_model=nmodels, use_clingo_module=False).by_arity.discard_quotes
opt_models = clyngor.opt_models_from_clyngor_answers(models)
return opt_models
def get_all_communities(lp_instance, encoding, nmodels=0):
"""Get all communities, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP model encoding file
nmodels (int, optional): Defaults to 0. number of models, 0 = all
Returns:
list: list of TermSets
"""
options = '--configuration handy --opt-strategy=usc,0 --opt-mode=optN'
prg = [encoding, lp_instance]
opt_models = clyngor.opt_models_from_clyngor_answers(clyngor.solve(prg, options=options, nb_model=nmodels, use_clingo_module=False).by_arity.discard_quotes)
return opt_models
def get_union_communities_from_g(grounding, optimum):
"""Get union of all community solutions
Args:
grounding (bytes): grounded model
optimum (str): optimal score
Returns:
TermSet: union
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode=brave --opt-mode=optN,' + str(optimum)
models = clyngor.solve_from_grounded(grounding, options=options, use_clingo_module=False)
best_model = None
for model in models.by_arity.discard_quotes.with_optimization:
best_model = model
return best_model
def get_union_communities_from_g_noopti(grounding):
"""Get union of all community solutions, from grounding, without optimal score
Args:
grounding (bytes): grounded instance
Returns:
TermSet: union
"""
options = '--configuration jumpy --opt-strategy=usc,5 --enum-mode brave --opt-mode=optN'
models = clyngor.solve_from_grounded(grounding, options=options, use_clingo_module=False)
best_model = None
for model in models.by_arity.discard_quotes.with_optimization:
best_model = model
return best_model
def get_union_communities_optimum(lp_instance, optimum, encoding):
"""Get union of community solutions, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP encoding model file
Returns:
TermSet: union
"""
options ='--configuration jumpy --opt-strategy=usc,5 --enum-mode=brave --opt-mode=optN --opt-bound='+str(optimum)
prg = [encoding, lp_instance]
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_union_communities(lp_instance, encoding):
"""Get union of community solutions, from TermSet
Args:
lp_instance (TermSet): microbiota model
optimum (str): optimal score
encoding (str): ASP encoding model file
Returns:
TermSet: union
"""
options ='--configuration jumpy --opt-strategy=usc,5 --enum-mode=brave --opt-mode=optN'
prg = [encoding, lp_instance]
best_model = None
models = clyngor.solve(prg, options=options, use_clingo_module=False)
for model in models.discard_quotes.by_arity.with_optimization:
best_model = model
return best_model
def get_unproducible(draft, seeds, targets, encoding):
"""Get unproducible targets in a microbiota
Args:
draft (TermSet): metabolic model
seeds (TermSet): seeds
targets (TermSet): targets
encoding (str): ASP model encoding
Returns:
TermSet: unproducible targets
"""
draft_f = utils.to_file(draft)
seed_f = utils.to_file(seeds)
target_f = utils.to_file(targets)
prg = [encoding, draft_f, seed_f, target_f]
solver = Gringo4Clasp()
models = solver.run(prg,collapseTerms=True,collapseAtoms=False)
os.unlink(draft_f)
os.unlink(seed_f)
os.unlink(target_f)
return models[0]
def get_transported(instance, encoding):
"""Get transported metabolites
Args:
instance (TermSet): microbiota model
encoding (str): ASP model encoding
Returns:
TermSet: transported metabolites
"""
instance_f = utils.to_file(instance)
prg = [encoding, instance_f]
solver = Gringo4Clasp()
models = solver.run(prg,collapseTerms=True,collapseAtoms=False)
os.unlink(instance_f)
return models[0]
def get_grounded_instance_exchanged_metabolites(instance, encoding, exchanged_in_escope=False):
"""Get grounding under compartmentalized framework
Args:
instance (TermSet): microbiota model
encoding (str): ASP model encoding
exchanged_in_escope (bool, default=False): additional option for ASP
Returns:
bytes: grounded model
"""
instance_f = utils.to_file(instance)
if exchanged_in_escope:
options = "--const exchanged_in_escope=1"
else:
options = "--const exchanged_in_escope=0"
print(os.path.abspath(instance_f))
prg = [encoding, instance_f]
grounder = Gringo4(gringo_options=options)
grounding = grounder.run(prg)
os.unlink(instance_f)
return grounding
def get_grounded_instance_exchanged_metabolites_from_file(instance_f, encoding, exchanged_in_escope=False):
"""Get grounding from file
Args:
instance_f (str): microbiota model file
encoding (str): ASP model encoding
exchanged_in_escope (bool, default=False): additional ASP option
Returns:
bytes: grounded model
"""
if exchanged_in_escope:
options = "--const exchanged_in_escope=1"
else:
options = "--const exchanged_in_escope=0"
print(os.path.abspath(instance_f))
prg = [encoding, instance_f]
grounder = Gringo4(gringo_options=options)
grounding = grounder.run(prg)
return grounding
def get_exchanged_metabolites_onesol(grounding):
"""Select community in compartmentalized framework
Args:
grounding (bytes): grounded model
Returns:
TermSet: solution
"""
options = "--configuration=jumpy --opt-strategy=usc,5"
solver = Clasp(clasp_options=options)
models = solver.run(grounding,collapseTerms=True,collapseAtoms=False)
return models
def get_exchanged_metabolites_intersection(grounding, optimum):
"""Get intersection of communities solutions
Args:
grounding (bytes): grounded model
optimum (str): optimal score
Returns:
TermSet: intersection
"""
options='--configuration jumpy --opt-strategy=usc,5 --enum-mode cautious --opt-mode=optN --opt-bound='+str(optimum)
solver = Clasp(clasp_options=options)
intersec = solver.run(grounding, collapseTerms=True, collapseAtoms=False)
return intersec[0]
def get_exchanged_metabolites_allsol(grounding, optimum, nmodels=0):
"""Get all communities
Args:
grounding (bytes): grounded model
optimum (str): optimal score
nmodels (int, optional): Defaults to 0. number of models, 0 = all
Returns:
Set: set of TermSets
"""
options = str(nmodels)+' --configuration jumpy --opt-strategy=usc,5 --opt-mode=optN --opt-bound='+str(optimum)
solver = Clasp(clasp_options=options)
models = solver.run(grounding, collapseTerms=True, collapseAtoms=False)
return models
def get_exchanged_metabolites_union(grounding, optimum):
"""Get union of community solutions
Args:
grounding (bytes): grounded model
optimum (str): optimal score
Returns:
TermSet: union
"""
options ='--configuration jumpy --opt-strategy=usc,5 --enum-mode brave --opt-mode=optN --opt-bound='+str(optimum)
solver = Clasp(clasp_options=options)
union = solver.run(grounding, collapseTerms=True, collapseAtoms=False)
return union[0] | PypiClean |
/EulerPy-1.4.0.tar.gz/EulerPy-1.4.0/README.rst | **********************************
EulerPy |Travis| |PyPI| |Homebrew|
**********************************
EulerPy is a command line tool designed to streamline the process of solving
Project Euler problems using Python. The package focuses on two main tasks:
firstly, to create Python "template" files with a docstring containing the
text of a Project Euler problem for ease-of-reference, and secondly, to check
whether a problem has been solved correctly.
============
Installation
============
EulerPy can be installed (and updated) from PyPI using `pip`_:
.. code-block:: bash
$ pip install --upgrade EulerPy
Conversely, it can be uninstalled using `pip`_ as well.
.. code-block:: bash
$ pip uninstall EulerPy
Alternatively, OS X users can install EulerPy using `Homebrew`_:
.. code-block:: bash
$ brew install euler-py
=====
Usage
=====
First, you'll want to ``cd`` to the directory where your Project Euler files
are being stored.
.. code-block:: bash
$ mkdir ~/project-euler
$ cd ~/project-euler
At this point, you'll probably want to run the ``euler`` command, which will
prompt to create ``001.py``, a file containing the text to Project Euler problem
#1 as its docstring.
.. code-block:: bash
$ euler
No Project Euler files found in the current directory.
Generate file for problem 1? [Y/n]: Y
Successfully created "001.py".
$ cat 001.py
"""
Project Euler Problem 1
=======================
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
At this point, you can open up your editor of choice and code up a solution
to the problem, making sure to ``print()`` the output. Once you feel that
you've solved the problem, run the ``euler`` command again to verify your
solution is correct. If the answer is correct, the solution will be printed
in green and the script will ask to generate the next problem file. If
incorrect, the solution will be printed in red instead. Additionally, the
time elapsed during the solution-checking process will also be printed.
.. code-block:: bash
$ euler
Checking "001.py" against solution: [no output] # (output in red)
$ echo print 42 >> 001.py
$ euler
Checking "001.py" against solution: 42 # (output in green)
Generate file for problem 2? [Y/n]: Y
Successfully created "002.py".
EulerPy also has a few command line options that act as different commands
(use ``euler --help`` to see a summary of all the options).
``--cheat / -c``
----------------
The ``--cheat`` option will print the answer to a problem after prompting
the user to ensure that they want to see it. If no problem argument is given,
it will print the answer to the problem that they are currently working on.
.. code-block:: bash
$ euler --cheat
View answer to problem 2? [y/N]: Y
The answer to problem 2 is <redacted>.
$ euler --cheat 100
View answer to problem 100? [y/N]: Y
The answer to problem 100 is <redacted>.
``--generate / -g``
-------------------
The ``--generate`` option will create a Python file for the given problem
number. If no problem number is given, it will overwrite the most recent
problem with a file containing only the problem docstring (after prompting
the user).
.. code-block:: bash
$ euler --generate
Generate file for problem 2? [Y/n]: Y
"002.py" already exists. Overwrite? [y/N]:
Successfully created "002.py".
$ euler --generate 5
Generate file for problem 5? [Y/n]: n
Aborted!
``euler <problem>`` is equivalent to ``euler --generate <problem>`` if the file
**does not** exist.
.. code-block:: bash
$ cat 005.py
cat: 005.py: No such file or directory
$ euler 5
Generate file for problem 5? [Y/n]: n
Aborted!
The file generation process will also automatically copy any relevant
resource files to a ``resources`` subdirectory.
.. code-block:: bash
$ euler 22
Generate file for problem 22? [Y/n]: Y
Successfully created "022.py".
Copied "names.txt" to project-euler/resources.
``--preview / -p``
------------------
The ``--preview`` option will print the text of a given problem to the terminal;
if no problem number is given, it will print the next problem instead.
.. code-block:: bash
$ euler --preview
Project Euler Problem 3
The prime factors of 13195 are 5, 7, 13 and 29.
What is the largest prime factor of the number 600851475143?
$ euler --preview 5
Project Euler Problem 5
2520 is the smallest number that can be divided by each of the numbers
from 1 to 10 without any remainder.
What is the smallest number that is evenly divisible by all of the numbers
from 1 to 20?
``--skip / -s``
---------------
The ``--skip`` option will prompt the user to "skip" to the next problem. As
of EulerPy v1.1, it will also append a "skipped" suffix to the skipped problem
file.
.. code-block:: bash
$ euler --skip
Current problem is problem 2.
Generate file for problem 3? [y/N]: Y
Successfully created "003.py".
Renamed "002.py" to "002-skipped.py".
``--verify / -v``
-----------------
The ``--verify`` option will check whether a given problem file outputs the
correct solution to the problem. If no problem number is given, it will
check the current problem.
.. code-block:: bash
$ euler --verify
Checking "003.py" against solution: [no output] # (output in red)
$ euler --verify 1
Checking "001.py" against solution: <redacted> # (output in green)
As of EulerPy v1.1, verifying a skipped problem file will remove the "skipped"
suffix from its filename.
.. code-block:: bash
$ euler --verify 2
Checking "002-skipped.py" against solution: <redacted>
Renamed "002-skipped.py" to "002.py".
``euler <problem>`` is equivalent to ``euler --verify <problem>`` if the file
**does** exist.
.. code-block:: bash
$ cat 001.py
"""
Project Euler Problem 1
=======================
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
$ euler 1
Checking "001.py" against solution: <redacted>
``--verify-all``
----------------
The ``--verify-all`` option was added in EulerPy v1.1. It essentially runs
``--verify`` on all the problem files it can find in the current directory,
but also prints an overview of all of the problems in the directory. Note
that if the verification encounters a ``KeyboardInterrupt`` exception, it will
skip the verification of that specific file. This allows for the ability to
skip verifying some files but not others, in the case that some solutions are
taking too long to compute.
.. code-block:: bash
$ euler --verify-all
Checking "001.py" against solution: <redacted>
Checking "002.py" against solution: ^C
Checking "003.py" against solution: [no output]
---------------------------------------------------------------
C = correct, I = incorrect, E = error, S = skipped, . = missing
Problems 001-020: C S I . . . . . . . . . . . . . . . . .
This option should be run after upgrading to v1.1 from EulerPy v1.0, as it will
automatically rename any problems that have been skipped using ``--skip``,
making them easy to distinguish from those that have been correctly solved.
File Prefixes
-------------
As of v1.3.0, EulerPy will attempt to keep the prefix of problem files
consistent. The motivation behind this is that ``import 001`` results in a
syntax error whereas ``import euler001`` is valid. By using the latter
naming scheme, it is possible to reuse code written in previous files.
.. code-block:: bash
$ mv 003.py euler003.py
$ euler --skip
Current problem is problem 3.
Generate file for problem 4? [y/N]: Y
Successfully created "euler004.py".
Renamed "euler003.py" to "euler003-skipped.py".
============
Contributing
============
See `CONTRIBUTING.rst`_.
=============
Miscellaneous
=============
The text for the problems in `problems.txt`_ were derived from Kyle Keen's
`Local Euler`_ project, and the solutions in `solutions.txt`_ were derived
from Bai Li's `projecteuler-solutions`_ repository.
See `this blog post`_ for insight into the development process.
EulerPy uses `Click`_ as a dependency for its CLI functionality.
=======
License
=======
EulerPy is licensed under the `MIT License`_.
.. |Travis| image:: https://img.shields.io/travis/iKevinY/EulerPy/master.svg
:alt: Build Status
:target: http://travis-ci.org/iKevinY/EulerPy
.. |PyPI| image:: https://img.shields.io/pypi/v/EulerPy.svg
:alt: PyPI Version
:target: https://pypi.python.org/pypi/EulerPy/
.. |Homebrew| image:: https://img.shields.io/homebrew/v/euler-py.svg
:alt: Homebrew Version
:target: https://github.com/Homebrew/homebrew-core/blob/master/Formula/euler-py.rb
.. _pip: http://www.pip-installer.org/en/latest/index.html
.. _Homebrew: http://brew.sh
.. _CONTRIBUTING.rst: https://github.com/iKevinY/EulerPy/blob/master/CONTRIBUTING.rst
.. _Local Euler: http://kmkeen.com/local-euler/
.. _problems.txt: https://github.com/iKevinY/EulerPy/blob/master/EulerPy/data/problems.txt
.. _solutions.txt: https://github.com/iKevinY/EulerPy/blob/master/EulerPy/data/solutions.txt
.. _projecteuler-solutions: https://github.com/luckytoilet/projecteuler-solutions
.. _this blog post: http://kevinyap.ca/2014/06/eulerpy-streamlining-project-euler/
.. _click: https://github.com/mitsuhiko/click
.. _MIT License: https://github.com/iKevinY/EulerPy/blob/master/LICENSE
| PypiClean |
/Appium-Python-Client-2.11.1.tar.gz/Appium-Python-Client-2.11.1/docs/_build/html/_static/language_data.js | var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
/* Non-minified version is copied as a separate JS file, is available */
/**
* Porter Stemmer
*/
var Stemmer = function() {
var step2list = {
ational: 'ate',
tional: 'tion',
enci: 'ence',
anci: 'ance',
izer: 'ize',
bli: 'ble',
alli: 'al',
entli: 'ent',
eli: 'e',
ousli: 'ous',
ization: 'ize',
ation: 'ate',
ator: 'ate',
alism: 'al',
iveness: 'ive',
fulness: 'ful',
ousness: 'ous',
aliti: 'al',
iviti: 'ive',
biliti: 'ble',
logi: 'log'
};
var step3list = {
icate: 'ic',
ative: '',
alize: 'al',
iciti: 'ic',
ical: 'ic',
ful: '',
ness: ''
};
var c = "[^aeiou]"; // consonant
var v = "[aeiouy]"; // vowel
var C = c + "[^aeiouy]*"; // consonant sequence
var V = v + "[aeiou]*"; // vowel sequence
var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0
var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1
var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1
var s_v = "^(" + C + ")?" + v; // vowel in stem
this.stemWord = function (w) {
var stem;
var suffix;
var firstch;
var origword = w;
if (w.length < 3)
return w;
var re;
var re2;
var re3;
var re4;
firstch = w.substr(0,1);
if (firstch == "y")
w = firstch.toUpperCase() + w.substr(1);
// Step 1a
re = /^(.+?)(ss|i)es$/;
re2 = /^(.+?)([^s])s$/;
if (re.test(w))
w = w.replace(re,"$1$2");
else if (re2.test(w))
w = w.replace(re2,"$1$2");
// Step 1b
re = /^(.+?)eed$/;
re2 = /^(.+?)(ed|ing)$/;
if (re.test(w)) {
var fp = re.exec(w);
re = new RegExp(mgr0);
if (re.test(fp[1])) {
re = /.$/;
w = w.replace(re,"");
}
}
else if (re2.test(w)) {
var fp = re2.exec(w);
stem = fp[1];
re2 = new RegExp(s_v);
if (re2.test(stem)) {
w = stem;
re2 = /(at|bl|iz)$/;
re3 = new RegExp("([^aeiouylsz])\\1$");
re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
if (re2.test(w))
w = w + "e";
else if (re3.test(w)) {
re = /.$/;
w = w.replace(re,"");
}
else if (re4.test(w))
w = w + "e";
}
}
// Step 1c
re = /^(.+?)y$/;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
re = new RegExp(s_v);
if (re.test(stem))
w = stem + "i";
}
// Step 2
re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
suffix = fp[2];
re = new RegExp(mgr0);
if (re.test(stem))
w = stem + step2list[suffix];
}
// Step 3
re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
suffix = fp[2];
re = new RegExp(mgr0);
if (re.test(stem))
w = stem + step3list[suffix];
}
// Step 4
re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
re2 = /^(.+?)(s|t)(ion)$/;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
re = new RegExp(mgr1);
if (re.test(stem))
w = stem;
}
else if (re2.test(w)) {
var fp = re2.exec(w);
stem = fp[1] + fp[2];
re2 = new RegExp(mgr1);
if (re2.test(stem))
w = stem;
}
// Step 5
re = /^(.+?)e$/;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
re = new RegExp(mgr1);
re2 = new RegExp(meq1);
re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
w = stem;
}
re = /ll$/;
re2 = new RegExp(mgr1);
if (re.test(w) && re2.test(w)) {
re = /.$/;
w = w.replace(re,"");
}
// and turn initial Y back to y
if (firstch == "y")
w = firstch.toLowerCase() + w.substr(1);
return w;
}
}
var splitChars = (function() {
var result = {};
var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
var i, j, start, end;
for (i = 0; i < singles.length; i++) {
result[singles[i]] = true;
}
var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
[722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
[1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
[1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
[1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
[2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
[2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
[2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
[2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
[2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
[2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
[2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
[3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
[3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
[3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
[3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
[3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
[3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
[4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
[4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
[4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
[4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
[5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
[6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
[6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
[6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
[6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
[7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
[7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
[8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
[8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
[8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
[10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
[11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
[12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
[12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
[12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
[19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
[42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
[42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
[43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
[43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
[43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
[43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
[44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
[57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
[64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
[65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
[65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
for (i = 0; i < ranges.length; i++) {
start = ranges[i][0];
end = ranges[i][1];
for (j = start; j <= end; j++) {
result[j] = true;
}
}
return result;
})();
function splitQuery(query) {
var result = [];
var start = -1;
for (var i = 0; i < query.length; i++) {
if (splitChars[query.charCodeAt(i)]) {
if (start !== -1) {
result.push(query.slice(start, i));
start = -1;
}
} else if (start === -1) {
start = i;
}
}
if (start !== -1) {
result.push(query.slice(start));
}
return result;
} | PypiClean |
/MaterialDjango-0.2.5.tar.gz/MaterialDjango-0.2.5/materialdjango/static/materialdjango/components/bower_components/app-localize-behavior/.github/ISSUE_TEMPLATE.md | <!-- Instructions: https://github.com/PolymerElements/app-localize-behavior/CONTRIBUTING.md#filing-issues -->
### Description
<!-- Example: The `paper-foo` element causes the page to turn pink when clicked. -->
### Expected outcome
<!-- Example: The page stays the same color. -->
### Actual outcome
<!-- Example: The page turns pink. -->
### Live Demo
<!-- Example: https://jsbin.com/cagaye/edit?html,output -->
### Steps to reproduce
<!-- Example
1. Put a `paper-foo` element in the page.
2. Open the page in a web browser.
3. Click the `paper-foo` element.
-->
### Browsers Affected
<!-- Check all that apply -->
- [ ] Chrome
- [ ] Firefox
- [ ] Safari 9
- [ ] Safari 8
- [ ] Safari 7
- [ ] Edge
- [ ] IE 11
- [ ] IE 10
| PypiClean |
/CouchDB-1.2.tar.gz/CouchDB-1.2/couchdb/mapping.py | import copy
from calendar import timegm
from datetime import date, datetime, time
from decimal import Decimal
from time import strptime, struct_time
from couchdb.design import ViewDefinition
from couchdb import util
__all__ = ['Mapping', 'Document', 'Field', 'TextField', 'FloatField',
'IntegerField', 'LongField', 'BooleanField', 'DecimalField',
'DateField', 'DateTimeField', 'TimeField', 'DictField', 'ListField',
'ViewField']
__docformat__ = 'restructuredtext en'
DEFAULT = object()
class Field(object):
"""Basic unit for mapping a piece of data between Python and JSON.
