text string | size int64 | token_count int64 |
|---|---|---|
__author__ = 'Danny Goodall'
| 29 | 12 |
import matplotlib.pyplot as plt
import os
import numpy as np
from datetime import datetime
from matplotlib.backends.backend_pdf import PdfPages
from emma.io.traceset import TraceSet
from emma.utils.utils import MaxPlotsReached, EMMAException
#plt.rcParams['axes.prop_cycle'] = plt.cycler(color=plt.get_cmap('flag').colors) # Use different cycling colors
#plt.style.use('bmh') # Use different style
def plt_save_pdf(path):
"""
Save plot as pdf to path
:param path:
:return:
"""
pp = PdfPages(path)
pp.savefig(dpi=300)
pp.close()
plt.clf()
plt.cla()
def plot_spectogram(trace_set,
sample_rate,
nfft=2**10,
noverlap=0,
cmap='plasma',
params=None,
num_traces=1024):
if not trace_set.windowed:
raise EMMAException("Trace set should be windowed")
# Check params
if params is not None:
if len(params) == 1:
nfft = int(params[0])
elif len(params) == 2:
nfft = int(params[0])
noverlap = int(nfft * int(params[1]) / 100.0)
all_signals = np.array([trace.signal for trace in trace_set.traces[0:num_traces]]).flatten()
"""
# Old style
for trace in trace_set.traces[0:num_traces]:
plt.specgram(trace.signal, NFFT=nfft, Fs=sample_rate, noverlap=noverlap, cmap=cmap)
"""
plt.specgram(all_signals, NFFT=nfft, Fs=sample_rate, noverlap=noverlap, cmap=cmap, mode='psd', scale='dB')
plt.tight_layout()
plt.show()
def plot_colormap(inputs,
show=True,
cmap='inferno',
draw_axis=True,
title='',
xlabel='',
ylabel='',
colorbar_label='',
save=False,
**kwargs):
"""
Plot signals given in the inputs numpy array in a colormap.
:param inputs:
:param show:
:param cmap:
:param draw_axis:
:param title:
:param cmap:
:param xlabel:
:param ylabel:
:param colorbar_label:
:param save:
:param kwargs:
:return:
"""
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
if inputs.dtype == np.complex64 or inputs.dtype == np.complex128:
inputs = np.real(inputs)
print("Warning: converting colormap to np.real(complex)")
#inputs += 0.01
vmin = inputs.min()
vmax = inputs.max()
colorplot = plt.imshow(inputs,
vmin=vmin,
vmax=vmax,
interpolation='nearest',
# norm=LogNorm(vmin=vmin, vmax=vmax),
cmap=cmap,
**kwargs)
if draw_axis:
# https://stackoverflow.com/questions/18195758/set-matplotlib-colorbar-size-to-match-graph
from mpl_toolkits.axes_grid1 import make_axes_locatable
axis = plt.gca()
figure = plt.gcf()
divider = make_axes_locatable(axis)
cax = divider.append_axes("right", size="5%", pad=0.05)
cbar = figure.colorbar(colorplot, cax=cax)
cbar.set_label(colorbar_label)
plt.tight_layout()
if save:
if title:
plt_save_pdf('/tmp/%s.pdf' % title)
else:
plt_save_pdf('/tmp/%s.pdf' % str(datetime.now()))
if show:
plt.show()
def _get_x_axis_values(signal, time_domain=True, sample_rate=1.0):
if not time_domain:
freqs = np.fft.fftfreq(len(signal), d=1.0/sample_rate)
x = np.fft.fftshift(freqs)
else:
x = range(0, len(signal))
return x
def plot_trace_sets(reference_signal,
trace_sets,
params=None,
no_reference_plot=False,
num_traces=1024,
title='',
xlabel='',
ylabel='',
colorbar_label='',
time_domain=True,
sample_rate=1.0):
"""
Plot num_traces signals from a list of trace sets using matplotlib
"""
saveplot = False
colormap = False
# Check params
if params is not None:
if len(params) >= 1:
if 'save' in params:
saveplot = True
if '2d' in params:
colormap = True
if not isinstance(trace_sets, list) or isinstance(trace_sets, TraceSet):
raise ValueError("Expected list of TraceSets")
if len(trace_sets) == 0:
return
# Make title
common_path = os.path.commonprefix([trace_set.name for trace_set in trace_sets])
if title == '':
title = "%d trace sets from %s" % (len(trace_sets), common_path)
if reference_signal.dtype == np.complex64 or reference_signal.dtype == np.complex128:
title += " (complex, only real values plotted)"
# Make plots
count = 0
all_signals = []
try:
for trace_set in trace_sets:
for trace in trace_set.traces:
all_signals.append(trace.signal)
count += 1
if count >= num_traces:
raise MaxPlotsReached
except MaxPlotsReached:
pass
finally:
if xlabel == '':
if time_domain:
xlabel = 'Samples'
else:
xlabel = 'Frequency (assuming sample rate %.2f)' % sample_rate
if colormap:
plot_colormap(np.array(all_signals),
show=False,
title=title,
xlabel=xlabel,
ylabel=ylabel,
colorbar_label=colorbar_label)
else:
plt.title(title)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
for signal in all_signals:
x = _get_x_axis_values(signal, sample_rate=sample_rate, time_domain=time_domain)
plt.plot(x, signal)
if not no_reference_plot:
x = _get_x_axis_values(reference_signal, sample_rate=sample_rate, time_domain=time_domain)
plt.plot(x, reference_signal, linewidth=2, linestyle='dashed')
if saveplot:
plt_save_pdf('/tmp/plotted_trace_sets.pdf')
plt.clf()
else:
plt.show()
def plot_correlations(values1, values2, label1="", label2="", show=False):
values1 = np.reshape(values1, (-1,)) # TODO doesnt account for numkeys. Use only for a single key byte!
values2 = np.reshape(values2, (-1,))
correlation = np.corrcoef(values1, values2, rowvar=False)[1, 0]
mean_values1 = np.mean(values1, axis=0)
mean_values2 = np.mean(values2, axis=0)
plt.title("Correlation: " + str(correlation))
plt.plot(values1, "o", label=label1, markersize=5.0)
plt.plot(values2, "o", label=label2, markersize=5.0)
#plt.plot(values1, values2, "o", label=label2, markersize=5.0)
plt.gca().legend()
if show:
plt.show()
def plot_keyplot(keyplot, time_domain=True, sample_rate=1.0, show=False):
plt.title("Keyplot")
if time_domain:
plt.xlabel("Samples")
else:
plt.xlabel("Frequency assuming sample rate of %.2f" % sample_rate)
plt.ylabel("Amplitude")
color_cycle = plt.rcParams['axes.prop_cycle'].by_key()['color']
for value, mean_signal in sorted(keyplot.items()):
color = color_cycle[int(value.rpartition(',')[2].strip(')'), 16) % len(color_cycle)]
x = _get_x_axis_values(mean_signal, sample_rate=sample_rate, time_domain=time_domain)
plt.plot(x, mean_signal, label=value, color=color)
plt.legend()
if show:
plt.show()
| 7,731 | 2,535 |
def background_function(data, context):
pass | 48 | 13 |
#!/usr/bin/env python3
"""List manually-installed Debian packages
This script can be used to see which packages are flagged as having been installed manually. Manually-installed
packages are not eligible for autoremove. Managing this flag will ensure that libraries are cleaned up when no longer
needed.
This script outputs two parts: first, a list of one package name per line for packages that are manually-installed and
also a "root" (see list-root-packages.py). Second, a single big line listing packages that are manually-installed but
not a "root". This output is not designed or intended to be machine-readable; this script is just a heuristic, it does
not even attempt to be bulletproof."""
__author__ = "David Osolkowski"
__copyright__ = "Copyright 2020 David Osolkowski"
__license__ = "MIT"
__status__ = "Development"
__version__ = "1.1.0"
from apt import cache
aptCache = cache.Cache()
# All installed packages
installed = {
pkg
for pkg in aptCache
if pkg.is_installed
}
installedNames = {pkg.name for pkg in installed}
# All installed dependencies of installed packages
depends = {
dep_pkg.name
for pkg in installed
for dep in pkg.installed.get_dependencies('PreDepends', 'Depends', 'Recommends')
for dep_pkg in dep
if dep_pkg.name in installedNames
}
# All installed suggestions of installed packages
suggests = {
dep_pkg.name
for pkg in installed
for dep in pkg.installed.get_dependencies('Suggests')
for dep_pkg in dep
if dep_pkg.name in installedNames
}
# All manually-installed packages that nothing installed depends on
manualRoots = [
pkg.name + (" (SUGGESTED)" if pkg.name in suggests else "")
for pkg in installed
if not pkg.is_auto_installed and pkg.name not in depends
]
manualRoots.sort()
print('\n'.join(manualRoots))
manualDepends = [
pkg.name
for pkg in installed
if not pkg.is_auto_installed and pkg.name in depends
]
manualDepends.sort()
print("\nManual depended on by something: " + ', '.join(manualDepends))
| 2,031 | 609 |
import pytest
from mfr.core.provider import ProviderMetadata
from mfr.extensions.pdf import PdfRenderer
@pytest.fixture
def metadata():
return ProviderMetadata('test', '.pdf', 'text/plain', '1234', 'http://wb.osf.io/file/test.pdf?token=1234')
@pytest.fixture
def file_path():
return '/tmp/test.pdf'
@pytest.fixture
def url():
return 'http://osf.io/file/test.pdf'
@pytest.fixture
def assets_url():
return 'http://mfr.osf.io/assets'
@pytest.fixture
def export_url():
return 'http://mfr.osf.io/export?url=' + url()
@pytest.fixture
def renderer(metadata, file_path, url, assets_url, export_url):
return PdfRenderer(metadata, file_path, url, assets_url, export_url)
class TestPdfRenderer:
def test_render_pdf(self, renderer, metadata, assets_url):
body = renderer.render()
assert '<base href="{}/{}/web/">'.format(assets_url, 'pdf') in body
assert '<div id="viewer" class="pdfViewer"></div>' in body
assert 'DEFAULT_URL = \'{}\''.format(metadata.download_url) in body
| 1,040 | 374 |
'''Boston Housing Classification'''
import numpy as np
from keras.datasets import boston_housing
from keras import models
from keras import layers
(train_data, train_targets), (test_data,
test_targets) = boston_housing.load_data()
mean = train_data.mean(axis=0)
train_data -= mean
std = train_data.std(axis=0)
train_data /= std
test_data -= mean
test_data /= std
def build_model():
model = models.Sequential()
model.add(
layers.Dense(
64, activation='relu', input_shape=(train_data.shape[1], )))
model.add(layers.Dense(64, activation='relu'))
model.add(layers.Dense(1))
model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])
return model
k = 4
num_val_samples = len(train_data) // k
num_epochs = 100
all_scores = []
for i in range(k):
print('processing fold #', i)
val_data = train_data[i * num_val_samples:(i + 1) * num_val_samples]
val_targets = train_targets[i * num_val_samples:(i + 1) * num_val_samples]
partial_train_data = np.concatenate(
[
train_data[:i * num_val_samples],
train_data[(i + 1) * num_val_samples:]
],
axis=0)
partial_train_targets = np.concatenate(
[
train_targets[:i * num_val_samples],
train_targets[(i + 1) * num_val_samples:]
],
axis=0)
model = build_model()
model.fit(
partial_train_data,
partial_train_targets,
epochs=num_epochs,
batch_size=1,
verbose=0)
val_mse, val_mae = model.evaluate(val_data, val_targets, verbose=0)
all_scores.append(val_mae)
# We figured out that we only need ~80 epochs
model = build_model()
model.fit(train_data, train_targets, epochs=80, batch_size=16)
test_mse_score, test_mae_score = model.evaluate(test_data, test_targets)
| 1,847 | 667 |
from django import forms
from django.contrib.admin.widgets import FilteredSelectMultiple
from django.contrib.auth.forms import ReadOnlyPasswordHashField
from users.models import User
from core.models import Course, Group
class AdminUserCreateForm(forms.ModelForm):
""""A form for creating new users. Includes all the required
fields, plus a repeated password."""
password1 = forms.CharField(label='Password', widget=forms.PasswordInput)
password2 = forms.CharField(label='Password confirmation', widget=forms.PasswordInput)
class Meta:
model = User
fields = ('netid', 'full_name', 'class_year',)
def clean_password2(self):
# Check that the two password entries match
password1 = self.cleaned_data.get("password1")
password2 = self.cleaned_data.get("password2")
if password1 and password2 and password1 != password2:
raise forms.ValidationError("Passwords don't match")
return password2
def save(self, commit=True):
# Save the provided password in hashed format
user = super().save(commit=False)
user.availability = b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
user.set_password(self.cleaned_data["password1"])
if commit:
user.save()
return user
class AdminUserChangeForm(forms.ModelForm):
"""A form for updating users. Includes all the fields on
the user, but replaces the password field with admin's
password hash display field.
"""
password = ReadOnlyPasswordHashField()
class Meta:
model = User
fields = ('netid', 'full_name', 'class_year', 'password', 'is_active', 'is_superuser')
courses = forms.ModelMultipleChoiceField(
queryset=Course.objects.all(),
required=False,
widget=FilteredSelectMultiple(
verbose_name='Courses',
is_stacked=False
)
)
groups = forms.ModelMultipleChoiceField(
queryset=Group.objects.all(),
required=False,
widget=FilteredSelectMultiple(
verbose_name='Groups',
is_stacked=False
)
)
def __init__(self, *args, **kwargs):
super(AdminUserChangeForm, self).__init__(*args, **kwargs)
if self.instance.pk:
self.fields['courses'].initial = self.instance.courses.all()
self.fields['groups'].initial = self.instance.groups.all()
def save(self, commit=True):
User = super(AdminUserChangeForm, self).save(commit=False)
if commit:
User.save()
if User.pk:
User.courses.set(self.cleaned_data['courses'])
User.groups.set(self.cleaned_data['groups'])
print(self)
self.save_m2m()
return User
def clean_password(self):
# Regardless of what the user provides, return the initial value.
# This is done here, rather than on the field, because the
# field does not have access to the initial value
return self.initial["password"]
| 3,094 | 903 |
"""
DEPLOY POWERBUILDER PACKAGES
Author: Stivan Kitchoukov
To run created file from command line: OrcaScr126 Deploy.dat
"""
import os
import subprocess
import time
PackageList = (
"cf_common",
"cf_account_ip",
"cf_ap",
"cf_ar",
"cf_cga",
"cf_common_trans",
"cf_crt",
"cf_ddc",
"cf_gain_loss",
"cf_gl_reports",
"cf_party",
"cf_party_group",
"cf_party_option",
"cf_pledge",
"cf_scheduled_reports",
"cf_spending_rules_report",
"cf_strategy",
"cf_strategy_reports",
"cf_taxforms"
)
LibList = ""
AppName = ""
for i in PackageList:
DevDeploy = "p_" + i + "_d"
StagingDeploy = "p_" + i + "_s"
PackagePath = os.path.normpath("C:/iPhiCore/" + i + ".pbt")
pbt = open(PackagePath, "r")
while True:
content = pbt.readline()
if not content: break
if content.lower().startswith("appname"):
AppName = content.lower().replace("appname ", "")
AppName = AppName.replace(";", "")
if content.lower().startswith("liblist"):
LibList = os.path.normpath(content.lower().replace('liblist "', '"' + "C:/iPhiCore/"))
LibList = LibList.replace("\\\\", "\\")
LibList = os.path.normpath(LibList.replace(".pbl;", ".pbl;" + "C:/iPhiCore/"))
LibList = LibList.replace('";', ';"')
File = open("Deploy.dat", "w")
File.write("Start Session\n")
File.write("set debug TRUE\n")
File.write('Set Liblist ' + LibList)
File.write('Set Application "' + os.path.normpath("C:/iPhiCore/" + i) + '.pbl" ' + AppName)
File.write("build application full\n")
File.write('build project "' + os.path.normpath("C:/iPhiCore/" + i) + '.pbl" "' + DevDeploy + '"\n')
File.write('build project "' + os.path.normpath("C:/iPhiCore/" + i) + '.pbl" "' + StagingDeploy + '"\n')
File.write("End Session")
File.close()
print(time.strftime("%H:%M:%S", time.localtime()) + " - Deploying:" + i + "...")
command = os.path.normpath("OrcaScr126 C:/Users/skitchoukov/Desktop/Python/Deploy.dat")
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE)
while True:
line = process.stdout.readline()
if not line: break
process.wait()
print(time.strftime("%H:%M:%S", time.localtime()) + " - Finished: " + str(process.returncode))
time.sleep(20) | 2,355 | 875 |
import os
import buildbot
import buildbot.process.factory
import buildbot.steps.shell
import buildbot.steps.source as source
import buildbot.steps.source.svn as svn
import buildbot.process.properties as properties
import zorg.buildbot.commands.LitTestCommand as lit_test_command
import zorg.buildbot.util.artifacts as artifacts
import zorg.buildbot.util.phasedbuilderutils as phased_builder_utils
reload(lit_test_command)
reload(artifacts)
reload(phased_builder_utils)
def getLibCXXBuilder(f=None, source_path=None,
lit_dir=None):
if f is None:
f = buildbot.process.factory.BuildFactory()
# Find the build directory. We assume if f is passed in that the build
# directory has already been found.
f = phased_builder_utils.getBuildDir(f)
# Grab the sources if we are not passed in any.
if source_path is None:
source_path = 'sources'
src_url = 'http://llvm.org/svn/llvm-project/libcxx/trunk'
f = phased_builder_utils.SVNCleanupStep(f, source_path)
f.addStep(svn.SVN(name='pull.src', mode='full', repourl=src_url,
workdir=source_path, method='fresh',
alwaysUseLatest=False, retry = (60, 5),
description='pull.src'))
# Grab the artifacts for our build.
f = artifacts.GetCompilerArtifacts(f)
host_compiler_dir = properties.WithProperties('%(builddir)s/host-compiler')
f = artifacts.GetCCFromCompilerArtifacts(f, host_compiler_dir)
f = artifacts.GetCXXFromCompilerArtifacts(f, host_compiler_dir)
# Build libcxx.
CC = properties.WithProperties('%(cc_path)s')
CXX = properties.WithProperties('%(cxx_path)s')
HEADER_INCLUDE = \
properties.WithProperties('-I %s' % os.path.join('%(builddir)s',
source_path,
'include'))
SOURCE_LIB = \
properties.WithProperties(os.path.join('%(builddir)s',
source_path, 'lib',
'libc++.1.dylib'))
f.addStep(buildbot.steps.shell.ShellCommand(
name='build.libcxx', command=['./buildit'], haltOnFailure=True,
workdir=os.path.join(source_path, 'lib'),
env={ 'CC' : CC, 'CXX' : CXX, 'TRIPLE' : '-apple-'}))
# Get the 'lit' sources if we need to.
if lit_dir is None:
lit_dir = 'lit.src'
f.addStep(svn.SVN(
name='pull.lit', mode='incremental', method='fresh',
repourl='http://llvm.org/svn/llvm-project/llvm/trunk/utils/lit',
workdir=lit_dir, alwaysUseLatest=False))
# Install a copy of 'lit' in a virtualenv.
f.addStep(buildbot.steps.shell.ShellCommand(
name='venv.lit.clean',
command=['rm', '-rf', 'lit.venv'],
workdir='.', haltOnFailure=True))
f.addStep(buildbot.steps.shell.ShellCommand(
name='venv.lit.make',
command=['/usr/local/bin/virtualenv', 'lit.venv'],
workdir='.', haltOnFailure=True))
f.addStep(buildbot.steps.shell.ShellCommand(
name='venv.lit.install',
command=[
properties.WithProperties('%(builddir)s/lit.venv/bin/python'),
'setup.py', 'install'],
workdir=lit_dir, haltOnFailure=True))
# Run the tests with the system's dylib
f.addStep(lit_test_command.LitTestCommand(
name='test.libcxx.system',
command=[
properties.WithProperties('%(builddir)s/lit.venv/bin/lit'),
'-v', '--show-xfail', '--show-unsupported',
properties.WithProperties(
'--param=cxx_under_test=%(cxx_path)s'),
'--param=use_system_lib=true',
'sources/test'],
workdir='.'))
# Run the tests with the newly built dylib
f.addStep(lit_test_command.LitTestCommand(
name='test.libcxx.new',
command=[
properties.WithProperties('%(builddir)s/lit.venv/bin/lit'),
'-v', '--show-xfail', '--show-unsupported',
properties.WithProperties(
'--param=cxx_under_test=%(cxx_path)s'),
'--param=use_system_lib=false',
'sources/test'],
workdir='.'))
return f
| 4,456 | 1,367 |
# Copyright (c) 2015 Intel Corporation
#
# 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 rules.conditions.conditionsBuilder import ConditionsBuilder
class RuleResultChecker(object):
@staticmethod
def __join_all_results__(list_of_results):
return reduce(lambda array_1, array_2: array_1 + array_2, list_of_results)
def __init__(self, rule):
self.rule = rule
if 'operator' in rule['conditions']:
self.rule_operator = rule['conditions']['operator']
else:
self.rule_operator = None
self.list_of_results = None
def is_fulfilled(self, list_of_results):
self.list_of_results = list_of_results
if self.rule_operator == ConditionsBuilder.OR:
return reduce(lambda x, y: x or y, self.__get_result_status_list__())
if self.rule_operator == ConditionsBuilder.AND or self.rule_operator is None:
return reduce(lambda x, y: x and y, self.__get_result_status_list__())
raise AttributeError("Unknown rule operator: " + str(self.rule_operator))
def __get_result_status_list__(self):
return map(lambda single_result: single_result.is_passed,
RuleResultChecker.__join_all_results__(self.list_of_results))
| 1,760 | 514 |
from typing import Callable, List, Sequence, Union
from fastapi import APIRouter, Header
from fastapi.params import Depends
from pydantic import BaseModel
from .crudset import BaseCrudSet
__all__ = ['ViewSet', 'CrudViewSet']
supported_methods_names: List[str] = [
'list', 'retrieve', 'create', 'update', 'partial_update', 'destroy']
class ViewSet:
""" router: APIRouter = None
base_path: str = None
class_tag: str = None
path_key: str = "id"
response_model: BaseModel = None
dependencies: Sequence[Depends] = None
"""
router: APIRouter = None
base_path: str = None
class_tag: str = None
path_key: str = "id"
response_model: BaseModel = None
dependencies: Sequence[Depends] = None
marked_functions: List = []
def __init__(self) -> APIRouter:
self.functions: List[Callable] = []
self.extra_functions: List[List] = []
self.execute()
def get_response_model(self, action: str) -> Union[BaseModel, None]:
""" if override this method, you can return different response model for different action """
if self.response_model is not None:
return self.response_model
return None
def get_dependencies(self, action: str) -> Sequence[Depends]:
""" if override this method, you can return different dependencies for different action """
if self.dependencies is not None:
return self.dependencies
return None
def execute(self) -> APIRouter:
if self.router is None:
self.router = APIRouter()
if self.base_path is None:
self.base_path = '/' + self.__class__.__name__.lower()
if self.class_tag is None:
self.class_tag = self.__class__.__name__
for func in supported_methods_names:
if hasattr(self, func):
self.functions.append(getattr(self, func))
for func in self.functions:
self._register_route(func)
for func, methods, path in self.find_marked_functions():
self._register_extra_route(func, methods=methods, path=path)
def _register_route(self, func: Callable, hidden_params: List[str] = ["self"]):
# hidden_params TODO: add support for hidden params
extras = {}
extras['response_model'] = self.get_response_model(func.__name__)
extras['dependencies'] = self.get_dependencies(func.__name__)
if func.__name__ == 'list':
self.router.add_api_route(self.base_path, func, tags=[
self.class_tag], methods=['GET'], **extras)
elif func.__name__ == 'retrieve':
self.router.add_api_route(f"{self.base_path}/\u007b{self.path_key}\u007d", func, tags=[
self.class_tag], methods=['GET'], **extras)
elif func.__name__ == 'create':
self.router.add_api_route(self.base_path, func, tags=[
self.class_tag], methods=['POST'], **extras)
elif func.__name__ == 'update':
self.router.add_api_route(f"{self.base_path}/\u007b{self.path_key}\u007d", func, tags=[
self.class_tag], methods=['PUT'], **extras)
elif func.__name__ == 'partial_update':
self.router.add_api_route(f"{self.base_path}/\u007b{self.path_key}\u007d", func, tags=[
self.class_tag], methods=['PATCH'], **extras)
elif func.__name__ == 'destroy':
self.router.add_api_route(f"{self.base_path}/\u007b{self.path_key}\u007d", func, tags=[
self.class_tag], methods=['DELETE'], **extras)
else:
print(f"Method {func.__name__} is not supported")
def _register_extra_route(self, func: Callable, methods: List[str] = ["GET"], path: str = None):
extras = {}
extras['response_model'] = self.get_response_model(func.__name__)
extras['dependencies'] = self.get_dependencies(func.__name__)
if path is None:
path = func.__name__
self.router.add_api_route(f"{self.base_path}{path}", func, tags=[
self.class_tag], methods=methods, **extras)
@classmethod
def extra_method(cls, methods: List[str] = ["GET"], path_key: str = None):
""" if you want to add extra method to the viewset, you can use this decorator """
def decorator(func):
cls.marked_functions.append([func, methods, path_key])
return func
return decorator
def find_marked_functions(self):
for func in dir(self):
for marked_func in self.marked_functions:
if func == marked_func[0].__name__:
self.extra_functions.append(marked_func)
self.marked_functions.remove(marked_func)
break
return self.extra_functions
class CrudViewSet(ViewSet):
"""
This is the base viewset for CRUD operations.
"""
crud: BaseCrudSet = None
model: BaseModel = None
async_db = False
def __init__(self):
assert self.crud is not None, "You must define crud model"
assert self.model is not None, "You must define model"
self._crud = self.crud()
super().__init__()
async def list(self) -> List[model]:
if self.async_db:
return await self._crud.list()
return self._crud.list()
async def retrieve(self, id: int) -> model:
if self.async_db:
return await self._crud.retrieve(id)
return self._crud.retrieve(id)
async def create(self, data: model) -> model:
if self.async_db:
return await self._crud.create(data)
return self._crud.create(data)
async def update(self, id: int, data: model) -> model:
if self.async_db:
return await self._crud.update(id, data)
return self._crud.update(id, data)
async def partial_update(self, id: int, data: model) -> model:
if self.async_db:
return await self._crud.partial_update(id, data)
return self._crud.partial_update(id, data)
async def destroy(self, id: int) -> model:
if self.async_db:
return await self._crud.destroy(id)
return self._crud.destroy(id)
| 6,372 | 1,893 |
import os
import time
import pymysql
import pandas as pd
from decouple import config
from datetime import datetime
from sklearn.linear_model import Lasso
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.model_selection import RandomizedSearchCV
from scipy.stats import uniform as sp_rand
def contentsbased1(user_id, movie_id, genres_p):
print('======== 전체영화 예상평점 - 장르 ===========')
print('START TIME : ', str(datetime.now())[10:19])
start = time.time()
conn = pymysql.connect(host=config('HOST'), port=3306, user=config('USER'),
password=config('PASSWORD'), db=config('DB'))
sql = 'SELECT * FROM wouldyouci.accounts_rating where user_id=' + str(user_id)
ratings = pd.read_sql_query(sql, conn)
genres = genres_p
conn.close()
user_profile = ratings.merge(genres, left_on='movie_id', right_index=True)
model = Lasso()
param_grid = {'alpha': sp_rand()}
research = RandomizedSearchCV(estimator=model,
param_distributions=param_grid,
n_iter=20,
cv=5,
random_state=406)
research.fit(user_profile[genres.columns], user_profile['score'])
predictions = research.best_estimator_.predict(genres)
genres.reset_index()
genres['predict'] = predictions
predicted_score = genres.at[movie_id, 'predict']
print('END TIME : ', str(datetime.now())[10:19])
end = time.time()
print('TOTAL TIME : ', end-start)
print('PREDICTED SCORE : ', predicted_score)
print()
return pd.DataFrame.to_json(genres['predict'])
def contentsbased2(user_id, movie_id, movies_p):
print('======== 전체 영화 예상평점 - 장르 & 감독 & 배우 ===========')
print('START TIME : ', str(datetime.now())[10:19])
start = time.time()
conn = pymysql.connect(host=config('HOST'), port=3306, user=config('USER'),
password=config('PASSWORD'), db=config('DB'))
sql = 'SELECT * FROM wouldyouci.accounts_rating where user_id=' + str(user_id)
ratings = pd.read_sql_query(sql, conn)
movies = movies_p
conn.close()
ratings = ratings.merge(movies, left_on='movie_id', right_index=True)
x_train, x_test, y_train, y_test = train_test_split(ratings[movies.columns],
ratings['score'],
random_state=406,
test_size=.1)
reg = LinearRegression()
reg.fit(x_train, y_train)
predictions = reg.predict(movies)
movies.reset_index()
movies['predict'] = predictions
print('END TIME : ', str(datetime.now())[10:19])
predicted_score = movies.at[movie_id, 'predict']
end = time.time()
print('TOTAL TIME : ', end-start)
print('PREDICTED SCORE : ', predicted_score)
print()
return pd.DataFrame.to_json(movies['predict'])
def contentsbased3(user_id, movie_id, movies_p):
print('======== 특정 영화 예상평점 - 장르 & 감독 & 배우 ===========')
print('START TIME : ', str(datetime.now())[10:19])
start = time.time()
conn = pymysql.connect(host=config('HOST'), port=3306, user=config('USER'),
password=config('PASSWORD'), db=config('DB'))
sql = 'SELECT * FROM wouldyouci.accounts_rating where user_id=' + str(user_id)
ratings = pd.read_sql_query(sql, conn)
movies = movies_p
conn.close()
ratings = ratings.merge(movies, left_on='movie_id', right_index=True)
train, test = train_test_split(ratings, test_size=0.1, random_state=406)
x_train = train[movies.columns]
y_train = train['score']
reg = Lasso(alpha=0.03)
reg.fit(x_train, y_train)
user_profile = []
user_profile.append([reg.intercept_, *reg.coef_])
user_profile = pd.DataFrame(user_profile,
index=train['user_id'].unique(),
columns=['intercept', *movies.columns])
intercept = user_profile.loc[user_id, 'intercept']
columns_score = sum(user_profile.loc[user_id, movies.columns] * movies.loc[movie_id, movies.columns])
predicted_score = intercept + columns_score
print('END TIME : ', str(datetime.now())[10:19])
end = time.time()
print('TOTAL TIME : ', end-start)
print('PREDICTED SCORE : ', predicted_score)
print()
return predicted_score
def contentsbased4(user_id, movie_id, movies_p):
print('======== 전체 영화 예상평점 - 장르 & 감독 ===========')
print('START TIME : ',str(datetime.now())[10:19] )
start = time.time()
conn = pymysql.connect(host=config('HOST'), port=3306, user=config('USER'),
password=config('PASSWORD'), db=config('DB'))
sql = 'SELECT * FROM wouldyouci.accounts_rating where user_id=' + str(user_id)
ratings = pd.read_sql_query(sql, conn)
movies = movies_p
conn.close()
ratings = ratings.merge(movies, left_on='movie_id', right_index=True)
x_train, x_test, y_train, y_test = train_test_split(ratings[movies.columns],
ratings['score'],
random_state=406,
test_size=0.1)
reg = LinearRegression()
reg.fit(x_train, y_train)
predictions = reg.predict(movies)
movies.reset_index()
movies['predict'] = predictions
predicted_score = movies.at[movie_id, 'predict']
print('END TIME : ', str(datetime.now())[10:19])
end = time.time()
print('TOTAL TIME : ', end-start)
print('PREDICTED SCORE : ', predicted_score)
return pd.DataFrame.to_json(movies['predict'])
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
a = time.time()
genres = pd.read_pickle(os.path.join(BASE_DIR, 'movie_director_train.p'))
b = time.time()
print('Time to read pickle file 1: ', b - a)
movies = pd.read_pickle(os.path.join(BASE_DIR, 'movie_train.p'))
c = time.time()
print('Time to read pickle file 2: ', c - b)
directors = pd.read_pickle(os.path.join(BASE_DIR, 'movie_director_train.p'))
d = time.time()
print('Time to read pickle file 3: ', d - c)
print()
contentsbased1(9000007, 10016, genres)
contentsbased2(9000007, 10016, movies)
contentsbased3(9000007, 10016, movies)
contentsbased4(9000007, 10016, directors)
| 6,456 | 2,271 |
subscription = 'us-hpccplatform-dev'
subscription_id = 'ec0ba952-4ae9-4f69-b61c-4b96ff470038'
resource_prefix = 'roshan-test-'
n_threads = 5
image = "UbuntuLTS"
priority = "Spot"
max_price = "0.00001"
eviction_policy = "Deallocate"
spot_region_map = {
'centralus': ['Standard_A3', 'Standard_E80ids_v4', 'Standard_D4a_v4', 'Standard_D4s_v3', 'Standard_D64_v3', 'Standard_E16-4as_v4', 'Standard_DS12-2_v2', 'Standard_D11_v2', 'Standard_E4_v5', 'Standard_M64ms_v2', 'Standard_D2_v2', 'Standard_A2m_v2', 'Standard_M32ms_v2', 'Standard_D8_v4', 'Standard_DS1', 'Standard_D48_v5', 'Standard_D8s_v5', 'Standard_E64d_v5', 'Standard_E8-4ds_v4', 'Standard_D64ds_v5', 'Standard_DS13_v2', 'Standard_E8_v4', 'Standard_D48as_v4', 'Standard_E4-2as_v4', 'Standard_A1_v2', 'Standard_E4-2ds_v4', 'Standard_E16_v3', 'Standard_E64-32s_v3', 'Standard_E4a_v4', 'Standard_E16-8s_v4', 'Standard_D64d_v5', 'Standard_E16-4ds_v4', 'Standard_M416s_v2', 'Standard_DS13-4_v2', 'Standard_F4s', 'Standard_E16ds_v4', 'Standard_M64s', 'Standard_D48d_v5', 'Standard_E48a_v4', 'Standard_E48s_v3', 'Standard_D16ds_v5', 'Standard_E64-16as_v4', 'Standard_E16_v4', 'Standard_E16-8ds_v4', 'Standard_F48s_v2', 'Standard_M128dms_v2', 'Standard_F16s_v2', 'Standard_D16_v5', 'Standard_NC24s_v3', 'Standard_D8a_v4', 'Standard_D32_v5', 'Standard_E8_v3', 'Standard_E8a_v4', 'Standard_M208s_v2', 'Standard_F2s_v2', 'Standard_E2d_v4', 'Standard_E32-16s_v4', 'Standard_M208ms_v2', 'Standard_D2_v5', 'Standard_DS13-2_v2', 'Basic_A0', 'Standard_E80is_v4', 'Standard_E20as_v4', 'Standard_DS12', 'Standard_E4-2s_v3', 'Standard_E32_v5', 'Standard_A5', 'Standard_M208-104ms_v2', 'Standard_E64-16s_v4', 'Standard_F8', 'Standard_D4ds_v4', 'Standard_D2as_v4', 'Standard_D96_v5', 'Standard_M32dms_v2', 'Standard_M32ts', 'Standard_M192ims_v2', 'Standard_M64m', 'Standard_E16d_v5', 'Standard_E8-2s_v3', 'Standard_D32s_v3', 'Standard_D2a_v4', 'Standard_E32-8ds_v4', 'Standard_DS15i_v2', 'Standard_M32-16ms', 'Standard_E64-16s_v3', 'Standard_D96s_v5', 'Standard_DS2_v2', 'Standard_M64-16ms', 'Standard_D2d_v4', 'Standard_D48a_v4', 'Standard_NC6s_v3', 'Standard_DS3', 'Standard_E32as_v4', 'Standard_E4s_v4', 'Standard_E2_v3', 'Standard_D32d_v5', 'Standard_D32_v3', 'Standard_E96-48as_v4', 'Standard_D96ds_v5', 'Standard_M32-8ms', 'Standard_F2s', 'Standard_A8_v2', 'Standard_E4_v3', 'Standard_F64s_v2', 'Standard_M192idms_v2', 'Standard_M208-52ms_v2', 'Standard_E96-24as_v4', 'Standard_E2ds_v4', 'Standard_A2_v2', 'Standard_D48_v4', 'Standard_E8d_v5', 'Standard_ND96asr_v4', 'Standard_M32ms', 'Standard_D16d_v5', 'Standard_F8s', 'Standard_E16-4s_v4', 'Standard_DS4', 'Standard_D8s_v3', 'Standard_E64_v4', 'Standard_D32-8s_v3', 'Standard_D4d_v4', 'Standard_E8-2ds_v4', 'Standard_E8s_v4', 'Standard_A6', 'Standard_D8d_v5', 'Standard_D8s_v4', 'Standard_E2s_v4', 'Standard_E64a_v4', 'Standard_F32s_v2', 'Standard_E32_v3', 'Standard_D4_v3', 'Standard_DS1_v2', 'Standard_M64ds_v2', 'Standard_D4s_v5', 'Standard_M128s', 'Standard_E20a_v4', 'Standard_M8-2ms', 'Standard_M128', 'Standard_E2_v5', 'Standard_D2ds_v4', 'Standard_DS15_v2', 'Standard_D96d_v5', 'Standard_E2as_v4', 'Standard_M416-104s_v2', 'Standard_E48as_v4', 'Standard_D64ds_v4', 'Standard_D4_v4', 'Standard_E64i_v3', 'Standard_D16s_v5', 'Standard_D32_v4', 'Standard_E4d_v4', 'Standard_E64_v3', 'Standard_M208-52s_v2', 'Standard_D16_v4', 'Standard_A7', 'Standard_D13', 'Standard_E32-8as_v4', 'Standard_DS12-1_v2', 'Standard_E8s_v3', 'Standard_E64-32as_v4', 'Standard_F16s', 'Standard_E64s_v4', 'Standard_NC24rs_v3', 'Standard_D4ds_v5', 'Standard_E16-8as_v4', 'Standard_D16d_v4', 'Standard_M192ids_v2', 'Standard_E48d_v5', 'Standard_E32-16ds_v4', 'Standard_D2_v3', 'Standard_D15_v2', 'Standard_E20_v4', 'Standard_M416is_v2', 'Standard_D4_v5', 'Standard_D11', 'Standard_M416-104ms_v2', 'Standard_DS2', 'Standard_DS14_v2', 'Standard_A2', 'Standard_F8s_v2', 'Standard_F4', 'Standard_DS11', 'Standard_D64d_v4', 'Standard_DS13', 'Standard_A4_v2', 'Standard_E32-8s_v4', 'Standard_F1s', 'Standard_D15i_v2', 'Standard_D2', 'Standard_E16as_v4', 'Standard_D8ds_v4', 'Standard_E20_v3', 'Standard_E96d_v5', 'Standard_M16-4ms', 'Standard_M8-4ms', 'Standard_E96a_v4', 'Standard_D16as_v4', 'Standard_E20d_v4', 'Standard_E8-4as_v4', 'Standard_D8as_v4', 'Standard_D3', 'Standard_D96as_v4', 'Standard_M128s_v2', 'Standard_E8as_v4', 'Standard_E64-32s_v4', 'Standard_D4s_v4', 'Standard_D96a_v4', 'Standard_M208-104s_v2', 'Standard_D64_v5', 'Standard_DS14-8_v2', 'Standard_D48s_v4', 'Standard_E32ds_v4', 'Standard_D12', 'Standard_D32s_v5', 'Standard_DS4_v2', 'Standard_D32ds_v4', 'Standard_E32s_v3', 'Standard_E64d_v4', 'Standard_E48_v5', 'Standard_D12_v2', 'Standard_D4as_v4', 'Standard_D64s_v3', 'Standard_D64_v4', 'Standard_M416-208ms_v2', 'Basic_A1', 'Standard_A0', 'Standard_M16s', 'Standard_A4m_v2', 'Standard_ND96asr_A100_v4', 'Standard_E16-4s_v3', 'Standard_M128ds_v2', 'Standard_DS5_v2', 'Standard_E2s_v3', 'Standard_E64_v5', 'Standard_E20s_v4', 'Standard_E20d_v5', 'Standard_E32d_v4', 'Standard_D13_v2', 'Standard_D32a_v4', 'Standard_D32as_v4', 'Standard_D8_v5', 'Standard_D2ds_v5', 'Standard_E4_v4', 'Standard_D64-32s_v3', 'Standard_F72s_v2', 'Standard_M32ls', 'Standard_E48_v3', 'Standard_D14_v2', 'Basic_A2', 'Standard_M32s', 'Standard_E48d_v4', 'Standard_D14', 'Standard_E2a_v4', 'Standard_M64ms', 'Standard_E4s_v3', 'Standard_E8-2s_v4', 'Standard_E32d_v5', 'Standard_M128ms_v2', 'Standard_D2s_v3', 'Standard_M16-8ms', 'Standard_D4', 'Standard_E20ds_v4', 'Standard_F16', 'Standard_E16_v5', 'Standard_F1', 'Standard_E8-4s_v3', 'Standard_E32_v4', 'Standard_D16a_v4', 'Standard_E4as_v4', 'Standard_E16d_v4', 'Standard_M128-64ms', 'Standard_E96as_v4', 'Standard_M64dms_v2', 'Standard_E32a_v4', '', 'Standard_D2s_v4', 'Standard_M192is_v2', 'Standard_NC12s_v3', 'Standard_D64a_v4', 'Standard_D16s_v4', 'Standard_E4-2s_v4', 'Standard_E8-4s_v4', 'Standard_E4ds_v4', 'Standard_F2', 'Standard_E32-8s_v3', 'Standard_D48ds_v5', 'Standard_E16-8s_v3', 'Standard_M16ms', 'Standard_E4d_v5', 'Standard_E8ds_v4', 'Standard_D32d_v4', 'Standard_E64s_v3', 'Standard_E20_v5', 'Standard_D4d_v5', 'Standard_E16s_v4', 'Standard_E8_v5', 'Standard_D8_v3', 'Standard_D32s_v4', 'Standard_M64', 'Standard_E32-16as_v4', 'Standard_DC4s', 'Standard_F4s_v2', 'Standard_E16s_v3', 'Standard_M8ms', 'Standard_DC2s', 'Basic_A4', 'Standard_D2_v4', 'Standard_E64is_v3', 'Standard_D4_v2', 'Standard_D8ds_v5', 'Standard_E64ds_v4', 'Standard_D3_v2', 'Standard_DS3_v2', 'Standard_E48ds_v4', 'Standard_M64-32ms', 'Standard_E64-16ds_v4', 'Standard_E16a_v4', 'Standard_D1_v2', 'Standard_A8m_v2', 'Standard_E48s_v4', 'Standard_E2d_v5', 'Standard_D2s_v5', 'Standard_D48_v3', 'Standard_D48d_v4', 'Standard_D48ds_v4', 'Standard_D1', 'Standard_E64-32ds_v4', 'Standard_E8d_v4', 'Standard_D2d_v5', 'Standard_E20s_v3', 'Standard_E32s_v4', 'Standard_D16ds_v4', 'Standard_A4', 'Standard_E2_v4', 'Standard_D64s_v5', 'Standard_D64as_v4', 'Standard_ND96amsr_A100_v4', 'Standard_D64s_v4', 'Standard_DS14', 'Standard_A1', 'Standard_D48s_v3', 'Standard_DS12_v2', 'Standard_M128-32ms', 'Standard_E96_v5', 'Standard_D32ds_v5', 'Standard_D48s_v5', 'Standard_M128ms', 'Standard_E64as_v4', 'Basic_A3', 'Standard_D8d_v4', 'Standard_HB120rs_v2', 'Standard_M64ls', 'Standard_D16_v3', 'Standard_D64-16s_v3', 'Standard_DS11_v2', 'Standard_E32-16s_v3', 'Standard_D16s_v3', 'Standard_M64s_v2', 'Standard_M416ms_v2', 'Standard_D32-16s_v3', 'Standard_E8-2as_v4', 'Standard_M128m', 'Standard_M416-208s_v2', 'Standard_DS11-1_v2', 'Standard_E48_v4', 'Standard_DS14-4_v2', 'Standard_D5_v2'],
'eastasia': ['Standard_D64s_v5', 'Standard_D32-8s_v3', 'Standard_D11_v2', 'Standard_D64s_v4', 'Standard_D16d_v5', 'Standard_D2s_v4', 'Standard_E32-16ds_v4', 'Standard_F2', 'Standard_D48s_v4', 'Standard_E4-2ds_v4', 'Standard_D2ds_v4', 'Standard_D96ds_v5', 'Standard_E96_v5', 'Standard_D5_v2', 'Standard_E48s_v4', 'Standard_D16ds_v4', 'Standard_D2_v3', 'Standard_E64_v5', 'Standard_D8_v4', 'Standard_D4s_v3', 'Standard_D16as_v4', 'Standard_E64-32s_v4', 'Standard_M416is_v2', 'Standard_D64a_v4', 'Standard_DS13-4_v2', 'Basic_A4', 'Standard_D48s_v5', 'Standard_M64-32ms', 'Standard_E48d_v4', 'Standard_M64ms', 'Standard_E64d_v5', 'Standard_E8_v4', 'Standard_F1s', 'Standard_D11', 'Standard_E8ds_v4', 'Standard_E64-32ds_v4', 'Standard_E32as_v4', 'Standard_E16d_v4', 'Standard_DS12_v2', 'Standard_D32a_v4', 'Standard_D8ds_v5', 'Standard_D32ds_v5', 'Standard_D2as_v4', 'Standard_E2_v4', 'Standard_D2s_v5', 'Standard_ND40s_v2', 'Standard_E16-4s_v4', 'Standard_E8d_v4', 'Standard_E8-2as_v4', 'Standard_M416s_v2', 'Standard_E8-2s_v3', 'Standard_E20_v3', 'Standard_D96a_v4', 'Standard_E20ds_v4', 'Standard_D16d_v4', 'Standard_D32_v4', 'Standard_D96s_v5', 'Standard_E8d_v5', 'Standard_DS11', 'Standard_M208-52ms_v2', 'Standard_E8-2ds_v4', 'Standard_M16s', 'Standard_E64ds_v4', 'Standard_M416-104s_v2', 'Standard_D64d_v4', 'Standard_E4-2as_v4', 'Standard_D32as_v4', 'Standard_E20a_v4', 'Standard_D96_v5', 'Standard_D8s_v3', 'Standard_F16', 'Standard_M416-208ms_v2', 'Standard_E32-8as_v4', 'Standard_D4', 'Standard_D4ds_v4', 'Standard_D48as_v4', 'Standard_D8as_v4', 'Standard_E64_v3', 'Standard_E20s_v4', 'Standard_D15i_v2', 'Standard_D48ds_v4', 'Standard_E16_v5', 'Standard_D64_v5', 'Standard_M128', 'Standard_D48ds_v5', 'Standard_M32-8ms', 'Standard_D16s_v5', 'Standard_D96d_v5', 'Standard_A1', 'Standard_E32_v5', 'Standard_E64-16s_v4', 'Standard_E2ds_v4', 'Standard_DS14-4_v2', 'Standard_D4d_v4', 'Standard_DS2_v2', 'Standard_M416ms_v2', 'Standard_D14_v2', 'Standard_E2s_v4', 'Standard_F8s_v2', 'Standard_E32a_v4', 'Standard_E64i_v3', 'Basic_A2', 'Standard_D8a_v4', 'Standard_E64-16s_v3', 'Standard_DS1', 'Standard_M32-16ms', 'Standard_E32s_v3', 'Standard_E20d_v5', 'Standard_E2s_v3', 'Standard_DS3_v2', 'Standard_D4s_v5', 'Standard_E64s_v4', 'Standard_E48s_v3', 'Standard_A2', 'Standard_E64-32s_v3', 'Standard_M8ms', 'Basic_A0', 'Standard_A8m_v2', 'Standard_D8s_v4', 'Standard_E4d_v5', 'Standard_E8s_v3', 'Standard_M32ts', 'Standard_DS1_v2', 'Standard_D2', 'Standard_D16_v5', 'Standard_E16s_v3', 'Standard_E2d_v5', 'Standard_D64_v3', 'Standard_D48s_v3', 'Standard_M16-4ms', 'Standard_D2_v2', 'Standard_M8-4ms', 'Standard_D4_v4', 'Standard_M32s', 'Standard_D4d_v5', 'Standard_DS12-1_v2', 'Standard_D96as_v4', 'Standard_E32-8ds_v4', 'Standard_E8-4s_v3', 'Standard_D2a_v4', 'Standard_A2m_v2', 'Standard_M208-104s_v2', 'Standard_E48as_v4', 'Standard_E20d_v4', 'Standard_F72s_v2', 'Standard_E16d_v5', 'Standard_M32ms', 'Standard_D8d_v5', 'Standard_A1_v2', 'Standard_E64s_v3', 'Standard_DS11-1_v2', 'Standard_D2ds_v5', 'Standard_D13', 'Standard_M128-32ms', 'Standard_E16-8s_v3', 'Standard_E16-4as_v4', 'Standard_M208s_v2', 'Standard_D48d_v5', 'Standard_E16_v4', 'Standard_D64ds_v4', 'Standard_E32s_v4', 'Standard_D32_v5', 'Standard_D16a_v4', 'Standard_M16-8ms', 'Standard_E4-2s_v4', 'Standard_D8d_v4', 'Standard_A4m_v2', 'Standard_D8s_v5', 'Standard_D8_v3', 'Standard_F32s_v2', 'Standard_E4a_v4', 'Standard_DS3', 'Standard_E2_v5', 'Standard_M64ls', 'Standard_A4', 'Standard_D32d_v5', 'Standard_A2_v2', 'Standard_E48ds_v4', 'Standard_F16s', 'Standard_M64', 'Standard_D2_v5', 'Standard_E20as_v4', 'Standard_DS14-8_v2', 'Standard_E8-2s_v4', 'Standard_D14', 'Standard_E20_v5', 'Standard_E2a_v4', 'Standard_M128-64ms', 'Standard_E32ds_v4', 'Standard_D48_v5', 'Standard_E4_v4', 'Standard_F64s_v2', 'Standard_DS5_v2', 'Standard_DS13', 'Basic_A3', 'Standard_D64ds_v5', 'Standard_DS12', 'Standard_DS13_v2', 'Standard_E16-8ds_v4', 'Standard_E20_v4', 'Standard_E4_v3', 'Standard_M64s', 'Standard_E8s_v4', 'Standard_E20s_v3', 'Standard_DS15_v2', 'Standard_E96a_v4', '', 'Standard_E4_v5', 'Standard_E64d_v4', 'Standard_DS4_v2', 'Standard_E4-2s_v3', 'Standard_E48_v4', 'Standard_E64-32as_v4', 'Standard_E48_v5', 'Standard_E48_v3', 'Standard_E8-4ds_v4', 'Standard_D16ds_v5', 'Standard_M128ms', 'Standard_E32-8s_v3', 'Standard_D32s_v3', 'Standard_D16s_v4', 'Standard_E96-24as_v4', 'Standard_E16as_v4', 'Standard_F8s', 'Standard_E8a_v4', 'Standard_DS13-2_v2', 'Standard_E16ds_v4', 'Standard_F4', 'Standard_D8ds_v4', 'Standard_M64-16ms', 'Standard_D15_v2', 'Standard_E2d_v4', 'Standard_E32-16s_v4', 'Standard_E32_v4', 'Standard_E16-4s_v3', 'Standard_E16-8as_v4', 'Standard_E8-4as_v4', 'Standard_A5', 'Standard_E8_v3', 'Basic_A1', 'Standard_E16_v3', 'Standard_D1_v2', 'Standard_D2d_v4', 'Standard_E32d_v5', 'Standard_D13_v2', 'Standard_D12_v2', 'Standard_E48a_v4', 'Standard_E8_v5', 'Standard_E96as_v4', 'Standard_M32ls', 'Standard_E32-8s_v4', 'Standard_F4s', 'Standard_D32-16s_v3', 'Standard_D3_v2', 'Standard_DS12-2_v2', 'Standard_D4as_v4', 'Standard_E80ids_v4', 'Standard_D2d_v5', 'Standard_DS14', 'Standard_D2s_v3', 'Standard_M128s', 'Standard_D4a_v4', 'Standard_D3', 'Standard_D1', 'Standard_D4s_v4', 'Standard_D32d_v4', 'Standard_E96d_v5', 'Standard_DS14_v2', 'Standard_E32_v3', 'Standard_D4_v2', 'Standard_M8-2ms', 'Standard_A7', 'Standard_A3', 'Standard_F1', 'Standard_E48d_v5', 'Standard_F2s', 'Standard_D48a_v4', 'Standard_E32d_v4', 'Standard_D12', 'Standard_E4as_v4', 'Standard_D16_v3', 'Standard_A6', 'Standard_D4_v5', 'Standard_D64-16s_v3', 'Standard_E2_v3', 'Standard_D64s_v3', 'Standard_E64is_v3', 'Standard_DS11_v2', 'Standard_E4ds_v4', 'Standard_E4d_v4', 'Standard_E96-48as_v4', 'Standard_E64a_v4', 'Standard_D16s_v3', 'Standard_D4ds_v5', 'Standard_F16s_v2', 'Standard_M208-104ms_v2', 'Standard_E8-4s_v4', 'Standard_DS2', 'Standard_DS4', 'Standard_M208-52s_v2', 'Standard_D32_v3', 'Standard_E64-16ds_v4', 'Standard_M416-104ms_v2', 'Standard_E16-8s_v4', 'Standard_E64as_v4', 'Standard_D64d_v5', 'Standard_D64-32s_v3', 'Standard_D2_v4', 'Standard_E4s_v3', 'Standard_DS15i_v2', 'Standard_E64_v4', 'Standard_E80is_v4', 'Standard_E32-16s_v3', 'Standard_D48d_v4', 'Standard_F8', 'Standard_D32s_v4', 'Standard_E4s_v4', 'Standard_D48_v4', 'Standard_D32s_v5', 'Standard_E16a_v4', 'Standard_M16ms', 'Standard_D4_v3', 'Standard_A4_v2', 'Standard_D8_v5', 'Standard_M64m', 'Standard_E8as_v4', 'Standard_D48_v3', 'Standard_D32ds_v4', 'Standard_E2as_v4', 'Standard_M416-208s_v2', 'Standard_A0', 'Standard_E64-16as_v4', 'Standard_F2s_v2', 'Standard_F4s_v2', 'Standard_M208ms_v2', 'Standard_M128m', 'Standard_F48s_v2', 'Standard_E16-4ds_v4', 'Standard_D16_v4', 'Standard_D64_v4', 'Standard_D64as_v4', 'Standard_E16s_v4', 'Standard_E32-16as_v4', 'Standard_A8_v2'],
'southeastasia': ['Standard_HC44-32rs', 'Standard_E32a_v4', 'Standard_D32as_v4', 'Standard_M64s_v2', 'Standard_H8m', 'Standard_NC24s_v2', 'Standard_D2ds_v4', 'Standard_M416-104s_v2', 'Standard_D8ds_v5', 'Standard_A2', 'Standard_D16d_v4', 'Standard_D2as_v4', 'Standard_M416ms_v2', 'Standard_E4s_v4', 'Standard_E32s_v4', 'Standard_A2m_v2', 'Standard_DS13-4_v2', 'Standard_NV32as_v4', 'Standard_A8m_v2', 'Standard_M32ts', 'Standard_E32s_v3', 'Standard_A4_v2', 'Standard_M8-2ms', 'Standard_D2_v4', 'Standard_G1', 'Standard_NV12', 'Standard_E64-32as_v4', 'Standard_E2_v3', 'Standard_D48_v5', 'Standard_M208s_v2', 'Standard_E32d_v5', 'Standard_M32-16ms', 'Standard_E96d_v5', 'Standard_E32d_v4', 'Standard_E16ds_v4', 'Standard_A1', 'Standard_D96s_v5', 'Standard_M64ls', 'Standard_M416-208s_v2', 'Standard_E8-2as_v4', 'Standard_E8-2s_v3', 'Standard_E8-4s_v3', 'Standard_E8s_v3', 'Standard_D5_v2', 'Standard_DS13-2_v2', 'Standard_NP40s', 'Standard_L32s_v2', 'Standard_E64-16ds_v4', 'Standard_E64_v5', 'Standard_E8-2ds_v4', 'Standard_D8d_v5', 'Standard_E4d_v4', 'Standard_E2_v5', 'Standard_D64ds_v5', 'Standard_ND24s', 'Standard_M32ls', 'Standard_NC6', 'Standard_D16s_v4', 'Standard_D4_v2', 'Standard_M64ms_v2', 'Standard_D64a_v4', 'Standard_D48_v4', 'Standard_D8s_v4', 'Standard_M64s', 'Standard_NC24rs_v3', 'Standard_E4a_v4', 'Standard_A5', 'Standard_M32-8ms', 'Standard_E20as_v4', 'Standard_F2', 'Standard_E4-2ds_v4', 'Standard_F2s', 'Standard_E8a_v4', 'Standard_E4s_v3', 'Standard_NC6s_v3', 'Standard_L8s', 'Standard_D32-16s_v3', 'Standard_D4ds_v4', 'Standard_M128ds_v2', 'Standard_GS5-16', 'Standard_F2s_v2', 'Standard_D3', 'Standard_D8d_v4', 'Standard_D2_v5', 'Standard_GS4-4', 'Standard_E32-16ds_v4', 'Standard_D16s_v3', 'Standard_D4_v4', 'Standard_E4-2s_v3', 'Standard_E16-8ds_v4', 'Standard_D32ds_v5', 'Standard_M192is_v2', 'Standard_E8d_v4', 'Standard_A8_v2', 'Standard_HC44rs', 'Standard_GS1', 'Standard_D32d_v4', 'Standard_DS12', 'Standard_M64-16ms', 'Standard_D4s_v3', 'Standard_A0', 'Standard_NC24r', 'Standard_E64a_v4', 'Standard_M128dms_v2', 'Standard_M128s', 'Standard_E48_v5', 'Standard_D2_v3', 'Standard_D48a_v4', 'Standard_DC8_v2', 'Standard_E96as_v4', 'Standard_E4_v3', 'Standard_A4', 'Standard_M64-32ms', 'Standard_D32_v5', 'Standard_E8_v5', 'Standard_D2s_v3', 'Standard_E16s_v4', 'Standard_E20s_v3', 'Standard_E32_v3', 'Standard_DS4_v2', 'Standard_E16-8s_v3', 'Standard_M208ms_v2', 'Standard_M128ms_v2', 'Standard_E16s_v3', 'Standard_L32s', 'Standard_D8ds_v4', 'Standard_D64d_v4', 'Standard_ND40rs_v2', 'Standard_D15_v2', 'Standard_E4_v4', 'Standard_D16_v3', 'Standard_NC16as_T4_v3', 'Standard_F8', 'Standard_D4d_v5', 'Standard_M208-104s_v2', 'Standard_NC6s_v2', 'Standard_D8as_v4', 'Standard_M64ms', 'Standard_NC12s_v3', 'Standard_H16mr', 'Standard_E20s_v4', 'Standard_GS5-8', 'Standard_GS3', 'Standard_E16-4s_v4', 'Standard_M16-4ms', 'Standard_D32s_v4', 'Standard_D2d_v5', 'Standard_E64s_v4', 'Standard_D13', 'Standard_D11', 'Standard_D4d_v4', 'Standard_E64-32s_v3', 'Standard_F8s_v2', 'Standard_NC12s_v2', 'Standard_M208-52ms_v2', 'Standard_NV16as_v4', 'Standard_E16-4as_v4', 'Standard_E8as_v4', 'Standard_NC24s_v3', 'Standard_E64-16as_v4', 'Standard_ND6s', 'Standard_E64_v3', 'Standard_D16_v4', 'Standard_E8-2s_v4', 'Standard_D16a_v4', 'Standard_E8d_v5', 'Standard_DS5_v2', 'Standard_M128ms', 'Standard_DC2s_v2', 'Standard_D48d_v5', 'Standard_E2as_v4', 'Standard_F32s_v2', 'Standard_D64_v3', 'Standard_D16ds_v5', 'Standard_E64-32s_v4', 'Standard_E96_v5', 'Standard_D4_v5', 'Standard_M64dms_v2', 'Standard_E96-48as_v4', 'Standard_D16_v5', 'Standard_D2a_v4', 'Standard_E20ds_v4', 'Standard_DS11', 'Standard_M8-4ms', 'Standard_NC8as_T4_v3', 'Standard_GS5', 'Standard_E4-2as_v4', 'Standard_D11_v2', 'Standard_E48as_v4', 'Standard_D32a_v4', 'Standard_D96ds_v5', 'Standard_L80s_v2', 'Standard_E16a_v4', 'Standard_E48d_v5', 'Standard_DS13', 'Standard_E32-8as_v4', 'Standard_DS4', 'Standard_F64s_v2', 'Standard_PB24s', 'Standard_D64_v4', 'Standard_D4ds_v5', 'Standard_D2d_v4', 'Standard_D64d_v5', 'Standard_D4s_v4', 'Standard_PB6s', 'Standard_H16', 'Standard_E32-8s_v3', 'Standard_D2', 'Standard_F1s', 'Standard_E2d_v5', 'Standard_F4s', 'Standard_M64m', 'Standard_E20d_v4', 'Standard_NC12', 'Standard_M16s', 'Standard_D1_v2', 'Standard_NV24', 'Standard_E32as_v4', 'Standard_ND12s', 'Standard_DS1', 'Standard_D12_v2', 'Standard_D8_v4', 'Standard_G4', 'Standard_D48_v3', 'Standard_A7', 'Standard_DS2_v2', 'Standard_E16-8as_v4', 'Standard_D64-16s_v3', 'Standard_E16_v4', 'Standard_DS2', 'Standard_NC4as_T4_v3', 'Standard_E64_v4', 'Standard_E8-4s_v4', 'Standard_NV48s_v3', 'Standard_E8_v3', 'Standard_F16s', 'Standard_DS12_v2', 'Standard_E4_v5', 'Standard_M16ms', 'Standard_D64s_v5', 'Standard_M192idms_v2', 'Standard_D8_v5', 'Standard_M192ids_v2', 'Standard_E80ids_v4', 'Standard_D32d_v5', 'Basic_A2', 'Standard_E8-4as_v4', 'Standard_D4', 'Standard_D32s_v3', 'Standard_GS2', 'Standard_D1', 'Standard_D2_v2', 'Standard_NC24', 'Standard_L16s_v2', 'Standard_E48_v4', 'Standard_M416-104ms_v2', 'Standard_H16m', 'Standard_M128-32ms', 'Standard_E4as_v4', 'Standard_D16ds_v4', 'Standard_E16_v5', '', 'Standard_E16_v3', 'Standard_M64ds_v2', 'Standard_E16-8s_v4', 'Standard_E32_v5', 'Standard_F8s', 'Standard_GS4-8', 'Standard_L64s_v2', 'Standard_E80is_v4', 'Standard_D4s_v5', 'Standard_M416s_v2', 'Standard_E32-16as_v4', 'Standard_HC44-16rs', 'Standard_E32_v4', 'Standard_L88is_v2', 'Standard_D48s_v4', 'Standard_D48d_v4', 'Standard_D16as_v4', 'Standard_A6', 'Standard_E64ds_v4', 'Standard_E8ds_v4', 'Standard_A1_v2', 'Standard_DC4s_v2', 'Standard_F16s_v2', 'Standard_NP10s', 'Standard_E64-16s_v3', 'Basic_A1', 'Standard_D16d_v5', 'Standard_M416is_v2', 'Standard_D2s_v4', 'Standard_DS11_v2', 'Standard_D3_v2', 'Standard_E64as_v4', 'Standard_D32-8s_v3', 'Standard_DS11-1_v2', 'Standard_D8s_v3', 'Standard_GS4', 'Standard_E2a_v4', 'Standard_D96d_v5', 'Standard_A4m_v2', 'Standard_M32dms_v2', 'Standard_E16d_v5', 'Standard_E64d_v5', 'Standard_NC64as_T4_v3', 'Standard_NV6', 'Standard_D48s_v5', 'Basic_A4', 'Standard_F48s_v2', 'Standard_M32ms', 'Standard_L48s_v2', 'Standard_E20a_v4', 'Standard_E96-24as_v4', 'Standard_E32ds_v4', 'Standard_DS13_v2', 'Standard_D48ds_v4', 'Standard_E16-4s_v3', 'Standard_E64i_v3', 'Standard_E20d_v5', 'Standard_E32-8s_v4', 'Standard_M208-104ms_v2', 'Standard_ND40s_v2', 'Standard_D96a_v4', 'Standard_D64s_v4', 'Standard_D32_v4', 'Standard_DS15_v2', 'Standard_M128s_v2', 'Standard_E32-8ds_v4', 'Standard_F72s_v2', 'Standard_M128-64ms', 'Standard_D64_v5', 'Standard_NV8as_v4', 'Standard_M416-208ms_v2', 'Standard_D4as_v4', 'Standard_D48as_v4', 'Standard_D12', 'Standard_E16d_v4', 'Standard_E2_v4', 'Standard_D4a_v4', 'Standard_F4', 'Standard_DS14-4_v2', 'Standard_D16s_v5', 'Standard_E64-16s_v4', 'Standard_E20_v5', 'Standard_D48s_v3', 'Standard_L4s', 'Standard_L8s_v2', 'Standard_PB12s', 'Standard_D32_v3', 'Standard_D64s_v3', 'Standard_F4s_v2', 'Standard_D14', 'Standard_G2', 'Standard_E48d_v4', 'Standard_NV4as_v4', 'Standard_D8s_v5', 'Standard_A2_v2', 'Standard_D2ds_v5', 'Standard_E48s_v3', 'Standard_E32-16s_v3', 'Standard_ND24rs', 'Standard_D8_v3', 'Standard_A3', 'Standard_D64ds_v4', 'Standard_F16', 'Standard_D13_v2', 'Standard_D14_v2', 'Standard_E8_v4', 'Standard_D48ds_v5', 'Standard_M32s', 'Standard_NP20s', 'Standard_E48ds_v4', 'Standard_E48a_v4', 'Standard_M32ms_v2', 'Standard_DS3_v2', 'Standard_NV12s_v3', 'Standard_DS1_v2', 'Standard_H16r', 'Standard_E96a_v4', 'Standard_E64s_v3', 'Standard_E16as_v4', 'Basic_A0', 'Standard_DS12-1_v2', 'Standard_D64-32s_v3', 'Standard_E64d_v4', 'Standard_E48_v3', 'Standard_E16-4ds_v4', 'Standard_E4ds_v4', 'Standard_M16-8ms', 'Standard_D15i_v2', 'Standard_M64', 'Standard_DS14_v2', 'Standard_M192ims_v2', 'Standard_E2s_v4', 'Standard_DS3', 'Standard_E32-16s_v4', 'Standard_E20_v4', 'Standard_M8ms', 'Standard_E64-32ds_v4', 'Standard_D4_v3', 'Standard_E48s_v4', 'Standard_E8s_v4', 'Standard_D64as_v4', 'Standard_E2d_v4', 'Standard_E20_v3', 'Standard_DS14', 'Standard_E64is_v3', 'Standard_G3', 'Standard_M128m', 'Standard_DS15i_v2', 'Standard_D32ds_v4', 'Standard_E2ds_v4', 'Standard_M208-52s_v2', 'Standard_D32s_v5', 'Standard_D96as_v4', 'Standard_E4d_v5', 'Standard_L16s', 'Standard_DS14-8_v2', 'Standard_E8-4ds_v4', 'Standard_NC24rs_v2', 'Standard_D96_v5', 'Standard_NV24s_v3', 'Basic_A3', 'Standard_F1', 'Standard_G5', 'Standard_E4-2s_v4', 'Standard_E2s_v3', 'Standard_H8', 'Standard_M128', 'Standard_D2s_v5', 'Standard_D8a_v4', 'Standard_DC1s_v2', 'Standard_DS12-2_v2'],
'eastus': ['Standard_M32ts', 'Standard_E48a_v4', 'Standard_E32-8s_v4', 'Standard_M32-8ms', 'Standard_NP20s', 'Standard_D32as_v4', 'Standard_E48as_v4', 'Standard_M8-2ms', 'Standard_D14', 'Standard_M64s_v2', 'Standard_D2a_v4', 'Standard_D16_v3', 'Standard_D64_v4', 'Standard_A8_v2', 'Standard_D48ds_v5', 'Standard_E4a_v4', 'Standard_D4_v4', 'Standard_E8-2ds_v4', 'Standard_E2ds_v4', 'Standard_E80is_v4', 'Standard_D16ds_v5', 'Standard_D48s_v5', 'Standard_DS11', 'Standard_NC6s_v2', 'Standard_D2ds_v5', 'Standard_M64-32ms', 'Standard_D32ds_v4', 'Standard_DS3_v2', 'Standard_E20d_v4', 'Standard_D64s_v5', 'Standard_HB60-15rs', 'Standard_HB120-96rs_v3', 'Standard_E16s_v4', 'Standard_E8-2as_v4', 'Standard_D48a_v4', 'Standard_M416-104s_v2', 'Standard_E2d_v4', 'Standard_E64-32as_v4', 'Standard_D8a_v4', 'Standard_D5_v2', 'Standard_DC2s', 'Standard_D4d_v5', 'Standard_E20as_v4', 'Standard_M64dms_v2', 'Standard_A1', 'Standard_D4_v2', 'Standard_M128dms_v2', 'Standard_M64ms', 'Standard_A4_v2', 'Standard_D2_v5', 'Standard_DS2_v2', 'Standard_DS13-2_v2', 'Standard_D4s_v4', 'Standard_L8s_v2', 'Standard_E32s_v4', 'Standard_H16', 'Standard_NC64as_T4_v3', 'Standard_NP10s', 'Standard_E32_v4', 'Standard_L88is_v2', 'Standard_D15i_v2', 'Standard_M192is_v2', 'Standard_HB120-64rs_v3', 'Standard_ND40rs_v2', 'Standard_E20_v3', 'Standard_D96d_v5', 'Standard_D2s_v4', 'Standard_E2as_v4', 'Standard_E64s_v3', 'Standard_M16-4ms', 'Standard_E64i_v3', 'Standard_A11', 'Standard_A1_v2', 'Standard_F72s_v2', 'Standard_D1_v2', 'Standard_M8-4ms', 'Standard_ND96asr_v4', 'Standard_D14_v2', 'Standard_E48s_v3', 'Standard_M64ls', 'Standard_D32a_v4', 'Standard_M64', 'Standard_DS11-1_v2', 'Standard_ND6s', 'Standard_D16s_v4', 'Standard_H8', 'Standard_ND40s_v2', 'Standard_HC44rs', 'Standard_A9', 'Standard_NC12s_v2', 'Standard_D96s_v5', 'Standard_D48_v4', 'Standard_H8m', 'Standard_DS1', 'Standard_D2_v4', 'Standard_E4as_v4', 'Standard_M16ms', 'Standard_D13', 'Standard_NC12', 'Standard_E8d_v5', 'Standard_E32s_v3', 'Standard_M416-104ms_v2', 'Standard_HC44-16rs', 'Standard_D96a_v4', 'Standard_M128-32ms', 'Standard_L48s_v2', 'Standard_HB60-45rs', 'Standard_D2', 'Standard_E16as_v4', 'Standard_E16a_v4', 'Standard_PB24s', 'Standard_M128ms_v2', 'Standard_M208s_v2', 'Standard_E4-2s_v3', 'Standard_E16-8as_v4', 'Standard_NV24', 'Standard_DC1s_v2', 'Standard_E64_v4', 'Standard_D32-8s_v3', 'Standard_D3_v2', 'Standard_E8_v5', 'Standard_D16ds_v4', 'Standard_L80s_v2', 'Standard_E20s_v3', 'Standard_D11', 'Standard_E2a_v4', 'Basic_A3', 'Standard_M192ims_v2', 'Standard_E20d_v5', 'Standard_D4_v3', 'Standard_NC24rs_v2', 'Standard_D8_v3', 'Standard_D2ds_v4', 'Standard_NP40s', 'Standard_D64_v3', 'Standard_D64d_v5', 'Standard_M128ms', 'Standard_M64-16ms', 'Standard_D2s_v5', 'Standard_D16_v5', 'Standard_DS13_v2', 'Standard_NV4as_v4', 'Standard_E32-8as_v4', 'Standard_E2_v3', 'Standard_E4ds_v4', 'Standard_H16m', 'Standard_NC24rs_v3', 'Standard_E64-16ds_v4', 'Standard_D32_v4', 'Standard_D48s_v4', 'Standard_M16-8ms', 'Standard_D96ds_v5', 'Standard_E32-16s_v3', 'Standard_NC24r', 'Standard_E16_v5', 'Standard_E64-16s_v3', 'Standard_E4-2s_v4', 'Standard_NV16as_v4', 'Standard_D64a_v4', 'Standard_E2_v5', 'Standard_HB120-32rs_v3', 'Standard_D48_v5', 'Standard_M8ms', 'Standard_DS13-4_v2', 'Standard_D4as_v4', 'Standard_E16_v3', 'Standard_F2s_v2', 'Standard_D16a_v4', 'Standard_E64s_v4', 'Standard_E8ds_v4', 'Standard_D2_v3', 'Standard_M32-16ms', 'Standard_PB6s', 'Standard_HB120-16rs_v3', 'Standard_E8s_v4', 'Standard_F1s', 'Standard_D16s_v5', 'Standard_E48_v4', 'Standard_D48_v3', 'Standard_E16-4as_v4', 'Standard_E8a_v4', 'Standard_F2s', 'Standard_DC4s', 'Standard_E48d_v4', 'Standard_DS12_v2', 'Standard_F48s_v2', 'Standard_F64s_v2', 'Standard_DS4', 'Standard_D4_v5', 'Standard_L16s_v2', 'Standard_D48as_v4', 'Standard_D4d_v4', 'Standard_E16-4s_v3', 'Standard_E96-48as_v4', 'Standard_DS14-8_v2', 'Standard_ND96amsr_A100_v4', 'Standard_M128s', 'Standard_F32s_v2', 'Standard_D8d_v5', 'Standard_E16d_v4', 'Standard_DS2', 'Standard_HB60rs', 'Standard_E2_v4', 'Standard_F16s', 'Standard_D48d_v4', 'Basic_A4', 'Standard_D4a_v4', 'Standard_L32s_v2', 'Standard_PB12s', 'Standard_E8-4ds_v4', 'Standard_D32d_v5', 'Standard_E4-2as_v4', 'Standard_D2_v2', 'Standard_E4-2ds_v4', 'Standard_D16_v4', 'Standard_E8as_v4', 'Standard_E96as_v4', '', 'Standard_HB120rs_v3', 'Standard_M32ls', 'Standard_F2', 'Standard_E8d_v4', 'Standard_E48d_v5', 'Standard_E20s_v4', 'Standard_D12_v2', 'Standard_NC12s_v3', 'Standard_D8s_v4', 'Standard_M64s', 'Standard_E20_v5', 'Standard_A0', 'Standard_D96_v5', 'Standard_E48s_v4', 'Standard_E96a_v4', 'Standard_E64ds_v4', 'Standard_F1', 'Standard_E48_v5', 'Standard_D32s_v4', 'Standard_E16_v4', 'Standard_D4ds_v4', 'Standard_E20_v4', 'Standard_M16s', 'Standard_E16-4s_v4', 'Standard_E96_v5', 'Standard_D8as_v4', 'Standard_E32ds_v4', 'Standard_A6', 'Standard_H16mr', 'Standard_D16d_v5', 'Standard_D32d_v4', 'Standard_E32-8s_v3', 'Standard_E4d_v4', 'Standard_DS4_v2', 'Standard_DS14', 'Standard_E32-16ds_v4', 'Standard_M128', 'Standard_D64s_v3', 'Standard_E8-2s_v3', 'Standard_E32-16as_v4', 'Standard_M32ms', 'Standard_NC24', 'Basic_A0', 'Standard_DS14-4_v2', 'Standard_E16d_v5', 'Standard_D32s_v5', 'Standard_NC8as_T4_v3', 'Standard_DC2s_v2', 'Standard_D64-32s_v3', 'Standard_E48ds_v4', 'Standard_E64-32ds_v4', 'Standard_A2_v2', 'Standard_E8_v4', 'Standard_DS1_v2', 'Standard_E2s_v4', 'Standard_E8-4s_v4', 'Standard_NC24s_v2', 'Standard_E16-8s_v3', 'Standard_E64-32s_v3', 'Standard_A4', 'Standard_E8-4as_v4', 'Standard_A7', 'Standard_F8s_v2', 'Standard_DS12', 'Standard_A8m_v2', 'Standard_E64d_v4', 'Standard_E32_v5', 'Standard_M192ids_v2', 'Standard_E64as_v4', 'Standard_D64ds_v4', 'Standard_D8ds_v5', 'Standard_HC44-32rs', 'Standard_E64-16s_v4', 'Standard_E2d_v5', 'Standard_F4s_v2', 'Standard_DS11_v2', 'Standard_D32_v5', 'Standard_NV12s_v3', 'Standard_E64is_v3', 'Standard_D3', 'Standard_M416is_v2', 'Standard_E8s_v3', 'Standard_E4s_v3', 'Standard_E32-8ds_v4', 'Standard_NC6', 'Standard_D8d_v4', 'Standard_E8-4s_v3', 'Basic_A2', 'Standard_E16-8s_v4', 'Standard_E4s_v4', 'Standard_ND12s', 'Standard_D8_v5', 'Standard_E64a_v4', 'Standard_D4', 'Standard_E16ds_v4', 'Standard_M208-104ms_v2', 'Standard_DC4s_v2', 'Standard_D8s_v3', 'Standard_M32s', 'Standard_E96-24as_v4', 'Standard_E64-16as_v4', 'Standard_A3', 'Standard_E2s_v3', 'Standard_E32as_v4', 'Standard_NV32as_v4', 'Standard_A5', 'Standard_DS3', 'Standard_D48d_v5', 'Standard_A8', 'Standard_D32_v3', 'Standard_E20a_v4', 'Standard_E8-2s_v4', 'Standard_E4_v3', 'Standard_M416ms_v2', 'Standard_M416-208ms_v2', 'Standard_M208-52s_v2', 'Standard_E64-32s_v4', 'Standard_E16s_v3', 'Standard_NV24s_v3', 'Standard_F16', 'Standard_A10', 'Standard_NV48s_v3', 'Basic_A1', 'Standard_D16as_v4', 'Standard_D2s_v3', 'Standard_NV6', 'Standard_D48s_v3', 'Standard_D2as_v4', 'Standard_D64s_v4', 'Standard_D96as_v4', 'Standard_DS13', 'Standard_D2d_v4', 'Standard_D4s_v3', 'Standard_NC16as_T4_v3', 'Standard_D64d_v4', 'Standard_F4', 'Standard_M64ms_v2', 'Standard_D2d_v5', 'Standard_NC6s_v3', 'Standard_E64d_v5', 'Standard_M208-104s_v2', 'Standard_M208-52ms_v2', 'Standard_D12', 'Standard_DS15i_v2', 'Standard_E64_v3', 'Standard_E96d_v5', 'Standard_M192idms_v2', 'Standard_F16s_v2', 'Standard_NV12', 'Standard_M128s_v2', 'Standard_D8ds_v4', 'Standard_F8', 'Standard_DC8_v2', 'Standard_E48_v3', 'Standard_M128ds_v2', 'Standard_D11_v2', 'Standard_E4d_v5', 'Standard_H16r', 'Standard_D64-16s_v3', 'Standard_NC4as_T4_v3', 'Standard_F8s', 'Standard_D8s_v5', 'Standard_D13_v2', 'Standard_E16-4ds_v4', 'Standard_A2m_v2', 'Standard_M64m', 'Standard_L64s_v2', 'Standard_D16d_v4', 'Standard_E32d_v4', 'Standard_E4_v4', 'Standard_E4_v5', 'Standard_E8_v3', 'Standard_D64_v5', 'Standard_D32-16s_v3', 'Standard_M64ds_v2', 'Standard_D64as_v4', 'Standard_M416-208s_v2', 'Standard_DS15_v2', 'Standard_M128m', 'Standard_A2', 'Standard_DS5_v2', 'Standard_E16-8ds_v4', 'Standard_F4s', 'Standard_E32d_v5', 'Standard_D32ds_v5', 'Standard_HB60-30rs', 'Standard_D48ds_v4', 'Standard_D4ds_v5', 'Standard_E64_v5', 'Standard_M208ms_v2', 'Standard_A4m_v2', 'Standard_DS14_v2', 'Standard_E32_v3', 'Standard_M416s_v2', 'Standard_D16s_v3', 'Standard_ND24rs', 'Standard_M32dms_v2', 'Standard_E80ids_v4', 'Standard_E32a_v4', 'Standard_D64ds_v5', 'Standard_NV8as_v4', 'Standard_D1', 'Standard_HB120rs_v2', 'Standard_M32ms_v2', 'Standard_D15_v2', 'Standard_D32s_v3', 'Standard_E20ds_v4', 'Standard_ND96asr_A100_v4', 'Standard_D8_v4', 'Standard_ND24s', 'Standard_D4s_v5', 'Standard_M128-64ms', 'Standard_DS12-1_v2', 'Standard_DS12-2_v2', 'Standard_E32-16s_v4', 'Standard_NC24s_v3'],
'eastus2': ['Standard_E64i_v3', 'Standard_DS11-1_v2', 'Standard_D14', 'Standard_F4', 'Standard_M32-16ms', 'Standard_E64s_v3', 'Standard_D8d_v5', 'Standard_E64d_v5', 'Standard_E64a_v4', 'Standard_E96a_v4', 'Standard_GS5-16', 'Standard_E64-16s_v4', 'Standard_E2_v3', 'Standard_M32dms_v2', 'Standard_E96-48as_v4', 'Standard_M416s_v2', 'Standard_E64s_v4', 'Standard_D8_v3', 'Standard_D4s_v5', 'Standard_F1s', 'Standard_D13', 'Standard_F1', 'Standard_NC6s_v3', 'Standard_E48s_v3', 'Standard_M64ls', 'Standard_D32-16s_v3', 'Standard_E2a_v4', 'Standard_D48_v5', 'Standard_D11_v2', 'Standard_E48_v5', 'Standard_DS13-4_v2', 'Standard_M192is_v2', 'Standard_E16_v3', 'Standard_DS13', 'Standard_D3_v2', 'Standard_E4-2ds_v4', 'Standard_E96as_v4', 'Standard_D64as_v4', 'Standard_F16', 'Standard_E8a_v4', 'Standard_D16ds_v4', 'Standard_E4s_v3', 'Standard_E20_v5', 'Standard_L8s', 'Standard_A4m_v2', 'Standard_D2ds_v4', 'Standard_DS12_v2', 'Standard_D32d_v5', 'Standard_M64-32ms', 'Standard_E4-2s_v4', 'Standard_D64a_v4', 'Standard_F64s_v2', 'Standard_D48s_v5', 'Standard_D64_v5', 'Standard_L48s_v2', 'Standard_E2s_v4', 'Standard_E16a_v4', 'Standard_M208-104ms_v2', 'Standard_D2d_v5', 'Standard_E32-16ds_v4', 'Standard_G3', 'Standard_G2', 'Standard_M128ms', 'Standard_E64-32as_v4', 'Standard_A2m_v2', 'Standard_E20as_v4', 'Basic_A1', 'Standard_G5', 'Standard_D3', 'Standard_E20_v4', 'Standard_M128s', 'Standard_D96ds_v5', 'Standard_E32_v5', 'Standard_M416-104ms_v2', 'Standard_M64dms_v2', 'Standard_DS2_v2', 'Standard_D8a_v4', 'Standard_D32ds_v5', 'Standard_E64_v4', 'Standard_M16s', 'Standard_E8-2s_v4', 'Standard_A6', 'Standard_DS15i_v2', 'Standard_GS2', 'Standard_D8as_v4', 'Standard_E2d_v4', 'Standard_D32_v4', 'Standard_D12_v2', 'Standard_D2_v5', 'Standard_A7', 'Standard_DS15_v2', 'Standard_D48d_v5', 'Standard_D15i_v2', 'Standard_E32ds_v4', 'Standard_D32s_v3', 'Standard_E32-8as_v4', 'Standard_D16_v4', 'Standard_D96as_v4', 'Standard_E48d_v5', 'Standard_NC16as_T4_v3', 'Standard_E32-8ds_v4', 'Standard_D4ds_v4', 'Standard_E32-16s_v3', 'Standard_E8_v5', 'Standard_D11', 'Standard_DS12-1_v2', 'Standard_D32_v5', 'Standard_L32s_v2', 'Standard_L32s', 'Standard_E20s_v4', 'Standard_E48a_v4', 'Standard_E20d_v4', 'Standard_D16s_v5', 'Standard_E16-4s_v3', 'Standard_E48s_v4', 'Standard_A4', 'Standard_A3', 'Standard_L16s_v2', 'Standard_D64-16s_v3', 'Standard_E64_v5', 'Standard_GS4-8', 'Standard_DS14', 'Standard_D64ds_v5', 'Standard_E8s_v4', 'Standard_DS14-8_v2', 'Standard_DS12', 'Standard_E4d_v5', 'Standard_NV24s_v3', 'Standard_E64-16as_v4', 'Basic_A2', 'Standard_D64s_v5', 'Standard_F8s_v2', 'Standard_D64s_v3', 'Standard_D2s_v5', 'Standard_A0', 'Standard_D4ds_v5', 'Standard_ND96amsr_A100_v4', '', 'Standard_NC12', 'Standard_M32ms_v2', 'Standard_NV12', 'Standard_GS4-4', 'Standard_E48_v3', 'Standard_F2s', 'Standard_NV6', 'Standard_D8_v5', 'Standard_D8_v4', 'Standard_D48d_v4', 'Standard_D48ds_v5', 'Standard_L80s_v2', 'Standard_D1_v2', 'Standard_M192idms_v2', 'Standard_F2s_v2', 'Standard_D32s_v4', 'Standard_M192ims_v2', 'Standard_E64-16s_v3', 'Standard_GS5-8', 'Standard_D32d_v4', 'Standard_L16s', 'Standard_D1', 'Standard_E16-4as_v4', 'Standard_DS5_v2', 'Standard_D96a_v4', 'Standard_D48s_v4', 'Standard_E64-16ds_v4', 'Standard_D2d_v4', 'Standard_E64-32s_v4', 'Standard_GS5', 'Standard_D32ds_v4', 'Standard_E8d_v4', 'Standard_D64d_v4', 'Standard_D16ds_v5', 'Standard_E64-32s_v3', 'Standard_D32s_v5', 'Standard_M8-4ms', 'Standard_D4_v3', 'Standard_D5_v2', 'Standard_A5', 'Standard_M208s_v2', 'Standard_E32as_v4', 'Standard_M416-208s_v2', 'Standard_M416-104s_v2', 'Standard_DS3_v2', 'Standard_M192ids_v2', 'Standard_E4-2as_v4', 'Standard_M128-32ms', 'Standard_NC24s_v3', 'Standard_D15_v2', 'Standard_E32d_v4', 'Standard_D2_v3', 'Standard_E16-8s_v3', 'Standard_M416is_v2', 'Standard_A1', 'Standard_D16_v3', 'Standard_E32_v4', 'Standard_F8s', 'Standard_L88is_v2', 'Standard_E2s_v3', 'Standard_M208-104s_v2', 'Standard_F16s_v2', 'Standard_E16_v4', 'Standard_E16d_v5', 'Standard_A2_v2', 'Standard_E48as_v4', 'Standard_E8-2s_v3', 'Standard_E4s_v4', 'Standard_D32as_v4', 'Standard_M32s', 'Standard_D64_v4', 'Standard_E4_v5', 'Standard_NC8as_T4_v3', 'Standard_E20_v3', 'Standard_D4d_v4', 'Standard_E8as_v4', 'Standard_E80ids_v4', 'Standard_M128-64ms', 'Standard_E2_v4', 'Standard_D96s_v5', 'Standard_E4_v4', 'Standard_D8s_v4', 'Standard_M208-52ms_v2', 'Standard_D8ds_v5', 'Standard_M128ds_v2', 'Standard_E48d_v4', 'Standard_D14_v2', 'Standard_E8-4ds_v4', 'Standard_GS4', 'Standard_E16ds_v4', 'Standard_E2d_v5', 'Standard_M208ms_v2', 'Standard_D4_v4', 'Standard_M16ms', 'Standard_L4s', 'Standard_D16s_v4', 'Standard_D8s_v5', 'Standard_M32ms', 'Standard_D2_v2', 'Standard_M64s', 'Standard_DS1_v2', 'Standard_D16d_v5', 'Standard_F72s_v2', 'Standard_A2', 'Standard_M128s_v2', 'Standard_NC64as_T4_v3', 'Standard_E96d_v5', 'Standard_E16as_v4', 'Standard_M8-2ms', 'Standard_D64ds_v4', 'Standard_D4d_v5', 'Standard_E4_v3', 'Standard_D12', 'Standard_D4_v5', 'Standard_E16_v5', 'Standard_DS4_v2', 'Standard_E64_v3', 'Standard_M32ls', 'Standard_G1', 'Standard_E8ds_v4', 'Standard_E8_v3', 'Basic_A3', 'Standard_E16-4ds_v4', 'Standard_A8_v2', 'Standard_F2', 'Standard_D48a_v4', 'Standard_E20a_v4', 'Standard_D64s_v4', 'Standard_M16-4ms', 'Standard_E32s_v3', 'Standard_M128m', 'Standard_DS11_v2', 'Standard_E8s_v3', 'Standard_D96_v5', 'Standard_NV24', 'Standard_D2a_v4', 'Standard_M128', 'Standard_M208-52s_v2', 'Standard_E16s_v3', 'Standard_D4_v2', 'Standard_M8ms', 'Standard_M416-208ms_v2', 'Standard_D8s_v3', 'Standard_D16d_v4', 'Standard_E8-2as_v4', 'Standard_A8m_v2', 'Standard_D64_v3', 'Standard_D48as_v4', 'Standard_M128ms_v2', 'Standard_DS13_v2', 'Standard_D48s_v3', 'Standard_DS1', 'Standard_E16-8ds_v4', 'Standard_M64ms_v2', 'Standard_E4ds_v4', 'Standard_E96_v5', 'Standard_F4s', 'Standard_E16-8as_v4', 'Standard_F48s_v2', 'Standard_D16as_v4', 'Standard_E80is_v4', 'Standard_GS1', 'Standard_D2', 'Standard_M64-16ms', 'Standard_F32s_v2', 'Standard_DS14_v2', 'Standard_D2s_v3', 'Standard_NV4as_v4', 'Standard_NV12s_v3', 'Standard_D32-8s_v3', 'Standard_E64-32ds_v4', 'Standard_D16s_v3', 'Standard_E48_v4', 'Standard_M416ms_v2', 'Standard_D2_v4', 'Standard_D96d_v5', 'Standard_E8_v4', 'Standard_D48ds_v4', 'Standard_D2ds_v5', 'Standard_M64s_v2', 'Standard_NC24rs_v3', 'Standard_E4d_v4', 'Standard_E32d_v5', 'Standard_F8', 'Standard_M16-8ms', 'Basic_A0', 'Standard_E20ds_v4', 'Standard_E96-24as_v4', 'Standard_D4s_v4', 'Standard_D13_v2', 'Standard_NV32as_v4', 'Standard_NV8as_v4', 'Standard_E8d_v5', 'Standard_E8-4s_v3', 'Standard_D16_v5', 'Standard_DS12-2_v2', 'Standard_E8-4s_v4', 'Standard_E16-8s_v4', 'Standard_E32-16s_v4', 'Standard_D48_v3', 'Standard_D4s_v3', 'Standard_F4s_v2', 'Standard_D4a_v4', 'Standard_E32-16as_v4', 'Standard_DS11', 'Standard_E4as_v4', 'Standard_D2as_v4', 'Standard_E32-8s_v3', 'Standard_E20s_v3', 'Standard_DS14-4_v2', 'Standard_E2_v5', 'Standard_M64ds_v2', 'Standard_D32_v3', 'Standard_D16a_v4', 'Standard_E64is_v3', 'Standard_E32_v3', 'Standard_L64s_v2', 'Standard_DS4', 'Standard_GS3', 'Standard_E8-2ds_v4', 'Standard_D4', 'Standard_M32-8ms', 'Standard_G4', 'Standard_E2ds_v4', 'Standard_M64ms', 'Standard_E16d_v4', 'Standard_D32a_v4', 'Standard_E32s_v4', 'Standard_D4as_v4', 'Standard_E4a_v4', 'Standard_M64m', 'Basic_A4', 'Standard_D48_v4', 'Standard_D64d_v5', 'Standard_NC24', 'Standard_E32-8s_v4', 'Standard_M128dms_v2', 'Standard_NV16as_v4', 'Standard_E64ds_v4', 'Standard_D8ds_v4', 'Standard_E16-4s_v4', 'Standard_E16s_v4', 'Standard_DS3', 'Standard_NC4as_T4_v3', 'Standard_A4_v2', 'Standard_A1_v2', 'Standard_DS13-2_v2', 'Standard_D2s_v4', 'Standard_E32a_v4', 'Standard_E48ds_v4', 'Standard_NC24r', 'Standard_D64-32s_v3', 'Standard_L8s_v2', 'Standard_NC12s_v3', 'Standard_E4-2s_v3', 'Standard_E8-4as_v4', 'Standard_D8d_v4', 'Standard_M64', 'Standard_E64as_v4', 'Standard_NC6', 'Standard_DS2', 'Standard_E2as_v4', 'Standard_E64d_v4', 'Standard_M32ts', 'Standard_NV48s_v3', 'Standard_F16s', 'Standard_E20d_v5'],
'westus': ['Standard_E16a_v4', 'Standard_D4_v2', 'Standard_D96a_v4', 'Standard_L64s_v2', 'Standard_E96a_v4', 'Standard_D1_v2', 'Standard_E20ds_v4', 'Standard_G1', 'Standard_E16-8s_v3', 'Standard_DC1s_v2', 'Standard_D8ds_v4', 'Standard_D48ds_v4', 'Standard_NV12s_v3', 'Standard_E32s_v3', 'Standard_DS3', 'Standard_D48ds_v5', 'Standard_A2_v2', 'Standard_D8s_v5', 'Standard_D16a_v4', 'Basic_A4', 'Standard_D32_v4', 'Standard_D2a_v4', 'Standard_A2', 'Standard_F64s_v2', 'Standard_D64s_v5', 'Standard_M128s', 'Standard_D32s_v5', 'Standard_E20_v5', 'Standard_D16d_v4', 'Standard_E4-2as_v4', 'Standard_E96_v5', 'Standard_F16', 'Standard_M64s_v2', 'Standard_E48s_v3', 'Standard_M32s', 'Standard_M208-104s_v2', 'Standard_D4d_v5', 'Standard_D64as_v4', 'Standard_M32ms', 'Standard_M128ms', 'Standard_D4a_v4', 'Standard_D32_v5', 'Standard_D16d_v5', 'Standard_M416-104s_v2', 'Standard_DS14_v2', 'Standard_L32s_v2', 'Standard_E8s_v3', 'Standard_F8s', 'Standard_E20as_v4', 'Standard_E20_v3', 'Standard_D15i_v2', 'Standard_E16-4s_v4', 'Standard_A0', 'Standard_M416ms_v2', 'Standard_M128s_v2', 'Standard_D8_v5', 'Standard_E80ids_v4', 'Standard_DS11_v2', 'Standard_E32_v3', 'Standard_DS14', 'Standard_D4d_v4', 'Standard_M64ms_v2', 'Standard_F4', 'Standard_D32s_v4', 'Standard_E4s_v4', 'Standard_E20s_v4', 'Standard_M16-8ms', 'Standard_F2s_v2', 'Standard_NC6s_v3', 'Standard_M416-104ms_v2', 'Standard_M192ids_v2', 'Standard_E16-8s_v4', 'Standard_E64_v5', 'Standard_E4d_v4', 'Standard_H8', 'Standard_D2ds_v5', 'Standard_DS1_v2', 'Standard_A11', 'Standard_M64dms_v2', 'Standard_F16s_v2', 'Standard_E64-16s_v4', 'Standard_D96d_v5', 'Standard_DS4', 'Standard_D8as_v4', 'Standard_E32-8s_v4', 'Standard_D1', 'Standard_E8s_v4', 'Standard_E16d_v4', 'Standard_M128-64ms', 'Standard_E64-32as_v4', 'Standard_D32_v3', 'Standard_DS11-1_v2', 'Standard_E48d_v5', 'Standard_G5', 'Standard_E2d_v5', 'Standard_E4as_v4', 'Standard_A4m_v2', 'Standard_E32as_v4', 'Standard_E8-2s_v4', 'Standard_D8d_v5', 'Standard_DS11', 'Standard_D16s_v4', 'Standard_D16_v5', 'Standard_D64ds_v4', 'Standard_F48s_v2', 'Standard_E80is_v4', 'Standard_D2as_v4', 'Standard_D2_v5', 'Standard_M208-52ms_v2', 'Standard_D2d_v4', 'Standard_NC8as_T4_v3', 'Standard_E16s_v3', 'Standard_E8-4s_v4', 'Standard_E8-2ds_v4', 'Standard_M64-16ms', 'Standard_E64a_v4', 'Standard_M16s', 'Standard_D2_v2', 'Basic_A1', 'Standard_D4_v4', 'Standard_E4d_v5', 'Standard_E64-16as_v4', 'Standard_GS3', 'Standard_D48d_v5', 'Standard_GS4-4', 'Standard_F4s', 'Standard_F1s', 'Standard_M416s_v2', 'Standard_M16-4ms', 'Standard_E20s_v3', 'Standard_D64ds_v5', 'Standard_D16s_v5', 'Standard_F72s_v2', 'Standard_D14', 'Standard_M64ds_v2', 'Standard_GS5-8', 'Standard_D64-16s_v3', 'Standard_E20_v4', 'Standard_D16ds_v5', 'Standard_E64i_v3', 'Standard_D96s_v5', 'Standard_D3_v2', 'Standard_M128-32ms', 'Standard_D16as_v4', 'Standard_D96as_v4', 'Standard_E16_v4', 'Standard_DC8_v2', 'Standard_E16-4s_v3', 'Standard_DS1', 'Standard_D64d_v4', 'Standard_L4s', 'Standard_A3', 'Standard_D12', 'Standard_DS5_v2', 'Standard_E96d_v5', 'Standard_E32-16s_v3', 'Standard_M8-2ms', 'Standard_D32ds_v4', 'Standard_NC12s_v3', 'Standard_A10', 'Standard_E2a_v4', 'Standard_D8_v3', 'Standard_E20d_v4', 'Standard_E32_v4', 'Standard_E2_v5', 'Standard_D4ds_v4', 'Standard_F16s', 'Standard_D4ds_v5', 'Standard_D32d_v5', 'Standard_E8_v4', 'Standard_DS13-4_v2', 'Standard_H8m', 'Standard_E64-32s_v3', 'Standard_D12_v2', 'Standard_D4_v5', 'Standard_A8_v2', 'Standard_E48_v3', 'Standard_M64m', 'Standard_A7', 'Standard_DS4_v2', 'Standard_DS14-8_v2', 'Standard_E48_v5', 'Standard_D16ds_v4', 'Standard_L32s', 'Standard_E16ds_v4', 'Standard_D8s_v4', 'Standard_E32a_v4', 'Standard_L88is_v2', 'Standard_E96-48as_v4', 'Standard_D48s_v4', 'Standard_E8_v3', 'Standard_D48_v4', 'Standard_E8-4s_v3', 'Standard_D2', 'Standard_E4a_v4', 'Standard_A6', 'Standard_E64-32ds_v4', 'Standard_E32s_v4', 'Standard_E32-16as_v4', 'Standard_A4', 'Standard_D4s_v3', 'Standard_D96_v5', 'Standard_M192is_v2', 'Standard_E2as_v4', 'Standard_E64-32s_v4', 'Standard_D2s_v3', 'Standard_M32-16ms', 'Standard_DS12-1_v2', 'Standard_D4s_v4', '', 'Standard_E64d_v4', 'Standard_E2s_v3', 'Basic_A0', 'Standard_GS1', 'Standard_D48_v5', 'Standard_D32a_v4', 'Standard_E16s_v4', 'Basic_A3', 'Standard_E32-8s_v3', 'Standard_NC24s_v3', 'Standard_E8-4as_v4', 'Standard_D96ds_v5', 'Standard_D64_v5', 'Standard_D5_v2', 'Standard_E64s_v3', 'Standard_E16-4ds_v4', 'Standard_E2_v3', 'Standard_H16m', 'Standard_E48a_v4', 'Standard_D64a_v4', 'Standard_DS12', 'Standard_E8ds_v4', 'Standard_D8ds_v5', 'Standard_D16s_v3', 'Standard_D32s_v3', 'Standard_D2d_v5', 'Standard_M32ms_v2', 'Standard_D13', 'Standard_M64s', 'Standard_E8d_v5', 'Standard_E64-16s_v3', 'Standard_D32as_v4', 'Standard_E2d_v4', 'Standard_D4s_v5', 'Standard_E48as_v4', 'Standard_F8s_v2', 'Standard_DS15_v2', 'Standard_D4_v3', 'Standard_M32ls', 'Standard_F32s_v2', 'Standard_A1', 'Standard_G2', 'Standard_M32ts', 'Standard_E16d_v5', 'Standard_D4', 'Standard_D8a_v4', 'Standard_A2m_v2', 'Standard_NV12s_v2', 'Standard_GS5', 'Standard_NC64as_T4_v3', 'Standard_DS2_v2', 'Standard_D16_v4', 'Standard_E16_v3', 'Standard_D16_v3', 'Standard_D64d_v5', 'Standard_NV6s_v2', 'Standard_E8-4ds_v4', 'Standard_E8_v5', 'Standard_E20d_v5', 'Standard_E32-8ds_v4', 'Standard_E32-16s_v4', 'Standard_E4ds_v4', 'Standard_M8-4ms', 'Standard_DS13_v2', 'Standard_D2s_v4', 'Standard_E96as_v4', 'Standard_E64ds_v4', 'Standard_E4s_v3', 'Standard_D32ds_v5', 'Standard_D11', 'Standard_D2s_v5', 'Standard_E64d_v5', 'Standard_F4s_v2', 'Standard_A8', 'Standard_M208-52s_v2', 'Standard_E4-2s_v4', 'Standard_GS2', 'Standard_E20a_v4', 'Standard_D32-8s_v3', 'Standard_E32ds_v4', 'Standard_H16r', 'Standard_M128ds_v2', 'Standard_D14_v2', 'Standard_E48_v4', 'Standard_D48s_v5', 'Standard_M128ms_v2', 'Standard_D2_v3', 'Standard_NV48s_v3', 'Standard_E8as_v4', 'Standard_E16-8as_v4', 'Standard_GS4', 'Standard_D2_v4', 'Standard_M16ms', 'Standard_G4', 'Standard_M208ms_v2', 'Standard_M416is_v2', 'Standard_E8d_v4', 'Standard_DS3_v2', 'Standard_DS13-2_v2', 'Standard_E2_v4', 'Standard_D64s_v4', 'Standard_D48s_v3', 'Standard_D64-32s_v3', 'Standard_D32-16s_v3', 'Standard_E4_v5', 'Standard_L16s', 'Standard_E48s_v4', 'Standard_E4_v4', 'Standard_D48as_v4', 'Standard_DS13', 'Standard_NC16as_T4_v3', 'Standard_E16-4as_v4', 'Standard_D8_v4', 'Standard_NV24s_v2', 'Standard_D48d_v4', 'Standard_L48s_v2', 'Standard_D11_v2', 'Standard_E4_v3', 'Standard_D48_v3', 'Standard_DC2s_v2', 'Standard_E8-2s_v3', 'Standard_DS14-4_v2', 'Standard_M32dms_v2', 'Standard_E48d_v4', 'Standard_E4-2s_v3', 'Standard_L8s', 'Standard_E32-16ds_v4', 'Standard_D64_v3', 'Standard_D8s_v3', 'Standard_L16s_v2', 'Standard_E64is_v3', 'Standard_D64s_v3', 'Standard_E16-8ds_v4', 'Standard_A8m_v2', 'Standard_E32-8as_v4', 'Standard_DS12_v2', 'Standard_NC4as_T4_v3', 'Standard_E64_v3', 'Standard_GS5-16', 'Standard_A1_v2', 'Standard_A5', 'Standard_NV24s_v3', 'Standard_D2ds_v4', 'Standard_E2s_v4', 'Standard_D4as_v4', 'Standard_M192idms_v2', 'Standard_E64-16ds_v4', 'Standard_M192ims_v2', 'Standard_DC4s_v2', 'Standard_D3', 'Standard_E32_v5', 'Standard_D8d_v4', 'Standard_E96-24as_v4', 'Standard_F8', 'Standard_L96s_v2', 'Standard_DS2', 'Standard_E64_v4', 'Standard_D13_v2', 'Standard_E16as_v4', 'Standard_E16_v5', 'Standard_E2ds_v4', 'Standard_NC24rs_v3', 'Standard_A4_v2', 'Standard_M64ls', 'Standard_D48a_v4', 'Standard_F2', 'Standard_M64ms', 'Standard_DS12-2_v2', 'Standard_E32d_v5', 'Standard_M64', 'Standard_E48ds_v4', 'Standard_M208s_v2', 'Standard_E8-2as_v4', 'Standard_M416-208ms_v2', 'Standard_M208-104ms_v2', 'Standard_G3', 'Standard_M8ms', 'Standard_F1', 'Standard_GS4-8', 'Standard_M64-32ms', 'Standard_A9', 'Standard_D32d_v4', 'Standard_M416-208s_v2', 'Standard_M128', 'Standard_F2s', 'Standard_E64s_v4', 'Standard_D64_v4', 'Standard_E32d_v4', 'Standard_H16mr', 'Standard_L8s_v2', 'Basic_A2', 'Standard_DS15i_v2', 'Standard_L80s_v2', 'Standard_D15_v2', 'Standard_H16', 'Standard_E8a_v4', 'Standard_M128dms_v2', 'Standard_E64as_v4', 'Standard_E4-2ds_v4', 'Standard_M32-8ms', 'Standard_M128m'],
