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TCU/usageexample/automationexample.py | p--q/TCU | 0 | 11767 | <reponame>p--q/TCU
#!/opt/libreoffice5.4/program/python
# -*- coding: utf-8 -*-
import unohelper # オートメーションには必須(必須なのはuno)。
def macro():
ctx = XSCRIPTCONTEXT.getComponentContext() # コンポーネントコンテクストの取得。
smgr = ctx.getServiceManager() # サービスマネージャーの取得。
tcu = smgr.createInstanceWithContext("pq.Tcu", ctx) # サービス名か実装名でインスタンス化。
print("\n".join(tcu.treelines(ctx)))
g_exportedScripts = macro, #マクロセレクターに限定表示させる関数をタプルで指定。
if __name__ == "__main__": # オートメーションで実行するとき
def automation(): # オートメーションのためにglobalに出すのはこの関数のみにする。
import officehelper
from functools import wraps
import sys
from com.sun.star.beans import PropertyValue
from com.sun.star.script.provider import XScriptContext
def connectOffice(func): # funcの前後でOffice接続の処理
@wraps(func)
def wrapper(): # LibreOfficeをバックグラウンドで起動してコンポーネントテクストとサービスマネジャーを取得する。
try:
ctx = officehelper.bootstrap() # コンポーネントコンテクストの取得。
except:
print("Could not establish a connection with a running office.", file=sys.stderr)
sys.exit()
print("Connected to a running office ...")
smgr = ctx.getServiceManager() # サービスマネジャーの取得。
print("Using {} {}".format(*_getLOVersion(ctx, smgr))) # LibreOfficeのバージョンを出力。
return func(ctx, smgr) # 引数の関数の実行。
def _getLOVersion(ctx, smgr): # LibreOfficeの名前とバージョンを返す。
cp = smgr.createInstanceWithContext('com.sun.star.configuration.ConfigurationProvider', ctx)
node = PropertyValue(Name = 'nodepath', Value = 'org.openoffice.Setup/Product' ) # share/registry/main.xcd内のノードパス。
ca = cp.createInstanceWithArguments('com.sun.star.configuration.ConfigurationAccess', (node,))
return ca.getPropertyValues(('ooName', 'ooSetupVersion')) # LibreOfficeの名前とバージョンをタプルで返す。
return wrapper
@connectOffice # createXSCRIPTCONTEXTの引数にctxとsmgrを渡すデコレータ。
def createXSCRIPTCONTEXT(ctx, smgr): # XSCRIPTCONTEXTを生成。
class ScriptContext(unohelper.Base, XScriptContext):
def __init__(self, ctx):
self.ctx = ctx
def getComponentContext(self):
return self.ctx
def getDesktop(self):
return ctx.getByName('/singletons/com.sun.star.frame.theDesktop') # com.sun.star.frame.Desktopはdeprecatedになっている。
def getDocument(self):
return self.getDesktop().getCurrentComponent()
return ScriptContext(ctx)
XSCRIPTCONTEXT = createXSCRIPTCONTEXT() # XSCRIPTCONTEXTの取得。
doc = XSCRIPTCONTEXT.getDocument() # 現在開いているドキュメントを取得。
doctype = "scalc", "com.sun.star.sheet.SpreadsheetDocument" # Calcドキュメントを開くとき。
# doctype = "swriter", "com.sun.star.text.TextDocument" # Writerドキュメントを開くとき。
if (doc is None) or (not doc.supportsService(doctype[1])): # ドキュメントが取得できなかった時またはCalcドキュメントではない時
XSCRIPTCONTEXT.getDesktop().loadComponentFromURL("private:factory/{}".format(doctype[0]), "_blank", 0, ()) # ドキュメントを開く。ここでdocに代入してもドキュメントが開く前にmacro()が呼ばれてしまう。
flg = True
while flg:
doc = XSCRIPTCONTEXT.getDocument() # 現在開いているドキュメントを取得。
if doc is not None:
flg = (not doc.supportsService(doctype[1])) # ドキュメントタイプが確認できたらwhileを抜ける。
return XSCRIPTCONTEXT
XSCRIPTCONTEXT = automation() # XSCRIPTCONTEXTを取得。
macro() # マクロの実行。
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SLpackage/private/pacbio/pythonpkgs/pbsmrtpipe/lib/python2.7/site-packages/pbsmrtpipe/validators.py | fanglab/6mASCOPE | 5 | 130183 | """General validation functions"""
from __future__ import absolute_import, division, print_function
import logging
import types
import inspect
from pbcommand.models import (FileTypes, TaskTypes, SymbolTypes, ResourceTypes, FileType)
from pbsmrtpipe.exceptions import (MalformedMetaTaskError, MalformedPipelineError)
from pbsmrtpipe.constants import RX_VERSION, RX_CHUNK_KEY, RX_TASK_ID
log = logging.getLogger(__name__)
def to_list_if_necessary(tuple_or_s):
if isinstance(tuple_or_s, tuple):
return list(tuple_or_s)
return tuple_or_s
def __validate_output_file_names(output_types, output_file_names):
errors = []
if isinstance(output_file_names, (list, tuple)):
for x in output_file_names:
if isinstance(x, (list, tuple)):
if len(x) != 2:
errors.append("Malformed output file name {x}. Expected 2-tuple (str, str).".format(x=x))
if len(output_file_names) == len(output_types):
# this is only branch where the outputs and override outputs file names are valid
return True
else:
errors.append("Malformed output file names. Expected {n}. Got {m}".format(n=output_types, m=output_file_names))
else:
errors.append("Malformed output file name. Expected [(str, str)]. Got {m}".format(m=output_file_names))
log.error("\n".join(errors))
raise ValueError("\n".join(errors))
def _validate_output_file_names(output_types, output_files_names_or_none):
if output_files_names_or_none is not None:
__validate_output_file_names(output_types, output_files_names_or_none)
out_names = output_files_names_or_none
else:
out_names = []
return out_names
def _validate_output_file_names_or_raise(output_types, output_file_names_or_none, task_id):
try:
return _validate_output_file_names(output_types, output_file_names_or_none)
except Exception:
msg = "task id {i} Output file types ({n}) and override output file names ({m}) supplied are NOT compatible ".format(n=len(output_types), m=len(output_file_names_or_none), i=task_id)
log.error(msg)
raise
def __validate_provided_file_types(file_types):
def _is_valid(x):
if not isinstance(x, FileType):
raise TypeError("Invalid FileType. Got {t}".format(t=type(x)))
for i in file_types:
_is_valid(i)
return file_types
def validate_provided_file_types(file_type_or_file_types):
if isinstance(file_type_or_file_types, FileType):
return [file_type_or_file_types]
return __validate_provided_file_types(file_type_or_file_types)
def __is_schema(d):
try:
p = d['property']
keys = p.keys()
oid = keys[0]
if len(keys) != 1:
raise IndexError
_ = d['property'][oid]['default']
return True
except (KeyError, IndexError):
return False
def _is_schema_list(value):
if isinstance(value, dict):
if value:
__is_schema(value)
return value
else:
# empty
return value
if isinstance(value, (list, tuple)):
return all(__is_schema(x) for x in value)
return False
def _validate_mutable_files(mutable_files_or_none, input_types, output_types):
"""
1. Valid well-formed string
2. Valid that indices are pointed
3. Valid the input/output types are the same
:param mutable_files_or_none: [("$input.0, "$output.0"), ]
:param input_types:
:param output_types:
:return:
"""
if mutable_files_or_none is None:
return ()
for mutable_file in mutable_files_or_none:
if len(mutable_file) != 2:
raise ValueError("Malformed mutable file name {n}. Expected tuple of (str, str)".format(n=mutable_file))
in_f, out_f = mutable_file
if not in_f.startswith("$inputs.") or not out_f.startswith("$outputs.0"):
raise ValueError("Malformed mutable file ({i}, {f})".format(i=in_f, f=out_f))
ix = int(in_f.split("$inputs.")[-1])
ox = int(out_f.split("$outputs.")[-1])
ixt = input_types[ix]
oxt = output_types[ox]
if ixt != oxt:
log.warn("Mutable types are different. {i} {t} -> {o} {f}".format(i=ix, t=ixt, o=ox, f=oxt))
# we got here, everything is fine
return mutable_files_or_none
def _validate_func_with_n_args(nargs, func):
p = inspect.getargspec(func)
if len(p.args) != nargs:
raise ValueError("Expected func {x} to have {n} args. Got {y}".format(x=func.__name__, n=nargs, y=len(p.args)))
return func
def _validate_chunk_only_input_type(in_out_types):
if len(in_out_types) == 1:
if in_out_types[0] == FileTypes.CHUNK:
return True
raise ValueError("Expected chunk file type in {i}".format(i=in_out_types))
def _get_class_attr_or_raise(class_name, attr, d):
if attr not in d:
raise MalformedMetaTaskError("MetaTask class '{c}' is missing required class var '{n}'".format(c=class_name, n=attr))
else:
return d[attr]
def _raise_malformed_task_attr(msg):
def _wrapper(m=None):
msg_ = msg + " " + m if m is not None else msg
raise MalformedMetaTaskError(msg_)
return _wrapper
def validate_task_type(x):
_raise = _raise_malformed_task_attr("IS_DISTRIBUTED must be a DI List or primitive value {x}.".format(x=bool))
if isinstance(x, bool):
return x
else:
_raise("Incompatible type. Expected bool")
return x
def _validate_in_out_types(x):
_raise = _raise_malformed_task_attr("In/Out types must be defined as list of (FileTypes.FILE, label, description) or a single value FileTypes.FILE")
processed_in_out_types = []
if isinstance(x, (list, tuple)):
for i in x:
_raise_type = lambda: _raise("Expected FileType. Got {t}".format(t=type(i)))
# Support the new and old format
if isinstance(i, (list, tuple)):
if len(i) == 3:
if isinstance(i[0], FileType):
processed_in_out_types.append(i[0])
else:
_raise_type()
else:
_raise_type()
elif isinstance(i, FileType):
processed_in_out_types.append(i)
else:
_raise_type()
else:
_raise("Got type {t}".format(t=type(x)))
return processed_in_out_types
def _validate_chunk_in_out_type(msg):
def _f(x):
_raise = _raise_malformed_task_attr("{m} Got {x}".format(x=x, m=msg))
x = _validate_in_out_types(x)
if isinstance(x, (list, tuple)):
if len(x) == 1:
if x[0] is FileTypes.CHUNK:
return x
_raise()
return _f
def _validate_scatter_output_types(x):
_f = _validate_chunk_in_out_type("Scatter outputs type must be ONLY one chunk file type")
return _f(x)
def _validate_gather_input_types(x):
_f = _validate_chunk_in_out_type("Gather input type must be ONLY one chunk file type")
return _f(x)
def _validate_gather_output_types(x):
_raise = _raise_malformed_task_attr("Gather output types must be a single file type. Got {x}".format(x=x))
if isinstance(x, (list, tuple)):
# Only one output is allowed
if len(x) == 1:
# old format
if isinstance(x, FileType):
return [x]
# New Format [(FileType, label, desc)]
if isinstance(x[0], (list, tuple)):
if isinstance(x[0][0], FileType):
return [x[0][0]]
_raise()
def _validate_schema_options(x):
_raise = _raise_malformed_task_attr("Schema options must be provided as DI list or dict. Got type {t}.".format(t=type(x)))
# Standard form
if isinstance(x, dict):
if x:
is_valid = _is_schema_list(x)
if is_valid:
return x
else:
# emtpy dict
return x
elif isinstance(x, (list, tuple)):
x = to_list_if_necessary(x)
if not __is_schema(x[0]):
_raise("When task options are provided as DI model list, the first item must be the schema options for the Task.")
return x
# All other cases fail
_raise()
def _validate_nproc(x):
msg = "NPROC ('{x}') must be a DI LIST or primitive int value, or {s}".format(x=x, s=SymbolTypes.MAX_NPROC)
_raise = _raise_malformed_task_attr(msg)
if isinstance(x, int):
if x > 0:
return x
_raise("NPROC must be > 0")
elif isinstance(x, str):
if x == SymbolTypes.MAX_NPROC:
return x
else:
_raise("")
elif isinstance(x, (tuple, list)):
# Validate DI
return to_list_if_necessary(x)
else:
_raise("Got type (t)").format(t=type(x))
return x
def _validate_task_id(x):
if isinstance(x, str):
if RX_TASK_ID.match(x):
return x
else:
raise MalformedMetaTaskError("Task id '{n}' must match {p}".format(p=RX_TASK_ID.pattern, n=x))
def _validate_resource_types(x):
if x is None:
return ()
_raise = _raise_malformed_task_attr("Resource types must be a list with valid values {x}.".format(x=ResourceTypes.ALL()))
if isinstance(x, (list, tuple)):
for i in x:
if i not in ResourceTypes.ALL():
_raise("Invalid resource value '{x}'".format(x=i))
return x
else:
_raise("Invalid type {x}".format(x=x))
def _validate_version(x):
m = RX_VERSION.match(x)
if m is None:
_raise_malformed_task_attr("Version '{v}' should match {p}".format(v=x, p=RX_VERSION.pattern))
return x
def _validate_nchunks(x):
if isinstance(x, str):
if x == SymbolTypes.MAX_NCHUNKS:
return x
if isinstance(x, int):
return x
if isinstance(x, (list, tuple)):
if isinstance(list(x)[-1], types.FunctionType):
# Add more validation here
return x
msg = "Chunk only supports int or {x}, or DI model list".format(x=SymbolTypes.MAX_NCHUNKS)
_raise_malformed_task_attr(msg)
def _validate_chunk_keys(chunk_keys):
if isinstance(chunk_keys, (list, tuple)):
if not chunk_keys:
_raise_malformed_task_attr("CHUNK_KEYS can NOT be empty.")
for chunk_key in chunk_keys:
if RX_CHUNK_KEY.match(chunk_key) is None:
_raise_malformed_task_attr("CHUNK_KEYS '{x}' must match pattern {p}".format(x=chunk_key, p=RX_CHUNK_KEY))
return chunk_keys
_raise_malformed_task_attr("CHUNK_KEYS '{m}' is malformed".format(m=chunk_keys))
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] |
encyclopaedia/labels.py | tcyrus/renpy-encyclopaedia | 0 | 10039 | <reponame>tcyrus/renpy-encyclopaedia
from renpy import store
class Labels(store.object):
"""Controls how the labels that display Encyclopaedia data appear.
Attributes:
percentage_label (str): Placed next to the percentage unlocked number
page_label (str): Placed before the entry page displayed
page_separator_label (str): Placed in-between the
current page number and the total page number
sort_number_label (str): Label for Number Sorting
sort_alphabetical_label (str): Label for Alphabetical sorting
sort_reverse_alphabetical_label (str): Label for Reverse Alphabetical
sorting
sort_subject_label (str): Label for Subject sorting
sort_unread_label (str): Label for Unread sorting
unread_entry_label (str): Default for the tag next to unread entries
locked_entry_label (str): Default for a "Locked Entry" button
"""
def __init__(self, encyclopaedia):
self.encyclopaedia = encyclopaedia
self.percentage_label = '%'
self.page_label = 'Page'
self.page_separator_label = '/'
self.sort_number_label = "Number"
self.sort_alphabetical_label = "A to Z"
self.sort_reverse_alphabetical_label = "Z to A"
self.sort_subject_label = "Subject"
self.sort_unread_label = "Unread"
self.unread_entry_label = "New!"
self.locked_entry_label = "???"
@property
def percentage_unlocked(self):
"""Percentage representation of the amount of the encyclopaedia
that's unlocked. ie: '50%'.
Returns:
str
"""
percentage_unlocked = int(self.encyclopaedia.percentage_unlocked)
return "{}{}".format(percentage_unlocked, self.percentage_label)
@property
def entry_current_page(self):
"""The sub-page of an entry that is being viewed.
Returns:
str
"""
try:
total_pages = self.encyclopaedia.active.pages
except AttributeError:
raise AttributeError(
"Cannot display Entry's current page when no entry is open."
)
label = "{0} {1} {2} {3}".format(
self.page_label,
self.encyclopaedia.sub_current_position,
self.page_separator_label,
total_pages
)
return label
@property
def sorting_mode(self):
"""Label for the encyclopaedia's current sorting mode.
Returns:
str
"""
enc = self.encyclopaedia
sorting_strings = {
enc.SORT_NUMBER: self.sort_number_label,
enc.SORT_ALPHABETICAL: self.sort_alphabetical_label,
enc.SORT_REVERSE_ALPHABETICAL: self.sort_reverse_alphabetical_label, # NOQA: E501
enc.SORT_SUBJECT: self.sort_subject_label,
enc.SORT_UNREAD: self.sort_unread_label
}
return sorting_strings[enc.sorting_mode]
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freezer/job.py | mr-smart/freezer | 0 | 94711 | <filename>freezer/job.py
"""
(c) Copyright 2014,2015 Hewlett-Packard Development Company, L.P.
(C) Copyright 2016 Hewlett Packard Enterprise Development Company LP
Licensed 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.
"""
import abc
import datetime
import os
import sys
import time
from oslo_config import cfg
from oslo_log import log
from oslo_utils import importutils
import six
from freezer.openstack import admin
from freezer.openstack import backup
from freezer.openstack import restore
from freezer.snapshot import snapshot
from freezer.utils import checksum
from freezer.utils import exec_cmd
from freezer.utils import utils
CONF = cfg.CONF
LOG = log.getLogger(__name__)
@six.add_metaclass(abc.ABCMeta)
class Job(object):
"""
:type storage: freezer.storage.base.Storage
:type engine: freezer.engine.engine.BackupEngine
"""
def __init__(self, conf_dict, storage):
self.conf = conf_dict
self.storage = storage
self.engine = conf_dict.engine
self._general_validation()
self._validate()
@abc.abstractmethod
def _validate(self):
"""
Method that validates if all arguments available to execute the job
or not
:return: True or raise an error
"""
pass
def _general_validation(self):
"""
Apply general validation rules.
:return: True or raise an error
"""
LOG.info("Validating args for the {0} job.".format(self.conf.action))
if not self.conf.action:
raise ValueError("Please provide a valid action with --action")
if self.conf.action in ('backup', 'restore', 'admin') \
and self.conf.backup_media == 'fs' \
and not self.conf.backup_name:
raise ValueError('A value for --backup-name is required')
@abc.abstractmethod
def execute(self):
pass
class InfoJob(Job):
def _validate(self):
# no validation required for this job
pass
def execute(self):
info = self.storage.info()
if not info:
return
fields = ["Container", "Size", "Object Count"]
data = []
for container in info:
values = [
container.get('container_name'),
container.get('size'),
container.get('objects_count')
]
data.append(values)
return [fields, data]
class BackupJob(Job):
def _validate(self):
if self.conf.mode == 'fs':
if not self.conf.path_to_backup:
raise ValueError('path-to-backup argument must be provided')
if self.conf.no_incremental and (self.conf.max_level or
self.conf.always_level):
raise Exception(
'no-incremental option is not compatible '
'with backup level options')
if self.conf.mode == 'nova':
if not self.conf.no_incremental:
raise ValueError("Incremental nova backup is not supported")
if not self.conf.nova_inst_id and not self.conf.project_id:
raise ValueError("nova-inst-id or project-id"
" argument must be provided")
if self.conf.mode == 'cinder':
if not self.conf.cinder_vol_id:
raise ValueError("cinder-vol-id argument must be provided")
if self.conf.mode == "cindernative":
if not self.conf.cindernative_vol_id:
raise ValueError("cindernative-vol-id"
" argument must be provided")
def execute(self):
LOG.info('Backup job started. '
'backup_name: {0}, container: {1}, hostname: {2}, mode: {3},'
' Storage: {4}, compression: {5}'
.format(self.conf.backup_name, self.conf.container,
self.conf.hostname, self.conf.mode, self.conf.storage,
self.conf.compression))
try:
if self.conf.mode is 'fs' and self.conf.sync:
LOG.info('Executing sync to flush the file system buffer.')
(out, err) = utils.create_subprocess('sync')
if err:
LOG.error('Error while sync exec: {0}'.format(err))
except Exception as error:
LOG.error('Error while sync exec: {0}'.format(error))
if not self.conf.mode:
raise ValueError("Empty mode")
mod_name = 'freezer.mode.{0}.{1}'.format(
self.conf.mode, self.conf.mode.capitalize() + 'Mode')
app_mode = importutils.import_object(mod_name, self.conf)
backup_level = self.backup(app_mode)
level = backup_level or 0
metadata = {
'curr_backup_level': level,
'fs_real_path': self.conf.path_to_backup,
'vol_snap_path': self.conf.path_to_backup,
'client_os': sys.platform,
'client_version': self.conf.__version__,
'time_stamp': self.conf.time_stamp,
}
fields = ['action',
'always_level',
'backup_media',
'backup_name',
'container',
'container_segments',
'dry_run',
'hostname',
'path_to_backup',
'max_level',
'mode',
'backup_name',
'time_stamp',
'log_file',
'storage',
'mode',
'os_auth_version',
'proxy',
'compression',
'ssh_key',
'ssh_username',
'ssh_host',
'ssh_port',
'consistency_checksum'
]
for field_name in fields:
metadata[field_name] = self.conf.__dict__.get(field_name, '') or ''
return metadata
def backup(self, app_mode):
"""
:type app_mode: freezer.mode.mode.Mode
:return:
"""
backup_media = self.conf.backup_media
time_stamp = utils.DateTime.now().timestamp
self.conf.time_stamp = time_stamp
if backup_media == 'fs':
LOG.info('Path to backup: {0}'.format(self.conf.path_to_backup))
app_mode.prepare()
snapshot_taken = snapshot.snapshot_create(self.conf)
if snapshot_taken:
app_mode.release()
try:
filepath = '.'
chdir_path = os.path.expanduser(
os.path.normpath(self.conf.path_to_backup.strip()))
if not os.path.exists(chdir_path):
msg = 'Path to backup does not exist {0}'.format(
chdir_path)
LOG.critical(msg)
raise IOError(msg)
if not os.path.isdir(chdir_path):
filepath = os.path.basename(chdir_path)
chdir_path = os.path.dirname(chdir_path)
os.chdir(chdir_path)
# Checksum for Backup Consistency
if self.conf.consistency_check:
ignorelinks = (self.conf.dereference_symlink is None or
self.conf.dereference_symlink == 'hard')
consistency_checksum = checksum.CheckSum(
filepath, ignorelinks=ignorelinks).compute()
LOG.info('Computed checksum for consistency {0}'.
format(consistency_checksum))
self.conf.consistency_checksum = consistency_checksum
return self.engine.backup(
backup_resource=filepath,
hostname_backup_name=self.conf.hostname_backup_name,
no_incremental=self.conf.no_incremental,
max_level=self.conf.max_level,
always_level=self.conf.always_level,
restart_always_level=self.conf.restart_always_level)
finally:
# whether an error occurred or not, remove the snapshot anyway
app_mode.release()
if snapshot_taken:
snapshot.snapshot_remove(
self.conf, self.conf.shadow,
self.conf.windows_volume)
backup_os = backup.BackupOs(self.conf.client_manager,
self.conf.container,
self.storage)
if backup_media == 'nova':
if self.conf.project_id:
return self.engine.backup_nova_tenant(
project_id=self.conf.project_id,
hostname_backup_name=self.conf.hostname_backup_name,
no_incremental=self.conf.no_incremental,
max_level=self.conf.max_level,
always_level=self.conf.always_level,
restart_always_level=self.conf.restart_always_level)
else:
LOG.info('Executing nova backup. Instance ID: {0}'.format(
self.conf.nova_inst_id))
hostname_backup_name = os.path.join(
self.conf.hostname_backup_name,
self.conf.nova_inst_id)
return self.engine.backup(
backup_resource=self.conf.nova_inst_id,
hostname_backup_name=hostname_backup_name,
no_incremental=self.conf.no_incremental,
max_level=self.conf.max_level,
always_level=self.conf.always_level,
restart_always_level=self.conf.restart_always_level)
elif backup_media == 'cindernative':
LOG.info('Executing cinder native backup. Volume ID: {0}, '
'incremental: {1}'.format(self.conf.cindernative_vol_id,
self.conf.incremental))
backup_os.backup_cinder(self.conf.cindernative_vol_id,
name=self.conf.backup_name,
incremental=self.conf.incremental)
elif backup_media == 'cinder':
LOG.info('Executing cinder snapshot. Volume ID: {0}'.format(
self.conf.cinder_vol_id))
backup_os.backup_cinder_by_glance(self.conf.cinder_vol_id)
elif backup_media == 'cinderbrick':
LOG.info('Executing cinder volume backup using os-brick. '
'Volume ID: {0}'.format(self.conf.cinderbrick_vol_id))
return self.engine.backup(
backup_resource=self.conf.cinderbrick_vol_id,
hostname_backup_name=self.conf.hostname_backup_name,
no_incremental=self.conf.no_incremental,
max_level=self.conf.max_level,
always_level=self.conf.always_level,
restart_always_level=self.conf.restart_always_level)
else:
raise Exception('unknown parameter backup_media %s' % backup_media)
return None
class RestoreJob(Job):
def _validate(self):
if not any([self.conf.restore_abs_path,
self.conf.nova_inst_id,
self.conf.cinder_vol_id,
self.conf.cindernative_vol_id,
self.conf.cinderbrick_vol_id,
self.conf.project_id]):
raise ValueError("--restore-abs-path is required")
if not self.conf.container:
raise ValueError("--container is required")
if self.conf.no_incremental and (self.conf.max_level or
self.conf.always_level):
raise Exception(
'no-incremental option is not compatible '
'with backup level options')
def execute(self):
conf = self.conf
LOG.info('Executing Restore...')
restore_timestamp = None
restore_abs_path = conf.restore_abs_path
if conf.restore_from_date:
restore_timestamp = utils.date_to_timestamp(conf.restore_from_date)
if conf.backup_media == 'fs':
self.engine.restore(
hostname_backup_name=self.conf.hostname_backup_name,
restore_resource=restore_abs_path,
overwrite=conf.overwrite,
recent_to_date=restore_timestamp,
backup_media=conf.mode)
try:
if conf.consistency_checksum:
backup_checksum = conf.consistency_checksum
restore_checksum = checksum.CheckSum(restore_abs_path,
ignorelinks=True)
if restore_checksum.compare(backup_checksum):
LOG.info('Consistency check success.')
else:
raise ConsistencyCheckException(
"Backup Consistency Check failed: backup checksum "
"({0}) and restore checksum ({1}) did not match.".
format(backup_checksum, restore_checksum.checksum))
except OSError as e:
raise ConsistencyCheckException(
"Backup Consistency Check failed: could not checksum file"
" {0} ({1})".format(e.filename, e.strerror))
return {}
res = restore.RestoreOs(conf.client_manager, conf.container,
self.storage)
if conf.backup_media == 'nova':
if self.conf.project_id:
return self.engine.restore_nova_tenant(
project_id=self.conf.project_id,
hostname_backup_name=self.conf.hostname_backup_name,
overwrite=conf.overwrite,
recent_to_date=restore_timestamp)
else:
LOG.info("Restoring nova backup. Instance ID: {0}, "
"timestamp: {1} network-id {2}".format(
conf.nova_inst_id,
restore_timestamp,
conf.nova_restore_network))
hostname_backup_name = os.path.join(
self.conf.hostname_backup_name,
self.conf.nova_inst_id)
self.engine.restore(
hostname_backup_name=hostname_backup_name,
restore_resource=conf.nova_inst_id,
overwrite=conf.overwrite,
recent_to_date=restore_timestamp,
backup_media=conf.mode)
elif conf.backup_media == 'cinder':
LOG.info("Restoring cinder backup from glance. Volume ID: {0}, "
"timestamp: {1}".format(conf.cinder_vol_id,
restore_timestamp))
res.restore_cinder_by_glance(conf.cinder_vol_id, restore_timestamp)
elif conf.backup_media == 'cindernative':
LOG.info("Restoring cinder native backup. Volume ID {0}, Backup ID"
" {1}, timestamp: {2}".format(conf.cindernative_vol_id,
conf.cindernative_backup_id,
restore_timestamp))
res.restore_cinder(conf.cindernative_vol_id,
conf.cindernative_backup_id,
restore_timestamp)
elif conf.backup_media == 'cinderbrick':
LOG.info("Restoring cinder backup using os-brick. Volume ID {0}, "
"timestamp: {1}".format(conf.cinderbrick_vol_id,
restore_timestamp))
self.engine.restore(
hostname_backup_name=self.conf.hostname_backup_name,
restore_resource=conf.cinderbrick_vol_id,
overwrite=conf.overwrite,
recent_to_date=restore_timestamp,
backup_media=conf.mode)
else:
raise Exception("unknown backup type: %s" % conf.backup_media)
return {}
class AdminJob(Job):
def _validate(self):
# no validation required in this job
if self.conf.backup_media == 'cindernative':
if not self.conf.fullbackup_rotation:
raise Exception("The parameter --fullbackup-rotation "
"is required")
elif not (self.conf.remove_from_date or self.conf.remove_older_than):
raise ValueError("You need to provide to remove backup older "
"than this time. You can use --remove-older-than "
"or --remove-from-date")
def execute(self):
# remove backups by freezer admin action
backup_media = self.conf.backup_media
if backup_media == 'cindernative':
admin_os = admin.AdminOs(self.conf.client_manager)
admin_os.del_off_limit_fullbackup(
self.conf.cindernative_vol_id,
self.conf.fullbackup_rotation)
return {}
if self.conf.remove_from_date:
timestamp = utils.date_to_timestamp(self.conf.remove_from_date)
else:
timestamp = datetime.datetime.now() - \
datetime.timedelta(days=float(self.conf.remove_older_than))
timestamp = int(time.mktime(timestamp.timetuple()))
if self.conf.backup_media == 'cinder':
old_backups = self.get_cinder_old_backups(
timestamp,
self.conf.cinder_vol_id
)
self.remove_backup_dirs(old_backups, self.conf.cinder_vol_id)
return {}
hostname_backup_name_set = set()
if self.conf.backup_media == 'nova':
if self.conf.project_id:
instance_ids = self.engine.get_nova_tenant(
self.conf.project_id)
for instance_id in instance_ids:
hostname_backup_name = os.path.join(
self.conf.hostname_backup_name, instance_id)
hostname_backup_name_set.add(hostname_backup_name)
else:
hostname_backup_name = os.path.join(
self.conf.hostname_backup_name,
self.conf.nova_inst_id)
hostname_backup_name_set.add(hostname_backup_name)
else:
hostname_backup_name_set.add(self.conf.hostname_backup_name)
for backup_name in hostname_backup_name_set:
self.storage.remove_older_than(self.engine,
timestamp,
backup_name)
return {}
def get_cinder_old_backups(self, timestamp, cinder_vol_id):
path_to_list = self.get_path_prefix(cinder_vol_id)
old_backups = []
backup_dirs = self.storage.listdir(path_to_list)
for backup_dir in backup_dirs:
if int(backup_dir) <= int(timestamp):
old_backups.append(backup_dir)
return old_backups
def remove_backup_dirs(self, backups_to_remove, cinder_vol_id):
path_prefix = self.get_path_prefix(cinder_vol_id)
for backup_to_remove in backups_to_remove:
path_to_remove = "{0}/{1}".format(path_prefix, backup_to_remove)
LOG.info("Remove backup: {0}".format(path_to_remove))
self.storage.rmtree(path_to_remove)
def get_path_prefix(self, cinder_vol_id):
if self.storage.type == 'swift':
path_prefix = "{0}/{1}/{2}".format(
self.storage.container,
self.storage.segments,
cinder_vol_id
)
elif self.storage.type in ['local', 'ssh', 's3']:
path_prefix = "{0}/{1}".format(
self.storage.storage_path,
cinder_vol_id
)
else:
path_prefix = ''
return path_prefix
class ExecJob(Job):
def _validate(self):
if not self.conf.command:
raise ValueError("--command option is required")
def execute(self):
if self.conf.command:
LOG.info('Executing exec job. Command: {0}'
.format(self.conf.command))
exec_cmd.execute(self.conf.command)
else:
LOG.warning(
'No command info options were set. Exiting.')
return {}
class ConsistencyCheckException(Exception):
pass
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1125,
13,
1678,
1209,
13,
2
] |
code/abc069_a_01.py | KoyanagiHitoshi/AtCoder | 3 | 98467 | n,m=map(int,input().split())
print((n-1)*(m-1)) | [
1,
302,
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1958,
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29876,
29899,
29896,
11877,
29898,
29885,
29899,
29896,
876,
2
] |
simple_downloader/drive_space.py | jsyrovy/simple-downloader | 0 | 182800 | <reponame>jsyrovy/simple-downloader
import dataclasses
import shutil
import hurry.filesize
@dataclasses.dataclass
class DriveSpace:
path: str
total: str
used: str
free: str
free_perc: str
def get_drive_space(path: str) -> DriveSpace:
total, used, free = shutil.disk_usage(path)
return DriveSpace(path,
hurry.filesize.size(total),
hurry.filesize.size(used),
hurry.filesize.size(free),
f"{(free / total) * 100:.0f}%")
| [
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] |
cogs/dynamicslowmode.py | MM-coder/salbot-rewrite | 0 | 147202 | <reponame>MM-coder/salbot-rewrite
"""
Created by Epic at 8/1/20
"""
import logging
import asyncio
import discord
from discord.ext import commands
from aiohttp import client_exceptions
class DynamicSlowmode(commands.Cog):
def __init__(self, bot):
self.bot = bot
self.logger = logging.getLogger("salbot.cogs.faq")
self.api = self.bot.get_cog("Api")
self.toxicity_threshold = .7
self.normal_cooldown_mapping = commands.CooldownMapping.from_cooldown(3, 5, commands.BucketType.channel)
self.toxicity_cooldown_mapping = commands.CooldownMapping.from_cooldown(2, 5, commands.BucketType.channel)
self.lockdown_cooldown_mapping = commands.CooldownMapping.from_cooldown(5, 2, commands.BucketType.channel)
self.normal_cooldown = 10
self.toxicity_cooldown = 20
self.default_cooldown = 0
self.cooldown_time = 60
@commands.Cog.listener()
async def on_message(self, message: discord.Message):
if message.author.bot:
return
try:
toxicity_result = await self.api.predict_toxicity(message.content)
is_toxic = False
for value in toxicity_result.values():
if value > self.toxicity_threshold:
is_toxic = True
break
except client_exceptions.ClientConnectionError:
self.logger.warning("Could not connect to MAX")
is_toxic = False
if is_toxic:
rate_limit = self.toxicity_cooldown_mapping.update_rate_limit(message)
if rate_limit and message.channel.slowmode_delay < self.toxicity_cooldown:
embed = discord.Embed(title="[Auto] Chat suspended",
description="The chat has been automatically suspended for toxicity.",
color=0xFF0000)
await message.channel.purge(limit=10)
await message.channel.send(embed=embed, delete_after=10)
await message.channel.edit(slowmode_delay=self.toxicity_cooldown)
await asyncio.sleep(self.cooldown_time)
await message.channel.edit(slowmode_delay=self.cooldown_time)
return
else:
rate_limit = self.normal_cooldown_mapping.update_rate_limit(message)
if rate_limit and message.channel.slowmode_delay < self.normal_cooldown:
embed = discord.Embed(title="[Auto] Chat suspended",
description="The chat has been automatically suspended.", color=0xFF0000)
await message.channel.purge(limit=10)
await message.channel.send(embed=embed, delete_after=10)
await message.channel.edit(slowmode_delay=self.normal_cooldown)
await asyncio.sleep(self.cooldown_time)
await message.channel.edit(slowmode_delay=self.cooldown_time)
return
rate_limit = self.lockdown_cooldown_mapping.update_rate_limit(message)
if rate_limit:
await message.channel.set_permissions(message.guild.default_role, send_messages=False)
embed = discord.Embed(title="[Auto] Chat suspended",
description="The chat has been automatically suspended.", color=0xFF0000)
await message.channel.send(embed=embed)
await asyncio.sleep(self.cooldown_time)
await message.channel.set_permissions(message.guild.default_role, send_messages=True)
def setup(bot):
bot.add_cog(DynamicSlowmode(bot))
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] |
aiidalab_sssp/inspect/plot_utils.py | aiidalab/aiidalab-sssp | 0 | 83163 | import random
import matplotlib.pyplot as plt
import numpy as np
def cmap(label: str) -> str:
"""Return RGB string of color for given standard psp label"""
_, pp_family, pp_z, pp_type, pp_version = label.split("/")
if pp_family == "sg15" and pp_version == "v1.0":
return "#000000"
if pp_family == "sg15" and pp_version == "v1.2":
return "#708090"
if pp_family == "gbrv" and pp_version == "v1":
return "#4682B4"
if pp_family == "psl" and pp_version == "v1.0.0" and pp_type == "us":
return "#F50E02"
if pp_family == "psl" and pp_version == "v1.0.0" and pp_type == "paw":
return "#2D8B00F"
if pp_family == "dojo" and pp_version == "v04":
return "#F9A501"
# TODO: more mapping
# if a unknow type generate random color based on ascii sum
ascn = sum([ord(c) for c in label])
random.seed(ascn)
return "#%06x" % random.randint(0, 0xFFFFFF)
def delta_measure_hist(pseudos: dict, measure_type):
px = 1 / plt.rcParams["figure.dpi"] # pixel in inches
fig, ax = plt.subplots(1, 1, figsize=(1024 * px, 360 * px))
structures = ["X", "XO", "X2O", "XO3", "X2O", "X2O3", "X2O5"]
num_structures = len(structures)
# element
try:
v0 = list(pseudos.values())[0]
element = v0["pseudo_info"]["element"]
except Exception:
element = None
if measure_type == "delta":
keyname = "delta"
ylabel = "Δ -factor"
elif measure_type == "nv_delta":
keyname = "rel_errors_vec_length"
ylabel = "ν -factor"
for i, (label, output) in enumerate(pseudos.items()):
N = len(structures)
idx = np.arange(N) # the x locations for the groups
width = 0.1 # the width of the bars
y_delta = []
for structure in structures:
try:
res = output["delta_measure"]["output_delta_analyze"][
f"output_{structure}"
]
y_delta.append(res[keyname])
except Exception:
y_delta.append(-1)
_, pp_family, pp_z, pp_type, pp_version = label.split("/")
out_label = f"{pp_z}/{pp_type}({pp_family}-{pp_version})"
ax.bar(
idx + width * i,
y_delta,
width,
color=cmap(label),
edgecolor="black",
linewidth=1,
label=out_label,
)
ax.legend()
ax.set_title(f"X={element}")
ax.axhline(y=1.0, linestyle="--", color="gray")
ax.set_ylabel(ylabel)
ax.set_ylim([0, 10])
ax.set_yticks(np.arange(10))
ax.set_xticks(list(range(num_structures)))
ax.set_xticklabels(structures)
return fig
def convergence(pseudos: dict, wf_name, measure_name, ylabel, threshold=None):
px = 1 / plt.rcParams["figure.dpi"]
fig, (ax1, ax2) = plt.subplots(
1, 2, gridspec_kw={"width_ratios": [2, 1]}, figsize=(1024 * px, 360 * px)
)
for label, output in pseudos.items():
# Calculate the avg delta measure value
structures = ["X", "XO", "X2O", "XO3", "X2O", "X2O3", "X2O5"]
lst = []
for structure in structures:
try:
res = output["delta_measure"]["output_delta_analyze"][
f"output_{structure}"
]
lst.append(res["rel_errors_vec_length"])
except Exception:
pass
avg_delta = sum(lst) / len(lst)
try:
res = output[wf_name]
x_wfc = res["output_parameters_wfc_test"]["ecutwfc"]
y_wfc = res["output_parameters_wfc_test"][measure_name]
x_rho = res["output_parameters_rho_test"]["ecutrho"]
y_rho = res["output_parameters_rho_test"][measure_name]
wfc_cutoff = res["final_output_parameters"]["wfc_cutoff"]
_, pp_family, pp_z, pp_type, pp_version = label.split("/")
out_label = f"{pp_z}/{pp_type}(ν={avg_delta:.2f})({pp_family}-{pp_version})"
ax1.plot(x_wfc, y_wfc, marker="o", color=cmap(label), label=out_label)
ax2.plot(
x_rho,
y_rho,
marker="o",
color=cmap(label),
label=f"cutoff wfc = {wfc_cutoff} Ry",
)
except Exception:
pass
ax1.set_ylabel(ylabel)
ax1.set_xlabel("Wavefuntion cutoff (Ry)")
ax1.set_title(
"Fixed rho cutoff at 200 * dual (dual=4 for NC and dual=8 for non-NC)"
)
# ax2.legend(loc='upper left', bbox_to_anchor=(1, 1.0))
ax1.legend()
ax2.set_xlabel("Charge density cudoff (Ry)")
ax2.set_title("Convergence test at fixed wavefunction cutoff")
ax2.legend()
if threshold:
ax1.axhline(y=threshold, color="r", linestyle="--")
ax2.axhline(y=threshold, color="r", linestyle="--")
ax1.set_ylim(-0.5 * threshold, 10 * threshold)
ax2.set_ylim(-0.5 * threshold, 10 * threshold)
plt.tight_layout()
return fig
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580,
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2537,
13,
2
] |
oops_fhir/r4/code_system/flag_priority_codes.py | Mikuana/oops_fhir | 0 | 32958 | <filename>oops_fhir/r4/code_system/flag_priority_codes.py
from pathlib import Path
from fhir.resources.codesystem import CodeSystem
from oops_fhir.utils import CodeSystemConcept
__all__ = ["FlagPriorityCodes"]
_resource = CodeSystem.parse_file(Path(__file__).with_suffix(".json"))
class FlagPriorityCodes:
"""
Flag Priority Codes
This value set is provided as an exemplar. The value set is driven by
IHE Table B.8-4: Abnormal Flags, Alert Priority.
Status: draft - Version: 4.0.1
Copyright None
http://hl7.org/fhir/flag-priority-code
"""
pn = CodeSystemConcept(
{"code": "PN", "definition": "No alarm.", "display": "No alarm"}
)
"""
No alarm
No alarm.
"""
pl = CodeSystemConcept(
{"code": "PL", "definition": "Low priority.", "display": "Low priority"}
)
"""
Low priority
Low priority.
"""
pm = CodeSystemConcept(
{"code": "PM", "definition": "Medium priority.", "display": "Medium priority"}
)
"""
Medium priority
Medium priority.
"""
ph = CodeSystemConcept(
{"code": "PH", "definition": "High priority.", "display": "High priority"}
)
"""
High priority
High priority.
"""
class Meta:
resource = _resource
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logux/apps.py | sobolevn/django-1 | 17 | 147770 | from django.apps import AppConfig
from logux import settings
from logux.utils import autodiscover
class LoguxConfig(AppConfig):
""" Logux app conf """
name = 'logux'
verbose_name = 'Logux'
def ready(self):
# check if all required settings is defined
settings.get_config()
# import all logux_actions.py and logux_subscriptions.py from consumer modules
autodiscover()
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premailer/__init__.py | locationlabs/premailer | 0 | 31698 | <reponame>locationlabs/premailer
__version__ = '1.12.1-LL'
__build__ = '' # set by the build server
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tests/test_rotations.py | MarceloJacinto/dsorlib | 0 | 187477 | <filename>tests/test_rotations.py<gh_stars>0
from numpy import array
from numpy.testing import assert_allclose
from dsorlib.rotations import Rot_to_quaternion, RPY_to_quaternion, quaternion_to_Rot, quaternion_to_RPY, RPY_to_RotZYX, \
RotZYX_to_RPY
"""
The following tests are conducted for the rotations module
The following URL was used to obtained the standard values to compare against
https://www.andre-gaschler.com/rotationconverter/
"""
def test1_Rot_to_quaternion():
"""
Test1 the method Rot_to_quaternion
"""
r = array([[-0.0690026, -0.9716355, 0.2261928],
[0.6932812, 0.1163334, 0.7112156],
[-0.7173561, 0.2058909, 0.6655893]])
q_obtained = Rot_to_quaternion(r)
q_expected = array([0.65439287, -0.19305097, 0.36046729, 0.63605396])
assert_allclose(q_obtained, q_expected, rtol=2e-07, verbose=True)
def test2_Rot_to_quaternion():
"""
Test2 the method Rot_to_quaternion
"""
r2 = array([[0.0516208, 0.0057865, 0.9986500],
[-0.2212602, 0.9751976, 0.0057865],
[-0.9738476, -0.2212602, 0.0516208]])
q2_obtained = Rot_to_quaternion(r2)
q2_expected = array([0.7208397, -0.0787438, 0.6840972, -0.0787438])
assert_allclose(q2_obtained, q2_expected, rtol=4e-07, verbose=True)
def test1_RPY_to_quaternion():
"""
Test1 the method RPY_to_quaternion
"""
roll: float = 0.3
pitch: float = 0.8
yaw: float = 1.67
q_obtained = RPY_to_quaternion(roll, pitch, yaw)
q_expected = array([0.65439287, -0.19305097, 0.36046729, 0.63605396])
assert_allclose(q_obtained, q_expected, rtol=2e-07, verbose=True)
def test2_RPY_to_quaternion():
"""
Test2 the method RPY_to_quaternion
"""
roll: float = 1.8
pitch: float = 1.8
yaw: float = 1.8
q_obtained = RPY_to_quaternion(roll, pitch, yaw)
q_expected = array([0.7208397, -0.0787438, 0.6840972, -0.0787438])
assert_allclose(q_obtained, q_expected, rtol=4e-07, verbose=True)
def test1_quaternion_to_Rot():
"""
Test1 the method quaternion_to_Rot
"""
q = array([0.65439287, -0.19305097, 0.36046729, 0.63605396])
rot_obtained = quaternion_to_Rot(q)
rot_expected = array([[-0.0690026, -0.9716355, 0.2261928],
[ 0.6932812, 0.1163334, 0.7112156],
[-0.7173561, 0.2058909, 0.6655893]])
assert_allclose(rot_obtained, rot_expected, rtol=2e-07, verbose=True)
def test2_quaternion_to_Rot():
"""
Test2 the method quaternion_to_Rot
"""
q = array([0.7208397, -0.0787438, 0.6840972, -0.0787438])
rot_obtained = quaternion_to_Rot(q)
rot_expected = array([[0.0516208, 0.0057865, 0.9986500],
[-0.2212602, 0.9751976, 0.0057865],
[-0.9738476, -0.2212602, 0.0516208]])
assert_allclose(rot_obtained, rot_expected, rtol=3e-06, verbose=True)
def test1_quaternion_to_RPY():
"""
Test1 the method quaternion_to_RPY
"""
q = array([0.65439287, -0.19305097, 0.36046729, 0.63605396])
roll_obtained, pitch_obtained, yaw_obtained = quaternion_to_RPY(q)
RPY_obtained = array([roll_obtained, pitch_obtained, yaw_obtained])
RPY_expected = array([0.3, 0.8, 1.67])
assert_allclose(RPY_obtained, RPY_expected, rtol=2e-07, verbose=True)
def test2_quaternion_to_RPY():
"""
Test2 the method quaternion_to_RPY
"""
q = array([0.7208397, -0.0787438, 0.6840972, -0.0787438])
roll_obtained, pitch_obtained, yaw_obtained = quaternion_to_RPY(q)
RPY_obtained = array([roll_obtained, pitch_obtained, yaw_obtained])
RPY_expected = array([-1.341592, 1.341593, -1.341592])
assert_allclose(RPY_obtained, RPY_expected, rtol=2e-07, verbose=True)
def test1_RPY_to_RotZYX():
"""
Test1 the method RPY_to_RotZYX
"""
roll: float = 0.3
pitch: float = 0.8
yaw: float = 1.67
rot_obtained = RPY_to_RotZYX(roll, pitch, yaw)
rot_expected = array([[-0.0690026, -0.9716355, 0.2261928],
[0.6932812, 0.1163334, 0.7112156],
[-0.7173561, 0.2058909, 0.6655893]])
assert_allclose(rot_obtained, rot_expected, rtol=7e-07, verbose=True)
def test2_RPY_to_RotZYX():
"""
Test2 the method RPY_to_RotZYX
"""
roll: float = 1.8
pitch: float = 1.8
yaw: float = 1.8
rot_obtained = RPY_to_RotZYX(roll, pitch, yaw)
rot_expected = array([[0.0516208, 0.0057865, 0.9986500],
[-0.2212602, 0.9751976, 0.0057865],
[-0.9738476, -0.2212602, 0.0516208]])
assert_allclose(rot_obtained, rot_expected, rtol=4e-06, verbose=True)
def test1_RotZYX_to_RPY():
"""
Test1 the method RotZYX_to_RPY
"""
r = array([[-0.0690026, -0.9716355, 0.2261928],
[0.6932812, 0.1163334, 0.7112156],
[-0.7173561, 0.2058909, 0.6655893]])
roll_obtained, pitch_obtained, yaw_obtained = RotZYX_to_RPY(r)
RPY_obtained = array([roll_obtained, pitch_obtained, yaw_obtained])
RPY_expected = array([0.3, 0.8, 1.67])
assert_allclose(RPY_obtained, RPY_expected, rtol=3e-07, verbose=True)
def test2_RotZYX_to_RPY():
"""
Test2 the method RotZYX_to_RPY
"""
r = array([[0.0516208, 0.0057865, 0.9986500],
[-0.2212602, 0.9751976, 0.0057865],
[-0.9738476, -0.2212602, 0.0516208]])
roll_obtained, pitch_obtained, yaw_obtained = RotZYX_to_RPY(r)
RPY_obtained = array([roll_obtained, pitch_obtained, yaw_obtained])
RPY_expected = array([-1.341593, 1.341593, -1.341593])
assert_allclose(RPY_obtained, RPY_expected, rtol=4e-07, verbose=True)
def main():
# Test the conversion from rotation matrix to quaternion
test1_Rot_to_quaternion()
test2_Rot_to_quaternion()
# Test the conversion from euler angles to quaternion
test1_RPY_to_quaternion()
test2_RPY_to_quaternion()
# Test the conversion from quaternion to rotation matrix
test1_quaternion_to_Rot()
test2_quaternion_to_Rot()
# Test the conversion from quaternion to euler angles
test1_quaternion_to_RPY()
test2_quaternion_to_RPY()
# Test the conversion from euler angles to rotation matrix
test1_RPY_to_RotZYX()
test2_RPY_to_RotZYX()
# Test the conversion from rotation matrix to euler angles
test1_RotZYX_to_RPY()
test2_RotZYX_to_RPY()
if __name__ == "__main__":
main()
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generate.py | ShuKar99/Multi-Threaded-Sudoku-Solver | 0 | 185746 | from sudoku import *
from thread import Threads
from copy import *
class SudokuCreater():
def __init__(self, sudoku):
self.sudoku= sudoku
dom= ['1','2','3','4','5','6','7','8','9']
self.constraints= self.sudoku.board_constraints()
self.domain= dict()
# all unassigned variables in the board have a domain [1,9]
for var in self.sudoku.variables:
if(self.sudoku.structure[var.i][var.j]=='0'):
self.domain[var]= deepcopy(dom)
else:
self.domain[var]= list(self.sudoku.structure[var.i][var.j])
def solve(self):
# we'll enforce node consistency through the GUI part
self.ac3()
return self.backtrack(dict())
def domain_update(self,X_value, Y):
"""
revise function will call this function to check if X_value is chosen as a value for variable X, does that leave any option for Y?