Instances of this class can be added to subclasses of `Document` to describe
the mapping of a document.
"""
def __init__(self, name=None, default=None):
self.name = name
self.default = default
def __get__(self, instance, owner):
if instance is None:
return self
value = instance._data.get(self.name)
if value is not None:
value = self._to_python(value)
elif self.default is not None:
default = self.default
if callable(default):
default = default()
value = default
return value
def __set__(self, instance, value):
if value is not None:
value = self._to_json(value)
instance._data[self.name] = value
def _to_python(self, value):
return util.utype(value)
def _to_json(self, value):
return self._to_python(value)
class MappingMeta(type):
def __new__(cls, name, bases, d):
fields = {}
for base in bases:
if hasattr(base, '_fields'):
fields.update(base._fields)
for attrname, attrval in d.items():
if isinstance(attrval, Field):
if not attrval.name:
attrval.name = attrname
fields[attrname] = attrval
d['_fields'] = fields
return type.__new__(cls, name, bases, d)
MappingMetaClass = MappingMeta('MappingMetaClass', (object,), {})
class Mapping(MappingMetaClass):
def __init__(self, **values):
self._data = {}
for attrname, field in self._fields.items():
if attrname in values:
setattr(self, attrname, values.pop(attrname))
else:
setattr(self, attrname, getattr(self, attrname))
def __iter__(self):
return iter(self._data)
def __len__(self):
return len(self._data or ())
def __delitem__(self, name):
del self._data[name]
def __getitem__(self, name):
return self._data[name]
def __setitem__(self, name, value):
self._data[name] = value
def get(self, name, default=None):
return self._data.get(name, default)
def setdefault(self, name, default):
return self._data.setdefault(name, default)
def unwrap(self):
return self._data
@classmethod
def build(cls, **d):
fields = {}
for attrname, attrval in d.items():
if not attrval.name:
attrval.name = attrname
fields[attrname] = attrval
d['_fields'] = fields
return type('AnonymousStruct', (cls,), d)
@classmethod
def wrap(cls, data):
instance = cls()
instance._data = data
return instance
def _to_python(self, value):
return self.wrap(value)
def _to_json(self, value):
return self.unwrap()
class ViewField(object):
r"""Descriptor that can be used to bind a view definition to a property of
a `Document` class.
>>> class Person(Document):
... name = TextField()
... age = IntegerField()
... by_name = ViewField('people', '''\
... function(doc) {
... emit(doc.name, doc);
... }''')
>>> Person.by_name
<ViewDefinition '_design/people/_view/by_name'>
>>> print(Person.by_name.map_fun)
function(doc) {
emit(doc.name, doc);
}
That property can be used as a function, which will execute the view.
>>> from couchdb import Database
>>> db = Database('python-tests')
>>> Person.by_name(db, count=3)
<ViewResults <PermanentView '_design/people/_view/by_name'> {'count': 3}>
The results produced by the view are automatically wrapped in the
`Document` subclass the descriptor is bound to. In this example, it would
return instances of the `Person` class. But please note that this requires
the values of the view results to be dictionaries that can be mapped to the
mapping defined by the containing `Document` class. Alternatively, the
``include_docs`` query option can be used to inline the actual documents in
the view results, which will then be used instead of the values.
If you use Python view functions, this class can also be used as a
decorator:
>>> class Person(Document):
... name = TextField()
... age = IntegerField()
...
... @ViewField.define('people')
... def by_name(doc):
... yield doc['name'], doc
>>> Person.by_name
<ViewDefinition '_design/people/_view/by_name'>
>>> print(Person.by_name.map_fun)
def by_name(doc):
yield doc['name'], doc
"""
def __init__(self, design, map_fun, reduce_fun=None, name=None,
language='javascript', wrapper=DEFAULT, **defaults):
"""Initialize the view descriptor.
:param design: the name of the design document
:param map_fun: the map function code
:param reduce_fun: the reduce function code (optional)
:param name: the actual name of the view in the design document, if
it differs from the name the descriptor is assigned to
:param language: the name of the language used
:param wrapper: an optional callable that should be used to wrap the
result rows
:param defaults: default query string parameters to apply
"""
self.design = design
self.name = name
self.map_fun = map_fun
self.reduce_fun = reduce_fun
self.language = language
self.wrapper = wrapper
self.defaults = defaults
@classmethod
def define(cls, design, name=None, language='python', wrapper=DEFAULT,
**defaults):
"""Factory method for use as a decorator (only suitable for Python
view code).
"""
def view_wrapped(fun):
return cls(design, fun, language=language, wrapper=wrapper,
**defaults)
return view_wrapped
def __get__(self, instance, cls=None):
if self.wrapper is DEFAULT:
wrapper = cls._wrap_row
else:
wrapper = self.wrapper
return ViewDefinition(self.design, self.name, self.map_fun,
self.reduce_fun, language=self.language,
wrapper=wrapper, **self.defaults)
class DocumentMeta(MappingMeta):
def __new__(cls, name, bases, d):
for attrname, attrval in d.items():
if isinstance(attrval, ViewField):
if not attrval.name:
attrval.name = attrname
return MappingMeta.__new__(cls, name, bases, d)
DocumentMetaClass = DocumentMeta('DocumentMetaClass', (object,), {})
class Document(DocumentMetaClass, Mapping):
def __init__(self, id=None, **values):
Mapping.__init__(self, **values)
if id is not None:
self.id = id
def __repr__(self):
return '<%s %r@%r %r>' % (type(self).__name__, self.id, self.rev,
dict([(k, v) for k, v in self._data.items()
if k not in ('_id', '_rev')]))
def _get_id(self):
if hasattr(self._data, 'id'): # When data is client.Document
return self._data.id
return self._data.get('_id')
def _set_id(self, value):
if self.id is not None:
raise AttributeError('id can only be set on new documents')
self._data['_id'] = value
id = property(_get_id, _set_id, doc='The document ID')
@property
def rev(self):
"""The document revision.
:rtype: basestring
"""
if hasattr(self._data, 'rev'): # When data is client.Document
return self._data.rev
return self._data.get('_rev')
def items(self):
"""Return the fields as a list of ``(name, value)`` tuples.
This method is provided to enable easy conversion to native dictionary
objects, for example to allow use of `mapping.Document` instances with
`client.Database.update`.
>>> class Post(Document):
... title = TextField()
... author = TextField()
>>> post = Post(id='foo-bar', title='Foo bar', author='Joe')
>>> sorted(post.items())
[('_id', 'foo-bar'), ('author', u'Joe'), ('title', u'Foo bar')]
:return: a list of ``(name, value)`` tuples
"""
retval = []
if self.id is not None:
retval.append(('_id', self.id))
if self.rev is not None:
retval.append(('_rev', self.rev))
for name, value in self._data.items():
if name not in ('_id', '_rev'):
retval.append((name, value))
return retval
@classmethod
def load(cls, db, id):
"""Load a specific document from the given database.
:param db: the `Database` object to retrieve the document from
:param id: the document ID
:return: the `Document` instance, or `None` if no document with the
given ID was found
"""
doc = db.get(id)
if doc is None:
return None
return cls.wrap(doc)
def store(self, db):
"""Store the document in the given database."""
db.save(self._data)
return self
@classmethod
def query(cls, db, map_fun, reduce_fun, language='javascript', **options):
"""Execute a CouchDB temporary view and map the result values back to
objects of this mapping.
Note that by default, any properties of the document that are not
included in the values of the view will be treated as if they were
missing from the document. If you want to load the full document for
every row, set the ``include_docs`` option to ``True``.
"""
return db.query(map_fun, reduce_fun=reduce_fun, language=language,
wrapper=cls._wrap_row, **options)
@classmethod
def view(cls, db, viewname, **options):
"""Execute a CouchDB named view and map the result values back to
objects of this mapping.
Note that by default, any properties of the document that are not
included in the values of the view will be treated as if they were
missing from the document. If you want to load the full document for
every row, set the ``include_docs`` option to ``True``.
"""
return db.view(viewname, wrapper=cls._wrap_row, **options)
@classmethod
def _wrap_row(cls, row):
doc = row.get('doc')
if doc is not None:
return cls.wrap(doc)
data = row['value']
data['_id'] = row['id']
if 'rev' in data: # When data is client.Document
data['_rev'] = data['rev']
return cls.wrap(data)
class TextField(Field):
"""Mapping field for string values."""
_to_python = util.utype
class FloatField(Field):
"""Mapping field for float values."""
_to_python = float
class IntegerField(Field):
"""Mapping field for integer values."""
_to_python = int
class LongField(Field):
"""Mapping field for long integer values."""
_to_python = util.ltype
class BooleanField(Field):
"""Mapping field for boolean values."""
_to_python = bool
class DecimalField(Field):
"""Mapping field for decimal values."""
def _to_python(self, value):
return Decimal(value)
def _to_json(self, value):
return util.utype(value)
class DateField(Field):
"""Mapping field for storing dates.
>>> field = DateField()
>>> field._to_python('2007-04-01')
datetime.date(2007, 4, 1)
>>> field._to_json(date(2007, 4, 1))
'2007-04-01'
>>> field._to_json(datetime(2007, 4, 1, 15, 30))
'2007-04-01'
"""
def _to_python(self, value):
if isinstance(value, util.strbase):
try:
value = date(*strptime(value, '%Y-%m-%d')[:3])
except ValueError:
raise ValueError('Invalid ISO date %r' % value)
return value
def _to_json(self, value):
if isinstance(value, datetime):
value = value.date()
return value.isoformat()
class DateTimeField(Field):
"""Mapping field for storing date/time values.
>>> field = DateTimeField()
>>> field._to_python('2007-04-01T15:30:00Z')
datetime.datetime(2007, 4, 1, 15, 30)
>>> field._to_python('2007-04-01T15:30:00.009876Z')
datetime.datetime(2007, 4, 1, 15, 30, 0, 9876)
>>> field._to_json(datetime(2007, 4, 1, 15, 30, 0))
'2007-04-01T15:30:00Z'
>>> field._to_json(datetime(2007, 4, 1, 15, 30, 0, 9876))
'2007-04-01T15:30:00.009876Z'
>>> field._to_json(date(2007, 4, 1))
'2007-04-01T00:00:00Z'
"""
def _to_python(self, value):
if isinstance(value, util.strbase):
try:
split_value = value.split('.') # strip out microseconds
if len(split_value) == 1: # No microseconds provided
value = split_value[0]
value = value.rstrip('Z') #remove timezone separator
value = datetime.strptime(value, '%Y-%m-%dT%H:%M:%S')
else:
value = value.rstrip('Z')
value = datetime.strptime(value, '%Y-%m-%dT%H:%M:%S.%f')
except ValueError:
raise ValueError('Invalid ISO date/time %r' % value)
return value
def _to_json(self, value):
if isinstance(value, struct_time):
value = datetime.utcfromtimestamp(timegm(value))
elif not isinstance(value, datetime):
value = datetime.combine(value, time(0))
return value.isoformat() + 'Z'
class TimeField(Field):
"""Mapping field for storing times.
>>> field = TimeField()
>>> field._to_python('15:30:00')
datetime.time(15, 30)
>>> field._to_json(time(15, 30))
'15:30:00'
>>> field._to_json(datetime(2007, 4, 1, 15, 30))
'15:30:00'
"""
def _to_python(self, value):
if isinstance(value, util.strbase):
try:
value = value.split('.', 1)[0] # strip out microseconds
value = time(*strptime(value, '%H:%M:%S')[3:6])
except ValueError:
raise ValueError('Invalid ISO time %r' % value)
return value
def _to_json(self, value):
if isinstance(value, datetime):
value = value.time()
return value.replace(microsecond=0).isoformat()
class DictField(Field):
"""Field type for nested dictionaries.
>>> from couchdb import Server
>>> server = Server()
>>> db = server.create('python-tests')
>>> class Post(Document):
... title = TextField()
... content = TextField()
... author = DictField(Mapping.build(
... name = TextField(),
... email = TextField()
... ))
... extra = DictField()
>>> post = Post(
... title='Foo bar',
... author=dict(name='John Doe',
... email='[email protected]'),
... extra=dict(foo='bar'),
... )
>>> post.store(db) #doctest: +ELLIPSIS
<Post ...>
>>> post = Post.load(db, post.id)
>>> post.author.name
u'John Doe'
>>> post.author.email
u'[email protected]'
>>> post.extra
{u'foo': u'bar'}
>>> del server['python-tests']
"""
def __init__(self, mapping=None, name=None, default=None):
default = default or {}
Field.__init__(self, name=name, default=lambda: default.copy())
self.mapping = mapping
def _to_python(self, value):
if self.mapping is None:
return value
else:
return self.mapping.wrap(value)
def _to_json(self, value):
if self.mapping is None:
return value
if not isinstance(value, Mapping):
value = self.mapping(**value)
return value.unwrap()
class ListField(Field):
"""Field type for sequences of other fields.
>>> from couchdb import Server
>>> server = Server()
>>> db = server.create('python-tests')
>>> class Post(Document):
... title = TextField()
... content = TextField()
... pubdate = DateTimeField(default=datetime.now)
... comments = ListField(DictField(Mapping.build(
... author = TextField(),
... content = TextField(),
... time = DateTimeField()
... )))
>>> post = Post(title='Foo bar')
>>> post.comments.append(author='myself', content='Bla bla',
... time=datetime.now())
>>> len(post.comments)
1
>>> post.store(db) #doctest: +ELLIPSIS
<Post ...>
>>> post = Post.load(db, post.id)
>>> comment = post.comments[0]
>>> comment['author']
u'myself'
>>> comment['content']
u'Bla bla'
>>> comment['time'] #doctest: +ELLIPSIS
u'...T...Z'
>>> del server['python-tests']
"""
def __init__(self, field, name=None, default=None):
default = default or []
Field.__init__(self, name=name, default=lambda: copy.copy(default))
if type(field) is type:
if issubclass(field, Field):
field = field()
elif issubclass(field, Mapping):
field = DictField(field)
self.field = field
def _to_python(self, value):
return self.Proxy(value, self.field)
def _to_json(self, value):
return [self.field._to_json(item) for item in value]
class Proxy(list):
def __init__(self, list, field):
self.list = list
self.field = field
def __lt__(self, other):
return self.list < other
def __le__(self, other):
return self.list <= other
def __eq__(self, other):
return self.list == other
def __ne__(self, other):
return self.list != other
def __gt__(self, other):
return self.list > other
def __ge__(self, other):
return self.list >= other
def __repr__(self):
return repr(self.list)
def __str__(self):
return str(self.list)
def __unicode__(self):
return util.utype(self.list)
def __delitem__(self, index):
if isinstance(index, slice):
self.__delslice__(index.start, index.stop)
else:
del self.list[index]
def __getitem__(self, index):
if isinstance(index, slice):
return self.__getslice__(index.start, index.stop)
return self.field._to_python(self.list[index])
def __setitem__(self, index, value):
if isinstance(index, slice):
self.__setslice__(index.start, index.stop, value)
else:
self.list[index] = self.field._to_json(value)
def __delslice__(self, i, j):
del self.list[i:j]
def __getslice__(self, i, j):
return ListField.Proxy(self.list[i:j], self.field)
def __setslice__(self, i, j, seq):
self.list[i:j] = (self.field._to_json(v) for v in seq)
def __contains__(self, value):
for item in self.list:
if self.field._to_python(item) == value:
return True
return False
def __iter__(self):
for index in range(len(self)):
yield self[index]
def __len__(self):
return len(self.list)
def __nonzero__(self):
return bool(self.list)
def append(self, *args, **kwargs):
if args or not isinstance(self.field, DictField):
if len(args) != 1:
raise TypeError('append() takes exactly one argument '
'(%s given)' % len(args))
value = args[0]
else:
value = kwargs
self.list.append(self.field._to_json(value))
def count(self, value):
return [i for i in self].count(value)
def extend(self, list):
for item in list:
self.append(item)
def index(self, value):
return self.list.index(self.field._to_json(value))
def insert(self, idx, *args, **kwargs):
if args or not isinstance(self.field, DictField):
if len(args) != 1:
raise TypeError('insert() takes exactly 2 arguments '
'(%s given)' % len(args))
value = args[0]
else:
value = kwargs
self.list.insert(idx, self.field._to_json(value))
def remove(self, value):
return self.list.remove(self.field._to_json(value))
def pop(self, *args):
return self.field._to_python(self.list.pop(*args)) | PypiClean |
/Captcha-Impulse-0.0.9.tar.gz/Captcha-Impulse-0.0.9/src/impulse/yolov5/utils/general.py | import contextlib
import glob
import logging
import math
import os
import platform
import random
import re
import shutil
import signal
import time
import urllib
from itertools import repeat
from multiprocessing.pool import ThreadPool
from pathlib import Path
from subprocess import check_output
from zipfile import ZipFile
import cv2
import numpy as np
import pandas as pd
import pkg_resources as pkg
import torch
import torchvision
import yaml
from utils.downloads import gsutil_getsize
from utils.metrics import box_iou, fitness
# Settings
FILE = Path(__file__).resolve()
ROOT = FILE.parents[1] # YOLOv5 root directory
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
VERBOSE = str(os.getenv('VERBOSE', True)).lower() == 'true' # global verbose mode
torch.set_printoptions(linewidth=320, precision=5, profile='long')
np.set_printoptions(linewidth=320, formatter={'float_kind': '{:11.5g}'.format}) # format short g, %precision=5
pd.options.display.max_columns = 10
cv2.setNumThreads(0) # prevent OpenCV from multithreading (incompatible with PyTorch DataLoader)
os.environ['NUMEXPR_MAX_THREADS'] = str(NUM_THREADS) # NumExpr max threads
def is_kaggle():
# Is environment a Kaggle Notebook?
try:
assert os.environ.get('PWD') == '/kaggle/working'
assert os.environ.get('KAGGLE_URL_BASE') == 'https://www.kaggle.com'
return True
except AssertionError:
return False
def set_logging(name=None, verbose=VERBOSE):
# Sets level and returns logger
if is_kaggle():
for h in logging.root.handlers:
logging.root.removeHandler(h) # remove all handlers associated with the root logger object
rank = int(os.getenv('RANK', -1)) # rank in world for Multi-GPU trainings
logging.basicConfig(format="%(message)s", level=logging.INFO if (verbose and rank in (-1, 0)) else logging.WARNING)
return logging.getLogger(name)
LOGGER = set_logging(__name__) # define globally (used in train.py, val.py, detect.py, etc.)