'westus2': ['Standard_D16ds_v4', 'Standard_E4d_v5', 'Standard_E8ds_v4', 'Standard_H16mr', 'Standard_E8-4ds_v4', 'Standard_E2d_v4', 'Standard_NC12s_v3', 'Standard_E48a_v4', 'Standard_M8ms', 'Standard_M208-104ms_v2', 'Standard_NC24', 'Standard_DS13-4_v2', 'Standard_D32s_v3', 'Standard_D96as_v4', 'Standard_E16s_v3', 'Standard_A2_v2', 'Standard_DC2s_v2', 'Standard_E20as_v4', 'Standard_F2s', 'Standard_E2s_v3', 'Standard_M208ms_v2', 'Standard_A4_v2', 'Standard_M416ms_v2', 'Standard_PB12s', 'Standard_D8d_v4', 'Standard_D8s_v4', 'Standard_L88is_v2', 'Standard_E4-2s_v3', 'Standard_E4-2as_v4', 'Standard_E96_v5', 'Standard_A5', 'Standard_E64s_v3', 'Standard_D32a_v4', 'Standard_D48_v5', 'Standard_M416-104s_v2', 'Standard_D48s_v5', 'Standard_D2s_v3', 'Standard_D96s_v5', 'Standard_D2_v3', 'Standard_M416s_v2', 'Standard_E64i_v3', 'Standard_E48_v3', 'Standard_D4s_v3', 'Standard_F8', 'Standard_A3', 'Standard_E32-16as_v4', 'Standard_M416-104ms_v2', 'Standard_D64_v5', 'Standard_DC1s_v2', 'Standard_E64a_v4', 'Standard_E20_v5', 'Standard_L8s_v2', 'Standard_E32ds_v4', 'Standard_E8_v4', 'Standard_D2s_v4', 'Standard_GS5-16', 'Standard_A4', 'Standard_E32a_v4', 'Standard_D12_v2', 'Basic_A3', 'Standard_A2', 'Standard_M32ls', 'Standard_E8s_v4', 'Standard_A4m_v2', 'Standard_NC24r', 'Standard_NC8as_T4_v3', 'Standard_E8d_v5', 'Standard_M64ms', 'Standard_E2_v5', 'Standard_D15i_v2', 'Standard_E64-32as_v4', 'Standard_D11_v2', 'Standard_E32_v3', 'Standard_E48d_v4', 'Standard_E8_v3', 'Standard_D4_v5', 'Standard_E32-16s_v3', 'Standard_A6', 'Standard_M192idms_v2', 'Standard_D8s_v3', 'Standard_D2_v2', 'Standard_M32-8ms', 'Standard_E32-8ds_v4', 'Standard_E16ds_v4', 'Standard_M208-52s_v2', 'Standard_E64d_v4', 'Standard_NC24s_v3', 'Standard_D32d_v5', 'Standard_M64-32ms', 'Standard_A1_v2', 'Standard_H16', 'Standard_E64-16ds_v4', 'Standard_E96d_v5', 'Standard_DS14_v2', 'Standard_D64ds_v4', 'Standard_D16ds_v5', 'Standard_E4_v3', 'Standard_NC24rs_v2', 'Standard_G2', 'Standard_GS2', 'Standard_E8-2as_v4', 'Standard_E4_v4', 'Standard_E20_v3', 'Standard_E64-16s_v4', 'Standard_NC16as_T4_v3', 'Standard_NV4as_v4', 'Standard_E16as_v4', 'Standard_L48s_v2', 'Standard_E32d_v5', 'Standard_NC64as_T4_v3', 'Standard_DS3_v2', 'Standard_DS14-8_v2', 'Standard_E2a_v4', 'Standard_F4s', 'Standard_D48s_v3', 'Standard_F2', 'Standard_M64', 'Standard_M64ls', 'Standard_E16d_v5', 'Standard_E64as_v4', 'Standard_DS13_v2', 'Standard_D32_v3', 'Standard_M64ds_v2', 'Standard_E4s_v4', 'Standard_DS12-1_v2', 'Standard_E2s_v4', 'Standard_M64s', 'Standard_NV8as_v4', 'Standard_DS11-1_v2', 'Standard_E64-32s_v3', 'Standard_D4s_v5', 'Standard_E16-8ds_v4', 'Standard_E8-4s_v3', 'Standard_D2ds_v5', 'Standard_E20s_v3', 'Standard_E48_v5', 'Standard_NC6s_v2', 'Standard_D48ds_v5', 'Standard_E2_v4', 'Standard_F32s_v2', 'Standard_E8a_v4', 'Standard_E80ids_v4', 'Standard_D4ds_v5', 'Standard_E16-8s_v4', 'Standard_L16s', 'Standard_DS13-2_v2', 'Standard_D64s_v5', 'Standard_D14_v2', 'Standard_E16s_v4', 'Standard_D96d_v5', 'Standard_E2d_v5', 'Standard_D16_v5', 'Standard_E16-4ds_v4', 'Standard_D48d_v5', 'Standard_L4s', 'Standard_E80is_v4', 'Standard_E64d_v5', 'Standard_E16-8s_v3', 'Standard_D64s_v3', 'Standard_E64-16as_v4', 'Standard_E16a_v4', 'Standard_D16d_v4', 'Standard_E20a_v4', 'Standard_ND40rs_v2', 'Standard_D64-32s_v3', 'Standard_E4ds_v4', 'Standard_D64_v4', '', 'Standard_D64a_v4', 'Standard_D8ds_v4', 'Standard_E8as_v4', 'Standard_E16-4as_v4', 'Standard_NC12s_v2', 'Standard_D32as_v4', 'Standard_E32_v5', 'Standard_G3', 'Standard_A1', 'Standard_E4-2ds_v4', 'Standard_D32s_v4', 'Standard_NV12s_v3', 'Standard_HC44rs', 'Standard_D2_v4', 'Standard_L80s_v2', 'Standard_M8-2ms', 'Standard_M128s', 'Standard_D4_v3', 'Standard_E64s_v4', 'Standard_NV48s_v3', 'Standard_E16-4s_v3', 'Standard_DS12-2_v2', 'Standard_D4d_v4', 'Standard_F72s_v2', 'Standard_L8s', 'Standard_D16s_v4', 'Standard_D16_v3', 'Standard_M32s', 'Standard_M32ms_v2', 'Standard_E4s_v3', 'Standard_D8as_v4', 'Standard_GS5-8', 'Standard_E64-16s_v3', 'Standard_D16s_v5', 'Standard_D16_v4', 'Standard_E8s_v3', 'Standard_D8_v3', 'Standard_NV16as_v4', 'Standard_D16d_v5', 'Standard_E16_v4', 'Standard_D32ds_v4', 'Standard_D64d_v4', 'Standard_E32as_v4', 'Standard_M64s_v2', 'Standard_E32s_v4', 'Standard_G4', 'Standard_E48d_v5', 'Standard_DC8_v2', 'Standard_DS4_v2', 'Standard_ND96asr_A100_v4', 'Standard_D32_v4', 'Standard_NV24', 'Standard_D8d_v5', 'Standard_D4d_v5', 'Standard_ND6s', 'Standard_E4-2s_v4', 'Standard_D64d_v5', 'Standard_G5', 'Standard_E16_v5', 'Standard_F1s', 'Standard_D32s_v5', 'Standard_D48d_v4', 'Standard_M128ds_v2', 'Standard_E4as_v4', 'Standard_E4d_v4', 'Standard_E16_v3', 'Standard_NP40s', 'Standard_NV24s_v3', 'Standard_D2ds_v4', 'Standard_E20d_v5', 'Standard_NV12', 'Standard_M64ms_v2', 'Standard_D96ds_v5', 'Standard_M208s_v2', 'Standard_E16-4s_v4', 'Standard_M208-104s_v2', 'Standard_E8d_v4', 'Standard_F4', 'Standard_E32-16ds_v4', 'Standard_M416-208s_v2', 'Standard_L32s_v2', 'Standard_E20_v4', 'Standard_L64s_v2', 'Basic_A0', 'Standard_M192is_v2', 'Standard_E32-8s_v3', 'Standard_D8_v5', 'Standard_M32ts', 'Standard_E64-32ds_v4', 'Standard_E48_v4', 'Standard_F48s_v2', 'Standard_GS1', 'Standard_E48ds_v4', 'Standard_D64ds_v5', 'Standard_E4_v5', 'Standard_L32s', 'Standard_D48_v3', 'Standard_D32_v5', 'Standard_D4s_v4', 'Standard_M64-16ms', 'Standard_NC24s_v2', 'Standard_D16s_v3', 'Standard_H16r', 'Standard_PB6s', 'Standard_E32-16s_v4', 'Standard_D8a_v4', 'Standard_DS12_v2', 'Standard_DS15i_v2', 'Standard_NC6s_v3', 'Standard_E96as_v4', 'Standard_NC4as_T4_v3', 'Standard_E32-8as_v4', 'Standard_A8m_v2', 'Standard_H16m', 'Standard_F16s', 'Standard_M32dms_v2', 'Standard_E8-4s_v4', 'Standard_NC6', 'Standard_E2ds_v4', 'Standard_GS4-4', 'Standard_M16-4ms', 'Standard_DC4s_v2', 'Standard_D4as_v4', 'Standard_M64dms_v2', 'Standard_M8-4ms', 'Standard_E8_v5', 'Standard_D48a_v4', 'Standard_E64_v5', 'Standard_M416is_v2', 'Standard_D48_v4', 'Standard_D16a_v4', 'Standard_M128dms_v2', 'Standard_M208-52ms_v2', 'Standard_PB24s', 'Standard_ND96asr_v4', 'Standard_A0', 'Standard_D96_v5', 'Standard_F16s_v2', 'Standard_M128-32ms', 'Standard_M128s_v2', 'Standard_NC24rs_v3', 'Standard_E16d_v4', 'Standard_D5_v2', 'Standard_M16-8ms', 'Standard_D4ds_v4', 'Standard_DS5_v2', 'Standard_D2a_v4', 'Standard_D96a_v4', 'Standard_H8', 'Standard_D64-16s_v3', 'Standard_M128ms', 'Standard_E4a_v4', 'Standard_DS15_v2', 'Standard_D8s_v5', 'Standard_GS5', 'Standard_ND12s', 'Standard_E64_v3', 'Standard_E2_v3', 'Standard_NV6', 'Standard_ND24s', 'Standard_DS1_v2', 'Standard_F4s_v2', 'Standard_GS4', 'Standard_E20d_v4', 'Standard_D48ds_v4', 'Standard_HB120rs_v2', 'Standard_G1', 'Standard_M128ms_v2', 'Standard_D48s_v4', 'Standard_E8-4as_v4', 'Standard_M416-208ms_v2', 'Standard_E8-2s_v4', 'Standard_DS11_v2', 'Standard_E8-2s_v3', 'Standard_NP20s', 'Standard_A8_v2', 'Standard_M32-16ms', 'Standard_D4_v4', 'Standard_L16s_v2', 'Standard_F8s_v2', 'Basic_A4', 'Standard_E20ds_v4', 'Standard_M128-64ms', 'Standard_D2d_v5', 'Standard_D48as_v4', 'Standard_D32-16s_v3', 'Standard_E64is_v3', 'Standard_D2d_v4', 'Standard_F64s_v2', 'Standard_E20s_v4', 'Standard_DS14-4_v2', 'Standard_E2as_v4', 'Standard_D32-8s_v3', 'Standard_ND24rs', 'Standard_E64ds_v4', 'Standard_A2m_v2', 'Standard_HC44-16rs', 'Standard_NC12', 'Standard_D13_v2', 'Standard_D3_v2', 'Standard_M128', 'Standard_D4a_v4', 'Standard_E64_v4', 'Standard_F16', 'Standard_E48s_v4', 'Standard_DS2_v2', 'Standard_D32d_v4', 'Standard_HC44-32rs', 'Standard_NP10s', 'Standard_NV32as_v4', 'Standard_A7', 'Standard_GS4-8', 'Standard_D32ds_v5', 'Standard_E16-8as_v4', 'Standard_E96a_v4', 'Standard_E48as_v4', 'Standard_E96-48as_v4', 'Standard_D2_v5', 'Standard_D64s_v4', 'Standard_F8s', 'Standard_D2s_v5', 'Standard_M16s', 'Standard_D15_v2', 'Standard_D1_v2', 'Standard_D16as_v4', 'Standard_D8_v4', 'Standard_E32d_v4', 'Standard_D2as_v4', 'Standard_D8ds_v5', 'Basic_A1', 'Standard_M128m', 'Standard_E96-24as_v4', 'Standard_M32ms', 'Standard_E32s_v3', 'Standard_M192ids_v2', 'Standard_H8m', 'Standard_E48s_v3', 'Standard_F1', 'Standard_M16ms', 'Standard_F2s_v2', 'Standard_GS3', 'Standard_D64as_v4', 'Standard_M192ims_v2', 'Standard_E32-8s_v4', 'Standard_E32_v4', 'Standard_E8-2ds_v4', 'Basic_A2', 'Standard_D64_v3', 'Standard_E64-32s_v4', 'Standard_D4_v2', 'Standard_M64m'],
'northcentralus': ['Standard_D48s_v4', 'Standard_D32as_v4', 'Standard_E4a_v4', 'Standard_E16s_v3', 'Standard_D2s_v5', 'Standard_D48ds_v5', 'Standard_E64-32ds_v4', 'Standard_M64dms_v2', 'Standard_D4_v3', 'Standard_D64s_v5', 'Standard_E64-16s_v3', 'Standard_D8s_v3', 'Standard_E64-16ds_v4', 'Standard_NC4as_T4_v3', 'Standard_D8ds_v4', 'Standard_E32_v3', 'Standard_NV32as_v4', 'Standard_D8as_v4', 'Standard_M128-32ms', 'Standard_E16-4s_v3', 'Standard_H16m', 'Standard_M64ms_v2', 'Standard_E64-32s_v4', 'Standard_D2ds_v5', 'Standard_D48as_v4', 'Standard_E8-4as_v4', 'Standard_M32ms', 'Standard_H16mr', 'Standard_E2_v5', 'Standard_M208ms_v2', 'Standard_M416-104s_v2', 'Standard_D48_v3', 'Standard_E32s_v3', 'Standard_E4d_v5', 'Standard_E64is_v3', 'Basic_A1', 'Standard_M208-52ms_v2', 'Standard_D8d_v4', 'Standard_DS13-4_v2', 'Standard_D4s_v5', 'Standard_DS1_v2', 'Standard_NV24', 'Standard_E64as_v4', 'Standard_F8s_v2', 'Standard_DS1', 'Standard_D14_v2', 'Standard_E32-16s_v4', 'Standard_E48s_v4', 'Standard_DS12_v2', 'Standard_D64ds_v5', 'Standard_E8ds_v4', 'Standard_DS14', 'Standard_M8ms', 'Standard_M64-32ms', 'Standard_D2d_v4', 'Standard_D11_v2', 'Standard_D32-8s_v3', 'Standard_E16-8s_v4', 'Standard_E48a_v4', 'Standard_D4as_v4', 'Standard_F2s_v2', 'Standard_DS11_v2', 'Standard_D13', 'Standard_D4_v5', 'Standard_E16-8as_v4', 'Standard_E8_v5', 'Standard_D2as_v4', 'Standard_DS12-1_v2', 'Standard_DC1s_v2', 'Standard_F8s', 'Standard_M32dms_v2', 'Standard_D64-16s_v3', 'Standard_NC8as_T4_v3', 'Standard_A7', 'Standard_M192ids_v2', 'Standard_DS13-2_v2', 'Standard_M128ms', 'Standard_DS14_v2', 'Standard_M128ms_v2', 'Standard_E16ds_v4', 'Standard_E32s_v4', 'Standard_E4s_v4', 'Standard_E80is_v4', 'Standard_M16s', 'Standard_D4_v4', 'Standard_D96_v5', 'Standard_DS3_v2', 'Standard_E20_v5', 'Standard_E32-8ds_v4', 'Standard_E64_v4', 'Standard_D4s_v4', 'Standard_E32-8s_v4', 'Standard_D48d_v4', 'Standard_E32ds_v4', 'Standard_D48s_v5', 'Standard_E20d_v5', 'Standard_D1_v2', 'Standard_E64s_v4', 'Standard_E4_v5', 'Standard_M416-208s_v2', 'Standard_E2s_v3', 'Standard_E8-4ds_v4', 'Standard_E48_v5', 'Standard_D8_v5', 'Standard_E8-2as_v4', 'Standard_F8', 'Standard_E64-16s_v4', 'Standard_DS12', 'Standard_M192is_v2', 'Standard_D8d_v5', 'Standard_D8s_v5', 'Standard_D16_v3', 'Standard_D16d_v4', 'Standard_D16s_v4', 'Standard_D2d_v5', 'Standard_A11', 'Standard_E8-2ds_v4', 'Standard_D32ds_v5', 'Standard_A2m_v2', 'Standard_D4a_v4', 'Standard_E32_v4', 'Standard_F16', 'Standard_M64ls', 'Standard_D3', 'Standard_M128dms_v2', 'Standard_DS15_v2', 'Standard_D64_v5', 'Standard_M128m', 'Standard_D48ds_v4', 'Standard_M128ds_v2', 'Standard_E16a_v4', 'Standard_A8', 'Standard_DS5_v2', 'Standard_D32-16s_v3', 'Standard_A4', 'Standard_D4d_v5', 'Standard_A8_v2', 'Standard_E16_v4', 'Standard_M128', 'Standard_E64_v5', 'Standard_D4_v2', 'Standard_M208-104ms_v2', 'Standard_DS3', 'Standard_E16-4as_v4', 'Standard_E48as_v4', 'Standard_H16r', 'Standard_D48_v5', 'Standard_F16s', 'Standard_D4', 'Standard_D96ds_v5', 'Standard_NV4as_v4', 'Standard_M208-52s_v2', 'Basic_A3', 'Standard_M64-16ms', 'Standard_DS2', 'Standard_M16-4ms', 'Standard_M32ts', 'Standard_D64ds_v4', 'Standard_NC24r', 'Standard_DS14-8_v2', '', 'Standard_A6', 'Standard_D32d_v5', 'Standard_E96-24as_v4', 'Standard_E80ids_v4', 'Standard_E20a_v4', 'Standard_A0', 'Standard_D12_v2', 'Standard_M192idms_v2', 'Standard_DS13_v2', 'Standard_D16ds_v5', 'Standard_E48d_v4', 'Standard_E16as_v4', 'Standard_E32a_v4', 'Standard_M32ms_v2', 'Standard_D2_v3', 'Standard_E20ds_v4', 'Standard_M64', 'Standard_F2s', 'Standard_E16_v5', 'Standard_E16-4s_v4', 'Standard_D32a_v4', 'Basic_A0', 'Standard_D2s_v3', 'Standard_E64-16as_v4', 'Standard_M32-8ms', 'Standard_E4d_v4', 'Standard_D64as_v4', 'Standard_NC16as_T4_v3', 'Standard_E48ds_v4', 'Standard_D2', 'Standard_D3_v2', 'Standard_E64d_v4', 'Standard_D32s_v5', 'Standard_F1s', 'Standard_F4s', 'Standard_D16a_v4', 'Standard_HB120rs_v2', 'Standard_D64d_v5', 'Standard_E48s_v3', 'Standard_A3', 'Standard_M416-104ms_v2', 'Standard_D16ds_v4', 'Standard_A1', 'Standard_D5_v2', 'Standard_E4ds_v4', 'Standard_D96a_v4', 'Standard_D4d_v4', 'Standard_E2a_v4', 'Standard_E32_v5', 'Standard_E96_v5', 'Standard_H8m', 'Standard_DS14-4_v2', 'Standard_NV12', 'Standard_E2s_v4', 'Standard_D48_v4', 'Standard_D16as_v4', 'Standard_E96-48as_v4', 'Standard_DS4_v2', 'Standard_DS15i_v2', 'Standard_E8a_v4', 'Standard_D16s_v5', 'Standard_D64d_v4', 'Standard_DS11', 'Standard_D4ds_v4', 'Standard_E8s_v3', 'Standard_D64_v3', 'Standard_DC8_v2', 'Standard_D2ds_v4', 'Standard_E4-2s_v4', 'Standard_E8_v4', 'Standard_E8as_v4', 'Standard_D64s_v3', 'Standard_D8ds_v5', 'Standard_E4-2as_v4', 'Standard_D13_v2', 'Standard_E64i_v3', 'Standard_M32ls', 'Standard_A2', 'Standard_D2_v2', 'Basic_A2', 'Standard_D64a_v4', 'Standard_D15_v2', 'Standard_E20s_v3', 'Standard_E16-8ds_v4', 'Standard_D2_v5', 'Standard_E8d_v5', 'Standard_D32s_v4', 'Standard_DS11-1_v2', 'Standard_E8-4s_v3', 'Standard_E32-16ds_v4', 'Standard_NC6', 'Standard_E2_v4', 'Standard_D32_v4', 'Standard_F64s_v2', 'Standard_M128-64ms', 'Standard_E20as_v4', 'Standard_E16-8s_v3', 'Standard_D48s_v3', 'Standard_E96as_v4', 'Standard_M32s', 'Standard_M416ms_v2', 'Standard_A2_v2', 'Standard_E4-2ds_v4', 'Standard_E48d_v5', 'Standard_M192ims_v2', 'Standard_NV8as_v4', 'Standard_A5', 'Standard_E2_v3', 'Standard_D32s_v3', 'Standard_D8s_v4', 'Standard_D32ds_v4', 'Standard_E4s_v3', 'Standard_E8s_v4', 'Standard_M64s', 'Standard_E8-4s_v4', 'Standard_M128s_v2', 'Standard_E96a_v4', 'Standard_E20_v4', 'Standard_E8-2s_v3', 'Standard_H8', 'Standard_NV16as_v4', 'Standard_D12', 'Standard_H16', 'Standard_D8a_v4', 'Standard_M128s', 'Standard_E4_v3', 'Standard_A10', 'Standard_F4', 'Standard_NV6', 'Standard_M416s_v2', 'Standard_E64-32s_v3', 'Standard_E32d_v5', 'Standard_D4s_v3', 'Standard_E4-2s_v3', 'Standard_D48d_v5', 'Standard_E2as_v4', 'Standard_E64_v3', 'Standard_D2a_v4', 'Standard_E32-8s_v3', 'Standard_D48a_v4', 'Basic_A4', 'Standard_D96d_v5', 'Standard_E8_v3', 'Standard_DC4s_v2', 'Standard_D8_v3', 'Standard_E16_v3', 'Standard_E32d_v4', 'Standard_M64ms', 'Standard_DS2_v2', 'Standard_M16-8ms', 'Standard_DS12-2_v2', 'Standard_D15i_v2', 'Standard_DC2s_v2', 'Standard_E16-4ds_v4', 'Standard_E16s_v4', 'Standard_M32-16ms', 'Standard_D1', 'Standard_E2d_v4', 'Standard_D2_v4', 'Standard_E2d_v5', 'Standard_E64d_v5', 'Standard_F16s_v2', 'Standard_E20s_v4', 'Standard_D64-32s_v3', 'Standard_E8d_v4', 'Standard_DS13', 'Standard_F32s_v2', 'Standard_A4m_v2', 'Standard_D32d_v4', 'Standard_E2ds_v4', 'Standard_D16s_v3', 'Standard_F72s_v2', 'Standard_E16d_v5', 'Standard_F4s_v2', 'Standard_E16d_v4', 'Standard_M208-104s_v2', 'Standard_E64ds_v4', 'Standard_D64_v4', 'Standard_D96s_v5', 'Standard_D96as_v4', 'Standard_E64-32as_v4', 'Standard_M416is_v2', 'Standard_D8_v4', 'Standard_DS4', 'Standard_A4_v2', 'Standard_D16d_v5', 'Standard_F48s_v2', 'Standard_E20_v3', 'Standard_E48_v4', 'Standard_E8-2s_v4', 'Standard_D14', 'Standard_A9', 'Standard_E96d_v5', 'Standard_D4ds_v5', 'Standard_M208s_v2', 'Standard_D11', 'Standard_M8-2ms', 'Standard_E4_v4', 'Standard_M416-208ms_v2', 'Standard_A8m_v2', 'Standard_F1', 'Standard_D32_v3', 'Standard_D2s_v4', 'Standard_E32-16s_v3', 'Standard_D64s_v4', 'Standard_E32-8as_v4', 'Standard_NC64as_T4_v3', 'Standard_D16_v5', 'Standard_M16ms', 'Standard_E32-16as_v4', 'Standard_E64s_v3', 'Standard_D32_v5', 'Standard_F2', 'Standard_NC12', 'Standard_E64a_v4', 'Standard_D16_v4', 'Standard_M64s_v2', 'Standard_E48_v3', 'Standard_M64ds_v2', 'Standard_M8-4ms', 'Standard_A1_v2', 'Standard_E4as_v4', 'Standard_NC24', 'Standard_E32as_v4', 'Standard_E20d_v4', 'Standard_M64m'],
'southcentralus': ['Standard_D48s_v3', 'Standard_D32s_v4', 'Standard_A7', 'Standard_DS2_v2', 'Standard_D32_v3', 'Standard_HC44rs', 'Standard_A8_v2', 'Standard_NC24', 'Standard_D48as_v4', 'Standard_D64_v4', 'Standard_ND24rs', 'Standard_D4', 'Standard_M416-208ms_v2', 'Standard_DS12-1_v2', 'Standard_E16_v3', 'Standard_E20ds_v4', 'Standard_DS13_v2', 'Standard_D32s_v3', 'Standard_DS12_v2', 'Standard_DS11-1_v2', 'Standard_NV16as_v4', 'Standard_E16-8ds_v4', 'Standard_D8s_v3', 'Standard_M128', 'Standard_E8-4ds_v4', 'Standard_D2_v4', 'Standard_E8-4as_v4', 'Standard_A2', 'Standard_D48_v4', 'Standard_M416s_v2', 'Standard_M416-208s_v2', 'Standard_E32s_v3', 'Standard_ND40rs_v2', 'Standard_HB60-15rs', 'Standard_D8s_v4', 'Standard_M416is_v2', 'Standard_A4m_v2', '', 'Standard_D32s_v5', 'Standard_D2_v5', 'Standard_D4d_v5', 'Standard_E16d_v5', 'Standard_F16s_v2', 'Standard_DC4s_v2', 'Standard_D2', 'Standard_E8_v4', 'Standard_NC6s_v2', 'Standard_D64-16s_v3', 'Standard_D8d_v5', 'Basic_A1', 'Standard_E20a_v4', 'Standard_E64-32s_v4', 'Standard_D4as_v4', 'Standard_A8', 'Standard_E4d_v4', 'Standard_M208s_v2', 'Standard_E8-4s_v3', 'Standard_D16d_v4', 'Standard_E8as_v4', 'Standard_E32as_v4', 'Standard_D16ds_v4', 'Standard_NC12s_v3', 'Standard_M32ms_v2', 'Standard_M8-4ms', 'Standard_A11', 'Standard_D32as_v4', 'Standard_E64-16as_v4', 'Standard_M128m', 'Standard_M64ms', 'Standard_D32-16s_v3', 'Standard_E16-4s_v4', 'Standard_A1', 'Standard_A2m_v2', 'Standard_D2s_v4', 'Standard_NV12', 'Standard_A0', 'Standard_D2ds_v5', 'Standard_E8-2ds_v4', 'Standard_D8ds_v5', 'Standard_F4s_v2', 'Standard_F1s', 'Standard_E16d_v4', 'Standard_DS14_v2', 'Standard_DS13-2_v2', 'Standard_DS11_v2', 'Standard_DS15_v2', 'Standard_D8ds_v4', 'Standard_D3', 'Standard_E2s_v3', 'Standard_ND40s_v2', 'Standard_D4_v4', 'Standard_F4', 'Standard_L8s_v2', 'Standard_D3_v2', 'Standard_E4s_v4', 'Standard_D64-32s_v3', 'Standard_E32d_v5', 'Standard_DS11', 'Standard_E16as_v4', 'Standard_E32-16s_v4', 'Standard_DC2s_v2', 'Standard_NV32as_v4', 'Standard_NC64as_T4_v3', 'Standard_E2s_v4', 'Standard_F2s_v2', 'Standard_E16-4as_v4', 'Standard_E16-4ds_v4', 'Standard_D15i_v2', 'Standard_NC6s_v3', 'Standard_M32-8ms', 'Standard_D48d_v4', 'Standard_M128dms_v2', 'Standard_E32-16as_v4', 'Standard_D96_v5', 'Standard_D64s_v5', 'Standard_E80ids_v4', 'Standard_E4-2s_v3', 'Standard_M192ims_v2', 'Standard_D1', 'Standard_HB120rs_v2', 'Standard_D2_v2', 'Standard_NC24s_v3', 'Basic_A4', 'Standard_E8-2s_v4', 'Standard_E96a_v4', 'Standard_D16_v4', 'Standard_E64-16s_v3', 'Standard_E32_v3', 'Standard_E4_v4', 'Standard_ND96asr_v4', 'Standard_E64-32ds_v4', 'Standard_E32s_v4', 'Standard_E4a_v4', 'Standard_D48s_v4', 'Standard_H8m', 'Standard_D2s_v5', 'Standard_M128-64ms', 'Basic_A3', 'Standard_D48ds_v5', 'Standard_E2a_v4', 'Standard_M8-2ms', 'Standard_E8_v3', 'Standard_HB60rs', 'Standard_E4-2as_v4', 'Standard_D11_v2', 'Standard_D2as_v4', 'Standard_D2ds_v4', 'Standard_ND24s', 'Standard_E4ds_v4', 'Standard_D4_v5', 'Standard_M192is_v2', 'Standard_E32d_v4', 'Standard_E64-16s_v4', 'Standard_E8-4s_v4', 'Standard_D32-8s_v3', 'Standard_D1_v2', 'Standard_A4', 'Standard_M16s', 'Standard_HB120rs_v3', 'Standard_M128s_v2', 'Standard_E96-48as_v4', 'Standard_E32-8s_v3', 'Standard_D16_v5', 'Standard_E48as_v4', 'Standard_E48d_v5', 'Standard_A2_v2', 'Standard_E16_v4', 'Standard_H16', 'Standard_E32a_v4', 'Standard_NC24r', 'Basic_A0', 'Standard_E16_v5', 'Standard_E4as_v4', 'Standard_E8s_v4', 'Standard_DS14-8_v2', 'Standard_E16a_v4', 'Standard_E20s_v4', 'Standard_E64_v3', 'Standard_L48s_v2', 'Standard_DS4_v2', 'Standard_L80s_v2', 'Standard_D32_v5', 'Standard_E8_v5', 'Standard_E2_v4', 'Standard_D4d_v4', 'Standard_M32s', 'Standard_M208-104ms_v2', 'Standard_F2s', 'Standard_E2d_v4', 'Standard_M64dms_v2', 'Standard_M64m', 'Standard_D5_v2', 'Standard_DS3_v2', 'Standard_D48_v5', 'Standard_E16-8s_v4', 'Standard_E8d_v5', 'Standard_E20_v5', 'Standard_D96d_v5', 'Standard_F1', 'Standard_D2a_v4', 'Standard_PB24s', 'Standard_L88is_v2', 'Standard_D16s_v5', 'Standard_E16-8s_v3', 'Standard_ND6s', 'Standard_E48s_v4', 'Standard_DS4', 'Standard_E20d_v5', 'Standard_E64ds_v4', 'Standard_D16s_v3', 'Standard_E32-8s_v4', 'Standard_D64s_v4', 'Standard_E2_v3', 'Standard_H16r', 'Standard_E32ds_v4', 'Standard_A3', 'Standard_M64ms_v2', 'Standard_DS1', 'Standard_D96s_v5', 'Standard_D8_v4', 'Standard_M32dms_v2', 'Standard_E32_v4', 'Standard_NC24s_v2', 'Standard_E96-24as_v4', 'Standard_HB120-16rs_v3', 'Standard_DS1_v2', 'Standard_M32ls', 'Standard_D48ds_v4', 'Standard_E20s_v3', 'Standard_D32a_v4', 'Standard_F16s', 'Standard_D16ds_v5', 'Standard_E4-2ds_v4', 'Standard_M128ds_v2', 'Standard_E48d_v4', 'Standard_DC8_v2', 'Standard_E16-4s_v3', 'Standard_E48_v5', 'Standard_E64a_v4', 'Standard_D8a_v4', 'Standard_L16s_v2', 'Standard_F8s', 'Standard_NC4as_T4_v3', 'Standard_D15_v2', 'Standard_D48s_v5', 'Standard_M64s', 'Standard_DS13', 'Standard_A4_v2', 'Standard_D32d_v5', 'Standard_D64a_v4', 'Standard_E64i_v3', 'Standard_M16-8ms', 'Standard_NC24rs_v3', 'Standard_E16s_v4', 'Standard_D64_v5', 'Standard_A5', 'Standard_D4_v2', 'Standard_D96a_v4', 'Standard_H8', 'Standard_E8a_v4', 'Standard_E8s_v3', 'Standard_D8s_v5', 'Standard_NC16as_T4_v3', 'Standard_E4d_v5', 'Standard_M64ds_v2', 'Standard_E80is_v4', 'Standard_F8', 'Standard_DS15i_v2', 'Standard_E8ds_v4', 'Standard_M416-104s_v2', 'Standard_D2_v3', 'Standard_F4s', 'Standard_E2d_v5', 'Standard_DS3', 'Standard_NV6', 'Standard_M64-32ms', 'Standard_D4ds_v4', 'Standard_E20_v4', 'Standard_A9', 'Standard_D11', 'Standard_HB60-45rs', 'Standard_D2s_v3', 'Standard_E4s_v3', 'Standard_NV24s_v3', 'Standard_D8_v5', 'Standard_D96as_v4', 'Standard_M128s', 'Standard_D48d_v5', 'Standard_D4s_v4', 'Standard_F32s_v2', 'Standard_D12_v2', 'Standard_A8m_v2', 'Standard_E16ds_v4', 'Standard_E96as_v4', 'Standard_F72s_v2', 'Standard_M192ids_v2', 'Standard_F64s_v2', 'Standard_E64_v5', 'Standard_E96d_v5', 'Standard_E64-32as_v4', 'Standard_NC12s_v2', 'Standard_E20as_v4', 'Standard_E48s_v3', 'Standard_HB120-64rs_v3', 'Standard_D8as_v4', 'Standard_E48ds_v4', 'Standard_D8d_v4', 'Standard_E32-16s_v3', 'Standard_NV48s_v3', 'Standard_E64_v4', 'Standard_L64s_v2', 'Standard_H16mr', 'Standard_M16ms', 'Standard_M32-16ms', 'Standard_M128ms', 'Standard_E4-2s_v4', 'Standard_E8d_v4', 'Standard_D2d_v5', 'Standard_M128ms_v2', 'Standard_DS2', 'Standard_F2', 'Standard_M208-104s_v2', 'Standard_E20d_v4', 'Standard_NC8as_T4_v3', 'Standard_E48_v3', 'Standard_DS13-4_v2', 'Standard_M32ms', 'Standard_HB120-96rs_v3', 'Standard_D16a_v4', 'Standard_D64as_v4', 'Standard_D16_v3', 'Standard_NC12', 'Standard_ND12s', 'Standard_NV24', 'Standard_D64s_v3', 'Standard_E64s_v3', 'Standard_E16-8as_v4', 'Standard_F8s_v2', 'Standard_E32-8as_v4', 'Standard_D4ds_v5', 'Standard_E48a_v4', 'Standard_E64-32s_v3', 'Standard_M192idms_v2', 'Standard_D48a_v4', 'Standard_HB120-32rs_v3', 'Standard_M8ms', 'Standard_D32ds_v4', 'Standard_DS14', 'Standard_M16-4ms', 'Standard_D4s_v3', 'Standard_D64_v3', 'Standard_E64as_v4', 'Standard_D12', 'Standard_F48s_v2', 'Standard_D16d_v5', 'Standard_HC44-16rs', 'Standard_DS12-2_v2', 'Standard_D96ds_v5', 'Standard_ND96asr_A100_v4', 'Standard_E20_v3', 'Standard_M32ts', 'Standard_PB6s', 'Standard_D4s_v5', 'Basic_A2', 'Standard_E4_v3', 'Standard_DS5_v2', 'Standard_M208-52s_v2', 'Standard_M208-52ms_v2', 'Standard_PB12s', 'Standard_D64ds_v5', 'Standard_E96_v5', 'Standard_M416-104ms_v2', 'Standard_L96s_v2', 'Standard_NV12s_v3', 'Standard_M128-32ms', 'Standard_D14_v2', 'Standard_D16s_v4', 'Standard_E32-8ds_v4', 'Standard_NC24rs_v2', 'Standard_D14', 'Standard_E8-2s_v3', 'Standard_E4_v5', 'Standard_NC6', 'Standard_D32d_v4', 'Standard_D2d_v4', 'Standard_D32ds_v5', 'Standard_E64d_v5', 'Standard_E64s_v4', 'Standard_HB60-30rs', 'Standard_A10', 'Standard_E8-2as_v4', 'Standard_NV8as_v4', 'Standard_E48_v4', 'Standard_E64-16ds_v4', 'Standard_DS14-4_v2', 'Standard_DS12', 'Standard_M64s_v2', 'Standard_D16as_v4', 'Standard_D4a_v4', 'Standard_E2_v5', 'Standard_D4_v3', 'Standard_E2as_v4', 'Standard_F16', 'Standard_H16m', 'Standard_D13_v2', 'Standard_L32s_v2', 'Standard_E32_v5', 'Standard_E32-16ds_v4', 'Standard_D48_v3', 'Standard_M64', 'Standard_E16s_v3', 'Standard_D64d_v5', 'Standard_D8_v3', 'Standard_E64is_v3', 'Standard_NV4as_v4', 'Standard_M416ms_v2', 'Standard_D64ds_v4', 'Standard_D32_v4', 'Standard_E2ds_v4', 'Standard_NV24s_v2', 'Standard_D64d_v4', 'Standard_D13', 'Standard_A1_v2', 'Standard_M64-16ms', 'Standard_A6', 'Standard_NV6s_v2', 'Standard_HC44-32rs', 'Standard_E64d_v4', 'Standard_M208ms_v2', 'Standard_M64ls', 'Standard_NV12s_v2', 'Standard_DC1s_v2'],
'westcentralus': ['Standard_D2_v3', 'Standard_D32_v5', 'Standard_F16s_v2', 'Standard_E2a_v4', 'Standard_F2s_v2', 'Standard_D2_v2', 'Standard_E20_v4', 'Standard_E64-16s_v4', 'Standard_E2s_v4', 'Standard_E4d_v5', 'Standard_E4_v3', 'Standard_DS11_v2', 'Standard_D32-16s_v3', 'Standard_D64d_v5', 'Standard_D8_v4', 'Standard_D8_v3', 'Standard_A5', 'Standard_D2_v4', 'Standard_E64-16as_v4', 'Standard_D64s_v5', 'Standard_D48d_v4', 'Standard_E96-24as_v4', 'Standard_A8m_v2', 'Standard_F4s', 'Standard_E16_v4', 'Standard_E8s_v4', 'Standard_E80is_v4', 'Standard_E16-4ds_v4', 'Standard_D64a_v4', 'Standard_DS15i_v2', 'Standard_E32a_v4', 'Standard_D32_v3', 'Standard_E64s_v4', 'Standard_D32s_v5', 'Standard_D32s_v3', 'Standard_E4as_v4', 'Standard_D8_v5', 'Standard_E64a_v4', 'Standard_D5_v2', 'Standard_E32-8ds_v4', 'Standard_E64-32as_v4', 'Standard_E96_v5', 'Standard_D32a_v4', 'Standard_F1s', 'Standard_D32d_v4', 'Standard_DS12_v2', 'Standard_E64d_v5', 'Standard_E20a_v4', 'Standard_F48s_v2', 'Standard_D8d_v5', 'Standard_E16s_v3', 'Standard_E8d_v5', 'Standard_A3', 'Standard_F4s_v2', 'Standard_DS1_v2', 'Standard_D16s_v4', 'Standard_DS5_v2', 'Standard_A0', 'Standard_E16-4s_v3', 'Standard_E16s_v4', 'Standard_E48a_v4', 'Standard_D32-8s_v3', 'Standard_D4_v2', 'Standard_E32-16s_v3', 'Standard_E32ds_v4', 'Standard_D8as_v4', 'Standard_E4_v4', 'Standard_A4', 'Standard_E96as_v4', 'Standard_E8-4s_v3', 'Standard_E64d_v4', 'Standard_E2ds_v4', 'Standard_D3_v2', 'Standard_D16ds_v5', 'Basic_A2', 'Standard_A6', 'Standard_A4m_v2', 'Standard_D15_v2', 'Standard_DS14-4_v2', 'Standard_D64ds_v5', 'Standard_F16', 'Standard_E16ds_v4', 'Standard_E48d_v4', 'Standard_E48_v5', 'Standard_E32s_v4', 'Basic_A1', 'Standard_D4a_v4', 'Standard_F1', 'Standard_E20_v3', 'Standard_E64_v5', 'Standard_D4ds_v5', 'Standard_F16s', 'Standard_E8-4s_v4', 'Standard_E4d_v4', 'Standard_D2s_v5', 'Standard_E80ids_v4', 'Standard_E16_v3', 'Standard_E64ds_v4', 'Standard_E8-2s_v3', 'Standard_E8-2ds_v4', 'Standard_E20as_v4', 'Standard_E4ds_v4', 'Standard_D16_v5', 'Standard_A1_v2', 'Standard_D64-16s_v3', 'Standard_D32ds_v4', 'Standard_E2_v4', 'Standard_D64s_v4', 'Standard_E64s_v3', 'Standard_E16-8s_v4', 'Standard_E32-16as_v4', 'Standard_DS12-1_v2', 'Standard_A2m_v2', 'Standard_D8a_v4', 'Standard_F64s_v2', 'Standard_D48s_v4', 'Standard_F2', 'Standard_E32d_v5', 'Standard_E2d_v5', 'Standard_E20_v5', 'Standard_F72s_v2', 'Standard_D16d_v5', 'Standard_E48_v3', 'Standard_E32as_v4', 'Standard_E64-32s_v3', 'Standard_D2s_v3', 'Standard_E64-32s_v4', 'Standard_D64s_v3', 'Standard_D4s_v5', 'Standard_D96as_v4', 'Standard_E32_v3', 'Standard_E8a_v4', 'Standard_DS3_v2', 'Standard_DS14_v2', 'Standard_D32d_v5', 'Standard_E48ds_v4', 'Standard_E64-32ds_v4', 'Standard_E32_v5', 'Standard_D96d_v5', 'Standard_E4-2s_v4', 'Standard_D16a_v4', 'Standard_D11_v2', 'Standard_D96s_v5', 'Standard_E48_v4', 'Standard_E48d_v5', 'Standard_D8d_v4', 'Standard_E16-8s_v3', 'Standard_D2d_v5', 'Standard_F8s', 'Standard_D4_v3', 'Standard_D8s_v4', 'Standard_D64d_v4', 'Standard_D16s_v5', 'Standard_D4s_v3', 'Standard_E4_v5', 'Standard_E16d_v5', 'Basic_A4', 'Standard_D64_v3', 'Standard_DS12-2_v2', 'Standard_D13_v2', 'Standard_D32ds_v5', 'Standard_D16s_v3', 'Standard_E4s_v4', 'Standard_E64-16ds_v4', 'Standard_E32s_v3', 'Standard_E8ds_v4', 'Standard_D8s_v5', 'Standard_D2_v5', 'Standard_D4d_v4', 'Standard_E32d_v4', 'Standard_D4d_v5', 'Standard_E32-16s_v4', 'Standard_E64-16s_v3', 'Standard_D48a_v4', 'Standard_D64-32s_v3', 'Standard_D16_v3', 'Standard_D16ds_v4', 'Standard_D2ds_v4', 'Standard_E20s_v3', 'Standard_E48as_v4', 'Standard_E16-4s_v4', 'Standard_E64as_v4', 'Standard_D64as_v4', 'Standard_DS13-4_v2', 'Standard_E2as_v4', 'Standard_E64_v4', 'Standard_E4-2s_v3', 'Standard_D48s_v5', 'Standard_D48as_v4', 'Standard_A8_v2', 'Standard_E2d_v4', 'Standard_E8_v3', 'Standard_D48_v4', 'Standard_DS11-1_v2', 'Standard_D64ds_v4', 'Standard_E8_v5', 'Standard_D4s_v4', 'Standard_E96-48as_v4', 'Standard_F8', 'Standard_E8d_v4', 'Standard_E20d_v4', 'Standard_D12_v2', 'Standard_D48_v5', 'Standard_E16d_v4', 'Standard_E16a_v4', 'Standard_A4_v2', 'Standard_E8-2as_v4', 'Standard_F8s_v2', 'Standard_E8s_v3', 'Standard_D2s_v4', 'Standard_D16_v4', 'Standard_F4', 'Standard_D4as_v4', 'Standard_A1', 'Standard_E8as_v4', 'Standard_E20d_v5', 'Standard_E16_v5', 'Standard_E4-2ds_v4', 'Standard_A2', 'Standard_F2s', 'Standard_D14_v2', 'Standard_D48_v3', 'Standard_D16as_v4', 'Standard_D48d_v5', 'Standard_D96ds_v5', 'Standard_A7', 'Standard_D8ds_v5', 'Standard_D2a_v4', 'Standard_E64is_v3', 'Standard_E4-2as_v4', 'Standard_E4a_v4', '', 'Standard_E32-16ds_v4', 'Standard_E2_v5', 'Standard_E16-8ds_v4', 'Standard_D15i_v2', 'Standard_D48ds_v4', 'Standard_E64_v3', 'Standard_D1_v2', 'Standard_DS2_v2', 'Basic_A3', 'Standard_DS4_v2', 'Standard_DS14-8_v2', 'Standard_E20s_v4', 'Standard_E16as_v4', 'Standard_D96_v5', 'Standard_E4s_v3', 'Standard_D32s_v4', 'Standard_E32-8as_v4', 'Standard_D2d_v4', 'Standard_E8-2s_v4', 'Standard_D4ds_v4', 'Standard_E48s_v4', 'Standard_F32s_v2', 'Standard_DS15_v2', 'Standard_E96d_v5', 'Standard_D2ds_v5', 'Standard_DS13-2_v2', 'Standard_E96a_v4', 'Standard_D16d_v4', 'Standard_D96a_v4', 'Standard_D48ds_v5', 'Standard_E16-8as_v4', 'Standard_E32-8s_v4', 'Standard_D8ds_v4', 'Standard_E2_v3', 'Standard_D4_v4', 'Standard_D2as_v4', 'Standard_E8_v4', 'Standard_D64_v5', 'Standard_E64i_v3', 'Standard_E16-4as_v4', 'Standard_E20ds_v4', 'Standard_E32-8s_v3', 'Standard_D48s_v3', 'Standard_E32_v4', 'Basic_A0', 'Standard_A2_v2', 'Standard_E8-4ds_v4', 'Standard_D8s_v3', 'Standard_D64_v4', 'Standard_E8-4as_v4', 'Standard_D32as_v4', 'Standard_E2s_v3', 'Standard_DS13_v2', 'Standard_D4_v5', 'Standard_D32_v4'],
'northeurope': ['Standard_E48_v4', 'Standard_M32ms', 'Standard_E32a_v4', 'Standard_D64s_v3', 'Standard_M32dms_v2', 'Standard_M128s_v2', 'Standard_F2s_v2', 'Basic_A0', 'Standard_E16-4s_v3', 'Standard_E32_v4', 'Standard_D64ds_v5', 'Standard_DS4_v2', 'Standard_NV24s_v3', 'Standard_D48s_v5', 'Standard_E4-2ds_v4', 'Standard_A5', 'Standard_D8s_v3', 'Standard_D8ds_v4', 'Standard_NC24rs_v3', 'Standard_F1', 'Standard_M128-32ms', 'Standard_D64ds_v4', 'Standard_D2_v5', 'Standard_D16_v4', 'Standard_E8-4ds_v4', 'Standard_E64ds_v4', 'Standard_D64d_v4', 'Standard_L8s_v2', 'Standard_E20a_v4', 'Standard_NC4as_T4_v3', 'Standard_A0', 'Standard_D2d_v4', 'Standard_E64_v4', 'Standard_E32_v3', 'Standard_E8-2s_v4', 'Standard_DS15_v2', 'Standard_E16-4ds_v4', 'Standard_E96as_v4', 'Standard_A4_v2', 'Standard_M32s', 'Standard_D8as_v4', 'Standard_F32s_v2', 'Standard_E64d_v4', 'Standard_E20_v4', 'Standard_E8-2s_v3', 'Standard_M416-104ms_v2', 'Standard_D48_v3', 'Standard_M64', 'Standard_D14', 'Standard_E48ds_v4', 'Standard_D4d_v4', 'Standard_D2s_v5', 'Standard_D2s_v4', 'Standard_D5_v2', 'Standard_M208-52ms_v2', 'Standard_E16-8ds_v4', 'Standard_NV12s_v3', 'Standard_D4s_v5', 'Standard_E64is_v3', 'Standard_D48d_v4', 'Standard_H16m', 'Standard_E16-8s_v4', 'Standard_E32-8ds_v4', 'Standard_NV6', 'Standard_E64-16s_v4', 'Standard_E32_v5', 'Standard_D12', 'Standard_M8-4ms', 'Standard_DS11', 'Standard_D2s_v3', 'Standard_D48_v5', 'Standard_D16_v3', 'Standard_D8d_v5', 'Standard_D8ds_v5', 'Standard_A10', 'Standard_E8a_v4', 'Standard_D1_v2', 'Standard_D48s_v3', 'Standard_NV8as_v4', 'Standard_D96a_v4', 'Standard_A7', 'Standard_D64s_v5', 'Standard_L88is_v2', 'Standard_D8d_v4', 'Standard_DS14-4_v2', 'Standard_E4-2as_v4', 'Standard_E16as_v4', 'Standard_M16ms', 'Standard_L32s_v2', 'Standard_E16-4s_v4', 'Standard_D64d_v5', 'Standard_D15_v2', 'Standard_D32ds_v4', 'Standard_A1', 'Standard_E64s_v3', 'Standard_E32-16as_v4', 'Standard_D64as_v4', 'Standard_E96-48as_v4', 'Standard_F4', 'Standard_NC12', 'Standard_M192idms_v2', 'Standard_D8_v4', 'Standard_E2d_v4', 'Standard_D4', 'Standard_NV16as_v4', 'Standard_E32-16s_v4', 'Standard_F4s', 'Standard_M192ims_v2', 'Standard_D32d_v5', 'Standard_M32-16ms', 'Standard_NC64as_T4_v3', 'Standard_M128dms_v2', 'Standard_F48s_v2', 'Standard_E4-2s_v3', 'Standard_D4s_v3', 'Standard_E16a_v4', 'Standard_DS14-8_v2', 'Basic_A1', 'Standard_DS14', '', 'Standard_M8ms', 'Standard_DS12_v2', 'Standard_D4_v3', 'Standard_E96a_v4', 'Standard_M8-2ms', 'Standard_E16d_v5', 'Standard_DS5_v2', 'Standard_M32ls', 'Standard_E48as_v4', 'Standard_E48d_v4', 'Standard_D32_v3', 'Standard_D64s_v4', 'Standard_DS2', 'Standard_M16s', 'Standard_M64s', 'Standard_E8-2as_v4', 'Standard_E64i_v3', 'Standard_E8as_v4', 'Standard_E8s_v4', 'Standard_D48a_v4', 'Standard_DS13_v2', 'Standard_D32ds_v5', 'Standard_D16s_v3', 'Standard_F8s', 'Standard_D4ds_v5', 'Standard_E32-8as_v4', 'Standard_D96d_v5', 'Standard_NC24r', 'Standard_M64s_v2', 'Standard_E20_v3', 'Standard_E48s_v4', 'Standard_D4ds_v4', 'Standard_E16d_v4', 'Standard_E2s_v3', 'Standard_D8a_v4', 'Standard_E8-2ds_v4', 'Standard_D2d_v5', 'Standard_D48d_v5', 'Standard_D16d_v4', 'Standard_E20s_v3', 'Standard_E2as_v4', 'Standard_M128ms_v2', 'Standard_M208-52s_v2', 'Standard_E16_v5', 'Standard_E48_v5', 'Standard_E32-16ds_v4', 'Standard_A9', 'Standard_D13_v2', 'Standard_D32-16s_v3', 'Standard_D8s_v4', 'Standard_D4_v5', 'Standard_DS12-1_v2', 'Standard_E64a_v4', 'Standard_E64-16ds_v4', 'Standard_D2ds_v4', 'Standard_D96as_v4', 'Standard_E16-4as_v4', 'Standard_F72s_v2', 'Standard_D32-8s_v3', 'Standard_M416-104s_v2', 'Standard_D48ds_v5', 'Standard_D2as_v4', 'Standard_DS14_v2', 'Standard_NC24s_v3', 'Standard_D16ds_v4', 'Standard_D4d_v5', 'Standard_F2s', 'Standard_D48ds_v4', 'Standard_HC44-16rs', 'Standard_E8d_v5', 'Standard_E8ds_v4', 'Standard_E8-4s_v4', 'Standard_E2ds_v4', 'Standard_DS4', 'Standard_D11', 'Standard_D48as_v4', 'Standard_E48a_v4', 'Standard_D2_v4', 'Standard_E32s_v3', 'Standard_E4d_v5', 'Standard_HC44-32rs', 'Standard_E64s_v4', 'Standard_E64-32ds_v4', 'Standard_E20d_v5', 'Standard_E4_v5', 'Standard_NC8as_T4_v3', 'Standard_D32s_v5', 'Standard_DC2s_v2', 'Standard_D2_v2', 'Standard_H8m', 'Standard_D32_v5', 'Standard_E16_v4', 'Standard_E20ds_v4', 'Standard_M208-104ms_v2', 'Standard_E4ds_v4', 'Standard_A4', 'Standard_F64s_v2', 'Standard_DS3', 'Standard_A11', 'Standard_E96_v5', 'Standard_D4as_v4', 'Standard_A8m_v2', 'Standard_DS12', 'Standard_D32d_v4', 'Standard_HC44rs', 'Standard_A6', 'Standard_E64-32as_v4', 'Standard_E32-16s_v3', 'Standard_E4_v4', 'Standard_F16s', 'Standard_M128-64ms', 'Standard_D8s_v5', 'Standard_H16mr', 'Standard_E2_v5', 'Standard_E96-24as_v4', 'Standard_L64s_v2', 'Standard_E16ds_v4', 'Standard_M64-16ms', 'Standard_A8', 'Standard_M416-208ms_v2', 'Standard_D96_v5', 'Standard_NV48s_v3', 'Standard_E4a_v4', 'Standard_D96ds_v5', 'Standard_M208ms_v2', 'Standard_M16-8ms', 'Standard_DC4s_v2', 'Standard_D4a_v4', 'Standard_M32-8ms', 'Standard_A2', 'Standard_DS1', 'Standard_E20_v5', 'Standard_E64as_v4', 'Standard_D16as_v4', 'Standard_A8_v2', 'Standard_L48s_v2', 'Standard_M32ms_v2', 'Standard_E48s_v3', 'Standard_DS2_v2', 'Standard_D8_v5', 'Standard_D48s_v4', 'Standard_A2_v2', 'Standard_E80is_v4', 'Standard_DS1_v2', 'Standard_D16_v5', 'Standard_D32as_v4', 'Standard_L80s_v2', 'Standard_NC16as_T4_v3', 'Standard_E8_v5', 'Standard_E2a_v4', 'Standard_D4_v4', 'Standard_E2_v4', 'Standard_DS15i_v2', 'Standard_D12_v2', 'Standard_E4_v3', 'Standard_DS11_v2', 'Standard_NV4as_v4', 'Standard_D3', 'Standard_H16', 'Standard_E2s_v4', 'Standard_E32s_v4', 'Standard_DS13-2_v2', 'Standard_E16s_v3', 'Standard_D64-16s_v3', 'Standard_L16s_v2', 'Standard_E20d_v4', 'Standard_E16-8as_v4', 'Basic_A3', 'Standard_E2_v3', 'Standard_D64a_v4', 'Standard_H16r', 'Standard_M128', 'Standard_M416is_v2', 'Standard_E48d_v5', 'Standard_F4s_v2', 'Standard_E64_v5', 'Standard_F16s_v2', 'Standard_M128m', 'Standard_D16a_v4', 'Standard_D15i_v2', 'Standard_D32_v4', 'Standard_E64-32s_v3', 'Standard_M64ms', 'Standard_F1s', 'Standard_D16s_v5', 'Standard_D64_v4', 'Standard_D13', 'Standard_M416-208s_v2', 'Standard_F8', 'Standard_M128ds_v2', 'Standard_D64_v5', 'Standard_E32-8s_v4', 'Standard_D16s_v4', 'Basic_A4', 'Standard_E20s_v4', 'Standard_M208s_v2', 'Standard_DS3_v2', 'Standard_NV24', 'Standard_E64d_v5', 'Standard_A1_v2', 'Standard_D4s_v4', 'Standard_DC8_v2', 'Standard_D8_v3', 'Standard_DC1s_v2', 'Standard_E4s_v3', 'Standard_F2', 'Standard_M192is_v2', 'Standard_E64-16s_v3', 'Standard_E80ids_v4', 'Standard_M64m', 'Standard_E8d_v4', 'Standard_E2d_v5', 'Standard_E4d_v4', 'Standard_E64-16as_v4', 'Standard_D4_v2', 'Standard_DS13', 'Standard_NC24', 'Standard_M16-4ms', 'Standard_F8s_v2', 'Standard_D64_v3', 'Standard_E4as_v4', 'Standard_F16', 'Standard_D3_v2', 'Standard_E8-4as_v4', 'Standard_E4s_v4', 'Standard_D2ds_v5', 'Standard_D32s_v4', 'Standard_NC6', 'Standard_E8_v3', 'Standard_M64ls', 'Standard_M128s', 'Standard_D1', 'Standard_M64dms_v2', 'Standard_M416ms_v2', 'Standard_E20as_v4', 'Standard_E8_v4', 'Standard_D16d_v5', 'Basic_A2', 'Standard_A3', 'Standard_E64-32s_v4', 'Standard_M32ts', 'Standard_E4-2s_v4', 'Standard_M128ms', 'Standard_E16_v3', 'Standard_E64_v3', 'Standard_M64ds_v2', 'Standard_NV12', 'Standard_E32d_v4', 'Standard_D2a_v4', 'Standard_D48_v4', 'Standard_M64ms_v2', 'Standard_NV32as_v4', 'Standard_DS11-1_v2', 'Standard_D32a_v4', 'Standard_M208-104s_v2', 'Standard_E32ds_v4', 'Standard_NC12s_v3', 'Standard_E8s_v3', 'Standard_DS12-2_v2', 'Standard_A4m_v2', 'Standard_E16-8s_v3', 'Standard_D2_v3', 'Standard_D2', 'Standard_E32d_v5', 'Standard_E8-4s_v3', 'Standard_E32-8s_v3', 'Standard_D64-32s_v3', 'Standard_E96d_v5', 'Standard_DS13-4_v2', 'Standard_E16s_v4', 'Standard_M64-32ms', 'Standard_A2m_v2', 'Standard_E32as_v4', 'Standard_E48_v3', 'Standard_M192ids_v2', 'Standard_D11_v2', 'Standard_D14_v2', 'Standard_D16ds_v5', 'Standard_D32s_v3', 'Standard_H8', 'Standard_M416s_v2', 'Standard_NC6s_v3', 'Standard_D96s_v5'],
'westeurope': ['Standard_F16s', 'Standard_D4ds_v5', 'Standard_DS14-4_v2', 'Standard_E32ds_v4', 'Standard_A9', 'Standard_A4m_v2', 'Standard_E8-2as_v4', 'Standard_D48ds_v5', 'Standard_M64ms', 'Standard_D16a_v4', 'Basic_A0', 'Standard_DS14', 'Standard_F8s', 'Standard_DS12_v2', 'Standard_E4a_v4', 'Standard_D2', 'Standard_D2ds_v5', 'Standard_E2s_v4', 'Standard_E64-16s_v4', 'Standard_E96_v5', 'Standard_D4', 'Standard_HB60-15rs', 'Standard_DS13_v2', 'Standard_E8_v5', 'Standard_HB120-32rs_v3', 'Standard_A4', 'Standard_HB60-30rs', 'Standard_NV16as_v4', 'Standard_DS3_v2', 'Standard_E8-4s_v3', 'Standard_E16d_v4', 'Standard_ND96asr_A100_v4', 'Standard_D4_v5', 'Standard_E8-2s_v4', 'Standard_E64a_v4', 'Standard_E48d_v5', 'Standard_D13', 'Standard_D32_v3', 'Standard_D64_v3', 'Standard_M32ts', 'Standard_HB60rs', 'Standard_E2s_v3', 'Standard_GS3', 'Standard_D8_v4', 'Standard_D96_v5', '', 'Standard_A5', 'Standard_D48a_v4', 'Standard_DS2_v2', 'Standard_A1', 'Standard_D8_v3', 'Standard_M128-32ms', 'Standard_E48_v3', 'Standard_E64_v5', 'Standard_F4', 'Standard_D4d_v4', 'Standard_E32as_v4', 'Standard_D64_v4', 'Standard_D2s_v5', 'Standard_DS13-4_v2', 'Standard_M32-8ms', 'Standard_D32_v4', 'Standard_NC24s_v3', 'Standard_DS14_v2', 'Standard_E8-4ds_v4', 'Standard_E16_v3', 'Standard_F2s', 'Standard_M128ds_v2', 'Standard_L64s_v2', 'Standard_E8ds_v4', 'Standard_D4_v4', 'Standard_E8-2ds_v4', 'Standard_NC12s_v2', 'Standard_E4_v4', 'Standard_D14_v2', 'Standard_M64dms_v2', 'Standard_E32-16s_v3', 'Standard_M64ds_v2', 'Standard_E80is_v4', 'Standard_DS12', 'Standard_M64s', 'Standard_M16-4ms', 'Standard_M192ims_v2', 'Standard_D32as_v4', 'Standard_D2_v4', 'Standard_E32-16as_v4', 'Standard_E16d_v5', 'Standard_DS4', 'Basic_A4', 'Standard_DS15i_v2', 'Standard_ND40rs_v2', 'Standard_M64-32ms', 'Standard_D64_v5', 'Standard_E20as_v4', 'Standard_NV12s_v3', 'Standard_E32_v4', 'Standard_D16s_v5', 'Standard_D48ds_v4', 'Standard_E8-2s_v3', 'Standard_D16ds_v4', 'Standard_M32dms_v2', 'Standard_DS12-1_v2', 'Standard_H8', 'Standard_NV48s_v3', 'Standard_D48_v3', 'Standard_L4s', 'Standard_D32ds_v5', 'Standard_D2a_v4', 'Standard_D2as_v4', 'Standard_D15_v2', 'Standard_D32s_v4', 'Standard_E48d_v4', 'Standard_GS1', 'Standard_E96-24as_v4', 'Standard_E2_v5', 'Standard_M64ms_v2', 'Standard_D14', 'Standard_D16d_v4', 'Standard_D11_v2', 'Standard_G4', 'Standard_E64-16s_v3', 'Standard_E96-48as_v4', 'Standard_M16ms', 'Standard_D2d_v4', 'Standard_E16s_v3', 'Standard_D8a_v4', 'Standard_E48s_v3', 'Standard_M416-208ms_v2', 'Basic_A2', 'Standard_M32s', 'Standard_M128s', 'Standard_D64d_v5', 'Standard_DC2s_v2', 'Standard_D4as_v4', 'Standard_D3_v2', 'Standard_NC6', 'Standard_DS5_v2', 'Standard_DS13-2_v2', 'Standard_D48s_v4', 'Standard_HB120rs_v3', 'Standard_F16', 'Standard_D4a_v4', 'Standard_DC2s', 'Standard_F8', 'Standard_DS1', 'Standard_E2_v4', 'Standard_NV6', 'Standard_D16_v5', 'Standard_A7', 'Standard_D16as_v4', 'Standard_E8a_v4', 'Standard_D8d_v5', 'Standard_E32-8as_v4', 'Standard_E96d_v5', 'Standard_NC24', 'Standard_M32ms_v2', 'Standard_NV32as_v4', 'Standard_D5_v2', 'Standard_DS11', 'Standard_M64ls', 'Standard_E16_v5', 'Standard_A1_v2', 'Standard_E16-8as_v4', 'Standard_E4d_v5', 'Standard_E8d_v5', 'Standard_L16s', 'Standard_D16ds_v5', 'Standard_DS11-1_v2', 'Standard_E20_v3', 'Standard_NC24rs_v3', 'Standard_D96as_v4', 'Standard_E32s_v4', 'Standard_H16m', 'Standard_NC6s_v2', 'Standard_E80ids_v4', 'Standard_E2_v3', 'Standard_DS11_v2', 'Standard_E20d_v5', 'Standard_F1', 'Standard_F2', 'Standard_E64_v3', 'Standard_E64-32s_v4', 'Standard_D16_v3', 'Standard_HC44-32rs', 'Standard_L88is_v2', 'Standard_D96d_v5', 'Standard_E16-4s_v3', 'Standard_ND12s', 'Standard_D32-8s_v3', 'Standard_A3', 'Standard_E64s_v4', 'Standard_H16', 'Standard_E16_v4', 'Standard_L16s_v2', 'Standard_DS1_v2', 'Standard_G1', 'Standard_E64d_v5', 'Standard_E16-4as_v4', 'Standard_F1s', 'Standard_L80s_v2', 'Standard_E32s_v3', 'Standard_E64-32ds_v4', 'Standard_D64a_v4', 'Standard_E20s_v3', 'Standard_HC44rs', 'Standard_D13_v2', 'Standard_DS3', 'Standard_D32s_v3', 'Standard_E32-8s_v3', 'Standard_D48s_v5', 'Standard_D48_v4', 'Standard_D64-32s_v3', 'Standard_M128ms', 'Standard_D11', 'Standard_GS5-8', 'Standard_E16-4s_v4', 'Standard_M8ms', 'Standard_D32d_v5', 'Standard_E2d_v5', 'Standard_D4d_v5', 'Standard_D2_v2', 'Standard_D32-16s_v3', 'Standard_DC4s_v2', 'Standard_E2as_v4', 'Standard_E20_v4', 'Standard_NC12', 'Standard_NC16as_T4_v3', 'Standard_E32d_v4', 'Standard_D2ds_v4', 'Standard_E64d_v4', 'Standard_E20ds_v4', 'Standard_E20_v5', 'Standard_A2m_v2', 'Standard_E16-8s_v4', 'Standard_D2d_v5', 'Standard_D8ds_v4', 'Standard_DS15_v2', 'Standard_E32d_v5', 'Standard_E4-2s_v4', 'Standard_E48s_v4', 'Standard_E8-4s_v4', 'Standard_M416ms_v2', 'Standard_E16-8s_v3', 'Standard_GS5-16', 'Standard_E64-32s_v3', 'Standard_M192ids_v2', 'Standard_E64-16as_v4', 'Standard_D4s_v5', 'Standard_E64_v4', 'Standard_M208-52s_v2', 'Standard_E32-16ds_v4', 'Standard_D12', 'Standard_NC24s_v2', 'Standard_M208s_v2', 'Standard_M128m', 'Standard_E32_v3', 'Standard_M192idms_v2', 'Standard_M208-104ms_v2', 'Standard_PB12s', 'Standard_E4s_v3', 'Standard_M128ms_v2', 'Basic_A3', 'Standard_PB24s', 'Standard_F4s', 'Standard_D64as_v4', 'Standard_D8s_v5', 'Standard_E16s_v4', 'Standard_M192is_v2', 'Standard_HB120rs_v2', 'Standard_ND6s', 'Standard_NV8as_v4', 'Standard_NC12s_v3', 'Standard_E16-8ds_v4', 'Standard_E32_v5', 'Standard_E16ds_v4', 'Standard_M32ms', 'Standard_D96a_v4', 'Standard_E16a_v4', 'Standard_D48_v5', 'Standard_E4as_v4', 'Standard_E96a_v4', 'Standard_E48as_v4', 'Standard_E64-32as_v4', 'Standard_E32-8s_v4', 'Standard_A10', 'Standard_D64ds_v5', 'Standard_PB6s', 'Standard_NC64as_T4_v3', 'Standard_D8_v5', 'Standard_L8s_v2', 'Standard_E4s_v4', 'Standard_M8-4ms', 'Standard_G5', 'Standard_E20a_v4', 'Standard_E64is_v3', 'Standard_DS13', 'Standard_E8s_v3', 'Standard_E16as_v4', 'Standard_M16s', 'Standard_E48_v5', 'Standard_HB120-16rs_v3', 'Standard_DS12-2_v2', 'Standard_HB60-45rs', 'Standard_D3', 'Standard_E4d_v4', 'Standard_D32ds_v4', 'Standard_D8d_v4', 'Standard_E4_v5', 'Standard_NC24r', 'Standard_M416is_v2', 'Standard_NV24', 'Standard_D16s_v4', 'Standard_HC44-16rs', 'Standard_M128s_v2', 'Standard_E8_v4', 'Standard_NC4as_T4_v3', 'Standard_L32s', 'Standard_DS14-8_v2', 'Standard_D64s_v4', 'Standard_D8as_v4', 'Standard_HB120-64rs_v3', 'Standard_D64-16s_v3', 'Standard_M64s_v2', 'Standard_DC8_v2', 'Standard_NV12', 'Standard_D4s_v3', 'Standard_DS4_v2', 'Standard_D32s_v5', 'Standard_NP20s', 'Standard_D64s_v5', 'Standard_M16-8ms', 'Standard_M416s_v2', 'Standard_A11', 'Standard_G3', 'Standard_L32s_v2', 'Standard_M208ms_v2', 'Standard_A8m_v2', 'Standard_HB120-96rs_v3', 'Standard_D32a_v4', 'Standard_GS5', 'Standard_D96s_v5', 'Standard_DC1s_v2', 'Standard_H16mr', 'Standard_D12_v2', 'Standard_NV4as_v4', 'Standard_A6', 'Standard_F16s_v2', 'Standard_H8m', 'Standard_D4s_v4', 'Standard_D48d_v4', 'Standard_F2s_v2', 'Standard_M32-16ms', 'Standard_F4s_v2', 'Standard_M416-104ms_v2', 'Standard_D96ds_v5', 'Standard_E32-16s_v4', 'Standard_ND24rs', 'Standard_D48as_v4', 'Standard_D64s_v3', 'Standard_D8s_v4', 'Standard_M128', 'Standard_D2_v5', 'Standard_D64ds_v4', 'Standard_M32ls', 'Standard_D2s_v4', 'Standard_E48_v4', 'Standard_NV24s_v3', 'Standard_DS2', 'Standard_F64s_v2', 'Standard_E8d_v4', 'Standard_M208-104s_v2', 'Standard_D16s_v3', 'Standard_D4ds_v4', 'Standard_D8ds_v5', 'Standard_E16-4ds_v4', 'Standard_NC8as_T4_v3', 'Standard_D4_v3', 'Standard_A8', 'Standard_A4_v2', 'Standard_E64as_v4', 'Standard_ND96asr_v4', 'Standard_F32s_v2', 'Standard_D48s_v3', 'Standard_ND24s', 'Standard_F72s_v2', 'Standard_GS4-8', 'Standard_NC24rs_v2', 'Standard_D2s_v3', 'Standard_M128-64ms', 'Standard_DC4s', 'Standard_GS4-4', 'Standard_D16d_v5', 'Standard_H16r', 'Standard_M64', 'Standard_E2ds_v4', 'Standard_E96as_v4', 'Standard_A2_v2', 'Standard_E8s_v4', 'Standard_E4-2s_v3', 'Standard_M64-16ms', 'Standard_GS2', 'Standard_A2', 'Standard_D32d_v4', 'Standard_E4-2as_v4', 'Standard_M128dms_v2', 'Standard_D1', 'Standard_E8_v3', 'Standard_E2a_v4', 'Standard_F48s_v2', 'Standard_E4_v3', 'Standard_E64s_v3', 'Standard_A8_v2', 'Standard_E48ds_v4', 'Standard_D48d_v5', 'Standard_NP40s', 'Standard_D1_v2', 'Standard_E64ds_v4', 'Standard_D64d_v4', 'Standard_E20s_v4', 'Standard_D4_v2', 'Standard_ND40s_v2', 'Standard_D15i_v2', 'Standard_F8s_v2', 'Standard_L8s', 'Standard_E2d_v4', 'Standard_D32_v5', 'Standard_D2_v3', 'Standard_E20d_v4', 'Standard_E32a_v4', 'Standard_E8as_v4', 'Standard_M416-208s_v2', 'Standard_A0', 'Standard_NC6s_v3', 'Standard_E64-16ds_v4', 'Standard_NP10s', 'Standard_M8-2ms', 'Basic_A1', 'Standard_M208-52ms_v2', 'Standard_D8s_v3', 'Standard_E48a_v4', 'Standard_GS4', 'Standard_D16_v4', 'Standard_E32-8ds_v4', 'Standard_M416-104s_v2', 'Standard_E8-4as_v4', 'Standard_M64m', 'Standard_E64i_v3', 'Standard_E4-2ds_v4', 'Standard_L48s_v2', 'Standard_G2', 'Standard_E4ds_v4'],
'japaneast': ['Standard_M8-2ms', 'Standard_F1', 'Standard_E4s_v3', 'Standard_E32d_v5', 'Standard_D64-32s_v3', 'Standard_A1_v2', 'Standard_D5_v2', 'Standard_D64d_v4', 'Standard_E8s_v4', 'Standard_NV6', 'Standard_F16s_v2', 'Standard_D4d_v4', 'Standard_L48s_v2', 'Standard_NC24rs_v3', 'Standard_D16d_v5', 'Standard_GS5-16', 'Standard_M128ds_v2', 'Standard_E64-32s_v4', 'Standard_E16-4ds_v4', 'Standard_E2_v4', 'Standard_D32_v3', 'Standard_E20_v4', 'Standard_M192ims_v2', 'Standard_E32s_v3', 'Standard_M128ms_v2', 'Standard_F48s_v2', 'Standard_D64-16s_v3', 'Standard_NV16as_v4', 'Standard_D64d_v5', 'Standard_D8s_v3', 'Standard_D48ds_v4', 'Standard_D48s_v4', 'Standard_E20_v5', 'Standard_E64d_v5', 'Standard_E8-4ds_v4', 'Standard_D48s_v3', 'Standard_M128ms', 'Standard_NV48s_v3', 'Standard_A4', 'Standard_F2s', 'Standard_E20d_v5', 'Standard_M64s', 'Standard_M416-104s_v2', 'Standard_D4a_v4', 'Standard_D2d_v5', 'Standard_DS4', 'Standard_E64-32as_v4', 'Standard_D4s_v3', 'Standard_DS3_v2', 'Standard_M32-16ms', 'Standard_E48as_v4', 'Standard_D4', 'Standard_A5', 'Standard_E32_v5', 'Standard_NC16as_T4_v3', 'Standard_NV24', 'Standard_D32ds_v4', 'Standard_F4', 'Standard_NC64as_T4_v3', 'Standard_D2ds_v4', 'Standard_DS5_v2', 'Standard_E4_v5', 'Standard_D13', 'Standard_E2s_v3', 'Standard_M416ms_v2', 'Standard_M128s', 'Standard_E8ds_v4', 'Standard_E32a_v4', 'Standard_D4d_v5', 'Standard_M416-208ms_v2', 'Standard_E96a_v4', 'Standard_E20as_v4', 'Standard_D96as_v4', 'Standard_D15_v2', 'Standard_E4-2s_v4', 'Standard_E8_v3', 'Standard_L4s', 'Standard_A3', 'Standard_E64i_v3', 'Standard_F2', 'Standard_E80ids_v4', 'Standard_D16_v4', 'Standard_D32_v5', 'Standard_D48s_v5', 'Standard_E32-16s_v3', 'Standard_D8d_v4', 'Standard_M416-104ms_v2', 'Standard_E8_v4', 'Standard_E96d_v5', 'Standard_G4', 'Standard_NV24s_v3', 'Standard_E20s_v4', 'Standard_M208s_v2', 'Standard_D8_v5', 'Standard_GS2', 'Standard_DS12-2_v2', 'Standard_DS1', 'Standard_A2', 'Standard_DS12', 'Standard_M64-16ms', 'Standard_E2d_v5', 'Standard_E4_v3', 'Standard_E20a_v4', 'Standard_D8_v4', 'Standard_D4_v3', 'Standard_M208-104s_v2', 'Standard_GS4', 'Standard_E16-4s_v4', 'Standard_A8m_v2', 'Standard_F2s_v2', 'Standard_E16_v5', 'Standard_D2_v5', 'Standard_E48s_v3', 'Standard_E32-8as_v4', 'Standard_D16ds_v5', 'Standard_E64s_v3', 'Standard_E20d_v4', 'Standard_E48d_v4', '', 'Standard_E48_v3', 'Standard_E8a_v4', 'Standard_D4s_v4', 'Standard_E32as_v4', 'Standard_D16d_v4', 'Standard_DS11_v2', 'Standard_F8s', 'Standard_D4ds_v4', 'Standard_DS15_v2', 'Standard_M192idms_v2', 'Standard_DS13-4_v2', 'Standard_D48_v4', 'Standard_A0', 'Standard_M32ms_v2', 'Standard_D12', 'Standard_M128-64ms', 'Standard_D2_v3', 'Standard_E16as_v4', 'Standard_E32-8s_v4', 'Standard_E16-8as_v4', 'Standard_DS14', 'Standard_E48d_v5', 'Standard_D8_v3', 'Standard_E64-32s_v3', 'Standard_E64as_v4', 'Standard_M32s', 'Standard_D4_v5', 'Standard_DS2', 'Standard_NC24s_v3', 'Standard_GS5-8', 'Standard_L64s_v2', 'Standard_E2_v5', 'Standard_E32_v4', 'Standard_NV12', 'Standard_D32d_v4', 'Standard_NV32as_v4', 'Standard_E64_v4', 'Standard_H16', 'Standard_E64-16s_v4', 'Standard_D14_v2', 'Standard_D48_v5', 'Standard_DS11', 'Standard_E48s_v4', 'Standard_H16r', 'Standard_D3_v2', 'Standard_D4as_v4', 'Standard_L8s', 'Standard_E8-2s_v3', 'Standard_G2', 'Standard_E64-16s_v3', 'Standard_E2ds_v4', 'Standard_E32ds_v4', 'Standard_D4s_v5', 'Basic_A3', 'Standard_E16_v4', 'Standard_D96ds_v5', 'Standard_D8as_v4', 'Standard_A8', 'Standard_D8s_v5', 'Standard_D2_v4', 'Standard_M32ls', 'Standard_M64m', 'Standard_M128s_v2', 'Standard_D48a_v4', 'Standard_M208-104ms_v2', 'Standard_D64ds_v4', 'Standard_DS14-4_v2', 'Standard_D32s_v4', 'Standard_E16d_v4', 'Standard_G5', 'Standard_NV4as_v4', 'Standard_E8d_v5', 'Standard_M64dms_v2', 'Standard_D48d_v5', 'Standard_E16s_v3', 'Standard_L8s_v2', 'Standard_A4_v2', 'Standard_D2s_v4', 'Standard_D64_v3', 'Standard_E16-8ds_v4', 'Standard_NC8as_T4_v3', 'Standard_F32s_v2', 'Standard_D2d_v4', 'Standard_D16_v3', 'Standard_D16s_v4', 'Standard_L32s_v2', 'Standard_D32s_v5', 'Standard_D32s_v3', 'Standard_E48a_v4', 'Standard_DS11-1_v2', 'Standard_F8s_v2', 'Standard_E64-16as_v4', 'Standard_D4ds_v5', 'Standard_E8-4s_v4', 'Standard_G3', 'Standard_HC44-32rs', 'Standard_E20ds_v4', 'Standard_D48_v3', 'Standard_D16_v5', 'Standard_D4_v4', 'Standard_E8-2ds_v4', 'Standard_D2s_v5', 'Standard_D32-8s_v3', 'Standard_M64s_v2', 'Standard_E8s_v3', 'Standard_D32_v4', 'Standard_D8ds_v4', 'Standard_E4-2ds_v4', 'Standard_E48_v5', 'Standard_D2as_v4', 'Standard_D16s_v5', 'Standard_G1', 'Standard_D32a_v4', 'Standard_D11', 'Standard_M64ls', 'Standard_E16-8s_v4', 'Standard_E4-2s_v3', 'Standard_A11', 'Standard_E64d_v4', 'Standard_D48as_v4', 'Standard_D16as_v4', 'Standard_M32ms', 'Standard_M16ms', 'Standard_DS1_v2', 'Standard_E96-24as_v4', 'Standard_A8_v2', 'Standard_E32-16s_v4', 'Standard_M16s', 'Standard_L16s_v2', 'Standard_D96_v5', 'Standard_D2_v2', 'Standard_M64-32ms', 'Standard_M128dms_v2', 'Standard_DS15i_v2', 'Standard_E16_v3', 'Standard_D64s_v3', 'Standard_DS12-1_v2', 'Standard_A2_v2', 'Standard_DS12_v2', 'Standard_D8d_v5', 'Standard_E32-16as_v4', 'Standard_F4s', 'Standard_M64ms', 'Standard_D11_v2', 'Standard_D2', 'Standard_D14', 'Standard_E16-4as_v4', 'Standard_F16', 'Standard_D64ds_v5', 'Standard_E32-8s_v3', 'Basic_A4', 'Standard_E16s_v4', 'Standard_E16ds_v4', 'Standard_E96-48as_v4', 'Standard_E8-4s_v3', 'Standard_E96_v5', 'Standard_L16s', 'Standard_D4_v2', 'Standard_E32d_v4', 'Standard_D96d_v5', 'Standard_D64s_v5', 'Standard_D48d_v4', 'Standard_DS3', 'Standard_M32-8ms', 'Standard_HB120rs_v2', 'Standard_D16ds_v4', 'Standard_M8-4ms', 'Standard_D3', 'Standard_GS1', 'Standard_M416s_v2', 'Standard_M64ds_v2', 'Standard_M128m', 'Standard_E64ds_v4', 'Standard_E8_v5', 'Standard_HC44rs', 'Basic_A1', 'Standard_DS13_v2', 'Standard_E20s_v3', 'Standard_A1', 'Standard_M208-52s_v2', 'Standard_M416is_v2', 'Standard_M128-32ms', 'Standard_NV12s_v3', 'Standard_DS14-8_v2', 'Standard_E96as_v4', 'Standard_GS5', 'Standard_DS4_v2', 'Standard_E80is_v4', 'Standard_E4_v4', 'Standard_E16d_v5', 'Standard_H8m', 'Standard_E32s_v4', 'Standard_E4d_v4', 'Standard_E2s_v4', 'Standard_A4m_v2', 'Standard_E48ds_v4', 'Standard_M16-4ms', 'Standard_D12_v2', 'Standard_D64as_v4', 'Standard_D48ds_v5', 'Standard_D1', 'Standard_D64_v4', 'Standard_E64_v3', 'Standard_DS13-2_v2', 'Standard_D8ds_v5', 'Standard_A9', 'Standard_M16-8ms', 'Standard_GS4-8', 'Standard_H16mr', 'Standard_E2a_v4', 'Standard_D16s_v3', 'Standard_E8-4as_v4', 'Standard_D32d_v5', 'Standard_D32as_v4', 'Standard_D32ds_v5', 'Standard_E64a_v4', 'Standard_M192is_v2', 'Standard_D13_v2', 'Standard_M192ids_v2', 'Basic_A0', 'Standard_A10', 'Standard_DS2_v2', 'Standard_D1_v2', 'Standard_D64_v5', 'Standard_D32-16s_v3', 'Standard_M32ts', 'Standard_GS4-4', 'Standard_D2ds_v5', 'Standard_D15i_v2', 'Standard_M128', 'Standard_E4as_v4', 'Standard_H8', 'Standard_E2_v3', 'Standard_A6', 'Standard_F4s_v2', 'Standard_NV8as_v4', 'Standard_E4s_v4', 'Standard_F72s_v2', 'Standard_E8-2s_v4', 'Standard_GS3', 'Standard_L80s_v2', 'Standard_E4a_v4', 'Standard_E4d_v5', 'Standard_F1s', 'Standard_M8ms', 'Standard_A7', 'Standard_DS13', 'Standard_DS14_v2', 'Standard_E8d_v4', 'Standard_M64ms_v2', 'Standard_D8s_v4', 'Standard_E8-2as_v4', 'Standard_E64_v5', 'Standard_E2as_v4', 'Standard_A2m_v2', 'Standard_D64a_v4', 'Standard_F64s_v2', 'Standard_E32-16ds_v4', 'Standard_E8as_v4', 'Basic_A2', 'Standard_E16-8s_v3', 'Standard_E4-2as_v4', 'Standard_E16-4s_v3', 'Standard_M208ms_v2', 'Standard_E2d_v4', 'Standard_D2a_v4', 'Standard_E32_v3', 'Standard_E64is_v3', 'Standard_D96a_v4', 'Standard_E4ds_v4', 'Standard_H16m', 'Standard_M32dms_v2', 'Standard_E64-16ds_v4', 'Standard_M64', 'Standard_D2s_v3', 'Standard_D96s_v5', 'Standard_NC6s_v3', 'Standard_E16a_v4', 'Standard_F8', 'Standard_NC4as_T4_v3', 'Standard_E48_v4', 'Standard_L32s', 'Standard_E32-8ds_v4', 'Standard_E20_v3', 'Standard_F16s', 'Standard_HC44-16rs', 'Standard_E64-32ds_v4', 'Standard_D8a_v4', 'Standard_D64s_v4', 'Standard_D16a_v4', 'Standard_M208-52ms_v2', 'Standard_NC12s_v3', 'Standard_M416-208s_v2', 'Standard_E64s_v4'],
'japanwest': ['Standard_D16ds_v5', 'Basic_A1', 'Standard_E2d_v4', 'Standard_E80is_v4', 'Standard_D32_v3', 'Standard_E16-8ds_v4', 'Standard_DS14', 'Standard_DS15_v2', 'Standard_A1', 'Standard_D64d_v4', 'Standard_DS1_v2', 'Standard_E64_v3', 'Standard_A5', 'Standard_D32_v5', 'Standard_E64-16s_v3', 'Standard_DS12_v2', 'Standard_D16_v5', 'Standard_DS14-4_v2', 'Standard_E20_v4', 'Standard_M32-8ms', 'Standard_M64ds_v2', 'Standard_D64s_v3', 'Basic_A4', 'Standard_A8_v2', 'Standard_M192idms_v2', 'Standard_F16s_v2', 'Standard_DS12-1_v2', 'Standard_M128ds_v2', 'Standard_D8_v4', 'Standard_D48ds_v4', 'Standard_E8-2ds_v4', 'Standard_M416-104s_v2', 'Standard_D4_v4', 'Standard_D64s_v5', 'Standard_E8ds_v4', 'Standard_E16_v4', 'Standard_DS2_v2', 'Standard_DS4_v2', 'Standard_M64ms', 'Standard_D8s_v5', 'Standard_M32-16ms', 'Standard_D48_v4', 'Standard_E8-2s_v4', 'Standard_M64s', 'Standard_E64d_v4', 'Standard_F4s', 'Standard_D16s_v3', 'Standard_M128-32ms', 'Standard_E48s_v4', 'Standard_M32ls', 'Standard_A1_v2', 'Standard_E16s_v3', 'Standard_D32s_v3', 'Standard_F72s_v2', 'Standard_M16-4ms', 'Standard_E64ds_v4', 'Standard_D1', 'Standard_E32s_v3', 'Standard_F2', 'Standard_E32-16ds_v4', 'Standard_D16_v3', 'Standard_E64s_v3', 'Standard_A4m_v2', 'Standard_E8_v4', 'Standard_DS11', 'Standard_E32_v5', '', 'Standard_E4_v4', 'Standard_D32d_v4', 'Standard_D8_v3', 'Standard_M416-208ms_v2', 'Standard_F32s_v2', 'Standard_D11', 'Standard_D2', 'Standard_D32-8s_v3', 'Standard_M16-8ms', 'Standard_E4_v5', 'Standard_DS13_v2', 'Standard_E20s_v3', 'Standard_E2_v4', 'Standard_D64ds_v5', 'Standard_M64s_v2', 'Standard_F1s', 'Standard_D16d_v5', 'Standard_D15_v2', 'Standard_E64i_v3', 'Standard_D96_v5', 'Standard_M32s', 'Standard_E64_v4', 'Standard_D2d_v4', 'Standard_E8s_v3', 'Standard_M416-104ms_v2', 'Standard_DS3', 'Standard_DS11-1_v2', 'Standard_F8s', 'Standard_D4_v5', 'Standard_M8ms', 'Standard_M128ms_v2', 'Standard_DS14-8_v2', 'Standard_E32-8s_v4', 'Standard_DS12', 'Standard_DS4', 'Standard_E64is_v3', 'Standard_E32ds_v4', 'Standard_M16s', 'Basic_A3', 'Standard_D32ds_v4', 'Standard_E16-4s_v3', 'Standard_D12', 'Standard_D8_v5', 'Standard_E48d_v5', 'Standard_DS3_v2', 'Standard_M8-2ms', 'Standard_D2_v2', 'Standard_F4s_v2', 'Standard_M208s_v2', 'Standard_A4_v2', 'Standard_E20ds_v4', 'Standard_E32_v4', 'Standard_D32d_v5', 'Standard_D96ds_v5', 'Standard_E64-32s_v3', 'Standard_D64d_v5', 'Standard_D16_v4', 'Standard_E4-2ds_v4', 'Standard_D2_v4', 'Standard_E8-4s_v4', 'Standard_D13', 'Standard_D48s_v5', 'Standard_M416-208s_v2', 'Standard_M128s_v2', 'Standard_D2s_v5', 'Standard_F8s_v2', 'Standard_D48s_v3', 'Standard_D2s_v4', 'Standard_E2ds_v4', 'Standard_M8-4ms', 'Standard_E64-32s_v4', 'Standard_D16s_v4', 'Standard_E4d_v5', 'Standard_F16s', 'Standard_D4_v2', 'Standard_D8d_v4', 'Standard_E2d_v5', 'Standard_E2s_v3', 'Standard_E48d_v4', 'Standard_E16-8s_v3', 'Standard_D16ds_v4', 'Standard_D32-16s_v3', 'Standard_DS5_v2', 'Standard_A6', 'Standard_A2m_v2', 'Standard_D3_v2', 'Standard_D4d_v4', 'Standard_E20_v3', 'Standard_E20s_v4', 'Standard_D32_v4', 'Standard_D64ds_v4', 'Standard_M192ids_v2', 'Standard_E8-4ds_v4', 'Standard_M416is_v2', 'Standard_E16-4s_v4', 'Standard_D14', 'Standard_D2ds_v5', 'Standard_D64_v3', 'Standard_F48s_v2', 'Standard_E64d_v5', 'Standard_D1_v2', 'Standard_DS13-4_v2', 'Standard_D96s_v5', 'Standard_D8ds_v5', 'Standard_E2_v5', 'Standard_D13_v2', 'Standard_E8s_v4', 'Standard_E16s_v4', 'Standard_D64_v5', 'Standard_DS13-2_v2', 'Standard_D16d_v4', 'Standard_M32dms_v2', 'Standard_M128', 'Standard_A8m_v2', 'Standard_F2s', 'Standard_M32ms', 'Standard_D48_v5', 'Standard_D48_v3', 'Standard_E64s_v4', 'Standard_M208-52s_v2', 'Standard_D4s_v5', 'Standard_E8_v3', 'Standard_D4d_v5', 'Standard_E32d_v4', 'Standard_E4s_v3', 'Standard_DS13', 'Standard_D32s_v4', 'Standard_E8d_v4', 'Standard_A2_v2', 'Standard_D64s_v4', 'Standard_D11_v2', 'Standard_E16d_v5', 'Standard_E4-2s_v4', 'Standard_M208-104ms_v2', 'Standard_D48ds_v5', 'Standard_E80ids_v4', 'Standard_D4ds_v5', 'Standard_D96d_v5', 'Standard_E16_v3', 'Standard_M64-32ms', 'Standard_M64ms_v2', 'Standard_E2_v3', 'Standard_E64_v5', 'Standard_E8d_v5', 'Standard_E96d_v5', 'Standard_D4', 'Standard_D8s_v3', 'Standard_M64dms_v2', 'Standard_M208ms_v2', 'Standard_D64-32s_v3', 'Standard_E32s_v4', 'Standard_E48s_v3', 'Standard_D2d_v5', 'Standard_F4', 'Standard_E8_v5', 'Standard_F16', 'Standard_M208-104s_v2', 'Standard_D2_v5', 'Standard_M32ms_v2', 'Standard_E8-2s_v3', 'Standard_M64-16ms', 'Standard_DS2', 'Standard_D8s_v4', 'Standard_E16-8s_v4', 'Standard_E20d_v4', 'Standard_D4s_v4', 'Standard_D4s_v3', 'Standard_DS1', 'Standard_M416s_v2', 'Standard_F1', 'Standard_E48_v3', 'Standard_M128s', 'Standard_D8d_v5', 'Standard_M64', 'Standard_E48_v4', 'Basic_A0', 'Standard_D4ds_v4', 'Standard_DS11_v2', 'Standard_D14_v2', 'Standard_M416ms_v2', 'Standard_D5_v2', 'Standard_E20d_v5', 'Standard_E4_v3', 'Standard_DS14_v2', 'Standard_F8', 'Standard_E4-2s_v3', 'Standard_F2s_v2', 'Standard_DS15i_v2', 'Standard_D48d_v5', 'Standard_D64-16s_v3', 'Standard_E4ds_v4', 'Standard_E8-4s_v3', 'Standard_M192is_v2', 'Standard_M32ts', 'Standard_E4d_v4', 'Standard_E48ds_v4', 'Standard_M192ims_v2', 'Standard_E48_v5', 'Standard_M64ls', 'Standard_E16ds_v4', 'Standard_D3', 'Standard_F64s_v2', 'Standard_E96_v5', 'Standard_D15i_v2', 'Standard_D4_v3', 'Standard_E32-16s_v3', 'Standard_D8ds_v4', 'Standard_A4', 'Standard_E64-16s_v4', 'Basic_A2', 'Standard_A0', 'Standard_E64-32ds_v4', 'Standard_D32s_v5', 'Standard_M128ms', 'Standard_E32-8s_v3', 'Standard_E16-4ds_v4', 'Standard_D2s_v3', 'Standard_D64_v4', 'Standard_D16s_v5', 'Standard_A7', 'Standard_E4s_v4', 'Standard_D48d_v4', 'Standard_M64m', 'Standard_E16_v5', 'Standard_M128m', 'Standard_E64-16ds_v4', 'Standard_D32ds_v5', 'Standard_D2_v3', 'Standard_E2s_v4', 'Standard_D12_v2', 'Standard_M208-52ms_v2', 'Standard_E32d_v5', 'Standard_M128-64ms', 'Standard_M128dms_v2', 'Standard_M16ms', 'Standard_A3', 'Standard_D2ds_v4', 'Standard_A2', 'Standard_E32_v3', 'Standard_E32-8ds_v4', 'Standard_D48s_v4', 'Standard_E20_v5', 'Standard_E16d_v4', 'Standard_DS12-2_v2', 'Standard_E32-16s_v4'],
'brazilsouth': ['Standard_M416s_v2', 'Standard_E8-2as_v4', 'Standard_F4s', 'Standard_E48_v3', 'Standard_D11', 'Standard_D2s_v4', 'Standard_F8s', 'Standard_DS15_v2', 'Standard_D4', 'Standard_D48d_v5', 'Standard_E48d_v5', 'Standard_D16_v5', 'Standard_E16_v4', 'Standard_A5', 'Standard_M64', 'Standard_D96_v5', 'Standard_E20s_v4', 'Standard_DS3', 'Standard_A3', 'Standard_D48ds_v4', 'Standard_E4-2ds_v4', 'Standard_DS13-2_v2', 'Standard_E2as_v4', 'Standard_E64as_v4', 'Standard_D5_v2', 'Standard_D16s_v5', 'Standard_D4_v2', 'Standard_E16_v5', 'Standard_E32s_v3', 'Standard_D8_v5', 'Standard_E64a_v4', 'Standard_DS2', 'Standard_E8_v5', 'Standard_E16-4s_v4', 'Standard_E48d_v4', 'Standard_M64m', 'Standard_F4s_v2', 'Standard_D32-8s_v3', 'Standard_D2_v3', 'Standard_E64is_v3', 'Standard_D2a_v4', 'Standard_D2', 'Standard_A8_v2', 'Standard_D32_v4', 'Standard_E20_v3', 'Standard_D96as_v4', 'Standard_M128-32ms', 'Standard_E16-8as_v4', 'Standard_DS13_v2', 'Standard_E8d_v4', 'Standard_F8s_v2', 'Standard_D16s_v3', 'Standard_E64s_v3', 'Standard_E8s_v3', 'Standard_E64_v3', 'Standard_D4ds_v5', 'Standard_M8ms', 'Standard_D2_v4', 'Standard_DS13-4_v2', 'Standard_F16', 'Standard_D8d_v4', 'Standard_D8s_v4', 'Standard_E8a_v4', 'Standard_E32-16ds_v4', 'Standard_E48s_v4', 'Standard_E64d_v5', 'Standard_D8_v4', 'Standard_A2', 'Standard_M128-64ms', 'Standard_E48ds_v4', 'Standard_E16-4ds_v4', 'Standard_D14', 'Standard_E32d_v5', 'Standard_M208-52s_v2', 'Standard_E8-2s_v3', 'Standard_F72s_v2', 'Standard_E48s_v3', 'Standard_E2_v3', 'Standard_D1_v2', 'Standard_D8ds_v5', 'Standard_E16-8ds_v4', 'Standard_E2d_v5', 'Standard_D16ds_v5', 'Standard_D48_v4', 'Standard_M128s_v2', 'Standard_E64d_v4', 'Standard_E8_v4', 'Standard_D32_v5', 'Standard_E4d_v4', 'Standard_D15i_v2', 'Standard_F1s', 'Standard_NV12s_v3', 'Standard_F2', 'Standard_A1', 'Standard_M416-208s_v2', 'Standard_E8as_v4', 'Standard_D2_v5', 'Standard_E64_v5', 'Standard_E16d_v5', 'Standard_D2ds_v5', 'Standard_F48s_v2', 'Standard_D48s_v4', 'Standard_M16-4ms', 'Standard_E64s_v4', 'Standard_D64s_v3', 'Standard_E80is_v4', 'Standard_D64s_v5', 'Standard_D32s_v4', 'Standard_DS12_v2', 'Standard_E96-24as_v4', 'Standard_M416ms_v2', 'Standard_A0', 'Standard_D32d_v4', 'Standard_M64dms_v2', 'Standard_E20_v4', 'Standard_E16-4as_v4', 'Standard_D32as_v4', 'Standard_E20d_v4', 'Standard_E32-8s_v4', 'Standard_E64-16as_v4', 'Standard_E4_v5', 'Standard_E8-4as_v4', '', 'Standard_E64_v4', 'Standard_D48a_v4', 'Standard_D8a_v4', 'Standard_D4as_v4', 'Standard_D16d_v4', 'Standard_F16s', 'Standard_D64s_v4', 'Standard_E2_v4', 'Standard_M416-104s_v2', 'Standard_E20a_v4', 'Standard_DS13', 'Basic_A4', 'Standard_E16a_v4', 'Standard_D2d_v5', 'Standard_E4_v3', 'Standard_DS2_v2', 'Standard_E8-4ds_v4', 'Standard_DS12-2_v2', 'Standard_E20ds_v4', 'Standard_F32s_v2', 'Standard_M128ms_v2', 'Standard_M16ms', 'Standard_D3_v2', 'Standard_D2as_v4', 'Standard_DS12', 'Standard_D8s_v3', 'Standard_E8d_v5', 'Standard_D64as_v4', 'Standard_M32ls', 'Standard_D12', 'Standard_DS3_v2', 'Standard_D32d_v5', 'Standard_D4a_v4', 'Standard_DS15i_v2', 'Standard_E96as_v4', 'Standard_D4_v3', 'Standard_A2m_v2', 'Standard_E2a_v4', 'Standard_D15_v2', 'Standard_M32ms_v2', 'Standard_E32-16s_v4', 'Standard_E16d_v4', 'Standard_M32dms_v2', 'Standard_E96-48as_v4', 'Standard_D32-16s_v3', 'Standard_E4as_v4', 'Standard_M16-8ms', 'Standard_A4', 'Standard_D4s_v4', 'Standard_A6', 'Standard_M8-2ms', 'Standard_D8as_v4', 'Standard_M32-8ms', 'Standard_E4-2as_v4', 'Standard_E32s_v4', 'Standard_E64-32as_v4', 'Standard_E4ds_v4', 'Standard_D2s_v3', 'Standard_E2s_v3', 'Standard_D96a_v4', 'Standard_D32ds_v4', 'Standard_E16ds_v4', 'Standard_A4m_v2', 'Standard_M32ts', 'Standard_D64d_v4', 'Standard_D8_v3', 'Standard_D96s_v5', 'Standard_A1_v2', 'Standard_M416-104ms_v2', 'Standard_D96ds_v5', 'Standard_D8s_v5', 'Standard_F64s_v2', 'Standard_E8s_v4', 'Standard_A7', 'Standard_D4s_v3', 'Standard_D4d_v5', 'Standard_D4s_v5', 'Basic_A2', 'Standard_E32-8as_v4', 'Standard_E16-8s_v4', 'Standard_E96_v5', 'Standard_E32-16s_v3', 'Standard_E64-16ds_v4', 'Standard_E32-8s_v3', 'Standard_E32_v4', 'Standard_E32d_v4', 'Standard_E32_v5', 'Standard_D64-32s_v3', 'Standard_E32as_v4', 'Standard_D8d_v5', 'Standard_E4a_v4', 'Standard_DS14_v2', 'Standard_D16s_v4', 'Standard_D64-16s_v3', 'Standard_E64i_v3', 'Standard_E2ds_v4', 'Standard_D16ds_v4', 'Standard_E20_v5', 'Standard_DS11', 'Standard_E8-4s_v3', 'Standard_M128s', 'Standard_M208-52ms_v2', 'Standard_D64a_v4', 'Standard_E8ds_v4', 'Standard_E48as_v4', 'Standard_M128m', 'Standard_D64_v3', 'Standard_M208s_v2', 'Standard_D14_v2', 'Standard_E20as_v4', 'Standard_D2s_v5', 'Standard_M64ms', 'Standard_M416-208ms_v2', 'Standard_D11_v2', 'Standard_D4_v5', 'Standard_D32ds_v5', 'Standard_M208-104s_v2', 'Standard_F4', 'Standard_DS12-1_v2', 'Standard_E16as_v4', 'Standard_F2s_v2', 'Standard_E32a_v4', 'Standard_E64-32ds_v4', 'Standard_D32s_v5', 'Standard_E32ds_v4', 'Standard_D48as_v4', 'Standard_E16s_v4', 'Standard_M64-16ms', 'Standard_D16_v3', 'Standard_D48_v3', 'Standard_E8-4s_v4', 'Standard_M64s', 'Standard_E64ds_v4', 'Standard_M16s', 'Standard_M64ls', 'Standard_M32-16ms', 'Standard_M192ids_v2', 'Basic_A1', 'Standard_D48s_v5', 'Standard_D64ds_v5', 'Standard_DS11-1_v2', 'Standard_F2s', 'Standard_E96a_v4', 'Standard_F1', 'Standard_D2ds_v4', 'Standard_D3', 'Standard_E8-2s_v4', 'Standard_M64ds_v2', 'Standard_DS4_v2', 'Standard_F8', 'Standard_M64ms_v2', 'Standard_D96d_v5', 'Standard_M192ims_v2', 'Standard_E8_v3', 'Standard_D16as_v4', 'Standard_D32_v3', 'Standard_DS14-4_v2', 'Standard_M128ds_v2', 'Standard_M64s_v2', 'Standard_E64-32s_v3', 'Standard_E16-4s_v3', 'Standard_E2d_v4', 'Standard_E4-2s_v4', 'Standard_M192is_v2', 'Standard_E16-8s_v3', 'Standard_M208-104ms_v2', 'Standard_E48_v4', 'Standard_E2_v5', 'Standard_E64-16s_v3', 'Standard_D4d_v4', 'Standard_M8-4ms', 'Standard_D16_v4', 'Standard_M32ms', 'Standard_D2d_v4', 'Standard_E32-8ds_v4', 'Standard_E96d_v5', 'Standard_E8-2ds_v4', 'Standard_E64-16s_v4', 'Standard_D13', 'Standard_DS11_v2', 'Standard_D48d_v4', 'Standard_E32_v3', 'Standard_E20s_v3', 'Standard_DS5_v2', 'Standard_D48s_v3', 'Standard_E20d_v5', 'Standard_A8m_v2', 'Standard_E16s_v3', 'Standard_D64_v4', 'Standard_E48a_v4', 'Standard_D48ds_v5', 'Standard_DS14-8_v2', 'Standard_D12_v2', 'Standard_A2_v2', 'Standard_DS1', 'Standard_M32s', 'Standard_NV48s_v3', 'Standard_E4-2s_v3', 'Standard_E4s_v4', 'Standard_M192idms_v2', 'Standard_D13_v2', 'Standard_D64d_v5', 'Standard_F16s_v2', 'Standard_D16a_v4', 'Standard_E48_v5', 'Standard_M128dms_v2', 'Standard_M208ms_v2', 'Standard_DS1_v2', 'Standard_E16_v3', 'Standard_E80ids_v4', 'Standard_D4_v4', 'Standard_D1', 'Standard_D2_v2', 'Standard_M64-32ms', 'Standard_D16d_v5', 'Standard_A4_v2', 'Standard_E4_v4', 'Standard_D64_v5', 'Standard_D64ds_v4', 'Standard_D48_v5', 'Basic_A0', 'Standard_DS14', 'Standard_E4d_v5', 'Standard_E64-32s_v4', 'Standard_M416is_v2', 'Standard_NV24s_v3', 'Standard_M128ms', 'Standard_D32a_v4', 'Basic_A3', 'Standard_D8ds_v4', 'Standard_E4s_v3', 'Standard_E32-16as_v4', 'Standard_DS4', 'Standard_E2s_v4', 'Standard_M128', 'Standard_D4ds_v4', 'Standard_D32s_v3'],
'australiasoutheast': ['Standard_F16', '', 'Standard_M208s_v2', 'Standard_D64d_v5', 'Standard_E20s_v4', 'Standard_E8_v4', 'Standard_DS11_v2', 'Standard_E4d_v4', 'Standard_DS11-1_v2', 'Standard_D14', 'Standard_D32-8s_v3', 'Standard_D5_v2', 'Standard_E32_v4', 'Standard_D48ds_v5', 'Standard_E32s_v4', 'Standard_E96_v5', 'Standard_D16s_v3', 'Standard_M416-104s_v2', 'Standard_DS12-1_v2', 'Standard_DS3_v2', 'Standard_E20d_v4', 'Standard_D8ds_v5', 'Standard_E16_v4', 'Standard_D2_v3', 'Standard_E20_v5', 'Standard_D32s_v3', 'Standard_DS14-4_v2', 'Basic_A4', 'Standard_DS2_v2', 'Standard_D4_v3', 'Standard_A2', 'Standard_D32ds_v4', 'Standard_E64-16ds_v4', 'Standard_D16d_v4', 'Standard_D3_v2', 'Standard_DS4_v2', 'Standard_E48_v3', 'Standard_D32_v4', 'Standard_E8-4s_v4', 'Standard_A2_v2', 'Standard_A8_v2', 'Standard_D32_v5', 'Standard_E20_v4', 'Standard_D11_v2', 'Standard_DS4', 'Standard_M208-104ms_v2', 'Standard_F2', 'Standard_E20_v3', 'Standard_D32d_v5', 'Standard_A4', 'Standard_D48d_v4', 'Standard_A6', 'Standard_D2', 'Standard_DS13_v2', 'Standard_E16d_v5', 'Standard_M128m', 'Standard_A1_v2', 'Standard_D16ds_v4', 'Standard_M416-104ms_v2', 'Standard_E64_v4', 'Standard_DS13', 'Standard_E8-4s_v3', 'Standard_D16ds_v5', 'Standard_D2s_v5', 'Standard_F8s_v2', 'Standard_D64s_v3', 'Standard_E16-4ds_v4', 'Standard_M416-208s_v2', 'Standard_D12', 'Standard_F16s_v2', 'Standard_F1s', 'Standard_DC4s_v2', 'Standard_E64is_v3', 'Standard_E96d_v5', 'Standard_E32ds_v4', 'Standard_D1_v2', 'Standard_M16s', 'Standard_M32ms', 'Standard_M8-4ms', 'Standard_M8ms', 'Standard_M208-52ms_v2', 'Standard_E8s_v3', 'Standard_A4m_v2', 'Standard_E8-2ds_v4', 'Standard_D64-16s_v3', 'Standard_D16_v3', 'Standard_M16-4ms', 'Standard_M416is_v2', 'Standard_F4', 'Standard_F72s_v2', 'Standard_F4s_v2', 'Standard_D48_v4', 'Standard_DS1', 'Basic_A3', 'Standard_E8-2s_v4', 'Standard_M208-52s_v2', 'Standard_D4d_v5', 'Standard_E32s_v3', 'Standard_D15i_v2', 'Standard_D4ds_v5', 'Standard_E80is_v4', 'Standard_A3', 'Standard_E64s_v3', 'Standard_E48d_v5', 'Standard_E4ds_v4', 'Standard_D48d_v5', 'Standard_E64i_v3', 'Standard_F64s_v2', 'Standard_D15_v2', 'Standard_M128-32ms', 'Standard_E4_v3', 'Standard_D4_v5', 'Standard_D8d_v4', 'Standard_M32s', 'Standard_F16s', 'Standard_D2s_v4', 'Standard_D48_v5', 'Standard_D8s_v4', 'Standard_DS13-2_v2', 'Standard_D13', 'Standard_D64_v5', 'Standard_D4ds_v4', 'Standard_D12_v2', 'Standard_E8_v3', 'Standard_M128', 'Standard_E8s_v4', 'Standard_D16_v4', 'Standard_E2s_v3', 'Standard_E2_v3', 'Standard_M32-8ms', 'Standard_E32-8s_v3', 'Standard_D32s_v4', 'Standard_D64s_v4', 'Standard_E4d_v5', 'Standard_D64-32s_v3', 'Standard_D48s_v3', 'Standard_M16-8ms', 'Standard_E16-8ds_v4', 'Standard_E48_v5', 'Standard_F8s', 'Standard_D8s_v3', 'Standard_DS14_v2', 'Standard_DS13-4_v2', 'Standard_D64ds_v5', 'Standard_DC8_v2', 'Standard_E4_v4', 'Standard_D64ds_v4', 'Standard_D48s_v5', 'Standard_M416ms_v2', 'Standard_E64s_v4', 'Standard_D64s_v5', 'Standard_E32-16s_v3', 'Standard_E64_v5', 'Standard_M128-64ms', 'Standard_E64d_v4', 'Standard_F1', 'Standard_F2s_v2', 'Standard_D2ds_v4', 'Standard_D8_v4', 'Standard_DS11', 'Basic_A1', 'Standard_E20d_v5', 'Standard_M64s', 'Standard_E48ds_v4', 'Standard_D4_v2', 'Standard_D4s_v4', 'Standard_D32d_v4', 'Standard_E16ds_v4', 'Standard_E16d_v4', 'Standard_E32-8ds_v4', 'Standard_D48ds_v4', 'Standard_DS12_v2', 'Standard_E64-16s_v3', 'Standard_F32s_v2', 'Standard_E20s_v3', 'Standard_E32-8s_v4', 'Standard_E16-8s_v4', 'Standard_M64ls', 'Standard_D96d_v5', 'Standard_D11', 'Standard_M64-32ms', 'Standard_DS14', 'Standard_E64-32s_v4', 'Standard_D8_v5', 'Standard_E16s_v3', 'Standard_A8m_v2', 'Standard_E16_v3', 'Standard_E4-2ds_v4', 'Standard_M64ms', 'Standard_E48s_v3', 'Standard_F8', 'Standard_D8d_v5', 'Standard_D2_v5', 'Standard_DS3', 'Standard_E2_v5', 'Standard_E64d_v5', 'Standard_A0', 'Standard_D96_v5', 'Standard_M8-2ms', 'Standard_E4-2s_v4', 'Standard_D2_v2', 'Standard_M64m', 'Standard_D14_v2', 'Standard_E8d_v4', 'Standard_D16d_v5', 'Standard_M32-16ms', 'Standard_D8s_v5', 'Standard_D3', 'Standard_DS1_v2', 'Standard_E32d_v4', 'Standard_D8ds_v4', 'Standard_E32-16s_v4', 'Standard_DS5_v2', 'Standard_D2d_v4', 'Standard_D4s_v5', 'Standard_D16s_v4', 'Standard_E4s_v3', 'Standard_E16-8s_v3', 'Standard_D64d_v4', 'Standard_E8-2s_v3', 'Standard_E16-4s_v4', 'Standard_A1', 'Standard_D1', 'Standard_DS2', 'Standard_D96s_v5', 'Standard_E48_v4', 'Standard_F4s', 'Standard_A2m_v2', 'Standard_E48s_v4', 'Standard_D2s_v3', 'Standard_D16_v5', 'Standard_A7', 'Standard_M208-104s_v2', 'Standard_D64_v3', 'Standard_M32ls', 'Standard_E8d_v5', 'Standard_E2s_v4', 'Standard_M32ts', 'Standard_E4s_v4', 'Standard_D96ds_v5', 'Standard_D32-16s_v3', 'Standard_M64-16ms', 'Standard_D16s_v5', 'Standard_E2_v4', 'Standard_E16_v5', 'Standard_D4s_v3', 'Standard_M208ms_v2', 'Standard_E32d_v5', 'Standard_DC1s_v2', 'Standard_D13_v2', 'Standard_F48s_v2', 'Standard_D2ds_v5', 'Standard_F2s', 'Standard_E16s_v4', 'Standard_D2d_v5', 'Standard_E64_v3', 'Standard_M128s', 'Standard_E4_v5', 'Standard_E64-16s_v4', 'Standard_D48_v3', 'Standard_M16ms', 'Standard_D32ds_v5', 'Standard_E32_v3', 'Standard_E8ds_v4', 'Standard_E32-16ds_v4', 'Standard_D64_v4', 'Standard_E32_v5', 'Standard_D32s_v5', 'Standard_D4d_v4', 'Standard_DS12', 'Standard_DS14-8_v2', 'Standard_M128ms', 'Standard_E2d_v5', 'Standard_D2_v4', 'Standard_E20ds_v4', 'Standard_E64-32s_v3', 'Basic_A2', 'Standard_D8_v3', 'Standard_E2d_v4', 'Standard_DC2s_v2', 'Standard_E80ids_v4', 'Standard_D4_v4', 'Standard_DS12-2_v2', 'Standard_M416s_v2', 'Standard_D48s_v4', 'Standard_E4-2s_v3', 'Standard_D4', 'Standard_E48d_v4', 'Basic_A0', 'Standard_A5', 'Standard_DS15i_v2', 'Standard_E8_v5', 'Standard_E64-32ds_v4', 'Standard_E2ds_v4', 'Standard_E16-4s_v3', 'Standard_A4_v2', 'Standard_E64ds_v4', 'Standard_D32_v3', 'Standard_M64', 'Standard_M416-208ms_v2', 'Standard_DS15_v2', 'Standard_E8-4ds_v4'],