"""
for Y_value in self.domain[Y]:
if Y_value != X_value:
return True
return False
def revise(self, X, Y):
"""
makes X arc consistent wrt to Y
"""
revised= False
#if a value in X's domain doesn't leave any option for Y, remove that value from X's domain
threads= []
for X_value in self.domain[X]:
threads.append(Threads(target= self.domain_update, args=(X_value,Y)))
for thread in threads:
thread.start()
for thread in threads:
if(thread.join()== False):
self.domain[X].remove(thread.args()[0])
revised= True
return revised
def add_arcs(self,variable):
# adds arc wrt to variable
arcs=[]
for constraint in self.constraints[variable]:
arcs.append((variable, constraint))
return arcs
def initial_arcs(self):
threads=[]
arcs=[]
for var in self.sudoku.variables:
threads.append(Threads(target= self.add_arcs, args=(var,)))
for thread in threads:
thread.start()
for thread in threads:
arcs+= thread.join()
return arcs
def ac3(self, arcs= None):
if arcs== None:
arcs= self.initial_arcs()
while(len(arcs)!=0):
arc= arcs.pop()
X= arc[0]
Y= arc[1]
if self.revise(X,Y):
#if revision emptied the domain of X, there's no solution
if(len(self.domain[X]) == 0):
return False
threads=[]
for constraint in self.constraints[X]:
if constraint == Y:
continue
else:
threads.append(Threads(target= self.revise, args= (constraint, X)))
for thread in threads:
thread.start()
for thread in threads:
if(thread.join()):
if(len(self.domain[thread.args()[0]]) ==0):
return False
return True
def assignment_complete(self, assignment):
return len(assignment) == len(self.sudoku.variables)
def is_constraint_consistent(self, constraint, assignment, assigned):
"""
will be called by is_consistent function to check if constraint is assigned or not
and if it is assigned, it's assignment should not be equal to assigned
"""
if constraint in assignment:
if assignment[constraint] == assigned:
return False
return True
def is_consistent(self, assignment, var, assigned):
"""
checks if var= assigned is consistent with the assignment done so far
"""
threads= []
for constraint in self.constraints[var]:
threads.append(Threads(target= self.is_constraint_consistent, args= (constraint, assignment, assigned)))
for thread in threads:
thread.start()
for thread in threads:
if(thread.join()== False):
return False
return True
def values_left_in_domain(self,variable):
"""
returns no. of values left in the domain of the variable
"""
return len(self.domain[variable])
def select_unassigned_variable(self, assignment):
"""
We'll choose the variable that has least possible values left in it's domain
"""
threads=[]
domain_values= dict()
for variable in self.sudoku.variables:
if variable not in assignment:
threads.append(Threads(target= self.values_left_in_domain, args=(variable,)))
for thread in threads:
thread.start()
for thread in threads:
domain_values[thread.args()[0]] = thread.join()
return sorted(domain_values, key= domain_values.get)[0]
def no_of_constraints(self, value, assignment, var):
"""
will be called by order_domain_values function to count the no. of contraints var= value puts on the neighnours of var
"""
count =0
for constraint in self.constraints[var]:
if value in self.domain[constraint]:
count+=1
return count
def order_domain_values(self, assignment, var):
"""
orders the domain of the variable var according to the constraints it puts on it's neighbours
"""
number_constrained= dict()
threads= []
for value in self.domain[var]:
threads.append(Threads(target= self.no_of_constraints, args= (value, assignment, var)))
for thread in threads:
thread.start()
for thread in threads:
number_constrained[thread.args()[0]] = thread.join()
return sorted(number_constrained, key= number_constrained.get)
def backtrack(self, assignment):
if self.assignment_complete(assignment):
return assignment
var= self.select_unassigned_variable(assignment)
for value in self.order_domain_values(assignment, var):
if self.is_consistent(assignment, var, value):
assignment[var]= value
#makes inferences from new assignment with ac3
arcs= [(constraint, var) for constraint in self.constraints[var]
if constraint not in assignment]
#make a copy of domains before calling ac3 so that changes to domains can be reverted if needed
t1= Threads(target= deepcopy, args= (self.domain,))
t1.start()
if self.ac3(arcs= arcs):
result = self.backtrack(assignment)
if result != None:
return result
assignment[var].remove(value)
self.domains= t1.join()
return None
def print_assignment(self, assignment):
for i in range(len(self.sudoku.structure)):
if i%3==0 and i!=0:
print("- - - - - - - -")
for j in range(len(self.sudoku.structure[i])):
if j%3==0 and j!=0:
print(" | ", end="")
if j==8:
if(self.sudoku.structure[i][j]=='0'):
print(assignment[Variable(i=i, j=j)])
else:
print(self.sudoku.structure[i][j])
else:
if(self.sudoku.structure[i][j]=='0'):
print(str(assignment[Variable(i=i, j=j)]) + " ", end= "" )
else:
print(str(self.sudoku.structure[i][j]) + " " , end="")
def main():
sudoku= Sudoku("problems/5.txt")
creator= SudokuCreater(sudoku)
assignment= creator.solve()
creator.print_assignment(assignment)
print(assignment[Variable(0,0)])
if __name__ == "__main__":
main()
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1115,
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] |
airbnb/app.py | serinamarie/Saltiest-Hackers | 0 | 190382 | <filename>airbnb/app.py<gh_stars>0
from flask import Flask, request
def create_app():
app = Flask(__name__)
@app.route('/')
def root():
return 'airbnb predictive project'
@app.route('/predict', methods=['POST'])
def predict(message=""):
try:
# find authorization header
content = request.get_json(force=True)
message = f'POST response recieved: {content}'
# prediction = get_predicted_price(content)
except Exception as identifier:
message = f'error: {identifier}'
return message
return app
# FLASK_APP=airbnb:APP FLASK_ENV=development flask run
# def tokenize(text):
# return [
# token for token in simple_preprocess(text) if token not in STOPWORDS
# ]
# @app.route('/', methods=['POST', 'GET'])
# def responses():
# response = requests.get(
# 'backendurlhere')
# return str(response.text)
# @app.route('/api', methods=['POST', 'GET'])
# def predict():
# data = request.get_json(force=True)
# desc = data['feature'][0]['description']
# description_length = len(tokenize(desc))
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accounts/migrations/0004_auto_20210517_1624.py | bencko/test_blog_api | 0 | 120781 | <filename>accounts/migrations/0004_auto_20210517_1624.py
# Generated by Django 3.2.3 on 2021-05-17 16:24
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('accounts', '0003_auto_20210517_1623'),
]
operations = [
migrations.RemoveField(
model_name='subscribeslist',
name='subscribed_to',
),
migrations.AddField(
model_name='subscribeslist',
name='subscribed_to',
field=models.ManyToManyField(blank=True, to='accounts.Subscribe'),
),
]
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] |
Core/brainSeg/__init__.py | YongLiuLab/BrainRadiomicsTools | 10 | 83548 | from . brainSeg import brainSeg | [
1,
515,
869,
17294,
17669,
1053,
17294,
17669,
2
] |
storm/stock/models.py | GaretJax/storm-erp | 0 | 186297 | import sqlalchemy as sa
from sqlalchemy.orm import relationship, backref, object_session
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.ext.declarative import declarative_base
from storm.database import mptt
Model = declarative_base()
class Location(mptt.MPTTBase, Model):
"""
A named location for some stock units.
"""
__tablename__ = 'storm_stock_location'
id = sa.Column(sa.Integer, primary_key=True)
name = sa.Column(sa.Unicode, nullable=False)
type = sa.Column(sa.String(50), nullable=True)
__mapper_args__ = {
'polymorphic_identity': None,
'polymorphic_on': type,
}
def __init__(self, name, parent=None):
self.name = name
if parent is not None:
self.parent = parent
def __repr__(self):
return 'Location({})'.format(self.name)
def stock_of(self, stock_unit, lot=None, virtual=False,
include_sublocations=False):
session = object_session(self)
quant_query = (session.query(sa.func.sum(Quant.quantity))
.select_from(Quant)
.filter(Quant.stock_unit == stock_unit))
if lot:
assert lot.stock_unit == stock_unit
quant_query = quant_query.filter(Quant.lot == lot)
if not include_sublocations:
quant_query = quant_query.filter(Quant.location == self)
else:
quant_query = quant_query.join(Location).filter(
mptt.descendants(self, include_self=True))
real = quant_query.scalar() or 0
if virtual:
moves_query = (session.query(sa.func.sum(Move.quantity))
.filter((Move.stock_unit == stock_unit) &
(Move.scheduled == True) & # NOQA
(Move.executed == False)))
if lot:
moves_query = moves_query.filter(Move.lot == lot)
if not include_sublocations:
moves_in_query = moves_query.filter(Move.target == self)
moves_out_query = moves_query.filter(Move.source == self)
else:
moves_query = moves_query.filter(
mptt.descendants(self, include_self=True))
moves_in_query = moves_query.join(Move.target)
moves_out_query = moves_query.join(Move.source)
quantities = session.query(
moves_in_query.as_scalar(),
moves_out_query.as_scalar()
)
moved_in, moved_out = quantities.one()
virtual = (moved_in or 0) - (moved_out or 0)
else:
virtual = 0
return real + virtual
class Warehouse(Location):
"""
A specialization of a location which acts as a wharehouse.
"""
__tablename__ = 'storm_stock_warehouse'
__table_args__ = tuple()
id = sa.Column(sa.Integer,
sa.ForeignKey(Location.id, onupdate='CASCADE',
ondelete='CASCADE'),
primary_key=True)
__mapper_args__ = {
'polymorphic_identity': 'warehouse',
}
def __repr__(self):
return 'Warehouse({})'.format(self.name)
class StockUnit(Model):
"""
Materialization of a specific product for organizational purposes in a
single organization.
"""
__tablename__ = 'storm_stock_unit'
id = sa.Column(sa.Integer, primary_key=True)
sku = sa.Column(sa.String(64), nullable=False, unique=True)
# TODO: measurement_quantity = sa.Column(...), normalized to SI -> custom
# in its own table (piece, carton, box, pallet,...)
# ref to item/product (upc -> on product)
def in_stock(self, location, virtual=False, include_sublocations=False):
return location.stock_of(self, virtual=virtual,
include_sublocations=include_sublocations)
class Lot(Model):
"""
A production lot is a set of items of the same type which have identical
traceability characteristics (e.g. quality, serial number, ...).
"""
__tablename__ = 'storm_stock_lot'
__table_args__ = (
sa.UniqueConstraint('stock_unit_id', 'serial'),
)
id = sa.Column(sa.Integer, primary_key=True)
stock_unit_id = sa.Column(sa.Integer, sa.ForeignKey(StockUnit.id),
nullable=False, index=True)
serial = sa.Column(sa.String(120), nullable=True)
quantity = sa.Column(sa.Numeric(18, 6), nullable=False)
# TODO: add a cost here?
# timestamp
stock_unit = relationship(StockUnit)
def in_stock(self, location, virtual=False, include_sublocations=False):
return location.stock_of(self.stock_unit, lot=self, virtual=virtual,
include_sublocations=include_sublocations)
class Batch(Model):
__tablename__ = 'storm_stock_batch'
id = sa.Column(sa.Integer, primary_key=True)
def schedule(self):
"""
Schedule the moves belonging to this batch by assigning concrete
locations and lots.
"""
self.moves.update({'scheduled': True}, synchronize_session='fetch')
def apply(self):
"""
Apply already scheduled stock moves by updating the quants.
"""
session = object_session(self)
with session.begin_nested():
for m in self.moves:
assert m.scheduled
if not m.quantity: # NOCOV
continue
table = Quant.__table__
query = (table.update()
.returning(table.c.id, table.c.quantity)
.where((table.c.location_id == m.source.id) &
(table.c.lot_id == m.lot.id))
.values(quantity=table.c.quantity - m.quantity))
source_quant = session.execute(query).fetchone()
if not source_quant:
session.add(Quant(
location=m.source,
lot=m.lot,
quantity=-m.quantity
))
query = (table.update()
.returning(table.c.id, table.c.quantity)
.where((table.c.location_id == m.target.id) &
(table.c.lot_id == m.lot.id))
.values(quantity=table.c.quantity + m.quantity))
target_quant = session.execute(query).fetchone()
if not target_quant:
session.add(Quant(
location=m.target,
lot=m.lot,
quantity=m.quantity
))
session.flush()
self.moves.update({'executed': True}, synchronize_session='fetch')
session.query(Quant).filter(Quant.quantity == 0).delete()
# class BatchStatus(states.StatusMixin, Model):
# __tablename__ = 'storm_stock_batch_status'
# __stateful_args__ = {
# 'relation': Batch,
# }
class Move(Model):
"""
A movement of a certain quantity of stock units belonging to a lot, from a
location to another one.
This relation has a minor denormalization on stock units + lots in order to
support automatic lot selection on move scheduling.
"""
__tablename__ = 'storm_stock_move'
id = sa.Column(sa.Integer, primary_key=True)
batch_id = sa.Column(sa.Integer, sa.ForeignKey(Batch.id), nullable=False)
source_location_id = sa.Column(sa.Integer, sa.ForeignKey(Location.id),
nullable=False)
target_location_id = sa.Column(sa.Integer, sa.ForeignKey(Location.id),
nullable=False)
stock_unit_id = sa.Column(sa.Integer, sa.ForeignKey(StockUnit.id),
nullable=False)
lot_id = sa.Column(sa.Integer, sa.ForeignKey(Lot.id), nullable=True)
quantity = sa.Column(sa.Numeric(18, 6), nullable=False)
scheduled = sa.Column(sa.Boolean, default=False)
executed = sa.Column(sa.Boolean, default=False)
batch = relationship(Batch, backref=backref('moves', lazy='dynamic'))
source = relationship(Location, foreign_keys=source_location_id,
backref=backref('moves_from'))
target = relationship(Location, foreign_keys=target_location_id,
backref=backref('moves_to'))
stock_unit = relationship(StockUnit, backref=backref('moves'))
lot = relationship(Lot, backref=backref('moves'))
__table_args__ = (
sa.UniqueConstraint('batch_id',
'source_location_id', 'target_location_id',
'stock_unit_id', 'lot_id'),
# postgresql_where=lot != None),
# sa.UniqueConstraint('batch_id',
# 'source_location_id', 'target_location_id',
# 'stock_unit_id',
# postgresql_where=lot == None),
# https://bitbucket.org/zzzeek/sqlalchemy/issue/3161/
)
class Quant(Model):
"""
The amount of products belonging to a certain lot in a given location.
"""
__tablename__ = 'storm_stock_quant'
__table_args__ = (
sa.UniqueConstraint('location_id', 'lot_id'),
)
id = sa.Column(sa.Integer, primary_key=True)
location_id = sa.Column(sa.Integer, sa.ForeignKey(Location.id),
nullable=False)
lot_id = sa.Column(sa.Integer, sa.ForeignKey(Lot.id), nullable=True)
quantity = sa.Column(sa.Numeric(18, 6), nullable=False)
location = relationship(Location, backref=backref('quants'))
lot = relationship(Lot, backref=backref('quants'))
stock_unit = association_proxy('lot', 'stock_unit')
# product
# (cost/price/value)
# owner
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famplex/html/__main__.py | steppi/famplex | 11 | 186203 | # -*- coding: utf-8 -*-
"""CLI for exporting FamPlex as a static site."""
from .api import html
if __name__ == '__main__':
html()
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] |
demos/webcam.py | ndoo/esp32-hanover-flipdot-firmware | 6 | 1613923 | <filename>demos/webcam.py
#!/usr/bin/python
from os import path
import socket
import struct
import sys
import time
import cv2
from lib import imageToBinary as i2b
MULTICAST_GROUP = ('172.16.58.3', 8080)
WIDTH = 96
HEIGHT = 32
vidcap = cv2.VideoCapture(cv2.CAP_DSHOW)
sock = socket.socket(socket.AF_INET, # Internet
socket.SOCK_DGRAM) # UDP
ttl = struct.pack('b', 1)
sock.setsockopt(socket.IPPROTO_IP, socket.IP_MULTICAST_TTL, ttl)
while True:
success,cv2_im = vidcap.read()
if success: sock.sendto(i2b.imageToBinary(cv2_im, WIDTH, HEIGHT, True, True), MULTICAST_GROUP)
time.sleep(0.1) | [
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dataset/research/__init__.py | mikhailkin/dataset | 0 | 93345 | <filename>dataset/research/__init__.py
""" Research module. """
from .grid import KV, Grid, Option, ConfigAlias
from .distributor import Worker, Distributor
from .workers import PipelineWorker
from .research import Research
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tests/process_data.py | IPetr0v/compromutator | 0 | 85929 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18})
def cut_by_item(dataframe, key, step):
item_range = np.arange(0, dataframe[key].max(), step)
grouped = dataframe.groupby(pd.cut(dataframe[key], item_range))
keys = [key for key, _ in grouped]
dataframes = [group for _, group in grouped]
return keys, dataframes
def plot_delays_by_rules(dataframe):
print 'Plotting by rules'
bounds = [31000, 64000, 85000, 105000]
#group_by_switches = dataframe.groupby(pd.cut(dataframe['network_size'], np.arange(0, 301, 100)))
group_by_switches = dataframe.groupby(pd.cut(dataframe['network_size'], [0, 100, 200, 250, 300]))
labels = [l for l, _ in group_by_switches]
delays = [d for _, d in group_by_switches]
#fig, axes = plt.subplots(2, 2)#, sharey=True)
ax_indices = [(0, 0), (0, 1), (1, 0), (1, 1)]
for label, delay, bound, idx in zip(labels, delays, bounds, ax_indices):
rule_interval = 100
grouped_by_rules = delay.groupby(pd.cut(
delay['graph_size'],
np.arange(0, bound, rule_interval))
#np.arange(0, max(delay['graph_size']), rule_interval))
)['duration']
mean = grouped_by_rules.mean()
#median = grouped_by_rules.median()
lower = grouped_by_rules.quantile(0.05)
upper = grouped_by_rules.quantile(0.95)
#mean = mean.rolling(window=5, min_periods=1).mean()
##median = median.rolling(window=5, min_periods=1).mean()
#lower = lower.rolling(window=5, min_periods=1).mean()
#upper = upper.rolling(window=5, min_periods=1).mean()
keys = [(k.left + k.right)/2.0 for k in mean.keys()]
plt.figure(figsize=(8, 6))
plt.ylim(0, 450)
plt.plot(keys, mean, 'green')
plt.fill_between(keys, lower, upper, color='green', alpha='0.15')
plt.xlabel(u'Количество правил')#('Rule number')
plt.ylabel(u'Задержка, мс')#('Delay, ms')
#plt.title('Delay by rule number')
plt.grid()
plt.tight_layout()
plt.savefig(data_dir + '/plot/' + 'delay_by_rules_%i_%i.pdf' % (label.left, label.right),
fmt='pdf')
#plt.show()
plt.gcf().clear()
#ax = axes[idx[0]][idx[1]]
#ax.plot(keys, mean, 'green')
#ax.fill_between(keys, lower, upper, color='green', alpha='0.15')
#ax.set_xlabel(u'Количество правил')#('Rule number')
#ax.set_ylabel(u'Задержка, мс')#('Delay, ms')
#ax.set_title(u'От %i до %i коммутаторов' % (label.left, label.right))#('Delay by rule number')
#ax.grid()
#fig.savefig(data_dir + '/plot/' + 'Delay by rule number', fmt='pdf')
##plt.show()
#plt.gcf().clear()
print 'Done'
def plot_delays_by_switches(dataframe):
print 'Plotting by switches'
switch_interval = 10
switch_bound = 301
dataframe = dataframe.sort_values(['graph_size'])
dataframe['duration'] = dataframe['duration'].rolling(window=3, min_periods=1).mean()
grouped_by_switches = dataframe.groupby(pd.cut(
dataframe['network_size'],
np.arange(0, switch_bound, switch_interval))
)['duration']
mean = grouped_by_switches.mean()
#median = grouped_by_switches.median()
#std = grouped_by_switches.std()
lower = grouped_by_switches.quantile(0.05)
upper = grouped_by_switches.quantile(0.95)
keys = [(k.left + k.right)/2.0 for k in mean.keys()]
mean = pd.Series(mean).reset_index(drop=True)
#median = pd.Series(median).reset_index(drop=True)
#std = pd.Series(std).reset_index(drop=True)
lower = pd.Series(lower).reset_index(drop=True)
upper = pd.Series(upper).reset_index(drop=True)
#mean = mean.rolling(window=5, min_periods=1).mean()
##median = median.rolling(window=5, min_periods=1).mean()
#lower = lower.rolling(window=5, min_periods=1).mean()
#upper = upper.rolling(window=5, min_periods=1).mean()
#plt.boxplot(data)
#plt.plot(keys, median, yerr=std, color='blue')
#plt.plot(keys, mean, 'ro')
plt.figure(figsize=(14, 6))
plt.errorbar(keys, mean, yerr=[lower, upper],
color='blue', fmt='o', markersize=9, capsize=6, elinewidth=3, capthick=2)
#plt.fill_between(keys, lower, upper, color='blue', alpha='0.15')
plt.xlabel(u'Количество коммутаторов')#('Network size')
plt.ylabel(u'Задержка, мс')#('Delay, ms')
#plt.title('Delay by network size')
plt.grid()
plt.tight_layout()
plt.savefig(data_dir + '/plot/' + 'delay_by_switches.pdf', fmt='pdf')
#plt.show()
plt.gcf().clear()
# By mean table size
#delays_table = delays
print 'Done'
def process_delays(delays):
delays = delays[delays['network_size'] % 5 == 0]
delays = delays[delays['network_size'] <= 305]
plot_delays_by_rules(delays)
plot_delays_by_switches(delays)
def predictions_boxplot(dataframe, delay):
#dataframe['packet_error'] = np.abs(dataframe['real_packets'] - dataframe['pred_packets'])
#dataframe['byte_error'] = np.abs(dataframe['real_bytes'] - dataframe['pred_bytes'])
#labels = list(reversed(['100 Kbps', '1 Mbps', '10 Mbps', '100 Mbps', '1 Gbps']))
labels = list(reversed([u'100 Кбит/с', u'1 Мбит/с', u'10 Мбит/с', u'100 Мбит/с', u'1 Гбит/с']))
bandwidths = reversed([int(b*1000000) for b in [0.1, 1, 10, 100, 1000]])
packet_data = []
byte_data = []
for bandwidth in bandwidths:
packet_data.append(dataframe[dataframe['bandwidth'] == bandwidth]['packet_error'])
byte_data.append(dataframe[dataframe['bandwidth'] == bandwidth]['byte_error'])
adjust_left = 0.21
packet_xlabel = u'Ошибка предсказания (количество пакетов)'#'Packet error'
byte_xlabel = u'Ошибка предсказания (количество байт)'#'Byte error'
#b = plt.boxplot(packet_data, showfliers=False, vert=False)
#print('Delay:', delay, '| Quantile:', [p.quantile(0.95) for p in packet_data])
#print 'Delay:', delay, '| Quantile:', [item.get_xdata() for item in b['whiskers']]
#return None # DEBUG
# Plot in normal scale
plt.figure(figsize=(8, 6))
plt.boxplot(packet_data, showfliers=False, vert=False)
plt.yticks([1, 2, 3, 4, 5], labels)
plt.xlabel(packet_xlabel)
plt.tight_layout()
plt.gcf().subplots_adjust(left=adjust_left)
plt.savefig(data_dir + '/plot/' + 'packet_error_%d.pdf' % delay, fmt='pdf')
#plt.show()
plt.gcf().clear()
# Plot in logarithmic scale
ax = plt.gca()
ax.set_xscale('log')
plt.boxplot(packet_data, showfliers=False, vert=False)
plt.yticks([1, 2, 3, 4, 5], labels)
plt.xlabel(packet_xlabel)
plt.tight_layout()
plt.gcf().subplots_adjust(left=adjust_left)
plt.savefig(data_dir + '/plot/' + 'packet_error_%d_log.pdf' % delay, fmt='pdf')
#plt.show()
plt.gcf().clear()
# Plot in normal scale
plt.boxplot(byte_data, showfliers=False, vert=False)
plt.yticks([1, 2, 3, 4, 5], labels)
plt.xlabel(byte_xlabel)
plt.tight_layout()
plt.gcf().subplots_adjust(left=adjust_left)
plt.savefig(data_dir + '/plot/' + 'byte_error_%d.pdf' % delay, fmt='pdf')
#plt.show()
plt.gcf().clear()
# Plot in logarithmic scale
ax = plt.gca()
ax.set_xscale('log')
plt.boxplot(byte_data, showfliers=False, vert=False)
plt.yticks([1, 2, 3, 4, 5], labels)
plt.xlabel(byte_xlabel)
plt.tight_layout()
plt.gcf().subplots_adjust(left=adjust_left)
plt.savefig(data_dir + '/plot/' + 'byte_error_%d_log.pdf' % delay, fmt='pdf')
#plt.show()
plt.gcf().clear()
def process_predictions(dataframe):
dataframe = dataframe[dataframe['real_packets'] > 0]
dataframe['packet_error'] = np.abs(dataframe['real_packets'] - dataframe['pred_packets'])
dataframe['byte_error'] = np.abs(dataframe['real_bytes'] - dataframe['pred_bytes'])
for delay in [0, 1, 33, 66, 333, 666, 2000]:
predictions_boxplot(dataframe[dataframe['delay'] == delay], delay)
def load(files):
dataframe_list = []
for dataframe_file in files:
df = pd.read_csv(dataframe_file, index_col=None, header=0)
dataframe_list.append(df)
return pd.concat(dataframe_list, ignore_index=True)
if __name__ == '__main__':
data_dir = './experiments'
delay_files = [data_dir + '/delay.csv']
#delay_files = [data_dir + '/no_delay_prediction']
prediction_files = [data_dir + '/prediction.csv']
#print 'Loading delays'
#delays = load(delay_files)
#process_delays(delays)
print 'Loading predictions'
predictions = load(prediction_files)
process_predictions(predictions) | [
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main.py | AntonHei/Undertale_DiscordRichPresence | 1 | 1603258 | <gh_stars>1-10
# ///////////////////////
# UndertaleDRP by AntonHei
# MIT License - Copyright (c) 2020 AntonHei
# ///////////////////////
# Imports
from pypresence import Presence
import time
import configparser
import os
from os import path
import json
import linecache
# General
config = configparser.ConfigParser()
file0 = configparser.ConfigParser()
drpconfig = configparser.ConfigParser()
undertaleDRPConfig = path.expandvars('config.ini')
saveGamePath = path.expandvars(r'%LOCALAPPDATA%' + r'\UNDERTALE\undertale.ini')
file0GamePath = path.expandvars(r'%LOCALAPPDATA%' + r'\UNDERTALE\file0')
undertaleDataPath = path.expandvars(r'data\{language}\undertale_data.json')
undertaleTranslationPath = path.expandvars(r'data\{language}\main_translations.json')
# UNDERTALE_DRP Data
config_showCurrentRoute = True
config_discordAppClientID = ""
# UNDERTALE Data
data_kills = ""
data_roomName = ""
data_roomArea = ""
data_roomAreaCodeName = ""
data_Name = ""
data_LV = ""
data_playtimeSeconds = ""
data_playtimeHours = ""
data_deaths = ""
# file0 Data
player_kills_ruins = None
player_kills_snowdin = None
player_kills_waterfall = None
player_kills_hotland = None
# Runtime Vars
startTime = ""
refreshInterval = 10
RPC = None
undertale_data = None
undertale_translations = None
areaPicNames = None
curDetails = None
curState = None
# Config Loadup
def drpConfigLoad():
global undertaleDataPath, undertaleTranslationPath
drpconfig.read(undertaleDRPConfig)
# Important data loads directly after reading
language = str(clearString(getDRPConfigData('UndertaleDRP', 'language')).split(".")[0])
undertaleDataPath = undertaleDataPath.replace('{language}', language)
undertaleTranslationPath = undertaleTranslationPath.replace('{language}', language)
def loadUndertaleDataJSON():
global undertale_data, undertale_translations
#UndertaleDRP Data
with open(undertaleDataPath) as f:
undertale_data = json.load(f)
# UndertaleDRP Translations
with open(undertaleTranslationPath) as f:
undertale_translations = json.load(f)
def configLoad():
config.read(saveGamePath)
def discordInit():
global RPC
client_id = config_discordAppClientID
RPC = Presence(client_id)
RPC.connect()
def getDRPConfigData(section, dataname):
return drpconfig[section][dataname]
def getConfigData(section, dataname):
return config[section][dataname]
def getfile0Line(line):
# Decrement with 1 because arrays start at 0
line -= 1
try:
return open(file0GamePath, "r").readlines()[line]
except:
return 0
def listToDict(lst):
op = {i: lst[i] for i in range(0, len(lst))}
return op
def prepareData():
global data_kills, data_roomName, data_roomArea, data_roomAreaCodeName, data_Name, data_LV, data_playtimeSeconds, data_playtimeHours, data_deaths, config_showCurrentRoute, config_discordAppClientID, areaPicNames, refreshInterval
# Getting the UndertaleDRP Config settings
config_showCurrentRoute = str(clearString(getDRPConfigData('UndertaleDRP', 'showRoute')).split(".")[0])
config_discordAppClientID = str(clearString(getDRPConfigData('UndertaleDRP', 'discordAppClientID')).split(".")[0])
refreshInterval = int(clearString(getDRPConfigData('UndertaleDRP', 'refreshInterval')).split(".")[0])
# Getting the Data
# Area kills
loadAreaKills()
# Discord App Area Pics
areaPicNames = listToDict(list(undertale_data['areaDiscordAppPicNames']))
# Rooms
curKills = str(clearString(getConfigData('General', 'Kills')).split(".")[0])
curRoomINT = int(clearString(getConfigData('General', 'Room')).split(".")[0])
curName = str(clearString(getConfigData('General', 'Name')).split(".")[0])
curLV = str(clearString(getConfigData('General', 'Love')).split(".")[0])
curPlaytimeINT = int(clearString(getConfigData('General', 'Time')).split(".")[0])
try:
curDeaths = str(clearString(getConfigData('General', 'Gameover')).split(".")[0])
except:
curDeaths = "0"
# Setting the Data
data_kills = curKills
data_roomName = undertale_data['rooms'][curRoomINT]['Name']
data_roomArea = undertale_data['rooms'][curRoomINT]['Area']
data_roomAreaCodeName = undertale_data['rooms'][curRoomINT]['Area_codename']
data_Name = curName
data_LV = curLV
data_playtimeSeconds = curPlaytimeINT / 30
data_playtimeHours = str(round(float(((curPlaytimeINT/30)/60)/60), 2)) # Calculate Frames to Seconds then to Minutes to Hours and cut off after 2 decimal places
data_deaths = curDeaths
def loadAreaKills():
#file0 is being used
global player_kills_ruins, player_kills_snowdin, player_kills_waterfall, player_kills_hotland
player_kills_ruins = str(getfile0Line(233))
player_kills_snowdin = str(getfile0Line(234))
player_kills_waterfall = str(getfile0Line(235))
player_kills_hotland = str(getfile0Line(236))
def clearString(str):
str = str.replace('"', '')
return str
def getAreaPicName(areaname):
return areaPicNames[0][areaname]
def convertToReadable(str):
# Location
str = str.replace("{room_name}", data_roomName)
str = str.replace("{room_area}", data_roomArea)
str = str.replace("{room_area_code_name}", data_roomAreaCodeName)
# Player
str = str.replace("{player_lv}", data_LV)
str = str.replace("{player_kills}", data_kills)
str = str.replace("{player_deaths}", data_deaths)
str = str.replace("{player_name}", data_Name)
# Area Kills
str = str.replace("{player_kills_ruins}", player_kills_ruins)
str = str.replace("{player_kills_snowdin}", player_kills_snowdin)
str = str.replace("{player_kills_waterfall}", player_kills_waterfall)
str = str.replace("{player_kills_hotland}", player_kills_hotland)
# General
str = str.replace("{played_time}", data_playtimeHours)
return str
def loadTranslations():
global curDetails, curState
# Loading Translations
curDetails = convertToReadable(undertale_translations['discordUI'][0]['details'])
curState = convertToReadable(undertale_translations['discordUI'][0]['state'])
# Routes: 0 - Neutral; 1 - Genocide
def caluclateCurrentRoute():
loadAreaKills()
ruinsNeededKills = 20
snowdinNeededKills = 16
waterfallNeededKills = 18
hotlandNeededKills = 40
if (data_roomAreaCodeName == "ruins" and int(player_kills_ruins) >= ruinsNeededKills):
return 1
if (data_roomAreaCodeName == "snowdin" and int(player_kills_snowdin) >= snowdinNeededKills):
return 1
if (data_roomAreaCodeName == "waterfall" and int(player_kills_waterfall) >= waterfallNeededKills):
return 1
if (data_roomAreaCodeName == "hotland" and int(player_kills_hotland) >= hotlandNeededKills):
return 1
return 0
def updateRPCWithRoute():
if (caluclateCurrentRoute() == 0):
RPC.update(
details=curDetails,
start=time.time() - int(data_playtimeSeconds),
large_image=getAreaPicName(data_roomArea),
large_text=data_roomArea,
small_image="sans_neutral",
small_text="Neutral Run",
state=curState
)
# If Route is Genocide
if (caluclateCurrentRoute() == 1):
RPC.update(
details=curDetails,
start=time.time() - int(data_playtimeSeconds),
large_image=getAreaPicName(data_roomArea),
large_text=data_roomArea,
small_image="sans_genocide",
small_text="Genocide Run",
state=curState
)
def updateRPC(calcNewTime):
#If time should be calculated or should continue
if(calcNewTime == True):
if (config_showCurrentRoute == "True"):
updateRPCWithRoute()
else:
RPC.update(
details=curDetails,
start=time.time() - int(data_playtimeSeconds),
large_image=getAreaPicName(data_roomArea),
large_text=data_roomArea,
state=curState
)
else:
if (config_showCurrentRoute == "True"):
updateRPCWithRoute()
else:
RPC.update(
details=curDetails,
start=startTime,
large_image=getAreaPicName(data_roomArea),
large_text=data_roomArea,
state=curState
)
def startUpdatePresence():
global startTime
print("Started Rich Presence")
startTime = time.time()-int(data_playtimeSeconds)
# Loading Translations
loadTranslations()
# Updates RPC with calculating a new Time
updateRPC(True)
def updatePresence():
print("Updated Rich Presence")
# Loading Translations
loadTranslations()
# Updates RPC without calculating a new Time
# Otherwise the Time would everytime reset to the time till the last save
updateRPC(False)
# Startup Discord Rich Presence
drpConfigLoad()
configLoad()
loadUndertaleDataJSON()
prepareData()
discordInit()
startUpdatePresence()
# Update Prodcedure
while True:
time.sleep(refreshInterval)
configLoad()
prepareData()
updatePresence()
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] |
app/board/handlers/figure.py | CodeSopranos/SopranosWeb | 0 | 130419 | from django.urls import reverse
from django.http import HttpResponse, HttpResponseRedirect
from django.contrib.auth import login, logout, authenticate
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth.decorators import login_required
from django.shortcuts import render, redirect, get_object_or_404
from django.contrib.auth.models import User
from board.models import Dashboard, Figure
from board.analyzer.Frequency import Frequency
@login_required(login_url='/board/signin/')
def add_figure(request, dashboard_id):
try:
figure_type = request.POST['figure_type']
except:
error_message = 'Please select figure type!'
context = {'error': error_message}
return get_dashboard(request, dashboard_id, additional_context=context)
dashboard = get_object_or_404(Dashboard, pk=dashboard_id)
analyzed_data = {'lol':1}
if figure_type == 'Frequency analysis':
analyzer = Frequency(dashboard.data)
analyzer.preprocess()
analyzed_data = analyzer.analyze().to_dict()
Figure.objects.create(dashboard=dashboard, type=figure_type, data=analyzed_data, params={'lol':1})
return HttpResponseRedirect(reverse('dashboard_by_id',
kwargs={'dashboard_id': dashboard_id}))
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] |
runs.py | petch/elsticity2019 | 1 | 37464 | <filename>runs.py
from ahm import *
from dfm import *
set_log_level(LogLevel.WARNING)
def run(N, n, h, k, c, g, f, ls='mumps', pc='default', do_write=True):
t1 = Timer()
m = int(N/n)
l = int(m/2)
fp, fm, fd, fb = fibers(N, N, l, h, n, k*n, do_write)
tp, tm, td, tb = fibers(N, N, 0, 0, n, k*n, do_write)
lp, lm, ld, lb = fibers(int(m/c), int(m/c), int(l/c), int(h/c), 1, k, do_write)
cp, cm, cd, cb = fibers(int(m/c), int(m/c), int(l/c/n), int(h/c/n), n, k*n, do_write)
E = [20e9, f*20e9]
mu, lmd = lame(E, [0.3, 0.3])
t1.stop()
t2 = Timer()
u = fem(fp, fm, fd, fb, mu, lmd, g, ls, pc, do_write)
ul2 = norm(u)
uli = norm(u.vector(), 'linf')
t2.stop()
t3 = Timer()
ua = ahm(lp + 'ahm_', lm, ld, lb, cp + 'ahm_', cm, cd, cb, mu, lmd, g, ls, pc, do_write)
ea = project(ua - u, u.function_space(), solver_type=ls, preconditioner_type=pc)
eal2 = norm(ea)/ul2
eali = norm(ea.vector(), 'linf')/uli
if do_write:
XDMFFile(fp + 'ahm_error.xdmf').write(ea)
t3.stop()
t4 = Timer()
ud = dfm(cp + 'dfm_', cm, cd, cb, mu, lmd, g, h/N, ls, pc, do_write)
ed = project(ud - u, u.function_space(), solver_type=ls, preconditioner_type=pc)
edl2 = norm(ed)/ul2
edli = norm(ed.vector(), 'linf')/uli
if do_write:
XDMFFile(fp + 'dfm_error.xdmf').write(ed)
t4.stop()
# print(t1.elapsed()[0], t2.elapsed()[0], t3.elapsed()[0], t4.elapsed()[0])
return eal2, eali, edl2, edli
# for ls in ['bicgstab', 'cg', 'gmres', 'minres', 'tfqmr']:
# for pc in ['amg', 'hypre_amg', 'hypre_euclid', 'hypre_parasails']:
# timer = Timer()
# try:
# eal2, eali, edl2, edli = run(256, 1, 2, 2, 1, ls, pc, False)
# print(ls, pc, timer.elapsed(), eal2, eali, edl2, edli)
# except:
# print(ls, pc, timer.elapsed(), 'error')
ls, pc, do_write = 'cg', 'amg', False
N0, n0, k0, d0, c0, f0 = 2048, 4, 1, 2, 1, 32
for g in [Constant([0, -1e5])]:
# run(N0, n0, d0, k0, c0, g, f0, ls, pc, True)
print('k\teal2\teali\tedl2\tedli')
for k in [1, 2, 4, 8, 16]:
eal2, eali, edl2, edli = run(N0, n0, d0, k, c0, g, f0, ls, pc, do_write)
print(f'{k*n0*n0}\t{eal2}\t{eali}\t{edl2}\t{edli}')
print('d\teal2\teali\tedl2\tedli')
for d in [2, 4, 8, 16, 32]:
eal2, eali, edl2, edli = run(N0, n0, d, k0, c0, g, f0, ls, pc, do_write)
print(f'{d/N0}\t{eal2}\t{eali}\t{edl2}\t{edli}')
print('f\teal2\teali\tedl2\tedli')
for f in [8, 16, 32, 64, 128]:
eal2, eali, edl2, edli = run(N0, n0, d0, k0, c0, g, f, ls, pc, do_write)
print(f'{f}\t{eal2}\t{eali}\t{edl2}\t{edli}')
print('n\teal2\teali\tedl2\tedli')
for n in [1, 2, 4, 8, 16]:
eal2, eali, edl2, edli = run(int(N0*n/16), n, d0, k0, c0, g, f0, ls, pc, do_write)
print(f'{n}\t{eal2}\t{eali}\t{edl2}\t{edli}')
print('h\teal2\teali\tedl2\tedli')
for c in [16, 8, 4, 2, 1]:
eal2, eali, edl2, edli = run(N0, n0, 16*d0, k0, c, g, f0, ls, pc, do_write)
print(f'{int(c/N0)}\t{eal2}\t{eali}\t{edl2}\t{edli}') | [
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mgcpy/independence_tests/unit_tests/mgc/data/gen_sims.py | neurodata-papers/mgc | 5 | 192526 | import numpy as np
from mgcpy.benchmarks.simulations import (circle_sim, cub_sim, exp_sim,
joint_sim, linear_sim, log_sim,
multi_indep_sim, multi_noise_sim,
quad_sim, root_sim, sin_sim,
spiral_sim, square_sim, step_sim,
two_parab_sim, ubern_sim, w_sim)
def gen_data(data_dir="./mgcpy/independence_tests/unit_tests/mgc/data/input/"):
NUM_SAMPLES = 50
NUM_DIMS = 1
def sin_sim_16(x, y): return sin_sim(x, y, period=16*np.pi)
def ellipsis_sim(x, y): return circle_sim(x, y, radius=5)
def square_sim_(x, y): return square_sim(x, y, period=-np.pi/4, indep=True)
simulations = [linear_sim, exp_sim, cub_sim, joint_sim, step_sim,
quad_sim, w_sim, spiral_sim, ubern_sim, log_sim,
root_sim, sin_sim, sin_sim_16, square_sim, two_parab_sim,
circle_sim, ellipsis_sim, square_sim_, multi_noise_sim, multi_indep_sim]
for simulation in simulations:
x, y = simulation(NUM_SAMPLES, NUM_DIMS)
np.savetxt(data_dir + str(simulation.__name__) + "_x.csv", x, delimiter=",")
np.savetxt(data_dir + str(simulation.__name__) + "_y.csv", y, delimiter=",")
def load_results(file_name, results_dir="./mgcpy/independence_tests/unit_tests/mgc/data/mgc/"):
mgc_results = np.genfromtxt(results_dir + file_name, delimiter=',')[1:]
pMGC = mgc_results[:, 0][0]
statMGC = mgc_results[:, 1][0]
pLocalCorr = mgc_results[:, 2:52]
localCorr = mgc_results[:, 52:102]
optimalScale = mgc_results[:, 102:104][0]
return (pMGC, statMGC, pLocalCorr, localCorr, optimalScale)
if __name__ == '__main__':
gen_data()
# print(load_results("linear_sim_res.csv"))
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] |
tfl_data.py | dongyan1024/overtime | 9 | 10553 | <reponame>dongyan1024/overtime<filename>tfl_data.py<gh_stars>1-10
import overtime as ot
times = ['14:00','14:05', '14:10', '14:15', '14:20', '14:25', '14:30', '14:35', '14:40', '14:45', '14:50', '14:55']
tfl_data = ot.TflInput(['victoria', 'central', 'bakerloo', 'piccadilly'], ['inbound', 'outbound'], times)
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services/catalog/tests/unit/with_dbs/test_entrypoint_dags.py | KZzizzle/osparc-simcore | 0 | 149855 | <gh_stars>0
# pylint:disable=unused-variable
# pylint:disable=unused-argument
# pylint:disable=redefined-outer-name
from typing import Dict, List
import pytest
from starlette.testclient import TestClient
from simcore_service_catalog.__version__ import api_version
from simcore_service_catalog.models.schemas.meta import Meta
core_services = ["postgres"]
ops_services = ["adminer"]
@pytest.mark.skip(reason="Failing on github actions")
def test_read_healthcheck(director_mockup, client: TestClient):
response = client.get("/")
assert response.status_code == 200
assert response.text == '":-)"'
@pytest.mark.skip(reason="Failing on github actions")
def test_read_meta(director_mockup, client: TestClient):
response = client.get("/v0/meta")
assert response.status_code == 200
meta = Meta(**response.json())
assert meta.version == api_version
assert meta.name == "simcore_service_catalog"
@pytest.mark.skip(reason="Failing on github actions")
def test_list_dags(director_mockup, client: TestClient):
response = client.get("/v0/dags")
assert response.status_code == 200
assert response.json() == []
# inject three dagin
response = client.get("/v0/dags")
assert response.status_code == 200
# TODO: assert i can list them as dagouts
# TODO: assert dagout have identifiers now
@pytest.mark.skip(reason="Failing on github actions")
def test_standard_operations_on_resource(
director_mockup, client: TestClient, fake_data_dag_in: Dict
):
response = client.post("/v0/dags", json=fake_data_dag_in)
assert response.status_code == 201
assert response.json() == 1
# list
response = client.get("/v0/dags")
assert response.status_code == 200
got = response.json()
assert isinstance(got, List)
assert len(got) == 1
# TODO: data_in is not the same as data_out??
data_out = got[0]
assert data_out["id"] == 1 # extra key, once in db
# get
response = client.get("/v0/dags/1")
assert response.status_code == 200
assert response.json() == data_out
# delete
response = client.delete("/v0/dags/1")
assert response.status_code == 204
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scratch/check_bins.py | AdriJD/cmb_sst_ksw | 0 | 47560 | <reponame>AdriJD/cmb_sst_ksw
'''
Test binning
'''
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import sys
import os
import numpy as np
from scipy.special import spherical_jn
sys.path.insert(0,'./../')
from sst import Fisher
opj = os.path.join
def bin_test(parity, bins=None, lmin=2, lmax=23):
'''
Init bins, run over them and test them.
'''
base_dir = '/mn/stornext/d8/ITA/spider/adri/analysis/20181025_sst/test/precomputed'
F = Fisher(base_dir)
F.init_bins(lmin=lmin, lmax=lmax, parity=parity, bins=bins)
bins = F.bins['bins']
pint = 1 if parity == 'odd' else 0
if F.mpi_rank == 0:
for i1, b1 in enumerate(bins):
for i2, b2 in enumerate(bins[i1:]):
i2 += i1
for i3, b3 in enumerate(bins[i2:]):
i3 += i2
ell1, ell2, ell3 = F.bins['first_pass'][i1,i2,i3]
num = F.bins['num_pass'][i1,i2,i3]
try:
if num == 0:
assert (ell1, ell2, ell3) == (0,0,0)
else:
assert (ell1, ell2, ell3) != (0,0,0)
if parity is not None:
assert (ell1 + ell2 + ell3) % 2 == pint
# check if first pass ells fit in bins
assert ell1 >= b1
assert ell2 >= b2
assert ell3 >= b3
try:
assert ell1 < bins[i1+1]
except IndexError:
if (i1 + 1) >= bins.size:
pass
else:
raise
try:
assert ell2 < bins[i2+1]
except IndexError:
if (i2 + 1) >= bins.size:
pass
else:
raise
try:
assert ell3 < bins[i3+1]
except IndexError:
if (i3 + 1) >= bins.size:
pass
else:
raise
# Check if first pass matches triangle cond.
assert abs(ell1 - ell2) <= ell3
assert ell3 <= (ell1 + ell2)
except:
print 'error in bin:'
print 'bin_idx: ({},{},{}), bin: ({},{},{}), no. gd_tuples: {}, '\
'u_ell: ({},{},{})'.format(i1, i2, i3, b1, b2, b3,
F.bins['num_pass'][i1,i2,i3],
ell1, ell2, ell3)
raise
print 'bins: ', F.bins['bins']
print 'lmin: ', F.bins['lmin']
print 'lmax: ', F.bins['lmax']
print 'sum num_pass: ', np.sum(F.bins['num_pass'])
print 'unique_ells: ', F.bins['unique_ells']
print 'num bins: ', F.bins['bins'].size
print 'shape num_pass: ', F.bins['num_pass'].shape
print 'shape first_pass: ', F.bins['first_pass'].shape, '\n'
if __name__ == '__main__':
lmin = 2
lmax = 40
for parity in ['even', 'odd', None]:
print 'parity: {}, lmin: {}, lmax: {}'.format(parity, lmin, lmax)
print 'default bins'
bin_test(lmin=lmin, lmax=lmax, parity=parity, bins=None)
print 'bins up to lmax'
bin_test(lmin=None, lmax=lmax, parity=parity, bins=[2,3,4,10,lmax])
print 'bins over lmax'
bin_test(lmin=None, lmax=lmax, parity=parity, bins=[2,3,4,10,lmax+12])
# if lmin and lmax of different binning schemes match, they
# should have matching sum(num_pass)
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29918,
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13,
2
] |
data/studio21_generated/interview/1618/starter_code.py | vijaykumawat256/Prompt-Summarization | 0 | 132148 | <gh_stars>0
def differentiate(equation, point):
| [
1,
529,
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29918,
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29900,
13,
1753,
17473,
403,
29898,
2573,
29892,
1298,
1125,
13,
12,
2
] |
routers/routers.py | Soulike/Class-Note-Manager-Python | 1 | 1603253 | <filename>routers/routers.py
from .Login import Login
from .NoteManagement import NoteManagement
from .ReactApp import ReactApp
# 注册所有子路由
def registerRouters(app):
app.register_blueprint(ReactApp)
app.register_blueprint(NoteManagement, url_prefix = '/server')
app.register_blueprint(Login, url_prefix = '/server')
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] |
SimPEG/utils/curvutils.py | jcapriot/simpeg | 1 | 165287 | <reponame>jcapriot/simpeg
from .code_utils import deprecate_module
deprecate_module("curvutils", "curv_utils", "0.15.0")
from .curv_utils import *
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detection/utils/misc_code.py | manogna-s/da-fer | 1 | 191550 | <gh_stars>1-10
"""
for image in os.listdir(images_path):
img = Image.open(os.path.join(images_path,image))
frame_draw = img.copy()
draw = ImageDraw.Draw(frame_draw)
for box in boxes:
draw.rectangle(box.tolist(), outline=(255, 0, 0), width=6)
for landmark in landmarks_points:
print(landmark)
draw.point(landmark,fill="black")
frame_draw.show()
d = display.display(draw, display_id=True)
"""
sys.exit()
# For a model pretrained on VGGFace2
model = InceptionResnetV1(pretrained='vggface2').eval()
# For a model pretrained on CASIA-Webface
model = InceptionResnetV1(pretrained='casia-webface').eval()
# For an untrained model with 100 classes
model = InceptionResnetV1(num_classes=100).eval()
# For an untrained 1001-class classifier
model = InceptionResnetV1(classify=True, num_classes=1001).eval()
# If required, create a face detection pipeline using MTCNN:
#mtcnn = MTCNN(image_size=<image_size>, margin=<margin>)
# Draw faces
frame_draw = img.copy()
draw = ImageDraw.Draw(frame_draw)
for box in boxes:
draw.rectangle(box.tolist(), outline=(255, 0, 0), width=6)
draw.point()
frame_draw.show()
d = display.display(draw, display_id=True)
# Create an inception resnet (in eval mode):
resnet = InceptionResnetV1(pretrained='vggface2').eval()
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2824,
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580,
13,
2
] |
survey/views_start.py | shagun30/djambala-2 | 0 | 107681 | # -*- coding: utf-8 -*-
"""
/dms/survey/views_start.py
.. enthaelt den View zum Starten der Dateneingabe des Fragebogens
Django content Management System
<NAME>
<EMAIL>
Die Programme des dms-Systems koennen frei genutzt und den spezifischen
Beduerfnissen entsprechend angepasst werden.
0.01 21.01.2008 Beginn der Arbeit
"""
from django.http import HttpResponseRedirect
from dms.roles import require_permission
from dms.queries import get_site_url
from dms_ext.extension import * # dms-Funktionen ueberschreiben
# -----------------------------------------------------
@require_permission('perm_manage_folderish')
def survey_start(request, item_container):
""" Eingaben in den Fragebogens unterbinden """
item_container.item.integer_2 = 1
item_container.item.save()
return HttpResponseRedirect(get_site_url(item_container, 'index.html'))
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] |
src/Python/Graphs/ConstructTree.py | sankhesh/vtk-examples | 0 | 132567 | #!/usr/bin/env python
import vtk
def main():
graph = vtk.vtkMutableDirectedGraph()
v1 = graph.AddVertex()
v2 = graph.AddChild(v1)
graph.AddChild(v1)
graph.AddChild(v2)
# equivalent to:
# V1 = g.AddVertex()
# V2 = g.AddVertex()
# V3 = g.AddVertex()
# V4 = g.AddVertex()
# g.AddEdge ( V1, V2 )
# g.AddEdge ( V1, V3 )
# g.AddEdge ( V2, V4 )
tree = vtk.vtkTree()
success = tree.CheckedShallowCopy(graph)
print('Success?', success)
# std::cout << 'Success? ' << success << std::endl
treeLayoutView = vtk.vtkGraphLayoutView()
treeLayoutView.AddRepresentationFromInput(tree)
treeLayoutView.SetLayoutStrategyToTree()
treeLayoutView.ResetCamera()
treeLayoutView.Render()
treeLayoutView.GetInteractor().Start()
if __name__ == '__main__':
main()
| [
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] |
desicos/abaqus/abaqus_functions.py | saullocastro/desicos | 1 | 106463 | r"""
=========================================================
Utilities Abaqus (:mod:`desicos.abaqus.abaqus_functions`)
=========================================================
.. currentmodule:: desicos.abaqus.abaqus_functions
Includes all utilities functions that must be executed from Abaqus.