class Profile(contextlib.ContextDecorator):
# Usage: @Profile() decorator or 'with Profile():' context manager
def __enter__(self):
self.start = time.time()
def __exit__(self, type, value, traceback):
print(f'Profile results: {time.time() - self.start:.5f}s')
class Timeout(contextlib.ContextDecorator):
# Usage: @Timeout(seconds) decorator or 'with Timeout(seconds):' context manager
def __init__(self, seconds, *, timeout_msg='', suppress_timeout_errors=True):
self.seconds = int(seconds)
self.timeout_message = timeout_msg
self.suppress = bool(suppress_timeout_errors)
def _timeout_handler(self, signum, frame):
raise TimeoutError(self.timeout_message)
def __enter__(self):
signal.signal(signal.SIGALRM, self._timeout_handler) # Set handler for SIGALRM
signal.alarm(self.seconds) # start countdown for SIGALRM to be raised
def __exit__(self, exc_type, exc_val, exc_tb):
signal.alarm(0) # Cancel SIGALRM if it's scheduled
if self.suppress and exc_type is TimeoutError: # Suppress TimeoutError
return True
class WorkingDirectory(contextlib.ContextDecorator):
# Usage: @WorkingDirectory(dir) decorator or 'with WorkingDirectory(dir):' context manager
def __init__(self, new_dir):
self.dir = new_dir # new dir
self.cwd = Path.cwd().resolve() # current dir
def __enter__(self):
os.chdir(self.dir)
def __exit__(self, exc_type, exc_val, exc_tb):
os.chdir(self.cwd)
def try_except(func):
# try-except function. Usage: @try_except decorator
def handler(*args, **kwargs):
try:
func(*args, **kwargs)
except Exception as e:
print(e)
return handler
def methods(instance):
# Get class/instance methods
return [f for f in dir(instance) if callable(getattr(instance, f)) and not f.startswith("__")]
def print_args(name, opt):
# Print argparser arguments
LOGGER.info(colorstr(f'{name}: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
def init_seeds(seed=0):
# Initialize random number generator (RNG) seeds https://pytorch.org/docs/stable/notes/randomness.html
# cudnn seed 0 settings are slower and more reproducible, else faster and less reproducible
import torch.backends.cudnn as cudnn
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
cudnn.benchmark, cudnn.deterministic = (False, True) if seed == 0 else (True, False)
def intersect_dicts(da, db, exclude=()):
# Dictionary intersection of matching keys and shapes, omitting 'exclude' keys, using da values
return {k: v for k, v in da.items() if k in db and not any(x in k for x in exclude) and v.shape == db[k].shape}
def get_latest_run(search_dir='.'):
# Return path to most recent 'last.pt' in /runs (i.e. to --resume from)
last_list = glob.glob(f'{search_dir}/**/last*.pt', recursive=True)
return max(last_list, key=os.path.getctime) if last_list else ''
def user_config_dir(dir='Ultralytics', env_var='YOLOV5_CONFIG_DIR'):
# Return path of user configuration directory. Prefer environment variable if exists. Make dir if required.
env = os.getenv(env_var)
if env:
path = Path(env) # use environment variable
else:
cfg = {'Windows': 'AppData/Roaming', 'Linux': '.config', 'Darwin': 'Library/Application Support'} # 3 OS dirs
path = Path.home() / cfg.get(platform.system(), '') # OS-specific config dir
path = (path if is_writeable(path) else Path('/tmp')) / dir # GCP and AWS lambda fix, only /tmp is writeable
path.mkdir(exist_ok=True) # make if required
return path
def is_writeable(dir, test=False):
# Return True if directory has write permissions, test opening a file with write permissions if test=True
if test: # method 1
file = Path(dir) / 'tmp.txt'
try:
with open(file, 'w'): # open file with write permissions
pass
file.unlink() # remove file
return True
except OSError:
return False
else: # method 2
return os.access(dir, os.R_OK) # possible issues on Windows
def is_docker():
# Is environment a Docker container?
return Path('/workspace').exists() # or Path('/.dockerenv').exists()
def is_colab():
# Is environment a Google Colab instance?
try:
import google.colab
return True
except ImportError:
return False
def is_pip():
# Is file in a pip package?
return 'site-packages' in Path(__file__).resolve().parts
def is_ascii(s=''):
# Is string composed of all ASCII (no UTF) characters? (note str().isascii() introduced in python 3.7)
s = str(s) # convert list, tuple, None, etc. to str
return len(s.encode().decode('ascii', 'ignore')) == len(s)
def is_chinese(s='人工智能'):
# Is string composed of any Chinese characters?
return re.search('[\u4e00-\u9fff]', s)
def emojis(str=''):
# Return platform-dependent emoji-safe version of string
return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str
def file_size(path):
# Return file/dir size (MB)
path = Path(path)
if path.is_file():
return path.stat().st_size / 1E6
elif path.is_dir():
return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / 1E6
else:
return 0.0
def check_online():
# Check internet connectivity
import socket
try:
socket.create_connection(("1.1.1.1", 443), 5) # check host accessibility
return True
except OSError:
return False
@try_except
@WorkingDirectory(ROOT)
def check_git_status():
# Recommend 'git pull' if code is out of date
msg = ', for updates see https://github.com/ultralytics/yolov5'
print(colorstr('github: '), end='')
assert Path('.git').exists(), 'skipping check (not a git repository)' + msg
assert not is_docker(), 'skipping check (Docker image)' + msg
assert check_online(), 'skipping check (offline)' + msg
cmd = 'git fetch && git config --get remote.origin.url'
url = check_output(cmd, shell=True, timeout=5).decode().strip().rstrip('.git') # git fetch
branch = check_output('git rev-parse --abbrev-ref HEAD', shell=True).decode().strip() # checked out
n = int(check_output(f'git rev-list {branch}..origin/master --count', shell=True)) # commits behind
if n > 0:
s = f"⚠️ YOLOv5 is out of date by {n} commit{'s' * (n > 1)}. Use `git pull` or `git clone {url}` to update."
else:
s = f'up to date with {url} ✅'
print(emojis(s)) # emoji-safe
def check_python(minimum='3.6.2'):
# Check current python version vs. required python version
check_version(platform.python_version(), minimum, name='Python ', hard=True)
def check_version(current='0.0.0', minimum='0.0.0', name='version ', pinned=False, hard=False, verbose=False):
# Check version vs. required version
current, minimum = (pkg.parse_version(x) for x in (current, minimum))
result = (current == minimum) if pinned else (current >= minimum) # bool
s = f'{name}{minimum} required by YOLOv5, but {name}{current} is currently installed' # string
if hard:
assert result, s # assert min requirements met
if verbose and not result:
LOGGER.warning(s)
return result
def check_img_size(imgsz, s=32, floor=0):
# Verify image size is a multiple of stride s in each dimension
if isinstance(imgsz, int): # integer i.e. img_size=640
new_size = max(make_divisible(imgsz, int(s)), floor)
else: # list i.e. img_size=[640, 480]
new_size = [max(make_divisible(x, int(s)), floor) for x in imgsz]
# if new_size != imgsz:
# print(f'WARNING: --img-size {imgsz} must be multiple of max stride {s}, updating to {new_size}')
return new_size
def check_imshow():
# Check if environment supports image displays
try:
assert not is_docker(), 'cv2.imshow() is disabled in Docker environments'
assert not is_colab(), 'cv2.imshow() is disabled in Google Colab environments'
cv2.imshow('test', np.zeros((1, 1, 3)))
cv2.waitKey(1)
cv2.destroyAllWindows()
cv2.waitKey(1)
return True
except Exception as e:
print(f'WARNING: Environment does not support cv2.imshow() or PIL Image.show() image displays\n{e}')
return False
def check_suffix(file='yolov5s.pt', suffix=('.pt',), msg=''):
# Check file(s) for acceptable suffix
if file and suffix:
if isinstance(suffix, str):
suffix = [suffix]
for f in file if isinstance(file, (list, tuple)) else [file]:
s = Path(f).suffix.lower() # file suffix
if len(s):
assert s in suffix, f"{msg}{f} acceptable suffix is {suffix}"
def check_yaml(file, suffix=('.yaml', '.yml')):
# Search/download YAML file (if necessary) and return path, checking suffix
return check_file(file, suffix)
def check_file(file, suffix='', add_suffix=False):
# Search/download file (if necessary) and return path
check_suffix(file, suffix) # optional
file = str(file) # convert to str()
file += "" if not add_suffix else ".png"
if Path(file).is_file() or file == '': # exists
return file
elif file.startswith(('http:/', 'https:/')): # download
url = file
if add_suffix:
url = url[:-4]
file = Path(urllib.parse.unquote(file).split('?')[0]).name # '%2F' to '/', split https://url.com/file.txt?auth
if Path(file).is_file():
print(f'Found {url} locally at {file}') # file already exists
else:
LOGGER.info(f'Downloading {url} to {file}...')
torch.hub.download_url_to_file(url, file, progress=False)
assert Path(file).exists() and Path(file).stat().st_size > 0, f'File download failed: {url}' # check
return file
else: # search
files = []
for d in 'data', 'models', 'utils': # search directories
files.extend(glob.glob(str(ROOT / d / '**' / file), recursive=True)) # find file
assert len(files), f'File not found: {file}' # assert file was found
assert len(files) == 1, f"Multiple files match '{file}', specify exact path: {files}" # assert unique
return files[0] # return file
def check_dataset(data, autodownload=True):
# Download and/or unzip dataset if not found locally
# Usage: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128_with_yaml.zip
# Download (optional)
extract_dir = ''
if isinstance(data, (str, Path)) and str(data).endswith('.zip'): # i.e. gs://bucket/dir/coco128.zip
download(data, dir='../datasets', unzip=True, delete=False, curl=False, threads=1)
data = next((Path('../datasets') / Path(data).stem).rglob('*.yaml'))
extract_dir, autodownload = data.parent, False
# Read yaml (optional)
if isinstance(data, (str, Path)):
with open(data, errors='ignore') as f:
data = yaml.safe_load(f) # dictionary
# Parse yaml
path = extract_dir or Path(data.get('path') or '') # optional 'path' default to '.'
for k in 'train', 'val', 'test':
if data.get(k): # prepend path
data[k] = str(path / data[k]) if isinstance(data[k], str) else [str(path / x) for x in data[k]]
assert 'nc' in data, "Dataset 'nc' key missing."
if 'names' not in data:
data['names'] = [f'class{i}' for i in range(data['nc'])] # assign class names if missing
train, val, test, s = (data.get(x) for x in ('train', 'val', 'test', 'download'))
if val:
val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])] # val path
if not all(x.exists() for x in val):
print('\nWARNING: Dataset not found, nonexistent paths: %s' % [str(x) for x in val if not x.exists()])
if s and autodownload: # download script
root = path.parent if 'path' in data else '..' # unzip directory i.e. '../'
if s.startswith('http') and s.endswith('.zip'): # URL
f = Path(s).name # filename
LOGGER.info(f'Downloading {s} to {f}...')
torch.hub.download_url_to_file(s, f, progress=False)
Path(root).mkdir(parents=True, exist_ok=True) # create root
ZipFile(f).extractall(path=root) # unzip
Path(f).unlink() # remove zip
r = None # success
elif s.startswith('bash '): # bash script
print(f'Running {s} ...')
r = os.system(s)
else: # python script
r = exec(s, {'yaml': data}) # return None
print(f"Dataset autodownload {f'success, saved to {root}' if r in (0, None) else 'failure'}\n")
else:
raise Exception('Dataset not found.')
return data # dictionary
def url2file(url):
# Convert URL to filename, i.e. https://url.com/file.txt?auth -> file.txt
url = str(Path(url)).replace(':/', '://') # Pathlib turns :// -> :/
file = Path(urllib.parse.unquote(url)).name.split('?')[0] # '%2F' to '/', split https://url.com/file.txt?auth
return file
def download(url, dir='.', unzip=True, delete=True, curl=False, threads=1):
# Multi-threaded file download and unzip function, used in data.yaml for autodownload
def download_one(url, dir):
# Download 1 file
f = dir / Path(url).name # filename
if Path(url).is_file(): # exists in current path
Path(url).rename(f) # move to dir
elif not f.exists():
LOGGER.info(f'Downloading {url} to {f}...')
if curl:
os.system(f"curl -L '{url}' -o '{f}' --retry 9 -C -") # curl download, retry and resume on fail
else:
torch.hub.download_url_to_file(url, f, progress=True) # torch download
if unzip and f.suffix in ('.zip', '.gz'):
print(f'Unzipping {f}...')