'australiaeast': ['Standard_E64-16s_v4', 'Standard_E8ds_v4', 'Standard_E16d_v4', 'Standard_L8s', 'Standard_G5', 'Standard_M16-8ms', 'Standard_D64s_v3', 'Standard_D16_v4', 'Standard_M64ms', 'Standard_E4_v5', 'Standard_D3', 'Standard_D4_v3', 'Standard_D8_v4', 'Standard_E16_v3', 'Standard_D48d_v4', 'Standard_E16_v4', 'Standard_F8s_v2', 'Standard_L32s', 'Standard_E48_v3', 'Standard_A4', 'Standard_E64-16as_v4', 'Standard_NC8as_T4_v3', 'Standard_E64a_v4', 'Standard_M128-64ms', 'Standard_DS14_v2', 'Standard_E16-4ds_v4', 'Standard_M192idms_v2', 'Standard_E16-8s_v4', 'Standard_E8-4ds_v4', 'Standard_F8s', 'Standard_D4_v5', 'Standard_E16as_v4', 'Standard_L88is_v2', 'Standard_F2', 'Standard_F16', 'Standard_D2_v2', 'Standard_F4', 'Standard_E48_v4', 'Standard_E32-16as_v4', 'Standard_E8-2s_v4', 'Standard_E2as_v4', 'Standard_GS3', 'Standard_D11_v2', 'Standard_D32s_v4', 'Standard_D2ds_v5', 'Standard_NC24rs_v3', 'Standard_E4-2ds_v4', 'Standard_NC12', 'Standard_D2', 'Standard_F48s_v2', 'Standard_L96s_v2', 'Standard_D16ds_v5', 'Standard_F72s_v2', 'Standard_E8_v4', 'Standard_E64-32s_v3', 'Standard_E64d_v5', 'Standard_D13', 'Standard_D14_v2', 'Standard_DS15_v2', 'Standard_E96-24as_v4', 'Standard_M128-32ms', 'Standard_D48s_v3', 'Standard_A6', 'Standard_D4a_v4', 'Standard_E48as_v4', 'Standard_E8a_v4', 'Standard_NV4as_v4', 'Standard_E8_v3', 'Standard_M128ms', 'Standard_H8m', 'Standard_DS14', 'Standard_M32ts', 'Standard_GS4', 'Standard_F1s', 'Standard_E32d_v5', 'Standard_E8d_v4', 'Standard_A8_v2', 'Standard_M128m', 'Standard_G2', 'Standard_E32-16ds_v4', 'Standard_M192ids_v2', 'Standard_E4a_v4', 'Standard_D32_v4', 'Standard_E32_v4', 'Standard_D13_v2', 'Standard_E8-4as_v4', 'Standard_D8as_v4', 'Standard_M32-16ms', 'Standard_D16as_v4', 'Standard_NC12s_v3', 'Standard_D16_v3', 'Standard_E48a_v4', 'Standard_E20ds_v4', 'Standard_D4ds_v5', 'Standard_F64s_v2', 'Standard_E8-2ds_v4', 'Standard_DS12-1_v2', 'Standard_E32_v3', 'Standard_E2_v3', 'Standard_M64-16ms', 'Standard_D16_v5', 'Standard_M128', 'Standard_D64-32s_v3', 'Standard_GS4-4', 'Standard_F32s_v2', 'Standard_DC4s_v2', 'Standard_E4_v3', 'Standard_NV16as_v4', 'Standard_NC4as_T4_v3', 'Standard_D8_v3', 'Standard_F2s_v2', 'Standard_M64ms_v2', 'Standard_E4d_v4', 'Standard_M128ds_v2', 'Standard_D2d_v5', 'Standard_DS4', 'Standard_E32-8s_v3', 'Standard_NV12s_v3', 'Standard_M8-4ms', 'Standard_E48d_v5', 'Standard_NC24s_v3', 'Standard_D2a_v4', 'Standard_DS15i_v2', 'Standard_GS4-8', 'Standard_M208-52ms_v2', 'Standard_A0', 'Standard_DS2_v2', 'Standard_H16', 'Standard_D8d_v4', 'Basic_A2', 'Standard_E64s_v3', 'Standard_DS14-8_v2', 'Standard_DS13_v2', 'Standard_E2d_v5', 'Standard_D96ds_v5', 'Standard_DS14-4_v2', 'Standard_E8s_v4', 'Standard_DS2', 'Standard_E32s_v4', 'Standard_D64-16s_v3', 'Standard_HB120rs_v2', 'Standard_E48d_v4', 'Standard_D8s_v5', 'Standard_E2s_v3', 'Standard_D48_v3', 'Standard_E32-8ds_v4', 'Standard_M64ds_v2', 'Standard_E20d_v5', 'Standard_D16ds_v4', 'Standard_D16s_v4', 'Standard_D64d_v4', 'Standard_D48as_v4', 'Standard_E64d_v4', 'Standard_D32a_v4', 'Standard_D96d_v5', 'Standard_E8_v5', 'Standard_E2s_v4', 'Standard_DC8_v2', 'Standard_D2_v3', 'Standard_DS5_v2', 'Standard_DC1s_v2', 'Standard_E8-4s_v3', 'Standard_M416ms_v2', 'Standard_D2s_v5', 'Standard_D2d_v4', 'Standard_DS3', 'Standard_F1', '', 'Standard_E4-2as_v4', 'Standard_E4-2s_v4', 'Standard_L64s_v2', 'Standard_A5', 'Standard_DS12', 'Standard_L16s_v2', 'Standard_F4s', 'Standard_D32s_v5', 'Standard_A3', 'Standard_D4_v2', 'Standard_DS3_v2', 'Standard_L48s_v2', 'Standard_F16s', 'Standard_DS13-4_v2', 'Standard_M192ims_v2', 'Standard_L32s_v2', 'Standard_D64s_v5', 'Standard_A2', 'Standard_D4s_v5', 'Standard_DS12_v2', 'Standard_E48s_v4', 'Standard_E4as_v4', 'Standard_NC64as_T4_v3', 'Standard_D14', 'Standard_D64a_v4', 'Standard_GS1', 'Standard_E16-8ds_v4', 'Standard_E20a_v4', 'Standard_E64_v4', 'Standard_A1_v2', 'Standard_E80is_v4', 'Standard_E48_v5', 'Standard_D32d_v5', 'Standard_D8_v5', 'Standard_E4d_v5', 'Standard_NV24s_v3', 'Standard_L8s_v2', 'Standard_E64_v3', 'Standard_NC24r', 'Standard_M416-104s_v2', 'Standard_D48d_v5', 'Standard_M416-104ms_v2', 'Standard_M16ms', 'Standard_E16a_v4', 'Standard_E2d_v4', 'Standard_M64s', 'Standard_DS12-2_v2', 'Standard_E8d_v5', 'Standard_E64i_v3', 'Standard_D48ds_v4', 'Standard_M32s', 'Standard_E4-2s_v3', 'Standard_D2s_v4', 'Standard_M128s_v2', 'Standard_E4_v4', 'Standard_E96as_v4', 'Standard_E20_v3', 'Standard_M32ms_v2', 'Standard_NV6', 'Standard_D8d_v5', 'Standard_M128ms_v2', 'Standard_D4s_v3', 'Standard_M32ls', 'Standard_M64m', 'Standard_M8ms', 'Standard_D16s_v3', 'Standard_D3_v2', 'Standard_D2s_v3', 'Standard_M64s_v2', 'Standard_M32-8ms', 'Standard_D96_v5', 'Standard_GS2', 'Standard_GS5', 'Standard_DS1', 'Standard_M64dms_v2', 'Standard_E20s_v4', 'Standard_E32-8s_v4', 'Standard_DS11', 'Standard_D32-8s_v3', 'Basic_A4', 'Standard_D48ds_v5', 'Standard_NC24', 'Standard_D4d_v5', 'Standard_E16-4s_v3', 'Standard_E64_v5', 'Standard_E32-16s_v3', 'Standard_D12', 'Standard_H8', 'Standard_D16d_v5', 'Standard_A4m_v2', 'Standard_M208-104ms_v2', 'Standard_NV8as_v4', 'Standard_D48s_v5', 'Standard_E4ds_v4', 'Standard_E32d_v4', 'Standard_E64ds_v4', 'Standard_D1_v2', 'Standard_E16ds_v4', 'Standard_E2_v4', 'Standard_M416-208ms_v2', 'Standard_D32s_v3', 'Standard_E96a_v4', 'Standard_L16s', 'Standard_D15_v2', 'Standard_D15i_v2', 'Standard_M128s', 'Standard_DS4_v2', 'Standard_D64as_v4', 'Standard_D48a_v4', 'Standard_D32ds_v5', 'Standard_E32-8as_v4', 'Standard_GS5-8', 'Basic_A1', 'Standard_E64-16s_v3', 'Standard_DS11_v2', 'Standard_E8s_v3', 'Standard_NC6', 'Standard_E48ds_v4', 'Standard_D8s_v3', 'Standard_NV48s_v3', 'Standard_M208s_v2', 'Standard_A8m_v2', 'Standard_D96s_v5', 'Standard_E20as_v4', 'Standard_E32s_v3', 'Standard_E16-4s_v4', 'Standard_M192is_v2', 'Standard_E20d_v4', 'Standard_M416-208s_v2', 'Standard_D32as_v4', 'Standard_D4ds_v4', 'Standard_DS13', 'Standard_E64s_v4', 'Standard_E2ds_v4', 'Standard_A2m_v2', 'Standard_E48s_v3', 'Standard_D11', 'Standard_E20_v4', 'Standard_L4s', 'Standard_D16d_v4', 'Standard_D96as_v4', 'Standard_F2s', 'Standard_F8', 'Standard_DC2s_v2', 'Standard_D4', 'Standard_M208-52s_v2', 'Standard_E32ds_v4', 'Basic_A3', 'Standard_D2as_v4', 'Standard_NV24', 'Standard_DS11-1_v2', 'Standard_M64', 'Standard_E80ids_v4', 'Standard_A4_v2', 'Standard_D16a_v4', 'Standard_D64s_v4', 'Standard_M8-2ms', 'Standard_D48_v4', 'Standard_E4s_v3', 'Standard_H16m', 'Standard_A2_v2', 'Standard_D1', 'Standard_D64d_v5', 'Standard_E32a_v4', 'Standard_E64-32ds_v4', 'Standard_G4', 'Standard_M416is_v2', 'Standard_H16r', 'Standard_DS13-2_v2', 'Standard_E20s_v3', 'Standard_D64_v5', 'Standard_E4s_v4', 'Standard_M128dms_v2', 'Standard_E2_v5', 'Standard_A7', 'Standard_D32_v3', 'Standard_NV32as_v4', 'Standard_M16s', 'Basic_A0', 'Standard_D8ds_v4', 'Standard_M32ms', 'Standard_A1', 'Standard_E64-32as_v4', 'Standard_M416s_v2', 'Standard_L80s_v2', 'Standard_E2a_v4', 'Standard_M32dms_v2', 'Standard_E96d_v5', 'Standard_NC16as_T4_v3', 'Standard_D64ds_v4', 'Standard_D4_v4', 'Standard_D96a_v4', 'Standard_E8as_v4', 'Standard_GS5-16', 'Standard_E16-4as_v4', 'Standard_E64as_v4', 'Standard_M16-4ms', 'Standard_D48_v5', 'Standard_DS1_v2', 'Standard_D64ds_v5', 'Standard_D32_v5', 'Standard_E32_v5', 'Standard_E32as_v4', 'Standard_D2_v5', 'Standard_E8-2s_v3', 'Standard_F16s_v2', 'Standard_NC6s_v3', 'Standard_D16s_v5', 'Standard_E8-4s_v4', 'Standard_D2ds_v4', 'Standard_D8s_v4', 'Standard_NV12', 'Standard_D32ds_v4', 'Standard_E64is_v3', 'Standard_E8-2as_v4', 'Standard_E64-32s_v4', 'Standard_E16s_v3', 'Standard_D64_v4', 'Standard_M64ls', 'Standard_D4s_v4', 'Standard_E16s_v4', 'Standard_D4d_v4', 'Standard_D12_v2', 'Standard_D2_v4', 'Standard_D8a_v4', 'Standard_D32-16s_v3', 'Standard_E32-16s_v4', 'Standard_H16mr', 'Standard_F4s_v2', 'Standard_M208ms_v2', 'Standard_E16-8s_v3', 'Standard_D4as_v4', 'Standard_G1', 'Standard_D5_v2', 'Standard_E64-16ds_v4', 'Standard_E16_v5', 'Standard_G3', 'Standard_M208-104s_v2', 'Standard_M64-32ms', 'Standard_D8ds_v5', 'Standard_D48s_v4', 'Standard_D64_v3', 'Standard_E16d_v5', 'Standard_E16-8as_v4', 'Standard_D32d_v4', 'Standard_E96-48as_v4', 'Standard_E20_v5', 'Standard_E96_v5'],
'westindia': ['Standard_DS4_v2', 'Standard_D3', 'Standard_D8d_v4', 'Standard_DS14-8_v2', 'Standard_D2_v3', 'Standard_E16d_v4', 'Standard_E64-16s_v3', 'Standard_D16d_v5', 'Standard_D2ds_v5', 'Standard_A4_v2', 'Standard_D48ds_v5', 'Basic_A1', 'Standard_D15_v2', 'Standard_F4s', 'Standard_E32_v4', 'Standard_E32ds_v4', 'Standard_D11', 'Standard_A1_v2', 'Standard_E8_v3', 'Standard_E64d_v4', 'Standard_D2', 'Standard_E20d_v5', 'Standard_D48_v5', 'Standard_D8ds_v5', 'Standard_D13_v2', 'Standard_D8d_v5', 'Standard_E32d_v5', 'Standard_E2s_v3', 'Standard_D48ds_v4', 'Basic_A3', 'Standard_D64s_v5', 'Standard_D4_v4', 'Standard_D32_v4', 'Standard_F4', 'Standard_E4s_v4', 'Standard_E8s_v4', 'Standard_D4s_v4', 'Standard_D2s_v4', 'Standard_E8d_v5', 'Standard_D2d_v5', 'Standard_D4d_v4', 'Standard_D96d_v5', 'Standard_F2', 'Standard_D16s_v3', 'Standard_A4m_v2', 'Standard_E96_v5', 'Standard_D16_v3', 'Standard_D4d_v5', 'Standard_E64-32ds_v4', 'Standard_F48s_v2', 'Standard_D4s_v3', 'Standard_E32-8ds_v4', 'Standard_D48s_v3', 'Standard_A7', 'Standard_D4', 'Standard_E16s_v4', 'Standard_E16_v5', 'Standard_F4s_v2', 'Standard_A6', 'Standard_D8s_v3', 'Standard_D64_v5', 'Standard_A2m_v2', 'Standard_D48_v3', 'Standard_E32-16ds_v4', 'Standard_D32_v3', 'Standard_D2s_v5', 'Standard_E64is_v3', 'Standard_E16-8s_v4', 'Standard_D96s_v5', 'Standard_E64d_v5', 'Standard_E80ids_v4', 'Standard_D64s_v4', 'Standard_DS14-4_v2', 'Standard_D2_v4', 'Standard_D64d_v4', 'Standard_E4-2s_v3', 'Standard_E16-8s_v3', 'Standard_E4-2s_v4', 'Standard_E2s_v4', 'Standard_D48_v4', 'Standard_D3_v2', 'Standard_DS15_v2', 'Standard_A8m_v2', 'Standard_E2_v4', 'Standard_DS13-4_v2', 'Standard_DS13_v2', 'Standard_DS12_v2', 'Standard_D64ds_v4', 'Standard_D4_v2', 'Standard_F72s_v2', 'Standard_F1', 'Standard_E48s_v3', 'Standard_E32s_v3', 'Standard_E4d_v4', 'Standard_E8ds_v4', 'Standard_F2s_v2', 'Standard_D12', 'Standard_D2_v2', 'Standard_E64-32s_v4', 'Standard_E20_v5', 'Standard_D48d_v5', 'Standard_D32-8s_v3', 'Standard_D8ds_v4', 'Standard_E8-2ds_v4', 'Standard_E4ds_v4', 'Standard_A1', 'Standard_E64ds_v4', 'Standard_D8_v5', 'Standard_F16', 'Standard_D32s_v5', 'Standard_D48d_v4', 'Standard_E48_v5', 'Standard_E2ds_v4', 'Standard_F16s_v2', 'Standard_E32-16s_v4', 'Standard_E8-4s_v3', 'Standard_E8_v5', 'Standard_DS3_v2', 'Standard_E64-32s_v3', 'Standard_E16_v4', 'Standard_D32_v5', 'Standard_E48_v3', 'Standard_DS2', 'Standard_A3', 'Basic_A2', 'Standard_E16-4s_v4', 'Standard_DS4', 'Standard_E32-8s_v3', 'Standard_DS11', 'Standard_D8_v4', 'Standard_D5_v2', 'Standard_D11_v2', 'Standard_E16-4ds_v4', 'Standard_E64-16s_v4', 'Standard_D48s_v5', 'Standard_D64ds_v5', 'Standard_E48d_v4', 'Standard_E32_v3', 'Standard_DS14', 'Standard_E64_v3', 'Standard_DS1_v2', 'Standard_E16-4s_v3', 'Standard_E48_v4', 'Standard_D16ds_v5', 'Standard_E48ds_v4', 'Standard_DS11-1_v2', 'Standard_D8s_v5', 'Standard_D32s_v3', 'Standard_E20_v4', 'Standard_D16d_v4', 'Standard_E2_v3', 'Standard_DS11_v2', '', 'Standard_E64_v5', 'Standard_D8s_v4', 'Standard_E4_v3', 'Standard_D16s_v5', 'Standard_D2_v5', 'Standard_E20_v3', 'Standard_DS1', 'Standard_DS13-2_v2', 'Standard_DS12-1_v2', 'Standard_E2_v5', 'Basic_A4', 'Standard_E4_v5', 'Standard_F32s_v2', 'Standard_DS15i_v2', 'Standard_D2d_v4', 'Standard_E4_v4', 'Standard_E32_v5', 'Standard_E32-8s_v4', 'Standard_E20s_v4', 'Standard_F8', 'Standard_D4_v5', 'Standard_D16_v5', 'Standard_E32d_v4', 'Standard_E16_v3', 'Standard_D64_v3', 'Standard_E8d_v4', 'Standard_D32ds_v5', 'Standard_D15i_v2', 'Standard_DS14_v2', 'Standard_A0', 'Standard_DS12', 'Standard_E32-16s_v3', 'Standard_A4', 'Standard_D16s_v4', 'Standard_E48d_v5', 'Standard_F8s_v2', 'Standard_D32s_v4', 'Standard_DS13', 'Standard_D1', 'Standard_E32s_v4', 'Standard_A5', 'Standard_E8_v4', 'Standard_D2s_v3', 'Standard_F8s', 'Standard_D14_v2', 'Standard_D4ds_v5', 'Standard_E64s_v3', 'Standard_E16s_v3', 'Standard_E80is_v4', 'Standard_E8-4s_v4', 'Standard_F16s', 'Standard_E64s_v4', 'Standard_F1s', 'Standard_D96ds_v5', 'Basic_A0', 'Standard_E8s_v3', 'Standard_E48s_v4', 'Standard_E96d_v5', 'Standard_DS5_v2', 'Standard_D8_v3', 'Standard_E8-2s_v3', 'Standard_E20ds_v4', 'Standard_E2d_v5', 'Standard_F2s', 'Standard_D32d_v4', 'Standard_D48s_v4', 'Standard_D2ds_v4', 'Standard_D13', 'Standard_D64-32s_v3', 'Standard_DS2_v2', 'Standard_E4s_v3', 'Standard_D64s_v3', 'Standard_E4d_v5', 'Standard_D64-16s_v3', 'Standard_E4-2ds_v4', 'Standard_E16-8ds_v4', 'Standard_D32ds_v4', 'Standard_E20d_v4', 'Standard_E16ds_v4', 'Standard_D1_v2', 'Standard_D12_v2', 'Standard_D64_v4', 'Standard_D4s_v5', 'Standard_E8-4ds_v4', 'Standard_D64d_v5', 'Standard_D14', 'Standard_D32d_v5', 'Standard_A2', 'Standard_A2_v2', 'Standard_F64s_v2', 'Standard_D4_v3', 'Standard_E64i_v3', 'Standard_E2d_v4', 'Standard_A8_v2', 'Standard_E20s_v3', 'Standard_E64_v4', 'Standard_D4ds_v4', 'Standard_D32-16s_v3', 'Standard_D96_v5', 'Standard_E16d_v5', 'Standard_D16_v4', 'Standard_D16ds_v4', 'Standard_E8-2s_v4', 'Standard_DS3', 'Standard_DS12-2_v2', 'Standard_E64-16ds_v4'],
'southindia': ['Standard_D14', 'Standard_D5_v2', 'Standard_E32-16s_v4', 'Standard_D64s_v4', 'Standard_D1_v2', 'Standard_A7', 'Standard_DS12-2_v2', 'Standard_D64ds_v5', 'Standard_E20_v3', 'Standard_D48_v5', 'Standard_E4_v4', 'Standard_E32-8s_v4', 'Standard_A0', 'Standard_D48d_v5', 'Standard_DS11', 'Standard_E16-4ds_v4', 'Standard_D48_v4', 'Standard_M128s', 'Standard_E8s_v4', 'Standard_D64-32s_v3', 'Standard_D16ds_v5', 'Standard_F1s', 'Standard_D3', 'Standard_E64-16ds_v4', 'Standard_M128-64ms', 'Standard_E20d_v5', 'Standard_E16_v4', 'Standard_D16d_v5', 'Standard_D8_v5', '', 'Standard_D4s_v5', 'Standard_M416-208s_v2', 'Standard_E20ds_v4', 'Standard_E16d_v5', 'Standard_D4ds_v5', 'Standard_D8ds_v5', 'Standard_DS13-2_v2', 'Standard_D16s_v4', 'Standard_D48d_v4', 'Standard_E20d_v4', 'Standard_D8s_v4', 'Standard_E4-2s_v4', 'Standard_D96s_v5', 'Standard_D64s_v5', 'Standard_E48s_v4', 'Standard_D64-16s_v3', 'Standard_D48s_v4', 'Standard_DS11-1_v2', 'Standard_D4s_v3', 'Standard_D2d_v5', 'Standard_D32_v5', 'Standard_D8d_v4', 'Standard_D2_v5', 'Standard_D2_v3', 'Standard_M208-104s_v2', 'Standard_F32s_v2', 'Standard_E80is_v4', 'Standard_E32_v3', 'Standard_D16ds_v4', 'Standard_E16s_v4', 'Standard_E16-4s_v3', 'Standard_D64_v4', 'Standard_D4_v4', 'Standard_E64-16s_v4', 'Standard_E48_v3', 'Standard_E96d_v5', 'Standard_D32_v3', 'Basic_A2', 'Standard_E64s_v3', 'Standard_E32s_v4', 'Standard_M32s', 'Standard_D8s_v3', 'Standard_E8-2s_v4', 'Standard_M8-4ms', 'Standard_D48_v3', 'Standard_D4_v5', 'Standard_E64_v3', 'Standard_E48d_v5', 'Standard_F8s_v2', 'Standard_E64-32ds_v4', 'Standard_DS3', 'Standard_D32_v4', 'Standard_E16d_v4', 'Standard_E64-32s_v4', 'Standard_D48ds_v5', 'Standard_D12_v2', 'Standard_DS13_v2', 'Standard_D16s_v5', 'Standard_D12', 'Standard_E8-4ds_v4', 'Standard_F72s_v2', 'Standard_D16d_v4', 'Standard_E20_v4', 'Standard_M64', 'Standard_E32_v4', 'Standard_D32-16s_v3', 'Standard_D32ds_v5', 'Standard_D8_v3', 'Standard_E80ids_v4', 'Standard_E2s_v4', 'Standard_E20s_v4', 'Standard_E4-2ds_v4', 'Standard_A4m_v2', 'Standard_E4s_v3', 'Standard_D4ds_v4', 'Standard_E48_v4', 'Standard_E64d_v5', 'Standard_E2s_v3', 'Standard_M416s_v2', 'Standard_D32d_v4', 'Standard_E64d_v4', 'Standard_E8ds_v4', 'Standard_F1', 'Standard_M8-2ms', 'Standard_DS12', 'Standard_E2d_v4', 'Standard_E8-4s_v4', 'Standard_D2_v2', 'Standard_M32ts', 'Standard_D15i_v2', 'Standard_E64i_v3', 'Standard_M208ms_v2', 'Standard_M208-52ms_v2', 'Standard_DS4', 'Standard_M416-104ms_v2', 'Standard_D16_v5', 'Standard_DS5_v2', 'Standard_D8d_v5', 'Standard_D32d_v5', 'Standard_E64s_v4', 'Standard_E32d_v4', 'Standard_F4s_v2', 'Standard_E16-4s_v4', 'Standard_M8ms', 'Standard_F8s', 'Standard_M208s_v2', 'Standard_D48s_v3', 'Standard_D2s_v3', 'Standard_A2m_v2', 'Standard_E8_v3', 'Standard_E64_v5', 'Standard_A3', 'Standard_D32-8s_v3', 'Standard_DS13-4_v2', 'Standard_E96_v5', 'Standard_F16s_v2', 'Standard_D16_v3', 'Standard_E20s_v3', 'Standard_M128ms', 'Standard_E8_v4', 'Standard_DS14', 'Standard_D3_v2', 'Basic_A0', 'Standard_E64is_v3', 'Standard_D11_v2', 'Standard_F2', 'Standard_E32ds_v4', 'Standard_E4ds_v4', 'Standard_D4s_v4', 'Standard_D64d_v5', 'Standard_E32-16ds_v4', 'Standard_E2_v4', 'Standard_E64-32s_v3', 'Standard_A6', 'Standard_D2ds_v4', 'Standard_A8_v2', 'Standard_E2_v3', 'Standard_A4', 'Standard_E48s_v3', 'Standard_F64s_v2', 'Standard_E8d_v5', 'Standard_DS12_v2', 'Standard_E8s_v3', 'Standard_E32-8s_v3', 'Standard_E4d_v5', 'Standard_M64ms', 'Standard_M16-8ms', 'Standard_E8-2s_v3', 'Standard_E4_v3', 'Standard_D32s_v5', 'Standard_D16_v4', 'Standard_E48ds_v4', 'Standard_E32-16s_v3', 'Standard_E2d_v5', 'Basic_A4', 'Standard_E4s_v4', 'Basic_A3', 'Standard_E16-8s_v4', 'Standard_M208-52s_v2', 'Standard_E8_v5', 'Standard_DS1_v2', 'Standard_DS2', 'Standard_D64d_v4', 'Standard_A4_v2', 'Standard_D8s_v5', 'Standard_D4d_v5', 'Standard_D64_v5', 'Standard_D32s_v4', 'Standard_E8d_v4', 'Standard_A1', 'Standard_M32ms', 'Standard_E48_v5', 'Standard_D16s_v3', 'Standard_F2s', 'Standard_F4', 'Standard_DS15_v2', 'Standard_M416is_v2', 'Standard_DS14_v2', 'Standard_M64-16ms', 'Standard_DS1', 'Standard_M64s', 'Standard_A1_v2', 'Standard_DS14-4_v2', 'Standard_M64-32ms', 'Standard_M416ms_v2', 'Standard_D96d_v5', 'Standard_D2', 'Standard_D14_v2', 'Standard_D11', 'Standard_D8_v4', 'Standard_F48s_v2', 'Basic_A1', 'Standard_E2ds_v4', 'Standard_E32_v5', 'Standard_E4_v5', 'Standard_E64_v4', 'Standard_D32ds_v4', 'Standard_D4_v2', 'Standard_F8', 'Standard_A8m_v2', 'Standard_E32-8ds_v4', 'Standard_M16-4ms', 'Standard_E8-4s_v3', 'Standard_D64ds_v4', 'Standard_E16-8s_v3', 'Standard_F16s', 'Standard_D2s_v5', 'Standard_D2d_v4', 'Standard_D2s_v4', 'Standard_M16ms', 'Standard_E20_v5', 'Standard_DS3_v2', 'Standard_D64s_v3', 'Standard_M416-208ms_v2', 'Standard_F2s_v2', 'Standard_E4-2s_v3', 'Standard_D4_v3', 'Standard_DS2_v2', 'Standard_M64ls', 'Standard_M128', 'Standard_D48ds_v4', 'Standard_D4', 'Standard_A2_v2', 'Standard_M64m', 'Standard_M416-104s_v2', 'Standard_A5', 'Standard_E16_v5', 'Standard_M32-8ms', 'Standard_D13', 'Standard_M208-104ms_v2', 'Standard_E2_v5', 'Standard_D2_v4', 'Standard_D96_v5', 'Standard_E16s_v3', 'Standard_D8ds_v4', 'Standard_E4d_v4', 'Standard_M32-16ms', 'Standard_DS14-8_v2', 'Standard_DS11_v2', 'Standard_M32ls', 'Standard_D64_v3', 'Standard_M128m', 'Standard_E32d_v5', 'Standard_A2', 'Standard_D32s_v3', 'Standard_F4s', 'Standard_E32s_v3', 'Standard_D96ds_v5', 'Standard_E16_v3', 'Standard_E16ds_v4', 'Standard_E48d_v4', 'Standard_F16', 'Standard_D15_v2', 'Standard_E64-16s_v3', 'Standard_DS12-1_v2', 'Standard_D13_v2', 'Standard_M128-32ms', 'Standard_M16s', 'Standard_D4d_v4', 'Standard_DS13', 'Standard_D2ds_v5', 'Standard_DS15i_v2', 'Standard_D1', 'Standard_E8-2ds_v4', 'Standard_E16-8ds_v4', 'Standard_DS4_v2', 'Standard_D48s_v5', 'Standard_E64ds_v4'],
'centralindia': ['Standard_E32s_v3', 'Standard_A6', 'Standard_E8d_v4', 'Standard_D64_v4', 'Standard_D4s_v3', 'Standard_D2_v3', 'Standard_D16as_v4', 'Standard_E48_v4', 'Standard_E64a_v4', 'Standard_M128-32ms', 'Standard_D48_v4', 'Standard_D15_v2', 'Basic_A3', 'Standard_D4_v2', 'Standard_D2s_v5', 'Standard_D11_v2', 'Standard_F2', 'Standard_M192ims_v2', 'Standard_E4-2as_v4', 'Standard_M128-64ms', 'Standard_D1_v2', 'Standard_E8_v5', 'Standard_D11', 'Standard_E48s_v4', 'Standard_D4_v4', 'Standard_E4_v5', 'Standard_H16m', 'Standard_E64-32ds_v4', 'Standard_D8_v4', 'Standard_E32_v4', 'Standard_DS5_v2', 'Standard_DS2', 'Standard_M64s', 'Standard_A4', 'Standard_L64s_v2', 'Standard_E32_v5', 'Standard_E20d_v5', 'Standard_E48d_v4', 'Standard_F16', 'Standard_E64d_v5', 'Standard_NV12s_v3', 'Standard_E32as_v4', 'Standard_E32-16as_v4', 'Standard_D64as_v4', 'Standard_E16ds_v4', 'Standard_F8s', 'Standard_E48d_v5', 'Standard_E16_v3', 'Standard_L48s_v2', 'Standard_L8s_v2', 'Standard_A2m_v2', 'Standard_D8ds_v5', 'Standard_E16-4s_v4', 'Standard_E8-4s_v3', 'Standard_F8', 'Standard_E32-16s_v3', 'Standard_D4as_v4', 'Standard_E48as_v4', 'Standard_E16-4as_v4', 'Standard_DS15i_v2', 'Standard_D14_v2', 'Standard_D1', 'Standard_E32-16s_v4', 'Standard_E4_v4', 'Standard_E4as_v4', 'Standard_D4ds_v5', 'Standard_D8d_v4', 'Standard_E8-4as_v4', 'Standard_D8as_v4', 'Standard_DS11_v2', 'Standard_E2d_v5', 'Standard_D8_v3', 'Standard_E16-8as_v4', 'Standard_M192ids_v2', 'Standard_D8d_v5', 'Standard_D2s_v3', 'Standard_D64a_v4', 'Standard_M416ms_v2', 'Standard_E32-8as_v4', 'Standard_E16a_v4', 'Standard_M16-4ms', 'Standard_E8d_v5', 'Standard_D5_v2', 'Standard_M192idms_v2', 'Standard_F1s', 'Standard_D2', 'Standard_D48ds_v4', 'Standard_E64d_v4', 'Standard_E64-32s_v3', 'Standard_E32-8ds_v4', 'Standard_E8_v3', 'Standard_DS13_v2', 'Basic_A4', 'Standard_E2d_v4', 'Standard_E8-4s_v4', 'Standard_E8ds_v4', 'Standard_D13', 'Standard_D8a_v4', 'Standard_E2ds_v4', 'Standard_M128ms', 'Standard_E48s_v3', 'Standard_DS15_v2', 'Standard_E32d_v5', 'Standard_DS4', 'Standard_E2_v5', 'Standard_NV8as_v4', 'Standard_D16a_v4', 'Standard_A2', 'Standard_D16s_v5', 'Standard_D96as_v4', '', 'Standard_F16s_v2', 'Standard_M8ms', 'Standard_HC44rs', 'Standard_E64-32s_v4', 'Standard_D64ds_v4', 'Standard_D16d_v4', 'Standard_D4', 'Standard_F2s_v2', 'Standard_E16s_v4', 'Standard_E20_v4', 'Standard_H8m', 'Standard_D15i_v2', 'Standard_D96_v5', 'Standard_E96a_v4', 'Standard_DS13', 'Standard_E8-2s_v3', 'Standard_E80ids_v4', 'Standard_E8as_v4', 'Standard_A0', 'Standard_E96-48as_v4', 'Standard_NV12', 'Standard_D32s_v3', 'Standard_E96as_v4', 'Standard_M128s', 'Basic_A2', 'Standard_E48a_v4', 'Standard_E20d_v4', 'Standard_D16s_v4', 'Standard_E2as_v4', 'Standard_L16s_v2', 'Standard_M64-16ms', 'Standard_D16_v4', 'Standard_E2a_v4', 'Standard_F64s_v2', 'Standard_D32_v5', 'Standard_M416s_v2', 'Standard_M64dms_v2', 'Standard_A5', 'Standard_E64_v3', 'Standard_D32as_v4', 'Standard_E32-8s_v3', 'Standard_NC6s_v3', 'Standard_M64ms', 'Standard_D32-16s_v3', 'Standard_E16-4s_v3', 'Standard_D4ds_v4', 'Standard_DS13-4_v2', 'Standard_D32ds_v5', 'Standard_D32s_v5', 'Standard_D2_v4', 'Standard_L96s_v2', 'Standard_M32ts', 'Standard_E4s_v4', 'Standard_E4_v3', 'Standard_M128', 'Standard_E8-2as_v4', 'Standard_DS12', 'Standard_E8_v4', 'Standard_A2_v2', 'Standard_A4_v2', 'Standard_E32-16ds_v4', 'Standard_M64', 'Standard_D8s_v4', 'Standard_E64s_v3', 'Standard_D64_v3', 'Standard_E16d_v5', 'Standard_M8-4ms', 'Standard_NC16as_T4_v3', 'Standard_D4_v3', 'Standard_E64as_v4', 'Standard_F16s', 'Standard_D64-32s_v3', 'Standard_E4s_v3', 'Standard_E8-2s_v4', 'Standard_DS13-2_v2', 'Standard_D14', 'Standard_D48ds_v5', 'Standard_D12', 'Standard_D32a_v4', 'Standard_DS3', 'Standard_F4s_v2', 'Standard_E20a_v4', 'Standard_NV4as_v4', 'Standard_E2s_v4', 'Standard_E48ds_v4', 'Standard_D8s_v3', 'Standard_D64ds_v5', 'Standard_M64ms_v2', 'Standard_DS1', 'Standard_A7', 'Standard_D96d_v5', 'Standard_D2ds_v4', 'Standard_M8-2ms', 'Standard_E32-8s_v4', 'Standard_D64_v5', 'Standard_D4s_v5', 'Standard_E8s_v3', 'Standard_E80is_v4', 'Standard_D48d_v5', 'Standard_H16r', 'Standard_E32d_v4', 'Standard_E2_v4', 'Standard_M16s', 'Standard_E64-16as_v4', 'Standard_D32-8s_v3', 'Standard_D16d_v5', 'Standard_D2_v2', 'Standard_D3_v2', 'Standard_M192is_v2', 'Standard_E64_v5', 'Standard_D32s_v4', 'Standard_D64s_v5', 'Standard_M16ms', 'Standard_E20s_v3', 'Standard_E64-16s_v4', 'Standard_E16-8s_v4', 'Standard_DS14-8_v2', 'Standard_E4-2s_v4', 'Standard_E16_v4', 'Standard_E8-4ds_v4', 'Standard_D32_v3', 'Standard_E4d_v4', 'Standard_D48as_v4', 'Standard_A4m_v2', 'Standard_M64ds_v2', 'Standard_M128s_v2', 'Standard_D16s_v3', 'Standard_M128ds_v2', 'Standard_D2d_v5', 'Standard_M208s_v2', 'Standard_D16_v3', 'Standard_D32d_v4', 'Standard_D48s_v4', 'Standard_E64-32as_v4', 'Standard_E64-16s_v3', 'Standard_F4s', 'Standard_NV24s_v3', 'Standard_E20_v3', 'Standard_D48s_v3', 'Standard_D8_v5', 'Standard_M64-32ms', 'Standard_DS3_v2', 'Standard_A8m_v2', 'Standard_M32ls', 'Standard_D2d_v4', 'Standard_M16-8ms', 'Standard_M32-16ms', 'Standard_D2_v5', 'Standard_E32ds_v4', 'Standard_D16ds_v5', 'Standard_E8a_v4', 'Standard_E48_v3', 'Standard_E20ds_v4', 'Standard_D2as_v4', 'Standard_DS11-1_v2', 'Standard_DS11', 'Standard_DS2_v2', 'Standard_NV48s_v3', 'Standard_E64_v4', 'Standard_F32s_v2', 'Standard_M416is_v2', 'Standard_D32ds_v4', 'Standard_L80s_v2', 'Standard_M128dms_v2', 'Standard_A1', 'Standard_D4_v5', 'Standard_E2_v3', 'Standard_D48_v5', 'Standard_DS1_v2', 'Standard_DS4_v2', 'Standard_E4-2s_v3', 'Standard_DS14-4_v2', 'Standard_DS12_v2', 'Standard_D96s_v5', 'Standard_D2s_v4', 'Standard_E32s_v4', 'Standard_H16', 'Standard_D48a_v4', 'Standard_D8s_v5', 'Standard_E64-16ds_v4', 'Standard_D48_v3', 'Standard_D32_v4', 'Standard_E8s_v4', 'Standard_E16_v5', 'Standard_D64d_v4', 'Standard_E4a_v4', 'Standard_D64s_v4', 'Standard_H16mr', 'Standard_D13_v2', 'Standard_NC4as_T4_v3', 'Standard_F72s_v2', 'Standard_H8', 'Standard_NC8as_T4_v3', 'Standard_E16as_v4', 'Standard_D16_v5', 'Standard_F48s_v2', 'Standard_M128ms_v2', 'Standard_E96d_v5', 'Standard_E16-8ds_v4', 'Standard_M32ms', 'Standard_A1_v2', 'Standard_D4s_v4', 'Standard_E20_v5', 'Standard_D16ds_v4', 'Standard_DS12-1_v2', 'Standard_F4', 'Standard_M64m', 'Standard_E8-2ds_v4', 'Standard_F2s', 'Standard_E16d_v4', 'Standard_D2ds_v5', 'Standard_E32_v3', 'Standard_E32a_v4', 'Standard_E4d_v5', 'Standard_M32s', 'Standard_F8s_v2', 'Standard_F1', 'Standard_DS12-2_v2', 'Standard_E16-8s_v3', 'Basic_A1', 'Standard_E20as_v4', 'Basic_A0', 'Standard_D4d_v5', 'Standard_D48s_v5', 'Standard_NV32as_v4', 'Standard_HC44-32rs', 'Standard_D48d_v4', 'Standard_D8ds_v4', 'Standard_D64-16s_v3', 'Standard_M64s_v2', 'Standard_NV6', 'Standard_D96ds_v5', 'Standard_DS14', 'Standard_NC12s_v3', 'Standard_A8_v2', 'Standard_NC24s_v3', 'Standard_E20s_v4', 'Standard_NV24', 'Standard_D96a_v4', 'Standard_M208ms_v2', 'Standard_E4-2ds_v4', 'Standard_NC64as_T4_v3', 'Standard_D32d_v5', 'Standard_M32ms_v2', 'Standard_DS14_v2', 'Standard_NC24rs_v3', 'Standard_D2a_v4', 'Standard_E64s_v4', 'Standard_E96-24as_v4', 'Standard_M32-8ms', 'Standard_D4d_v4', 'Standard_M64ls', 'Standard_E64ds_v4', 'Standard_E48_v5', 'Standard_E16-4ds_v4', 'Standard_HC44-16rs', 'Standard_D4a_v4', 'Standard_D64s_v3', 'Standard_M32dms_v2', 'Standard_E96_v5', 'Standard_M128m', 'Standard_A3', 'Standard_L32s_v2', 'Standard_D64d_v5', 'Standard_NV16as_v4', 'Standard_E4ds_v4', 'Standard_E16s_v3', 'Standard_D3', 'Standard_E2s_v3', 'Standard_D12_v2'],
'canadacentral': ['Standard_M128-32ms', 'Standard_M64dms_v2', 'Standard_E32s_v4', 'Standard_E48_v4', 'Standard_E2_v5', 'Standard_D4ds_v5', 'Standard_E80ids_v4', 'Standard_M416-208ms_v2', 'Standard_GS5', 'Standard_D48s_v4', 'Standard_E48d_v5', 'Basic_A3', 'Standard_D48_v3', 'Standard_D64ds_v5', 'Standard_M32ms_v2', 'Standard_DS4_v2', 'Standard_D2_v4', 'Basic_A1', 'Standard_E4s_v3', 'Standard_NC12s_v3', 'Standard_D4_v2', 'Standard_E32_v3', 'Standard_E2d_v4', 'Standard_E32-16s_v4', 'Standard_D16s_v4', 'Standard_E16_v5', 'Standard_NV16as_v4', 'Standard_A4m_v2', 'Standard_E20ds_v4', 'Standard_E32-8s_v3', 'Standard_D8_v4', 'Standard_A3', 'Standard_D2d_v5', 'Standard_E8_v5', 'Standard_D64s_v4', 'Standard_E64-32ds_v4', 'Standard_D2_v3', 'Standard_M64s_v2', 'Standard_E16_v4', '', 'Standard_E32-16s_v3', 'Standard_DS15i_v2', 'Standard_F16s', 'Standard_D48_v5', 'Standard_E16-4s_v3', 'Standard_F2', 'Standard_D16_v4', 'Standard_NC6s_v3', 'Standard_D64_v3', 'Standard_DC1s_v2', 'Standard_E64s_v4', 'Standard_DS11-1_v2', 'Standard_E16-8s_v4', 'Standard_M64-16ms', 'Standard_D32ds_v5', 'Standard_D16d_v4', 'Standard_D4ds_v4', 'Standard_E64_v3', 'Standard_F32s_v2', 'Standard_F72s_v2', 'Standard_D48d_v5', 'Standard_E32-8ds_v4', 'Standard_D4d_v5', 'Standard_E16s_v4', 'Standard_M208-52s_v2', 'Standard_F2s', 'Standard_NC24rs_v3', 'Standard_L8s', 'Standard_M208-104ms_v2', 'Standard_G3', 'Standard_D16s_v5', 'Standard_E8s_v4', 'Standard_E64ds_v4', 'Standard_E16-8s_v3', 'Standard_M128m', 'Standard_NV8as_v4', 'Standard_DC8_v2', 'Standard_D48ds_v4', 'Standard_D64-32s_v3', 'Standard_M416-104s_v2', 'Standard_M16-8ms', 'Standard_M32dms_v2', 'Standard_M16-4ms', 'Standard_D13_v2', 'Standard_E32d_v5', 'Standard_DS12-2_v2', 'Standard_DS1_v2', 'Standard_F8', 'Standard_M128-64ms', 'Standard_E8d_v5', 'Standard_D32s_v4', 'Standard_D15i_v2', 'Standard_D32s_v3', 'Standard_D32-8s_v3', 'Standard_E4-2ds_v4', 'Basic_A4', 'Standard_A1_v2', 'Standard_E16_v3', 'Standard_D64_v5', 'Standard_E8-2s_v3', 'Standard_D48ds_v5', 'Standard_DC2s_v2', 'Standard_D64d_v4', 'Standard_A1', 'Standard_DS14-4_v2', 'Standard_M128ms_v2', 'Standard_F8s', 'Standard_A0', 'Standard_A5', 'Standard_G4', 'Standard_DS11_v2', 'Standard_E4-2s_v4', 'Standard_E20d_v4', 'Standard_M64ms_v2', 'Standard_E64is_v3', 'Standard_E8_v3', 'Standard_E4d_v4', 'Standard_DS5_v2', 'Standard_E32d_v4', 'Standard_F2s_v2', 'Standard_M8ms', 'Standard_E48s_v4', 'Standard_HB120rs_v2', 'Standard_E16s_v3', 'Standard_M8-2ms', 'Standard_E8_v4', 'Standard_D8d_v4', 'Standard_D48s_v5', 'Standard_E48d_v4', 'Standard_D64s_v3', 'Standard_DS15_v2', 'Standard_D96_v5', 'Standard_D96d_v5', 'Standard_D11_v2', 'Standard_DC4s_v2', 'Standard_A8m_v2', 'Standard_E8-2s_v4', 'Standard_E80is_v4', 'Standard_E32ds_v4', 'Standard_D4s_v3', 'Standard_D8_v5', 'Standard_D4_v4', 'Standard_M64m', 'Standard_A2_v2', 'Standard_D32-16s_v3', 'Standard_M128ms', 'Standard_E4_v3', 'Standard_D32_v5', 'Standard_D14_v2', 'Standard_E96_v5', 'Standard_D2d_v4', 'Standard_D64-16s_v3', 'Standard_E2s_v4', 'Standard_DS3_v2', 'Standard_F1', 'Standard_E64-16ds_v4', 'Standard_NV32as_v4', 'Standard_M192ims_v2', 'Standard_E2ds_v4', 'Standard_E16d_v5', 'Standard_E64-16s_v4', 'Standard_D64_v4', 'Standard_D4_v3', 'Standard_E32-8s_v4', 'Standard_D2s_v3', 'Standard_E64s_v3', 'Standard_E2s_v3', 'Standard_M32-8ms', 'Standard_D4s_v4', 'Standard_E2d_v5', 'Standard_E16-4ds_v4', 'Standard_M32s', 'Standard_M32ms', 'Standard_M32ls', 'Standard_D8ds_v4', 'Standard_D8_v3', 'Standard_E2_v4', 'Standard_M32ts', 'Standard_M8-4ms', 'Standard_M128ds_v2', 'Standard_E64-32s_v3', 'Standard_D32_v3', 'Standard_E20_v3', 'Standard_F4', 'Standard_M64ls', 'Standard_L32s', 'Standard_M16s', 'Standard_E4_v4', 'Standard_M16ms', 'Standard_M128dms_v2', 'Standard_D2s_v4', 'Standard_DS13-2_v2', 'Standard_M64-32ms', 'Standard_M128s_v2', 'Standard_D4d_v4', 'Standard_E4_v5', 'Standard_E4s_v4', 'Standard_D32s_v5', 'Standard_G5', 'Standard_E2_v3', 'Standard_D8s_v5', 'Standard_DS14-8_v2', 'Standard_E48_v3', 'Standard_E48ds_v4', 'Standard_D4s_v5', 'Standard_D96ds_v5', 'Standard_E16d_v4', 'Standard_E64-32s_v4', 'Standard_E64_v5', 'Standard_M128s', 'Standard_E64d_v5', 'Standard_E20d_v5', 'Standard_F16', 'Standard_E64i_v3', 'Standard_NV4as_v4', 'Standard_M192ids_v2', 'Standard_E8s_v3', 'Standard_E48s_v3', 'Standard_E4d_v5', 'Standard_E32_v5', 'Standard_F1s', 'Standard_E16-8ds_v4', 'Standard_E8ds_v4', 'Standard_M64ms', 'Standard_M32-16ms', 'Standard_F4s', 'Standard_D2_v2', 'Standard_D64s_v5', 'Standard_D2_v5', 'Standard_D96s_v5', 'Standard_D32d_v4', 'Standard_D5_v2', 'Standard_D12_v2', 'Standard_M64s', 'Standard_D32ds_v4', 'Standard_D8s_v3', 'Standard_DS12_v2', 'Standard_E20s_v4', 'Standard_D32d_v5', 'Standard_GS2', 'Standard_A6', 'Standard_D8s_v4', 'Standard_A4_v2', 'Standard_E20_v5', 'Standard_M192is_v2', 'Standard_E96d_v5', 'Standard_M192idms_v2', 'Standard_F8s_v2', 'Standard_E48_v5', 'Standard_DS13_v2', 'Standard_DS12-1_v2', 'Standard_A4', 'Standard_DS14_v2', 'Standard_D8ds_v5', 'Standard_GS1', 'Standard_E32-16ds_v4', 'Standard_D16_v5', 'Standard_D4_v5', 'Standard_A8_v2', 'Standard_A7', 'Standard_D48s_v3', 'Standard_D3_v2', 'Standard_GS3', 'Standard_D15_v2', 'Standard_D16s_v3', 'Standard_G1', 'Standard_D8d_v5', 'Standard_G2', 'Standard_M416-208s_v2', 'Standard_GS5-16', 'Standard_E32s_v3', 'Standard_D16d_v5', 'Standard_E8d_v4', 'Standard_E8-2ds_v4', 'Standard_GS4-4', 'Standard_E16ds_v4', 'Standard_E20s_v3', 'Standard_D64d_v5', 'Standard_D48d_v4', 'Standard_E64-16s_v3', 'Standard_E8-4s_v3', 'Standard_D2ds_v5', 'Standard_M208-104s_v2', 'Standard_D16ds_v5', 'Standard_F4s_v2', 'Standard_D16ds_v4', 'Standard_D16_v3', 'Standard_F64s_v2', 'Standard_E8-4ds_v4', 'Standard_E4ds_v4', 'Standard_F48s_v2', 'Standard_F16s_v2', 'Standard_GS5-8', 'Basic_A0', 'Standard_L16s', 'Standard_DS13-4_v2', 'Standard_A2m_v2', 'Standard_E64_v4', 'Standard_M208-52ms_v2', 'Standard_E64d_v4', 'Standard_GS4-8', 'Standard_GS4', 'Basic_A2', 'Standard_M416-104ms_v2', 'Standard_D2s_v5', 'Standard_NC24s_v3', 'Standard_E4-2s_v3', 'Standard_M64ds_v2', 'Standard_M128', 'Standard_D64ds_v4', 'Standard_D2ds_v4', 'Standard_DS2_v2', 'Standard_D48_v4', 'Standard_E32_v4', 'Standard_D32_v4', 'Standard_E20_v4', 'Standard_E8-4s_v4', 'Standard_A2', 'Standard_L4s', 'Standard_E16-4s_v4', 'Standard_M64', 'Standard_D1_v2'],
'canadaeast': ['Standard_D32ds_v4', 'Standard_D32s_v5', 'Standard_D64_v4', 'Standard_E80ids_v4', 'Standard_D64-32s_v3', 'Standard_A8_v2', 'Standard_F1', 'Standard_G4', 'Standard_D16ds_v4', 'Standard_M8ms', 'Standard_E8-2s_v4', 'Standard_D8s_v5', 'Standard_DS12-1_v2', 'Standard_GS5-16', 'Standard_E64_v4', 'Standard_D64_v5', 'Standard_L8s', 'Standard_E20d_v4', 'Standard_D2_v5', 'Standard_D16s_v3', 'Standard_M128ms', 'Standard_GS3', 'Standard_E64-16s_v3', 'Standard_DS14-8_v2', 'Standard_GS2', 'Standard_E16d_v4', 'Standard_M128m', 'Standard_D8_v4', 'Standard_F4s', 'Standard_DS14_v2', 'Standard_E32_v5', 'Standard_DS1_v2', 'Standard_E8_v5', 'Standard_G2', 'Standard_E2_v5', 'Standard_D48s_v3', 'Basic_A1', 'Standard_E16-4s_v3', 'Standard_F16s_v2', 'Standard_D13_v2', 'Standard_E48_v5', 'Standard_A3', 'Standard_D32_v4', 'Standard_E48ds_v4', 'Basic_A4', 'Standard_E8d_v5', 'Standard_E32d_v4', 'Standard_E2d_v4', 'Standard_E2ds_v4', 'Standard_D2_v4', 'Standard_E16-4ds_v4', 'Standard_D4s_v3', 'Standard_E4_v4', 'Standard_D16s_v4', 'Standard_A8m_v2', 'Standard_GS4', 'Standard_D64ds_v5', 'Standard_D96s_v5', 'Standard_D2d_v5', 'Standard_D64s_v4', 'Standard_E16d_v5', 'Standard_L4s', 'Standard_DC2s_v2', 'Standard_E20s_v3', 'Standard_E2d_v5', 'Standard_D48_v4', 'Standard_E16_v4', 'Standard_E4_v5', 'Standard_E32-16ds_v4', 'Standard_E8ds_v4', 'Standard_F64s_v2', 'Standard_E32-8s_v3', 'Standard_M32-8ms', 'Standard_M16-4ms', 'Standard_E96_v5', 'Standard_D5_v2', 'Standard_E4-2s_v3', 'Standard_E20_v5', 'Standard_F2', 'Standard_D16_v4', 'Standard_D48s_v4', 'Standard_D3_v2', 'Standard_M64s', 'Standard_E2s_v4', 'Standard_D4s_v5', 'Standard_M64', 'Basic_A0', 'Standard_M64m', 'Standard_E48_v3', 'Standard_E32-8ds_v4', 'Standard_DC4s_v2', 'Standard_E16-8s_v3', 'Standard_E32_v3', 'Standard_GS4-4', 'Standard_E64i_v3', 'Standard_D32-16s_v3', 'Standard_E48s_v3', 'Standard_D32_v3', 'Standard_DC1s_v2', 'Standard_F48s_v2', 'Standard_DS5_v2', 'Standard_A4_v2', 'Standard_D4_v4', 'Standard_E96d_v5', 'Standard_DS12_v2', 'Standard_L16s', 'Standard_DS13-4_v2', 'Standard_D32d_v4', 'Standard_E64-16s_v4', 'Standard_F8s', 'Standard_F16s', 'Standard_D32ds_v5', 'Standard_M64-32ms', 'Standard_D32_v5', 'Standard_M32s', 'Standard_E4-2s_v4', 'Standard_E48d_v5', 'Standard_E8-2ds_v4', 'Standard_E4ds_v4', 'Standard_D8_v3', 'Standard_E8-4s_v3', 'Standard_D16d_v5', 'Standard_D64d_v5', 'Standard_F2s', 'Standard_E32-16s_v4', 'Standard_E16s_v3', 'Standard_D32s_v3', 'Standard_D4_v3', 'Standard_A5', 'Standard_DC8_v2', 'Standard_M8-4ms', 'Standard_E16_v3', 'Standard_D15_v2', 'Standard_D48_v3', 'Standard_G3', 'Standard_D96d_v5', 'Standard_E16ds_v4', 'Standard_D8ds_v4', 'Standard_A0', 'Standard_D8s_v4', 'Standard_E64d_v5', 'Standard_D4_v2', 'Standard_D2_v3', 'Standard_M128-64ms', 'Standard_F32s_v2', 'Standard_E16-8s_v4', 'Standard_D16d_v4', 'Standard_GS5', 'Standard_D4ds_v4', 'Standard_GS1', 'Standard_F4', 'Standard_D2s_v5', 'Standard_M32ms', 'Standard_D48ds_v4', 'Standard_GS4-8', 'Standard_E64s_v4', 'Standard_D96_v5', 'Standard_D2ds_v5', 'Standard_D32s_v4', 'Standard_E64-32s_v3', 'Standard_M64ms', 'Basic_A3', 'Standard_M32ts', 'Standard_E48_v4', 'Standard_F8', 'Standard_E64s_v3', 'Standard_A1', 'Standard_D64_v3', 'Standard_E64d_v4', 'Standard_A4', 'Standard_E32_v4', 'Standard_D8_v5', 'Standard_E80is_v4', 'Standard_E16_v5', 'Standard_D11_v2', 'Standard_E8_v3', 'Standard_E8s_v3', 'Standard_E32-16s_v3', 'Standard_E2_v3', 'Standard_D1_v2', 'Standard_D15i_v2', 'Standard_D64s_v3', 'Standard_DS4_v2', 'Standard_E20d_v5', 'Standard_D16_v3', 'Standard_M16s', 'Standard_E32-8s_v4', 'Standard_M128-32ms', 'Standard_M128s', 'Standard_M8-2ms', 'Standard_E8_v4', 'Standard_E20ds_v4', 'Standard_E4_v3', 'Standard_A2_v2', 'Standard_D64-16s_v3', 'Standard_A6', 'Standard_M16ms', 'Standard_E2_v4', 'Standard_E64-16ds_v4', 'Standard_A2m_v2', 'Standard_M64ls', '', 'Standard_D4ds_v5', 'Standard_DS15i_v2', 'Standard_E8-4s_v4', 'Standard_E32s_v4', 'Standard_D2d_v4', 'Standard_D12_v2', 'Standard_E4-2ds_v4', 'Standard_D2ds_v4', 'Standard_E64is_v3', 'Standard_E16-8ds_v4', 'Standard_E4s_v4', 'Standard_E64_v3', 'Standard_L32s', 'Basic_A2', 'Standard_E64ds_v4', 'Standard_DS3_v2', 'Standard_D2s_v4', 'Standard_D4d_v4', 'Standard_D2s_v3', 'Standard_D32d_v5', 'Standard_D8s_v3', 'Standard_E16-4s_v4', 'Standard_M64-16ms', 'Standard_A2', 'Standard_E64-32s_v4', 'Standard_DS13-2_v2', 'Standard_M32-16ms', 'Standard_G5', 'Standard_E8d_v4', 'Standard_D4_v5', 'Standard_E32s_v3', 'Standard_E8-2s_v3', 'Standard_D4s_v4', 'Standard_D4d_v5', 'Standard_E16s_v4', 'Standard_E8-4ds_v4', 'Standard_DS15_v2', 'Standard_D16ds_v5', 'Standard_A1_v2', 'Standard_E48s_v4', 'Standard_E4d_v5', 'Standard_D48_v5', 'Standard_M16-8ms', 'Standard_F1s', 'Standard_A4m_v2', 'Standard_D64d_v4', 'Standard_E20_v4', 'Standard_G1', 'Standard_D48d_v4', 'Standard_DS11-1_v2', 'Standard_D8ds_v5', 'Standard_M128', 'Standard_F8s_v2', 'Standard_E20_v3', 'Standard_E2s_v3', 'Standard_D64s_v5', 'Standard_E20s_v4', 'Standard_E48d_v4', 'Standard_E64_v5', 'Standard_D96ds_v5', 'Standard_E4s_v3', 'Standard_DS11_v2', 'Standard_GS5-8', 'Standard_E32d_v5', 'Standard_D32-8s_v3', 'Standard_DS2_v2', 'Standard_E8s_v4', 'Standard_D48ds_v5', 'Standard_E64-32ds_v4', 'Standard_D64ds_v4', 'Standard_D16s_v5', 'Standard_D2_v2', 'Standard_DS14-4_v2', 'Standard_F16', 'Standard_A7', 'Standard_D48d_v5', 'Standard_E32ds_v4', 'Standard_D14_v2', 'Standard_DS13_v2', 'Standard_F4s_v2', 'Standard_F2s_v2', 'Standard_D8d_v4', 'Standard_D16_v5', 'Standard_DS12-2_v2', 'Standard_E4d_v4', 'Standard_D48s_v5', 'Standard_F72s_v2', 'Standard_M32ls', 'Standard_D8d_v5'],
'uksouth': ['Standard_E32ds_v4', 'Standard_D32_v3', 'Standard_F2s', 'Standard_D48s_v5', 'Standard_D2d_v4', 'Standard_D1_v2', 'Standard_E32as_v4', 'Standard_E64_v3', 'Standard_M208-104s_v2', 'Standard_E64-32s_v3', 'Standard_E4a_v4', 'Standard_GS5-16', 'Standard_E32d_v4', 'Standard_NC64as_T4_v3', 'Standard_D32_v4', 'Standard_NV8as_v4', 'Standard_E2_v4', 'Standard_E64-32as_v4', 'Standard_F16s_v2', 'Standard_G4', 'Standard_DC1s_v2', 'Standard_L16s_v2', 'Standard_D64-16s_v3', 'Standard_D16d_v4', 'Standard_M16ms', 'Standard_D32ds_v4', 'Standard_E48s_v4', 'Standard_D2ds_v4', 'Standard_E48_v4', 'Standard_M64ls', 'Standard_L80s_v2', 'Standard_M208ms_v2', 'Standard_D8d_v4', 'Standard_D2_v3', 'Standard_L8s', 'Standard_M128ds_v2', 'Standard_D8_v5', 'Standard_E20s_v4', 'Standard_E20_v3', 'Standard_E48a_v4', 'Standard_M416is_v2', 'Standard_A2_v2', 'Standard_M16s', 'Standard_DS11_v2', 'Standard_E2ds_v4', 'Standard_DS13-2_v2', 'Standard_M32ts', 'Standard_E16_v4', 'Standard_D4d_v4', 'Standard_NC12', 'Standard_E8_v3', 'Standard_D48a_v4', 'Standard_E16s_v4', 'Standard_E20d_v5', 'Standard_E16a_v4', 'Standard_M32-16ms', 'Standard_E4-2s_v4', 'Basic_A4', 'Standard_E4_v4', 'Standard_E64s_v3', 'Standard_E96d_v5', 'Standard_E4d_v4', 'Standard_NV4as_v4', 'Standard_F48s_v2', 'Standard_D16ds_v5', 'Standard_D64_v5', 'Standard_D15i_v2', 'Standard_E8as_v4', 'Standard_E8ds_v4', 'Standard_F32s_v2', 'Standard_M64-16ms', 'Standard_E8s_v3', 'Standard_DS15i_v2', 'Standard_M128s_v2', 'Standard_E8_v4', 'Standard_E16_v5', 'Standard_E64-16ds_v4', 'Standard_G3', 'Standard_E20a_v4', 'Standard_E8a_v4', 'Standard_E20ds_v4', 'Standard_M192ids_v2', 'Standard_M64m', 'Standard_M192is_v2', 'Standard_E64_v5', 'Standard_E64a_v4', 'Standard_E16-8s_v3', 'Standard_GS3', 'Standard_DS3_v2', 'Standard_M8ms', 'Standard_D4d_v5', 'Standard_DS12_v2', 'Standard_D4ds_v4', 'Standard_NV12', 'Standard_E4s_v4', 'Standard_E32-8s_v3', 'Standard_E8-2as_v4', 'Standard_NV32as_v4', 'Standard_D8_v4', 'Basic_A3', 'Basic_A1', 'Standard_M128-32ms', 'Standard_A1_v2', 'Standard_F8s_v2', 'Standard_DC4s_v2', 'Standard_E16-8ds_v4', 'Standard_E64s_v4', 'Standard_D32s_v3', 'Standard_GS4-4', 'Standard_D4_v3', 'Standard_E2d_v4', 'Standard_M416-208ms_v2', 'Standard_M64s_v2', 'Standard_D96as_v4', 'Standard_M64s', 'Standard_F1', 'Standard_M8-4ms', 'Standard_M208-52ms_v2', 'Standard_D4as_v4', 'Standard_E2as_v4', 'Standard_E2a_v4', 'Standard_E64i_v3', 'Standard_E4d_v5', 'Standard_GS1', 'Standard_M208s_v2', 'Standard_F16s', 'Standard_E8_v5', 'Standard_E64is_v3', 'Standard_NV12s_v3', 'Standard_M32ms_v2', 'Standard_D2_v2', 'Standard_E16s_v3', 'Standard_A7', 'Standard_A3', 'Standard_D5_v2', 'Standard_E20_v5', 'Standard_E2_v3', 'Standard_E16d_v5', 'Standard_A4m_v2', 'Standard_D2a_v4', 'Standard_M128dms_v2', 'Standard_E48s_v3', 'Standard_D48_v3', 'Standard_M16-8ms', 'Standard_E64-16s_v4', 'Standard_F8s', 'Standard_D64ds_v4', 'Standard_D8_v3', 'Standard_NC4as_T4_v3', 'Standard_D2s_v4', 'Standard_E4_v3', 'Standard_GS4', 'Standard_L48s_v2', 'Standard_F4s_v2', 'Standard_GS5-8', 'Standard_D64s_v5', 'Standard_E4-2ds_v4', 'Standard_E64-16as_v4', 'Standard_NC6s_v3', 'Standard_A0', 'Standard_M192idms_v2', 'Standard_NC12s_v3', 'Standard_D48as_v4', 'Standard_E32-16s_v4', 'Standard_E64d_v4', 'Standard_E64-32ds_v4', 'Standard_E8-4ds_v4', 'Standard_D32_v5', 'Standard_DS4_v2', 'Standard_E32-8ds_v4', 'Standard_E96as_v4', 'Standard_E80is_v4', 'Standard_F2', 'Standard_E64-32s_v4', 'Standard_D96s_v5', 'Standard_E96-48as_v4', 'Standard_NC24', 'Standard_E32-8as_v4', 'Standard_D64-32s_v3', 'Standard_H16mr', 'Standard_D64ds_v5', 'Standard_NV24s_v3', 'Standard_D64s_v3', 'Standard_NV16as_v4', 'Standard_D2s_v5', 'Standard_M208-104ms_v2', 'Standard_DS13-4_v2', 'Standard_E8s_v4', 'Standard_D16ds_v4', 'Standard_E64_v4', 'Standard_D2as_v4', 'Standard_A1', 'Standard_E8-4as_v4', 'Standard_H8', 'Standard_D48ds_v5', 'Standard_D32s_v5', 'Standard_DS2_v2', 'Standard_D2d_v5', 'Standard_DC2s_v2', 'Standard_A8m_v2', 'Standard_D32s_v4', 'Standard_E8-4s_v4', 'Standard_D12_v2', 'Standard_D16_v4', 'Standard_E48_v3', 'Standard_D32a_v4', 'Standard_M32ms', 'Standard_G2', 'Standard_D48_v5', 'Standard_M128', 'Standard_A4_v2', 'Standard_G5', 'Standard_E4-2as_v4', 'Standard_M64-32ms', 'Standard_D32-8s_v3', 'Standard_E20_v4', 'Standard_E16-4s_v4', 'Standard_F8', 'Standard_F16', 'Standard_D16_v5', 'Standard_E32d_v5', 'Standard_NC16as_T4_v3', 'Standard_D64a_v4', 'Standard_L4s', 'Standard_D4_v5', 'Standard_E96_v5', 'Standard_D16a_v4', 'Standard_E32s_v3', 'Standard_E32s_v4', 'Standard_D8ds_v5', 'Standard_E48as_v4', 'Standard_D15_v2', 'Standard_E4_v5', 'Standard_E4ds_v4', 'Standard_D2s_v3', 'Standard_DS14_v2', 'Standard_D16_v3', 'Standard_NV48s_v3', 'Standard_M64ds_v2', 'Standard_E8-2s_v3', 'Standard_E4-2s_v3', 'Standard_D8ds_v4', 'Standard_D32ds_v5', 'Standard_E16ds_v4', 'Standard_E32_v3', 'Basic_A2', 'Standard_A2m_v2', 'Standard_D16s_v5', 'Standard_D64as_v4', 'Standard_DS12-2_v2', '', 'Standard_A2', 'Standard_M416ms_v2', 'Standard_D64_v3', 'Standard_NC24r', 'Standard_E32-16as_v4', 'Standard_D48d_v5', 'Standard_D13_v2', 'Standard_E48_v5', 'Standard_E2s_v3', 'Standard_D3_v2', 'Standard_E20d_v4', 'Standard_L32s', 'Standard_M8-2ms', 'Standard_D48s_v4', 'Standard_L8s_v2', 'Standard_E16_v3', 'Standard_E20s_v3', 'Standard_DC8_v2', 'Standard_D16s_v3', 'Standard_M16-4ms', 'Standard_DS14-4_v2', 'Standard_A6', 'Standard_M416-104ms_v2', 'Standard_D8s_v3', 'Standard_H8m', 'Standard_M64dms_v2', 'Standard_DS12-1_v2', 'Standard_E8-4s_v3', 'Standard_D96_v5', 'Standard_M64ms_v2', 'Standard_D48s_v3', 'Standard_E4as_v4', 'Standard_D8d_v5', 'Standard_E8-2ds_v4', 'Standard_NC24s_v3', 'Standard_L32s_v2', 'Standard_E96-24as_v4', 'Standard_M416s_v2', 'Standard_E32a_v4', 'Standard_M128s', 'Standard_F4', 'Standard_M64', 'Standard_D64_v4', 'Standard_E8-2s_v4', 'Standard_D64d_v4', 'Standard_F2s_v2', 'Standard_M128ms_v2', 'Standard_A4', 'Standard_H16r', 'Standard_DS1_v2', 'Standard_E32_v5', 'Standard_D2_v4', 'Standard_D4s_v5', 'Standard_NC24rs_v3', 'Standard_M32s', 'Standard_E2d_v5', 'Standard_E48d_v4', 'Standard_NV24', 'Standard_GS2', 'Standard_E80ids_v4', 'Standard_M32dms_v2', 'Standard_D96a_v4', 'Standard_D8s_v5', 'Standard_E32-16ds_v4', 'Standard_E32-16s_v3', 'Standard_GS5', 'Standard_D16as_v4', 'Standard_M32-8ms', 'Standard_D48d_v4', 'Standard_F64s_v2', 'Standard_DS11-1_v2', 'Standard_D11_v2', 'Standard_E16-4ds_v4', 'Standard_E8d_v4', 'Standard_GS4-8', 'Standard_DS5_v2', 'Standard_E48ds_v4', 'Standard_D32d_v4', 'Standard_H16m', 'Standard_D48_v4', 'Standard_E64ds_v4', 'Standard_L64s_v2', 'Standard_D4s_v3', 'Standard_D64s_v4', 'Standard_D64d_v5', 'Standard_D96ds_v5', 'Standard_E16-8s_v4', 'Standard_DS15_v2', 'Standard_G1', 'Standard_F72s_v2', 'Standard_D32as_v4', 'Standard_DS14-8_v2', 'Standard_A5', 'Standard_H16', 'Standard_E16d_v4', 'Standard_E32_v4', 'Standard_D2_v5', 'Standard_NV6', 'Standard_E64as_v4', 'Standard_L16s', 'Standard_D32d_v5', 'Standard_D16s_v4', 'Standard_E16as_v4', 'Standard_E32-8s_v4', 'Standard_NC8as_T4_v3', 'Standard_F4s', 'Standard_DS13_v2', 'Standard_E4s_v3', 'Standard_D16d_v5', 'Standard_D8s_v4', 'Standard_D8as_v4', 'Standard_E64-16s_v3', 'Standard_D4a_v4', 'Standard_M32ls', 'Standard_F1s', 'Standard_D96d_v5', 'Standard_D2ds_v5', 'Standard_NC6', 'Standard_E64d_v5', 'Standard_E20as_v4', 'Standard_D4_v2', 'Standard_M208-52s_v2', 'Standard_E16-8as_v4', 'Standard_M192ims_v2', 'Standard_D8a_v4', 'Standard_E8d_v5', 'Standard_D4_v4', 'Standard_D14_v2', 'Standard_E96a_v4', 'Standard_M416-104s_v2', 'Standard_D48ds_v4', 'Standard_M128ms', 'Standard_E48d_v5', 'Standard_E16-4as_v4', 'Standard_D4ds_v5', 'Standard_E16-4s_v3', 'Standard_D32-16s_v3', 'Standard_A8_v2', 'Basic_A0', 'Standard_M416-208s_v2', 'Standard_E2_v5', 'Standard_M64ms', 'Standard_M128-64ms', 'Standard_D4s_v4', 'Standard_E2s_v4', 'Standard_M128m'],
'ukwest': ['Standard_F2s_v2', 'Standard_M416-208s_v2', 'Standard_M208-52s_v2', 'Standard_F16s', 'Standard_E64s_v4', 'Standard_D48_v4', 'Standard_F8s', 'Standard_M8-4ms', 'Standard_A4m_v2', 'Standard_E4_v4', 'Standard_M128-32ms', 'Standard_E16-8ds_v4', 'Standard_D16_v4', 'Standard_D32a_v4', 'Standard_DC4s_v2', 'Standard_E64-32s_v4', 'Standard_M416ms_v2', 'Standard_D48s_v3', 'Standard_D32s_v5', 'Standard_DS4_v2', 'Standard_E32-16s_v3', 'Standard_E2_v3', 'Standard_E32-8ds_v4', 'Standard_F1', 'Standard_E32_v4', 'Standard_M128s', 'Standard_E8_v5', 'Standard_F4s', 'Standard_D32s_v3', 'Standard_D8s_v5', 'Standard_DS13_v2', 'Standard_D48a_v4', 'Standard_E16ds_v4', 'Standard_D4s_v5', 'Standard_E4_v5', 'Standard_D64a_v4', 'Standard_D16s_v5', 'Standard_D32-8s_v3', 'Standard_E16_v5', 'Standard_E64-32ds_v4', 'Standard_A8m_v2', 'Standard_A8_v2', 'Standard_E48_v4', 'Standard_E8s_v3', 'Standard_E32-8s_v3', 'Standard_D2s_v4', 'Standard_E2ds_v4', 'Standard_M32ls', 'Standard_E20_v3', 'Standard_D64_v4', 'Standard_A4_v2', 'Standard_D8s_v3', 'Standard_D64ds_v5', 'Standard_D16a_v4', 'Standard_F4s_v2', 'Standard_M64-16ms', 'Standard_DS11-1_v2', 'Standard_D48d_v5', 'Standard_D2_v5', 'Standard_E20ds_v4', 'Standard_A5', 'Standard_E16-8s_v4', 'Standard_D32_v3', 'Standard_E4-2s_v3', 'Standard_D8_v3', 'Standard_DS15i_v2', 'Standard_E4d_v4', 'Standard_E64is_v3', 'Standard_D2s_v3', 'Standard_D4ds_v4', 'Standard_E8-4s_v3', 'Standard_D64s_v4', 'Standard_E16s_v4', 'Standard_E16_v3', 'Standard_M16-8ms', 'Standard_E32ds_v4', 'Standard_E8-4ds_v4', 'Standard_E64_v5', 'Standard_M128ms', 'Standard_F4', 'Standard_E32_v5', 'Standard_E64_v3', 'Standard_E64s_v3', 'Standard_E64-16s_v4', 'Standard_E16_v4', 'Standard_D8d_v4', 'Standard_D48ds_v5', 'Standard_E80ids_v4', 'Standard_D64_v5', 'Standard_D48d_v4', 'Standard_D32-16s_v3', 'Standard_E32-8s_v4', 'Standard_E64-16s_v3', 'Standard_E8ds_v4', 'Standard_D48_v3', 'Standard_M128', 'Standard_D2_v4', 'Standard_DS1_v2', 'Standard_E64-32s_v3', 'Standard_M208ms_v2', 'Standard_D48ds_v4', 'Standard_D96ds_v5', 'Standard_M64ls', 'Standard_E8-2s_v4', 'Standard_D14_v2', '', 'Standard_D4_v5', 'Standard_D15i_v2', 'Standard_D15_v2', 'Standard_F32s_v2', 'Standard_E32d_v4', 'Standard_D2s_v5', 'Standard_M32-8ms', 'Standard_D8ds_v5', 'Standard_D2a_v4', 'Standard_D32s_v4', 'Standard_D96d_v5', 'Standard_E8d_v4', 'Standard_D3_v2', 'Standard_M32s', 'Standard_D4s_v4', 'Standard_E64_v4', 'Standard_D8a_v4', 'Standard_D1_v2', 'Standard_D4_v4', 'Standard_D8_v5', 'Standard_E20_v5', 'Standard_E4d_v5', 'Standard_E16d_v5', 'Standard_M208s_v2', 'Standard_M32ts', 'Standard_M64-32ms', 'Standard_E32_v3', 'Standard_D96s_v5', 'Standard_DS2_v2', 'Standard_D64-32s_v3', 'Standard_M416s_v2', 'Standard_F8', 'Standard_DS14_v2', 'Standard_DS3_v2', 'Standard_E64ds_v4', 'Standard_D8d_v5', 'Standard_E20_v4', 'Standard_DS14-4_v2', 'Standard_E48_v5', 'Standard_F72s_v2', 'Standard_E32s_v3', 'Standard_E8s_v4', 'Standard_D4ds_v5', 'Standard_E2s_v4', 'Standard_M416-104s_v2', 'Standard_D8_v4', 'Standard_DS5_v2', 'Standard_E20s_v3', 'Standard_D11_v2', 'Standard_E64d_v4', 'Standard_M64ms', 'Standard_F48s_v2', 'Standard_F64s_v2', 'Basic_A4', 'Standard_F8s_v2', 'Standard_D64s_v3', 'Standard_A7', 'Standard_DS13-4_v2', 'Standard_D32ds_v4', 'Standard_M16s', 'Standard_D48s_v4', 'Standard_E48_v3', 'Standard_E48ds_v4', 'Basic_A0', 'Standard_E4s_v4', 'Standard_A4', 'Standard_D48s_v5', 'Standard_E8-2ds_v4', 'Standard_D4a_v4', 'Standard_D16ds_v5', 'Standard_E16s_v3', 'Standard_D64_v3', 'Standard_F16s_v2', 'Standard_M64m', 'Standard_DS12-1_v2', 'Standard_M416-104ms_v2', 'Standard_D16_v5', 'Standard_M128-64ms', 'Standard_D96a_v4', 'Standard_D4d_v5', 'Standard_E2_v4', 'Standard_E4s_v3', 'Standard_E4_v3', 'Standard_D48_v5', 'Standard_M64s', 'Standard_A1_v2', 'Standard_E32d_v5', 'Standard_DS12-2_v2', 'Standard_E20d_v5', 'Standard_D8ds_v4', 'Standard_DC2s_v2', 'Standard_E64i_v3', 'Standard_E32s_v4', 'Basic_A3', 'Standard_E20s_v4', 'Standard_D2ds_v5', 'Standard_M208-104ms_v2', 'Standard_A0', 'Standard_E4-2ds_v4', 'Basic_A1', 'Standard_D32ds_v5', 'Standard_M208-52ms_v2', 'Standard_DS14-8_v2', 'Standard_D2_v2', 'Standard_DS11_v2', 'Standard_A2', 'Standard_D96_v5', 'Standard_D13_v2', 'Standard_A3', 'Standard_M8ms', 'Standard_M32ms', 'Standard_DS15_v2', 'Standard_E80is_v4', 'Standard_E48s_v3', 'Standard_E8-4s_v4', 'Standard_D2_v3', 'Standard_D64s_v5', 'Standard_E4ds_v4', 'Standard_DC1s_v2', 'Standard_E2_v5', 'Standard_D16d_v5', 'Standard_D2d_v5', 'Standard_F16', 'Standard_D2d_v4', 'Standard_D4_v2', 'Standard_D64d_v4', 'Standard_D2ds_v4', 'Standard_DS13-2_v2', 'Standard_M208-104s_v2', 'Standard_F2s', 'Standard_M416-208ms_v2', 'Standard_M64', 'Standard_D16_v3', 'Standard_E16-8s_v3', 'Basic_A2', 'Standard_D12_v2', 'Standard_A2_v2', 'Standard_DC8_v2', 'Standard_D64-16s_v3', 'Standard_A1', 'Standard_D64d_v5', 'Standard_D16s_v3', 'Standard_D16d_v4', 'Standard_E20d_v4', 'Standard_D32d_v5', 'Standard_E16-4s_v3', 'Standard_F1s', 'Standard_E96d_v5', 'Standard_E32-16s_v4', 'Standard_DS12_v2', 'Standard_D32_v4', 'Standard_E48d_v4', 'Standard_A2m_v2', 'Standard_E8_v4', 'Standard_D4_v3', 'Standard_E16d_v4', 'Standard_E48s_v4', 'Standard_D8s_v4', 'Standard_M16-4ms', 'Standard_E64d_v5', 'Standard_M128m', 'Standard_D4s_v3', 'Standard_M16ms', 'Standard_E48d_v5', 'Standard_E32-16ds_v4', 'Standard_E16-4ds_v4', 'Standard_E2s_v3', 'Standard_M32-16ms', 'Standard_D16ds_v4', 'Standard_E16-4s_v4', 'Standard_E8d_v5', 'Standard_D64ds_v4', 'Standard_D5_v2', 'Standard_D32d_v4', 'Standard_E96_v5', 'Standard_E2d_v4', 'Standard_M416is_v2', 'Standard_E64-16ds_v4', 'Standard_E8_v3', 'Standard_M8-2ms', 'Standard_D16s_v4', 'Standard_F2', 'Standard_E8-2s_v3', 'Standard_D4d_v4', 'Standard_E4-2s_v4', 'Standard_D32_v5', 'Standard_E2d_v5', 'Standard_A6'],
'koreacentral': ['Standard_M416-104ms_v2', 'Standard_M64-32ms', 'Standard_D96d_v5', 'Standard_E8_v4', 'Standard_M208-104s_v2', 'Standard_D64s_v3', 'Standard_E64d_v4', 'Standard_DS14-8_v2', 'Standard_E8_v3', 'Standard_F4s', 'Standard_M16s', 'Standard_F72s_v2', 'Standard_E32s_v3', 'Standard_E16-4s_v4', '', 'Standard_E8-4as_v4', 'Standard_D2ds_v5', 'Standard_E16-8s_v3', 'Standard_D8_v3', 'Standard_E8-4s_v4', 'Basic_A4', 'Standard_E64-32ds_v4', 'Standard_F2', 'Standard_D1_v2', 'Standard_D16as_v4', 'Standard_E64_v4', 'Standard_E80is_v4', 'Standard_D64_v4', 'Standard_E64-16s_v4', 'Standard_D64_v3', 'Standard_D8ds_v5', 'Standard_E8-4ds_v4', 'Standard_NC64as_T4_v3', 'Standard_M208-104ms_v2', 'Standard_D2ds_v4', 'Standard_D48s_v3', 'Standard_E48ds_v4', 'Standard_D4as_v4', 'Standard_HC44-32rs', 'Standard_E2d_v4', 'Standard_A2_v2', 'Standard_M32-8ms', 'Standard_E48s_v4', 'Standard_D2_v5', 'Basic_A3', 'Standard_NC16as_T4_v3', 'Standard_E48_v4', 'Standard_M128ms', 'Standard_NC4as_T4_v3', 'Standard_D14_v2', 'Standard_E32s_v4', 'Standard_D96_v5', 'Standard_D16_v3', 'Standard_D15_v2', 'Standard_E4_v3', 'Standard_F16', 'Standard_E16d_v4', 'Standard_D48_v3', 'Standard_D48s_v4', 'Standard_E16s_v4', 'Standard_D8a_v4', 'Standard_E20as_v4', 'Standard_E20s_v4', 'Standard_E20_v3', 'Standard_E8d_v4', 'Basic_A1', 'Standard_M8ms', 'Standard_A4', 'Standard_F8s_v2', 'Standard_DS13_v2', 'Standard_HC44rs', 'Standard_E32-8s_v4', 'Standard_D5_v2', 'Standard_E64-32s_v4', 'Standard_E8-2ds_v4', 'Standard_D8ds_v4', 'Standard_E96-48as_v4', 'Standard_A8_v2', 'Standard_HC44-16rs', 'Standard_M64ls', 'Standard_E16_v4', 'Standard_F1', 'Standard_D64s_v5', 'Standard_NC12s_v3', 'Standard_D64-16s_v3', 'Standard_A8m_v2', 'Standard_E48d_v4', 'Standard_D96as_v4', 'Standard_E32d_v4', 'Standard_E16-8ds_v4', 'Standard_D32s_v4', 'Standard_D96s_v5', 'Standard_D48a_v4', 'Standard_D32as_v4', 'Standard_M32-16ms', 'Standard_D8s_v4', 'Standard_D32s_v3', 'Standard_D4ds_v5', 'Standard_D4a_v4', 'Standard_E4-2ds_v4', 'Standard_E32-16ds_v4', 'Standard_D64d_v4', 'Standard_E96-24as_v4', 'Standard_D64s_v4', 'Standard_NV32as_v4', 'Standard_D32_v5', 'Standard_M8-4ms', 'Standard_E16ds_v4', 'Standard_E96as_v4', 'Standard_E20_v4', 'Standard_F1s', 'Standard_E2_v5', 'Standard_E32d_v5', 'Standard_E2s_v3', 'Standard_E8s_v3', 'Standard_E64s_v4', 'Standard_F8s', 'Standard_DS12-1_v2', 'Standard_E32as_v4', 'Standard_E20ds_v4', 'Standard_A1_v2', 'Standard_E4as_v4', 'Standard_D16d_v5', 'Standard_DS12_v2', 'Standard_M416-208ms_v2', 'Standard_M416is_v2', 'Standard_E64d_v5', 'Standard_D48as_v4', 'Standard_E48_v5', 'Standard_NC6s_v3', 'Standard_E64-16ds_v4', 'Standard_D13_v2', 'Standard_A4m_v2', 'Standard_D16s_v5', 'Basic_A0', 'Standard_E4d_v5', 'Standard_DS13-2_v2', 'Standard_D8_v4', 'Standard_D96a_v4', 'Standard_M32ts', 'Standard_A0', 'Standard_E32-16s_v4', 'Standard_DS1_v2', 'Standard_F32s_v2', 'Standard_E96_v5', 'Standard_E4d_v4', 'Standard_E8-2s_v3', 'Standard_F48s_v2', 'Standard_D2_v3', 'Standard_D32ds_v5', 'Standard_E16-4s_v3', 'Standard_D64a_v4', 'Standard_M16-4ms', 'Standard_E8-2s_v4', 'Standard_D4s_v3', 'Standard_A6', 'Standard_E2a_v4', 'Standard_NV4as_v4', 'Standard_D2as_v4', 'Standard_E64-16as_v4', 'Standard_E16-8s_v4', 'Standard_E64-32s_v3', 'Standard_E8-2as_v4', 'Standard_DS4_v2', 'Standard_D64ds_v4', 'Standard_M416-208s_v2', 'Standard_D48s_v5', 'Standard_D32ds_v4', 'Standard_DS5_v2', 'Standard_F2s_v2', 'Standard_E32a_v4', 'Standard_E16-8as_v4', 'Standard_E32_v4', 'Standard_E4a_v4', 'Standard_E8ds_v4', 'Standard_E16-4ds_v4', 'Standard_D16d_v4', 'Standard_E64as_v4', 'Standard_E32ds_v4', 'Standard_E64_v5', 'Standard_E8s_v4', 'Standard_D32_v4', 'Standard_E2d_v5', 'Standard_E4-2as_v4', 'Standard_M416s_v2', 'Standard_E16d_v5', 'Standard_NC8as_T4_v3', 'Standard_E8as_v4', 'Standard_E8_v5', 'Standard_E4_v5', 'Standard_D16s_v3', 'Standard_E16as_v4', 'Standard_E96a_v4', 'Standard_E16a_v4', 'Standard_F8', 'Standard_D48d_v5', 'Standard_E16_v5', 'Standard_D2_v2', 'Standard_D4_v4', 'Standard_D4d_v4', 'Standard_DS3_v2', 'Standard_E48_v3', 'Standard_E32-8s_v3', 'Standard_E20_v5', 'Standard_E20d_v4', 'Standard_M16-8ms', 'Standard_D8s_v5', 'Standard_D32_v3', 'Standard_E4ds_v4', 'Standard_F2s', 'Standard_F4s_v2', 'Standard_M8-2ms', 'Standard_M416-104s_v2', 'Standard_E8-4s_v3', 'Standard_E4_v4', 'Standard_E16-4as_v4', 'Standard_NC24s_v3', 'Standard_E2ds_v4', 'Standard_E64a_v4', 'Standard_E32_v3', 'Standard_D64as_v4', 'Standard_D4s_v4', 'Standard_E64_v3', 'Standard_D32-8s_v3', 'Standard_E16_v3', 'Standard_E8a_v4', 'Standard_D11_v2', 'Standard_A5', 'Standard_M128m', 'Standard_D32a_v4', 'Standard_D64ds_v5', 'Standard_DS2_v2', 'Standard_M208-52ms_v2', 'Standard_E2as_v4', 'Standard_DS13-4_v2', 'Standard_E64-16s_v3', 'Standard_D32d_v5', 'Standard_A4_v2', 'Standard_NV16as_v4', 'Standard_D8_v5', 'Standard_F4', 'Standard_E20s_v3', 'Standard_M208-52s_v2', 'Standard_D16ds_v4', 'Standard_D96ds_v5', 'Standard_E32-16as_v4', 'Standard_D48ds_v4', 'Standard_M32s', 'Standard_E4s_v3', 'Standard_D2s_v5', 'Standard_M128s', 'Standard_A2m_v2', 'Standard_D16ds_v5', 'Standard_E48d_v5', 'Standard_D16s_v4', 'Standard_E64i_v3', 'Standard_D4d_v5', 'Standard_D32s_v5', 'Standard_E32-8as_v4', 'Standard_DS14_v2', 'Standard_D64d_v5', 'Standard_E32-8ds_v4', 'Standard_D12_v2', 'Standard_D2_v4', 'Standard_E64s_v3', 'Standard_M128-32ms', 'Standard_D32d_v4', 'Standard_D2a_v4', 'Standard_D15i_v2', 'Standard_M64ms', 'Standard_A3', 'Standard_D4ds_v4', 'Standard_E48a_v4', 'Standard_NC24rs_v3', 'Standard_M128-64ms', 'Standard_D8d_v5', 'Standard_M64', 'Standard_D16_v5', 'Standard_E32-16s_v3', 'Standard_D8as_v4', 'Standard_E48as_v4', 'Standard_M16ms', 'Standard_DS15i_v2', 'Standard_A1', 'Standard_E2s_v4', 'Standard_E20a_v4', 'Standard_E20d_v5', 'Standard_E4-2s_v4', 'Standard_D64-32s_v3', 'Standard_D48ds_v5', 'Standard_DS11_v2', 'Standard_D48_v4', 'Standard_E4s_v4', 'Standard_E64is_v3', 'Standard_M64m', 'Standard_E4-2s_v3', 'Basic_A2', 'Standard_M32ls', 'Standard_M64s', 'Standard_F16s_v2', 'Standard_D3_v2', 'Standard_D16_v4', 'Standard_F16s', 'Standard_M64-16ms', 'Standard_NV8as_v4', 'Standard_M416ms_v2', 'Standard_D4_v3', 'Standard_E64-32as_v4', 'Standard_D48d_v4', 'Standard_E80ids_v4', 'Standard_E8d_v5', 'Standard_DS11-1_v2', 'Standard_M208s_v2', 'Standard_D64_v5', 'Standard_D2s_v3', 'Standard_DS15_v2', 'Standard_E64ds_v4', 'Standard_D2d_v4', 'Standard_D8s_v3', 'Standard_E16s_v3', 'Standard_E32_v5', 'Standard_D2d_v5', 'Standard_D48_v5', 'Standard_DS14-4_v2', 'Standard_E2_v3', 'Standard_D8d_v4', 'Standard_M208ms_v2', 'Standard_D4s_v5', 'Standard_D2s_v4', 'Standard_D16a_v4', 'Standard_DS12-2_v2', 'Standard_M32ms', 'Standard_D4_v2', 'Standard_F64s_v2', 'Standard_A7', 'Standard_D32-16s_v3', 'Standard_E48s_v3', 'Standard_M128', 'Standard_E2_v4', 'Standard_A2', 'Standard_D4_v5', 'Standard_E96d_v5'],
'koreasouth': ['Standard_E64-16ds_v4', 'Standard_D4_v5', 'Standard_A2m_v2', 'Standard_D2_v3', 'Standard_D96a_v4', 'Standard_E32d_v5', 'Standard_E20s_v4', 'Standard_E64-32s_v3', 'Standard_M32ts', 'Standard_M416is_v2', 'Standard_E8_v5', 'Standard_E32ds_v4', 'Standard_D2a_v4', 'Standard_M64ms', 'Standard_D32ds_v5', 'Standard_E32d_v4', 'Standard_D64a_v4', 'Standard_E48_v3', 'Standard_E2s_v4', 'Standard_E8as_v4', 'Standard_D64d_v4', 'Standard_DS5_v2', 'Standard_F4s_v2', 'Standard_D4d_v4', 'Standard_D64s_v4', 'Standard_E20ds_v4', 'Standard_E8-2ds_v4', 'Standard_D64_v4', 'Standard_D64as_v4', 'Standard_M64-16ms', 'Standard_D32_v3', 'Standard_E64s_v4', 'Basic_A0', 'Standard_E64-16s_v3', 'Standard_E4s_v4', 'Standard_D13_v2', 'Standard_M208-52ms_v2', 'Standard_E8-4ds_v4', 'Standard_D32-16s_v3', 'Standard_E8-2s_v4', 'Standard_E16ds_v4', 'Standard_D32ds_v4', 'Standard_E96-24as_v4', 'Standard_M208ms_v2', 'Standard_D64_v3', 'Standard_D16_v3', 'Standard_E16d_v4', 'Standard_E48ds_v4', 'Standard_D64s_v5', 'Standard_E16_v5', 'Standard_F16s', 'Standard_E4-2s_v3', 'Standard_D48d_v5', 'Standard_DS14-4_v2', 'Standard_D8_v5', 'Standard_D4s_v5', 'Standard_E64_v5', 'Standard_F8', 'Standard_D8ds_v4', 'Standard_E20_v4', 'Standard_D48_v4', 'Standard_F64s_v2', 'Standard_F1s', 'Standard_E64d_v5', 'Standard_D16a_v4', 'Standard_E20_v3', 'Standard_D2ds_v5', 'Standard_D48s_v3', 'Standard_E2a_v4', 'Standard_A5', 'Standard_D4_v4', 'Standard_D11_v2', 'Standard_E4s_v3', 'Standard_E4_v5', 'Standard_DS11_v2', 'Standard_DS1_v2', 'Standard_E64-32s_v4', 'Standard_E4_v3', 'Standard_E16-4as_v4', 'Standard_D2s_v5', 'Standard_D96_v5', 'Standard_D4_v3', 'Standard_M8-4ms', 'Standard_D2_v5', 'Standard_D48_v3', 'Standard_D1_v2', 'Standard_E2_v4', 'Standard_E96as_v4', 'Standard_D32_v4', 'Standard_E64-32as_v4', 'Standard_M208-104ms_v2', 'Standard_E48as_v4', 'Standard_D16as_v4', 'Standard_D2s_v4', 'Standard_D96d_v5', 'Standard_D32s_v5', 'Standard_D32a_v4', 'Standard_NC64as_T4_v3', 'Standard_E8_v3', 'Standard_D4d_v5', 'Standard_A1', 'Standard_D64d_v5', 'Standard_D16s_v4', 'Standard_D8a_v4', 'Standard_E32s_v3', 'Standard_A4', 'Standard_D48s_v4', 'Standard_E80is_v4', 'Standard_E2d_v5', 'Standard_E8-4s_v3', 'Standard_DS13_v2', 'Standard_F1', 'Standard_E8_v4', 'Basic_A1', 'Standard_E2ds_v4', 'Standard_E48s_v4', 'Standard_E48d_v4', 'Standard_E16as_v4', 'Standard_D8s_v5', 'Standard_E32-8as_v4', 'Standard_M32-8ms', 'Standard_NC4as_T4_v3', 'Standard_E96d_v5', 'Standard_DS14-8_v2', 'Standard_E64s_v3', 'Standard_E32_v5', 'Standard_E32-8s_v4', 'Standard_D16ds_v5', 'Standard_D16ds_v4', 'Standard_D2d_v5', 'Standard_E2_v3', 'Standard_E64ds_v4', 'Standard_E20_v5', 'Basic_A3', 'Standard_D64ds_v5', 'Standard_M416-104s_v2', 'Standard_E16s_v4', 'Standard_E20d_v5', 'Standard_A1_v2', 'Standard_D4ds_v5', 'Standard_D16_v4', 'Standard_E48_v5', 'Standard_D64s_v3', 'Standard_D4ds_v4', 'Standard_E64_v4', 'Standard_E16-4s_v4', 'Standard_DS15_v2', 'Standard_E16d_v5', 'Standard_D4s_v4', 'Standard_M416-104ms_v2', 'Standard_A8_v2', 'Standard_D16_v5', 'Standard_DS12_v2', 'Basic_A4', 'Standard_E32-8ds_v4', 'Standard_F4s', 'Standard_M416-208ms_v2', 'Standard_E4as_v4', '', 'Standard_M16ms', 'Standard_A2_v2', 'Standard_E16s_v3', 'Standard_F32s_v2', 'Standard_M64', 'Standard_F4', 'Standard_E64a_v4', 'Standard_A8m_v2', 'Standard_D8s_v3', 'Standard_M64ls', 'Standard_D4as_v4', 'Standard_D2_v2', 'Standard_DS13-2_v2', 'Standard_E8-2as_v4', 'Standard_D64ds_v4', 'Standard_DS3_v2', 'Standard_A7', 'Standard_E32-16s_v4', 'Standard_E96-48as_v4', 'Standard_E2_v5', 'Standard_F2s_v2', 'Standard_E48d_v5', 'Standard_D16s_v3', 'Standard_E64d_v4', 'Standard_E8-4s_v4', 'Standard_F48s_v2', 'Standard_D96s_v5', 'Standard_E20as_v4', 'Standard_M16-8ms', 'Standard_A0', 'Standard_D3_v2', 'Standard_F2s', 'Standard_NC16as_T4_v3', 'Standard_F2', 'Standard_D32-8s_v3', 'Standard_A3', 'Standard_A4_v2', 'Standard_M16-4ms', 'Standard_M208-52s_v2', 'Standard_DS2_v2', 'Standard_DS14_v2', 'Standard_E32-8s_v3', 'Standard_D8as_v4', 'Standard_A2', 'Standard_D64-32s_v3', 'Standard_F72s_v2', 'Standard_M32-16ms', 'Standard_E8-2s_v3', 'Standard_E64i_v3', 'Standard_D15_v2', 'Standard_M32s', 'Standard_E8s_v3', 'Basic_A2', 'Standard_D8_v3', 'Standard_D8s_v4', 'Standard_D96ds_v5', 'Standard_D48ds_v4', 'Standard_D4_v2', 'Standard_A4m_v2', 'Standard_D64_v5', 'Standard_E64-16as_v4', 'Standard_D32_v5', 'Standard_E64is_v3', 'Standard_D48a_v4', 'Standard_E20s_v3', 'Standard_F16s_v2', 'Standard_DS13-4_v2', 'Standard_E32a_v4', 'Standard_M8-2ms', 'Standard_D16d_v4', 'Standard_D48ds_v5', 'Standard_E96a_v4', 'Standard_E64as_v4', 'Standard_M16s', 'Standard_D48s_v5', 'Standard_F8s_v2', 'Standard_M128-32ms', 'Standard_D96as_v4', 'Standard_E48_v4', 'Standard_D15i_v2', 'Standard_D2d_v4', 'Standard_M32ls', 'Standard_M8ms', 'Standard_E16-4ds_v4', 'Standard_E4-2ds_v4', 'Standard_E16_v3', 'Standard_D8d_v5', 'Standard_D32d_v5', 'Standard_M32ms', 'Standard_E4_v4', 'Standard_DS15i_v2', 'Standard_D32s_v4', 'Standard_E8ds_v4', 'Standard_E8d_v5', 'Standard_E4ds_v4', 'Standard_D2ds_v4', 'Standard_D2_v4', 'Standard_M64s', 'Standard_D48_v5', 'Standard_D12_v2', 'Standard_D32s_v3', 'Standard_E32-16as_v4', 'Standard_E4d_v5', 'Standard_D2s_v3', 'Standard_DS4_v2', 'Standard_A6', 'Standard_E4-2as_v4', 'Standard_E32as_v4', 'Standard_E8a_v4', 'Standard_D32as_v4', 'Standard_E2d_v4', 'Standard_E64-32ds_v4', 'Standard_DS11-1_v2', 'Standard_M128s', 'Standard_E32_v4', 'Standard_M416ms_v2', 'Standard_E16-8ds_v4', 'Standard_E16a_v4', 'Standard_E16_v4', 'Standard_D2as_v4', 'Standard_D64-16s_v3', 'Standard_D32d_v4', 'Standard_D14_v2', 'Standard_NC8as_T4_v3', 'Standard_E80ids_v4', 'Standard_E32-16s_v3', 'Standard_D4s_v3', 'Standard_E16-8s_v4', 'Standard_M128-64ms', 'Standard_D5_v2', 'Standard_E64_v3', 'Standard_D8ds_v5', 'Standard_M416s_v2', 'Standard_E32_v3', 'Standard_E8s_v4', 'Standard_M416-208s_v2', 'Standard_E8d_v4', 'Standard_E16-4s_v3', 'Standard_D16d_v5', 'Standard_D48d_v4', 'Standard_E2s_v3', 'Standard_M208s_v2', 'Standard_E64-16s_v4', 'Standard_D8_v4', 'Standard_F8s', 'Standard_E32-16ds_v4', 'Standard_E16-8as_v4', 'Standard_E8-4as_v4', 'Standard_E48s_v3', 'Standard_D4a_v4', 'Standard_E48a_v4', 'Standard_E20d_v4', 'Standard_E4d_v4', 'Standard_D8d_v4', 'Standard_E20a_v4', 'Standard_E4a_v4', 'Standard_M208-104s_v2', 'Standard_E4-2s_v4', 'Standard_M128ms', 'Standard_E96_v5', 'Standard_DS12-1_v2', 'Standard_D16s_v5', 'Standard_M128', 'Standard_M64-32ms', 'Standard_M128m', 'Standard_D48as_v4', 'Standard_E2as_v4', 'Standard_E32s_v4', 'Standard_F16', 'Standard_E16-8s_v3', 'Standard_M64m', 'Standard_DS12-2_v2'],
'francecentral': ['Standard_E32-8s_v4', 'Standard_D4s_v5', 'Standard_DS3_v2', 'Standard_D64-16s_v3', 'Standard_E64_v4', 'Standard_D4s_v4', 'Standard_D96s_v5', 'Standard_M16s', 'Standard_M32ms_v2', 'Standard_M64dms_v2', 'Standard_D64d_v4', 'Standard_M128-32ms', 'Standard_E4-2s_v3', 'Standard_E8_v5', 'Standard_D2s_v4', 'Standard_M128-64ms', 'Standard_A1_v2', 'Standard_E32-8s_v3', 'Standard_NC24rs_v3', 'Standard_D4_v5', 'Standard_E2_v3', 'Standard_A8_v2', 'Standard_D8d_v5', 'Standard_D64d_v5', 'Standard_E20s_v3', 'Standard_DS5_v2', 'Standard_D48_v4', 'Standard_D2_v4', 'Standard_E4ds_v4', 'Standard_DS15_v2', 'Standard_E64-32s_v3', 'Standard_D2_v2', 'Standard_D32_v3', 'Standard_DS13-2_v2', 'Standard_E16-8s_v3', 'Standard_F2s_v2', 'Standard_M8-4ms', 'Standard_M8-2ms', 'Standard_D48ds_v5', 'Standard_E32d_v5', 'Standard_M64ms', 'Standard_F8s', 'Standard_E2s_v3', 'Standard_D48s_v3', 'Standard_D64_v3', 'Standard_M64', 'Standard_DS12-2_v2', 'Standard_D48d_v4', 'Standard_D8_v3', 'Standard_E4-2ds_v4', 'Standard_DS14_v2', 'Standard_E16-4s_v3', 'Standard_D4ds_v4', 'Standard_E16d_v5', 'Standard_NV12s_v3', 'Standard_M32ls', 'Standard_E2d_v5', 'Standard_E16-8ds_v4', 'Standard_D96d_v5', 'Standard_M32-8ms', 'Standard_D16s_v3', 'Standard_D8s_v4', 'Standard_D32ds_v4', 'Standard_M128s_v2', 'Standard_E20_v3', 'Standard_F8s_v2', 'Basic_A3', 'Standard_D48_v5', 'Standard_D8_v4', 'Standard_E64i_v3', 'Standard_D64s_v3', 'Standard_D3_v2', 'Standard_M192idms_v2', 'Standard_E16s_v4', 'Standard_F2s', 'Standard_D16s_v4', 'Standard_E32-16s_v4', 'Standard_D16d_v4', 'Standard_E32ds_v4', 'Standard_E16-8s_v4', 'Standard_NC12s_v3', 'Standard_M128ds_v2', 'Standard_E2ds_v4', 'Standard_E32_v3', 'Standard_D8ds_v4', 'Standard_DS14-8_v2', 'Standard_E64s_v4', 'Standard_D48s_v5', '', 'Standard_D14_v2', 'Standard_NC6s_v3', 'Standard_D32s_v3', 'Standard_D2s_v5', 'Standard_D15i_v2', 'Standard_A2m_v2', 'Standard_M64m', 'Standard_M192ims_v2', 'Standard_M32ms', 'Standard_D4_v3', 'Basic_A4', 'Standard_D32-8s_v3', 'Standard_E64-32ds_v4', 'Standard_DS12_v2', 'Standard_D4ds_v5', 'Standard_D2s_v3', 'Standard_E4-2s_v4', 'Standard_E16-4ds_v4', 'Standard_L32s_v2', 'Standard_F48s_v2', 'Standard_E16ds_v4', 'Standard_E48d_v5', 'Standard_E64_v3', 'Standard_DS14-4_v2', 'Standard_E32-8ds_v4', 'Standard_A1', 'Standard_E20d_v4', 'Standard_E2_v5', 'Standard_D32d_v5', 'Standard_D64_v4', 'Standard_E8-4s_v4', 'Standard_E16d_v4', 'Standard_L48s_v2', 'Standard_A0', 'Standard_D48_v3', 'Standard_E4_v3', 'Standard_DS1_v2', 'Standard_E48ds_v4', 'Standard_E80ids_v4', 'Standard_DS11-1_v2', 'Standard_E4s_v3', 'Standard_D16s_v5', 'Standard_E8s_v4', 'Standard_E64d_v5', 'Standard_E20s_v4', 'Standard_D48d_v5', 'Standard_F16s', 'Standard_A7', 'Standard_D2ds_v4', 'Standard_E8_v4', 'Standard_M64s', 'Standard_D2d_v4', 'Standard_M16ms', 'Standard_D16_v4', 'Standard_D4s_v3', 'Standard_D96_v5', 'Standard_E48_v3', 'Standard_E4_v5', 'Standard_E64ds_v4', 'Standard_D32d_v4', 'Standard_E64d_v4', 'Standard_DS13-4_v2', 'Standard_D48ds_v4', 'Standard_E20_v5', 'Standard_D64s_v5', 'Standard_A2', 'Standard_D2_v5', 'Standard_M16-8ms', 'Standard_F4s_v2', 'Standard_D4_v2', 'Standard_E96d_v5', 'Basic_A2', 'Standard_D8ds_v5', 'Basic_A1', 'Standard_E32s_v4', 'Standard_M192ids_v2', 'Standard_E8_v3', 'Standard_E4_v4', 'Standard_E4d_v4', 'Standard_D32s_v4', 'Standard_M16-4ms', 'Standard_E64-16ds_v4', 'Standard_D8d_v4', 'Standard_D64s_v4', 'Standard_M64s_v2', 'Standard_E4d_v5', 'Standard_D32_v5', 'Standard_DS11_v2', 'Standard_F2', 'Standard_E80is_v4', 'Standard_E32d_v4', 'Standard_A4m_v2', 'Standard_A2_v2', 'Standard_D2ds_v5', 'Standard_M128ms', 'Standard_D64_v5', 'Standard_A4_v2', 'Standard_D2d_v5', 'Standard_A3', 'Standard_A5', 'Standard_E48_v5', 'Standard_M128m', 'Standard_E8s_v3', 'Standard_E2d_v4', 'Standard_M64ds_v2', 'Standard_F16', 'Standard_M32dms_v2', 'Standard_F32s_v2', 'Standard_E4s_v4', 'Standard_A6', 'Standard_D4d_v5', 'Standard_E2s_v4', 'Standard_F1s', 'Standard_F64s_v2', 'Standard_D16_v3', 'Standard_E8d_v5', 'Standard_E8-2s_v3', 'Standard_E64-16s_v4', 'Standard_D15_v2', 'Standard_D16_v5', 'Standard_F72s_v2', 'Standard_D16d_v5', 'Standard_D32-16s_v3', 'Standard_E8-4s_v3', 'Standard_DS2_v2', 'Standard_M64-32ms', 'Standard_E8d_v4', 'Standard_E32-16ds_v4', 'Standard_M192is_v2', 'Standard_E32_v4', 'Standard_E8-2s_v4', 'Standard_L64s_v2', 'Standard_F8', 'Standard_D32_v4', 'Standard_D5_v2', 'Standard_D16ds_v4', 'Standard_E8-4ds_v4', 'Standard_E96_v5', 'Standard_E64is_v3', 'Basic_A0', 'Standard_D2_v3', 'Standard_DS4_v2', 'Standard_E16s_v3', 'Standard_M32-16ms', 'Standard_D8s_v5', 'Standard_M64ls', 'Standard_D64ds_v5', 'Standard_D12_v2', 'Standard_E64_v5', 'Standard_E2_v4', 'Standard_NV24s_v3', 'Standard_F4', 'Standard_E64s_v3', 'Standard_E64-32s_v4', 'Standard_D48s_v4', 'Standard_D8s_v3', 'Standard_M128dms_v2', 'Standard_E16_v5', 'Standard_E48s_v3', 'Standard_DS13_v2', 'Standard_E8-2ds_v4', 'Standard_NV48s_v3', 'Standard_E48_v4', 'Standard_M64ms_v2', 'Standard_M64-16ms', 'Standard_D96ds_v5', 'Standard_E20d_v5', 'Standard_M32ts', 'Standard_DS12-1_v2', 'Standard_F16s_v2', 'Standard_D11_v2', 'Standard_M8ms', 'Standard_E16-4s_v4', 'Standard_E48s_v4', 'Standard_A4', 'Standard_M128s', 'Standard_F1', 'Standard_E32s_v3', 'Standard_D16ds_v5', 'Standard_D64-32s_v3', 'Standard_F4s', 'Standard_E16_v4', 'Standard_E48d_v4', 'Standard_L16s_v2', 'Standard_M128', 'Standard_M128ms_v2', 'Standard_E20ds_v4', 'Standard_D4d_v4', 'Standard_D13_v2', 'Standard_D32ds_v5', 'Standard_E32-16s_v3', 'Standard_E8ds_v4', 'Standard_E32_v5', 'Standard_A8m_v2', 'Standard_D1_v2', 'Standard_D64ds_v4', 'Standard_L80s_v2', 'Standard_E64-16s_v3', 'Standard_D32s_v5', 'Standard_M32s', 'Standard_D8_v5', 'Standard_L8s_v2', 'Standard_D4_v4', 'Standard_E20_v4', 'Standard_NC24s_v3', 'Standard_DS15i_v2', 'Standard_E16_v3'],
'southafricanorth': ['Standard_D4s_v4', 'Standard_DS13_v2', 'Standard_E32s_v4', 'Standard_D64-32s_v3', 'Standard_DS11', 'Standard_E64d_v4', 'Standard_E80is_v4', 'Standard_DS14', 'Standard_D15_v2', 'Standard_M64dms_v2', 'Standard_D32-16s_v3', 'Standard_E64d_v5', 'Standard_E4_v4', 'Standard_D2s_v3', 'Standard_D48s_v4', 'Standard_DS5_v2', 'Standard_D4d_v4', 'Standard_DS15i_v2', 'Standard_E8_v5', 'Standard_M64ls', 'Standard_M128s_v2', 'Standard_M32ms_v2', 'Standard_D48ds_v4', 'Standard_E16-8s_v4', 'Standard_D3_v2', 'Standard_D4ds_v5', 'Standard_D48s_v5', 'Standard_E96d_v5', 'Standard_E16-4s_v4', 'Standard_M8ms', 'Standard_D2_v3', 'Standard_DS14_v2', 'Standard_E16-4ds_v4', 'Standard_E32_v3', 'Standard_DS4', 'Standard_D64ds_v5', 'Standard_D48d_v4', 'Standard_D64_v4', 'Standard_DS11-1_v2', '', 'Standard_E2s_v3', 'Standard_DS1', 'Standard_E8-4s_v4', 'Standard_E64_v5', 'Standard_D64ds_v4', 'Standard_E32_v5', 'Standard_M208-52ms_v2', 'Standard_E96_v5', 'Standard_M32-16ms', 'Standard_E4_v5', 'Standard_D2ds_v4', 'Standard_F2', 'Standard_M16ms', 'Standard_D1', 'Standard_M208-52s_v2', 'Standard_D8s_v3', 'Standard_D96_v5', 'Standard_D32-8s_v3', 'Standard_E64s_v4', 'Standard_E16ds_v4', 'Standard_D8ds_v4', 'Standard_D8d_v5', 'Standard_D5_v2', 'Standard_F72s_v2', 'Standard_F4', 'Standard_D96s_v5', 'Standard_M32ms', 'Standard_E2_v5', 'Standard_D8d_v4', 'Standard_A2m_v2', 'Standard_E64-32ds_v4', 'Standard_E48d_v5', 'Standard_D11_v2', 'Standard_E64-32s_v4', 'Standard_E48s_v3', 'Standard_E80ids_v4', 'Standard_M416-208s_v2', 'Standard_E48s_v4', 'Standard_D16s_v5', 'Standard_M128dms_v2', 'Standard_M8-4ms', 'Standard_D2_v4', 'Standard_M32ts', 'Standard_M16s', 'Standard_E4ds_v4', 'Standard_M128ms_v2', 'Standard_M416-208ms_v2', 'Standard_D48_v4', 'Standard_D16_v4', 'Standard_D8_v5', 'Standard_A8_v2', 'Standard_D4d_v5', 'Standard_M128s', 'Standard_M128-64ms', 'Standard_E48_v3', 'Standard_E64_v3', 'Standard_M208-104s_v2', 'Standard_DS13-4_v2', 'Standard_D2s_v5', 'Standard_A4m_v2', 'Standard_DS3', 'Standard_E64ds_v4', 'Standard_M32ls', 'Standard_E16_v5', 'Standard_D16ds_v5', 'Standard_D16_v5', 'Standard_M16-8ms', 'Standard_M64ms', 'Standard_D64_v3', 'Standard_E20_v5', 'Standard_E2_v3', 'Standard_M208-104ms_v2', 'Standard_DS2_v2', 'Standard_M192is_v2', 'Standard_D48ds_v5', 'Standard_M192ims_v2', 'Standard_D16ds_v4', 'Standard_DS2', 'Standard_F2s', 'Standard_F4s', 'Standard_D96ds_v5', 'Standard_F64s_v2', 'Standard_E8-4ds_v4', 'Standard_E8s_v4', 'Standard_DS12', 'Standard_E16s_v3', 'Standard_M192idms_v2', 'Standard_D16s_v4', 'Standard_F4s_v2', 'Standard_E20s_v3', 'Standard_M32-8ms', 'Standard_A2_v2', 'Standard_D12_v2', 'Standard_E32d_v5', 'Standard_E2_v4', 'Standard_D2d_v5', 'Standard_D64s_v5', 'Standard_D16_v3', 'Standard_E64is_v3', 'Standard_E16d_v4', 'Standard_M128-32ms', 'Standard_E64i_v3', 'Standard_D2d_v4', 'Standard_NV12s_v3', 'Standard_DS13-2_v2', 'Standard_E16-8s_v3', 'Standard_D12', 'Standard_E16-4s_v3', 'Standard_DS3_v2', 'Standard_DS11_v2', 'Standard_E8-4s_v3', 'Standard_E4-2s_v4', 'Standard_F1', 'Standard_E4s_v4', 'Standard_DS12-2_v2', 'Standard_D32ds_v5', 'Standard_D11', 'Standard_M64s', 'Standard_E20_v4', 'Standard_D4s_v3', 'Standard_D4s_v5', 'Standard_D8_v3', 'Standard_E8ds_v4', 'Standard_E64-16ds_v4', 'Standard_D8s_v4', 'Standard_M128ds_v2', 'Standard_E4d_v4', 'Standard_D4_v5', 'Standard_D15i_v2', 'Standard_DS1_v2', 'Standard_D4_v3', 'Standard_D4_v2', 'Standard_E8_v4', 'Standard_D8s_v5', 'Standard_M416-104ms_v2', 'Standard_E8-2s_v4', 'Standard_D4_v4', 'Standard_F8s', 'Standard_M32dms_v2', 'Standard_DS14-4_v2', 'Standard_D32s_v4', 'Standard_F1s', 'Standard_D2_v5', 'Standard_E32-8s_v3', 'Standard_E48ds_v4', 'Standard_E16d_v5', 'Standard_M192ids_v2', 'Standard_E32-16s_v3', 'Standard_DS15_v2', 'Standard_D3', 'Standard_D13', 'Standard_E16_v4', 'Standard_M64ds_v2', 'Standard_D64_v5', 'Standard_E48_v5', 'Standard_E2ds_v4', 'Standard_M32s', 'Standard_D64s_v3', 'Standard_NV48s_v3', 'Standard_E32-16ds_v4', 'Standard_D2ds_v5', 'Standard_D32s_v5', 'Standard_D32_v3', 'Standard_D1_v2', 'Standard_A4_v2', 'Standard_E20d_v4', 'Standard_D2s_v4', 'Standard_E16_v3', 'Standard_D48s_v3', 'Standard_E2s_v4', 'Standard_E4-2ds_v4', 'Standard_M64', 'Standard_D14', 'Standard_D48d_v5', 'Standard_E4d_v5', 'Standard_D32_v5', 'Standard_D13_v2', 'Standard_F8s_v2', 'Standard_E16-8ds_v4', 'Standard_F16', 'Standard_D32ds_v4', 'Standard_F2s_v2', 'Standard_M128ms', 'Standard_D64d_v5', 'Standard_E4-2s_v3', 'Standard_E20ds_v4', 'Standard_DS12-1_v2', 'Standard_M64-16ms', 'Standard_E8-2s_v3', 'Standard_M16-4ms', 'Standard_D32d_v5', 'Standard_D16s_v3', 'Standard_E8_v3', 'Standard_E2d_v4', 'Standard_D8ds_v5', 'Standard_E32-8ds_v4', 'Standard_D32_v4', 'Standard_E32_v4', 'Standard_M8-2ms', 'Standard_E8d_v4', 'Standard_DS4_v2', 'Standard_E64s_v3', 'Standard_E20_v3', 'Standard_E20d_v5', 'Standard_E8d_v5', 'Standard_D64-16s_v3', 'Standard_A8m_v2', 'Standard_E32s_v3', 'Standard_E48_v4', 'Standard_E16s_v4', 'Standard_E20s_v4', 'Standard_E64-16s_v4', 'Standard_E64_v4', 'Standard_D4ds_v4', 'Standard_D48_v3', 'Standard_DS12_v2', 'Standard_E32ds_v4', 'Standard_F8', 'Standard_F32s_v2', 'Standard_E8s_v3', 'Standard_DS14-8_v2', 'Standard_D14_v2', 'Standard_F16s', 'Standard_E4s_v3', 'Standard_M64s_v2', 'Standard_D2_v2', 'Standard_M64ms_v2', 'Standard_M416-104s_v2', 'Standard_A1_v2', 'Standard_M64-32ms', 'Standard_NV24s_v3', 'Standard_E64-16s_v3', 'Standard_D96d_v5', 'Standard_E48d_v4', 'Standard_D64s_v4', 'Standard_M64m', 'Standard_E4_v3', 'Standard_E2d_v5', 'Standard_D48_v5', 'Standard_E32-8s_v4', 'Standard_D4', 'Standard_D32d_v4', 'Standard_D2', 'Standard_D16d_v4', 'Standard_E32-16s_v4', 'Standard_F16s_v2', 'Standard_E64-32s_v3', 'Standard_E8-2ds_v4', 'Standard_E32d_v4', 'Standard_F48s_v2', 'Standard_DS13', 'Standard_D32s_v3', 'Standard_D8_v4', 'Standard_M128m', 'Standard_D64d_v4', 'Standard_D16d_v5', 'Standard_M128'],