"""
from __future__ import absolute_import
import math
import numpy as np
from .constants import (TOL, FLOAT, COLORS, COLOR_WHINE, COLOR_DARK_BLUE,
COLOR_BLACK)
from . import utils
def configure_session():
"""Improve layout and colors of the current figures in visualization
"""
from abaqus import session
from abaqusConstants import (ON, OFF, SMALL, DASHED, OUTSIDE,
HOLLOW_CIRCLE, DECIMAL, INCREMENT)
plot_names=session.xyDataObjects.keys()
if not 'XYPlot-1' in session.xyPlots.keys():
xyp=session.XYPlot('XYPlot-1')
else:
xyp=session.xyPlots['XYPlot-1']
chartName=xyp.charts.keys()[0]
chart=xyp.charts[chartName]
tmp=session.xyDataObjects.keys()
if len(tmp)==0:
return
xy1=session.xyDataObjects[tmp[0]]
c1=session.Curve(xyData=xy1)
chart.setValues(curvesToPlot=(c1,),)
session.viewports['Viewport: 1'].setValues(displayedObject=xyp)
chart=session.charts['Chart-1']
chart.minorAxis1GridStyle.setValues(show=True)
chart.majorAxis1GridStyle.setValues(show=True)
chart.majorAxis1GridStyle.setValues(style=DASHED)
chart.minorAxis2GridStyle.setValues(show=True)
chart.majorAxis2GridStyle.setValues(show=True)
chart.majorAxis2GridStyle.setValues(style=DASHED)
chart.gridArea.style.setValues(fill=False)
chart.legend.setValues(show=False) # necessary to update legend values
chart.legend.setValues(show=True)
chart.legend.area.setValues(inset=True)
chart.legend.area.setValues(originOffset=(0.,0.))
chart.legend.area.style.setValues(fill=True)
chart.legend.textStyle.setValues(
font='-*-arial narrow-medium-r-normal-*-*-480-*-*-p-*-*-*')
for name in plot_names:
c=session.Curve(xyData=session.xyDataObjects[name])
chart=session.xyPlots['XYPlot-1'].charts['Chart-1']
chart.setValues(curvesToPlot=(c,))
chart.fitCurves(fitAxes1=True, fitAxes2=True)
curve=session.charts['Chart-1'].curves[name]
curve.curveOptions.setValues(showSymbol=ON)
curve.curveOptions.setValues(symbolSize=SMALL)
curve.lineStyle.setValues(thickness=1.6)
curve.symbolStyle.setValues(size=5,
marker=HOLLOW_CIRCLE)
ax=chart.axes1[0]
ay=chart.axes2[0]
ax.labelStyle.setValues(
font='-*-arial narrow-bold-r-normal-*-*-480-*-*-p-*-*-*',
color=COLOR_BLACK)
ax.titleStyle.setValues(
font='-*-arial narrow-bold-r-normal-*-*-480-*-*-p-*-*-*',
color=COLOR_BLACK)
ay.labelStyle.setValues(
font='-*-arial narrow-bold-r-normal-*-*-480-*-*-p-*-*-*',
color=COLOR_BLACK)
ay.titleStyle.setValues(
font='-*-arial narrow-bold-r-normal-*-*-480-*-*-p-*-*-*',
color=COLOR_BLACK)
ax.setValues(tickPlacement=OUTSIDE)
ax.axisData.setValues(labelFormat=DECIMAL,
labelNumDigits=0,
minorTickCount=4,)
ay.setValues(tickPlacement=OUTSIDE)
ay.axisData.setValues(labelFormat=DECIMAL,
labelNumDigits=0,)
if ax.axisData.title.find('ispl')>-1:
ax.axisData.setValues(labelNumDigits=1)
if name.find('circumference') > -1:
ax.axisData.setValues(tickMode=INCREMENT,
tickIncrement=20,
minorTickCount=0,
minAutoCompute=False,
minValue=-180,
maxAutoCompute=False,
maxValue=185)
#
if (name.find('FI_HSNFCCRT') > -1 or name.find('FI_HSNFTCRT') > -1
or name.find('FI_HSNMCCRT') > -1 or name.find('FI_HSNMTCRT') > -1
or name.find('FI_TSAIW') > -1):
ay.axisData.setValues(labelNumDigits=1,
minAutoCompute=False,
minValue=0,
maxAutoCompute=False,
maxValue=2)
curve.lineStyle.setValues(thickness=1.6,
color=COLOR_WHINE)
curve.curveOptions.setValues(showSymbol=OFF)
ay.titleStyle.setValues(color=COLOR_WHINE)
ay.labelStyle.setValues(color=COLOR_WHINE)
#
if (name.find('MS_HSNFCCRT') > -1 or name.find('MS_HSNFTCRT') > -1
or name.find('MS_HSNMCCRT') > -1 or name.find('MS_HSNMTCRT') > -1
or name.find('MS_TSAIW') > -1
or name.find('MS_MAX') > -1 or name.find('MS_MIN') > -1):
ay.axisData.setValues(labelNumDigits=1,
minAutoCompute=False,
minValue=-0.5,
maxAutoCompute=False,
maxValue=1.0)
curve.lineStyle.setValues(thickness=1.6,
color=COLOR_DARK_BLUE)
curve.curveOptions.setValues(showSymbol=OFF)
ay.titleStyle.setValues(color=COLOR_DARK_BLUE)
ay.labelStyle.setValues(color=COLOR_DARK_BLUE)
def print_png(filename):
"""Print a png file from the current viewport
Parameters
----------
filename : str
The name of the output png file.
"""
from abaqus import session
from abaqusConstants import PNG
viewport=session.viewports[session.currentViewportName]
session.printToFile(fileName=filename,
format=PNG,
canvasObjects=(viewport,))
def set_default_view(cc):
"""Set a default view in order to compare figures from different models
Parameters
----------
cc : :class:`.ConeCyl` object
"""
from abaqusConstants import (USER_SPECIFIED, NODAL, COMPONENT, EXTRA_FINE,
FREE, UNIFORM, CONTINUOUS, ON, OFF)
odb=cc.attach_results()
if not odb:
print('No .odb file found for %s!' % cc.jobname)
return
dtm=odb.rootAssembly.datumCsyses[
'ASSEMBLY__T-INSTANCECYLINDER-CSYSCYLINDER']
viewport=session.viewports[session.currentViewportName]
viewport.odbDisplay.basicOptions.setValues(
averageElementOutput=False, transformationType=USER_SPECIFIED,
datumCsys=dtm)
viewport.odbDisplay.setPrimaryVariable(
variableLabel='U',
outputPosition=NODAL,
refinement=(COMPONENT, 'U1'),)
viewport.obasicOptions.setValues(averageElementOutput=True,
curveRefinementLevel=EXTRA_FINE)
viewport.odbDisplay.commonOptions.setValues(visibleEdges=FREE,
deformationScaling=UNIFORM,
uniformScaleFactor=5)
viewport.odbDisplay.contourOptions.setValues(contourStyle=CONTINUOUS)
viewport.restore()
viewport.viewportAnnotationOptions.setValues(compass=OFF)
viewport.viewportAnnotationOptions.setValues(triad=ON)
viewport.viewportAnnotationOptions.setValues(title=OFF)
viewport.viewportAnnotationOptions.setValues(state=OFF)
viewport.viewportAnnotationOptions.setValues(legend=ON)
viewport.viewportAnnotationOptions.setValues(legendTitle=OFF)
viewport.viewportAnnotationOptions.setValues(legendBox=OFF)
viewport.viewportAnnotationOptions.setValues(
legendFont='-*-arial narrow-bold-r-normal-*-*-140-*-*-p-*-*-*')
viewport.viewportAnnotationOptions.setValues(
legendFont='-*-arial narrow-bold-r-normal-*-*-180-*-*-p-*-*-*')
viewport.viewportAnnotationOptions.setValues(legendPosition=(1, 99))
viewport.viewportAnnotationOptions.setValues(legendDecimalPlaces=1)
viewport.setValues(origin=(0.0, -1.05833435058594),
height=188.030563354492,
width=203.452590942383)
viewport.view.setValues(viewOffsetX=-2.724,
viewOffsetY=-52.6898,
cameraUpVector=(-0.453666, -0.433365, 0.778705),
nearPlane=1192.17,
farPlane=2323.39,
width=750.942,
height=665.183,
cameraPosition=(1236.44, 1079.87, 889.94),
cameraTarget=(27.3027, -54.758, 306.503))
def edit_keywords(mod, text, before_pattern=None, insert=False):
"""Edit the keywords to add commands not available in Abaqus CAE
Parameters
----------
mod : Abaqus Model object
The model for which the keywords will be edited.
text : str
The text to be included.
before_pattern : str, optional
One pattern used to find where to put the given text.
insert : bool, optional
Insert the text instead of replacing it.
"""
mod.keywordBlock.synchVersions(storeNodesAndElements=False)
sieBlocks=mod.keywordBlock.sieBlocks
if before_pattern is None:
index=len(sieBlocks) - 2
else:
index=None
for i in range(len(sieBlocks)):
sieBlock=sieBlocks[i]
if sieBlock.find(before_pattern) > -1:
index=i-1
break
if index is None:
print('WARNING - *edit_keywords failed !')
print(' %s pattern not found !' % before_pattern)
#TODO better error handling here...
if insert:
mod.keywordBlock.insert(index, text)
else:
mod.keywordBlock.replace(index, text)
def create_composite_layup(name, stack, plyts, mat_names, region, part,
part_csys, symmetric=False, scaling_factor=1.,
axis_normal=2):
r"""Creates a composite layup
Parameters
----------
name : str
Name of the new composite layup.
stack : list
Stacking sequence represented by a list of orientations in degress.
The stacking sequence starts inwards a ends outwards. The 0 degree
angle is along the axial direction and the angles are measured using
the right-hand rule with the normal direction being normal to the
shell surface pointing outwards.
plyts : list
List containing the ply thicknesses.
mat_names : list
List containing the material name for each ply.
region : an Abaqus Region object
The region consisting of geometric faces, where this laminate will be
assigned to.
part : an Abaqus part Object
A part object where the layup will be created.
part_csys : a valid Datum object
The cylindrical coordinate system of the part object.
symmetric : bool, optional
A boolean telling whether the laminate is symmetric.
scaling_factor : float, optional
A scaling factor to be applied to each ply thickness. Used to apply
thickness imperfection in some cases.
axis_normal : int, optional
Reference
"""
from abaqusConstants import (MIDDLE_SURFACE, FROM_SECTION, SHELL, ON, OFF,
DEFAULT, UNIFORM, SIMPSON, GRADIENT, SYSTEM, ROTATION_NONE,
AXIS_1, AXIS_2, AXIS_3, SPECIFY_THICKNESS, SPECIFY_ORIENT,
SINGLE_VALUE)
myLayup=part.CompositeLayup(name=name,
description='stack from inside to outside',
offsetType=MIDDLE_SURFACE,
symmetric=False,
thicknessAssignment=FROM_SECTION,
elementType=SHELL)
myLayup.Section(preIntegrate=OFF,
integrationRule=SIMPSON,
thicknessType=UNIFORM,
poissonDefinition=DEFAULT,
temperature=GRADIENT,
useDensity=OFF)
if axis_normal == 1:
axis = AXIS_1
elif axis_normal == 2:
axis = AXIS_2
elif axis_normal == 3:
axis = AXIS_3
else:
raise ValueError('Invalid value for `axis_normal`')
myLayup.ReferenceOrientation(orientationType=SYSTEM,
localCsys=part_csys,
fieldName='',
additionalRotationType=ROTATION_NONE,
angle=0.,
additionalRotationField='',
axis=axis)
#CREATING ALL PLIES
numIntPoints=3
if len(stack)==1:
numIntPoints=5
for i, angle in enumerate(stack):
plyt=plyts[i]
mat_name=mat_names[i]
myLayup.CompositePly(suppressed=False,
plyName='ply_%02d' % (i+1),
region=region,
material=mat_name,
thicknessType=SPECIFY_THICKNESS,
thickness=plyt*scaling_factor,
orientationValue=angle,
orientationType=SPECIFY_ORIENT,
numIntPoints=numIntPoints)
def create_isotropic_section(name, mat_names, region, part, model,T,Sect_name,OFFTS):
"""Creates an isotropic section
"""
from abaqusConstants import (MIDDLE_SURFACE, FROM_SECTION, SHELL, ON, OFF,
DEFAULT, UNIFORM, SIMPSON, GRADIENT, SYSTEM, ROTATION_NONE,
AXIS_1, AXIS_2, AXIS_3, SPECIFY_THICKNESS, SPECIFY_ORIENT,NO_IDEALIZATION,
SINGLE_VALUE)
model.HomogeneousShellSection(name=name,
preIntegrate=OFF, material=mat_names[0],
thicknessType=UNIFORM, thickness=T, thicknessField='',
idealization=NO_IDEALIZATION, poissonDefinition=DEFAULT,
thicknessModulus=None, temperature=GRADIENT, useDensity=OFF,
integrationRule=SIMPSON, numIntPts=5)
region = region
if OFFTS==0.0:
part.SectionAssignment(region=region, sectionName=Sect_name,
offset=OFFTS,offsetType=MIDDLE_SURFACE,
offsetField='',
thicknessAssignment=FROM_SECTION)
else:
part.SectionAssignment(region=region, sectionName=Sect_name,
offset=OFFTS,offsetType=SINGLE_VALUE,
offsetField='',
thicknessAssignment=FROM_SECTION)
def modify_composite_layup(part, layup_name, modify_func):
"""Modify plies within a composite layup
Directly modififying plies within a CompositeLayup is not possible, as
the plies are read-only after creation. This function emulates modifying,
by deleting and then re-creating plies, with modifications.
Parameters
----------
part : an Abaqus part object
The part that the to-be-modified layup is attached to.
layup_name : str
Name of the layup that is to be modified.
modify_func : function
Function that will be called for each ply. It should take as arguments
the ply index and a dictionary of keyword arguments. This dictionary
contains all keyword arguments that would re-create the original ply,
if passed to the ``CompositePly``-constructor. This function should
should make the necessary changes this dictionary and then return it.
The returned dictionary will then be used to create the new ply.
"""
from abaqusConstants import SPECIFY_ORIENT, CSYS
layup = part.compositeLayups[layup_name]
ply_data = []
STORE_PLY_ATTRS = ['additionalRotationField', 'additionalRotationType',
'angle', 'axis', 'material', 'numIntPoints', 'orientation',
'orientationType', 'orientationValue', 'plyName', 'region',
'suppressed', 'thickness', 'thicknessType']
for ply in layup.plies.values():
ply_data.append(dict((attr, getattr(ply, attr)) for attr in STORE_PLY_ATTRS))
layup.deletePlies()
for i, kwargs in enumerate(ply_data):
kwargs['region'] = part.sets[kwargs['region'][0]]
if kwargs['orientationType'] != SPECIFY_ORIENT:
kwargs.pop('orientationValue')
if kwargs['orientationType'] != CSYS:
kwargs.pop('orientation')
kwargs = modify_func(i, kwargs)
layup.CompositePly(**kwargs)
def createDiscreteField(mod, odb, step_name, frame_num):
from abaqusConstants import (NODES, PRESCRIBEDCONDITION_DOF)
u=odb.steps[step_name].frames[frame_num].fieldOutputs['U']
ur=odb.steps[step_name].frames[frame_num].fieldOutputs['UR']
datas=[]
for u_value, ur_value in zip(u.values, ur.values):
id=u_value.nodeLabel
data=np.concatenate((u_value.data, ur_value.data))
datas.append([id, data])
datas.sort(key=lambda x: x[0])
list_ids=[]
list_dof_values=[]
for data in datas:
list_ids += [data[0] for i in range(6)]
for dof in range(1,7):
list_dof_values += [float(dof), data[1][dof-1]]
tuple_ids=tuple(list_ids)
tuple_dof_values=tuple(list_dof_values)
mod.DiscreteField(name='discreteField',
description='',
location=NODES,
fieldType=PRESCRIBEDCONDITION_DOF,
dataWidth=2,
defaultValues=(0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
data=(('', 2, tuple_ids, tuple_dof_values),))
def create_sketch_plane(cc, entity):
"""Creates a sketch plane tangent to the shell surface
Parameters
----------
cc : :class:`.ConeCyl` object
entity : object
Any object with the attribute: ``thetadeg``, usually a
:class:`.Imperfection`.
Returns
-------
plane : :class:`.Plane` object
"""
from abaqus import mdb
from .utils import geom
part = mdb.models[cc.model_name].parts[cc.part_name_shell]
for plane in cc.sketch_planes:
if abs(plane.thetadeg - entity.thetadeg) < TOL:
return plane
x1, y1, z1 = utils.cyl2rec(1.05*cc.r, entity.thetadeg, 0.)
v1 = np.array([x1, y1, z1], dtype=FLOAT)
x2, y2, z2 = utils.cyl2rec(1.05*cc.r2, entity.thetadeg, cc.h)
v2 = np.array([x2, y2, z2], dtype=FLOAT)
v3 = np.cross(v2, v1)
if abs(v3.max()) > abs(v3.min()):
v3 = v3/v3.max() * cc.h/2.
else:
v3 = v3/abs(v3.min()) * cc.h/2.
x3, y3, z3 = v2 + v3
pt = part.DatumPointByCoordinate(coords=(x1, y1, z1))
p1 = part.datums[pt.id]
pt = part.DatumPointByCoordinate(coords=(x2, y2, z2))
p2 = part.datums[pt.id]
pt = part.DatumPointByCoordinate(coords=(x3, y3, z3))
p3 = part.datums[pt.id]
plane = geom.Plane()
plane.p1 = p1
plane.p2 = p2
plane.p3 = p3
plane.part = part
plane.create()
plane.thetadeg = entity.thetadeg
cc.sketch_planes.append(plane)
return plane
def set_colors_ti(cc):
from abaqus import mdb, session
from abaqusConstants import ON
part = mdb.models[cc.model_name].parts[cc.part_name_shell]
viewport = session.viewports[session.currentViewportName]
if viewport.displayedObject is None:
viewport.setValues(displayedObject=part)
cmap = viewport.colorMappings['Set']
viewport.setColor(colorMapping=cmap)
viewport.enableMultipleColors()
viewport.setColor(initialColor='#BDBDBD')
keys = part.sets.keys()
names = [k for k in keys if 'Set_measured_imp_t' in k]
# If there are not enough colors for all thicknesses,
# repeat the same color for multiple subsequent thickness sets
repeat = int(math.ceil(max(len(names), 1.0) / float(len(COLORS))))
overrides = dict((name, (True, COLORS[i//repeat], 'Default',
COLORS[i//repeat])) for i, name in enumerate(names))
dummylen = len(keys)-len(overrides)
new_COLORS = tuple([COLORS[-1]]*dummylen + list(COLORS))
session.autoColors.setValues(colors=new_COLORS)
cmap.updateOverrides(overrides=overrides)
keys_to_hide = set(keys) - set(names)
overrides = dict([[k, (False, )] for k in keys_to_hide])
cmap.updateOverrides(overrides=overrides)
viewport.partDisplay.setValues(mesh=ON)
viewport.partDisplay.geometryOptions.setValues(referenceRepresentation=ON)
viewport.disableMultipleColors()
def printLBmodes():
from abaqus import session
from abaqusConstants import DPI_1200, EXTRA_FINE, OFF, PNG
vp = session.viewports[session.currentViewportName]
session.psOptions.setValues(logo=OFF,
resolution=DPI_1200,
shadingQuality=EXTRA_FINE)
session.printOptions.setValues(reduceColors=False)
for i in range(1,51):
vp.odbDisplay.setFrame(step=0, frame=i)
session.printToFile(fileName='mode %02d.png'%i,
format=PNG,
canvasObjects=(vp,))
def get_current_odbdisplay():
from abaqus import session
viewport = session.viewports[session.currentViewportName]
try:
name = viewport.odbDisplay.name
except:
return None
return viewport.odbDisplay
def get_current_odb():
from abaqus import session
viewport = session.viewports[session.currentViewportName]
odbdisplay = get_current_odbdisplay()
if odbdisplay:
return session.odbs[odbdisplay.name]
else:
return None
def get_current_step_name():
odbdisplay = get_current_odbdisplay()
if odbdisplay:
index, frame_num = odbdisplay.fieldFrame
return odbdisplay.fieldSteps[index][0]
else:
return None
def get_current_frame():
odbdisplay = get_current_odbdisplay()
if not odbdisplay:
return None
step_name = get_current_step_name()
step_num, frame_num = odbdisplay.fieldFrame
odb = get_current_odb()
step = odb.steps[step_name]
return step.frames[frame_num]
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plugins/libinst.cfg.puppet/src/libinst/cfg/puppet/nodes.py | gonicus/clacks | 2 | 1604210 | <gh_stars>1-10
# This file is part of the clacks framework.
#
# http://clacks-project.org
#
# Copyright:
# (C) 2010-2012 GONICUS GmbH, Germany, http://www.gonicus.de
#
# License:
# GPL-2: http://www.gnu.org/licenses/gpl-2.0.html
#
# See the LICENSE file in the project's top-level directory for details.
import re
import os
class PuppetNodeManager(object):
__node = re.compile("^node\s+['\"]?([^'\"\s]+)['\"]?(\s+inherits ['\"]?([^'\"]+)['\"]?)?\s*{$")
__include = re.compile("^include\s+['\"]*([^'\"]+)['\"]*$")
__var = re.compile("^\$([^\s=]+)\s*=\s*(['\"]?[^'\"]+['\"]?)$")
def __init__(self, path):
self.__path = path
self.__nodes = {}
trigger = False
# Create file, if it does not exist yet
if not os.path.exists(path):
open(path, "a")
for line in open(path, "r").readlines():
line = line.strip()
# Look for nodes
if line.startswith("node "):
name, dummy, inherit = self.__node.match(line).groups()
if not name in self.__nodes:
self.__nodes[name] = {'var': {}, 'inherit': inherit, 'include': []}
trigger = True
continue
# Look at the stuff inside of the node definition
if trigger:
# ... trigger an store process if the node is ready
if line.startswith("}"):
trigger = False
continue
# ... save potential variables
if line.startswith("$"):
key, value = self.__var.match(line).groups()
self.__nodes[name]['var'][key] = value
# ... save potential includes
if line.startswith("include"):
self.__nodes[name]['include'].append(self.__include.match(line).groups()[0])
def add(self, name, variables={}, includes=[], inherit=None):
self.__nodes[name] = {'var': variables, 'inherit': inherit, 'include': includes}
def remove(self, name):
del self.__nodes[name]
def write(self):
with open(self.__path, "w") as f:
f.write(self.__repr__())
def has(self, name):
return name in self.__nodes
def __repr__(self):
res = ""
for node, data in self.__nodes.items():
# Filter empty variables
r_vars = dict([(x, data['var'][x]) for x in data['var'] if data['var'][x]])
res += "node '%s' %s{\n" % (node, "inherits " + data['inherit'] + " " if data['inherit'] else "")
res += "\n".join(map(lambda x: "\tinclude %s" % x, data['include']))
res += "\n"
res += "\n".join(map(lambda x: "\t$%s = %s" % (x, r_vars[x]), r_vars))
res += "\n}\n\n"
return res.strip() + "\n"
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tests/algorithm/test_tournament_selector.py | wbknez/evored-warrior | 0 | 180980 | """
"""
from copy import copy
from random import randint
from unittest import TestCase
from pathos.multiprocessing import ProcessPool
from evored.genome import Genome
from evored.algorithm.selection import TournamentSelector
class TournamentSelectorTest(TestCase):
"""
Test suite for TournamentSelector.
"""
pool = ProcessPool(processes=2)
"""
The process pool for testing.
"""
def setUp(self):
self.params = {"selector.tournament_size": 4}
self.selector = TournamentSelector()
def tearDown(self):
pass
def test_basic_tournament_selection(self):
genomes = [
Genome(list(range(randint(1, 10))), 20),
Genome(list(range(randint(1, 10))), 32),
Genome(list(range(randint(1, 10))), 44),
Genome(list(range(randint(1, 10))), 2),
]
results = self.selector.select(None, genomes, self.params)
self.assertEqual(genomes[2], results)
def test_tournament_selection_in_parallel(self):
genomes = [
Genome(list(range(randint(1, 10))), 20),
Genome(list(range(randint(1, 10))), 44),
Genome(list(range(randint(1, 10))), 32),
Genome(list(range(randint(1, 10))), 2),
]
expected = [copy(genomes[1]) for _ in range(4)]
results = self.selector.evolve(genomes, self.pool, self.params)
self.assertEqual(len(results), 4)
self.assertEqual(results, expected)
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] |
pycatia/space_analyses_interfaces/section.py | evereux/catia_python | 90 | 179805 | #! usr/bin/python3.6
"""
Module initially auto generated using V5Automation files from CATIA V5 R28 on 2020-07-06 14:02:20.222384
.. warning::
The notes denoted "CAA V5 Visual Basic Help" are to be used as reference only.
They are there as a guide as to how the visual basic / catscript functions work
and thus help debugging in pycatia.
"""
from typing import TYPE_CHECKING
from pycatia.navigator_interfaces.annotated_views import AnnotatedViews
from pycatia.navigator_interfaces.group import Group
from pycatia.navigator_interfaces.marker_3Ds import Marker3Ds
from pycatia.system_interfaces.any_object import AnyObject
from pycatia.system_interfaces.system_service import SystemService
if TYPE_CHECKING:
from pycatia.in_interfaces.document import Document
class Section(AnyObject):
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| System.IUnknown
| System.IDispatch
| System.CATBaseUnknown
| System.CATBaseDispatch
| System.AnyObject
| Section
|
| Represents the Section object.
| The Section object is a specification of a sectioning display and
| computationwith a section plane, section slice or section box.
"""
def __init__(self, com_object):
super().__init__(com_object)
self.section = com_object
@property
def annotated_views(self) -> AnnotatedViews:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property AnnotatedViews() As AnnotatedViews (Read Only)
|
| Returns the AnnotatedViews collection of the section.
|
| Example:
|
| This example retrieves the AnnotatedViews collection of NewSection
| Section.
|
|
| Dim TheAnnotatedViewsList As AnnotatedViews
| Set TheAnnotatedViewsList = NewSection.AnnotatedViews
:return: AnnotatedViews
:rtype: AnnotatedViews
"""
return AnnotatedViews(self.section.AnnotatedViews)
@property
def behavior(self) -> int:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Behavior() As CatSectionBehavior
|
| Returns or sets the general behavior of the section: Freeze, Automatic
| update, manual update
|
| The behavior value are defined in CatSectionBehavior.
|
| Example:
|
| The first example retrieves the behavior of NewSection
| Section.
|
|
| Dim SectionBehavior As CatSectionBehavior
| Behavior = NewSection.Behavior
|
|
|
|
|
| The second example sets the behavior of NewSection
| Section.
|
|
| NewSection.Behavior = catSectionBehaviorAutomatic
:return: int
:rtype: int
"""
return self.section.Behavior
@behavior.setter
def behavior(self, value: int):
"""
:param int value:
"""
self.section.Behavior = value
@property
def cut_mode(self) -> int:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CutMode() As long
|
| Returns or sets the cutting mode of the section.
|
| The cutting mode value is 1 for clipping or 0 without
| clipping.
|
| Example:
|
| The first example retrieves the cutting mode of NewSection
| Section.
|
|
| Dim SectionMode As Integer
| SectionMode = NewSection.CutMode
|
|
|
|
|
| The second example sets the cutting mode of NewSection
| Section.
|
|
| NewSection.CutMode = 1
:return: int
:rtype: int
"""
return self.section.CutMode
@cut_mode.setter
def cut_mode(self, value: int):
"""
:param int value:
"""
self.section.CutMode = value
@property
def group(self) -> Group:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Group() As Group
|
| Returns or sets the sectioned group.
|
| By default, it is the all leaves group.
|
| Example:
|
| The first example retrieves the group of NewSection
| Section.
|
| Dim AGroup As Group
| AGroup = NewSection.Group
|
| The second example sets the group of NewSection
| Section.
|
| Dim AGroup As Group
| NewSection.Group = AGroup
:return: Group
:rtype: Group
"""
return Group(self.section.Group)
@group.setter
def group(self, value: Group):
"""
:param Group value:
"""
self.section.Group = value
@property
def height(self) -> float:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Height() As double
|
| Returns or sets the height of the section.
|
| The height value must be greater than 0.
|
| Example:
|
| The first example retrieves the height of NewSection
| Section.
|
|
| Dim SectionHeight As double
| SectionHeight = NewSection.Height
|
|
|
|
|
| The second example sets the height value of NewSection
| Section.
|
|
| NewSection.Height = 100.
:return: float
:rtype: float
"""
return self.section.Height
@height.setter
def height(self, value: float):
"""
:param float value:
"""
self.section.Height = value
@property
def marker_3ds(self) -> Marker3Ds:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-06-11 12:40:47.360445)
| o Property Marker3Ds() As Marker3Ds (Read Only)
|
| Returns the Marker3Ds collection of the section.
|
| Example:
|
| This example retrieves the Marker3Ds collection of NewSection
| Section.
|
|
| Dim TheMarker3DsList As Marker3Ds
| Set TheMarker3DsList = NewSection.Marker3Ds
:return: Marker3Ds
:rtype: Marker3Ds
"""
return Marker3Ds(self.section.Marker3Ds)
@property
def thickness(self) -> float:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Thickness() As double
|
| Returns or sets the thickness of the section.
|
| The thickness value must be greater than 0.
|
| Example:
|
| The first example retrieves the thickness of NewSection
| Section.
|
|
| Dim SectionThickness As double
| SectionThickness = NewSection.Thickness
|
|
|
|
|
| The second example sets the thickness value of NewSection
| Section.
|
|
| NewSection.Thickness = 100.
:return: float
:rtype: float
"""
return self.section.Thickness
@thickness.setter
def thickness(self, value: float):
"""
:param float value:
"""
self.section.Thickness = value
@property
def type(self) -> int:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Type() As CatSectionType
|
| Returns or sets the type of the section.
|
| The type value are defined in CatSectionType.
|
| Example:
|
| The first example retrieves the type of NewSection
| Section.
|
|
| Dim SectionType As CatSectionType
| SectionType = NewSection.Type
|
|
|
|
|
| The second example sets the type of NewSection
| Section.
|
|
| NewSection.Type = catSectionTypeSlice
:return: int
:rtype: int
"""
return self.section.Type
@type.setter
def type(self, value: int):
"""
:param int value:
"""
self.section.Type = value
@property
def width(self) -> float:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Width() As double
|
| Returns or sets the width of the section.
|
| The width value must be greater than 0.
|
| Example:
|
| The first example retrieves the width of NewSection
| Section.
|
|
| Dim SectionWidth As double
| SectionWidth = NewSection.Width
|
|
|
|
|
| The second example sets the width value of NewSection
| Section.
|
|
| NewSection.Width = 100.
:return: float
:rtype: float
"""
return self.section.Width
@width.setter
def width(self, value: float):
"""
:param float value:
"""
self.section.Width = value
def export(self) -> 'Document':
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384))
| o Func Export() As Document
|
| Exports the sections curves of the section in a document.
|
| Returns:
| The document
| Example:
|
| This example exports the section curves of NewSection Section in
| PartDoc document.
|
|
| Dim PartDoc As Document
| PartDoc = NewSection.Export
:return: Document
:rtype: Document
"""
from pycatia.in_interfaces.document import Document
return Document(self.section.Export())
def get_position(self) -> tuple:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384))
| o Sub GetPosition(CATSafeArrayVariant oComponents)
|
| Retrieves the position of the section.
|
| The position of the section is made of a coordinate system whose origin is
| the center of the section, and X and Y axes lie on the section. It is retrieved
| in an array of the X, Y, Z axes components and the origin components with
| respect to the absolute coordinate system.
|
| Parameters:
|
| oComponents
| The position of the section
|
| oComponents( 0) is the X component of the
| X-axis
| oComponents( 1) is the Y component of the
| X-axis
| oComponents( 2) is the Z component of the
| X-axis
| oComponents( 3) is the X component of the
| Y-axis
| oComponents( 4) is the Y component of the
| Y-axis
| oComponents( 5) is the Z component of the
| Y-axis
| oComponents( 6) is the X component of the
| Z-axis
| oComponents( 7) is the Y component of the
| Z-axis
| oComponents( 8) is the Z component of the
| Z-axis
| oComponents( 9) is the X component of the
| origin
| oComponents(10) is the Y component of the
| origin
| oComponents(11) is the Z component of the origin
|
|
| Example:
|
| This example retrieves the position of NewSection
| Section.
|
|
| Dim Components (11)
| NewSection.GetPosition Components
:return: tuple
:rtype: tuple
"""
vba_function_name = 'get_position'
vba_code = """
Public Function get_position(section)
Dim oComponents(11)
section.GetPosition oComponents
get_position = oComponents
End Function
"""
system_service = self.application.system_service
return system_service.evaluate(vba_code, 0, vba_function_name, [self.com_object])
def is_empty(self) -> int:
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384))
| o Func IsEmpty() As long
|
| Indicates whether the section is empty.
|
| The indicator value is 0 if the section is empty or 1 if the section
| comprise at least one segment.
|
| Example:
|
| This example retrieves the information on NewSection
| Section.
|
|
| Dim Indicator
| Indicator = NewSection.IsEmpty
:return: int
:rtype: int
"""
return self.section.IsEmpty()
def set_position(self, i_components: tuple):
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384))
| o Sub SetPosition(CATSafeArrayVariant iComponents)
|
| Sets the position of the section.
|
| Parameters:
|
| oComponents
| The position of the section with respect to the absolute coordinate
| system
|
| iComponents( 0) is the X component of the
| X-axis
| iComponents( 1) is the Y component of the
| X-axis
| iComponents( 2) is the Z component of the
| X-axis
| iComponents( 3) is the X component of the
| Y-axis
| iComponents( 4) is the Y component of the
| Y-axis
| iComponents( 5) is the Z component of the
| Y-axis
| iComponents( 6) is the X component of the
| Z-axis
| iComponents( 7) is the Y component of the
| Z-axis
| iComponents( 8) is the Z component of the
| Z-axis
| iComponents( 9) is the X component of the
| origin
| iComponents(10) is the Y component of the
| origin
| iComponents(11) is the Z component of the origin
|
|
| Example:
|
| This example sets the position of NewSection
| Section.
|
|
| Dim MatrixPos (11) As Double
| MatrixPos( 0) = 1.0
| MatrixPos( 1) = 0.0
| MatrixPos( 2) = 0.0
| MatrixPos( 3) = 0.0
| MatrixPos( 4) = 1.0
| MatrixPos( 5) = 0.0
| MatrixPos( 6) = 0.0
| MatrixPos( 7) = 0.0
| MatrixPos( 8) = 1.0
| MatrixPos( 9) = 1000.0
| MatrixPos(10) = 0.0
| MatrixPos(11) = 0.0
| NewSection.SetPosition MatrixPos
:param tuple i_components:
"""
return self.section.SetPosition(i_components)
def __repr__(self):
return f'Section(name="{self.name}")'
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obniz/parts/Moving/StepperMotor/__init__.py | izm51/obniz-python-sdk | 11 | 8683 | from attrdict import AttrDefault
import asyncio
class StepperMotor:
def __init__(self):
self.keys = ['<KEY> 'common']
self.required_keys = ['a', 'b', 'aa', 'bb']
self._step_instructions = AttrDefault(bool,
{
'1': [[0, 1, 1, 1], [1, 0, 1, 1], [1, 1, 0, 1], [1, 1, 1, 0]],
'2': [[0, 0, 1, 1], [1, 0, 0, 1], [1, 1, 0, 0], [0, 1, 1, 0]],
'1-2': [[0, 1, 1, 1], [0, 0, 1, 1], [1, 0, 1, 1], [1, 0, 0, 1], [1, 1, 0, 1], [1, 1, 0, 0], [1, 1, 1, 0], [0, 1, 1, 0]]
}
)
self.type = None
self.current_step = 0
self._step_type = '2'
self.frequency = 100
self.rotation_step_count = 100
self.milli_meter_step_count = 1
@staticmethod
def info():
return AttrDefault(bool, {'name': 'StepperMotor'})
def wired(self, obniz):
self.obniz = obniz
if obniz.is_valid_io(*[self.params.common]):
self.common = obniz.get_io(*[self.params.common])
self.common.output(*[True])
self.type = 'unipolar'
else:
self.type = 'bipolar'
self.ios = []
self.ios.append(*[obniz.get_io(*[self.params.a])])
self.ios.append(*[obniz.get_io(*[self.params.b])])
self.ios.append(*[obniz.get_io(*[self.params.aa])])
self.ios.append(*[obniz.get_io(*[self.params.bb])])
async def step_wait(self, step_count):
if type(step_count) in ['int', 'float']:
raise Exception('must provide number')
step_count = round(*[step_count])
if step_count == 0:
return
step_count_abs = abs(*[step_count])
instructions = self._get_step_instructions(*[])
instruction_length = len(instructions)
array = []
current_phase = self.current_step % instruction_length
if current_phase < 0:
current_phase = (instruction_length - current_phase * -1)
if step_count > 0:
for i in range(0, len(instructions), 1):
current_phase += 1
if current_phase >= instruction_length:
current_phase = 0
array.append(*[instructions[current_phase]])
else:
for i in range(0, len(instructions), 1):
current_phase -= 1
if current_phase < 0:
current_phase = (instruction_length - 1)
array.append(*[instructions[current_phase]])
msec = 1000 / self.frequency
msec = int(*[msec])
if msec < 1:
msec = 1
def anonymous0(index):
instruction = array[index]
for i in range(0, len(self.ios), 1):
self.ios[i].output(*[instruction[i]])
state = anonymous0
states = []
for i in range(0, instruction_length, 1):
states.append(*[AttrDefault(bool, {'duration': msec, 'state': state})])
await self.obniz.io.repeat_wait(*[states, step_count_abs])
self.current_step += step_count
async def step_to_wait(self, destination):
mustmove = (destination - self.current_step)
await self.step_wait(*[mustmove])
async def hold_wait(self):
instructions = self._get_step_instructions(*[])
instruction_length = len(instructions)
current_phase = self.current_step % instruction_length
if current_phase < 0:
current_phase = (instruction_length - current_phase * -1)
for i in range(0, len(self.ios), 1):
self.ios[i].output(*[instructions[current_phase][i]])
await self.obniz.ping_wait(*[])
async def free_wait(self):
for i in range(0, len(self.ios), 1):
self.ios[i].output(*[True])
await self.obniz.ping_wait(*[])
def step_type(self, step_type):
new_type = self._step_instructions[step_type]
if not new_type:
raise Exception('unknown step type ' + str(step_type))
self._step_type = step_type
def speed(self, step_per_sec):
self.frequency = step_per_sec
def current_rotation(self):
return self.current_step / self.rotation_step_count * 360
def current_angle(self):
angle = int(*[self.current_rotation(*[]) * 1000]) % 360000 / 1000
if angle < 0:
angle = (360 - angle)
return angle
async def rotate_wait(self, rotation):
rotation /= 360
needed = rotation * self.rotation_step_count
await self.step_wait(*[needed])
async def rotate_to_wait(self, angle):
needed = (angle - self.current_angle(*[]))
if abs(*[needed]) > 180:
needed = (needed - 360) if needed > 0 else (360 + needed)
needed = needed / 360 * self.rotation_step_count
await self.step_wait(*[needed])
def current_distance(self):
return self.current_step / self.milli_meter_step_count
async def move_wait(self, distance):
needed = distance * self.milli_meter_step_count
await self.step_wait(*[needed])
async def move_to_wait(self, destination):
needed = (destination - self.current_distance(*[])) * self.milli_meter_step_count
await self.step_wait(*[needed])
def _get_step_instructions(self):
return self._step_instructions[self._step_type] | [
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] |
L8-pandas-autocorr.py | jdherman/eci273 | 10 | 43109 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# read CSV data into a "dataframe" - pandas can parse dates
# this will be familiar to R users (not so much matlab users)
df = pd.read_csv('data/SHA.csv', index_col=0, parse_dates=True)
Q = df.SHA_INFLOW_CFS # a pandas series (daily)
# Q = Q.resample('AS-OCT').sum() # annual values
print(Q.autocorr(lag=1))
# plot a correlogram with confidence bounds
pd.plotting.autocorrelation_plot(Q)
plt.xlim([0,365])
plt.show()
from statsmodels.tsa import stattools
pacf,ci = stattools.pacf(Q, nlags=7, alpha=0.05)
plt.plot(pacf, linewidth=2)
plt.plot(ci, linestyle='dashed', color='0.5')
plt.show()
# we did this with pandas to simplify the resampling operations
# but we can also do it with numpy
# (using annual flow values)
Q = df.SHA_INFLOW_CFS.resample('AS-OCT').sum().values # now a numpy array
def autocorr(x,k):
return np.corrcoef(x[:len(x)-k], x[k:])[0,1]
print(autocorr(Q,k=1))
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] |
dosu/utils.py | tsandrini/DoSU | 0 | 45198 | <filename>dosu/utils.py
"""
__/\\\\\\\\\\\\______________________/\\\\\\\\\\\____/\\\________/\\\_
_\/\\\////////\\\__________________/\\\/////////\\\_\/\\\_______\/\\\_
_\/\\\______\//\\\________________\//\\\______\///__\/\\\_______\/\\\_
_\/\\\_______\/\\\_____/\\\\\______\////\\\_________\/\\\_______\/\\\_
_\/\\\_______\/\\\___/\\\///\\\_______\////\\\______\/\\\_______\/\\\_
_\/\\\_______\/\\\__/\\\__\//\\\_________\////\\\___\/\\\_______\/\\\_
_\/\\\_______/\\\__\//\\\__/\\\___/\\\______\//\\\__\//\\\______/\\\__
_\/\\\\\\\\\\\\/____\///\\\\\/___\///\\\\\\\\\\\/____\///\\\\\\\\\/___
_\////////////________\/////_______\///////////________\/////////_____
Created by <NAME>
"""
import yaml
import os
from .settings import HOME
class Config:
config_paths = (
HOME + '/.config/dosu/config.yml',
HOME + '/.dosu.yml',
)
def __init__(self):
self.config = self.load_raw_config()
self.subjects = self.load_subjects()
def load_raw_config(self):
for config_path in self.config_paths:
try:
with open(config_path, 'r') as ymlfile:
return yaml.load(ymlfile)
except IOError as e:
continue
else:
return None
def load_subjects(self):
if not self.config:
return None
base = self.get('general.root_dir')
if not base:
print ("DoSU root dir is not defined in config file")
sys.exit(2)
return set([name for name in os.listdir(base) if os.path.isdir(base + '/' + name)])
def get(self, key, fallback=None):
"""
Gets a cached value by its key using dotted notation
"""
try:
tmp = self.config
for fragment in key.split('.'):
tmp = tmp[fragment]
return tmp
except KeyError as e:
return fallback if fallback != None else key
def load_file(path):
with open(path, 'r') as f:
data = f.read()
return data
config = Config()
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2
] |
src/lib/pdb.py | DTenore/skulpt | 2,671 | 128113 | <reponame>DTenore/skulpt<filename>src/lib/pdb.py<gh_stars>1000+
import _sk_fail; _sk_fail._("pdb")
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] |
DeepSpeech/bin/import_ccpmf.py | adimaini/WEAT-WEFAT | 1 | 1604520 | <reponame>adimaini/WEAT-WEFAT<filename>DeepSpeech/bin/import_ccpmf.py
#!/usr/bin/env python
"""
Importer for dataset published from Centre de Conférence <NAME>-France
Ministère de l'Économie, des Finances et de la Relance
"""
import csv
import sys
import os
import progressbar
import subprocess
import zipfile
from glob import glob
from multiprocessing import Pool
import hashlib
import decimal
import math
import unicodedata
import re
import sox
import xml.etree.ElementTree as ET
try:
from num2words import num2words
except ImportError as ex:
print("pip install num2words")
sys.exit(1)
import requests
import json
from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
from deepspeech_training.util.helpers import secs_to_hours
from deepspeech_training.util.importers import (
get_counter,
get_importers_parser,
get_imported_samples,
get_validate_label,
print_import_report,
)
from ds_ctcdecoder import Alphabet
FIELDNAMES = ["wav_filename", "wav_filesize", "transcript"]
SAMPLE_RATE = 16000
CHANNELS = 1
BIT_DEPTH = 16
MAX_SECS = 10
MIN_SECS = 0.85
DATASET_RELEASE_CSV = "https://data.economie.gouv.fr/explore/dataset/transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020/download/?format=csv&timezone=Europe/Berlin&lang=fr&use_labels_for_header=true&csv_separator=%3B"
DATASET_RELEASE_SHA = [
("863d39a06a388c6491c6ff2f6450b151f38f1b57", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.001"),
("2f3a0305aa04c61220bb00b5a4e553e45dbf12e1", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.002"),
("5e55e9f1f844097349188ac875947e5a3d7fe9f1", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.003"),
("8bf54842cf07948ca5915e27a8bd5fa5139c06ae", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.004"),
("c8963504aadc015ac48f9af80058a0bb3440b94f", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.005"),
("d95e225e908621d83ce4e9795fd108d9d310e244", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.006"),
("de6ed9c2b0ee80ca879aae8ba7923cc93217d811", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.007"),
("234283c47dacfcd4450d836c52c25f3e807fc5f2", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.008"),
("4e6b67a688639bb72f8cd81782eaba604a8d32a6", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.009"),
("4165a51389777c8af8e6253d87bdacb877e8b3b0", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.010"),
("34322e7009780d97ef5bd02bf2f2c7a31f00baff", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.011"),
("48c5be3b2ca9d6108d525da6a03e91d93a95dbac", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.012"),
("87573172f506a189c2ebc633856fe11a2e9cd213", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.013"),
("6ab2c9e508e9278d5129f023e018725c4a7c69e8", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.014"),
("4f84df831ef46dce5d3ab3e21817687a2d8c12d0", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.015"),
("e69bfb079885c299cb81080ef88b1b8b57158aa6", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.016"),
("5f764ba788ee273981cf211b242c29b49ca22c5e", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.017"),
("b6aa81a959525363223494830c1e7307d4c4bae6", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.018"),
("91ddcf43c7bf113a6f2528b857c7ec22a50a148a", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.019"),
("fa1b29273dd77b9a7494983a2f9ae52654b931d7", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.020"),
("1113aef4f5e2be2f7fbf2d54b6c710c1c0e7135f", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.021"),
("ce6420d5d0b6b5135ba559f83e1a82d4d615c470", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.022"),
("d0976ed292ac24fcf1590d1ea195077c74b05471", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.023"),
("ec746cd6af066f62d9bf8d3b2f89174783ff4e3c", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.024"),
("570d9e1e84178e32fd867171d4b3aaecda1fd4fb", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.025"),
("c29ccc7467a75b2cae3d7f2e9fbbb2ab276cb8ac", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.026"),
("08406a51146d88e208704ce058c060a1e44efa50", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.027"),
("199aedad733a78ea1e7d47def9c71c6fd5795e02", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.028"),
("db856a068f92fb4f01f410bba42c7271de0f231a", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.029"),
("e3c0135f16c6c9d25a09dcb4f99a685438a84740", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.030"),
("e51b8bb9c0ae4339f98b4f21e6d29b825109f0ac", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.031"),
("be5e80cbc49b59b31ae33c30576ef0e1a162d84e", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.032"),
("501df58e3ff55fcfd75b93dab57566dc536948b8", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.033"),
("1a114875811a8cdcb8d85a9f6dbee78be3e05131", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.034"),
("465d824e7ee46448369182c0c28646d155a2249b", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.035"),
("37f341b1b266d143eb73138c31cfff3201b9d619", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.036"),
("9e7d8255987a8a77a90e0d4b55c8fd38b9fb5694", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.037"),
("54886755630cb080a53098cb1b6c951c6714a143", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.038"),
("4b7cbb0154697be795034f7a49712e882a97197a", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.039"),
("c8e1e565a0e7a1f6ff1dbfcefe677aa74a41d2f2", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip.040"),
]
def _download_and_preprocess_data(csv_url, target_dir):
dataset_sources = os.path.join(target_dir, "transcriptionsXML_audioMP3_MEFR_CCPMF_2012-2020", "data.txt")
if os.path.exists(dataset_sources):
return dataset_sources
# Making path absolute
target_dir = os.path.abspath(target_dir)
csv_ref = requests.get(csv_url).text.split('\r\n')[1:-1]
for part in csv_ref:
part_filename = requests.head(part).headers.get("Content-Disposition").split(" ")[1].split("=")[1].replace('"', "")
if not os.path.exists(os.path.join(target_dir, part_filename)):
part_path = maybe_download(part_filename, target_dir, part)
def _big_sha1(fname):
s = hashlib.sha1()
buffer_size = 65536
with open(fname, "rb") as f:
while True:
data = f.read(buffer_size)
if not data:
break
s.update(data)
return s.hexdigest()
for (sha1, filename) in DATASET_RELEASE_SHA:
print("Checking {} SHA1:".format(filename))
csum = _big_sha1(os.path.join(target_dir, filename))
if csum == sha1:
print("\t{}: OK {}".format(filename, sha1))
else:
print("\t{}: ERROR: expected {}, computed {}".format(filename, sha1, csum))
assert csum == sha1
# Conditionally extract data
_maybe_extract(target_dir, "transcriptionsXML_audioMP3_MEFR_CCPMF_2012-2020", "transcriptionsxml_audiomp3_mefr_ccpmf_2012-2020_2.zip", "transcriptionsXML_audioMP3_MEFR_CCPMF_2012-2020.zip")
# Produce source text for extraction / conversion
return _maybe_create_sources(os.path.join(target_dir, "transcriptionsXML_audioMP3_MEFR_CCPMF_2012-2020"))
def _maybe_extract(target_dir, extracted_data, archive, final):
# If target_dir/extracted_data does not exist, extract archive in target_dir
extracted_path = os.path.join(target_dir, extracted_data)
archive_path = os.path.join(target_dir, archive)
final_archive = os.path.join(extracted_path, final)
if not os.path.exists(extracted_path):
if not os.path.exists(archive_path):
print('No archive "%s" - building ...' % archive_path)
all_zip_parts = glob(archive_path + ".*")
all_zip_parts.sort()
cmdline = "cat {} > {}".format(" ".join(all_zip_parts), archive_path)
print('Building with "%s"' % cmdline)
subprocess.check_call(cmdline, shell=True, cwd=target_dir)
assert os.path.exists(archive_path)
print('No directory "%s" - extracting archive %s ...' % (extracted_path, archive_path))
with zipfile.ZipFile(archive_path) as zip_f:
zip_f.extractall(extracted_path)
with zipfile.ZipFile(final_archive) as zip_f:
zip_f.extractall(target_dir)
else:
print('Found directory "%s" - not extracting it from archive.' % extracted_path)
def _maybe_create_sources(dir):
dataset_sources = os.path.join(dir, "data.txt")
MP3 = glob(os.path.join(dir, "**", "*.mp3"))
XML = glob(os.path.join(dir, "**", "*.xml"))
MP3_XML_Scores = []
MP3_XML_Fin = {}
for f_mp3 in MP3:
for f_xml in XML:
b_mp3 = os.path.splitext(os.path.basename(f_mp3))[0]
b_xml = os.path.splitext(os.path.basename(f_xml))[0]
a_mp3 = b_mp3.split('_')
a_xml = b_xml.split('_')
score = 0
date_mp3 = a_mp3[0]
date_xml = a_xml[0]
if date_mp3 != date_xml:
continue
for i in range(min(len(a_mp3), len(a_xml))):
if (a_mp3[i] == a_xml[i]):
score += 1
if score >= 1:
MP3_XML_Scores.append((f_mp3, f_xml, score))
# sort by score
MP3_XML_Scores.sort(key=lambda x: x[2], reverse=True)
for s_mp3, s_xml, score in MP3_XML_Scores:
#print(s_mp3, s_xml, score)
if score not in MP3_XML_Fin:
MP3_XML_Fin[score] = {}
if s_mp3 not in MP3_XML_Fin[score]:
try:
MP3.index(s_mp3)
MP3.remove(s_mp3)
MP3_XML_Fin[score][s_mp3] = s_xml
except ValueError as ex:
pass
else:
print("here:", MP3_XML_Fin[score][s_mp3], s_xml, file=sys.stderr)
with open(dataset_sources, "w") as ds:
for score in MP3_XML_Fin:
for mp3 in MP3_XML_Fin[score]:
xml = MP3_XML_Fin[score][mp3]
if os.path.getsize(mp3) > 0 and os.path.getsize(xml) > 0:
mp3 = os.path.relpath(mp3, dir)
xml = os.path.relpath(xml, dir)
ds.write('{},{},{:0.2e}\n'.format(xml, mp3, 2.5e-4))
else:
print("Empty file {} or {}".format(mp3, xml), file=sys.stderr)
print("Missing XML pairs:", MP3, file=sys.stderr)
return dataset_sources
def maybe_normalize_for_digits(label):
# first, try to identify numbers like "50 000", "260 000"
if " " in label:
if any(s.isdigit() for s in label):
thousands = re.compile(r"(\d{1,3}(?:\s*\d{3})*(?:,\d+)?)")
maybe_thousands = thousands.findall(label)
if len(maybe_thousands) > 0:
while True:
(label, r) = re.subn(r"(\d)\s(\d{3})", "\\1\\2", label)
if r == 0:
break
# this might be a time or duration in the form "hh:mm" or "hh:mm:ss"
if ":" in label:
for s in label.split(" "):
if any(i.isdigit() for i in s):
date_or_time = re.compile(r"(\d{1,2}):(\d{2}):?(\d{2})?")
maybe_date_or_time = date_or_time.findall(s)
if len(maybe_date_or_time) > 0:
maybe_hours = maybe_date_or_time[0][0]
maybe_minutes = maybe_date_or_time[0][1]
maybe_seconds = maybe_date_or_time[0][2]
if len(maybe_seconds) > 0:
label = label.replace("{}:{}:{}".format(maybe_hours, maybe_minutes, maybe_seconds), "{} heures {} minutes et {} secondes".format(maybe_hours, maybe_minutes, maybe_seconds))
else:
label = label.replace("{}:{}".format(maybe_hours, maybe_minutes), "{} heures et {} minutes".format(maybe_hours, maybe_minutes))
new_label = []
# pylint: disable=too-many-nested-blocks
for s in label.split(" "):
if any(i.isdigit() for i in s):
s = s.replace(",", ".") # num2words requires "." for floats
s = s.replace("\"", "") # clean some data, num2words would choke on 1959"
last_c = s[-1]
if not last_c.isdigit(): # num2words will choke on "0.6.", "24 ?"