if f.suffix == '.zip':
ZipFile(f).extractall(path=dir) # unzip
elif f.suffix == '.gz':
os.system(f'tar xfz {f} --directory {f.parent}') # unzip
if delete:
f.unlink() # remove zip
dir = Path(dir)
dir.mkdir(parents=True, exist_ok=True) # make directory
if threads > 1:
pool = ThreadPool(threads)
pool.imap(lambda x: download_one(*x), zip(url, repeat(dir))) # multi-threaded
pool.close()
pool.join()
else:
for u in [url] if isinstance(url, (str, Path)) else url:
download_one(u, dir)
def make_divisible(x, divisor):
# Returns nearest x divisible by divisor
if isinstance(divisor, torch.Tensor):
divisor = int(divisor.max()) # to int
return math.ceil(x / divisor) * divisor
def clean_str(s):
# Cleans a string by replacing special characters with underscore _
return re.sub(pattern="[|@#!¡·$€%&()=?¿^*;:,¨´><+]", repl="_", string=s)
def one_cycle(y1=0.0, y2=1.0, steps=100):
# lambda function for sinusoidal ramp from y1 to y2 https://arxiv.org/pdf/1812.01187.pdf
return lambda x: ((1 - math.cos(x * math.pi / steps)) / 2) * (y2 - y1) + y1
def colorstr(*input):
# Colors a string https://en.wikipedia.org/wiki/ANSI_escape_code, i.e. colorstr('blue', 'hello world')
*args, string = input if len(input) > 1 else ('blue', 'bold', input[0]) # color arguments, string
colors = {'black': '\033[30m', # basic colors
'red': '\033[31m',
'green': '\033[32m',
'yellow': '\033[33m',
'blue': '\033[34m',
'magenta': '\033[35m',
'cyan': '\033[36m',
'white': '\033[37m',
'bright_black': '\033[90m', # bright colors
'bright_red': '\033[91m',
'bright_green': '\033[92m',
'bright_yellow': '\033[93m',
'bright_blue': '\033[94m',
'bright_magenta': '\033[95m',
'bright_cyan': '\033[96m',
'bright_white': '\033[97m',
'end': '\033[0m', # misc
'bold': '\033[1m',
'underline': '\033[4m'}
return ''.join(colors[x] for x in args) + f'{string}' + colors['end']
def labels_to_class_weights(labels, nc=80):
# Get class weights (inverse frequency) from training labels
if labels[0] is None: # no labels loaded
return torch.Tensor()
labels = np.concatenate(labels, 0) # labels.shape = (866643, 5) for COCO
classes = labels[:, 0].astype(np.int) # labels = [class xywh]
weights = np.bincount(classes, minlength=nc) # occurrences per class
# Prepend gridpoint count (for uCE training)
# gpi = ((320 / 32 * np.array([1, 2, 4])) ** 2 * 3).sum() # gridpoints per image
# weights = np.hstack([gpi * len(labels) - weights.sum() * 9, weights * 9]) ** 0.5 # prepend gridpoints to start
weights[weights == 0] = 1 # replace empty bins with 1
weights = 1 / weights # number of targets per class
weights /= weights.sum() # normalize
return torch.from_numpy(weights)
def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
# Produces image weights based on class_weights and image contents
class_counts = np.array([np.bincount(x[:, 0].astype(np.int), minlength=nc) for x in labels])
image_weights = (class_weights.reshape(1, nc) * class_counts).sum(1)
# index = random.choices(range(n), weights=image_weights, k=1) # weight image sample
return image_weights
def coco80_to_coco91_class(): # converts 80-index (val2014) to 91-index (paper)
# https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/
# a = np.loadtxt('data/coco.names', dtype='str', delimiter='\n')
# b = np.loadtxt('data/coco_paper.names', dtype='str', delimiter='\n')
# x1 = [list(a[i] == b).index(True) + 1 for i in range(80)] # darknet to coco
# x2 = [list(b[i] == a).index(True) if any(b[i] == a) else None for i in range(91)] # coco to darknet
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 67, 70, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 90]
return x
def xyxy2xywh(x):
# Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] where xy1=top-left, xy2=bottom-right
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = (x[:, 0] + x[:, 2]) / 2 # x center
y[:, 1] = (x[:, 1] + x[:, 3]) / 2 # y center
y[:, 2] = x[:, 2] - x[:, 0] # width
y[:, 3] = x[:, 3] - x[:, 1] # height
return y
def xywh2xyxy(x):
# Convert nx4 boxes from [x, y, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = x[:, 0] - x[:, 2] / 2 # top left x
y[:, 1] = x[:, 1] - x[:, 3] / 2 # top left y
y[:, 2] = x[:, 0] + x[:, 2] / 2 # bottom right x
y[:, 3] = x[:, 1] + x[:, 3] / 2 # bottom right y
return y
def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
# Convert nx4 boxes from [x, y, w, h] normalized to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = w * (x[:, 0] - x[:, 2] / 2) + padw # top left x
y[:, 1] = h * (x[:, 1] - x[:, 3] / 2) + padh # top left y
y[:, 2] = w * (x[:, 0] + x[:, 2] / 2) + padw # bottom right x
y[:, 3] = h * (x[:, 1] + x[:, 3] / 2) + padh # bottom right y
return y
def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
# Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] normalized where xy1=top-left, xy2=bottom-right
if clip:
clip_coords(x, (h - eps, w - eps)) # warning: inplace clip
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = ((x[:, 0] + x[:, 2]) / 2) / w # x center
y[:, 1] = ((x[:, 1] + x[:, 3]) / 2) / h # y center
y[:, 2] = (x[:, 2] - x[:, 0]) / w # width
y[:, 3] = (x[:, 3] - x[:, 1]) / h # height
return y
def xyn2xy(x, w=640, h=640, padw=0, padh=0):
# Convert normalized segments into pixel segments, shape (n,2)
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = w * x[:, 0] + padw # top left x
y[:, 1] = h * x[:, 1] + padh # top left y
return y
def segment2box(segment, width=640, height=640):
# Convert 1 segment label to 1 box label, applying inside-image constraint, i.e. (xy1, xy2, ...) to (xyxy)
x, y = segment.T # segment xy
inside = (x >= 0) & (y >= 0) & (x <= width) & (y <= height)
x, y, = x[inside], y[inside]
return np.array([x.min(), y.min(), x.max(), y.max()]) if any(x) else np.zeros((1, 4)) # xyxy
def segments2boxes(segments):
# Convert segment labels to box labels, i.e. (cls, xy1, xy2, ...) to (cls, xywh)
boxes = []
for s in segments:
x, y = s.T # segment xy
boxes.append([x.min(), y.min(), x.max(), y.max()]) # cls, xyxy
return xyxy2xywh(np.array(boxes)) # cls, xywh
def resample_segments(segments, n=1000):
# Up-sample an (n,2) segment
for i, s in enumerate(segments):
x = np.linspace(0, len(s) - 1, n)
xp = np.arange(len(s))
segments[i] = np.concatenate([np.interp(x, xp, s[:, i]) for i in range(2)]).reshape(2, -1).T # segment xy
return segments
def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
# Rescale coords (xyxy) from img1_shape to img0_shape
if ratio_pad is None: # calculate from img0_shape
gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1]) # gain = old / new
pad = (img1_shape[1] - img0_shape[1] * gain) / 2, (img1_shape[0] - img0_shape[0] * gain) / 2 # wh padding
else:
gain = ratio_pad[0][0]
pad = ratio_pad[1]
coords[:, [0, 2]] -= pad[0] # x padding
coords[:, [1, 3]] -= pad[1] # y padding
coords[:, :4] /= gain
clip_coords(coords, img0_shape)
return coords
def clip_coords(boxes, shape):
# Clip bounding xyxy bounding boxes to image shape (height, width)
if isinstance(boxes, torch.Tensor): # faster individually
boxes[:, 0].clamp_(0, shape[1]) # x1
boxes[:, 1].clamp_(0, shape[0]) # y1
boxes[:, 2].clamp_(0, shape[1]) # x2
boxes[:, 3].clamp_(0, shape[0]) # y2
else: # np.array (faster grouped)
boxes[:, [0, 2]] = boxes[:, [0, 2]].clip(0, shape[1]) # x1, x2
boxes[:, [1, 3]] = boxes[:, [1, 3]].clip(0, shape[0]) # y1, y2
def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False,
labels=(), max_det=300):
"""Runs Non-Maximum Suppression (NMS) on inference results
Returns:
list of detections, on (n,6) tensor per image [xyxy, conf, cls]
"""
nc = prediction.shape[2] - 5 # number of classes
xc = prediction[..., 4] > conf_thres # candidates
# Checks
assert 0 <= conf_thres <= 1, f'Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0'
assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
# Settings
min_wh, max_wh = 2, 7680 # (pixels) minimum and maximum box width and height
max_nms = 30000 # maximum number of boxes into torchvision.ops.nms()
time_limit = 10.0 # seconds to quit after
redundant = True # require redundant detections
multi_label &= nc > 1 # multiple labels per box (adds 0.5ms/img)
merge = False # use merge-NMS
t = time.time()
output = [torch.zeros((0, 6), device=prediction.device)] * prediction.shape[0]
for xi, x in enumerate(prediction): # image index, image inference
# Apply constraints
# x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0 # width-height
x = x[xc[xi]] # confidence
# Cat apriori labels if autolabelling
if labels and len(labels[xi]):
l = labels[xi]
v = torch.zeros((len(l), nc + 5), device=x.device)
v[:, :4] = l[:, 1:5] # box
v[:, 4] = 1.0 # conf
v[range(len(l)), l[:, 0].long() + 5] = 1.0 # cls
x = torch.cat((x, v), 0)
# If none remain process next image
if not x.shape[0]:
continue
# Compute conf
x[:, 5:] *= x[:, 4:5] # conf = obj_conf * cls_conf
# Box (center x, center y, width, height) to (x1, y1, x2, y2)
box = xywh2xyxy(x[:, :4])
# Detections matrix nx6 (xyxy, conf, cls)
if multi_label:
i, j = (x[:, 5:] > conf_thres).nonzero(as_tuple=False).T
x = torch.cat((box[i], x[i, j + 5, None], j[:, None].float()), 1)
else: # best class only
conf, j = x[:, 5:].max(1, keepdim=True)
x = torch.cat((box, conf, j.float()), 1)[conf.view(-1) > conf_thres]
# Filter by class
if classes is not None:
x = x[(x[:, 5:6] == torch.tensor(classes, device=x.device)).any(1)]
# Apply finite constraint
# if not torch.isfinite(x).all():
# x = x[torch.isfinite(x).all(1)]
# Check shape
n = x.shape[0] # number of boxes
if not n: # no boxes
continue
elif n > max_nms: # excess boxes
x = x[x[:, 4].argsort(descending=True)[:max_nms]] # sort by confidence
# Batched NMS
c = x[:, 5:6] * (0 if agnostic else max_wh) # classes
boxes, scores = x[:, :4] + c, x[:, 4] # boxes (offset by class), scores
i = torchvision.ops.nms(boxes, scores, iou_thres) # NMS
if i.shape[0] > max_det: # limit detections
i = i[:max_det]
if merge and (1 < n < 3E3): # Merge NMS (boxes merged using weighted mean)
# update boxes as boxes(i,4) = weights(i,n) * boxes(n,4)
iou = box_iou(boxes[i], boxes) > iou_thres # iou matrix
weights = iou * scores[None] # box weights
x[i, :4] = torch.mm(weights, x[:, :4]).float() / weights.sum(1, keepdim=True) # merged boxes
if redundant:
i = i[iou.sum(1) > 1] # require redundancy
output[xi] = x[i]
if (time.time() - t) > time_limit:
print(f'WARNING: NMS time limit {time_limit}s exceeded')
break # time limit exceeded
return output
def strip_optimizer(f='best.pt', s=''): # from utils.general import *; strip_optimizer()
# Strip optimizer from 'f' to finalize training, optionally save as 's'
x = torch.load(f, map_location=torch.device('cpu'))
if x.get('ema'):
x['model'] = x['ema'] # replace model with ema
for k in 'optimizer', 'best_fitness', 'wandb_id', 'ema', 'updates': # keys
x[k] = None
x['epoch'] = -1
x['model'].half() # to FP16
for p in x['model'].parameters():
p.requires_grad = False
torch.save(x, s or f)
mb = os.path.getsize(s or f) / 1E6 # filesize
print(f"Optimizer stripped from {f},{(' saved as %s,' % s) if s else ''} {mb:.1f}MB")
def print_mutation(results, hyp, save_dir, bucket):
evolve_csv, results_csv, evolve_yaml = save_dir / 'evolve.csv', save_dir / 'results.csv', save_dir / 'hyp_evolve.yaml'
keys = ('metrics/precision', 'metrics/recall', 'metrics/mAP_0.5', 'metrics/mAP_0.5:0.95',
'val/box_loss', 'val/obj_loss', 'val/cls_loss') + tuple(hyp.keys()) # [results + hyps]
keys = tuple(x.strip() for x in keys)
vals = results + tuple(hyp.values())
n = len(keys)
# Download (optional)
if bucket:
url = f'gs://{bucket}/evolve.csv'
if gsutil_getsize(url) > (os.path.getsize(evolve_csv) if os.path.exists(evolve_csv) else 0):
os.system(f'gsutil cp {url} {save_dir}') # download evolve.csv if larger than local
# Log to evolve.csv
s = '' if evolve_csv.exists() else (('%20s,' * n % keys).rstrip(',') + '\n') # add header
with open(evolve_csv, 'a') as f:
f.write(s + ('%20.5g,' * n % vals).rstrip(',') + '\n')
# Print to screen
print(colorstr('evolve: ') + ', '.join(f'{x.strip():>20s}' for x in keys))
print(colorstr('evolve: ') + ', '.join(f'{x:20.5g}' for x in vals), end='\n\n\n')
# Save yaml
with open(evolve_yaml, 'w') as f:
data = pd.read_csv(evolve_csv)
data = data.rename(columns=lambda x: x.strip()) # strip keys
i = np.argmax(fitness(data.values[:, :7])) #
f.write('# YOLOv5 Hyperparameter Evolution Results\n' +
f'# Best generation: {i}\n' +
f'# Last generation: {len(data) - 1}\n' +
'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' +
'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
yaml.safe_dump(hyp, f, sort_keys=False)
if bucket:
os.system(f'gsutil cp {evolve_csv} {evolve_yaml} gs://{bucket}') # upload
def apply_classifier(x, model, img, im0):
# Apply a second stage classifier to YOLO outputs
# Example model = torchvision.models.__dict__['efficientnet_b0'](pretrained=True).to(device).eval()
im0 = [im0] if isinstance(im0, np.ndarray) else im0
for i, d in enumerate(x): # per image
if d is not None and len(d):
d = d.clone()
# Reshape and pad cutouts
b = xyxy2xywh(d[:, :4]) # boxes
b[:, 2:] = b[:, 2:].max(1)[0].unsqueeze(1) # rectangle to square
b[:, 2:] = b[:, 2:] * 1.3 + 30 # pad
d[:, :4] = xywh2xyxy(b).long()
# Rescale boxes from img_size to im0 size
scale_coords(img.shape[2:], d[:, :4], im0[i].shape)
# Classes
pred_cls1 = d[:, 5].long()
ims = []
for j, a in enumerate(d): # per item
cutout = im0[i][int(a[1]):int(a[3]), int(a[0]):int(a[2])]
im = cv2.resize(cutout, (224, 224)) # BGR
# cv2.imwrite('example%i.jpg' % j, cutout)
im = im[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416
im = np.ascontiguousarray(im, dtype=np.float32) # uint8 to float32
im /= 255 # 0 - 255 to 0.0 - 1.0
ims.append(im)
pred_cls2 = model(torch.Tensor(ims).to(d.device)).argmax(1) # classifier prediction
x[i] = x[i][pred_cls1 == pred_cls2] # retain matching class detections
return x
def increment_path(path, exist_ok=False, sep='', mkdir=False):
# Increment file or directory path, i.e. runs/exp --> runs/exp{sep}2, runs/exp{sep}3, ... etc.
path = Path(path) # os-agnostic
if path.exists() and not exist_ok:
path, suffix = (path.with_suffix(''), path.suffix) if path.is_file() else (path, '')
dirs = glob.glob(f"{path}{sep}*") # similar paths
matches = [re.search(rf"%s{sep}(\d+)" % path.stem, d) for d in dirs]
i = [int(m.groups()[0]) for m in matches if m] # indices
n = max(i) + 1 if i else 2 # increment number
path = Path(f"{path}{sep}{n}{suffix}") # increment path
if mkdir:
path.mkdir(parents=True, exist_ok=True) # make directory
return path
# Variables
NCOLS = 0 if is_docker() else shutil.get_terminal_size().columns # terminal window size for tqdm | PypiClean |
/MetaGram-2.0.2.tar.gz/MetaGram-2.0.2/pyrogram/crypto/aes.py |
import logging
log = logging.getLogger(__name__)
try:
import tgcrypto
log.info("Using TgCrypto")
def ige256_encrypt(data: bytes, key: bytes, iv: bytes) -> bytes:
return tgcrypto.ige256_encrypt(data, key, iv)
def ige256_decrypt(data: bytes, key: bytes, iv: bytes) -> bytes:
return tgcrypto.ige256_decrypt(data, key, iv)
def ctr256_encrypt(data: bytes, key: bytes, iv: bytearray, state: bytearray = None) -> bytes:
return tgcrypto.ctr256_encrypt(data, key, iv, state or bytearray(1))
def ctr256_decrypt(data: bytes, key: bytes, iv: bytearray, state: bytearray = None) -> bytes:
return tgcrypto.ctr256_decrypt(data, key, iv, state or bytearray(1))
def xor(a: bytes, b: bytes) -> bytes:
return int.to_bytes(
int.from_bytes(a, "big") ^ int.from_bytes(b, "big"),
len(a),
"big",
)
except ImportError:
import pyaes
log.warning(
"TgCrypto is missing! "
"Pyrogram will work the same, but at a much slower speed. "
"More info: https://docs.pyrogram.org/topics/speedups"
)
def ige256_encrypt(data: bytes, key: bytes, iv: bytes) -> bytes:
return ige(data, key, iv, True)
def ige256_decrypt(data: bytes, key: bytes, iv: bytes) -> bytes:
return ige(data, key, iv, False)
def ctr256_encrypt(data: bytes, key: bytes, iv: bytearray, state: bytearray = None) -> bytes:
return ctr(data, key, iv, state or bytearray(1))
def ctr256_decrypt(data: bytes, key: bytes, iv: bytearray, state: bytearray = None) -> bytes:
return ctr(data, key, iv, state or bytearray(1))
def xor(a: bytes, b: bytes) -> bytes:
return int.to_bytes(
int.from_bytes(a, "big") ^ int.from_bytes(b, "big"),
len(a),
"big",
)
def ige(data: bytes, key: bytes, iv: bytes, encrypt: bool) -> bytes:
cipher = pyaes.AES(key)
iv_1 = iv[:16]
iv_2 = iv[16:]
data = [data[i: i + 16] for i in range(0, len(data), 16)]
if encrypt:
for i, chunk in enumerate(data):
iv_1 = data[i] = xor(cipher.encrypt(xor(chunk, iv_1)), iv_2)
iv_2 = chunk
else:
for i, chunk in enumerate(data):
iv_2 = data[i] = xor(cipher.decrypt(xor(chunk, iv_2)), iv_1)
iv_1 = chunk
return b"".join(data)
def ctr(data: bytes, key: bytes, iv: bytearray, state: bytearray) -> bytes:
cipher = pyaes.AES(key)
out = bytearray(data)
chunk = cipher.encrypt(iv)
for i in range(0, len(data), 16):
for j in range(0, min(len(data) - i, 16)):
out[i + j] ^= chunk[state[0]]
state[0] += 1
if state[0] >= 16:
state[0] = 0
if state[0] == 0:
for k in range(15, -1, -1):
try:
iv[k] += 1
break
except ValueError:
iv[k] = 0
chunk = cipher.encrypt(iv)
return out | PypiClean |
/JWaves-0.0.1.tar.gz/JWaves-0.0.1/src/S02_firstTestsB.py | import numpy as np
from scipy.io import loadmat
import matplotlib.pyplot as plt
import sys
sys.path.append('.')
from RPA import Lattice, System, Units
from MagneticFormFactor import formFactor
from scipy.ndimage import gaussian_filter
import time
start = time.time()
#########
lat=[10.088,11.943,3.42]#
T=0.1# in K
Hc=0.25;
H=[0,0,Hc];# in [T]
J1=0#-0.1484/3.9892**2#
J2=0#-0.1023/3.9892**2#
facO21=0#
J1S1=np.zeros((8,8))
J1S1[:3,:3]=J1*np.eye(3)
J2S1=np.zeros((8,8))
J2S1[:3,:3]=J2*np.eye(3)
# 'Jx' 'Jy' 'Jz' 'O20' 'O2+1' 'O2-1' 'O2+2' 'O2-2'
# 1 2 3 4 5 6 7 8
J2S1[4,4]=facO21;
##
epsilon=0.05;
omega=np.arange(0,9,epsilon/3)#
wid=0.1
# ElasticThreshold=1e-2
Qz=np.arange(0,2,0.075)
Qy=np.zeros_like(Qz)#((len(Qz)))
Qx=np.zeros_like(Qz)
QRLU=np.asarray([Qx,Qy,Qz])
positions = np.asarray([[0.4242,0.1110,0.25],
[0.5758,0.8890,0.75]])
lattice = Lattice(S=[15/2,15/2],g = [4/3,4/3],active = [1,1],positions = positions,
label = ['Dy1','Dy1'], site = [1,1], lattice = [10.0884,11.9427,3.4289,90,90,90])
S = System(temperature=T,magneticField=H, lattice=lattice)
S.lattice.generateCouplings(maxDistance = 3.51)
distances = [3.5082,3.4289]
Js = [J1S1,J2S1]
S.lattice.addExchangeInteractions(Js,distances)
S.operators = loadmat(r'C:\Users\lass_j\Documents\Software\RPA\RPA for Simon\operators\operatorsSHO_sxtal0p45.mat')['operator']
S.operators = np.asarray([S.operators,S.operators])
S.energies = np.array([[0,0.626,2.12,3.07,5.36,8.22]])
# InitialDistributionSite1_Ext
sizeS = 3.9892
doubling = False # Along c only
config = 1 # not sure
Ncell = 1
nExt = [1,1,Ncell]
numOperators = S.operators.shape[-1]
site1 = np.zeros((numOperators,len(S.lattice.r)))
site1[2,0] = sizeS
site1[2,1] = site1[2,0]*config
fc = site1
fullConfiguration = np.repeat(fc, Ncell,axis=-1)
spins = np.repeat(site1[:3],Ncell,axis=-1)
if doubling: # add AFM along c
tt=np.ones_like(fullConfiguration)
tt[:,-2::4]=-tt[:,-2::4]
tt[:,-1::4]=-tt[:,-1::4]
fullConfiguration=fullConfiguration*tt;
S.lattice.NCell = int(np.product(nExt))
S.lattice.nExt = nExt
fig,Ax = plt.subplots(nrows=2,ncols=2,figsize=(14,10))
Ax = Ax.flatten()
for field,ax in zip([0.0,0.1,0.5,1.0],Ax):
S.magneticField = np.array([0.0,field,Hc])
S.fullConfiguration = fullConfiguration
S.solveSelfConsistency()
print(np.round(np.real(S.fullConfiguration),4))
S.calculateChi0(omega)
Y = [np.imag(S.Chi0_inelastic[i,i,0,:]) for i in range(3)]
Y.append(np.sum(Y,axis=0))
Y = np.asarray(Y)
for y,c,title in zip(Y,['b','r','g','k--'],['Jx','Jy','Jz','Jtot']):
ax.plot(omega,y,c,label=title)
ax.set_xlabel('Energy [meV]')
ax.set_ylabel('Imag(X_0 inelastic)')
ax.set_title('Magnetic Field = ('+', '.join(['{:}'.format(x) for x in S.magneticField])+') [T]')
ax.legend()
fig.tight_layout()
##
hh = np.arange(0,2,0.05);
sqw=np.zeros((len(hh),len(omega)))
for hi,h in enumerate(hh):
S.magneticField = np.array([0,h,Hc]);
S.solveSelfConsistency()
S.calculateChi0(omega)
sqw[hi,:]=np.imag(np.sum(S.Chi0_inelastic[[0,1,2],[0,1,2],0,:],axis=0).T)
fig2,ax2 = plt.subplots()
p = ax2.pcolormesh(hh,omega,sqw.T,shading='auto')#;shading flat
ax2.set_xlabel('H (T)')
ax2.set_ylabel('Energy (meV)')
p.set_clim(0,500)
fig2.colorbar(p) | PypiClean |
/GraphLab_Create-2.1-cp27-none-macosx_10_5_x86_64.macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.macosx_10_11_intel.macosx_10_11_x86_64.whl/graphlab/toolkits/feature_engineering/_numeric_imputer.py | import graphlab as _gl
# Toolkit utils.
from graphlab.toolkits.feature_engineering._feature_engineering import Transformer
from graphlab.toolkits._model import _get_default_options_wrapper
from graphlab.toolkits._internal_utils import _toolkit_repr_print
from graphlab.toolkits._internal_utils import _precomputed_field
from graphlab.util import _raise_error_if_not_of_type
# Feature engineering utils
from . import _internal_utils
from ._doc_utils import republish_docs
_fit_examples_doc = '''
# Create the data
>>> sf = graphlab.SFrame({'a' : [1,2,3,4,5], 'b' : [2,3,4,2,3]})