'uaenorth': ['Standard_D16s_v3', 'Standard_DS13', 'Standard_E4-2s_v4', 'Standard_E32-8s_v3', 'Standard_E64d_v5', 'Standard_D32d_v5', 'Standard_DS2_v2', 'Standard_D4s_v3', 'Standard_E16_v5', 'Standard_E32_v3', 'Standard_E4-2ds_v4', 'Standard_F64s_v2', 'Standard_D2_v2', 'Standard_E64s_v3', 'Standard_M192idms_v2', 'Standard_E4d_v5', 'Standard_M32dms_v2', 'Standard_M64-32ms', 'Standard_M64ms_v2', 'Standard_M416-104ms_v2', 'Standard_E48_v3', 'Standard_D32d_v4', 'Standard_E48d_v4', 'Standard_E20_v3', 'Standard_M128ms_v2', 'Standard_D3_v2', 'Standard_D64ds_v5', 'Standard_D64-32s_v3', 'Standard_D48d_v5', 'Standard_D48_v5', 'Standard_D15_v2', 'Standard_M32ms_v2', 'Standard_E4_v4', 'Standard_D48s_v4', 'Standard_E96d_v5', 'Standard_M8-2ms', 'Standard_D4_v5', 'Standard_D32_v5', 'Standard_E32_v5', 'Standard_DS12', 'Standard_M192ims_v2', 'Standard_E32-16s_v4', 'Standard_D14_v2', 'Standard_D32_v3', 'Standard_DS13-4_v2', 'Standard_E20ds_v4', 'Standard_A2m_v2', 'Standard_M128-32ms', 'Standard_D2s_v3', 'Standard_M32ls', 'Standard_M192is_v2', 'Standard_D11_v2', 'Standard_E2_v5', 'Standard_D2', 'Standard_F1', 'Standard_E64is_v3', 'Standard_D2ds_v4', 'Standard_DS11_v2', 'Standard_E64-16s_v4', 'Standard_DS14-4_v2', 'Standard_M32ms', 'Standard_D32s_v3', 'Standard_E64s_v4', 'Standard_NV24s_v3', 'Standard_D4_v3', 'Standard_D1', 'Standard_D16d_v5', 'Standard_D8d_v4', 'Standard_M8-4ms', 'Standard_F16s', 'Standard_D16s_v4', 'Standard_E64-16ds_v4', 'Standard_D8d_v5', 'Standard_E64d_v4', 'Standard_DS11-1_v2', 'Standard_D32_v4', 'Standard_D13_v2', 'Standard_D13', 'Standard_DS15_v2', 'Standard_D4d_v5', 'Standard_D64d_v5', 'Standard_D64s_v4', 'Standard_M16-8ms', 'Standard_D4_v2', 'Standard_D11', 'Standard_E32d_v4', 'Standard_E4_v3', 'Standard_E32ds_v4', 'Standard_D64d_v4', 'Standard_E8-4ds_v4', 'Standard_D4s_v4', 'Standard_DS11', 'Standard_E16-4s_v4', 'Standard_E64_v4', 'Standard_DS1_v2', 'Standard_E48_v4', 'Standard_DS12-1_v2', 'Standard_D32s_v5', 'Standard_D32ds_v4', 'Standard_DS13-2_v2', 'Standard_E2d_v5', 'Standard_E4-2s_v3', 'Standard_M16s', 'Standard_DS2', 'Standard_E32d_v5', 'Standard_D8s_v5', 'Standard_E48ds_v4', 'Standard_E2s_v3', 'Standard_E8d_v5', 'Standard_D15i_v2', 'Standard_F48s_v2', 'Standard_E8_v3', 'Standard_E16d_v5', 'Standard_E4_v5', 'Standard_E16-8s_v4', 'Standard_D8s_v3', 'Standard_E8-2ds_v4', 'Standard_M32-16ms', 'Standard_DS15i_v2', 'Standard_E4d_v4', 'Standard_M64ls', 'Standard_M416is_v2', '', 'Standard_M128ms', 'Standard_E8ds_v4', 'Standard_E16-8ds_v4', 'Standard_D12_v2', 'Standard_F32s_v2', 'Standard_E2ds_v4', 'Standard_E32_v4', 'Standard_E96_v5', 'Standard_E16-4s_v3', 'Standard_D48_v4', 'Standard_M64ds_v2', 'Standard_E32-16ds_v4', 'Standard_E32-8s_v4', 'Standard_D64ds_v4', 'Standard_M8ms', 'Standard_D16_v4', 'Standard_M64s', 'Standard_M16-4ms', 'Standard_D4', 'Standard_E2s_v4', 'Standard_E64_v5', 'Standard_M208-104ms_v2', 'Standard_M208-52ms_v2', 'Standard_DS12-2_v2', 'Standard_M64dms_v2', 'Standard_D48s_v5', 'Standard_D8_v4', 'Standard_F8s', 'Standard_D16ds_v4', 'Standard_DS12_v2', 'Standard_M208s_v2', 'Standard_HB120rs_v2', 'Standard_D64_v5', 'Standard_DS13_v2', 'Standard_DS14', 'Standard_M208-104s_v2', 'Standard_M416-208ms_v2', 'Standard_M128m', 'Standard_M416ms_v2', 'Standard_E80ids_v4', 'Standard_F1s', 'Standard_D32-16s_v3', 'Standard_E20s_v3', 'Standard_D2s_v5', 'Standard_E8_v4', 'Standard_E2_v3', 'Standard_F2s_v2', 'Standard_E64ds_v4', 'Standard_A4m_v2', 'Standard_NV48s_v3', 'Standard_D48ds_v5', 'Standard_M208-52s_v2', 'Standard_E16s_v3', 'Standard_NV12s_v3', 'Standard_F8s_v2', 'Standard_M32ts', 'Standard_D96d_v5', 'Standard_E4s_v3', 'Standard_E2_v4', 'Standard_E32s_v3', 'Standard_D4s_v5', 'Standard_E16ds_v4', 'Standard_M32-8ms', 'Standard_E20_v5', 'Standard_E8-2s_v3', 'Standard_D32ds_v5', 'Standard_A8m_v2', 'Standard_D8_v5', 'Standard_D3', 'Standard_E64-32s_v3', 'Standard_D16_v5', 'Standard_D96s_v5', 'Standard_E20s_v4', 'Standard_M416-104s_v2', 'Standard_E16_v3', 'Standard_D4ds_v4', 'Standard_E48d_v5', 'Standard_M64m', 'Standard_E8-2s_v4', 'Standard_E2d_v4', 'Standard_D4ds_v5', 'Standard_F8', 'Standard_M416s_v2', 'Standard_E64-32ds_v4', 'Standard_D96_v5', 'Standard_D8ds_v4', 'Standard_D2d_v5', 'Standard_DS3_v2', 'Standard_D14', 'Standard_D96ds_v5', 'Standard_D32-8s_v3', 'Standard_E16s_v4', 'Standard_DS5_v2', 'Standard_E20d_v5', 'Standard_M128s_v2', 'Standard_E8s_v3', 'Standard_M32s', 'Standard_A2_v2', 'Standard_D48s_v3', 'Standard_D2s_v4', 'Standard_D48ds_v4', 'Standard_F4', 'Standard_M208ms_v2', 'Standard_E32-16s_v3', 'Standard_M128ds_v2', 'Standard_D2_v3', 'Standard_DS3', 'Standard_E4s_v4', 'Standard_D64s_v3', 'Standard_A1_v2', 'Standard_F72s_v2', 'Standard_E48_v5', 'Standard_E32s_v4', 'Standard_E8-4s_v3', 'Standard_D5_v2', 'Standard_E64i_v3', 'Standard_M64-16ms', 'Standard_E8_v5', 'Standard_A4_v2', 'Standard_E64_v3', 'Standard_F16', 'Standard_E8-4s_v4', 'Standard_F16s_v2', 'Standard_A8_v2', 'Standard_D16s_v5', 'Standard_D48_v3', 'Standard_DS14-8_v2', 'Standard_D64_v3', 'Standard_E48s_v4', 'Standard_DS1', 'Standard_D16ds_v5', 'Standard_E20_v4', 'Standard_M16ms', 'Standard_D64s_v5', 'Standard_E64-16s_v3', 'Standard_F4s_v2', 'Standard_M64', 'Standard_E16_v4', 'Standard_F2', 'Standard_D8_v3', 'Standard_D48d_v4', 'Standard_D4_v4', 'Standard_E32-8ds_v4', 'Standard_D64_v4', 'Standard_E20d_v4', 'Standard_DS4_v2', 'Standard_D16_v3', 'Standard_D2_v4', 'Standard_D12', 'Standard_E64-32s_v4', 'Standard_DS14_v2', 'Standard_E8s_v4', 'Standard_M128s', 'Standard_D64-16s_v3', 'Standard_M64ms', 'Standard_D8s_v4', 'Standard_E8d_v4', 'Standard_D4d_v4', 'Standard_D2d_v4', 'Standard_F2s', 'Standard_D1_v2', 'Standard_F4s', 'Standard_M128dms_v2', 'Standard_E4ds_v4', 'Standard_E16-8s_v3', 'Standard_D32s_v4', 'Standard_E16d_v4', 'Standard_D8ds_v5', 'Standard_E16-4ds_v4', 'Standard_DS4', 'Standard_D2_v5', 'Standard_E80is_v4', 'Standard_M128', 'Standard_M128-64ms', 'Standard_D2ds_v5', 'Standard_M64s_v2', 'Standard_E48s_v3', 'Standard_D16d_v4', 'Standard_M416-208s_v2', 'Standard_M192ids_v2'],
'australiacentral': ['Standard_E8-2ds_v4', 'Standard_D48_v5', 'Standard_E64ds_v4', 'Basic_A3', 'Standard_E8_v5', 'Standard_E16s_v4', 'Standard_M128-64ms', 'Standard_D32s_v3', 'Standard_E32-16s_v4', 'Standard_D4ds_v4', 'Standard_D64-32s_v3', 'Standard_M64-16ms', 'Standard_E2s_v4', 'Standard_E8s_v3', 'Standard_E32_v5', 'Standard_D8d_v5', 'Standard_E16-4s_v3', 'Standard_F1', 'Standard_E32s_v3', 'Standard_D8s_v3', 'Standard_E16d_v4', 'Standard_E80ids_v4', 'Standard_D8ds_v5', 'Standard_M16-8ms', 'Standard_E64d_v4', 'Standard_E8-4s_v4', 'Standard_F16s', 'Standard_E32_v3', 'Standard_A6', 'Standard_M416-208ms_v2', 'Standard_A2', 'Standard_F2s_v2', 'Standard_M128', 'Standard_DS11-1_v2', 'Standard_M416-104s_v2', 'Standard_F8s', 'Standard_E16_v3', 'Standard_E4s_v3', 'Standard_F16', 'Standard_DS5_v2', 'Standard_D48_v4', 'Standard_D48d_v5', 'Standard_D16ds_v4', 'Standard_D16ds_v5', 'Standard_A8_v2', 'Standard_A5', 'Standard_E32-16s_v3', 'Standard_E80is_v4', 'Standard_D16s_v5', 'Standard_E64_v5', 'Standard_D3_v2', 'Basic_A1', 'Basic_A2', 'Standard_E16s_v3', 'Standard_M8-4ms', 'Standard_M416s_v2', 'Standard_DS11_v2', 'Standard_DS4_v2', 'Standard_DS1_v2', 'Standard_E64_v4', 'Standard_DS14-4_v2', '', 'Standard_D16s_v4', 'Standard_M208s_v2', 'Standard_D8_v5', 'Standard_E16-8s_v3', 'Basic_A0', 'Standard_E48_v5', 'Standard_A4_v2', 'Standard_E4ds_v4', 'Standard_E20d_v4', 'Standard_M32s', 'Standard_E2d_v5', 'Standard_D1_v2', 'Standard_E4_v5', 'Standard_M32-16ms', 'Standard_M416is_v2', 'Standard_E96d_v5', 'Standard_E20s_v4', 'Standard_E64s_v3', 'Standard_F1s', 'Standard_D64s_v4', 'Standard_M16s', 'Standard_D4s_v5', 'Standard_D16d_v5', 'Standard_E8_v4', 'Standard_M32-8ms', 'Standard_D8ds_v4', 'Standard_D5_v2', 'Standard_D2s_v4', 'Standard_D2d_v5', 'Standard_D64_v5', 'Standard_E2_v3', 'Standard_D16_v5', 'Standard_D2_v4', 'Standard_M208-52s_v2', 'Standard_F8s_v2', 'Standard_E32d_v5', 'Standard_D2_v2', 'Standard_E8ds_v4', 'Standard_E4_v3', 'Standard_DS15_v2', 'Standard_DS2_v2', 'Standard_E48d_v4', 'Standard_D64d_v5', 'Standard_D4ds_v5', 'Standard_D32d_v5', 'Standard_F48s_v2', 'Standard_D48ds_v5', 'Standard_D4d_v4', 'Standard_D8_v3', 'Standard_E64-16s_v4', 'Standard_D96d_v5', 'Standard_M416-208s_v2', 'Standard_D32ds_v5', 'Standard_DS15i_v2', 'Standard_D2d_v4', 'Standard_E20_v5', 'Standard_E16-8ds_v4', 'Standard_M32ts', 'Standard_D4s_v4', 'Standard_M64', 'Standard_D32s_v5', 'Standard_E16-4ds_v4', 'Standard_F16s_v2', 'Standard_E2d_v4', 'Standard_E20_v3', 'Standard_D48s_v3', 'Standard_M64m', 'Standard_E64-32ds_v4', 'Standard_D16_v3', 'Standard_E48s_v3', 'Standard_E20s_v3', 'Standard_E64s_v4', 'Standard_A0', 'Standard_E8d_v4', 'Standard_A3', 'Standard_D32s_v4', 'Standard_D32_v5', 'Standard_E48_v3', 'Standard_D32-16s_v3', 'Standard_E4-2ds_v4', 'Standard_M208-104ms_v2', 'Standard_D32_v4', 'Standard_E2ds_v4', 'Standard_D2ds_v5', 'Standard_D2s_v5', 'Standard_D16s_v3', 'Standard_M416ms_v2', 'Standard_M16-4ms', 'Standard_F32s_v2', 'Standard_DS13-2_v2', 'Standard_E96_v5', 'Standard_E16-8s_v4', 'Standard_E4_v4', 'Standard_E8_v3', 'Standard_D96ds_v5', 'Standard_E4d_v5', 'Standard_E32-8s_v4', 'Standard_D48_v3', 'Standard_E32_v4', 'Standard_E16ds_v4', 'Standard_E4-2s_v3', 'Standard_M8ms', 'Standard_E20d_v5', 'Standard_E4d_v4', 'Standard_DS12-1_v2', 'Standard_E64-32s_v3', 'Standard_M64ms', 'Standard_F8', 'Standard_F4s_v2', 'Standard_M64-32ms', 'Standard_E48ds_v4', 'Standard_M416-104ms_v2', 'Standard_D32-8s_v3', 'Standard_A1', 'Standard_F4', 'Standard_D8_v4', 'Standard_E16_v5', 'Standard_E48d_v5', 'Standard_D14_v2', 'Standard_F4s', 'Standard_E20_v4', 'Standard_D13_v2', 'Standard_E48_v4', 'Standard_E2_v5', 'Standard_D12_v2', 'Standard_D64_v4', 'Standard_M32ms', 'Standard_D64s_v3', 'Standard_D96_v5', 'Standard_D8s_v4', 'Standard_E8d_v5', 'Standard_D48s_v5', 'Standard_D2s_v3', 'Standard_E20ds_v4', 'Standard_D4_v3', 'Standard_M128-32ms', 'Standard_D64ds_v5', 'Standard_F64s_v2', 'Standard_D64s_v5', 'Standard_E8s_v4', 'Standard_D32d_v4', 'Standard_A1_v2', 'Standard_D16d_v4', 'Standard_D96s_v5', 'Standard_M64ls', 'Standard_A2m_v2', 'Standard_E8-4ds_v4', 'Standard_DS12_v2', 'Standard_D48s_v4', 'Standard_E32-8ds_v4', 'Standard_E64_v3', 'Standard_D2_v3', 'Standard_E2_v4', 'Standard_M208-104s_v2', 'Standard_D48ds_v4', 'Standard_D4_v4', 'Standard_F2', 'Standard_E4s_v4', 'Standard_D15_v2', 'Standard_M128s', 'Standard_D4_v5', 'Standard_E8-2s_v3', 'Standard_E16d_v5', 'Standard_M128ms', 'Standard_M64s', 'Standard_E2s_v3', 'Standard_DS13_v2', 'Standard_A8m_v2', 'Standard_A4', 'Standard_D4s_v3', 'Basic_A4', 'Standard_E64-32s_v4', 'Standard_DS14_v2', 'Standard_D64d_v4', 'Standard_DS14-8_v2', 'Standard_E8-2s_v4', 'Standard_DS13-4_v2', 'Standard_D32_v3', 'Standard_A4m_v2', 'Standard_D64_v3', 'Standard_D8s_v5', 'Standard_F72s_v2', 'Standard_D4d_v5', 'Standard_M208-52ms_v2', 'Standard_M208ms_v2', 'Standard_E64-16s_v3', 'Standard_E64-16ds_v4', 'Standard_E32ds_v4', 'Standard_M32ls', 'Standard_A2_v2', 'Standard_D2_v5', 'Standard_F2s', 'Standard_E64d_v5', 'Standard_M16ms', 'Standard_DS3_v2', 'Standard_M128m', 'Standard_D64-16s_v3', 'Standard_E48s_v4', 'Standard_D8d_v4', 'Standard_D4_v2', 'Standard_DS12-2_v2', 'Standard_E4-2s_v4', 'Standard_M8-2ms', 'Standard_A7', 'Standard_D64ds_v4', 'Standard_E8-4s_v3', 'Standard_D11_v2', 'Standard_E16_v4', 'Standard_E32-8s_v3', 'Standard_D16_v4', 'Standard_D2ds_v4', 'Standard_D48d_v4', 'Standard_E32d_v4', 'Standard_E32-16ds_v4', 'Standard_E32s_v4', 'Standard_D15i_v2', 'Standard_E16-4s_v4', 'Standard_D32ds_v4'],
'switzerlandnorth': ['Standard_D16s_v3', 'Standard_D2_v4', 'Standard_E64_v3', 'Standard_F64s_v2', 'Standard_F16s_v2', '', 'Standard_E8s_v3', 'Standard_E20d_v4', 'Standard_E16-8ds_v4', 'Standard_D4ds_v5', 'Standard_E16s_v4', 'Standard_D4s_v5', 'Standard_M64-16ms', 'Standard_E16d_v5', 'Standard_E32s_v4', 'Standard_E32-16s_v4', 'Standard_E64-32ds_v4', 'Standard_DS14-4_v2', 'Standard_D64_v4', 'Standard_NC6s_v3', 'Standard_D64_v3', 'Standard_F72s_v2', 'Standard_E64d_v5', 'Standard_D4d_v5', 'Standard_E8d_v5', 'Standard_F16s', 'Standard_E20_v4', 'Standard_D8s_v4', 'Standard_E4-2s_v3', 'Standard_F4s', 'Standard_F8s', 'Standard_D8s_v5', 'Standard_D4s_v3', 'Standard_A2_v2', 'Standard_M8-4ms', 'Standard_F1', 'Standard_E64_v4', 'Standard_E8-4s_v4', 'Standard_D32d_v4', 'Standard_D2ds_v5', 'Standard_DS2_v2', 'Standard_D15_v2', 'Standard_E2_v4', 'Standard_M128ms', 'Standard_E2s_v4', 'Standard_D16s_v4', 'Standard_E48_v4', 'Standard_D48_v4', 'Standard_D2_v5', 'Standard_D4ds_v4', 'Standard_D12_v2', 'Standard_E64s_v3', 'Standard_D96d_v5', 'Standard_E20d_v5', 'Standard_D2_v2', 'Standard_DS12-1_v2', 'Standard_A1_v2', 'Standard_A4m_v2', 'Standard_E64-16s_v4', 'Standard_D8d_v5', 'Standard_D16_v4', 'Standard_D8ds_v4', 'Standard_F8', 'Standard_NV48s_v3', 'Standard_M128', 'Standard_M32ts', 'Standard_D32ds_v5', 'Standard_DS14_v2', 'Standard_NV12s_v3', 'Standard_D3_v2', 'Standard_D48ds_v4', 'Standard_M32s', 'Standard_E64-16ds_v4', 'Standard_M32-8ms', 'Standard_DS13_v2', 'Standard_E32-16s_v3', 'Standard_D64-32s_v3', 'Standard_NC24rs_v3', 'Standard_D4d_v4', 'Standard_D16s_v5', 'Standard_D4_v3', 'Standard_E8-2ds_v4', 'Standard_E32_v4', 'Standard_D4_v4', 'Standard_E2d_v5', 'Standard_E4-2s_v4', 'Standard_D5_v2', 'Standard_M16-4ms', 'Standard_M64m', 'Standard_E16_v5', 'Standard_DS13-4_v2', 'Standard_D32ds_v4', 'Standard_DS5_v2', 'Standard_D64_v5', 'Standard_D32s_v3', 'Standard_E32d_v4', 'Standard_NC12s_v3', 'Standard_E48s_v4', 'Standard_F48s_v2', 'Standard_D48d_v5', 'Standard_E4ds_v4', 'Standard_D4s_v4', 'Standard_D32_v4', 'Standard_E8_v4', 'Standard_E8ds_v4', 'Standard_DS14-8_v2', 'Standard_D48s_v5', 'Standard_E32-16ds_v4', 'Standard_E16s_v3', 'Standard_E4-2ds_v4', 'Standard_D64ds_v4', 'Standard_D64d_v4', 'Standard_E96d_v5', 'Standard_F1s', 'Standard_F4', 'Standard_E64s_v4', 'Standard_DS11_v2', 'Standard_E32ds_v4', 'Standard_E20s_v3', 'Standard_E16-8s_v4', 'Standard_D2_v3', 'Standard_E48d_v5', 'Standard_E4_v3', 'Standard_D48d_v4', 'Standard_E96_v5', 'Standard_D16ds_v5', 'Standard_D64s_v3', 'Standard_NC24s_v3', 'Standard_D15i_v2', 'Standard_M32ls', 'Standard_E2_v3', 'Standard_E64-16s_v3', 'Standard_E20ds_v4', 'Standard_D96ds_v5', 'Standard_E4d_v5', 'Standard_D48_v3', 'Standard_E16-4s_v4', 'Standard_D64ds_v5', 'Standard_D4_v2', 'Standard_DS15i_v2', 'Standard_D32s_v4', 'Standard_E8-2s_v3', 'Standard_F2s', 'Standard_D2d_v5', 'Standard_D8_v3', 'Standard_E16d_v4', 'Standard_E48d_v4', 'Standard_E20_v3', 'Standard_M128s', 'Standard_E48ds_v4', 'Standard_E64d_v4', 'Standard_E64-32s_v4', 'Standard_E8-4s_v3', 'Standard_M64ms', 'Standard_E2ds_v4', 'Standard_M64s', 'Standard_DS15_v2', 'Standard_E8_v3', 'Standard_E32d_v5', 'Standard_E4_v4', 'Standard_E4s_v4', 'Standard_E80is_v4', 'Standard_D8d_v4', 'Standard_E16ds_v4', 'Standard_E32-8s_v3', 'Standard_M128-64ms', 'Standard_D13_v2', 'Standard_NV24s_v3', 'Standard_E4d_v4', 'Standard_E20s_v4', 'Standard_E32s_v3', 'Standard_E2s_v3', 'Standard_D2d_v4', 'Standard_M64-32ms', 'Standard_D64d_v5', 'Standard_E4_v5', 'Standard_D8s_v3', 'Standard_E48_v5', 'Standard_M16-8ms', 'Standard_D2s_v3', 'Standard_D11_v2', 'Standard_E32_v5', 'Standard_M128-32ms', 'Standard_D32_v5', 'Standard_D96s_v5', 'Standard_DS13-2_v2', 'Standard_D48s_v4', 'Standard_E2d_v4', 'Standard_D32-8s_v3', 'Standard_D64-16s_v3', 'Standard_E32-8ds_v4', 'Standard_D14_v2', 'Standard_D48s_v3', 'Standard_M32-16ms', 'Standard_E8-2s_v4', 'Standard_E64is_v3', 'Standard_E16-8s_v3', 'Standard_D64s_v5', 'Standard_E16-4s_v3', 'Standard_M32ms', 'Standard_M64', 'Standard_DS12_v2', 'Standard_D32d_v5', 'Standard_DS3_v2', 'Standard_M64ls', 'Standard_E48s_v3', 'Standard_D1_v2', 'Standard_M8-2ms', 'Standard_F4s_v2', 'Standard_E8s_v4', 'Standard_E4s_v3', 'Standard_D16ds_v4', 'Standard_E80ids_v4', 'Standard_D8ds_v5', 'Standard_D32-16s_v3', 'Standard_D32_v3', 'Standard_E8d_v4', 'Standard_E32_v3', 'Standard_A8m_v2', 'Standard_D16_v3', 'Standard_D96_v5', 'Standard_E16-4ds_v4', 'Standard_E8-4ds_v4', 'Standard_E48_v3', 'Standard_D48_v5', 'Standard_D2s_v4', 'Standard_E16_v4', 'Standard_E20_v5', 'Standard_F16', 'Standard_M8ms', 'Standard_M16s', 'Standard_D2ds_v4', 'Standard_E32-8s_v4', 'Standard_DS12-2_v2', 'Standard_D16d_v5', 'Standard_D2s_v5', 'Standard_D16_v5', 'Standard_M16ms', 'Standard_DS11-1_v2', 'Standard_D4_v5', 'Standard_D32s_v5', 'Standard_D8_v4', 'Standard_F2', 'Standard_F8s_v2', 'Standard_D16d_v4', 'Standard_F32s_v2', 'Standard_E64i_v3', 'Standard_D8_v5', 'Standard_A8_v2', 'Standard_DS1_v2', 'Standard_D64s_v4', 'Standard_D48ds_v5', 'Standard_A2m_v2', 'Standard_E2_v5', 'Standard_A4_v2', 'Standard_F2s_v2', 'Standard_E8_v5', 'Standard_E64ds_v4', 'Standard_E16_v3', 'Standard_E64-32s_v3', 'Standard_E64_v5', 'Standard_M128m', 'Standard_DS4_v2'],
'germanywestcentral': ['Standard_DS2_v2', 'Standard_M192is_v2', 'Standard_NC4as_T4_v3', 'Standard_E4s_v4', 'Standard_M64s', 'Standard_M128-32ms', 'Standard_E32s_v3', 'Standard_D14_v2', 'Standard_E64s_v3', 'Standard_M416-208ms_v2', 'Standard_F1', 'Standard_F2s', 'Standard_M32ts', 'Standard_D2_v2', 'Standard_E64-32s_v4', 'Standard_D32d_v4', 'Standard_E8d_v4', 'Standard_D16s_v5', 'Standard_D4d_v5', 'Standard_E16-8ds_v4', 'Standard_D48d_v4', 'Standard_NC64as_T4_v3', 'Standard_F16s_v2', 'Standard_F64s_v2', 'Standard_M128dms_v2', 'Standard_M208-52s_v2', 'Standard_E64-32s_v3', 'Standard_E16_v4', 'Standard_DS15_v2', 'Standard_E8s_v4', 'Standard_M32ls', 'Standard_D16s_v3', 'Standard_D64-16s_v3', 'Standard_D15_v2', 'Standard_F8', 'Standard_M128s', 'Standard_E20_v5', 'Standard_E48ds_v4', 'Standard_DS12-1_v2', 'Standard_D64d_v4', 'Standard_D5_v2', 'Standard_E64_v5', 'Standard_E16s_v4', 'Standard_D11_v2', 'Standard_D48s_v4', 'Standard_E2_v4', 'Standard_DS15i_v2', 'Standard_E32_v3', 'Standard_D48_v3', 'Standard_M64dms_v2', 'Standard_DS11_v2', 'Standard_E64is_v3', 'Standard_D96s_v5', 'Standard_E96_v5', 'Standard_D32-16s_v3', 'Standard_E16d_v4', 'Standard_D32s_v4', 'Standard_F72s_v2', 'Standard_D64s_v4', 'Standard_M208ms_v2', 'Standard_F4s', 'Standard_D32ds_v4', 'Standard_E32_v5', 'Standard_E48_v5', 'Standard_D32d_v5', 'Standard_E32-8s_v3', 'Standard_F8s', 'Standard_E64_v4', 'Standard_E8-4ds_v4', 'Standard_D4_v3', 'Standard_F4s_v2', 'Standard_D4_v5', 'Standard_E8-2s_v4', 'Standard_E20_v3', 'Standard_D64_v4', 'Standard_E64d_v5', 'Standard_M64-16ms', 'Standard_M16ms', 'Standard_D48_v5', '', 'Standard_D8_v4', 'Standard_D64-32s_v3', 'Standard_D16_v3', 'Standard_E2_v3', 'Standard_E2_v5', 'Standard_DS11-1_v2', 'Standard_D64_v5', 'Standard_E32-16s_v3', 'Standard_F4', 'Standard_E8-4s_v4', 'Standard_E64_v3', 'Standard_D96d_v5', 'Standard_D16ds_v5', 'Standard_D32s_v5', 'Standard_M32-8ms', 'Standard_E2ds_v4', 'Standard_D16d_v5', 'Standard_M32ms_v2', 'Standard_M64-32ms', 'Standard_M64ms_v2', 'Standard_E4_v5', 'Standard_E8-2s_v3', 'Standard_D4d_v4', 'Standard_E8ds_v4', 'Standard_M64ms', 'Standard_D13_v2', 'Standard_D8ds_v5', 'Standard_D15i_v2', 'Standard_E16-4ds_v4', 'Standard_E4-2ds_v4', 'Standard_M128', 'Standard_E64-16ds_v4', 'Standard_D48ds_v5', 'Standard_M416ms_v2', 'Standard_D8_v5', 'Standard_D16_v5', 'Standard_D16_v4', 'Standard_E80is_v4', 'Standard_DS14-4_v2', 'Standard_D2_v3', 'Standard_D3_v2', 'Standard_E16s_v3', 'Standard_E2s_v3', 'Standard_E8-4s_v3', 'Standard_D8d_v4', 'Standard_DS12_v2', 'Standard_DS13_v2', 'Standard_E32s_v4', 'Standard_A4m_v2', 'Standard_M208-104ms_v2', 'Standard_D16s_v4', 'Standard_NC16as_T4_v3', 'Standard_D64s_v3', 'Standard_M64ds_v2', 'Standard_M128ms_v2', 'Standard_D2s_v4', 'Standard_M8ms', 'Standard_E2d_v5', 'Standard_D48s_v5', 'Standard_D4s_v4', 'Standard_D2d_v5', 'Standard_F16s', 'Standard_M32ms', 'Standard_E16-8s_v4', 'Standard_E20d_v5', 'Standard_E48d_v5', 'Standard_E32-16ds_v4', 'Standard_E48s_v4', 'Standard_M32-16ms', 'Standard_DS3_v2', 'Standard_E32ds_v4', 'Standard_E2d_v4', 'Standard_E64i_v3', 'Standard_E8_v4', 'Standard_DS1_v2', 'Standard_M128s_v2', 'Standard_D12_v2', 'Standard_E2s_v4', 'Standard_M32s', 'Standard_D4ds_v4', 'Standard_E64d_v4', 'Standard_D32_v3', 'Standard_E4-2s_v3', 'Standard_E4s_v3', 'Standard_D64s_v5', 'Standard_D4_v4', 'Standard_D2s_v5', 'Standard_E80ids_v4', 'Standard_D8s_v4', 'Standard_D16ds_v4', 'Standard_D32_v5', 'Standard_M64ls', 'Standard_A1_v2', 'Standard_M128m', 'Standard_E20ds_v4', 'Standard_M16-4ms', 'Standard_M128ds_v2', 'Standard_E32_v4', 'Standard_DS14-8_v2', 'Standard_D1_v2', 'Standard_D4_v2', 'Standard_M192ims_v2', 'Standard_D8ds_v4', 'Standard_E64-16s_v4', 'Standard_E16-4s_v3', 'Standard_E4d_v4', 'Standard_E16-4s_v4', 'Standard_A2_v2', 'Standard_M416s_v2', 'Standard_F32s_v2', 'Standard_E32d_v5', 'Standard_M8-4ms', 'Standard_E32-16s_v4', 'Standard_M416-208s_v2', 'Standard_F8s_v2', 'Standard_D2ds_v4', 'Standard_DS12-2_v2', 'Standard_E20s_v4', 'Standard_F1s', 'Standard_E64-16s_v3', 'Standard_D64ds_v5', 'Standard_M16s', 'Standard_M16-8ms', 'Standard_M32dms_v2', 'Standard_E16ds_v4', 'Standard_E48s_v3', 'Standard_F48s_v2', 'Standard_E20s_v3', 'Standard_D2_v5', 'Standard_E4ds_v4', 'Standard_F2', 'Standard_M64', 'Standard_D48s_v3', 'Standard_A4_v2', 'Standard_DS13-2_v2', 'Standard_M192ids_v2', 'Standard_F2s_v2', 'Standard_E16-8s_v3', 'Standard_D48_v4', 'Standard_E8-2ds_v4', 'Standard_D2s_v3', 'Standard_D32ds_v5', 'Standard_D96_v5', 'Standard_E4_v4', 'Standard_E32d_v4', 'Standard_D32s_v3', 'Standard_D8_v3', 'Standard_E64s_v4', 'Standard_M416-104ms_v2', 'Standard_E48d_v4', 'Standard_D16d_v4', 'Standard_E48_v4', 'Standard_A2m_v2', 'Standard_E64-32ds_v4', 'Standard_D48ds_v4', 'Standard_D4s_v3', 'Standard_E16d_v5', 'Standard_E20_v4', 'Standard_D32_v4', 'Standard_D4ds_v5', 'Standard_DS14_v2', 'Standard_E4d_v5', 'Standard_D4s_v5', 'Standard_D48d_v5', 'Standard_M128ms', 'Standard_M208-104s_v2', 'Standard_DS13-4_v2', 'Standard_M208s_v2', 'Standard_D2_v4', 'Standard_M8-2ms', 'Standard_D2d_v4', 'Standard_E16_v5', 'Standard_M416-104s_v2', 'Standard_E48_v3', 'Standard_M416is_v2', 'Standard_E32-8s_v4', 'Standard_D64_v3', 'Standard_A8m_v2', 'Standard_D64d_v5', 'Standard_E16_v3', 'Standard_NC8as_T4_v3', 'Standard_D64ds_v4', 'Standard_E4-2s_v4', 'Standard_E20d_v4', 'Standard_E64ds_v4', 'Standard_D2ds_v5', 'Standard_DS5_v2', 'Standard_E4_v3', 'Standard_DS4_v2', 'Standard_M192idms_v2', 'Standard_E8_v3', 'Standard_D8s_v5', 'Standard_M64m', 'Standard_D8s_v3', 'Standard_D8d_v5', 'Standard_E8s_v3', 'Standard_E8_v5', 'Standard_F16', 'Standard_M208-52ms_v2', 'Standard_D32-8s_v3', 'Standard_M128-64ms', 'Standard_E32-8ds_v4', 'Standard_E96d_v5', 'Standard_D96ds_v5', 'Standard_M64s_v2', 'Standard_E8d_v5', 'Standard_A8_v2'],
'norwayeast': ['Standard_DS12-2_v2', 'Standard_D96ds_v5', 'Standard_D48s_v3', 'Standard_E4_v4', 'Standard_D96d_v5', 'Standard_E48s_v4', 'Standard_E64_v5', '', 'Standard_E64d_v4', 'Standard_E4s_v4', 'Standard_DS3_v2', 'Standard_E2d_v5', 'Standard_E64-16s_v4', 'Standard_E64s_v4', 'Standard_D8d_v4', 'Standard_D32d_v4', 'Standard_D16s_v5', 'Standard_M128ds_v2', 'Standard_DS14-8_v2', 'Standard_D4_v2', 'Standard_E8_v5', 'Standard_E2_v4', 'Standard_M64m', 'Standard_E32-8s_v3', 'Standard_D16ds_v5', 'Standard_E32-8ds_v4', 'Standard_E48_v5', 'Standard_D2_v5', 'Standard_M32ts', 'Standard_D48ds_v5', 'Standard_E4ds_v4', 'Standard_E64is_v3', 'Standard_E32d_v5', 'Standard_F64s_v2', 'Standard_D13_v2', 'Standard_M192idms_v2', 'Standard_F2s_v2', 'Standard_D8_v5', 'Standard_D32s_v5', 'Standard_M8-4ms', 'Standard_E64ds_v4', 'Standard_D48_v4', 'Standard_D16_v3', 'Standard_E8-2s_v3', 'Standard_M64s_v2', 'Standard_D48_v5', 'Standard_A2_v2', 'Standard_D4d_v5', 'Standard_E64i_v3', 'Standard_E80ids_v4', 'Standard_D15i_v2', 'Standard_E20s_v4', 'Standard_D4s_v3', 'Standard_D64_v4', 'Standard_A2m_v2', 'Standard_D4ds_v4', 'Standard_E16-8ds_v4', 'Standard_D48_v3', 'Standard_DS1_v2', 'Standard_DS13-2_v2', 'Standard_E8-2ds_v4', 'Standard_F32s_v2', 'Standard_D64d_v4', 'Standard_E48d_v5', 'Standard_D1_v2', 'Standard_E64_v4', 'Standard_E80is_v4', 'Standard_E96d_v5', 'Standard_E16s_v4', 'Standard_E64-16ds_v4', 'Standard_D32-8s_v3', 'Standard_D64_v5', 'Standard_M192ids_v2', 'Standard_M128s', 'Standard_D2_v2', 'Standard_E4s_v3', 'Standard_E4-2ds_v4', 'Standard_E4d_v4', 'Standard_D8_v3', 'Standard_D4_v3', 'Standard_E48d_v4', 'Standard_F1s', 'Standard_E32_v5', 'Standard_DS5_v2', 'Standard_F2', 'Standard_D48d_v5', 'Standard_M64dms_v2', 'Standard_D2s_v5', 'Standard_D64s_v5', 'Standard_D48s_v5', 'Standard_M8-2ms', 'Standard_E8s_v3', 'Standard_E16_v4', 'Standard_NV24s_v3', 'Standard_M16s', 'Standard_D48s_v4', 'Standard_E64-32ds_v4', 'Standard_M32-8ms', 'Standard_M16-8ms', 'Standard_M16ms', 'Standard_DS4_v2', 'Standard_D64s_v4', 'Standard_E4-2s_v4', 'Standard_D8s_v5', 'Standard_E32d_v4', 'Standard_F72s_v2', 'Standard_D2ds_v5', 'Standard_M64ds_v2', 'Standard_E64-16s_v3', 'Standard_E16ds_v4', 'Standard_E2ds_v4', 'Standard_E32-16s_v3', 'Standard_D4s_v4', 'Standard_F4s_v2', 'Standard_E64_v3', 'Standard_E20d_v5', 'Standard_E32_v3', 'Standard_E16_v5', 'Standard_D16d_v4', 'Standard_M32ms_v2', 'Standard_M32ms', 'Standard_E2_v5', 'Standard_D2s_v4', 'Standard_A8m_v2', 'Standard_E32s_v3', 'Standard_E32-16ds_v4', 'Standard_DS13-4_v2', 'Standard_E64-32s_v4', 'Standard_F8s', 'Standard_F8', 'Standard_D2d_v5', 'Standard_D11_v2', 'Standard_M128ms_v2', 'Standard_D64-32s_v3', 'Standard_M128dms_v2', 'Standard_M128-32ms', 'Standard_E16-4s_v3', 'Standard_D2d_v4', 'Standard_DS15_v2', 'Standard_F16', 'Standard_M128-64ms', 'Standard_F1', 'Standard_E16-8s_v4', 'Standard_D8ds_v5', 'Standard_E96_v5', 'Standard_E16_v3', 'Standard_M192is_v2', 'Standard_M128s_v2', 'Standard_F16s_v2', 'Standard_E8d_v5', 'Standard_D48d_v4', 'Standard_M32-16ms', 'Standard_M192ims_v2', 'Standard_M8ms', 'Standard_DS13_v2', 'Standard_E4d_v5', 'Standard_D4s_v5', 'Standard_D32s_v3', 'Standard_DS12-1_v2', 'Standard_E20d_v4', 'Standard_D64ds_v4', 'Standard_D2s_v3', 'Standard_E64d_v5', 'Standard_D32d_v5', 'Standard_E64s_v3', 'Standard_D64d_v5', 'Standard_E8-4s_v4', 'Standard_M64ms_v2', 'Standard_M64-16ms', 'Standard_E2_v3', 'Standard_E16-8s_v3', 'Standard_M64ls', 'Standard_DS14-4_v2', 'Standard_M16-4ms', 'Standard_M32ls', 'Standard_E20_v4', 'Standard_D48ds_v4', 'Standard_D3_v2', 'Standard_DS15i_v2', 'Standard_E20ds_v4', 'Standard_D64s_v3', 'Standard_E20_v3', 'Standard_D8ds_v4', 'Standard_D8s_v3', 'Standard_M128', 'Standard_F48s_v2', 'Standard_D16s_v3', 'Standard_DS14_v2', 'Standard_D32_v3', 'Standard_E48ds_v4', 'Standard_E16-4s_v4', 'Standard_E8_v3', 'Standard_E32-16s_v4', 'Standard_D4ds_v5', 'Standard_E48s_v3', 'Standard_D32ds_v5', 'Standard_A4m_v2', 'Standard_E8d_v4', 'Standard_D32_v5', 'Standard_NV12s_v3', 'Standard_M128ms', 'Standard_M64', 'Standard_E64-32s_v3', 'Standard_D32ds_v4', 'Standard_E4_v5', 'Standard_M64-32ms', 'Standard_A4_v2', 'Standard_D5_v2', 'Standard_E32s_v4', 'Standard_E8ds_v4', 'Standard_E2s_v3', 'Standard_E4_v3', 'Standard_E48_v4', 'Standard_M32dms_v2', 'Standard_E20s_v3', 'Standard_DS2_v2', 'Standard_D96_v5', 'Standard_E8-2s_v4', 'Standard_D96s_v5', 'Standard_D2_v4', 'Standard_A1_v2', 'Standard_D2ds_v4', 'Standard_E8-4s_v3', 'Standard_D64-16s_v3', 'Standard_E20_v5', 'Standard_F4s', 'Standard_M32s', 'Standard_D16s_v4', 'Standard_DS11-1_v2', 'Standard_E16s_v3', 'Standard_E8s_v4', 'Standard_E2s_v4', 'Standard_D32s_v4', 'Standard_D64ds_v5', 'Standard_E16d_v4', 'Standard_M64s', 'Standard_M64ms', 'Standard_E8_v4', 'Standard_D16d_v5', 'Standard_D2_v3', 'Standard_D16_v5', 'Standard_D32_v4', 'Standard_E48_v3', 'Standard_D16_v4', 'Standard_E4-2s_v3', 'Standard_D16ds_v4', 'Standard_D8_v4', 'Standard_M128m', 'Standard_D4d_v4', 'Standard_E16-4ds_v4', 'Standard_F4', 'Standard_F2s', 'Standard_D4_v5', 'Standard_E8-4ds_v4', 'Standard_D8d_v5', 'Standard_DS12_v2', 'Standard_D32-16s_v3', 'Standard_F8s_v2', 'Standard_E16d_v5', 'Standard_F16s', 'Standard_D4_v4', 'Standard_E32-8s_v4', 'Standard_E32ds_v4', 'Standard_NV48s_v3', 'Standard_E32_v4', 'Standard_DS11_v2', 'Standard_A8_v2', 'Standard_D64_v3', 'Standard_D8s_v4', 'Standard_E2d_v4', 'Standard_D15_v2', 'Standard_D12_v2', 'Standard_D14_v2'],
'westus3': ['Standard_M416-208s_v2', 'Standard_E64-16s_v3', 'Standard_D4d_v4', 'Standard_E8-4s_v3', 'Standard_D32-16s_v3', 'Standard_M64-32ms', 'Standard_E4-2s_v3', 'Standard_D4', 'Standard_D16s_v5', 'Standard_D48_v4', 'Standard_D64s_v4', 'Standard_E48_v4', 'Standard_DS14', 'Standard_A2m_v2', 'Standard_D4_v3', 'Standard_E32s_v3', 'Standard_E64d_v4', 'Standard_DS5_v2', 'Standard_D32s_v4', 'Standard_F16s_v2', 'Standard_E64is_v3', 'Standard_F16s', 'Standard_D48d_v4', 'Standard_E4s_v4', 'Standard_M416-104s_v2', 'Standard_NC12s_v3', 'Standard_F64s_v2', 'Standard_D2s_v3', 'Standard_D14', 'Standard_D8ds_v4', 'Standard_DS1_v2', 'Standard_D32_v4', 'Standard_M128-32ms', 'Standard_DS13', 'Standard_E16-4ds_v4', 'Standard_D8_v3', 'Standard_F2s_v2', 'Standard_D48s_v3', 'Standard_D32d_v4', 'Standard_DS14-4_v2', 'Standard_D13', 'Standard_F4s', 'Standard_D1_v2', 'Standard_D64s_v5', 'Standard_DS15_v2', 'Standard_E8_v4', 'Standard_E32-16s_v4', 'Standard_E20_v4', 'Standard_E16ds_v4', 'Standard_NC6s_v3', 'Standard_A4m_v2', 'Standard_D64-32s_v3', 'Standard_DS12', 'Standard_M64-16ms', 'Standard_E48_v3', 'Standard_E32-8s_v3', 'Standard_D11', 'Standard_E2_v3', 'Standard_NC24s_v3', 'Standard_E16_v4', 'Standard_E2s_v3', 'Standard_F1s', 'Standard_DS4_v2', 'Standard_D16_v3', 'Standard_M208-104s_v2', 'Standard_F1', 'Standard_E64_v4', 'Standard_E8-4s_v4', 'Standard_E16s_v3', 'Standard_D4_v4', 'Standard_E64-16s_v4', 'Standard_D15i_v2', 'Standard_F32s_v2', 'Standard_D64s_v3', 'Standard_DS14_v2', 'Standard_M128', 'Standard_E64s_v3', 'Standard_E20d_v4', 'Standard_E4d_v4', 'Standard_D16ds_v4', 'Standard_E80ids_v4', 'Standard_M32ls', 'Standard_A1_v2', 'Standard_E8s_v3', 'Standard_F4s_v2', 'Standard_D32s_v5', 'Standard_M416is_v2', 'Standard_M32-16ms', 'Standard_A4_v2', 'Standard_D8_v4', 'Standard_DS11-1_v2', 'Standard_D4s_v3', 'Standard_E32-16s_v3', 'Standard_F4', 'Standard_M64s', 'Standard_E32_v3', 'Standard_D2', 'Standard_E64-32ds_v4', 'Standard_E64i_v3', 'Standard_D32ds_v4', 'Standard_E4_v3', 'Standard_D16d_v4', 'Standard_DS14-8_v2', 'Standard_A2_v2', 'Standard_D2s_v4', 'Standard_A8_v2', 'Standard_M128-64ms', 'Standard_E32s_v4', 'Standard_E20s_v4', 'Standard_F8s_v2', 'Standard_DS3', 'Standard_M208-52ms_v2', 'Standard_E32-16ds_v4', 'Standard_E20s_v3', 'Standard_E20_v3', 'Standard_ND96asr_A100_v4', 'Standard_NC24rs_v3', 'Standard_E80is_v4', 'Standard_E8d_v4', 'Standard_D3', 'Standard_M8-2ms', 'Standard_M208s_v2', 'Standard_DS13-2_v2', 'Standard_M128s', 'Standard_E16-4s_v3', 'Standard_D4s_v4', 'Standard_E16s_v4', 'Standard_E2_v4', 'Standard_D32-8s_v3', 'Standard_E64_v3', 'Standard_D15_v2', 'Standard_D2_v3', 'Standard_M208-52s_v2', 'Standard_E4s_v3', 'Standard_D2s_v5', 'Standard_D16s_v3', 'Standard_F72s_v2', 'Standard_D2d_v4', 'Standard_E4-2ds_v4', 'Standard_E4_v4', 'Standard_D48s_v5', 'Standard_F8', 'Standard_M64ls', 'Standard_DS2_v2', 'Standard_DS1', 'Standard_D2ds_v4', 'Standard_M128ms', 'Standard_M208-104ms_v2', 'Standard_D32s_v3', 'Standard_D16s_v4', 'Standard_D16_v4', 'Standard_E64s_v4', 'Standard_E48ds_v4', 'Standard_M16-4ms', 'Standard_E32-8ds_v4', 'Standard_E4-2s_v4', 'Standard_E2ds_v4', 'Standard_D1', 'Standard_D4_v2', 'Standard_E8-2s_v3', 'Standard_E8s_v4', 'Standard_D4s_v5', 'Standard_M16-8ms', 'Standard_D48ds_v4', 'Standard_M16s', 'Standard_D64d_v4', 'Standard_E16-8s_v4', 'Standard_D5_v2', 'Standard_DS2', 'Standard_D11_v2', 'Standard_A8m_v2', 'Standard_D96s_v5', 'Standard_M32ts', 'Standard_DS4', 'Standard_M416-208ms_v2', 'Standard_E8-2ds_v4', 'Standard_DS11_v2', 'Standard_E64-16ds_v4', 'Standard_E8-2s_v4', 'Standard_E32_v4', 'Standard_DS13_v2', 'Standard_M32ms', 'Standard_DS13-4_v2', 'Standard_D64ds_v4', 'Standard_E32-8s_v4', 'Standard_D48_v3', 'Standard_DS15i_v2', 'Standard_M8-4ms', 'Standard_E8ds_v4', 'Standard_DS12_v2', 'Standard_D4ds_v4', 'Standard_E64-32s_v3', 'Standard_D8s_v4', 'Standard_F8s', 'Standard_F2s', 'Standard_D32_v3', 'Standard_E16-8s_v3', 'Standard_D12', 'Standard_M416-104ms_v2', 'Standard_M416s_v2', 'Standard_D3_v2', 'Standard_E16_v3', 'Standard_E4ds_v4', 'Standard_M416ms_v2', 'Standard_E48s_v3', 'Standard_E2d_v4', 'Standard_M64ms', 'Standard_M8ms', 'Standard_E48s_v4', 'Standard_DS11', 'Standard_DS3_v2', 'Standard_E2s_v4', 'Standard_DS12-1_v2', 'Standard_E8-4ds_v4', 'Standard_F2', 'Standard_D8s_v5', 'Standard_E8_v3', 'Standard_D2_v2', 'Standard_E16-4s_v4', 'Standard_D48s_v4', 'Standard_E64ds_v4', 'Standard_D12_v2', 'Standard_D2_v4', 'Standard_M208ms_v2', 'Standard_D64_v4', 'Standard_E32d_v4', 'Standard_F48s_v2', 'Standard_M32-8ms', 'Standard_M32s', 'Standard_M16ms', 'Standard_D13_v2', 'Standard_E20ds_v4', 'Standard_E16-8ds_v4', 'Standard_M64m', 'Standard_D8s_v3', 'Standard_F16', 'Standard_M64', 'Standard_D64-16s_v3', 'Standard_E32ds_v4', 'Standard_D64_v3', 'Standard_DS12-2_v2', 'Standard_E48d_v4', 'Standard_E16d_v4', 'Standard_E64-32s_v4', 'Standard_D8d_v4', 'Standard_D14_v2', 'Standard_M128m'],
'australiacentral2': ['Standard_M416-104s_v2', 'Standard_M128ms', 'Standard_D4s_v4', 'Standard_F1s', 'Standard_E4-2s_v4', 'Standard_E32_v3', 'Standard_A4m_v2', 'Standard_D2s_v3', 'Standard_D8ds_v5', 'Standard_E64-32s_v4', 'Standard_E32-16s_v4', 'Standard_M128-64ms', 'Standard_E4_v4', 'Standard_M64s', 'Standard_D16_v4', 'Standard_D2d_v4', 'Standard_E32-8s_v4', 'Standard_E16-4ds_v4', 'Standard_D8d_v4', 'Standard_DS12-2_v2', 'Standard_E20_v3', 'Standard_D4ds_v4', 'Standard_F48s_v2', 'Standard_F16', 'Standard_F16s', 'Standard_DS14-8_v2', 'Standard_D2_v4', 'Standard_A5', 'Standard_M128', 'Standard_M128-32ms', 'Standard_E48d_v4', 'Standard_F8s_v2', 'Standard_M32s', 'Standard_A8m_v2', 'Standard_E16_v5', 'Standard_D11_v2', 'Standard_D64d_v4', 'Standard_D2ds_v4', 'Standard_D48ds_v5', 'Standard_A1', 'Standard_D14_v2', 'Standard_D8_v5', 'Standard_E2d_v5', 'Standard_D32_v5', 'Standard_D2s_v4', 'Standard_M64ms', 'Standard_E8-4ds_v4', 'Standard_M16ms', 'Standard_E8d_v4', 'Standard_E8-4s_v3', 'Standard_D32-16s_v3', 'Standard_D48ds_v4', 'Standard_E32d_v4', 'Standard_E8ds_v4', 'Standard_E16s_v3', 'Standard_D1_v2', 'Standard_E64_v5', 'Standard_M8-4ms', 'Standard_M208-52ms_v2', 'Standard_D96ds_v5', 'Standard_E48_v3', 'Standard_F72s_v2', 'Standard_E2ds_v4', 'Standard_E2_v4', 'Standard_D4_v5', 'Standard_E48ds_v4', 'Standard_D64d_v5', 'Standard_E32-8s_v3', 'Standard_E32_v5', 'Standard_D64_v4', 'Standard_D15_v2', 'Standard_D4s_v5', 'Standard_E32s_v3', 'Basic_A1', 'Standard_D48d_v5', 'Standard_E64d_v4', 'Standard_A2m_v2', 'Standard_M208-104ms_v2', 'Standard_F4s', 'Standard_D8_v3', 'Standard_E16_v3', 'Standard_DS11-1_v2', 'Standard_DS15i_v2', 'Standard_D4ds_v5', 'Standard_E64s_v4', 'Standard_D16ds_v4', 'Standard_E48_v4', 'Standard_E16-4s_v3', 'Standard_D16d_v4', 'Standard_E64_v3', 'Standard_D4_v4', 'Standard_A8_v2', 'Standard_E8s_v3', 'Standard_DS11_v2', 'Standard_D8s_v3', 'Standard_D4_v3', 'Standard_M416s_v2', 'Standard_E20s_v4', 'Standard_D2_v5', 'Standard_D64ds_v5', 'Standard_D16s_v4', 'Standard_D32-8s_v3', 'Standard_F32s_v2', 'Standard_E32s_v4', 'Standard_E4_v3', 'Standard_E4ds_v4', 'Standard_D4_v2', 'Standard_F4s_v2', 'Standard_DS4_v2', 'Standard_A3', 'Standard_D64_v3', 'Standard_M32ls', 'Standard_E2s_v4', 'Standard_D13_v2', 'Standard_D32d_v5', 'Standard_M416ms_v2', 'Standard_DS14-4_v2', 'Standard_E32_v4', 'Standard_A0', 'Standard_E2d_v4', 'Standard_D2s_v5', 'Standard_D8d_v5', 'Standard_E20ds_v4', 'Standard_A2', 'Standard_DS1_v2', 'Standard_M64-32ms', 'Standard_E96d_v5', 'Standard_E16-4s_v4', 'Standard_M8ms', 'Standard_D64-32s_v3', 'Standard_D48_v4', 'Standard_E64-32s_v3', 'Standard_D64-16s_v3', 'Standard_M32-16ms', 'Standard_DS13_v2', '', 'Standard_M32ts', 'Standard_D64s_v4', 'Standard_D4d_v4', 'Standard_E4s_v4', 'Standard_DS13-4_v2', 'Standard_M64ls', 'Standard_E16-8s_v3', 'Standard_D2_v3', 'Standard_F8s', 'Standard_D48d_v4', 'Standard_D5_v2', 'Standard_D3_v2', 'Standard_D48s_v5', 'Standard_E4-2ds_v4', 'Standard_F64s_v2', 'Standard_E64-32ds_v4', 'Standard_M32ms', 'Standard_M32-8ms', 'Standard_D2_v2', 'Standard_D15i_v2', 'Standard_D64s_v5', 'Standard_E48_v5', 'Standard_E80is_v4', 'Standard_E8-2s_v4', 'Standard_DS14_v2', 'Standard_E96_v5', 'Standard_E48s_v3', 'Standard_M208ms_v2', 'Standard_E20_v4', 'Standard_D48s_v3', 'Standard_E20d_v4', 'Standard_D8s_v5', 'Standard_E2_v5', 'Standard_DS5_v2', 'Standard_E48s_v4', 'Standard_E2s_v3', 'Standard_D48_v5', 'Standard_D96d_v5', 'Standard_E4-2s_v3', 'Standard_D12_v2', 'Standard_E8_v4', 'Standard_M416-208s_v2', 'Standard_M8-2ms', 'Standard_E16ds_v4', 'Standard_E8_v5', 'Standard_M64m', 'Standard_E16d_v5', 'Standard_DS2_v2', 'Standard_D16ds_v5', 'Standard_A2_v2', 'Standard_E8-2s_v3', 'Standard_D48_v3', 'Standard_E64s_v3', 'Standard_A4_v2', 'Standard_D32_v4', 'Standard_E48d_v5', 'Standard_D32s_v3', 'Standard_D64ds_v4', 'Standard_E4d_v5', 'Standard_M128s', 'Standard_F2s', 'Standard_E16_v4', 'Standard_D64s_v3', 'Standard_DS12_v2', 'Standard_D96s_v5', 'Standard_D8s_v4', 'Standard_E16-8ds_v4', 'Standard_E64-16s_v3', 'Standard_E16d_v4', 'Standard_F1', 'Standard_DS3_v2', 'Standard_DS13-2_v2', 'Standard_D4s_v3', 'Standard_D32ds_v5', 'Standard_E8d_v5', 'Standard_M208s_v2', 'Standard_E32ds_v4', 'Standard_E64d_v5', 'Standard_F8', 'Standard_DS12-1_v2', 'Basic_A2', 'Basic_A4', 'Standard_E8-2ds_v4', 'Standard_D16d_v5', 'Standard_M416-104ms_v2', 'Standard_E8s_v4', 'Basic_A0', 'Standard_M208-104s_v2', 'Standard_E32-16s_v3', 'Standard_E64-16s_v4', 'Standard_A1_v2', 'Standard_M16-4ms', 'Standard_D2ds_v5', 'Standard_E64_v4', 'Standard_F2s_v2', 'Standard_M64', 'Standard_M16s', 'Standard_F2', 'Standard_E32-8ds_v4', 'Standard_D2d_v5', 'Standard_D96_v5', 'Standard_E16-8s_v4', 'Standard_A4', 'Standard_E20d_v5', 'Standard_M16-8ms', 'Standard_E8_v3', 'Standard_E64-16ds_v4', 'Standard_E2_v3', 'Standard_D16_v5', 'Standard_D48s_v4', 'Standard_E16s_v4', 'Standard_D16_v3', 'Standard_D16s_v5', 'Standard_D32s_v4', 'Standard_M64-16ms', 'Standard_A7', 'Standard_D32ds_v4', 'Standard_E4d_v4', 'Standard_D8_v4', 'Standard_M208-52s_v2', 'Standard_M128m', 'Standard_F16s_v2', 'Standard_A6', 'Standard_E32-16ds_v4', 'Standard_E32d_v5', 'Standard_D32_v3', 'Standard_M416is_v2', 'Standard_D16s_v3', 'Standard_E20_v5', 'Standard_D32s_v5', 'Standard_D8ds_v4', 'Standard_DS15_v2', 'Basic_A3', 'Standard_D64_v5', 'Standard_E64ds_v4', 'Standard_F4', 'Standard_E80ids_v4', 'Standard_E20s_v3', 'Standard_E8-4s_v4', 'Standard_E4_v5', 'Standard_E4s_v3', 'Standard_M416-208ms_v2', 'Standard_D32d_v4', 'Standard_D4d_v5']
}
region_codes = [
'eastus',
'westus',
'japaneast',
'southindia',
'centralindia',
'ukwest',
'germanywestcentral',
'eastasia',
'brazilsouth',
'canadacentral',
'australiaeast',
'australiacentral'
]
sizes = [
"Standard_D2s_v3", # 4 vCPU, 32 Gb Ram
"Standard_A8_v2", # 8 vCPU, 16 Gb Ram
"Standard_NC8as_T4_v3", # 8 56 GiB"
"Standard_NV6s_v2",
"Standard_H8m",
"Standard_D4a_v4", # 4 16 GiB 100 GiB
"Standard_D8a_v4", # 8 32 GiB 200 GiB
"Standard_D4as_v4", # 4 16 GiB 32 GiB
"Standard_D8as_v4", # 8 32 GiB 64 GiB
"Standard_D8ds_v5", # 8 32 GiB 300 GiB
"Standard_D2_v3", # 2 8 GiB 50 GiB
"Standard_D4_v3", # 4 16 GiB 100 GiB
"Standard_D8_v3", # 8 32 GiB 200 GiB
"Standard_DS3_v2", # 4 14 GiB 28 GiB
"Standard_F4s_v2", # 4 8 GiB 32 GiB
"Standard_F8s_v2", # 8 16 GiB 64 GiB
"Standard_F4", # 4 8 GiB 64 GiB
"Standard_F8", # 8 16 GiB 128 GiB
"Standard_E4ds_v5", # 4 32 GiB 150 GiB
"Standard_E8ds_v5", # 8 64 GiB 300 GiB
"Standard_E2s_v3", # 2 16 GiB 32 GiB
"Standard_E4s_v3", # 4 32 GiB 64 GiB
"Standard_E8s_v3", # 8 64 GiB 128 GiB
"Standard_NC6s_v3", # 6 56 GiB 340 GiB
"Standard_NC12s_v3", # 12 112 GiB 680 GiB
"Standard_NC4as_T4_v3", # 4 28 GiB 180 GiB"
"Standard_NV12s_v2",
"Standard_H8",
"Standard_H16"
]
resource_names = [resource_prefix + location for location in region_codes] | 237,639 | 124,283 |
"""
utilities
----------
Common utilities for use within ``netrd``.
"""
from .threshold import threshold
from .graph import (
create_graph,
ensure_undirected,
undirected,
ensure_unweighted,
unweighted,
)
from .read import read_time_series
from .cluster import clusterGraph
from .standardize import mean_GNP_distance
from .entropy import (
js_divergence,
entropy_from_seq,
joint_entropy,
conditional_entropy,
categorized_data,
linear_bins,
)
__all__ = [
'threshold',
'clusterGraph',
'js_divergence',
'entropy_from_seq',
'joint_entropy',
'conditional_entropy',
'categorized_data',
'linear_bins',
'create_graph',
'undirected',
'ensure_undirected',
'unweighted',
'ensure_unweighted',
'read_time_series',
'mean_GNP_distance',
]
| 830 | 288 |
class Solution:
def findBall(self, grid: List[List[int]]) -> List[int]:
m, n = len(grid), len(grid[0])
fall = list(range(n))
for i in range(m):
next_fall = [-1 for _ in range(n)]
for j in range(n):
if grid[i][j] == 1:
if j > 0 and grid[i][j-1] == 1:
next_fall[j] = fall[j-1]
else:
if j + 1 < n and grid[i][j+1] == -1:
next_fall[j] = fall[j+1]
fall = next_fall
res = [-1 for _ in range(n)]
for j, ball in enumerate(fall):
if ball != -1:
res[ball] = j
return res
| 697 | 230 |
from .base import Column
from .util import get_inner_spec, get_inner_columns
class TupleColumn(Column):
py_types = (list, tuple)
def __init__(self, nested_columns, **kwargs):
self.nested_columns = nested_columns
super(TupleColumn, self).__init__(**kwargs)
def write_data(self, items, buf):
items = list(zip(*items))
for i, x in enumerate(self.nested_columns):
x.write_data(list(items[i]), buf)
def write_items(self, items, buf):
return self.write_data(items, buf)
def read_data(self, n_items, buf):
rv = [x.read_data(n_items, buf) for x in self.nested_columns]
return list(zip(*rv))
def read_items(self, n_items, buf):
return self.read_data(n_items, buf)
def create_tuple_column(spec, column_by_spec_getter):
inner_spec = get_inner_spec('Tuple', spec)
columns = get_inner_columns(inner_spec)
return TupleColumn([column_by_spec_getter(x) for x in columns])
| 980 | 331 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import sys
import tensorflow as tf
from dataset import load_data
from vae import VAE
from conv_vae import ConvVAE
IMAGE_SIZE = 28
IMAGE_PIXELS = IMAGE_SIZE * IMAGE_SIZE
# Define the VAE network architecture
def network_architecture(vae_type, latent_dim):
if vae_type == 'conv':
network_architecture = \
{'n_input': 1, # Number of input channels
'kernel_outer': 5, # Convolution kernel sizes for outer layers
'kernel_inner': 3, # Convolution kernel sizes for inner layers
'n_filters_1': 64, # Number of output convolution filters at layer 1
'n_filters_2': 64, # Number of output convolution filters at layer 2
'n_filters_3': 64, # Number of output convolution filters at layer 3
'n_filters_4': 64, # Number of output convolution filters at layer 4
'n_hidden': 500, # Dimensionality of intermediate layer
'n_z': latent_dim} # Dimensionality of latent space
else:
network_architecture = \
{'n_input': IMAGE_PIXELS, # MNIST data input
'n_hidden_1': 500, # Dimensionality of hidden layer 1
'n_hidden_2': 500, # Dimensionality of hidden layer 2
'n_z': latent_dim} # Dimensionality of latent space
return network_architecture
def main(_):
model_path = 'models/' + FLAGS.name
data = load_data(FLAGS.dataset, one_hot=True, validation_size=10000)
# Define and instantiate VAE model
if FLAGS.vae_type == 'vae':
vae = VAE(network_architecture=network_architecture(FLAGS.vae_type, FLAGS.latent_dim), batch_size=FLAGS.batch_size, learn_rate=FLAGS.learn_rate)
elif FLAGS.vae_type == 'conv':
vae = ConvVAE(network_architecture=network_architecture(FLAGS.vae_type, FLAGS.latent_dim), batch_size=FLAGS.batch_size, learn_rate=FLAGS.learn_rate)
else:
raise ValueError("Autoencoder type should be either conv or vae. Received: {}.".format(FLAGS.vae_type))
# Wish to allocate approximately gpu_memory_frac% of GPU memory
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=FLAGS.gpu_memory_frac)
with tf.device('/gpu:%d' % FLAGS.gpu_device):
sess = tf.Session(config=tf.ConfigProto(log_device_placement=FLAGS.log_device_placement, gpu_options=gpu_options))
tf.set_random_seed(FLAGS.seed)
# Initialise tf variables
init = tf.global_variables_initializer()
# Launch session
sess.run(init)
num_samples = data.train.num_examples
### Training cycle ###
for epoch in range(FLAGS.n_epochs):
avg_cost = 0.
avg_recon = 0.
avg_latent = 0.
total_batch = int(num_samples / FLAGS.batch_size)
# Loop over all batches
for i in range(total_batch):
batch_xs, _ = data.train.next_batch(FLAGS.batch_size)
# Fit training using batch data
if FLAGS.vae_type == 'conv':
cost, recon, latent = vae.partial_fit(sess, batch_xs, FLAGS.keep_prob)
else:
cost, recon, latent = vae.partial_fit(sess, batch_xs)
# Compute average losses
avg_cost += (cost / num_samples) * FLAGS.batch_size
avg_recon += (recon / num_samples) * FLAGS.batch_size
avg_latent += (latent / num_samples) * FLAGS.batch_size
# Display logs per epoch step
if epoch % FLAGS.display_step == 0:
print("Epoch: %04d / %04d, Cost= %04f, Recon= %04f, Latent= %04f" % \
(epoch, FLAGS.n_epochs, avg_cost, avg_recon, avg_latent))
# Create a saver object that will store all the parameter variables
saver = tf.train.Saver()
saver.save(sess, model_path)
print("Model saved as: %s" % model_path)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--name', type=str, default='digit_model_all', help='Name of model to train')
parser.add_argument('--seed', type=int, default='0', help='Sets the random seed for both numpy and tf')
parser.add_argument('--dataset', type=str, default='mnist', help='Name of dataset to load')
parser.add_argument('--vae_type', type=str, default='vae', help='Either a standard VAE (vae) or a convolutational VAE (conv)')
parser.add_argument('--batch_size', type=int, default='100', help='Sets the batch size')
parser.add_argument('--learn_rate', type=float, default='1e-5', help='Sets the learning rate')
parser.add_argument('--n_epochs', type=int, default='50', help='Number of training epochs')
parser.add_argument('--latent_dim', type=int, default='2', help='Latent dimensionality of the VAE')
parser.add_argument('--keep_prob', type=float, default='1.0', help='Sets the dropout rate')
parser.add_argument('--gpu_device', type=int, default=0, help='Specifying which GPU device to use')
parser.add_argument('--log_device_placement', type=bool, default=False, help='Logs the devices that operations and tensors are assigned to')
parser.add_argument('--gpu_memory_frac', type=float, default=0.8, help='Specifying what fraction of your GPU memory to occupy')
parser.add_argument('--display_step', type=int, default='5', help='Display step during training')
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
| 5,518 | 1,839 |
from django.contrib.contenttypes import fields as ct_fields
from django.contrib.contenttypes import models as ct_models
from django.db import models, transaction
from django.db.models import Sum
from django.utils.encoding import python_2_unicode_compatible
from nodeconductor.logging.log import LoggableMixin
from nodeconductor.quotas import exceptions, managers
from nodeconductor.core.models import UuidMixin, NameMixin, ReversionMixin, DescendantMixin
@python_2_unicode_compatible
class Quota(UuidMixin, NameMixin, LoggableMixin, ReversionMixin, models.Model):
"""
Abstract quota for any resource.
Quota can exist without scope - for example quota for all projects or all customers on site
If quota limit is defined as -1 quota will never be exceeded
"""
class Meta:
unique_together = (('name', 'content_type', 'object_id'),)
limit = models.FloatField(default=-1)
usage = models.FloatField(default=0)
content_type = models.ForeignKey(ct_models.ContentType, null=True)
object_id = models.PositiveIntegerField(null=True)
scope = ct_fields.GenericForeignKey('content_type', 'object_id')
objects = managers.QuotaManager('scope')
def is_exceeded(self, delta=None, threshold=None):
"""
Check is quota exceeded
If delta is not None then checks if quota exceeds with additional delta usage
If threshold is not None then checks if quota usage over threshold * limit
"""
if self.limit == -1:
return False
usage = self.usage
limit = self.limit
if delta is not None:
usage += delta
if threshold is not None:
limit = threshold * limit
return usage > limit
def __str__(self):
return '%s quota for %s' % (self.name, self.scope)
def get_log_fields(self):
return ('uuid', 'name', 'limit', 'usage', 'scope')
class QuotaModelMixin(models.Model):
"""
Add general fields and methods to model for quotas usage. Model with quotas have inherit this mixin.
For quotas implementation such methods and fields have to be defined:
- QUOTAS_NAMES - list of names for object quotas
- can_user_update_quotas(self, user) - return True if user has permission to update quotas of this object
Additional optional fields:
- GLOBAL_COUNT_QUOTA_NAME - name of global count quota. It presents - global quota will be automatically created
for model
Use such methods to change objects quotas:
set_quota_limit, set_quota_usage, add_quota_usage.
Other useful methods: validate_quota_change, get_sum_of_quotas_as_dict. Please check their docstrings for more details.
"""
QUOTAS_NAMES = [] # this list has to be overridden
class Meta:
abstract = True
quotas = ct_fields.GenericRelation('quotas.Quota', related_query_name='quotas')
def set_quota_limit(self, quota_name, limit):
self.quotas.filter(name=quota_name).update(limit=limit)
def set_quota_usage(self, quota_name, usage, fail_silently=False):
with transaction.atomic():
try:
original_quota = self.quotas.get(name=quota_name)
except Quota.DoesNotExist:
if not fail_silently:
raise
else:
self._add_delta_to_ancestors('usage', quota_name, usage - original_quota.usage)
original_quota.usage = usage
original_quota.save(update_fields=['usage'])
def add_quota_usage(self, quota_name, usage_delta, fail_silently=False):
"""
Add usage_delta to current quota usage
If <fail_silently> is True - operation will not fail if quota does not exist
"""
self._add_delta_to_editable_field('usage', quota_name, usage_delta, fail_silently)
def _add_delta_to_editable_field(self, field, quota_name, delta, fail_silently=False):
"""
Add delta to quota <field>
If <fail_silently> is True - operation will not fail if quota does not exist
"""
if not delta:
return
with transaction.atomic():
try:
original_quota = self.quotas.select_for_update().get(name=quota_name)
except Quota.DoesNotExist, e:
if not fail_silently:
raise e
else:
# Django's F() expressions makes quota.is_exceeded() unusable in signals
# wrap update into a safe transaction instead (may not work with sqlite)
setattr(original_quota, field, getattr(original_quota, field) + delta)
original_quota.save(update_fields=[field])
self._add_delta_to_ancestors(field, quota_name, delta)
def _add_delta_to_ancestors(self, field, quota_name, delta):
if not delta or not isinstance(self, DescendantMixin):
return
ancestors = (a for a in self.get_ancestors() if isinstance(a, QuotaModelMixin))
for ancestor in ancestors:
with transaction.atomic():
try:
quota = ancestor.quotas.select_for_update().get(name=quota_name)
except Quota.DoesNotExist:
# ignore quotas change if parent does not have such quota
pass
else:
setattr(quota, field, getattr(quota, field) + delta)
quota.save(update_fields=[field])
def validate_quota_change(self, quota_deltas, raise_exception=False):
"""
Get error messages about object and his ancestor quotas that will be exceeded if quota_delta will be added.
raise_exception - if True QuotaExceededException will be raised if validation fails
quota_deltas - dictionary of quotas deltas, example:
{
'ram': 1024,
'storage': 2048,
...
}
Example of output:
['ram quota limit: 1024, requires: 2048(instance#1)', ...]
"""
errors = []
for name, delta in quota_deltas.iteritems():
quota = self.quotas.get(name=name)
if quota.is_exceeded(delta):
errors.append('%s quota limit: %s, requires %s (%s)\n' % (
quota.name, quota.limit, quota.usage + delta, quota.scope))
if isinstance(self, DescendantMixin):
for parent in self.get_parents():
if isinstance(parent, QuotaModelMixin) and parent.quotas.filter(name=name).exists():
errors += parent.validate_quota_change(quota_deltas)
if not raise_exception:
return errors
else:
if errors:
raise exceptions.QuotaExceededException('One or more quotas were exceeded: %s' % ';'.join(errors))
def can_user_update_quotas(self, user):
"""
Return True if user has permission to update quota
"""
return False
@classmethod
def get_sum_of_quotas_as_dict(cls, scopes, quota_names=None, fields=['usage', 'limit']):
"""
Return dictionary with sum of all scopes' quotas.
Dictionary format:
{
'quota_name1': 'sum of limits for quotas with such quota_name1',
'quota_name1_usage': 'sum of usages for quotas with such quota_name1',
...
}
All `scopes` have to be instances of the same model.
`fields` keyword argument defines sum of which fields of quotas will present in result.
"""
if not scopes:
return {}
if quota_names is None:
quota_names = cls.QUOTAS_NAMES
scope_models = set([scope._meta.model for scope in scopes])
if len(scope_models) > 1:
raise exceptions.QuotaError('All scopes have to be instances of the same model')
filter_kwargs = {
'content_type': ct_models.ContentType.objects.get_for_model(scopes[0]),
'object_id__in': [scope.id for scope in scopes],
'name__in': quota_names
}
result = {}
if 'usage' in fields:
items = Quota.objects.filter(**filter_kwargs)\
.values('name').annotate(usage=Sum('usage'))
for item in items:
result[item['name'] + '_usage'] = item['usage']
if 'limit' in fields:
items = Quota.objects.filter(**filter_kwargs)\
.exclude(limit=-1).values('name').annotate(limit=Sum('limit'))
for item in items:
result[item['name']] = item['limit']
for name in quota_names:
if name not in result:
result[name] = -1
return result
| 8,810 | 2,517 |
"""
Distributed Proximal Policy Optimization (Distributed PPO or DPPO) continuous
version implementation with distributed Tensorflow and Python’s multiprocessing
package. This implementation uses normalized running rewards with GAE. The code
is tested with Gym’s continuous action space environment, Pendulum-v0 on Colab.
"""
from __future__ import absolute_import, division, print_function, unicode_literals
#!pip install -q tf-nightly
import tensorflow as tf
tf.reset_default_graph()
import numpy as np
import matplotlib.pyplot as plt
import gym
import time
from multiprocessing import Process
# The following class is adapted from OpenAI's baseline:
# https://github.com/openai/baselines/blob/master/baselines/common/running_mean_std.py
# https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
# This class is used for the normalization of rewards in this program before GAE computation.
class RunningStats(object):
def __init__(self, epsilon=1e-4, shape=()):
self.mean = np.zeros(shape, 'float64')
self.var = np.ones(shape, 'float64')
self.std = np.ones(shape, 'float64')
self.count = epsilon
def update(self, x):
batch_mean = np.mean(x, axis=0)
batch_var = np.var(x, axis=0)
batch_count = x.shape[0]
self.update_from_moments(batch_mean, batch_var, batch_count)
def update_from_moments(self, batch_mean, batch_var, batch_count):
delta = batch_mean - self.mean
new_mean = self.mean + delta * batch_count / (self.count + batch_count)
m_a = self.var * self.count
m_b = batch_var * batch_count
M2 = m_a + m_b + np.square(delta) * self.count * batch_count / (self.count + batch_count)
new_var = M2 / (self.count + batch_count)
self.mean = new_mean
self.var = new_var
self.std = np.maximum(np.sqrt(self.var), 1e-6)
self.count = batch_count + self.count
class PPO(object):
def __init__(self, scope, sess, env, global_PPO=None):
self.sess = sess
self.env = env
#OPT_A = tf.train.AdamOptimizer(A_LR, beta1=0.99, beta2=0.999, name='OPT_A')
#OPT_C = tf.train.AdamOptimizer(C_LR, beta1=0.99, beta2=0.999, name='OPT_C')
OPT_A = tf.train.AdamOptimizer(A_LR, name='OPT_A')
OPT_C = tf.train.AdamOptimizer(C_LR, name='OPT_C')
with tf.variable_scope(scope): # scope is either global or wid
self.state = tf.placeholder(tf.float32, [None, S_DIM], 'state')
# critic
with tf.variable_scope('critic'):
h1 = tf.layers.dense(self.state, hidden, tf.nn.relu, name='hidden', trainable=True)
self.val = tf.layers.dense(h1, 1, name='val', trainable=True)
self.critic_params = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=scope + '/critic')
self.discounted_r = tf.placeholder(tf.float32, [None, 1], 'discounted_r')
self.advantage = self.discounted_r - self.val
self.closs = tf.reduce_mean(tf.square(self.advantage))
self.ctrain_op = OPT_C.minimize(self.closs)
with tf.variable_scope('cgrads'):
self.critic_grad_op = tf.gradients(self.closs, self.critic_params)
# actor
self.pi, self.pi_params = self._build_anet(scope, 'pi', self.env, trainable=True)
self.oldpi, self.oldpi_params = self._build_anet(scope, 'oldpi', self.env, trainable=True) # originally trainable=False
with tf.variable_scope('sample_action'):
self.sample_op = tf.squeeze(self.pi.sample(1), axis=0) # choosing action
with tf.variable_scope('update_oldpi'):
self.update_oldpi_op = [oldp.assign(p) for p, oldp in zip(self.pi_params, self.oldpi_params)]
self.act = tf.placeholder(tf.float32, [None, A_DIM], 'action')
self.adv = tf.placeholder(tf.float32, [None, 1], 'advantage')
with tf.variable_scope('loss'):
with tf.variable_scope('surrogate'):
ratio = self.pi.prob(self.act) / self.oldpi.prob(self.act)
surr = ratio * self.adv
self.aloss = -tf.reduce_mean(tf.minimum(surr, tf.clip_by_value(ratio, 1.-epsilon, 1.+epsilon)*self.adv))
with tf.variable_scope('atrain'):
self.atrain_op = OPT_A.minimize(self.aloss)
with tf.variable_scope('agrads'):
self.pi_grad_op = tf.gradients(self.aloss, self.pi_params)
if scope != net_scope: # not global
with tf.name_scope('params'): # push/pull from local/worker perspective
with tf.name_scope('push_to_global'):
self.push_actor_pi_params = OPT_A.apply_gradients(zip(self.pi_grad_op, global_PPO.pi_params))
self.push_critic_params = OPT_C.apply_gradients(zip(self.critic_grad_op, global_PPO.critic_params))
with tf.name_scope('pull_fr_global'):
self.pull_actor_pi_params = [local_params.assign(global_params) for local_params, global_params in zip(self.pi_params, global_PPO.pi_params)]
self.pull_critic_params = [local_params.assign(global_params) for local_params, global_params in zip(self.critic_params, global_PPO.critic_params)]
def update(self, s, a, r, adv):
self.sess.run(self.update_oldpi_op)
for _ in range(A_EPOCH): # train actor
self.sess.run(self.atrain_op, {self.state: s, self.act: a, self.adv: adv})
# update actor
self.sess.run([self.push_actor_pi_params,
self.pull_actor_pi_params],
{self.state: s, self.act: a, self.adv: adv})
for _ in range(C_EPOCH): # train critic
# update critic
self.sess.run(self.ctrain_op, {self.state: s, self.discounted_r: r})
self.sess.run([self.push_critic_params,
self.pull_critic_params],
{self.state: s, self.discounted_r: r})
def _build_anet(self, scope, name, env, trainable):
with tf.variable_scope(name):
h1 = tf.layers.dense(self.state, hidden, tf.nn.relu, name='hidden', trainable=trainable)
mu = self.env.action_space.high * tf.layers.dense(h1, A_DIM, tf.nn.tanh, name='mu', trainable=trainable)
sigma = tf.layers.dense(h1, A_DIM, tf.nn.softplus, name='sigma', trainable=trainable)
norm_dist = tf.distributions.Normal(loc=mu, scale=sigma)
params = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=scope + '/' + name)
return norm_dist, params
def choose_action(self, s):
s = s[None, :]
a = self.sess.run(self.sample_op, {self.state: s})[0]
return np.clip(a, self.env.action_space.low, self.env.action_space.high)
def get_val(self, s):
if s.ndim < 2: s = s[None, :]
return self.sess.run(self.val, {self.state: s})[0, 0]
# This function is adapted from OpenAI's Baseline
# GAE computation
# returns TD lamda return & advantage
def add_vtarg_and_adv(self, R, done, V, v_s_, gamma, lam):
# Compute target value using TD(lambda) estimator, and advantage with GAE(lambda)
# last element is only used for last vtarg, but we already zeroed it if last new = 1
done = np.append(done, 0)
V_plus = np.append(V, v_s_)
T = len(R)
adv = gaelam = np.empty(T, 'float32')
lastgaelam = 0
for t in reversed(range(T)):
nonterminal = 1-done[t+1]
delta = R[t] + gamma * V_plus[t+1] * nonterminal - V_plus[t]
gaelam[t] = lastgaelam = delta + gamma * lam * nonterminal * lastgaelam
#print("adv=", adv.shape)
#print("V=", V.shape)
#print("V_plus=", V_plus.shape)
tdlamret = np.vstack(adv) + V
#print("tdlamret=", tdlamret.shape)
return tdlamret, adv # tdlamret is critic_target or Qs
class Worker(object):
def __init__(self, wid, GLOBAL_PPO, GLOBAL_EP, GLOBAL_RUNNING_R, sess):
self.wid = wid
self.env = gym.make(GAME).unwrapped
self.g_ppo = GLOBAL_PPO
self.ppo = PPO(wid, sess, self.env, GLOBAL_PPO)
self.running_stats_r = RunningStats()
self.sess = sess
self.GLOBAL_EP = GLOBAL_EP
self.GLOBAL_RUNNING_R = GLOBAL_RUNNING_R
def work(self):
T = 0
t = 0
SESS = self.sess
GLOBAL_EP = self.GLOBAL_EP
GLOBAL_RUNNING_R = self.GLOBAL_RUNNING_R
while SESS.run(GLOBAL_EP) < EP_MAX:
s = self.env.reset()
buffer_s, buffer_a, buffer_r, buffer_done, buffer_V = [], [], [], [], []
ep_r = 0
for t in range(EP_LEN):
a = self.ppo.choose_action(s)
s_, r, done, _ = self.env.step(a)
buffer_s.append(s)
buffer_a.append(a)
buffer_r.append(r)
buffer_done.append(done)
v = self.ppo.get_val(s)
buffer_V.append(v)
s = s_
ep_r += r
# update ppo
if (t+1) % BATCH == 0 or t == EP_LEN-1:
self.running_stats_r.update(np.array(buffer_r))
buffer_r = np.clip( (np.array(buffer_r) - self.running_stats_r.mean) / self.running_stats_r.std, -stats_CLIP, stats_CLIP )
v_s_ = self.ppo.get_val(s_)
tdlamret, adv = self.ppo.add_vtarg_and_adv(np.vstack(buffer_r), np.vstack(buffer_done), np.vstack(buffer_V), v_s_, GAMMA, lamda)
bs, ba, br, b_adv = np.vstack(buffer_s), np.vstack(buffer_a), tdlamret, np.vstack(adv)
buffer_s, buffer_a, buffer_r, buffer_done, buffer_V = [], [], [], [], []
self.ppo.update(bs, ba, br, b_adv)
SESS.run(GLOBAL_EP.assign_add(1.0))
qe = GLOBAL_RUNNING_R.enqueue(ep_r)
SESS.run(qe)
GAME = 'Pendulum-v0'
env = gym.make(GAME).unwrapped
net_scope = 'global'
EP_MAX = 500 #500 # max number of episodes
EP_LEN = 200 # episode length
GAMMA = 0.9
lamda = 0.95 #0.95
hidden = 50 #100
A_LR = 0.0001 # actor's learning rate
C_LR = 0.0002 # critic's learning rate
BATCH = 32 # minibatch size
A_EPOCH = 10 # number of epoch
C_EPOCH = 10 # number of epoch
S_DIM, A_DIM = 3, 1 # state, action dimension
stats_CLIP = 10 # upper bound of RunningStats
epsilon=0.2
cluster = tf.train.ClusterSpec({
"worker": ["localhost:3331",
"localhost:3332",
"localhost:3333",
"localhost:3334"
],
"ps": ["localhost:3330"]
})
def parameter_server():
#tf.reset_default_graph()
server = tf.train.Server(cluster,
job_name="ps",
task_index=0)
sess = tf.Session(target=server.target)
with tf.device("/job:ps/task:0"):
GLOBAL_PPO = PPO(net_scope, sess, env, global_PPO=None) # only need its params
GLOBAL_EP = tf.Variable(0.0, name='GLOBAL_EP') # num of global episodes
# a queue of ep_r
GLOBAL_RUNNING_R = tf.FIFOQueue(EP_MAX, tf.float32, shared_name="GLOBAL_RUNNING_R")
print("Parameter server: waiting for cluster connection...")
sess.run(tf.report_uninitialized_variables())
print("Parameter server: cluster ready!")
print("Parameter server: initializing variables...")
sess.run(tf.global_variables_initializer())
print("Parameter server: variables initialized")
while True:
time.sleep(1.0)
if sess.run(GLOBAL_RUNNING_R.size()) >= EP_MAX: # GLOBAL_EP starts from 0, hence +1 to max_global_episodes
time.sleep(10.0)
GLOBAL_RUNNING_R_list = []
ep_r_prev = 0.0
for i in range(sess.run(GLOBAL_RUNNING_R.size())):
ep_r = sess.run(GLOBAL_RUNNING_R.dequeue())
if i==0:
GLOBAL_RUNNING_R_list.append(ep_r) # for display
else:
GLOBAL_RUNNING_R_list.append(GLOBAL_RUNNING_R_list[-1]*0.9 + ep_r*0.1) # for display
break
# display
plt.plot(np.arange(len(GLOBAL_RUNNING_R_list)), GLOBAL_RUNNING_R_list)
plt.xlabel('episode')
plt.ylabel('reward')
plt.show()
#print("Parameter server: blocking...")
#server.join() # currently blocks forever
print("Parameter server: ended...")
def worker(worker_n):
#tf.reset_default_graph()
server = tf.train.Server(cluster,
job_name="worker",
task_index=worker_n)
sess = tf.Session(target=server.target)
with tf.device("/job:ps/task:0"):
GLOBAL_PPO = PPO(net_scope, sess, env, global_PPO=None) # only need its params
GLOBAL_EP = tf.Variable(0.0, name='GLOBAL_EP') # num of global episodes
# a queue of ep_r
GLOBAL_RUNNING_R = tf.FIFOQueue(EP_MAX, tf.float32, shared_name="GLOBAL_RUNNING_R")
"""
with tf.device(tf.train.replica_device_setter(
worker_device='/job:worker/task:' + str(worker_n),
cluster=cluster)):
"""
print("Worker %d: waiting for cluster connection..." % worker_n)
sess.run(tf.report_uninitialized_variables())
print("Worker %d: cluster ready!" % worker_n)
#while sess.run(tf.report_uninitialized_variables()):
while (sess.run(tf.report_uninitialized_variables())).any(): # ********** .any() .all() **********
print("Worker %d: waiting for variable initialization..." % worker_n)
time.sleep(1.0)
print("Worker %d: variables initialized" % worker_n)
w = Worker(str(worker_n), GLOBAL_PPO, GLOBAL_EP, GLOBAL_RUNNING_R, sess)
print("Worker %d: created" % worker_n)
sess.run(tf.global_variables_initializer()) # got to initialize after Worker creation
w.work()
print("Worker %d: w.work()" % worker_n)
#print("Worker %d: blocking..." % worker_n)
server.join() # currently blocks forever
print("Worker %d: ended..." % worker_n)
start_time = time.time()
ps_proc = Process(target=parameter_server, daemon=True)
w1_proc = Process(target=worker, args=(0, ), daemon=True)
w2_proc = Process(target=worker, args=(1, ), daemon=True)
w3_proc = Process(target=worker, args=(2, ), daemon=True)
w4_proc = Process(target=worker, args=(3, ), daemon=True)
ps_proc.start()
w1_proc.start()
w2_proc.start()
w3_proc.start()
w4_proc.start()
# if not join, parent will terminate before children
# & children will terminate as well cuz children are daemon
ps_proc.join()
#w1_proc.join()
#w2_proc.join()
#w3_proc.join()
#w4_proc.join()
for proc in [w1_proc,
w2_proc,
w3_proc,
w4_proc,
ps_proc]:
proc.terminate() # only way to kill server is to kill it's process
print('All done.')
print("--- %s seconds ---" % (time.time() - start_time))
| 15,049 | 5,255 |
from django.contrib.auth.decorators import login_required
from django.urls import reverse_lazy
class LoginRequiredMiddleware:
"""Middleware for all views requires a login.
To exclude a view from checking, the login_exempt decorator is used.
"""
def __init__(self, get_response):
self.get_response = get_response
def __call__(self, request):
return self.get_response(request)
def process_view(self, request, view_func, view_args, view_kwargs):
if request.user.is_authenticated:
return None
if getattr(view_func, 'login_exempt', False):
return None
if reverse_lazy('admin:index') == request.path or reverse_lazy('admin:login') == request.path:
return None
login_url = reverse_lazy('account:login')
return login_required(view_func, login_url=login_url)(request, *view_args, **view_kwargs)
| 910 | 260 |
# utility modules
import os
from os import path
import shutil
import sys
import time
import json
import argparse
import numpy as np
from pprint import pprint as pr
ITEM_DIM=100
dir_path = path.dirname(path.dirname(path.dirname(path.realpath(__file__))))
sys.path.append(dir_path)
import settings
# -----------------------------------------------------------------------------
def main():
parser = argparse.ArgumentParser()
# data I/O
parser.add_argument('--model_directory', type=str, default=settings.MODEL_STORE_PATH,
help='Location for parameter checkpoints and samples')
parser.add_argument('--model_file_name', type=str, default='seq_rnn',
help='model file name (will create a separated folder)')
parser.add_argument('--data_set', type=str, default='linux_data',
help='Can be fake_seq | quick_draw')
parser.add_argument('--checkpoint_interval', type=int, default=1,
help='Every how many epochs to write checkpoint/samples?')
parser.add_argument('--report_interval', type=int, default=20,
help='Every how many epochs to report current situation?')
parser.add_argument('--validation_interval', type=int, default=50,
help='Every how many epochs to do validation current situation?')
parser.add_argument('--load_params', dest='load_params', action='store_true',
help='Restore training from previous model checkpoint')
# model
parser.add_argument('--hist_length', type=int, default=5,
help='The minimum length of history sequence')
parser.add_argument('--training_num', type=int, default=None,
help='number of training samples')
parser.add_argument('--training_epoch', type=int, default=1,
help='number of training epoch')
parser.add_argument('--val_portion', type=float, default=0.4,
help='The portion of data to be validation data')
parser.add_argument('--shuffle', dest='shuffle', action='store_true',
help='shuffle the training samples or not')
# hyper-parameter for optimization
parser.add_argument('-l', '--learning_rate', type=float,
default=0.01, help='Base learning rate')
parser.add_argument('-e', '--lr_decay', type=float, default=0.999995,
help='Learning rate decay, applied every step of the optimization')
parser.add_argument('-b', '--batch_size', type=int, default=128,
help='Batch size during training per GPU')
parser.add_argument('-p', '--dropout_rate', type=float, default=0.2,
help='Dropout strength, where 0 = No dropout, higher = more dropout.')
parser.add_argument('-x', '--max_epochs', type=int, default=5000,
help='The maximum epochs to run')
parser.add_argument('-g', '--nr_gpu', type=int, default=1,
help='The number GPUs to distribute the training across')
# reproducibility:random seed
parser.add_argument('-s', '--random_seed', type=int, default=42,
help='Random seed to use')
args = parser.parse_args()
print('INFO CHECK!\ninput args:\n', json.dumps(vars(args), indent=4, separators=(',', ':')))
################################################
# The main program starts
################################################
# fix random seed for reproducibility
args.random_state = np.random.RandomState(args.random_seed)
# tf.set_random_seed(args.random_seed)
train(args)
def train(args):
class_num = {'quick_draw': 10,'fake_seq':1,'linux_data':101}[args.data_set]
args.class_num=class_num
# initialize data loaders for train/test splits
# data loader
print(args.data_set)
if args.data_set == 'linux_data':
import data.linux_code_data as linux_code_data
print('start loading dataset',args.data_set)
train_data = linux_code_data.DataLoader(args,'train')
print('dataset',args.data_set,'loading completed')
from learner_model.SeqRNN import Sequence_RNN_Model_Session as model_session
print('import seq RNN model okay')
elif args.data_set == 'shakespeare_data':
import data.shakespeare_data as shakespeare_data
print('start loading dataset',args.data_set)
train_data = linux_code_data.DataLoader(args,'train')
test_data = linux_code_data.DataLoader(args,'test')
print('dataset',args.data_set,'loading completed')
from learner_model.SeqRNN import Sequence_RNN_Model_Session as model_session
print('import seq RNN model okay')
else:
print('this dataset is not available , or the dataset name not correct')
quit()
model_path_name=path.join(args.model_directory,args.model_file_name)
print(model_path_name)
file_path_name=path.join(args.model_directory,args.model_file_name+"Gen")
if os.path.exists(model_path_name) and args.load_params == True :
try:
model = model_session.restore(model_path_name)
except:
print("error happens, now remove the original folder name from",model_path_name)
shutil.rmtree(model_path_name)
os.makedirs(model_path_name)
model = model_session.create(class_num=len(train_data.dictionary))
session = model_session(model,args)
else:
try:
os.makedirs(model_path_name)
except:
print("directory okay")
if os.path.exists(model_path_name) == False:
print("there is no previous file")
if args.load_params == False:
print("deliberately do want to laod a previous model")
print("create a new model")
model = model_session.create(class_num=len(train_data.dictionary))
session = model_session(model,args)
print(model)
session.register_dictionary(train_data.dictionary)
session.register_index(train_data.index)
if args.training_num is None:
args.training_num = train_data.record_num
print('Last Check :overall training number',train_data.record_num)
# Train the model, iterating on the data in batches of 32 samples
iteration=0
for iEpoch in range(args.training_epoch):
for data in train_data:
# x, y = training_data.next_batch(args.batch_size)
x=data
session.train(x)
if iteration % args.report_interval == 0:
score = session.evaluate(data, batch_size=args.batch_size)
# print(" training batch score" , score)
if iteration % args.validation_interval == 0:
session.generate(random_sentence_start=x,file_directory=file_path_name)
if iteration % args.checkpoint_interval == 0:
session.save(model_path_name)
iteration+=1
print("Final model %s" % model)
model_session.save(model,model_path_name)
def test(args):
model_path_name=path.join(args.model_directory,args.model_file_name)
model = ModelSession.restore(model_path_name)
print(model)
accuracy = model.test(test_data.X_data, test_data.Y_data)
print("Test accuracy %0.4f" % accuracy)
if __name__ == "__main__":
main()
| 7,417 | 2,148 |
"""
Rectify the face photo according to the paper: Real-Time Exemplar-Based Face Sketch Synthesis.
shape: h=250, w=200
position: left eye (x=75,y=125), right eye (x=125, y=125)
This module use similarity transformation to roughly align the two eyes.
Specifically, the transformation matrix can be written as:
S = |s_x cos(\theta), sin(\theta) , t_x |
|-sin(\theta) , s_y cos(\theta), t_y |
There are 5 degrees in the above function, needs at least 3 points(x, y) to solve it.
we can simply hallucinate a third point such that it forms an equilateral triangle with the two known points.
Reference:
http://www.learnopencv.com/average-face-opencv-c-python-tutorial/
http://blog.csdn.net/GraceDD/article/details/51382952
"""
import math
import numpy as np
import os
import dlib
import cv2 as cv
from PIL import Image
import matplotlib.pyplot as plt
from natsort import natsorted
def detect_fiducial_points(img, predictor_path):
"""
Detect face landmarks and return the mean points of left and right eyes.
If there are multiple faces in one image, only select the first one.
"""
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predictor_path)
dets = detector(img, 1)
if len(dets) < 1:
return []
for k, d in enumerate(dets):
shape = predictor(img, d)
break
landmarks = []
for i in range(68):
landmarks.append([shape.part(i).x, shape.part(i).y])
landmarks = np.array(landmarks)
left_eye = landmarks[36:42]
right_eye = landmarks[42:48]
mouth = landmarks[48:68]
return np.array([np.mean(left_eye, 0), np.mean(right_eye, 0)]).astype('int')
def similarityTransform(inPoints, outPoints) :
"""
Calculate similarity transform:
Input:
(left eye, right eye) in (x, y)
inPoints: (2, 2), numpy array.
outPoints: (2, 2), numpy array
Return:
A partial affine transform.