s = s[:-1]
if any(i.isalpha() for i in s): # So we have any(isdigit()) **and** any(sialpha), like "3D"
ns = []
for c in s:
nc = c
if c.isdigit(): # convert "3" to "trois-"
try:
nc = num2words(c, lang="fr") + "-"
except decimal.InvalidOperation as ex:
print("decimal.InvalidOperation: '{}'".format(s))
raise ex
ns.append(nc)
s = "".join(s)
else:
try:
s = num2words(s, lang="fr")
except decimal.InvalidOperation as ex:
print("decimal.InvalidOperation: '{}'".format(s))
raise ex
new_label.append(s)
return " ".join(new_label)
def maybe_normalize_for_specials_chars(label):
label = label.replace("%", "pourcents")
label = label.replace("/", ", ") # clean intervals like 2019/2022 to "2019 2022"
label = label.replace("-", ", ") # clean intervals like 70-80 to "70 80"
label = label.replace("+", " plus ") # clean + and make it speakable
label = label.replace("€", " euros ") # clean euro symbol and make it speakable
label = label.replace("., ", ", ") # clean some strange "4.0., " (20181017_Innovation.xml)
label = label.replace("°", " degré ") # clean some strange "°5" (20181210_EtatsGeneraux-1000_fre_750_und.xml)
label = label.replace("...", ".") # remove ellipsis
label = label.replace("..", ".") # remove broken ellipsis
label = label.replace("m²", "mètre-carrés") # 20150616_Defi_Climat_3_wmv_0_fre_minefi.xml
label = label.replace("[end]", "") # broken tag in 20150123_Entretiens_Tresor_PGM_wmv_0_fre_minefi.xml
label = label.replace(u'\xB8c', " ç") # strange cedilla in 20150417_Printemps_Economie_2_wmv_0_fre_minefi.xml
label = label.replace("C0²", "CO 2") # 20121016_Syteme_sante_copie_wmv_0_fre_minefi.xml
return label
def maybe_normalize_for_anglicisms(label):
label = label.replace("B2B", "B to B")
label = label.replace("B2C", "B to C")
label = label.replace("#", "hashtag ")
label = label.replace("@", "at ")
return label
def maybe_normalize(label):
label = maybe_normalize_for_specials_chars(label)
label = maybe_normalize_for_anglicisms(label)
label = maybe_normalize_for_digits(label)
return label
def one_sample(sample):
file_size = -1
frames = 0
audio_source = sample[0]
target_dir = sample[1]
dataset_basename = sample[2]
start_time = sample[3]
duration = sample[4]
label = label_filter_fun(sample[5])
sample_id = sample[6]
_wav_filename = os.path.basename(audio_source.replace(".wav", "_{:06}.wav".format(sample_id)))
wav_fullname = os.path.join(target_dir, dataset_basename, _wav_filename)
if not os.path.exists(wav_fullname):
subprocess.check_output(["ffmpeg", "-i", audio_source, "-ss", str(start_time), "-t", str(duration), "-c", "copy", wav_fullname], stdin=subprocess.DEVNULL, stderr=subprocess.STDOUT)
file_size = os.path.getsize(wav_fullname)
frames = int(subprocess.check_output(["soxi", "-s", wav_fullname], stderr=subprocess.STDOUT))
_counter = get_counter()
_rows = []
if file_size == -1:
# Excluding samples that failed upon conversion
_counter["failed"] += 1
elif label is None:
# Excluding samples that failed on label validation
_counter["invalid_label"] += 1
elif int(frames/SAMPLE_RATE*1000/10/2) < len(str(label)):
# Excluding samples that are too short to fit the transcript
_counter["too_short"] += 1
elif frames/SAMPLE_RATE < MIN_SECS:
# Excluding samples that are too short
_counter["too_short"] += 1
elif frames/SAMPLE_RATE > MAX_SECS:
# Excluding very long samples to keep a reasonable batch-size
_counter["too_long"] += 1
else:
# This one is good - keep it for the target CSV
_rows.append((os.path.join(dataset_basename, _wav_filename), file_size, label))
_counter["imported_time"] += frames
_counter["all"] += 1
_counter["total_time"] += frames
return (_counter, _rows)
def _maybe_import_data(xml_file, audio_source, target_dir, rel_tol=1e-1):
dataset_basename = os.path.splitext(os.path.split(xml_file)[1])[0]
wav_root = os.path.join(target_dir, dataset_basename)
if not os.path.exists(wav_root):
os.makedirs(wav_root)
source_frames = int(subprocess.check_output(["soxi", "-s", audio_source], stderr=subprocess.STDOUT))
print("Source audio length: %s" % secs_to_hours(source_frames / SAMPLE_RATE))
# Get audiofile path and transcript for each sentence in tsv
samples = []
tree = ET.parse(xml_file)
root = tree.getroot()
seq_id = 0
this_time = 0.0
this_duration = 0.0
prev_time = 0.0
prev_duration = 0.0
this_text = ""
for child in root:
if child.tag == "row":
cur_time = float(child.attrib["timestamp"])
cur_duration = float(child.attrib["timedur"])
cur_text = child.text
if this_time == 0.0:
this_time = cur_time
delta = cur_time - (prev_time + prev_duration)
# rel_tol value is made from trial/error to try and compromise between:
# - cutting enough to skip missing words
# - not too short, not too long sentences
is_close = math.isclose(cur_time, this_time + this_duration, rel_tol=rel_tol)
is_short = ((this_duration + cur_duration + delta) < MAX_SECS)
# when the previous element is close enough **and** this does not
# go over MAX_SECS, we append content
if (is_close and is_short):
this_duration += cur_duration + delta
this_text += cur_text
else:
samples.append((audio_source, target_dir, dataset_basename, this_time, this_duration, this_text, seq_id))
this_time = cur_time
this_duration = cur_duration
this_text = cur_text
seq_id += 1
prev_time = cur_time
prev_duration = cur_duration
# Keep track of how many samples are good vs. problematic
_counter = get_counter()
num_samples = len(samples)
_rows = []
print("Processing XML data: {}".format(xml_file))
pool = Pool()
bar = progressbar.ProgressBar(max_value=num_samples, widgets=SIMPLE_BAR)
for i, processed in enumerate(pool.imap_unordered(one_sample, samples), start=1):
_counter += processed[0]
_rows += processed[1]
bar.update(i)
bar.update(num_samples)
pool.close()
pool.join()
imported_samples = get_imported_samples(_counter)
assert _counter["all"] == num_samples
assert len(_rows) == imported_samples
print_import_report(_counter, SAMPLE_RATE, MAX_SECS)
print("Import efficiency: %.1f%%" % ((_counter["total_time"] / source_frames)*100))
print("")
return _counter, _rows
def _maybe_convert_wav(mp3_filename, _wav_filename):
if not os.path.exists(_wav_filename):
print("Converting {} to WAV file: {}".format(mp3_filename, _wav_filename))
transformer = sox.Transformer()
transformer.convert(samplerate=SAMPLE_RATE, n_channels=CHANNELS, bitdepth=BIT_DEPTH)
try:
transformer.build(mp3_filename, _wav_filename)
except sox.core.SoxError:
pass
def write_general_csv(target_dir, _rows, _counter):
target_csv_template = os.path.join(target_dir, "ccpmf_{}.csv")
with open(target_csv_template.format("train"), "w") as train_csv_file: # 80%
with open(target_csv_template.format("dev"), "w") as dev_csv_file: # 10%
with open(target_csv_template.format("test"), "w") as test_csv_file: # 10%
train_writer = csv.DictWriter(train_csv_file, fieldnames=FIELDNAMES)
train_writer.writeheader()
dev_writer = csv.DictWriter(dev_csv_file, fieldnames=FIELDNAMES)
dev_writer.writeheader()
test_writer = csv.DictWriter(test_csv_file, fieldnames=FIELDNAMES)
test_writer.writeheader()
bar = progressbar.ProgressBar(max_value=len(_rows), widgets=SIMPLE_BAR)
for i, item in enumerate(bar(_rows)):
i_mod = i % 10
if i_mod == 0:
writer = test_writer
elif i_mod == 1:
writer = dev_writer
else:
writer = train_writer
writer.writerow({"wav_filename": item[0], "wav_filesize": item[1], "transcript": item[2]})
print("")
print("~~~~ FINAL STATISTICS ~~~~")
print_import_report(_counter, SAMPLE_RATE, MAX_SECS)
print("~~~~ (FINAL STATISTICS) ~~~~")
print("")
if __name__ == "__main__":
PARSER = get_importers_parser(description="Import XML from Conference Centre for Economics, France")
PARSER.add_argument("target_dir", help="Destination directory")
PARSER.add_argument("--filter_alphabet", help="Exclude samples with characters not in provided alphabet")
PARSER.add_argument("--normalize", action="store_true", help="Converts diacritic characters to their base ones")
PARAMS = PARSER.parse_args()
validate_label = get_validate_label(PARAMS)
ALPHABET = Alphabet(PARAMS.filter_alphabet) if PARAMS.filter_alphabet else None
def label_filter_fun(label):
if PARAMS.normalize:
label = unicodedata.normalize("NFKD", label.strip()) \
.encode("ascii", "ignore") \
.decode("ascii", "ignore")
label = maybe_normalize(label)
label = validate_label(label)
if ALPHABET and label:
try:
ALPHABET.encode(label)
except KeyError:
label = None
return label
dataset_sources = _download_and_preprocess_data(csv_url=DATASET_RELEASE_CSV, target_dir=PARAMS.target_dir)
sources_root_dir = os.path.dirname(dataset_sources)
all_counter = get_counter()
all_rows = []
with open(dataset_sources, "r") as sources:
for line in sources.readlines():
d = line.split(",")
this_xml = os.path.join(sources_root_dir, d[0])
this_mp3 = os.path.join(sources_root_dir, d[1])
this_rel = float(d[2])
wav_filename = os.path.join(sources_root_dir, os.path.splitext(os.path.basename(this_mp3))[0] + ".wav")
_maybe_convert_wav(this_mp3, wav_filename)
counter, rows = _maybe_import_data(this_xml, wav_filename, sources_root_dir, this_rel)
all_counter += counter
all_rows += rows
write_general_csv(sources_root_dir, _counter=all_counter, _rows=all_rows)
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9507,
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4206,
353,
903,
26026,
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5215,
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281,
485,
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445,
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13,
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599,
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2863,
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4632,
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3972,
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903,
11808,
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497,
29918,
11808,
29892,
903,
5727,
29922,
497,
29918,
5727,
29897,
13,
2
] |
okta/models/app/AppUserProfile.py | xmercury-qb/okta-sdk-python | 1 | 110320 | <gh_stars>1-10
class AppUserProfile:
types = {
'username': str,
'password': <PASSWORD>
}
def __init__(self):
self.username = None # str
self.password = None # str
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setup.py | rmax/django-dummyimage | 11 | 101222 | <filename>setup.py
#!/usr/bin/env python
from setuptools import setup, find_packages
setup(
name = "django-dummyimage",
version = "0.1.1",
description = "Dynamic Dummy Image Generator For Django!",
author = "<NAME>",
author_email = "<EMAIL>",
url = "https://github.com/darkrho/django-dummyimage",
license = "BSD",
packages = find_packages(),
zip_safe=False, # because we're including media that Django needs
include_package_data = True,
install_requires = [
'django',
'pil',
],
classifiers=[
'Programming Language :: Python',
'Framework :: Django',
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
],
)
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21251,
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29897,
13,
2
] |
_posts/ideals_varieties_and_algorithms/chapter3/section2/ex-3-2-2.py | hidenori-shinohara/hidenori-shionohara.github.io | 0 | 1603012 | from sympy import *
from sympy.polys.orderings import monomial_key
x, y, z = symbols('x y z')
print(groebner([x*y - 1, x*z - 1], x, y, z, order='lex'))
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] |
profiles/apps.py | mlutok/portal_backend | 1 | 142161 | from django.apps import AppConfig
class ProfilesConfig(AppConfig):
name = "profiles"
verbose_name = "Profiles of Players"
def ready(self):
from . import signals
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src/fortrace/application/userManagement.py | dasec/ForTrace | 1 | 1603319 | <reponame>dasec/ForTrace<gh_stars>1-10
# Copyright (C) 2013-2014 <NAME>
# This file is part of fortrace - http://fortrace.fbi.h-da.de
# See the file 'docs/LICENSE' for copying permission.
# Modified by <NAME> in 2021
from __future__ import absolute_import
from __future__ import print_function
try:
import logging
import sys
import platform
import threading
import subprocess
import inspect # for listing all method of a class
import base64
import re
import six.moves.cPickle
# base class VMM side
from fortrace.application.application import ApplicationVmmSide
from fortrace.application.application import ApplicationVmmSideCommands
#
import fortrace.utility.picklehelper as ph
import fortrace.utility.guesttime as gt
# base class guest side
from fortrace.application.application import ApplicationGuestSide
from fortrace.application.application import ApplicationGuestSideCommands
from fortrace.utility.line import lineno
# module specific imports
import os.path
import getpass
except ImportError as ie:
print(("Import error! in userManagement.py " + str(ie)))
exit(1)
###############################################################################
# Host side implementation
###############################################################################
class UserManagementVmmSide(ApplicationVmmSide):
"""
This class is a remote control on the host-side to control a real <userManagement>
running on a guest.
"""
def __init__(self, guest_obj, args):
"""
Set default attribute values only.
@param guest_obj: The guest on which this application is running. (will be inserted from guest::application())
@param args: containing
logger: Logger name for logging.
"""
try:
super(UserManagementVmmSide, self).__init__(guest_obj, args)
self.logger.info("function: UserManagementVmmSide::__init__")
self.window_id = None
except Exception as e:
raise Exception(
lineno() + " Error: UserManagementHostSide::__init__ " + self.guest_obj.guestname + " " + str(e))
def open(self):
"""
Sends a command to open a userManagement on the associated guest.
"""
try:
self.logger.info("function: UserManagementVmmSide::open")
self.window_id = self.guest_obj.current_window_id
self.guest_obj.send("application " + "userManagement " + str(self.window_id) + " open ") # some parameters
self.guest_obj.current_window_id += 1
except Exception as e:
raise Exception("error UserManagementVmmSide::open: " + str(e))
def close(self):
"""Sends a command to close a <userManagement> on the associated guest.
"""
try:
self.logger.info("function: UserManagementVmmSide::close")
self.guest_obj.send("application " + "userManagement " + str(self.window_id) + " close ")
except Exception as e:
raise Exception("error UserManagementVmmSide:close()" + str(e))
def addUser(self, user_name, password):
"""
Creating a User on the guest system. Password should not exceed 14 characters
@param user_name: Name ot the user to create
@param password: <PASSWORD>
"""
if len(password) < 15 or password is None:
try:
self.logger.info("function: UserManagementVmmSide:addUser")
self.logger.debug("Adding user " + user_name + "; password: " + password)
ac = {"usr_name": user_name,
"password": password}
pcl_ac = ph.base64pickle(ac)
pcl_ac = pcl_ac.decode()
pw_cmd = "application userManagement " + str(self.window_id) + " addUser " + pcl_ac
self.is_busy = True
self.guest_obj.send(pw_cmd)
except Exception as e:
raise Exception("error UserManagementVmmSide:addUser " + str(e))
else:
self.logger.error(
"function: UserManagementVmmSide::addUser failed: Password exeeds maximum supported length or no password is provided")
def changeUser(self, user_name, password=None):
"""
Change the user that will be logged in to after next reboot
@param user_name: Name of the user that will be set at active
@param password: Password of the user account
"""
try:
self.logger.info("function: UserManagementVmmSide:changeUser")
self.logger.debug("Set " + user_name + "as default autostart user")
ac = {"usr_name": user_name,
"password": password}
pcl_ac = ph.base64pickle(ac)
pcl_ac = pcl_ac.decode()
pw_cmd = "application userManagement " + str(self.window_id) + " changeUser " + pcl_ac
self.is_busy = True
self.guest_obj.send(pw_cmd)
except Exception as e:
raise Exception("error UserManagementVmmSide:changeUser")
def deleteUser(self, user_name, d_type):
"""
Deleting a User on the guest system
@param user_name: Name of the user to delete
@param d_type: Type of deleting user data ("keep", "delete", "secure")
"""
try:
self.logger.info("function: UserManagementVmmSide:deleteUser")
self.logger.debug("deleting user" + user_name + "; deletion type:" + d_type)
ac = {"usr_name": user_name,
"del_type": d_type}
pcl_ac = ph.base64pickle(ac)
pcl_ac = pcl_ac.decode()
pw_cmd = "application userManagement " + str(self.window_id) + " deleteUser " + pcl_ac
self.is_busy = True
self.guest_obj.send(pw_cmd)
except Exception as e:
raise Exception("error UserManagementVmmSide:deleteUser() " + str(e))
###############################################################################
# Commands to parse on host side
###############################################################################
class UserManagementVmmSideCommands(ApplicationVmmSideCommands):
"""
Class with all commands for <userManagement> which will be received from the agent on the guest.
Static only.
"""
@staticmethod
def commands(guest_obj, cmd):
# cmd[0] = win_id; cmd[1] = state
module_name = "userManagement"
guest_obj.logger.debug("UserManagementVmmSideCommands::commands: " + cmd)
cmd = cmd.split(" ")
try:
if "opened" in cmd[1]:
guest_obj.logger.debug("in opened")
for obj in guest_obj.applicationWindow[module_name]:
if cmd[0] == str(obj.window_id):
guest_obj.logger.debug("window_id: " + str(obj.window_id) + " found!")
guest_obj.logger.info(module_name + " with id: " + str(obj.window_id) + " is_opened = true")
obj.is_opened = True
guest_obj.logger.debug("obj.is_opened is True now!")
if "busy" in cmd[1]:
guest_obj.logger.debug("in busy")
for obj in guest_obj.applicationWindow[module_name]:
if cmd[0] == str(obj.window_id):
guest_obj.logger.info(module_name + " with id: " + str(obj.window_id) + " is_busy = true")
obj.is_busy = True
if "ready" in cmd[1]:
guest_obj.logger.debug("in ready")
for obj in guest_obj.applicationWindow[module_name]:
if cmd[0] == str(obj.window_id):
guest_obj.logger.info(module_name + " with id: " + str(obj.window_id) + " is_busy = false")
obj.is_busy = False
if "error" in cmd[1]:
guest_obj.logger.debug("in error")
for obj in guest_obj.applicationWindow[module_name]:
if cmd[0] == str(obj.window_id):
guest_obj.logger.info(module_name + " with id: " + str(obj.window_id) + " has_error = True")
obj.has_error = True
except Exception as e:
raise Exception(module_name + "_host_side_commands::commands " + str(e))
###############################################################################
# Guest side implementation
###############################################################################
class UserManagementGuestSide(ApplicationGuestSide):
"""<userManagement> implementation of the guest side.
Usually Windows, Linux guest's
class attributes
window_id - The ID for the opened object
"""
def __init__(self, agent_obj, logger):
super(UserManagementGuestSide, self).__init__(agent_obj, logger)
try:
self.module_name = "userManagement"
self.timeout = None
self.window_is_crushed = None
self.window_id = None
self.agent_object = agent_obj
except Exception as e:
raise Exception("Error in " + self.__class__.__name__ +
": " + str(e))
def open(self, args):
"""
Open a <userManagement> and save the userManagement object with an id in a dictionary.
Set page load timeout to 30 seconds.
return:
Send to the host in the known to be good state:
'application <userManagement> window_id open'.
'application <userManagement> window_id ready'.
in the error state:
'application <userManagement> window_id error'.
additionally the 'window_is_crushed' attribute is set; so the next
call will open a new window.
"""
try:
arguments = args.split(" ")
var = arguments[0]
var2 = arguments[1]
self.logger.info(self.module_name + "GuestSide::open")
if var == "type":
self.logger.debug("wait for start UserManagement...")
# start application <skeletion>
self.logger.debug("started!")
elif var == "type2":
self.logger.debug("wait for start UserManagement...")
# start application <skeletion>
self.logger.debug("started!")
else:
self.logger.error("skeletion type " + var +
" not implemented")
return
# send some information about the userManagement state
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " opened")
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " ready")
self.window_is_crushed = False
except Exception as e:
self.logger.info("UserManagementGuestSide::open: Close all open windows and clear the userManagement list")
subprocess.call(["taskkill", "/IM", "userManagement.exe", "/F"])
# for obj in self.agent_object.applicationWindow[self.module_name]:
# self.agent_obj.applicationWindow[self.module_name].remove(obj)
# set a crushed flag.
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Error in " + self.__class__.__name__ + "::open" + ": selenium is crushed: " + str(e))
def close(self):
"""Close one given window by window_id"""
self.logger.info(self.__class__.__name__ +
"::close ")
self.seleniumDriver.quit()
def addUser(self, args):
"""
add a new user account to guest and prepare fortrace installation for that user
"""
self.logger.info(self.__class__.__name__ +
"::addUser ")
ad = ph.base64unpickle(args)
user = ad["usr_name"]
password = ad["password"]
if platform.system() == "Windows":
self.agent_object.send(
"application " + self.module_name + " " + str(self.window_id) + " creating user: " + user + " - password: " + password)
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " busy")
self.__createUser(user, password)
# add new user to group administrators
group = self.__getAdmingroupname()
self.__groupAdd(user, group)
# create user home directory
self.__createHomeDir(user, password)
# copy fortrace data to new users Desktop and enable script execution on first login
self.__copyInstallationFiles(user, password)
# set new user as active
self.logger.info(self.__class__.__name__ +
"::User created ")
# update guest timestamp
gTime = gt.getGuestTime()
self.agent_object.send("time {0}".format(gTime))
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " ready")
self.window_is_crushed = False
else:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Unknown System Platform, only Windows is supported at the moment")
# TODO: Add option to change user dynamical
def changeUser(self, args):
"""
Change the user, that will be logged in when the system starts up next time.
"""
self.logger.info(self.__class__.__name__ +
"::changeUser")
ad = ph.base64unpickle(args)
user = ad["usr_name"]
password = ad["password"]
if platform.system() == "Windows":
if password is None:
password = ""
logon_path = "HKEY_LOCAL_MACHINE\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon"
try:
self.agent_object.send(
"application " + self.module_name + " " + str(self.window_id) + " Changing active User on next reboot to: " + user)
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " busy")
subprocess.call(["CMD", "/c", "reg", "ADD", logon_path, "/v", "AutoAdminLogon", "/t", "REG_SZ", "/d", "1", "/f"])
subprocess.call(["CMD", "/c", "reg", "ADD", logon_path, "/v", "DefaultUserName", "/t", "REG_SZ", "/d", user, "/f"])
subprocess.call(["CMD", "/c", "reg", "ADD", logon_path, "/v", "DefaultPassword", "/t", "REG_SZ", "/d", password, "/f"])
#update Guest timestamp
gTime = gt.getGuestTime()
self.agent_object.send("time {0}".format(gTime))
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " ready")
self.window_is_crushed = False
except Exception as e:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Could not set " + user + " as default autostart user: " + lineno() + ' ' + str(e))
else:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Unknown System Platform, only Windows is supported at the moment")
def deleteUser(self, args):
"""
Delete user from the system
"""
self.logger.info(self.__class__.__name__ +
"::DeleteUser")
# extract Arguments
ad = ph.base64unpickle(args)
user = ad["usr_name"]
d_type = ad["del_type"]
if platform.system() == "Windows":
self.logger.debug(self.__class__.__name__ + "::DeletionType: " + d_type)
status = False
# Check if user is currently logged in
identity = getpass.getuser()
if identity.upper() == user.upper():
self.logger.error("User cannot delete itself")
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " user cannot delete itself")
# Delete user
else:
self.agent_object.send(
"application " + self.module_name + " " + str(self.window_id) + " Deleting User: " + user + " - deletion type: " + d_type)
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " busy")
try:
subprocess.call(["CMD", "/c", "net", "user", user, "/delete"])
self.logger.debug(self.__class__.__name__ + "::UserDeleted")
status = True
except Exception as e:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Could not delete user " + user + ": " + str(e))
# delete files after deleting the user
if status:
self.logger.info(self.__class__.__name__ + "::DeleteUserFiles of user: {0}".format(user))
sysdrive = os.getenv("SystemDrive")
user_fortrace_path = "{0}\\Users\\{1}\\Desktop\\fortrace".format(sysdrive, user)
user_fortrace_autostart = "{0}\\Users\\{1}\\AppData\\Roaming\\Microsoft\\Windows\\Start Menu\\Programs\\Startup\\startGuestAgent.lnk".format(sysdrive, user)
user_fortrace_python = "{0}\\Users\\{1}\\AppData\\Roaming\\Python".format(sysdrive, user)
homeDir = "{0}\\Users\\{1}".format(sysdrive, user)
# secure delete fortrace-data to reduce artifacts
try:
self.logger.debug(self.__class__.__name__ + "::deleting fortrace directory")
self.__secureDelete(user_fortrace_path)
self.logger.debug(self.__class__.__name__ + "::fortrace directory deleted")
self.logger.debug(self.__class__.__name__ + "::deleting autostart link")
# sdelete cannot delete a symbolic link
subprocess.call(["CMD", "/c", "del", user_fortrace_autostart, "/f", "/q"])
#self.__secureDeleteDirectory("\"{0}\"".format(user_fortrace_autostart))
#self.__secureDelete(user_fortrace_autostart)
self.logger.debug(self.__class__.__name__ + "::Link deleted")
self.logger.debug(self.__class__.__name__ + "::deleting Python site-packages")
self.__secureDelete(user_fortrace_python)
self.logger.debug(self.__class__.__name__ + "::Python site-packages deleted")
except Exception as e:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Could not autostart-Link " + user + ": " + str(e))
# Decide how to handle user home directory
if d_type.upper() == "KEEP":
self.logger.debug(self.__class__.__name__ + "::DeleteUserFiles(NONE)")
elif d_type.upper() == "DELETE":
self.logger.debug(self.__class__.__name__ + "::DeleteUserFiles(regular)")
self.__deleteDirectory(homeDir)
elif d_type.upper() == "SECURE":
self.logger.debug(self.__class__.__name__ + "::DeleteUserFiles(secure)")
self.__secureDelete(homeDir)
# TODO: remove workaround to delete undeletable AppData Dirs
subprocess.call(["CMD", "/c", "rd", "/s", "/q", homeDir])
# execute SDelete twice to ensure the Appdata\local directory is deleted as well
else:
self.logger.error("Wrong Parameter for user file deletion. Keeping user files!")
gTime = gt.getGuestTime()
self.agent_object.send("time {0}".format(gTime))
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " ready")
self.window_is_crushed = False
def __createUser(self, user, password):
"""
Create a new user account on the system
@param user: Name of the new user
@param password: Password of the <PASSWORD>
"""
try:
subprocess.call(["CMD", "/c", "NET", "USER", user, password, "/ADD"])
except Exception as e:
self.logger.error("adding user failed: " + lineno() + ' ' + str(e))
def __groupAdd(self, user, group):
# Todo: group remove
"""
Add a user to a existing group
@param user: Username to add
@param group: Name of the group to that the user will be added
"""
self.logger.info(self.__class__.__name__ +
"::groupAdd")
try:
subprocess.call(["CMD", "/c", "NET", "LOCALGROUP", group, user, "/ADD"])
except Exception as e:
self.logger.error("CMD", "/c", "User " + user + "could not be added to group " + group + ": " + lineno() + ' ' + str(e))
def __createHomeDir(self, user, password):
"""
Create the user directory on the system
@param user: Name of the new user
@param password: <PASSWORD> the <PASSWORD>
"""
self.logger.info(self.__class__.__name__ +
"::createHomeDir")
# check if Home-Directory already exists
# check for system drive letter
sysdrive = os.getenv("SystemDrive")
if os.path.exists(sysdrive + ":\\Users\\" + user):
self.logger.debug(self.__class__.__name__ +
"::HomeDir is already existing")
return
else:
# force creation of user directories by running command in user context
currentUser = getpass.getuser()
psexec_p = sysdrive + "\\Users\\{0}\\Desktop\\fortrace\\contrib\\windows-utils\\PsExec64.exe".format(currentUser)
wmic_p = sysdrive + "\\Windows\\system32\\wbem\\wmic"
try:
# opens an Windows Management Instrumentation session, which is directly closed again
# this is enough to create the new users home directory
# Parameter:
# -u: User
# -p: Password
# -nobanner/-accepteula: suppress unnecessary output
subprocess.call([psexec_p, "-u", user, "-p", password, "-nobanner", "-accepteula", wmic_p, "QUIT"])
except Exception as e:
self.logger.error("Creating Home Directory for user " + user + "failed: " + lineno() + ' ' + str(e))
def __copyInstallationFiles(self, user, password):
"""
Copy the fortrace folder to a new users desktop, so it can be installed and executed
@param user: Name of the new user
@param password: Password of the <PASSWORD> user
"""
self.logger.info(self.__class__.__name__ +
"::copyInstallationFiles")
sysdrive = os.getenv("SystemDrive")
currentUser = getpass.getuser()
fortrace_p = sysdrive + "\\Users\\{0}\\Desktop\\fortrace".format(currentUser)
fortrace_target_p = sysdrive + "\\Users\\{0}\\Desktop\\fortrace\\".format(user)
try:
# Parameter:
# /c ignore errors
# /e copies all subdirectories, including emtpy ones
# /y overwrites existing files
# /q supresses output
subprocess.call(["CMD", "/c", "Xcopy", fortrace_p, fortrace_target_p, "/c", "/e", "/y", "/q"])
except Exception as e:
self.logger.error("Copying fortrace data to new users Desktop failed: " + lineno() + ' ' + str(e))
self.logger.info(self.__class__.__name__ +
"::CreateStartupLink")
# set necessary paths for Link creation
link_dir = "{0}\\Users\\{1}\\AppData\\Roaming\\Microsoft\\Windows\\Start Menu\\Programs\\Startup".format(
sysdrive, user)
link_name = sysdrive + "\\Users\\{0}\\AppData\\Roaming\\Microsoft\\Windows\\Start Menu\\Programs\\Startup\\Installfortrace.lnk".format(
user)
link_target = sysdrive + "\\Users\\{0}\\Desktop\\fortrace\\install_tools\\autoinstall.bat".format(user)
psexec_p = sysdrive + "\\Users\\{0}\\Desktop\\fortrace\\contrib\\windows-utils\\PsExec64.exe".format(currentUser)
try:
os.mkdir(link_dir)
subprocess.call(
[psexec_p, "-u", user, "-p", password, "-nobanner", "-accepteula", "cmd", "/c", "MKLINK", link_name,
link_target])
except Exception as e:
self.logger.error("Link for automatic installation could not be created: " + lineno() + ' ' + str(e))
def __disablePasswordExpiration(self, user):
"""
Disable the password expiration for a new user
@param user: Name of the user account for that the expiration should be disabled
Function is not in use at the moment, keep if "expired password" Error appears again
"""
self.logger.info(self.__class__.__name__ +
"::disablePasswordExpiration")
try:
subprocess.call(["CMD", "/c", "WMIC", "USERACCOUNT", "WHERE", "NAME=\'{0}\'".format(user), "SET",
"PasswordExpires=FALSE"])
except Exception as e:
self.logger.error("disabling Passwort expiration was not possible: " + lineno() + ' ' + str(e))
def __getAdmingroupname(self):
"""
Identify the default system language and therefore return the name of the Admin-group
"""
self.logger.info(self.__class__.__name__ +
"::getAdminGroupName")
language_code = 0
group = "Administrators"
try:
# Get system language and extract the language code
output = subprocess.check_output(["CMD", "/c", "WMIC", "OS", "GET", "oslanguage"])
output = str(output)
language_code = re.findall(r'\d+', output)[0]
except Exception as e:
self.logger.error("Language could not be read from system: " + lineno() + ' ' + str(e))
if language_code == 0:
self.logger.error("No Language Code was extracted")
self.logger.debug("::Returning default language group Administrators")
group = "Administrators"
return group
elif language_code == "1031":
self.logger.info("::System language is german")
self.logger.debug("::Returning group Administratoren")
group = "Administratoren"
return group
elif language_code == "1033":
self.logger.info("::System language is english")
self.logger.debug("::Returning group Administrators")
group = "Administrators"
return group
else:
# installation should be english, therefore the default group will be Administrators
self.logger.error("unsupported system language code \"{0}\", trying to use default group".format(language_code))
self.logger.debug("::Returning default language group Administrators")
group = "Administrators"
return group
def __deleteDirectory(self, directory):
"""
Removes target directory
@param directory: target directory to delete
"""
try:
subprocess.call(["CMD", "/c", "rmdir", directory, "/S", "/Q"])
self.logger.debug(self.__class__.__name__ + "::userfiles deleted")
except Exception as e:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.logger.error("Could not delete userfiles:: " + lineno() + ' ' + str(e))
def __secureDelete(self, target):
"""
Secure deletion of a file or directory using the cipher command
@param target: Target to delete
"""
self.logger.info(self.__class__.__name__ +
"::secureDelete")
self.logger.debug(self.__class__.__name__ +
"::securely deleting" + target)
sysdrive = os.getenv("SystemDrive")
user = getpass.getuser()
sdelete_p = "{0}\\Users\\{1}\\Desktop\\fortrace\\contrib\\windows-utils\\sdelete64.exe".format(sysdrive, user)
try:
self.logger.debug(self.__class__.__name__ + "::Secure Deleting user files. This may taka a while...")
self.agent_object.send("application " + self.module_name + " " + str(
self.window_id) + "Secure Deleting user files. This may taka a while...")
self.agent_object.send("application " + self.module_name + " " + str(
self.window_id) + "Secure Deleting {0}".format(target))
# Secure delete Files at provided path
# -s Recurse subdirectories (if directory)
# -p Number of times to overwrite
# -r Remove Read-Only attribute.
# -q run without listing deleted files
subprocess.call([sdelete_p, "-s", "-r", "-q", "-p", "1", "-nobanner", "-accepteula", target])
except Exception as e:
self.window_is_crushed = True
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " error")
self.agent_object.send("application " + self.module_name + " " + str(self.window_id) + " secure deletion was not possible")
self.logger.error("Could not delete target:: " + lineno() + ' ' + str(e))
###############################################################################
# Commands to parse on guest side
###############################################################################
class UserManagementGuestSideCommands(ApplicationGuestSideCommands):
"""
Class with all commands for one application.
call the ask method for an object. The call will be done by a thread, so if the timeout is
reached, the open application will be closed and opened again.
Static only.
"""
@staticmethod
def commands(agent_obj, obj, cmd): # commands(obj, cmd) obj from list objlist[window_id] win id in cmd[1]?
try:
agent_obj.logger.info("static function UserManagementGuestSideCommands::commands")
agent_obj.logger.debug("command to parse: " + cmd)
com = cmd.split(" ")
if len(com) > 3:
args = " ".join(com[3:])
module = com[0] # inspect.stack()[-1][1].split(".")[0]
window_id = com[1]
method_string = com[2]
method_found = False
methods = inspect.getmembers(obj, predicate=inspect.ismethod)
for method in methods:
# method[0] will now contain the name of the method
# method[1] will contain the value
if method[0] == method_string:
# start methods as threads
method_found = True
agent_obj.logger.debug("method to call: " + method[0] + "(" + args + ")")
agent_obj.logger.debug("args")
tmp_thread = threading.Thread(target=method[1], args=(args,))
agent_obj.logger.debug("thread is defined")
tmp_thread.start()
agent_obj.logger.debug("thread started")
# increased timeout for secure deletion of user files
tmp_thread.join(3600) # Wait until the thread is completed
if tmp_thread.is_alive():
# close userManagement and set obj to crashed
agent_obj.logger.error("thread is alive... time outed")
agent_obj.logger.info(
"UserManagementGuestSideCommands::commands: Close all open windows and " + "clear the userManagement list")
subprocess.call(["taskkill", "/IM", "userManagement.exe", "/F"])
for obj in agent_obj.applicationWindow[module]:
agent_obj.applicationWindow[module].remove(obj)
# set a crushed flag.
obj.is_opened = False
obj.is_busy = False
obj.has_error = True
agent_obj.logger.info("application " + module + " " + str(window_id) + " error")
agent_obj.send("application " + module + " " + str(window_id) + " error")
if not method_found:
raise Exception("Method " + method_string + " is not defined!")
except Exception as e:
raise Exception("Error in UserManagementGuestSideCommands::commands " + str(e))
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] |
example.py | davehenton/tf-lyrics | 0 | 34601 | <gh_stars>0
from tflyrics import Poet, LyricsGenerator
artists = ['<NAME>', '<NAME>', 'The Beatles']
gen = LyricsGenerator(artists, per_artist=5)
ds = gen.as_dataset(batch_size=4)
p = Poet()
p.train_on(ds, n_epochs=10)
poem = p.generate(start_string='Hey ', n_gen_chars=1000)
print(poem)
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pkmn_type_scrapper.py | Cesar-Miranda/Pkm_Scrapper_DataAnalysis | 0 | 53772 | import scrapy
from scrapy.crawler import CrawlerProcess
def pkm_spider():
class PkmSpider(scrapy.Spider):
name = 'pkms'
def start_requests(self):
yield scrapy.Request('https://bulbapedia.bulbagarden.net/wiki/Bulbasaur_(Pok%C3%A9mon)')
def parse(self, response):
items = {}
# name = response.css('span.CurrentConditions--tempValue--1RYJJ::text').extract()
name = str(response.css('h1.firstHeading::text').get(default='Not Applicable').strip())[:-10]
next_pkm = str(response.xpath('//*[@id="mw-content-text"]/div/table[1]/tbody/tr[2]/td[3]/table/tbody/tr/td[1]/a/span/text()').get(default='Not Applicable').strip())[6:]
if next_pkm == 'plicable':
next_pkm = str(response.xpath('//*[@id="mw-content-text"]/div/table[1]/tbody/tr[1]/td[3]/table/tbody/tr/td[1]/a/span/text()').get(default='Not Applicable').strip())[6:]
else:
pass
type1 = response.xpath('//*[@id="mw-content-text"]/div/table[2]/tbody/tr[2]/td/table/tbody/tr/td[1]/table/tbody/tr/td[1]/a/span/b/text()').get(default='Not Applicable').strip()
type2 = response.xpath('//*[@id="mw-content-text"]/div/table[2]/tbody/tr[2]/td/table/tbody/tr/td[1]/table/tbody/tr/td[2]/a/span/b/text()').get(default='Not Applicable').strip()
items['name'] = name
items['type1'] = type1
items['type2'] = type2
yield items
yield scrapy.Request(f'https://bulbapedia.bulbagarden.net/wiki/{next_pkm}_(Pok%C3%A9mon)', callback=self.parse)
process = CrawlerProcess(settings={
'FEED_URI': 'pkmns_name_type.csv',
'FEED_FORMAT': 'csv'
})
process.crawl(PkmSpider)
process.start()
if __name__ == "__main__":
pkm_spider()
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Posts/viewsAPI.py | CMPUT404-Fa21-Organization/CMPUT404-Project-Social-Distribution | 3 | 483 | from django.conf import settings
from django.core import serializers
from django.utils import timezone
import requests
from Posts.commentModel import Comments
#from Posts.commentView import add_Comment
from rest_framework import status
from rest_framework.decorators import api_view, authentication_classes, permission_classes
from rest_framework.response import Response
from django.shortcuts import HttpResponse, render
from requests import get
from .serializers import CommentSerializer, PostSerializer
from Author.serializers import LikeSerializer
from Author.models import Like
from Author.views import updateForeignAuthors, GetForeignAuthors
from .models import Post, Author
from .form import PostForm
from Posts.commentForm import CommentForm
import json
import uuid
import re
import base64
from django.db.models import Q
import django.core
from permissions import CustomAuthentication, AccessPermission
from django.core.paginator import Paginator
import traceback
def newPost(request, uid=None, auth_pk=None):
form = PostForm(request.POST, request.FILES)
if form.is_valid():
title = form.cleaned_data['title']
descirption = form.cleaned_data['description']
categories = form.cleaned_data['categories'].split(' ')
visibility = form.cleaned_data['visibility']
unlisted = form.cleaned_data['unlisted']
contentType = form.cleaned_data['contentType']
if contentType == "application/app":
content = request.FILES['file'].read() #Inputfile
elif contentType in ["image/png", "image/jpeg",]:
content = base64.b64encode(request.FILES['file'].read()) #Inputfile
else:
content = form.cleaned_data["text"]
source = settings.SERVER_URL + "/"
origin = settings.SERVER_URL + "/"
author_id = Author.objects.get(pk=auth_pk)
id = author_id.url
author = json.loads(serializers.serialize('json', Author.objects.filter(pk=auth_pk), fields=('type', 'id', 'host', 'displayName', 'url', 'github',)))[0]['fields']
if uid == None:
r_uid = uuid.uuid4().hex
uid = re.sub('-', '', r_uid)
id = id + '/posts/' + uid + "/"
comments_id = id + "comments/"
published = timezone.now()
posts = Post(pk=uid, id=id, author_id=author_id, author=author, title=title, source=source, origin=origin, description=descirption, contentType=contentType, count=0, size=10, categories=categories,visibility=visibility, unlisted=unlisted, published=published, content=content, comments=comments_id)
posts.save()
return True
else:
print(request.data)
print(form.errors)
print(form.data)
return False
def add_Comment(request, post_pk, auth_pk, uid=None):
form = CommentForm(request.POST, request.FILES)
if form.is_valid():
updateForeignAuthors()
published = timezone.now()
contentType = form.cleaned_data['contentType']
if contentType == "application/app":
content = request.FILES['file'].read() #Inputfile
elif contentType in ["image/png", "image/jpeg",]:
content = base64.b64encode(request.FILES['file'].read()) #Inputfile
else:
content = form.cleaned_data["text"]
author_id = json.loads(serializers.serialize('json', Author.objects.filter(email=auth_pk), fields=('type', 'id', 'host', 'displayName', 'url', 'github',)))[0]['fields']
post = Post.objects.get(pk = post_pk)
post_pk_str = post_pk
if uid == None:
r_uid = uuid.uuid4().hex
uid = re.sub('-', '', r_uid)
comment_id = getattr(post, 'comments') + uid
comments = Comments(pk=uid, id=comment_id, Post_pk=post, Post_pk_str = post_pk_str, auth_pk_str = auth_pk, author=author_id, size=10, published=published, contentType=contentType, content=content)
comments.save()
return True
else:
print(request.data)
return False
@api_view(['GET',])
@authentication_classes([CustomAuthentication])
@permission_classes([AccessPermission])
def PostLikesView(request, post_pk, auth_pk):
post = Post.objects.get(post_pk = post_pk)
author = Author.objects.get(pk = auth_pk)
likeObjs = Like.objects.filter(~Q(auth_pk = author), object = post.id)
Likes = LikeSerializer(likeObjs, read_only=True, many=True)
likes = []
for l in Likes.data:
like = {}
for key in l:
if(key != "context"):
like[key] = l[key]
like["@context"] = l["context"]
like["author"] = json.loads(django.core.serializers.serialize('json', Author.objects.filter(id=l["author"]), fields=('type', 'id', 'displayName', 'host', 'url', 'github',)))[0]['fields']
likes.append(like)
response_dict = {
"type": "likes",
"items": likes
}
return Response(response_dict)
@api_view(['GET', 'POST',])
@authentication_classes([CustomAuthentication])
@permission_classes([AccessPermission])
def PostsList(request, auth_pk=None):
page_number = request.GET.get('page')
if 'size' in request.GET:
page_size = request.GET.get('size')
else:
page_size = 5
if request.method == 'GET':
if auth_pk:
try:
author = Author.objects.get(auth_pk=auth_pk)
posts = Post.objects.filter(author_id=author, id__icontains = "linkedspace")
code = status.HTTP_200_OK
paginator = Paginator(posts, page_size)
page_obj = paginator.get_page(page_number)
data = PostSerializer(page_obj.object_list, many=True).data
except Exception as e:
print(e)
data = {}
code = status.HTTP_400_BAD_REQUEST
else:
code = status.HTTP_200_OK
posts = Post.objects.filter(id__icontains = "linkedspace")
paginator = Paginator(posts, page_size)
page_obj = paginator.get_page(page_number)
data = PostSerializer(page_obj.object_list, many=True).data
elif request.method == 'POST':
if newPost(request, auth_pk=request.data['auth_pk']):
code = status.HTTP_201_CREATED
post = Post.objects.latest("published")
data = PostSerializer(post).data
else:
code = status.HTTP_400_BAD_REQUEST
data = {}
return Response(data, code)
@api_view(['GET', 'POST',])
@authentication_classes([CustomAuthentication])
@permission_classes([AccessPermission])
def commentListView(request, post_pk, auth_pk=None):
page_number = request.GET.get('page')
if 'size' in request.GET:
page_size = request.GET.get('size')
else:
page_size = 5
if request.method == 'GET':
comments = Comments.objects.filter(Post_pk_str=post_pk)
post = Post.objects.get(pk=post_pk)
post_id = getattr(post, 'id')
comment_id = getattr(post, 'comments')
paginator = Paginator(comments, page_size)
page_obj = paginator.get_page(page_number)
serializer = CommentSerializer(page_obj.object_list, many=True)
response_dict = {
"type": "comments",
"page": page_number,
"size": page_size,
"post": post_id,
"id": comment_id,
"comments": serializer.data,
}
return Response(response_dict)
elif request.method == 'POST':
if add_Comment(request, post_pk=request.data['Post_pk'], auth_pk=request.data['auth_pk']):
code = status.HTTP_202_ACCEPTED
comment = Comments.objects.latest("published")
data = CommentSerializer(comment).data
else:
code = status.HTTP_400_BAD_REQUEST
data = {}
return Response(data, code)
@api_view(['GET', 'POST', 'PUT', 'DELETE', ])
@authentication_classes([CustomAuthentication])
@permission_classes([AccessPermission])
def PostDetail(request, post_pk, auth_pk=None):
page_number = request.GET.get('page')
if 'size' in request.GET:
page_size = request.GET.get('size')
else:
page_size = 5
if request.method == 'GET':
try:
code = status.HTTP_200_OK
post = Post.objects.get(post_pk=post_pk)
serializer = PostSerializer(post)
except Exception as e:
print(e)
code = status.HTTP_404_NOT_FOUND
post = Post.objects.all()
paginator = Paginator(post, page_size)
page_obj = paginator.get_page(page_number)
serializer = PostSerializer(page_obj.object_list, many=True)
elif request.method == 'POST':
try:
code = status.HTTP_200_OK
post = Post.objects.get(post_pk=post_pk)
if 'title' in request.data.keys():
post.title = request.data['title']
if 'description' in request.data.keys():
post.description = request.data['description']
if 'categories' in request.data.keys():
post.categories = request.data['categories'].split(' ')
if 'visibility' in request.data.keys():
post.visibility = request.data['visibility']
if 'unlisted' in request.data.keys():
post.unlisted = request.data['unlisted']
if 'contentType' in request.data.keys():
post.contentType = request.data['contentType']
if post.contentType == "application/app":
post.content = request.FILES['file'].read() #Inputfile
elif post.contentType in ["image/png", "image/jpeg",]:
post.content = base64.b64encode(request.FILES['file'].read()) #Inputfile
else:
post.content = request.data["text"]
post.save()
serializer = PostSerializer(post)
except Exception as e:
print(e)
code = status.HTTP_400_BAD_REQUEST
post = Post.objects.all()
paginator = Paginator(post, page_size)
page_obj = paginator.get_page(page_number)
serializer = PostSerializer(page_obj.object_list, many=True)
elif request.method == 'PUT':
try:
code = status.HTTP_201_CREATED
assert newPost(request, post_pk, request.data['auth_pk'])==True
post = Post.objects.get(post_pk=post_pk)
serializer = PostSerializer(post)
except Exception as e:
print(e)
code = status.HTTP_400_BAD_REQUEST
post = Post.objects.all()
paginator = Paginator(post, page_size)
page_obj = paginator.get_page(page_number)
serializer = PostSerializer(page_obj.object_list, many=True)
elif request.method == 'DELETE':
try:
post = Post.objects.get(post_pk=post_pk)
post.delete()
code = status.HTTP_200_OK
except Exception as e:
print(e)
code = status.HTTP_404_NOT_FOUND
post = Post.objects.all()
paginator = Paginator(post, page_size)
page_obj = paginator.get_page(page_number)
serializer = PostSerializer(page_obj.object_list, many=True)
return Response(serializer.data, code)
@api_view(['GET', 'POST', ])
@authentication_classes([CustomAuthentication])
@permission_classes([AccessPermission])
def commentDetail(request, post_pk, comment_pk, auth_pk=None):
page_number = request.GET.get('page')
if 'size' in request.GET:
page_size = request.GET.get('size')
else:
page_size = 5
if request.method == 'GET':
try:
code = status.HTTP_200_OK
comment = Comments.objects.get(pk=comment_pk)
serializer = CommentSerializer(comment)
except Exception as e:
print(e)
code = status.HTTP_404_NOT_FOUND
comment = Comments.objects.all()
paginator = Paginator(comment, page_size)
page_obj = paginator.get_page(page_number)
serializer = CommentSerializer(page_obj.object_list, many=True)
elif request.method == 'POST':
try:
code = status.HTTP_200_OK
comment = Comments.objects.get(pk=comment_pk)
if 'contentType' in request.data.keys():
comment.contentType = request.data['contentType']
if 'text' in request.data.keys():
comment.content = request.data['text']
comment.save()
serializer = CommentSerializer(comment)
except Exception as e:
print(e)
code = status.HTTP_400_BAD_REQUEST
comment = Comments.objects.all()
paginator = Paginator(comment, page_size)
page_obj = paginator.get_page(page_number)
serializer = CommentSerializer(page_obj.object_list, many=True)
return Response(serializer.data, code)
@api_view(['GET',])
def connection(request, auth_id=None):
data = []
team3 = get('https://social-dis.herokuapp.com/posts', auth=('socialdistribution_t03','c404t03'))
if team3.status_code == 200:
data.append(team3.json())
team15 = get('https://unhindled.herokuapp.com/service/allposts/', auth=('connectionsuperuser','404connection'))
if team15.status_code == 200:
data.append(team15.json())
team17 = get('https://cmput404f21t17.herokuapp.com/service/connect/public/', auth=('4cbe2def-feaa-4bb7-bce5-<PASSWORD>','123456'))
if team17.status_code == 200:
data.append(team17.json())
return Response({'connection': data})
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src/brewlog/utils/app.py | zgoda/brewlog | 3 | 110522 | from flask import Flask
class Brewlog(Flask):
@property
def jinja_options(self):
options = dict(super().jinja_options)
options.update({
'trim_blocks': True,
'lstrip_blocks': True,
})
return options
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python/toy/weather_wechat.py | tagwan/scripts | 0 | 38632 | <reponame>tagwan/scripts
import requests
import json
import datetime
def weather(city):
url = "http://wthrcdn.etouch.cn/weather_mini?city=%s" % city
try:
data = requests.get(url).json()['data']
city = data['city']
ganmao = data['ganmao']
today_weather = data['forecast'][0]
res = "老婆今天是{}\n今天天气概况\n城市: {:<10}\n时间: {:<10}\n高温: {:<10}\n低温: {:<10}\n风力: {:<10}\n风向: {:<10}\n天气: {:<10}\n\n稍后会发送近期温度趋势图，请注意查看。\
".format(
ganmao,
city,
datetime.datetime.now().strftime('%Y-%m-%d'),
today_weather['high'].split()[1],
today_weather['low'].split()[1],
today_weather['fengli'].split('[')[2].split(']')[0],
today_weather['fengxiang'], today_weather['type'],
)
return {"source_data": data, "res": res}
except Exception as e:
return str(e)
"""
获取天气预报趋势图
"""
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import re
import datetime
def Future_weather_states(forecast, save_path, day_num=5):
'''
展示未来的天气预报趋势图
:param forecast: 天气预报预测的数据
:param day_num: 未来几天
:return: 趋势图
'''
future_forecast = forecast
dict = {}
for i in range(day_num):
data = []
date = future_forecast[i]["date"]
date = int(re.findall("\d+", date)[0])
data.append(int(re.findall("\d+", future_forecast[i]["high"])[0]))
data.append(int(re.findall("\d+", future_forecast[i]["low"])[0]))
data.append(future_forecast[i]["type"])
dict[date] = data
data_list = sorted(dict.items())
date = []
high_temperature = []
low_temperature = []
for each in data_list:
date.append(each[0])
high_temperature.append(each[1][0])
low_temperature.append(each[1][1])
fig = plt.plot(date, high_temperature, "r", date, low_temperature, "b")
current_date = datetime.datetime.now().strftime('%Y-%m')
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
plt.xlabel(current_date)
plt.ylabel("℃")
plt.legend(["高温", "低温"])
plt.xticks(date)
plt.title("最近几天温度变化趋势")
plt.savefig(save_path)
"""
发送到企业微信
"""
# -*- coding: utf-8 -*-
import requests
import json
class DLF:
def __init__(self, corpid, corpsecret):
self.url = "https://qyapi.weixin.qq.com/cgi-bin"
self.corpid = corpid
self.corpsecret = corpsecret
self._token = self._get_token()
def _get_token(self):
'''
获取企业微信API接口的access_token
:return:
'''
token_url = self.url + "/gettoken?corpid=%s&corpsecret=%s" % (self.corpid, self.corpsecret)
try:
res = requests.get(token_url).json()
token = res['access_token']
return token
except Exception as e:
return str(e)
def _get_media_id(self, file_obj):
get_media_url = self.url + "/media/upload?access_token={}&type=file".format(self._token)
data = {"media": file_obj}
try:
res = requests.post(url=get_media_url, files=data)
media_id = res.json()['media_id']
return media_id
except Exception as e:
return str(e)
def send_text(self, agentid, content, touser=None, toparty=None):
send_msg_url = self.url + "/message/send?access_token=%s" % (self._token)
send_data = {
"touser": touser,
"toparty": toparty,
"msgtype": "text",
"agentid": agentid,
"text": {
"content": content
}
}
try:
res = requests.post(send_msg_url, data=json.dumps(send_data))
except Exception as e:
return str(e)
def send_image(self, agentid, file_obj, touser=None, toparty=None):
media_id = self._get_media_id(file_obj)
send_msg_url = self.url + "/message/send?access_token=%s" % (self._token)
send_data = {
"touser": touser,
"toparty": toparty,
"msgtype": "image",
"agentid": agentid,
"image": {
"media_id": media_id
}
}
try:
res = requests.post(send_msg_url, data=json.dumps(send_data))
except Exception as e:
return str(e)
"""
main脚本
"""
# -*- coding: utf-8 -*-
from plugins.weather_forecast import weather
from plugins.trend_chart import Future_weather_states
from plugins.send_wechat import DLF
import os
# 企业微信相关信息
corpid = "xxx"
corpsecret = "xxx"
agentid = "xxx"
# 天气预报趋势图保存路径
_path = os.path.dirname(os.path.abspath(__file__))
save_path = os.path.join(_path, './tmp/weather_forecast.jpg')
# 获取天气预报信息
content = weather("大兴")
# 发送文字消息
dlf = DLF(corpid, corpsecret)
dlf.send_text(agentid=agentid, content=content['res'], toparty='1')
# 生成天气预报趋势图
Future_weather_states(content['source_data']['forecast'], save_path)
# 发送图片消息
file_obj = open(save_path, 'rb')
dlf.send_image(agentid=agentid, toparty='1', file_obj=file_obj)
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] |
data/free_st_chinese_mandarin_corpus.py | yeyupiaoling/MASR | 126 | 196409 | <filename>data/free_st_chinese_mandarin_corpus.py
import argparse
import functools
import codecs
import os
from utility import download, unpack
from utility import add_arguments, print_arguments
URL_ROOT = 'http://www.openslr.org/resources/38'
DATA_URL = URL_ROOT + '/ST-CMDS-20170001_1-OS.tar.gz'
MD5_DATA = 'c28ddfc8e4ebe48949bc79a0c23c5545'
parser = argparse.ArgumentParser(description=__doc__)
add_arg = functools.partial(add_arguments, argparser=parser)
parser.add_argument("--target_dir",
default="../dataset/audio/",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument("--annotation_text",
default="../dataset/annotation/",
type=str,
help="Sound annotation text save path. (default: %(default)s)")
args = parser.parse_args()
def create_annotation_text(data_dir, annotation_path):
print('Create Free ST-Chinese-Mandarin-Corpus annotation text ...')