# Create the imputer for the features ['a', 'b'].
>>> imputer = graphlab.feature_engineering.NumericImputer(
features = ['a', 'b'], strategy = 'mean')
# Learn the sufficient stats required for imputation of each column.
>>> imputer = imputer.fit(sf)
# Return the list of mean for each of the columns.
>>> imputer['means']
Columns:
a float
b float
Rows: 1
Data:
+-----+-----+
| a | b |
+-----+-----+
| 3.0 | 2.8 |
+-----+-----+
[1 rows x 2 columns]
'''
_fit_transform_examples_doc = '''
# Create the data
>>> sf = graphlab.SFrame({'a' : [1,2,None,4,5], 'b' : [2,3,None,5,6]})
# Create the imputer for the features ['a', 'b'].
>>> imputer = graphlab.feature_engineering.NumericImputer(
features = ['a', 'b'])
# Fit and transform on the same data.
>>> transformed_sf = imputer.fit_transform(sf)
Columns:
a float
b float
Rows: 5
Data:
+-----+-----+
| a | b |
+-----+-----+
| 1.0 | 2.0 |
| 2.0 | 3.0 |
| 3.0 | 4.0 |
| 4.0 | 5.0 |
| 5.0 | 6.0 |
+-----+-----+
[5 rows x 2 columns]
'''
_transform_examples_doc = '''
# Integer/Float columns
# ----------------------------------------------------------------------
# Create the data
>>> sf = graphlab.SFrame({'a' : [1,2,4,5], 'b' : [2,3,5,6]})
# Create the imputer for the features ['a', 'b'].
>>> imputer = graphlab.feature_engineering.NumericImputer(
features = ['a', 'b']).fit(sf)
# Impute the missing values in new data.
>>> sf_new = graphlab.SFrame({'a' : [1,2,None,4,5], 'b' : [2,3,None,5,6]})
>>> transformed_sf = imputer.transform(sf_new)
Columns:
a float
b float
Rows: 5
Data:
+-----+-----+
| a | b |
+-----+-----+
| 1.0 | 2.0 |
| 2.0 | 3.0 |
| 3.0 | 4.0 |
| 4.0 | 5.0 |
| 5.0 | 6.0 |
+-----+-----+
[5 rows x 2 columns]
# Lists can contain numeric and None values.
# ----------------------------------------------------------------------
>>> sf = graphlab.SFrame({'lst': [[1, 2],
[2, 3],
[3, 4],
[5, 6],
[6, 7]]})
# Construct and fit an imputer for the column['lst'].
>>> from graphlab.toolkits.feature_engineering import NumericImputer
>>> imputer = graphlab.feature_engineering.create(sf,
NumericImputer(features = ['lst']))
# Impute the missing values in the new data.
>>> new_sf = graphlab.SFrame({'lst': [[1, 2],
[2, 3],
[3, 4],
[None, None],
[5, 6],
[6, 7]]})
>>> transformed_sf = imputer.transform(sf)
Columns:
a list
Rows: 6
Data:
+------------+
| lst |
+------------+
| [1, 2] |
| [2, 3] |
| [3, 4] |
| [3.4, 4.4] |
| [5, 6] |
| [6, 7] |
+------------+
[6 rows x 1 columns]
# Dictionaries (Assumes sparse data format)
# ----------------------------------------------------------------------
# Construct and fit an imputer for the column ['dict'].
>>> from graphlab.toolkits.feature_engineering import NumericImputer
>>> sf = graphlab.SFrame({'dict':
[{'a':1, 'b': 2, 'c': 3},
{'a':0, 'b': 0, 'c': 0},
{'b':4, 'c': 0, 'd': 6}]})
>>> imputer = graphlab.toolkits.feature_engineering.create(sf,
NumericImputer(features = ['dict']))
# Impute the missing values for the new data.
>>> sf = graphlab.SFrame({'dict':
[{'a':1, 'b': 2, 'c': 3},
None,
{'b':4, 'c': None, 'd': 6}]})
>>> transformed_sf = imputer.transform(sf)
Columns:
dict dict
Rows: 3
Data:
+-------------------------------+
| dict |
+-------------------------------+
| {'a': 1, 'c': 3, 'b': 2} |
| {'a': 0.3333333333333333, ... |
| {'c': 1.0, 'b': 4, 'd': 6} |
+-------------------------------+
[3 rows x 1 columns]
'''
@republish_docs
class NumericImputer(Transformer):
'''
Impute missing values with feature means.
Input columns to the NumericImputer must be of type *int*, *float*,
*dict*, *list*, or *array.array*. For each column in the input, the transformed output is
a column where the input is retained as is if:
* there is no missing value.
Inputs that do not satisfy the above are set to the mean value of that
feature.
The behavior for different input data column types is as follows:
(see :func:`~graphlab.feature_engineering.NumericImputer.transform` for
for examples).
* **float** : If there is a missing value, it is replaced with the mean
of that column.
* **int** : Behaves the same way as *float*.
* **list** : Each index of the list is treated as a feature column, and
missing values are replaced with per-feature means. This is the same as
unpacking, computing the mean, and re-packing. All elements must be of
type *float*, *int*, or *None*. See :func:`~graphlab.SFrame.pack_columns`
for more information.
* **array** : Same behavior as *list*
* **dict** : Same behavior as *list*, except keys not present in a
particular row are implicitly interpreted as having the value 0. This
makes the *dict* type a sparse representation of a vector.
Parameters
----------
features : list[str] | str | None, optional
Name(s) of feature column(s) to be transformed. If set to None, then all
feature columns are used.
excluded_features : list[str] | str | None, optional
Name(s) of feature columns in the input dataset to be ignored. Either
`excluded_features` or `features` can be passed, but not both.
strategy: 'auto'|'mean', optional
The strategy with which to perform imputation.Currently can be 'auto'
or 'mean'. Both currently perform mean imputation.
output_column_prefix : str, optional
The prefix to use for the column name of each transformed column.
When provided, the transformation will add columns to the input data,
where the new name is "`output_column_prefix`.original_column_name".
If `output_column_prefix=None` (default), then the output column name
is the same as the original feature column name.
Returns
-------
out : NumericImputer
A NumericImputer object which is initialized with the defined parameters.
See Also
--------
graphlab.toolkits.feature_engineering._numeric_imputer.NumericImputer
graphlab.toolkits.feature_engineering.create
Notes
-----
- If the SFrame to be transformed already contains a column with the
designated output column name, then that column will be replaced with the
new output. In particular, this means that `output_column_prefix=None` will
overwrite the original feature columns.
Examples
--------
.. sourcecode:: python
# Create data.
>>> sf = graphlab.SFrame({'a': [1,3], 'b' : [2,4]})
# Create a transformer.
>>> from graphlab.toolkits.feature_engineering import NumericImputer
>>> imputer = graphlab.feature_engineering.create(sf,
NumericImputer(features = ['a', 'b'], strategy = 'mean'))
# Transform the data.
>>> new_sf = graphlab.SFrame({'a': [1,None,3], 'b' : [2, None,4]})
>>> transformed_sf = imputer.transform(new_sf)
# Save the transformer.
>>> imputer.save('save-path')
# Return the means.
>>> imputer['means']
Columns:
a float
b float
Rows: 1
Data:
+-----+-----+
| a | b |
+-----+-----+
| 2.0 | 3.0 |
+-----+-----+
[1 rows x 2 columns]
'''
# Doc strings
_fit_examples_doc = _fit_examples_doc
_transform_examples_doc = _transform_examples_doc
_fit_transform_examples_doc = _fit_transform_examples_doc
# Default options
get_default_options = staticmethod(_get_default_options_wrapper(
'_MeanImputer', 'toolkits.feature_engineering._mean_imputer',
'MeanImputer', True))
def __init__(self, features=None, excluded_features=None, strategy='auto',
output_column_prefix=None):
# Process and make a copy of the features, exclude.
_features, _exclude = _internal_utils.process_features(
features, excluded_features)
# Type checking
_raise_error_if_not_of_type(strategy, [str])
# Set up options
opts = {
'strategy' : strategy,
'output_column_prefix': output_column_prefix
}
if _exclude:
opts['exclude'] = True
opts['features'] = _exclude
else:
opts['exclude'] = False
opts['features'] = _features
# Initialize object
proxy = _gl.extensions._MeanImputer()
proxy.init_transformer(opts)
super(NumericImputer, self).__init__(proxy, self.__class__)
def _get_summary_struct(self):
_features = _precomputed_field(
_internal_utils.pretty_print_list(self.get('features')))
_exclude = _precomputed_field(
_internal_utils.pretty_print_list(self.get('excluded_features')))
fields = [
("Features", _features),
("Excluded features", _exclude),
]
section_titles = ['Model fields']
return ([fields], section_titles)
def __repr__(self):
(sections, section_titles) = self._get_summary_struct()
return _toolkit_repr_print(self, sections, section_titles, 30)
@classmethod
def _get_instance_and_data(cls):
sf = _gl.SFrame({'a': [1, 2, 3], 'b': [2, 3, 4]})
imputer = _gl.feature_engineering.NumericImputer(
features = ['a', 'b'], strategy = 'mean')
return imputer.fit(sf), sf | PypiClean |
/netket-3.9.2.tar.gz/netket-3.9.2/netket/graph/lattice.py |
from dataclasses import dataclass
from math import pi
from netket.utils.types import Array
from typing import Callable, Dict, Sequence, Tuple, Union, Optional, TYPE_CHECKING
import warnings
import numpy as _np
from netket.utils.deprecation import deprecated as _deprecated
from netket.utils import HashableArray
from netket.utils.float import comparable, comparable_periodic, is_approx_int
from netket.utils.group import PointGroup, PermutationGroup, trivial_point_group
from .graph import Graph
from ._lattice_edge_logic import (
get_nn_edges,
get_custom_edges,
create_site_positions,
CustomEdgeT,
)
if TYPE_CHECKING:
from .space_group import SpaceGroupBuilder
PositionT = _np.ndarray
CoordT = _np.ndarray
class InvalidSiteError(Exception):
pass
class InvalidWaveVectorError(Exception):
pass
@dataclass
class LatticeSite:
"""
Contains information about a single :class:`~netket.graph.Lattice` site.
"""
id: int
"""Integer ID of this site"""
position: PositionT
"""Real-space position of this site"""
basis_coord: CoordT
"""basis coordinates of this site"""
def __repr__(self):
s = ", ".join(map(str, (self.id, self.basis_coord)))
return f"LatticeSite({s})"
def _create_sites(basis_vectors, extent, site_offsets):
basis_coords, positions = create_site_positions(basis_vectors, extent, site_offsets)
sites = [
LatticeSite(id=idx, position=pos, basis_coord=coord)
for idx, (coord, pos) in enumerate(zip(basis_coords, positions))
]
return sites, basis_coords, positions
def deprecated(alternative):
def wrapper(fn):
msg = (
f"{fn.__name__} is deprecated and may be removed in the future. "
f"You can use `{alternative}`` instead."
)
f = _deprecated(msg)(fn)
return f
return wrapper
REPR_TEMPLATE = """Lattice(
n_nodes={},
extent={},
basis_vectors=
{},
site_offsets=
{},
)
"""
class Lattice(Graph):
r"""
A lattice built by periodic arrangement of a given unit cell.
The lattice is represented as a Bravais lattice with (:code:`basis_vectors`)
:math:`\{a_d\}_{d=1}^D` (where :math:`D = \mathtt{ndim}` is the dimension of the
lattice) and a unit cell consisting of one or more sites,
The positions of those sites within the unit cell can be specified by the
:code:`site_offsets` parameter. The :code:`extent` is a array where
:code:`extent[d]` specifies the number of times each unit cell is translated along
direction :math:`d`.
The full lattice is then generated by placing a site at each of the points
.. math::
R_{rq} = \sum_{d=1}^D r_d a_d + b_q \in \mathbb R^D
where :math:`r_d \in \{1, \ldots, \mathtt{extent}[d]\}` and
:math:`b_q = \mathtt{site\_offsets}[q]`.
We also refer to :math:`q` as the `label` of the site within the unit cell.
The lattice class supports three ways of addressing a specific lattice site:
id
An integer index that is used to identify the site in :code:`self.edges()` and
also corresponds to the index of the corresponding site in sequences like
:code:`self.nodes()`, :code:`self.positions` or :code:`self.basis_coords`.
positions
Real-space position vector :math:`R_{rq}` as defined above, which is available
from :func:`~netket.graph.Lattice.positions` and can be resolved into an id via
:func:`~netket.graph.Lattice.id_from_position`.
basis coordinates
where each site is specified by a vector :code:`[r1, ..., rD, q]`
with :math:`r` being the integer vector of length :code:`ndim` specifying the
cell position as multiples of the primitive vectors and the site label :math:`q`
giving the number of the site within the unit cell.
Basis coordinates are available from :func:`~netket.graph.Lattice.basis_coords`
and can be resolved into an id via
:func:`~netket.graph.Lattice.id_from_basis_coords`.
"""
# Initialization
# ------------------------------------------------------------------------
def __init__(
self,
basis_vectors: _np.ndarray,
extent: _np.ndarray,
*,
pbc: Union[bool, Sequence[bool]] = True,
site_offsets: Optional[_np.ndarray] = None,
atoms_coord: Optional[_np.ndarray] = None,
distance_atol: float = 1e-5,
point_group: Optional[PointGroup] = None,
max_neighbor_order: Optional[int] = None,
custom_edges: Optional[Sequence[CustomEdgeT]] = None,
):
"""
Constructs a new ``Lattice`` given its side length and the features of the unit
cell.
Args:
basis_vectors: The basis vectors of the lattice. Should be an array
of shape `(ndim, ndim)` where each `row` is a basis vector.
extent: The number of copies of the unit cell; needs to be an array
of length `ndim`.
pbc: If ``True`` then the constructed lattice
will have periodic boundary conditions, otherwise
open boundary conditions are imposed. Can also be an boolean sequence
of length `ndim`, indicating either open or closed boundary conditions
separately for each direction.
site_offsets: The position offsets of sites in the unit cell (one site at
the origin by default).
distance_atol: Distance below which spatial points are considered equal for
the purpose of identifying nearest neighbors.
point_group: Default `PointGroup` object for constructing space groups
max_neighbor_order: For :code:`max_neighbor_order == k`, edges between up
to :math:`k`-nearest neighbor sites (measured by their Euclidean distance)
are included in the graph. The edges can be distinguished by their color,
which is set to :math:`k - 1` (so nearest-neighbor edges have color 0).
By default, nearest neighbours (:code:`max_neighbor_order=1`) are autogenerated
unless :code:`custom_edges` is passed.
custom_edges: (Optional) Lists all edges starting in one unit cell, which
are repeated in every unit cell of the constructed lattice.
Should be a list of tuples; each tuple should contain the following:
* index of the starting point in the unit cell
* index of the endpoint in the unit cell
* vector pointing from the former to the latter
* color of the edge (optional)
If colors are not supplied, they are assigned sequentially starting from 0.
Cannot be used together with `max_neighbor_order`.
Examples:
Constructs a Kagome lattice with 3 × 3 unit cells:
>>> import numpy as np
>>> from netket.graph import Lattice
>>> # Hexagonal lattice basis
>>> sqrt3 = np.sqrt(3.0)
>>> basis = np.array([
... [1.0, 0.0],
... [0.5, sqrt3 / 2.0],
... ])
>>> # Kagome unit cell
>>> cell = np.array([
... basis[0] / 2.0,
... basis[1] / 2.0,
... (basis[0]+basis[1])/2.0
... ])
>>> g = Lattice(basis_vectors=basis, site_offsets=cell, extent=[3, 3])
>>> print(g.n_nodes)
27
>>> print(g.basis_coords[:6])
[[0 0 0]
[0 0 1]
[0 0 2]
[0 1 0]
[0 1 1]
[0 1 2]]
>>> print(g.positions[:6])
[[0.5 0. ]
[0.25 0.4330127 ]
[0.75 0.4330127 ]
[1. 0.8660254 ]
[0.75 1.29903811]
[1.25 1.29903811]]
Constructs a rectangular lattice with distinct horizontal and vertical edges:
>>> import numpy as np
>>> from netket.graph import Lattice
>>> basis = np.array([
... [1.0,0.0],
... [0.0,0.5],
... ])
>>> custom_edges = [
... (0, 0, [1.0,0.0], 0),
... (0, 0, [0.0,0.5], 1),
... ]
>>> g = Lattice(basis_vectors=basis, pbc=False, extent=[4,6],
... custom_edges=custom_edges)
>>> print(g.n_nodes)
24
>>> print(len(g.edges(filter_color=0)))
18
>>> print(len(g.edges(filter_color=1)))
20
"""
# Clean input parameters
self._basis_vectors = self._clean_basis(basis_vectors)
self._ndim = self._basis_vectors.shape[1]
self._site_offsets, site_pos_fractional = self._clean_site_offsets(
site_offsets,
atoms_coord,
self._basis_vectors,
)
self._pbc = self._clean_pbc(pbc, self._ndim)
self._extent = _np.asarray(extent, dtype=int)
self._lattice_dims = _np.expand_dims(self._extent, 1) * self.basis_vectors
self._inv_dims = _np.linalg.inv(self._lattice_dims)
self._point_group = point_group
# Generate sites
self._sites, self._basis_coords, self._positions = _create_sites(
self._basis_vectors,
self._extent,
self._site_offsets,
)
self._basis_coord_to_site = {
HashableArray(p.basis_coord): p.id for p in self._sites
}
int_positions = self._to_integer_position(self._positions)
self._int_position_to_site = {
HashableArray(pos): index for index, pos in enumerate(int_positions)
}
# Generate edges
if custom_edges is not None:
if max_neighbor_order is not None:
raise ValueError(
"custom_edges and max_neighbor_order cannot be specified at the same time"
)
colored_edges = get_custom_edges(
self._basis_vectors,
self._extent,
self._site_offsets,
self._pbc,
distance_atol,
custom_edges,
)
else:
if max_neighbor_order is None:
max_neighbor_order = 1
colored_edges = get_nn_edges(
self._basis_vectors,
self._extent,
self._site_offsets,
self._pbc,
distance_atol,
max_neighbor_order,
)
super().__init__(colored_edges, len(self._sites))
@staticmethod
def _clean_basis(basis_vectors):
"""Check and convert `basis_vectors` init argument."""
basis_vectors = _np.asarray(basis_vectors)
if basis_vectors.ndim != 2:
raise ValueError(
"'basis_vectors' must have ndim==2 (as array of primitive vectors)"
)
if basis_vectors.shape[0] != basis_vectors.shape[1]:
raise ValueError("The number of primitive vectors must match their length")
return basis_vectors
# TODO: remove atoms_coord argument.
@staticmethod
def _clean_site_offsets(site_offsets, atoms_coord, basis_vectors):
"""Check and convert `site_offsets` init argument."""
if atoms_coord is not None and site_offsets is not None:
raise ValueError(
"atoms_coord is deprecated and replaced by site_offsets, "
"so both cannot be specified at the same time."