"""
s60 = math.sin(60*math.pi/180)
c60 = math.cos(60*math.pi/180)
inPts = np.copy(inPoints).tolist()
outPts = np.copy(outPoints).tolist()
xin = c60*(inPts[0][0] - inPts[1][0]) - s60*(inPts[0][1] - inPts[1][1]) + inPts[1][0]
yin = s60*(inPts[0][0] - inPts[1][0]) + c60*(inPts[0][1] - inPts[1][1]) + inPts[1][1]
inPts.append([np.int(xin), np.int(yin)])
xout = c60*(outPts[0][0] - outPts[1][0]) - s60*(outPts[0][1] - outPts[1][1]) + outPts[1][0]
yout = s60*(outPts[0][0] - outPts[1][0]) + c60*(outPts[0][1] - outPts[1][1]) + outPts[1][1]
outPts.append([np.int(xout), np.int(yout)])
tform = cv.estimateRigidTransform(np.array([inPts]), np.array([outPts]), False)
return tform
def rectify_img(img_path, predictor_path):
template_eye_pos = np.array([[75, 125], [125, 125]])
template_size = (200, 250)
img = cv.imread(img_path)
detected_eyes = detect_fiducial_points(np.array(img), predictor_path)
if not len(detected_eyes):
return None
trans = similarityTransform(detected_eyes, template_eye_pos)
rect_img = cv.warpAffine(img, trans, template_size)
return rect_img
def align_img(ref_path, src_path, predictor_path):
ref_img = cv.imread(ref_path)
src_img = cv.imread(src_path)
ref_eyes = detect_fiducial_points(np.array(ref_img), predictor_path)
src_eyes = detect_fiducial_points(np.array(src_img), predictor_path)
trans = similarityTransform(src_eyes, ref_eyes)
rect_img = cv.warpAffine(src_img, trans, (200, 250))
return rect_img
if __name__ == '__main__':
src_dir = '../result_ours/CUFSF_intersect/ours_result'
ref_dir = '../result_ours/CUFSF_intersect/gt_sketch'
save_dir = '../result_ours/CUFSF_intersect/ours_warp'
if not os.path.exists(save_dir): os.mkdir(save_dir)
ref_img_list = natsorted(os.listdir(ref_dir))
src_img_list = natsorted(os.listdir(src_dir))
for i in range(len(ref_img_list)):
ref_path = os.path.join(ref_dir, ref_img_list[i])
src_path = os.path.join(src_dir, src_img_list[i])
save_path = os.path.join(save_dir, ref_img_list[i])
warp_src = align_img(ref_path, src_path, './shape_predictor_68_face_landmarks.dat')
cv.imwrite(save_path, warp_src)
# template_eye_pos = np.array([[75, 125], [125, 125]])
# template_size = (200, 250)
# img_path = '/disk1/cfchen/data/FERET/original_photo/00001.jpg'
# img = cv.imread(img_path)
# detected_eyes = detect_fiducial_points(np.array(img), './shape_predictor_68_face_landmarks.dat')
# trans = similarityTransform(detected_eyes, template_eye_pos)
# rect_img = cv.warpAffine(img, trans, template_size)
# cv.imshow('test', rect_img)
# cv.waitKey()
| 4,741 | 1,920 |
from data_wrangling import *
from flask import Flask, jsonify, render_template
app = Flask(__name__)
@app.route("/")
def index():
return render_template('index.html')
@app.route("/names")
def names():
# Store results into a dictionary
forecast = get_samples()
return jsonify(forecast)
# Redirect back to home page
# return redirect("http://localhost:5000/", code=302)
@app.route("/pie")
def make_pie_chart():
data = [{
"labels": get_otu_pie_labels(),
"values": get_otu_pie_values(),
"type": "pie"}]
return jsonify(data)
if __name__ == "__main__":
app.run(debug=True)
| 643 | 223 |
#
# PySNMP MIB module BW-BroadworksEMSFault (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/BW-BroadworksEMSFault
# Produced by pysmi-0.3.4 at Wed May 1 11:42:07 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
OctetString, Integer, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsIntersection, ValueRangeConstraint, SingleValueConstraint, ValueSizeConstraint, ConstraintsUnion = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "ValueRangeConstraint", "SingleValueConstraint", "ValueSizeConstraint", "ConstraintsUnion")
alarmName, problemText, common, component, subcomponent, systemName, identifier, severity, alarmState, faultFields, timeStamp, recommendedActionsText = mibBuilder.importSymbols("BroadworksFault", "alarmName", "problemText", "common", "component", "subcomponent", "systemName", "identifier", "severity", "alarmState", "faultFields", "timeStamp", "recommendedActionsText")
ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "NotificationGroup")
MibIdentifier, IpAddress, ObjectIdentity, Counter32, Integer32, Bits, ModuleIdentity, TimeTicks, MibScalar, MibTable, MibTableRow, MibTableColumn, Unsigned32, Counter64, NotificationType, iso, Gauge32 = mibBuilder.importSymbols("SNMPv2-SMI", "MibIdentifier", "IpAddress", "ObjectIdentity", "Counter32", "Integer32", "Bits", "ModuleIdentity", "TimeTicks", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Unsigned32", "Counter64", "NotificationType", "iso", "Gauge32")
DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention")
systemFaults = ModuleIdentity((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1))
systemFaults.setRevisions(('2000-09-19 14:31',))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
if mibBuilder.loadTexts: systemFaults.setRevisionsDescriptions(('',))
if mibBuilder.loadTexts: systemFaults.setLastUpdated('200201220000Z')
if mibBuilder.loadTexts: systemFaults.setOrganization('Broadsoft, Inc')
if mibBuilder.loadTexts: systemFaults.setContactInfo('Broadsoft, Inc. 220 Perry Parkway Gaithersburg, MD 20877 301-977-9440')
if mibBuilder.loadTexts: systemFaults.setDescription('The defines the fault ')
bwPMElementManagementSystemBELaunched = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3001)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemBELaunched.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemBELaunched.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemBEShutDown = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3002)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemBEShutDown.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemBEShutDown.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemBERestarted = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3003)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemBERestarted.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemBERestarted.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemBEDeath = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3004)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemBEDeath.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemBEDeath.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemFELaunched = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3005)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemFELaunched.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemFELaunched.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemFEShutDown = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3006)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemFEShutDown.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemFEShutDown.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemFERestarted = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3007)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemFERestarted.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemFERestarted.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
bwPMElementManagementSystemFEDeath = NotificationType((1, 3, 6, 1, 4, 1, 6431, 1, 1, 1, 3008)).setObjects(("BroadworksFault", "identifier"), ("BroadworksFault", "timeStamp"), ("BroadworksFault", "alarmName"), ("BroadworksFault", "systemName"), ("BroadworksFault", "severity"), ("BroadworksFault", "component"), ("BroadworksFault", "subcomponent"), ("BroadworksFault", "problemText"), ("BroadworksFault", "recommendedActionsText"))
if mibBuilder.loadTexts: bwPMElementManagementSystemFEDeath.setStatus('current')
if mibBuilder.loadTexts: bwPMElementManagementSystemFEDeath.setDescription('For the actual description, refer the BroadWorks FaultManagementGuide as it may contain variable data.')
mibBuilder.exportSymbols("BW-BroadworksEMSFault", bwPMElementManagementSystemBEDeath=bwPMElementManagementSystemBEDeath, bwPMElementManagementSystemFEShutDown=bwPMElementManagementSystemFEShutDown, bwPMElementManagementSystemBELaunched=bwPMElementManagementSystemBELaunched, PYSNMP_MODULE_ID=systemFaults, bwPMElementManagementSystemFELaunched=bwPMElementManagementSystemFELaunched, bwPMElementManagementSystemBEShutDown=bwPMElementManagementSystemBEShutDown, bwPMElementManagementSystemFEDeath=bwPMElementManagementSystemFEDeath, bwPMElementManagementSystemFERestarted=bwPMElementManagementSystemFERestarted, systemFaults=systemFaults, bwPMElementManagementSystemBERestarted=bwPMElementManagementSystemBERestarted)
| 8,813 | 3,020 |
import pytest
from problems.wildcard_matching import Solution
@pytest.mark.parametrize("s, p, expected", [
("", "", True),
("", "*", True),
("", "**", True),
("a", "*", True),
("ab", "*", True),
("ab", "a*", True),
("ab", "*b", True),
("ab", "a*b", True),
("ab", "a*bc", False),
("ab", "a*cb", False),
("ab", "ac*b", False),
("ab", "ca*b", False),
("ab", "a?", True),
("a", "a?", False),
(
"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"*aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa*",
False),
(
"ababbbaabaabaabbbaabaabaaaababaaaabbbabaabbbababbababaababbaababaaabaaaabbbbabbaaaabaaaabbaababbabaababbaaaaabaababbbbbabbaaabbabbbaaabaaaaabbabbbaabababbabbbaaabaabaabababaaabababbbbaababaabababaabba",
"**b**a*****abaab*abb**bb*aba***a*a*aab***b*ab*baa*b*b*a**baba****b****bb*abba*bab*****bbab*aab****bab*ba",
True),
])
def test_isMatch(s, p, expected):
assert Solution().isMatch(s, p) == expected
| 9,145 | 2,444 |
# Copyright 2018 luozhouyang
#
# 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 unittest
from .data import SkipGramDataSet
import os
_CURRENT_DIR = os.path.abspath(os.path.dirname(__file__))
LICENSE_FILE = os.path.join(os.path.curdir, "LICENSE")
INIT_FILE = os.path.join(_CURRENT_DIR, "__init__.py")
TEST_FILE = os.path.join(_CURRENT_DIR, "test.txt")
class TestDataSet(unittest.TestCase):
def testGenBatchInputs(self):
ds = SkipGramDataSet(file=TEST_FILE)
BATCH_SIZE = 16
features, labels = ds.gen_batch_inputs(BATCH_SIZE, 1)
for i in range(BATCH_SIZE):
print("%s --> %s" % (ds.id2word[features[i]], ds.id2word[labels[i]]))
for i in range(16):
features, labels = ds.gen_batch_inputs(BATCH_SIZE, 1)
for i in range(BATCH_SIZE):
print("%s --> %s" % (ds.id2word[features[i]], ds.id2word[labels[i]]))
if __name__ == "__main__":
unittest.main()
| 1,484 | 510 |
"""
This script serializes the entire traffic dump, including websocket traffic,
as JSON, and either sends it to an elasticsearch endpoint for permenant storage.
Unlike some plugins, this one sends all requests and responses to elasticsearch
in real-time.
This script is based on the original mitmproxy scripts jsondump.py and har_dump.py
Usage:
mitmproxy
-s elasticArchive.py
--set elasticsearch_URL=http://<your elasticsearch server>:9200/mitmproxy/_doc
OPTIONAL
--set storeBinaryContent=true
--set elastic_username=<username>
--set elastic_password=<password>
You can also put those --set options inside ~/.mitmproxy/config.yaml but I prefer setting
them at startup
"""
from threading import Thread
from queue import Queue
import base64
import json
import requests
from mitmproxy import ctx
from mitmproxy.net.http import encoding
HTTP_WORKERS = 10
class elasticArchive:
"""
elasticArchive performs JSON serialization and some extra processing
for out-of-the-box Elasticsearch support, and then either writes
the result to a file or sends it to a URL.
"""
def __init__(self):
self.transformations = None
self.storeBinaryContent = None
self.url = None
self.auth = None
self.queue = Queue()
print("elasticArchive loaded")
def done(self):
self.queue.join()
fields = {
'timestamp': (
('error', 'timestamp'),
('request', 'timestamp_start'),
('request', 'timestamp_end'),
('response', 'timestamp_start'),
('response', 'timestamp_end'),
('client_conn', 'timestamp_start'),
('client_conn', 'timestamp_end'),
('client_conn', 'timestamp_tls_setup'),
('server_conn', 'timestamp_start'),
('server_conn', 'timestamp_end'),
('server_conn', 'timestamp_tls_setup'),
('server_conn', 'timestamp_tcp_setup'),
),
'ip': (
('server_conn', 'source_address'),
('server_conn', 'ip_address'),
('server_conn', 'address'),
('client_conn', 'address'),
),
'ws_messages': (
('messages', ),
),
'headers': (
('request', 'headers'),
('response', 'headers'),
),
'content': (
('request', 'content'),
('response', 'content'),
),
'tls': (
('client_conn', 'tls_extensions'),
),
}
def _init_transformations(self):
self.transformations = [
{
'fields': self.fields['headers'],
'func': dict,
},
{
'fields': self.fields['tls'],
'func': lambda exts: [{
str(ext[0]): str(ext[1]),
} for ext in exts],
},
{
'fields': self.fields['timestamp'],
'func': lambda t: int(t * 1000),
},
{
'fields': self.fields['ip'],
'func': lambda addr: {
'host': addr[0].replace('::ffff:', ''),
'port': addr[1],
},
},
{
'fields': self.fields['ws_messages'],
'func': lambda ms: [{
'type': m[0],
'from_client': m[1],
'content': base64.b64encode(bytes(m[2], 'utf-8')) if strutils.is_mostly_bin(m[2]) else m[2],
'timestamp': int(m[3] * 1000),
} for m in ms],
}
]
@staticmethod
def transform_field(obj, path, func):
"""
Apply a transformation function `func` to a value
under the specified `path` in the `obj` dictionary.
"""
for key in path[:-1]:
if not (key in obj and obj[key]):
return
obj = obj[key]
if path[-1] in obj and obj[path[-1]]:
obj[path[-1]] = func(obj[path[-1]])
@classmethod
def convert_to_strings(cls, obj):
"""
Recursively convert all list/dict elements of type `bytes` into strings.
"""
if isinstance(obj, dict):
return {cls.convert_to_strings(key): cls.convert_to_strings(value)
for key, value in obj.items()}
elif isinstance(obj, list) or isinstance(obj, tuple):
return [cls.convert_to_strings(element) for element in obj]
elif isinstance(obj, bytes):
return str(obj)[2:-1]
return obj
def worker(self):
while True:
frame = self.queue.get()
self.dump(frame)
self.queue.task_done()
def dump(self, frame):
"""
Transform and dump (write / send) a data frame.
"""
#print('Frame= %s' % frame)
requestContentType = None
responseContentType = None
requestContentEncoding = None
responseContentEncoding = None
for header in frame["request"]["headers"]:
h = header[0].decode('utf-8')
#print(h)
if h.lower() == "content-type":
requestContentType = header[1].decode("utf-8")
if h.lower() == "content-encoding":
requestContentEncoding = header[1].decode("utf-8")
for header in frame["response"]["headers"]:
h = header[0].decode('utf-8')
#print(h)
if h.lower() == "content-type":
responseContentType = header[1].decode("utf-8")
if h.lower() == "content-encoding":
responseContentEncoding = header[1].decode("utf-8")
for tfm in self.transformations:
for field in tfm['fields']:
self.transform_field(frame, field, tfm['func'])
#print("requestContentType %s" % requestContentType)
#print("responseContentType %s" % responseContentType)
#print("requestContentEncoding %s" % requestContentEncoding)
#print("responseContentEncoding %s" % responseContentEncoding)
if responseContentEncoding:
rawContent = frame["response"]["content"]
#print(type(rawContent))
#print("rawContent %s " % rawContent)
#print("decoding content of type %s" % responseContentEncoding)
#print("decoding with input string of type %s" % type(responseContentEncoding))
decodedContent = encoding.decode(rawContent, responseContentEncoding)
#print("decodedContent %s" % decodedContent)
frame["response"]["content"] = decodedContent
if self.storeBinaryContent:
if self.isBinaryContent(requestContentType):
frame["request"]["content"] = base64.b64encode(frame["request"]["content"])
if self.isBinaryContent(responseContentType):
frame["response"]["content"] = base64.b64encode(frame["response"]["content"])
else:
if self.isBinaryContent(requestContentType):
frame["request"]["content"] = "Binary content removed"
if self.isBinaryContent(responseContentType):
frame["response"]["content"] = "Binary content removed"
frame = self.convert_to_strings(frame)
print("Sending frame to Elasticsearch")
# If you need to debug this, print/log frame and result as it will show you
# what wasc sent and what errors you got back. This generates a lot of noise though...
result = requests.post(self.url, json=json.dumps(frame), auth=(self.auth or None))
print(result.text)
@staticmethod
def isBinaryContent(contentType):
if contentType is None:
print("Check is None")
return False
else:
print(contentType)
if contentType.startswith("text/"):
return False
elif contentType.startswith("multipart/form-data"):
return False
elif contentType.startswith("application/json"):
return False
elif contentType.startswith("application/xml"):
return False
else:
return True
@staticmethod
def load(loader):
"""
Extra options to be specified in `~/.mitmproxy/config.yaml`.
"""
loader.add_option('elasticsearch_URL', str, 'http://localhost:9200/mitmproxy/_doc',
'Elasticsearch resource path including index (mitmproxy) and type (usually _doc) ')
loader.add_option('storeBinaryContent', bool, False,
'Store binary content in Elasticsearch. If true, it will get pretty big pretty fast. Text is always stored.')
loader.add_option('elastic_username', str, '',
'Basic auth username for URL destinations.')
loader.add_option('elastic_password', str, '',
'Basic auth password for URL destinations.')
def configure(self, _):
"""
Determine the destination type and path, initialize the output
transformation rules.
"""
self.storeBinaryContent = ctx.options.storeBinaryContent
print('storeBinaryContent set to %s' % self.storeBinaryContent)
print('Sending all data frames to %s' % ctx.options.elasticsearch_URL)
if ctx.options.elasticsearch_URL.startswith('http'):
self.url = ctx.options.elasticsearch_URL
ctx.log.info('Sending all data frames to %s' % self.url)
if ctx.options.elastic_username and ctx.options.elastic_password:
self.auth = (ctx.options.elastic_username, ctx.options.elastic_password)
ctx.log.info('HTTP Basic auth enabled.')
else:
print("Invalid elasticsearch_URL. Exiting.")
exit()
self._init_transformations()
for i in range(HTTP_WORKERS):
print("Start of create worker loop")
t = Thread(target=self.worker)
t.daemon = True
t.start()
print("Started HTTP worker")
def response(self, flow):
"""
Dump request/response pairs.
"""
self.queue.put(flow.get_state())
print("Put frame on queue (response)")
def error(self, flow):
"""
Dump errors.
"""
self.queue.put(flow.get_state())
def websocket_end(self, flow):
"""
Dump websocket messages once the connection ends.
Alternatively, you can replace `websocket_end` with
`websocket_message` if you want the messages to be
dumped one at a time with full metadata. Warning:
this takes up _a lot_ of space.
"""
self.queue.put(flow.get_state())
def websocket_error(self, flow):
"""
Dump websocket errors.
"""
self.queue.put(flow.get_state())
addons = [elasticArchive()] # pylint: disable=invalid-name
| 11,140 | 2,962 |
from django.test import TestCase
from django.utils import timezone
from model_bakery import baker
from app_covid19data.models import DataCovid19Item
class Covid19dataTest(TestCase):
def create_DataCovid19Item(self, country='countryTest', state='stateTest', latitude=1, longitude=1):
return DataCovid19Item.objects.create(country=country, state=state, latitude=latitude,
longitude=longitude, date=timezone.now())
def test_covid19data_creation(self):
# w = self.create_DataCovid19Item()
w = baker.make(DataCovid19Item)
self.assertTrue(isinstance(w, DataCovid19Item))
r = f'Daily data from {w.country}/{w.state} at {w.date}' \
f'Lat/Long: {w.latitude}/{w.longitude}' \
f'\nConfirmed: {w.confirmed_cases}' \
f'\nDeaths: {w.dead_cases}' \
f'\nRecovered: {w.recovered_cases}' \
f'\nActive: {w.active_cases}' \
f'\nIncidence: {w.incidence_rate}' \
f'\nFatality Ratio: {w.case_fatality_ratio}'
self.assertEqual(w.__str__(), r)
def test_covid19data_exception(self):
self.assertRaises(Exception, self.create_DataCovid19Item, latitude='1')
def test_covid19data_save(self):
# w = self.create_DataCovid19Item()
w = baker.make(DataCovid19Item)
w.latitude = '1'
self.assertRaises(Exception, w.save) | 1,425 | 501 |
from python import SolvingBase
class Solving(SolvingBase):
def first_problem(self):
floor = 0
with open(self.test_case, 'r', encoding='utf-8') as file:
instructions = file.read()
for command in instructions:
floor += 1 if command == '(' else -1
return floor
def second_problem(self):
floor = 0
with open(self.test_case, 'r', encoding='utf-8') as file:
instructions = file.read()
for command_index, command in enumerate(instructions):
floor += 1 if command == '(' else -1
if floor == -1:
return command_index + 1
if __name__ == "__main__":
solve = Solving(test_case=False)
print(f"First Problem: {solve.first_problem()}\nSecond Problem: {solve.second_problem()}")
| 823 | 247 |
import numpy as np
import pandas as pd
import datetime
from downscale.utils.decorators import timer_decorator
def select_range(month_begin, month_end, year_begin, year_end, date_begin, date_end):
import pandas as pd
if (month_end != month_begin) or (year_begin != year_end):
dates = pd.date_range(date_begin, date_end, freq='M')
iterator = zip(dates.day, dates.month, dates.year)
else:
dates = pd.to_datetime(date_end)
iterator = zip([dates.day], [dates.month], [dates.year])
return iterator
def select_range_7days_for_long_periods_prediction(begin="2017-8-2", end="2020-6-30", prm=None):
"""
This function takes as input a date range (begin and end) and split it in 7-days range around excluded dates
Works if we have only one splitting in a week
"""
begin = np.datetime64(pd.to_datetime(begin))
end = np.datetime64(pd.to_datetime(end))
# Define 7 days periods within date range
dates = pd.date_range(start=begin, end=end, freq="7D")
dates_shift = pd.date_range(start=begin, end=end, freq="7D").shift()
dates_shift = dates_shift.where(dates_shift <= end, [end])
# Split range around selected dates
if prm["GPU"]:
d1 = datetime.datetime(2017, 8, 1, 6)
d2 = datetime.datetime(2018, 8, 1, 6)
d3 = datetime.datetime(2019, 5, 1, 6)
d4 = datetime.datetime(2019, 6, 1, 6)
d5 = datetime.datetime(2020, 6, 2, 6)
splitting_dates = [np.datetime64(date) for date in [d1, d2, d3, d4, d5]]
else:
d1 = datetime.datetime(2017, 8, 1, 6)
d2 = datetime.datetime(2018, 8, 1, 6)
d3 = datetime.datetime(2019, 6, 1, 6)
d6 = datetime.datetime(2020, 7, 1, 6)
splitting_dates = [np.datetime64(date) for date in [d1, d2, d3, d6]]
begins = []
ends = []
for index, (begin, end) in enumerate(zip(dates.values, dates_shift.values)):
# Add one day to begin after first element
begin = begin if index == 0 else begin + np.timedelta64(1, "D")
end = end + np.timedelta64(23, "h")
if begin > end:
continue
split = False
for splt_date in splitting_dates:
# If date range needs to be splitted
if begin <= splt_date < end:
begins.append(begin)
ends.append(splt_date - np.timedelta64(1, "h"))
begins.append(splt_date)
ends.append(end)
split = True
# If we didn't split date range
if not split:
begins.append(begin)
ends.append(end)
begins = [pd.to_datetime(begin) for begin in begins]
ends = [pd.to_datetime(end) for end in ends]
return begins, ends
def select_range_30_days_for_long_periods_prediction(begin="2017-8-2", end="2020-6-30", GPU=False):
begin = np.datetime64(pd.to_datetime(begin))
end = np.datetime64(pd.to_datetime(end))
# Define 30 days periods within date range
dates = pd.date_range(start=begin, end=end, freq="MS")
dates_shift = pd.date_range(start=begin, end=end, freq="M", closed='right').shift()
dates_shift = dates_shift.where(dates_shift <= end, [end])
# Split range around selected dates
if not GPU:
d1 = datetime.datetime(2017, 8, 1, 6)
d2 = datetime.datetime(2018, 8, 1, 6)
d3 = datetime.datetime(2019, 6, 1, 6)
d6 = datetime.datetime(2020, 7, 1, 6)
splitting_dates = [np.datetime64(date) for date in [d1, d2, d3, d6]]
else:
d1 = datetime.datetime(2017, 8, 1, 6)
d2 = datetime.datetime(2018, 8, 1, 6)
d3 = datetime.datetime(2019, 5, 1, 6)
d4 = datetime.datetime(2019, 6, 1, 6)
d5 = datetime.datetime(2020, 6, 2, 6)
splitting_dates = [np.datetime64(date) for date in [d1, d2, d3, d4, d5]]
begins = []
ends = []
for index, (begin, end) in enumerate(zip(dates.values, dates_shift.values)):
# Add one day to begin after first element
end = end + np.timedelta64(23, "h")
split = False
for splt_date in splitting_dates:
# If date range needs to be splitted
if begin <= splt_date < end:
begins.append(begin)
ends.append(splt_date - np.timedelta64(1, "h"))
begins.append(splt_date)
ends.append(end)
split = True
# If we didn't split date range
if not split:
begins.append(begin)
ends.append(end)
# begins = [pd.to_datetime(begin) for begin in begins]
for index, begin in enumerate(begins):
if not isinstance(begin, str):
begins[index] = pd.to_datetime(begin)
# ends = [pd.to_datetime(end) for end in ends]
for index, end in enumerate(ends):
if not isinstance(end, str):
ends[index] = pd.to_datetime(end)
return begins, ends
def print_current_line(time_step, nb_sim, division):
nb_sim_divided = nb_sim // division
for k in range(1, division + 1):
print(f" {k}/{division}") if (time_step == k * nb_sim_divided) else True
def change_dtype_if_required(variable, dtype):
if variable.dtype != dtype:
variable = variable.astype(dtype, copy=False)
return variable
def change_several_dtype_if_required(list_variable, dtypes):
result = []
for variable, dtype in zip(list_variable, dtypes):
if isinstance(variable, (list, int, float)):
variable = np.array(variable)
result.append(change_dtype_if_required(variable, dtype))
return result
def change_dtype_decorator(dtype):
"""Timer decorator"""
def decorator(function):
def wrapper(*args, **kwargs):
result = function(*args, **kwargs)
result = change_dtype_if_required(result, dtype)
return result
return wrapper
return decorator
def assert_equal_shapes(arrays, shape):
for k in range(len(arrays) - 1):
assert arrays[k].shape == shape
def round(t1, t2):
return np.round(t2 - t1, 2)
def reshape_list_array(list_array=None, shape=None):
"""
Utility function that takes as input a list of arrays to reshape to the same shape
Parameters
----------
list_array : list
List of arrays
shape : tuple
typle of shape
Returns
-------
result : list
List of reshaped arrays
"""
result = []
for array in list_array:
result.append(np.reshape(array, shape))
return result
def several_empty_like(array_like, nb_empty_arrays=None):
result = []
for array in range(nb_empty_arrays):
result.append(np.empty_like(array_like))
return result
def _list_to_array_if_required(list_or_array):
if isinstance(list_or_array, list):
return np.array(list_or_array)
else:
return list_or_array
def lists_to_arrays_if_required(lists_or_arrays):
if np.ndim(lists_or_arrays) > 1:
return (_list_to_array_if_required(list_or_array) for list_or_array in lists_or_arrays)
else:
return _list_to_array_if_required(lists_or_arrays)
@timer_decorator("statistical description array", unit="minute", level="")
def print_statistical_description_array(array, name="Acceleration CNN", level="________"):
print(f"{level}{name} min", np.nanmin(array))
print(f"\n{level}{name} q0.10", np.nanquantile(array, 0.1))
print(f"\n{level}{name} q0.25", np.nanquantile(array, 0.25))
print(f"\n{level}{name} median", np.nanmedian(array))
print(f"\n{level}{name} q0.75", np.nanquantile(array, 0.75))
print(f"\n{level}{name} q0.90", np.nanquantile(array, 0.9))
print(f"\n{level}{name} q0.95", np.nanquantile(array, 0.95))
print(f"\n{level}{name} q0.99", np.nanquantile(array, 0.99))
print(f"\n{level}{name} maximum", np.nanmax(array))
return None
def print_with_frame(text):
print('\n\n__________________________')
print('__________________________\n')
print(f'_______{text}_______\n')
print('__________________________')
print('__________________________\n\n')
def print_begin_end(begin, end):
print('\n\n__________________________')
print('__________________________\n')
print(f'_______{begin}___________\n')
print(f'_______{end}___________\n')
print('__________________________')
print('__________________________\n\n')
def print_second_begin_end(begin, end):
print('\n__________________________')
print(f'____{begin}___')
print(f'____{end}___')
print('__________________________')
def print_intro():
intro = """
''' '
' ' '
''' ''' '''
+ hs ' ''''' '.' '
'shh ho ' '
.yhhh hh+ ' ''
/hhhs +hhh/
hhhh' hhhh '''
ohhho +hhh: '. '.'
'yhhh: ohhh: ''''' ''' .
.+. -hhhy. ohhh: ' ''''' ''
-hhho' /hhhs' ohhh: '''''''''
:hhhhhhyhhh+ ohhh/ .' ''
/hhho+hhhhh: +hhh+ '. '.'
+hhh+ '+hy /hhho ''
ohhh/ ' :hhhs'
'shhh: :yhhy-
gyhhhg Wind speed 'shhh/
hyhhyf +hhhs'
:hhhs' Downscaling -hhhh:
+hhho 'ohhhsg
hhh/ using CNN :yhhh
hy- '+hh
o' by Louis Le Toumelin .s
CEN - Meteo-France
"""
print(intro)
| 10,032 | 3,383 |
from __future__ import annotations
import pathlib
import typing as t
import numpy as np
import math
def rgb_to_hsv(r, g, b):
r = float(r)
g = float(g)
b = float(b)
high = max(r, g, b)
low = min(r, g, b)
h, s, v = high, high, high
d = high - low
s = 0 if high == 0 else d/high
if high == low:
h = 0.0
else:
h = {
r: (g - b) / d + (6 if g < b else 0),
g: (b - r) / d + 2,
b: (r - g) / d + 4,
}[high]
h /= 6
return h, s, v
def hsv_to_rgb(h, s, v):
i = math.floor(h*6)
f = h*6 - i
p = v * (1-s)
q = v * (1-f*s)
t = v * (1-(1-f)*s)
r, g, b = [
(v, t, p),
(q, v, p),
(p, v, t),
(p, q, v),
(t, p, v),
(v, p, q),
][int(i%6)]
return r, g, b
def rgb_to_hsl(r, g, b):
r = float(r)
g = float(g)
b = float(b)
high = max(r, g, b)
low = min(r, g, b)
h, s, l = ((high + low) / 2,)*3
if high == low:
h = 0.0
s = 0.0
else:
d = high - low
s = d / (2 - high - low) if l > 0.5 else d / (high + low)
h = {
r: (g - b) / d + (6 if g < b else 0),
g: (b - r) / d + 2,
b: (r - g) / d + 4,
}[high]
h /= 6
return h, s, l
def hsl_to_rgb(h, s, l):
def hue_to_rgb(p, q, t):
t += 1 if t < 0 else 0
t -= 1 if t > 1 else 0
if t < 1/6: return p + (q - p) * 6 * t
if t < 1/2: return q
if t < 2/3: return p + (q - p) * (2/3 - t) * 6
return p
if s == 0:
r, g, b = l, l, l
else:
q = l * (1 + s) if l < 0.5 else l + s - l * s
p = 2 * l - q
r = hue_to_rgb(p, q, h + 1/3)
g = hue_to_rgb(p, q, h)
b = hue_to_rgb(p, q, h - 1/3)
return r, g, b
def hex_to_rgb(rgb: str) -> t.Tuple[float, float, float]:
assert rgb[0] == "#"
if len(rgb) == len("#rgb"):
elementlength = 1
else:
assert len(rgb) == len("#rrggbb")
elementlength = 2
return [int(rgb[i:i + elementlength], 16) / (16 ** elementlength - 1)
for i in range(1, len(rgb), elementlength)]
def rgb_to_hex(r: float, g: float, b: float) -> str:
assert 0 <= r <= 1
assert 0 <= g <= 1
assert 0 <= b <= 1
return "#" + "".join(
"%02x" % int(round(c * 255)) for c in (r, g, b))
def lighter(rgb: str, pct: float):
assert 0 < pct <= 100
r, g, b = hex_to_rgb(rgb)
h, s, l = rgb_to_hsl(r, g, b)
l = 1 - (1 - l) / (1 + pct / 100)
return rgb_to_hex(*hsl_to_rgb(h, s, l))
class RunDataNoMatchException(Exception):
def __init__(self, runData: RunData):
self.runData = runData
super().__init__("Ran out of data to match")
class RunDataOutOfLinesException(Exception):
def __init__(self):
super().__init__("No more lines")
TYPE_MAP = {
"go-native": "Go (native)",
"go": "Go (WebAssembly)",
"tinygo": "TinyGo",
"fzf-for-js": "fzf-for-js",
"gopherjs": "GopherJS",
"go-debugnogc": "Go (WebAssembly; no GC)",
"tinygo-leakinggc": "TinyGo (no GC)",
"go-native-nogc": "Go (native; no GC)",
}
COLOUR_MAP = {
"Go (native)": ["#003f5c", "#668eaa", "#002633"],
"Go (native; no GC)": ["#ffa600", "#ffcc33"],
"Go (WebAssembly)": ["#58508d", "#9e94c5", "#262145"],
"Go (WebAssembly; no GC)": ["#9e94ff", "#b7b2ff"],
"TinyGo": ["#bc5090", "#df94be", "#8F2464"],
"TinyGo (no GC)": ["#00c786", "#33ffa0"],
"fzf-for-js": ["#ff6361", "#ffa097", "#cc2020"],
"GopherJS": ["#ffa600", "#ffc171", "#cc5000"],
}
COLOUR_MAP = {
**COLOUR_MAP,
**{f"{key} - {browser}": [lighter(v, pct) for v in value]
for key, value in COLOUR_MAP.items()
for browser, pct in [
("Firefox", 20),
("Chrome", 40),
("Safari", 60),
("Edge", 80),
]}
}
LOG2_MAP = {2**i: i for i in range(40)}
class RunData:
fzf_type: str = None
nrlines: int = None
lines_load_time_ms: int = None
fzf_init_time_ms: int = None
memory_used_mib: float = None
search_times_ms_nr_results: t.MutableMapping[str, t.Tuple[int, int]] = None
aborted: bool
browser: bool
def popuntilstartmatch(self, lines: t.MutableSequence[str], start: str) -> str:
try:
while not (line := lines.pop()).startswith(start):
if line.startswith("******"):
self.aborted = True
lines.append(line)
raise RunDataNoMatchException(self)
except IndexError:
self.aborted = True
raise RunDataNoMatchException(self)
return line
def __init__(self, lines: t.MutableSequence[str]):
self.aborted = False
self.search_times_ms_nr_results = {}
try:
while not (line := lines.pop()).startswith("******"):
pass
except IndexError:
raise RunDataOutOfLinesException()
line = self.popuntilstartmatch(lines, "fzf-type: ")
raw_fzf_type = line.split()[1]
if any(raw_fzf_type.endswith(f"-{x}")
for x in ("edge", "safari", "firefox", "chrome")):
base, browser = raw_fzf_type.rsplit("-", 1)
self.fzf_type = TYPE_MAP[base] + f" - {browser.capitalize()}"
self.browser = True
else:
self.fzf_type = TYPE_MAP[raw_fzf_type]
self.browser = False
line = self.popuntilstartmatch(lines, "lines.txt loaded:")
_, _, nrlines, _, _, lines_load_time_ms = line.split()
self.nrlines = int(nrlines)
self.lines_load_time_ms = int(lines_load_time_ms)
line = self.popuntilstartmatch(lines, "Fzf initialized ")
self.fzf_init_time_ms = int(line.split()[-1]) - self.lines_load_time_ms
while "hello world" not in self.search_times_ms_nr_results:
line = self.popuntilstartmatch(lines, "Searching for '")
nrresults = int(line.split()[-2])
line = lines.pop()
assert line.startswith(f"--- ../{self.nrlines}.txt "), line
searchtime = int(line.split()[2])
searchterm = line.split(" ", 4)[-1]
if lines[-1].startswith("hash: "):
line = lines.pop()
assert line.startswith("hash: ")
hash = line.split()[1][:5]
else:
hash = None
if lines[-1].startswith("+++ filename "):
line = lines.pop()
gosearchtime = int(line.split()[2])
else:
gosearchtime = None
self.search_times_ms_nr_results[searchterm] = (searchtime, gosearchtime, hash, nrresults)
if self.browser:
self.memory_used_mib = None
else:
line = self.popuntilstartmatch(lines, " Maximum resident set size (kbytes):")
self.memory_used_mib = float(line.split()[-1]) / 1024
def __repr__(self):
aborted = "<aborted>" if self.aborted else ""
memused = self.memory_used_mib and round(self.memory_used_mib, 1)
return (
f"RunData{aborted}: {self.fzf_type}({self.nrlines}). "
f"load {self.lines_load_time_ms} ms; "
f"fzf init {self.fzf_init_time_ms} ms; "
f"search results: {self.search_times_ms_nr_results}; "
f"memory used results: {memused} MiB; "
)
def loadRunData() -> t.Sequence[RunData]:
runDatas: t.MutableSequence[RunData] = []
for filename in (
pathlib.Path(__file__).parent / "results-native-2.txt",
pathlib.Path(__file__).parent / "results-native-nogc-2.txt",
pathlib.Path(__file__).parent / "results.browsers.txt",
pathlib.Path(__file__).parent / "results-new.txt",
pathlib.Path(__file__).parent / "results-debugnogc.txt",
):
data = pathlib.Path(filename).read_text()
lines = list(reversed(data.splitlines()))
while True:
try:
runData = RunData(lines)
runDatas.append(runData)
except RunDataNoMatchException as e:
runDatas.append(e.runData)
except RunDataOutOfLinesException:
break
hashes = {}
for runData in runDatas:
if runData.aborted:
continue
key = runData.nrlines
myhashes = tuple([i[2] for i in runData.search_times_ms_nr_results.values()])
if key in hashes:
if hashes[key][0] != myhashes:
print(f"For {key}:\n {hashes[key][0]} ({hashes[key][1]}) !=\n {myhashes} {runData.fzf_type}")
breakpoint()
else:
hashes[key] = (myhashes, runData.fzf_type)
return t.cast(t.Sequence[RunData], runDatas)
def markdown_table(data, large_small_multiplier) -> str:
totaldata = {
key: {
nr: np.sum(data[key][nr]) for nr in data[key]
} for key in data
}
return "\n".join(
[
"|".join(["Haystack size", *[key for key in data]]),
"|".join(["---"] * (len(data) + 1)),
*[
"|".join([
f"2<sup>{LOG2_MAP[nr]}</sup> = {nr}",
*["---" if np.isnan(dfk[nr])
else
f"{dfk[nr]:.2f} ({dfk[nr] * large_small_multiplier / nr:.1f})"
for key, dfk in totaldata.items()],
])
for nr in list(data.values())[0]
]
]
)
def do_create_table_and_plot(
ax,
nrlinesexp: t.Sequence[int],
data_element_getter: t.Callable[[RunData], t.Sequence[float]],
to_show: t.Sequence[t.Optional[str]],
colourmap: t.Sequence[int],
ylim: t.Tuple[float, float],
large_small_multiplier: float=1e6,
):
runDatas = loadRunData()
fzf_types = {r.fzf_type for r in runDatas}
assert all(key in fzf_types for key in to_show if key is not None)
data = {key: {2**nr: [] for nr in nrlinesexp}
for key in to_show if key is not None}
runData: RunData
datalength = len(colourmap)
for runData in runDatas:
if (
runData.aborted
or (key := runData.fzf_type) not in data
or (nrlines := runData.nrlines) not in data[key]):
continue
data[key][nrlines].append(data_element_getter(runData))
assert datalength == len(data[key][nrlines][-1])
# calculate averages
for key in data:
for nr in data[key]:
if data[key][nr]:
data[key][nr] = np.mean(data[key][nr], axis=0)
else:
data[key][nr] = np.full((datalength, ), np.nan)
xaxis = nrlinesexp - nrlinesexp[0]
ax.set_xticks(xaxis)
ax.set_xticklabels([f"$2^{{{exp}}}$" for exp in nrlinesexp], rotation=45)
gap = (ylim[1] - ylim[0]) / 500
bargap = "".join(" " if k is None else "b" for k in to_show)
nrbars = bargap.count("b")
nrgaps = len(bargap.strip()) - nrbars
width = 0.9 / (nrbars + nrgaps / 2)
x_offset = -0.45
for label in to_show:
if label is None:
x_offset += width / 2
continue
bottom = np.zeros((len(xaxis), ))
for a in range(datalength):
itemdata = np.array([data[label][2**exp][a] for exp in nrlinesexp]
) / 2**nrlinesexp * large_small_multiplier
colour = COLOUR_MAP[label][colourmap[a]]
ax.bar(xaxis[:] + x_offset,
itemdata - (gap if a < datalength - 1 else 0),
bottom=bottom,
width=width,
color=colour,
label = label if a == min(1, datalength - 1) else None)
bottom += itemdata
x_offset += width
ax.set_ylim(*ylim)
return markdown_table(data, large_small_multiplier)
| 11,979 | 4,425 |
'''
The follwing code runs a test lstm network on the CIFAR dataset
I will explicitly write the networks here for ease of understanding
with cnn_sropout = 0.4 and rnn dropout = 0.2 and lr = 1e-3 res = 8
################# cnn_lstm_True Validation Accuracy = [0.363, 0.4258, 0.4332, 0.4142, 0.4802, 0.4838, 0.4988, 0.4694, 0.5018, 0.5072, 0.5216, 0.5204, 0.5282, 0.5354, 0.5392, 0.541, 0.5372, 0.5496, 0.5488, 0.5458, 0.5514, 0.5464, 0.5598, 0.5612, 0.549, 0.561, 0.562, 0.5608, 0.572, 0.5562]
################# cnn_lstm_True Training Accuracy = [0.2576222, 0.37971112, 0.41331112, 0.43568888, 0.45224443, 0.46142223, 0.4724, 0.48204446, 0.4924889, 0.49795556, 0.5046667, 0.50751114, 0.5161778, 0.5168, 0.5233778, 0.52584445, 0.53113335, 0.5362, 0.5368, 0.5395333, 0.5430667, 0.5438667, 0.54568887, 0.54833335, 0.5525111, 0.5526, 0.55462223, 0.5564889, 0.55682224, 0.5594]
with cnn_sropout = 0.4 and rnn dropout = 0.2 and lr = 1e-3 res = 16
################# extended_cnn_one_img Validation Accuracy = [0.4394, 0.481, 0.529, 0.5436, 0.5632, 0.5732, 0.5672, 0.5796, 0.5934, 0.6008, 0.5946, 0.5978, 0.6074, 0.6104, 0.6134, 0.6156, 0.6122, 0.6168, 0.6064, 0.6142, 0.6182, 0.6208, 0.6314, 0.6186, 0.614, 0.6234, 0.6166, 0.621, 0.6124, 0.6086]
################# extended_cnn_one_img Training Accuracy = [0.28697777, 0.42, 0.46337777, 0.49582222, 0.52477777, 0.54244447, 0.5523111, 0.56891114, 0.58144444, 0.5856, 0.5954667, 0.60253334, 0.60866666, 0.61322224, 0.62204444, 0.6220889, 0.627, 0.6315778, 0.63177776, 0.63802224, 0.63993335, 0.64397776, 0.6459778, 0.6482889, 0.65115553, 0.64971113, 0.653, 0.65335554, 0.65393335, 0.6591778]
################# cnn_convlstm_True Validation Accuracy = [0.4204, 0.4466, 0.5022, 0.5348, 0.5416, 0.542, 0.5822, 0.5834, 0.5962, 0.6112, 0.6086, 0.6198, 0.611, 0.6158, 0.6174, 0.6324, 0.6374, 0.6374, 0.6318, 0.639, 0.643, 0.6486, 0.6452, 0.6456, 0.6456, 0.644, 0.6628, 0.6512, 0.6426, 0.6474]
################# cnn_convlstm_True Training Accuracy = [0.28697777, 0.42, 0.46337777, 0.49582222, 0.52477777, 0.54244447, 0.5523111, 0.56891114, 0.58144444, 0.5856, 0.5954667, 0.60253334, 0.60866666, 0.61322224, 0.62204444, 0.6220889, 0.627, 0.6315778, 0.63177776, 0.63802224, 0.63993335, 0.64397776, 0.6459778, 0.6482889, 0.65115553, 0.64971113, 0.653, 0.65335554, 0.65393335, 0.6591778]
with cnn_sropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 res = 8 out.813114
################# cnn_lstm_True Validation Accuracy = [0.3308, 0.3894, 0.4208, 0.4178, 0.4472, 0.4612, 0.4562, 0.4678, 0.4576, 0.4804, 0.4888, 0.4942, 0.504, 0.5104, 0.5124, 0.4714, 0.
5052, 0.5128, 0.5178, 0.5214, 0.5184, 0.5234, 0.5138, 0.5288, 0.534, 0.5274, 0.5338, 0.5252, 0.5196, 0.5238, 0.533, 0.5228, 0.5294, 0.541, 0.5432, 0.5308, 0.5396, 0.5438, 0.5548, 0.5496, 0.5416, 0.5376, 0.5434, 0.5482, 0.5476, 0.544, 0.5478, 0.5488, 0.5316, 0.541, 0.5458, 0.5502, 0.5538, 0.545, 0.5434, 0.5446, 0.5262, 0.565, 0.5524, 0.547, 0.558, 0.5534, 0.5504, 0.5572, 0.558, 0.5518, 0.5628, 0.5458, 0.5492, 0.554, 0.5502, 0.5662, 0.5554, 0.5544, 0.556, 0.5614, 0.556, 0.5494, 0.5626, 0.553, 0.5548, 0.5552, 0.5594, 0.5624, 0.5602, 0.5586, 0.5626, 0.5552, 0.5556, 0.5568, 0.5614, 0.5646, 0.5588, 0.5546, 0.5672, 0.5686, 0.5654, 0.5696, 0.561, 0.5594]
################# cnn_lstm_True Training Accuracy = [0.24964444, 0.35444444, 0.39055556, 0.40411112, 0.42033333, 0.4307778, 0.4413778, 0.4502, 0.45922223, 0.4670222, 0.47257778, 0.47993332, 0.48346666, 0.48924443, 0.49424446, 0.49951112, 0.50535554, 0.507, 0.5122667, 0.51573336, 0.5187111, 0.52257776, 0.52484447, 0.52666664, 0.5283333, 0.5331333, 0.5357556, 0.5382222, 0.5380667, 0.54113334, 0.5438667, 0.5438222, 0.54602224, 0.5493778, 0.55248886, 0.55455554, 0.5526, 0.55502224, 0.5570222, 0.557, 0.5587556, 0.5602889, 0.56182224, 0.5638667, 0.5647111, 0.5691778, 0.5662889, 0.5692222, 0.56711113, 0.57075554, 0.5707333, 0.57548887, 0.5728667, 0.57446665, 0.5751778, 0.57706666, 0.5799556, 0.5784444, 0.5833333, 0.583, 0.58104444, 0.58404446, 0.58264446, 0.5810222, 0.5852444, 0.5855778, 0.5874, 0.5886889, 0.5931111, 0.5919333, 0.59191114, 0.5890222, 0.59022224, 0.59191114, 0.58986664, 0.5920445, 0.5929111, 0.5968222, 0.5930667, 0.59926665, 0.59415555, 0.5968889, 0.5962222, 0.59933335, 0.5995778, 0.5975111, 0.6013333, 0.6011111, 0.6008667, 0.60124445, 0.6018889, 0.60388887, 0.6032, 0.6028889, 0.60502225, 0.6044667, 0.60304445, 0.60517776, 0.6042445, 0.6062667]
with cnn_sropout = 0.2 and rnn dropout = 0.2 and lr = 5e-4 res = 8 out.812846
################# extended_cnn_one_img Validation Accuracy = [0.3528, 0.3696, 0.3942, 0.4074, 0.4162, 0.4102, 0.4304, 0.4336, 0.4502, 0.4432, 0.4534, 0.458, 0.4572, 0.4596, 0.453, 0.45
36, 0.468, 0.472, 0.47, 0.4638, 0.475, 0.4618, 0.466, 0.473, 0.4718, 0.4648, 0.467, 0.4684, 0.4666, 0.4708, 0.4746, 0.4752, 0.4722, 0.4814, 0.4782, 0.4836, 0.4778, 0.4712, 0.4828, 0.471
6, 0.481, 0.4762, 0.475, 0.4746, 0.4784, 0.479, 0.4806, 0.4776, 0.4786, 0.4798, 0.478, 0.4786, 0.4814, 0.4792, 0.4728, 0.4764, 0.471, 0.475, 0.467, 0.4794, 0.4802, 0.4814, 0.4766, 0.471
2, 0.4782, 0.4822, 0.4746, 0.473, 0.4758, 0.4748, 0.4726, 0.4756, 0.4758, 0.4782, 0.4786, 0.4714, 0.4752, 0.4752, 0.4728, 0.4814, 0.478, 0.4746, 0.4704, 0.481, 0.4728, 0.4734, 0.4778, 0
.4764, 0.4746, 0.4814, 0.4754, 0.4804, 0.4776, 0.4736, 0.4716, 0.475, 0.4754, 0.481, 0.4862, 0.4714]
################# extended_cnn_one_img Training Accuracy = [0.2808, 0.39051113, 0.4234, 0.44626668, 0.4642, 0.47853333, 0.4906889, 0.50313336, 0.5134889, 0.52297777, 0.5306, 0.53653336
, 0.5456, 0.5512222, 0.5568, 0.56384444, 0.5692667, 0.5714667, 0.5779333, 0.5827778, 0.58984447, 0.5953778, 0.5967111, 0.60213333, 0.6068222, 0.61006665, 0.6106222, 0.6146, 0.6157111, 0
.61895555, 0.6228, 0.6257778, 0.625, 0.62846667, 0.63384444, 0.6364889, 0.63751113, 0.6385111, 0.64015555, 0.64522225, 0.6471111, 0.6487333, 0.6544222, 0.6525111, 0.6541778, 0.6599778,
0.6571111, 0.6606445, 0.6649778, 0.66595554, 0.66293335, 0.6677333, 0.67242223, 0.6685778, 0.67415553, 0.67284447, 0.67606664, 0.67822224, 0.6788889, 0.68075556, 0.68237776, 0.6800889,
0.68597776, 0.6885333, 0.6876444, 0.6862889, 0.6900667, 0.6915111, 0.6921333, 0.69166666, 0.6956667, 0.6958445, 0.69706666, 0.6955111, 0.6986, 0.70177776, 0.7012889, 0.70471114, 0.70537
776, 0.70317775, 0.7037778, 0.70611113, 0.7081556, 0.70717776, 0.71, 0.7101111, 0.71122223, 0.7131778, 0.7135556, 0.7114889, 0.7172889, 0.71206665, 0.7187333, 0.7174889, 0.7177333, 0.72
12667, 0.72146666, 0.71922225, 0.7218222, 0.7225556]
################# cnn_lstm_True Validation Accuracy = [0.3562, 0.4108, 0.4418, 0.468, 0.48, 0.4946, 0.4864, 0.5004, 0.5002, 0.521, 0.5286, 0.5346, 0.5376, 0.5412, 0.55, 0.5554, 0.5374,
0.5576, 0.571, 0.5506, 0.5658, 0.575, 0.5744, 0.5736, 0.5734, 0.5796, 0.573, 0.5888, 0.5766, 0.5766, 0.5814, 0.5784, 0.5756, 0.5816, 0.5844, 0.5826, 0.5878, 0.583, 0.5914, 0.5846, 0.5868, 0.5764, 0.5888, 0.5938, 0.5884, 0.5892, 0.5814, 0.5946, 0.5846, 0.5918, 0.5902, 0.5908, 0.5862, 0.5914, 0.5934, 0.5904, 0.591, 0.5996, 0.5876, 0.5954, 0.5924, 0.5976, 0.5858, 0.5944, 0.5912, 0.588, 0.594, 0.5902, 0.5898, 0.5882, 0.5852, 0.5844, 0.5862, 0.5878, 0.5884, 0.5972, 0.5944, 0.5882, 0.5828, 0.5908, 0.589, 0.5916, 0.5966, 0.593, 0.5802, 0.5934, 0.5908, 0.5952, 0.587, 0.5858, 0.5918, 0.591, 0.5912, 0.589, 0.5882, 0.5906, 0.5878, 0.588, 0.5894, 0.5916]
################# cnn_lstm_True Training Accuracy = [0.2808, 0.39051113, 0.4234, 0.44626668, 0.4642, 0.47853333, 0.4906889, 0.50313336, 0.5134889, 0.52297777, 0.5306, 0.53653336, 0.5456, 0.5512222, 0.5568, 0.56384444, 0.5692667, 0.5714667, 0.5779333, 0.5827778, 0.58984447, 0.5953778, 0.5967111, 0.60213333, 0.6068222, 0.61006665, 0.6106222, 0.6146, 0.6157111, 0.61895555, 0.6228, 0.6257778, 0.625, 0.62846667, 0.63384444, 0.6364889, 0.63751113, 0.6385111, 0.64015555, 0.64522225, 0.6471111, 0.6487333, 0.6544222, 0.6525111, 0.6541778, 0.6599778, 0.6571111, 0.6606445, 0.6649778, 0.66595554, 0.66293335, 0.6677333, 0.67242223, 0.6685778, 0.67415553, 0.67284447, 0.67606664, 0.67822224, 0.6788889, 0.68075556, 0.68237776, 0.6800889, 0.68597776, 0.6885333, 0.6876444, 0.6862889, 0.6900667, 0.6915111, 0.6921333, 0.69166666, 0.6956667, 0.6958445, 0.69706666, 0.6955111, 0.6986, 0.70177776, 0.7012889, 0.70471114, 0.70537776, 0.70317775, 0.7037778, 0.70611113, 0.7081556, 0.70717776, 0.71, 0.7101111, 0.71122223, 0.7131778, 0.7135556, 0.7114889, 0.7172889, 0.71206665, 0.7187333, 0.7174889, 0.7177333, 0.7212667, 0.72146666, 0.71922225, 0.7218222, 0.7225556]
with cnn_sropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 and 500 epochs out.813765
################# extended_cnn_one_img Training Accuracy = [0.24584444, 0.35053334, 0.38793334, 0.40875554, 0.4229111, 0.4331111, 0.44337776, 0.44886667, 0.45893332, 0.46524444, 0.47291112, 0.47626665, 0.4856889, 0.48975554, 0.4916, 0.4988, 0.5033111, 0.5056889, 0.5113556, 0.5152444, 0.5168222, 0.5198889, 0.5234889, 0.52444446, 0.5282889, 0.5336889, 0.53297776, 0.5376889, 0.54246664, 0.53664446, 0.5434, 0.5458, 0.5467333, 0.5486444, 0.5535111, 0.5506222, 0.5524667, 0.55295557, 0.55697775, 0.5574667, 0.5597111, 0.5593111, 0.56273335, 0.56615555, 0.56457776, 0.5658889, 0.56504446, 0.56744444, 0.5668667, 0.5719111, 0.56886667, 0.57093334, 0.5731556, 0.5764889, 0.5733111, 0.5746889, 0.5784889, 0.57868886, 0.5796667, 0.57868886, 0.58095556, 0.5823333, 0.5834444, 0.58566666, 0.5847778, 0.5849111, 0.58408886, 0.5852889, 0.58735555, 0.58813334, 0.58802223, 0.5897111, 0.5891778, 0.59106666, 0.58977777, 0.59164447, 0.5935778, 0.59155554, 0.5924444, 0.5958, 0.5974889, 0.5984222, 0.59635556, 0.59797776, 0.5967111, 0.59882224, 0.59864444, 0.59995556, 0.59793335, 0.6014, 0.5981111, 0.60044444, 0.60055554, 0.60208887, 0.6009778, 0.60113335, 0.6046, 0.6018889, 0.60624444, 0.6012, 0.60373336, 0.6020667, 0.60388887, 0.60364443, 0.60344446, 0.60855556, 0.6080667, 0.6056, 0.6059333, 0.61097777, 0.6092, 0.6079778, 0.6118444, 0.6070667, 0.6104, 0.60895556, 0.6101556, 0.6104444, 0.61002225, 0.6122, 0.6102222, 0.6121778, 0.61095554, 0.6102667, 0.61075556, 0.61311114, 0.6121778, 0.6160667, 0.61502224, 0.61444443, 0.61435556, 0.61344445, 0.61355555, 0.6150444, 0.6168444, 0.6152889, 0.6140444, 0.6184222, 0.61513335, 0.6177111, 0.61388886, 0.61653334, 0.61455554, 0.61595553, 0.62053335, 0.61826664, 0.6192667, 0.62093335, 0.6173556, 0.61895555, 0.61726665, 0.6194222, 0.6232, 0.62115556, 0.6197111, 0.62035555, 0.61844444, 0.62042224, 0.618, 0.6223556, 0.61902225, 0.62288886, 0.6220222, 0.6221778, 0.6239111, 0.6190889, 0.6250889, 0.6246, 0.6218, 0.62484443, 0.6250889, 0.6202889, 0.6244889, 0.62333333, 0.62457776, 0.6242, 0.6236, 0.6252, 0.6274667, 0.6245555, 0.6241111, 0.6262, 0.6253778, 0.6244444, 0.6254, 0.6255556, 0.6254, 0.62355554, 0.62986666, 0.6236445, 0.6255556, 0.62682223, 0.6252222, 0.6265778, 0.62684447, 0.62684447, 0.6264667, 0.6289333, 0.63042223, 0.62946665, 0.62873334, 0.6296889, 0.6269111, 0.6298222, 0.62975556, 0.6280889, 0.6296667, 0.6295556, 0.62873334, 0.6278222, 0.6266222, 0.6314222, 0.63211113, 0.62813336, 0.6260667, 0.6296889, 0.6291111, 0.63251114, 0.62813336, 0.63071114, 0.62946665, 0.6320889, 0.62913334, 0.63177776, 0.6306667, 0.63008887, 0.6332222, 0.6346, 0.63104445, 0.6309111, 0.6326, 0.6289333, 0.6310667, 0.6288889, 0.6339333, 0.63155556, 0.6330889, 0.6311111, 0.634, 0.63233334, 0.6316222, 0.63533336, 0.6349556, 0.63482225, 0.63224447, 0.6336667, 0.6331556, 0.6326, 0.63533336, 0.63024443, 0.6355778, 0.6332222, 0.6337111, 0.6360889, 0.6368222, 0.6360889, 0.6338222, 0.6360222, 0.63537776, 0.6355111, 0.6344444, 0.63255554, 0.634, 0.6377778, 0.6331111, 0.63493335, 0.63935554, 0.63553333, 0.63537776, 0.6352889, 0.63637775, 0.6369111, 0.6370889, 0.6368, 0.6359556, 0.6358889, 0.6383111, 0.6369111, 0.6352889, 0.6394445, 0.6378667, 0.63688886, 0.6374889, 0.6386222, 0.63902223, 0.6359556, 0.6384889, 0.63893336, 0.63897777, 0.6379111, 0.63611114, 0.6355778, 0.6419778, 0.6392, 0.6389111, 0.6415333, 0.63953334, 0.63868886, 0.6379111, 0.63913333, 0.63766664, 0.6381556, 0.6368222, 0.6410667, 0.6410667, 0.6398444, 0.63795555, 0.63913333, 0.6403111, 0.6416, 0.6383333, 0.63766664, 0.63964444, 0.64206666, 0.6381556, 0.63857776, 0.6432, 0.6412, 0.64064443, 0.63824445, 0.63766664, 0.6410889, 0.63915557, 0.64075553, 0.6404667, 0.64093333, 0.64284444, 0.6405111, 0.63835555, 0.6406, 0.6419111, 0.6398, 0.64115554, 0.6413556, 0.6391111, 0.64213336, 0.64104444, 0.64022225, 0.6409111, 0.64262223, 0.6416444, 0.6382, 0.6426889, 0.64284444, 0.64493334, 0.63913333, 0.6441111, 0.6398, 0.6419111, 0.6436, 0.6432, 0.63942224, 0.64055556, 0.6418889, 0.6424222, 0.63997775, 0.6433111, 0.644, 0.64306664, 0.6451333, 0.6403555, 0.6419111, 0.64273334, 0.6437111, 0.6440667, 0.6418667, 0.6412889, 0.6440667, 0.6432, 0.64526665, 0.64357775, 0.64475554, 0.6430445, 0.64426666, 0.6438444, 0.6436889, 0.6428, 0.64213336, 0.641, 0.64446664, 0.6433778, 0.6418, 0.6429333, 0.6446667, 0.6440667, 0.6464, 0.6455111, 0.6448889, 0.6445111, 0.644, 0.6441778, 0.6432222, 0.6438, 0.64408886, 0.64713335, 0.6451111, 0.6422222, 0.64706665, 0.6412889, 0.64408886, 0.6448445, 0.6454222, 0.6473333, 0.6446, 0.6433778, 0.6444889, 0.6439111, 0.64522225, 0.6419111, 0.6449111, 0.64486665, 0.6442889, 0.6469778, 0.6426889, 0.6433333, 0.6464222, 0.6457555, 0.6475111, 0.6465333, 0.64537776, 0.6464, 0.6455778, 0.6430445, 0.64566666, 0.6456889, 0.6478, 0.6455333, 0.64435554, 0.64713335, 0.647, 0.64662224, 0.6469778, 0.6496222, 0.6471556, 0.6464667, 0.64364445, 0.64504445, 0.6447778, 0.6450222, 0.64857775, 0.64626664, 0.6459778, 0.64437777, 0.6447333, 0.6483333, 0.64633334, 0.64768887, 0.64606667, 0.6450667, 0.6474, 0.6499111, 0.6482, 0.6452, 0.64455557, 0.64555556, 0.6479333, 0.64588886, 0.645, 0.64797777, 0.64615554, 0.6454, 0.64804447, 0.647, 0.6514, 0.64791113, 0.64966667, 0.6441778, 0.64926666, 0.6470444, 0.6458, 0.64806664, 0.6482889, 0.6496889, 0.6482222, 0.6465778, 0.6495111, 0.6444889, 0.64757776, 0.64746666, 0.65224445, 0.64753336, 0.6496889, 0.6497333, 0.64537776, 0.6504222, 0.6500889, 0.6496, 0.65062225, 0.6485556, 0.6477778, 0.6486889, 0.64784443, 0.6482667, 0.6487333, 0.64831114, 0.6482, 0.6495778, 0.6486, 0.64651114, 0.64964443]
################# cnn_lstm_True Validation Accuracy = [0.3258, 0.3998, 0.4076, 0.4294, 0.4372, 0.4422, 0.451, 0.4632, 0.4748, 0.477, 0.4832, 0.4968, 0.4994, 0.503, 0.5034, 0.5236, 0.526, 0.5234, 0.5166, 0.534, 0.5202, 0.5254, 0.5302, 0.5328, 0.5454, 0.5486, 0.5388, 0.5438, 0.5492, 0.5422, 0.545, 0.5508, 0.5528, 0.5472, 0.5574, 0.5572, 0.553, 0.555, 0.5528, 0.556, 0.5542, 0.5568, 0.5648, 0.5676, 0.557, 0.5638, 0.56, 0.554, 0.5686, 0.568, 0.5676, 0.5602, 0.5674, 0.5626, 0.568, 0.5692, 0.5686, 0.5644, 0.568, 0.5724, 0.5688, 0.5652, 0.5766, 0.5758, 0.572, 0.5648, 0.5664, 0.571, 0.5752, 0.5738, 0.5834, 0.5786, 0.5676, 0.5814, 0.5706, 0.5756, 0.5734, 0.5784, 0.5702, 0.5754, 0.5702, 0.5686, 0.5736, 0.5814, 0.5752, 0.586, 0.576, 0.5808, 0.5864, 0.5776, 0.5764, 0.5796, 0.5734, 0.5688, 0.584, 0.583, 0.585, 0.5692, 0.5818, 0.5878, 0.582, 0.572, 0.5874, 0.5854, 0.5942, 0.5814, 0.5964, 0.5848, 0.5852, 0.5888, 0.5876, 0.5818, 0.5832, 0.5856, 0.584, 0.5798, 0.5872, 0.584, 0.5842, 0.5848, 0.5848, 0.5834, 0.5856, 0.5892, 0.5848, 0.5842, 0.5838, 0.5784, 0.5748, 0.5848, 0.5836, 0.5878, 0.5872, 0.5864, 0.5798, 0.5838, 0.5802, 0.588, 0.5904, 0.5854, 0.5834, 0.5856, 0.5928, 0.5916, 0.581, 0.5816, 0.5878, 0.5796, 0.5932, 0.584, 0.5938, 0.582, 0.5874, 0.5892, 0.5864, 0.583, 0.576, 0.5912, 0.5932, 0.5944, 0.5894, 0.5892, 0.5954, 0.5874, 0.5882, 0.5954, 0.591, 0.5912, 0.5826, 0.5888, 0.597, 0.594, 0.587, 0.5894, 0.5848, 0.5982, 0.5968, 0.5878, 0.5898, 0.5808, 0.5876, 0.5808, 0.5844, 0.5944, 0.5844, 0.5932, 0.5884, 0.594, 0.5948, 0.5848, 0.5964, 0.5794, 0.5872, 0.5864, 0.5858, 0.5858, 0.5912, 0.5888, 0.5924, 0.5912, 0.599, 0.5954, 0.5854, 0.5938, 0.591, 0.5896, 0.5952, 0.5858, 0.597, 0.585, 0.5852, 0.5906, 0.5926, 0.5814, 0.592, 0.589, 0.587, 0.5938, 0.5938, 0.592, 0.596, 0.5954, 0.587, 0.596, 0.586, 0.5954, 0.5908, 0.5916, 0.5946, 0.5874, 0.5982, 0.5922, 0.5972, 0.586, 0.5942, 0.5898, 0.5978, 0.5988, 0.5882, 0.5942, 0.5962, 0.5922, 0.5926, 0.591, 0.594, 0.5892, 0.587, 0.5884, 0.591, 0.5926, 0.5926, 0.5924, 0.5874, 0.593, 0.5952, 0.5902, 0.5958, 0.5832, 0.5942, 0.588, 0.5954, 0.59, 0.5908, 0.5888, 0.5976, 0.5936, 0.5938, 0.5904, 0.5988, 0.585, 0.5942, 0.5938, 0.5988, 0.5934, 0.5998, 0.5958, 0.5994, 0.5922, 0.5904, 0.5836, 0.5914, 0.589, 0.5942, 0.5918, 0.5976, 0.5876, 0.596, 0.602, 0.5864, 0.5852, 0.5938, 0.5944, 0.5908, 0.598, 0.5916, 0.5886, 0.5916, 0.5852, 0.58, 0.583, 0.5928, 0.5916, 0.5908, 0.5952, 0.5858, 0.5918, 0.5934, 0.5976, 0.586, 0.5906, 0.583, 0.5986, 0.5856, 0.5886, 0.5932, 0.5938, 0.5918, 0.5936, 0.5848, 0.5924, 0.5922, 0.5926, 0.589, 0.5928, 0.595, 0.5888, 0.5932, 0.5898, 0.5838, 0.5842, 0.5976, 0.5918, 0.5936, 0.593, 0.593, 0.5844, 0.5918, 0.5986, 0.6016, 0.5896, 0.5988, 0.601, 0.5956, 0.5932, 0.5904, 0.5974, 0.5862, 0.6016, 0.5966, 0.5908, 0.5886, 0.5918, 0.5906, 0.5944, 0.5902, 0.591, 0.5868, 0.5924, 0.5934, 0.5946, 0.596, 0.5918, 0.597, 0.5868, 0.5882, 0.5834, 0.5856, 0.5898, 0.5934, 0.5862, 0.5892, 0.5928, 0.5902, 0.592, 0.59, 0.5844, 0.5836, 0.5864, 0.5894, 0.5912, 0.5932, 0.5854, 0.5896, 0.593, 0.5864, 0.6004, 0.5906, 0.5868, 0.5984, 0.5912, 0.5892, 0.596, 0.592, 0.5972, 0.5964, 0.5996, 0.5936, 0.5958, 0.5942, 0.5904, 0.5966, 0.5952, 0.5882, 0.5966, 0.5958, 0.5948, 0.5932, 0.6024, 0.6, 0.5972, 0.5968, 0.5954, 0.595, 0.595, 0.5944, 0.5952, 0.5952, 0.6006, 0.597, 0.5948, 0.59, 0.5936, 0.5916, 0.5946, 0.5984, 0.5914, 0.5988, 0.5964, 0.5908, 0.5906, 0.593, 0.5894, 0.5938, 0.5916, 0.5916, 0.5908, 0.5994, 0.594, 0.5926, 0.5946, 0.601, 0.5966, 0.5992, 0.6, 0.5968, 0.5948, 0.591, 0.5972, 0.5952, 0.595, 0.591, 0.5948, 0.5956, 0.5956, 0.5932, 0.5962, 0.5992, 0.6028, 0.5988, 0.5962, 0.6004, 0.5978, 0.5924, 0.5922, 0.5952, 0.5982, 0.604, 0.5998, 0.6052, 0.5932, 0.602, 0.6012, 0.5986, 0.604, 0.5932, 0.5916, 0.5932, 0.5926, 0.5972, 0.5916, 0.5996, 0.5984, 0.5954, 0.5992, 0.6088, 0.5998, 0.5956, 0.5982, 0.5908, 0.5972, 0.5966, 0.5936, 0.5864, 0.5968, 0.587, 0.5912, 0.5936, 0.594, 0.605, 0.6]
################# cnn_lstm_True Training Accuracy = [0.24584444, 0.35053334, 0.38793334, 0.40875554, 0.4229111, 0.4331111, 0.44337776, 0.44886667, 0.45893332, 0.46524444, 0.47291112, 0.47626665, 0.4856889, 0.48975554, 0.4916, 0.4988, 0.5033111, 0.5056889, 0.5113556, 0.5152444, 0.5168222, 0.5198889, 0.5234889, 0.52444446, 0.5282889, 0.5336889, 0.53297776, 0.5376889, 0.54246664, 0.53664446, 0.5434, 0.5458, 0.5467333, 0.5486444, 0.5535111, 0.5506222, 0.5524667, 0.55295557, 0.55697775, 0.5574667, 0.5597111, 0.5593111, 0.56273335, 0.56615555, 0.56457776, 0.5658889, 0.56504446, 0.56744444, 0.5668667, 0.5719111, 0.56886667, 0.57093334, 0.5731556, 0.5764889, 0.5733111, 0.5746889, 0.5784889, 0.57868886, 0.5796667, 0.57868886, 0.58095556, 0.5823333, 0.5834444, 0.58566666, 0.5847778, 0.5849111, 0.58408886, 0.5852889, 0.58735555, 0.58813334, 0.58802223, 0.5897111, 0.5891778, 0.59106666, 0.58977777, 0.59164447, 0.5935778, 0.59155554, 0.5924444, 0.5958, 0.5974889, 0.5984222, 0.59635556, 0.59797776, 0.5967111, 0.59882224, 0.59864444, 0.59995556, 0.59793335, 0.6014, 0.5981111, 0.60044444, 0.60055554, 0.60208887, 0.6009778, 0.60113335, 0.6046, 0.6018889, 0.60624444, 0.6012, 0.60373336, 0.6020667, 0.60388887, 0.60364443, 0.60344446, 0.60855556, 0.6080667, 0.6056, 0.6059333, 0.61097777, 0.6092, 0.6079778, 0.6118444, 0.6070667, 0.6104, 0.60895556, 0.6101556, 0.6104444, 0.61002225, 0.6122, 0.6102222, 0.6121778, 0.61095554, 0.6102667, 0.61075556, 0.61311114, 0.6121778, 0.6160667, 0.61502224, 0.61444443, 0.61435556, 0.61344445, 0.61355555, 0.6150444, 0.6168444, 0.6152889, 0.6140444, 0.6184222, 0.61513335, 0.6177111, 0.61388886, 0.61653334, 0.61455554, 0.61595553, 0.62053335, 0.61826664, 0.6192667, 0.62093335, 0.6173556, 0.61895555, 0.61726665, 0.6194222, 0.6232, 0.62115556, 0.6197111, 0.62035555, 0.61844444, 0.62042224, 0.618, 0.6223556, 0.61902225, 0.62288886, 0.6220222, 0.6221778, 0.6239111, 0.6190889, 0.6250889, 0.6246, 0.6218, 0.62484443, 0.6250889, 0.6202889, 0.6244889, 0.62333333, 0.62457776, 0.6242, 0.6236, 0.6252, 0.6274667, 0.6245555, 0.6241111, 0.6262, 0.6253778, 0.6244444, 0.6254, 0.6255556, 0.6254, 0.62355554, 0.62986666, 0.6236445, 0.6255556, 0.62682223, 0.6252222, 0.6265778, 0.62684447, 0.62684447, 0.6264667, 0.6289333, 0.63042223, 0.62946665, 0.62873334, 0.6296889, 0.6269111, 0.6298222, 0.62975556, 0.6280889, 0.6296667, 0.6295556, 0.62873334, 0.6278222, 0.6266222, 0.6314222, 0.63211113, 0.62813336, 0.6260667, 0.6296889, 0.6291111, 0.63251114, 0.62813336, 0.63071114, 0.62946665, 0.6320889, 0.62913334, 0.63177776, 0.6306667, 0.63008887, 0.6332222, 0.6346, 0.63104445, 0.6309111, 0.6326, 0.6289333, 0.6310667, 0.6288889, 0.6339333, 0.63155556, 0.6330889, 0.6311111, 0.634, 0.63233334, 0.6316222, 0.63533336, 0.6349556, 0.63482225, 0.63224447, 0.6336667, 0.6331556, 0.6326, 0.63533336, 0.63024443, 0.6355778, 0.6332222, 0.6337111, 0.6360889, 0.6368222, 0.6360889, 0.6338222, 0.6360222, 0.63537776, 0.6355111, 0.6344444, 0.63255554, 0.634, 0.6377778, 0.6331111, 0.63493335, 0.63935554, 0.63553333, 0.63537776, 0.6352889, 0.63637775, 0.6369111, 0.6370889, 0.6368, 0.6359556, 0.6358889, 0.6383111, 0.6369111, 0.6352889, 0.6394445, 0.6378667, 0.63688886, 0.6374889, 0.6386222, 0.63902223, 0.6359556, 0.6384889, 0.63893336, 0.63897777, 0.6379111, 0.63611114, 0.6355778, 0.6419778, 0.6392, 0.6389111, 0.6415333, 0.63953334, 0.63868886, 0.6379111, 0.63913333, 0.63766664, 0.6381556, 0.6368222, 0.6410667, 0.6410667, 0.6398444, 0.63795555, 0.63913333, 0.6403111, 0.6416, 0.6383333, 0.63766664, 0.63964444, 0.64206666, 0.6381556, 0.63857776, 0.6432, 0.6412, 0.64064443, 0.63824445, 0.63766664, 0.6410889, 0.63915557, 0.64075553, 0.6404667, 0.64093333, 0.64284444, 0.6405111, 0.63835555, 0.6406, 0.6419111, 0.6398, 0.64115554, 0.6413556, 0.6391111, 0.64213336, 0.64104444, 0.64022225, 0.6409111, 0.64262223, 0.6416444, 0.6382, 0.6426889, 0.64284444, 0.64493334, 0.63913333, 0.6441111, 0.6398, 0.6419111, 0.6436, 0.6432, 0.63942224, 0.64055556, 0.6418889, 0.6424222, 0.63997775, 0.6433111, 0.644, 0.64306664, 0.6451333, 0.6403555, 0.6419111, 0.64273334, 0.6437111, 0.6440667, 0.6418667, 0.6412889, 0.6440667, 0.6432, 0.64526665, 0.64357775, 0.64475554, 0.6430445, 0.64426666, 0.6438444, 0.6436889, 0.6428, 0.64213336, 0.641, 0.64446664, 0.6433778, 0.6418, 0.6429333, 0.6446667, 0.6440667, 0.6464, 0.6455111, 0.6448889, 0.6445111, 0.644, 0.6441778, 0.6432222, 0.6438, 0.64408886, 0.64713335, 0.6451111, 0.6422222, 0.64706665, 0.6412889, 0.64408886, 0.6448445, 0.6454222, 0.6473333, 0.6446, 0.6433778, 0.6444889, 0.6439111, 0.64522225, 0.6419111, 0.6449111, 0.64486665, 0.6442889, 0.6469778, 0.6426889, 0.6433333, 0.6464222, 0.6457555, 0.6475111, 0.6465333, 0.64537776, 0.6464, 0.6455778, 0.6430445, 0.64566666, 0.6456889, 0.6478, 0.6455333, 0.64435554, 0.64713335, 0.647, 0.64662224, 0.6469778, 0.6496222, 0.6471556, 0.6464667, 0.64364445, 0.64504445, 0.6447778, 0.6450222, 0.64857775, 0.64626664, 0.6459778, 0.64437777, 0.6447333, 0.6483333, 0.64633334, 0.64768887, 0.64606667, 0.6450667, 0.6474, 0.6499111, 0.6482, 0.6452, 0.64455557, 0.64555556, 0.6479333, 0.64588886, 0.645, 0.64797777, 0.64615554, 0.6454, 0.64804447, 0.647, 0.6514, 0.64791113, 0.64966667, 0.6441778, 0.64926666, 0.6470444, 0.6458, 0.64806664, 0.6482889, 0.6496889, 0.6482222, 0.6465778, 0.6495111, 0.6444889, 0.64757776, 0.64746666, 0.65224445, 0.64753336, 0.6496889, 0.6497333, 0.64537776, 0.6504222, 0.6500889, 0.6496, 0.65062225, 0.6485556, 0.6477778, 0.6486889, 0.64784443, 0.6482667, 0.6487333, 0.64831114, 0.6482, 0.6495778, 0.6486, 0.64651114, 0.64964443]
with cnn_sropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 with 10 samples and 500 epochs out.813128
################# cnn_lstm_True Validation Accuracy = [0.3506, 0.4258, 0.437, 0.4526, 0.4624, 0.462, 0.49, 0.5016, 0.5074, 0.5234, 0.5178, 0.523, 0.5234, 0.5174, 0.5366, 0.5146, 0.545, 0.539, 0.5384, 0.5426, 0.546, 0.5574, 0.5508, 0.5322, 0.5694, 0.549, 0.563, 0.5702, 0.5606, 0.5674, 0.5814, 0.5678, 0.564, 0.5678, 0.5648, 0.5654, 0.5846, 0.5776, 0.5796, 0.5712, 0.591, 0.5772, 0.5746, 0.592, 0.587, 0.5906, 0.592, 0.5766, 0.5812, 0.5778, 0.5878, 0.5786, 0.5934, 0.594, 0.5948, 0.5892, 0.5896, 0.5884, 0.5826, 0.5834, 0.5848, 0.5862, 0.5932, 0.5956, 0.598, 0.5874, 0.5996, 0.5958, 0.5862, 0.5734, 0.5808, 0.5898, 0.5836, 0.599, 0.5804, 0.5862, 0.5952, 0.5968, 0.5952, 0.5926, 0.5896, 0.5932, 0.5944, 0.5842, 0.5878, 0.5882, 0.5846, 0.5954, 0.5968, 0.5872, 0.588, 0.6004, 0.5896, 0.5984, 0.5936, 0.5972, 0.5958, 0.5916, 0.5908, 0.5922, 0.5856, 0.598, 0.5912, 0.5946, 0.5886, 0.5952, 0.5884, 0.5944, 0.5968, 0.5792, 0.5984, 0.6004, 0.5882, 0.5906, 0.583, 0.6026, 0.5956, 0.5998, 0.5966, 0.5888, 0.591, 0.5936, 0.5928, 0.594, 0.6046, 0.5994, 0.5874, 0.589, 0.5996, 0.597, 0.599, 0.5946, 0.5896, 0.5952, 0.5892, 0.6004, 0.5942, 0.5884, 0.6062, 0.5984, 0.6058, 0.5998, 0.6006, 0.6016, 0.591, 0.5888, 0.578, 0.586, 0.5946, 0.5878, 0.5936, 0.5892, 0.5956, 0.5926, 0.6004, 0.5898, 0.5922, 0.5952, 0.5988, 0.5882, 0.593, 0.5928, 0.6006, 0.5946, 0.5946, 0.5988, 0.5986, 0.5928, 0.5908, 0.591, 0.602, 0.5976, 0.5986, 0.5966, 0.5898, 0.5978, 0.59, 0.5944, 0.5962, 0.6016, 0.5942, 0.5966, 0.5926, 0.5918, 0.5956, 0.5904, 0.5856, 0.6024, 0.5896, 0.5936, 0.5952, 0.6006, 0.5866, 0.5988, 0.5912, 0.6016, 0.5882, 0.5984, 0.6006, 0.6034, 0.5936, 0.603, 0.599, 0.602, 0.5978, 0.5914, 0.5958, 0.6014, 0.6006, 0.5844, 0.5888, 0.6066, 0.5986, 0.5916, 0.5946, 0.5972, 0.5948, 0.5968, 0.599, 0.6024, 0.594, 0.5946, 0.5978, 0.5954, 0.5934, 0.5964, 0.5946, 0.5938, 0.5886, 0.5948, 0.6006, 0.5954, 0.6036, 0.6, 0.601, 0.5994, 0.5932, 0.6024, 0.5894, 0.5936, 0.5906, 0.6042, 0.6076, 0.599, 0.598, 0.6006, 0.5958, 0.5972, 0.5964, 0.593, 0.5986, 0.5982, 0.5952, 0.5984, 0.5856, 0.5946, 0.6052, 0.6022, 0.5936, 0.6028, 0.5934, 0.5954, 0.5962, 0.6054, 0.6006, 0.5992, 0.5954, 0.5974, 0.605, 0.593, 0.6052, 0.5942, 0.6002, 0.6026, 0.5936, 0.6034, 0.5864, 0.6016, 0.5956, 0.6008, 0.5974, 0.6104, 0.6052, 0.6106, 0.6038, 0.6064, 0.5978, 0.5994, 0.5972, 0.6048, 0.6022, 0.6022, 0.6016, 0.5902, 0.6144, 0.6008, 0.6028, 0.6026, 0.5988, 0.6028, 0.603, 0.5952, 0.5992, 0.5926, 0.6, 0.5978, 0.6028, 0.5992, 0.5994, 0.5946, 0.6006, 0.6056, 0.6002, 0.6022, 0.6024, 0.6008, 0.5994, 0.5996, 0.5966, 0.6026, 0.6014, 0.601, 0.596, 0.5976, 0.5968, 0.603, 0.5968, 0.5982, 0.5998, 0.6012, 0.605, 0.6052, 0.6, 0.6084, 0.601, 0.604, 0.5938, 0.6006, 0.6022, 0.598, 0.597, 0.6066, 0.6022, 0.5992, 0.5964, 0.5956, 0.6026, 0.5998, 0.6074, 0.6016, 0.6036, 0.613, 0.596, 0.6, 0.6016, 0.5972, 0.6012, 0.6, 0.6074, 0.601, 0.6026, 0.6058, 0.6018, 0.6032, 0.5986, 0.6048, 0.6034, 0.6066, 0.6078, 0.6066, 0.5954, 0.6016, 0.5984, 0.5944, 0.6018, 0.6016, 0.603, 0.599, 0.6038, 0.591, 0.6014, 0.5974, 0.5966, 0.6004, 0.5954, 0.5908, 0.5892, 0.5892, 0.6, 0.593, 0.5986, 0.6034, 0.5994, 0.5988, 0.606, 0.6068, 0.6006, 0.6052, 0.5976, 0.5958, 0.5918, 0.5974, 0.5984, 0.6052, 0.6046, 0.601, 0.6138, 0.5994, 0.6016, 0.5964, 0.6054, 0.6004, 0.5936, 0.6012, 0.5992, 0.5976, 0.5868, 0.5986, 0.5872, 0.5934, 0.5958, 0.5954, 0.5932, 0.6008, 0.5954, 0.5902, 0.6016, 0.5998, 0.5956, 0.597, 0.5914, 0.5964, 0.6022, 0.5962, 0.593, 0.5982, 0.5926, 0.5968, 0.6006, 0.5952, 0.596, 0.5908, 0.6022, 0.5952, 0.6026, 0.599, 0.5986, 0.598, 0.5972, 0.602, 0.6014, 0.6022, 0.598, 0.6014, 0.5994, 0.5984, 0.602, 0.5976, 0.5946, 0.5998, 0.6026, 0.604, 0.598, 0.5948, 0.602, 0.5988, 0.5974, 0.6036, 0.5964, 0.599, 0.598, 0.5992, 0.5984, 0.601, 0.5956, 0.6012, 0.6014, 0.6034, 0.6004, 0.6004, 0.598, 0.5976, 0.6028, 0.5954, 0.598, 0.5976, 0.5932, 0.5944, 0.6046, 0.602, 0.6006, 0.6, 0.6036, 0.604, 0.6058, 0.5958, 0.6002, 0.6036, 0.6052, 0.6044]
################# cnn_lstm_True Training Accuracy = [0.26002222, 0.37235555, 0.41088888, 0.43533334, 0.45157778, 0.46348888, 0.47482222, 0.48466668, 0.49411112, 0.4982, 0.5069111, 0.51173335, 0.5198445, 0.52104443, 0.5298667, 0.5331111, 0.5375556, 0.5388889, 0.5466, 0.54815555, 0.54928887, 0.5550445, 0.5568445, 0.56435555, 0.5647333, 0.56446666, 0.56495553, 0.5708, 0.5726, 0.57673335, 0.57835555, 0.57893336, 0.5798889, 0.58257776, 0.58442223, 0.58875555, 0.5867556, 0.59044445, 0.58846664, 0.5932889, 0.5962, 0.5942889, 0.5940667, 0.5989111, 0.60044444, 0.60028887, 0.6003778, 0.60044444, 0.60286665, 0.60444444, 0.60675555, 0.6076222, 0.6081111, 0.6105111, 0.6144889, 0.61135554, 0.6096, 0.614, 0.61671114, 0.61568886, 0.6184667, 0.61675555, 0.61737776, 0.62513334, 0.6207111, 0.62144446, 0.62255555, 0.6216, 0.623, 0.6256222, 0.62593335, 0.6261333, 0.6252889, 0.6291111, 0.62855554, 0.6308445, 0.6297111, 0.6308889, 0.63173336, 0.63395554, 0.6346, 0.63195556, 0.6347333, 0.63453335, 0.6356889, 0.63533336, 0.6365778, 0.6391778, 0.63802224, 0.6388, 0.63924444, 0.6368222, 0.64228886, 0.64086664, 0.6418222, 0.642, 0.6408, 0.6379778, 0.6434444, 0.6421111, 0.63993335, 0.64295554, 0.64522225, 0.64635557, 0.64482224, 0.64753336, 0.64824444, 0.64795554, 0.6487778, 0.64864445, 0.6474, 0.6500222, 0.6481111, 0.65037775, 0.647, 0.6498889, 0.6495111, 0.6509111, 0.6482, 0.65184444, 0.6502444, 0.64982224, 0.6518667, 0.6504889, 0.6533333, 0.6520889, 0.6557556, 0.6536889, 0.6522222, 0.65475553, 0.6579111, 0.6558889, 0.6580667, 0.6559111, 0.65533334, 0.65782225, 0.65662223, 0.6535111, 0.6564222, 0.6553556, 0.65855557, 0.65846664, 0.6594, 0.6558222, 0.6600222, 0.6581778, 0.6584, 0.6606445, 0.6607111, 0.65933335, 0.6636889, 0.65875554, 0.6593556, 0.6616222, 0.66224444, 0.6608222, 0.6646889, 0.6640222, 0.6595111, 0.66215557, 0.66393334, 0.6637333, 0.6625556, 0.66044444, 0.6639111, 0.66591114, 0.66595554, 0.66573334, 0.66591114, 0.6688667, 0.66573334, 0.6650444, 0.6655333, 0.6683111, 0.6671778, 0.66642225, 0.66826665, 0.66855556, 0.67113334, 0.6687111, 0.6679111, 0.66804445, 0.66844445, 0.6673333, 0.66977775, 0.6693556, 0.6670222, 0.6693556, 0.66744447, 0.66911113, 0.66915554, 0.66844445, 0.6711556, 0.6716667, 0.6711111, 0.672, 0.6707111, 0.67113334, 0.67064446, 0.67104447, 0.6739778, 0.67255557, 0.6720222, 0.67073333, 0.67271113, 0.67233336, 0.673, 0.6721778, 0.6762, 0.6724, 0.6713333, 0.6718, 0.67208886, 0.67642224, 0.6724667, 0.6754889, 0.6734, 0.67311114, 0.6744222, 0.6762, 0.6722444, 0.6767333, 0.6790444, 0.67377776, 0.6742667, 0.6772, 0.67646664, 0.67455554, 0.6768, 0.67242223, 0.6748889, 0.67646664, 0.6785333, 0.6776, 0.67333335, 0.6766667, 0.67704445, 0.67653334, 0.67542225, 0.6809555, 0.6784889, 0.6774222, 0.6812, 0.6820889, 0.6766, 0.67631114, 0.6772444, 0.67962223, 0.67855555, 0.68017775, 0.67906666, 0.67811114, 0.6754, 0.67957777, 0.6800889, 0.6798, 0.6809555, 0.6788222, 0.67866665, 0.6785333, 0.6772889, 0.68035555, 0.6809111, 0.6808889, 0.6816222, 0.68, 0.6821778, 0.67877775, 0.68024445, 0.6807778, 0.68002224, 0.67913336, 0.68306667, 0.68075556, 0.68186665, 0.6824889, 0.67917776, 0.68222225, 0.6826889, 0.6804889, 0.6809555, 0.68197775, 0.68146664, 0.68237776, 0.68277776, 0.67984444, 0.68002224, 0.6838222, 0.6838889, 0.6868, 0.6828667, 0.6806, 0.68124443, 0.68237776, 0.6806667, 0.6828667, 0.684, 0.6830889, 0.6838, 0.68197775, 0.6838889, 0.6784667, 0.6829778, 0.6866889, 0.6834222, 0.6838222, 0.68644446, 0.68351114, 0.6870222, 0.6800889, 0.68813336, 0.6838222, 0.6875333, 0.68633336, 0.6861778, 0.685, 0.6834667, 0.6867333, 0.68486667, 0.6841111, 0.6859111, 0.6858, 0.68597776, 0.6850889, 0.6895111, 0.68684447, 0.6862222, 0.6888222, 0.68813336, 0.6896222, 0.68586665, 0.68484443, 0.6884889, 0.68453336, 0.68575555, 0.68682224, 0.68693334, 0.6864222, 0.6860667, 0.6869556, 0.6881111, 0.6865111, 0.6879111, 0.68653333, 0.6862889, 0.69204444, 0.68648887, 0.6857778, 0.6902, 0.68873334, 0.6896667, 0.6882, 0.68582225, 0.6904, 0.6892667, 0.6860667, 0.6887778, 0.68906665, 0.6867333, 0.68957776, 0.69082224, 0.68986666, 0.6870222, 0.6892667, 0.6920222, 0.68953335, 0.6888222, 0.6920222, 0.6873556, 0.6916222, 0.6893778, 0.68968886, 0.6890889, 0.6911778, 0.6907333, 0.6916222, 0.6887556, 0.69375557, 0.6906222, 0.6885333, 0.68995553, 0.69233334, 0.6880889, 0.69166666, 0.69097775, 0.69082224, 0.69184446, 0.69002223, 0.69075555, 0.6938222, 0.69346666, 0.69137776, 0.6933333, 0.69233334, 0.69206667, 0.68997777, 0.6902222, 0.6944444, 0.69255555, 0.6926, 0.6915778, 0.69164443, 0.6934, 0.6918, 0.69435555, 0.6911333, 0.693, 0.69226664, 0.6914222, 0.69386667, 0.6925111, 0.6921333, 0.6954, 0.69355553, 0.69402224, 0.69406664, 0.69328886, 0.69211113, 0.69317776, 0.69086665, 0.6944444, 0.6914667, 0.6902222, 0.69533336, 0.69593334, 0.69306666, 0.69355553, 0.693, 0.6969333, 0.69064444, 0.69548887, 0.69442225, 0.69406664, 0.6944444, 0.6964889, 0.6958445, 0.6977556, 0.69424444, 0.69497776, 0.69526666, 0.6947333, 0.69777775, 0.6968222, 0.6994889, 0.6950667, 0.6911111, 0.6942222, 0.6976445, 0.69586664, 0.6967111, 0.6934, 0.6963556, 0.69366664, 0.6979333, 0.69677776, 0.6964889, 0.6929333, 0.6951333, 0.6950222, 0.6978667, 0.6924222, 0.69644445, 0.6926889, 0.6948, 0.6967111, 0.69884443, 0.69975555, 0.69802225, 0.69626665, 0.69817775, 0.6986222, 0.6982, 0.697, 0.6974667, 0.6984444, 0.6949111, 0.6966, 0.69615555, 0.69735557, 0.6937111, 0.6951333, 0.69906664, 0.69515556, 0.6963556, 0.6979778, 0.69582224, 0.697, 0.6959111, 0.69817775, 0.69688886, 0.6994889, 0.6986, 0.6960222, 0.6968, 0.69942224, 0.6992, 0.6955111, 0.70015556, 0.69395554, 0.69688886]
with cnn_dropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 with 5 samples and 200 epochs, hs = 256 out.836808
with cnn_dropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 with 5 samples and 500 epochs, hs = 256 out.850568
with cnn_dropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 with 10 samples and 200 epochs, hs = 256 out.846535
################# cnn_lstm_True Validation Accuracy = [0.339, 0.3814, 0.4168, 0.4498, 0.453, 0.4722, 0.4766, 0.4924, 0.4932, 0.5042, 0.5004, 0.5084, 0.4992, 0.5072, 0.5184, 0.5258, 0.5286, 0.5358, 0.5306, 0.5372, 0.549, 0.5322, 0.55, 0.5528, 0.5488, 0.535, 0.555, 0.5514, 0.5558, 0.5496, 0.557, 0.5474, 0.5448, 0.5578, 0.5644, 0.5724, 0.5662, 0.5638, 0.5668, 0.5534, 0.5596, 0.56, 0.564, 0.5706, 0.5672, 0.5678, 0.5798, 0.5744, 0.5696, 0.5624, 0.5772, 0.5702, 0.5746, 0.5762, 0.5668, 0.5714, 0.5772, 0.5698, 0.5736, 0.5798, 0.5808, 0.5746, 0.5758, 0.578, 0.5758, 0.5756, 0.5728, 0.5818, 0.5848, 0.5808, 0.585, 0.5786, 0.5762, 0.572, 0.5806, 0.5826, 0.5728, 0.578, 0.5782, 0.5678, 0.5822, 0.5804, 0.5814, 0.584, 0.5852, 0.5842, 0.5844, 0.578, 0.5828, 0.583, 0.5746, 0.5766, 0.5778, 0.5736, 0.5686, 0.5838, 0.5718, 0.5912, 0.5802, 0.5782, 0.5892, 0.589, 0.586, 0.5764, 0.5836, 0.5846, 0.5784, 0.5856, 0.5924, 0.5794, 0.5812, 0.5802, 0.577, 0.574, 0.5758, 0.574, 0.5876, 0.5826, 0.576, 0.5904, 0.5784, 0.59, 0.5798, 0.5762, 0.587, 0.5818, 0.577, 0.584, 0.5872, 0.5818, 0.5798, 0.579, 0.5792, 0.5846, 0.59, 0.584, 0.581, 0.5812, 0.5834, 0.5798, 0.582, 0.5838, 0.5844, 0.575, 0.5864, 0.5876, 0.5784, 0.589, 0.5796, 0.5782, 0.5838, 0.5784, 0.5828, 0.5776, 0.5878, 0.5914, 0.5878, 0.584, 0.584, 0.5786, 0.5874, 0.5874, 0.5878, 0.584, 0.5854, 0.5878, 0.5788, 0.586, 0.5828, 0.5814, 0.5868, 0.5838, 0.5794, 0.5738, 0.5678, 0.584, 0.5646, 0.5784, 0.5874, 0.5862, 0.5814, 0.576, 0.579, 0.5842, 0.5866, 0.5828, 0.5788, 0.5824, 0.5784, 0.5804, 0.5918, 0.583, 0.5838, 0.581, 0.5772, 0.5854, 0.579, 0.5856, 0.5838, 0.5684]
################# cnn_lstm_True Training Accuracy = [0.25933334, 0.35897776, 0.40086666, 0.41968888, 0.43133333, 0.4426222, 0.45602223, 0.464, 0.4725111, 0.4824, 0.48344445, 0.4886889, 0.4959778, 0.50024444, 0.5028222, 0.5082222, 0.50993335, 0.51266664, 0.51886666, 0.52084446, 0.52646667, 0.52404445, 0.5317111, 0.5313778, 0.5377778, 0.5391778, 0.5374889, 0.5467333, 0.54455554, 0.54733336, 0.54833335, 0.5536, 0.5534667, 0.5556222, 0.559, 0.5606889, 0.5632222, 0.56493336, 0.56306666, 0.5652889, 0.57233334, 0.57015556, 0.5712, 0.57144445, 0.57442224, 0.57515556, 0.57857776, 0.5813778, 0.5827111, 0.5814, 0.5822, 0.58335555, 0.58815557, 0.5899111, 0.5893111, 0.5896889, 0.5938889, 0.59315556, 0.59037775, 0.5937778, 0.59675556, 0.5979556, 0.60024446, 0.60231113, 0.5999111, 0.6032889, 0.6035333, 0.59848887, 0.60015553, 0.60568887, 0.6070222, 0.6063333, 0.6086889, 0.609, 0.6100444, 0.608, 0.61284447, 0.61013335, 0.6125778, 0.61417776, 0.6145778, 0.61653334, 0.61782223, 0.6174, 0.61873335, 0.6196667, 0.61877775, 0.6184667, 0.6224222, 0.6238222, 0.6217333, 0.6231111, 0.62384444, 0.6241111, 0.62593335, 0.62633336, 0.6242889, 0.62824446, 0.6285333, 0.62684447, 0.6272, 0.6290889, 0.6309111, 0.62942225, 0.6313556, 0.6296889, 0.63328886, 0.6348444, 0.63564444, 0.6356, 0.6346667, 0.63733333, 0.6368222, 0.63895553, 0.6392, 0.6382889, 0.6387778, 0.6429778, 0.6417111, 0.6396222, 0.6428, 0.6437333, 0.64342225, 0.6436889, 0.64651114, 0.6487778, 0.64806664, 0.6462, 0.64526665, 0.64604443, 0.64802223, 0.6433111, 0.6487333, 0.6496222, 0.64915556, 0.6493111, 0.6515778, 0.65037775, 0.6518667, 0.65433335, 0.65011114, 0.65484446, 0.6539111, 0.65246665, 0.6572222, 0.65664446, 0.6535778, 0.65617776, 0.65826666, 0.6585778, 0.6563778, 0.6543111, 0.6588889, 0.6595111, 0.66033334, 0.65742224, 0.66184443, 0.6596, 0.6606445, 0.66444445, 0.66106665, 0.6597111, 0.6607556, 0.6629111, 0.6594889, 0.6645333, 0.66524446, 0.6639778, 0.66444445, 0.66444445, 0.669, 0.6661111, 0.6661111, 0.6684667, 0.66915554, 0.66746664, 0.66884446, 0.6691333, 0.6706222, 0.66966665, 0.6698222, 0.67057776, 0.66962224, 0.6712889, 0.67204446, 0.6702222, 0.67388886, 0.6762889, 0.6710889, 0.67404443, 0.67264444, 0.67275554, 0.6758222, 0.6774222, 0.6727778, 0.6743111, 0.67755556, 0.6782, 0.6754, 0.6779778]
with cnn_dropout = 0.4 and rnn dropout = 0.2 and lr = 5e-4 with res = 8 with 10 samples and 500 epochs, hs = 256 out.850588
200 20 8 256 1 3 0
out.418207
200 20 8 256 1 0 0
out.418221
50 20 8 256 1 0 0
out.418247
'''
from __future__ import division, print_function, absolute_import
print('Starting..................................')
import sys
sys.path.insert(1, '/home/labs/ahissarlab/orra/imagewalker')
import numpy as np
import cv2
import misc
import pandas as pd
import matplotlib.pyplot as plt
import pickle
from keras_utils import *
from misc import *
import tensorflow.keras as keras
import tensorflow as tf
from tensorflow.keras.datasets import cifar10
# load dataset
(trainX, trainy), (testX, testy) = cifar10.load_data()
images, labels = trainX, trainy
#Define function for low resolution lens on syclop
def bad_res101(img,res):
sh=np.shape(img)
dwnsmp=cv2.resize(img,res, interpolation = cv2.INTER_CUBIC)
upsmp = cv2.resize(dwnsmp,sh[:2], interpolation = cv2.INTER_CUBIC)
return upsmp
def bad_res102(img,res):
sh=np.shape(img)
dwnsmp=cv2.resize(img,res, interpolation = cv2.INTER_AREA)
return dwnsmp
# import importlib
# importlib.reload(misc)
# from misc import Logger
import os
kernel_regularizer_list = [None, keras.regularizers.l1(),keras.regularizers.l2(),keras.regularizers.l1_l2()]
optimizer_list = [tf.keras.optimizers.Adam, tf.keras.optimizers.Nadam, tf.keras.optimizers.RMSprop]
if len(sys.argv) > 1:
paramaters = {
'epochs' : int(sys.argv[1]),
'sample' : int(sys.argv[2]),
'res' : int(sys.argv[3]),
'hidden_size' : int(sys.argv[4]),
'concat' : int(sys.argv[5]),
'regularizer' : kernel_regularizer_list[int(sys.argv[6])],
'optimizer' : optimizer_list[int(sys.argv[7])],
'cnn_dropout' : 0.4,
'rnn_dropout' : 0.2,
'lr' : 5e-4,
'run_id' : np.random.randint(1000,9000)
}
else:
paramaters = {
'epochs' : 1,
'sample' : 5,
'res' : 8,
'hidden_size' : 128,
'concat' : 1,
'regularizer' : None,
'optimizer' : optimizer_list[0],
'cnn_dropout' : 0.4,
'rnn_dropout' : 0.2,
'lr' : 5e-4,
'run_id' : np.random.randint(1000,9000)
}
print(paramaters)
for key,val in paramaters.items():
exec(key + '=val')
epochs = epochs
sample = sample
res = res
hidden_size =hidden_size
concat = concat
regularizer = regularizer
optimizer = optimizer
cnn_dropout = cnn_dropout
rnn_dropout = rnn_dropout
lr = lr
run_id = run_id
n_timesteps = sample
def split_dataset_xy(dataset):
dataset_x1 = [uu[0] for uu in dataset]
dataset_x2 = [uu[1] for uu in dataset]
dataset_y = [uu[-1] for uu in dataset]
return (np.array(dataset_x1),np.array(dataset_x2)[:,:n_timesteps,:]),np.array(dataset_y)
def cnn_lstm(n_timesteps = 5, hidden_size = 128,input_size = 32, concat = True):
'''
CNN RNN combination that extends the CNN to a network that achieves
~80% accuracy on full res cifar.
Parameters
----------
n_timesteps : TYPE, optional
DESCRIPTION. The default is 5.
img_dim : TYPE, optional
DESCRIPTION. The default is 32.
hidden_size : TYPE, optional
DESCRIPTION. The default is 128.
input_size : TYPE, optional
DESCRIPTION. The default is 32.
Returns
-------
model : TYPE
DESCRIPTION.
'''
inputA = keras.layers.Input(shape=(n_timesteps,input_size,input_size,3))
inputB = keras.layers.Input(shape=(n_timesteps,2))
# define CNN model
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3),activation='relu', padding = 'same'))(inputA)
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(32,(3,3),activation='relu', padding = 'same'))(x1)
x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(64,(3,3),activation='relu', padding = 'same'))(x1)
x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Conv2D(128,(3,3),activation='relu', padding = 'same'))(x1)
x1=keras.layers.TimeDistributed(keras.layers.MaxPooling2D(pool_size=(2, 2)))(x1)
x1=keras.layers.TimeDistributed(keras.layers.Dropout(cnn_dropout))(x1)
print(x1.shape)
x1=keras.layers.TimeDistributed(keras.layers.Flatten())(x1)
print(x1.shape)
if concat:
x = keras.layers.Concatenate()([x1,inputB])
else:
x = x1
print(x.shape)
# define LSTM model
x = keras.layers.LSTM(hidden_size,input_shape=(n_timesteps, None),return_sequences=True,recurrent_dropout=rnn_dropout)(x)
x = keras.layers.Flatten()(x)
x = keras.layers.Dense(10,activation="softmax")(x)
model = keras.models.Model(inputs=[inputA,inputB],outputs=x, name = 'cnn_lstm_{}'.format(concat))
opt=tf.keras.optimizers.Adam(lr=5e-4)
model.compile(
optimizer=opt,
loss="sparse_categorical_crossentropy",
metrics=["sparse_categorical_accuracy"],
)
return model
rnn_net = cnn_lstm(n_timesteps = sample, hidden_size = hidden_size,input_size = res, concat = True)
# cnn_net = extended_cnn_one_img(n_timesteps = sample, input_size = res, dropout = cnn_dropout)
# hp = HP()
# hp.save_path = 'saved_runs'
# hp.description = "syclop cifar net search runs"
# hp.this_run_name = 'syclop_{}'.format(rnn_net.name)
# deploy_logs()
train_dataset, test_dataset = create_cifar_dataset(images, labels,res = res,
sample = sample, return_datasets=True,
mixed_state = False, add_seed = 0,
)
#bad_res_func = bad_res101, up_sample = True)
train_dataset_x, train_dataset_y = split_dataset_xy(train_dataset)
test_dataset_x, test_dataset_y = split_dataset_xy(test_dataset)
# print("##################### Fit {} and trajectories model on training data res = {} ##################".format(cnn_net.name,res))
# cnn_history = cnn_net.fit(
# train_dataset_x,
# train_dataset_y,
# batch_size=64,
# epochs=epochs,
# # We pass some validation for
# # monitoring validation loss and metrics
# # at the end of each epoch
# validation_data=(test_dataset_x, test_dataset_y),
# verbose = 0)
# print('################# {} Validation Accuracy = '.format(cnn_net.name),cnn_history.history['val_sparse_categorical_accuracy'])
print("##################### Fit {} and trajectories model on training data res = {} ##################".format(rnn_net.name,res))
rnn_history = rnn_net.fit(
train_dataset_x,
train_dataset_y,
batch_size=64,
epochs=epochs,
# We pass some validation for
# monitoring validation loss and metrics
# at the end of each epoch
validation_data=(test_dataset_x, test_dataset_y),
verbose = 0)
# print('################# {} Validation Accuracy = '.format(cnn_net.name),cnn_history.history['val_sparse_categorical_accuracy'])
# print('################# {} Training Accuracy = '.format(cnn_net.name),rnn_history.history['sparse_categorical_accuracy'])
print('################# {} Validation Accuracy = '.format(rnn_net.name),rnn_history.history['val_sparse_categorical_accuracy'])
print('################# {} Training Accuracy = '.format(rnn_net.name),rnn_history.history['sparse_categorical_accuracy'])
plt.figure()
plt.plot(rnn_history.history['sparse_categorical_accuracy'], label = 'train')
plt.plot(rnn_history.history['val_sparse_categorical_accuracy'], label = 'val')
# plt.plot(cnn_history.history['sparse_categorical_accuracy'], label = 'cnn train')
# plt.plot(cnn_history.history['val_sparse_categorical_accuracy'], label = 'cnn val')
plt.legend()
plt.grid()
plt.title('{} on cifar res = {} hs = {} dropout = {} num samples = {}'.format(rnn_net.name, res, hidden_size,cnn_dropout, sample))
plt.savefig('{} on Cifar res = {}, no upsample, val accur = {} hs = {} dropout = {}.png'.format(rnn_net.name,res,rnn_history.history['val_sparse_categorical_accuracy'][-1], hidden_size,cnn_dropout))
with open('/home/labs/ahissarlab/orra/imagewalker/cifar_net_search/{}HistoryDict{}_{}'.format(rnn_net.name, hidden_size,cnn_dropout), 'wb') as file_pi:
pickle.dump(rnn_history.history, file_pi)
dataset_update(rnn_history, rnn_net,paramaters)
write_to_file(rnn_history, rnn_net,paramaters)
| 46,444 | 39,782 |
# Filenames :
# Python bytecode : 3.8
# Time succses decompiled Sat Sep 26 13:17:38 2020
# Selector <module> in line 1 file
# Timestamp in code : 2020-06-27 04:07:18
import requests
ses = requests.Session()
from bs4 import BeautifulSoup as parser
class browser:
def __init__(self, kuki):
self._browser__kuki = {'cookie': kuki}
def get(self, link):
return parser(ses.get(('https://mbasic.facebook.com' + link), headers=(self._browser__kuki)).content, 'html.parser')
| 497 | 191 |
#
# working
# this function takes steps and detail of steps as input
# we declare a zero level above which any up step will be considered as a valley that is climbed
# we run from 0 to length of steps
# if we detect a "U" we increase the zero level
# similary if we detect "D" we decrease the zero level
# thus calculating the net valley value
def FindValleys(t, steps):
pass
zeroLevel = 0
Valley = 0
for i in range(t):
if steps[i] == "U":
zeroLevel = zeroLevel + 1
else:
zeroLevel = zeroLevel - 1
if steps[i] == "U" and zeroLevel ==0:
Valley = Valley + 1
return Valley
# drive code
# this code takes number os steps and details of steps as input
# where steps will be given in "U" for step up and "D" for step down
# we pass this data to Function FindValleys()
if __name__ == "__main__":
t = int(input())
steps = list(map(int, input().strip().split()))
print(FindValleys(t, steps))
| 1,025 | 309 |
import albumentations as A
import random
import cv2
import os
import numpy as np
import matplotlib.pyplot as plt
class SemanticCopyandPaste(A.DualTransform):
def __init__(self,
nClass,
path2rgb,
path2mask,
shift_x_limit = [0,0],
shift_y_limit = [0,0],
rotate_limit = [0,0],
scale = [0,0],
class_weights = [],
always_apply = False,
show_stats = False,
auto_weights = False,
p=0.5):
super().__init__(always_apply=always_apply, p=p)
self.nClass = nClass
self.rgb_base = path2rgb
self.mask_base = path2mask
self.rgbs = os.listdir(path2rgb)
self.masks = os.listdir(path2mask)
self.nImages = len(self.rgbs)
self.threshold = 30
self.targetClass= 0
self.c_image = None # candidate image
self.c_mask = None # candidate mask
self.found = False
self.imgRow = None # for image translation
self.imgCol = None # for image translation
self.shift_x_limit = shift_x_limit
self.shift_y_limit = shift_y_limit
self.rotate_limit = rotate_limit
self.scale = scale
self.transformation_matrix = None
self.translated_mask = None
self.counter = 0
self.class_counter = np.zeros(self.nClass, dtype=np.int64)
# Class weights is used to control what classes to be augmented more than the others
self.class_weights = [abs(ele) for ele in class_weights]
self.class_pool = []
self.img_pool = np.zeros((self.nClass, len(self.masks))) - 1 # Use -1 as the flag of empty
self.class_pixels_statistics = np.zeros((self.nClass,1), dtype=np.float64)
self.auto_weights = auto_weights
# Image pool initialization for fast image lookup
# Go through all masks, and find out what class(es) each mask has
class_count_tmp = np.zeros((self.nClass, 1), dtype=np.int)
for i in range(len(self.masks)):
c_mask = cv2.imread(os.path.join(self.mask_base, self.masks[i]))
assert c_mask is not None, "Your image directories may contain some non-image hidden files. Image is empty!"
for j in range(self.nClass):
if self.target_class_in_image(c_mask, j):
self.img_pool[j, class_count_tmp[j, 0]] = i
class_count_tmp[j, 0] += 1
# Initialization for weighted class augmentation
if self.auto_weights:
print('- Copy and Paste: Auto weights calculation used -')
tmp = np.copy(self.class_pixels_statistics)
tmp = 1 / tmp
tmp[0,0] = 0
self.class_weights = np.round(tmp / np.sum(tmp) * 100) # Normalized
for i in range(nClass):
for j in range(np.int(self.class_weights[i])):
self.class_pool.append(i)
else:
if not class_weights:
print('- Copy and Paste: Using equal weights for all classes (background not included) -')
for i in range(1,self.nClass): self.class_pool.append(i)
else:
print('- Copy and Paste: Using user defined class weights -')
self.class_weights = np.round(self.class_weights / np.sum(self.class_weights) * 100) # Normalized
assert len(class_weights) == nClass, "class_weights' length != nClass, nClass should also include the background class."
for i in range(nClass):
for j in range(np.int(self.class_weights[i])):
self.class_pool.append(i)
# Params checking
assert len(self.rgbs) == len(self.masks), "rgb path's file count != mask path's file count"
assert self.nClass > 0, "Incorrect class number"
if shift_x_limit is not None:
assert type(shift_x_limit) == list and type(shift_y_limit) == list and type(rotate_limit) == list and type(scale) == list
assert abs(shift_x_limit[0]) <= 1 and abs(shift_y_limit[0]) <= 1 and abs(rotate_limit[0]) <= 1 and abs(rotate_limit[1]) <= 1 and scale[0] >= 0 and scale[1] >= scale[0] and scale[1] >= 1, 'The range for shift_x/y_limit and rotate is [-1 to 1], and [0 to 1] for scale'
if show_stats: print('Pixel Count for Each Class: \n', self.class_pixels_statistics)
def apply(self, image, **params):
'''
Args:
image: 3-channel RGB images
This function will first randomly generate a class that being copied (Exclude 0, which is the background class). Then randomly picks a mask via provided path, and search whether it contains the previously picked target class. Keep randomly picks a new mask until a match is found. Finally start doing copy and paste process.
