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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
# TODO: import framework api under this directory
__all__ = [
'create_parameter', 'ParamAttr', 'CPUPlace', 'CUDAPlace', 'CUDAPinnedPlace',
'get_default_dtype', 'set_default_dtype'
]
__all__ += [
'grad', 'LayerList', 'load', 'save', 'to_variable', 'no_grad',
'DataParallel'
]
from . import random
from .random import seed
from .framework import get_default_dtype
from .framework import set_default_dtype
from ..fluid.framework import ComplexVariable #DEFINE_ALIAS
from ..fluid.param_attr import ParamAttr #DEFINE_ALIAS
# from ..fluid.layers.tensor import create_global_var #DEFINE_ALIAS
from ..fluid.layers.tensor import create_parameter #DEFINE_ALIAS
from ..fluid.core import CPUPlace #DEFINE_ALIAS
from ..fluid.core import CUDAPlace #DEFINE_ALIAS
from ..fluid.core import CUDAPinnedPlace #DEFINE_ALIAS
from ..fluid.core import VarBase #DEFINE_ALIAS
from paddle.fluid import core #DEFINE_ALIAS
from ..fluid.dygraph.base import no_grad #DEFINE_ALIAS
from ..fluid.dygraph.base import to_variable #DEFINE_ALIAS
from ..fluid.dygraph.base import grad #DEFINE_ALIAS
from .io import save
from .io import load
from ..fluid.dygraph.parallel import DataParallel #DEFINE_ALIAS
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"""
MyMemory Translated
@website https://mymemory.translated.net/
@provide-api yes (https://mymemory.translated.net/doc/spec.php)
@using-api yes
@results JSON
@stable yes
@parse url, title, content
"""
import re
from sys import version_info
from searx.utils import is_valid_lang
if version_info[0] == 3:
unicode = str
categories = ['general']
url = u'http://api.mymemory.translated.net/get?q={query}&langpair={from_lang}|{to_lang}{key}'
web_url = u'http://mymemory.translated.net/en/{from_lang}/{to_lang}/{query}'
weight = 100
parser_re = re.compile(u'.*?([a-z]+)-([a-z]+) (.{2,})$', re.I)
api_key = ''
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import numpy as np
np.set_printoptions(formatter={'float': lambda x: "{0:0.3f}".format(x)})
import matplotlib.pyplot as plt
import tensorflow as tf
import logging
import os
from scipy.io import savemat
from scipy.stats import norm
logger = logging.getLogger("logger")
###################################
####### HISTOGRAM OBJECTS #########
###################################
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] | 3.268908 | 119 |
import pytest
@pytest.fixture
@pytest.fixture
@pytest.fixture
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import uuid
from thundra import constants, utils
from thundra.application.application_info_provider import ApplicationInfoProvider
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import functools
import logging
from spaceone.api.inventory.v1 import resource_group_pb2
from spaceone.core.pygrpc.message_type import *
from spaceone.core import utils
from spaceone.inventory.model.resource_group_model import ResourceGroup, Resource
__all__ = ['ResourceGroupInfo', 'ResourceGroupsInfo']
_LOGGER = logging.getLogger(__name__)
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"""
Train the NN model.
"""
import sys
import _thread
import keras
import warnings
import argparse
import numpy as np
import pandas as pd
from data.data import process_data
from model import model
from keras.models import Model
from keras.callbacks import EarlyStopping
from tkinter import ttk, filedialog, dialog
import os
import tkinter
import tkinter.messagebox
warnings.filterwarnings("ignore")
file_path1=""
file_path2=""
modelName = None
def train_model(model, X_train, y_train, name, config,lag,callBack):
"""train
train a single model.
# Arguments
model: Model, NN model to train.
X_train: ndarray(number, lags), Input data for train.
y_train: ndarray(number, ), result data for train.
name: String, name of model.
config: Dict, parameter for train.
"""
model.compile(loss="mse", optimizer="rmsprop", metrics=['mape'])
# early = EarlyStopping(monitor='val_loss', patience=30, verbose=0, mode='auto')
hist = model.fit(
X_train, y_train,
batch_size=config["batch"],
epochs=config["epochs"],
validation_split=0.05,
callbacks=[callBack]
)
model.save('model/' + name + '-' + str(lag) + '.h5')
def train_allDense_model(model, X_train, y_train, name, config,lag,callBack):
"""train
train a single model.
# Arguments
model: Model, NN model to train.
X_train: ndarray(number, lags), Input data for train.
y_train: ndarray(number, ), result data for train.
name: String, name of model.
config: Dict, parameter for train.