)
if atoms_coord is not None:
warnings.warn(
"atoms_coord is deprecated and may be removed in future versions, "
"please use site_offsets instead",
FutureWarning,
stacklevel=3,
)
site_offsets = atoms_coord
if site_offsets is None:
site_offsets = _np.zeros(basis_vectors.shape[0])[None, :]
site_offsets = _np.asarray(site_offsets)
fractional_coords = site_offsets @ _np.linalg.inv(basis_vectors)
fractional_coords_int = comparable_periodic(fractional_coords)
# Check for duplicates (also across unit cells)
uniques, idx = _np.unique(fractional_coords_int, axis=0, return_index=True)
if len(site_offsets) != len(uniques):
site_offsets = site_offsets[idx]
fractional_coords = fractional_coords[idx]
fractional_coords_int = fractional_coords_int[idx]
warnings.warn(
"Some atom positions are not unique. Duplicates were dropped, and "
f"now atom positions are {site_offsets}",
UserWarning,
)
# Check if any site is outside primitive cell (may cause KDTree to malfunction)
if _np.any(fractional_coords_int < comparable(0.0)) or _np.any(
fractional_coords_int > comparable(1.0)
):
warnings.warn(
"Some sites were specified outside the primitive unit cell. This may"
"cause errors in automatic edge finding.",
UserWarning,
)
return site_offsets, fractional_coords
@staticmethod
def _clean_pbc(pbc, ndim):
"""Check and convert `pbc` init argument."""
if isinstance(pbc, bool):
return _np.array([pbc] * ndim, dtype=bool)
elif (
not isinstance(pbc, Sequence)
or len(pbc) != ndim
or not all(isinstance(b, bool) for b in pbc)
):
raise ValueError(
"pbc must be either a boolean or a sequence of booleans with length"
"equal to the lattice dimension"
)
else:
return _np.asarray(pbc, dtype=bool)
# Properties
# ------------------------------------------------------------------------
@property
def basis_vectors(self):
"""Basis vectors of the lattice"""
return self._basis_vectors
@property
def site_offsets(self):
"""Position offsets of sites in the unit cell"""
return self._site_offsets
@property
def ndim(self):
"""Dimension of the lattice"""
return self._ndim
@property
def pbc(self):
"""
Array of bools such that `pbc[d]` indicates whether dimension d has
periodic boundaries.
"""
return self._pbc
@property
def extent(self):
"""
Extent of the lattice
"""
return self._extent
@property
def sites(self) -> Sequence[LatticeSite]:
"""Sequence of lattice site objects"""
return self._sites
@property
def positions(self) -> PositionT:
"""Real-space positions of all lattice sites"""
return self._positions
@property
def basis_coords(self) -> CoordT:
"""basis coordinates of all lattice sites"""
return self._basis_coords
# Site lookup
# ------------------------------------------------------------------------
def _to_integer_position(self, positions: PositionT) -> Array:
frac_positions = _np.matmul(positions, self._inv_dims)
return comparable_periodic(frac_positions, self.pbc)
@staticmethod
def _get_id_from_dict(
dict: Dict[HashableArray, int], key: Array
) -> Union[int, Array]:
try:
if key.ndim == 1:
return dict[HashableArray(key)]
elif key.ndim == 2:
return _np.array([dict[HashableArray(k)] for k in key])
else:
raise ValueError("Input needs to be rank 1 or rank 2 array")
except KeyError as e:
raise InvalidSiteError(
"Some coordinates do not correspond to a valid lattice site"
) from e
def id_from_position(self, position: PositionT) -> Union[int, Array]:
"""
Returns the id for a site at the given position. When passed a rank-2 array
where each row is a position, returns an array of the corresponding ids.
Throws an `InvalidSiteError` if any of the positions do not correspond
to a site.
"""
int_pos = self._to_integer_position(position)
ids = self._get_id_from_dict(self._int_position_to_site, int_pos)
return ids
def id_from_basis_coords(self, basis_coords: CoordT) -> Union[int, Array]:
"""
Return the id for a site at the given basis coordinates. When passed a rank-2
array where each row is a coordinate vector, returns an array of the
corresponding ids. Throws an `InvalidSiteError` if any of the coords do
not correspond to a site.
"""
key = _np.asarray(basis_coords)
return self._get_id_from_dict(self._basis_coord_to_site, key)
def position_from_basis_coords(self, basis_coords: CoordT) -> PositionT:
"""
Return the position of the site with given basis coordinates.
When passed a rank-2 array where each row is a coordinate vector,
this method returns an array of the corresponding positions.
Throws an `InvalidSiteError` if no site is found for any of the coordinates.
"""
ids = self.id_from_basis_coords(basis_coords)
return self.positions[ids]
def to_reciprocal_lattice(self, ks: Array) -> Array:
"""
Converts wave vectors from Cartesian axes to reciprocal lattice vectors.
Arguments:
ks: wave vectors in Cartesian axes. Multidimensional arrays are accepted,
the Cartesian coordinates must form the last dimension.
Returns:
The same wave vectors in the reciprocal basis **of the simulation box.**
Valid wave vector components in this basis are integers in (periodic BCs)
or zero (in open BCs).
Throws an `InvalidWaveVectorError` if any of the supplied wave vectors
are not reciprocal lattice vectors of the simulation box.
"""
# Ensure that ks has at least 2 dimensions
ks = _np.asarray(ks)
if ks.ndim == 1:
ks = ks[_np.newaxis, :]
result = ks @ self._lattice_dims.T / (2 * pi)
# Check that these are integers
is_valid = is_approx_int(result)
if not _np.all(is_valid):
raise InvalidWaveVectorError(
"Some wave vectors are not reciprocal lattice vectors of the simulation"
"box spanned by\n"
+ "\n".join(
[
str(self._lattice_dims[i])
+ (" (PBC)" if self.pbc[i] else " (OBC)")
for i in range(self.ndim)
]
)
)
result = _np.asarray(_np.rint(result), dtype=int)
# For axes with non-periodic BCs, the k-component must be 0
is_valid = _np.logical_or(self.pbc, result == 0)
if not _np.all(is_valid):
raise InvalidWaveVectorError(
"Some wave vectors are inconsistent with open boundary conditions"
)
return result
# Generating space groups
# -----------------------------------------------------------------------
def space_group_builder(
self, point_group: Optional[PointGroup] = None
) -> "SpaceGroupBuilder":
"""
Returns a `SpaceGroupBuilder` object that represents the spatial symmetries of
`self`.
Arguments:
point_group: a `PointGroup` object describing the point-group
symmetries of `self`. Optional, if not supplied, the
`PointGroup` object provided at construction is used.
Returns:
A `SpaceGroupBuilder` object that generates `PermutationGroup`s
encoding the action of `point_group`, the translation group of `self`,
and the space group obtained as their semidirect product as
permutations of the sites of `self`. It also yields space group irreps
for symmetrising wave functions.
"""
from .space_group import SpaceGroupBuilder
if point_group is None:
if isinstance(self._point_group, PointGroup):
point_group = self._point_group
elif isinstance(self._point_group, Callable):
self._point_group = self._point_group()
point_group = self._point_group
else:
raise RuntimeError(
"space_group_builder() missing required argument 'point_group'\n"
"(lattice has no default point group)"
)
return SpaceGroupBuilder(self, point_group)
def space_group(self, point_group: Optional[PointGroup] = None) -> PermutationGroup:
"""
Returns the space group generated by the translation symmetries of `self`
and the elements of `point_group` as a `PermutationGroup` acting on the
sites of `self`.
If no `point_group` is specified, uses the point group provided upon
construction.
"""
return self.space_group_builder(point_group).space_group
def point_group(self, point_group: Optional[PointGroup] = None) -> PermutationGroup:
"""
Returns the action of `point_group` on the sites of `self` as a
`PermutationGroup`. If no `point_group` is specified, uses the point group
provided upon construction.
"""
return self.space_group_builder(point_group).point_group
def rotation_group(
self, point_group: Optional[PointGroup] = None
) -> PermutationGroup:
"""
Returns the action of rotations (i.e. symmetries with determinant +1) in
`point_group` on the sites of `self` as a `PermutationGroup`.
If no `point_group` is specified, uses the point group provided upon
construction.
"""
return self.space_group_builder(point_group).rotation_group
def translation_group(
self, dim: Optional[Union[int, Sequence[int]]] = None
) -> PermutationGroup:
"""
Returns the group of lattice translations of `self` as a `PermutationGroup`
acting on the sites of `self`.
"""
return self.space_group_builder(
trivial_point_group(self.ndim)
).translation_group(dim)
# Output and drawing
# ------------------------------------------------------------------------
def __repr__(self) -> str:
return REPR_TEMPLATE.format(
self.n_nodes,
self._extent,
str(self.basis_vectors).replace("\n", "\n" + " " * 8),
str(self.site_offsets).replace("\n", "\n" + " " * 8),
)
def draw(
self,
ax=None,
figsize: Optional[Tuple[Union[int, float]]] = None,
node_color: str = "#1f78b4",
node_size: int = 300,
edge_color: str = "k",
curvature: float = 0.2,
font_size: int = 12,
font_color: str = "k",
):
"""
Draws the ``Lattice`` graph
Args:
ax: Matplotlib axis object.
figsize: (width, height) tuple of the generated figure.
node_color: String with the colour of the nodes.
node_size: Area of the nodes (as in matplotlib.pyplot.scatter).
edge_color: String with the colour of the edges.
curvature: A Bezier curve is fit, where the "height" of the curve is
`curvature` times the "length" of the curvature.
font_size: fontsize of the labels for each node.
font_color: Colour of the font used to label nodes.
Returns:
Matplotlib axis object containing the graph's drawing.
"""
import matplotlib.pyplot as plt # pylint: disable=import-outside-toplevel
# Check if lattice is 1D or 2D... or notnetketwarnings.py
if self._ndim == 1:
positions = _np.pad(self.positions, (0, 1), "constant")
elif self._ndim == 2:
positions = self.positions
else:
raise ValueError(
"Make sure that the graph is 1D or 2D in order to be drawn. "
f" Now it is {self._ndim}D"
)
if ax is None:
_, ax = plt.subplots(figsize=figsize)
for edge in self.edges():
x1, y1 = positions[edge[0]]
x2, y2 = positions[edge[1]]
annotation = ax.annotate(
"",
xy=(x1, y1),
xycoords="data",
xytext=(x2, y2),
textcoords="data",
arrowprops=dict(
arrowstyle="-",
color=edge_color,
shrinkA=0,
shrinkB=0,
patchA=None,
patchB=None,
connectionstyle=f"arc3,rad={curvature}",
),
)
ax.scatter(
*positions.T,
s=node_size,
c=node_color,
marker="o",
zorder=annotation.get_zorder() + 1,
)
for node in self.nodes():
x1, y1 = positions[node]
ax.text(
x1,
y1,
str(node),
horizontalalignment="center",
verticalalignment="center",
fontsize=font_size,
color=font_color,
zorder=annotation.get_zorder() + 1,
)
ax.axis("equal")
return ax
# Backwards compatibility
# ------------------------------------------------------------------------
@deprecated("basis_coords[site_id, -1]")
def atom_label(self, site_id: int) -> int:
"""Deprecated. please use :code:`basis_coords[site_id, -1]` instead."""
return self.basis_coords[site_id, -1]
@deprecated("basis_coords[site_id, :-1]")
def site_to_vector(self, site_id: int) -> CoordT:
"""Deprecated. please use :code:`basis_coords[site_id, :-1]` instead."""
return self.basis_coords[site_id, :-1]
@deprecated("positions[site_id]")
def site_to_coord(self, site_id: int) -> PositionT:
"""Deprecated. please use :code:`positions[site_id]` instead."""
return self.positions[site_id]
@deprecated("id_from_basis_coords([*vector, 0])")
def vector_to_site(self, vector: CoordT) -> int:
"""Deprecated. please use :code:`id_from_basis_coords([*vector, 0])` instead."""
# Note: This only gives one site within the unit cell, so that
# `vector_to_site(site_to_vector(i)) == i` is _not_ true in general,
# which is consistent with the behavior of the v2 lattice.
return self.id_from_basis_coords([*vector, 0])
@deprecated("position_from_basis_coords([*vector, label])")
def vector_to_coord(self, vector: CoordT, label: int) -> PositionT:
"Deprecated. please use :code:`position_from_basis_coords([*vector, label])`."
return self.position_from_basis_coords([*vector, label])
@property
@deprecated("positions")
def coordinates(self) -> PositionT:
"""Deprecated. please use :code:`positions` instead."""
return self.positions
@property
@deprecated("site_offsets")
def atoms_coord(self) -> PositionT:
"""Deprecated. please use :code:`site_offsets` instead."""
return self._site_offsets | PypiClean |
/BIT_Online_Code_Helper-1.0.4-py3-none-any.whl/bit-online-code-helper/bitonline/LocalTestCodeManager.py | import subprocess
import os
from log.LogManager import *
from tqdm import tqdm
class _LocalTestCodeManager:
def __remove_existed_exe(self):
if os.path.exists('a.exe'):
os.remove('a.exe')
def __compile_source_file(self, source_file_path):
self.__remove_existed_exe()
if not os.path.exists(source_file_path):
tip(LocalTestCodeLogs.SOURCE_FILE_NOT_FOUND)
return False
tip(LocalTestCodeLogs.COMPILE_PENDING)
compile_process = subprocess.Popen(['g++', source_file_path, '-std=c++11'], shell=True, stdin=subprocess.PIPE,
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = compile_process.communicate()
compile_process.terminate()
if len(err.decode()) != 0:
tip(LocalTestCodeLogs.COMPILE_FAILED)
return False
else:
tip(LocalTestCodeLogs.COMPILE_SUCCESS)
return True
def __local_test_code(self, problem_info):
is_pass = True
tip(LocalTestCodeLogs.LOCAL_TEST_BEGIN)
index = 1
test_failed_case_index = []
pbar = tqdm(total=len(problem_info.test_cases_and_results),
unit='cases')
for test_case in problem_info.test_cases_and_results:
test_process = subprocess.Popen(['a.exe'], shell=True, stdin=subprocess.PIPE,
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = test_process.communicate(test_case['test_case'].encode())
is_case_pass = out.decode() == test_case['result']
if not is_case_pass:
test_failed_case_index.append(index)
is_pass = False
index += 1
pbar.update(1)
test_process.terminate()
pbar.close()
if is_pass:
tip(LocalTestCodeLogs.TEST_SUCCESS)
else:
tip(LocalTestCodeLogs.TEST_FAILURE_CASE)
for index in test_failed_case_index:
print(index, end=' ')
print('')
divide_line()
return is_pass
def run(self, source_file_path, problem_info):
print(problem_info.title + '\n')
if self.__compile_source_file(source_file_path):
return self.__local_test_code(problem_info)
return False
local_test_code_manager = _LocalTestCodeManager() | PypiClean |
/Faker-19.3.1.tar.gz/Faker-19.3.1/faker/providers/address/fr_FR/__init__.py | from typing import Tuple
from .. import Provider as AddressProvider
class Provider(AddressProvider):
city_suffixes = (
"Ville",
"Bourg",
"-les-Bains",
"-sur-Mer",
"-la-Forêt",
"boeuf",
"nec",
"dan",
)
city_prefixes = ("Saint", "Sainte")
street_prefixes = ("rue", "rue", "chemin", "avenue", "boulevard")
city_formats = (
"{{city_prefix}} {{first_name}}",
"{{city_prefix}} {{first_name}}{{city_suffix}}",
"{{last_name}}",
"{{last_name}}",
"{{last_name}}",
"{{last_name}}",
"{{last_name}}{{city_suffix}}",
"{{last_name}}{{city_suffix}}",
"{{last_name}}{{city_suffix}}",
"{{last_name}}-sur-{{last_name}}",
)
street_name_formats = (
"{{street_prefix}} {{last_name}}",
"{{street_prefix}} {{first_name}} {{last_name}}",
"{{street_prefix}} de {{last_name}}",
)
street_address_formats = (
"{{street_name}}",
"{{building_number}}, {{street_name}}",
"{{building_number}}, {{street_name}}",
"{{building_number}}, {{street_name}}",
"{{building_number}}, {{street_name}}",
"{{building_number}}, {{street_name}}",
)
address_formats = ("{{street_address}}\n{{postcode}} {{city}}",)
building_number_formats = ("%", "%#", "%#", "%#", "%##")
countries = (
"Afghanistan",
"Afrique du sud",
"Albanie",
"Algérie",
"Allemagne",
"Andorre",
"Angola",
"Anguilla",
"Antarctique",
"Antigua et Barbuda",
"Antilles néerlandaises",
"Arabie saoudite",
"Argentine",
"Arménie",
"Aruba",
"Australie",
"Autriche",
"Azerbaïdjan",
"Bahamas",
"Bahrain",
"Bangladesh",
"Belgique",
"Belize",
"Benin",
"Bermudes (Les)",
"Bhoutan",
"Biélorussie",
"Bolivie",
"Bosnie-Herzégovine",
"Botswana",
"Bouvet (Îles)",
"Brunei",
"Brésil",
"Bulgarie",
"Burkina Faso",
"Burundi",
"Cambodge",
"Cameroun",
"Canada",
"Cap Vert",
"Cayman (Îles)",
"Chili",
"Chine (Rép. pop.)",
"Christmas (Île)",
"Chypre",
"Cocos (Îles)",
"Colombie",
"Comores",
"Cook (Îles)",
"Corée du Nord",
"Corée, Sud",
"Costa Rica",
"Croatie",
"Cuba",
"Côte d'Ivoire",
"Danemark",
"Djibouti",
"Dominique",
"Égypte",
"El Salvador",
"Émirats arabes unis",
"Équateur",
"Érythrée",
"Espagne",
"Estonie",
"États-Unis",
"Ethiopie",
"Falkland (Île)",
"Fidji (République des)",
"Finlande",
"France",
"Féroé (Îles)",
"Gabon",
"Gambie",
"Ghana",
"Gibraltar",
"Grenade",
"Groenland",
"Grèce",
"Guadeloupe",
"Guam",
"Guatemala",
"Guinée",
"Guinée Equatoriale",
"Guinée-Bissau",
"Guyane",
"Guyane française",
"Géorgie",
"Géorgie du Sud et Sandwich du Sud (Îles)",
"Haïti",
"Heard et McDonald (Îles)",
"Honduras",
"Hong Kong",
"Hongrie",
"Îles Mineures Éloignées des États-Unis",
"Inde",
"Indonésie",
"Irak",
"Iran",
"Irlande",
"Islande",
"Israël",
"Italie",
"Jamaïque",
"Japon",
"Jordanie",
"Kazakhstan",
"Kenya",
"Kirghizistan",
"Kiribati",
"Koweit",
"La Barbad",
"Laos",
"Lesotho",
"Lettonie",
"Liban",
"Libye",
"Libéria",
"Liechtenstein",
"Lithuanie",
"Luxembourg",
"Macau",
"Macédoine du Nord",
"Madagascar",
"Malaisie",
"Malawi",
"Maldives (Îles)",
"Mali",
"Malte",
"Mariannes du Nord (Îles)",
"Maroc",
"Marshall (Îles)",
"Martinique",
"Maurice",
"Mauritanie",
"Mayotte",
"Mexique",
"Micronésie (États fédérés de)",
"Moldavie",
"Monaco",
"Mongolie",
"Montserrat",
"Mozambique",
"Myanmar",
"Namibie",
"Nauru",
"Nepal",
"Nicaragua",
"Niger",
"Nigeria",
"Niue",
"Norfolk (Îles)",
"Norvège",
"Nouvelle Calédonie",
"Nouvelle-Zélande",
"Oman",
"Ouganda",
"Ouzbékistan",
"Pakistan",
"Palau",
"Panama",
"Papouasie-Nouvelle-Guinée",
"Paraguay",
"Pays-Bas",
"Philippines",
"Pitcairn (Îles)",
"Pologne",
"Polynésie française",
"Porto Rico",
"Portugal",
"Pérou",
"Qatar",
"Roumanie",
"Royaume-Uni",
"Russie",
"Rwanda",
"Rép. Dém. du Congo",
"République centrafricaine",
"République Dominicaine",
"République tchèque",
"Réunion (La)",
"Sahara Occidental",
"Saint Pierre et Miquelon",
"Saint Vincent et les Grenadines",
"Saint-Kitts et Nevis",
"Saint-Marin (Rép. de)",
"Sainte Hélène",
"Sainte Lucie",
"Samoa",
"Samoa",
"Seychelles",
"Sierra Leone",
"Singapour",
"Slovaquie",
"Slovénie",
"Somalie",
"Soudan",
"Sri Lanka",
"Suisse",
"Suriname",
"Suède",
"Svalbard et Jan Mayen (Îles)",
"Swaziland",
"Syrie",
"São Tomé et Príncipe (Rép.)",
"Sénégal",
"Tadjikistan",
"Taiwan",
"Tanzanie",
"Tchad",
"Territoire britannique de l'océan Indien",
"Territoires français du sud",
"Thailande",
"Timor",
"Togo",
"Tokelau",
"Tonga",
"Trinité et Tobago",
"Tunisie",
"Turkménistan",
"Turks et Caïques (Îles)",
"Turquie",
"Tuvalu",
"Ukraine",
"Uruguay",
"Vanuatu",
"Vatican (Etat du)",
"Venezuela",
"Vierges (Îles)",
"Vierges britanniques (Îles)",
"Vietnam",
"Wallis et Futuna (Îles)",
"Yemen",
"Yougoslavie",
"Zambie",
"Zaïre",
"Zimbabwe",
)
regions = (
"Alsace",
"Aquitaine",
"Auvergne",
"Bourgogne",
"Bretagne",
"Centre",
"Champagne-Ardenne",
"Corse",
"Franche-Comté",
"Île-de-France",
"Languedoc-Roussillon",
"Limousin",
"Lorraine",
"Midi-Pyrénées",
"Nord-Pas-de-Calais",
"Basse-Normandie",
"Haute-Normandie",
"Pays-de-Loire",
"Picardie",
"Poitou-Charentes",
"Province-Alpes-Côte d'Azur",
"Rhone-Alpes",
"Guadeloupe",
"Martinique",
"Guyane",
"Réunion",