Since semantic segmentation's annotation may not be labeled in the same way as instance segmentation therefore currently we copy and paste entire mask without further processing.
'''
self.targetClass = random.choice(self.class_pool)
# Finding candidates with the target class
ret = -1
while ret == -1:
ret = int(random.choice(self.img_pool[self.targetClass, :]))
c_image = cv2.imread(os.path.join(self.rgb_base, self.rgbs[ret]))
c_mask = cv2.imread(os.path.join(self.mask_base, self.masks[ret]))
c_image = cv2.cvtColor(c_image, cv2.COLOR_BGR2RGB)
self.found = True
self.c_mask = c_mask
self.c_image = c_image
return self.copy_and_paste_image(self.c_image, self.c_mask, image, self.targetClass)
def apply_to_mask(self, mask, **params):
assert self.found == True
return self.copy_and_paste_mask(self.c_mask, mask, self.targetClass)
# Augmentation will be added to rgb2 (extract content from rgb1)
# Mask1 is need to know where to extract pixels for color image copy and paste
def copy_and_paste_image(self, rgb1, mask1, rgb2, targetClassForAug):
assert rgb1 is not None
assert rgb2 is not None
assert mask1 is not None
assert mask1.shape[2] == 3 # We imread it without further process, so its a 3 channel
if rgb2.shape != rgb1.shape:
r, c, _ = rgb2.shape
rgb1 = cv2.resize(rgb1, (c,r), interpolation = cv2.INTER_NEAREST)
mask1 = cv2.resize(mask1, (c,r), interpolation = cv2.INTER_NEAREST)
tmp = mask1[...,1] # All 3 channels have same content, we take 1 to process
masks = [(tmp == v) for v in range(self.nClass)]
masks = np.stack(masks, axis=-1).astype('float') # mask.shape = (x,y,ClassNums)
self.c_mask = masks
masks[..., targetClassForAug] = self.imgTransform(masks[..., targetClassForAug], self.shift_x_limit, self.shift_y_limit)
self.translated_mask = masks[..., targetClassForAug]
rgb1 = cv2.warpAffine(rgb1, self.transformation_matrix, (self.imgCol, self.imgRow))
# Pasting
mask_3channel = np.stack((self.translated_mask,self.translated_mask,self.translated_mask),axis=2)
idxs = mask_3channel > 0
rgb2[idxs] = rgb1[idxs]
return rgb2.astype('uint8')
def copy_and_paste_mask(self, mask1, mask2, targetClassForAug):
'''
Args:
mask1 = randomly picked qualified mask from apply(), has shape = (x, y, nClasses)
mask2 = dataloader loaded mask, aug is added to mask2
'''
assert mask2.shape[2] == self.nClass # Processed by dataloader, so its a nClass channel
assert self.translated_mask is not None
mask2_1channel = np.argmax(mask2, axis=2)
# Pasting augmentation
mask2_1channel[self.translated_mask > 0] = targetClassForAug
masks = [(mask2_1channel == v) for v in range(self.nClass)] # mask.shape = (x,y,ClassNums)
masks = np.stack(masks, axis=-1).astype('float')
# Reset
self.c_mask = None
self.found == False
self.transformation_matrix = None
self.translated_mask = None
return masks
# We imread the mask, so it's a 3-channel mask (not one-hot encoded)
def target_class_in_image(self, mask, targetClassIdx):
#hard coded pixel threshold
s = np.sum(mask[..., 0] == targetClassIdx)
self.class_pixels_statistics[targetClassIdx, 0] += s
if s > self.threshold:
return True
return False
def imgTransform(self, image, offset_x_limit, offset_y_limit ):
'''
Args:
image: it can be mask or rgb image
offset_x_limt: x-axis shift limit [-1,1]
offset_y_limt: y-axis shift limit [-1,1]
'''
self.imgRow, self.imgCol = image.shape
col_shift = random.uniform(offset_x_limit[0], offset_x_limit[1])*self.imgCol
row_shift = random.uniform(offset_y_limit[0], offset_y_limit[1])*self.imgRow
rotate_deg= random.uniform(self.rotate_limit[0], self.rotate_limit[1])*180
scale_coef= random.uniform(self.scale[0] , self.scale[1])
self.transformation_matrix = cv2.getRotationMatrix2D((self.imgRow//2, self.imgCol//2), rotate_deg, scale_coef)
self.transformation_matrix[0,2] += col_shift
self.transformation_matrix[1,2] += row_shift
return cv2.warpAffine(image, self.transformation_matrix, (self.imgCol, self.imgRow))
def apply_to_bbox(self, bbox, **params):
return bbox
def apply_to_keypoint(self, keypoint, **params):
return keypoint
def get_transform_init_args_names(self):
return ("image", "mask")
| 10,419 | 3,251 |
# Generated by Django 3.1.7 on 2021-03-04 14:42
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('jobs', '0004_job_title'),
]
operations = [
migrations.AddField(
model_name='job',
name='github_url',
field=models.URLField(default='https://github.com/TobiAdeniyi'),
preserve_default=False,
),
]
| 435 | 148 |
from django.db import models
# Create your models here.
class organization(models.Model):
username = models.CharField(max_length=1000)
email= models.URLField()
img= models.ImageField( upload_to='pics',null=True,blank=True)
# number = models.IntegerField()
password= models.CharField(max_length=200)
des = models.TextField()
cammount=models.IntegerField(null=True,blank=True)
Dname=models.TextField(null=True,blank=True)
| 454 | 144 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import time,sys
from parser.parser import *
from database_Manager.databaseManager import *
from collections import Counter
if __name__ == '__main__':
#global Variables, chnages for a specific action (1 : do the action , 0 : don't do the action)
action=0
if len(sys.argv) != 2:
print "[Usage] python search.py <0(deleteTable) | 1 (creatTable) | 2 (run indexation)"
sys.exit(1)
else:
if sys.argv[1]!="0" and sys.argv[1]!="1" and sys.argv[1]!="2" :
print "first argument should be 0 or 1 or 2"
sys.exit(1)
action=int(sys.argv[1])
myParser=parser()
myDatabaseManager=databaseManager()
if action==0:
print ("delete tables...")
myDatabaseManager.deleteTables()
elif action==1:
print "create tables..."
myDatabaseManager.createTables()
else:
start_time=time.clock()
#words to add in the database (to not have duplicates words)
addWordsList=[]
#List wchich contains parsing list result for each file
list_Of_Result_ParsingDocument=[]
List_Title_Documents=[]
for num in range (139):
#pas de fichier commençant avec le numéro 0 et 127
if num !=0 and num!=127:
#add documents titles
List_Title_Documents.append("D"+str(num)+".html")
path = "RessourcesProjet/corpus-utf8/D"+str(num)+".html"
resultList=myParser.parse(path)
#print type (resultList)
#maintain a list of all parsing list result
list_Of_Result_ParsingDocument.append(resultList)
#contain words which apppears once in all files
addWordsList= list(set(addWordsList+resultList))#list union
print "parsing done for : "+ path
addWordsList.sort()
#file = open("save_file", "r+")
#for elt in addWordsList:
# file.write(elt+"\n")
#for word in addWordsList:
# print "===> " + word
print ">>>>>>> Number of words :" + str(len(addWordsList))
#create a global dict of where key is(idWord,idDoc) and value is freq
globalDictWithFrequencies={}
for idDoc ,subList in enumerate(list_Of_Result_ParsingDocument):
print "traitment doc : " + str(idDoc+1)
dicSubList=Counter(subList)
for word,freq in dicSubList.iteritems():
idWord=addWordsList.index(word)
globalDictWithFrequencies[(idWord+1,idDoc+1)]=freq
print ">>>>>>> length global dic : " + str(len(globalDictWithFrequencies))
print ">>>>>>> adding block of elements in the database"
#add elements in the database
myDatabaseManager.addElementDocumentsTable(List_Title_Documents)
myDatabaseManager.addElementsIndexTable(addWordsList)
myDatabaseManager.addElementIndexDocumentsCorrespondences(globalDictWithFrequencies)
print ">>>>>>> Total process Time : ", time.clock() - start_time, "seconds" | 2,693 | 1,025 |
# -*- coding:utf8 -*-
import os
import re
import dsf
def change_branch(branch, cwd=None):
# checkout the branch
dsf.core.shell.run(['git', 'checkout', branch], cwd=cwd)
def get_current_branch(cwd=None):
output = dsf.core.shell.get_output_from_command(['git', 'branch'], cwd=cwd)
for line in output:
if line[0:2] == '* ':
branch = line[2:].rstrip()
return branch
# if we get here, we are not on a current branch
return "* HEADLESS"
def is_repository(cwd=None):
# make sure we have a current working directory
if not cwd:
cwd = os.getcwd()
# quickest test - is there a .git folder?
dotgit_folder = os.path.join(cwd, '.git')
if not os.path.isdir(dotgit_folder):
return False
# is the folder a real git repo?
output = dsf.core.shell.get_output_from_command(['git', 'status'], cwd=cwd)
regex=re.compile("fatal: Not a git repository")
if any(regex.match(line) for line in output):
return False
# what about when self.repodir is a subfolder of a git repo?
output = dsf.core.shell.get_output_from_command(['git', 'rev-parse', '--show-toplevel'], cwd=cwd)
if output[0].rstrip() != dsf.core.fs.get_realpath(cwd):
return False
# if we get here, then it is a git repo
return True | 1,214 | 468 |
def is_prime(n: int) -> bool:
'''
This function returns True if n is a prime number otherwise return False.
'''
if n <= 1:
return False
d = 2
while d * d <= n and n % d != 0:
d += 1
return d * d > n
| 243 | 84 |
import json
from argparse import ArgumentParser
import pandas as pd
from utils import db, db_utils
from utils.db import Data, SupportData
filter_feature = 'Comments Concatenated'
validation = 'Validation'
def main(file):
db_utils.create_postgres_db()
db.dal.connect()
session = db.dal.Session()
df = pd.read_excel(file)
data_columns = [filter_feature, validation]
data = df[data_columns]
support_data = json.loads(df[df.columns.difference(data_columns)].to_json(orient='records'))
for i in range(len(data)):
data_row = data.iloc[i]
support_data_row = support_data[i]
data_obj = Data(filter_feature=str(data_row[filter_feature]), validation=int(data_row[validation]))
session.add(data_obj)
session.flush()
support_data_obj = SupportData(support_data=support_data_row)
data_obj.support_data = support_data_obj
support_data_obj.data = data_obj
support_data_obj.data_id = support_data_obj.data.id
session.add(support_data_obj)
session.commit()
print(f'Loaded {len(data)} records of data and support_data.')
if __name__ == '__main__':
program_desc = '''This application will get the spreadsheet and pull out essential data to fill out
the database. It will populate the database in the `data` table. It also put all
other data in the database as well in support_data table.'''
parser = ArgumentParser(description=program_desc)
parser.add_argument("file", help="specify path to file")
args = parser.parse_args()
main(file=args.file)
| 1,628 | 495 |
import multiprocessing
from typing import (
Callable,
Tuple,
)
from ..data_logging.data_recorder import DataRecorder
from ..driver.ask_tell_driver import AskTellDriver
from ..optimizer.ask_tell_optimizer import AskTellOptimizer
from .ask_tell_parallel_driver_fns import *
class AskTellParallelDriver(AskTellDriver):
def __init__(self,
nprocs: int = multiprocessing.cpu_count()):
self._num_evaluations: int = 0
self._num_iterations: int = 0
self._nprocs = nprocs
self._pool = None
# self.evaluations = []
def __getstate__(self):
"""
This prevents the pool from being pickled when using the pool...
"""
self_dict = self.__dict__.copy()
if 'pool' in self_dict:
del self_dict['pool']
return self_dict
def __setstate__(self, state):
"""
This prevents the pool from being pickled when using the pool...
"""
self.__dict__.update(state)
def __del__(self):
"""
This prevents the pool from being pickled when using the pool...
"""
if hasattr(self, 'pool') and self._pool is not None:
self._pool.close()
def setup(
self,
objective: Callable[[any], Tuple[float, float, any]],
recorder: DataRecorder,
) -> None:
"""
Must be called before calling step() or run().
Sets the objective function for this driver and the data recorder.
:param objective: objective function for evaluating candidate solutions
:param recorder: data recorder
:return:
"""
self._pool = multiprocessing.Pool(
initializer=make_initializer(objective),
processes=self._nprocs)
def step(self,
optimizer: AskTellOptimizer,
) -> bool:
"""
Steps the optimizer through one iteration of generating candidates, evaluating them, and updating with their
evaluations.
:param optimizer: the optimizer to use
:return: True if the optimizer reached a stopping point (via calling optimizer.stop())
"""
# print('step()')
num_candidates = optimizer.get_num_candidates()
candidates = optimizer.ask(num_candidates)
evaluations = self._pool.map(evaluate, candidates)
num_candidates = len(evaluations)
# print('telling')
# self.evaluations = list(evaluations)
optimizer.tell(evaluations)
self._num_evaluations += num_candidates
self._num_iterations += 1
# print('done')
return optimizer.stop()
def get_num_evaluations(self) -> int:
return self._num_evaluations
def get_num_iterations(self) -> int:
return self._num_iterations
| 2,882 | 798 |
import torch.nn as nn
import torch.nn.functional as F
from pygcn.layers import GraphConvolution, MyGraphConvolution
class GCN(nn.Module):
def __init__(self, nfeat, nhid, nclass, dropout):
super(GCN, self).__init__()
self.gc1 = GraphConvolution(nfeat, nhid)
self.gc2 = GraphConvolution(nhid, nclass)
self.dropout = dropout
def forward(self, x, adj):
x = F.relu(self.gc1(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc2(x, adj)
return F.log_softmax(x, dim=1)
class MyGCN_v1(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v1, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, nhid)
self.gc2 = MyGraphConvolution(nhid, nhid)
self.gc3 = MyGraphConvolution(nhid, nhid)
self.gc4 = MyGraphConvolution(nhid, nhid)
self.gc5 = MyGraphConvolution(nhid, nhid)
self.gc6 = MyGraphConvolution(nhid, nout)
self.dropout = dropout
def forward(self, x, adj):
x = F.relu(self.gc1(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.relu(self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.relu(self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.relu(self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.relu(self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
return x
class MyGCN_v2(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v2, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, 12)
self.gc2 = MyGraphConvolution(12, 10)
self.gc3 = MyGraphConvolution(10, 8)
self.gc4 = MyGraphConvolution(8, 6)
self.gc5 = MyGraphConvolution(6, 4)
self.gc6 = MyGraphConvolution(4, nout)
self.dropout = dropout
def forward(self, x, adj):
x = F.tanhshrink(self.gc1(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
return x
class MyGCN_v3(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v3, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, 12)
self.gc2 = MyGraphConvolution(12, 10)
self.gc3 = MyGraphConvolution(10, 8)
self.gc4 = MyGraphConvolution(8, 6)
self.gc5 = MyGraphConvolution(6, 4)
self.gc6 = MyGraphConvolution(4, nout)
self.dropout = dropout
def forward(self, x, adj):
x = (self.gc1(x, adj))
x = F.dropout(x, p=0, training=self.training)
x = (self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
return x
class MyGCN_v4(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v4, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, 12)
self.gc2 = MyGraphConvolution(12, 10)
self.gc3 = MyGraphConvolution(10, 8)
self.gc4 = MyGraphConvolution(8, 6)
self.gc5 = MyGraphConvolution(6, 4)
self.gc6 = MyGraphConvolution(4, nout)
self.dropout = dropout
def forward(self, x, adj):
x = (self.gc1(x, adj))
x = F.dropout(x, p=0, training=self.training)
x = F.relu(self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
return x
class MyGCN_v5(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v5, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, 12)
self.gc2 = MyGraphConvolution(12, 10)
self.gc3 = MyGraphConvolution(10, 8)
self.gc4 = MyGraphConvolution(8, 6)
self.gc5 = MyGraphConvolution(6, 4)
self.gc6 = MyGraphConvolution(4, nout)
self.dropout = dropout
def forward(self, x, adj):
x = (self.gc1(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.relu(self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = F.tanhshrink(self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
return x
class MyGCN_v6(nn.Module):
def __init__(self, nfeat, nhid, nout, dropout):
super(MyGCN_v6, self).__init__()
self.gc1 = MyGraphConvolution(nfeat, 12)
self.gc2 = MyGraphConvolution(12, 11)
self.gc3 = MyGraphConvolution(11, 10)
self.gc4 = MyGraphConvolution(10, 9)
self.gc5 = MyGraphConvolution(9, 8)
self.gc6 = MyGraphConvolution(8, 7)
self.gc7 = MyGraphConvolution(7, 6)
self.gc8 = MyGraphConvolution(6, 5)
self.gc9 = MyGraphConvolution(5, 4)
self.gc10 = MyGraphConvolution(4, nout)
self.dropout = dropout
def forward(self, x, adj):
x = (self.gc1(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc2(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc3(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc4(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = (self.gc5(x, adj))
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc6(x, adj)
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc7(x, adj)
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc8(x, adj)
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc9(x, adj)
x = F.dropout(x, self.dropout, training=self.training)
x = self.gc10(x, adj)
return x
| 7,123 | 2,802 |
from selenium import webdriver
from selenium.common import exceptions
import time
import sched
MOODLE_USER_NAME = ""
MOODLE_PASSWORD = ""
MOODLE_HOME_PAGE = "Moodle Address" # THe moodle main homepage
COURSE_TITLE = "Name of the course as it shows up on the left" # What course to search for in the list
START_HOUR, START_MINUTE, START_SECS = 16, 0, 0 # Starts at 16:00:00
SLEEP_INTERVAL = 60 # For what duration to sleep in-between attempts (in seconds)
WEBDRIVER_EXECUTABLE_PATH = "./chromedriver" # Path to the Chrome WebDriver
CHROME_EXECUTABLE_PATH = "/usr/bin/google-chrome" # Path to the Chrome browser
IS_HEADLESS = True # Whether or not to display the Chrome GUI.
def init_browser():
options = webdriver.ChromeOptions()
options.add_argument('--ignore-certificate-errors')
options.add_argument("--test-type")
if IS_HEADLESS:
options.add_argument("--headless")
options.binary_location = CHROME_EXECUTABLE_PATH
browser = webdriver.Chrome(executable_path=WEBDRIVER_EXECUTABLE_PATH, chrome_options=options)
browser.get(MOODLE_HOME_PAGE)
return browser
def login_to_moodle(browser):
# <input type="text" name="username" id="login_username" class="form-control" value="" autocomplete="username">
user_input = browser.find_element_by_id("login_username")
user_input.send_keys(MOODLE_USER_NAME)
# <input type="password" name="password" id="login_password" class="form-control" value="" autocomplete="current-password">
password_input = browser.find_element_by_id("login_password")
password_input.send_keys(MOODLE_PASSWORD)
# <input type="submit" class="btn btn-primary btn-block" value="Log in">
all_btns = browser.find_elements_by_class_name("btn-primary")
for x in all_btns:
if x.get_attribute("type") == "submit" and x.get_attribute("value") == "Log in":
x.click()
return
raise Exception("Could not find the submit button for some reason.")
def go_to_course_page(browser):
all_links = browser.find_elements_by_tag_name("a")
for x in all_links:
if x.get_attribute("title") == COURSE_TITLE:
x.click()
return
def go_to_attendance(browser):
all_links = browser.find_elements_by_tag_name("a")
for x in all_links:
if x.text == "Attendance":
x.click()
return
def handle_attendance(browser):
all_links = browser.find_elements_by_tag_name("a")
found_submit_attendance = False
for x in all_links:
if x.text == "Submit attendance":
x.click()
found_submit_attendance = True
break
if not found_submit_attendance:
return False
all_spans = browser.find_elements_by_tag_name("span")
for x in all_spans:
if x.text == "Present":
x.click()
break
submit_btn = browser.find_element_by_id("id_submitbutton")
submit_btn.click()
return True
def create_time_today(hour, min, sec):
now = time.localtime()
when = time.mktime((now.tm_year, now.tm_mon, now.tm_mday, hour, min, sec, 1, 85, 0))
return when
def log(msg):
print(time.asctime()+": %s" % msg)
def wait_until_lesson_starts_and_launch_job(job):
log("Waiting for the time %02d:%02d:%02d" % (START_HOUR, START_MINUTE, START_SECS))
s = sched.scheduler(time.time, time.sleep)
s.enterabs(create_time_today(START_HOUR, START_MINUTE, START_SECS), 1, job)
s.run()
def main():
log("The time has come! starting attempts.")
is_successful = False
browser = init_browser()
while not is_successful:
try:
login_to_moodle(browser)
go_to_course_page(browser)
go_to_attendance(browser)
is_successful = handle_attendance(browser)
except exceptions.WebDriverException as e:
log("Error WebDriverException...")
browser.close()
if is_successful:
log("Done!") # Will stop iterating afterwards (while condition)
else:
log("Failed. Sleeping now. will try again in %d seconds" % SLEEP_INTERVAL)
time.sleep(SLEEP_INTERVAL)
if __name__ == '__main__':
# main()
wait_until_lesson_starts_and_launch_job(job=main)
| 4,255 | 1,417 |
# -*- coding: utf-8 -*-
from datetime import datetime
def cp56timebcd(buf):
pass
def cp56time2a_to_time(buf):
microsecond = (buf[1] & 0xFF) << 8 | (buf[0] & 0xFF)
microsecond %= 1000
second = int(microsecond)
minute = buf[2] & 0x3F
hour = buf[3] & 0x1F
day = buf[4] & 0x1F
month = (buf[5] & 0x0F) - 1
year = (buf[6] & 0x7F) + 2000
return datetime(year, month, day, minute, hour, second, microsecond)
| 445 | 208 |
# -*- coding: utf-8 -*-
u"""Yara Scanner module for SecureTea AntiVirus.
Project:
╔═╗┌─┐┌─┐┬ ┬┬─┐┌─┐╔╦╗┌─┐┌─┐
╚═╗├┤ │ │ │├┬┘├┤ ║ ├┤ ├─┤
╚═╝└─┘└─┘└─┘┴└─└─┘ ╩ └─┘┴ ┴
Author: Abhishek Sharma <abhishek_official@hotmail.com> , Jul 4 2019
Version: 1.4
Module: SecureTea
"""
from securetea.lib.antivirus.scanner.scanner_parent import Scanner
import sys
import os
yara_status = True
try:
import yara
except ImportError:
yara_status = False
print("[-] Yara not installed")
except AttributeError:
yara_status = False
print("[-] Yara not configured: libyara.so not found")
except Exception as e:
yara_status = False
print(e)
class YaraScanner(Scanner):
"""YaraScanner class."""
def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None):
"""
Initialize YaraEngine.
Args:
debug (bool): Log on terminal or not
config_path (str): Configuration JSON file path
vt_api_key (str): VirusTotal API Key
file_list (list): List of files to scan
Raises:
None
Returns:
None
"""
# Initialize parent class
super().__init__(debug, config_path, file_list, vt_api_key)
if self.os_name:
try:
# Load threads
self._WORKERS = self.config_dict[self.os_name]["scanner"]["yara"]["threads"]
# Load Yara rules storage path
self._YARA_STORAGE = self.config_dict[self.os_name]["update"]["yara"]["storage"]
except KeyError:
self.logger.log(
"Could not load configuration for: {}".format(self.os_name),
logtype="error"
)
sys.exit(0)
else:
self.logger.log(
"Could not determine the OS",
logtype="error"
)
sys.exit(0)
def scan_file(self, file_path):
"""
Scan file using Yara rules.
Args:
file_path (str): Path of the file to scan
Raises:
None
Returns:
None
"""
if yara_status:
yara_files_list = os.listdir(self._YARA_STORAGE)
for yara_file in yara_files_list:
if yara_file.endswith(".yar") or yara_file.endswith(".yara"):
yara_file_path = os.path.join(self._YARA_STORAGE, yara_file)
rule_compile = yara.compile(yara_file_path)
matches = rule_compile.match(file_path)
if matches:
self.logger.log(
"Possible malicious file detected: {0}".format(file_path),
logtype="warning"
)
if file_path not in self.malicious_file_list:
self.malicious_file_list.append(file_path)
super().check_virus_total(file_path)
return
return
| 3,119 | 965 |
from os import times
from typing import Generator, Optional, Union, NamedTuple
import numpy as np
import torch as th
from gym import spaces
from stable_baselines3.common.type_aliases import RolloutBufferSamples
from stable_baselines3.common.buffers import RolloutBuffer
from stable_baselines3.common.vec_env import VecNormalize
class AnalysisRolloutBufferSamples(NamedTuple):
observations: th.Tensor
actions: th.Tensor
old_values: th.Tensor
old_log_prob: th.Tensor
advantages: th.Tensor
returns: th.Tensor
times: th.Tensor
class RolloutBufferMultiLevel(RolloutBuffer):
"""
Rollout buffer used in on-policy algorithm PPO_SL.
It corresponds to ``buffer_size`` transitions collected
using the current policy.
This experience will be discarded after the policy update.
In order to use PPO objective, we also store the current value of each state
and the log probability of each taken action.
The term rollout here refers to the model-free notion and should not
be used with the concept of rollout used in model-based RL or planning.
Hence, it is only involved in policy and value function training but not action selection.
:param buffer_size: Max number of element in the buffer
:param observation_space: Observation space
:param action_space: Action space
:param device:
:param gae_lambda: Factor for trade-off of bias vs variance for Generalized Advantage Estimator
Equivalent to classic advantage when set to 1.
:param gamma: Discount factor
:param n_envs: Number of parallel environments
"""
def __init__(
self,
buffer_size: int,
observation_space: spaces.Space,
action_space: spaces.Space,
device: Union[th.device, str] = "cpu",
gae_lambda: float = 1,
gamma: float = 0.99,
n_envs: int = 1,
):
super(RolloutBufferMultiLevel, self).__init__(buffer_size, observation_space, action_space, device, gae_lambda, gamma, n_envs=n_envs)
self.times = None
self.reset()
def reset(self) -> None:
self.times = np.zeros((self.buffer_size, self.n_envs), dtype=np.float32)
super(RolloutBufferMultiLevel, self).reset()
def record_times(self, comp_times: np.ndarray) -> None:
'warning: usage only valid if this function is excuted right before `add` function'
self.times[self.pos] = comp_times
def swap_and_flatten_for_analysis(self, arr: np.ndarray) -> np.ndarray:
"""
Swap and then flatten axes 0 (buffer_size) and 1 (n_envs)
to convert shape from [n_steps, n_envs, ...] (when ... is the shape of the features)
to [n_steps * n_envs, ...] (which maintain the order)
:param arr:
:return:
"""
shape = arr.shape
if len(shape) < 3:
shape = shape + (1,)
return arr.swapaxes(0, 1).reshape(shape[0] * shape[1], *shape[2:], order='F')
def get_analysis_batch(self, batch_size: Optional[int] = None) -> Generator[RolloutBufferSamples, None, None]:
# Return everything, don't create minibatches
if batch_size is None:
batch_size = self.buffer_size * self.n_envs
indices = np.random.permutation(self.buffer_size * self.n_envs)
# Prepare the data
if not self.generator_ready:
_tensor_names = [
"observations",
"actions",
"values",
"log_probs",
"advantages",
"returns",
"times",
]
for tensor in _tensor_names:
self.__dict__[tensor] = self.swap_and_flatten_for_analysis(self.__dict__[tensor])
self.generator_ready = True
start_idx = 0
while start_idx < batch_size:
yield self._get_analysis_samples(indices[start_idx : start_idx + batch_size])
start_idx += batch_size
def _get_analysis_samples(self, batch_inds: np.ndarray, env: Optional[VecNormalize] = None) -> RolloutBufferSamples:
data = (
self.observations[batch_inds],
self.actions[batch_inds],
self.values[batch_inds].flatten(),
self.log_probs[batch_inds].flatten(),
self.advantages[batch_inds].flatten(),
self.returns[batch_inds].flatten(),
self.times[batch_inds].flatten(),
)
return AnalysisRolloutBufferSamples(*tuple(map(self.to_torch, data)))
def get_sync(self, sync_rollout_buffer, batch_size: Optional[int] = None) -> Generator[RolloutBufferSamples, None, None]:
assert self.full, ""
indices = np.random.permutation(self.buffer_size * self.n_envs)
# Prepare the data
if not self.generator_ready:
_tensor_names = [
"observations",
"actions",
"values",
"log_probs",
"advantages",
"returns",
]
for tensor in _tensor_names:
self.__dict__[tensor] = self.swap_and_flatten(self.__dict__[tensor])
sync_rollout_buffer.__dict__[tensor] = sync_rollout_buffer.swap_and_flatten(sync_rollout_buffer.__dict__[tensor])
self.generator_ready = True
sync_rollout_buffer.generator_ready = True
# Return everything, don't create minibatches
if batch_size is None:
batch_size = self.buffer_size * self.n_envs
start_idx = 0
while start_idx < self.buffer_size * self.n_envs:
yield self._get_samples(indices[start_idx : start_idx + batch_size])
yield sync_rollout_buffer._get_samples(indices[start_idx : start_idx + batch_size])
start_idx += batch_size
| 5,823 | 1,712 |
"""
Plot for NCAR Arctic Systems workshop poster. Graph is DJF sea ice volume
from PIOMAS over the satellite era.
Notes
-----
Author : Zachary Labe
Date : 4 April 2018
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from mpl_toolkits.basemap import Basemap, addcyclic, shiftgrid
import nclcmaps as ncm
import datetime
import read_MonthlyOutput as MO
import calc_Utilities as UT
import cmocean
import itertools
### Directory and time
directorydata = '/home/zlabe/Documents/Projects/Tests/SIV_animate/Data/'
directoryfigure = '/home/zlabe/Desktop/'
now = datetime.datetime.now()
currentmn = str(now.month-1)
currentdy = str(now.day)
currentyr = str(now.year)
years = np.arange(1979,2018,1)
### Define time
now = datetime.datetime.now()
currentmn = str(now.month)
currentdy = str(now.day)
currentyr = str(now.year)
currenttime = currentmn + '_' + currentdy + '_' + currentyr
titletime = currentmn + '/' + currentdy + '/' + currentyr
print('\n' '----Plotting Poster Figure 2 - %s----' % titletime)
### Read data
years,j,f,d = np.genfromtxt(directorydata + 'monthly_piomas.txt',
unpack=True,delimiter='',usecols=[0,1,2,12])
siv = (j[1:] + f[1:] + d[:-1])/3
### Plot Figure
def adjust_spines(ax, spines):
for loc, spine in ax.spines.items():
if loc in spines:
spine.set_position(('outward', 5))
else:
spine.set_color('none')
if 'left' in spines:
ax.yaxis.set_ticks_position('left')
else:
ax.yaxis.set_ticks([])
if 'bottom' in spines:
ax.xaxis.set_ticks_position('bottom')
else:
ax.xaxis.set_ticks([])
fig = plt.figure()
ax = plt.subplot()
adjust_spines(ax, ['left', 'bottom'])
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['left'].set_color('dimgrey')
ax.spines['bottom'].set_color('dimgrey')
ax.spines['left'].set_linewidth(2)
ax.spines['bottom'].set_linewidth(2)
ax.tick_params('both',length=4,width=2,which='major',color='dimgrey',pad=1)
ax.yaxis.grid(zorder=1,color='darkgrey',alpha=1,linewidth=0.4)
plt.plot(years[1:],siv,color=cmocean.cm.balance(0.78),linewidth=3.5,marker='o',markersize=7,
label=r'\textbf{PIOMAS v2.1 [Zhang and Rothrock, 2003]}')
plt.xticks(np.arange(1980,2021,10),list(map(str,np.arange(1980,2021,10))),
fontsize=13,color='dimgrey')
plt.yticks(np.arange(14,29,2),list(map(str,np.arange(14,29,2))),fontsize=13,
color='dimgrey')
plt.ylabel(r'\textbf{VOLUME [$\times$1000 km$^{3}$]}',
color='k',fontsize=16)
plt.title(r'\textbf{DEC-FEB : ARCTIC SEA ICE}',color='K',fontsize=27)
le = plt.legend(shadow=False,fontsize=8,loc='upper center',
bbox_to_anchor=(0.27, 0.07),fancybox=True,frameon=False,ncol=1)
for text in le.get_texts():
text.set_color('dimgrey')
plt.xlim([1980,2020])
plt.ylim([14,28])
plt.savefig(directoryfigure + 'PosterFig2.png',dpi=1000) | 3,032 | 1,210 |
from distutils.core import setup
setup(name='piku-binary', version='0.0.1', scripts=['piku.py'])
| 97 | 35 |
import random
from heaps import max_heaps, min_heaps
def heap_sort(array):
array = max_heaps.build_max_heap(array)
i = len(array) - 1
output = []
while i >= 0:
output.insert(0, array[0])
array = array[1:]
array = max_heaps.max_heap(array, 0)
i = i - 1
return output
if __name__ == '__main__':
# array = [5, 1, 3, 4, 2]
array = [random.randrange(0,10) for x in range(15)]
print(max_heaps.build_max_heap(array))
print(heap_sort(array))
print(min_heaps.build_min_heap(array))
| 552 | 227 |
#!/usr/bin/env python3
'''
Super SIM UPLMN Codec
@version 1.0.0
@author Tony Smith (@smittytone)
@copyright Twilio, Inc.
@licence MIT
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the "Software"),
to deal in the Software without restriction, including without limitation
the rights to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE
OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
'''
'''
IMPORTS
'''
import unittest
from plmn_codec import plmn_encoder, plmn_decoder, decode_table, decode_lte, decode_gsm, main
'''
TEST CASES
'''
class CodecTests(unittest.TestCase):
def test_plmn_encoder(self):
# Basic cases
self.assertEqual(plmn_encoder("310", "410"), "1300144080")
self.assertEqual(plmn_encoder("310", "260"), "1300624080")
# Over-long MCC, MNC
self.assertEqual(plmn_encoder("3108", "410333"), "1300144080")
# Short MNC
self.assertEqual(plmn_encoder("289", "88"), "82F9884080")
def test_plmn_decoder(self):
# Basic cases
self.assertEqual(plmn_decoder("1300144080"), ("310", "410", 64, 128))
self.assertEqual(plmn_decoder("1300624080"), ("310", "260", 64, 128))
# Over-long PLMN
self.assertEqual(plmn_decoder("1300624080FFFFFF"), ("310", "260", 64, 128))
# Short MNC
self.assertEqual(plmn_decoder("82F9884080"), ("289", "88", 64, 128))
def test_decode_table(self):
# Basic cases
self.assertEqual(decode_table("AT+CRSM=214,28512,0,0,10,13006240801300144080"), "1. MCC: 310 MNC: 260 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT\n2. MCC: 310 MNC: 410 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT")
self.assertEqual(decode_table("10,13006240801300144080"), "1. MCC: 310 MNC: 260 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT\n2. MCC: 310 MNC: 410 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT")
self.assertEqual(decode_table("13006240801300144080"), "1. MCC: 310 MNC: 260 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT\n2. MCC: 310 MNC: 410 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT")
self.assertEqual(decode_table("+CRSM: 144,0,13006240801300144080"), "1. MCC: 310 MNC: 260 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT\n2. MCC: 310 MNC: 410 RAT(s): E-UTRAN in WB-S1, NB-S1 modes, GSM + EC-GSM-IoT")
# Short table entry
self.assertEqual(decode_table("82F988408"), "")
def test_decode_lte(self):
self.assertEqual(decode_lte(0xFF), "UTRAN, E-UTRAN in WB-S1, NB-S1 modes, NG-RAN -- WARNING: Reserved bits set")
self.assertEqual(decode_lte(0x00), "")
self.assertEqual(decode_lte(0x01), " -- WARNING: Reserved bits set")
self.assertEqual(decode_lte(0x02), " -- WARNING: Reserved bits set")
self.assertEqual(decode_lte(0x50), "E-UTRAN in NB-S1 mode only")
def test_decode_gsm(self):
self.assertEqual(decode_gsm(0xFF), "GSM + EC-GSM-IoT, GSM COMPACT, CDMA2000 HRPD, CDMA2000 1xRTT -- WARNING: Reserved bits set")
self.assertEqual(decode_gsm(0x00), "")
self.assertEqual(decode_gsm(0x01), " -- WARNING: Reserved bits set")
self.assertEqual(decode_gsm(0x02), " -- WARNING: Reserved bits set")
self.assertEqual(decode_gsm(0x84), "GSM")
self.assertEqual(decode_gsm(0x88), "EC-GSM-IoT")
# main() tests: arguments
def test_main_missing_final_arg(self):
with self.assertRaises(SystemExit) as cm:
main(["-p","13006240801300144080","-p"])
self.assertEqual(cm.exception.code, 1)
def test_main_missing_inline_arg(self):
with self.assertRaises(SystemExit) as cm:
main(["-p"])
self.assertEqual(cm.exception.code, 1)
def test_main_bad_arg(self):
with self.assertRaises(SystemExit) as cm:
main(["-q","13006240801300144080"])
self.assertEqual(cm.exception.code, 1)
def test_main_malformed_table(self):
with self.assertRaises(SystemExit) as cm:
main(["-p","130062408013001440"])
self.assertEqual(cm.exception.code, 1)
def test_main_mispaired_mcc_mnc(self):
with self.assertRaises(SystemExit) as cm:
main(["310", "410", "310"])
self.assertEqual(cm.exception.code, 1)
def test_main_no_args(self):
with self.assertRaises(SystemExit) as cm:
main([])
self.assertEqual(cm.exception.code, 0)
'''
RUNTIME START
'''
if __name__ == '__main__':
unittest.main() | 5,321 | 2,301 |
import param
from setuptools import find_packages, setup
extras_require = {
'build': ['param >=1.7.0', 'setuptools'],
'tests': [
'flake8',
'twine',
'rfc3986',
'keyring'
],
}
setup_args = dict(
name="jupyter-panel-proxy",
description='Jupyter Server Proxy for Panel applications',
version=param.version.get_setup_version(
__file__,
"panel_server",
archive_commit="$Format:%h$",
),
long_description=open('README.md').read(),
long_description_content_type="text/markdown",
author="Julia Signell",
author_email= "developers@holoviz.org",
maintainer= "HoloViz developers",
maintainer_email= "developers@pyviz.org",
url="https://github.com/holoviz/jupyter-panel-proxy",
project_urls = {
"Bug Tracker": "http://github.com/holoviz/jupyter-panel-proxy/issues",
"Documentation": "https://github.com/holoviz/jupyter-panel-proxy/blob/master/README.md",
"Source Code": "https://github.com/holoviz/jupyter-panel-proxy",
},
platforms=['Windows', 'Mac OS X', 'Linux'],
license='BSD',
classifiers = [
"License :: OSI Approved :: BSD License",
"Development Status :: 5 - Production/Stable",
"Programming Language :: Python",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Operating System :: OS Independent",
"Intended Audience :: Science/Research",
"Intended Audience :: Developers",
"Natural Language :: English",
"Topic :: Scientific/Engineering",
"Topic :: Software Development :: Libraries"
],
python_requires=">=3.6",
install_requires=['jupyter-server-proxy', 'panel >=0.11'],
extras_require=extras_require,
packages=find_packages(),
entry_points={
'jupyter_serverproxy_servers': [
'panel = panel_server:setup_panel_server',
]
},
)
if __name__ == '__main__':
setup(**setup_args)
| 2,110 | 682 |
import api
import logging
import pathlib
import click
import itertools
import us
from api.can_api_definition import CovidActNowAreaTimeseries
from api.can_api_definition import CovidActNowBulkTimeseries
from libs.pipelines import api_pipeline
from libs.datasets.dataset_utils import AggregationLevel
from libs.datasets import combined_datasets
from libs.enums import Intervention
from libs.datasets.dataset_utils import AggregationLevel
PROD_BUCKET = "data.covidactnow.org"
_logger = logging.getLogger(__name__)
@click.group("api")
def main():
pass
@main.command()
@click.option(
"--output-dir",
"-o",
type=pathlib.Path,
help="Output directory to save schemas in.",
default="api/schemas",
)
def update_schemas(output_dir):
"""Updates all public facing API schemas."""
schemas = api.find_public_model_classes()
for schema in schemas:
path = output_dir / f"{schema.__name__}.json"
_logger.info(f"Updating schema {schema} to {path}")
path.write_text(schema.schema_json(indent=2))
@main.command()
@click.option(
"--input-dir",
"-i",
default="results",
help="Input directory of state projections",
type=pathlib.Path,
)
@click.option(
"--output",
"-o",
default="results/output/states",
help="Output directory for artifacts",
type=pathlib.Path,
)
@click.option(
"--summary-output",
default="results/output",
help="Output directory for state summaries.",
type=pathlib.Path,
)
@click.option("--aggregation-level", "-l", type=AggregationLevel)
@click.option("--state")
@click.option("--fips")
def generate_api(input_dir, output, summary_output, aggregation_level, state, fips):
"""The entry function for invocation"""
active_states = [state.abbr for state in us.STATES]
us_latest = combined_datasets.build_us_latest_with_all_fields().get_subset(
aggregation_level, state=state, fips=fips, states=active_states
)
us_timeseries = combined_datasets.build_us_timeseries_with_all_fields().get_subset(
aggregation_level, state=state, fips=fips, states=active_states
)
for intervention in list(Intervention):
_logger.info(f"Running intervention {intervention.name}")
all_timeseries = api_pipeline.run_on_all_fips_for_intervention(
us_latest, us_timeseries, intervention, input_dir
)
county_timeseries = [
output for output in all_timeseries if output.aggregate_level is AggregationLevel.COUNTY
]
api_pipeline.deploy_single_level(intervention, county_timeseries, summary_output, output)
state_timeseries = [
output for output in all_timeseries if output.aggregate_level is AggregationLevel.STATE
]
api_pipeline.deploy_single_level(intervention, state_timeseries, summary_output, output)
@main.command("generate-top-counties")
@click.option(
"--disable-validation", "-dv", is_flag=True, help="Run the validation on the deploy command",
)
@click.option(
"--input-dir", "-i", default="results", help="Input directory of state/county projections",
)
@click.option(
"--output",
"-o",
default="results/top_counties",
help="Output directory for artifacts",
type=pathlib.Path,
)
@click.option("--state")
@click.option("--fips")
def generate_top_counties(disable_validation, input_dir, output, state, fips):
"""The entry function for invocation"""
intervention = Intervention.SELECTED_INTERVENTION
active_states = [state.abbr for state in us.STATES]
us_latest = combined_datasets.build_us_latest_with_all_fields().get_subset(
AggregationLevel.COUNTY, states=active_states, state=state, fips=fips
)
us_timeseries = combined_datasets.build_us_timeseries_with_all_fields().get_subset(
AggregationLevel.COUNTY, states=active_states, state=state, fips=fips
)
def sort_func(output: CovidActNowAreaTimeseries):
return -output.projections.totalHospitalBeds.peakShortfall
all_timeseries = api_pipeline.run_on_all_fips_for_intervention(
us_latest,
us_timeseries,
Intervention.SELECTED_INTERVENTION,
input_dir,
sort_func=sort_func,
limit=100,
)
bulk_timeseries = CovidActNowBulkTimeseries(__root__=all_timeseries)
api_pipeline.deploy_json_api_output(
intervention, bulk_timeseries, output, filename_override="counties_top_100.json"
)
# top_counties_pipeline.deploy_results(county_results_api, "counties_top_100", output)
# _logger.info("finished top counties job")
| 4,579 | 1,454 |
# -*- coding: utf-8 -*-
"""
/***************************************************************************
WilliamWallaceDialog
A QGIS plugin
This plugin do a supervised classification
-------------------
begin : 2016-05-17
git sha : $Format:%H$
copyright : (C) 2016 by Gillian
email : gillian.milani@geo.uzh.ch
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
"""
import os
from PyQt4 import QtGui, uic, QtCore, QtSql
s = QtCore.QSettings()
FORM_CLASS, _ = uic.loadUiType(os.path.join(
os.path.dirname(__file__), 'choose_db_dialog_base.ui'))
class ChooseDbDialog(QtGui.QDialog, FORM_CLASS):
def __init__(self, parent = None):
"""Constructor."""
super(ChooseDbDialog, self).__init__(parent)
self.setupUi(self)
listOfConnections = self.getPostgisConnections()
self.fillComboBox(listOfConnections)
currentConnection = s.value('WallacePlugins/connectionName')
if currentConnection is not None:
index = self.comboBox.findData(currentConnection)
self.comboBox.setCurrentIndex(index)
def fillComboBox(self, list):
self.comboBox.addItem('', None)
for name in list:
self.comboBox.addItem(name, name)
def getPostgisConnections(self):
keyList = []
for key in s.allKeys():
if key.startswith('PostgreSQL/connections'):
if key.endswith('database'):
connectionName = key.split('/')[2]
keyList.append(connectionName)
return keyList
| 2,335 | 588 |
# PYTHON - MIT - UNICAMP
# =============================================================================
# Created By : Matheus Percário Bruder
# Created Date : February 7th, 2021
# ============================================================================
def f_1(a):
return 2 * a
def f_2(b):
return 3 * b
def composite_result(f, g, x):
return f(g(x))
def composite(f, g):
def inner_func(x):
return f(g(x))
return inner_func
# print(composite_result(f_1, f_2, 5))
# composite_f1_2 = composite(f_1, f_2)
# print(composite_f1_2(5))
| 573 | 209 |
import threading
import time
from math import atan, pi
import numpy as np
from serial import Serial
class Lidar:
RESULT_OK = 0
RESULT_TIMEOUT = -1
RESULT_FAIL = -2
DEFAULT_TIMEOUT = 2000
cmd_stop = 0x65
cmd_scan = 0x60
cmd_force_scan = 0x61
cmd_reset = 0x80
cmd_force_stop = 0x00
cmd_get_eai = 0x55
cmd_get_device_info = 0x90
cmd_get_device_health = 0x92
ans_type_devinfo = 0x4
and_type_devhealth = 0x6
cmd_sync_byte = 0xA5
cmdflag_has_payload = 0x80
ans_sync_byte1 = 0xA5
ans_sync_byte2 = 0x5A
ans_type_measurement = 0x81
resp_measurement_syncbit = (0x1 << 0)
resp_measurement_quality_shift = 2
resp_measurement_sync_quality_shift = 8
resp_measurement_checkbit = (0x1 << 0)
resp_measurement_angle_shift = 1
resp_measurement_angle_sample_shift = 8
resp_measurement_distance_shift = 2
resp_measurement_distance_half_shift = 1
class LaserScan:
class LaserConfig:
min_angle = -pi # Start angle for the laser scan [rad]
max_angle = pi # Stop angle for the laser scan [rad]
ang_increment = None # Scan resolution [rad]
time_increment = None # Scan resolution [s]
scan_time = None # Time between scans
min_range = 0.15 # Minimum range [m]
max_range = 10.0 # Maximum range [m]
range_res = None # Range resolution [m]
ranges = [] # Array of ranges
intensities = [] # Array of intensities
self_time_stamp = None # Self reported time stamp [ns]
system_time_stamp = None # System time when first range was measured [ns]
config = LaserConfig()
class YDLidarX4:
def __init__(self, port):
self._port = port
self._baudrate = 128000
self._isConnected = False
self._isScanning = False
try:
self._serial = Serial(self._port, self._baudrate, timeout=2.0)
self._isConnected = True
self._serial.reset_input_buffer()
self._serial.write([0xA5, 0x00])
self._serial.write([0xA5, 0x65])
self._serial.setDTR(0)
self._serial.flush()
except Exception as e:
print("Cannot open port {}".format(self._port))
return
self._scan = LaserScan()
self.thread = threading.Thread(target=self.cacheScanData)
def cacheScanData(self):
index = 0
self._scan.ranges = np.zeros(20)
# print(self.scan.ranges.shape)
while self._isScanning:
for pos in range(self._scan.ranges.shape[0]):
self._scan.ranges[pos] = pos
pass
def getScanData(self):
nodes = self._scan
count = nodes.ranges.shape[0]
all_nodes_counts = count
each_angle = 360.0 / all_nodes_counts
angle_compensate_nodes = np.zeros((all_nodes_counts, 2), dtype=int)
for i in range(all_nodes_counts):
if nodes[i, 0] != 0:
angle = (nodes[i, 1] >>
Lidar.resp_measurement_angle_shift)/64.0
inter = int(angle/each_angle)
angle_pre = angle - inter * each_angle
angle_next = (inter+1)*each_angle - angle
if angle_pre < angle_next:
if inter < all_nodes_counts:
angle_compensate_nodes[inter] = nodes[i]
else:
if inter < all_nodes_counts - 1:
angle_compensate_nodes[inter+1] = nodes[i]
diff_angle = nodes.config.max_angle - nodes.config.min_angle
counts = int(all_nodes_counts * (diff_angle / (2*pi)))
angle_start = int(pi + nodes.config.min_angle)
node_start = int(all_nodes_counts * (angle_start / (2*pi)))
nodes.ranges = np.zeros(counts)
index = 0
for i in range(all_nodes_counts):
dist_range = angle_compensate_nodes[i, 0] / 4000
if i < all_nodes_counts // 2:
index = all_nodes_counts // 2 - 1 - i
else:
index = all_nodes_counts - 1 - (i-all_nodes_counts//2)
if dist_range > nodes.config.max_range or dist_range < nodes.config.min_range:
dist_range = 0.0
pos = index - node_start
if 0 <= pos and pos < counts:
scan.ranges[pos] = dist_range
if diff_angle == 2*pi:
nodes.config.ang_increment = diff_angle / counts
else:
nodes.config.ang_increment = diff_angle / (counts - 1)
# for i in range(0, self.scan.ranges.shape[0], 3):
# pass
# for i in range(20):
# angle = self.scan.config.min_angle + i * self.scan.config.ang_increment
# dist = self.scan.ranges[i]
# print("{}: {}".format(angle, dist))
# print("\n\n")
return nodes
def startScanning(self):
if not self._isConnected:
return
self._serial.setDTR(1)
self._serial.flush()
self._serial.write([0xA5, 0x60])
time.sleep(0.1)
header = list(self._serial.read(7)) # read lidar_ans_header
# print(header)
self._isScanning = True
self.thread.start()
def stopScanning(self):
if not self._isConnected:
return
self._serial.setDTR(0)
self._serial.flush()
self._isScanning = False
class YDLidarX42:
def __init__(self, port):
self._port = port
self._baudrate = 128000
self.scan = LaserScan()
self.scan.config.min_angle = -pi
self.scan.config.max_angle = pi
self.scan.config.min_range = 0.25
self.scan.config.max_range = 10.0
self._intensities = False
self._auto_reconnect = True
self._resolution_fixed = True
self._reversion = False
self._low_exposure = False
self._samp_rate = 4
self._frequency = 7
self._node_counts = 720
self._each_angle = 0.5
self._isConnect = False
self._isScanning = False
self.device_info = {
"Model": None,
"Firmware version": None,
"Hardware version": None,
"Serial number": None
}
self.device_health = {
"Status": None,
"Error code": None
}
self.thread = threading.Thread(target=self.cacheScanData)
self.laser = LaserScan()
self.count = 3600
self.scan_node_buf = np.zeros((self.count, 2), dtype=int)
self._package_sample_index = 0
def initialize(self):
try:
if not self._isConnect:
self._serial = Serial(self._port, self._baudrate, timeout=2.0)
self._isConnect = True
self._serial.reset_input_buffer()
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_force_stop])
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_stop])
self.clearDTR()
# self.setDTR()
else:
raise Exception("Already connected")
if self._isScanning:
return True
else:
if not self.getDeviceHealth():
return False
if not self.getDeviceInfo():
return False
except Exception as e:
print(e)
return False
def startScan(self):
self._serial.reset_input_buffer()
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_force_stop])
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_stop])
m_pointTime = 1e9 / 5000
self.setDTR()
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_scan])
time.sleep(0.1)
header = list(self._serial.read(7)) # read lidar_ans_header
# data = list(self._serial.read(10)) # read data
print(header)
# print(data)
self._isScanning = True
self.thread.start()
def stopScan(self):
self._isScanning = False
self.thread.join()
def getDeviceHealth(self):
self._serial.reset_input_buffer()
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_get_device_health])
time.sleep(0.1)
header = list(self._serial.read(7)) # read lidar_ans_header
data = list(self._serial.read(header[2])) # read data
if not any(data):
return True
return False
def getDeviceInfo(self):
self._serial.reset_input_buffer()
self._serial.write([Lidar.cmd_sync_byte, Lidar.cmd_get_device_info])
time.sleep(0.1)
header = list(self._serial.read(7)) # read lidar_ans_header
data = list(self._serial.read(header[2])) # read data
if data[0] == 6:
self.device_info["Model"] = "X4"
ver = int.from_bytes(data[1:3], byteorder='little', signed=False)
self.device_info["Firmware version"] = "{}.{}.{}".format(
ver >> 8, (ver & 0xff)//10, (ver & 0xff) % 10)
self.device_info["Hardware version"] = str(data[3])
self.device_info["Serial number"] = "".join(map(str, data[4:]))
print(self.device_info)
return True
@classmethod
def _AngleCorr(cls, dist):
if dist == 0:
return 0
else:
return int((atan(((21.8 * (155.3 - (dist / 4.0))) / 155.3) / (dist / 4.0)) * 180.0/pi)*64.0)
def waitScanData(self, nodebuffer, count):
if not self._isConnect:
count = 0
recvNodeCount = 0
while recvNodeCount < count:
node = self.waitPackage()
nodebuffer[recvNodeCount] = node
recvNodeCount += 1
if recvNodeCount == count:
break
return nodebuffer, count
def waitPackage(self):
node = np.array([0, Lidar.resp_measurement_checkbit], dtype=int)
packageSampleDistance = []
recvPos = 0
recvBuffer = []
packageBuffer = []
CheckSum = 0
CheckSumCal = 0
CheckSumResult = False
SampleNumlAndCTCal = 0
LastSampleAngleCal = 0
package_sample_num = 0
FirstSampleAngle = 0
LastSampleAngle = 0
IntervalSampleAngle = 0
package_type = 0
if self._package_sample_index == 0:
recvPos = 0
while self._isScanning:
currentByte = ord(self._serial.read())
if recvPos == 0:
if currentByte == 0xAA:
pass
else:
continue
elif recvPos == 1:
CheckSumCal = 0x55AA
if currentByte == 0x55:
pass
else:
recvPos = 0
continue
elif recvPos == 2:
SampleNumlAndCTCal = currentByte
package_type = currentByte & 0x01
if package_type == 0 or package_type == 1:
if package_type == 1:
scan_frequence = (currentByte & 0xFE) >> 1
else:
recvPos = 0
continue
elif recvPos == 3:
SampleNumlAndCTCal += (currentByte * 0x100)
package_sample_num = currentByte
elif recvPos == 4:
if currentByte & Lidar.resp_measurement_checkbit:
FirstSampleAngle = currentByte
else:
recvPos = 0
continue
elif recvPos == 5:
FirstSampleAngle += currentByte * 0x100
CheckSumCal ^= FirstSampleAngle
FirstSampleAngle = FirstSampleAngle >> 1
elif recvPos == 6:
if currentByte & Lidar.resp_measurement_checkbit:
LastSampleAngle = currentByte
else:
recvPos = 0
continue
elif recvPos == 7:
LastSampleAngle = currentByte * 0x100 + LastSampleAngle
LastSampleAngleCal = LastSampleAngle
LastSampleAngle = LastSampleAngle >> 1
if package_sample_num == 1:
IntervalSampleAngle = 0
else:
if LastSampleAngle < FirstSampleAngle:
if (FirstSampleAngle >= 180 * 64) and (LastSampleAngle <= 180*64):
IntervalSampleAngle = float(
(360 * 64 + LastSampleAngle - FirstSampleAngle) / (package_sample_num - 1))
else:
if FirstSampleAngle > 360:
IntervalSampleAngle = float(
LastSampleAngle-FirstSampleAngle)/(package_sample_num - 1)
else:
temp = FirstSampleAngle
FirstSampleAngle = LastSampleAngle
LastSampleAngle = temp
IntervalSampleAngle = float(
(LastSampleAngle - FirstSampleAngle)/(package_sample_num-1))
else:
IntervalSampleAngle = float(
(LastSampleAngle - FirstSampleAngle)/(package_sample_num-1))
IntervalSampleAngle_LastPackage = IntervalSampleAngle
elif recvPos == 8:
CheckSum = currentByte
elif recvPos == 9:
CheckSum += (currentByte*0x100)
packageBuffer.append(currentByte)
recvPos += 1
if recvPos == 10:
package_recvPos = recvPos
break
if recvPos == 10:
recvPos = 0
packageSampleDistance.clear()
inComingByte = self._serial.inWaiting()
recvBuffer = list(self._serial.read(inComingByte))
Valu8Tou16 = 0
for i in range(inComingByte):
if recvPos % 2 == 1:
Valu8Tou16 += recvBuffer[i] * 0x100
CheckSumCal ^= Valu8Tou16
packageSampleDistance.append(Valu8Tou16)
else:
Valu8Tou16 = recvBuffer[i]
packageBuffer.append(recvBuffer[i])
recvPos += 1
if package_sample_num * 2 == recvPos:
package_recvPos += recvPos
else:
recvBuffer.clear()
CheckSumCal ^= SampleNumlAndCTCal
CheckSumCal ^= LastSampleAngleCal
if CheckSumCal != CheckSum:
CheckSumResult = False
else:
CheckSumResult = True
sync_flag = 0
if package_type == 0:
sync_flag = 2
else:
sync_flag = 1
sync_quality = 10
if CheckSumResult and recvBuffer != []:
node[0] = packageSampleDistance[self._package_sample_index]
AngleCorrectForDistance = self._AngleCorr(node[0])
temp = FirstSampleAngle + IntervalSampleAngle * \
self._package_sample_index + AngleCorrectForDistance
if temp < 0:
node[1] = (int(temp + 360 * 64) << 1) + \
Lidar.resp_measurement_checkbit
else:
if temp > 360 * 64:
node[1] = (int(temp - 360*64) << 1) + \
Lidar.resp_measurement_checkbit
else:
node[1] = (int(temp) << 1)+Lidar.resp_measurement_checkbit
else:
sync_flag = 2
sync_quality = 10
self._package_sample_index += 1
if self._package_sample_index >= package_sample_num:
self._package_sample_index = 0
return node
def cacheScanData(self):
count = 128
local_buff = np.zeros((count, 2), dtype=int)
local_scan = np.zeros((3600, 2), dtype=int)
scan_count = 0
while self._isScanning:
local_buff, count = self.waitScanData(local_buff, count)
print(local_buff)
# package_sample_index = 0
# package_sample_num = 0
# recvPos = 0
# packageBuffer = []
# CheckSumCal = 0x55AA
# CheckSum = 0
# SampleNumlAndCTCal = 0
# LastSampleAngleCal = 0
# FirstSampleAngle = 0
# LastSampleAngle = 0
# IntervalSampleAngle = 0
# IntervalSampleAngle_LastPackage = 0
def doProcessSimple(self):
# node [ $distance_q2$, $angle_q6_checkbit$ ]
nodes = self.scan_node_buf
all_nodes_counts = self._node_counts
each_angle = 360.0 / all_nodes_counts
angle_compensate_nodes = np.zeros((all_nodes_counts, 2), dtype=int)
for i in range(self.count):
if nodes[i, 0] != 0:
angle = (nodes[i, 1] >>
Lidar.resp_measurement_angle_shift)/64.0
inter = int(angle/each_angle)
angle_pre = angle - inter * each_angle
angle_next = (inter+1)*each_angle - angle
if angle_pre < angle_next:
if inter < all_nodes_counts:
angle_compensate_nodes[inter] = nodes[i]
else:
if inter < all_nodes_counts - 1:
angle_compensate_nodes[inter+1] = nodes[i]
# print(nodes[i], angle, inter, angle_pre, angle_next)
# print("\n")
diff_angle = self.scan.config.max_angle - self.scan.config.min_angle
counts = int(all_nodes_counts * (diff_angle / (2*pi)))
angle_start = int(pi + self.scan.config.min_angle)
node_start = int(all_nodes_counts * (angle_start / (2*pi)))
self.scan.ranges = np.zeros(counts)
index = 0
for i in range(all_nodes_counts):
dist_range = angle_compensate_nodes[i, 0] / 4000
if i < all_nodes_counts // 2:
index = all_nodes_counts // 2 - 1 - i
else:
index = all_nodes_counts - 1 - (i-all_nodes_counts//2)
if dist_range > self.scan.config.max_range or dist_range < self.scan.config.min_range:
dist_range = 0.0
pos = index - node_start
if 0 <= pos and pos < counts:
self.scan.ranges[pos] = dist_range
if diff_angle == 2*pi:
self.scan.config.ang_increment = diff_angle / counts
else:
self.scan.config.ang_increment = diff_angle / (counts - 1)
# for i in range(0, self.scan.ranges.shape[0], 3):
# pass
# for i in range(20):
# angle = self.scan.config.min_angle + i * self.scan.config.ang_increment
# dist = self.scan.ranges[i]
# print("{}: {}".format(angle, dist))
# print("\n\n")
def setDTR(self):
if not self._isConnect:
return
else:
self._serial.setDTR(1)
self._serial.flush()
def clearDTR(self):
if not self._isConnect:
return
else:
self._serial.setDTR(0)
self._serial.flush()
# if __name__ == "__main__":
# lidar = YDLidarX4("/dev/ttyUSB0")
# lidar.initialize()
# lidar.startScan()
# # for i in range(5):
# # lidar.doProcessSimple()
# # print(lidar._serial.inWaiting())
# time.sleep(1)
# lidar.stopScan()
# while True:
# scan = LaserScan()
| 20,039 | 6,161 |
'''
Copyright (C) 2018 Intel Corporation
?
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
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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.
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SPDX-License-Identifier: Apache-2.0
'''
import os
base_path = os.path.split(os.path.realpath(__file__))[0].split(os.sep)
def mkdirs(path):
if not os.path.exists(path):
os.makedirs(path)
__TEMP_DIR = None
def getTmpDir():
pathList = ["/var/log", "/tmp", "~/tmp"]
for each in pathList:
if os.access(each, os.R_OK | os.W_OK):
path = each
break
else:
path = "~/tmp"
global __TEMP_DIR
if __TEMP_DIR is None:
__TEMP_DIR = os.path.join(path, "oat")
path = os.path.expanduser(path)
path = os.path.normpath(path)
mkdirs(path)
return path
class UiWindows(object):
def __init__(self, bound):
if u"top" not in bound:
bound = bound[u"bounds"]
self.t = bound[u"top"]
self.l1 = bound[u"left"]
self.r = bound[u"right"]
self.b = bound[u"bottom"]
def __str__(self):
return "lefttop: %d, %d rightbottom: %d, %d" % (self.l1, self.t, self.r, self.b)
def getWidth(self):
return self.r - self.l1
def getHeight(self):
return self.b - self.t
def getMidPoint(self):
return (self.l1 + self.r) / 2, (self.t + self.b) / 2
def getTop(self):
return self.t
def getLeft(self):
return self.l1
| 1,868 | 660 |
# Licensed under a 3-clause BSD style license - see LICENSE
from __future__ import print_function, division
__all__ = ["Photometry_legacy"]
from ..Utils.import_modules import *
from .. import Utils
from .. import Core
from .. import Atmosphere
######################## class Photometry ########################
class Photometry_legacy(object):
"""Photometry_legacy
This class allows to fit the flux from the primary star
of a binary system, assuming it is heated by the secondary
(which in most cases will be a pulsar).
It is meant to deal with photometry data. Many sets of photometry
data (i.e. different filters) are read. For each data set, one can
calculate the predicted flux of the model at every data point (i.e.
for a given orbital phase).
"""
def __init__(self, atmo_fln, data_fln, ndiv, porb, x2sini, edot=1., read=True):
"""__init__(atmo_fln, data_fln, ndiv, porb, x2sini, edot=1., read=True)
This class allows to fit the flux from the primary star
of a binary system, assuming it is heated by the secondary
(which in most cases will be a pulsar).
It is meant to deal with photometry data. Many sets of photometry
data (i.e. different filters) are read. For each data set, one can
calculate the predicted flux of the model at every data point (i.e.
for a given orbital phase).
atmo_fln (str): A file containing the grid model information for each
data set. The format of each line of the file is as follows:
Col 0: band name
Col 1: band filename
data_fln (str): A file containing the information for each data set.
Three formats are currently supported.
9-column (preferred):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for flux/magnitude
Col 3: column id for flux/magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: softening parameter for asinh magnitude conversion. If
the value is 0., then standard magnitudes are used.
Col 7: flux or mag flag. Currently, all the data must be in the
same format.
'mag' means magnitude system
'flux' means flux system
Col 8: filename
8-column (support for asinh magnitudes, no fluxes input):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for magnitude
Col 3: column id for magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: softening parameter for asinh magnitude conversion. If
the value is 0., then standard magnitudes are used.
Col 7: filename
7-column (only support standard magnitude input):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for magnitude
Col 3: column id for magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: filename
ndiv (int): The number of surface slice. Defines how coarse/fine the
surface grid is.
porb (float): Orbital period of the system in seconds.
x2sini (float): Projected semi-major axis of the secondary (pulsar)
in light-second.
edot (float): Irradiated energy from the secondary, aka pulsar (i.e.
spin-down luminosity) in erg/s. This is only used for the
calculation of the irradiation efficiency so it does not
enter in the modeling itself.
read (bool): If True, Icarus will use the pre-calculated geodesic
primitives. This is the recommended option, unless you have the
pygts package installed to calculate it on the spot.
>>> fit = Photometry(atmo_fln, data_fln, ndiv, porb, x2sini)
"""
DeprecationWarning("This is the old Photometry class. Use the one from the Photometry instead.")
# We define some class attributes.
self.porb = porb
self.x2sini = x2sini
self.edot = edot
# We read the data.
self._Read_data(data_fln)
# We read the atmosphere models with the atmo_grid class
self._Read_atmo(atmo_fln)
# We make sure that the length of data and atmo_dict are the same
if len(self.atmo_grid) != len(self.data['id']):
print('The number of atmosphere grids and data sets '
'(i.e. photometric bands) do not match!!!')
return
else:
# We keep in mind the number of datasets
self.ndataset = len(self.atmo_grid)
# We initialize some important class attributes.
self._Init_lightcurve(ndiv, read=read)
self._Setup()
def Calc_chi2(self, par, offset_free=1, func_par=None, nsamples=None, influx=False, full_output=False, verbose=False):
"""Calc_chi2(par, offset_free=1, func_par=None, nsamples=None, influx=False, full_output=False, verbose=False)
Returns the chi-square of the fit of the data to the model.
par (list/array): Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus (can be None).
[8]: Absorption A_V (can be None).
Note: DM and A_V can be set to None. In which case, if
offset_free = 1, these parameters will be fit for.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
offset_free (int):
1) offset_free = 0:
If the offset is not free and the DM and A_V are specified, the chi2
is calculated directly without allowing an offset between the data and
the bands.
The full chi2 should be:
chi2 = sum[ w_i*(off_i-dm-av*C_i)**2]
+ w_dm*(dm-dm_obs)**2
+ w_av*(av-av_obs)**2, with w = 1/sigma**2
The extra terms (i.e. dm-dm_obs and av-av_obs) should be included
as priors.
1) offset_free = 1:
The model light curves are fitted to the data with an arbitrary offset
for each band. After, a post-fit is performed in order to adjust the offsets
of the curves accounting for the fact that the absolute calibration of the
photometry may vary.
Note:
The errors should be err**2 = calib_err**2 + 1/sum(flux_err)**2
but we neglect the second term because it is negligeable.
func_par (None): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
nsamples (None): Number of points for the lightcurve sampling.
If None, the lightcurve will be sampled at the observed data
points.
influx (False): If true, will calculate the fit between the data and the
model in the flux domain.
full_output (bool): If true, will output a dictionnary of additional parameters.
'offset' (array): the calculated offset for each band.
'par' (array): the input parameters (useful if one wants to get the optimized
values of DM and A_V.
'res' (array): the fit residuals.
verbose (bool): If true will display the list of parameters and fit information.
>>> chi2 = self.Calc_chi2([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# We can provide a function that massages the input parameters and returns them.
# This function can, for example, handle fixed parameters or boundary limits.
if func_par is not None:
par = func_par(par)
# check if we are dealing with a dictionary
if isinstance(par, dict):
par = [par['incl'], par['corotation'], par['filling'], par['tnight'], par['gravdark'], par['k1'], par['tday'], par['dm'], par['av']]
if offset_free == 0:
pred_flux = self.Get_flux(par, flat=True, nsamples=nsamples, verbose=verbose)
((par[7],par[8]), chi2_data, rank, s) = Utils.Misc.Fit_linear(self.mag-pred_flux, x=self.ext, err=self.mag_err, b=par[7], m=par[8])
if full_output:
residuals = ( (self.mag-pred_flux) - (self.ext*par[8] + par[7]) ) / self.mag_err
offset = np.zeros(self.ndataset)
chi2_band = 0.
chi2 = chi2_data + chi2_band
else:
# Calculate the theoretical flux
pred_flux = self.Get_flux(par, flat=False, nsamples=nsamples, verbose=verbose)
# Calculate the residuals between observed and theoretical flux
if influx: # Calculate the residuals in the flux domain
res1 = np.array([ Utils.Misc.Fit_linear(self.data['flux'][i], x=Utils.Flux.Mag_to_flux(pred_flux[i], flux0=self.atmo_grid[i].flux0), err=self.data['flux_err'][i], b=0., inline=True) for i in np.arange(self.ndataset) ])
offset = -2.5*np.log10(res1[:,1])
if full_output:
print( "Impossible to return proper residuals" )
residuals = None
else: # Calculate the residuals in the magnitude domain
res1 = np.array([ Utils.Misc.Fit_linear(self.data['mag'][i]-pred_flux[i], err=self.data['mag_err'][i], m=0., inline=True) for i in np.arange(self.ndataset) ])
offset = res1[:,0]
if full_output:
residuals = [ ((self.data['mag'][i]-pred_flux[i]) - offset[i])/self.data['mag_err'][i] for i in np.arange(self.ndataset) ]
chi2_data = res1[:,2].sum()
# Fit for the best offset between the observed and theoretical flux given the DM and A_V
res2 = Utils.Misc.Fit_linear(offset, x=self.data['ext'], err=self.data['calib'], b=par[7], m=par[8], inline=True)
par[7], par[8] = res2[0], res2[1]
chi2_band = res2[2]
# Here we add the chi2 of the data from that of the offsets for the bands.
chi2 = chi2_data + chi2_band
# Update the offset to be the actual offset between the data and the band (i.e. minus the DM and A_V contribution)
offset -= self.data['ext']*par[8] + par[7]
# Output results
if verbose:
print('chi2: {:.3f}, chi2 (data): {:.3f}, chi2 (band offset): {:.3f}, DM: {:.3f}, A_V: {:.3f}'.format(chi2, chi2_data, chi2_band, par[7], par[8]))
if full_output:
return chi2, {'offset':offset, 'par':par, 'res':residuals}
else:
return chi2
def Get_flux(self, par, flat=False, func_par=None, DM_AV=False, nsamples=None, verbose=False):
"""Get_flux(par, flat=False, func_par=None, DM_AV=False, nsamples=None, verbose=False)
Returns the predicted flux (in magnitude) by the model evaluated
at the observed values in the data set.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus (optional).
[8]: Absorption A_V (optional).
Note: Can also be a dictionary:
par.keys() = ['av', 'corotation', 'dm', 'filling',
'gravdark', 'incl','k1','tday','tnight']
flat (False): If True, the values are returned in a 1D vector.
If False, predicted values are grouped by data set left in a list.
func_par (None): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
DM_AV (False): If true, will include the DM and A_V in the flux.
nsamples (None): Number of points for the lightcurve sampling.
If None, the lightcurve will be sampled at the observed data
points.
Note: tirr = (par[6]**4 - par[3]**4)**0.25
>>> self.Get_flux([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# func_par
if func_par is not None:
par = func_par(par)
# check if we are dealing with a dictionary
if isinstance(par, dict):
par = [par['incl'], par['corotation'], par['filling'], par['tnight'], par['gravdark'], par['k1'], par['tday'], par['dm'], par['av']]
# We call Make_surface to make the companion's surface.
self.Make_surface(par, verbose=verbose)
# If nsamples is None we evaluate the lightcurve at each data point.
if nsamples is None:
phases = self.data['phase']
# If nsamples is set, we evaluate the lightcurve at nsamples
else:
phases = (np.arange(nsamples, dtype=float)/nsamples).repeat(self.ndataset).reshape((nsamples,self.ndataset)).T
# If DM_AV, we take into account the DM and AV into the flux here.
if DM_AV:
DM_AV = self.data['ext']*par[8] + par[7]
else:
DM_AV = self.data['ext']*0.
# Calculate the actual lightcurves
flux = []
for i in np.arange(self.ndataset):
# If we use the interpolation method and if the filter is the same as a previously
# calculated one, we do not recalculate the fluxes and simply copy them.
if nsamples is not None and self.grouping[i] < i:
flux.append(flux[self.grouping[i]])
else:
flux.append( np.array([self.star.Mag_flux(phase, atmo_grid=self.atmo_grid[i]) for phase in phases[i]]) + DM_AV[i] )
# If nsamples is set, we interpolate the lightcurve at nsamples.
if nsamples is not None:
for i in np.arange(self.ndataset):
ws, inds = Utils.Series.Getaxispos_vector(phases[i], self.data['phase'][i])
flux[i] = flux[i][inds]*(1-ws) + flux[i][inds+1]*ws
# We can flatten the flux array to simplify some of the calculations in the Calc_chi2 function
if flat:
return np.hstack(flux)
else:
return flux
def Get_flux_theoretical(self, par, phases, func_par=None, verbose=False):
"""Get_flux_theoretical(par, phases, func_par=None, verbose=False)
Returns the predicted flux (in magnitude) by the model evaluated at the
observed values in the data set.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus.
[8]: Absorption A_V.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
phases: A list of orbital phases at which the model should be
evaluated. The list must have the same length as the
number of data sets, each element can contain many phases.
func_par (None): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
verbose (False)
Note: tirr = (par[6]**4 - par[3]**4)**0.25
>>> self.Get_flux_theoretical([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.], [[0.,0.25,0.5,0.75]]*4)
"""
# func_par
if func_par is not None:
par = func_par(par)
# check if we are dealing with a dictionary
if isinstance(par, dict):
par = [par['incl'], par['corotation'], par['filling'], par['tnight'], par['gravdark'], par['k1'], par['tday'], par['dm'], par['av']]
# We call Make_surface to make the companion's surface.
self.Make_surface(par, verbose=verbose)
DM_AV = self.data['ext']*par[8] + par[7]
flux = []
for i in np.arange(self.ndataset):
# If the filter is the same as a previously calculated one
# we do not recalculate the fluxes and simply copy them.
if self.grouping[i] < i:
flux.append( flux[self.grouping[i]] )
else:
flux.append( np.array([self.star.Mag_flux(phase, atmo_grid=self.atmo_grid[i]) for phase in phases[i]]) + DM_AV[i] )
return flux
def Get_Keff(self, par, nphases=20, atmo_grid=0, func_par=None, make_surface=False, verbose=False):
"""
Returns the effective projected velocity semi-amplitude of the star in m/s.
The luminosity-weighted average velocity of the star is returned for
nphases, for the specified dataset, and a sin wave is fitted to them.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature.
[7]: Distance modulus.
[8]: Absorption A_V.
nphases (int): Number of phases to evaluate the velocity at.
atmo_grid (int, AtmoGridPhot): The atmosphere grid to use for the velocity
calculation. Can be an integer that represents the index of the atmosphere
grid object in self.atmo_grid, and it can be an AtmoGridPhot instance.
func_par (function): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
make_surface (bool): Whether lightcurve.make_surface should be called
or not. If the flux has been evaluate before and the parameters have
not changed, False is fine.
verbose (bool): Verbosity. Will plot the velocities and the sin fit.
"""
# If it is required to recalculate the stellar surface.
if make_surface:
self.Make_surface(par, func_par=func_par, verbose=verbose)
# Deciding which atmosphere grid we use to evaluate Keff
if isinstance(atmo_grid, int):
atmo_grid = self.atmo_grid[atmo_grid]
# Get the Keffs and fluxes
phases = np.arange(nphases)/float(nphases)
Keffs = np.array( [self.star.Keff(phase, atmo_grid=atmo_grid) for phase in phases] )
tmp = Utils.Misc.Fit_linear(Keffs, np.sin(cts.TWOPI*(phases)), inline=True)
if verbose:
pylab.plot(np.linspace(0.,1.), tmp[1]*np.sin(np.linspace(0.,1.)*cts.TWOPI)+tmp[0])
pylab.scatter(phases, Keffs)
Keff = tmp[1]
return Keff
def _Init_lightcurve(self, ndiv, read=False):
"""_Init_lightcurve(ndiv, read=False)
Call the appropriate Lightcurve class and initialize
the stellar array.
>>> self._Init_lightcurve(ndiv)
"""
self.star = Core.Star(ndiv, read=read)
return
def Make_surface(self, par, func_par=None, verbose=False):
"""Make_surface(par, func_par=None, verbose=False)
This function gets the parameters to construct to companion
surface model and calls the Make_surface function from the
Lightcurve object.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus (optional). Not needed here.
[8]: Absorption A_V (optional). Not needed here.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
func_par (None): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
>>> self.Make_surface([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# Apply a function that can modify the value of parameters.
if func_par is not None:
par = func_par(par)
# check if we are dealing with a dictionary
if isinstance(par, dict):
par = [par['incl'], par['corotation'], par['filling'], par['tnight'], par['gravdark'], par['k1'], par['tday'], par['dm'], par['av']]
# Verify parameter values to make sure they make sense.
#if par[6] < par[3]: par[6] = par[3]
# Let's move on with the flux calculation.
q = par[5] * self.K_to_q
tirr = (par[6]**4 - par[3]**4)**0.25
if verbose:
print( "#####\n" + str(par[0]) + ", " + str(par[1]) + ", " + str(par[2]) + ", " + str(par[3]) + ", " + str(par[4]) + ", " + str(par[5]) + ", " + str(par[6]) + ", " + str(par[7]) + ", " + str(par[8]) + "\n" + "q: " + str(q) + ", tirr: " + str(tirr) )
self.star.Make_surface(q=q, omega=par[1], filling=par[2], temp=par[3], tempgrav=par[4], tirr=tirr, porb=self.porb, k1=par[5], incl=par[0])
return
def Plot(self, par, nphases=51, verbose=True, func_par=None, nsamples=None, output=False):
"""
Plots the observed and predicted values along with the
light curve.
par (list): Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus.
[8]: Absorption A_V.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
nphases (int): Orbital phase resolution of the model
light curve.
verbose (bool): verbosity.
func_par (function): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
nsamples (int): Number of points for the lightcurve sampling.
If None, the lightcurve will be sampled at the observed data
points.
output (bool): If true, will return the model flux values and the offsets.
>>> self.Plot([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# Calculate the orbital phases at which the flux will be evaluated
phases = np.resize(np.linspace(0.,1.,nphases), (self.ndataset, nphases))
# Fit the data in order to get the offset
chi2, extras = self.Calc_chi2(par, offset_free=1, verbose=verbose, func_par=func_par, nsamples=nsamples, full_output=True)
offset = extras['offset']
par = extras['par']
# Calculate the theoretical flux at the orbital phases.
pred_flux = self.Get_flux_theoretical(par, phases)
# Calculating the min and the max
tmp = []
for i in np.arange(self.ndataset):
tmp = np.r_[tmp, pred_flux[i]+offset[i]]
minmag = tmp.min()
maxmag = tmp.max()
deltamag = (maxmag - minmag)
spacing = 0.2
#---------------------------------
##### Plot using matplotlib
try:
fig = pylab.gcf()
try:
ax = pylab.gca()
except:
ax = fig.add_subplot(1,1,1)
except:
fig, ax = pylab.subplots(nrows=1, ncols=1)
ncolors = self.ndataset - 1
if ncolors == 0:
ncolors = 1
for i in np.arange(self.ndataset):
color = np.ones((self.data['mag'][i].size,1), dtype=float) * matplotlib.cm.jet(float(i)/ncolors)
ax.errorbar(self.data['phase'][i], self.data['mag'][i], yerr=self.data['mag_err'][i], fmt='none', ecolor=color[0])
ax.scatter(self.data['phase'][i], self.data['mag'][i], edgecolor=color, facecolor=color)
ax.plot(phases[i], pred_flux[i], 'k--')
ax.plot(phases[i], pred_flux[i]+offset[i], 'k-')
ax.text(1.01, pred_flux[i].max(), self.data['id'][i])
ax.set_xlim([0,1])
ax.set_ylim([maxmag+spacing*deltamag, minmag-spacing*deltamag])
ax.set_xlabel( "Orbital Phase" )
ax.set_ylabel( "Magnitude" )
pylab.draw()
if output:
return pred_flux, offset
return
def Plot_theoretical(self, par, nphases=31, verbose=False, device='/XWIN', func_par=None, output=False):
"""Plot_theoretical(par, nphases=31, verbose=False, device='/XWIN', func_par=None, output=False)
Plots the predicted light curves.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus.
[8]: Absorption A_V.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
nphases (31): Orbital phase resolution of the model
light curve.
verbose (False): verbosity.
device ('/XWIN'): Device driver for Pgplot (can be '/XWIN',
'filename.ps/PS', 'filename.ps./CPS', '/AQT' (on mac only)).
func_par (None): Function that takes the parameter vector and
returns the parameter vector. This allow for possible constraints
on the parameters. The vector returned by func_par must have a length
equal to the number of expected parameters.
output (False): If true, will return the model flux values and the offsets.
>>> self.Plot_theoretical([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# Calculate the orbital phases at which the flux will be evaluated
phases = np.resize(np.linspace(0.,1.,nphases), (self.ndataset, nphases))
# Calculate the theoretical flux at the orbital phases.
pred_flux = self.Get_flux_theoretical(par, phases, func_par=func_par, verbose=verbose)
# Loop over the data set and plot the flux, theoretical flux and offset theoretical flux
for i in np.arange(self.ndataset):
plotxy(pred_flux[i], phases[i], color=1+i, line=1, rangey=[np.max(pred_flux)+0.5,np.min(pred_flux)-0.5], rangex=[0.,1.], device=device)
if output:
return pred_flux
return
def Pretty_print(self, par, make_surface=True, verbose=True):
"""Pretty_print(par, make_surface=True, verbose=True)
Return a nice representation of the important
parameters.
par: Parameter list.
[0]: Orbital inclination in radians.
[1]: Corotation factor.
[2]: Roche-lobe filling.
[3]: Companion temperature.
[4]: Gravity darkening coefficient.
[5]: K (projected velocity semi-amplitude) in m/s.
[6]: Front side temperature or irradiation temperature.
The irradiation temperature is in the case of the
photometry_modeling_temperature class.
[7]: Distance modulus.
[8]: Absorption A_V.
Note: Can also be a dictionary:
par.keys() = ['av','corotation','dm','filling','gravdark','incl','k1','tday','tnight']
make_surface (True): Whether to recalculate the
surface of the star or not.
verbose (True): Output the nice representation
of the important parameters or just return them
as a list.
>>> self.Pretty_print([PIBYTWO,1.,0.9,4000.,0.08,300e3,5000.,10.,0.])
"""
# check if we are dealing with a dictionary
if isinstance(par, dict):
par = [par['incl'], par['corotation'], par['filling'], par['tnight'], par['gravdark'], par['k1'], par['tday'], par['dm'], par['av']]
incl = par[0]
corot = par[1]
fill = par[2]
temp_back = par[3]
gdark = par[4]
K = par[5]
temp_front = par[6]
DM = par[7]
A_V = par[8]
if DM is None: DM = 0.
if A_V is None: A_V = 0.
q = K * self.K_to_q
tirr = (temp_front**4 - temp_back**4)**0.25
if make_surface:
self.star.Make_surface(q=q, omega=corot, filling=fill, temp=temp_back, tempgrav=gdark, tirr=tirr, porb=self.porb, k1=K, incl=incl)
separation = self.star.separation
roche = self.star.Roche()
Mwd = self.star.mass1
Mns = self.star.mass2
# below we transform sigma from W m^-2 K^-4 to erg s^-1 cm^-2 K^-4
# below we transform the separation from m to cm
Lirr = tirr**4 * (cts.sigma*1e3) * (separation*100)**2 * 4*cts.PI
eff = Lirr/self.edot
# we convert Lirr in Lsun units
Lirr /= 3.839e33
if verbose:
print( "##### Pretty Print #####" )
print( "%9.7f, %3.1f, %9.7f, %10.5f, %4.2f, %9.2f, %9.7f, %6.3f, %6.3f" %tuple(par) )
print( "" )
print( "Corotation factor: %4.2f" %corot )
print( "Gravity Darkening: %5.3f" %gdark )
print( "" )
print( "Filling factor: %6.4f" %fill )
print( "Orbital separation: %5.4e km" %(separation/1000) )
print( "Roche lobe size: %6.4f (orb. sep.)" %roche )
print( "" )
print( "Irradiation efficiency: %6.4f" %eff )
print( "Irration luminosity: %5.4e Lsun" %Lirr )
print( "Backside temperature: %7.2f K" %temp_back )
print( "Frontside temperature: %7.2f (tabul.), %7.2f (approx.) K" %(np.exp(self.star.logteff.max()),temp_front) )
print( "" )
print( "Distance Modulus: %6.3f" %DM )
print( "Absorption (V band): %6.3f" %A_V )
print( "" )
print( "Inclination: %5.3f rad (%6.2f deg)" %(incl,incl*cts.RADTODEG) )
print( "K: %7.3f km/s" %(K/1000) )
print( "" )
print( "Mass ratio: %6.3f" %q )
print( "Mass NS: %5.3f Msun" %Mns )
print( "Mass Comp: %5.3f Msun" %Mwd )
return np.r_[corot,gdark,fill,separation,roche,eff,tirr,temp_back,np.exp(self.star.logteff.max()),temp_front,DM,A_V,incl,incl*cts.RADTODEG,K,q,Mns,Mwd]
def _Read_atmo(self, atmo_fln):
"""_Read_atmo(atmo_fln)
Reads the atmosphere model data.
atmo_fln (str): A file containing the grid model information for each
data set. The format of each line of the file is as follows:
Col 0: band name
Col 1: band filename
>>> self._Read_atmo(atmo_fln)
"""
f = open(atmo_fln,'r')
lines = f.readlines()
self.atmo_grid = []
for line in lines:
if (line[0] != '#') and (line[0] != '\n'):
tmp = line.split()
self.atmo_grid.append(Atmosphere.AtmoGridPhot.ReadHDF5(tmp[1]))
return
def _Read_data(self, data_fln):
"""_Read_data(data_fln)
Reads the photometric data.
data_fln (str): A file containing the information for each data set.
Three formats are currently supported.
9-column (preferred):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for flux/magnitude
Col 3: column id for flux/magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: softening parameter for asinh magnitude conversion. If
the value is 0., then standard magnitudes are used.
Col 7: flux or mag flag. Currently, all the data must be in the
same format.
'mag' means magnitude system
'flux' means flux system
Col 8: filename
8-column (support for asinh magnitudes, no fluxes input):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for magnitude
Col 3: column id for magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: softening parameter for asinh magnitude conversion. If
the value is 0., then standard magnitudes are used.
Col 7: filename
7-column (only support standard magnitude input):
Col 0: band name
Col 1: column id for orbital phase. Orbital phases must be 0-1.
Phase 0 is defined as the primary star (the one modelled),
located at inferior conjunction.
Col 2: column id for magnitude
Col 3: column id for magnitude error
Col 4: shift to phase zero. Sometimes people use other
definition for orbital phases, so this allows to correct for
it.
Col 5: band calibration error, in magnitude
Col 6: filename
>>> self._Read_data(data_fln)
"""
f = open(data_fln,'r')
lines = f.readlines()
self.data = {'phase':[], 'mag':[], 'mag_err':[], 'flux':[], 'flux_err':[], 'calib':[], 'fln':[], 'id':[], 'softening':[]}
for line in lines:
if (line[0] != '#') and (line[0] != '\n'):
tmp = line.split()
## Old version of the data files
if len(tmp) == 7:
d = np.loadtxt(tmp[-1], usecols=[int(tmp[1]),int(tmp[2]),int(tmp[3])], unpack=True)
## With the flag '_' in the observation id, we do not take %1 so that
## we preserve the long-term phase coherence.
if tmp[0].find('_') != -1:
self.data['phase'].append( np.atleast_1d(d[0] - float(tmp[4])) )
else:
self.data['phase'].append( np.atleast_1d((d[0] - float(tmp[4]))%1.) )
self.data['mag'].append( np.atleast_1d(d[1]) )
self.data['mag_err'].append( np.atleast_1d(d[2]) )
self.data['calib'].append( float(tmp[5]) )
self.data['fln'].append( tmp[-1] )
self.data['id'].append( tmp[0] )
self.data['softening'].append( 0. )
## Old version of the data files including asinh magnitudes
elif len(tmp) == 8:
d = np.loadtxt(tmp[-1], usecols=[int(tmp[1]),int(tmp[2]),int(tmp[3])], unpack=True)
# With the flag '_' in the observation id, we do not take %1 so that
# we preserve the long-term phase coherence.
if tmp[0].find('_') != -1:
self.data['phase'].append( np.atleast_1d(d[0] - float(tmp[4])) )
else:
self.data['phase'].append( np.atleast_1d((d[0] - float(tmp[4]))%1.) )
self.data['mag'].append( np.atleast_1d(d[1]) )
self.data['mag_err'].append( np.atleast_1d(d[2]) )
self.data['calib'].append( float(tmp[5]) )
self.data['fln'].append( tmp[-1] )
self.data['id'].append( tmp[0] )
self.data['softening'].append( float(tmp[6]) )
## Current version of the data files including asinh magnitudes
elif len(tmp) == 9:
d = np.loadtxt(tmp[-1], usecols=[int(tmp[1]),int(tmp[2]),int(tmp[3])], unpack=True)
## Data can be set in magnitude
if tmp[-2] == 'mag':
# With the flag '_' in the observation id, we do not take %1 so that
# we preserve the long-term phase coherence.
if tmp[0].find('_') != -1:
self.data['phase'].append( np.atleast_1d(d[0] - float(tmp[4])) )
else:
self.data['phase'].append( np.atleast_1d((d[0] - float(tmp[4]))%1.) )
self.data['mag'].append( np.atleast_1d(d[1]) )
self.data['mag_err'].append( np.atleast_1d(d[2]) )
self.data['calib'].append( float(tmp[5]) )
self.data['fln'].append( tmp[-1] )
self.data['id'].append( tmp[0] )
self.data['softening'].append( float(tmp[6]) )
## Data can be set in flux
elif tmp[-2] == 'flux':
# With the flag '_' in the observation id, we do not take %1 so that
# we preserve the long-term phase coherence.
if tmp[0].find('_') != -1:
self.data['phase'].append( np.atleast_1d(d[0] - float(tmp[4])) )
else:
self.data['phase'].append( np.atleast_1d((d[0] - float(tmp[4]))%1.) )
self.data['flux'].append( np.atleast_1d(d[1]) )
self.data['flux_err'].append( np.atleast_1d(d[2]) )
self.data['calib'].append( float(tmp[5]) )
self.data['fln'].append( tmp[-1] )
self.data['id'].append( tmp[0] )
self.data['softening'].append( float(tmp[6]) )
## Current version of the data files including asinh magnitudes
else:
raise Exception("The data file does not have the expected number of columns.")
return
def _Setup(self):
"""_Setup()
Stores some important information in class variables.
>>> self._Setup()
"""
# We calculate the constant for the conversion of K to q (observed
# velocity semi-amplitude to mass ratio, with K in m/s)
self.K_to_q = Utils.Binary.Get_K_to_q(self.porb, self.x2sini)
# Storing values in 1D arrays.
# The V band extinction will be extracted from the atmosphere_grid class
ext = []
self.data['ext'] = []
# Converting magnitudes <-> fluxes in case this would be needed for upper limits
if len(self.data['flux']) == 0:
has_mag = True
else:
has_mag = False
# The grouping will define datasets that are in the same band and can be evaluated only once in order to save on computation.
grouping = np.arange(self.ndataset)
for i in np.arange(self.ndataset):
ext.extend(self.data['phase'][i]*0.+self.atmo_grid[i].meta['ext'])
self.data['ext'].append(self.atmo_grid[i].meta['ext'])
if self.data['softening'][i] == 0:
if has_mag:
flux,flux_err = Utils.Flux.Mag_to_flux(self.data['mag'][i], mag_err=self.data['err'][i], flux0=self.atmo_grid[i].meta['zp'])
self.data['flux'].append( flux )
self.data['flux_err'].append( flux_err )
else:
mag,mag_err = Utils.Flux.Flux_to_mag(self.data['flux'][i], flux_err=self.data['flux_err'][i], flux0=self.atmo_grid[i].meta['zp'])
self.data['mag'].append( mag )
self.data['mag_err'].append( mag_err )
else:
flux,flux_err = Utils.Flux.Asinh_to_flux(self.data['mag'][i], mag_err=self.data['mag_err'][i], flux0=self.atmo_grid[i].meta['zp'], softening=self.data['softening'][i])
self.data['flux'].append( flux )
self.data['flux_err'].append( flux_err )
for j in np.arange(i+1):
if self.data['id'][i] == self.data['id'][j]:
grouping[i] = j
break
self.ext = np.asarray(ext)
self.grouping = np.asarray(grouping)
self.data['ext'] = np.asarray(self.data['ext'])
self.data['calib'] = np.asarray(self.data['calib'])
self.mag = np.hstack(self.data['mag'])
self.mag_err = np.hstack(self.data['mag_err'])
self.phase = np.hstack(self.data['phase'])
self.flux = np.hstack(self.data['flux'])
self.flux_err = np.hstack(self.data['flux_err'])
self.ndata = self.flux.size
return
######################## class Photometry ########################
| 44,983 | 13,385 |
#a2.t4 #This program is to create a function to check carbondioxide content in air
#taking advantage of python statistics library
import statistics
def check_air_quality(carbondioxide_data):
if statistics.median(carbondioxide_data) >= 400 and statistics.median(carbondioxide_data) < 700:
return "EXCELLENT"
elif statistics.median(carbondioxide_data) >= 700 and statistics.median(carbondioxide_data) < 900:
return "GOOD"
elif statistics.median(carbondioxide_data) >= 900 and statistics.median(carbondioxide_data) < 1100:
return "FAIR"
elif statistics.median(carbondioxide_data) >= 1100 and statistics.median(carbondioxide_data) < 1600:
return "MEDIOCRE"
elif statistics.median(carbondioxide_data) >= 1600 and statistics.median(carbondioxide_data) <=2100:
return "BAD"
| 827 | 315 |
import json
import os
import uuid
from django import forms
from captcha.fields import ReCaptchaField
from phonenumber_field.formfields import PhoneNumberField
from django.utils.translation import gettext_lazy as _
from django.utils.translation import get_language
from geodata.models import NPA
from business.models import Request
class BusinessAddForm(forms.Form):
name = forms.CharField(
label=_('Company name'),
max_length=255,
help_text=_('The name of the company.'),
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
description = forms.CharField(
label=_('Description'),
help_text=_('A short description of the services of the company.'),
widget=forms.Textarea(attrs={
'class': 'form-control form-control-sm',
'rows': 5
})
)
address = forms.CharField(
label=_('Street and number'),
max_length=255,
help_text=_('The street and street number of your address'),
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
location = forms.ModelChoiceField(
label=_('City'),
help_text=_('Where is the company based?'),
queryset=NPA.objects.all(),
widget=forms.Select(attrs={
'class': 'form-control form-control-sm'
})
)
category = forms.CharField(
label=_('Categories'),
max_length=255,
help_text=_('List possible categories of the service that the company provides (eg. Food, Books, Drinks, Music, Games, Mobility)'),
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
delivery = forms.CharField(
label=_('Delivery locations'),
max_length=255,
help_text=_('Where are you delivering ? Whole Switzerland, cantons, districts, municipalities, be as precise as possible.'),
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
website = forms.CharField(
label=_('Website'),
max_length=255,
help_text=_('Company website, if any.'),
required=False,
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
phone = forms.CharField(
label=_('Phone number'),
max_length=100,
help_text=_('Company phone number, if any.'),
required=False,
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
email = forms.CharField(
label=_('Email address'),
max_length=255,
help_text=_('Company email address, if any.'),
required=False,
widget=forms.TextInput(attrs={
'class': 'form-control form-control-sm'
})
)
if os.environ.get("RUNNING_ENV", default='dev') != 'dev':
captcha = ReCaptchaField(
label=''
)
def get_location_choices(self):
return [
(0, 'Test')
]
def save_request(self):
location = str(self.cleaned_data['location']) + ' [PK:' + str(self.cleaned_data['location'].pk) + ']'
# Create request
r = Request(
name=self.cleaned_data['name'],
description=self.cleaned_data['description'],
address=self.cleaned_data['address'],
location=location,
website=self.cleaned_data['website'],
phone=self.cleaned_data['phone'],
email=self.cleaned_data['email'],
category=self.cleaned_data['category'],
delivery=self.cleaned_data['delivery'],
source=1,
checksum='Web Form',
source_uuid=str(uuid.uuid4()),
lang=get_language()
)
r.save()
# Set status
r.set_status(r.events.NEW)
| 3,952 | 1,159 |
#!/usr/bin/env python3
from .init import robotics_init_
from .robotics_layers import RoboticsLinear
from .epsilon_greedy import EpsilonGreedy
| 144 | 47 |
#!/usr/local/bin/python3
import argparse
import sys
from handlers.mongo_handler import Mongo_Handler
from bson.json_util import dumps
custom_mongo = Mongo_Handler("resource_db", "resources")
def list_resources(user,resource):
if resource is not None:
return custom_mongo.get_from_mongo("resource_id", resource)
if user is not None:
resources=custom_mongo.get_all_resources()
return list(filter(lambda x: x["ownership_id"] == user,resources))
return custom_mongo.get_all_resources()
def remove_resources(user,resource,all):
if resource is not None:
return custom_mongo.delete_in_mongo("resource_id", resource)
if user is not None and all:
return custom_mongo.remove_resources("ownership_id",user)
if user is None and all:
return custom_mongo.remove_resources()
return "No action taken (missing --all flag?)"
parser = argparse.ArgumentParser(description='Operational management of resources.')
parser.add_argument('action', metavar='action', type=str,
help='Operation to perform: list/remove')
parser.add_argument('-u',
'--user',
help='Filter action by user ID')
parser.add_argument('-r',
'--resource',
help='Filter action by resource ID')
parser.add_argument('-a',
'--all',
action='store_true',
help='Apply action to all resources.')
args = vars(parser.parse_args())
if args["action"] == "list":
result = dumps(list_resources(args['user'],args['resource']))
elif args["action"] == "remove":
if args["resource"] is not None:
args["all"] = False
result = remove_resources(args['user'],args['resource'],args['all'])
else:
print("Allowed actions are 'remove' or 'list'")
sys.exit(-1)
print(result)
| 1,897 | 540 |
IntxLNK/ u s r / l i b / p y t h o n 3 . 5 / o s . p y | 56 | 55 |
# speaker_2_sound.py
# 한 스피커로 녹음해서 정위상, 역위상 wav를 생성한 다음 정위상은 왼쪽, 역위상은 오른쪽 스피커에서 재생시키는 소스코드
# (정위상, 역위상 파일을 하나의 스테레오 wav로 만듦)
# 음성(소음) 녹음, 재생 하는 패키지(wav파일)
import pyaudio
import wave
# 위상 반전, 파장 결합(Merge), 소리 재생 하는 패키지
from pydub import AudioSegment
from pydub.playback import play
from scipy.io import wavfile
import matplotlib.pyplot as plt
CHUNK = 1024
FORMAT = pyaudio.paInt16 # Portaudio Sample Format 설정
CHANNELS = 1 # 채널
RATE = 44100
RECORD_SECONDS = 5 # 녹음 시간(초)
thread = None
# 녹음한 wav 파일 이름 지정
WAVE_OUTPUT_FILENAME = "originalAudio.wav"
p = pyaudio.PyAudio()
stream = p.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
input=True, # input 스트림 명시
frames_per_buffer=CHUNK)
print("Start to record the audio.")
frames = []
for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
data = stream.read(CHUNK)
frames.append(data)
print("Recording is finished.")
stream.stop_stream()
stream.close()
p.terminate()
wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
wf.setnchannels(CHANNELS)
wf.setsampwidth(p.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))
wf.close()
# 지정한 wav 파일 load
originalSound = AudioSegment.from_file(WAVE_OUTPUT_FILENAME, format="wav")
# 기존 wav 파일 역위상 파장 생성
reversedSound = originalSound.invert_phase()
# 역위상 파장 wav파일로 저장 (생략 가능)
reversedSound.export("reversedAudio.wav", format="wav")
# 정위상 재생
# play(originalSound)
# 역위상 재생
# play(reversedSound)
# 정 위상을 왼쪽에서 재생 (스테레오) (pan 100% left)
# pannedLeft = originalSound.pan(-1) # -1은 100% 왼쪽으로 이동 시킨다는 의미
# play(pannedLeft)
# 정 위상을 왼쪽에서 재생 (스테레오) (pan 100% right)
# pannedRight = reversedSound.pan(1) # +1은 100% 오른쪽으로 이동 시킨다는 의미
# play(pannedRight)
# 스테레오 두 파일을 왼쪽에서 들리는 모노, 오른쪽에서만 들리는 모노로 바꾼다음 합쳐서 하나의 스테레오 파일로 만듦
stereo_sound = AudioSegment.from_mono_audiosegments(
originalSound, reversedSound)
play(stereo_sound)
stereo_sound.export("stereo_sound.wav", format="wav")
# 파형 출력 (그래프)
sample_rate, audio_samples = wavfile.read("stereo_sound.wav", 'rb')
# Show some basic information about the audio.
duration = len(audio_samples)/sample_rate
print(f'Sample rate: {sample_rate} Hz')
print(f'Total duration: {duration:.2f}s')
print(f'Size of the input: {len(audio_samples)}')
plt.plot(audio_samples)
plt.show()
| 2,310 | 1,344 |
#Crie um programa que leia quanto dinheiro uma pessoa tem na carteira e mostre quantos dólares ela pode comprar.
real = float(input("quantos reais voce tem na carteira: R$"))
dolar = real/5.31
print("com R${:.2f} voce pode comprar U${:.2f}.".format(real,dolar)) | 263 | 97 |
"""ADS1220 example (monitor for negative voltage)."""
from time import sleep
from machine import Pin, SPI # type: ignore
from ads1220 import ADC
cs = 15 # Chip select pin
drdy = 27 # Data ready pin
spi = SPI(1,
baudrate=10000000, # 10 MHz (try lower speed to troubleshoot)
sck=Pin(14),
mosi=Pin(13),
miso=Pin(12),
phase=1) # ADS1220 uses SPI mode 1
adc = ADC(spi, cs, drdy)
def test():
"""Test code."""
adc.conversion_continuous() # Set continuous conversion mode
adc.pga_off() # Disable gain
adc.fir_filter(1) # Simultaneous 50-Hz and 60-Hz rejection
adc.operating_mode(2) # Turbo mode
adc.data_rate(2) # 180 SPS
adc.start_conversion() # Start conversions
adc.select_channel(0) # Select channel 0 (0 to 3 ADC channels)
sleep(.1) # Ensure ADC ready
try:
while True:
result = adc.read_wait_negative(timeout=1000)
if result:
print("Negative voltage acquired.")
else:
print("Timeout.")
sleep(3)
except KeyboardInterrupt:
print("\nCtrl-C pressed to exit.")
finally:
adc.power_down()
spi.deinit()
test()
| 1,230 | 454 |
### Class to define 3D U-Net.
from typing import List, Tuple
import numpy as np
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from models.custom_layers import Softmax3d
class AnalysisLayer(nn.Module):
"""Module for analysis layer of U-Net architecture."""
def __init__(self, n_features: int,
conv_size: int = 3,
first: bool = False,
pooling: nn.MaxPool3d = None,
upconv: nn.ConvTranspose3d = None):
"""Initialisation of layer.
Args:
n_features: Number of input features (output will be double).
conv_size: Size of convolution kernel.
first: Whether this is the first layer in the U-Net.
pooling: Pooling layer (if supplied).
upconv : Upconvolution layer (for bottom layer of U-Net).
"""
super(AnalysisLayer, self).__init__()
if first:
features_in = 1 # TODO adapt for RGB images
else:
features_in = n_features
self.pooling = pooling
self.conv1 = nn.Conv3d(features_in, n_features,
kernel_size=conv_size)
self.bn1 = nn.BatchNorm3d(n_features)
self.relu = nn.ReLU(inplace=True)
self.conv2 = nn.Conv3d(n_features, n_features*2,
kernel_size=conv_size)
self.bn2 = nn.BatchNorm3d(n_features*2)
self.upconv = upconv
def forward(self, x: Variable) -> Variable:
"""Forward pass through layer."""
if self.pooling is not None:
x = self.pooling(x)
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
x = self.relu(x)
if self.upconv is not None:
x = self.upconv(x)
return x
class SynthesisLayer(nn.Module):
"""Module for synthesis layer of U-Net architecture."""
def __init__(self, n_features: int, conv_size: int = 3,
upconv_size: int = 2, last: bool = False):
"""Initialisation.
Args:
n_features: Number of input features (remember shortcut layers!).
conv_size: Size of convolution layer kernel.
upconv_size: Size and stride of upconvolution layer kernel.
last: Whether this is the final layer in the network.
"""
super(SynthesisLayer, self).__init__()
features_out = n_features // 3
self.conv1 = nn.Conv3d(n_features, features_out,
kernel_size=conv_size)
self.bn1 = nn.BatchNorm3d(features_out)
self.relu = nn.ReLU(inplace=True)
self.conv2 = nn.Conv3d(features_out, features_out,
kernel_size=conv_size)
self.bn2 = nn.BatchNorm3d(features_out)
if last:
self.upconv = None
else:
self.upconv = nn.ConvTranspose3d(features_out, features_out,
kernel_size=upconv_size,
stride=upconv_size)
def forward(self, x: Variable) -> Variable:
"""Forward pass through layer."""
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.bn2(x)
x = self.relu(x)
if self.upconv is not None:
x = self.upconv(x)
return x
class FinalLayer(nn.Module):
"""Final layer to reduce to classed pixels."""
def __init__(self, n_features: int, n_classes: int):
"""Initilisation.
Args:
n_features: Number of input features.
n_classes: Final number of classes.
"""
super(FinalLayer, self).__init__()
self.conv_fc = nn.Conv3d(n_features, n_classes, kernel_size=1)
self.softmax = Softmax3d()
def forward(self, x: Variable) -> Variable:
"""Forward pass through layer."""
x = self.conv_fc(x)
x = self.softmax(x)
return x
class UNet3D(nn.Module):
"""3D U-Net network architecture."""
def __init__(self, n_layer: int, n_class: int, features_root: int,
input_size: Tuple[int], pool_size: int = 2,
conv_size: int = 3, upconv_size: int = 2):
"""Initialisation of network.