"""
model.compile(loss="mse", optimizer="rmsprop",metrics=['mape'])
hist = model.fit(
X_train, y_train,
batch_size=config["batch"],
epochs=config["epochs"],
callbacks = [callBack]
)
model.save('model/' + name + '-' + str(lag) + '.h5')
lagIntStart = 0
lagIntEnd = 0
def open_file_train():
'''
打开文件
:return:
'''
file_path1 = filedialog.askopenfilename(title=u'选择训练集', initialdir=(os.path.expanduser('./data/100211data/100211_all_train.csv')))
fileStr1.set(file_path1)
print('打开文件：', file_path1)
window = tkinter.Tk()
window.title('入口') # 标题
window.geometry('600x400') # 窗口尺寸
if __name__ == '__main__':
runUI()
# main(sys.argv)
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8,
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95,
246,
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17497,
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10786,
8054,
87,
7029,
11537,
220,
1303,
13328,
103,
245,
20998,
96,
22887,
118,
43380,
116,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1057,
10080,
3419,
198,
220,
220,
220,
1303,
1388,
7,
17597,
13,
853,
85,
8,
198
] | 2.330321 | 996 |
# stdlib
import random
# third party
import numpy as np
import torch
| [
2,
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2,
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198,
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] | 3.380952 | 21 |
from fcrepo_verify.utils import get_data_dir, replace_strings_in_file
from fcrepo_verify.constants import BAG_DATA_DIR
import os
import tempfile
config = MockConfig({})
config.dir = "/tmp"
| [
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] | 2.910448 | 67 |
import logging
import os
import traceback
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input
from dash.exceptions import PreventUpdate
from plotly import graph_objects
from .dash_app import DashApp
from ._plotly_plots import plot_scalars
from .player_controls import STEP_COUNT, parse_step_count
from .._vis_base import display_name, gui_interrupt, benchmark
BENCHMARK_BUTTON = Input('benchmark-button', 'n_clicks')
PROFILE_BUTTON = Input('profile-button', 'n_clicks')
NO_BENCHMARK_TEXT = '*No benchmarks available.*'
NO_PROFILES_TEXT = '*No profiles available.*'
REFRESH_GRAPHS_BUTTON = Input('refresh-graphs-button', 'n_clicks')
TENSORBOARD_STATUS = Input('tensorboard-status', 'children')
| [
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12,
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51,
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10786,
83,
22854,
3526,
12,
13376,
3256,
705,
17197,
11537,
628,
198
] | 3.055777 | 251 |
from flask import Flask
from filesbuilder import FilesBuilder
from inputoutput import IO
#writeExcelFile
if __name__ == '__main__':
App = Bootstrap()
App.run() | [
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] | 3.226415 | 53 |
"""
Ax_Metrics - Test io.emfetch package
------------------------------------------------------------------------------
Author: Dan Kamins <dos at axonchisel dot net>
Copyright (c) 2014 Dan Kamins, AxonChisel.net
"""
# ----------------------------------------------------------------------------
import pytest
import axonchisel.metrics.foundation.chrono.timerange as timerange
from axonchisel.metrics.io.emfetch.interface import EMFetcher
from axonchisel.metrics.io.emfetch.base import EMFetcherBase
import axonchisel.metrics.io.emfetch.plugins.emf_random as emf_random
from axonchisel.metrics.io.emfetch.tmrange_time_t import TimeRange_time_t
# ----------------------------------------------------------------------------
class TestEMFetcher(object):
"""
Test general EMFetcher.
"""