"Saint-Pierre-et-Miquelon",
"Mayotte",
"Saint-Barthélémy",
"Saint-Martin",
"Wallis-et-Futuna",
"Polynésie française",
"Nouvelle-Calédonie",
)
departments = (
("01", "Ain"),
("02", "Aisne"),
("03", "Allier"),
("04", "Alpes-de-Haute-Provence"),
("05", "Hautes-Alpes"),
("06", "Alpes-Maritimes"),
("07", "Ardèche"),
("08", "Ardennes"),
("09", "Ariège"),
("10", "Aube"),
("11", "Aude"),
("12", "Aveyron"),
("13", "Bouches-du-Rhône"),
("14", "Calvados"),
("15", "Cantal"),
("16", "Charente"),
("17", "Charente-Maritime"),
("18", "Cher"),
("19", "Corrèze"),
("2A", "Corse-du-Sud"),
("2B", "Haute-Corse"),
("21", "Côte-d'Or"),
("22", "Côtes-d'Armor"),
("23", "Creuse"),
("24", "Dordogne"),
("25", "Doubs"),
("26", "Drôme"),
("27", "Eure"),
("28", "Eure-et-Loir"),
("29", "Finistère"),
("30", "Gard"),
("31", "Haute-Garonne"),
("32", "Gers"),
("33", "Gironde"),
("34", "Hérault"),
("35", "Ille-et-Vilaine"),
("36", "Indre"),
("37", "Indre-et-Loire"),
("38", "Isère"),
("39", "Jura"),
("40", "Landes"),
("41", "Loir-et-Cher"),
("42", "Loire"),
("43", "Haute-Loire"),
("44", "Loire-Atlantique"),
("45", "Loiret"),
("46", "Lot"),
("47", "Lot-et-Garonne"),
("48", "Lozère"),
("49", "Maine-et-Loire"),
("50", "Manche"),
("51", "Marne"),
("52", "Haute-Marne"),
("53", "Mayenne"),
("54", "Meurthe-et-Moselle"),
("55", "Meuse"),
("56", "Morbihan"),
("57", "Moselle"),
("58", "Nièvre"),
("59", "Nord"),
("60", "Oise"),
("61", "Orne"),
("62", "Pas-de-Calais"),
("63", "Puy-de-Dôme"),
("64", "Pyrénées-Atlantiques"),
("65", "Hautes-Pyrénées"),
("66", "Pyrénées-Orientales"),
("67", "Bas-Rhin"),
("68", "Haut-Rhin"),
("69", "Rhône"),
("70", "Haute-Saône"),
("71", "Saône-et-Loire"),
("72", "Sarthe"),
("73", "Savoie"),
("74", "Haute-Savoie"),
("75", "Paris"),
("76", "Seine-Maritime"),
("77", "Seine-et-Marne"),
("78", "Yvelines"),
("79", "Deux-Sèvres"),
("80", "Somme"),
("81", "Tarn"),
("82", "Tarn-et-Garonne"),
("83", "Var"),
("84", "Vaucluse"),
("85", "Vendée"),
("86", "Vienne"),
("87", "Haute-Vienne"),
("88", "Vosges"),
("89", "Yonne"),
("90", "Territoire de Belfort"),
("91", "Essonne"),
("92", "Hauts-de-Seine"),
("93", "Seine-Saint-Denis"),
("94", "Val-de-Marne"),
("95", "Val-d'Oise"),
("971", "Guadeloupe"),
("972", "Martinique"),
("973", "Guyane"),
("974", "La Réunion"),
("976", "Mayotte"),
)
def street_prefix(self) -> str:
"""
:example: 'rue'
"""
return self.random_element(self.street_prefixes)
def city_prefix(self) -> str:
"""
:example: 'rue'
"""
return self.random_element(self.city_prefixes)
def administrative_unit(self) -> str:
"""
:example: 'Guadeloupe'
"""
return self.random_element(self.regions)
region = administrative_unit
def department(self) -> Tuple[str, str]:
"""
Randomly returns a french department ('departmentNumber' , 'departmentName').
:example: ('2B' . 'Haute-Corse')
"""
return self.random_element(self.departments)
def department_name(self) -> str:
"""
Randomly returns a french department name.
:example: 'Ardèche'
"""
return self.department()[1]
def department_number(self) -> str:
"""
Randomly returns a french department number.
:example: '59'
"""
return self.department()[0]
def postcode(self) -> str:
"""
Randomly returns a postcode generated from existing french department number.
exemple: '33260'
"""
department = self.department_number()
if department in ["2A", "2B"]:
department = "20"
return f"{department}{self.random_number(digits=5 - len(department), fix_len=True)}" | PypiClean |
/MedPy-0.4.0.tar.gz/MedPy-0.4.0/bin/medpy_graphcut_voxel.py | # build-in modules
from argparse import RawTextHelpFormatter
import argparse
import logging
import os
# third-party modules
import scipy
# path changes
# own modules
from medpy.core import ArgumentError, Logger
from medpy.io import load, save, header
from medpy import graphcut
from medpy.graphcut.wrapper import split_marker
# information
__author__ = "Oskar Maier"
__version__ = "r0.3.1, 2012-03-23"
__email__ = "[email protected]"
__status__ = "Release"
__description__ = """
Perform a binary graph cut using Boykov's max-flow/min-cut algorithm.
This implementation does only compute a boundary term and does not use
any regional term. The desired boundary term can be selected via the
--boundary argument. Depending on the selected term, an additional
image has to be supplied as badditional.
In the case of the difference of means, it is the original image.
Furthermore the algorithm requires a binary image with foreground
markers and a binary image with background markers.
Additionally a filename for the created binary mask marking foreground
and background has to be supplied.
Note that the input images must be of the same dimensionality,
otherwise an exception is thrown.
Note to take into account the input images orientation.
Note that the quality of the resulting segmentations depends also on
the quality of the supplied markers.
Copyright (C) 2013 Oskar Maier
This program comes with ABSOLUTELY NO WARRANTY; This is free software,
and you are welcome to redistribute it under certain conditions; see
the LICENSE file or <http://www.gnu.org/licenses/> for details.
"""
# code
def main():
# parse cmd arguments
parser = getParser()
parser.parse_args()
args = getArguments(parser)
# prepare logger
logger = Logger.getInstance()
if args.debug: logger.setLevel(logging.DEBUG)
elif args.verbose: logger.setLevel(logging.INFO)
# check if output image exists
if not args.force:
if os.path.exists(args.output):
logger.warning('The output image {} already exists. Exiting.'.format(args.output))
exit(-1)
# select boundary term
['diff_linear', 'diff_exp', 'diff_div', 'diff_pow', 'max_linear', 'max_exp', 'max_div', 'max_pow']
if 'diff_linear' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_difference_linear
logger.info('Selected boundary term: linear difference of intensities')
elif 'diff_exp' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_difference_exponential
logger.info('Selected boundary term: exponential difference of intensities')
elif 'diff_div' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_difference_division
logger.info('Selected boundary term: divided difference of intensities')
elif 'diff_pow' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_difference_power
logger.info('Selected boundary term: power based / raised difference of intensities')
elif 'max_linear' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_maximum_linear
logger.info('Selected boundary term: linear maximum of intensities')
elif 'max_exp' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_maximum_exponential
logger.info('Selected boundary term: exponential maximum of intensities')
elif 'max_div' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_maximum_division
logger.info('Selected boundary term: divided maximum of intensities')
elif 'max_pow' == args.boundary:
boundary_term = graphcut.energy_voxel.boundary_maximum_power
logger.info('Selected boundary term: power based / raised maximum of intensities')
# load input images
badditional_image_data, reference_header = load(args.badditional)
markers_image_data, _ = load(args.markers)
# split marker image into fg and bg images
fgmarkers_image_data, bgmarkers_image_data = split_marker(markers_image_data)
# check if all images dimensions are the same
if not (badditional_image_data.shape == fgmarkers_image_data.shape == bgmarkers_image_data.shape):
logger.critical('Not all of the supplied images are of the same shape.')
raise ArgumentError('Not all of the supplied images are of the same shape.')
# extract spacing if required
if args.spacing:
spacing = header.get_pixel_spacing(reference_header)
logger.info('Taking spacing of {} into account.'.format(spacing))
else:
spacing = False
# generate graph
logger.info('Preparing BK_MFMC C++ graph...')
gcgraph = graphcut.graph_from_voxels(fgmarkers_image_data,
bgmarkers_image_data,
boundary_term = boundary_term,
boundary_term_args = (badditional_image_data, args.sigma, spacing))
# execute min-cut
logger.info('Executing min-cut...')
maxflow = gcgraph.maxflow()
logger.debug('Maxflow is {}'.format(maxflow))
# reshape results to form a valid mask
logger.info('Applying results...')
result_image_data = scipy.zeros(bgmarkers_image_data.size, dtype=scipy.bool_)
for idx in range(len(result_image_data)):
result_image_data[idx] = 0 if gcgraph.termtype.SINK == gcgraph.what_segment(idx) else 1
result_image_data = result_image_data.reshape(bgmarkers_image_data.shape)
# save resulting mask
save(result_image_data.astype(scipy.bool_), args.output, reference_header, args.force)
logger.info('Successfully terminated.')
def getArguments(parser):
"Provides additional validation of the arguments collected by argparse."
return parser.parse_args()
def getParser():
"Creates and returns the argparse parser object."
parser = argparse.ArgumentParser(description=__description__, formatter_class=RawTextHelpFormatter)
parser.add_argument('sigma', type=float, help='The sigma required for the boundary terms.')
parser.add_argument('badditional', help='The additional image required by the boundary term. See there for details.')
parser.add_argument('markers', help='Image containing the foreground (=1) and background (=2) markers.')
parser.add_argument('output', help='The output image containing the segmentation.')
parser.add_argument('--boundary', default='diff_exp', help='The boundary term to use. Note that the ones prefixed with diff_ require the original image, while the ones prefixed with max_ require the gradient image.', choices=['diff_linear', 'diff_exp', 'diff_div', 'diff_pow', 'max_linear', 'max_exp', 'max_div', 'max_pow'])
parser.add_argument('-s', dest='spacing', action='store_true', help='Set this flag to take the pixel spacing of the image into account. The spacing data will be extracted from the baddtional image.')
parser.add_argument('-f', dest='force', action='store_true', help='Set this flag to silently override files that exist.')
parser.add_argument('-v', dest='verbose', action='store_true', help='Display more information.')
parser.add_argument('-d', dest='debug', action='store_true', help='Display debug information.')
return parser
if __name__ == "__main__":
main() | PypiClean |
/B9gemyaeix-4.14.1.tar.gz/B9gemyaeix-4.14.1/weblate/trans/views/settings.py |
from django.conf import settings
from django.contrib.auth.decorators import login_required
from django.core.exceptions import ObjectDoesNotExist, PermissionDenied, ValidationError
from django.http import FileResponse, Http404, JsonResponse
from django.shortcuts import get_object_or_404, redirect
from django.utils.decorators import method_decorator
from django.utils.translation import gettext as _
from django.views.decorators.cache import never_cache
from django.views.decorators.http import require_POST
from django.views.generic import TemplateView, View
from weblate.lang.models import Language
from weblate.trans.forms import (
AnnouncementForm,
ComponentDeleteForm,
ComponentMoveForm,
ComponentRenameForm,
ComponentSettingsForm,
ProjectDeleteForm,
ProjectLanguageDeleteForm,
ProjectRenameForm,
ProjectSettingsForm,
TranslationDeleteForm,
)
from weblate.trans.models import Announcement, Change, Component
from weblate.trans.tasks import (
component_removal,
create_project_backup,
project_removal,
)
from weblate.trans.util import redirect_param, render
from weblate.utils import messages
from weblate.utils.stats import ProjectLanguage
from weblate.utils.views import (
get_component,
get_project,
get_translation,
show_form_errors,
)
@never_cache
@login_required
def change_project(request, project):
obj = get_project(request, project)
if not request.user.has_perm("project.edit", obj):
raise Http404()
if request.method == "POST":
settings_form = ProjectSettingsForm(request, request.POST, instance=obj)
if settings_form.is_valid():
settings_form.save()
messages.success(request, _("Settings saved"))
return redirect("settings", project=obj.slug)
else:
messages.error(
request, _("Invalid settings, please check the form for errors!")
)
else:
settings_form = ProjectSettingsForm(request, instance=obj)
return render(
request,
"project-settings.html",
{"object": obj, "form": settings_form},
)
@never_cache
@login_required
def change_component(request, project, component):
obj = get_component(request, project, component)
if not request.user.has_perm("component.edit", obj):
raise Http404()
if request.method == "POST":
form = ComponentSettingsForm(request, request.POST, instance=obj)
if form.is_valid():
form.save()
messages.success(request, _("Settings saved"))
return redirect("settings", project=obj.project.slug, component=obj.slug)
else:
messages.error(
request, _("Invalid settings, please check the form for errors!")
)
# Get a fresh copy of object, otherwise it will use unsaved changes
# from the failed form
obj = Component.objects.get(pk=obj.pk)
else:
form = ComponentSettingsForm(request, instance=obj)
if obj.repo_needs_merge():
messages.warning(
request,
_(
"The repository is outdated, you might not get "
"expected results until you update it."
),
)
return render(
request,
"component-settings.html",
{"project": obj.project, "object": obj, "form": form},
)
@never_cache
@login_required
@require_POST
def dismiss_alert(request, project, component):
obj = get_component(request, project, component)
if not request.user.has_perm("component.edit", obj):
raise Http404()
try:
alert = obj.alert_set.get(name=request.POST["dismiss"])
if alert.obj.dismissable:
alert.dismissed = True
alert.save(update_fields=["dismissed"])
except ObjectDoesNotExist:
pass
return redirect_param(obj, "#alerts")
@login_required
@require_POST
def remove_translation(request, project, component, lang):
obj = get_translation(request, project, component, lang)
if not request.user.has_perm("translation.delete", obj):
raise PermissionDenied()
form = TranslationDeleteForm(obj, request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#delete")
obj.remove(request.user)
messages.success(request, _("Translation has been removed."))
return redirect(obj.component)
@login_required
@require_POST
def remove_component(request, project, component):
obj = get_component(request, project, component)
if not request.user.has_perm("component.edit", obj):
raise PermissionDenied()
form = ComponentDeleteForm(obj, request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#delete")
component_removal.delay(obj.pk, request.user.pk)
messages.success(request, _("Translation component was scheduled for removal."))
return redirect(obj.project)
@login_required
@require_POST
def remove_project(request, project):
obj = get_project(request, project)
if not request.user.has_perm("project.edit", obj):
raise PermissionDenied()
form = ProjectDeleteForm(obj, request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#delete")
project_removal.delay(obj.pk, request.user.pk)
messages.success(request, _("Project was scheduled for removal."))
return redirect("home")
@login_required
@require_POST
def remove_project_language(request, project, lang):
project_object = get_project(request, project)
language_object = get_object_or_404(Language, code=lang)
obj = ProjectLanguage(project_object, language_object)
if not request.user.has_perm("translation.delete", obj):
raise PermissionDenied()
form = ProjectLanguageDeleteForm(obj, request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#delete")
for translation in obj.translation_set:
translation.remove(request.user)
messages.success(request, _("Language of the project was removed."))
return redirect(project_object)
def perform_rename(form_cls, request, obj, perm: str):
if not request.user.has_perm(perm, obj):
raise PermissionDenied()
# Make sure any non-rename related issues are resolved first
try:
obj.full_clean()
except ValidationError as err:
messages.error(
request,
_("Cannot rename due to outstanding issue in the configuration: %s") % err,
)
return redirect_param(obj, "#rename")
form = form_cls(request, request.POST, instance=obj)
if not form.is_valid():
show_form_errors(request, form)
# Reload the object from db to revert possible rejected change
obj.refresh_from_db()
return redirect_param(obj, "#rename")
# Invalidate old stats
obj.stats.invalidate()
obj = form.save()
# Invalidate new stats
obj.stats.invalidate()
return redirect(obj)
@login_required
@require_POST
def rename_component(request, project, component):
obj = get_component(request, project, component)
return perform_rename(ComponentRenameForm, request, obj, "component.edit")
@login_required
@require_POST
def move_component(request, project, component):
obj = get_component(request, project, component)
return perform_rename(ComponentMoveForm, request, obj, "project.edit")
@login_required
@require_POST
def rename_project(request, project):
obj = get_project(request, project)
return perform_rename(ProjectRenameForm, request, obj, "project.edit")
@login_required
@require_POST
def announcement_translation(request, project, component, lang):
obj = get_translation(request, project, component, lang)
if not request.user.has_perm("component.edit", obj):
raise PermissionDenied()
form = AnnouncementForm(request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#announcement")
Announcement.objects.create(
user=request.user,
project=obj.component.project,
component=obj.component,
language=obj.language,
**form.cleaned_data,
)
return redirect(obj)
@login_required
@require_POST
def announcement_component(request, project, component):
obj = get_component(request, project, component)
if not request.user.has_perm("component.edit", obj):
raise PermissionDenied()
form = AnnouncementForm(request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#announcement")
Announcement.objects.create(
user=request.user, project=obj.project, component=obj, **form.cleaned_data
)
return redirect(obj)
@login_required
@require_POST
def announcement_project(request, project):
obj = get_project(request, project)
if not request.user.has_perm("project.edit", obj):
raise PermissionDenied()
form = AnnouncementForm(request.POST)
if not form.is_valid():
show_form_errors(request, form)
return redirect_param(obj, "#announcement")
Announcement.objects.create(user=request.user, project=obj, **form.cleaned_data)
return redirect(obj)
@login_required
@require_POST
def announcement_delete(request, pk):
announcement = get_object_or_404(Announcement, pk=pk)
if request.user.has_perm("announcement.delete", announcement):
announcement.delete()
return JsonResponse({"responseStatus": 200})
@login_required
def component_progress(request, project, component):
obj = get_component(request, project, component)
return_url = "component" if "info" in request.GET else "guide"
if not obj.in_progress():
return redirect(return_url, **obj.get_reverse_url_kwargs())
progress, log = obj.get_progress()
return render(
request,
"component-progress.html",
{
"object": obj,
"progress": progress,
"log": "\n".join(log),
"return_url": return_url,
},
)
class BackupsMixin:
@method_decorator(login_required)
def setup(self, request, *args, **kwargs):
super().setup(request, *args, **kwargs)
self.obj = get_project(request, kwargs["project"])
if not request.user.has_perm("project.edit", self.obj):
raise PermissionDenied()
class BackupsView(BackupsMixin, TemplateView):
template_name = "trans/backups.html"
def post(self, request, *args, **kwargs):
create_project_backup.delay(self.obj.pk)
messages.success(
request, _("Backup was triggered, it will be shorly available.")