Args:
n_layer: Number of U-Net resolution steps, equivalent to number of
analysis layers.
n_class: Number of output classes.
features_root: Number of features in the first layer of the network.
input_size: Size of 3D input image to network.
pool_size: Size and stride of the max pooling window.
conv_size: Size of the convolution kernel.
upconv_size: Size and stride of the upconvolution kernel.
"""
super(UNet3D, self).__init__()
self.n_layer = n_layer
self.n_class = n_class
self.features_root = features_root
self.input_size = input_size
self.pool_size = pool_size
self.conv_size = conv_size
self.upconv_size = upconv_size
self.pool = nn.MaxPool3d(kernel_size=self.pool_size,
stride=self.pool_size)
self.layers = self.__construct_layers()
# Crop sizes for concatenation at shortcut connections.
self.dimen_diff = [self.calc_dimen_diff(i)
for i in range(self.n_layer-1)]
def __construct_layers(self) -> nn.ModuleList:
"""Instantiates layers for network.
Returns:
A module list of layers in the network.
"""
n_features = self.features_root
layers = nn.ModuleList([])
# Analysis path
for i in range(self.n_layer):
if i == 0:
layers.append(AnalysisLayer(n_features, first=True))
elif i == self.n_layer-1:
# lowest layer
upconv = nn.ConvTranspose3d(n_features*2, n_features*2,
kernel_size=self.upconv_size,
stride=self.upconv_size)
layers.append(AnalysisLayer(n_features, pooling=self.pool,
upconv=upconv))
else:
layers.append(AnalysisLayer(n_features, pooling=self.pool))
n_features *= 2
# Synthesis path
for i in range(self.n_layer-1, 0, -1):
n_features += n_features // 2 # shortcut connection
if i == 1:
layers.append(SynthesisLayer(n_features, last=True))
else:
layers.append(SynthesisLayer(n_features))
n_features //= 3
# Final layer
layers.append(FinalLayer(n_features, self.n_class))
return layers
def calc_layer_dimension(self, n: int) -> np.ndarray:
"""Calculates the shape of a U-Net layer for shortcut connections.
If the layer is an analysis (downward) resolution step, calculates
the output of that layer before max pooling. If the layer is a
synthesis step, calculates the input before the first convolution.
Args:
n: Layer number (first analysis layer is 0).
Returns:
The shape of the output Tensor.
"""
if n > self.n_layer-1: # this is a synthesis path layer
shape = self.calc_layer_dimension(self.n_layer-1)
num_operations = n - self.n_layer + 1
for i in range(num_operations):
if i != 0:
shape -= (2 * (self.conv_size - 1))
shape *= self.upconv_size
else: # this is an analysis path layer
shape = np.array(self.input_size)
for i in range(n+1):
if i != 0:
shape //= self.pool_size
shape -= (2 * (self.conv_size - 1))
return shape
def calc_dimen_diff(self, res_step: int) -> List[int]:
"""Calculate dimension difference between up and down layers.
The difference is the size difference (in pixels) between the
input to the `n`th layer of the U-Net and the corresponding
layer in the synthesis path. Used for concatenation in
shortcut connections.
Args:
res_step: Resolution step of network (max is self.n_layer-1).
Returns:
A list of the shape difference in each axis.
"""
shape_analysis = self.calc_layer_dimension(res_step)
shape_synthesis = self.calc_layer_dimension(2 * (self.n_layer-1)
- res_step)
return (shape_analysis - shape_synthesis)
def forward(self, x: Variable) -> Variable:
"""Forward pass through network.
Args:
x: Network input.
Returns:
The output of the network.
"""
dw_features = []
shortcut_count = 0
for i, layer in enumerate(self.layers):
if i > self.n_layer-1 and i < len(self.layers)-1:
# Concatenate shortcut connection.
i_short = 2 * (self.n_layer-1) - i # shortcut index
difference = self.dimen_diff[i_short]
crop = [(di // 2 + (di % 2 > 0), di // 2)
for di in difference]
shortcut = dw_features[i_short][:,:,
(crop[0][0]):(dw_features[i_short].size()[2] - crop[0][1]),
(crop[1][0]):(dw_features[i_short].size()[3] - crop[1][1]),
(crop[2][0]):(dw_features[i_short].size()[4] - crop[2][1])]
x = torch.cat((shortcut, x), dim=1)
shortcut_count += 1
x = layer(x)
if i < self.n_layer-1:
# Save for shortcut connection.
dw_features.append(x.clone())
return x
| 10,026 | 2,960 |
print('Hello World Python') | 27 | 7 |
# -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
import time
from alibabacloud_tea_util.client import Client as UtilClient
from Tea.exceptions import TeaException
from Tea.request import TeaRequest
from Tea.core import TeaCore
from antchain_alipay_util.client import Client as AlipayUtilClient
from alibabacloud_rpc_util.client import Client as RPCUtilClient
from Tea.exceptions import UnretryableException
from antchain_sdk_ebc import models as ebc_models
from alibabacloud_tea_util import models as util_models
class Client(object):
def __init__(self, config, _endpoint=None, _region_id=None, _access_key_id=None, _access_key_secret=None,
_protocol=None, _user_agent=None, _read_timeout=None, _connect_timeout=None, _http_proxy=None,
_https_proxy=None, _socks_5proxy=None, _socks_5net_work=None, _no_proxy=None, _max_idle_conns=None,
_security_token=None):
"""
Init client with Config
@param config: config contains the necessary information to create a client
"""
self._endpoint = _endpoint
self._region_id = _region_id
self._access_key_id = _access_key_id
self._access_key_secret = _access_key_secret
self._protocol = _protocol
self._user_agent = _user_agent
self._read_timeout = _read_timeout
self._connect_timeout = _connect_timeout
self._http_proxy = _http_proxy
self._https_proxy = _https_proxy
self._socks_5proxy = _socks_5proxy
self._socks_5net_work = _socks_5net_work
self._no_proxy = _no_proxy
self._max_idle_conns = _max_idle_conns
self._security_token = _security_token
if UtilClient.is_unset(config):
raise TeaException({
"code": "ParameterMissing",
"message": "'config' can not be unset"
})
self._access_key_id = config.access_key_id
self._access_key_secret = config.access_key_secret
self._security_token = config.security_token
self._endpoint = config.endpoint
self._protocol = config.protocol
self._user_agent = config.user_agent
self._read_timeout = config.read_timeout
self._connect_timeout = config.connect_timeout
self._http_proxy = config.http_proxy
self._https_proxy = config.https_proxy
self._no_proxy = config.no_proxy
self._socks_5proxy = config.socks_5proxy
self._socks_5net_work = config.socks_5net_work
self._max_idle_conns = config.max_idle_conns
def do_request(self, version, action, protocol, method, pathname, request, runtime):
"""
Encapsulate the request and invoke the network
@type action: str
@param action: api name
@type protocol: str
@param protocol: http or https
@type method: str
@param method: e.g. GET
@type pathname: str
@param pathname: pathname of every api
@type request: dict
@param request: which contains request params
@param runtime: which controls some details of call api, such as retry times
@rtype: dict
@return: the response
"""
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": UtilClient.default_number(runtime.read_timeout, self._read_timeout),
"connectTimeout": UtilClient.default_number(runtime.connect_timeout, self._connect_timeout),
"httpProxy": UtilClient.default_string(runtime.http_proxy, self._http_proxy),
"httpsProxy": UtilClient.default_string(runtime.https_proxy, self._https_proxy),
"noProxy": UtilClient.default_string(runtime.no_proxy, self._no_proxy),
"maxIdleConns": UtilClient.default_number(runtime.max_idle_conns, self._max_idle_conns),
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
_request.protocol = UtilClient.default_string(self._protocol, protocol)
_request.method = method
_request.pathname = pathname
_request.query = {
"method": action,
"version": version,
"sign_type": "HmacSHA1",
"req_time": AlipayUtilClient.get_timestamp(),
"req_msg_id": UtilClient.get_nonce(),
"access_key": self._access_key_id,
"charset": "UTF-8",
"baseSdkVersion": "Tea-SDK",
"sdkVersion": "Tea-SDK-20200929"
}
if not UtilClient.empty(self._security_token):
_request.query["security_token"] = self._security_token
_request.headers = {
"host": self._endpoint,
"user-agent": self.get_user_agent()
}
tmp = UtilClient.anyify_map_value(RPCUtilClient.query(request))
_request.body = UtilClient.to_form_string(tmp)
_request.headers["content-type"] = "application/x-www-form-urlencoded"
signed_param = TeaCore.merge(_request.query,
RPCUtilClient.query(request))
_request.query["sign"] = AlipayUtilClient.get_signature(signed_param, self._access_key_secret)
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
obj = UtilClient.read_as_json(_response.body)
res = UtilClient.assert_as_map(obj)
resp = UtilClient.assert_as_map(res.get('response'))
if AlipayUtilClient.has_error(res):
raise TeaException({
"message": resp.get('result_msg'),
"data": resp,
"code": resp.get('result_code')
})
return resp
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_user_agent(self):
"""
Get user agent
@rtype: str
@return: user agent
"""
user_agent = "TeaClient/1.0.0"
return UtilClient.get_user_agent(user_agent)
def create_baas_ebc_organization(self, request):
"""
Description: 创建企业
Summary: 创建企业
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_organization_ex(request, runtime)
def create_baas_ebc_organization_ex(self, request, runtime):
"""
Description: 创建企业
Summary: 创建企业
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcOrganizationResponse().from_map(self.do_request("1.0", "baas.ebc.organization.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_person(self, request):
"""
Description: 创建个人
Summary: 创建个人
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_person_ex(request, runtime)
def create_baas_ebc_person_ex(self, request, runtime):
"""
Description: 创建个人
Summary: 创建个人
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcPersonResponse().from_map(self.do_request("1.0", "baas.ebc.person.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_organization_user(self, request):
"""
Description: 企业用户注册
Summary: 企业用户注册
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_organization_user_ex(request, runtime)
def create_baas_ebc_organization_user_ex(self, request, runtime):
"""
Description: 企业用户注册
Summary: 企业用户注册
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcOrganizationUserResponse().from_map(self.do_request("1.0", "baas.ebc.organization.user.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def cancel_baas_ebc_person(self, request):
"""
Description: 个人退出
Summary: 个人退出
"""
runtime = util_models.RuntimeOptions(
)
return self.cancel_baas_ebc_person_ex(request, runtime)
def cancel_baas_ebc_person_ex(self, request, runtime):
"""
Description: 个人退出
Summary: 个人退出
"""
UtilClient.validate_model(request)
return ebc_models.CancelBaasEbcPersonResponse().from_map(self.do_request("1.0", "baas.ebc.person.cancel", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def resume_baas_ebc_person(self, request):
"""
Description: 用户复入
Summary: 用户复入
"""
runtime = util_models.RuntimeOptions(
)
return self.resume_baas_ebc_person_ex(request, runtime)
def resume_baas_ebc_person_ex(self, request, runtime):
"""
Description: 用户复入
Summary: 用户复入
"""
UtilClient.validate_model(request)
return ebc_models.ResumeBaasEbcPersonResponse().from_map(self.do_request("1.0", "baas.ebc.person.resume", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_organization_class(self, request):
"""
Description: 创建班级
Summary: 创建班级
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_organization_class_ex(request, runtime)
def create_baas_ebc_organization_class_ex(self, request, runtime):
"""
Description: 创建班级
Summary: 创建班级
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcOrganizationClassResponse().from_map(self.do_request("1.0", "baas.ebc.organization.class.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_organization_class(self, request):
"""
Description: 更新班级
Summary: 更新班级
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_organization_class_ex(request, runtime)
def update_baas_ebc_organization_class_ex(self, request, runtime):
"""
Description: 更新班级
Summary: 更新班级
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcOrganizationClassResponse().from_map(self.do_request("1.0", "baas.ebc.organization.class.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def add_baas_ebc_class_user(self, request):
"""
Description: 增加学员
Summary: 增加学员
"""
runtime = util_models.RuntimeOptions(
)
return self.add_baas_ebc_class_user_ex(request, runtime)
def add_baas_ebc_class_user_ex(self, request, runtime):
"""
Description: 增加学员
Summary: 增加学员
"""
UtilClient.validate_model(request)
return ebc_models.AddBaasEbcClassUserResponse().from_map(self.do_request("1.0", "baas.ebc.class.user.add", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def delete_baas_ebc_class_user(self, request):
"""
Description: 删除学员
Summary: 删除学员
"""
runtime = util_models.RuntimeOptions(
)
return self.delete_baas_ebc_class_user_ex(request, runtime)
def delete_baas_ebc_class_user_ex(self, request, runtime):
"""
Description: 删除学员
Summary: 删除学员
"""
UtilClient.validate_model(request)
return ebc_models.DeleteBaasEbcClassUserResponse().from_map(self.do_request("1.0", "baas.ebc.class.user.delete", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_organization_class(self, request):
"""
Description: 班级查询
Summary: 班级查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_organization_class_ex(request, runtime)
def query_baas_ebc_organization_class_ex(self, request, runtime):
"""
Description: 班级查询
Summary: 班级查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcOrganizationClassResponse().from_map(self.do_request("1.0", "baas.ebc.organization.class.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_class_user(self, request):
"""
Description: 班级明细查询
Summary: 班级明细查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_class_user_ex(request, runtime)
def query_baas_ebc_class_user_ex(self, request, runtime):
"""
Description: 班级明细查询
Summary: 班级明细查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcClassUserResponse().from_map(self.do_request("1.0", "baas.ebc.class.user.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_organization_course(self, request):
"""
Description: 发布课程
Summary: 发布课程
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_organization_course_ex(request, runtime)
def create_baas_ebc_organization_course_ex(self, request, runtime):
"""
Description: 发布课程
Summary: 发布课程
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcOrganizationCourseResponse().from_map(self.do_request("1.0", "baas.ebc.organization.course.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_organization_course(self, request):
"""
Description: 更新课程
Summary: 更新课程
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_organization_course_ex(request, runtime)
def update_baas_ebc_organization_course_ex(self, request, runtime):
"""
Description: 更新课程
Summary: 更新课程
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcOrganizationCourseResponse().from_map(self.do_request("1.0", "baas.ebc.organization.course.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def add_baas_ebc_course_class(self, request):
"""
Description: 将班级添加到课程中
Summary: 增加课程班级
"""
runtime = util_models.RuntimeOptions(
)
return self.add_baas_ebc_course_class_ex(request, runtime)
def add_baas_ebc_course_class_ex(self, request, runtime):
"""
Description: 将班级添加到课程中
Summary: 增加课程班级
"""
UtilClient.validate_model(request)
return ebc_models.AddBaasEbcCourseClassResponse().from_map(self.do_request("1.0", "baas.ebc.course.class.add", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def add_baas_ebc_course_user(self, request):
"""
Description: 将学员添加到课程中
Summary: 增加课程学员
"""
runtime = util_models.RuntimeOptions(
)
return self.add_baas_ebc_course_user_ex(request, runtime)
def add_baas_ebc_course_user_ex(self, request, runtime):
"""
Description: 将学员添加到课程中
Summary: 增加课程学员
"""
UtilClient.validate_model(request)
return ebc_models.AddBaasEbcCourseUserResponse().from_map(self.do_request("1.0", "baas.ebc.course.user.add", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def delete_baas_ebc_course_class(self, request):
"""
Description: 删除课程中的班级
Summary: 删除课程班级
"""
runtime = util_models.RuntimeOptions(
)
return self.delete_baas_ebc_course_class_ex(request, runtime)
def delete_baas_ebc_course_class_ex(self, request, runtime):
"""
Description: 删除课程中的班级
Summary: 删除课程班级
"""
UtilClient.validate_model(request)
return ebc_models.DeleteBaasEbcCourseClassResponse().from_map(self.do_request("1.0", "baas.ebc.course.class.delete", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def delete_baas_ebc_course_user(self, request):
"""
Description: 删除课程中的学员
Summary: 删除课程学员
"""
runtime = util_models.RuntimeOptions(
)
return self.delete_baas_ebc_course_user_ex(request, runtime)
def delete_baas_ebc_course_user_ex(self, request, runtime):
"""
Description: 删除课程中的学员
Summary: 删除课程学员
"""
UtilClient.validate_model(request)
return ebc_models.DeleteBaasEbcCourseUserResponse().from_map(self.do_request("1.0", "baas.ebc.course.user.delete", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_user_cert(self, request):
"""
Description: 发布证书
Summary: 发布证书
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_user_cert_ex(request, runtime)
def create_baas_ebc_user_cert_ex(self, request, runtime):
"""
Description: 发布证书
Summary: 发布证书
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcUserCertResponse().from_map(self.do_request("1.0", "baas.ebc.user.cert.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_user_cert(self, request):
"""
Description: 更新证书
Summary: 更新证书
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_user_cert_ex(request, runtime)
def update_baas_ebc_user_cert_ex(self, request, runtime):
"""
Description: 更新证书
Summary: 更新证书
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcUserCertResponse().from_map(self.do_request("1.0", "baas.ebc.user.cert.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_organization_cert(self, request):
"""
Description: 查询证书
Summary: 查询企业证书
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_organization_cert_ex(request, runtime)
def query_baas_ebc_organization_cert_ex(self, request, runtime):
"""
Description: 查询证书
Summary: 查询企业证书
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcOrganizationCertResponse().from_map(self.do_request("1.0", "baas.ebc.organization.cert.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_user_cert(self, request):
"""
Description: 查询用户证书
Summary: 查询用户证书
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_user_cert_ex(request, runtime)
def query_baas_ebc_user_cert_ex(self, request, runtime):
"""
Description: 查询用户证书
Summary: 查询用户证书
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcUserCertResponse().from_map(self.do_request("1.0", "baas.ebc.user.cert.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_cert(self, request):
"""
Description: 证书明细查询
Summary: 证书明细查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_cert_ex(request, runtime)
def query_baas_ebc_cert_ex(self, request, runtime):
"""
Description: 证书明细查询
Summary: 证书明细查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcCertResponse().from_map(self.do_request("1.0", "baas.ebc.cert.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def apply_baas_ebc_cert_url(self, request):
"""
Description: 申请证书信息上传url，证书未发布则会返回证书图片、证书持有人、证书其他信息的文件上传url。
证书已发布则会返回证书图片、证书其他信息的文件上传url。
文件最大5M
Summary: 申请证书信息上传url
"""
runtime = util_models.RuntimeOptions(
)
return self.apply_baas_ebc_cert_url_ex(request, runtime)
def apply_baas_ebc_cert_url_ex(self, request, runtime):
"""
Description: 申请证书信息上传url，证书未发布则会返回证书图片、证书持有人、证书其他信息的文件上传url。
证书已发布则会返回证书图片、证书其他信息的文件上传url。
文件最大5M
Summary: 申请证书信息上传url
"""
UtilClient.validate_model(request)
return ebc_models.ApplyBaasEbcCertUrlResponse().from_map(self.do_request("1.0", "baas.ebc.cert.url.apply", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_auth(self, request):
"""
Description: 新增授权关系，仅限联盟管理员调用
Summary: 新增授权关系
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_auth_ex(request, runtime)
def create_baas_ebc_auth_ex(self, request, runtime):
"""
Description: 新增授权关系，仅限联盟管理员调用
Summary: 新增授权关系
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcAuthResponse().from_map(self.do_request("1.0", "baas.ebc.auth.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_auth(self, request):
"""
Description: 更新授权关系，仅限联盟管理员调用
Summary: 更新授权关系
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_auth_ex(request, runtime)
def update_baas_ebc_auth_ex(self, request, runtime):
"""
Description: 更新授权关系，仅限联盟管理员调用
Summary: 更新授权关系
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcAuthResponse().from_map(self.do_request("1.0", "baas.ebc.auth.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_auth_status(self, request):
"""
Description: 更新授权关系状态，仅限联盟管理员调用
Summary: 更新授权关系状态
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_auth_status_ex(request, runtime)
def update_baas_ebc_auth_status_ex(self, request, runtime):
"""
Description: 更新授权关系状态，仅限联盟管理员调用
Summary: 更新授权关系状态
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcAuthStatusResponse().from_map(self.do_request("1.0", "baas.ebc.auth.status.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_data_price(self, request):
"""
Description: 更新数据价值
Summary: 更新数据价值
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_data_price_ex(request, runtime)
def update_baas_ebc_data_price_ex(self, request, runtime):
"""
Description: 更新数据价值
Summary: 更新数据价值
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcDataPriceResponse().from_map(self.do_request("1.0", "baas.ebc.data.price.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_consumption_amount(self, request):
"""
Description: 查询消费者消费金额
Summary: 查询消费者消费金额
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_consumption_amount_ex(request, runtime)
def query_baas_ebc_consumption_amount_ex(self, request, runtime):
"""
Description: 查询消费者消费金额
Summary: 查询消费者消费金额
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcConsumptionAmountResponse().from_map(self.do_request("1.0", "baas.ebc.consumption.amount.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_organization_course(self, request):
"""
Description: 课程明细查询
Summary: 课程明细查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_organization_course_ex(request, runtime)
def query_baas_ebc_organization_course_ex(self, request, runtime):
"""
Description: 课程明细查询
Summary: 课程明细查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcOrganizationCourseResponse().from_map(self.do_request("1.0", "baas.ebc.organization.course.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_course_chapter(self, request):
"""
Description: 课程章节发布
Summary: 课程章节发布
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_course_chapter_ex(request, runtime)
def create_baas_ebc_course_chapter_ex(self, request, runtime):
"""
Description: 课程章节发布
Summary: 课程章节发布
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcCourseChapterResponse().from_map(self.do_request("1.0", "baas.ebc.course.chapter.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def update_baas_ebc_course_chapter(self, request):
"""
Description: 课程章节更新
Summary: 课程章节更新
"""
runtime = util_models.RuntimeOptions(
)
return self.update_baas_ebc_course_chapter_ex(request, runtime)
def update_baas_ebc_course_chapter_ex(self, request, runtime):
"""
Description: 课程章节更新
Summary: 课程章节更新
"""
UtilClient.validate_model(request)
return ebc_models.UpdateBaasEbcCourseChapterResponse().from_map(self.do_request("1.0", "baas.ebc.course.chapter.update", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def create_baas_ebc_course_record(self, request):
"""
Description: 创建学习记录
Summary: 创建学习记录
"""
runtime = util_models.RuntimeOptions(
)
return self.create_baas_ebc_course_record_ex(request, runtime)
def create_baas_ebc_course_record_ex(self, request, runtime):
"""
Description: 创建学习记录
Summary: 创建学习记录
"""
UtilClient.validate_model(request)
return ebc_models.CreateBaasEbcCourseRecordResponse().from_map(self.do_request("1.0", "baas.ebc.course.record.create", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_course_chapter(self, request):
"""
Description: 课程章节查询
Summary: 课程章节查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_course_chapter_ex(request, runtime)
def query_baas_ebc_course_chapter_ex(self, request, runtime):
"""
Description: 课程章节查询
Summary: 课程章节查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcCourseChapterResponse().from_map(self.do_request("1.0", "baas.ebc.course.chapter.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_course_record(self, request):
"""
Description: 学习记录查询
Summary: 学习记录查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_course_record_ex(request, runtime)
def query_baas_ebc_course_record_ex(self, request, runtime):
"""
Description: 学习记录查询
Summary: 学习记录查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcCourseRecordResponse().from_map(self.do_request("1.0", "baas.ebc.course.record.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
def query_baas_ebc_organization_user(self, request):
"""
Description: 企业用户查询
Summary: 企业用户查询
"""
runtime = util_models.RuntimeOptions(
)
return self.query_baas_ebc_organization_user_ex(request, runtime)
def query_baas_ebc_organization_user_ex(self, request, runtime):
"""
Description: 企业用户查询
Summary: 企业用户查询
"""
UtilClient.validate_model(request)
return ebc_models.QueryBaasEbcOrganizationUserResponse().from_map(self.do_request("1.0", "baas.ebc.organization.user.query", "HTTPS", "POST", "/gateway.do", request.to_map(), runtime))
| 29,343 | 10,375 |
import maya.api.OpenMaya as om2
import maya.cmds as cmds
def get_uuid(mobject):
"""Return a `maya.api.OpenMaya.MObject` UUID.
Args:
mobject (maya.api.OpenMaya.MObject): MObject to get the UUID of.
Returns:
str: The MObject UUID.
"""
return om2.MFnDependencyNode(mobject).uuid().asString()
def set_uuid(mobject, uuid):
"""Set a `maya.api.OpenMaya.MObject` UUID.
Args:
mobject (maya.api.OpenMaya.MObject): MObject to set the UUID of.
uuid (str): UUID to set on the MObject
Raises:
ValueError: If the UUID is not formatted as a valid Maya UUID.
# TODO: Use a different error type.
ValueError: If the UUID is already taken.
"""
pattern = re.compile(
r"[A-Z0-9]{8}-[A-Z0-9]{4}-[A-Z0-9]{4}-[A-Z0-9]{4}-[A-Z0-9]{12}"
)
if not pattern.match(uuid):
raise ValueError("'{}' is not a valid UUID".format(uuid))
existing_node = cmds.ls(uuid)
if existing_node:
raise ValueError(
"The uuid '{}' is already assigned to the node {}".format(
uuid, existing_node[0]
)
)
uuid = om2.MUuid(uuid)
om2.MFnDependencyNode(mobject).setUuid(uuid)
def get_mobject(node):
"""Return a `maya.api.OpenMaya.MObject` from a node name.
Args:
node (str): Name of the node.
It should be unique as it is forwarded to
`maya.api.OpenMaya.MSelectionList.add`.
Returns:
maya.api.OpenMaya.MObject: The underlying MObject.
"""
sel_list = om2.MSelectionList()
sel_list.add(node)
mobject = sel_list.getDependNode(0)
return mobject
def get_mplug(attribute):
"""Return a `maya.api.OpenMaya.MPlug` from a node attribute.
Args:
node (str): Name of the attribute.
It is formatted as `{node_name}.{attribute_name}`.
It should be unique as it is forwarded to
`maya.api.OpenMaya.MSelectionList.add`.
Returns:
maya.api.OpenMaya.MPlug: The underlying MPlug.
"""
sel_list = om2.MSelectionList()
sel_list.add(attribute)
mobject = sel_list.getPlug(0)
return mobject
def all_subclasses(cls):
"""Recursively find subclasses of a class.
The subclasses should already be imported for this function to work properly.
Args:
cls (type): Class to inspect.
Returns:
set[type]: The set of subclasses.
"""
return set(cls.__subclasses__()).union(
[s for c in cls.__subclasses__() for s in all_subclasses(c)]
)
| 2,560 | 898 |
import os
import random
from discord.ext import commands
from dotenv import load_dotenv
load_dotenv()
TOKEN = os.getenv('DISCORD_TOKEN')
bot = commands.Bot(command_prefix='m!')
@bot.command(name='compliment', help='Makes you feel better')
async def nine_nine(ctx):
compliments = [
'Everyone has imperfections, you\'re great!',
'Don\'t be pessimistic, go enjoy life!',
(
'Think of the worst person you\'ve ever met and be happy you\'re not like him.'
'Think of @! Allen#0001 giving you mod perms'
),
]
response = random.choice(compliments)
await ctx.send(response)
@bot.event
async def on_message_delete(message):
await message.channel.send('Some mf deleted a message, who spotted him')
bot.run(TOKEN) | 812 | 282 |
'''
Modulo que implementa as funcoes de plot da curva roc
'''
import matplotlib.pyplot as plt
import numpy as np
import os
from sklearn.metrics import plot_roc_curve
plt.style.use('ggplot')
def plot_results(_id, best_clf, x_test, y_test, method, variant, P, R, output):
if not os.path.exists(output + '/ARR_ROC/'+variant+'/y_pred'):
os.makedirs(output + '/ARR_ROC/'+variant+'/y_pred')
if not os.path.exists(output + '/ARR_ROC/'+variant+'/y_pred_roc'):
os.makedirs(output + '/ARR_ROC/'+variant+'/y_pred_roc')
from sklearn.metrics._plot.base import _get_response
y_pred_roc, _ = _get_response(x_test, best_clf, 'auto', pos_label=None)
arr_roc = output + '/ARR_ROC/{}/y_pred_roc/{}_{}_{}_{}.txt'.format(variant, method, _id.replace(' ', ''), str(P), str(R))
np.savetxt(arr_roc, y_pred_roc)
y_predict = best_clf.predict(x_test)
arr_roc = output + '/ARR_ROC/{}/y_pred/{}_{}_{}_{}.txt'.format(variant, method, _id.replace(' ', ''), str(P), str(R))
np.savetxt(arr_roc, y_predict)
plot_roc_curve(best_clf, x_test, y_test)
#PLOTANDO LINHA DIAGONAL --> y = x
plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='g', alpha=.8)
# PLOTANDO INFORMACOES BASICA DO GRAFICO
plt.title('{} - {}/{} - P: {}, R:{}'.format(_id, method, variant, P, R))
plt.legend(loc="lower right")
if not os.path.exists(output + '/ROC_'+variant):
os.makedirs(output + '/ROC_'+variant)
plt.savefig(output + '/ROC_{}/{}_{}_{}_{}_{}.png'.format(variant, variant, method, _id.replace(' ', ''), P, R))
plt.close() | 1,602 | 645 |
from fcapsy import Lattice, Context, Concept
from fcapsy.similarity import jaccard
from fcapsy.algorithms.rice_siff import concept_subset
object_labels = tuple(range(5))
attribute_labels = tuple(range(4))
bools = [
[1, 0, 0, 0],
[1, 1, 1, 0],
[0, 1, 0, 1],
[1, 1, 0, 0],
[0, 0, 1, 0],
]
context = Context(bools, object_labels, attribute_labels)
def test_rice_siff_algorithm():
lattice = Lattice(context)
concepts = concept_subset(context, jaccard)
for concept in concepts:
assert concept in lattice.concepts
| 552 | 216 |
"""Implements direct fidelity estimation.
Fidelity between the desired pure state rho and the actual state sigma is
defined as:
F(rho, sigma) = Tr (rho sigma)
It is a unit-less measurement between 0.0 and 1.0. The following two papers
independently described a faster way to estimate its value:
Direct Fidelity Estimation from Few Pauli Measurements
https://arxiv.org/abs/1104.4695
Practical characterization of quantum devices without tomography
https://arxiv.org/abs/1104.3835
This code implements the algorithm proposed for an example circuit (defined in
the function build_circuit()) and a noise (defines in the variable noise).
"""
import argparse
import asyncio
from dataclasses import dataclass
import itertools
from typing import cast
from typing import List
from typing import Optional
from typing import Tuple
import sys
import numpy as np
import cirq
def build_circuit() -> Tuple[cirq.Circuit, List[cirq.Qid]]:
# Builds an arbitrary circuit to test. Do not include a measurement gate.
# The circuit need not be Clifford, but if it is, simulations will be
# faster.
qubits: List[cirq.Qid] = cast(List[cirq.Qid], cirq.LineQubit.range(3))
circuit: cirq.Circuit = cirq.Circuit(cirq.CNOT(qubits[0], qubits[2]),
cirq.Z(qubits[0]), cirq.H(qubits[2]),
cirq.CNOT(qubits[2], qubits[1]),
cirq.X(qubits[0]), cirq.X(qubits[1]),
cirq.CNOT(qubits[0], qubits[2]))
print('Circuit used:')
print(circuit)
return circuit, qubits
def compute_characteristic_function(circuit: cirq.Circuit,
pauli_string: cirq.PauliString,
qubits: List[cirq.Qid],
density_matrix: np.ndarray):
n_qubits = len(qubits)
d = 2**n_qubits
qubit_map = dict(zip(qubits, range(n_qubits)))
# rho_i or sigma_i in https://arxiv.org/abs/1104.3835
trace = pauli_string.expectation_from_density_matrix(
density_matrix, qubit_map)
assert np.isclose(trace.imag, 0.0, atol=1e-6)
trace = trace.real
prob = trace * trace / d # Pr(i) in https://arxiv.org/abs/1104.3835
return trace, prob
async def estimate_characteristic_function(circuit: cirq.Circuit,
pauli_string: cirq.PauliString,
qubits: List[cirq.Qid],
sampler: cirq.Sampler,
samples_per_term: int):
"""
Estimates the characteristic function using a (noisy) circuit simulator by
sampling the results.
Args:
circuit: The circuit to run the simulation on.
pauli_string: The Pauli string.
qubits: The list of qubits.
sampler: Either a noisy simulator or an engine.
samples_per_term: An integer greater than 0, the number of samples.
Returns:
The estimated characteristic function.
"""
p = cirq.PauliSumCollector(circuit=circuit,
observable=pauli_string,
samples_per_term=samples_per_term)
await p.collect_async(sampler=sampler)
sigma_i = p.estimated_energy()
assert np.isclose(sigma_i.imag, 0.0, atol=1e-6)
sigma_i = sigma_i.real
return sigma_i
def _randomly_sample_from_stabilizer_bases(
stabilizer_basis: List[cirq.DensePauliString], n_clifford_trials: int,
n_qubits: int):
"""
Given a stabilizer basis, randomly creates Pauli states by including the
basis vector or not.
Args:
stabilizer_basis: A list of Pauli strings that is the stabilizer basis
to sample from.
n_clifford_trials: An integer that is the number of samples to return.
n_qubits: An integer that is the number of qubits.
Returns:
A list of Pauli strings that is the Pauli states built.
"""
dense_pauli_strings = []
for _ in range(n_clifford_trials):
# Build the Pauli string as a random sample of the basis elements.
dense_pauli_string = cirq.DensePauliString.eye(n_qubits)
for stabilizer in stabilizer_basis:
if np.random.randint(2) == 1:
dense_pauli_string *= stabilizer
dense_pauli_strings.append(dense_pauli_string)
return dense_pauli_strings
def _enumerate_all_from_stabilizer_bases(
stabilizer_basis: List[cirq.DensePauliString], n_qubits: int):
"""
Given a stabilizer basis, creates the exhaustive list of Pauli states that
are spanned by the basis.
Args:
stabilizer_basis: A list of Pauli strings that is the stabilizer basis
to build all the Pauli strings.
n_qubits: An integer that is the number of qubits.
Returns:
A list of Pauli strings that is the Pauli states built.
"""
dense_pauli_strings = []
for coefficients in itertools.product([False, True], repeat=n_qubits):
dense_pauli_string = cirq.DensePauliString.eye(n_qubits)
for (keep, stabilizer) in zip(coefficients, stabilizer_basis):
if keep:
dense_pauli_string *= stabilizer
dense_pauli_strings.append(dense_pauli_string)
return dense_pauli_strings
@dataclass
class PauliTrace:
"""
A class that contains the Pauli states as described on page 2 of:
https://arxiv.org/abs/1104.3835
"""
# Pauli string.
P_i: cirq.PauliString
# Coefficient of the ideal pure state expanded in the Pauli basis scaled by
# sqrt(dim H), formally defined at bottom of left column of page 2.
rho_i: float
# A probablity (between 0.0 and 1.0) that is the relevance distribution,
# formally defined at top of right column of page 2.
Pr_i: float
def _estimate_pauli_traces_clifford(n_qubits: int,
clifford_state: cirq.CliffordState,
n_clifford_trials: Optional[int]):
"""
Estimates the Pauli traces in case the circuit is Clifford. When we have a
Clifford circuit, there are 2**n Pauli traces that have probability 1/2**n
and all the other traces have probability 0. In addition, there is a fast
way to compute find out what the traces are. See the documentation of
cirq.CliffordState for more detail. This function uses the speedup to sample
the Pauli states with non-zero probability.
Args:
n_qubits: An integer that is the number of qubits.
clifford_state: The basis of the Pauli states with non-zero probability.
n_clifford_trials: An integer that is the number of Pauli states to
sample. If set to None, we do an exhaustive search.
Returns:
A list of Pauli states (represented as tuples of Pauli string, rho_i,
and probability.
"""
# When the circuit consists of Clifford gates only, we can sample the
# Pauli states more efficiently as described on page 4 of:
# https://arxiv.org/abs/1104.4695
d = 2**n_qubits
# The stabilizers_basis variable only contains basis vectors. For
# example, if we have n=3 qubits, then we should have 2**n=8 Pauli
# states that we can sample, but the basis will still have 3 entries. We
# must flip a coin for each, whether or not to include them.
stabilizer_basis: List[cirq.DensePauliString] = clifford_state.stabilizers()
if n_clifford_trials is not None:
dense_pauli_strings = _randomly_sample_from_stabilizer_bases(
stabilizer_basis, n_clifford_trials, n_qubits)
else:
dense_pauli_strings = _enumerate_all_from_stabilizer_bases(
stabilizer_basis, n_qubits)
pauli_traces: List[PauliTrace] = []
for dense_pauli_string in dense_pauli_strings:
# The code below is equivalent to calling
# clifford_state.wave_function() and then calling
# compute_characteristic_function() on the results (albeit with a
# wave function instead of a density matrix). It is, however,
# unncessary to do so. Instead we directly obtain the scalar rho_i.
rho_i = dense_pauli_string.coefficient
assert np.isclose(rho_i.imag, 0.0, atol=1e-6)
rho_i = rho_i.real
dense_pauli_string *= rho_i
assert np.isclose(abs(rho_i), 1.0, atol=1e-6)
Pr_i = 1.0 / d
pauli_traces.append(
PauliTrace(P_i=dense_pauli_string.sparse(), rho_i=rho_i, Pr_i=Pr_i))
return pauli_traces
def _estimate_pauli_traces_general(qubits: List[cirq.Qid],
circuit: cirq.Circuit):
"""
Estimates the Pauli traces in case the circuit is not Clifford. In this case
we cannot use the speedup implemented in the function
_estimate_pauli_traces_clifford() above, and so do a slow, density matrix
simulation.
Args:
qubits: The list of qubits.
circuit: The (non Clifford) circuit.
Returns:
A list of Pauli states (represented as tuples of Pauli string, rho_i,
and probability.
"""
n_qubits = len(qubits)
dense_simulator = cirq.DensityMatrixSimulator()
# rho in https://arxiv.org/abs/1104.3835
clean_density_matrix = cast(
cirq.DensityMatrixTrialResult,
dense_simulator.simulate(circuit)).final_density_matrix
pauli_traces: List[PauliTrace] = []
for P_i in itertools.product([cirq.I, cirq.X, cirq.Y, cirq.Z],
repeat=n_qubits):
pauli_string = cirq.PauliString(dict(zip(qubits, P_i)))
rho_i, Pr_i = compute_characteristic_function(circuit, pauli_string,
qubits,
clean_density_matrix)
pauli_traces.append(PauliTrace(P_i=pauli_string, rho_i=rho_i,
Pr_i=Pr_i))
return pauli_traces
@dataclass
class TrialResult:
"""
Contains the results of a trial, either by simulator or actual run
"""
# The index in the list of Pauli traces.
i: int
# Coefficient of the measured/simulated pure state expanded in the Pauli
# basis scaled by sqrt(dim H), formally defined at bottom of left column of
# second page of https://arxiv.org/abs/1104.3835
sigma_i: float
@dataclass
class DFEIntermediateResult:
"""
A container for the various debug and run data from calling the function
direct_fidelity_estimation(). This is useful when running a long-computation
on an actual computer, which is expensive. This way, runs can be more easily
debugged offline.
"""
# If the circuit is Clifford, the Clifford state from which we can extract
# a list of Pauli strings for a basis of the stabilizers.
clifford_state: Optional[cirq.CliffordState]
# The list of Pauli traces we can sample from.
pauli_traces: List[PauliTrace]
# Measurement results from sampling the circuit.
trial_results: List[TrialResult]
def direct_fidelity_estimation(circuit: cirq.Circuit, qubits: List[cirq.Qid],
sampler: cirq.Sampler, n_trials: int,
n_clifford_trials: Optional[int],
samples_per_term: int):
"""
Implementation of direct fidelity estimation, as per 'Direct Fidelity
Estimation from Few Pauli Measurements' https://arxiv.org/abs/1104.4695 and
'Practical characterization of quantum devices without tomography'
https://arxiv.org/abs/1104.3835.
Args:
circuit: The circuit to run the simulation on.
qubits: The list of qubits.
sampler: Either a noisy simulator or an engine.
n_trial: The total number of Pauli measurements.
n_clifford_trials: In case the circuit is Clifford, we specify the
number of trials to estimate the noise-free pauli traces.
samples_per_term: if set to 0, we use the 'sampler' parameter above as
a noise (must be of type cirq.DensityMatrixSimulator) and
simulate noise in the circuit. If greater than 0, we instead use the
'sampler' parameter directly to estimate the characteristic
function.
Returns:
The estimated fidelity and a log of the run.
"""
# n_trials is upper-case N in https://arxiv.org/abs/1104.3835
# Number of qubits, lower-case n in https://arxiv.org/abs/1104.3835
n_qubits = len(qubits)
d = 2**n_qubits
clifford_circuit = True
clifford_state: Optional[cirq.CliffordState] = None
try:
clifford_state = cirq.CliffordState(
qubit_map={qubits[i]: i for i in range(len(qubits))})
for gate in circuit.all_operations():
clifford_state.apply_unitary(gate)
except ValueError:
clifford_circuit = False
# Computes for every \hat{P_i} of https://arxiv.org/abs/1104.3835
# estimate rho_i and Pr(i). We then collect tuples (rho_i, Pr(i), \hat{Pi})
# inside the variable 'pauli_traces'.
if clifford_circuit:
assert clifford_state is not None
pauli_traces = _estimate_pauli_traces_clifford(
n_qubits, cast(cirq.CliffordState, clifford_state),
n_clifford_trials)
else:
pauli_traces = _estimate_pauli_traces_general(qubits, circuit)
p = np.asarray([x.Pr_i for x in pauli_traces])
if not clifford_circuit:
# For Clifford circuits, we do a Monte Carlo simulations, and thus there
# is no guarantee that it adds up to 1.0 (but it should to the limit).
assert np.isclose(np.sum(p), 1.0, atol=1e-6)
# The package np.random.choice() is quite sensitive to probabilities not
# summing up to 1.0. Even an absolute difference below 1e-6 (as checked just
# above) does bother it, so we re-normalize the probs.
p /= np.sum(p)
fidelity = 0.0
if samples_per_term == 0:
# sigma in https://arxiv.org/abs/1104.3835
if not isinstance(sampler, cirq.DensityMatrixSimulator):
raise TypeError('sampler is not a cirq.DensityMatrixSimulator '
'but samples_per_term is zero.')
noisy_simulator = cast(cirq.DensityMatrixSimulator, sampler)
noisy_density_matrix = cast(
cirq.DensityMatrixTrialResult,
noisy_simulator.simulate(circuit)).final_density_matrix
trial_results: List[TrialResult] = []
for _ in range(n_trials):
# Randomly sample as per probability.
i = np.random.choice(len(pauli_traces), p=p)
Pr_i = pauli_traces[i].Pr_i
measure_pauli_string: cirq.PauliString = pauli_traces[i].P_i
rho_i = pauli_traces[i].rho_i
if samples_per_term > 0:
sigma_i = asyncio.get_event_loop().run_until_complete(
estimate_characteristic_function(circuit, measure_pauli_string,
qubits, sampler,
samples_per_term))
else:
sigma_i, _ = compute_characteristic_function(
circuit, measure_pauli_string, qubits, noisy_density_matrix)
trial_results.append(TrialResult(i=i, sigma_i=sigma_i))
fidelity += Pr_i * sigma_i / rho_i
estimated_fidelity = fidelity / n_trials * d
dfe_intermediate_result = DFEIntermediateResult(
clifford_state=clifford_state,
pauli_traces=pauli_traces,
trial_results=trial_results)
return estimated_fidelity, dfe_intermediate_result
def parse_arguments(args):
"""Helper function that parses the given arguments."""
parser = argparse.ArgumentParser('Direct fidelity estimation.')
parser.add_argument('--n_trials',
default=10,
type=int,
help='Number of trials to run.')
# TODO(#2802): Offer some guidance on how to set this flag. Maybe have an
# option to do an exhaustive sample and do numerical studies to know which
# choice is the best.
parser.add_argument('--n_clifford_trials',
default=3,
type=int,
help='Number of trials for Clifford circuits. This is '
'in effect when the circuit is Clifford. In this '
'case, we randomly sample the Pauli traces with '
'non-zero probabilities. The higher the number, '
'the more accurate the overall fidelity '
'estimation, at the cost of extra computing and '
'measurements. If set to None, we exhaustively '
'enumerate all the Pauli traces.')
parser.add_argument('--samples_per_term',
default=0,
type=int,
help='Number of samples per trial or 0 if no sampling.')
return vars(parser.parse_args(args))
def main(*, n_trials: int, n_clifford_trials: Optional[int],
samples_per_term: int):
circuit, qubits = build_circuit()
noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(0.1))
print('Noise model: %s' % (noise))
noisy_simulator = cirq.DensityMatrixSimulator(noise=noise)
estimated_fidelity, _ = direct_fidelity_estimation(
circuit,
qubits,
noisy_simulator,
n_trials=n_trials,
n_clifford_trials=n_clifford_trials,
samples_per_term=samples_per_term)
print('Estimated fidelity: %f' % (estimated_fidelity))
if __name__ == '__main__':
main(**parse_arguments(sys.argv[1:]))
| 17,766 | 5,543 |
# -*- coding: utf-8 -*-
'''
Created on Mar 21, 2016
@author: fky
'''
import matplotlib.pyplot as plt
decisionNode = dict(boxstyle='sawtooth',fc='0.8')
leafNode = dict(boxstyle='round4',fc='0.8')
arrow_args = dict(arrowstyle='<-')
def plotNode(nodeTxt,centerPt,parentPt,nodeType):
createPlot.ax1.annotate(nodeTxt,xy=parentPt,xycoords='axes fraction',xytext=centerPt,textcoords='axes fraction',
va='center',ha='center',bbox=nodeType,arrowprops=arrow_args)
def createPlot():
fig=plt.figure(1,facecolor='white')
fig.clf()
createPlot.ax1=plt.subplot(111,frameon=False)
plotNode('a decision node', (0.5,0.1), (0.1,0.5), decisionNode)
plotNode('a leaf node', (0.8,0.1), (0.3,0.8), leafNode)
plt.show()
def getNumLeafs(myTree):
numLeafs = 0
firstStr = list(myTree.keys())[0]
secondDict = myTree[firstStr]
for key in secondDict.keys():
if type(secondDict[key]).__name__ == 'dict':
numLeafs += getNumLeafs(secondDict[key])
else:
numLeafs += 1
return numLeafs
def getTreeDepth(myTree):
maxDepth = 0
firstStr = list(myTree.keys())[0]
print(firstStr)
secondDict = myTree[firstStr]
for key in secondDict.keys():
if type(secondDict[key]).__name__=='dict':
thisDepth = 1+ getTreeDepth(secondDict[key])
else:
thisDepth = 1
if thisDepth > maxDepth:
maxDepth= thisDepth
return maxDepth
def retrieveTree(i):
listOfTree = [{'no surfacing':{0:'no',1:{'flippers':{0:'no',1:'yes'}}}},
{'no surfacing':{0:'no',1:{'flippers':{0:{'head':{0:'no',1:'yes'}},1:'no'}}}}
]
return listOfTree[i]
def plotMidText(cntrPt,parentPt,txtString):
xMid = (parentPt[0]-cntrPt[0])/2.0 + cntrPt[0]
yMid = (parentPt[1]-cntrPt[1])/2.0 + cntrPt[1]
createPlot.ax1.text(xMid,yMid,txtString)
def plotTree(myTree,parentPt,nodeTxt):
numLeafs = getNumLeafs(myTree)
depth = getTreeDepth(myTree)
firstStr = list(myTree.keys())[0]
cntrPt = (plotTree.xOff+(1.0+float(numLeafs))/2.0/plotTree.totalW,plotTree.yOff)
plotMidText(cntrPt, parentPt, nodeTxt)
plotNode(firstStr, cntrPt, parentPt, decisionNode)
secondDict = myTree[firstStr]
plotTree.yOff = plotTree.yOff - 1.0/plotTree.totalD
for key in secondDict.keys():
if type(secondDict[key]).__name__ == 'dict':
plotTree(secondDict[key], cntrPt, str(key))
else:
plotTree.xOff = plotTree.xOff + 1.0/plotTree.totalW
plotNode(secondDict[key],(plotTree.xOff,plotTree.yOff),cntrPt,leafNode)
plotMidText((plotTree.xOff,plotTree.yOff), cntrPt, str(key))
plotTree.yOff = plotTree.yOff + 1.0/plotTree.totalD
def createPlot_2(inTree):
fig=plt.figure(1,facecolor='white')
fig.clf()
axprops = dict(xticks=[],yticks=[])
createPlot.ax1=plt.subplot(111,frameon=False)
plotTree.totalW = float(getNumLeafs(inTree))
plotTree.totalD=float(getTreeDepth(inTree))
plotTree.xOff = -0.5/plotTree.totalW;
plotTree.yOff = 1.0
plotTree(inTree,(0.5,1.0),'')
plt.show()
if __name__=='__main__':
mytree = retrieveTree(0)
createPlot_2(mytree) | 3,364 | 1,393 |
a = r'
(?x)
foo
'
# comment
a : source.python
: source.python
= : keyword.operator.assignment.python, source.python
: source.python
r : source.python, storage.type.string.python, string.regexp.quoted.single.python
' : punctuation.definition.string.begin.python, source.python, string.regexp.quoted.single.python
: invalid.illegal.newline.python, source.python, string.regexp.quoted.single.python
: source.python
( : punctuation.parenthesis.begin.python, source.python
? : invalid.illegal.operator.python, source.python
x : source.python
) : punctuation.parenthesis.end.python, source.python
: source.python
foo : source.python
' : punctuation.definition.string.begin.python, source.python, string.quoted.docstring.single.python
: invalid.illegal.newline.python, source.python, string.quoted.docstring.single.python
# : comment.line.number-sign.python, punctuation.definition.comment.python, source.python
comment : comment.line.number-sign.python, source.python
| 1,197 | 326 |
# This program is made by Hasan Senyurt for ISTAC A.S. - Inventory Management Software
from tkinter import *
import pandas as pd
from tkinter import ttk
from tkinter import messagebox
from datetime import datetime
import getpass
############################################################
# Arranging row colors of the tables.
def coloring3():
for i in table3.get_children():
if int(table3.index(i)) % 2 == 0:
table3.item(i,tags=("even"))
else:
table3.item(i,tags=("odd"))
table3.tag_configure("even",background="Azure2")
table3.tag_configure("odd",background="ghost white")
def coloring2():
for i in table2.get_children():
if int(table2.index(i)) % 2 == 0:
table2.item(i,tags=("even"))
else:
table2.item(i,tags=("odd"))
table2.tag_configure("even",background="Azure2")
table2.tag_configure("odd",background="ghost white")
def coloring():
for i in table.get_children():
if int(table.index(i)) % 2 == 0:
table.item(i,tags=("even"))
else:
table.item(i,tags=("odd"))
table.tag_configure("even",background="Azure2")
table.tag_configure("odd",background="ghost white")
############################################################
############################################################
# Keeping log records.
def logs():
global logfile
logfile = open("logs.log","a")
logfile.write(str(datetime.now())[:19]+"\t"+format(getpass.getuser(),"20s"))
def logsclose():
logfile.close()
############################################################
############################################################
# Saving changed data before quiting program.
def beforeExit():
if messagebox.askokcancel("Çıkış", "Çıkış yapmak istiyor musunuz?"):
if filter_cancel['state'] == ACTIVE:
returnTable()
if filter_cancel2['state'] == ACTIVE:
returnTable2()
if filter_cancel3['state'] == ACTIVE:
returnTable3()
export("local")
export2("local")
export3("local")
window.destroy()
############################################################
############################################################
# Saving changes on table to data file after every operation.
def updateTable(tablo,liste):
global p,p2,p3
if p != 1 and liste == "Depo Listesi.xlsx":
for i in tablo.get_children():
tablo.delete(i)
data = pd.read_excel("Tablolar/"+liste)
data = data.fillna('')
for i in range(0,len(data)):
tablo.insert(parent = '', index='end',id=i+1, values=[data.loc[i][j] for j in range(0,len(data.columns))])
coloring()
if p2 != 1 and liste == "Zimmet Listesi.xlsx":
for i in tablo.get_children():
tablo.delete(i)
data = pd.read_excel("Tablolar/"+liste)
data = data.fillna('')
for i in range(0,len(data)):
tablo.insert(parent = '', index='end',id=i+1, values=[data.loc[i][j] for j in range(0,len(data.columns))])
coloring2()
if p3 != 1 and liste == "Hurda Listesi.xlsx":
for i in tablo.get_children():
tablo.delete(i)
data = pd.read_excel("Tablolar/"+liste)
data = data.fillna('')
for i in range(0,len(data)):
tablo.insert(parent = '', index='end',id=i+1, values=[data.loc[i][j] for j in range(0,len(data.columns))])
coloring3()
############################################################
############################################################
# Loading data to both three tables from data files.
def importExcel3():
global items3
items3 = pd.read_excel("Tablolar/Hurda Listesi.xlsx")
global columns3
columns3 = list()
for i in items3.columns:
columns3.append(i)
table3['columns'] = columns3
table3.column("#0", width=0, stretch=NO)
for i in range(0,len(columns3)):
if(i ==4):
table3.column(columns3[i],width=428,minwidth=750) #392
elif i==0:
table3.column(columns3[i],width=100,minwidth=100)
elif i == 1:
table3.column(columns3[i],width=300,minwidth=300)
else:
table3.column(columns3[i],width=100,minwidth=100)
table3.heading("#0", text="")
for i in range(0,len(columns3)):
table3.heading(columns3[i],text=columns3[i],anchor="w")
items3 = items3.fillna('')
items3['Açıklama'] = items3['Açıklama'].astype(str)
for i in range(0,len(items3)):
table3.insert(parent = '', index='end',id=i+1, values=[items3.loc[i][j] for j in range(0,len(items3.columns))])
coloring3()
def importExcel2():
global items2
items2 = pd.read_excel("Tablolar/Zimmet Listesi.xlsx")
global columns2
columns2 = list()
for i in items2.columns:
columns2.append(i)
table2['columns'] = columns2
table2.column("#0", width=0, stretch=NO)
for i in range(0,len(columns2)):
if(i==1):
table2.column(columns2[i],width=260,minwidth=260)
elif i ==7:
table2.column(columns2[i],width=126,minwidth=750)
elif i==0:
table2.column(columns2[i],width=90,minwidth=90)
elif i ==5 or i ==6:
table2.column(columns2[i],width=134,minwidth=134)
elif i ==4:
table2.column(columns2[i],width=134,minwidth=134)
else:
table2.column(columns2[i],width=75,minwidth=75)
table2.heading("#0", text="")
for i in range(0,len(columns2)):
table2.heading(columns2[i],text=columns2[i],anchor="w")
items2 = items2.fillna('')
items2['Tarih'] = items2['Tarih'].astype(str)
items2['Açıklama'] = items2['Açıklama'].astype(str)
for i in range(0,len(items2)):
table2.insert(parent = '', index='end',id=i+1, values=[items2.loc[i][j] for j in range(0,len(items2.columns))])
coloring2()
def importExcel():
global items
items = pd.read_excel("Tablolar/Depo Listesi.xlsx")
global columns
columns = list()
for i in items.columns:
columns.append(i)
table['columns'] = columns
table.column("#0", width=0, stretch=NO)
for i in range(0,len(columns)):
if(i ==4):
table.column(columns[i],width=378,minwidth=750) #392
elif i==0:
table.column(columns[i],width=100,minwidth=100)
elif i == 1:
table.column(columns[i],width=300,minwidth=300)
else:
table.column(columns[i],width=75,minwidth=75)
table.heading("#0", text="")
for i in range(0,len(columns)):
table.heading(columns[i],text=columns[i],anchor="w")
items = items.fillna('')
items['Açıklama'] = items['Açıklama'].astype(str)
for i in range(0,len(items)):
table.insert(parent = '', index='end',id=i+1, values=[items.loc[i][j] for j in range(0,len(items.columns))])
coloring()
############################################################
############################################################
# Solving problem because of upper 'i' character in Turkish alphabet.
def entryUpper(entry):
up = str()
for i in entry:
if i == 'i':
up = up + 'İ'
else:
up = up + i.upper()
return up
############################################################
############################################################
# Clearing all items on junk table.
def removeAll():
for i in table3.get_children():
table3.delete(i)
logs()
logfile.write("HURDA LİSTESİ"+"\t"+"TEMİZLEME"+" "+"HURDA LİSTESİ TEMİZLENDİ."+"\n")
logsclose()
export3("local")
############################################################
############################################################
# Cancelling filter option to return normal sized table.
def returnTable3():
global p3
p3 = 0
for i in table3.get_children():
table3.delete(i)
for i in range(0,len(new_table3)):
table3.insert(parent = '', index=index3[i],id=i+1, values=[new_table3[i][j] for j in range(0,len(new_table3[0]))])
filter_button3['state'] = ACTIVE
filter_cancel3['state'] = DISABLED
excel_button3['state'] = ACTIVE
export3("local")
updateTable(table3,"Hurda Listesi.xlsx")
def returnTable2():
global p2
p2=0
extratable = []
for i in table2.get_children():
extratable.append(table2.item(i).get("values"))
for i in table2.get_children():
table2.delete(i)
newlist = filtertable + extratable
for i in range(0,len(newlist)):
table2.insert(parent = '', index='end',id=i+1, values=[newlist[i][j] for j in range(0,len(newlist[0]))])
sorting(table2)
filter_button2['state'] = ACTIVE
filter_cancel2['state'] = DISABLED
excel_button2['state'] = ACTIVE
export2("local")
updateTable(table2,"Zimmet Listesi.xlsx")
def returnTable():
global p
p = 0
extratable = []
for i in table.get_children():
extratable.append(table.item(i).get("values"))
for i in table.get_children():
table.delete(i)
newlist = new_table + extratable
for i in range(0,len(newlist)):
table.insert(parent = '', index='end',id=i+1, values=[newlist[i][j] for j in range(0,len(newlist[0]))])
sorting(table)
filter_button['state'] = ACTIVE
filter_cancel['state'] = DISABLED
excel_button['state'] = ACTIVE
export("local")
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# Filtering products by their name or person.
def filter3():
global p3
p3 = 0
flag = False
if category_entry3.get().isspace() or category_entry3.get() == '':
messagebox.showwarning("UYARI","Lütfen Ürün İsmi Girin!")
flag = True
global new_table3,index3
new_table3 = []
index3 = []
if flag == False:
p3 = 1
for i in table3.get_children():
index3.append(table3.index(i))
for i in table3.get_children():
if str(entryUpper(category_entry3.get())) not in str(entryUpper(table3.item(i).get("values")[1])):
new_table3.append(table3.item(i).get("values"))
table3.delete(i)
else:
new_table3.append(table3.item(i).get("values"))
filter_button3['state'] = DISABLED
filter_cancel3['state'] = ACTIVE
excel_button3['state'] = DISABLED
def filter2():
global filtertable
global p2
p2 = 0
if control_menu.get() == "Seç:":
messagebox.showwarning("UYARI","Lütfen Kategori Seçiniz!")
elif control_menu.get() == "Ürün: ":
ctrl = False
filtertable = []
if category_entry2.get().isspace() or category_entry2.get() == '':
messagebox.showwarning("UYARI","Lütfen Ürün İsmi Girin!")
ctrl = True
if ctrl == False:
p2 = 1
for i in table2.get_children():
if str(entryUpper(category_entry2.get())) not in str(entryUpper(table2.item(i).get("values")[1])):
filtertable.append(table2.item(i).get("values"))
table2.delete(i)
filter_button2['state'] = DISABLED
filter_cancel2['state'] = ACTIVE
excel_button2['state'] = DISABLED
elif control_menu.get() == "Kişi: ":
ctrl = False
filtertable = []
if category_entry2.get().isspace() or category_entry2.get() == '':
messagebox.showwarning("UYARI","Lütfen Kişi İsmi Girin!")
ctrl = True
if ctrl == False:
p2= 1
for i in table2.get_children():
if str(entryUpper(category_entry2.get())) not in str(entryUpper(table2.item(i).get("values")[4])) and str(entryUpper(category_entry2.get())) not in str(entryUpper(table2.item(i).get("values")[5])):
filtertable.append(table2.item(i).get("values"))
table2.delete(i)
filter_button2['state'] = DISABLED
filter_cancel2['state'] = ACTIVE
excel_button2['state'] = DISABLED
def filter():
global p
p = 0
flag = False
if category_entry.get().isspace() or category_entry.get() == '':
messagebox.showwarning("UYARI","Lütfen Ürün İsmi Girin!")
flag = True
global new_table
new_table = []
if flag == False:
p = 1
for i in table.get_children():
if str(entryUpper(category_entry.get())) not in str(entryUpper(table.item(i).get("values")[1])):
new_table.append(table.item(i).get("values"))
table.delete(i)
filter_button['state'] = DISABLED
filter_cancel['state'] = ACTIVE
excel_button['state'] = DISABLED
#print(entryUpper(category_entry))
############################################################
############################################################
# Prevents entring nonnumeric values to amount of product entries.
def testVal(inStr,acttyp):
if acttyp == '1': #insert
if not inStr.isdigit():
return False
return True
############################################################
############################################################
# Adding product back to inventory from registered list by clicking with mouse.
def addBack2():
flag = False
flag2 = False
try:
iselected = table2.focus()
for o in table.get_children():
if(str(table.item(o).get("values")[0]) == str(table2.item(iselected).get("values")[0])
and str(table.item(o).get("values")[1]) == str(table2.item(iselected).get("values")[1])
and str(table.item(o).get("values")[3]) == str(table2.item(iselected).get("values")[3])
and str(table.item(o).get("values")[4]) == aciklama02.get()):
flag2 = True
break
if miktar02.get().isspace() or miktar02.get() == '':
messagebox.showwarning("UYARI!","Lütfen Miktar Girin!")
flag = True
else:
if (str(table2.item(iselected).get("values")[0]) == str(malzeme0x.cget("text"))
and str(table2.item(iselected).get("values")[1]) == str(malzeme_metin0x.cget("text"))
and str(table2.item(iselected).get("values")[3]) == str(olcu0x.cget("text"))
and str(table2.item(iselected).get("values")[4]) == str(veren0x.cget("text"))
and str(table2.item(iselected).get("values")[5]) == str(alan0x.cget("text"))
and str(table2.item(iselected).get("values")[6]) == str(tarih0x.cget("text"))):
if flag2 == True:
if int(miktar02.get()) >= int(table2.item(iselected).get("values")[2]):
table.item(o,values=(table.item(o).get("values")[0],table.item(o).get("values")[1],int(table.item(o).get("values")[2])
+int(table2.item(iselected).get("values")[2]),table.item(o).get("values")[3],table.item(o).get("values")[4]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(iselected).get("values")[0])+" - "+str(table2.item(iselected).get("values")[1])+" - "
+str(table2.item(iselected).get("values")[2])+" - "+str(table2.item(iselected).get("values")[3])+" - "+str(table2.item(iselected).get("values")[4])
+" - "+str(table2.item(iselected).get("values")[5])+" - "+str(table2.item(iselected).get("values")[6])+" - "+str(table2.item(iselected).get("values")[7])+"\n")
logsclose()
else:
table.item(o,values=(table.item(o).get("values")[0],table.item(o).get("values")[1],int(table.item(o).get("values")[2])
+int(miktar02.get()),table.item(o).get("values")[3],table.item(o).get("values")[4]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(iselected).get("values")[0])+" - "+str(table2.item(iselected).get("values")[1])+" - "
+miktar02.get()+" - "+str(table2.item(iselected).get("values")[3])+" - "+str(table2.item(iselected).get("values")[4])
+" - "+str(table2.item(iselected).get("values")[5])+" - "+str(table2.item(iselected).get("values")[6])+" - "+str(table2.item(iselected).get("values")[7])+"\n")
logsclose()
else:
if int(miktar02.get()) >= int(table2.item(iselected).get("values")[2]):
try:
table.insert(parent = '', index="end",id=max([int(q) for q in table.get_children()])+1,values=(str(table2.item(iselected).get("values")[0]),
table2.item(iselected).get("values")[1],int(table2.item(iselected).get("values")[2]),table2.item(iselected).get("values")[3],aciklama02.get()))
sorting(table)
except:
table.insert(parent = '', index="end",id=1,values=(table2.item(iselected).get("values")[0],table2.item(iselected).get("values")[1]
,int(table2.item(iselected).get("values")[2]),table2.item(iselected).get("values")[3],aciklama02.get()))
sorting(table)
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(iselected).get("values")[0])+" - "+str(table2.item(iselected).get("values")[1])+" - "
+str(table2.item(iselected).get("values")[2])+" - "+str(table2.item(iselected).get("values")[3])+" - "+str(table2.item(iselected).get("values")[4])
+" - "+str(table2.item(iselected).get("values")[5])+" - "+str(table2.item(iselected).get("values")[6])+" - "+aciklama02.get()+"\n")
logsclose()
else:
try:
table.insert(parent = '', index="end",id=1,values=(table2.item(iselected).get("values")[0],table2.item(iselected).get("values")[1]
,miktar02.get(),table2.item(iselected).get("values")[3],aciklama02.get()))
sorting(table)
except:
table.insert(parent = '', index="end",id=max([int(q) for q in table.get_children()])+1,values=(str(table2.item(iselected).get("values")[0]),
table2.item(iselected).get("values")[1],miktar02.get(),table2.item(iselected).get("values")[3],aciklama02.get()))
sorting(table)
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(iselected).get("values")[0])+" - "+str(table2.item(iselected).get("values")[1])+" - "
+miktar02.get()+" - "+str(table2.item(iselected).get("values")[3])+" - "+str(table2.item(iselected).get("values")[4])
+" - "+str(table2.item(iselected).get("values")[5])+" - "+str(table2.item(iselected).get("values")[6])+" - "+aciklama02.get()+"\n")
logsclose()
if(int(miktar02.get())) >= int(table2.item(int(iselected)).get("values")[2]):
real_table3 = []
indexlist = []
table2.delete(iselected)
for i in table2.get_children():
real_table3.append(table2.item(i).get("values"))
indexlist.append(i)
for x in table2.get_children():
table2.delete(x)
for l in range(0,len(real_table3)):
table2.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
sorting(table2)
else:
table2.item(iselected, text="",values=(table2.item(iselected).get("values")[0],table2.item(iselected).get("values")[1],
table2.item(iselected).get("values")[2]-int(miktar02.get())
,table2.item(iselected).get("values")[3],table2.item(iselected).get("values")[4],table2.item(iselected).get("values")[5],
table2.item(iselected).get("values")[6],table2.item(iselected).get("values")[7]))
export("local")
export2("local")
else:
messagebox.showwarning("UYARI","Farklı Bir Ürün Seçili!")
except IndexError:
messagebox.showwarning("UYARI","Ürün Seçili Değil!")
############################################################
############################################################
# Adding product back to inventory from registered list by its product number.
def addBack():
try:
global real_table6
real_table6 = []
flag = False
flag2 = False
for j in table2.get_children():
if(malzeme0.get() == str(table2.item(j).get("values")[0]) and veren0.get() == str(table2.item(j).get("values")[4])
and alan0.get() == str(table2.item(j).get("values")[5])):
flag = True
break
if flag == True:
for i in table2.get_children():
if(malzeme0.get().isspace() or malzeme0.get() == '' or miktar0.get().isspace() or miktar0.get() == ''
or veren0.get().isspace() or veren0.get() == '' or alan0.get().isspace() or alan0.get() == ''):
messagebox.showwarning("UYARI","Parametreleri lütfen doldurun!")
break
elif(str(table2.item(i).get("values")[0]) == malzeme0.get()):
for o in table.get_children():
if(str(table.item(o).get("values")[0]) == str(table2.item(i).get("values")[0])
and str(table.item(o).get("values")[1]) == str(table2.item(i).get("values")[1])
and str(table.item(o).get("values")[3]) == str(table2.item(i).get("values")[3])
and str(table.item(o).get("values")[4]) == aciklama0.get()):
flag2 = True
break
if(table2.item(i).get("values")[2] - int(miktar0.get())) <=0:
if flag2 == True:
if int(miktar0.get()) >= int(table2.item(i).get("values")[2]):
table.item(o,values=(table.item(o).get("values")[0],table.item(o).get("values")[1],int(table.item(o).get("values")[2])
+int(table2.item(i).get("values")[2]),table.item(o).get("values")[3],table.item(o).get("values")[4]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+str(table2.item(i).get("values")[2])+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
else:
table.item(o,values=(table.item(o).get("values")[0],table.item(o).get("values")[1],int(table.item(o).get("values")[2])
+int(miktar0.get()),table.item(o).get("values")[3],table.item(o).get("values")[4]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
else:
if int(miktar0.get()) >= int(table2.item(i).get("values")[2]):
if aciklama0.get().isspace() or aciklama0.get() == '':
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+str(table2.item(i).get("values")[2])+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+str(table2.item(i).get("values")[7])+"\n")
logsclose()
else:
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],aciklama0.get()))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],aciklama0.get()))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+str(table2.item(i).get("values")[2])+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
else:
if aciklama0.get().isspace() or aciklama0.get() == '':
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+str(table2.item(i).get("values")[7])+"\n")
logsclose()
else:
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],aciklama0.get()))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],aciklama0.get()))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
real_table3 = []
indexlist = []
table2.delete(i)
for c in table2.get_children():
real_table3.append(table2.item(c).get("values"))
indexlist.append(c)
for x in table2.get_children():
table2.delete(x)
for l in range(0,len(real_table3)):
table2.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
sorting(table)
sorting(table2)
break
else:
## insert kısmı
if flag2 == True:
table.item(o,values=(table.item(o).get("values")[0],table.item(o).get("values")[1],int(table.item(o).get("values")[2])
+int(miktar0.get()),table.item(o).get("values")[3],table.item(o).get("values")[4]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
else:
if aciklama0.get().isspace() or aciklama0.get() == '':
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[7]))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+str(table2.item(i).get("values")[7])+"\n")
logsclose()
else:
try:
table.insert(parent='',index = 'end',id = max([int(q) for q in table.get_children()])+1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],aciklama0.get()))
except:
table.insert(parent='',index = 'end',id = 1,values=(table2.item(i).get("values")[0],
table2.item(i).get("values")[1],int(miktar0.get()),table2.item(i).get("values")[3],aciklama0.get()))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"GERİ EKLEME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktar0.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+aciklama0.get()+"\n")
logsclose()
##
table2.item(i,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1],table2.item(i).get("values")[2]
-int(miktar0.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[4],table2.item(i).get("values")[5]
,table2.item(i).get("values")[6],table2.item(i).get("values")[7]))
#table.item(i).get("values")[2] +=1
sorting(table)
sorting(table2)
break
break
export("local")
export2("local")
elif flag == False:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
except IndexError:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
except ValueError:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
############################################################
############################################################
# Sorting products according to their product id on the tables.
def sorting(table_list):
if p != 1 and p2 !=1:
try:
sort_list = [table_list.item(a).get("values") for a in table_list.get_children()]
intlist = []
strlist = []
for i in range(0,len(sort_list)):
if type(sort_list[i][0]) == int:
intlist.append(int(sort_list[i][0]))
else:
strlist.append(sort_list[i][0])
intlist.sort()
real_table4 = []
sortlist2 = []
for i in range(0,len(intlist)):
for j in table_list.get_children():
if str(intlist[i]) == str(table_list.item(j).get("values")[0]):
sortlist2.append(table_list.item(j).get("values"))
table_list.delete(j)
break
for i in range(0,len(strlist)):
for j in table_list.get_children():
if str(strlist[i]) == str(table_list.item(j).get("values")[0]):
sortlist2.append(table_list.item(j).get("values"))
table_list.delete(j)
break
for x in table_list.get_children():
table_list.delete(x)
for i in range(0,len(sortlist2)):
table_list.insert(parent = '', index='end',id=i+1, values=[sortlist2[i][j] for j in range(0,len(sortlist2[0]))])
except:
print("Sorting Sorunu")
coloring()
coloring2()
coloring3()
############################################################
############################################################
# Editting mouse-selected registered product.
def edit4():
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"DÜZENLEME"+" "+str(table2.item(selectedItemx).get("values")[0])+" - "+str(table2.item(selectedItemx).get("values")[1])+" - "
+str(table2.item(selectedItemx).get("values")[2])+" - "+str(table2.item(selectedItemx).get("values")[3])+" - "+str(table2.item(selectedItemx).get("values")[4]
+" - "+str(table2.item(selectedItemx).get("values")[5])+" - "+str(table2.item(selectedItemx).get("values")[6])+" - "+str(table2.item(selectedItemx).get("values")[7])))
table2.item(selectedItemx, text="",values=(malzemet.get(),malzeme_metint.get()
,miktart.get(),olcut.get(),verent.get(),alant.get(),tariht.get(),aciklamat.get()))
logfile.write(" -------YENİ ÜRÜN:------- "+malzemet.get()+" - "+malzeme_metint.get()+" - "
+miktart.get()+" - "+olcut.get()+" - "+verent.get()+" - "+alant.get()+" - "+tariht.get()+" - "+aciklamat.get()+"\n")
logsclose()
sorting(table2)
export2("local")
############################################################
############################################################
# Selecting product with mouse to edit it.
def selectReg():
try:
global selectedItemx
selectedItemx = table2.focus()
malzemet.delete(0,END)
malzeme_metint.delete(0,END)
miktart.delete(0,END)
olcut.delete(0,END)
verent.delete(0,END)
alant.delete(0,END)
tariht.delete(0,END)
aciklamat.delete(0,END)
malzemet.insert(0,str(table2.item(selectedItemx).get("values")[0]))
malzeme_metint.insert(0,str(table2.item(selectedItemx).get("values")[1]))
miktart.insert(0,str(table2.item(selectedItemx).get("values")[2]))
olcut.insert(0,str(table2.item(selectedItemx).get("values")[3]))
verent.insert(0,str(table2.item(selectedItemx).get("values")[4]))
alant.insert(0,str(table2.item(selectedItemx).get("values")[5]))
tariht.insert(0,str(table2.item(selectedItemx).get("values")[6]))
aciklamat.insert(0,str(table2.item(selectedItemx).get("values")[7]))
duzenlet['state'] = ACTIVE
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin!")
############################################################
############################################################
# Editting registered product which searched by its product number.
def edit3():
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"DÜZENLEME"+" "+str(table2.item(productR).get("values")[0])+" - "+str(table2.item(productR).get("values")[1])+" - "
+str(table2.item(productR).get("values")[2])+" - "+str(table2.item(productR).get("values")[3])+" - "+str(table2.item(productR).get("values")[4]
+" - "+str(table2.item(productR).get("values")[5])+" - "+str(table2.item(productR).get("values")[6])+" - "+str(table2.item(productR).get("values")[7])))
table2.item(productR, text="",values=(malzemeq2.get(),malzeme_metinq.get()
,miktarq.get(),olcuq.get(),verenq.get(),alanq.get(),tarihq.get(),aciklamaq.get()))
logfile.write(" -------YENİ ÜRÜN:------- "+malzemeq2.get()+" - "+malzeme_metinq.get()+" - "
+miktarq.get()+" - "+olcuq.get()+" - "+verenq.get()+" - "+alanq.get()+" - "+tarihq.get()+" - "+aciklamaq.get()+"\n")
logsclose()
sorting(table2)
export2("local")
############################################################
# Searching product by its product id.
def searchRegist():
try:
ctrl = False
global productR
productR = 0
for i in table2.get_children():
if(malzemeq.get() == str(table2.item(i).get("values")[0])):
productR = i
malzemeq['state'] = DISABLED
malzemeq2.delete(0,END)
malzeme_metinq.delete(0,END)
miktarq.delete(0,END)
olcuq.delete(0,END)
aciklamaq.delete(0,END)
verenq.delete(0,END)
alanq.delete(0,END)
tarihq.delete(0,END)
duzenleq['state'] = ACTIVE
malzemeq2.insert(0,str(table2.item(i).get("values")[0]))
malzeme_metinq.insert(0,str(table2.item(i).get("values")[1]))
miktarq.insert(0,str(table2.item(i).get("values")[2]))
olcuq.insert(0,str(table2.item(i).get("values")[3]))
aciklamaq.insert(0,str(table2.item(i).get("values")[7]))
verenq.insert(0,str(table2.item(i).get("values")[4]))
alanq.insert(0,str(table2.item(i).get("values")[5]))
tarihq.insert(0,str(table2.item(i).get("values")[6]))
ctrl = True
break
if ctrl == False:
messagebox.showwarning("UYARI","Ürün Mevcut Değil!")
except IndexError:
messagebox.showwarning("UYARI","Ürün Bulunamadı!")
except ValueError:
messagebox.showwarning("UYARI","Ürün Bulunamadı!")
############################################################
############################################################
# Deleting mouse-selected registered product on the table.
def deleteSelectedReg():
try:
selected = table2.focus()
if miktarr2.get().isspace() or miktarr2.get() == '':
if table2.item(selected).get("values")[2]<=1:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,1,table2.item(selected).get("values")[3],str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,
values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,1,table2.item(selected).get("values")[3],
str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(selected).get("values")[0])+" - "+str(table2.item(selected).get("values")[1])+" - "
+"1"+" - "+str(table2.item(selected).get("values")[3])+" - "+str(table2.item(selected).get("values")[4])
+" - "+str(table2.item(selected).get("values")[5])+" - "+str(table2.item(selected).get("values")[6])+" - "+hurdaaciklama4.get()+"\n")
logsclose()
real_table3 = []
indexlist = []
table2.delete(selected)
for i in table2.get_children():
real_table3.append(table2.item(i).get("values"))
indexlist.append(i)
for x in table2.get_children():
table2.delete(x)
for l in range(0,len(real_table3)):
table2.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,1,table2.item(selected).get("values")[3],str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,
values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,1,table2.item(selected).get("values")[3],
str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(selected).get("values")[0])+" - "+str(table2.item(selected).get("values")[1])+" - "
+"1"+" - "+str(table2.item(selected).get("values")[3])+" - "+str(table2.item(selected).get("values")[4])
+" - "+str(table2.item(selected).get("values")[5])+" - "+str(table2.item(selected).get("values")[6])+" - "+hurdaaciklama4.get()+"\n")
logsclose()
table2.item(selected, text="",values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1],table2.item(selected).get("values")[2]-1
,table2.item(selected).get("values")[3],table2.item(selected).get("values")[4],table2.item(selected).get("values")[5]
,table2.item(selected).get("values")[6],table2.item(selected).get("values")[7]))
else:
if(table2.item(selected).get("values")[2] - int(miktarr2.get())) <=0:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,int(table2.item(selected).get("values")[2]),table2.item(selected).get("values")[3],str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,
values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,int(table2.item(selected).get("values")[2]),table2.item(selected).get("values")[3],
str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(selected).get("values")[0])+" - "+str(table2.item(selected).get("values")[1])+" - "
+str(table2.item(selected).get("values")[2])+" - "+str(table2.item(selected).get("values")[3])+" - "+str(table2.item(selected).get("values")[4])
+" - "+str(table2.item(selected).get("values")[5])+" - "+str(table2.item(selected).get("values")[6])+" - "+hurdaaciklama4.get()+"\n")
logsclose()
real_table4 = []
indexlist2 = []
table2.delete(selected)
for i in table2.get_children():
real_table4.append(table2.item(i).get("values"))
indexlist2.append(i)
for x in table2.get_children():
table2.delete(x)
for l in range(0,len(real_table4)):
table2.insert(parent = '', index='end',id=indexlist2[l],values=[real_table4[l][a] for a in range (0,len(real_table4[0]))])
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,int(miktarr2.get()),table2.item(selected).get("values")[3],str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,
values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,int(miktarr2.get()),table2.item(selected).get("values")[3],
str(str(hurdaaciklama4.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(selected).get("values")[0])+" - "+str(table2.item(selected).get("values")[1])+" - "
+miktarr2.get()+" - "+str(table2.item(selected).get("values")[3])+" - "+str(table2.item(selected).get("values")[4])
+" - "+str(table2.item(selected).get("values")[5])+" - "+str(table2.item(selected).get("values")[6])+" - "+hurdaaciklama4.get()+"\n")
logsclose()
table2.item(selected, text="",values=(table2.item(selected).get("values")[0],table2.item(selected).get("values")[1]
,table2.item(selected).get("values")[2]-int(miktarr2.get())
,table2.item(selected).get("values")[3],table2.item(selected).get("values")[4],table2.item(selected).get("values")[5]
,table2.item(selected).get("values")[6],table2.item(selected).get("values")[7]))
sorting(table2)
export2("local")
export3("local")
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin!")
############################################################
############################################################
# Deleting registered product which searched by its product id.
def deleteReg():
try:
global real_table5
real_table5 = []
flag = False
for j in table2.get_children():
if(malzemer.get() == str(table2.item(j).get("values")[0])):
flag = True
break
if flag == True:
for i in table2.get_children():
if(malzemer.get().isspace() or malzemer.get() == '' or miktarr.get().isspace() or miktarr.get() == ''):
messagebox.showwarning("UYARI","Parametreyi lütfen doldurun!")
break
elif(str(table2.item(i).get("values")[0]) == malzemer.get()):
if(table2.item(i).get("values")[2] - int(miktarr.get())) <=0:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1]
,int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],str(str(hurdaaciklama3.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+str(table2.item(i).get("values")[2])+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+hurdaaciklama3.get()+"\n")
logsclose()
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1]
,int(table2.item(i).get("values")[2]),table2.item(i).get("values")[3],str(str(hurdaaciklama3.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+str(table2.item(i).get("values")[2])+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+hurdaaciklama3.get()+"\n")
logsclose()
real_table3 = []
indexlist= []
table2.delete(i)
for j in table2.get_children():
real_table3.append(table2.item(j).get("values"))
indexlist.append(j)
for x in table2.get_children():
table2.delete(x)
for l in range(0,len(real_table3)):
table2.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
break
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1]
,int(miktarr.get()),table2.item(i).get("values")[3],str(str(hurdaaciklama3.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktarr.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+hurdaaciklama3.get()+"\n")
logsclose()
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1]
,int(int(miktarr.get())),table2.item(i).get("values")[3],str(str(hurdaaciklama3.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("ZİMMET LİSTESİ"+"\t"+"SİLME"+" "+str(table2.item(i).get("values")[0])+" - "+str(table2.item(i).get("values")[1])+" - "
+miktarr.get()+" - "+str(table2.item(i).get("values")[3])+" - "+str(table2.item(i).get("values")[4])
+" - "+str(table2.item(i).get("values")[5])+" - "+str(table2.item(i).get("values")[6])+" - "+hurdaaciklama3.get()+"\n")
logsclose()
table2.item(i,values=(table2.item(i).get("values")[0],table2.item(i).get("values")[1],table2.item(i).get("values")[2]
-int(miktarr.get()),table2.item(i).get("values")[3],table2.item(i).get("values")[4],table2.item(i).get("values")[5]
,table2.item(i).get("values")[6],table2.item(i).get("values")[7]))
#table.item(i).get("values")[2] +=1
break
sorting(table2)
export2("local")
export3("local")
elif flag == False:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
except IndexError:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
except ValueError:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
############################################################
############################################################
# Cleaning entries and back buttons on the interface.
def clearReg():
malzemer.delete(0,END)
miktarr.delete(0,END)
miktarr2.delete(0,END)
hurdaaciklama3.delete(0,END)
hurdaaciklama4.delete(0,END)
def backReg():
remove_register_frame.place_forget()
malzemer.delete(0,END)
miktarr.delete(0,END)
miktarr2.delete(0,END)
hurdaaciklama3.delete(0,END)
hurdaaciklama4.delete(0,END)
def clearAll():
malzeme0.delete(0,END)
miktar0.delete(0,END)
aciklama0.delete(0,END)
veren0.delete(0,END)
alan0.delete(0,END)
miktar02.delete(0,END)
aciklama02.delete(0,END)
malzeme0x.configure(text="")
malzeme_metin0x.configure(text="")
olcu0x.configure(text="")
veren0x.configure(text="")
alan0x.configure(text="")
tarih0x.configure(text="")
ekle02['state'] = DISABLED
def backMain():
malzeme0.delete(0,END)
miktar0.delete(0,END)
aciklama0.delete(0,END)
veren0.delete(0,END)
alan0.delete(0,END)
miktar02.delete(0,END)
aciklama02.delete(0,END)
malzeme0x.configure(text="")
malzeme_metin0x.configure(text="")
olcu0x.configure(text="")
veren0x.configure(text="")
alan0x.configure(text="")
tarih0x.configure(text="")
ekle02['state'] = DISABLED
back_register_frame.place_forget()
############################################################
############################################################
# Selecting product on registered table.
def selecting():
try:
selectinq = table2.focus()
miktar02.delete(0,END)
aciklama02.delete(0,END)
malzeme0x.configure(text=table2.item(selectinq).get("values")[0],fg="red")
malzeme_metin0x.configure(text=table2.item(selectinq).get("values")[1],fg="red",font=("",7))
miktar02.insert(0,table2.item(selectinq).get("values")[2])
olcu0x.configure(text=table2.item(selectinq).get("values")[3],fg="red")
veren0x.configure(text=table2.item(selectinq).get("values")[4],fg="red")
alan0x.configure(text=table2.item(selectinq).get("values")[5],fg="red")
tarih0x.configure(text=table2.item(selectinq).get("values")[6],fg="red")
aciklama02.insert(0,table2.item(selectinq).get("values")[7])
ekle02['state'] = ACTIVE
except IndexError:
messagebox.showerror("UYARI","Ürün Seçilmedi!")
############################################################
############################################################
# Interface of adding registered product back to inventory.
def backInventory():
back_register_frame.place(x=0,y=0)
malzeme_label = Label(back_register_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=16)
malzeme_label = Label(back_register_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=39)
malzeme_label = Label(back_register_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=64)
malzeme_label = Label(back_register_frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=89)
malzeme_label = Label(back_register_frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=114)
malzeme0.place(x=100,y=16)
miktar0.place(x=100,y=39)
aciklama0.place(x=100,y=64)
veren0.place(x=100,y=89)
alan0.place(x=100,y=114)
ekle0.place(x=80,y=134)
malzeme_label = Label(back_register_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=210)
malzeme_label = Label(back_register_frame,text="M.M: ",bg="LavenderBlush2").place(x=0,y=235)
malzeme_label = Label(back_register_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=260)
malzeme_label = Label(back_register_frame,text="Ölçü: ",bg="LavenderBlush2").place(x=5,y=285)
malzeme_label = Label(back_register_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=310)
malzeme_label = Label(back_register_frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=335)
malzeme_label = Label(back_register_frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=360)
malzeme_label = Label(back_register_frame,text="Teslim Tarihi: ",bg="LavenderBlush2").place(x=5,y=385)
malzeme_label = Label(back_register_frame,text="________________SEÇEREK EKLE________________",bg="LavenderBlush2",fg = "indian red").place(x=0,y=160)
malzeme_label = Label(back_register_frame,text="NO İLE EKLE",bg="LavenderBlush2",fg = "indian red").place(x=5,y=0)
malzeme0x.place(x=100,y=210)
malzeme_metin0x.place(x=35,y=238)
olcu0x.place(x=100,y=285)
veren0x.place(x=100,y=335)
alan0x.place(x=100,y=360)
tarih0x.place(x=100,y=385)
miktar02.place(x=100,y=260)
aciklama02.place(x=100,y=310)
sec0.place(x=80,y=182)
ekle02.place(x=12,y=410)
geri02.place(x=87,y=410)
temizle02.place(x=162,y=410)
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# Adding product to registered list from inventory by mouse-click.
def selectRegister():
flag = False
flag2 = False
for o in table2.get_children():
if(str(smalzeme.cget("text")) == str(table2.item(o).get("values")[0]) and str(saciklama.get()) == str(table2.item(o).get("values")[7])
and str(vereny2.get()) == str(table2.item(o).get("values")[4]) and str(alany2.get()) == str(table2.item(o).get("values")[5])
and str(tarihy2.get()) == str(table2.item(o).get("values")[6])):
flag2 = True
break
try:
iselected = table.focus()
if miktary2.get().isspace() or miktary2.get() == '':
messagebox.showwarning("UYARI!","Lütfen Miktar Girin!")
flag = True
elif vereny2.get().isspace() or vereny2.get() == '' or alany2.get().isspace() or alany2.get() == '' :
messagebox.showwarning("UYARI!","Lütfen Personel İsimlerini Giriniz!")
flag = True
else:
if (str(table.item(iselected).get("values")[0]) == str(smalzeme.cget("text"))
and str(table.item(iselected).get("values")[1]) == str(smalzeme_metin.cget("text"))
and str(table.item(iselected).get("values")[3]) == str(solcu.cget("text"))):
if flag2 == True:
if int(miktary2.get()) >= int(table.item(iselected).get("values")[2]):
table2.item(o,text="",values=(table2.item(o).get("values")[0],table2.item(o).get("values")[1],int(table.item(iselected).get("values")[2])+table2.item(o).get("values")[2],
table2.item(o).get("values")[3],table2.item(o).get("values")[4],table2.item(o).get("values")[5],table2.item(o).get("values")[6],
table2.item(o).get("values")[7]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table2.item(o).get("values")[0])+" - "+str(table2.item(o).get("values")[1])+" - "
+str(table.item(iselected).get("values")[2])+" - "+str(table2.item(o).get("values")[3])+" - "+str(table2.item(o).get("values")[4])+" - "
+str(table2.item(o).get("values")[5])+" - "+str(table2.item(o).get("values")[6])+" - "+str(table2.item(o).get("values")[7])+"\n")
logsclose()
else:
table2.item(o,text="",values=(table2.item(o).get("values")[0],table2.item(o).get("values")[1],int(miktary2.get())+table2.item(o).get("values")[2],
table2.item(o).get("values")[3],table2.item(o).get("values")[4],table2.item(o).get("values")[5],table2.item(o).get("values")[6],
table2.item(o).get("values")[7]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table2.item(o).get("values")[0])+" - "+str(table2.item(o).get("values")[1])+" - "
+miktary2.get()+" - "+str(table2.item(o).get("values")[3])+" - "+str(table2.item(o).get("values")[4])+" - "
+str(table2.item(o).get("values")[5])+" - "+str(table2.item(o).get("values")[6])+" - "+str(table2.item(o).get("values")[7])+"\n")
logsclose()
else:
if int(miktary2.get()) >= int(table.item(iselected).get("values")[2]):
try:
table2.insert(parent = '', index='end',id=1,values=(table.item(iselected).get("values")[0],table.item(iselected).get("values")[1]
,int(table.item(iselected).get("values")[2]),table.item(iselected).get("values")[3],vereny2.get(),alany2.get()
,str(tarihy2.get()),saciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(iselected).get("values")[0])+" - "+str(table.item(iselected).get("values")[1])+" - "
+str(table.item(iselected).get("values")[2])+" - "+str(table.item(iselected).get("values")[3])+" - "+vereny2.get()+" - "
+alany2.get()+" - "+str(tarihy2.get())+" - "+saciklama.get()+"\n")
logsclose()
except:
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(iselected).get("values")[0],
table.item(iselected).get("values")[1]
,int(table.item(iselected).get("values")[2]),table.item(iselected).get("values")[3],vereny2.get(),alany2.get()
,str(tarihy2.get()),saciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(iselected).get("values")[0])+" - "+str(table.item(iselected).get("values")[1])+" - "
+str(table.item(iselected).get("values")[2])+" - "+str(table.item(iselected).get("values")[3])+" - "+vereny2.get()+" - "
+alany2.get()+" - "+str(tarihy2.get())+" - "+saciklama.get()+"\n")
logsclose()
else:
try:
table2.insert(parent = '', index='end',id=1,values=(table.item(iselected).get("values")[0],table.item(iselected).get("values")[1]
,miktary2.get(),table.item(iselected).get("values")[3],vereny2.get(),alany2.get()
,str(tarihy2.get()),saciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(iselected).get("values")[0])+" - "+str(table.item(iselected).get("values")[1])+" - "
+miktary2.get()+" - "+str(table.item(iselected).get("values")[3])+" - "+vereny2.get()+" - "
+alany2.get()+" - "+str(tarihy2.get())+" - "+saciklama.get()+"\n")
logsclose()
except:
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(iselected).get("values")[0],
table.item(iselected).get("values")[1]
,miktary2.get(),table.item(iselected).get("values")[3],vereny2.get(),alany2.get()
,str(tarihy2.get()),saciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(iselected).get("values")[0])+" - "+str(table.item(iselected).get("values")[1])+" - "
+miktary2.get()+" - "+str(table.item(iselected).get("values")[3])+" - "+vereny2.get()+" - "
+alany2.get()+" - "+str(tarihy2.get())+" - "+saciklama.get()+"\n")
logsclose()
if(int(miktary2.get())) >= int(table.item(int(iselected)).get("values")[2]):
real_table3 = []
indexlist = []
table.delete(iselected)
for i in table.get_children():
real_table3.append(table.item(i).get("values"))
indexlist.append(i)
for x in table.get_children():
table.delete(x)
for l in range(0,len(real_table3)):
table.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
else:
table.item(iselected, text="",values=(table.item(iselected).get("values")[0],table.item(iselected).get("values")[1],
table.item(iselected).get("values")[2]-int(miktary2.get())
,table.item(iselected).get("values")[3],table.item(iselected).get("values")[4]))
else:
messagebox.showwarning("UYARI","Farklı Bir Ürün Seçili!")
sorting(table)
sorting(table2)
export("local")
export2("local")
except IndexError:
messagebox.showwarning("UYARI","Ürün Seçili Değil!")
############################################################
############################################################
# Adding product to registered list from inventory by product id.
def noRegister():
flag = False
flag2 = False
for o in table2.get_children():
if(str(malzemey.get()) == str(table2.item(o).get("values")[0]) and str(aciklamay.get()) == str(table2.item(o).get("values")[7])
and str(vereny.get()) == str(table2.item(o).get("values")[4]) and str(alany.get()) == str(table2.item(o).get("values")[5])
and str(tarihy.get()) == str(table2.item(o).get("values")[6])):
flag2 = True
break
for i in table.get_children():
if miktary.get().isspace() or miktary.get() == '':
messagebox.showwarning("UYARI!","Lütfen Miktar Girin!")
flag = True
break
elif vereny.get().isspace() or vereny.get() == '' or alany.get().isspace() or alany.get() == '' :
messagebox.showwarning("UYARI!","Lütfen Personel İsimlerini Giriniz!")
flag = True
break
else:
if(malzemey.get() == str(table.item(i).get("values")[0])):
if flag2 == True:
if int(miktary.get()) >= int(table.item(i).get("values")[2]):
table2.item(o,text="",values=(table2.item(o).get("values")[0],table2.item(o).get("values")[1],int(table.item(i).get("values")[2])+
table2.item(o).get("values")[2],
table2.item(o).get("values")[3],table2.item(o).get("values")[4],table2.item(o).get("values")[5],table2.item(o).get("values")[6],
table2.item(o).get("values")[7]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table2.item(o).get("values")[0])+" - "+str(table2.item(o).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table2.item(o).get("values")[3])+" - "+str(table2.item(o).get("values")[4])+" - "
+str(table2.item(o).get("values")[5])+" - "+str(table2.item(o).get("values")[6])+" - "+str(table2.item(o).get("values")[7])+"\n")
logsclose()
else:
table2.item(o,text="",values=(table2.item(o).get("values")[0],table2.item(o).get("values")[1],int(miktary.get())+table2.item(o).get("values")[2],
table2.item(o).get("values")[3],table2.item(o).get("values")[4],table2.item(o).get("values")[5],table2.item(o).get("values")[6],
table2.item(o).get("values")[7]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table2.item(o).get("values")[0])+" - "+str(table2.item(o).get("values")[1])+" - "
+miktary.get()+" - "+str(table2.item(o).get("values")[3])+" - "+str(table2.item(o).get("values")[4])+" - "
+str(table2.item(o).get("values")[5])+" - "+str(table2.item(o).get("values")[6])+" - "+str(table2.item(o).get("values")[7])+"\n")
logsclose()
else:
if int(miktary.get()) >= int(table.item(i).get("values")[2]):
try:
if aciklamay.get().isspace() or aciklamay.get() == '':
table2.insert(parent = '', index='end',id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,table.item(i).get("values")[2],table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(table.item(i).get("values")[4])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+str(table.item(i).get("values")[4])+"\n")
logsclose()
else:
table2.insert(parent = '', index='end',id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,table.item(i).get("values")[2],table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(aciklamay.get())))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+aciklamay.get()+"\n")
logsclose()
except:
if aciklamay.get().isspace() or aciklamay.get() == '':
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,table.item(i).get("values")[2],table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(table.item(i).get("values")[4])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+str(table.item(i).get("values")[4])+"\n")
logsclose()
else:
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,table.item(i).get("values")[2],table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(aciklamay.get())))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+aciklamay.get()+"\n")
logsclose()
else:
try:
if aciklamay.get().isspace() or aciklamay.get() == '':
table2.insert(parent = '', index='end',id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,miktary.get(),table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(table.item(i).get("values")[4])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+miktary.get()+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+str(table.item(i).get("values")[4])+"\n")
logsclose()
else:
table2.insert(parent = '', index='end',id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,miktary.get(),table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(aciklamay.get())))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+miktary.get()+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+aciklamay.get()+"\n")
logsclose()
except:
if aciklamay.get().isspace() or aciklamay.get() == '':
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,miktary.get(),table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(table.item(i).get("values")[4])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+miktary.get()+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+str(table.item(i).get("values")[4])+"\n")
logsclose()
else:
table2.insert(parent = '', index='end',id=max([int(q) for q in table2.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,miktary.get(),table.item(i).get("values")[3],vereny.get()
,alany.get(),str(tarihy.get()),str(aciklamay.get())))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"ZİMMETLEME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+miktary.get()+" - "+str(table.item(i).get("values")[3])+" - "+vereny.get()+" - "
+alany.get()+" - "+str(tarihy.get())+" - "+aciklamay.get()+"\n")
logsclose()
if(int(miktary.get())) >= int(table.item(i).get("values")[2]):
real_table3 = []
indexlist = []
table.delete(i)
for j in table.get_children():
real_table3.append(table.item(j).get("values"))
indexlist.append(j)
for x in table.get_children():
table.delete(x)
for l in range(0,len(real_table3)):
table.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
else:
table.item(i, text="",values=(table.item(i).get("values")[0],table.item(i).get("values")[1],table.item(i).get("values")[2]-int(miktary.get())
,table.item(i).get("values")[3],table.item(i).get("values")[4]))
flag = True
break
sorting(table)
sorting(table2)
export("local")
export2("local")
if flag == False:
messagebox.showwarning("UYARI","Ürün Bulunamadı!")
############################################################
############################################################
# Selecting product with mouse on registered table part.
def selectRegistered():
try:
miktary2.delete(0,END)
saciklama.delete(0,END)
global selected1
selected1 = table.focus()
smalzeme.place(x=100,y=225)
smalzeme.configure(text=table.item(selected1).get("values")[0],fg="red")
smalzeme_metin.place(x=100,y=250)
smalzeme_metin.configure(text=table.item(selected1).get("values")[1],fg="red")
miktary2.insert(0,table.item(selected1).get("values")[2])
solcu.place(x=100,y=300)
solcu.configure(text=table.item(selected1).get("values")[3],fg="red")
saciklama.insert(0,table.item(selected1).get("values")[4])
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin")
############################################################
############################################################
# cleaning and back button
def clearagain():
malzemey.delete(0,END)
miktary.delete(0,END)
vereny.delete(0,END)
alany.delete(0,END)
tarihy.delete(0,END)
aciklamay.delete(0,END)
miktary2.delete(0,END)
vereny2.delete(0,END)
alany2.delete(0,END)
tarihy2.delete(0,END)
smalzeme.configure(text="")
smalzeme_metin.configure(text="")
solcu.configure(text="")
saciklama.delete(0,END)
def backagain():
malzemey.delete(0,END)
miktary.delete(0,END)
vereny.delete(0,END)
alany.delete(0,END)
tarihy.delete(0,END)
aciklamay.delete(0,END)
miktary2.delete(0,END)
vereny2.delete(0,END)
alany2.delete(0,END)
tarihy2.delete(0,END)
smalzeme.configure(text="")
smalzeme_metin.configure(text="")
solcu.configure(text="")
saciklama.delete(0,END)
remove_frame.place_forget()
registered_remove_frame.place_forget()
add_button.place(x=120,y=75)
remove_button.place(x=120,y=225)
edit_button.place(x=120,y=300)
registered_removeitem_button.place(x=120,y=150)
############################################################
############################################################
# Interface of adding registered product back to inventory from registered list.
def removeRegistered():
add_button.place_forget()
remove_button.place_forget()
edit_button.place_forget()
registered_removeitem_button.place_forget()
remove_frame.place(x=0,y=0)
registered_remove_frame.place(x=0,y=0)
malzeme_label = Label(registered_remove_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=25)
malzeme_label = Label(registered_remove_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=50)
malzeme_label = Label(registered_remove_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=75)
malzeme_label = Label(registered_remove_frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=100)
malzeme_label = Label(registered_remove_frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=125)
malzeme_label = Label(registered_remove_frame,text="Teslim Tarihi: ",bg="LavenderBlush2").place(x=5,y=150)
miktary2.place(x=95,y=275)
malzemey.place(x=95,y=25)
miktary.place(x=95,y=50)
aciklamay.place(x=95,y=75)
vereny.place(x=95,y=100)
alany.place(x=95,y=125)
tarihy.place(x=95,y=150)
ekley.place(x=250,y=75)
sec.place(x=250,y=272)
malzeme_label = Label(registered_remove_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=225)
malzeme_label = Label(registered_remove_frame,text="Malzeme Metni: ",bg="LavenderBlush2").place(x=5,y=250)
malzeme_label = Label(registered_remove_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=275)
malzeme_label = Label(registered_remove_frame,text="Ölçü Birimi: ",bg="LavenderBlush2").place(x=5,y=300)
malzeme_label = Label(registered_remove_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=325)
malzeme_label = Label(registered_remove_frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=360)
malzeme_label = Label(registered_remove_frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=385)
malzeme_label = Label(registered_remove_frame,text="Teslim Tarihi: ",bg="LavenderBlush2").place(x=5,y=410)
secmeli = Label(registered_remove_frame,text="SEÇEREK ZİMMETLE",bg="LavenderBlush2",fg="indian red")
secmeli.place(x=110,y=200)
secmeli.config(font=("Calibri",12))
secmeli2 = Label(registered_remove_frame,text="NO İLE ZİMMETLE",bg="LavenderBlush2",fg="indian red")
secmeli2.place(x=120,y=0)
secmeli2.config(font=("Calibri",12))
malzeme_label = Label(registered_remove_frame,text="_____________________________________________________________________________ ",bg="LavenderBlush2").place(x=2,y=180)
vereny2.place(x=95,y=360)
alany2.place(x=95,y=385)
tarihy2.place(x=95,y=410)
saciklama.place(x=95,y=325)
ekley2.place(x=250,y=320)
geriy.place(x=250,y=355)
temizley.place(x=250,y=390)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# Editing registered product selecting with mouse.
def sec_fr():
malzB.place_forget()
secB.place_forget()
geriB.place_forget()
sec_Frame.place(x=0,y=0)
sect.place(x=75,y=60)
malzeme_label = Label(sec_Frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=125)
malzeme_label = Label(sec_Frame,text="Malzeme Metni: ",bg="LavenderBlush2").place(x=5,y=150)
malzeme_label = Label(sec_Frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=175)
malzeme_label = Label(sec_Frame,text="Ölçü: ",bg="LavenderBlush2").place(x=5,y=200)
malzeme_label = Label(sec_Frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=225)
malzeme_label = Label(sec_Frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=250)
malzeme_label = Label(sec_Frame,text="Tarih: ",bg="LavenderBlush2").place(x=5,y=275)
malzeme_label = Label(sec_Frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=300)
malzemet.place(x=100,y=125)
malzeme_metint.place(x=100,y=150)
miktart.place(x=100,y=175)
olcut.place(x=100,y=200)
verent.place(x=100,y=225)
alant.place(x=100,y=250)
tariht.place(x=100,y=275)
aciklamat.place(x=100,y=300)
duzenlet.place(x=35,y=350)
gerit.place(x=130,y=350)
temizlet.place(x=85,y=400)
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# Cleaning and back buttons.
def clearEditto():
malzemeq.delete(0,END)
malzemeq2.delete(0,END)
malzeme_metinq.delete(0,END)
miktarq.delete(0,END)
olcuq.delete(0,END)
verenq.delete(0,END)
alanq.delete(0,END)
tarihq.delete(0,END)
aciklamaq.delete(0,END)
duzenleq['state'] = DISABLED
malzemeq['state'] = NORMAL
def clearEditto2():
malzemet.delete(0,END)
malzeme_metint.delete(0,END)
miktart.delete(0,END)
olcut.delete(0,END)
verent.delete(0,END)
alant.delete(0,END)
tariht.delete(0,END)
aciklamat.delete(0,END)
duzenlet['state'] = DISABLED
def backEditto():
malzemeq['state'] = NORMAL
duzenleq['state'] = DISABLED
malzemeq.delete(0,END)
malzemeq2.delete(0,END)
malzeme_metinq.delete(0,END)
miktarq.delete(0,END)
olcuq.delete(0,END)
verenq.delete(0,END)
alanq.delete(0,END)
tarihq.delete(0,END)
aciklamaq.delete(0,END)
malzNo_frame.place_forget()
edit_register_frame.place(x=0,y=0)
malzB.place(x=50,y=150)
secB.place(x=50,y=225)
geriB.place(x=61,y=375)
def backEditto2():
malzemet.delete(0,END)
malzeme_metint.delete(0,END)
miktart.delete(0,END)
olcut.delete(0,END)
verent.delete(0,END)
alant.delete(0,END)
tariht.delete(0,END)
aciklamat.delete(0,END)
duzenlet['state'] = DISABLED
sec_Frame.place_forget()
edit_register_frame.place(x=0,y=0)
malzB.place(x=50,y=150)
secB.place(x=50,y=225)
geriB.place(x=61,y=375)
############################################################
############################################################
# editing registered product with searching its product id.
def malzNo():
malzB.place_forget()
secB.place_forget()
geriB.place_forget()
malzNo_frame.place(x=0,y=0)
malzeme_label = Label(malzNo_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=25)
malzemeq.place(x=100,y=25)
bulq.place(x=75,y=60)
malzeme_label = Label(malzNo_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=125)
malzeme_label = Label(malzNo_frame,text="Malzeme Metni: ",bg="LavenderBlush2").place(x=5,y=150)
malzeme_label = Label(malzNo_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=175)
malzeme_label = Label(malzNo_frame,text="Ölçü: ",bg="LavenderBlush2").place(x=5,y=200)
malzeme_label = Label(malzNo_frame,text="Teslim Eden: ",bg="LavenderBlush2").place(x=5,y=225)
malzeme_label = Label(malzNo_frame,text="Teslim Alan: ",bg="LavenderBlush2").place(x=5,y=250)
malzeme_label = Label(malzNo_frame,text="Tarih: ",bg="LavenderBlush2").place(x=5,y=275)
malzeme_label = Label(malzNo_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=300)
malzeme_label = Label(malzNo_frame,text="______________________________________________ ",bg="LavenderBlush2").place(x=0,y=90)
malzemeq2.place(x=100,y=125)
malzeme_metinq.place(x=100,y=150)
miktarq.place(x=100,y=175)
olcuq.place(x=100,y=200)
verenq.place(x=100,y=225)
alanq.place(x=100,y=250)
tarihq.place(x=100,y=275)
aciklamaq.place(x=100,y=300)
duzenleq.place(x=35,y=350)
geriq.place(x=130,y=350)
temizleq.place(x=85,y=400)
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# back button
def backRegis():
edit_register_frame.place_forget()
############################################################
############################################################
# interface of edit screen.
def editRegister():
edit_register_frame.place(x=0,y=0)
malzB.place(x=50,y=150)
secB.place(x=50,y=225)
geriB.place(x=61,y=375)
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# interface of deleting registered product
def removeRegister():
remove_register_frame.place(x=0,y=0)
malzeme_label = Label(remove_register_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=5,y=25)
malzeme_label = Label(remove_register_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=60)
malzeme_label = Label(remove_register_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=95)
malzemer.place(x=100,y=27)
miktarr.place(x=100,y=62)
hurdaaciklama3.place(x=100,y=97)
cikarr.place(x=80,y=135)
malzeme_label = Label(remove_register_frame,text="Miktar: ",bg="LavenderBlush2").place(x=5,y=220)
malzeme_label = Label(remove_register_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=5,y=255)
secmeli = Label(remove_register_frame,text="SEÇEREK SİL",bg="LavenderBlush2",fg="indian red")
secmeli.place(x=80,y=182)
secmeli.config(font=("Calibri",12))
secmeli2 = Label(remove_register_frame,text="NO İLE SİL",bg="LavenderBlush2",fg="indian red")
secmeli2.place(x=85,y=0)
secmeli2.config(font=("Calibri",12))
malzeme_label2 = Label(remove_register_frame,text="______________________________________________ ",bg="LavenderBlush2")
malzeme_label2.place(x=2,y=161)
miktarr2.place(x=100,y=222)
hurdaaciklama4.place(x=100,y=257)
cikarr2.place(x=15,y=305)
gerir.place(x=145,y=305)
temizler.place(x=85,y=355)
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# editing nonregistered product on inventroy by selecting with mouse.
def edit2():
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"DÜZENLEME"+" "+str(table.item(selectedItem).get("values")[0])+" - "+str(table.item(selectedItem).get("values")[1])+" - "
+str(table.item(selectedItem).get("values")[2])+" - "+str(table.item(selectedItem).get("values")[3])+" - "+str(table.item(selectedItem).get("values")[4]))
table.item(selectedItem, text="",values=(malzeme_no3.get(),malzeme_metin3.get()
,miktar3.get(),olcu3.get(),aciklama3.get()))
logfile.write(" -------YENİ ÜRÜN:------- "+malzeme_no3.get()+" - "+malzeme_metin3.get()+" - "
+miktar3.get()+" - "+olcu3.get()+" - "+aciklama3.get()+"\n")
logsclose()
sorting(table)
export("local")
############################################################
############################################################
# cleaning and back buttons.
def clearEdit2():
malzeme_no3.delete(0,END)
malzeme_metin3.delete(0,END)
miktar3.delete(0,END)
olcu3.delete(0,END)
aciklama3.delete(0,END)
editB2['state'] = DISABLED
def backEdit():
malzeme_no3.delete(0,END)
malzeme_metin3.delete(0,END)
miktar3.delete(0,END)
olcu3.delete(0,END)
aciklama3.delete(0,END)
registered_edit_frame.place_forget()
editB2['state'] = DISABLED
notregistered_edit_button.place(x=145,y=125)
registered_edit_button.place(x=146,y=225)
############################################################
############################################################
# selecting product with mouse to edit it.
def findSelected():
try:
global selectedItem
selectedItem = table.focus()
malzeme_no3.delete(0,END)
malzeme_metin3.delete(0,END)
miktar3.delete(0,END)
olcu3.delete(0,END)
aciklama3.delete(0,END)
malzeme_no3.insert(0,str(table.item(selectedItem).get("values")[0]))
malzeme_metin3.insert(0,str(table.item(selectedItem).get("values")[1]))
miktar3.insert(0,str(table.item(selectedItem).get("values")[2]))
olcu3.insert(0,str(table.item(selectedItem).get("values")[3]))
aciklama3.insert(0,str(table.item(selectedItem).get("values")[4]))
editB2['state'] = ACTIVE
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin!")