f_a = codecs.open(os.path.join(annotation_path, 'free_st_chinese_mandarin_corpus.txt'), 'w', 'utf-8')
for subfolder, _, filelist in sorted(os.walk(data_dir)):
for file in filelist:
if '.wav' in file:
file = os.path.join(subfolder, file)
with codecs.open(file[:-4] + '.txt', 'r', 'utf-8') as f:
line = f.readline()
f_a.write(file[3:] + '\t' + line + '\n')
f_a.close()
def prepare_dataset(url, md5sum, target_dir, annotation_path):
"""Download, unpack and create manifest file."""
data_dir = os.path.join(target_dir, 'ST-CMDS-20170001_1-OS')
if not os.path.exists(data_dir):
filepath = download(url, md5sum, target_dir)
unpack(filepath, target_dir)
os.remove(filepath)
else:
print("Skip downloading and unpacking. Free ST-Chinese-Mandarin-Corpus data already exists in %s." % target_dir)
create_annotation_text(data_dir, annotation_path)
def main():
print_arguments(args)
if args.target_dir.startswith('~'):
args.target_dir = os.path.expanduser(args.target_dir)
prepare_dataset(url=DATA_URL,
md5sum=MD5_DATA,
target_dir=args.target_dir,
annotation_path=args.annotation_text)
if __name__ == '__main__':
main()
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server/src/voodoo/gen/caller_checker.py | zstars/weblabdeusto | 0 | 75106 | ALL = 'All servers'
def caller_check(servers = ALL):
def func_wrapper(func):
# TODO: To be implemented. Could get current_app and check it. Useful for anything?
return func
return func_wrapper
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adapt.py | fredericcassin/adapt-config | 0 | 87405 | #!/usr/bin/env python3
import fnmatch
import os
import sys
import yaml
import json
import re
import glob
import argparse
import csv
from jinja2 import Template
import yamlordereddictloader
import fs
from shutil import copyfile
from jsonpath_rw import jsonpath, parse
from box import Box
from deepmerge import always_merger
def not_yet_implemented():
print("Error: NOT YET IMPLEMENTED.")
exit(1)
# ==========================================================
# Add a patch to the patches structure for the scanned current file
# ==========================================================
def add_patch(patches, current_file, fileRelPath, fileformat, **attributes):
change = dict()
for attribute, value in attributes.items():
change[attribute] = value
if (current_file is None) or fileRelPath != current_file['file'] or fileformat != current_file['format']:
current_file = dict()
current_file['file'] = fileRelPath
current_file['format'] = fileformat
current_file['changes'] = list()
patches.append(current_file)
current_file['changes'].append(change)
return current_file
# ==========================================================
# Add an artifact to the artifacts structure. The artifact is unique according the [type, name] key thus avoiding duplicated artifacts
# The index arg is like a method static var to manage indexes for [type,name] keys
# ==========================================================
def add_artifact(artifacts, type, name, index=dict(), **attributes):
if type not in artifacts:
artifacts[type] = list()
index[type] = dict()
if name in index[type]:
artifact = index[type][name]
else:
artifact = dict()
artifact['name'] = name
artifacts[type].append(artifact)
index[type][name] = artifact
for attribute, value in attributes.items():
artifact[attribute] = value
# ==========================================================
# Resolve with a given context a value contaning possible Jinja rules
# ==========================================================
def resolve(value, context):
if not type(value) is str:
return value
return Template(value).render(context)
# ==========================================================
# Do a global rollback in a folder tree of a patched resource
# All patched files are suffixed by .orig
# ==========================================================
def rollback_resource(args):
files_to_rollback = []
target_dir = args.TARGET_PATH
origin_folder = os.getcwd()
target_dir = os.path.abspath(target_dir)
# we work with relative paths to the kubespray root, then we go to this root folder
os.chdir(target_dir)
for root, _, filenames in os.walk('.'):
for filename in fnmatch.filter(filenames, '*.orig'):
relative_filename = os.path.join(root, filename)
files_to_rollback.append(relative_filename)
for filename_orig in files_to_rollback:
filename = filename_orig[:-5]
copyfile(filename_orig, filename)
os.chdir(origin_folder)
# ==========================================================
# Create the specific scan resulting of a Kubespray Playbook root folder scan
# Returns the artifacts structured result of the scan
# ==========================================================
def scan_kubespray_playbook(args):
current_file = None
artifacts = dict()
patches = artifacts['patch'] = list()
yaml_files_to_scan = []
files_to_scan_regex = []
for root, _, filenames in os.walk('.'):
for filename in fnmatch.filter(filenames, 'main.yml'):
yaml_files_to_scan.append(os.path.join(root, filename))
for filename in fnmatch.filter(filenames, '*.repo.j2'):
files_to_scan_regex.append(os.path.join(root, filename))
pattern_image_repo = re.compile('(.+)_image_repo')
pattern_download_url = re.compile('(.+)_download_url')
pattern_image_tag = re.compile('(.+)_image_tag')
pattern_context_loaded = re.compile('(.+)_version')
pattern_image_id = re.compile('([^/]+/)?(.*)')
pattern_url = re.compile(r'(?:https?:\/\/(?:[^\/]+\/)+)([^\/]+)')
context = {'image_arch': 'amd64'}
# Merge optional additonal context from arguments
if not args.context is None:
for key, value in args.context:
context[key] = value
# Scann all yaml files of the current folder
for filename in yaml_files_to_scan:
with open(filename, "r", encoding='utf8') as yamlFile:
doc_data = yaml.load(yamlFile, Loader=yamlordereddictloader.Loader)
fileformat = 'yaml'
if doc_data is None:
continue
data = doc_data if type(doc_data) is list else [doc_data]
for elem in data:
# Because faster and simpler and enouth for now: only global yaml vars are considered, no recursion into child elements
for key, value in elem.items():
# Case of an empty string, we ignore the key
if type(value) is str and len(value) == 0: continue
if pattern_context_loaded.match(key) is not None:
# Case of a yaml var that could be used by the Jinja templating for searched artifacts var values
context[key] = resolve(value, context)
continue
varname_matching = pattern_image_tag.match(key)
if varname_matching is not None:
# Case of a yaml var {name}_image_tag
name = varname_matching.group(1)
context[key] = resolved_value = resolve(
value, context)
add_artifact(artifacts, type='image_repo', name=name,
tag=resolved_value)
varname_matching = pattern_image_repo.match(key)
if varname_matching is not None:
# Case of a yaml var {name}_image_repo
name = varname_matching.group(1)
context[key] = resolved_value = resolve(
value, context)
image_id_matching = pattern_image_id.match(
resolved_value)
if image_id_matching is not None:
# the {name}_image_repo value is an image provided by an Internet URL, so we create a patch changing the registry prefix of this value
# to use a local registry where the image will be pushed in
current_file = add_patch(patches, current_file, filename, fileformat, json_path = varname_matching.group(0),
new_value = '{{{{ local_registry }}}}/{}'.format(
image_id_matching.group(2)),
old_value = value,
name = name)
# The image downloaded from the Internet mut be pushed to the local registry so it is added to the list of artifacts to dump
add_artifact(artifacts, type='image_repo', name=name,
ref=resolved_value, image=image_id_matching.group(2))
continue
varname_matching = pattern_download_url.match(key)
if varname_matching is not None:
# Case of a yaml var {name}_download_url
name = varname_matching.group(1)
context[key] = resolved_value = resolve(
value, context)
artifact_url = pattern_url.match(resolved_value)
if artifact_url is not None:
download_url_filename = artifact_url.group(1)
# The {name}_image_repo value is a file Internet download, we change the URL to use a local http or file repo
current_file = add_patch(patches, current_file, filename, fileformat, json_path = varname_matching.group(0),
new_value = '{{{{ local_folder }}}}/{}'.format(
download_url_filename),
old_value = value,
name = name)
# The file downloaded from the Internet must be pushed to the local repo so it is added to the list of artifacts to dump
add_artifact(artifacts, type='download_url', name=name,
url=resolved_value, filename=download_url_filename)
# Scan not structured files.
# And no ulike for Helm Charts, YAML files are not scanned as unstructured files
# so we don't execute files_to_scan_regex.extend(yaml_files_to_scan)
# scan git clone <url<name>> <folder>
# don't use this more comple able to capture the [named section] containing a given gpgcheck
#gpgcheck_re = re.compile(r'\[(?P<section_name>[^\n]*)\](?:(?!\n\[[^\n].*|\ngpgcheck=1)\n[^\n]*)*\n(?P<left_term>gpgcheck\s*=)\s*(?P<value>1)', re.MULTILINE + re.DOTALL)
gpgcheck_re = re.compile(r'^(?P<left_term>gpgcheck\s*=)\s*(?P<value>1)$', re.MULTILINE)
for filename in files_to_scan_regex:
with open(filename, "r", encoding='utf8') as unstructured_file:
data = unstructured_file.read()
for item in re.finditer(gpgcheck_re, data):
left_term, value = item.group('left_term'), item.group('value')
new_value = '{left_term}{value}'.format(left_term=left_term, value='0')
current_file = add_patch(patches, current_file, filename, 'text', new_value=new_value, old_value=item.group(0))
return artifacts
# ==========================================================
# Do a recursive scan of an OpenWhisk Helm Chart part elemTuple at given jsonpath for a current scanned file
# Add scanned dependencies resources in artifacts and change to be done in patches structure
# ==========================================================
def scan_helm_chart_element(artifacts, patches, current_file, filename, fileformat, jsonPath, elemTuple):
elem, keyElem, parentTuple = elemTuple
if type(elem) is list:
index = 0
for item in elem:
indexPath = '[{}]'.format(index)
current_file = scan_helm_chart_element(artifacts, patches, current_file, filename, fileformat, indexPath if jsonPath is None else jsonPath + indexPath, (item, index, elemTuple))
index += 1
elif type(elem) is dict or isinstance(elem, yamlordereddictloader.OrderedDict):
pattern_image_id = re.compile('([^/]+/)?(.*)')
# Because faster and simpler and enouth for now: only global yaml vars are considered, no recursion into child elements
for key, value in elem.items():
if (key == 'imageName' or key == 'image') and type(value) is str:
# Case of a yaml var imageName
#name = elem['name'] if 'name' in elem else jsonPath
image_id_matching = pattern_image_id.match(value)
if image_id_matching is not None:
# the value is an image provided by an Internet docker image name, so we create a patch changing the registry prefix of this value
# to use a local registry where the image will be pushed in
imageRef = value
imageName = image_id_matching.group(2)
imageTag = elem['imageTag'] if 'imageTag' in elem else None
imageNameTag = imageName if imageTag is None else imageName + ':' + imageTag
current_file = add_patch(patches, current_file, filename, fileformat, json_path = key if jsonPath is None else jsonPath + '.' + key,
new_value = '{{{{ local_registry }}}}/{}'.format(imageName),
old_value = value,
name = imageName)
# The image downloaded from the Internet mut be pushed to the local registry so it is added to the list of artifacts to dump
add_artifact(artifacts, type='image_repo', name=imageNameTag,
ref=imageRef, image=imageRef, tag=imageTag)
elif key == 'name' and type(value) is str and ('prefix' in elem or 'tag' in elem) and (keyElem == 'image' or (parentTuple[1] == 'blackboxes')):
# Case of a json var of type docker image
imageName = value
imagePrefix = elem['prefix'] if 'prefix' in elem else None
imageRef = imageName if imagePrefix is None else imagePrefix + '/' + imageName
imageTag = elem['tag'] if 'tag' in elem else None
imageNameTag = imageName if imageTag is None else imageName + ':' + imageTag
# the value is an image provided by an Internet docker image name, so we create a patch changing the registry prefix of this value
# to use a local registry where the image will be pushed in
current_file = add_patch(patches, current_file, filename, fileformat, json_path = jsonPath + '.prefix',
new_value = '{{ local_registry }}',
old_value = imagePrefix,
name = imageName)
# The image downloaded from the Internet mut be pushed to the local registry so it is added to the list of artifacts to dump
add_artifact(artifacts, type='image_repo', name=imageNameTag,
ref=imageRef, image=imageRef, tag=imageTag)
else:
current_file = scan_helm_chart_element(artifacts, patches, current_file, filename, fileformat, key if jsonPath is None else jsonPath + '.' + key, (value, key, elemTuple))
return current_file
# ==========================================================
# log functions
# ==========================================================
def log_error(message, args = None):
log(False, 'Error', message)
def log_alert(message, args = None):
log(False if args is None else args.quiet, 'Warning', message)
def log(is_quiet, level, message):
if not is_quiet:
print('{}:{}'.format(level, message))
# ==========================================================
# evaluate the x value as a python sentence using the context v
# ==========================================================
def eval_elem(x, v):
try:
if type(x) is str:
return eval(x)
else:
return x
except Exception as e:
log_error('"{}": {}'.format(x, e))
# ==========================================================
# map a function recursively to the something yaml doc
# ==========================================================
def recursive_map(something, func):
if isinstance(something, dict):
accumulator = {}
for key, value in something.items():
accumulator[key] = recursive_map(value, func)
return accumulator
elif isinstance(something, (list, tuple, set)):
accumulator = []
for item in something:
accumulator.append(recursive_map(item, func))
return type(something)(accumulator)
else:
return func(something)
# ==========================================================
# insert / update the scan_result yaml doc with the value using the parser as the path to to the value
# ==========================================================
def update_recursively(scan_result, parser, value):
# Not resolve means the parent (parser.left) must be extended by the parser.right
tp = type(parser)
if tp is jsonpath.Child:
tpr = type(parser.right)
recurs_value = None
if tpr is jsonpath.Fields:
recurs_value = dict()
elif tpr is jsonpath.Slice:
recurs_value = []
else:
raise Exception('Cannot manage a parser type {} in the recursive update'.format(tpr))
elem = update_recursively(scan_result, parser.left, recurs_value)
elif tp is jsonpath.Root:
return scan_result
# elem is extended by parser.right
if tpr is jsonpath.Fields:
if (len(parser.right.fields) != 1):
raise Exception('Several paths due to {}'.format(parser.right.fields))
if not type(elem) is dict:
raise Exception('Cannot create for the type {} the attribute {}'.format(type(elem), parser.right.fields[0]))
if not parser.right.fields[0] in elem:
elem[parser.right.fields[0]] = value
else:
elem[parser.right.fields[0]] = always_merger.merge(elem[parser.right.fields[0]], value)
return elem[parser.right.fields[0]]
elif tpr is jsonpath.Slice:
if parser.right.start is None and parser.right.end is None and parser.right.step is None:
elem.append(value)
return elem[-1]
raise Exception('Inconsistent algorithm')
# ==========================================================
# update the scan_result yaml doc using the set yaml descriptor and the context v
# ==========================================================
def update(scan_result, set, v):
parser = parse(set['path'])
update_recursively(scan_result, parser, recursive_map(set['value'], lambda x: eval_elem(x, v)))
# ==========================================================
# Create the specific scan resulting of a OpenWhisk Helm Chart root folder scan
# Returns the artifacts structured result of the scan
# ==========================================================
def scan_file(file_system, fs_path, data, actions, args, scan_result):
# Scan JSON well formed files
for action in actions:
if 'get' in action:
results = [match.value for match in parse(action['get']).find(data)]
else:
results = [data]
for item_data in results:
v = Box(item_data)
if 'perform' in action and not any([isinstance(item_data, list), isinstance(item_data, tuple)]):
perform_list = [action['perform']] if type(action['perform']) is dict else action['perform']
for perform in perform_list:
performed = v['performed'] = []
perform_result = None
try:
if 'finditer' in perform:
match_re = re.compile(perform['finditer'], re.MULTILINE)
matching_data = recursive_map(perform['value'], lambda x: eval_elem(x, v))
perform_result = []
for r in re.finditer(match_re, matching_data): perform_result.append(r)
elif 'match' in perform:
match_re = re.compile(perform['match'], re.MULTILINE)
matching_data = recursive_map(perform['value'], lambda x: eval_elem(x, v))
perform_result = re.match(match_re, matching_data)
else:
log_error('{} is an invalid perform item'.format(perform), args)
performed.append(perform_result)
if 'name' in perform: v[perform['name']] = perform_result
except Exception as e:
log_error('"{}" {}'.format(perform, e), args)
# do the set on each get item
if 'set' in action:
# get the hasattr condition
attr_list = []
if 'hasattr' in action:
attr_list = action['hasattr'] if type(action['hasattr']) is list else [action['hasattr']]
# get the if condition
if_condition = 'True'
if 'if' in action: if_condition = action['if']
try:
for attr in attr_list:
if attr[0] == '!':
if hasattr(v, attr[1:]):
if_condition = 'False'
break
else:
if not hasattr(v, attr):
if_condition = 'False'
break
except Exception as e:
v = item_data
try:
if eval(if_condition):
try:
update(scan_result, action['set'], v)
except Exception as e:
log_error('"{}" {}'.format(action['set'], e), args)
except Exception as e:
log_alert('"{}" {}'.format(if_condition, e), args)
# ==========================================================
# Create the scan resulting of a directory scan
# Returns the artifacts structured result of the scan
# ==========================================================
def scan_resource(args):
# read configurations
configs = list()
with open(args.CONFIG, "r", encoding='utf8') as config_yaml_file:
config_docs = yaml.load_all(config_yaml_file)
for config in config_docs:
configs.append(config)
# take into account context option
if type(args.context) is str:
try:
# A context for immediate substitution during the apply is provided. We tranform it in JSON/YAML
args.context = json.loads(args.context)
except ValueError:
args.context = eval(args.context)
## Take into account rollback option
if args.rollback: rollback_resource(args)
target_dir = args.TARGET_PATH
#(deprecated) origin_folder = os.getcwd()
target_dir = os.path.abspath(target_dir)
# we work with relative paths, then we go to this folder
# (deprecated) os.chdir(target_dir)
scan_result = dict()
res = scan_result['resource'] = dict()
res['path'] = target_dir
# check the type of resource
# if os.path.isdir('./roles/kubespray-defaults'):
# artifacts = scan_kubespray_playbook(args)
# elif os.path.isfile('./Chart.yml') or os.path.isfile('./Chart.yaml'):
# artifacts = scan_helm_chart(args)
# else:
# print("Error: '{}' seems to be not a kubespray playbook or a helm chart folder".format(target_dir))
# exit(1)
supported_file_contents = ['yaml', 'json', 'text']
for config in configs:
for content_type in supported_file_contents:
for typed_file_patterns in parse('$.{}.[*]'.format(content_type)).find(config):
print(typed_file_patterns.value)
inclusions = [match.value for match in parse('[*].include[*]').find(typed_file_patterns.value)]
exclusions = [match.value for match in parse('[*].exclude[*]').find(typed_file_patterns.value)]
with fs.open_fs(target_dir) as file_system:
for fs_path in file_system.walk.files(filter=None):
is_included = True
if len(inclusions) > 0:
is_included = False
for inclusion in inclusions:
if fs.glob.match(inclusion, fs_path):
is_included = True
break
for exclusion in exclusions:
if fs.glob.match(exclusion, fs_path):
is_included = False
break
if not is_included: continue
# The fs_path must be analysed, we get this content
try:
with file_system.open(fs_path, "r", encoding='utf8') as file_to_scan:
if content_type == 'yaml':
data = yaml.load(file_to_scan, Loader=yamlordereddictloader.Loader)
elif content_type == 'json':
data = json.load(file_to_scan)
elif content_type == 'text':
data = file_to_scan.load()
else:
log_alert('{} is a unknown file content type and then ignored. Only {} are supported.'.format(content_type, supported_file_contents), args)
# The file content data is scanned
if 'actions' in typed_file_patterns.value:
scan_file(file_system, fs_path, data, typed_file_patterns.value['actions'], args, scan_result)
else:
log_alert('{} is a unknown file content type and then ignored. Only {} are supported.'.format(content_type, supported_file_contents), args)
except yaml.parser.ParserError as ex:
log_alert('YAML error {} in {}. The file is ignored.'.format(ex, fs_path), args)
except yaml.scanner.ScannerError as ex:
log_alert('YAML error {} in {}. The file is ignored.'.format(ex, fs_path), args)
# restore the current working folder
#(deprecated) os.chdir(origin_folder)
# returns the scan result
return scan_result
# ==========================================================
# Get the output stream from args
# ==========================================================
def get_output_stream(args):
return sys.stdout if args.output is None else open(args.output, 'w', encoding='utf8')
# ==========================================================
# Get the input stream from args
# ==========================================================
def get_input_stream(args):
return sys.stdin if args.input is None else open(args.input, 'r', encoding='utf8')
# ==========================================================
# Dump the json structured content to the given stream in a YAML format
# ==========================================================
def dump_as_yaml(content, stream, args):
yaml.safe_dump(content, stream, default_flow_style=False)
# (deprecated because introduce 'item': !!python/unicode "some string"
# see https://stackoverflow.com/questions/20352794/pyyaml-is-producing-undesired-python-unicode-output/20369984
# yaml.dump(yaml_doc['patches'], sys.stdout, encoding='utf-8', allow_unicode=True,
# Dumper=yamlordereddictloader.Dumper)
# ==========================================================
# Dump the json structured content to the given stream in a CSV format
# The columns are defined by args.type
# ==========================================================
def dump_as_csv(content, stream, args, fieldnames_by_type={'download_url': ['name', 'url', 'filename'],
'image_repo': ['name', 'ref', 'tag', 'image'],
'git_repo': ['name', 'url', 'folder'],
'patch': ['file', 'json_path', 'name', 'new_value', 'old_value']}):
# Convert a patch list to be serializable in CSV
if args.type == 'patch':
content_csv = list()
for patched_file in content:
for patch in patched_file['changes']:
patch['file'] = patched_file['file']
content_csv.append(patch)
content = content_csv
listWriter = csv.DictWriter(
stream,
fieldnames=fieldnames_by_type[args.type] if args.type in fieldnames_by_type else content[0].keys(
),
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_NONNUMERIC
)
listWriter.writerows(content)
# ==========================================================
# Dump the json structured content to the given stream in a format specified by args.format
# ==========================================================
def dump(content, stream, args):
globals()['dump_as_' + args.format](content, stream, args)
# ==========================================================
# Transform a jsonpath into a list of items like this:
# aaa.bbb[0][5].ccc ==> ('aaa', 'bbb', 0, 5, 'ccc')
# The resulting list facilitates the jsonpath processing
# ==========================================================
def jsonpath_to_list(str_path):
doted_list = str_path.split('.')
result = list()
for path_elem in doted_list:
elem_array = jsonpath_to_list.pathElem.match(path_elem)
if elem_array is None:
raise ValueError('{} is not a valid JSON/YAML path'.format(str_path))
else:
if not elem_array.group(1) is None: result.append(elem_array.group(1))
if not elem_array.group(2) is None: result.append(int(elem_array.group(2)))
return result
jsonpath_to_list.pathElem = re.compile(r'([^\[]*)(?:\[([0-9]+)\])?')
# ==========================================================
# Function returning a tuple which matches the json_path in thr root strctured object
# Returns a tuple (parent, key to the leaf , leaf)
# ==========================================================
def get_from_json_path(root, json_path):
if type(json_path) is str:
json_path = jsonpath_to_list(json_path)
key = json_path[0]
if (isinstance(key, int) and isinstance(root, list) and key < len(root)) or (key in root):
return (root, key, root[key]) if len(json_path) == 1 else get_from_json_path(root[key], json_path[1:])
return (None, None, None)
# ==========================================================
# Apply change to a data as a structured content (json or YAML)
# The change is as it is contained in a scan result
# Returns True if a change on the data has been done
# ==========================================================
def apply_change(data, change, args, filename):
has_changed = False
# Make imediately the template jinja2 exec using a context if it is provided, only on new values
new_value = change['new_value'] if args.context is None else resolve(change['new_value'], args.context)
old_value = change['old_value']
if 'json_path' in change:
# Case of a JSON / YAML change
if type(data) is str:
raise RuntimeError('The file cannot be read in YAML while a YAML modification must be applied to it')
key = json_path = change['json_path']
path_end, key, replaced_value = get_from_json_path(data, json_path)
if not replaced_value is None:
if replaced_value != old_value and replaced_value != new_value:
raise RuntimeError("'{}:{}' = '{}' but must be equal to '{}' to be changed to '{}'".format(
filename, json_path, replaced_value, old_value, new_value))
if replaced_value == new_value:
print("{}: '{}' = '{}' not found because probably the change has been done by a previous change".format(
filename, json_path, replaced_value))
else:
path_end[key] = new_value
has_changed = True
if args.dry_run:
print("Dry-run: file {}, '{}' at {} is replaced by '{}'".format(filename, old_value, json_path, new_value))
else:
raise RuntimeError('{} not found', json_path)
else:
# Case of a textual search and replace
count = 0
while data.find(old_value) != -1:
data = data.replace(old_value, new_value, 1)
count += 1
has_changed = True
if args.dry_run and count > 0:
print("Dry-run: file {}, {} '{}' has been replaced by {}".format(filename, str(count), old_value, new_value))
if count == 0:
print("{}: '{}' not found because probably the change has been done by a previous change".format(
filename, old_value))
return data, has_changed
# ==========================================================
# Apply changes to a given file of a given format.
# Returns True if the file has been changed
# ==========================================================
def apply_changes_to_file(filename, fileformat, changes, args):
is_file_changed = False
is_content_changed = False
doc_data = None
with open(filename, "r", encoding='utf8') as file_to_change:
try:
# PyYAML/yaml is able to read json too
doc_data = yaml.load(file_to_change, Loader=yamlordereddictloader.Loader)
except:
# If the file cannot be read as structured format, we work with text related changes
file_to_change.seek(0)
doc_data = file_to_change.read()
for change in changes:
try:
doc_data, has_changed = apply_change(doc_data, change, args, filename)
if has_changed: is_content_changed = True
except RuntimeError as err:
print('Error in file {}: {}'.format(filename, str(err)))
if not args.dry_run:
# We stop immediately
raise err
if is_content_changed:
if args.rollbackable:
# The file has been changed, whe make a copy if not already done and then the file is updated
filename_orig = filename + '.orig'
if args.dry_run:
print(
"Dry-run: {} has been copied to {}".format(filename, filename_orig))
else:
if not os.path.exists(filename_orig):
copyfile(filename, filename_orig)
else:
if args.dry_run:
print("Dry-run: {} already exists".format(filename_orig))
if not args.dry_run:
# Update the file
with open(filename, 'w', encoding='utf8') as updated_file:
if type(doc_data) is str and fileformat == 'text':
updated_file.write(doc_data)
else:
if fileformat == 'yaml':
yaml.dump(doc_data, updated_file, encoding='utf-8', default_flow_style=False,
Dumper=yamlordereddictloader.Dumper)
elif fileformat == 'json':
json.dump(doc_data, updated_file, sort_keys = False, indent = 4, ensure_ascii = False)
else:
raise RuntimeError('{} is not a supported file format. The file {} has not been changed'.format(fileformat, filename))
is_file_changed = True
return is_file_changed
# ==========================================================
# Apply a patch as it is structured in a scan result
# args give options and the target folder where to apply changes
# ==========================================================
def apply_patch(patch, args):
if args.rollback: rollback_resource(args)
if type(args.context) is str:
try:
# A context for immediate substitution during the apply is provided. We tranform it in JSON/YAML
args.context = json.loads(args.context)
except ValueError:
args.context = eval(args.context)
target_dir = args.TARGET_PATH
origin_folder = os.getcwd()
target_dir = os.path.abspath(target_dir)
# we work with relative paths to the kubespray root, then we go to this root folder
os.chdir(target_dir)
# iterate changes file by file
for file_changes in patch:
filename = file_changes['file']
fileformat = file_changes['format']
if apply_changes_to_file(filename, fileformat, file_changes['changes'], args):
if args.dry_run:
print("Dry-run: {} has been patched".format(filename))
else:
print("{} has been patched".format(filename))
# restore the current folder
os.chdir(origin_folder)
# ==========================================================
# scan command execution: build a YAML file containing all changes and Internet dependencies required by
# a kubespray playbook or an Helm Chart to be usd in a offline environment
# ==========================================================
def do_scan(args):
args.format = 'yaml'
yaml_doc = scan_resource(args)
dump(yaml_doc, get_output_stream(args), args)
# ==========================================================
# dump command execution: use as input the YAML file generated by scan.
# Produce the output for a given type of object in the CSV format by default
# ==========================================================
def do_dump(args):
yaml_doc = yaml.load(get_input_stream(
args), Loader=yamlordereddictloader.Loader)
if type(yaml_doc) is dict or isinstance(yaml_doc, yamlordereddictloader.OrderedDict):
# the yaml_doc seems to be a YAML document, we use it to execute a dump
dump(yaml_doc[args.type] if args.type in yaml_doc else list(), get_output_stream(args), args)
else:
print("Error: the input stream is not a valid YAML for the dump command.")
exit(1)
# ==========================================================
# apply command execution: use as input the YAML file generated by scan.
# Do changes (or simulate it if --dry-run) in a given folder tree of a
# Kubespray Ansible Playbook or a OpenWhisk Helm Chart
# ==========================================================
def do_apply(args):
not_yet_implemented()
if args.dry_run and args.rollback:
print("Error: the dry-run and rollback options cannot be used together.")
exit(1)
yaml_doc = yaml.load(get_input_stream(
args), Loader=yamlordereddictloader.Loader)
if type(yaml_doc) is dict or isinstance(yaml_doc, yamlordereddictloader.OrderedDict):
apply_patch(yaml_doc['patch'], args)
else:
print("Error: the input stream is not a valid YAML for the dump command.")
exit(1)
# ==========================================================
# roolback command execution
# ==========================================================
def do_rollback(args):
rollback_resource(args)
# ==========================================================
# list-vars command execution
# ==========================================================
def do_list_vars(args):
vars_in_new_values = set()
pattern_jinja_var = re.compile(r'\{\{[\s\r\n]*(?P<var_name>[A-Za-z_][\-A-Za-z_0-9]*)[\s\r\n]*\}\}')
yaml_doc = yaml.load(get_input_stream(
args), Loader=yamlordereddictloader.Loader)
if type(yaml_doc) is dict or isinstance(yaml_doc, yamlordereddictloader.OrderedDict):
for file_change in yaml_doc['patch']:
for change in file_change['changes']:
for var in re.findall(pattern_jinja_var, change['new_value']):
vars_in_new_values.add(var)
else:
print("Error: the input stream is not a valid YAML for the dump command.")
exit(1)
print(vars_in_new_values)
# ==========================================================
# Get the args parser related to given args
# ==========================================================
def parse_args(args):
# ==========================================================
# CLI syntax configuration and documentation defined and processed by the argparse python standard lib
# ==========================================================
parser = argparse.ArgumentParser(
description='CLI tool helper to adapt software configuration by scanning and changing files in a directory', formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--version', action='version', version='1.0.0')
parser.add_argument('CONFIG', help='configuration file')
subparsers = parser.add_subparsers()
scan_parser = subparsers.add_parser(
'scan', help='make a scan (read only) and produce a YAML result which lists identified elements and patches to apply')
scan_parser.set_defaults(func=do_scan)
rollback_parser = subparsers.add_parser(
'rollback', help='do a rollback using a rollback file generated by a patch command')
rollback_parser.set_defaults(func=do_rollback)
dump_parser = subparsers.add_parser(
'dump', help='dump the input generated by the scan to produce a given type of object in the CSV format by default', formatter_class=argparse.RawTextHelpFormatter)
dump_parser.set_defaults(func=do_dump)
apply_parser = subparsers.add_parser(
'apply', help='apply changes identified by a scan and produce a rollback file if not already exists')
apply_parser.set_defaults(func=do_apply)
list_vars_parser = subparsers.add_parser(
'list-vars', help='list variables you can subsitute on applied changes using the command apply and the option --context')
list_vars_parser.set_defaults(func=do_list_vars)
list_vars_parser.add_argument(
'-i', '--input', help='file path of the source file as the YAML result of the scan command')
rollback_parser.add_argument('TARGET_PATH',
help='Kubespray playbook or helm chart folder location where to apply patches', default='.')
scan_parser.add_argument('--rollback', action='store_true',
help='do a global rollback before')
scan_parser.add_argument('--quiet', action='store_true',
help='do not display warnings and info messages')
scan_parser.add_argument(
'-o', '--output', help='file path of the destination file for the YAML result')
scan_parser.add_argument('TARGET_PATH',
help='Kubespray playbook or helm chart folder location', default='.')
scan_parser.add_argument(
'--context', help="""context as a json string to resolve scanned values on the fly (example: --context '{"a":"v1","b":3}')""")
dump_parser.add_argument(
'-t', '--type', nargs='?', default='patch', choices=['patch', 'download_url', 'image_repo', 'git_repo'], help='type of entry to dump')
dump_parser.add_argument(
'-f', '--format', nargs='?', default='csv', choices=['yaml', 'csv'], help='''output format of the dumped data.
For the CSV format, columns order depends of the type:
download_url: name, url, filename
image_repo: name, ref, tag, image
git_repo: name, url, folder
patch: file, json_path, name, new_value, old_value''')
dump_parser.add_argument(
'-i', '--input', help='file path of the source file as the YAML result of the scan command')
dump_parser.add_argument(
'-o', '--output', help='file path of the destination file for the YAML result')
apply_parser.add_argument(
'-i', '--input', help='file path of the patch file as the YAML result of the scan command')
apply_parser.add_argument(
'--rollbackable', action='store_true', help='files are copied to a same_filename.orig before any change. This copy is used by the --rollback operation')
apply_parser.add_argument(
'--context', help="""context as a json string to resolve patched values on the fly (example: --context '{"a":"v1","b":3}')""")
apply_parser.add_argument('--dry-run', action='store_true',
help='do all things whithout changing the playbook or helm chart. All changes are displayed on the standard output')
apply_parser.add_argument('--rollback', action='store_true',
help='do a global rollback before')
apply_parser.add_argument('TARGET_PATH',
help='Kubespray playbook or helm chart folder location where to apply patches', default='.')
return parser.parse_args(args)
# ==========================================================
# ========================== main ==========================
# ==========================================================
if __name__ == '__main__':
# ==========================================================
# Unit testing section, Sorry to not be capable to use advanced unit testing tools, but I'am a kind of beginner in the Python world
# ==========================================================
# For local test, uncomment the session you want to test:
"""
# Full Kubespray test session: --> rollback --> scan --> apply
sys_argv = sys.argv.copy()
sys.argv.extend(['rollback', r'c:\projects\src\kubespray'])
args = parser.parse_args()
args.func(args)
sys.argv = sys_argv.copy()
sys.argv.extend(['scan', '-o', r'c:\projects\src\scan.yml', r'c:\projects\src\kubespray'])
args = parser.parse_args()
args.func(args)
sys.argv = sys_argv.copy()
#sys.argv.extend(['apply', '--context', '{"local_registry":"W.X.Y.Z:5000","local_hfs":"http://W.X.Y.Z:80"}', '--input', r'c:\projects\src\scan.yml',
# r'c:\projects\src\kubespray'])
sys.argv.extend(['apply', '--input', r'c:\projects\src\scan.yml', r'c:\projects\src\kubespray'])
"""
# Helm Chart
sys.argv.extend(['openwhisk.adapt.yaml', 'scan', '--quiet', '-o', r'c:\projects\src\openwhisk.scan.yml', r'c:\projects\src\incubator-openwhisk-deploy-kube-master.old/helm/openwhisk'])
#sys.argv.extend(['dump', '--format', 'csv', '--type', 'image_repo', '--input', 'c:/projects/src/chart-scan.yml'])
#sys.argv.extend(['dump', '--format', 'csv', '--type', 'git_repo', '--input', 'c:/projects/src/chart-scan.yml'])
#sys.argv.extend(['apply', '--context', "{'local_registry':'W.X.Y.Z:5000'}", '--input', 'c:/projects/src/chart-scan.yml',
# '--dry-run', r'c:\projects\src\incubator-openwhisk-deploy-kube-master.old\helm\openwhisk'])
"""
# Full Helm test session: --> rollback --> scan --> apply
sys_argv = sys.argv.copy()
sys.argv.extend(['rollback', r'C:\projects\src\incubator-openwhisk-deploy-kube-master.old\helm\openwhisk'])
args = parser.parse_args()
args.func(args)
sys.argv = sys_argv.copy()
sys.argv.extend(['scan', '-o', r'c:\projects\src\chart-scan.yml', r'c:\projects\src\incubator-openwhisk-deploy-kube-master.old/helm/openwhisk'])
args = parser.parse_args()
args.func(args)
sys.argv = sys_argv.copy()
sys.argv.extend(['apply', '--context', '{"local_registry":"W.X.Y.Z:5000","local_hfs":"http://W.X.Y.Z:80"}', '--input', 'c:/projects/src/chart-scan.yml',
r'c:\projects\src\incubator-openwhisk-deploy-kube-master.old\helm\openwhisk'])
"""
#sys.argv.extend(['rollback', '--help'])
#sys.argv.extend(['list-vars', '--input', 'c:/projects/src/chart-scan.yml'])
#sys.argv.extend(['dump', '--help'])
# ==========================================================
# Parse args and execute the command with options if the syntax is OK
# ==========================================================
parser = parse_args(sys.argv[1:])
parser.func(parser)
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] |
tvm_benchmark/test_resnet_inference.py | adwwsd/HAWQ | 0 | 28573 | <gh_stars>0
import torch
import tvm
from tvm import autotvm
from tvm import relay
from tvm.contrib import download
from tvm.contrib.debugger import debug_runtime
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
import argparse
import os
from os.path import join, isfile
import sys
import json, requests
from io import BytesIO
import re
import mixed_precision_models.quantized_resnet_v1 as quantized_resnet_v1
from mixed_precision_models.layers import QConfig, QuantizeContext
import hawq_utils_resnet
import torch.cuda.profiler as profiler
import pyprof
pyprof.init()
import logging
logging.basicConfig(level=logging.CRITICAL)
parser = argparse.ArgumentParser(description='Resnet accuracy test',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--model-dir', required=True,
help='Model data directory')
parser.add_argument('--debug-unit', default=None,
help='Debug specific unit input, compare the unit input to the pytorch result (stage1_unit1, stage1_unit2 ...)')
parser.add_argument('--rounding', default='TONEAREST',
help='Round scheme (TONEAREST, TRUNCATE)')
parser.add_argument('--num-classes', type=int, default=1000,
help='Total number of classes')
parser.add_argument('--arch', default='resnet50',
help='resnet architecture')
args = parser.parse_args()
###############################################################################
# Set target device
# -----------------
TARGET_NAME = 'cuda'
CTX = tvm.context(TARGET_NAME, 0)
#CTX = tvm.gpu(0)
###############################################################################
# Load params
# -----------------
if args.arch == 'resnet50':
isRes18 = False
if args.num_classes == 10: # Cifar 10
num_stages = 3
units = [3, 4, 6]
print("Use Cifar 10")
else:
num_stages = 4
units = [3, 4, 6, 3]
elif args.arch == 'resnet18':
isRes18 = True
num_stages = 4
units = [2, 2, 2, 2]
else:
assert 0
weights = np.load(os.path.join(args.model_dir, "weights.npy"), allow_pickle=True)[()]
bias = np.load(os.path.join(args.model_dir, "bias.npy"), allow_pickle=True)[()]
hawq_utils_resnet.load_qconfig("uint4", "int4", num_stages, units, file_name=os.path.join(args.model_dir, "quantized_checkpoint.pth.tar"), isRes18=isRes18)
#hawq_utils_resnet50.load_qconfig("int8", "int8", num_stages, units, file_name=os.path.join(args.model_dir, "quantized_checkpoint.pth.tar"))
input_image = np.load(os.path.join(args.model_dir, "input_image_batch_1.npy"))
input_image = input_image / QuantizeContext.qconfig_dict["conv0_qconfig"].input_scale
input_image = np.clip(input_image, -128, 127)
if args.rounding == "TONEAREST":
input_image = np.round(input_image)
elif args.rounding == "TRUNCATE":
input_image = np.trunc(input_image)
input_image = input_image.astype("int8")
params = {**weights, **bias}
###############################################################################
# Load model
# -----------------
batch_size = 8
shape = list(input_image.shape)
image_shape = (shape[3], shape[1], shape[2])
input_dtype = 'int8'
model_type = "int4"
num_layers = 18 if isRes18 else 50
data_layout = "NHWC"
kernel_layout = "HWOI"
func, _ = quantized_resnet_v1.get_workload(batch_size=batch_size,
image_shape=image_shape,
num_classes=args.num_classes,
num_layers=num_layers,
dtype=input_dtype,
data_layout=data_layout,
kernel_layout=kernel_layout,
with_bn=False,
debug_unit=args.debug_unit,
rounding=args.rounding)
# Download ImageNet categories
categ_url = "https://github.com/uwsaml/web-data/raw/main/vta/models/"
categ_fn = "synset.txt"
download.download(join(categ_url, categ_fn), categ_fn)
synset = eval(open(categ_fn).read())
image = input_image
input_data = np.repeat(image, batch_size, axis=0)
###############################################################################
# Run the model
# -----------------
log_filename = "/home/zach_zheng/hawq_tvm/mixed_precision_models/tuning_logs/resnet%d_%s_%s_batch_%d.log" % (num_layers, data_layout, model_type, batch_size)
if not os.path.exists(log_filename):
log_filename = None
else:
print("Apply tuning log " + log_filename)
with autotvm.apply_history_best(log_filename):
with relay.build_config(opt_level=3):
print("building relay")
graph, lib, params = relay.build(func, target=TARGET_NAME, params=params)
if args.debug_unit is not None:
m = tvm.contrib.graph_runtime.create(graph, lib, CTX)
#m = tvm.contrib.graph_executor.create(graph, lib, CTX)
# Set the network parameters and inputs
m.set_input(**params)
m.set_input('data', input_data)
m.run()
np.set_printoptions(threshold=sys.maxsize)
out = m.get_output(0).asnumpy()
if not os.path.exists(os.path.join(args.model_dir, "tvm_result")):
os.mkdir(os.path.join(args.model_dir, "tvm_result"))
unit_str_regex = re.search('stage(\d)_unit(\d)', args.debug_unit)
if unit_str_regex is not None:
unit_str = unit_str_regex.group(0)
else:
unit_str = ""
if args.debug_unit == "fc_input":
actual_result = out
np.save(os.path.join(args.model_dir, "tvm_result/fc_input_int8.npy"), actual_result[0])
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/fc_input_int8.npy")).astype("int8")
elif args.debug_unit == "fc_output":
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/fc_output_int32.npy"))
actual_result = out
np.save(os.path.join(args.model_dir, "tvm_result/fc_output_int32.npy"), actual_result[0])
# golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/fc_output_float32.npy"))#.astype("int32")
elif args.debug_unit == "avg_pool":
actual_result = out
np.save(os.path.join(args.model_dir, "tvm_result/avg_pool_int32.npy"), actual_result[0])
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/avg_pool_int32.npy")).astype("int32")
elif args.debug_unit == "softmax":
actual_result = out
np.save(os.path.join(args.model_dir, "tvm_result/avg_pool_int32.npy"), actual_result[0])
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/avg_pool_int32.npy")).astype("int32")
elif args.debug_unit == unit_str + "_output":
actual_result = out * QuantizeContext.qconfig_dict["%s_qconfig_add" % unit_str].output_scale
# actual_result = out
np.save(os.path.join(args.model_dir, "tvm_result/%s_output_int32.npy" % unit_str), actual_result[0])
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/%s_output_float32.npy" % unit_str))
elif args.debug_unit == unit_str + "_input":
actual_result = hawq_utils_resnet.unpack_int4_to_int32(out)
np.save(os.path.join(args.model_dir, "tvm_result/%s_input_int4.npy" % unit_str), actual_result[0])
golden_result = np.load(os.path.join(args.model_dir, "pytorch_result/%s_input_int4.npy" % unit_str)).astype("int32")
else:
print("Error: Unsupported debug unit.")
print("Above is Pytorch result, under is TVM result")
tvm.testing.assert_allclose(golden_result, actual_result[0])
print(args.debug_unit + " is 100% matched !")
else:
module = tvm.contrib.graph_runtime.create(graph, lib, ctx=CTX)
#module = tvm.contrib.graph_executor.create(graph, lib, ctx=CTX)
module.set_input(**params)
module.set_input('data', input_data)
module.run()
tvm_output = module.get_output(0)
print(tvm_output.shape)
for b in range(batch_size):
top_categories = np.argsort(tvm_output.asnumpy()[b])
# Report top-5 classification results
print("\n prediction for sample {}".format(b))
print("\t#1:", synset[top_categories[-1]])
print("\t#2:", synset[top_categories[-2]])
print("\t#3:", synset[top_categories[-3]])
print("\t#4:", synset[top_categories[-4]])
print("\t#5:", synset[top_categories[-5]])
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] |
atv/tests/factories.py | City-of-Helsinki/atv | 0 | 166978 | import factory
from django.contrib.auth.models import Group
class GroupFactory(factory.django.DjangoModelFactory):
name = factory.Sequence(lambda n: "group-%d" % n)
class Meta:
model = Group
django_get_or_create = ("name",)
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scripts/pickrunner/visibility_widget.py | ColinKennedy/pickrunner | 1 | 76406 | <reponame>ColinKennedy/pickrunner
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''A set of small widgets that are meant to show/hide themselves.'''
# IMPORT THIRD-PARTY LIBRARIES
from Qt import QtWidgets
from Qt import QtCore
class ExpandCollapseWidget(QtWidgets.QWidget):
'''A "show/hide" widget which opens and closes itself.
It works by creating an inner widget which is hidden by default which you
can expand/collapse using "toggle" or "set_children_visible". To add your
widgets to the section that shows/hides itself, use "add_layout" or
"add_widget".
'''
toggled = QtCore.Signal()
def __init__(
self,
label='',
side='left',
layout=QtWidgets.QVBoxLayout,
parent=None):
'''Create the GUI's widgets.
Args:
label (:obj:`str`, optional):
A word or phrase to put next to the button.
Suggestion: "Advanced Settings". Default: "".
side (:obj:`str`, optional):
Which direction of the widget to display the show/hide button.
Options: ('left', 'right'). Default: 'left'.
layout (:obj:`<callable=QtWidgets.QBoxLayout>`, optional):
The layout for all the widgets that will be shown/hidden.
Default: 'QtWidgets.QVBoxLayout'.
parent (:obj:`<QtCore.QObject>`, optional):
The Qt-based associated object. Default is None.
'''
super(ExpandCollapseWidget, self).__init__(parent=parent)
self.setLayout(layout())
options = ('left', 'right')
if side.lower() not in options:
raise ValueError('Got side: "{side}" but expected an option, '
'"{opt}"'.format(side=side, opt=options))
self.button = QtWidgets.QToolButton(parent=self)
self.label = QtWidgets.QLabel(label, parent=self)
self.expand_widget = QtWidgets.QWidget(parent=self)
self.expand_widget.setLayout(self.layout().__class__())
top_layout = QtWidgets.QHBoxLayout()
if side.lower() == 'left':
top_layout.addWidget(self.button)
top_layout.addWidget(self.label)
elif side.lower() == 'right':
top_layout.addWidget(self.label)
top_layout.addWidget(self.button)
self.layout().addLayout(top_layout)
self.layout().addWidget(self.expand_widget)
self.init_default_settings()
self.init_interactive_settings()
def init_default_settings(self):
'''Set-up our expand/collapse button's appearance.'''
# Hide children by default
self.set_children_visible(False)
self.button.setArrowType(QtCore.Qt.RightArrow)
self.button.setToolTip('Click to expand or collapse the section below')
self.label.setToolTip('Click the expand button to show/hide widgets')
self.button.setObjectName('expand_button')
self.label.setObjectName('expand_label')
self.expand_widget.setObjectName('expand_hide_widget')
self.update_toggle_button(self.expand_widget.isVisible())
def init_interactive_settings(self):
'''Set our widget's toggle button to emit a signal when it is clicked.'''
self.button.clicked.connect(self.toggled.emit)
self.toggled.connect(self.toggle)
def add_layout(self, layout, *args, **kwargs):
'''Add Qt layout to the shown/hidden widgets.'''
self.expand_widget.layout().addLayout(layout)
def add_widget(self, widget, *args, **kwargs):
'''Add Qt widget to the shown/hidden widgets.'''
self.expand_widget.layout().addWidget(widget, *args, **kwargs)
def set_children_visible(self, visible):
'''Show/Hide the widgets contained in this object.
This method will also update all GUI-appearance related code, like
changing the button icon.
Args:
visible (bool): Show the widgets if True. Hide them if False.
'''
self.expand_widget.setVisible(visible)
self.update_toggle_button(visible)
def update_toggle_button(self, is_visible):
'''Set the show/hide section to the given value.'''
if is_visible:
self.button.setArrowType(QtCore.Qt.DownArrow)
else:
self.button.setArrowType(QtCore.Qt.RightArrow)
def toggle(self):
'''If the inner-widget section is hidden, show it, and vice-versa.'''
self.set_children_visible(not self.expand_widget.isVisible())
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] |
tools/benchmark/do_not_run_create_benchmark_data.py | dangervon/ironic | 0 | 37718 | <gh_stars>0
#
# Licensed 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.
import sys
import time
from oslo_db.sqlalchemy import enginefacade
from sqlalchemy import sql
from ironic.common import service
from ironic.conf import CONF # noqa To Load Configuration
from ironic.objects import node
def _create_test_nodes():
print("Starting creation of fake nodes.")
start = time.time()
node_count = 10000
checkin = time.time()
for i in range(0, node_count):
new_node = node.Node({
'power_state': 'power off',
'driver': 'ipmi',
'driver_internal_info': {'test-meow': i},
'name': 'BenchmarkTestNode-%s' % i,
'driver_info': {
'ipmi_username': 'admin',
'ipmi_password': '<PASSWORD>',
'ipmi_address': 'testhost%s.env.top.level.domain' % i},
'resource_class': 'CUSTOM_BAREMETAL',
'properties': {
'cpu': 4,
'memory': 32,
'cats': i,
'meowing': True}})
new_node.create()
delta = time.time() - checkin
if delta > 10:
checkin = time.time()
print('* At %s nodes, %0.02f seconds. Total elapsed: %s'
% (i, delta, time.time() - start))
created = time.time()
elapse = created - start
print('Created %s nodes in %s seconds.\n' % (node_count, elapse))
def _mix_up_nodes_data():
engine = enginefacade.writer.get_engine()
conn = engine.connect()
# A list of commands to mix up indexed field data a bit to emulate what
# a production database may somewhat look like.
commands = [
"UPDATE nodes set maintenance = True where RAND() < 0.1", # noqa Easier to read this way
"UPDATE nodes set driver = 'redfish' where RAND() < 0.5", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor01' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor02' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor03' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor04' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor05' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set reservation = 'fake_conductor06' where RAND() < 0.02", # noqa Easier to read this way
"UPDATE nodes set provision_state = 'active' where RAND() < 0.8", # noqa Easier to read this way
"UPDATE nodes set power_state = 'power on' where provision_state = 'active' and RAND() < 0.95", # noqa Easier to read this way
"UPDATE nodes set provision_state = 'available' where RAND() < 0.1", # noqa Easier to read this way
"UPDATE nodes set provision_state = 'manageable' where RAND() < 0.1", # noqa Easier to read this way
"UPDATE nodes set provision_state = 'clean wait' where RAND() < 0.05", # noqa Easier to read this way
"UPDATE nodes set provision_state = 'error' where RAND() < 0.05", # noqa Easier to read this way
"UPDATE nodes set owner = (select UUID()) where RAND() < 0.2", # noqa Easier to read this way
"UPDATE nodes set lessee = (select UUID()) where RAND() < 0.2", # noqa Easier to read this way
"UPDATE nodes set instance_uuid = (select UUID()) where RAND() < 0.95 and provision_state = 'active'", # noqa Easier to read this way
"UPDATE nodes set last_error = (select UUID()) where RAND() <0.05", # noqa Easier to read this way
]
start = time.time()
for command in commands:
print("Executing SQL command: \\" + command + ";\n")
conn.execute(sql.text(command))
print("* Completed command. %0.04f elapsed since start of commands."