)
return redirect("backups", project=self.obj.slug)
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["keep_count"] = settings.PROJECT_BACKUP_KEEP_COUNT
context["keep_days"] = settings.PROJECT_BACKUP_KEEP_DAYS
context["object"] = self.obj
context["backups"] = self.obj.list_backups()
return context
class BackupsDownloadView(BackupsMixin, View):
def get(self, request, *args, **kwargs):
for backup in self.obj.list_backups():
if backup["name"] == kwargs["backup"]:
return FileResponse(
open(backup["path"], "rb"),
as_attachment=True,
filename=backup["name"],
)
raise Http404 | PypiClean |
/DocOnce-1.5.15-py3-none-any.whl/doconce/plaintext.py | from __future__ import absolute_import
from builtins import str
from builtins import range
from past.builtins import basestring
import sys
import regex as re
from .common import default_movie, plain_exercise, bibliography, \
cite_with_multiple_args2multiple_cites, fix_ref_section_chapter
from .misc import option
def plain_author(authors_and_institutions, auth2index,
inst2index, index2inst, auth2email):
text = '\n'
for author in auth2index:
email = auth2email[author]
email_text = '' if email is None else '(%s)' % email
text += ' '.join([author, str(auth2index[author]), email_text]) + '\n'
text += '\n'
for index in index2inst:
text += '[%d] %s\n' % (index, index2inst[index])
text += '\n'
return text
def plain_ref_and_label(section_label2title, format, filestr):
filestr = fix_ref_section_chapter(filestr, format)
# remove label{...} from output (when only label{} on a line, remove
# the newline too, leave label in figure captions, and remove all the rest)
#filestr = re.sub(r'^label\{.+?\}\s*$', '', filestr, flags=re.MULTILINE)
cpattern = re.compile(r'^label\{.+?\}\s*$', flags=re.MULTILINE)
filestr = cpattern.sub('', filestr)
#filestr = re.sub(r'^(FIGURE:.+)label\{(.+?)\}', '\g<1>{\g<2>}', filestr, flags=re.MULTILINE)
cpattern = re.compile(r'^(FIGURE:.+)label\{(.+?)\}', flags=re.MULTILINE)
filestr = cpattern.sub('\g<1>{\g<2>}', filestr)
filestr = re.sub(r'label\{.+?\}', '', filestr) # all the remaining
# replace all references to sections:
for label in section_label2title:
filestr = filestr.replace('ref{%s}' % label,
'"%s"' % section_label2title[label])
from .common import ref2equations
filestr = ref2equations(filestr)
return filestr
def plain_index_bib(filestr, index, citations, pubfile, pubdata):
if citations:
filestr = cite_with_multiple_args2multiple_cites(filestr)
for label in citations:
filestr = filestr.replace('cite{%s}' % label,
'[%d]' % citations[label])
if pubfile is not None:
bibtext = bibliography(pubdata, citations, format='doconce')
bibtext = re.sub(r'label\{.+?\} ', '', bibtext)
# Remove boldface _author_ (typically 12. _John Doe and Jane Doe_.)
bibtext = re.sub(r'(\d+)\. _(.+)_\.', '\g<2>', bibtext)
filestr = re.sub(r'^BIBFILE:.+$', bibtext, filestr, flags=re.MULTILINE)
# remove all index entries:
filestr = re.sub(r'idx\{.+?\}\n?', '', filestr)
# no index since line numbers from the .do.txt (in index dict)
# never correspond to the output format file
#filestr += '\n\n======= Index =======\n\n'
#for word in index:
# filestr + = '%s, line %s\n' % (word, ', '.join(index[word]))
return filestr
def plain_toc(sections, filestr):
# Find minimum section level
tp_min = 4
for title, tp, label in sections:
if tp < tp_min:
tp_min = tp
s = 'Table of contents:\n\n'
for title, tp, label in sections:
s += ' '*(2*(tp-tp_min)) + title + '\n'
return s
def plain_box(text, title=''):
"""Wrap a box around the text, with a title on the upper box border."""
lines = text.splitlines()
maxlen = max([len(line) for line in lines])
newlines = []
# title can be :: since equations and code must be preceeded by ::
# and plaintext inserts a double colon
if title == '' or title.lower() == 'none' or title == '::':
newlines.append('|-' + '-'*maxlen + '-|')
else:
newlines.append(title + ' ' + '-'*(maxlen-len(title)) + '--|')
for line in lines:
newlines.append('| ' + line + ' '*(maxlen-len(line)) + ' |')
newlines.append('|-' + '-'*maxlen + '-|')
# Drop blank lines at the beginning
drop = 0
for line in newlines[1:]:
if re.search(r'[^\-| ]', line):
break
else:
drop += 1
for i in range(drop):
del newlines[1]
if re.search(r'^\w', newlines[0]):
# Insert a blank line
newlines.insert(1, '| ' + ' '*maxlen + ' |')
# Drop blank lines at the end
drop = 0
for line in reversed(newlines[:-1]):
if re.search(r'[^\-| ]', line):
break
else:
drop += 1
for i in range(1, drop+1, 1):
del newlines[-2]
return '\n' + '\n'.join(newlines) + '\n'
def plain_quiz(quiz):
# Simple typesetting of a quiz
import string
question_prefix = quiz.get('question prefix',
option('quiz_question_prefix=', 'Question:'))
common_choice_prefix = option('quiz_choice_prefix=', 'Choice')
quiz_expl = option('quiz_explanations=', 'on')
text = '\n\n'
if 'new page' in quiz:
text += '======= %s =======\n\n' % (quiz['new page'])
# Don't write Question: ... if inside an exercise section
if quiz.get('embedding', 'None') in ['exercise',]:
pass
else:
text += '\n'
if question_prefix:
text += '%s ' % (question_prefix)
text += quiz['question'] + '\n\n'
# List choices as paragraphs
for i, choice in enumerate(quiz['choices']):
#choice_no = i+1
choice_no = string.ascii_uppercase[i]
answer = choice[0].capitalize() + '!'
choice_prefix = common_choice_prefix
if 'choice prefix' in quiz:
if isinstance(quiz['choice prefix'][i], basestring):
choice_prefix = quiz['choice prefix'][i]
if choice_prefix == '' or choice_prefix[-1] in ['.', ':', '?']:
pass # don't add choice number/letter
else:
choice_prefix += ' %s:' % choice_no
# Let choice start with a newline if pure code starts the choice
# (test for different code block types so this function can work
# for other formats too...)
choice = choice[1].lstrip()
code_starters = 'Code::', '~~~', '```', '{{{'
for code_starter in code_starters:
if choice.startswith(code_starter):
choice = '\n' + choice
# Cannot treat explanations
text += '%s %s\n\n' % (choice_prefix, choice)
return text
def define(FILENAME_EXTENSION,
BLANKLINE,
INLINE_TAGS_SUBST,
CODE,
LIST,
ARGLIST,
TABLE,
EXERCISE,
FIGURE_EXT,
CROSS_REFS,
INDEX_BIB,
TOC,
ENVIRS,
QUIZ,
INTRO,
OUTRO,
filestr):
# all arguments are dicts and accept in-place modifications (extensions)
FILENAME_EXTENSION['plain'] = '.txt'
BLANKLINE['plain'] = '\n'
# replacement patterns for substitutions of inline tags
encoding = 'utf-8'
INLINE_TAGS_SUBST['plain'] = {
'math': r'\g<begin>\g<subst>\g<end>', # drop $ signs
'math2': r'\g<begin>\g<puretext>\g<end>',
'emphasize': None,
'bold': None,
'figure': None,
'movie': default_movie,
'verbatim': r'\g<begin>\g<subst>\g<end>', # no ` chars
#'linkURL': r'\g<begin>\g<link> (\g<url>)\g<end>',
'linkURL2': r'\g<link> (\g<url>)',
'linkURL3': r'\g<link> (\g<url>)',
'linkURL2v': r'\g<link> (\g<url>)',
'linkURL3v': r'\g<link> (\g<url>)',
'plainURL': r'\g<url>',
'colortext': '\g<text>',
'title': r'======= \g<subst> =======\n', # doconce top section, to be substituted later
'author': plain_author,
'date': r'\nDate: \g<subst>\n',
'chapter': lambda m: '%s\n%s' % (m.group('subst'), '%'*len(m.group('subst'))),
'section': lambda m: '%s\n%s' % (m.group('subst'), '='*len(m.group('subst'))),
'subsection': lambda m: '%s\n%s' % (m.group('subst'), '-'*len(m.group('subst'))),
'subsubsection': lambda m: '%s\n%s\n' % (m.group('subst'), '~'*len(m.group('subst'))),
'paragraph': r'*\g<subst>*\g<space>', # extra blank
'abstract': r'\n*\g<type>.* \g<text>\g<rest>',
'linebreak': r'\g<text>',
'footnote': None,
'non-breaking-space': ' ',
'ampersand2': r' \g<1>&\g<2>',
}
from .rst import rst_code
CODE['plain'] = rst_code
from .common import DEFAULT_ARGLIST
ARGLIST['plain'] = DEFAULT_ARGLIST
LIST['plain'] = {
'itemize':
{'begin': '', 'item': '*', 'end': '\n'},
'enumerate':
{'begin': '', 'item': '%d.', 'end': '\n'},
'description':
{'begin': '', 'item': '%s', 'end': '\n'},
'separator': '\n',
}
CROSS_REFS['plain'] = plain_ref_and_label
from .rst import rst_table
TABLE['plain'] = rst_table
#TABLE['plain'] = plain_table
EXERCISE['plain'] = plain_exercise
INDEX_BIB['plain'] = plain_index_bib
TOC['plain'] = plain_toc
from .common import indent_lines
ENVIRS['plain'] = {
'warning': lambda block, format, title='Warning', text_size='normal':
plain_box(block, title),
'notice': lambda block, format, title='Notice', text_size='normal':
plain_box(block, title),
'question': lambda block, format, title='Question', text_size='normal':
plain_box(block, title),
'hint': lambda block, format, title='Hint', text_size='normal':
plain_box(block, title),
'summary': lambda block, format, title='Summary', text_size='normal':
plain_box(block, title),
'block': lambda block, format, title='Block', text_size='normal':
plain_box(block, title),
'box': lambda block, format, title='none', text_size='normal':
plain_box(block, title),
'quote': lambda block, format, title='none', text_size='normal':
indent_lines(block, 'plain'),
}
QUIZ['plain'] = plain_quiz | PypiClean |
/CNFgen-0.9.2-py3-none-any.whl/cnfgen/families/cliquecoloring.py | from itertools import combinations
from cnfgen.formula.cnf import CNF
from cnfgen.localtypes import non_negative_int
def CliqueColoring(n, k, c, formula_class=CNF):
r"""Clique-coloring CNF formula
The formula claims that a graph :math:`G` with :math:`n` vertices
simultaneously contains a clique of size :math:`k` and a coloring
of size :math:`c`.
If :math:`k = c + 1` then the formula is clearly unsatisfiable,
and it is the only known example of a formula hard for cutting
planes proof system. [1]_
Variables :math:`e_{u,v}` to encode the edges of the graph.
Variables :math:`q_{i,v}` encode a function from :math:`[k]` to
:math:`[n]` that represents a clique.
Variables :math:`r_{v,\ell}` encode a function from :math:`[n]` to
:math:`[c]` that represents a coloring.
Parameters
----------
n : number of vertices in the graph
k : size of the clique
c : size of the coloring
Returns
-------
A CNF object
References
----------
.. [1] Pavel Pudlak.
Lower bounds for resolution and cutting plane proofs and
monotone computations.
Journal of Symbolic Logic (1997)
"""
non_negative_int(n, 'n')
non_negative_int(k, 'k')
non_negative_int(c, 'c')
description = "There is a graph of {0} vertices with a {1}-clique and a {2}-coloring".format(
n, k, c)
F = formula_class(description=description)
# Variables
e = F.new_combinations(n,2,label='e_{{{}}}')
q = F.new_mapping(k,n,label='q_{{{0},{1}}}')
r = F.new_mapping(n,c,label='r_{{{0},{1}}}')
# some vertex is i'th member of clique
F.force_complete_mapping(q)
F.force_functional_mapping(q)
F.force_injective_mapping(q)
for u, v in e.indices():
for i, j in combinations(q.domain(), 2):
F.add_clause([e(u, v), -q(i, u), -q(j, v)])
F.add_clause([e(u, v), -q(i, v), -q(j, u)])
# every vertex v has exactly one colour
F.force_complete_mapping(r)
F.force_functional_mapping(r)
# neighbours have distinct colours
for u, v in e.indices():
for ell in r.range():
F.add_clause([-e(u, v), -r(u, ell), -r(v, ell)])
return F | PypiClean |
/Cubane-1.0.11.tar.gz/Cubane-1.0.11/cubane/ishop/static/cubane/ishop/js/default.js | (function(){
"use strict";
cubane.require('cubane.dialog');
if ( window['ishop'] === undefined ) window.ishop = {};
/*******************************************************************************
* Calculate and round price and convert from net to gross based on current vat
* rate.
******************************************************************************/
ishop.PriceInputController = function(url, vat, net, gross, price_calculation) {
this.init(url, vat, net, gross, price_calculation);
};
ishop.PriceInputController.prototype = {
PRICE_CALCULATION: {
GROSS: 'gross',
GROSS_ONLY: 'gross-only',
NET: 'net'
},
init: function(url, vat, net, gross, price_calculation) {
this._bound = {
onVatChanged: $.proxy(this.onVatChanged, this),
onNetChanged: $.proxy(this.onNetChanged, this),
onGrossChanged: $.proxy(this.onGrossChanged, this),
};
this._url = url;
this._vat = vat;
this._net = net;
this._gross = gross;
this._price_calculation = price_calculation;
this._vat.bind('change', this._bound.onVatChanged);
this._net.bind('change', this._bound.onNetChanged);
this._gross.bind('change', this._bound.onGrossChanged);
},
dispose: function() {
this._vat.unbind('change', this._bound.onVatChanged);
this._net.unbind('change keyup', this._bound.onNetChanged);
this._gross.unbind('change keyup', this._bound.onGrossChanged);
this._bound = null;
this._url = null;
this._vat = null;
this._net = null;
this._gross = null;
this._price_calculation = null;
},
onVatChanged: function() {
if ( this._price_calculation == this.PRICE_CALCULATION.GROSS ) {
this.update($('#id_net_price').val(), null);
} else if ( this._price_calculation == this.PRICE_CALCULATION.NET ) {
this.update(null, $('#id_gross_price').val());
}
},
onNetChanged: function() {
this.update($('#id_net_price').val(), null);
},
onGrossChanged: function() {
this.update(null, $('#id_gross_price').val());
},
update: function(net, gross) {
var data = {
vat: $('#id_vat').val()
};
if ( net !== null ) data['net'] = net;
if ( gross !== null ) data['gross'] = gross;
$.post(this._url, data, $.proxy(function(json) {
$('#id_net_price').val(json.net);
$('#id_gross_price').val(json.gross);
}, this), 'json');
}
};
/*******************************************************************************
* Round price values after changing them
******************************************************************************/
ishop.PriceRounder = function(url, elements) {
this.init(url, elements);
};
ishop.PriceRounder.prototype = {
init: function(url, elements) {
this._bound = {
onChanged: $.proxy(this.onChanged, this)
}
this._url = url
this._elements = elements;
this._elements.bind('change', this._bound.onChanged);
},
dispose: function() {
this._elements.unbind('change', this._bound.onChanged);
this._url = null;
this._elements = null;
this._bound = null;
},
onChanged: function(e) {
var input = $(e.target);
$.post(this._url, { value: input.val() }, function(json) {
input.val(json.value);
}, 'json');
}
};
/*******************************************************************************
* Stock level controller
******************************************************************************/
ishop.StockLevelController = function () {
this.init();
};
ishop.StockLevelController.prototype = {
init: function () {
this._bound = {
onStockChanged: $.proxy(this.onStockChanged, this)
};
$('.stock').bind('change', this._bound.onStockChanged);
this.updateUIState();
},
dispose: function () {
$('.stock').unbind('change', this._bound.onStockChanged);
this._bound = null;
},
onStockChanged: function (e) {
var select = $(e.target);
this.updateUIState(select);
},
updateUIState: function(select) {
if ( !select ) {
var elements = $('.stock');
for ( var i = 0; i < elements.length; i++ ) {
this.updateUIState(elements.eq(i));
}
} else {
var level = select.closest('tr').find('.stocklevel');
if ( select.val() == '3' ) {
level.css('opacity', 1).attr('disabled', false);
} else {
level.css('opacity', 0.3).attr('disabled', true);
}
}
}
};
/*
* US States
*/
$(document).ready(function() {
var usstates = new innershed.USStates();
var usstates_delivery = new innershed.USStates(
$('#id_delivery_country'),
$('#id_delivery_county'),
$('#id_delivery_postcode')
);
});
/*
* Shop Data Import
*/
$(document).ready(function() {
$('.cubane-ishop-dataimport-form form').on('submit', function() {
cubane.dialog.working('Importing data', 'This process may take a minute, Please Wait...');
});
});
}()); | PypiClean |
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