############################################################
############################################################
# interface of edit screen on inventory.
def selectedEdit():
notregistered_edit_button.place_forget()
registered_edit_button.place_forget()
registered_edit_frame.place(x=0,y=0)
no_malzeme3 = Label(registered_edit_frame,text="Malzeme No: ",bg="LavenderBlush2").place(x=25,y=100)
malzeme_no3.place(x=125,y=102)
malzeme_met = Label(registered_edit_frame,text="Malzeme Metni: ",bg="LavenderBlush2").place(x=25,y=140)
malzeme_metin3.place(x=125,y=142)
miktar3_ = Label(registered_edit_frame,text="Miktar: ",bg="LavenderBlush2").place(x=25,y=180)
miktar3.place(x=125,y=182)
olcu3_ = Label(registered_edit_frame,text="Ölçü Birimi: ",bg="LavenderBlush2").place(x=25,y=220)
olcu3.place(x=125,y=222)
aciklama3_ = Label(registered_edit_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=25,y=260)
aciklama3.place(x=125,y=262,width=225)
searchB2.place(x=138,y=40)
editB2.place(x=75,y=300)
backB2.place(x=200,y=300)
clearB2.place(x=138,y=350)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# editing nonregistered product by searching it product id.
def edit1():
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"DÜZENLEME"+" "+str(table.item(productE).get("values")[0])+" - "+str(table.item(productE).get("values")[1])+" - "
+str(table.item(productE).get("values")[2])+" - "+str(table.item(productE).get("values")[3])+" - "+str(table.item(productE).get("values")[4]))
table.item(productE, text="",values=(malzeme_no2.get(),malzeme_metin2.get()
,miktar2.get(),olcu2.get(),aciklama2.get()))
logfile.write(" -------YENİ ÜRÜN:------- "+malzeme_no2.get()+" - "+malzeme_metin2.get()+" - "
+miktar2.get()+" - "+olcu2.get()+" - "+aciklama2.get()+"\n")
logsclose()
sorting(table)
export("local")
############################################################
############################################################
# cleaning and back buttons.
def clearEdit():
malzeme_no1.delete(0,END)
malzeme_no2.delete(0,END)
malzeme_metin2.delete(0,END)
miktar2.delete(0,END)
olcu2.delete(0,END)
aciklama2.delete(0,END)
editB['state'] = DISABLED
malzeme_no1['state'] = NORMAL
def backToEdit():
malzeme_no1['state'] = NORMAL
malzeme_no1.delete(0,END)
malzeme_no2.delete(0,END)
malzeme_metin2.delete(0,END)
miktar2.delete(0,END)
olcu2.delete(0,END)
aciklama2.delete(0,END)
editB['state'] = DISABLED
notregistered_edit_frame.place_forget()
notregistered_edit_button.place(x=142,y=145)
registered_edit_button.place(x=143,y=245)
############################################################
############################################################
# searching entered product id by user on the table to edit.
def search():
ctrl = False
global productE
productE = 0
for i in table.get_children():
if(malzeme_no1.get() == str(table.item(i).get("values")[0])):
productE = i
malzeme_no1['state'] = DISABLED
malzeme_no2.delete(0,END)
malzeme_metin2.delete(0,END)
miktar2.delete(0,END)
olcu2.delete(0,END)
aciklama2.delete(0,END)
editB['state'] = ACTIVE
malzeme_no2.insert(0,str(table.item(i).get("values")[0]))
malzeme_metin2.insert(0,str(table.item(i).get("values")[1]))
miktar2.insert(0,str(table.item(i).get("values")[2]))
olcu2.insert(0,str(table.item(i).get("values")[3]))
aciklama2.insert(0,str(table.item(i).get("values")[4]))
ctrl = True
break
if ctrl == False:
messagebox.showwarning("UYARI","Ürün Mevcut Değil!")
############################################################
############################################################
# interface of edit screen on inventory.
def no():
notregistered_edit_button.place_forget()
registered_edit_button.place_forget()
notregistered_edit_frame.place(x=0,y=0)
no_malzeme = Label(notregistered_edit_frame,text="Malzeme No: ",bg="LavenderBlush2").place(x=25,y=20)
malzeme_no1.place(x=125,y=22)
no_malzeme2 = Label(notregistered_edit_frame,text="Malzeme No: ",bg="LavenderBlush2").place(x=25,y=100)
malzeme_no2.place(x=125,y=102)
malzeme_met = Label(notregistered_edit_frame,text="Malzeme Metni: ",bg="LavenderBlush2").place(x=25,y=140)
malzeme_metin2.place(x=125,y=142)
miktar2_ = Label(notregistered_edit_frame,text="Miktar: ",bg="LavenderBlush2").place(x=25,y=180)
miktar2.place(x=125,y=182)
olcu2_ = Label(notregistered_edit_frame,text="Ölçü Birimi: ",bg="LavenderBlush2").place(x=25,y=220)
olcu2.place(x=125,y=222)
aciklama2_ = Label(notregistered_edit_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=25,y=260)
aciklama2.place(x=125,y=262,width=225)
malzeme_label = Label(notregistered_edit_frame,text="_____________________________________________________________________________ ",bg="LavenderBlush2").place(x=2,y=55)
searchB.place(x=265,y=18)
editB.place(x=75,y=300)
backB.place(x=200,y=300)
clearB.place(x=138,y=350)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# cleaning button
def clear_remove():
malzeme_no.delete(0,END)
sayi.delete(0,END)
sayi2.delete(0,END)
hurdaaciklama.delete(0,END)
hurdaaciklama2.delete(0,END)
############################################################
############################################################
# deleting nonregistered item by selecting with mouse.
def decrease():
try:
selected = table.focus()
if sayi2.get().isspace() or sayi2.get() == '':
if table.item(selected).get("values")[2]<=1:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,1,table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,1,table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+"1"+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
real_table3 = []
indexlist = []
table.delete(selected)
for i in table.get_children():
real_table3.append(table.item(i).get("values"))
indexlist.append(i)
for x in table.get_children():
table.delete(x)
for l in range(0,len(real_table3)):
table.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,1,table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,1,table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+"1"+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
table.item(selected, text="",values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1],table.item(selected).get("values")[2]-1
,table.item(selected).get("values")[3],table.item(selected).get("values")[4]))
else:
if(table.item(selected).get("values")[2] - int(sayi2.get())) <=0:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,int(table.item(selected).get("values")[2]),table.item(selected).get("values")[3]
,str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+str(table.item(selected).get("values")[2])+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,int(table.item(selected).get("values")[2]),table.item(selected).get("values")[3]
,str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+str(table.item(selected).get("values")[2])+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
real_table4 = []
indexlist2 = []
table.delete(selected)
for i in table.get_children():
real_table4.append(table.item(i).get("values"))
indexlist2.append(i)
for x in table.get_children():
table.delete(x)
for l in range(0,len(real_table4)):
table.insert(parent = '', index='end',id=indexlist2[l],values=[real_table4[l][a] for a in range (0,len(real_table4[0]))])
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,int(sayi2.get()),table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+sayi2.get()+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,int(sayi2.get()),table.item(selected).get("values")[3],str(str(hurdaaciklama2.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(selected).get("values")[0])+" - "+str(table.item(selected).get("values")[1])+" - "
+sayi2.get()+" - "+str(table.item(selected).get("values")[3])+" - "+hurdaaciklama2.get()+"\n")
logsclose()
table.item(selected, text="",values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,table.item(selected).get("values")[2]-int(sayi2.get())
,table.item(selected).get("values")[3],table.item(selected).get("values")[4]))
sorting(table)
export("local")
export3("local")
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin!")
############################################################
############################################################
# deleting nonregistered item by searching it with product id.
def removeNotRegisteredItem():
global real_table2
real_table2 = []
flag = False
for j in table.get_children():
if(malzeme_no.get() == str(table.item(j).get("values")[0])):
flag = True
break
if flag == True:
for i in table.get_children():
if(malzeme_no.get().isspace() or malzeme_no.get() == '' or sayi.get().isspace() or sayi.get() == ''):
messagebox.showwarning("UYARI","Parametreyi lütfen doldurun!")
break
elif(str(table.item(i).get("values")[0]) == malzeme_no.get()):
if(table.item(i).get("values")[2] - int(sayi.get())) <=0:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,int(table.item(i).get("values")[2]),table.item(i).get("values")[3],str(str(hurdaaciklama.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,int(table.item(i).get("values")[2]),table.item(i).get("values")[3],str(str(hurdaaciklama.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+str(table.item(i).get("values")[2])+" - "+str(table.item(i).get("values")[3])+" - "+hurdaaciklama.get()+"\n")
logsclose()
real_table3 = []
indexlist = []
table.delete(i)
for j in table.get_children():
real_table3.append(table.item(j).get("values"))
indexlist.append(j)
for x in table.get_children():
table.delete(x)
for l in range(0,len(real_table3)):
table.insert(parent = '', index='end',id=indexlist[l],values=[real_table3[l][a] for a in range (0,len(real_table3[0]))])
else:
try:
table3.insert(parent = '', index=0,id=1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,int(sayi.get()),table.item(i).get("values")[3],str(str(hurdaaciklama.get())+" "+str(datetime.now())[0:19])))
except:
table3.insert(parent = '', index=0,id=max([int(q) for q in table3.get_children()])+1,values=(table.item(i).get("values")[0],table.item(i).get("values")[1]
,int(sayi.get()),table.item(i).get("values")[3],str(str(hurdaaciklama.get())+" "+str(datetime.now())[0:19])))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"SİLME"+" "+str(table.item(i).get("values")[0])+" - "+str(table.item(i).get("values")[1])+" - "
+sayi.get()+" - "+str(table.item(i).get("values")[3])+" - "+hurdaaciklama.get()+"\n")
logsclose()
table.item(i,values=(table.item(i).get("values")[0],table.item(i).get("values")[1],table.item(i).get("values")[2]
-int(sayi.get()),table.item(i).get("values")[3],table.item(i).get("values")[4]))
#table.item(i).get("values")[2] +=1
break
sorting(table)
export("local")
export3("local")
elif flag == False:
messagebox.showwarning("UYARI","Böyle Bir Ürün Yok!")
############################################################
############################################################
# interface of deleting screen.
def removeNotRegistered():
add_button.place_forget()
remove_button.place_forget()
edit_button.place_forget()
registered_removeitem_button.place_forget()
remove_frame.place(x=0,y=0)
notregistered_remove_frame.place(x=0,y=0)
malzeme_label = Label(notregistered_remove_frame,text="Malzeme NO: ",bg="LavenderBlush2").place(x=25,y=40)
malzeme_no.place(x=125,y=40)
miktar_label = Label(notregistered_remove_frame,text="Miktar: ",bg="LavenderBlush2").place(x=25,y=80)
sayi.place(x=125,y=80)
miktar_label = Label(notregistered_remove_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=25,y=120)
hurdaaciklama.place(x=125,y=120)
remove_notregistered.place(x=265,y=75)
miktar2_label = Label(notregistered_remove_frame,text="Miktar: ",bg="LavenderBlush2").place(x=25,y=215)
sayi2.place(x=125,y=217)
miktar2_label = Label(notregistered_remove_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=25,y=255)
hurdaaciklama2.place(x=125,y=257)
secmeli = Label(notregistered_remove_frame,text="SEÇEREK SİL",bg="LavenderBlush2",fg="indian red")
secmeli.place(x=150,y=180)
secmeli.config(font=("Calibri",12))
secmeli2 = Label(notregistered_remove_frame,text="NO İLE SİL",bg="LavenderBlush2",fg="indian red")
secmeli2.place(x=150,y=0)
secmeli2.config(font=("Calibri",12))
malzeme_label = Label(notregistered_remove_frame,text="_____________________________________________________________________________ ",bg="LavenderBlush2").place(x=2,y=160)
clear_remove2.place(x=150,y=360)
remove_notregistered2.place(x=60,y=310)
geri.place(x=215,y=310)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# back button
def backRemoveRegister():
malzeme_no.delete(0, END)
sayi.delete(0, END)
sayi2.delete(0, END)
hurdaaciklama.delete(0,END)
hurdaaciklama2.delete(0,END)
remove_frame.place_forget()
notregistered_remove_frame.place_forget()
add_button.place(x=120,y=75)
remove_button.place(x=120,y=225)
edit_button.place(x=120,y=300)
registered_removeitem_button.place(x=120,y=150)
############################################################
############################################################
# interface of adding nonregistered item to table.
def addNotRegistered():
add_button.place_forget()
remove_button.place_forget()
edit_button.place_forget()
add_frame.place(x=0,y=0),
notregistered_item_frame.place(x=0,y=0)
registered_removeitem_button.place_forget()
malzeme_label = Label(notregistered_item_frame,text="Malzeme No: ",bg="LavenderBlush2").place(x=50,y=25)
malzeme.place(x=50,y=50)
malzeme_metin_label = Label(notregistered_item_frame,text="Malzeme metni: ",bg="LavenderBlush2").place(x=50,y=80)
malzeme_metin.place(x=50,y=105)
miktar_label = Label(notregistered_item_frame,text="Adet: ",bg="LavenderBlush2").place(x=50,y=135)
miktar.place(x=50,y=160)
olcu_label = Label(notregistered_item_frame,text="Ölçü: ",bg="LavenderBlush2").place(x=50,y=190)
olcu.place(x=50,y=215)
aciklama_label = Label(notregistered_item_frame,text="Açıklama: ",bg="LavenderBlush2").place(x=50,y=245)
aciklama.place(x=50,y=270)
aciklama_label = Label(notregistered_item_frame,text="_____________________________________________________________________________ ",bg="LavenderBlush2").place(x=2,y=380)
artma_label = Label(notregistered_item_frame,text="Adet: ",bg="LavenderBlush2").place(x=202,y=407)
artma.place(x=245,y=408)
add_notregistered_button.place(x=75,y=300)
back_button.place(x=200,y=300)
clear_button.place(x=137,y=350)
increase_button.place(x=65,y=405)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# back button
def backToRegister():
malzeme.delete(0, END)
malzeme_metin.delete(0, END)
miktar.delete(0,END)
olcu.delete(0, END)
aciklama.delete(0, END)
artma.delete(0, END)
notregistered_item_frame.place_forget()
add_frame.place_forget()
add_button.place(x=120,y=75)
remove_button.place(x=120,y=225)
edit_button.place(x=120,y=300)
registered_removeitem_button.place(x=120,y=150)
############################################################
############################################################
# adding nonregistered item to inventory
def addNotRegisteredItem():
flag = False
try:
for i in table.get_children():
if(malzeme.get().isspace() or malzeme.get() == '' or malzeme_metin.get().isspace() or malzeme_metin.get() == ''
or olcu.get().isspace() or olcu.get() == ''):
flag = True
messagebox.showwarning("UYARI","Lütfen parametreleri doldurun!")
break
elif(str(table.item(i).get("values")[0]) == malzeme.get() and str(table.item(i).get("values")[1]) == malzeme_metin.get() and
str(table.item(i).get("values")[3]) == olcu.get() and str(table.item(i).get("values")[4]) == aciklama.get()):
flag = True
if miktar.get().isspace() or miktar.get() == '':
table.item(i,values=(table.item(i).get("values")[0],table.item(i).get("values")[1],table.item(i).get("values")[2]+1
,table.item(i).get("values")[3],table.item(i).get("values")[4]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()+" - "
+"1"+" - "+olcu.get()+" - "+aciklama.get()+"\n")
logsclose()
break
else:
table.item(i,values=(table.item(i).get("values")[0],table.item(i).get("values")[1],
table.item(i).get("values")[2]+int(miktar.get())
,table.item(i).get("values")[3],table.item(i).get("values")[4]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()+" - "
+miktar.get()+" - "+olcu.get()+" - "+aciklama.get()+"\n")
logsclose()
break
except ValueError:
messagebox.showwarning("UYARI","Lütfen Miktarı sayı olarak giriniz!")
if(flag == False):
if miktar.get().isspace() or miktar.get() == '':
try:
table.insert(parent='',index='end',id = max([int(q) for q in table.get_children()])+1,values = (malzeme.get(),malzeme_metin.get(),1,olcu.get(),aciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()+" - "
+"1"+" - "+olcu.get()+" - "+aciklama.get()+"\n")
logsclose()
except:
table.insert(parent='',index='end',id = 1,values = (malzeme.get(),malzeme_metin.get(),1,olcu.get(),aciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()+" - "+"1"+" - "
+olcu.get()+" - "+aciklama.get()+"\n")
logsclose()
else:
try:
table.insert(parent='',index='end',id = max([int(q) for q in table.get_children()])+1,values = (malzeme.get(),malzeme_metin.get(),int(miktar.get()),olcu.get(),aciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()
+" - "+miktar.get()+" - "+olcu.get()+" - "+aciklama.get()+"\n")
logsclose()
except:
table.insert(parent='',index='end',id = 1,values = (malzeme.get(),malzeme_metin.get(),int(miktar.get()),olcu.get(),aciklama.get()))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+malzeme.get()+" - "+malzeme_metin.get()+" - "+miktar.get()
+" - "+olcu.get()+" - "+aciklama.get()+" - ")
logsclose()
sorting(table)
export("local")
############################################################
############################################################
# increasing amount of selected item on the inventory.
def increase():
try:
selected = table.focus()
if artma.get().isspace() or artma.get() == '':
table.item(selected, text="",values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1],table.item(selected).get("values")[2]+1
,table.item(selected).get("values")[3],table.item(selected).get("values")[4]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+str(table.item(selected).get("values")[0])+" - "+str((table.item(selected).get("values")[1]))+" - "
+"1"+" - "+str(table.item(selected).get("values")[3])+" - "+str(table.item(selected).get("values")[4])+"\n")
logsclose()
else:
table.item(selected, text="",values=(table.item(selected).get("values")[0],table.item(selected).get("values")[1]
,table.item(selected).get("values")[2]+int(artma.get())
,table.item(selected).get("values")[3],table.item(selected).get("values")[4]))
logs()
logfile.write("DEPO LİSTESİ"+"\t"+"EKLEME"+" "+str(table.item(selected).get("values")[0])+" - "+str((table.item(selected).get("values")[1]))+" - "
+artma.get()+" - "+str(table.item(selected).get("values")[3])+" - "+str(table.item(selected).get("values")[4])+"\n")
logsclose()
export("local")
except IndexError:
messagebox.showwarning("UYARI","Lütfen Ürün Seçin!")
############################################################
# clear button
def clear():
malzeme.delete(0, END)
malzeme_metin.delete(0, END)
miktar.delete(0,END)
olcu.delete(0, END)
aciklama.delete(0, END)
artma.delete(0, END)
############################################################
############################################################
# interface of removing nonregistered item
def removeItemFrame(inventory_frame,inventory_frame2,remove_frame,add_button,remove_button,edit_button):
add_button.place_forget()
remove_button.place_forget()
registered_removeitem_button.place_forget()
edit_button.place_forget()
notregistered_remove_frame.place(x=0,y=0)
############################################################
############################################################
# interface of editing nonregistered item.
def editFrame(inventory_frame,inventory_frame2,edit_frame,add_button,remove_button,edit_button,editBack_item_button):
add_button.place_forget()
remove_button.place_forget()
edit_button.place_forget()
registered_removeitem_button.place_forget()
inventory_frame.place(x=0,y=0)
inventory_frame2.place(x=950,y=100)
edit_frame.place(x=0,y=0)
editBack_item_button.place(x=160,y=400)
notregistered_edit_button.place(x=142,y=145)
registered_edit_button.place(x=143,y=245)
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# back button
def back(add_button,remove_button,edit_button,add_frame,remove_frame,edit_frame):
add_frame.place_forget()
remove_frame.place_forget()
edit_frame.place_forget()
add_button.place(x=120,y=75)
remove_button.place(x=120,y=225)
edit_button.place(x=120,y=300)
registered_removeitem_button.place(x=120,y=150)
#########################################################################################################
#########################################################################################################
# select inventory table to see it.
def showInventory(inventory_frame,inventory_frame2,register_frame,register_frame2):
## gizlenen
inventory_frame.place_forget()
inventory_frame2.place_forget()
register_frame.place_forget()
register_frame2.place_forget()
junk_frame.place_forget()
photo2.place_forget()
## görüntülenen
inventory_frame.place(x=0,y=0)
inventory_frame2.place(x=950,y=100)
register_select.configure(bg="white")
inventory_select.configure(bg="cadet blue")
junk_select.configure(bg="white")
global p, p2
if p == 0 and p2 == 1:
p2 = 0
sorting(table)
export("local")
p2 = 1
elif p == 0 and p2 == 0:
sorting(table)
export("local")
updateTable(table,"Depo Listesi.xlsx")
############################################################
############################################################
# select registered product table to see it.
def showRegister(inventory_frame,inventory_frame2,register_frame,register_frame2):
##gizlenen
inventory_frame.place_forget()
inventory_frame2.place_forget()
register_frame.place_forget()
register_frame2.place_forget()
junk_frame.place_forget()
photo2.place_forget()
## görüntülenen
register_frame.place(x=0,y=0)
register_frame2.place(x=1075,y=100)
remove_product.place(x=64,y=125)
edit_product.place(x=64,y=275)
back_product.place(x=54,y=200)
register_select.configure(bg="cadet blue")
inventory_select.configure(bg="white")
junk_select.configure(bg="white")
global p,p2
if p == 1 and p2 == 0:
p = 0
sorting(table2)
export2("local")
p = 1
updateTable(table2,"Zimmet Listesi.xlsx")
############################################################
############################################################
# select junk table to see it.
def showJunk(inventory_frame,inventory_frame2,register_frame,register_frame2):
inventory_frame.place_forget()
inventory_frame2.place_forget()
register_frame.place_forget()
register_frame2.place_forget()
junk_frame.place(x=0,y=0)
photo2.place(x=1060,y=250)
register_select.configure(bg="white")
inventory_select.configure(bg="white")
junk_select.configure(bg="cadet blue")
updateTable(table3,"Hurda Listesi.xlsx")
############################################################
############################################################
# saving inventory data to excel file.
def export(control):
coloring()
global p,p2
if p != 1:
global excel
excel_row = list()
for i in table.get_children():
excel_row.append(table.item(i).get("values"))
excel_column = list()
for i in range(0,len(items.columns)):
excel_column.append(table.heading(i)["text"])
excel = pd.DataFrame(excel_row,columns=excel_column)
if control == "server":
print()
elif control == "local":
writer = pd.ExcelWriter("Tablolar/Depo Listesi.xlsx")
excel.to_excel(writer,sheet_name='Envanter',index=False,na_rep ='NaN')
for column in excel:
column_width = max(excel[column].astype(str).map(len).max(), len(column))
col_idx = excel.columns.get_loc(column)
writer.sheets['Envanter'].set_column(col_idx, col_idx, column_width)
col_idx = excel.columns.get_loc('Malzeme')
writer.sheets['Envanter'].set_column(col_idx, col_idx, 15)
col_idx = excel.columns.get_loc('Açıklama')
writer.sheets['Envanter'].set_column(col_idx, col_idx, 50)
writer.save()
coloring()
############################################################
############################################################
# saving registered product table data to excel file.
def export2(control):
coloring2()
global p,p2
if p2 !=1:
global excel2
excel_row2 = list()
for i in table2.get_children():
excel_row2.append(table2.item(i).get("values"))
excel_column2 = list()
for i in range(0,len(items2.columns)):
excel_column2.append(table2.heading(i)["text"])
excel2 = pd.DataFrame(excel_row2,columns=excel_column2)
excel2['Açıklama'] = excel2['Açıklama'].astype(str)
if control == "server":
print()
elif control == "local":
writer = pd.ExcelWriter("Tablolar/Zimmet Listesi.xlsx")
excel2.to_excel(writer,sheet_name='Zimmet Listesi',index=False,na_rep ='NaN')
for column in excel2:
column_width = max(excel2[column].astype(str).map(len).max(), len(column))
col_idx = excel2.columns.get_loc(column)
writer.sheets['Zimmet Listesi'].set_column(col_idx, col_idx, column_width)
col_idx = excel2.columns.get_loc('Malzeme')
writer.sheets['Zimmet Listesi'].set_column(col_idx, col_idx, 15)
col_idx = excel2.columns.get_loc('Açıklama')
writer.sheets['Zimmet Listesi'].set_column(col_idx, col_idx, 50)
writer.save()
coloring2()
############################################################
############################################################
# saving junk table data to excel file.
def export3(control):
coloring3()
global p,p2
if p3 !=1:
global excel3
excel_row3 = list()
for i in table3.get_children():
excel_row3.append(table3.item(i).get("values"))
excel_column3 = list()
for i in range(0,len(items.columns)):
excel_column3.append(table3.heading(i)["text"])
excel3 = pd.DataFrame(excel_row3,columns=excel_column3)
if control == "server":
print()
elif control == "local":
writer = pd.ExcelWriter("Tablolar/Hurda Listesi.xlsx")
excel3.to_excel(writer,sheet_name='Hurda Listesi',index=False,na_rep ='NaN')
for column in excel3:
column_width = max(excel3[column].astype(str).map(len).max(), len(column))
col_idx = excel3.columns.get_loc(column)
writer.sheets['Hurda Listesi'].set_column(col_idx, col_idx, column_width)
col_idx = excel3.columns.get_loc('Malzeme')
writer.sheets['Hurda Listesi'].set_column(col_idx, col_idx, 15)
col_idx = excel3.columns.get_loc('Açıklama')
writer.sheets['Hurda Listesi'].set_column(col_idx, col_idx, 50)
writer.save()
coloring3()
############################################################
########################################################### MAIN FUNCTION #############################################################
def main():
#main window
global window
window = Tk()
window.title("Envanter")
window.geometry("1350x600")
window.configure(bg="Lavender")
window.resizable(False, False)
# logos
photo = Canvas(window,width=100, height=55, bg='Lavender',highlightthickness=0)
logo = PhotoImage(file="Media/logo.png")
photo.create_image(0, 0, image=logo, anchor=NW)
photo.place(x=1255,y=555)
window.iconbitmap('Media/simge.ico')
global photo2
photo2 = Canvas(window,width=275, height=130, bg='lavender',highlightthickness=0)
logo2 = PhotoImage(file="Media/buyuklogo.png")
photo2.create_image(0, 0, image=logo2, anchor=NW)
photo2.place(x=1060,y=250)
# Inventory screen
inventory_frame = Frame(window,width=950,height=600,highlightbackground='black',highlightthickness=3)
inventory_frame.place(x=0,y=0)
# Registered product table screen
inventory_frame2 = Frame(window,highlightbackground='black',width=400,height=450,bg="Lavender")
inventory_frame2.place(x=950,y=100)
global inventory_select
inventory_select = Button(window,text = "Depo Listesi",width=10,bg="cadet blue",command= lambda : showInventory(inventory_frame,inventory_frame2,register_frame,register_frame2))
inventory_select.place(x=1060,y=30)
#frames of inventory screen
global add_frame,remove_frame
add_frame = Frame(inventory_frame2,width=400,height=445,bg="Lavender")
remove_frame = Frame(inventory_frame2,width=400,height=445,bg="Lavender")
edit_frame = Frame(inventory_frame2,width=400,height=445,bg="LavenderBlush2",highlightbackground='black',highlightthickness=1)
global add_button,remove_button,edit_button
#Buttons on inventory screen
add_button = Button(inventory_frame2,text = 'Depoya Ürün Ekle',width=20,height = 2,bg="light steel blue",command = addNotRegistered)
add_button.place(x=120,y=75)
remove_button = Button(inventory_frame2,text = 'Depodan Ürün Sil',width=20,height =2,bg='light steel blue',command = removeNotRegistered)
remove_button.place(x=120,y=225)
edit_button = Button(inventory_frame2,text = 'Depodaki Ürünü Düzenle',width=20,height=2,bg='light steel blue',command = lambda: editFrame(inventory_frame,inventory_frame2,edit_frame,add_button,remove_button,edit_button,editBack_item_button))
edit_button.place(x=120,y=300)
global excel_button
excel_button = Button(inventory_frame,text = 'Excele Aktar',width=20,height=2,bg = 'cadet blue',command= lambda: export("local"))
excel_button.place(x=650,y=545)
#Filter system of inventory screen
global category_entry,filter_button,filter_cancel
category_label = Label(inventory_frame,text = 'Ürün İsmi Giriniz: ')
category_label.place(x=30,y=555)
category_entry = Entry(inventory_frame,width = 25)
category_entry.place(x=140,y=557)
filter_button = Button(inventory_frame,text = 'Filtrele',width=20,height=2,bg='cadet blue',command=filter)
filter_button.place(x=350,y=545)
filter_cancel = Button(inventory_frame,text = 'X',width=2,height=2,bg='salmon',command=returnTable)
filter_cancel.place(x=520,y=545)
filter_cancel['state'] = DISABLED
## Second frame, adding product
global registered_item_button
global notregistered_item_frame
notregistered_item_frame = Frame(add_frame,width=400,height=442,highlightbackground='black',highlightthickness=1,bg= "LavenderBlush2")
## Adding nonregistered product
global malzeme, malzeme_metin, olcu, aciklama, miktar, artma
malzeme = Entry(notregistered_item_frame)
malzeme_metin = Entry(notregistered_item_frame)
miktar = Entry(notregistered_item_frame,validate="key")
miktar['validatecommand'] = (miktar.register(testVal),'%P','%d')
olcu = Entry(notregistered_item_frame)
aciklama = Entry(notregistered_item_frame)
artma = Entry(notregistered_item_frame,width=10,validate="key")
artma['validatecommand'] = (artma.register(testVal),'%P','%d')
global add_notregistered_button, back_button, clear_button, increase_button
add_notregistered_button = Button(notregistered_item_frame,text="Ekle",width = 10,command=addNotRegisteredItem)
back_button = Button(notregistered_item_frame,text="Geri",width = 10,command=backToRegister)
clear_button = Button(notregistered_item_frame,text="Temizle",width = 10,command=clear)
increase_button = Button(notregistered_item_frame,text="Seçili Ürünü Arttır",width = 15,command=increase)
editBack_item_button = Button(edit_frame,text ='Geri',width = 10, height =1,bg="light steel blue",command = lambda: back(add_button,remove_button,edit_button,add_frame,remove_frame,edit_frame))
## Deleting and adding registered product to registered list from inventory.
global notregistered_removeitem_button
global registered_removeitem_button
notregistered_removeitem_button = Button(remove_frame,text='Ürün Sil',width=15,height=2,bg="gray",command = removeNotRegistered)
registered_removeitem_button = Button(inventory_frame2,text="Depodaki Ürünü Zimmetle",width=20,height=2,bg='light steel blue',command=removeRegistered)
registered_removeitem_button.place(x=120,y=150)
global notregistered_remove_frame
global registered_remove_frame
notregistered_remove_frame = Frame(remove_frame,width=400,height=442,highlightbackground='black',highlightthickness=1,bg="LavenderBlush2")
registered_remove_frame = Frame(remove_frame,width=400,height=442,highlightbackground='black',highlightthickness=1,bg="LavenderBlush2")
global malzemey,miktary,aciklamay,miktary2,sec,ekley,geriy,temizley,sec2,vereny,alany,tarihy,vereny2,alany2,tarihy2,ekley2
global smalzeme,smalzeme_metin,solcu,saciklama
smalzeme = Label(registered_remove_frame,text="",bg="LavenderBlush2")
smalzeme_metin = Label(registered_remove_frame,text="",bg="LavenderBlush2")
solcu = Label(registered_remove_frame,text="",bg="LavenderBlush2")
malzemey = Entry(registered_remove_frame)
miktary = Entry(registered_remove_frame,validate="key")
miktary['validatecommand'] = (miktary.register(testVal),'%P','%d')
aciklamay = Entry(registered_remove_frame)
vereny = Entry(registered_remove_frame)
alany = Entry(registered_remove_frame)
tarihy = Entry(registered_remove_frame)
miktary2 = Entry(registered_remove_frame,validate="key")
miktary2['validatecommand'] = (miktary2.register(testVal),'%P','%d')
saciklama = Entry(registered_remove_frame)
vereny2 = Entry(registered_remove_frame)
alany2 = Entry(registered_remove_frame)
tarihy2 = Entry(registered_remove_frame)
sec = Button(registered_remove_frame,text="Seç",width=10,command=selectRegistered)
ekley = Button(registered_remove_frame,text="Ekle",width=10,command=noRegister)
ekley2 = Button(registered_remove_frame,text="Ekle",width=10,command=selectRegister)
geriy = Button(registered_remove_frame,text="Geri",width=10,command=backagain)
temizley = Button(registered_remove_frame,text="Temizle",width=10,command=clearagain)
global malzeme_no, sayi, sayi2, hurdaaciklama,hurdaaciklama2
malzeme_no = Entry(notregistered_remove_frame)
sayi = Entry(notregistered_remove_frame,validate="key")
sayi['validatecommand'] = (sayi.register(testVal),'%P','%d')
hurdaaciklama = Entry(notregistered_remove_frame)
sayi2 = Entry(notregistered_remove_frame,validate="key")
sayi2['validatecommand'] = (sayi2.register(testVal),'%P','%d')
hurdaaciklama2 = Entry(notregistered_remove_frame)
global remove_notregistered, remove_notregistered2, geri,clear_remove2
remove_notregistered = Button(notregistered_remove_frame,text="Çıkar",width=10,command=removeNotRegisteredItem)
remove_notregistered2 = Button(notregistered_remove_frame,text="Seçili Ürünü Çıkar",width=15,command=decrease)
geri = Button(notregistered_remove_frame,text="Geri",width=10,command=backRemoveRegister)
clear_remove2 = Button(notregistered_remove_frame,text="Temizle",width=10,command=clear_remove)
## editing nonregistered product
global notregistered_edit_frame
global registered_edit_frame
global notregistered_edit_button
global registered_edit_button
notregistered_edit_frame =Frame(edit_frame,width=400,height=440,bg="LavenderBlush2")
registered_edit_frame = Frame(edit_frame,width=400,height=440,bg="LavenderBlush2")
notregistered_edit_button = Button(edit_frame,text="Malzeme No'ya Göre",width=15,height=2,bg="light steel blue",command=no)
registered_edit_button = Button(edit_frame,text="Seçilen Ürüne Göre",width=15,height=2,bg="light steel blue",command=selectedEdit)
global malzeme_no1,malzeme_no2,malzeme_metin2,miktar2,olcu2,aciklama2
malzeme_no1 = Entry(notregistered_edit_frame)
malzeme_no2 = Entry(notregistered_edit_frame)
malzeme_metin2 = Entry(notregistered_edit_frame)
miktar2 = Entry(notregistered_edit_frame,validate="key")
miktar2['validatecommand'] = (miktar2.register(testVal),'%P','%d')
olcu2 = Entry(notregistered_edit_frame)
aciklama2 = Entry(notregistered_edit_frame)
global searchB,editB,backB,clearB
searchB = Button(notregistered_edit_frame,text="Bul",width=10,command=search)
editB = Button(notregistered_edit_frame,text="Düzenle",width=10,command=edit1)
editB['state'] = DISABLED
backB = Button(notregistered_edit_frame,text="Geri",width=10,command=backToEdit)
clearB = Button(notregistered_edit_frame,text="Temizle",width=10,command=clearEdit)
global malzeme_no3,malzeme_metin3,miktar3,olcu3,aciklama3
malzeme_no3 = Entry(registered_edit_frame)
malzeme_metin3 = Entry(registered_edit_frame)
miktar3 = Entry(registered_edit_frame,validate="key")
miktar3['validatecommand'] = (miktar3.register(testVal),'%P','%d')
olcu3 = Entry(registered_edit_frame)
aciklama3 = Entry(registered_edit_frame)
global searchB2,editB2,backB2,clearB2
searchB2 = Button(registered_edit_frame,text="Seç",width=10,command=findSelected)
editB2 = Button(registered_edit_frame,text="Düzenle",width=10,command=edit2)
editB2['state'] = DISABLED
backB2 = Button(registered_edit_frame,text="Geri",width=10,command=backEdit)
clearB2 = Button(registered_edit_frame,text="Temizle",width=10,command=clearEdit2)
############################################################################################################
################################################# Registered product List
global register_select
register_select = Button(window,text = "Zimmet Listesi",width=11,bg="white",command=lambda:showRegister(inventory_frame,inventory_frame2,register_frame,register_frame2))
register_select.place(x=1150,y=30)
#frames of registered product list
register_frame = Frame(window,width=1050,height=600,highlightbackground='black',highlightthickness=3)
register_frame2 = Frame(window,highlightbackground='black',width=250,height=450,bg ="lavender")
global remove_product,edit_product,back_product
#buttons of registered product list
remove_product = Button(register_frame2,text="Ürün Sil",width=15,height=2,bg = 'light steel blue',command=removeRegister)
back_product = Button(register_frame2,text="Ürünü Depoya Geri Al",width=18,height=2,bg = 'light steel blue',command=backInventory)
edit_product = Button(register_frame2,text="Ürün Düzenle",width=15,height=2,bg = 'light steel blue',command=editRegister)
# Edit part of registered product list
global malzB,secB,geriB
global remove_register_frame,edit_register_frame,back_register_frame
remove_register_frame = Frame(register_frame2,width=245,height=445,highlightbackground='black',highlightthickness=1,bg="LavenderBlush2")
edit_register_frame = Frame(register_frame2,width=245,height=445,highlightbackground='black',highlightthickness=1,bg="LavenderBlush2")
back_register_frame = Frame(register_frame2,width=245,height=445,highlightbackground='black',highlightthickness=1,bg="LavenderBlush2")
global malzNo_frame, sec_Frame
malzNo_frame = Frame(edit_register_frame,width=243,height=443,bg="LavenderBlush2")
sec_Frame = Frame(edit_register_frame,width=243,height=443,bg="LavenderBlush2")
malzB = Button(edit_register_frame,text="Malzeme No'ya Göre",width=18,height=2,bg = 'light steel blue',command=malzNo)
secB = Button(edit_register_frame,text="Seçilen Ürüne Göre",width=18,height=2,bg = 'light steel blue',command=sec_fr)
geriB = Button(edit_register_frame,text="Geri",width=15,height=1,bg = 'light steel blue',command=backRegis)
## search product id to edit registered product.
global malzemeq,malzemeq2,malzeme_metinq,miktarq,olcuq,verenq,alanq,tarihq,aciklamaq
global bulq,duzenleq,geriq,temizleq
malzemeq = Entry(malzNo_frame)
malzemeq2 = Entry(malzNo_frame)
malzeme_metinq = Entry(malzNo_frame)
miktarq = Entry(malzNo_frame,validate="key")
miktarq['validatecommand'] = (miktarq.register(testVal),'%P','%d')
olcuq = Entry(malzNo_frame)
verenq = Entry(malzNo_frame)
alanq = Entry(malzNo_frame)
tarihq = Entry(malzNo_frame)
aciklamaq = Entry(malzNo_frame)
bulq = Button(malzNo_frame,text="Bul",width = 10,command=searchRegist)
duzenleq = Button(malzNo_frame,text="Düzenle",width = 10,command=edit3)
geriq = Button(malzNo_frame,text="Geri",width = 10,command=backEditto)
temizleq = Button(malzNo_frame,text="Temizle",width = 10,command=clearEditto)
duzenleq['state'] = DISABLED
## select product to edit registered product.
global malzemet,malzemet2,malzeme_metint,miktart,olcut,verent,alant,tariht,aciklamat
global sect,duzenlet,gerit,temizlet
malzemet = Entry(sec_Frame)
malzeme_metint = Entry(sec_Frame)
miktart = Entry(sec_Frame,validate="key")
miktart['validatecommand'] = (miktart.register(testVal),'%P','%d')
olcut= Entry(sec_Frame)
verent = Entry(sec_Frame)
alant = Entry(sec_Frame)
tariht = Entry(sec_Frame)
aciklamat = Entry(sec_Frame)
sect = Button(sec_Frame,text="Seç",width = 10,command=selectReg)
duzenlet = Button(sec_Frame,text="Düzenle",width = 10,command=edit4)
gerit = Button(sec_Frame,text="Geri",width = 10,command=backEditto2)
temizlet = Button(sec_Frame,text="Temizle",width = 10,command=clearEditto2)
duzenlet['state'] = DISABLED
# export button
global excel_button2
excel_button2 = Button(register_frame,text = 'Excele Aktar',width=20,height=2,bg = 'cadet blue',command= lambda: export2("local"))
excel_button2.place(x=650,y=545)
# filtering options
global control_menu
control_menu = StringVar(register_frame)
option = ("Ürün: ","Kişi: ")
control_menu.set("Seç:")
category_label2 = Label(register_frame,text="Kategori Seç: ")
category_label2.place(x=45,y=541)
option_menu = OptionMenu(register_frame,control_menu,*option)
option_menu.config(bg="cadet blue")
option_menu["menu"].config(bg="white")
option_menu.place(x=45,y=560)
global category_entry2,filter_button2,filter_cancel2
category_entry2 = Entry(register_frame,width = 25)
category_entry2.place(x=140,y=565)
# filter system of registered product list
filter_button2 = Button(register_frame,text = 'Filtrele',width=20,height=2,bg='cadet blue',command=filter2)
filter_button2.place(x=350,y=545)
filter_cancel2 = Button(register_frame,text = 'X',width=2,height=2,bg='salmon',command= returnTable2)
filter_cancel2.place(x=520,y=545)
filter_cancel2['state'] = DISABLED
# removing registered product
global malzemer,miktarr,miktarr2,cikarr,cikarr2,gerir,temizler,hurdaaciklama3,hurdaaciklama4
malzemer = Entry(remove_register_frame)
miktarr = Entry(remove_register_frame,validate="key")
miktarr['validatecommand'] = (miktarr.register(testVal),'%P','%d')
hurdaaciklama3 = Entry(remove_register_frame)
miktarr2 = Entry(remove_register_frame,validate="key")
miktarr2['validatecommand'] = (miktarr2.register(testVal),'%P','%d')
hurdaaciklama4 = Entry(remove_register_frame)
cikarr = Button(remove_register_frame,text="Çıkar",width = 10,command=deleteReg)
cikarr2 = Button(remove_register_frame,text="Seçili Ürünü Çıkar",width = 15,command=deleteSelectedReg)
gerir = Button(remove_register_frame,text="Geri",width = 10,command=backReg)
temizler = Button(remove_register_frame,text="Temizle",width = 10,command=clearReg)
global malzeme0,miktar0,aciklama0,veren0,alan0,miktar02,aciklama02
global malzeme0x, malzeme_metin0x,olcu0x,veren0x,alan0x,tarih0x
global ekle0,sec0,ekle02,geri02,temizle02
malzeme0 = Entry(back_register_frame)
miktar0 = Entry(back_register_frame,validate="key")
miktar0['validatecommand'] = (miktar0.register(testVal),'%P','%d')
aciklama0 = Entry(back_register_frame)
veren0 = Entry(back_register_frame)
alan0 = Entry(back_register_frame)
miktar02 = Entry(back_register_frame,validate="key")
miktar02['validatecommand'] = (miktar02.register(testVal),'%P','%d')
aciklama02 = Entry(back_register_frame)
# adding registered product back to inventory as nonregisterede product
malzeme0x = Label(back_register_frame,text="",bg="LavenderBlush2")
malzeme_metin0x = Label(back_register_frame,text="",bg="LavenderBlush2")
olcu0x = Label(back_register_frame,text="",bg="LavenderBlush2")
veren0x = Label(back_register_frame,text="",bg="LavenderBlush2")
alan0x = Label(back_register_frame,text="",bg="LavenderBlush2")
tarih0x = Label(back_register_frame,text="",bg="LavenderBlush2")
ekle0 = Button(back_register_frame,text="Ekle",width = 10,command=addBack)
sec0 = Button(back_register_frame,text="Seç",width = 10,command=selecting)
ekle02 = Button(back_register_frame,text="Ekle",width = 8,command=addBack2)
geri02 = Button(back_register_frame,text="Geri",width = 8,command = backMain)
temizle02 = Button(back_register_frame,text="Temizle",width = 8,command=clearAll)
ekle02['state'] = DISABLED
## JUNK LIST
global junk_select
junk_select = Button(window,text= "Hurda Listesi",width = 10,bg = "white",command=lambda : showJunk(inventory_frame,inventory_frame2,register_frame,register_frame2))
junk_select.place(x=1245,y=30)
global junk_frame
junk_frame = Frame(window,width=1050,height=600,highlightbackground='black',highlightthickness=3)
global category_entry3,filter_button3,filter_cancel3
category_label3 = Label(junk_frame,text = 'Ürün İsmi Giriniz: ')
category_label3.place(x=30,y=555)
category_entry3 = Entry(junk_frame,width = 25)
category_entry3.place(x=140,y=557)
filter_button3 = Button(junk_frame,text = 'Filtrele',width=20,height=2,bg='cadet blue',command=filter3)
filter_button3.place(x=350,y=545)
filter_cancel3 = Button(junk_frame,text = 'X',width=2,height=2,bg='salmon',command = returnTable3)
filter_cancel3.place(x=520,y=545)
global excel_button3
excel_button3 = Button(junk_frame,text = 'Excele Aktar',width=20,height=2,bg="cadet blue",command=lambda: export3("local"))
excel_button3.place(x=650,y=545)
filter_cancel3['state'] = DISABLED
global clearallbutton
clearallbutton = Button(junk_frame,text = 'Listeyi Temizle',width=15,height=2,bg="salmon",command=removeAll)
clearallbutton.place(x=910,y=545)
########################################################################### TABLE - DATA ######################################################
# Table properties
style = ttk.Style()
style.theme_use("default")
style.configure("Treeview",
background="azure",
foreground="black",
rowheight=51,
fieldbackground="azure",
font = (None,8)
)
style.map('Treeview',
background=[('selected', 'blue')])
#creating three tables which are inventory list, registered product list and junk list.
global table,table2,table3
table = ttk.Treeview(inventory_frame, selectmode="browse")
table2 = ttk.Treeview(register_frame, selectmode="browse")
table3 = ttk.Treeview(junk_frame, selectmode="browse")
#scrollbars of tables
scrollbar = ttk.Scrollbar(inventory_frame, orient="vertical", command=table.yview)
scrollbar.place(x=930, y=0, height=540)
scrollbar2 = ttk.Scrollbar(inventory_frame, orient="horizontal", command=table.xview)
scrollbar2.place(x=0, y=524, width=930)
scrollbar3 = ttk.Scrollbar(register_frame, orient="vertical", command=table2.yview)
scrollbar3.place(x=1030, y=0, height=542)
scrollbar4 = ttk.Scrollbar(register_frame, orient="horizontal", command=table2.xview)
scrollbar4.place(x=0, y=527, width=1030)
scrollbar5 = ttk.Scrollbar(junk_frame, orient="vertical", command=table3.yview)
scrollbar5.place(x=1030, y=0, height=542)
scrollbar6 = ttk.Scrollbar(junk_frame, orient="horizontal", command=table3.xview)
scrollbar6.place(x=0, y=527, width=1030)
table.configure(yscrollcommand=scrollbar.set,xscrollcommand=scrollbar2.set)
table2.configure(yscrollcommand=scrollbar3.set,xscrollcommand=scrollbar4.set)
table3.configure(yscrollcommand=scrollbar5.set,xscrollcommand=scrollbar6.set)
table.place(x=0,y=0)
table2.place(x=0,y=0)
table3.place(x=0,y=0)
#load data.
importExcel()
importExcel2()
importExcel3()
global p,p2,p3
p = 0
p2 = 0
p3 = 0
# saving before quiting program.
window.protocol("WM_DELETE_WINDOW",beforeExit)
window.mainloop()
main()
| 162,093 | 57,488 |
##################################################################################################
# Copyright (c) 2012 Brett Dixon
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in
# the Software without restriction, including without limitation the rights to use,
# copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
# Software, and to permit persons to whom the Software is furnished to do so,
# subject to the following conditions:
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
# FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
# COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
# IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
##################################################################################################
import argparse
import datetime
import json
from optparse import make_option
from django.core.management.base import BaseCommand
from django.utils import timezone
from frog.models import ReleaseNotes
class Command(BaseCommand):
help = 'Add a new ReleaseNote'
def add_arguments(self, parser):
parser.add_argument('content')
parser.add_argument('-d', '--date', default=None, help='In the format %d/%m/%Y or 31/01/2017 for January 31, 2017')
def handle(self, *args, **options):
date = timezone.now()
datestr = options.get('date')
if datestr:
date = datetime.datetime.strptime(datestr, '%d/%m/%Y')
note = ReleaseNotes(notes=options['content'].replace('\\\\n', '\\').replace('\\n', '\n'))
note.save()
note.date = date
note.save()
self.stdout.write('Added {}'.format(note))
| 2,164 | 646 |
# corpus.exceptions
# Custom exceptions for corpus handling.
#
# Author: Benjamin Bengfort <bbengfort@districtdatalabs.com>
# Created: Mon Jul 18 09:57:26 2016 -0400
#
# Copyright (C) 2016 District Data Labs
# For license information, see LICENSE.txt
#
# ID: exceptions.py [63935bc] benjamin@bengfort.com $
"""
Custom exceptions for corpus handling.
"""
##########################################################################
## Corpus Exceptions
##########################################################################
class CorpusException(Exception):
"""
Something went wrong in the corpus app.
"""
pass
class BitlyAPIError(CorpusException):
"""
Something went wrong trying to shorten a url.
"""
pass
class FetchError(CorpusException):
"""
Something went wrong trying to fetch a url using requests.
"""
pass
class NLTKError(CorpusException):
"""
Something went wrong when using NLTK.
"""
pass
| 977 | 293 |
import glob
import os
import sys
from pprint import pprint
from typing import List
from lark import Lark
from protogen.grammar.transformer import PGTransformer
from protogen.util import PGFile
class PGParser(object):
def __init__(self, inputs: List[str],
syntaxPath: str = 'grammar/proto_gen.lark'):
# Clean up and list input files.
self._files = {}
for items in inputs:
for item in glob.glob(items):
self._files[item] = None # Add placeholder in dict for parsing
if len(self._files) == 0:
print('No valid files were specified.')
print('Note: a glob pattern is acceptible for multiple files.\n')
print('Example:\n *.protogen\n')
print('You can also specify more than one file, '
'separated by spaces.\n')
print('Example:\n a.protogen b.protogen c.protogen')
sys.exit(1)
with open(os.path.join(os.path.dirname(__file__),
syntaxPath), 'r') as file:
grammar = file.read()
self._parser = Lark(grammar=grammar, parser='lalr',
propagate_positions=True)
def parse(self):
for item in self._files:
try:
with open(item, 'r') as data:
self._files[item] = self._parser.parse(data.read())
# MyTransformer().transform(parser._files[item])
except IsADirectoryError as e:
print('You must specify files. For multiple files in a '
'directory, a glob pattern may be used.')
print('Example: directory/*.protogen')
sys.exit(2)
def transform(self):
self._trees = {}
for file in self._files:
self._trees[file] = PGTransformer().transform(self._files[file])
# pprint(self._trees[file])
outfiles = []
for tree in self._trees:
# len(_files) == len(_trees) AND order == 'same'
outfiles.append(PGFile(tree, self._trees[tree]))
return outfiles
def display(self):
for item in self._files:
print("--- BEGIN FILE: {} ---".format(item))
print(self._files[item].pretty())
print("--- END FILE: {} ---".format(item))
def _display(self):
for item in self._files:
print("--- BEGIN FILE: {} ---".format(item))
print(self._files[item])
print("--- END FILE: {} ---".format(item))
def pretty(self):
pprint(self._files)
| 2,617 | 723 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""Set up the Impala shell python package."""
import datetime
import os
import re
import sys
import time
from impala_shell import impala_build_version
from setuptools import find_packages, setup
from textwrap import dedent
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
def parse_requirements(requirements_file='requirements.txt'):
"""
Parse requirements from the requirements file, stripping comments.
Args:
requirements_file: path to a requirements file
Returns:
a list of python packages
"""
lines = []
with open(requirements_file) as reqs:
for _ in reqs:
line = _.split('#')[0]
if line.strip():
lines.append(line)
return lines
def get_version():
"""Generate package version string when calling 'setup.py'.
When setup.py is being used to CREATE a distribution, e.g., via setup.py sdist
or setup.py bdist, then use the output from impala_build_version.get_version(),
and append modifiers as specified by the RELEASE_TYPE and OFFICIAL environment
variables. By default, the package created will be a dev release, designated
by timestamp. For example, if get_version() returns the string 3.0.0-SNAPSHOT,
the package version may be something like 3.0.0.dev20180322154653.
It's also possible set an evironment variable for BUILD_VERSION to override the
default build value returned from impala_build_version.get_version().
E.g., to specify an offical 3.4 beta 2 release (3.4b2), one would call:
BUILD_VERSION=3.4 RELEASE_TYPE=b2 OFFICIAL=true python setup.py sdist
The generated version string will be written to a version.txt file to be
referenced when the distribution is installed.
When setup.py is invoked during installation, e.g., via pip install or
setup.py install, read the package version from the version.txt file, which
is presumed to contain a single line containing a valid PEP-440 version string.
The file should have been generated when the distribution being installed was
created. (Although a version.txt file can also be created manually.)
See https://www.python.org/dev/peps/pep-0440/ for more info on python
version strings.
Returns:
A package version string compliant with PEP-440
"""
version_file = os.path.join(CURRENT_DIR, 'version.txt')
if not os.path.isfile(version_file):
# If setup.py is being executed to create a distribution, e.g., via setup.py
# sdist or setup.py bdist, then derive the version and WRITE the version.txt
# file that will later be used for installations.
if os.getenv('BUILD_VERSION') is not None:
package_version = os.getenv('BUILD_VERSION')
else:
version_match = re.search('\d+\.\d+\.\d+', impala_build_version.get_version())
if version_match is None:
sys.exit('Unable to acquire Impala version.')
package_version = version_match.group(0)
# packages can be marked as alpha, beta, or rc RELEASE_TYPE
release_type = os.getenv('RELEASE_TYPE')
if release_type:
if not re.match('(a|b|rc)\d+?', release_type):
msg = """\
RELEASE_TYPE \'{0}\' does not conform to any PEP-440 release format:
aN (for alpha releases)
bN (for beta releases)
rcN (for release candidates)
where N is the number of the release"""
sys.exit(dedent(msg).format(release_type))
package_version += release_type
# packages that are not marked OFFICIAL have ".dev" + a timestamp appended
if os.getenv('OFFICIAL') != 'true':
epoch_t = time.time()
ts_fmt = '%Y%m%d%H%M%S'
timestamp = datetime.datetime.fromtimestamp(epoch_t).strftime(ts_fmt)
package_version = '{0}.dev{1}'.format(package_version, timestamp)
with open('version.txt', 'w') as version_file:
version_file.write(package_version)
else:
# If setup.py is being invoked during installation, e.g., via pip install
# or setup.py install, we expect a version.txt file from which to READ the
# version string.
with open(version_file) as version_file:
package_version = version_file.readline()
return package_version
setup(
name='impala_shell',
python_requires='>2.6, <3.0.0',
version=get_version(),
description='Impala Shell',
long_description_content_type='text/markdown',
long_description=open('README.md').read(),
author="Impala Dev",
author_email='dev@impala.apache.org',
url='https://impala.apache.org/',
license='Apache Software License',
packages=find_packages(),
include_package_data=True,
install_requires=parse_requirements(),
entry_points={
'console_scripts': [
'impala-shell = impala_shell.impala_shell:impala_shell_main'
]
},
classifiers=[
'Development Status :: 5 - Production/Stable',
'Environment :: Console',
'Intended Audience :: Developers',
'Intended Audience :: End Users/Desktop',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: Apache Software License',
'Operating System :: MacOS :: MacOS X',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python :: 2 :: Only',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Topic :: Database :: Front-Ends'
]
)
| 6,145 | 1,868 |
from common.mod import Mod | 26 | 7 |
__author__ = 'baohua'
from subprocess import PIPE, Popen
from tripled.common.constants import NODE_ROLES
class Node(object):
"""
An instance of the server in the stack.
"""
def __init__(self, ip, role):
self.ip = ip
self.role = NODE_ROLES.get(role, NODE_ROLES['compute'])
def is_reachable(self, dst):
"""
Return whether the dst is reachable from the node.
>>> Node().is_reachable(Node('127.0.0.1'))
True
>>> Node().is_reachable(Node('169.254.254.254'))
False
"""
cmd = 'ping %s -c 3 -W 2' % dst.ip
output, error = Popen(cmd, stdout=PIPE, stderr=PIPE, shell=True).communicate()
if not error and output and '0% packet loss' in output:
return True
else:
return False
class Control(Node):
"""
An instance of the control node in the stack.
"""
def __init__(self, ip='127.0.0.1'):
super(Control, self).__init__(ip, role='control')
class Network(Node):
"""
An instance of the control node in the stack.
"""
def __init__(self, ip='127.0.0.1'):
super(Network, self).__init__(ip, role='network')
class Compute(Node):
"""
An instance of the control node in the stack.
"""
def __init__(self, ip='127.0.0.1'):
super(Compute, self).__init__(ip, role='compute')
if __name__ == '__main__':
import doctest
doctest.testmod()
| 1,453 | 501 |
#! /usr/bin/env python
print "OpenCV Python version of convexhull"
# import the necessary things for OpenCV
import cv2.cv as cv
# to generate random values
import random
# how many points we want at max
_MAX_POINTS = 100
if __name__ == '__main__':
# main object to get random values from
my_random = random.Random ()
# create the image where we want to display results
image = cv.CreateImage ( (500, 500), 8, 3)
# create the window to put the image in
cv.NamedWindow ('hull', cv.CV_WINDOW_AUTOSIZE)
while True:
# do forever
# get a random number of points
count = my_random.randrange (0, _MAX_POINTS) + 1
# initialisations
points = []
for i in range (count):
# generate a random point
points.append ( (
my_random.randrange (0, image.width / 2) + image.width / 4,
my_random.randrange (0, image.width / 2) + image.width / 4
))
# compute the convex hull
storage = cv.CreateMemStorage(0)
hull = cv.ConvexHull2 (points, storage, cv.CV_CLOCKWISE, 1)
# start with an empty image
cv.SetZero (image)
# draw all the points as circles in red
for i in range (count):
cv.Circle (image, points [i], 2,
(0, 0, 255, 0),
cv.CV_FILLED, cv.CV_AA, 0)
# Draw the convex hull as a closed polyline in green
cv.PolyLine(image, [hull], 1, cv.RGB(0,255,0), 1, cv.CV_AA)
# display the final image
cv.ShowImage ('hull', image)
# handle events, and wait a key pressed
k = cv.WaitKey (0) % 0x100
if k == 27:
# user has press the ESC key, so exit
break
cv.DestroyAllWindows()
| 1,814 | 594 |
import torch
import torch.nn as nn
class WN(torch.nn.Module):
"""
WN block for affine coupling layer. Actual version
"""
def __init__(self, num_channels, mel_channels, n_layers=8, residual_channels=512,
gate_channels=256, skip_channels=256):
"""
Parameters
----------
num_channels : int
Number of x_a channels
mel_channels : int
Number of spectrogram (condition c) channels
----------
Parameters from original paper
----------
n_layers : int
The depth of WN (default : 8)
residual_channels : int
Number of chanels used by residual connections (default : 512)
gate_channels : int
Number of filters and gates channels (default : 256)
skip_channels : int
Number of chanels used by skip connections
"""
super(WN, self).__init__()
self.n_layers = n_layers
self.num_channels = num_channels
self.residual_channels = residual_channels
self.gate_channels = gate_channels
self.skip_channels = skip_channels
self.mel_channels = mel_channels
self.dilations_list = [2**i for i in range(n_layers)]
self.conv_input = nn.Conv1d(in_channels=num_channels, out_channels=residual_channels, kernel_size=1)
self.conv_filter = nn.ModuleList([
torch.nn.utils.weight_norm(nn.Conv1d(
in_channels=residual_channels,
out_channels=gate_channels,
kernel_size=3,
dilation=d,
padding=(2 * d // 2)
), name='weight') for d in self.dilations_list])
self.conv_gate = nn.ModuleList([
torch.nn.utils.weight_norm(nn.Conv1d(
in_channels=residual_channels,
out_channels=gate_channels,
kernel_size=3,
dilation=d,
padding=(2 * d // 2)
), name='weight') for d in self.dilations_list])
self.conv_mel = nn.ModuleList([
torch.nn.utils.weight_norm(nn.Conv1d(
in_channels=mel_channels,
out_channels=gate_channels * 2,
kernel_size=1
), name='weight') for _ in range(len(self.dilations_list))])
self.conv_residual = nn.ModuleList([
torch.nn.utils.weight_norm(nn.Conv1d(
in_channels=gate_channels,
out_channels=residual_channels,
kernel_size=1
), name='weight') for _ in range(len(self.dilations_list) - 1)])
self.conv_skip = nn.ModuleList([
torch.nn.utils.weight_norm(nn.Conv1d(
in_channels=gate_channels,
out_channels=skip_channels,
kernel_size=1
), name='weight') for _ in range(len(self.dilations_list))])
self.conv_out = nn.Conv1d(
in_channels=skip_channels,
out_channels=2 * num_channels, # log s, t
kernel_size=1)
self.conv_out.weight.data.uniform_(-0.0001, 0.0001)
self.conv_out.bias.data.uniform_(-0.0001, 0.0001)
def forward(self, x_a, c):
"""
Parameters
----------
x_a : FloatTensor of size batch_size * num_channels * T
Unchangable part of embedding
c : FloatTensor of size batch_size * mel_channels * T
Upsampled mel-spectrogram
"""
assert x_a.size(2) == c.size(2) # Проверить, что спектрограмме не забыли сделать upsampling
x_acc = 0
x = self.conv_input(x_a)
for i in range(len(self.dilations_list)):
x_filter = self.conv_filter[i](x)
x_gate = self.conv_gate[i](x)
c_proj = self.conv_mel[i](c)
x_filter = x_filter + c_proj[:, :self.gate_channels]
x_gate = x_gate + c_proj[:, self.gate_channels:]
x_gate = torch.sigmoid(x_gate)
x_filter = torch.tanh(x_filter)
x_filter_gate = x_gate * x_filter
x_skip = self.conv_skip[i](x_filter_gate)
if i != len(self.dilations_list) - 1:
x_res = self.conv_residual[i](x_filter_gate)
x = x + x_res
x_acc = x_acc + x_skip
return self.conv_out(x_acc)
class VanillaWN(torch.nn.Module):
"""
WN block for affine coupling layer.
"""
def __init__(self, num_channels, mel_channels, n_layers=4, residual_channels=128,
gate_channels=64, skip_channels=64, pre_channels=32):
"""
Parameters
----------
num_channels : int
Number of x_a channels
mel_channels : int
Number of spectrogram (condition c) channels
----------
Parameters from original paper
----------
n_layers : int
The depth of WN (default : 8)
residual_channels : int
Number of chanels used by residual connections (default : 512)
gate_channels : int
Number of filters and gates channels (default : 256)
skip_channels : int
Number of chanels used by skip connections
pre_channels : int
Number of channels in final non-linearity
"""
super(VanillaWN, self).__init__()
self.n_layers = n_layers
self.num_channels = num_channels
self.residual_channels = residual_channels
self.gate_channels = gate_channels
self.skip_channels = skip_channels
self.mel_channels = mel_channels
self.dilations_list = [2**i for i in range(n_layers)]
self.conv_input = nn.Conv1d(in_channels=num_channels, out_channels=residual_channels, kernel_size=1)
self.conv_filter = nn.ModuleList([
nn.Conv1d(
in_channels=residual_channels,
out_channels=gate_channels,
kernel_size=3,
dilation=d,
padding=(2 * d // 2)
) for d in self.dilations_list])
self.conv_gate = nn.ModuleList([
nn.Conv1d(
in_channels=residual_channels,
out_channels=gate_channels,
kernel_size=3,
dilation=d,
padding=(2 * d // 2)
) for d in self.dilations_list])
self.conv_mel = nn.ModuleList([
nn.Conv1d(
in_channels=mel_channels,
out_channels=gate_channels * 2,
kernel_size=1
) for _ in range(len(self.dilations_list))])
self.conv_residual = nn.ModuleList([
nn.Conv1d(
in_channels=gate_channels,
out_channels=residual_channels,
kernel_size=1
) for _ in range(len(self.dilations_list) - 1)])
self.conv_skip = nn.ModuleList([
nn.Conv1d(
in_channels=gate_channels,
out_channels=skip_channels,
kernel_size=1
) for _ in range(len(self.dilations_list))])
self.conv_out_1 = nn.Conv1d(
in_channels=skip_channels,
out_channels=pre_channels,
kernel_size=1)
self.conv_out_2 = nn.Conv1d(
in_channels=pre_channels,
out_channels=2 * num_channels,
kernel_size=1)
def forward(self, x_a, c):
"""
Parameters
----------
x_a : FloatTensor of size batch_size * num_channels * T
Unchangable part of embedding
c : FloatTensor of size batch_size * mel_channels * T
Upsampled mel-spectrogram
"""
assert x_a.size(2) == c.size(2) # Проверить, что спектрограмме не забыли сделать upsampling
x_acc = 0
x = self.conv_input(x_a)
for i in range(len(self.dilations_list)):
x_filter = self.conv_filter[i](x)
x_gate = self.conv_gate[i](x)
c_proj = self.conv_mel[i](c)
x_filter = x_filter + c_proj[:, :self.gate_channels]
x_gate = x_gate + c_proj[:, self.gate_channels:]
x_gate = torch.sigmoid(x_gate)
x_filter = torch.tanh(x_filter)
x_filter_gate = x_gate * x_filter
x_skip = self.conv_skip[i](x_filter_gate)
if i != len(self.dilations_list) - 1:
x_res = self.conv_residual[i](x_filter_gate)
x = x + x_res
x = x * 0.5**0.5
x_acc = x_acc + x_skip
return self.conv_out_2(torch.relu(self.conv_out_1(x_acc)))
| 8,912 | 2,885 |
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: mission_raw_server/mission_raw_server.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from . import mavsdk_options_pb2 as mavsdk__options__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='mission_raw_server/mission_raw_server.proto',
package='mavsdk.rpc.mission_raw_server',
syntax='proto3',
serialized_options=_b('\n\034io.mavsdk.mission_raw_serverB\025MissionRawServerProto'),
serialized_pb=_b('\n+mission_raw_server/mission_raw_server.proto\x12\x1dmavsdk.rpc.mission_raw_server\x1a\x14mavsdk_options.proto\"!\n\x1fSubscribeIncomingMissionRequest\"\xa1\x01\n\x17IncomingMissionResponse\x12\x44\n\x0emission_result\x18\x01 \x01(\x0b\x32,.mavsdk.rpc.mission_raw_server.MissionResult\x12@\n\x0cmission_plan\x18\x02 \x01(\x0b\x32*.mavsdk.rpc.mission_raw_server.MissionPlan\"$\n\"SubscribeCurrentItemChangedRequest\"^\n\x1a\x43urrentItemChangedResponse\x12@\n\x0cmission_item\x18\x01 \x01(\x0b\x32*.mavsdk.rpc.mission_raw_server.MissionItem\"\x1a\n\x18SubscribeClearAllRequest\"&\n\x10\x43learAllResponse\x12\x12\n\nclear_type\x18\x01 \x01(\r\"\x1f\n\x1dSetCurrentItemCompleteRequest\" \n\x1eSetCurrentItemCompleteResponse\"\xd8\x01\n\x0bMissionItem\x12\x0b\n\x03seq\x18\x01 \x01(\r\x12\r\n\x05\x66rame\x18\x02 \x01(\r\x12\x0f\n\x07\x63ommand\x18\x03 \x01(\r\x12\x0f\n\x07\x63urrent\x18\x04 \x01(\r\x12\x14\n\x0c\x61utocontinue\x18\x05 \x01(\r\x12\x0e\n\x06param1\x18\x06 \x01(\x02\x12\x0e\n\x06param2\x18\x07 \x01(\x02\x12\x0e\n\x06param3\x18\x08 \x01(\x02\x12\x0e\n\x06param4\x18\t \x01(\x02\x12\t\n\x01x\x18\n \x01(\x05\x12\t\n\x01y\x18\x0b \x01(\x05\x12\t\n\x01z\x18\x0c \x01(\x02\x12\x14\n\x0cmission_type\x18\r \x01(\r\"P\n\x0bMissionPlan\x12\x41\n\rmission_items\x18\x01 \x03(\x0b\x32*.mavsdk.rpc.mission_raw_server.MissionItem\"1\n\x0fMissionProgress\x12\x0f\n\x07\x63urrent\x18\x01 \x01(\x05\x12\r\n\x05total\x18\x02 \x01(\x05\"\xa4\x03\n\rMissionResult\x12\x43\n\x06result\x18\x01 \x01(\x0e\x32\x33.mavsdk.rpc.mission_raw_server.MissionResult.Result\x12\x12\n\nresult_str\x18\x02 \x01(\t\"\xb9\x02\n\x06Result\x12\x12\n\x0eRESULT_UNKNOWN\x10\x00\x12\x12\n\x0eRESULT_SUCCESS\x10\x01\x12\x10\n\x0cRESULT_ERROR\x10\x02\x12!\n\x1dRESULT_TOO_MANY_MISSION_ITEMS\x10\x03\x12\x0f\n\x0bRESULT_BUSY\x10\x04\x12\x12\n\x0eRESULT_TIMEOUT\x10\x05\x12\x1b\n\x17RESULT_INVALID_ARGUMENT\x10\x06\x12\x16\n\x12RESULT_UNSUPPORTED\x10\x07\x12\x1f\n\x1bRESULT_NO_MISSION_AVAILABLE\x10\x08\x12\"\n\x1eRESULT_UNSUPPORTED_MISSION_CMD\x10\x0b\x12\x1d\n\x19RESULT_TRANSFER_CANCELLED\x10\x0c\x12\x14\n\x10RESULT_NO_SYSTEM\x10\r2\xf6\x04\n\x17MissionRawServerService\x12\x96\x01\n\x18SubscribeIncomingMission\x12>.mavsdk.rpc.mission_raw_server.SubscribeIncomingMissionRequest\x1a\x36.mavsdk.rpc.mission_raw_server.IncomingMissionResponse\"\x00\x30\x01\x12\x9f\x01\n\x1bSubscribeCurrentItemChanged\x12\x41.mavsdk.rpc.mission_raw_server.SubscribeCurrentItemChangedRequest\x1a\x39.mavsdk.rpc.mission_raw_server.CurrentItemChangedResponse\"\x00\x30\x01\x12\x9b\x01\n\x16SetCurrentItemComplete\x12<.mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteRequest\x1a=.mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteResponse\"\x04\x80\xb5\x18\x01\x12\x81\x01\n\x11SubscribeClearAll\x12\x37.mavsdk.rpc.mission_raw_server.SubscribeClearAllRequest\x1a/.mavsdk.rpc.mission_raw_server.ClearAllResponse\"\x00\x30\x01\x42\x35\n\x1cio.mavsdk.mission_raw_serverB\x15MissionRawServerProtob\x06proto3')
,
dependencies=[mavsdk__options__pb2.DESCRIPTOR,])
_MISSIONRESULT_RESULT = _descriptor.EnumDescriptor(
name='Result',
full_name='mavsdk.rpc.mission_raw_server.MissionResult.Result',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='RESULT_UNKNOWN', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_SUCCESS', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_ERROR', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_TOO_MANY_MISSION_ITEMS', index=3, number=3,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_BUSY', index=4, number=4,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_TIMEOUT', index=5, number=5,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_INVALID_ARGUMENT', index=6, number=6,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_UNSUPPORTED', index=7, number=7,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_NO_MISSION_AVAILABLE', index=8, number=8,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_UNSUPPORTED_MISSION_CMD', index=9, number=11,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_TRANSFER_CANCELLED', index=10, number=12,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESULT_NO_SYSTEM', index=11, number=13,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=1028,
serialized_end=1341,
)
_sym_db.RegisterEnumDescriptor(_MISSIONRESULT_RESULT)
_SUBSCRIBEINCOMINGMISSIONREQUEST = _descriptor.Descriptor(
name='SubscribeIncomingMissionRequest',
full_name='mavsdk.rpc.mission_raw_server.SubscribeIncomingMissionRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=100,
serialized_end=133,
)
_INCOMINGMISSIONRESPONSE = _descriptor.Descriptor(
name='IncomingMissionResponse',
full_name='mavsdk.rpc.mission_raw_server.IncomingMissionResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='mission_result', full_name='mavsdk.rpc.mission_raw_server.IncomingMissionResponse.mission_result', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mission_plan', full_name='mavsdk.rpc.mission_raw_server.IncomingMissionResponse.mission_plan', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=136,
serialized_end=297,
)
_SUBSCRIBECURRENTITEMCHANGEDREQUEST = _descriptor.Descriptor(
name='SubscribeCurrentItemChangedRequest',
full_name='mavsdk.rpc.mission_raw_server.SubscribeCurrentItemChangedRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=299,
serialized_end=335,
)
_CURRENTITEMCHANGEDRESPONSE = _descriptor.Descriptor(
name='CurrentItemChangedResponse',
full_name='mavsdk.rpc.mission_raw_server.CurrentItemChangedResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='mission_item', full_name='mavsdk.rpc.mission_raw_server.CurrentItemChangedResponse.mission_item', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=337,
serialized_end=431,
)
_SUBSCRIBECLEARALLREQUEST = _descriptor.Descriptor(
name='SubscribeClearAllRequest',
full_name='mavsdk.rpc.mission_raw_server.SubscribeClearAllRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=433,
serialized_end=459,
)
_CLEARALLRESPONSE = _descriptor.Descriptor(
name='ClearAllResponse',
full_name='mavsdk.rpc.mission_raw_server.ClearAllResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='clear_type', full_name='mavsdk.rpc.mission_raw_server.ClearAllResponse.clear_type', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=461,
serialized_end=499,
)
_SETCURRENTITEMCOMPLETEREQUEST = _descriptor.Descriptor(
name='SetCurrentItemCompleteRequest',
full_name='mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=501,
serialized_end=532,
)
_SETCURRENTITEMCOMPLETERESPONSE = _descriptor.Descriptor(
name='SetCurrentItemCompleteResponse',
full_name='mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=534,
serialized_end=566,
)
_MISSIONITEM = _descriptor.Descriptor(
name='MissionItem',
full_name='mavsdk.rpc.mission_raw_server.MissionItem',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='seq', full_name='mavsdk.rpc.mission_raw_server.MissionItem.seq', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='frame', full_name='mavsdk.rpc.mission_raw_server.MissionItem.frame', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='command', full_name='mavsdk.rpc.mission_raw_server.MissionItem.command', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='current', full_name='mavsdk.rpc.mission_raw_server.MissionItem.current', index=3,
number=4, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='autocontinue', full_name='mavsdk.rpc.mission_raw_server.MissionItem.autocontinue', index=4,
number=5, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='param1', full_name='mavsdk.rpc.mission_raw_server.MissionItem.param1', index=5,
number=6, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='param2', full_name='mavsdk.rpc.mission_raw_server.MissionItem.param2', index=6,
number=7, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='param3', full_name='mavsdk.rpc.mission_raw_server.MissionItem.param3', index=7,
number=8, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='param4', full_name='mavsdk.rpc.mission_raw_server.MissionItem.param4', index=8,
number=9, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='x', full_name='mavsdk.rpc.mission_raw_server.MissionItem.x', index=9,
number=10, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='y', full_name='mavsdk.rpc.mission_raw_server.MissionItem.y', index=10,
number=11, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='z', full_name='mavsdk.rpc.mission_raw_server.MissionItem.z', index=11,
number=12, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mission_type', full_name='mavsdk.rpc.mission_raw_server.MissionItem.mission_type', index=12,
number=13, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=569,
serialized_end=785,
)
_MISSIONPLAN = _descriptor.Descriptor(
name='MissionPlan',
full_name='mavsdk.rpc.mission_raw_server.MissionPlan',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='mission_items', full_name='mavsdk.rpc.mission_raw_server.MissionPlan.mission_items', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=787,
serialized_end=867,
)
_MISSIONPROGRESS = _descriptor.Descriptor(
name='MissionProgress',
full_name='mavsdk.rpc.mission_raw_server.MissionProgress',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='current', full_name='mavsdk.rpc.mission_raw_server.MissionProgress.current', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='total', full_name='mavsdk.rpc.mission_raw_server.MissionProgress.total', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=869,
serialized_end=918,
)
_MISSIONRESULT = _descriptor.Descriptor(
name='MissionResult',
full_name='mavsdk.rpc.mission_raw_server.MissionResult',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='result', full_name='mavsdk.rpc.mission_raw_server.MissionResult.result', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='result_str', full_name='mavsdk.rpc.mission_raw_server.MissionResult.result_str', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_MISSIONRESULT_RESULT,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=921,
serialized_end=1341,
)
_INCOMINGMISSIONRESPONSE.fields_by_name['mission_result'].message_type = _MISSIONRESULT
_INCOMINGMISSIONRESPONSE.fields_by_name['mission_plan'].message_type = _MISSIONPLAN
_CURRENTITEMCHANGEDRESPONSE.fields_by_name['mission_item'].message_type = _MISSIONITEM
_MISSIONPLAN.fields_by_name['mission_items'].message_type = _MISSIONITEM
_MISSIONRESULT.fields_by_name['result'].enum_type = _MISSIONRESULT_RESULT
_MISSIONRESULT_RESULT.containing_type = _MISSIONRESULT
DESCRIPTOR.message_types_by_name['SubscribeIncomingMissionRequest'] = _SUBSCRIBEINCOMINGMISSIONREQUEST
DESCRIPTOR.message_types_by_name['IncomingMissionResponse'] = _INCOMINGMISSIONRESPONSE
DESCRIPTOR.message_types_by_name['SubscribeCurrentItemChangedRequest'] = _SUBSCRIBECURRENTITEMCHANGEDREQUEST
DESCRIPTOR.message_types_by_name['CurrentItemChangedResponse'] = _CURRENTITEMCHANGEDRESPONSE
DESCRIPTOR.message_types_by_name['SubscribeClearAllRequest'] = _SUBSCRIBECLEARALLREQUEST
DESCRIPTOR.message_types_by_name['ClearAllResponse'] = _CLEARALLRESPONSE
DESCRIPTOR.message_types_by_name['SetCurrentItemCompleteRequest'] = _SETCURRENTITEMCOMPLETEREQUEST
DESCRIPTOR.message_types_by_name['SetCurrentItemCompleteResponse'] = _SETCURRENTITEMCOMPLETERESPONSE
DESCRIPTOR.message_types_by_name['MissionItem'] = _MISSIONITEM
DESCRIPTOR.message_types_by_name['MissionPlan'] = _MISSIONPLAN
DESCRIPTOR.message_types_by_name['MissionProgress'] = _MISSIONPROGRESS
DESCRIPTOR.message_types_by_name['MissionResult'] = _MISSIONRESULT
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
SubscribeIncomingMissionRequest = _reflection.GeneratedProtocolMessageType('SubscribeIncomingMissionRequest', (_message.Message,), dict(
DESCRIPTOR = _SUBSCRIBEINCOMINGMISSIONREQUEST,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.SubscribeIncomingMissionRequest)
))
_sym_db.RegisterMessage(SubscribeIncomingMissionRequest)
IncomingMissionResponse = _reflection.GeneratedProtocolMessageType('IncomingMissionResponse', (_message.Message,), dict(
DESCRIPTOR = _INCOMINGMISSIONRESPONSE,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.IncomingMissionResponse)
))
_sym_db.RegisterMessage(IncomingMissionResponse)
SubscribeCurrentItemChangedRequest = _reflection.GeneratedProtocolMessageType('SubscribeCurrentItemChangedRequest', (_message.Message,), dict(
DESCRIPTOR = _SUBSCRIBECURRENTITEMCHANGEDREQUEST,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.SubscribeCurrentItemChangedRequest)
))
_sym_db.RegisterMessage(SubscribeCurrentItemChangedRequest)
CurrentItemChangedResponse = _reflection.GeneratedProtocolMessageType('CurrentItemChangedResponse', (_message.Message,), dict(
DESCRIPTOR = _CURRENTITEMCHANGEDRESPONSE,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.CurrentItemChangedResponse)
))
_sym_db.RegisterMessage(CurrentItemChangedResponse)
SubscribeClearAllRequest = _reflection.GeneratedProtocolMessageType('SubscribeClearAllRequest', (_message.Message,), dict(
DESCRIPTOR = _SUBSCRIBECLEARALLREQUEST,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.SubscribeClearAllRequest)
))
_sym_db.RegisterMessage(SubscribeClearAllRequest)
ClearAllResponse = _reflection.GeneratedProtocolMessageType('ClearAllResponse', (_message.Message,), dict(
DESCRIPTOR = _CLEARALLRESPONSE,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.ClearAllResponse)
))
_sym_db.RegisterMessage(ClearAllResponse)
SetCurrentItemCompleteRequest = _reflection.GeneratedProtocolMessageType('SetCurrentItemCompleteRequest', (_message.Message,), dict(
DESCRIPTOR = _SETCURRENTITEMCOMPLETEREQUEST,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteRequest)
))
_sym_db.RegisterMessage(SetCurrentItemCompleteRequest)
SetCurrentItemCompleteResponse = _reflection.GeneratedProtocolMessageType('SetCurrentItemCompleteResponse', (_message.Message,), dict(
DESCRIPTOR = _SETCURRENTITEMCOMPLETERESPONSE,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.SetCurrentItemCompleteResponse)
))
_sym_db.RegisterMessage(SetCurrentItemCompleteResponse)
MissionItem = _reflection.GeneratedProtocolMessageType('MissionItem', (_message.Message,), dict(
DESCRIPTOR = _MISSIONITEM,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.MissionItem)
))
_sym_db.RegisterMessage(MissionItem)
MissionPlan = _reflection.GeneratedProtocolMessageType('MissionPlan', (_message.Message,), dict(
DESCRIPTOR = _MISSIONPLAN,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.MissionPlan)
))
_sym_db.RegisterMessage(MissionPlan)
MissionProgress = _reflection.GeneratedProtocolMessageType('MissionProgress', (_message.Message,), dict(
DESCRIPTOR = _MISSIONPROGRESS,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.MissionProgress)
))
_sym_db.RegisterMessage(MissionProgress)
MissionResult = _reflection.GeneratedProtocolMessageType('MissionResult', (_message.Message,), dict(
DESCRIPTOR = _MISSIONRESULT,
__module__ = 'mission_raw_server.mission_raw_server_pb2'
# @@protoc_insertion_point(class_scope:mavsdk.rpc.mission_raw_server.MissionResult)
))
_sym_db.RegisterMessage(MissionResult)
DESCRIPTOR._options = None
_MISSIONRAWSERVERSERVICE = _descriptor.ServiceDescriptor(
name='MissionRawServerService',
full_name='mavsdk.rpc.mission_raw_server.MissionRawServerService',
file=DESCRIPTOR,
index=0,
serialized_options=None,
serialized_start=1344,
serialized_end=1974,
methods=[
_descriptor.MethodDescriptor(
name='SubscribeIncomingMission',
full_name='mavsdk.rpc.mission_raw_server.MissionRawServerService.SubscribeIncomingMission',
index=0,
containing_service=None,
input_type=_SUBSCRIBEINCOMINGMISSIONREQUEST,
output_type=_INCOMINGMISSIONRESPONSE,
serialized_options=None,
),
_descriptor.MethodDescriptor(
name='SubscribeCurrentItemChanged',
full_name='mavsdk.rpc.mission_raw_server.MissionRawServerService.SubscribeCurrentItemChanged',
index=1,
containing_service=None,
input_type=_SUBSCRIBECURRENTITEMCHANGEDREQUEST,
output_type=_CURRENTITEMCHANGEDRESPONSE,
serialized_options=None,
),
_descriptor.MethodDescriptor(
name='SetCurrentItemComplete',
full_name='mavsdk.rpc.mission_raw_server.MissionRawServerService.SetCurrentItemComplete',
index=2,
containing_service=None,
input_type=_SETCURRENTITEMCOMPLETEREQUEST,
output_type=_SETCURRENTITEMCOMPLETERESPONSE,
serialized_options=_b('\200\265\030\001'),
),
_descriptor.MethodDescriptor(
name='SubscribeClearAll',
full_name='mavsdk.rpc.mission_raw_server.MissionRawServerService.SubscribeClearAll',
index=3,
containing_service=None,
input_type=_SUBSCRIBECLEARALLREQUEST,
output_type=_CLEARALLRESPONSE,
serialized_options=None,
),
])
_sym_db.RegisterServiceDescriptor(_MISSIONRAWSERVERSERVICE)
DESCRIPTOR.services_by_name['MissionRawServerService'] = _MISSIONRAWSERVERSERVICE
# @@protoc_insertion_point(module_scope)
| 27,514 | 10,445 |
import numpy as np
basis_gradient = [[-1.0, -1.0], [1.0, 0.0], [0.0, 1.0]]
e = [[[int((i - j) * (j - k) * (k - i) / 2) for k in range(3)]
for j in range(3)] for i in range(3)]
tri = np.random.rand(3,3)
# tri = np.array([[0,0,0],[1.1,0,0],[0,1.1,0]])
# tri = np.array([[0,0,0],[1,1,0],[0,1,0]])
surf_curl = np.empty((3,3))
g1 = tri[1] - tri[0]
g2 = tri[2] - tri[0]
unscaled_normal = np.cross(g1, g2)
jacobian_mag = np.linalg.norm(unscaled_normal)
normal = unscaled_normal / jacobian_mag
for basis_idx in range(3):
for s in range(3):
surf_curl[basis_idx][s] = (
+ basis_gradient[basis_idx][0] * g2[s]
- basis_gradient[basis_idx][1] * g1[s]
) / jacobian_mag;
print(tri, jacobian_mag, normal)
print(basis_gradient)
jacobian = np.array([
g1, g2, unscaled_normal
]).T
inv_jacobian = np.linalg.inv(jacobian)
real_basis_gradient = np.zeros((3,3))
for basis_idx in range(3):
for j in range(3):
real_basis_gradient[basis_idx][j] = sum(
[basis_gradient[basis_idx][d] * inv_jacobian[d][j] for d in range(2)]
)
surf_curl2 = np.zeros((3,3))
for basis_idx in range(3):
for s in range(3):
for b in range(3):
for c in range(3):
surf_curl2[basis_idx][s] += e[b][c][s] * normal[b] * real_basis_gradient[basis_idx][c]
print(surf_curl)
print(surf_curl2)
np.testing.assert_almost_equal(surf_curl, surf_curl2)
| 1,420 | 651 |
from re import sub
import requests
class ReportSubmitter():
def submit_report(series_id, series_token, report, url="http://localhost:4500/reports"):
'''
Submits a report to the GA4GH testbed api.
Required arguments:
series_id - A series ID is needed by server to group the report
series_token - A token is needed to verify authenticity
report - GA4GH report in JSON format
url - URL of the testbed server
'''
header = {"GA4GH-TestbedReportSeriesId": series_id, "GA4GH-TestbedReportSeriesToken": series_token}
submit_request = requests.post(url, headers=header ,json=report)
results = {
"status_code": submit_request.status_code,
"error_message": None,
"report_id": None
}
if submit_request.status_code == 200:
results["report_id"] = submit_request.json()["id"]
else:
if "message" in submit_request.json().keys():
results["error_message"] = submit_request.json()["message"]
return results
| 1,119 | 310 |
###############################################################################
# Caleydo - Visualization for Molecular Biology - http://caleydo.org
# Copyright (c) The Caleydo Team. All rights reserved.
# Licensed under the new BSD license, available at http://caleydo.org/license
###############################################################################
from builtins import str
import logging
_log = logging.getLogger(__name__)
# extend a dictionary recursively
def extend(target, w):
for k, v in w.items():
if isinstance(v, dict):
if k not in target:
target[k] = extend({}, v)
else:
target[k] = extend(target[k], v)
else:
target[k] = v
return target
def replace_variables_f(s, lookup):
import re
s = str(s)
if re.match(r'^\$\{([^}]+)\}$', s): # full string is a pattern
s = s[2:len(s) - 1]
v = lookup(s)
if v is None:
_log.error('cant resolve ' + s)
return '$unresolved$'
return v
def match(m):
v = lookup(m.group(1))
if v is None:
_log.error('cant resolve ' + m.group(1))
return '$unresolved$'
return str(v)
return re.sub(r'\$\{([^}]+)\}', match, s)
def replace_variables(s, variables):
return replace_variables_f(s, lambda x: variables.get(x, None))
def replace_nested_variables(obj, lookup):
if isinstance(obj, list):
return [replace_nested_variables(o, lookup) for o in obj]
elif isinstance(obj, str):
return replace_variables_f(obj, lookup)
elif isinstance(obj, dict):
return {k: replace_nested_variables(v, lookup) for k, v in obj.items()}
return obj
| 1,611 | 536 |
from ait.core.server.plugins import Plugin
from gevent import Greenlet, sleep
class PacketAccumulator(Plugin):
def __init__(self, inputs=None, outputs=None, zmq_args=None, timer_seconds=1, max_size_octets=1024):
super().__init__(inputs, outputs, zmq_args)
self.packet_queue = []
self.size_packet_queue_octets = 0
self.glet = Greenlet.spawn(self.periodic_check)
if timer_seconds > 0:
self.timer_seconds = timer_seconds
else:
msg = f"PacketAccumulator -> timer value {timer_seconds} must be greater "
msg += "than or equal to 0! Defaulting to 1 second."
self.timer_seconds = 1
self.log.error(msg)
if max_size_octets > 0:
self.max_size_octets = max_size_octets
else:
msg = f"PacketAccumulator -> Maximum accumulation size {max_size_octets} octets must "
msg += "be greater than 0! Defaulting to 1024 octets."
self.max_size_octets = 1024
self.log.error(msg)
def periodic_check(self):
while True:
sleep(self.timer_seconds)
self.emit()
def process(self, data, topic=None):
data_len = len(data)
# Does not fit, need to emit
if self.size_packet_queue_octets + data_len > self.max_size_octets:
self.emit()
# It fits! Add and defer emission
self.packet_queue.append(data)
self.size_packet_queue_octets += data_len
def emit(self):
if self.packet_queue:
payload = self.packet_queue.pop(0)
for i in self.packet_queue:
payload += i
self.publish(payload)
self.size_packet_queue_octets = 0
self.packet_queue.clear()
| 1,785 | 566 |
import cocotb
import unittest
import crv_unittest
from cocotb.triggers import Timer
@cocotb.test()
def test_crv(dut):
suite = unittest.TestSuite()
suite.addTests(unittest.TestLoader().loadTestsFromModule(crv_unittest))
unittest.TextTestRunner().run(suite)
yield Timer(1000)
| 294 | 111 |
import hashlib
import json
from .client import CacheAction
from .utils import streamed_errors, DAGParsingFailed, DAGUnsupportedFlowLanguage
from .custom_flowgraph import FlowGraph
from metaflow import Run, Step, DataArtifact, namespace
from metaflow.exception import MetaflowNotFound
namespace(None) # Always use global namespace by default
class GenerateDag(CacheAction):
"""
Generates a DAG for a given Run.
Parameters
----------
flow_id : str
The flow id that this codepackage belongs to.
Required for finding the correct class inside the parser logic.
run_number : str
Run number to construct rest of the pathspec
Returns
--------
List or None
example:
[
boolean,
{
"step_name": {
'type': string,
'box_next': boolean,
'box_ends': string,
'next': list,
'doc': string
},
...
}
]
First field conveys whether dag generation was successful.
Second field contains the actual DAG.
"""
@classmethod
def format_request(cls, flow_id, run_number, invalidate_cache=False):
msg = {
'flow_id': flow_id,
'run_number': run_number
}
key_identifier = "{}/{}".format(flow_id, run_number)
result_key = 'dag:result:%s' % hashlib.sha1((key_identifier).encode('utf-8')).hexdigest()
stream_key = 'dag:stream:%s' % hashlib.sha1((key_identifier).encode('utf-8')).hexdigest()
return msg,\
[result_key],\
stream_key,\
[stream_key],\
invalidate_cache
@classmethod
def response(cls, keys_objs):
'''
Returns the generated DAG result
'''
return [json.loads(val) for key, val in keys_objs.items() if key.startswith('dag:result')][0]
@classmethod
def stream_response(cls, it):
for msg in it:
yield msg
@classmethod
def execute(cls,
message=None,
keys=None,
existing_keys={},
stream_output=None,
invalidate_cache=False,
**kwargs):
results = {}
flow_id = message['flow_id']
run_number = message['run_number']
result_key = [key for key in keys if key.startswith('dag:result')][0]
with streamed_errors(stream_output):
run = Run("{}/{}".format(flow_id, run_number))
param_step = Step("{}/_parameters".format(run.pathspec))
try:
dag = DataArtifact("{}/_graph_info".format(param_step.task.pathspec)).data
except MetaflowNotFound:
dag = generate_dag(run)
results[result_key] = json.dumps(dag)
return results
# Utilities
def generate_dag(run: Run):
try:
# Initialize a FlowGraph object
graph = FlowGraph(source=run.code.flowspec, name=run.parent.id)
# Build the DAG based on the DAGNodes given by the FlowGraph for the found FlowSpec class.
steps_info, graph_structure = graph.output_steps()
graph_info = {
"steps": steps_info,
"graph_structure": graph_structure,
"doc": graph.doc
}
return graph_info
except Exception as ex:
if ex.__class__.__name__ == 'KeyError' and "python" in str(ex):
raise DAGUnsupportedFlowLanguage(
'DAG parsing is not supported for the language used in this Flow.'
) from None
else:
raise DAGParsingFailed(f"DAG Parsing failed: {str(ex)}")
| 3,679 | 1,031 |
"""
Synthetic example with high concurrency. Used primarily to stress test the
library.
"""
import argparse
import sys
import time
import threading
import random
# Comment out to test against the published copy
import os
sys.path.insert(1, os.path.dirname(os.path.realpath(__file__)) + '/../..')
import opentracing
import splunktracing
def sleep_dot():
"""Short sleep and writes a dot to the STDOUT.
"""
time.sleep(0.05)
sys.stdout.write('.')
sys.stdout.flush()
def add_spans():
"""Calls the opentracing API, doesn't use any LightStep-specific code.
"""
with opentracing.tracer.start_active_span('trivial/initial_request') as parent_scope:
parent_scope.span.set_tag('url', 'localhost')
parent_scope.span.log_event('All good here!', payload={'N': 42, 'pi': 3.14, 'abc': 'xyz'})
parent_scope.span.set_tag('span_type', 'parent')
parent_scope.span.set_baggage_item('checked', 'baggage')
rng = random.SystemRandom()
for i in range(50):
time.sleep(rng.random() * 0.2)
sys.stdout.write('.')
sys.stdout.flush()
# This is how you would represent starting work locally.
with opentracing.tracer.start_active_span('trivial/child_request') as child_scope:
child_scope.span.log_event('Uh Oh!', payload={'error': True})
child_scope.span.set_tag('span_type', 'child')
# Play with the propagation APIs... this is not IPC and thus not
# where they're intended to be used.
text_carrier = {}
opentracing.tracer.inject(child_scope.span.context, opentracing.Format.TEXT_MAP, text_carrier)
span_context = opentracing.tracer.extract(opentracing.Format.TEXT_MAP, text_carrier)
with opentracing.tracer.start_active_span(
'nontrivial/remote_span',
child_of=span_context) as remote_scope:
remote_scope.span.log_event('Remote!')
remote_scope.span.set_tag('span_type', 'remote')
time.sleep(rng.random() * 0.1)
opentracing.tracer.flush()
def splunk_tracer_from_args():
"""Initializes splunk from the commandline args.
"""
parser = argparse.ArgumentParser()
parser.add_argument('--token', help='Your Splunk HEC token.',
default='{your_access_token}')
parser.add_argument('--host', help='The HEC host to contact.',
default='127.0.0.1')
parser.add_argument('--port', help='The Splunk HEC port.',
type=int, default=8088)
parser.add_argument('--no_tls', help='Disable TLS for reporting',
dest="no_tls", action='store_true')
parser.add_argument('--component_name', help='The Splunk component name',
default='NonTrivialExample')
args = parser.parse_args()
if args.no_tls:
collector_encryption = 'none'
else:
collector_encryption = 'tls'
return splunktracing.Tracer(
component_name=args.component_name,
access_token=args.token,
collector_host=args.host,
collector_port=args.port,
collector_encryption=collector_encryption)
if __name__ == '__main__':
print('Hello '),
# Use LightStep's opentracing implementation
with splunk_tracer_from_args() as tracer:
opentracing.tracer = tracer
for j in range(20):
threads = []
for i in range(64):
t = threading.Thread(target=add_spans)
threads.append(t)
t.start()
for t in threads:
t.join()
print('\n')
print(' World!')
| 3,803 | 1,171 |
# -*- coding: utf-8 -*-
"""
Created on Fri Mar 18 13:41:17 2016
@author: Tobias Jachowski
"""
import inspect
import numbers
from pyoti.data.datasource import DataSource
from pyoti.picklable import unboundfunction
class GenericDataFile(DataSource):
def __init__(self, load_data, filename, directory=None, samplingrate=1.0,
**kwargs):
"""
load_data : function
filename : str
directory : str
samplingrate : float
**kwargs
"""
super().__init__(filename=filename, directory=directory, **kwargs)
self.load_data = unboundfunction(load_data)
if isinstance(samplingrate, numbers.Number):
self.samplingrate = samplingrate
else:
samplingrate_args = {}
for par in inspect.getargspec(samplingrate)[0]:
if par in kwargs: # par can be anything, except load_data,
# filename, directory or samplingrate
samplingrate_args[par] = kwargs.get(par)
if par == 'filename': # automatically use filename
samplingrate_args['filename'] = self.absfile
self.samplingrate = samplingrate(**samplingrate_args)
self.load_data_args = {}
for par in inspect.getargspec(load_data)[0]:
if par in kwargs:
self.load_data_args[par] = kwargs.get(par)
self.name = ("Generic data originally loaded from \n"
" %s with \n"
" samplingrate %s Hz") % (self.absfile_orig,
self.samplingrate)
def as_array(self):
filename = self.absfile
data = self.load_data(filename, **self.load_data_args)
return data
class GenericData(DataSource):
def __init__(self, load_data, samplingrate=1.0, **kwargs):
"""
load_data : function
samplingrate : float
"""
self.load_data = unboundfunction(load_data)
if isinstance(samplingrate, numbers.Number):
self.samplingrate = samplingrate
else:
samplingrate_args = {}
for par in inspect.getargspec(samplingrate)[0]:
if par in kwargs:
samplingrate_args[par] = kwargs.pop(par)
self.samplingrate = samplingrate(**samplingrate_args)
self.fun_args = {}
for par in inspect.getargspec(load_data)[0]:
if par in kwargs:
self.fun_args[par] = kwargs.pop(par)
self.name = ("Generic data with \n"
" samplingrate %s Hz") % (self.samplingrate)
def as_array(self):
data = self.load_data(**self.fun_args)
return data
| 2,773 | 783 |
def variable_lists(node):
nodes = node.flatten(ordered=False, reverse=False, inverse=False)
#store some variable names, in private or shared
assigned_var = []
type_info = []
#get iterator name
iterator_name = node[0].name
for n in nodes:
if n.cls == "Assign":
#index = n.parent.children.index(n)
#lhs var of the assignment
if n[0].cls == "Var":
if n[0].name not in assigned_var:
assigned_var.append(n[0].name)
type_info.append(n[0].type)
"""
if n[0].cls == "Set":
var_name = n[0].name
#subnodes to Set
#index = n.parent.children.index(n)
#subnodes = n.parent[index].flatten(ordered=False, reverse=False, inverse=False)
subnodes = n[0].flatten(ordered=False, reverse=False, inverse=False)
for subnode in subnodes[1:]:
if subnode.name and subnode.name == iterator_name:
shared_variable.append(var_name)
#print(subnode.name)
"""
#multiple return from function are assigned to vars
if n.cls == "Assigns": #and n.backend == "func_returns":
for sub_node in n:
if sub_node.cls == "Var":
if sub_node.name not in assigned_var:
assigned_var.append(sub_node.name)
type_info.append(sub_node.type)
#get the iteration variable in the for loop
if n.cls == "Var" and n.parent.cls == "For":
if n.name not in assigned_var:
assigned_var.append(n.name)
type_info.append(n.type)
#shared_variable = list(set(shared_variable))
#print(shared_variable)
#for n in nodes:
# if (n.cls == "Var" or n.cls == "Get") and n.backend != "reserved" and n.name \
# not in [shared_variable, node[0].name]:
# private_variable.append(n.name)
#private_variable = list(set(private_variable))
#return private_variable, shared_variable, assigned_var, type_info
return assigned_var, type_info
def omp(node, start, stop, step):
assigned_var, type_info = variable_lists(node)
#out = "#pragma omp parallel for\nfor (%(0)s=" + start + \
# "; %(0)s<=" + stop + "; %(0)s"
temp_str = ""
if len(assigned_var) > 1:
temp_str = ", ".join(assigned_var[1:])
temp_str = "firstprivate(" + temp_str + ")"
out = "#pragma omp parallel for " + temp_str + "\nfor (%(0)s=" + start + \
"; %(0)s<=" + stop + "; %(0)s"
return out
def tbb(node, start, stop, step):
assigned_var, type_info = variable_lists(node)
any_vec_or_mat = False
for var, type in zip(assigned_var, type_info):
if type not in ["uword", "int", "float", "double"]:
any_vec_or_mat = True
#tbb.counter += 1
out = "{\n"
#str_val = str(tbb.counter)
if any_vec_or_mat:
declare_struct = "struct tbb_var_struct" + "\n{"
for var, type in zip(assigned_var, type_info):
if type not in ["uword", "int", "float", "double"]:
declare_struct += "\n" + type + " " + var + ";"
declare_struct += "\n} " + ";\n"
declare_struct += "tbb::combinable<struct tbb_var_struct" + "> tbb_per_thread_data" + " ;\n"
out += declare_struct
#for var, type in zip(assigned_var, type_info):
# out += "tbb::enumerable_thread_specific<" + type + "> " + "_" + var + " = " + var + " ;\n"
out += "tbb::parallel_for(tbb::blocked_range<size_t>(" + start + ", " + stop + "+1" + \
"),\n" + "[&]" + "(const tbb::blocked_range<size_t>& _range) \n{\n"
#assign to local L, x, y
for var, type in zip(assigned_var, type_info):
if type in ["uword", "int", "float", "double"]:
out += type + " " + var + ";\n"
if any_vec_or_mat:
out += "struct tbb_var_struct" + " tbb_struct_vars = tbb_per_thread_data" + ".local() ;\n"
for var, type in zip(assigned_var, type_info):
if type not in ["uword", "int", "float", "double"]:
out += type + "& " + var + " = " + "tbb_struct_vars." + var + ";\n"
#for var, type in zip(assigned_var, type_info):
# out += type + "& " + var + " = _" + var + ".local() ;\n"
out += "for (" + "%(0)s = _range.begin(); %(0)s != _range.end(); %(0)s"
# special case for '+= 1'
if step == "1":
out += "++"
else:
out += "+=" + step
out += ")\n{\n%(2)s\n}"
out += "\n}\n);\n"
out += "}"
return out
#tbb.counter = 0
| 4,721 | 1,613 |
#!/usr/bin/python3
import unittest
from unittest.mock import MagicMock, call
from clock import clock
class TestClock(unittest.TestCase):
def setUp(self):
self.grid = MagicMock()
self.clock = clock.Clock(self.grid)
def test_grid_is_cleared_before_setting_new_led(self):
self.clock.update_time(1, 26)
calls = [call.clear(), call.set_led(0, 0)]
self.grid.assert_has_calls(calls, any_order=False)
def test_fades_out_before_clearing(self):
self.clock.update_time(1, 26)
calls = [call.fade_out(), call.clear(), call.set_led(0, 0)]
self.grid.assert_has_calls(calls, any_order=False)
def test_fades_in_after_setting_last_led(self):
self.clock.update_time(1, 26)
calls = [call.set_led(3, 4), call.fade_in()]
self.grid.assert_has_calls(calls, any_order=False)
def test_fade_can_be_disabled(self):
self.clock = clock.Clock(self.grid, animations_on=False)
self.clock.update_time(1, 26)
self.grid.fade_out.assert_not_called()
self.grid.fade_in.assert_not_called()
if __name__ == '__main__':
unittest.main()
| 1,154 | 434 |
#!/usr/bin/env python3
"""A script to iterate through directories and produce cropped images.
The images contain the video screen area of YouTube videos. The screenshots
were taken from my computer, with 900/1600 resolution, and the location is
always the same for the ROI.
Ideally a future version will automatically detect the location based on
some algorithm/strategy.
Free to use, under MIT License.
"""
import argparse
import asyncio
import logging
import os
import cv2
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--input", required=True, help="input directory", dest="input_directory")
args = ap.parse_args()
logging.basicConfig(format="[%(thread)-5d]%(asctime)s: %(message)s")
logger = logging.getLogger('async')
logger.setLevel(logging.INFO)
async def crop_image(image_file, image_index, semaphore):
""""
:type image_file: str
:type image_index: int
:type semaphore: asyncio.BoundedSemaphore
"""
async with semaphore:
img = cv2.imread(image_file, -1)
output_folder = os.path.dirname(image_file)
output_file = os.path.join(output_folder, "screenshot_{}.png".format(image_index))
logger.info("Writing file: {}".format(output_file))
video_screenshot = img[255:760, 125:1025]
cv2.imwrite(output_file, video_screenshot)
async def main():
"""Process directories recursively, creating cropped screen shots."""
tasks = list()
# semaphore to process 5 files at most
semaphore = asyncio.BoundedSemaphore(6)
for _, folders, _ in os.walk(args.input_directory):
for folder in folders:
image_index = 0
images_folder = os.path.join(args.input_directory, folder)
for _, _, image_files in os.walk(images_folder): # type: str
for image_file in image_files:
if os.path.isdir(os.path.join(images_folder, image_file)):
continue
if len(image_file) < len("_.___") or image_file[-4:] not in [".png", ".jpg"]:
continue
image_file = os.path.join(images_folder, image_file)
tasks.append(asyncio.ensure_future(crop_image(image_file, image_index, semaphore)))
image_index += 1
await asyncio.sleep(0)
await asyncio.gather(*tasks)
if __name__ == '__main__':
"""Start main loop."""
logger.info("Starting main loop")
loop = asyncio.get_event_loop()
loop.set_debug(True)
loop.run_until_complete(main())
logger.info("Completed")
| 2,580 | 812 |
from cartography.intel.jamf import computers
from cartography.util import timeit
@timeit
def start_jamf_ingestion(neo4j_session, config):
common_job_parameters = {
"UPDATE_TAG": config.update_tag,
}
computers.sync(neo4j_session, config.jamf_base_uri, config.jamf_user, config.jamf_password, common_job_parameters)
| 336 | 117 |
# -*- coding: utf-8 -*-
from setuptools import find_packages, setup
import os
import re
package = 'python_aisweb'
init_py = open(os.path.join(package, '__init__.py')).read()
version = re.search(
"^__version__ = ['\"]([^'\"]+)['\"]", init_py, re.MULTILINE).group(1)
author = re.search(
"^__author__ = ['\"]([^'\"]+)['\"]", init_py, re.MULTILINE).group(1)
email = re.search(
"^__email__ = ['\"]([^'\"]+)['\"]", init_py, re.MULTILINE).group(1)
try:
import pypandoc
readme = pypandoc.convert('README.md', 'rst')
except (IOError, ImportError):
readme = ''
with open('requirements.txt') as f:
requirements = f.read().splitlines()
setup(
name='python-aisweb',
packages=find_packages(),
version=version,
description='API Wrapper for brazilian AIS services.',
long_description=readme,
author=author,
author_email=email,
url='https://github.com/carlosdamazio/python-aisweb',
install_requires=requirements,
license="MIT",
keywords=['dev', 'api', 'aisweb', 'aeronautics'],
classifiers=[
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Natural Language :: English',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 3',
],
)
| 1,297 | 454 |
import pytest
import requests
MY_KEY = '02db6ca787d18d34175d3c7996cf193b'
@pytest.mark.parametrize("key , q , extras" , [
(MY_KEY , "London" , "okay") ,
('' , "London" , "Wrong key"),
('abc' , "London" , "Wrong key"),
(MY_KEY , "abc" , "Wrong city"),
(MY_KEY , " " , "blank city"),
('' , '' , 'Wong all'),
])
def test_current_weather(key,q,extras):
url = "http://api.openweathermap.org/data/2.5/weather?q={}&appid={}".format(q,key)
response = requests.get(url)
response = response.json()
if(extras == "okay"):
assert response["cod"] == 200
assert response["name"] == q
if(extras == "blank city"):
assert response["cod"] == '404'
assert response["message"] == "city not found"
if(extras == "Wrong city"):
assert response["cod"] == '404'
assert response["message"] == "city not found"
if(extras == "Wrong key"):
assert response["cod"] == 401
assert response["message"] == "Invalid API key. Please see http://openweathermap.org/faq#error401 for more info."
if(extras == "Wrong all"):
assert response["cod"] == 401
assert response["message"] == "Invalid API key. Please see http://openweathermap.org/faq#error401 for more info."
| 1,254 | 563 |