% (time.time() - start))
def main():
service.prepare_command()
CONF.set_override('debug', False)
_create_test_nodes()
if __name__ == '__main__':
sys.exit(main())
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j24/learn.py | juhi24/j24py | 0 | 58409 | <filename>j24/learn.py<gh_stars>0
# coding: utf-8
from __future__ import absolute_import, division, print_function, unicode_literals
__metaclass__ = type
import pandas as pd
import matplotlib.pyplot as plt
def fit_predict(t, km):
km.fit(t.T)
classes = pd.Series(data=km.predict(t.T), index=t.columns)
return classes
def centroids(t, km):
"""cluster centroids as DataFrame"""
return pd.DataFrame(km.cluster_centers_.T, index=t.index)
def class_fraction(classes):
"""occurrence fraction of each cluster"""
counts = classes.groupby(classes).count()
return counts/classes.count()
def normalized_class_sizes(classes):
"""cluster sizes normalized around 1"""
return class_fraction(classes)*classes.unique().size
def pca_stats(pca):
with plt.style.context('fivethirtyeight'):
plt.figure();
plt.title('Explained variance ratio over component');
plt.plot(pca.explained_variance_ratio_);
plt.figure();
plt.title('Cumulative explained variance over component');
plt.plot(pca.explained_variance_ratio_.cumsum());
print('PCA captures {:.2f}% of the variance in the dataset.'.format(pca.explained_variance_ratio_.sum() * 100))
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ocellaris/__init__.py | TormodLandet/Ocellaris | 1 | 58956 | # Copyright (C) 2015-2019 <NAME>
# SPDX-License-Identifier: Apache-2.0
# Check for presence of FEniCS etc
from .verify_environment import verify_env
verify_env()
__version__ = '2019.0.2'
# This should potentially be made local to the mesh creation routines
import dolfin
dolfin.parameters['ghost_mode'] = 'shared_vertex'
del dolfin
def get_version():
"""
Return the version number of Ocellaris
"""
return __version__
def get_detailed_version():
"""
Return the version number of Ocellaris including
source control commit revision information
"""
import os
import subprocess
this_dir = os.path.dirname(os.path.abspath(__file__))
proj_dir = os.path.abspath(os.path.join(this_dir, '..'))
if os.path.isdir(os.path.join(proj_dir, '.git')):
cmd = ['git', 'describe', '--always']
version = subprocess.check_output(cmd, cwd=proj_dir)
local_version = '+git.' + version.decode('utf8').strip()
else:
local_version = ''
return get_version() + local_version
# Convenience imports for scripting
from .simulation import Simulation
from .run import setup_simulation, run_simulation
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main_app/app.py | johncoleman83/AirBnB | 2 | 1610911 | #!/usr/bin/python3
"""
Flask App that integrates with AirBnB static HTML Template
"""
from flask import Flask, render_template, request, url_for
import json
from models import storage
import requests
from uuid import uuid4
# flask setup
app = Flask(__name__)
app.url_map.strict_slashes = False
port = 8000
host = '0.0.0.0'
# begin flask page rendering
@app.teardown_appcontext
def teardown_db(exception):
"""
after each request, this method calls .close() (i.e. .remove()) on
the current SQLAlchemy Session
"""
storage.close()
@app.route('/', methods=['GET', 'POST'])
def main_index():
"""
handles request to main index, currently a login page
"""
cache_id = uuid4()
if request.method == 'GET':
return render_template('index.html', cache_id=cache_id, message=None)
if request.method == 'POST':
email = request.form.get('email', None)
password = request.form.get('password', None)
payload = {
'email': email,
'password': password
}
headers = {
'content-type': 'application/json'
}
action = request.form.get('action')
if action == 'login':
url = 'http://0.0.0.0:5001/auth/login'
elif action == 'signup':
url = 'http://0.0.0.0:5001/auth/register'
else:
auth_token = request.form.get('logout')
return logout(auth_token=auth_token)
r = requests.post(url, headers=headers,
data=json.dumps(payload))
r_data = r.json()
if r_data.get('error'):
return render_template('index.html',
cache_id=cache_id,
message=r_data.get('error'))
auth_token = r_data.get('auth_token')
if auth_token is None:
return render_template('index.html',
cache_id=cache_id,
message=r_data.get('error'))
if 'register' in url:
signup_message = 'thank you for signing up'
return render_template('index.html',
cache_id=cache_id,
message=signup_message)
state_objs = storage.all('State').values()
states = dict([state.name, state] for state in state_objs)
amens = list(storage.all('Amenity').values())
cache_id = uuid4()
return render_template('places.html', cache_id=cache_id, states=states,
amens=amens, auth_token=auth_token)
@app.route('/logout', methods=['GET', 'POST'])
def logout(auth_token=None):
"""
handles request to main index, currently a login page
"""
if request.method == 'GET':
cache_id =uuid4()
return render_template('404.html', cache_id=cache_id), 404
cache_id = uuid4()
if auth_token is None:
auth_token = request.form.get('logout')
headers = {
'content-type': 'application/json',
'Authorization': 'Bearer {}'.format(auth_token)
}
url = 'http://0.0.0.0:5001/auth/logout'
r = requests.post(url, headers=headers)
r_data = r.json()
if r_data.get('error'):
return render_template('index.html',
cache_id=cach_id,
message=r_data.get('error'))
message = 'You are now logged out.'
cache_id = uuid4()
return render_template('index.html',
cache_id=cache_id,
message=message)
@app.errorhandler(404)
def page_not_found(error):
"""
404 Error Handler
"""
cache_id = uuid4()
return render_template('404.html', cache_id=cache_id), 404
if __name__ == "__main__":
"""
MAIN Flask App
"""
app.run(host=host, port=port)
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me/storage/mongodb/collections/Collection.py | me-env/me. | 2 | 1608693 | from me.storage.mongodb.config import BULK_LIMIT, BULK_MIN
from me.storage.mongodb.config import mongo_to_python
from me.tools import fread_json
class Collection:
def __init__(self, db, name, logger, reset=False, schema_file=None):
self.db = db
self.name = name
self.bulk_buffer = []
self.schema = fread_json(schema_file)
self.col = self.getCollection()
self.log = logger
if reset is True and self.col is not None:
self.resetCollection()
elif self.col is None:
self.createCollection(self.schema)
def collectionExists(self):
return self.name in self.db.list_collection_names()
def getCollection(self):
if not self.collectionExists():
return None
return self.db[self.name]
def createCollection(self, val_expr=None):
self.db.create_collection(self.name)
if val_expr:
self.log.debug("val_expr", val_expr)
self.db.command('collMod', self.name, validator=val_expr, validationLevel='moderate')
self.col = self.getCollection()
self.log.info(f"Collection {self.name} created.")
def dropCollection(self):
self.col.drop()
self.log.info(f"Collection {self.name} dropped.")
def resetCollection(self):
"""
Drop the collection and recreate it
"""
self.dropCollection()
self.createCollection(self.schema)
self.log.info(f"Collection {self.name} reset.")
def deleteAll(self):
self.col.delete_many({})
def bulkWrite(self, content, force=False):
self.bulk_buffer.append(content)
if len(self.bulk_buffer) >= BULK_LIMIT or force:
self.flushBulk()
def flushBulk(self):
if len(self.bulk_buffer) >= BULK_MIN:
self.log.debug('Write Flush', self.name, "len", len(self.bulk_buffer))
results = self.col.bulk_write(self.bulk_buffer)
self.bulk_buffer = []
self.log.debug("bulk write result", results.bulk_api_result)
def flush(self):
self.flushBulk()
def update(self, query, update):
self.col.update_many(query, update)
def insert(self, document):
self.log.debug('insert', document)
self.col.insert_one(document)
def delete(self, query):
self.col.delete_one(query)
@property
def schema_types(self):
__required = {i: object for i in self.schema['$jsonSchema']['required']}
self.log.debug(self.schema['$jsonSchema']['properties'])
__properties = {i: self.schema['$jsonSchema']['properties'][i]['bsonType'] for i in self.schema['$jsonSchema']['properties']}
res = {**__required, **__properties}
check = {i: mongo_to_python(res[i], 'check') for i in res}
convert = {i: mongo_to_python(res[i], 'convert') for i in res}
return check, convert
def __getitem__(self, arg):
"""
:description: Perform a query over a collection (within a specific shard)
:arg arg: filters to perform the query
"""
return self.col.find(arg)
def __str__(self):
return ''.join([u.__str__() for u in self.col.find({})])
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] |
gym_combat/gym_combat/envs/main.py | refaev/combat_gym | 0 | 3992 | <filename>gym_combat/gym_combat/envs/main.py
from matplotlib import style
from tqdm import tqdm
style.use("ggplot")
from gym_combat.envs.Arena.CState import State
from gym_combat.envs.Arena.Entity import Entity
from gym_combat.envs.Arena.Environment import Environment, Episode
from gym_combat.envs.Common.constants import *
from gym_combat.envs.Qtable import Qtable_DecisionMaker
from gym_combat.envs.DQN import DQNAgent_keras
from gym_combat.envs.Greedy import Greedy_player
import matplotlib.pyplot as plt
def print_start_of_game_info(blue_decision_maker, red_decision_maker):
print("Starting tournament!")
print("Blue player type: ", Agent_type_str[blue_decision_maker.type()])
if blue_decision_maker.path_model_to_load==None:
print("Blue player starting with no model")
else:
print("Blue player starting tournament with trained model: " , blue_decision_maker.path_model_to_load)
print("Red player type: ", Agent_type_str[red_decision_maker.type()])
if red_decision_maker.path_model_to_load==None:
print("Red player starting with no model")
else:
print("Red player starting tournament with trained model: " , red_decision_maker.path_model_to_load)
print("Number of rounds: ", NUM_OF_EPISODES)
print("~~~ GO! ~~~\n\n")
def evaluate(episode_number):
#if episode_number % EVALUATE_PLAYERS_EVERY == 0:
a = episode_number % EVALUATE_PLAYERS_EVERY
if a>=0 and a<EVALUATE_BATCH_SIZE:
EVALUATE = True
else:
EVALUATE = False
return EVALUATE
def print_states(observation_for_blue_s0, observation_for_blue_s1):
import matplotlib.pyplot as plt
plt.matshow(observation_for_blue_s0.img)
plt.show()
plt.matshow(observation_for_blue_s1.img)
plt.show()
if __name__ == '__main__':
env = Environment(IS_TRAINING)
print("Starting Blue player")
blue_decision_maker = DQNAgent_keras.DQNAgent_keras()
#blue_decision_maker = DQNAgent_keras.DQNAgent_keras(UPDATE_CONTEXT=True, path_model_to_load='conv1(6_6_1_256)_conv2(4_4_256_128)_conv3(3_3_128_128)_flatten_fc__blue_202001_ 0.95max_ -0.04avg_ -3.10min__1620558885.model')
print("Starting red player")
### Red Decision Maker
red_decision_maker = Greedy_player.Greedy_player()
env.blue_player = Entity(blue_decision_maker)
env.red_player = Entity(red_decision_maker)
print_start_of_game_info(blue_decision_maker, red_decision_maker)
NUM_OF_EPISODES = env.NUMBER_OF_EPISODES
for episode in tqdm(range(1, NUM_OF_EPISODES + 1), ascii=True, unit='episodes'):
EVALUATE = evaluate(episode)
current_episode = Episode(episode, EVALUATE, show_always=False if IS_TRAINING else True)
# set new start position for the players
env.reset_game(episode)
# get observation
observation_for_blue_s0: State = env.get_observation_for_blue()
action_blue = -1
# initialize the decision_makers for the players
blue_decision_maker.set_initial_state(observation_for_blue_s0, episode)
#red_decision_maker.set_initial_state(observation_for_red_s0, episode) # for non-greedy players
blue_won_the_game = False
red_won_the_game = False
for steps_current_game in range(1, MAX_STEPS_PER_EPISODE + 1):
##### Blue's turn! #####
observation_for_blue_s0: State = env.get_observation_for_blue()
current_episode.print_episode(env, steps_current_game)
action_blue: AgentAction = blue_decision_maker.get_action(observation_for_blue_s0, EVALUATE)
env.take_action(Color.Blue, action_blue) # take the action!
current_episode.print_episode(env, steps_current_game)
current_episode.is_terminal = (env.compute_terminal(whos_turn=Color.Blue) is not WinEnum.NoWin)
if current_episode.is_terminal:# Blue won the game!
blue_won_the_game=True
else:
##### Red's turn! #####
observation_for_red_s0: State = env.get_observation_for_red()
action_red: AgentAction = red_decision_maker.get_action(observation_for_red_s0, EVALUATE)
env.take_action(Color.Red, action_red) # take the action!
current_episode.is_terminal = (env.compute_terminal(whos_turn=Color.Red) is not WinEnum.NoWin)
if current_episode.is_terminal: # Blue won the game!
red_won_the_game = True
current_episode.print_episode(env, steps_current_game)
reward_step_blue, reward_step_red = env.handle_reward(steps_current_game)
current_episode.episode_reward_red += reward_step_red
current_episode.episode_reward_blue += reward_step_blue
observation_for_blue_s1: State = env.get_observation_for_blue()
blue_decision_maker.update_context(observation_for_blue_s0, action_blue, reward_step_blue, observation_for_blue_s1,
current_episode.is_terminal, EVALUATE)
if steps_current_game == MAX_STEPS_PER_EPISODE:
# if we exited the loop because we reached MAX_STEPS_PER_EPISODE
current_episode.is_terminal = True
if blue_won_the_game or red_won_the_game:
break
# for statistics
env.update_win_counters(steps_current_game)
env.data_for_statistics(current_episode.episode_reward_blue, current_episode.episode_reward_red, steps_current_game, blue_decision_maker.get_epsolon())
env.evaluate_info(EVALUATE, episode, steps_current_game, blue_decision_maker.get_epsolon())
if current_episode.episode_number % SAVE_STATS_EVERY == 0:
if False:#blue_decision_maker.type()== AgentType.DQN_keras or blue_decision_maker.type() == AgentType.DQN_basic:
blue_decision_maker._decision_maker.print_model(observation_for_blue_s0, episode, "conv")#env.save_folder_path)
# print info of episode:
current_episode.print_info_of_episode(env, steps_current_game, blue_decision_maker.get_epsolon(), episode)
env.end_run()
if blue_decision_maker.type() == AgentType.DQN_keras or blue_decision_maker.type() == AgentType.DQN_basic:
blue_decision_maker._decision_maker.print_model(observation_for_blue_s0, episode, env.save_folder_path)
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qf_lib/analysis/strategy_monitoring/assets_monitoring_sheet.py | webclinic017/qf-lib | 198 | 100317 | # Copyright 2016-present CERN – European Organization for Nuclear Research
#
# Licensed 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 datetime import datetime
from typing import List, Union, Dict
import numpy as np
import matplotlib as plt
import pandas as pd
from pandas.core.dtypes.common import is_numeric_dtype
from qf_lib.analysis.strategy_monitoring.pnl_calculator import PnLCalculator
from qf_lib.backtesting.contract.contract import Contract
from qf_lib.analysis.common.abstract_document import AbstractDocument
from qf_lib.backtesting.contract.contract_to_ticker_conversion.base import ContractTickerMapper
from qf_lib.backtesting.portfolio.transaction import Transaction
from qf_lib.common.enums.frequency import Frequency
from qf_lib.common.enums.price_field import PriceField
from qf_lib.common.exceptions.future_contracts_exceptions import NoValidTickerException
from qf_lib.common.tickers.tickers import Ticker
from qf_lib.common.utils.dateutils.timer import SettableTimer
from qf_lib.common.utils.error_handling import ErrorHandling
from qf_lib.common.utils.logging.qf_parent_logger import qf_logger
from qf_lib.containers.dataframe.prices_dataframe import PricesDataFrame
from qf_lib.containers.dataframe.qf_dataframe import QFDataFrame
from qf_lib.containers.futures.future_tickers.future_ticker import FutureTicker
from qf_lib.containers.futures.futures_adjustment_method import FuturesAdjustmentMethod
from qf_lib.containers.futures.futures_chain import FuturesChain
from qf_lib.containers.series.prices_series import PricesSeries
from qf_lib.containers.series.simple_returns_series import SimpleReturnsSeries
from qf_lib.data_providers.data_provider import DataProvider
from qf_lib.documents_utils.document_exporting.element.df_table import DFTable
from qf_lib.documents_utils.document_exporting.element.heading import HeadingElement
from qf_lib.documents_utils.document_exporting.element.new_page import NewPageElement
from qf_lib.documents_utils.document_exporting.element.paragraph import ParagraphElement
from qf_lib.documents_utils.document_exporting.pdf_exporter import PDFExporter
from qf_lib.settings import Settings
@ErrorHandling.class_error_logging()
class AssetPerfAndDrawdownSheet(AbstractDocument):
"""
For each of the given tickers, provides performance and drawdown comparison of the strategy vs buy and hold.
It also computed the performance contribution and PnL of each of the assets with the given frequency (either yearly
or monthly).
Note: It is assumed that at the beginning no positions are open in the portfolio.
Parameters
-----------
category_to_model_tickers: Dict[str, List[Ticker]]
Dictionary mapping a string, which denotes a category / sector etc, into a list of tickers. The categories are
used to provide aggregated information about performance contribution in each of them (e.g. to compute
performance contribution of different sectors, a dictionary mapping sector names into tickers objects).
contract_ticker_mapper: ContractTickerMapper
An instance of the ContractTickerMapper used to map the tickers into corresponding contracts, which are
used in the Transactions objects
transactions: Union[List[Transaction], str]
Either list of Transaction objects or a path to the Transactions file.
start_date: datetime
end_date: datetime
Dates to used as start and end date for the statistics
data_provider: DataProvider
Data provider used to download the prices and future contracts information, necessary to compute Buy and Hold
benchmark performance
settings: Settings
Necessary settings
pdf_exporter: PDFExporter
Used to export the document to PDF
title: str
Title of the document, will be a part of the filename. Do not use special characters.
initial_cash: int
Initial cash in the portfolio (used to compute the performance contribution for each asset)
frequency: Frequency
Frequency which should be used to compute the performance contribution. Currently only Yearly and Monthly
frequencies are supported.
"""
def __init__(self, category_to_model_tickers: Dict[str, List[Ticker]], contract_ticker_mapper: ContractTickerMapper,
transactions: Union[List[Transaction], str], start_date: datetime, end_date: datetime,
data_provider: DataProvider, settings: Settings, pdf_exporter: PDFExporter,
title: str = "Assets Monitoring Sheet", initial_cash: int = 10000000,
frequency: Frequency = Frequency.YEARLY):
super().__init__(settings, pdf_exporter, title=title)
self.tickers = [t for tickers_list in category_to_model_tickers.values() for t in tickers_list]
self._ticker_to_category = {ticker: c for c, tickers_list in category_to_model_tickers.items()
for ticker in tickers_list}
self._contract_ticker_mapper = contract_ticker_mapper
self._pnl_calculator = PnLCalculator(data_provider, contract_ticker_mapper)
self.transactions = self._parse_transactions_file(transactions) if isinstance(transactions, str) \
else transactions
self._start_date = start_date
self._end_date = end_date
self._data_provider = data_provider
self._initial_cash = initial_cash
if frequency not in (Frequency.MONTHLY, Frequency.YEARLY):
raise NotImplementedError("Only monthly and yearly frequencies are currently supported.")
self._frequency = frequency
self._max_columns_per_page = 7
self._logger = qf_logger.getChild(self.__class__.__name__)
def build_document(self):
self._add_header()
self.document.add_element(ParagraphElement("\n"))
ticker_to_pnl_series = self._compute_pnl()
self._add_pnl_and_performance_contribution_tables(ticker_to_pnl_series)
self._add_performance_statistics(ticker_to_pnl_series)
def _parse_transactions_file(self, path_to_transactions_file: str) -> List[Transaction]:
""" Parse the Transactions csv file created by the Monitor and generate a list of transactions objects. """
transactions_df = pd.read_csv(path_to_transactions_file)
transactions = [
Transaction(
time=pd.to_datetime(row.loc["Timestamp"]),
contract=Contract(
symbol=row.loc["Contract symbol"],
security_type=row.loc["Security type"],
exchange=row.loc["Exchange"],
contract_size=row.loc["Contract size"]
),
quantity=row.loc["Quantity"],
price=row.loc["Price"],
commission=row.loc["Commission"]
) for _, row in transactions_df.iterrows()
]
return transactions
def _compute_pnl(self) -> Dict[Ticker, PricesSeries]:
""" Computes PnL time series for each of the tickers. """
ticker_to_pnl_series = {ticker: self._pnl_calculator.compute_pnl(ticker, self.transactions, self._start_date,
self._end_date) for ticker in self.tickers}
return ticker_to_pnl_series
def _add_performance_statistics(self, ticker_to_pnl_series: Dict[Ticker, PricesSeries]):
""" Generate performance and drawdown plots, which provide the comparison between the strategy performance
and Buy and Hold performance for each of the assets.
"""
self.document.add_element(NewPageElement())
self.document.add_element(HeadingElement(level=2, text="Performance and Drawdowns - Strategy vs Buy and Hold"))
self.document.add_element(ParagraphElement("\n"))
for ticker in self.tickers:
grid = self._get_new_grid()
buy_and_hold_returns = self._generate_buy_and_hold_returns(ticker)
strategy_exposure_series = ticker_to_pnl_series[ticker].to_simple_returns().fillna(0.0)
strategy_exposure_series = strategy_exposure_series.where(strategy_exposure_series == 0.0).fillna(1.0)
strategy_returns = buy_and_hold_returns * strategy_exposure_series
strategy_returns = strategy_returns.dropna()
strategy_returns.name = "Strategy"
if len(strategy_returns) > 0:
perf_chart = self._get_perf_chart([buy_and_hold_returns, strategy_returns], False,
"Performance - {}".format(ticker.name))
underwater_chart = self._get_underwater_chart(strategy_returns.to_prices(),
title="Drawdown - {}".format(ticker.name),
benchmark_series=buy_and_hold_returns.to_prices(),
rotate_x_axis=True)
grid.add_chart(perf_chart)
grid.add_chart(underwater_chart)
self.document.add_element(grid)
else:
self._logger.warning("No data is available for {}. No plots will be generated.".format(ticker.name))
def _generate_buy_and_hold_returns(self, ticker: Ticker) -> SimpleReturnsSeries:
""" Computes series of simple returns, which would be returned by the Buy and Hold strategy. """
if isinstance(ticker, FutureTicker):
try:
ticker.initialize_data_provider(SettableTimer(self._end_date), self._data_provider)
futures_chain = FuturesChain(ticker, self._data_provider, FuturesAdjustmentMethod.BACK_ADJUSTED)
prices_series = futures_chain.get_price(PriceField.Close, self._start_date, self._end_date)
except NoValidTickerException:
prices_series = PricesSeries()
else:
prices_series = self._data_provider.get_price(ticker, PriceField.Close, self._start_date, self._end_date)
returns_tms = prices_series.to_simple_returns().replace([-np.inf, np.inf], np.nan).fillna(0.0)
returns_tms.name = "Buy and Hold"
return returns_tms
def _add_pnl_and_performance_contribution_tables(self, ticker_to_pnl: Dict[Ticker, PricesSeries]):
# For each ticker compute the PnL for each period (each year, month etc)
pnl_df = QFDataFrame.from_dict(ticker_to_pnl)
agg_performance = pnl_df.groupby(pd.Grouper(key=pnl_df.index.name, freq=self._frequency.to_pandas_freq())) \
.apply(lambda s: s.iloc[-1] - s.iloc[0])
# Format the column labels, so that they point exactly to the considered time frame
column_labels_format = {
Frequency.YEARLY: "%Y",
Frequency.MONTHLY: "%b %Y",
}
columns_format = column_labels_format[self._frequency]
performance_df = agg_performance.rename(index=lambda timestamp: timestamp.strftime(columns_format))
# Transpose the original data frame, so that performance for each period is presented in a separate column
performance_df = performance_df.transpose()
performance_df.index = performance_df.index.set_names("Asset")
performance_df = performance_df.reset_index()
performance_df["Asset"] = performance_df["Asset"].apply(lambda t: t.name)
performance_tables = self._create_performance_tables(performance_df.copy())
performance_contribution_tables = self._create_performance_contribution_tables(performance_df.copy())
# Add the text and all figures into the document
self.document.add_element(HeadingElement(level=2, text="Profit and Loss"))
self.document.add_element(ParagraphElement("The following tables provide the details on the Total profit and "
"loss for each asset (notional in currency units)."))
self.document.add_element(ParagraphElement("\n"))
for table in performance_tables:
self.document.add_element(HeadingElement(level=3, text="Performance between: {} - {}".format(
table.model.data.columns[1], table.model.data.columns[-1])))
self.document.add_element(table)
self.document.add_element(ParagraphElement("\n"))
self.document.add_element(NewPageElement())
# Add performance contribution table
self.document.add_element(HeadingElement(level=2, text="Performance contribution"))
for table in performance_contribution_tables:
self.document.add_element(HeadingElement(level=3, text="Performance contribution between {} - {}".format(
table.model.data.columns[1], table.model.data.columns[-1])))
self.document.add_element(table)
def _create_performance_tables(self, performance_df: QFDataFrame) -> List[DFTable]:
""" Create a formatted DFTable out of the performance_df data frame. """
numeric_columns = [col for col in performance_df.columns if is_numeric_dtype(performance_df[col])]
performance_df[numeric_columns] = performance_df[numeric_columns].applymap(lambda x: '{:,.0f}'.format(x))
performance_df = performance_df.set_index("Asset").sort_index()
# Divide the performance df into a number of data frames, so that each of them contains up to
# self.max_col_per_page columns, but keep the first column of the original df in all of them
split_dfs = np.array_split(performance_df, np.ceil(performance_df.num_of_columns / self._max_columns_per_page),
axis=1)
df_tables = [DFTable(df.reset_index(), css_classes=['table', 'shrink-font', 'right-align', 'wide-first-column'])
for df in split_dfs]
return df_tables
def _create_performance_contribution_tables(self, performance_df: QFDataFrame) -> List[DFTable]:
"""
Create a list of DFTables with assets names in the index and different years / months in columns, which contains
details on the performance contribution for each asset.
"""
# Create a QFSeries which contains the initial amount of cash in the portfolio for each year / month
numeric_columns = [col for col in performance_df.columns if is_numeric_dtype(performance_df[col])]
portfolio_values = performance_df[numeric_columns].sum().shift(fill_value=self._initial_cash).cumsum()
performance_df[numeric_columns] = performance_df[numeric_columns] / portfolio_values[numeric_columns]
# Add category column and aggregate data accordingly
ticker_name_to_category = {t.name: category for t, category in self._ticker_to_category.items()}
performance_df["Category"] = performance_df["Asset"].apply(lambda t: ticker_name_to_category[t])
all_categories = list(set(ticker_name_to_category.values()))
performance_df = performance_df.sort_values(by=["Category", "Asset"])
performance_df = performance_df.groupby("Category").apply(
lambda d: pd.concat([PricesDataFrame({**{"Asset": [d.name], "Category": [d.name]},
**{c: [d[c].sum()] for c in numeric_columns}}), d],
ignore_index=True)).drop(columns=["Category"])
# Add the Total Performance row (divide by 2 as the df contains already aggregated data for each group)
total_sum_row = performance_df[numeric_columns].sum() / 2
total_sum_row["Asset"] = "Total Performance"
performance_df = performance_df.append(total_sum_row, ignore_index=True)
# Format the rows using the percentage formatter
performance_df[numeric_columns] = performance_df[numeric_columns].applymap(lambda x: '{:.2%}'.format(x))
# Divide the performance dataframe into a number of dataframes, so that each of them contains up to
# self._max_columns_per_page columns
split_dfs = np.array_split(performance_df.set_index("Asset"),
np.ceil((performance_df.num_of_columns - 1) / self._max_columns_per_page), axis=1)
df_tables = [DFTable(df.reset_index(), css_classes=['table', 'shrink-font', 'right-align', 'wide-first-column'])
for df in split_dfs]
# Get the indices of rows, which contain category info
category_indices = performance_df[performance_df["Asset"].isin(all_categories)].index
for df_table in df_tables:
# Add table formatting, highlight rows showing the total contribution of the given category
df_table.add_rows_styles(category_indices, {"font-weight": "bold", "font-size": "0.95em",
"background-color": "#cbd0d2"})
df_table.add_rows_styles([performance_df.index[-1]], {"font-weight": "bold", "font-size": "0.95em",
"background-color": "#b9bcbd"})
return df_tables
def save(self, report_dir: str = ""):
# Set the style for the report
plt.style.use(['tearsheet'])
filename = "%Y_%m_%d-%H%M {}.pdf".format(self.title)
filename = datetime.now().strftime(filename)
return self.pdf_exporter.generate([self.document], report_dir, filename)
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] |
prologix_usb.py | rohankumardubey/pylt | 0 | 54089 | #!/usr/local/bin/python
from __future__ import print_function
import sys
import time
import serial
import pylt
pusb = dict()
ver = "Prologix GPIB-USB Controller version 6.95"
hwset = (
"addr",
"auto",
"eoi",
"eos",
"eot_enable",
"eot_char",
"read_tmo_ms"
)
def def_set(setting):
setting["auto"] = 0
setting["eoi"] = 1
setting["eos"] = 0
setting["eot_enable"] = 0
setting["eot_char"] = 0
setting["read_tmo_ms"] = 500
setting["rd_mode"] = "eoi"
setting["autocr"] = 1
class prologix_usb(object):
def __init__(self, name):
self.name = name
self.debug_fd = open("_." + name, "w")
self.debug("====", "=============================")
self.ser = serial.Serial("/dev/" + name, 115200, timeout = 0.5)
self.version_check()
self.curset = dict()
self.rd_settings()
d = dict()
def_set(d)
self.set(d)
pusb[name] = self
def debug(self, pfx, str):
print((self.name, "%.6f" % time.time(), pfx, str),
file=self.debug_fd)
self.debug_fd.flush()
def version_check(self):
self.ser.write("\r")
self.cmd("++mode 1")
self.cmd("++auto 0")
self.cmd("++addr 0")
self.cmd("++savecfg 0")
self.cmd("++ifc")
while True:
x = self.ask("++ver")
if x == ver:
break;
assert x == ver
def ask(self, str):
self.cmd(str)
x = self.ser.readline()
x = x.strip("\r\n")
self.debug("{r", x)
return (x)
def rd_settings(self):
for i in hwset:
self.curset[i] = self.ask("++" + i)
def cmd(self, str):
assert str[0:2] == "++"
self.debug("}w", str)
self.ser.write(str + "\r")
def rd_eoi(self):
self.cmd("++read eoi")
x = self.ser.readline()
self.debug("<eoi<", x)
return (x)
def rd_chr(self, chr):
self.cmd("++read %d" % chr)
x = self.ser.readline()
self.debug("<%d<" % chr, x)
return (x)
def rd_bin(self, nbr, eoi = True):
if eoi:
self.cmd("++read eoi")
else:
self.cmd("++read")
x = self.ser.read(nbr)
x = bytearray(x)
self.debug("<%d/%d<" % (nbr, len(x)), x)
return (x)
def wr(self, str):
assert str[0:2] != "++"
self.debug(">", str)
self.ser.write(str + "\r")
def set(self, settings):
for i in hwset:
if i not in settings:
continue
if str(settings[i]) == self.curset[i]:
continue
self.cmd("++" + i + " %d" % settings[i])
self.curset[i] = "%d" % settings[i]
if "read_tmo_ms" in settings:
to = settings["read_tmo_ms"]
self.ser.timeout = (to + 500) * 1e-3
def spoll(self):
self.cmd("++spoll")
while True:
a = self.ser.readline()
self.debug("<sp<", a)
if a.strip().isdigit():
break
return(int(a))
def trigger(self):
self.cmd("++trg")
def clear(self):
self.cmd("++clr")
class gpib_dev(pylt.pylt):
def __init__(self, name, adr):
if not name in pusb:
x = prologix_usb(name)
self.pusb = pusb[name]
self.debug_fd = self.pusb.debug_fd
pylt.pylt.__init__(self)
self.setting = dict()
def_set(self.setting)
self.setting["addr"] = adr
def wr(self, str):
self.pusb.set(self.setting)
self.pusb.wr(str)
def rd_eoi(self, tmo=None, fail=True):
self.pusb.set(self.setting)
x = self.pusb.rd_eoi()
if self.setting["autocr"]:
x = x.strip("\r\n")
return (x)
def rd_chr(self, chr=10, tmo=None, fail=True):
self.pusb.set(self.setting)
x = self.pusb.rd_chr(chr)
if self.setting["autocr"]:
x = x.strip("\r\n")
return (x)
def rd_bin(self, cnt=1, tmo=None, fail=True):
self.pusb.set(self.setting)
x = self.pusb.rd_bin(cnt)
return (x)
def rd(self, tmo=None, fail=True):
m = self.setting["rd_mode"]
if m == "eoi":
return self.rd_eoi()
else:
return self.rd_chr(m)
def attr(self, name, val):
self.setting[name] = val
def spoll(self):
self.pusb.set(self.setting)
return(self.pusb.spoll())
def trigger(self):
self.pusb.set(self.setting)
return(self.pusb.trigger())
def clear(self):
self.pusb.set(self.setting)
self.pusb.clear()
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] |
ML/nlp/reuters_analysis.py | saneravi/ML_Stuff | 209 | 107210 | #!/usr/bin/env python
from collections import defaultdict
import numpy as np
from nltk.corpus import reuters
def analyze_data_distribution(cat2count):
i = 1
most_frequent_words = sorted(cat2count.items(),
key=lambda n: n[1]['train'],
reverse=True)
for el in most_frequent_words:
cat = el[0]
print("\t{:>2}: {:<20}: {:>4}\t{:>4}\t{:0.1f}"
.format(i, cat,
cat2count[cat]['train'],
cat2count[cat]['test'],
np.array(cat2count[cat]['words']).mean()))
i += 1
def analyze_vocabulary(corpus):
word2count = defaultdict(int)
for word in corpus:
word2count[word] += 1
most_freq = sorted(word2count.items(), key=lambda n: n[1], reverse=True)
for i, el in enumerate(most_freq[:10]):
print("{}. frequent word is {} ({} occurences)"
.format(i, el[0], el[1]))
# Create vocabulary
min_occurences = 20
max_occurences = 50
vocabulary = [word[0]
for word in word2count.items()
if word[1] >= min_occurences and word[1] <= max_occurences]
# Design decision: Should there be a pseudo-word OOV
# (out of vocabulary)?
with_oov = True
if with_oov:
word2wid = {'<OOV>': 0}
else:
word2wid = {}
vocabulary = list(vocabulary)
for wid, word in enumerate(vocabulary, start=len(word2wid)):
word2wid[word] = wid
print("Created word2wid")
# Analyze the vocabulary
print("total vocabulary = {}".format(len(word2count)))
print("vocabulary size = {} (min_occ={}, max_occ={})"
.format(len(word2wid), min_occurences, max_occurences))
def main(categories, document_ids, verbose=False):
print(f"categories: {categories}")
print("number of categories: {}".format(len(categories)))
cat2catid = {}
for catid, cat in enumerate(sorted(categories)):
cat2catid[cat] = catid
documents = document_ids
test = [d for d in documents if d.startswith('test/')]
train = [d for d in documents if d.startswith('training/')]
print("train documents: {}".format(len(train)))
print("test documents: {}".format(len(test)))
# make it easy to map data to label
# gather simple statistics
id2cats = defaultdict(list)
cat2count = {}
for cat in categories:
for fid in reuters.fileids(cat):
id2cats[fid].append(cat)
if cat not in cat2count:
cat2count[cat] = {'train': 0, 'test': 0, 'words': []}
if fid in train:
cat2count[cat]['train'] += 1
else:
cat2count[cat]['test'] += 1
cat2count[cat]['words'].append(len(reuters.words(fid)))
print("How many labels do documents usually have?")
labelcount2doccount = defaultdict(int)
for _, cats in id2cats.items():
labelcount2doccount[len(cats)] += 1
s = sorted(labelcount2doccount.items(), reverse=True, key=lambda n: n[1])
for labelcount, documentcount in s:
print("\tlabelcount={:>3}, documentcount={:>3}"
.format(labelcount, documentcount))
# Analyze data distribution to classes
analyze_data_distribution(cat2count)
# Build corpus
corpus = []
for document_id in train:
corpus += list(reuters.words(document_id))
analyze_vocabulary(corpus)
def find_class_predictors(ys):
class_pred_corr = [[0.0 for _ in range(90)] for _ in range(90)]
class_pred_total = [[0.0 for _ in range(90)] for _ in range(90)]
for document_cats in ys:
for take_i in range(90):
for predict_i in range(90):
if take_i == 0:
continue
class_pred_total[take_i][predict_i] += 1
if document_cats[take_i] == document_cats[predict_i]:
class_pred_corr[take_i][predict_i] += 1
acc = []
for i in range(90):
line = []
for j in range(90):
if class_pred_total[i][j] == 0.0:
score = 0.0
else:
score = class_pred_corr[i][j] / class_pred_total[i][j]
line.append(score)
acc.append(line)
return acc
def print_class_predictors(acc):
score_list = []
for take_i in range(90):
for predict_i in range(90):
score_list.append({'take': take_i,
'pred': predict_i,
'acc': acc[take_i][predict_i]})
score_list = sorted(score_list, key=lambda n: n['acc'], reverse=True)
for el in score_list:
if el['take'] == el['pred']:
continue
take = reuters.labels[el['take']]
pred = reuters.labels[el['pred']]
print("{} => {} ({})".format(take, pred, el['acc']))
if __name__ == '__main__':
# main(reuters.categories(), reuters.fileids())
import reuters
acc = find_class_predictors(reuters.load_data()['y_train'])
print_class_predictors(acc)
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convert_rhd.py | miketrumpis/rhd-to-hdf5 | 0 | 1605128 | <reponame>miketrumpis/rhd-to-hdf5
#!/usr/bin/env python
import os
import sys
import json
import numpy as np
import h5py
import logging
from rhdlib.rhd_reader import RHDFile, signed_arrays
def convert(filenames, outfile):
"""
Concatenate the contents of the RHD files into contiguous HDF5 datasets
Parameters
----------
filenames: sequence
Sequence of RHD paths.
outfile: Path, str
Output path for the HDF5 file
"""
info = logging.getLogger().info
info('Creating RHD file maps')
rhd_files = [RHDFile(f) for f in filenames]
with h5py.File(outfile, 'w') as data:
first_file = rhd_files[0]
arrays = first_file.struct_map
hdf_arrays = dict()
hdf_offsets = dict()
for name, shape in arrays:
if name in signed_arrays:
dtype = 'h'
else:
dtype = first_file.rhd_map[name].dtype
num_channels = shape[0]
all_samples = np.sum([rhd.array_sizes[name][1] for rhd in rhd_files])
shape = (num_channels, all_samples) if num_channels > 1 else (all_samples,)
info('dataset name {}, dtype {}, shape {}'.format(name, dtype, shape))
arr = data.create_dataset(name, dtype=dtype, shape=shape, chunks=True)
hdf_arrays[name] = arr
hdf_offsets[name] = 0
for n, rhd in enumerate(rhd_files):
print('Converting {} ({} of {})'.format(rhd.file_path, n + 1, len(rhd_files)))
rhd.to_arrays(arrays=hdf_arrays, offsets=hdf_offsets, apply_scales=False)
info('Offsets: {}'.format(list(hdf_offsets.items())))
data.attrs['JSON_header'] = json.dumps(first_file.header)
info('End of conversion')
print('Done: {}'.format(outfile))
if __name__ == '__main__':
import argparse
from glob import glob
class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawDescriptionHelpFormatter):
pass
app_description = \
"""Combine and convert packetized Intan RHD files into continuous arrays in HDF5 format.
Arrays in the output file may include:
* amplifier_data: converted to signed int16, scale to uV by multiplying 0.195
* aux_input_data: unsigned uint16, scale by 37.4e-6 for Volts (sampled at 1/4 rate as amplifier data)
* board_adc_data: converted to signed int16, scale by 312.5e-6 for Volts
* supply_voltage_data: uint16, scale by 74.8e-6 for Volts (sampled once per data block)
* temp_sensor_data: uint16, scale by 0.01
* board_dig_in_data: boolean
* board_dig_out_data: boolean
To load (Python example):
>>> import h5py
>>> f = h5py.File('ecog_256_array.h5', 'r')
>>> electrodes_uv = f['amplifier_data'][:, 100:200] * 0.195
>>> electrodes_uv.shape
(256, 100)
>>> f['amplifier_data'].shape # total available data
(256, 7200000)
The original header information is stored as a JSON string, which can be parsed like this:
>>> import json
>>> header = json.loads(f.attrs['JSON_header'])
>>> header['sample_rate']
20000.0
"""
ap = argparse.ArgumentParser(description=app_description, formatter_class=CustomFormatter)
ap.add_argument('--doc', action='store_true', help='Print usage message to README.txt')
ap.add_argument('hdf_file', type=str, nargs='?', help='Output filename (.h5 extension will be issued)',
default='out')
ap.add_argument('-i', '--input-files', type=str, nargs='+', help='Input RHD files in order')
ap.add_argument('-d', '--input-dir', type=str, help='Input directory: RHD files will be converted in sorted order')
ap.add_argument('-v', '--verbose', action='store_true', help='Turn on logging channel')
args = ap.parse_args()
if args.doc:
with open('README.txt', 'w') as fw:
fw.write(app_description)
sys.exit(0)
if args.verbose:
root = logging.getLogger()
root.setLevel(logging.INFO)
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
root.addHandler(handler)
if args.input_files is not None and len(args.input_files):
input_files = args.input_files
elif args.input_dir is not None and len(args.input_dir):
input_files = glob(os.path.join(os.path.abspath(args.input_dir), '*.rhd'))
input_files = sorted(input_files)
else:
print('No input files were given!')
ap.print_usage()
sys.exit(2)
print(input_files)
outfile = os.path.splitext(args.hdf_file)[0] + '.h5'
print(outfile)
convert(input_files, outfile)
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users/serializers.py | tahasama/Bugatti-Django-Docker-API | 0 | 150660 | from django.db import transaction
from rest_framework import serializers
from dj_rest_auth.registration.serializers import RegisterSerializer
from django_countries.serializer_fields import CountryField
from .models import GENDER_CHOICES,CustomUser
class CustomUserRegistrationSerializer(RegisterSerializer):
name=serializers.CharField(max_length=100)
gender=serializers.ChoiceField(choices=GENDER_CHOICES)
phone_number = serializers.CharField(max_length=40)
net_worth = serializers.CharField(max_length=255)
country=CountryField()
@transaction.atomic
def save(self,request):
user=super().save(request)
user.name=self.data.get("name")
user.gender=self.data.get("gender")
user.phone_number=self.data.get("phone_number")
user.country=self.data.get("country")
user.net_worth=self.data.get("net_worth")
user.save()
return user
class CustomUserDetailsSerializer(serializers.ModelSerializer):
class Meta:
model=CustomUser
fields=['pk','email','name','phone_number','gender','country','net_worth']
read_only_fields=['pk','email','name','net_worth']
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AlphaGoZero/code/UI/UI.py | OoSnowfxm/AlphaZero_Othello | 0 | 46941 | '''
@Author: fxm
@Date: Dec 27, 2020.
@Title: UI class.
'''
import sys
sys.path.append('..')
import pygame
import logging
from pygame.locals import *
import pygame.gfxdraw
from collections import namedtuple
from Framework.Net import dotdict
from Othello.Board import Board
log = logging.getLogger(__name__)
'''
参数设置
'''
SIZE = 30 # 棋盘每个点之间的间隔
Line_Points = 9 # 棋盘每行/每列点数
Outer_Width = 20 # 棋盘外宽度
Border_Width = 4 # 边框宽度
Inside_Width = 4 # 边框跟实际的棋盘之间的间隔
Border_Length = SIZE * (Line_Points - 1) + Inside_Width * 2 + Border_Width # 边框线的长度
Start_X = Outer_Width + int(Border_Width / 2) + Inside_Width # 起始点X坐标
Start_Y = Outer_Width + int(Border_Width / 2) + Inside_Width # 起始点Y坐标
SCREEN_HEIGHT = SIZE * (Line_Points - 1) + Outer_Width \
* 2 + Border_Width + Inside_Width * 2 # 游戏屏幕的高
SCREEN_WIDTH = SCREEN_HEIGHT + 200 # 游戏屏幕的宽
Stone_Radius = SIZE // 2 # 棋子半径
Checkerboard_Color = (0xE3, 0x92, 0x65) # 棋盘颜色
BLACK_COLOR = (0, 0, 0) # 黑色
WHITE_COLOR = (255, 255, 255) # 白色
RED_COLOR = (245, 222, 179) # 淡黄色
BLUE_COLOR = (30, 30, 200) # 蓝色
RIGHT_INFO_POS_X = SCREEN_HEIGHT + Stone_Radius * 2 + 10
'''
UI类，游戏界面设置对象
'''
class UI():
'''
初始化
参数设置：
game：游戏对象
screen_h：游戏屏幕高
screen_w：游戏屏幕宽
'''
def __init__(self, game):
self.game = game
self.screen_h = SCREEN_HEIGHT
self.screen_w = SCREEN_WIDTH
'''输出一段文字信息'''
def printText(self, screen, font, x, y, text, fcolor=(255, 255, 255)):
imgText = font.render(text, True, fcolor)
screen.blit(imgText, (x, y))
'''画棋盘'''
def drawCheckerboard(self, screen):
# 填充棋盘背景色
screen.fill(Checkerboard_Color)
# 画棋盘网格线外的边框
pygame.draw.rect(screen, BLACK_COLOR, (Outer_Width, Outer_Width, \
Border_Length, Border_Length), Border_Width)
# 画网格线
for i in range(Line_Points): #竖线
pygame.draw.line(screen, BLACK_COLOR, (Start_Y, Start_Y + SIZE * i), \
(Start_Y + SIZE * (Line_Points - 1), Start_Y + SIZE * i), 1)
for j in range(Line_Points): #横线
pygame.draw.line(screen, BLACK_COLOR, (Start_X + SIZE * j, Start_X), \
(Start_X + SIZE * j, Start_X + SIZE * (Line_Points - 1)), 1)
'''画棋子'''
def drawChessman(self, screen, point, stone_color):
pygame.gfxdraw.aacircle(screen, Start_X + SIZE * point[0] + SIZE // 2, \
Start_Y + SIZE * point[1] + SIZE // 2, Stone_Radius, stone_color)
pygame.gfxdraw.filled_circle(screen, Start_X + SIZE * point[0] + SIZE // 2, \
Start_Y + SIZE * point[1] + SIZE // 2, Stone_Radius, stone_color)
'''画一个单独的不在棋盘内的棋子'''
def drawChessmanPos(self, screen, pos, stone_color):
pygame.gfxdraw.aacircle(screen, pos[0], pos[1], Stone_Radius, stone_color)
pygame.gfxdraw.filled_circle(screen, pos[0], pos[1], Stone_Radius, stone_color)
'''画提示可以走的棋子位置'''
def drawMoves(self, screen, point, stone_color):
pygame.gfxdraw.aacircle(screen, Start_X + SIZE * point[0] + SIZE // 2, \
Start_Y + SIZE * point[1] + SIZE // 2, Stone_Radius // 3, stone_color)
pygame.gfxdraw.filled_circle(screen, Start_X + SIZE * point[0] + SIZE // 2, \
Start_Y + SIZE * point[1] + SIZE // 2, Stone_Radius // 3, stone_color)
'''画右侧信息显示'''
def drawRightInfo(self, screen, font, moves, curplayer, is_human_first):
self.drawChessmanPos(screen, (SCREEN_HEIGHT + Stone_Radius, Start_X + Stone_Radius), BLACK_COLOR)
self.drawChessmanPos(screen, (SCREEN_HEIGHT + Stone_Radius, Start_X + Stone_Radius * 4), WHITE_COLOR)
if is_human_first == True:
self.printText(screen, font, RIGHT_INFO_POS_X, Start_X + 3, '玩家', BLUE_COLOR)
self.printText(screen, font, RIGHT_INFO_POS_X, Start_X + Stone_Radius * 3 + 3, '电脑', BLUE_COLOR)
else:
self.printText(screen, font, RIGHT_INFO_POS_X, Start_X + 3, '电脑', BLUE_COLOR)
self.printText(screen, font, RIGHT_INFO_POS_X, Start_X + Stone_Radius * 3 + 3, '玩家', BLUE_COLOR)
if curplayer == -1:
self.printText(screen, font, SCREEN_HEIGHT, SCREEN_HEIGHT//2, f'当前出棋：黑棋', BLUE_COLOR)
else:
self.printText(screen, font, SCREEN_HEIGHT, SCREEN_HEIGHT//2, f'当前出棋：白棋', BLUE_COLOR)
'''根据鼠标点击位置，返回游戏区坐标'''
def getClickpoint(self, click_pos):
pos_x = click_pos[0] - Start_X
pos_y = click_pos[1] - Start_Y
# 如果鼠标点击范围不在游戏区内，就返回None
if pos_x < -Inside_Width or pos_y < -Inside_Width:
return None
x = int(pos_x / SIZE)
y = int(pos_y / SIZE)
# 如果鼠标点击范围超过棋盘另一侧长度，也返回None
if x >= Line_Points or y >= Line_Points:
return None
return (x, y)
'''画出棋盘的所有信息'''
def drawAll(self, screen, board, end, moves, curplayer, is_human_first):
# 画棋盘
font1 = pygame.font.SysFont('SimHei', 72)
font2 = pygame.font.SysFont('SimHei', 24)
fwidth, fheight = font1.size('黑方获胜')
self.drawCheckerboard(screen)
self.drawRightInfo(screen, font2, moves, curplayer, is_human_first)
# 画棋盘上已有的棋子
for i in range(len(board)):
for j in range(len(board[0])):
if board[i][j] == 1:
self.drawChessman(screen, (j,i), WHITE_COLOR)
elif board[i][j] == -1:
self.drawChessman(screen, (j,i), BLACK_COLOR)
if (is_human_first == True and curplayer == -1) or \
(is_human_first == False and curplayer == 1):
for move in moves:
x = move[0]
y = move[1]
self.drawMoves(screen, (y,x), RED_COLOR)
if end != -2:
if end == 1:
self.printText(screen, font1, (SCREEN_WIDTH - fwidth)//2, (SCREEN_HEIGHT - fheight)//2, '白子获胜', RED_COLOR)
elif end == -1:
self.printText(screen, font1, (SCREEN_WIDTH - fwidth)//2, (SCREEN_HEIGHT - fheight)//2, '黑子获胜', RED_COLOR)
elif end == 0:
self.printText(screen, font1, (SCREEN_WIDTH - fwidth)//2, (SCREEN_HEIGHT - fheight)//2, '平局', RED_COLOR)
pygame.display.flip()
'''人类走棋'''
def humanplay(self, board):
valid = self.game.getValid(board, 1)
while True:
for event in pygame.event.get():
if event.type == MOUSEBUTTONDOWN: # 鼠标有输入，则为落子
pressed_array = pygame.mouse.get_pressed()
if pressed_array[0]:
mouse_pos = pygame.mouse.get_pos()
point = self.getClickpoint(mouse_pos)
y,x = point[0], point[1]
if ((0 <= x) and (x < self.game.size) and (0 <= y) and (y < self.game.size)) or \
((x == self.game.size) and (y == 0)):
a = self.game.size * x + y if x != -1 else self.game.size ** 2
if valid[a]:
return a
else:continue
else:continue
'''游戏仿真主过程'''
def display(self, screen, ai, is_human_first):
if is_human_first:
players = ['human', None, 'ai']
else:
players = ['ai', None, 'human']
curplayer = -1
board = self.game.initBoard()
while True:
b = Board(self.game.size)
b.matrix = board
moves = b.getLegalMoves(curplayer)
end = self.game.getGameEnded(board, curplayer)
self.drawAll(screen, board, curplayer * end, moves, curplayer, is_human_first)
if end != -2:
continue
# 如果当前无路可走，就让对方连走两步
if self.game.getNoAction(board, curplayer) == True:
# 更改状态，交换执棋者
board, curplayer = self.game.getNextState(board, curplayer, self.game.size **2)
continue
if players[curplayer+1] == 'human':
action = self.humanplay(self.game.getCanonicalForm(board, curplayer))
elif players[curplayer+1] == 'ai':
action = ai(self.game.getCanonicalForm(board, curplayer))
valids = self.game.getValid(self.game.getCanonicalForm(board, curplayer), 1)
# 如果动作不在合法动作列表内，返回错误
if valids[action] == 0:
log.error(f'Action {action} is not valid!')
log.debug(f'valids = {valids}')
assert valids[action] > 0
# 更改状态，交换执棋者
board, curplayer = self.game.getNextState(board, curplayer, action) | [
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] |
im_v2/common/db/remove_db.py | alphamatic/amp | 5 | 50340 | <gh_stars>1-10
#!/usr/bin/env python
"""
Script to remove IM database using connection.
# Remove a DB named 'test_db' using environment variables: >
remove_db.py --db_name 'test_db'
"""
import argparse
import helpers.hparser as hparser
import helpers.hsql as hsql
import im_v2.im_lib_tasks as imvimlita
def _parse() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
)
parser.add_argument(
"--db_name",
action="store",
required=True,
type=str,
help="DB to drop",
)
parser.add_argument(
"--db_stage",
action="store",
type=str,
default="local",
help="Which env is used: local, dev or prod",
)
parser = hparser.add_verbosity_arg(parser)
return parser
def _main(parser: argparse.ArgumentParser) -> None:
args = parser.parse_args()
# Load DB credentials from env file.
db_stage = args.db_stage
env_file = imvimlita.get_db_env_path(db_stage)
connection_params = hsql.get_connection_info_from_env_file(env_file)
#
db_connection = hsql.get_connection(*connection_params)
# Drop selected database.
hsql.remove_database(connection=db_connection, dbname=args.db_name)
if __name__ == "__main__":
_main(_parse())
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] |
qiime_2_ll_quick_viewer/cli.py | gluque/qiime_2_ll_quick_viewer | 1 | 188834 | # -*- coding: utf-8 -*-
"""Console script for qiime_2_ll_quick_viewer."""
import click
from qiime_2_ll_quick_viewer import qiime_2_ll_quick_viewer
CONTEXT_SETTINGS = dict(help_option_names=['-h', '--help'])
@click.command(context_settings=CONTEXT_SETTINGS)
@click.option('-f', '--filename', required=True,
help="Full path to a Qiime2 visualization file (*.qzv).")
@click.option('-p', '--port', required=True, default=8080,
help="Port to launch the web server.")
def main(filename, port):
"""Quick viewer for Qiime 2 artifacts.
It launches a simple web server to visualize the contents of the data
folder in a browser.
You can access to the server using a SSH tunnel session.
"""
qiime_2_ll_quick_viewer.launch_server(filename, port)
if __name__ == "__main__":
main()
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] |
cfgov/jobmanager/models/django.py | thephillipsequation/cfgov-refresh | 0 | 135384 | <gh_stars>0
from django.db import models
from wagtail.admin.edit_handlers import FieldPanel, InlinePanel
from wagtail.core.fields import RichTextField
from modelcluster.fields import ParentalKey
from modelcluster.models import ClusterableModel
class ApplicantType(models.Model):
applicant_type = models.CharField(max_length=255)
display_title = models.CharField(
max_length=255,
blank=True,
null=True)
description = models.TextField()
def __str__(self):
return self.applicant_type
class Meta:
ordering = ['applicant_type']
def __lt__(self, other):
return self.applicant_type < other.applicant_type
def __gt__(self, other):
return self.applicant_type > other.applicant_type
class Grade(models.Model):
grade = models.CharField(max_length=32)
salary_min = models.IntegerField()
salary_max = models.IntegerField()
def __str__(self):
return self.grade
class Meta:
ordering = ['grade']
def __lt__(self, other):
return self.grade < other.grade
def __gt__(self, other):
return self.grade > other.grade
class JobCategory(models.Model):
job_category = models.CharField(max_length=255)
blurb = RichTextField(null=True, blank=True)
def __str__(self):
return self.job_category
class Meta:
ordering = ['job_category']
class ServiceType(models.Model):
service_type = models.CharField(max_length=255)
def __str__(self):
return self.service_type
class Meta:
ordering = ['service_type']
class JobLength(models.Model):
job_length = models.CharField(max_length=255)
def __str__(self):
return self.job_length
class Meta:
ordering = ['job_length']
class JobLocation(ClusterableModel):
abbreviation = models.CharField(
max_length=2,
primary_key=True)
name = models.CharField(max_length=255)
def __str__(self):
return self.name
class Meta:
ordering = ('abbreviation',)
class Region(JobLocation):
panels = [
FieldPanel('abbreviation'),
FieldPanel('name'),
InlinePanel('states', label="States"),
InlinePanel('cities', label="Cities"),
]
class Office(JobLocation):
panels = [
FieldPanel('abbreviation'),
FieldPanel('name'),
InlinePanel('cities', label="Office location", max_num=1),
]
class State(models.Model):
name = models.CharField(
max_length=255,
verbose_name="State name")
abbreviation = models.CharField(
max_length=2,
primary_key=True)
region = ParentalKey(
'Region',
related_name="states")
def __str__(self):
return self.name
class Meta:
ordering = ('abbreviation',)
class City(models.Model):
name = models.CharField(
max_length=255,
verbose_name="City name")
state = models.ForeignKey(
State,
null=False,
blank=False,
default=None,
related_name='cities')
location = ParentalKey(
'JobLocation',
related_name='cities'
)
class Meta:
ordering = ('state_id', 'name')
def __str__(self):
return '{}, {}'.format(self.name, self.state.abbreviation)
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2
] |
python/revegetate.py | TenType/competition | 1 | 170418 | <reponame>TenType/competition
n, m = map(int, input().split())
connected = []
seeds = []
for i in range(0, n):
connected.append([])
for i in range(0, m):
a, b = map(int, input().split())
if (b not in connected[a-1]):
connected[a-1].append(b)
if (a not in connected[b-1]):
connected[b-1].append(a)
print(connected)
# for each pasture
for i in range(0, n):
# for each seed
for j in range(1, 4):
valid = True
# for each other pasture
for k in range(1, 4):
if k == j:
continue
if k in connected[j]:
valid = False
break
if valid:
seeds.append(k)
break
print(seeds)
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] |
lib/datasets/carla.py | BuiKhoi/DDRNet.pytorch | 0 | 160702 | <reponame>BuiKhoi/DDRNet.pytorch
# ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by <NAME> (<EMAIL>)
# ------------------------------------------------------------------------------
import os
import cv2
import numpy as np
from PIL import Image
import torch
from torch.nn import functional as F
from .base_dataset import BaseDataset
class Carla(BaseDataset):
def __init__(self,
root,
list_path,
num_samples=None,
num_classes=8,
multi_scale=True,
flip=True,
ignore_label=-1,
base_size=2048,
crop_size=(512, 1024),
downsample_rate=1,
scale_factor=16,
mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225]):
super(Carla, self).__init__(ignore_label, base_size,
crop_size, downsample_rate, scale_factor, mean, std, )
self.root = root
self.list_path = list_path
self.num_classes = num_classes
self.multi_scale = multi_scale
self.flip = flip
self.img_list = [line.strip().split() for line in open(root + list_path)]
self.files = self.read_files()
if num_samples:
self.files = self.files[:num_samples]
self.label_mapping = {
0: 0, 1: 1, 2: 2, 3: 3, 4: 4,
5: 5, 6: 6, 7: 7, 8: 8
}
# Nothing, Bridges, Pedestrian, Road, Road line, Side walk, Traffic sign, Traffic light, Vehicles
# self.class_weights = None
self.class_weights = torch.FloatTensor([
0.0373, 0.9345, 1.4843, 0.8373,
1.2577, 0.918, 1.2489, 1.245, 1.037
]).cuda()
self.color_palette = [
(0, 0, 0),
(150, 100, 100),
(220, 20, 60),
(128, 64, 128),
(157, 234, 50),
(244, 35, 232),
(220, 220, 0),
(250, 170, 30),
(0, 0, 142)
]
def read_files(self):
files = []
if 'test' in self.list_path:
for item in self.img_list:
image_path = item
name = os.path.splitext(os.path.basename(image_path[0]))[0]
files.append({
"img": image_path[0],
"name": name,
})
else:
for item in self.img_list:
image_path, label_path = item
name = os.path.splitext(os.path.basename(label_path))[0]
files.append({
"img": image_path,
"label": label_path,
"name": name,
"weight": 1
})
return files
def convert_label(self, label, inverse=False):
temp = label.copy()
if inverse:
for v, k in self.label_mapping.items():
label[temp == k] = v
else:
for k, v in self.label_mapping.items():
label[temp == k] = v
return label
def __getitem__(self, index):
item = self.files[index]
name = item["name"]
image = cv2.imread(os.path.join(self.root, 'carla', item["img"]),
cv2.IMREAD_COLOR)
size = image.shape
if 'test' in self.list_path:
image = self.input_transform(image)
image = image.transpose((2, 0, 1))
return image.copy(), np.array(size), name
label = cv2.imread(os.path.join(self.root, 'carla', item["label"]),
cv2.IMREAD_GRAYSCALE)
label = self.convert_label(label)
image, label = self.gen_sample(image, label,
self.multi_scale, self.flip)
return image.copy(), label.copy(), np.array(size), name
def multi_scale_inference(self, config, model, image, scales=[1], flip=False):
batch, _, ori_height, ori_width = image.size()
assert batch == 1, "only supporting batchsize 1."
image = image.numpy()[0].transpose((1, 2, 0)).copy()
stride_h = np.int(self.crop_size[0] * 1.0)
stride_w = np.int(self.crop_size[1] * 1.0)
final_pred = torch.zeros([1, self.num_classes,
ori_height, ori_width]).cuda()
for scale in scales:
new_img = self.multi_scale_aug(image=image,
rand_scale=scale,
rand_crop=False)
height, width = new_img.shape[:-1]
if scale <= 1.0:
new_img = new_img.transpose((2, 0, 1))
new_img = np.expand_dims(new_img, axis=0)
new_img = torch.from_numpy(new_img)
preds = self.inference(config, model, new_img, flip)
preds = preds[:, :, 0:height, 0:width]
else:
new_h, new_w = new_img.shape[:-1]
rows = np.int(np.ceil(1.0 * (new_h -
self.crop_size[0]) / stride_h)) + 1
cols = np.int(np.ceil(1.0 * (new_w -
self.crop_size[1]) / stride_w)) + 1
preds = torch.zeros([1, self.num_classes,
new_h, new_w]).cuda()
count = torch.zeros([1, 1, new_h, new_w]).cuda()
for r in range(rows):
for c in range(cols):
h0 = r * stride_h
w0 = c * stride_w
h1 = min(h0 + self.crop_size[0], new_h)
w1 = min(w0 + self.crop_size[1], new_w)
h0 = max(int(h1 - self.crop_size[0]), 0)
w0 = max(int(w1 - self.crop_size[1]), 0)
crop_img = new_img[h0:h1, w0:w1, :]
crop_img = crop_img.transpose((2, 0, 1))
crop_img = np.expand_dims(crop_img, axis=0)
crop_img = torch.from_numpy(crop_img)
pred = self.inference(config, model, crop_img, flip)
preds[:, :, h0:h1, w0:w1] += pred[:, :, 0:h1 - h0, 0:w1 - w0]
count[:, :, h0:h1, w0:w1] += 1
preds = preds / count
preds = preds[:, :, :height, :width]
preds = F.interpolate(
preds, (ori_height, ori_width),
mode='bilinear', align_corners=config.MODEL.ALIGN_CORNERS
)
final_pred += preds
return final_pred
def save_pred(self, image, preds, sv_path, name):
h, w = preds.shape
image_canvas = np.empty((w, h*2, 3), np.uint8)
image_canvas[:h] = image[:, :, ::-1]
image_canvas[h:] = self.fill_color_palette(self.color_palette, preds)
cv2.imwrite(
os.path.join(sv_path, name[0] + '.png'),
image_canvas
)
def fill_color_palette(self, labels, segmentation):
canvas = np.zeros((*segmentation.shape, 3), np.uint8)
for idx, label in enumerate(labels):
indices = np.where(segmentation == idx)
canvas[indices[0], indices[1], :] = label
return canvas
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] |
examples/distributed_dl/distributed_ml.py | james-tn/ray-on-aml | 19 | 117045 | <filename>examples/distributed_dl/distributed_ml.py
from ray_on_aml.core import Ray_On_AML
from azureml.core import Run
import numpy as np
import torch
import torch.optim as optim
import torch.nn as nn
from torchvision import datasets, transforms
from torch.utils.data import DataLoader
import torch.nn.functional as F
import ray.train.torch
from ray import train
from ray.train import Trainer
from ray import tune
# from ray.tune import Callback
import torch
import torch.nn as nn
from torch.nn.modules.utils import consume_prefix_in_state_dict_if_present
from torch.optim import Adam
import numpy as np
def train_func(config):
cuda = torch.device('cuda')
n = 100
# create a toy dataset
# data : X - dim = (n, 4)
# target : Y - dim = (n, 1)
X = torch.Tensor(np.random.normal(0, 1, size=(n, 4))).detach().to(cuda)
Y = torch.Tensor(np.random.uniform(0, 1, size=(n, 1))).detach().to(cuda)
# toy neural network : 1-layer
# wrap the model in DDP
model = ray.train.torch.prepare_model(nn.Linear(4, 1))
criterion = nn.MSELoss()
optimizer = Adam(model.parameters(), lr=3e-4)
for epoch in range(config["num_epochs"]):
y = model.forward(X)
# compute loss
loss = criterion(y, Y)
print("epoch ", epoch, " loss ", loss)
# back-propagate loss
optimizer.zero_grad()
loss.backward()
optimizer.step()
# To fetch non-DDP state_dict
# w/o DDP: model.state_dict()
# w/ DDP: model.module.state_dict()
# See: https://github.com/ray-project/ray/issues/20915
state_dict = model.state_dict()
consume_prefix_in_state_dict_if_present(state_dict, "module.")
train.save_checkpoint(epoch=epoch, model_weights=state_dict)
if __name__ == "__main__":
run = Run.get_context()
ws = run.experiment.workspace
ray_on_aml =Ray_On_AML()
ray = ray_on_aml.getRay()
if ray: #in the headnode
print("head node detected")
print("test distributed DL trainining")
print("resources for ray cluster ", ray.cluster_resources())
trainer = Trainer(backend="torch", num_workers=2,use_gpu =True)
trainer.start()
trainer.run(train_func, config={"num_epochs": 5})
trainer.shutdown()
print(trainer.latest_checkpoint)
else:
print("in worker node")
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396,
281,
29914,
29877,
360,
11191,
29901,
1904,
29889,
3859,
29918,
8977,
580,
13,
4706,
396,
281,
29914,
29871,
360,
11191,
29901,
1904,
29889,
5453,
29889,
3859,
29918,
8977,
580,
13,
4706,
396,
2823,
29901,
2045,
597,
3292,
29889,
510,
29914,
764,
29899,
4836,
29914,
764,
29914,
12175,
29914,
29906,
29900,
29929,
29896,
29945,
13,
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353,
1904,
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29918,
8977,
580,
13,
4706,
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29918,
13506,
29918,
262,
29918,
3859,
29918,
8977,
29918,
361,
29918,
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3859,
29918,
8977,
29892,
376,
5453,
23157,
13,
4706,
7945,
29889,
7620,
29918,
3198,
3149,
29898,
1022,
2878,
29922,
1022,
2878,
29892,
1904,
29918,
705,
5861,
29922,
3859,
29918,
8977,
29897,
13,
13,
13,
13,
361,
4770,
978,
1649,
1275,
376,
1649,
3396,
1649,
1115,
13,
1678,
1065,
353,
7525,
29889,
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29918,
4703,
580,
13,
1678,
16904,
353,
1065,
29889,
735,
15362,
29889,
1287,
3493,
13,
1678,
15570,
29918,
265,
29918,
8807,
353,
29934,
388,
29918,
2951,
29918,
23956,
580,
13,
1678,
15570,
353,
15570,
29918,
265,
29918,
8807,
29889,
657,
29934,
388,
580,
13,
13,
1678,
565,
15570,
29901,
396,
262,
278,
2343,
3177,
13,
4706,
1596,
703,
2813,
2943,
17809,
1159,
13,
4706,
1596,
703,
1688,
13235,
360,
29931,
7945,
2827,
1159,
13,
4706,
1596,
703,
13237,
363,
15570,
9867,
9162,
15570,
29889,
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29918,
13237,
3101,
13,
13,
13,
4706,
1020,
4983,
353,
3201,
4983,
29898,
27852,
543,
7345,
305,
613,
954,
29918,
1287,
414,
29922,
29906,
29892,
1509,
29918,
29887,
3746,
353,
5574,
29897,
13,
4706,
1020,
4983,
29889,
2962,
580,
13,
4706,
1020,
4983,
29889,
3389,
29898,
14968,
29918,
9891,
29892,
2295,
3790,
29908,
1949,
29918,
1022,
2878,
29879,
1115,
29871,
29945,
1800,
13,
4706,
1020,
4983,
29889,
845,
329,
3204,
580,
13,
13,
4706,
1596,
29898,
3018,
4983,
29889,
12333,
29918,
3198,
3149,
29897,
13,
1678,
1683,
29901,
13,
4706,
1596,
703,
262,
15645,
2943,
1159,
13,
2
] |
src/z3c/viewtemplate/macro.py | zopefoundation/z3c.viewtemplate | 0 | 1608576 | ##############################################################################
#
# Copyright (c) 2005 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
"""
$Id$
"""
__docformat__ = "reStructuredText"
from StringIO import StringIO
from zope.tal.talinterpreter import TALInterpreter
class Macro(object):
"""Provides a single macro from a template for rendering."""
def __init__(self, template, macroName, view, request, contentType):
self.template = template
self.macroName = macroName
self.view = view
self.request = request
self.contentType = contentType
def __call__(self, *args, **kwargs):
try:
program = self.template.macros[self.macroName]
except KeyError:
raise KeyError('Macro "%s" not found in file "%s"'% (
self.macroName, self.template.filename))
output = StringIO(u'')
namespace = self.template.pt_getContext(self.view,
self.request,
options=kwargs)
context = self.template.pt_getEngineContext(namespace)
debug_flags = self.request.debug
TALInterpreter(
program,
None,
context,
output,
tal=True,
showtal=getattr(debug_flags, 'showTAL', 0),
strictinsert=0,
sourceAnnotations=getattr(debug_flags, 'sourceAnnotations', 0),
)()
if not self.request.response.getHeader("Content-Type"):
self.request.response.setHeader("Content-Type",
self.contentType)
return output.getvalue()
| [
1,
835,
13383,
13383,
13383,
13383,
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2277,
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13383,
13383,
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13,
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29908,
13,
29938,
1204,
29938,
13,
15945,
29908,
13,
1649,
1514,
4830,
1649,
353,
376,
276,
19560,
2955,
1626,
29908,
13,
13,
3166,
1714,
5971,
1053,
1714,
5971,
13,
13,
3166,
503,
2300,
29889,
20411,
29889,
20411,
1639,
1457,
357,
1053,
323,
1964,
4074,
1457,
357,
13,
13,
1990,
4326,
307,
29898,
3318,
1125,
13,
1678,
9995,
1184,
29894,
2247,
263,
2323,
11758,
515,
263,
4472,
363,
15061,
1213,
15945,
13,
13,
1678,
822,
4770,
2344,
12035,
1311,
29892,
4472,
29892,
11758,
1170,
29892,
1776,
29892,
2009,
29892,
2793,
1542,
1125,
13,
4706,
1583,
29889,
6886,
353,
4472,
13,
4706,
1583,
29889,
25254,
1170,
353,
11758,
1170,
13,
4706,
1583,
29889,
1493,
353,
1776,
13,
4706,
1583,
29889,
3827,
353,
2009,
13,
4706,
1583,
29889,
3051,
1542,
353,
2793,
1542,
13,
13,
1678,
822,
4770,
4804,
12035,
1311,
29892,
334,
5085,
29892,
3579,
19290,
1125,
13,
4706,
1018,
29901,
13,
9651,
1824,
353,
1583,
29889,
6886,
29889,
8628,
1883,
29961,
1311,
29889,
25254,
1170,
29962,
13,
4706,
5174,
7670,
2392,
29901,
13,
9651,
12020,
7670,
2392,
877,
15735,
307,
11860,
29879,
29908,
451,
1476,
297,
934,
11860,
29879,
29908,
29915,
29995,
313,
13,
18884,
1583,
29889,
25254,
1170,
29892,
1583,
29889,
6886,
29889,
9507,
876,
13,
4706,
1962,
353,
1714,
5971,
29898,
29884,
29915,
1495,
13,
4706,
7397,
353,
1583,
29889,
6886,
29889,
415,
29918,
657,
2677,
29898,
1311,
29889,
1493,
29892,
13,
462,
462,
18884,
1583,
29889,
3827,
29892,
13,
462,
462,
18884,
3987,
29922,
19290,
29897,
13,
4706,
3030,
353,
1583,
29889,
6886,
29889,
415,
29918,
657,
12412,
2677,
29898,
22377,
29897,
13,
4706,
4744,
29918,
15764,
353,
1583,
29889,
3827,
29889,
8382,
13,
4706,
323,
1964,
4074,
1457,
357,
29898,
13,
18884,
1824,
29892,
13,
18884,
6213,
29892,
13,
18884,
3030,
29892,
13,
18884,
1962,
29892,
13,
18884,
5969,
29922,
5574,
29892,
13,
18884,
1510,
20411,
29922,
657,
5552,
29898,
8382,
29918,
15764,
29892,
525,
4294,
29911,
1964,
742,
29871,
29900,
511,
13,
18884,
9406,
7851,
29922,
29900,
29892,
13,
18884,
2752,
2744,
1333,
800,
29922,
657,
5552,
29898,
8382,
29918,
15764,
29892,
525,
4993,
2744,
1333,
800,
742,
29871,
29900,
511,
13,
18884,
1723,
580,
13,
4706,
565,
451,
1583,
29889,
3827,
29889,
5327,
29889,
657,
7850,
703,
3916,
29899,
1542,
29908,
1125,
13,
9651,
1583,
29889,
3827,
29889,
5327,
29889,
842,
7850,
703,
3916,
29899,
1542,
613,
13,
462,
462,
9651,
1583,
29889,
3051,
1542,
29897,
13,
4706,
736,
1962,
29889,
657,
1767,
580,
13,
13,
2
] |
Chapter 05/thread_sync.py | bpbpublications/Advance-Core-Python-Programming | 0 | 90764 | <gh_stars>0
import threading
x = 0
range_val = int(input("Enter the range : "))
def thread_sync(lock):
global x
for i in range(range_val):
# lock.acquire()
x += 1
lock.release()
lock = threading.Lock()
t1 = threading.Thread(target = thread_sync, args = (lock,))
t2 = threading.Thread(target = thread_sync, args = (lock,))
t1.start()
t2.start()
t1.join()
t2.join()
print(x)
| [
1,
529,
12443,
29918,
303,
1503,
29958,
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13,
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292,
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3244,
29918,
16593,
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6389,
353,
313,
908,
29892,
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30004,
13,
29873,
29906,
353,
3244,
292,
29889,
4899,
29898,
5182,
353,
3244,
29918,
16593,
29892,
6389,
353,
313,
908,
29892,
876,
30004,
13,
29873,
29896,
29889,
2962,
26471,
13,
29873,
29906,
29889,
2962,
26471,
13,
29873,
29896,
29889,
7122,
26471,
13,
29873,
29906,
29889,
7122,
26471,
13,
30004,
13,
2158,
29898,
29916,
8443,
13,
2
] |
backend/test.py | Harin329/Masterplan | 0 | 38114 | <reponame>Harin329/Masterplan<gh_stars>0
import boto3
import os
from dotenv import load_dotenv
load_dotenv()
client = boto3.client(
'dynamodb',
aws_access_key_id=os.getenv('AWS_ACCESS_KEY_ID'),
aws_secret_access_key=os.getenv('AWS_SECRET_ACCESS_KEY'),
region_name="us-east-1"
)
| [
1,
529,
276,
1112,
420,
29958,
21972,
262,
29941,
29906,
29929,
29914,
19203,
9018,
29966,
12443,
29918,
303,
1503,
29958,
29900,
13,
5215,
289,
3747,
29941,
13,
5215,
2897,
13,
3166,
8329,
6272,
1053,
2254,
29918,
6333,
6272,
13,
13,
1359,
29918,
6333,
6272,
580,
13,
13,
4645,
353,
289,
3747,
29941,
29889,
4645,
29898,
13,
1678,
525,
29881,
2926,
10396,
742,
13,
1678,
25879,
29918,
5943,
29918,
1989,
29918,
333,
29922,
359,
29889,
657,
6272,
877,
29909,
7811,
29918,
2477,
23524,
29918,
10818,
29918,
1367,
5477,
13,
1678,
25879,
29918,
19024,
29918,
5943,
29918,
1989,
29922,
359,
29889,
657,
6272,
877,
29909,
7811,
29918,
1660,
22245,
29911,
29918,
2477,
23524,
29918,
10818,
5477,
13,
1678,
5120,
29918,
978,
543,
375,
29899,
23027,
29899,
29896,
29908,
13,
29897,
13,
2
] |
med_files_api/med_result/migrations/0003_auto_20200509_1024.py | TheProrok29/med-files-api | 0 | 101591 | <reponame>TheProrok29/med-files-api
# Generated by Django 3.0.5 on 2020-05-09 08:24
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('med_result', '0002_medresult_name'),
]
operations = [
migrations.AlterField(
model_name='medresult',
name='date_of_exam',
field=models.DateField(),
),
]
| [
1,
529,
276,
1112,
420,
29958,
1576,
29925,
729,
554,
29906,
29929,
29914,
2168,
29899,
5325,
29899,
2754,
13,
29937,
3251,
630,
491,
15337,
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29941,
29889,
29900,
29889,
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373,
29871,
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29900,
29906,
29900,
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29900,
29945,
29899,
29900,
29929,
29871,
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29947,
29901,
29906,
29946,
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13,
3166,
9557,
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2585,
1053,
9725,
800,
29892,
4733,
13,
13,
13,
1990,
341,
16783,
29898,
26983,
800,
29889,
29924,
16783,
1125,
13,
13,
1678,
9962,
353,
518,
13,
4706,
6702,
2168,
29918,
2914,
742,
525,
29900,
29900,
29900,
29906,
29918,
2168,
2914,
29918,
978,
5477,
13,
1678,
4514,
13,
13,
1678,
6931,
353,
518,
13,
4706,
9725,
800,
29889,
2499,
357,
3073,
29898,
13,
9651,
1904,
29918,
978,
2433,
2168,
2914,
742,
13,
9651,
1024,
2433,
1256,
29918,
974,
29918,
735,
314,
742,
13,
9651,
1746,
29922,
9794,
29889,
2539,
3073,
3285,
13,
4706,
10353,
13,
1678,
4514,
13,
2
] |
render_utils.py | IBM/photorealistic-blocksworld | 17 | 50045 | from __future__ import print_function
import sys, random, json, os, tempfile
from collections import Counter
import numpy as np
INSIDE_BLENDER = True
try:
import bpy
from mathutils import Vector
except ImportError as e:
INSIDE_BLENDER = False
if INSIDE_BLENDER:
try:
import utils
except ImportError as e:
print("\nERROR")
print("Running render_images.py from Blender and cannot import utils.py.")
print("You may need to add a .pth file to the site-packages of Blender's")
print("bundled python with a command like this:\n")
print("echo $PWD >> $BLENDER/$VERSION/python/lib/python3.5/site-packages/clevr.pth")
print("\nWhere $BLENDER is the directory where Blender is installed, and")
print("$VERSION is your Blender version (such as 2.78).")
sys.exit(1)
def render_scene(args,
output_image='render.png',
output_scene='render_json',
output_blendfile=None,
objects=[],
**kwargs
):
# Load the main blendfile
bpy.ops.wm.open_mainfile(filepath=args.base_scene_blendfile)
# Load materials
utils.load_materials(args.material_dir)
# Set render arguments so we can get pixel coordinates later.
# We use functionality specific to the CYCLES renderer so BLENDER_RENDER
# cannot be used.
render_args = bpy.context.scene.render
render_args.engine = "CYCLES"
render_args.filepath = output_image
render_args.resolution_x = args.width
render_args.resolution_y = args.height
render_args.resolution_percentage = 100
render_args.tile_x = args.render_tile_size
render_args.tile_y = args.render_tile_size
if args.use_gpu == 1:
# Blender changed the API for enabling CUDA at some point
if bpy.app.version < (2, 78, 0):
bpy.context.user_preferences.system.compute_device_type = 'CUDA'
bpy.context.user_preferences.system.compute_device = 'CUDA_0'
else:
cycles_prefs = bpy.context.user_preferences.addons['cycles'].preferences
cycles_prefs.compute_device_type = 'CUDA'
# Some CYCLES-specific stuff
bpy.data.worlds['World'].cycles.sample_as_light = True
bpy.context.scene.cycles.blur_glossy = 2.0
bpy.context.scene.cycles.samples = args.render_num_samples
bpy.context.scene.cycles.transparent_min_bounces = args.render_min_bounces
bpy.context.scene.cycles.transparent_max_bounces = args.render_max_bounces
if args.use_gpu == 1:
bpy.context.scene.cycles.device = 'GPU'
# This will give ground-truth information about the scene and its objects
scene_struct = {
'image_filename': os.path.basename(output_image),
'objects': [],
'directions': {},
}
scene_struct.update(kwargs)
if bpy.app.version < (2, 80, 0):
bpy.ops.mesh.primitive_plane_add(radius=5)
else:
bpy.ops.mesh.primitive_plane_add(size=5)
plane = bpy.context.object
def rand(L):
return 2.0 * L * (random.random() - 0.5)
# Add random jitter to camera position
if args.camera_jitter > 0:
for i in range(3):
bpy.data.objects['Camera'].location[i] += rand(args.camera_jitter)
# Figure out the left, up, and behind directions along the plane and record
# them in the scene structure
camera = bpy.data.objects['Camera']
plane_normal = plane.data.vertices[0].normal
if bpy.app.version < (2, 80, 0):
cam_behind = camera.matrix_world.to_quaternion() * Vector((0, 0, -1))
cam_left = camera.matrix_world.to_quaternion() * Vector((-1, 0, 0))
cam_up = camera.matrix_world.to_quaternion() * Vector((0, 1, 0))
else:
cam_behind = camera.matrix_world.to_quaternion() @ Vector((0, 0, -1))
cam_left = camera.matrix_world.to_quaternion() @ Vector((-1, 0, 0))
cam_up = camera.matrix_world.to_quaternion() @ Vector((0, 1, 0))
plane_behind = (cam_behind - cam_behind.project(plane_normal)).normalized()
plane_left = (cam_left - cam_left.project(plane_normal)).normalized()
plane_up = cam_up.project(plane_normal).normalized()
# Delete the plane; we only used it for normals anyway. The base scene file
# contains the actual ground plane.
utils.delete_object(plane)
# Save all six axis-aligned directions in the scene struct
scene_struct['directions']['behind'] = tuple(plane_behind)
scene_struct['directions']['front'] = tuple(-plane_behind)
scene_struct['directions']['left'] = tuple(plane_left)
scene_struct['directions']['right'] = tuple(-plane_left)
scene_struct['directions']['above'] = tuple(plane_up)
scene_struct['directions']['below'] = tuple(-plane_up)
# Add random jitter to lamp positions
if args.key_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Key'].location[i] += rand(args.key_light_jitter)
if args.back_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Back'].location[i] += rand(args.back_light_jitter)
if args.fill_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Fill'].location[i] += rand(args.fill_light_jitter)
# Now make some random objects
blender_objects = add_objects(args, scene_struct, camera, objects)
# Render the scene and dump the scene data structure
scene_struct['objects'] = objects
scene_struct['relationships'] = compute_all_relationships(scene_struct)
while True:
try:
bpy.ops.render.render(write_still=True)
break
except Exception as e:
print(e)
with open(output_scene, 'w') as f:
json.dump(scene_struct, f, indent=2)
if output_blendfile is not None:
bpy.ops.wm.save_as_mainfile(filepath=output_blendfile)
def add_objects(args, scene_struct, camera, objects):
"""
Add objects to the current blender scene
"""
blender_objects = []
for obj in objects:
# Actually add the object to the scene
utils.add_object(args.shape_dir,
obj["shape"],
obj["size"],
obj["location"],
theta=obj["rotation"])
bobj = bpy.context.object
blender_objects.append(bobj)
utils.add_material(obj["material"], Color=obj["color"])
obj["pixel_coords"] = utils.get_camera_coords(camera, bobj.location)
loc = np.array(bobj.location)
dim = np.array(bobj.dimensions)
half = dim / 2
corners = []
corners.append(loc + half * [1,1,1])
corners.append(loc + half * [1,1,-1])
corners.append(loc + half * [1,-1,1])
corners.append(loc + half * [1,-1,-1])
corners.append(loc + half * [-1,1,1])
corners.append(loc + half * [-1,1,-1])
corners.append(loc + half * [-1,-1,1])
corners.append(loc + half * [-1,-1,-1])
import mathutils
corners_camera_coords = np.array([ utils.get_camera_coords(camera, mathutils.Vector(tuple(corner)))
for corner in corners ])
xmax = np.amax(corners_camera_coords[:,0])
ymax = np.amax(corners_camera_coords[:,1])
xmin = np.amin(corners_camera_coords[:,0])
ymin = np.amin(corners_camera_coords[:,1])
obj["bbox"] = (float(xmin), float(ymin), float(xmax), float(ymax))
return blender_objects
def compute_all_relationships(scene_struct, eps=0.2):
"""
Computes relationships between all pairs of objects in the scene.
Returns a dictionary mapping string relationship names to lists of lists of
integers, where output[rel][i] gives a list of object indices that have the
relationship rel with object i. For example if j is in output['left'][i] then
object j is left of object i.
"""
all_relationships = {}
for name, direction_vec in scene_struct['directions'].items():
if name == 'above' or name == 'below': continue
all_relationships[name] = []
for i, obj1 in enumerate(scene_struct['objects']):
coords1 = obj1['location']
related = set()
for j, obj2 in enumerate(scene_struct['objects']):
if obj1 == obj2: continue
coords2 = obj2['location']
diff = [coords2[k] - coords1[k] for k in [0, 1, 2]]
dot = sum(diff[k] * direction_vec[k] for k in [0, 1, 2])
if dot > eps:
related.add(j)
all_relationships[name].append(sorted(list(related)))
return all_relationships
def check_visibility(blender_objects, min_pixels_per_object):
"""
Check whether all objects in the scene have some minimum number of visible
pixels; to accomplish this we assign random (but distinct) colors to all
objects, and render using no lighting or shading or antialiasing; this
ensures that each object is just a solid uniform color. We can then count
the number of pixels of each color in the output image to check the visibility
of each object.
Returns True if all objects are visible and False otherwise.
"""
f, path = tempfile.mkstemp(suffix='.png')
object_colors = render_shadeless(blender_objects, path=path)
img = bpy.data.images.load(path)
p = list(img.pixels)
color_count = Counter((p[i], p[i+1], p[i+2], p[i+3])
for i in range(0, len(p), 4))
os.remove(path)
if len(color_count) != len(blender_objects) + 1:
return False
for _, count in color_count.most_common():
if count < min_pixels_per_object:
return False
return True
def render_shadeless(blender_objects, path='flat.png'):
"""
Render a version of the scene with shading disabled and unique materials
assigned to all objects, and return a set of all colors that should be in the
rendered image. The image itself is written to path. This is used to ensure
that all objects will be visible in the final rendered scene.
"""
render_args = bpy.context.scene.render
# Cache the render args we are about to clobber
old_filepath = render_args.filepath
old_engine = render_args.engine
old_use_antialiasing = render_args.use_antialiasing
# Override some render settings to have flat shading
render_args.filepath = path
render_args.engine = 'BLENDER_RENDER'
render_args.use_antialiasing = False
# Move the lights and ground to layer 2 so they don't render
utils.set_layer(bpy.data.objects['Lamp_Key'], 2)
utils.set_layer(bpy.data.objects['Lamp_Fill'], 2)
utils.set_layer(bpy.data.objects['Lamp_Back'], 2)
utils.set_layer(bpy.data.objects['Ground'], 2)
# Add random shadeless materials to all objects
object_colors = set()
old_materials = []
for i, obj in enumerate(blender_objects):
old_materials.append(obj.data.materials[0])
bpy.ops.material.new()
mat = bpy.data.materials['Material']
mat.name = 'Material_%d' % i
while True:
r, g, b = [random.random() for _ in range(3)]
if (r, g, b) not in object_colors: break
object_colors.add((r, g, b))
mat.diffuse_color = [r, g, b]
mat.use_shadeless = True
obj.data.materials[0] = mat
# Render the scene
bpy.ops.render.render(write_still=True)
# Undo the above; first restore the materials to objects
for mat, obj in zip(old_materials, blender_objects):
obj.data.materials[0] = mat
# Move the lights and ground back to layer 0
utils.set_layer(bpy.data.objects['Lamp_Key'], 0)
utils.set_layer(bpy.data.objects['Lamp_Fill'], 0)
utils.set_layer(bpy.data.objects['Lamp_Back'], 0)
utils.set_layer(bpy.data.objects['Ground'], 0)
# Set the render settings back to what they were
render_args.filepath = old_filepath
render_args.engine = old_engine
render_args.use_antialiasing = old_use_antialiasing
return object_colors
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display_stats.py | rionbr/ddi-blumenau | 1 | 124620 | # coding=utf-8
# Author: <NAME>
# Date: Nov 16, 2014
#
# Description: Plot DDI Statistics
#
#
# coding=utf-8
from __future__ import division
import numpy as np
import pandas as pd
import scipy.stats
from scipy import stats
slice = pd.IndexSlice
pd.set_option('display.max_rows', 24)
pd.set_option('display.max_columns', 24)
pd.set_option('display.width', 300)
pd.set_option('display.precision', 2)
pd.set_option('display.float_format', lambda x: '%.2f' % x)
import util
from collections import OrderedDict
import math
def calc_conf_interval(r, **kwargs):
df = kwargs['n_runs']-1
mean = r.iloc[0]
std = r.iloc[1]
sigma = std/math.sqrt(n_runs)
(ci_min,ci_max) = stats.t.interval(alpha=0.95, df=n_runs-1, loc=mean, scale=sigma)
return pd.Series([ci_min, ci_max], index=['ci_min', 'ci_max'])
#
# Load CSVs
#
dfu, dfc, dfi = util.dfUsersInteractionsSummary(loadCoAdmin=False)
#dfig = dfi.groupby('id_user').agg({'n_drugs':'sum','n_ij_ddi':'sum','n_coadmin':'sum'})
dfd = pd.read_csv('results/dd_drugs.csv.gz', header=0, encoding='utf-8',
names=['id_user','DB_label','count','en_i'],
dtype={'id_user':np.int64})
print '>> dfu'
print dfu.head()
print dfu.shape
print '>> dfc'
print dfc.head()
print dfc.shape
print '>> dfi'
print dfi.head()
print dfi.shape
print '>> dfd'
print dfd.head()
print dfd.shape
dfiu = pd.merge(dfi, dfu[['gender','age','age_group']], how='left', left_on='id_user', right_index=True)
print '>> dfiu'
print dfiu.head()
print '--- --- ---'
#
# Removed Hormones
#
female_hormones = ['Ethinyl Estradiol','Estradiol','Norethisterone','Levonorgestrel','Estrogens Conj.']
dfiu_nh = dfiu.loc[ (~(dfiu['en_i'].isin(female_hormones)) & ~(dfiu['en_j'].isin(female_hormones)) ) , : ].reset_index(drop=True)
dfu['len_ij_ddi_not_hormone'] = dfiu_nh['len_ij_ddi']
dfiug_nh = dfiu_nh.groupby('id_user').agg({'len_ij_ddi':'sum','id_user':'count'})
dfu['n_ij_ddi_not_hormone'] = dfiug_nh['id_user']
print dfu.loc[ dfu['len_ij_ddi']>dfu['len_ij_ddi_not_hormone'], : ].head()
#
# Variables
#
n_user = len( dfu.index.unique() )
n_user_adult = len( dfu.loc[ (dfu['age']>=20), : ].index.unique() )
n_user_male = len( dfu.loc[ (dfu['gender']=='Male'), : ].index.unique() )
n_user_female = len( dfu.loc[ (dfu['gender']=='Female'), : ].index.unique() )
n_user_40p = len( dfu.loc[ ( (dfu['age']>=40) ), :].index.unique() )
n_user_65p = len( dfu.loc[ ( (dfu['age']>=66) ), :].index.unique() )
n_a = dfu['n_a'].sum()
n_i = dfd.groupby('DB_label').agg({'en_i':'first'}).shape[0]
n_i_inter = len(np.unique(dfi[['db_i','db_j']].values))
n_ij = dfu['n_ij'].sum()
n_ij_ddi = dfu['n_ij_ddi'].sum()
n_ij_ddi_unique = len( dfiu['db_ij'].unique() )
n_ij_ddi_unique_nh = len( dfiu_nh['db_ij'].unique() )
n_user_gt2drugs = len( dfu.loc[ (dfu['n_i']>1), : ].index.unique() )
n_user_gt1coadmin = len( dfu.loc[ (dfu['n_ij']>0), : ].index.unique() )
n_user_male_ij = len( dfu.loc[ ((dfu['gender']=='Male') & (dfu['n_ij']>0)), : ].index.unique() )
n_user_female_ij = len( dfu.loc[ ((dfu['gender']=='Female') & (dfu['n_ij']>0)), : ].index.unique() )
n_user_ij_ddi = len( dfu.loc[ (dfu['n_ij_ddi']>0), : ].index.unique() )
n_user_ij_ddi_major = len( dfiu.loc[ (dfiu['severity'].isin(['Major'])) , : ]['id_user'].unique() )
n_user_adult_ij_ddi = len( dfu.loc[ ((dfu['age']>=20) & (dfu['n_ij_ddi']>0)), : ].index.unique() )
n_user_adult_ij_ddi_major = len( dfiu.loc[ ((dfiu['age']>=20) & (dfiu['severity'].isin(['Major']))) , : ]['id_user'].unique() )
n_males_qt1inter = len( dfu.loc[ ((dfu['gender']=='Male') & (dfu['n_ij_ddi']>0)), : ].index.unique() )
n_females_qt1inter = len( dfu.loc[ ((dfu['gender']=='Female') & (dfu['n_ij_ddi']>0)), : ].index.unique() )
n_males_qt1inter_nh = len( dfu.loc[ ((dfu['gender']=='Male') & (dfu['n_ij_ddi_not_hormone']>0)), : ].index.unique() )
n_females_qt1inter_nh = len( dfu.loc[ ((dfu['gender']=='Female') & (dfu['n_ij_ddi_not_hormone']>0)), : ].index.unique() )
n_user_ij_ddi_40p = len( dfu.loc[ ((dfu['n_ij_ddi']>0) & (dfu['age']>=40) ), :].index.unique() )
n_user_ij_ddi_major_65p = len( dfiu.loc[ ((dfiu['age']>=66) & (dfiu['severity'].isin(['Major']))) , : ]['id_user'].unique() )
##
print '--- RRC/RRI direct computation ---'
p_female = n_user_female/n_user
p_male = n_user_male/n_user
print 'P(u^[F]) = {:,.4f}'.format( (p_female) )
print 'P(u^[M]) = {:,.4f}'.format( (p_male) )
print
RRCF = (n_user_female_ij/n_user_female)/(n_user_male_ij/n_user_male)
RRIF = (n_females_qt1inter/n_user_female)/(n_males_qt1inter/n_user_male)
print 'RRC^[F] = ( |U^[c,F]| / |U^[F]| ) / ( |U^[c,M]| / |U^[M]| ) = ({:,d} / {:,d}) / ({:,d}/{:,d}) = {:,.4f}'.format( n_user_female_ij,n_user_female,n_user_male_ij,n_user_male,RRCF )
print 'RRI^[F] = ( |U^[c,F]| / |U^[F]| ) / ( |U^[c,M]| / |U^[M]| ) = ({:,d} / {:,d}) / ({:,d}/{:,d}) = {:,.4f}'.format( n_females_qt1inter,n_user_female,n_males_qt1inter,n_user_male,RRIF )
#print 'P(u^{i*}) = No Hormones'
#p_iNHf = n_females_qt1inter_nh/n_user
#p_iNHm = n_males_qt1inter_nh/n_user
#print 'P(I*>0|g=F) / P(I*>0|g=F) = {:,.4f} / {:,.4f} = {:,.4f}'.format( (p_iNHf/p_f) , (p_iNHm/p_m) , (p_iNHf/p_f)/(p_iNHm/p_m) )
# Load BNU
dfBnu = util.BnuData(age_per_gender=False)
city_pop = int(dfBnu['population'].sum())
city_pop_males = int(dfBnu['males'].sum())
city_pop_females = int(dfBnu['females'].sum())
city_pop_adults = int(dfBnu.iloc[:,4:21].sum().sum())
# Load Censo
#dfCenso = util.dfCenso(age_per_gender=False)
#
# Overall Statistics
#
print '--- Overall Statistics ---'
print "Blumenau population: {:,d}".format(city_pop)
print "Blumenau Males: {:,d}".format(city_pop_males)
print "Blumenau Females: {:,d}".format(city_pop_females)
print
print "Pronto population: {:,d} ({:.2%} of Blumenau)".format(n_user, n_user/city_pop)
print "Pronto males: {:,d} ({:.2%})".format(n_user_male, n_user_male/n_user)
print "Pronto females: {:,d} ({:.2%})".format(n_user_female, n_user_female/n_user)
print
print "Pronto adults (>=20) {:,d}".format(n_user_adult)
print "Unique drugs: {:,d}".format(n_i)
print "Unique drugs involved in DDI: {:,d}".format(n_i_inter)
print "Drugs intervals dispensed: {:,d}".format(n_a)
print "Co-administrations: {:,d}".format(n_ij)
print "Interactions: {:,d} ({:.2%})".format(n_ij_ddi, n_ij_ddi/n_ij )
print "Unique DDI pairs: {:,d}".format(n_ij_ddi_unique)
print "Unique DDI pairs (not hormones): {:,d}".format(n_ij_ddi_unique_nh)
print "Patients with 2+ drugs dispensed: {:,d} ({:.2%})".format(n_user_gt2drugs, n_user_gt2drugs/n_user)
print
print "Patients with 1+ co-administration: {:,d} ({:.2%})".format(n_user_gt1coadmin, n_user_gt1coadmin/n_user)
print "Male patients with 1+ co-administration: {:,d}, ({:.2%})".format(n_user_male_ij , n_user_male_ij/n_user_gt1coadmin)
print "Female patients with 1+ co-administration: {:,d}, ({:.2%})".format(n_user_female_ij , n_user_female_ij/n_user_gt1coadmin)
print
print "Patients with 1+ DDI: {:,d} ({:.2%} Pronto, {:.2%} Bnu)".format(n_user_ij_ddi, n_user_ij_ddi/n_user, n_user_ij_ddi/city_pop)
print "Male patients with 1+ DDI: {:,d} ({:.2%})".format(n_males_qt1inter, n_males_qt1inter/n_user_ij_ddi)
print "Female patients with 1+ DDI: {:,d} ({:.2%})".format(n_females_qt1inter, n_females_qt1inter/n_user_ij_ddi)
print
print "Adults patients (20+) with 1+ DDI: {:,d} ({:.2%} Pronto Adults, {:.2%} Bnu Adults/{:.2%} Pronto, {:.2%} Bnu)".format(n_user_adult_ij_ddi, n_user_adult_ij_ddi/n_user_adult, n_user_adult_ij_ddi/city_pop_adults, n_user_adult_ij_ddi/n_user, n_user_adult_ij_ddi/city_pop)
print "Adult patients (20+) with 1+ MAJOR DDI: {:,d} ({:.2%} Pronto Adults, {:.2%} Bnu Adults/{:.2%} Pronto, {:.2%} Bnu)".format(n_user_adult_ij_ddi_major, n_user_adult_ij_ddi_major/n_user_adult, n_user_adult_ij_ddi_major/city_pop_adults, n_user_adult_ij_ddi_major/n_user, n_user_adult_ij_ddi_major/city_pop)
print "Elderly patients (40+) with 1+ DDI: {:,d} ({:.2%} of patients with DDI, {:.2%} of 40+ patients)".format(n_user_ij_ddi_40p, n_user_ij_ddi_40p/n_user_ij_ddi, n_user_ij_ddi_40p/n_user_40p)
print "Elderly patients (65+) with 1+ MAJOR DDI: {:,d} ({:.2%} of 65+ patients)".format(n_user_ij_ddi_major_65p, n_user_ij_ddi_major_65p/n_user_65p)
#
# Education Stats (everyone)
#
print 'Education (everyone)'
dfEdu = dfu['education'].value_counts().to_frame()
dfEdu.sort_index(inplace=True)
dfEdu['prob1'] = dfEdu['education'] / dfEdu['education'].sum()
dfEdu['cumsum1'] = dfEdu['prob1'].cumsum()
#dfEdu = dfEdu.iloc[:-1,:]
dfEdu['prob2'] = dfEdu['education'] / dfEdu.iloc[:-1,0].sum()
dfEdu['cumsum2'] = dfEdu['prob2'].cumsum()
print dfEdu.to_latex(escape=False)
print dfEdu.sum()
#
# Education stats (above 25 y-old)
#
print 'Education (>25 yld)'
dfEdu = dfu.loc[ dfu['age']>=25 , 'education'].value_counts().to_frame()
dfEdu.sort_index(inplace=True)
dfEdu['prob1'] = dfEdu['education'] / dfEdu['education'].sum()
dfEdu['cumsum1'] = dfEdu['prob1'].cumsum()
#dfEdu = dfEdu.iloc[:-1,:]
dfEdu['prob2'] = dfEdu['education'] / dfEdu.iloc[:-1,0].sum()
dfEdu['cumsum2'] = dfEdu['prob2'].cumsum()
print dfEdu.to_latex(escape=False)
print dfEdu.sum()
#
# Age (Just Patient age distribution, nothing more)
#
print 'Age (distribution)'
dfAge = dfu['age_group'].value_counts().to_frame().sort_index()
dfAge['prob'] = dfAge['age_group'] / dfAge['age_group'].sum()
dfAge['cumsum'] = dfAge['prob'].cumsum()
print dfAge
print dfAge.sum()
#
# DDI per Severity
#
print '--- DDI per Severity ---'
dfi_s = dfi.groupby('severity').agg({'inter':'count','id_user': pd.Series.nunique})
dfi_s.rename(columns={'inter':'n_ij_ddi','id_user':'users'}, inplace=True) # RENAME id_usuario to users
dfi_s['i_per'] = dfi_s['n_ij_ddi'] / dfi_s['n_ij_ddi'].sum() * 100
dfi_s['u_per-pronto'] = dfi_s['users'] / n_user * 100
dfi_s['u_per-pop'] = dfi_s['users'] / city_pop * 100
#dfi_s = dfi_s.rename(index={'NONE':'None'})
columns = ['n_ij_ddi','i_per','users','u_per-pronto','u_per-pop']
print dfi_s.to_latex(columns=columns)
print dfi_s.sum(axis=0)
## Print summing None and *
dfi_s_ = dfi_s
dfi_s_['severity_s'] = pd.Categorical(['Major','Moderate','Minor','None','None'], ordered=True)
dfi_s_ = dfi_s_.groupby('severity_s').agg(sum)
print dfi_s_.to_latex(columns=columns)
## Print only for adult population
dfiu_s = dfiu.loc[ (dfiu['age']>=20), : ].groupby('severity').agg({'id_user':pd.Series.nunique})
dfiu_s.rename(columns={'id_user':'users'}, inplace=True) # RENAME id_usuario to users
dfiu_s['u_per-pronto-adult'] = dfiu_s['users'] / n_user_adult * 100
print dfiu_s.to_latex()
#print dfiu_s.head()
dfiu_s_ = dfiu_s
dfiu_s_['severity_s'] = pd.Categorical(['Major','Moderate','Minor','None','None'], ordered=True)
dfiu_s_ = dfiu_s_.groupby('severity_s').agg(sum)
print dfiu_s_.to_latex()
## Print summing Major-Moderate and Moderate-Minor
dfi_ = dfi[['severity','inter','id_user']].copy()
dfi_['severity'] = dfi_['severity'].cat.add_categories(['MajorModerate','ModerateMinor'])
dfi_majmod = dfi_.copy()
dfi_modmin = dfi_.copy()
dfi_majmod.loc[ (dfi_majmod['severity'].isin(['Major','Moderate'])) , 'severity'] = 'MajorModerate'
dfi_modmin.loc[ (dfi_modmin['severity'].isin(['Moderate','Minor'])) , 'severity'] = 'ModerateMinor'
dfi_majmod_s = dfi_majmod.groupby('severity').agg({'inter':'count','id_user':pd.Series.nunique})
dfi_modmin_s = dfi_modmin.groupby('severity').agg({'inter':'count','id_user':pd.Series.nunique})
dfi_majmod_s.rename(columns={'inter':'n_ij_ddi','id_user':'users'}, inplace=True) # RENAME id_usuario to users
dfi_modmin_s.rename(columns={'inter':'n_ij_ddi','id_user':'users'}, inplace=True) # RENAME id_usuario to users
dfi_majmod_s['i_per'] = dfi_majmod_s['n_ij_ddi'] / dfi_majmod_s['n_ij_ddi'].sum()
dfi_majmod_s['u_per-pronto'] = dfi_majmod_s['users'] / n_user * 100
dfi_majmod_s['u_per-pop'] = dfi_majmod_s['users'] / city_pop * 100
dfi_modmin_s['i_per'] = dfi_modmin_s['n_ij_ddi'] / dfi_modmin_s['n_ij_ddi'].sum()
dfi_modmin_s['u_per-pronto'] = dfi_modmin_s['users'] / n_user * 100
dfi_modmin_s['u_per-pop'] = dfi_modmin_s['users'] / city_pop * 100
print dfi_majmod_s.to_latex(columns=columns)
print dfi_modmin_s.to_latex(columns=columns)
## Print summing Major-Moderate and Moderate-Minor only for ADULTs
dfi_ = dfiu.loc[ (dfiu['age']>=20) , ['severity','id_user']].copy()
dfi_['severity'] = dfi_['severity'].cat.add_categories(['MajorModerate','ModerateMinor'])
dfi_majmod = dfi_.copy()
dfi_modmin = dfi_.copy()
dfi_majmod.loc[ (dfi_majmod['severity'].isin(['Major','Moderate'])) , 'severity'] = 'MajorModerate'
dfi_modmin.loc[ (dfi_modmin['severity'].isin(['Moderate','Minor'])) , 'severity'] = 'ModerateMinor'
dfi_majmod_s = dfi_majmod.groupby('severity').agg({'id_user':pd.Series.nunique})
dfi_modmin_s = dfi_modmin.groupby('severity').agg({'id_user':pd.Series.nunique})
dfi_majmod_s.rename(columns={'id_user':'users'}, inplace=True)
dfi_modmin_s.rename(columns={'id_user':'users'}, inplace=True)
dfi_majmod_s['u_per-pronto-adult'] = dfi_majmod_s['users'] / n_user_adult * 100
dfi_modmin_s['u_per-pronto-adult'] = dfi_modmin_s['users'] / n_user_adult * 100
print dfi_majmod_s.to_latex()
print dfi_modmin_s.to_latex()
#
# DDI per Gender
#
print '--- DDI per Gender ---'
dfi_g = dfiu.groupby('gender').agg({'inter':'count','id_user': pd.Series.nunique})
dfi_g.rename(columns={'inter':'n_ij_ddi','id_user':'users'}, inplace=True) # RENAME id_usuario to users
dfi_g['i_per'] = dfi_g['n_ij_ddi'] / dfi_g['n_ij_ddi'].sum()
dfi_g['u_per-pronto'] = dfi_g['users'] / n_user * 100
dfi_g['u_per-pop'] = dfi_g['users'] / city_pop * 100
columns = ['n_ij_ddi','i_per','users','u_per-pronto','u_per-pop']
print dfi_g.to_latex(columns=columns)
print dfi_g.sum(axis=0)
#
# DDI per Age
#
print '--- DDI per Age ---'
dfu_y = dfu.loc[ (dfu['n_ij_ddi']>0) , : ].reset_index().groupby('age_group').agg({'n_ij_ddi':'sum','id_user':pd.Series.nunique})
dfu_y.rename(columns={'id_user':'n_u_ddi'}, inplace=True) # RENAME id_usuario to users
dfu_y['i_per'] = dfu_y['n_ij_ddi'] / dfu_y['n_ij_ddi'].sum()
dfu_y['u_per-pronto'] = dfu_y['n_u_ddi'] / n_user * 100
dfu_y['u_per-city'] = dfu_y['n_u_ddi'] / city_pop * 100
print dfu_y[['n_ij_ddi','i_per','n_u_ddi','u_per-pronto','u_per-city']].to_latex(escape=False)
print dfu_y.sum(axis=0)
# Print summing None and *
dfu_y = dfu_y.rename(index={'*':'NONE'}).rename(index={'NONE':'n/a'})
print dfu_y.groupby(dfu_y.index).agg(sum)[['n_ij_ddi','i_per','n_u_ddi','u_per-pronto','u_per-city']].to_latex(escape=False)
#
# RRC/RRI per Gender
#
pd.set_option('display.precision', 4)
pd.set_option('display.float_format', lambda x: '%.4f' % x)
print '--- RRC/RRI per Gender ---'
dfR_g = pd.concat([
dfu.reset_index().groupby('gender').agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u'}),
dfu.loc[ (dfu['n_i']>=2) , :].reset_index().groupby('gender', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{n2}'}),
dfu.loc[ (dfu['n_ij']>0) , :].reset_index().groupby('gender', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{c}'}),
dfu.loc[ (dfu['n_ij_ddi']>0) , :].reset_index().groupby('gender', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{i}'})
], axis=1)
dfR_g.to_csv('csv/gender.csv', encoding='utf-8')
dfR_g['RRC^{F}'] = (dfR_g['u^{c}'] / dfR_g['u']) / (dfR_g.loc['Male','u^{c}'] / dfR_g.loc['Male','u'])
dfR_g['RRI^{F}'] = (dfR_g['u^{i}'] / dfR_g['u']) / (dfR_g.loc['Male','u^{i}'] / dfR_g.loc['Male','u'])
print dfR_g.to_latex(escape=False)
#
# RRC/RRI per Severity and Gender
#
print '--- RRC/RRI per Severity & Gender ---'
dfR_gs = dfiu.groupby(['gender','severity']).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u'})
dfR_gs = dfR_gs.unstack(level=0)
dfR_gs.columns = ['%s^{i,%s}_{s}' % (i,j[0]) for i,j in dfR_gs.columns.values]
dfR_gs['RRI^{F}_{s}'] = (dfR_gs['u^{i,F}_{s}'] / n_user_female) / ( dfR_gs['u^{i,M}_{s}'] / n_user_male)
print dfR_gs.to_latex(escape=False)
#
# RRC/RRI per Age
#
print '--- RRC/RRI per Age ---'
dfR_y = pd.concat([
dfu.reset_index().groupby('age_group').agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u'}),
dfu.loc[ (dfu['n_i']>=2) , :].reset_index().groupby('age_group', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{n2}'}),
dfu.loc[ (dfu['n_ij']>0) , :].reset_index().groupby('age_group', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{c}'}),
dfu.loc[ (dfu['n_ij_ddi']>0) , :].reset_index().groupby('age_group', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{i}'})
], axis=1)
# Make Short Table (Concatenating edges values)
df00_89 = dfR_y.iloc[ 0:18, 0:4 ]
df00_89.index = df00_89.index.add_categories(['90+'])
df90_pl = dfR_y.iloc[ 18: , 0:4 ].sum(axis=0).to_frame(name='90+').T
dfRs_y = pd.concat([df00_89, df90_pl], axis=0)
dfR_y.to_csv('csv/age.csv', encoding='utf-8')
dfRs_y['RC^{y}'] = dfRs_y['u^{c}'] / dfRs_y['u^{n2}']
dfRs_y['RI^{y}'] = dfRs_y['u^{i}'] / dfRs_y['u^{c}']
print dfRs_y.to_latex(escape=False)
#dfRs_y.to_csv('csv/age_short.csv', encoding='utf-8')
#
# RRC/RRI per Age and Gender
#
print '--- RRC/RRI per Age and Gender ---'
dfR_gy_u = dfu.reset_index().groupby(['gender','age_group'], sort=False).agg({'id_user':pd.Series.nunique}).astype(np.int64)
dfR_gy_u.rename(columns={'id_user':'u'}, inplace=True)
dfR_gy_n = dfu.loc[ (dfu['n_i']>=2) , :].reset_index().groupby(['gender','age_group'], sort=False).agg({'id_user':pd.Series.nunique}).astype(np.int64)
dfR_gy_n.rename(columns={'id_user':'u^{n2}'}, inplace=True)
dfR_gy_c = dfu.loc[ (dfu['n_ij']>0) , :].reset_index().groupby(['gender','age_group'], sort=False).agg({'id_user':pd.Series.nunique}).astype(np.int64)
dfR_gy_c.rename(columns={'id_user':'u^{c}'}, inplace=True)
dfR_gy_i = dfu.loc[ (dfu['n_ij_ddi']>=1) , :].reset_index().groupby(['gender','age_group'], sort=False).agg({'id_user':pd.Series.nunique}).astype(np.int64)
dfR_gy_i.rename(columns={'id_user':'u^{i}'}, inplace=True)
for (gender,dftmp_u), (_,dftmp_n), (_, dftmp_c), (_,dftmp_i) in zip(dfR_gy_u.groupby(level=0), dfR_gy_n.groupby(level=0), dfR_gy_c.groupby(level=0), dfR_gy_i.groupby(level=0)):
print gender
dfR_gy = pd.concat([dftmp_u,dftmp_n,dftmp_c,dftmp_i], axis=1)
dfR_gy.index = dfR_gy.index.droplevel(level=0)
# Make Short Table (Concatenating edges values)
df00_89 = dfR_gy.iloc[ 0:18, 0:4 ]
df90_pl = dfR_gy.iloc[ 18: , 0:4 ].sum(axis=0).to_frame(name='90+').T
dfRs_gy = pd.concat([df00_89, df90_pl], axis=0)
dfR_gy.to_csv('csv/age_%s.csv' % (gender.lower()), encoding='utf-8')
dfRs_gy['RC^{y}'] = dfRs_gy['u^{c}'] / dfRs_gy['u^{n2}']
dfRs_gy['RI^{y}'] = dfRs_gy['u^{i}'] / dfRs_gy['u^{c}']
print dfRs_gy.to_latex(escape=False)
# Statistical Test Males and Females distribution per age are different
ui_gy_m = dfR_gy_i.loc[ slice['Male',:] , 'u^{i}'].values
ui_gy_f = dfR_gy_i.loc[ slice['Female',:] , 'u^{i}'].values
tstat, pvalue = stats.chisquare(ui_gy_f, f_exp=ui_gy_m)
print 'Chi Square the two samples are independent'
print 't-stat: {:.4f}, p-value: {:.4f}'.format(tstat, pvalue)
KS, pvalue = stats.ks_2samp(ui_gy_m, ui_gy_f)
print 'Kolmogorov-Sminov statistic two samples came from the same continuos distribution'
print 't-stat: {:.4f}, p-value: {:.4f}'.format(KS, pvalue)
#
# RRC/RRI per Number of Unique Drugs
#
dfR = pd.concat([
dfu.reset_index().groupby('n_i', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u'}),
dfu.loc[ (dfu['n_i']>=2) , :].reset_index().groupby('n_i', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{n2}'}),
dfu.loc[ (dfu['n_ij']>0) , :].reset_index().groupby('n_i', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{c}'}),
dfu.loc[ (dfu['n_ij_ddi']>=1) , :].reset_index().groupby('n_i', sort=False).agg({'id_user':pd.Series.nunique}).rename(columns={'id_user':'u^{i}'})
], axis=1).fillna(0).astype(np.int64)
# Make Short Table (Concatenating edges values)
df00_20 = dfR.iloc[ 0:20, 0:4 ]
df20_pl = dfR.iloc[ 20: , 0:4 ].sum(axis=0).to_frame(name='>20').T
dfRs = pd.concat([df00_20, df20_pl], axis=0)
dfRs['RRC^{y}'] = (dfRs['u^{c}'] / dfRs['u']) / (dfRs.loc[2,'u^{c}'] / dfRs.loc[2,'u'])
dfRs['RRI^{y}'] = (dfRs['u^{i}'] / dfRs['u']) / (dfRs.loc[2,'u^{i}'] / dfRs.loc[2,'u'])
# Don't forget to remove the extra zeros manually, Rion
print dfRs.to_latex(escape=False)
#
# RRI^g > x
#
dfR = pd.concat([
dfiu.loc[ (dfiu['gender']=='Male') , : ].groupby(['db_ij']).agg({'id_user':set}).rename(columns={'id_user':'set(u^{M})'}),
dfiu.loc[ (dfiu['gender']=='Female') , : ].groupby(['db_ij']).agg({'id_user':set}).rename(columns={'id_user':'set(u^{F})'}),
dfiu.groupby(['db_ij']).agg({'severity':'first','db_i':'first','db_j':'first'})
], axis=1, sort=False)
dfR[['set(u^{F})','set(u^{M})']] = dfR[['set(u^{F})','set(u^{M})']].applymap(lambda x:set([]) if isinstance(x,float) else x)
dfR['u^{i,M}'] = dfR['set(u^{M})'].apply(len)
dfR['u^{i,F}'] = dfR['set(u^{F})'].apply(len)
dfR['u^{i}'] = dfR.apply(lambda r:len(r['set(u^{M})'].union(r['set(u^{F})'])), axis=1)
dfR['RRI^{F}'] = (dfR['u^{i,F}'] / n_user_female) / (dfR['u^{i,M}'] / n_user_female)
dfR['RRI^{M}'] = (dfR['u^{i,M}'] / n_user_male) / (dfR['u^{i,F}'] / n_user_female)
print dfR.head()
us,ds = [],[]
for RRIgx in [1,2,3,4,5,6,7,8,9,10]:
n_i_female = len( np.unique( dfR.loc[ (dfR['RRI^{F}']>=RRIgx) , ['db_i','db_j'] ].values ) )
n_i_male = len( np.unique( dfR.loc[ (dfR['RRI^{M}']>=RRIgx) , ['db_i','db_j'] ].values ) )
n_ij_female = dfR.loc[ (dfR['RRI^{F}']>=RRIgx) , : ].shape[0]
n_ij_male = dfR.loc[ (dfR['RRI^{M}']>=RRIgx) , : ].shape[0]
n_ij_major_female = dfR.loc[ ((dfR['severity']=='Major') & (dfR['RRI^{F}']>=RRIgx)), : ].shape[0]
n_ij_major_male = dfR.loc[ ((dfR['severity']=='Major') & (dfR['RRI^{M}']>=RRIgx)), : ].shape[0]
ds.append( (RRIgx,n_i_female,n_i_male,n_ij_female,n_ij_male,n_ij_major_female,n_ij_major_male) )
n_user_minrri_female = len( set.union( *dfR.loc[ (dfR['RRI^{F}']>=RRIgx) , 'set(u^{F})'].tolist() ) )
n_user_minrri_male = len( set.union( *dfR.loc[ (dfR['RRI^{M}']>=RRIgx), 'set(u^{M})'].tolist() ) )
n_user_minrri_maj_female = len( set.union( *dfR.loc[ ((dfR['severity']=='Major') & (dfR['RRI^{F}']>=RRIgx)), 'set(u^{F})'].tolist() ) )
n_user_minrri_maj_male = len( set.union( *dfR.loc[ ((dfR['severity']=='Major') & (dfR['RRI^{M}']>=RRIgx)), 'set(u^{M})'].tolist() ) )
us.append( (RRIgx,n_user_minrri_female,n_user_minrri_male,n_user_minrri_maj_female,n_user_minrri_maj_male) )
dfRdr = pd.DataFrame(ds, columns=['RRI>x','d^{F}','d^{M}','ij^{F}','ij^{M}','ij^{F}_{maj}','ij^{M}_{maj}']).set_index('RRI>x')
dfRur = pd.DataFrame(us, columns=['RRI>x','u^{F}','u^{M}','u^{F}_{maj}','u^{M}_{maj}']).set_index('RRI>x')
dfRur['u^{F}-per'] = dfRur['u^{F}'] / n_user_female
dfRur['u^{M}-per'] = dfRur['u^{M}'] / n_user_male
dfRur['u^{F}_{maj}-per'] = dfRur['u^{F}_{maj}'] / n_user_female
dfRur['u^{M}_{maj}-per'] = dfRur['u^{M}_{maj}'] / n_user_male
print dfRdr.to_latex(escape=False)
print dfRur.to_latex(escape=False)
#
# Null Models - Age
# RI^{y}
#
pd.set_option('display.precision', 2)
pd.set_option('display.float_format', lambda x: '%.2f' % x)
dfN = pd.read_csv('csv/age_gender_null.csv', index_col=0, encoding='utf-8')
n_runs = dfN['run'].max()
dfN['u^{i}_{rnd}'] = dfN['u^{i,F}_{rnd}'] + dfN['u^{i,M}_{rnd}']
dfN = dfN.groupby('age_group').agg(OrderedDict([
('u',['mean']),
('u^{i}_{rnd}',['mean','std']),
]))
dfN.columns = ['-'.join(col).strip() for col in dfN.columns.values]
dfN00_89 = dfN.iloc[ 0:18, : ]
dfN90_pl = dfN.iloc[ 18: , : ].sum(axis=0).to_frame(name='90+').T
dfN = pd.concat([dfN00_89, dfN90_pl], axis=0)
dfN['RI^{y}_{rnd}'] = dfN['u^{i}_{rnd}-mean'] / dfR_y['u^{c}']
dfN[['u^{i}_{rnd}-ci_min','u^{i}_{rnd}-ci_max']] = dfN[['u^{i}_{rnd}-mean','u^{i}_{rnd}-std']].apply(calc_conf_interval, axis=1, n_runs=n_runs)
dfN['RI^{y}_{rnd}-ci_min'] = dfN['u^{i}_{rnd}-ci_min'] / dfR_y['u^{c}']
dfN['RI^{y}_{rnd}-ci_max'] = dfN['u^{i}_{rnd}-ci_max'] / dfR_y['u^{c}']
print dfN.to_latex(escape=False)
#
# Null Models - Age & Gender
# RI^{y,g}
dfN = pd.read_csv('csv/age_gender_null.csv', index_col=0, encoding='utf-8')
dfM = pd.read_csv('csv/age_male.csv', index_col=0, encoding='utf-8')
dfF = pd.read_csv('csv/age_female.csv', index_col=0, encoding='utf-8')
n_runs = dfN['run'].max()
dfN['u^{i}_{rnd}'] = dfN['u^{i,F}_{rnd}'] + dfN['u^{i,M}_{rnd}']
dfN = dfN.groupby('age_group').agg(OrderedDict([
('u',['mean']),
('u^{i}_{rnd}',['mean','std']),
('u^{i,F}_{rnd}',['mean','std']),
('u^{i,M}_{rnd}',['mean','std'])
]))
dfN.columns = ['-'.join(col).strip() for col in dfN.columns.values]
dfN['u'] = dfM['u'] + dfF['u']
dfN['u^{F}'] = dfF['u']
dfN['u^{M}'] = dfM['u']
dfN['u^{c,F}'] = dfF['u^{c}']
dfN['u^{c,M}'] = dfM['u^{c}']
dfN00_89 = dfN.iloc[ 0:18, : ]
dfN90_pl = dfN.iloc[ 18: , : ].sum(axis=0).to_frame(name='90+').T
dfN = pd.concat([dfN00_89, dfN90_pl], axis=0)
dfN['RI^{y,F}_{rnd}'] = dfN['u^{i,F}_{rnd}-mean'] / dfF['u^{c}']
dfN['RI^{y,M}_{rnd}'] = dfN['u^{i,M}_{rnd}-mean'] / dfM['u^{c}']
# Confidence Interval
dfN[['u^{i,F}_{rnd}-ci_min','u^{i,F}_{rnd}-ci_max']] = dfN[['u^{i,F}_{rnd}-mean','u^{i,F}_{rnd}-std']].apply(calc_conf_interval, axis=1, n_runs=n_runs)
dfN[['u^{i,M}_{rnd}-ci_min','u^{i,M}_{rnd}-ci_max']] = dfN[['u^{i,M}_{rnd}-mean','u^{i,M}_{rnd}-std']].apply(calc_conf_interval, axis=1, n_runs=n_runs)
dfN['RI^{y,F}_{rnd}-ci_min'] = dfN['u^{i,F}_{rnd}-ci_min'] / dfN['u^{c,F}']
dfN['RI^{y,F}_{rnd}-ci_max'] = dfN['u^{i,F}_{rnd}-ci_max'] / dfN['u^{c,F}']
dfN['RI^{y,M}_{rnd}-ci_min'] = dfN['u^{i,M}_{rnd}-ci_min'] / dfN['u^{c,M}']
dfN['RI^{y,M}_{rnd}-ci_max'] = dfN['u^{i,M}_{rnd}-ci_max'] / dfN['u^{c,M}']
print dfN.to_latex(escape=False)
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13,
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] |
composite/serializers.py | Skydipper/Composite | 0 | 112861 | """Serializers"""
import logging
def serialize_composite_output(analysis, type):
"""."""
return {
'id': None,
'type': type,
'attributes': {
'thumb_url': analysis.get('thumb_url', None),
'tile_url':analysis.get('tile_url', None),
'dem':analysis.get('dem', None),
'zonal_stats':analysis.get('zonal_stats', None)
}
} | [
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ex088.py | nascimentobrenda24/PythonExercises | 1 | 42031 | <filename>ex088.py
# Faça um programa que ajude um jogador da MEGA SENA a criar palpites. O programa vai perguntar quantos jogos serão
# gerados e vai sortear 6 números entre 1 e 60 para cada jogo, cadastrando tudo em uma lista composta.
from random import randint
games = []
temp = []
print('-'*30)
print(' JOGA NA MEGA SENA ')
print('-'*30)
q = int(input('Quantos jogos você quer que eu sortei? '))
tot = 1
while tot <= q:
cont = 0
while True:
num = randint(1, 60)
if num not in temp:
temp.append(num)
cont += 1
if cont >= 6:
break
temp.sort()
games.append(temp[:])
temp.clear()
tot += 1
print(f'=-'*3, f'SORTEANDO {q} JOGOS', '-='*3)
for i, l in enumerate(games):
print(f'Jogo {i+1}: {l}')
print('-='*5, 'BOA SORTE', '-='*5)
| [
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signuplogin/views.py | xflows/textflows | 18 | 46284 | <gh_stars>10-100
from django.contrib.auth.models import User
from django.contrib.auth import authenticate, login, logout
from django.shortcuts import render, get_object_or_404, redirect
from django.utils import timezone
def signuplogin(request):
if request.method == 'POST':
if request.POST.get('login'):
uname = request.POST['username']
passw = request.POST['password']
user = authenticate(username=uname, password=passw)
if user is not None:
login(request, user)
if not request.POST.get('remember', None):
request.session.set_expiry(0)
return ajaxresponse(request, 'OK')
else:
return ajaxresponse(request, 'ERR')
elif request.POST.get('register'):
uname = request.POST['rusername']
passw = request.POST['rpassword']
rpass = request.POST['repeat_password']
mail = request.POST['email']
try:
tuser = User.objects.get(username__exact=uname)
except User.DoesNotExist:
tuser = None
if User.objects.filter(email=mail).count()>0:
return ajaxresponse(request, 'MAILTAKEN')
if tuser is not None:
return ajaxresponse(request, 'TAKEN')
else:
new_user = User.objects.create_user(uname, mail, passw, last_login = timezone.now() )
user = authenticate(username=uname, password=passw)
login(request, user)
return ajaxresponse(request, 'OK')
else:
return render(request, 'signuplogin/signuplogin.html')
def ajaxresponse(request, txt):
return render(request, 'signuplogin/ajaxresponse.html', {'response':txt}) | [
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gridded/tests/test_ugrid/test_find_nodes.py | groutr/gridded | 49 | 51287 | <reponame>groutr/gridded
#!/usr/bin/env python
"""
Testing of code to find nodes.
Currently only nearest neighbor.
"""
from __future__ import (absolute_import, division, print_function)
import numpy as np
from .utilities import twenty_one_triangles
def test_locate_node(twenty_one_triangles):
"""Test finding a single node."""
ugrid = twenty_one_triangles
assert ugrid.locate_nodes((4.58, 5.08)) == 6
def test_locate_nodes(twenty_one_triangles):
"""Test finding multiple nodes at once."""
ugrid = twenty_one_triangles
assert np.array_equal(ugrid.locate_nodes(((4.58, 5.08),
(4.81, 0.89),
(6.43, 12.9),
(8.74, 6.86),
(5.12, 7.31),
)), (6, 0, 17, 10, 8))
def test_locate_exact(twenty_one_triangles):
"""
The nearest neighbor of the exact node locations had better be
the nodes!
"""
ugrid = twenty_one_triangles
assert np.array_equal(ugrid.locate_nodes(ugrid.nodes),
list(range(len(ugrid.nodes))))
def test_locate_middle(twenty_one_triangles):
"""See what happens the point is equidistant to two nodes."""
ugrid = twenty_one_triangles
# (3,5) is equidistant between nodes 2, 6 and 7
# 2 is returned, but might be arbitrary
# assert ugrid.locate_nodes( (3, 5) ) == 2
# Perturb the point a bit, and nearest changes to:
assert ugrid.locate_nodes((3.0000000001, 5)) == 6
assert ugrid.locate_nodes((3, 5.00000000001)) == 7
assert ugrid.locate_nodes((3, 4.99999999999)) == 2
if __name__ == '__main__':
test_locate_nodes()
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remoto/lib/__init__.py | ktdreyer/remoto | 0 | 90567 | """
This module is meant for vendorizing Python libraries. Most libraries will need
to have some ``sys.path`` alterations done unless they are doing relative
imports.
Do **not** add anything to this module that does not represent a vendorized
library.
Vendored libraries should go into the ``vendor`` directory and imported from
there. This is so we allow libraries that are installed normally to be imported
if the vendored module is not available.
The import dance here is done so that all other imports throught ceph-deploy
are kept the same regardless of where the module comes from.
The expected way to import execnet would look like this::
from remoto.lib import execnet
"""
import sys
import os
this_dir = os.path.abspath(os.path.dirname(__file__))
vendor_dir = os.path.join(this_dir, 'vendor')
try:
# vendored
if vendor_dir not in sys.path:
sys.path.insert(0, vendor_dir)
import execnet
except ImportError as err:
# normally installed
import execnet # noqa
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trlib/environments/wrappers/persistent_action_wrapper.py | albertometelli/pfqi | 2 | 111329 | <gh_stars>1-10
from gym.wrappers import TimeLimit
class PersistentActionWrapper(TimeLimit):
def __init__(self, env, persistence=1, gamma=1, max_episode_steps=None):
super(PersistentActionWrapper, self).__init__(env, max_episode_steps)
self.persistence = max(1, persistence)
self.gamma = gamma ** persistence
self.gamma_single_step = gamma
self._max_episode_single_steps = max_episode_steps
self.env._max_episode_steps = max_episode_steps
self._max_episode_steps = max_episode_steps // self.persistence + (max_episode_steps % self.persistence > 0)
def step(self, action):
cum_rew = 0.
remaining_single_steps = self._max_episode_single_steps - self._elapsed_single_steps
for i in range(min(self.persistence, remaining_single_steps)):
state, reward, done, info = self.env.step(action)
cum_rew += reward * self.gamma_single_step ** i
self._elapsed_single_steps += 1
if done:
break
# done is set to True by TimeLimit when the episode terminate due to the end of the horizon.
# We want done being set to True only when the environment set done to True.
if done and self._elapsed_single_steps == self._max_episode_single_steps:
done = False
self._elapsed_steps += 1
if self._elapsed_steps >= self._max_episode_steps:
info['PersistentActionWrapper.truncated'] = not done
return state, cum_rew, done, info
def reset(self, **kwargs):
self._elapsed_steps = 0
self._elapsed_single_steps = 0
return self.env.reset(**kwargs)
def render(self, mode='human'):
remaining_single_steps = self._max_episode_single_steps - self._elapsed_single_steps
for i in range(min(self.persistence, remaining_single_steps)):
super(PersistentActionWrapper, self).render(mode)
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post.py | strickyak/gforth-transpiler | 2 | 122326 | # Filter to normalize how floating point numbers are printed
# to clean up diffs between gforth and transpiler output.
#
# python post.py < output > normalized_output
import re, sys
SEARCH_FLOAT = re.compile(r'([-]?([0-9]+[.][0-9]*|[0-9]*[.][0-9]+)([eE][-]?[0-9]+)?)(.*)$').search
for line in sys.stdin:
done, rest = '', line.rstrip()
while rest:
m = SEARCH_FLOAT(rest)
if not m:
done += rest
break
start, end = m.start(1), m.end(1)
front, middle, back = rest[:start], rest[start:end], rest[end:]
done += front + ('%.15g' % float(m.group(1)))
rest = back
# print 'TRANFORM', m.group(1), ('%.15g' % float(m.group(1)))
print done
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koocook_core/tests/test_support/test_quantity.py | KooCook/koocook-dj | 1 | 188579 | <filename>koocook_core/tests/test_support/test_quantity.py
import unittest
from koocook_core.support import quantity, unit
class TestQuantity(unittest.TestCase):
int_amounts = tuple(range(20))
float_amounts = tuple(x / 8 for x in range(20))
amounts = int_amounts + float_amounts
def setUp(self) -> None:
self.quantity1 = quantity.parse_quantity('1/3 g')
self.quantity2 = quantity.parse_quantity('2/3 g')
self.quantity3 = quantity.parse_quantity('3 g')
self.quantity4 = quantity.parse_quantity('1 g')
self.quantity5 = quantity.parse_quantity('4 g')
self.quantity6 = quantity.parse_quantity('4/3 g')
def test_quantity_amount_can_be_int(self):
for amount in TestQuantity.int_amounts:
with self.subTest(amount=amount):
try:
quantity.Quantity(amount, unit.MassUnit.GRAM)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_quantity_amount_can_be_float(self):
for amount in TestQuantity.float_amounts:
with self.subTest(amount=amount):
try:
quantity.Quantity(amount, unit.MassUnit.GRAM)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_quantity_unit_can_be_Unit(self):
for U in unit.units:
for u in U:
with self.subTest(unit=u):
try:
quantity.Quantity(1, u)
quantity.Quantity(2., u)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_quantity_unit_can_be_str_symbol(self):
for U in unit.units:
for u in U:
with self.subTest(unit=u):
try:
quantity.Quantity(1, u.symbol)
quantity.Quantity(1.5, u.symbol)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_quantity_unit_can_be_str_plural(self):
for U in unit.units:
for u in U:
with self.subTest(unit=u):
try:
quantity.Quantity(0.5, u.plural)
quantity.Quantity(1.5, u.plural)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_quantity_unit_can_be_str_singular(self):
for U in unit.units:
for u in U:
with self.subTest(unit=u):
try:
quantity.Quantity(1, u.singular)
quantity.Quantity(1., u.singular)
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_parse_quantity_is_inverse_of_get_db_str(self):
for U in unit.units:
for u in U:
for amount in TestQuantity.amounts:
with self.subTest(amount=amount, unit=u):
try:
quantity.parse_quantity(quantity.Quantity(amount, u).get_db_str())
except ValueError as e:
raise self.failureException(f'test raised {e.__class__.__name__} unexpectedly') from e
def test_add_with_both_amount_are_fraction(self):
summation1 = self.quantity1 + self.quantity1
with self.subTest():
self.assertEqual(summation1, self.quantity2)
summation2 = self.quantity1 + self.quantity2
with self.subTest():
self.assertEqual(summation2, self.quantity4)
def test_add_with_both_amount_are_int(self):
summation = self.quantity3 + self.quantity4
self.assertEqual(summation, self.quantity5)
def test_add_fraction_with_int(self):
summation = self.quantity1 + self.quantity4
self.assertEqual(summation, self.quantity6)
def test_add_with_different_unit(self):
summation = quantity.parse_quantity('0.002 kg') + self.quantity4
self.assertEqual(summation, quantity.parse_quantity('0.003 kg'))
def test_with_same_quantity_many_times(self):
result = quantity.Quantity.mul_quantity(self.quantity1, self.quantity3)
self.assertEqual(result, self.quantity4)
def test_with_mul_same_unit(self):
result = self.quantity1 * self.quantity3
self.assertEqual(result, self.quantity4)
def test_with_mul_different_unit(self):
result = self.quantity4 * quantity.parse_quantity('3000 mg')
self.assertEqual(result, self.quantity3)
def test_with_div_same_unit(self):
result = self.quantity6 / self.quantity3
self.assertEqual(result, quantity.parse_quantity('4/9 g'))
def test_with_div_different_unit(self):
result = self.quantity5 / quantity.parse_quantity('2000 mg')
self.assertEqual(result, quantity.parse_quantity('2 g'))
def test_change_quantity_to_decimal(self):
with self.subTest():
self.assertEqual(self.quantity4.decimal, '1.0 gram')
self.assertEqual(self.quantity3.decimal, '3.0 grams')
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PyFlow/ConfigManager.py | luzpaz/PyFlow | 1,463 | 1612332 | ## Copyright 2015-2019 <NAME>, <NAME>
## Licensed 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.
import os
import json
from Qt import QtCore, QtGui
from PyFlow.Core.Common import *
from PyFlow.Input import InputAction, InputManager, InputActionType
@SingletonDecorator
class ConfigManager(object):
"""Responsible for registering configuration files, reading/writing values to registered config files by aliases, providing QSettings from registered aliases."""
CONFIGS_STORAGE = {}
CONFIGS_DIR = os.path.join(os.path.abspath(os.path.dirname(__file__)), "Configs")
INPUT_CONFIG_PATH = os.path.join(CONFIGS_DIR, "input.json")
def __init__(self, *args, **kwargs):
self.registerConfigFile("PREFS", os.path.join(self.CONFIGS_DIR, "prefs.ini"))
self.registerConfigFile("APP_STATE", os.path.join(self.CONFIGS_DIR, "config.ini"))
if not os.path.exists(self.INPUT_CONFIG_PATH):
self.createDefaultInput()
data = InputManager().serialize()
if not os.path.exists(os.path.dirname(self.INPUT_CONFIG_PATH)):
os.makedirs(os.path.dirname(self.INPUT_CONFIG_PATH))
with open(self.INPUT_CONFIG_PATH, "w") as f:
json.dump(data, f)
else:
with open(self.INPUT_CONFIG_PATH, "r") as f:
data = json.load(f)
InputManager().loadFromData(data)
@staticmethod
def shouldRedirectOutput():
return ConfigManager().getPrefsValue("PREFS", "General/RedirectOutput") == "true"
def registerConfigFile(self, alias, absPath):
if alias not in self.CONFIGS_STORAGE:
self.CONFIGS_STORAGE[alias] = absPath
return True
return False
def getSettings(self, alias):
if alias in self.CONFIGS_STORAGE:
settings = QtCore.QSettings(self.CONFIGS_STORAGE[alias], QtCore.QSettings.IniFormat)
return settings
def getPrefsValue(self, configAlias, valueKey):
settings = self.getSettings(configAlias)
if settings:
if settings.contains(valueKey):
return settings.value(valueKey)
def createDefaultInput(self):
InputManager().registerAction(InputAction(name="Canvas.Pan", actionType=InputActionType.Mouse, group="Navigation", mouse=QtCore.Qt.MouseButton.MiddleButton))
InputManager().registerAction(InputAction(name="Canvas.Pan", actionType=InputActionType.Mouse, group="Navigation", mouse=QtCore.Qt.MouseButton.LeftButton, modifiers=QtCore.Qt.AltModifier))
InputManager().registerAction(InputAction(name="Canvas.Zoom", actionType=InputActionType.Mouse, group="Navigation", mouse=QtCore.Qt.MouseButton.RightButton))
InputManager().registerAction(InputAction(name="Canvas.FrameSelected", actionType=InputActionType.Keyboard, group="Navigation", key=QtCore.Qt.Key_F))
InputManager().registerAction(InputAction(name="Canvas.FrameAll", actionType=InputActionType.Keyboard, group="Navigation", key=QtCore.Qt.Key_H))
InputManager().registerAction(InputAction(name="Canvas.ZoomIn", actionType=InputActionType.Keyboard, group="Navigation", key=QtCore.Qt.Key_Equal, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.ZoomOut", actionType=InputActionType.Keyboard, group="Navigation", key=QtCore.Qt.Key_Minus, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.ResetScale", actionType=InputActionType.Keyboard, group="Navigation", key=QtCore.Qt.Key_R, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.AlignLeft", actionType=InputActionType.Keyboard, group="Refactoring", modifiers=QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier, key=QtCore.Qt.Key_Left))
InputManager().registerAction(InputAction(name="Canvas.AlignTop", actionType=InputActionType.Keyboard, group="Refactoring", modifiers=QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier, key=QtCore.Qt.Key_Up))
InputManager().registerAction(InputAction(name="Canvas.AlignRight", actionType=InputActionType.Keyboard, group="Refactoring", modifiers=QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier, key=QtCore.Qt.Key_Right))
InputManager().registerAction(InputAction(name="Canvas.AlignBottom", actionType=InputActionType.Keyboard, group="Refactoring", modifiers=QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier, key=QtCore.Qt.Key_Down))
InputManager().registerAction(InputAction(name="Canvas.Undo", actionType=InputActionType.Keyboard, group="Editing", modifiers=QtCore.Qt.ControlModifier, key=QtCore.Qt.Key_Z))
InputManager().registerAction(InputAction(name="Canvas.Redo", actionType=InputActionType.Keyboard, group="Editing", modifiers=QtCore.Qt.ControlModifier, key=QtCore.Qt.Key_Y))
InputManager().registerAction(InputAction(name="Canvas.KillSelected", actionType=InputActionType.Keyboard, group="Editing", key=QtCore.Qt.Key_Delete))
InputManager().registerAction(InputAction(name="Canvas.CopyNodes", actionType=InputActionType.Keyboard, group="Editing", key=QtCore.Qt.Key_C, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.CutNodes", actionType=InputActionType.Keyboard, group="Editing", key=QtCore.Qt.Key_X, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.DragCopyNodes", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.LeftButton, modifiers=QtCore.Qt.AltModifier))
InputManager().registerAction(InputAction(name="Canvas.DragCopyNodes", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.MiddleButton, modifiers=QtCore.Qt.AltModifier))
InputManager().registerAction(InputAction(name="Canvas.DragNodes", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.MiddleButton))
InputManager().registerAction(InputAction(name="Canvas.DragNodes", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.LeftButton))
InputManager().registerAction(InputAction(name="Canvas.DragChainedNodes", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.MiddleButton))
InputManager().registerAction(InputAction(name="Canvas.PasteNodes", actionType=InputActionType.Keyboard, group="Editing", key=QtCore.Qt.Key_V, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.DuplicateNodes", actionType=InputActionType.Keyboard, group="Editing", key=QtCore.Qt.Key_D, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="Canvas.DisconnectPin", actionType=InputActionType.Mouse, group="Editing", mouse=QtCore.Qt.MouseButton.LeftButton, modifiers=QtCore.Qt.AltModifier))
InputManager().registerAction(InputAction(name="App.NewFile", actionType=InputActionType.Keyboard, group="IO", key=QtCore.Qt.Key_N, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="App.Save", actionType=InputActionType.Keyboard, group="IO", key=QtCore.Qt.Key_S, modifiers=QtCore.Qt.ControlModifier))
InputManager().registerAction(InputAction(name="App.SaveAs", actionType=InputActionType.Keyboard, group="IO", key=QtCore.Qt.Key_S, modifiers=QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier))
InputManager().registerAction(InputAction(name="App.Load", actionType=InputActionType.Keyboard, group="IO", key=QtCore.Qt.Key_O, modifiers=QtCore.Qt.ControlModifier))
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extraResources/electron-backend/routes/delete_toa_entry.py | vilaj46/ad1-ad2-briefs | 0 | 55884 | <reponame>vilaj46/ad1-ad2-briefs
from classes.Table_Of_Authorities import get_my_toa
def delete_toa_entry(IDNumber):
TABLE_OF_AUTHORITIES = get_my_toa()
old_entries = TABLE_OF_AUTHORITIES.data['entries']
index = TABLE_OF_AUTHORITIES.find_index_with_IDNumber(IDNumber)
if str(index) != 'False':
new_entries = old_entries[0:index] + \
old_entries[index + 1:len(old_entries)]
TABLE_OF_AUTHORITIES.set_entries(new_entries)
TABLE_OF_AUTHORITIES.set_entries_to_one()
TABLE_OF_AUTHORITIES.check_entries_for_errors()
return {
'entries': new_entries,
'toaEntriesError': TABLE_OF_AUTHORITIES.data['toaEntriesError'],
'toaNumbersError': TABLE_OF_AUTHORITIES.data['toaNumbersError']
}
else:
TABLE_OF_AUTHORITIES.set_entries_to_one()
return 'Something went wrong.', 404
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Class10_Test.py | Kiran1178/Python201901 | 0 | 164058 | # # ###
# #
# letter = input ("Please enter a letter:\n")
# if (letter == 'i'):
# print ("am lettera vowela")
# elif (letter== 'a'):
# print("am lettera vowela")
# if (letter == 'u'):
# print ("am lettera vowela")
# elif (letter== 'e'):
# print("am lettera vowela")
# if (letter == 'o'):
# print('am lettera vowela')
# else:
# print("am lettera vowela nye")
#
# if (letter=='i') | (letter=='a')|(letter=='u')|(letter=='e'):
# print('am lettera vowela')
# else:
# print('am lettera vowela')
# txt="Hello i have a Aieroplane"
# x=txt.split("hello", "i have a Aieroplane")
# print(x)
# #
# for i in v:
# if(i=='a' or i=='e' or i=='i' or i=='o' or i=='u'):
#
# print('i')
# print('e')
# print('a')
#
#
# n=int(input("enter the number:"))
# temp=n
# rev=0
# while(n>0):
# dig=n%10
# rev=rev*10+dig
# n=n//10
# if(temp==rev):
# print("The number is a palindrome!")
# else:
# print("The number is not a palindrome!")
#
# NUMBERS = ["zero", "one", "two","three","four","five","six","seven","eight","nine",
# "ten"]
# TENS = ["", "", "twenty", "thirty", "forty", "fifty", "sixty", "seventy", "eighty",
# "ninety"]
# HUNNITS = ["","hundred","thousand","million","billion","trillion"]
#
# n = eval(input("What is the number the you want to convert? "))
# def convert():
# if n >= 20:
# tens = n // 10
# units = n % 10
#
# if units != 0:
# result = TENS[tens] + "-" + NUMBERS[units]
# else:
# result = TENS[tens]
# else:
# result = NUMBERS[n]
#
# print (result)
#
# def convert2():
# if n >=100:
# tens2 = n//100
# units2 = n%100
#
# if units2 != 0:
# result2 = HUNNITS[tens2] + "-" + TENS[tens2] + "and" + NUMBERS[units2]
# else:
# result2 = HUNNITS[tens2]
# else:
# result2 = HUNNITS[n]
#
# print(result2)
# def main():
# if n >=20 and n< 100:
# x = convert()
# if n >=100:
# y = convert2()
#
# main()
def check_vowels():
input_str = input("Enter string: ")
str_without_space = input_str.replace(' ', '')
if len([char for char in str_without_space if char in ['a', 'e', 'i', 'o', 'u']]) == len(input_str):
print("input contains all the vowels")
else:
print("string does not have all the vowels")
#
def check_palindrom():
num = input("Enter number")
if num == num[::-1]:
print("input is palindrome")
else:
print("input is not a palindrome")
check_palindrom()
#
def convert_Number_to_words():
dicto = {'0': 'zero', '1': 'one', '2': 'two', '3': 'three', '4': 'four', '5': 'five', '6': 'six', '7': 'seven', '8': 'eight', '9':'nine'}
num = input("Enter number: ")
try:
for item in list(str(num)):
print(dicto[item], end=' ')
except KeyError:
raise ("Invalid input")
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linter.py | Adarma/SublimeLinter-contrib-dxl | 1 | 87650 | <reponame>Adarma/SublimeLinter-contrib-dxl
#
# linter.py
# Linter for SublimeLinter, a code checking framework for Sublime Text 3
#
# Written by <NAME>
# Copyright (c) 2014 <NAME>
#
# License: MIT
#
"""This module exports the Dxl plugin class."""
from SublimeLinter.lint import Linter, util
from os.path import abspath, dirname, join, isfile
def LinterPath():
"""Ascertain the dxl.exe path from this .py files path because sublime.packages_path is unavailable at startup."""
ThisPath = abspath(dirname(__file__))
if isfile(ThisPath):
# We are in a .sublime-package file in the 'Installed Package' folder
return abspath(join(ThisPath, '..', '..', 'Packages', 'DXL', 'Lint', 'dxl.exe'))
else:
# We are in a subfolder of the 'Packages' folder
return abspath(join(ThisPath, '..', 'DXL', 'Lint', 'dxl.exe'))
LINTER_PATH = LinterPath()
class Dxl(Linter):
"""Provides an interface to dxl."""
defaults = {
'selector': 'source.dxl'
}
cmd = [LINTER_PATH]
regex = (
r'^-(?:(?P<error>E)|(?P<warning>W))- DXL:'
r' <(?P<path>.*?):(?P<line>[0-9]+)> '
r'''(?P<message>(?:undeclared variable|badly formed token|incorrect arguments? for(?: function)|Invalid '//<Requires>' syntax: Expected '#include '|could not (?:open|run) include file) \((?P<near>.*?)\).*|.*)'''
)
tempfile_suffix = 'dxl'
error_stream = util.STREAM_STDOUT
| [
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metameasure/test_metameasure.py | analyticsdept/py-metameasure | 0 | 198545 | <gh_stars>0
from metameasure import MetaMeasure
import unittest
class TestMetaMeasure(unittest.TestCase):
def setUp(self):
self.m = MetaMeasure(max_size_bytes=10000, reset_when_threshold_exceeded=True)
def test_byte_measure(self):
d = {}
self.assertEqual(self.m.measure(d), 64)
def test_max_bytes(self):
self.assertEqual(self.m.max_size_bytes, 10000)
def test_reset_when_threshold_exceeded(self):
self.assertEqual(self.m.reset_when_threshold_exceeded, True)
def test_kb_to_bytes(self):
expected = 1000
self.assertEqual(expected, self.m.bytes(kb=1))
def test_mb_to_bytes(self):
expected = 1000000
self.assertEqual(expected, self.m.bytes(mb=1))
def test_gb_to_bytes(self):
expected = 1000000000
self.assertEqual(expected, self.m.bytes(gb=1))
def test_tb_to_bytes(self):
expected = 1000000000000
self.assertEqual(expected, self.m.bytes(tb=1))
if __name__ == "__main__":
unittest.main() | [
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tests/io/test_hdf.py | lepy/sdata | 1 | 111542 | <filename>tests/io/test_hdf.py
import sys
import os
import pandas as pd
modulepath = os.path.dirname(__file__)
sys.path.insert(0, os.path.join(modulepath, "..", "..", "..", "src"))
import sdata
import uuid
from sdata.io.hdf import FlatHDFDataStore
def test_flathdfstore():
store = FlatHDFDataStore("/tmp/flatstore1.h5", mode="w")
print(store)
assert len(store.keys())==0
data = sdata.Data(name="otto",
uuid=sdata.uuid_from_str("otto"),
table=pd.DataFrame({"a": [1, 2, 3]}),
description="Hallo\nSpencer")
store.put(data)
print(store.keys())
datac = data.copy()
datac.name = "otto2"
datac.uuid = 'b8315be85d9945579cf8dc6a80a62524'
datac.df["b"] = datac.df["a"] ** 2
datac.df
datac.metadata.add("force", 1.23, dtype="float", description="a force", label="F")
datac.metadata.add("runid", 123, dtype="int", description="a int", label="r")
print(datac)
store.put(datac)
store.keys()
ldata = store.get_data_by_uuid(data.uuid)
assert data.sha3_256 == ldata.sha3_256
ldatac = store.get_data_by_uuid('b8315be85d9945579cf8dc6a80a62524')
print(datac)
ldatac.metadata.df
print([ldatac.description])
print(ldatac.describe())
assert datac.sha3_256 == ldatac.sha3_256
store.close()
def test_flatstoreexample():
store = FlatHDFDataStore(filepath="/tmp/mystoreexample.h5")
data = sdata.Data(name="otto",
uuid="d4e97cedca6238bea16732ce88c1922f",
table=pd.DataFrame({"a": [1, 2, 3]}),
description="Hallo\nSpencer")
store.put(data)
loaded_data = store.get_data_by_uuid("d4e97cedca6238bea16732ce88c1922f")
assert data.sha3_256 == loaded_data.sha3_256
store.close() | [
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] |
linearmodels/tests/panel/results/parse_stata_results.py | clarityai-eng/linearmodels | 0 | 65337 | <filename>linearmodels/tests/panel/results/parse_stata_results.py
from io import StringIO
import os
from typing import List
import pandas as pd
from linearmodels.shared.utility import AttrDict
filename = "stata-panel-simulated-results.txt"
cwd = os.path.split(os.path.abspath(__file__))[0]
blocks = {}
block: List[str] = []
key = ""
with open(os.path.join(cwd, filename)) as results:
for line in results.readlines():
line = line.strip()
if not line:
continue
if "###!" in line:
if key:
blocks[key] = block
block = []
key = line.split("!")[1]
block.append(line)
if block:
blocks[key] = block
def parse_block(block):
params = {}
stats = {}
for i, line in enumerate(block):
if "b/t" in line:
params_start = i + 1
if "rss" in line:
stats_start = i
if "** Variance **" in line:
variance_start = i + 1
for i in range(params_start, stats_start, 3):
name, value = block[i].split("\t")
value = float(value)
tstat = float(block[i + 1])
pvalue = float(block[i + 1])
params[name] = pd.Series({"param": value, "tstat": tstat, "pvalue": pvalue})
params = pd.DataFrame(params).sort_index()
for i in range(stats_start, variance_start - 1):
if "\t" in block[i]:
name, value = block[i].split("\t")
stats[name] = float(value)
else:
stats[block[i]] = None
stats = pd.Series(stats)
var = "\n".join(block[variance_start + 1 :])
variance = pd.read_csv(StringIO("," + var.replace("\t", ",")))
index = variance.pop(variance.columns[0])
index.name = None
variance.index = index
out = AttrDict(variance=variance, params=params.T)
for key in stats.index:
out[key] = stats.loc[key]
return out
def data():
data_blocks = {}
for key in blocks:
data_blocks[key] = parse_block(blocks[key])
return data_blocks
if __name__ == "__main__":
print(data())
| [
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] |
Controller/controleTelas.py | IuriBritoDev/TKINO | 0 | 34715 | from View import telaRelatorio, telaNovoProjeto, telaAbrirProjeto, telaCadastro, telaConfigura, telaConexao, telaEditarControle, telaPopUp
from View.Painel import painelSensores, painelControladores, painelConexao
from View.Conexao import telaConAnalogAnalog, telaConAnalogDigit, telaConDigitAnalog, telaConDigitDigit
# Abre as telas da aba de seleção
def AbreTelaNovoProjeto(tela):
telaNovoProjeto.TelaNovoProjeto(tela)
def AbreTelaAbrirProjeto(tela):
telaAbrirProjeto.TelaAbrirProjeto(tela)
def AbreTelaRelatorio(tela):
telaRelatorio.TelaRelatorio(tela)
def AbreTelaCadastro(tela):
telaCadastro.TelaCadastro(tela)
def AbreTelaConfigura(tela):
telaConfigura.TelaConfigura(tela)
def AbreTelaConexao(tela):
telaConexao.TelaConexao(tela)
# Abre telas de conexões de atuadores
def AbreTelaConAnAn(tela):
telaConAnalogAnalog.TelaConAnalogAnalog(tela)
def AbreTelaConAnDig(tela):
telaConAnalogDigit.TelaConAnalogDig(tela)
def AbreTelaConDigAn(tela):
telaConDigitAnalog.TelaConDigAnalog(tela)
def AbreTelaConDigDig(tela):
telaConDigitDigit.TelaConDigDig(tela)
# Abre os frames das abas
def AbreFrameSensores(frame):
painelSensores.PainelSensores(frame)
def AbreFrameControladores(frame, tela):
painelControladores.PainelControladores(frame, tela)
def AbreFrameConexao(frame, tela):
painelConexao.PainelConexao(frame, tela)
# Abre telas de edição da conexão e controladores
def AbreEditorControlador(tela, controle):
telaEditarControle.TelaEditarControle(tela, controle)
# Abre telas de PopUP
def AbrePopUp(tela, mensagem):
telaPopUp.TelaPopUp(tela, mensagem) | [
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] |
exercises/part2/common-architectures/attention_setup.py | jacobdanovitch/allennlp-guide | 0 | 101328 | import torch
from allennlp.modules.attention import (
DotProductAttention,
BilinearAttention,
LinearAttention,
)
from allennlp.modules.matrix_attention import (
DotProductMatrixAttention,
BilinearMatrixAttention,
LinearMatrixAttention,
)
from allennlp.nn import Activation
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