#
# Setup / Teardown
#
#
# Tests
#
| [
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2276,
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37,
316,
2044,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1303,
198,
220,
220,
220,
1303,
31122,
1220,
1665,
446,
593,
198,
220,
220,
220,
1303,
628,
198,
220,
220,
220,
1303,
198,
220,
220,
220,
1303,
30307,
198,
220,
220,
220,
1303,
628,
628,
628
] | 3.344828 | 261 |
# Importando apenas uma funcionalidade da biblioteca - peça a raiz quadrada de um número e arredonde ele para cima.
from math import sqrt, ceil
n = float(input('Digite um número para ver a sua raiz quadrada: '))
print('A raiz quadrada de {} é {}' .format(n, sqrt(n)))
| [
2,
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198
] | 2.61165 | 103 |
import pytest
from hamcrest import assert_that, contains_inanyorder
from tests.testing_utils import param_wrapper, run_flake8, run_pylint
strip_params = [
# code, flake8 rules, pylint rules
param_wrapper("s.strip('abca')", {'B005'}, set(), id='strip_string'),
param_wrapper(r"s.strip(r'\n\t ')", {'B005'}, set(), id='strip_raw_string'),
param_wrapper("s.lstrip('abca')", {'B005'}, set(), id='lstrip_string'),
param_wrapper(r"s.lstrip(r'\n\t ')", {'B005'}, set(), id='lstrip_raw_string'),
param_wrapper("s.rstrip('abca')", {'B005'}, set(), id='rstrip_string'),
param_wrapper(r"s.rstrip(r'\n\t ')", {'B005'}, set(), id='rstrip_raw_string'),
]
@pytest.mark.parametrize('content,flake8_errors,pylint_errors', strip_params)
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6,
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6,
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81,
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62,
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198,
220,
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7,
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1,
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81,
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7,
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6,
33,
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6,
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900,
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4686,
11639,
81,
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62,
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62,
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33809,
198,
60,
628,
198,
31,
9078,
9288,
13,
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13,
17143,
316,
380,
2736,
10786,
11299,
11,
47597,
23,
62,
48277,
11,
79,
2645,
600,
62,
48277,
3256,
10283,
62,
37266,
8,
198
] | 2.430421 | 309 |
from tapis_cli.display import Verbosity
from tapis_cli.clients.services.mixins import Username
from . import API_NAME, SERVICE_VERSION
from .models import Profile
from .formatters import ProfilesFormatOne
__all__ = ['ProfilesShow']
| [
6738,
9814,
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62,
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] | 3.560606 | 66 |
from dazzler import Dazzler
from dazzler.components import core
from dazzler.system import Page, BindingContext, Trigger
from tests.components import spec_components as spec
app = Dazzler(__name__)
aspect_types = {
'array': {
'value': [1, 2, 3],
'json': True,
},
'bool': {
'value': True,
},
'number': {
'value': 42,
},
'object': {
'value': {'foo': 'bar'},
'json': True,
},
'string': {
'value': 'foo bar',
},
'enum': {
'value': 'News',
},
'union': {
'value': 1,
},
'array_of': {
'value': [6, 7, 8, 9],
'json': True,
},
'shape': {
'value': {'color': '#000', 'fontSize': 777},
'json': True,
},
}
button_ids = ['set-{}'.format(y) for y in aspect_types]
output_ids = ['out-{}'.format(y) for y in aspect_types]
layout = core.Container([
core.Container([core.Button(x, identity=x) for x in button_ids]),
spec.TestComponent('', identity='spec-output', id='spec-output'),
])
page = Page(
'page',
url='/',
layout=layout
)
app.add_page(page)
for button in button_ids:
page.bind(Trigger(button, 'clicks'))(on_click_render_type)
if __name__ == '__main__':
app.start('-v --debug=1 --port=8155'.split())
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8,
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13,
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62,
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7,
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8,
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25,
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220,
220,
220,
2443,
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7,
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7,
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11,
705,
565,
3378,
6,
4008,
7,
261,
62,
12976,
62,
13287,
62,
4906,
8,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
598,
13,
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10786,
12,
85,
1377,
24442,
28,
16,
1377,
634,
28,
23,
18742,
4458,
35312,
28955,
198
] | 2.178631 | 599 |
import graphene
from ..types import ErrorType # noqa Import ErrorType for backwards compatability
| [
11748,
42463,
198,
198,
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17267,
13047,
6030,
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16196,
8330,
1799,
198
] | 4.545455 | 22 |
#MenuTitle: Access to segments
# -*- coding: utf-8 -*-
from GlyphsApp.plugins import *
g = Glyphs.font.selectedLayers[0].parent
paths = Glyphs.font.selectedLayers[0].paths
for path in paths:
segments = path.segments
for segment in segments:
print type(segment.points[0]), dir(segment.points[0])
| [
2,
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7,
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13,
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58,
15,
12962,
198
] | 2.608333 | 120 |
import sys
sys.path.append('/opt')
import os
import boto3
import json
import dill
import ast
import base64
import shutil
import time
import pandas as pd
from boto3 import resource
from boto3.dynamodb.conditions import Key, Attr
# Dynamo Config
dynamo_resource = resource('dynamodb')
dynamo = boto3.client('dynamodb')
METADATA_TABLE = 'HomeworksMetadata'
TEST_CASES_TABLE = 'HomeworksTestCases'
GRADEBOOK_TABLE = 'Gradebook'
# Return Codes
SUCCESS = 200
ERROR = 400
# Request Types
STUDENT_REQUEST = 'STUDENT_GRADE'
ALL_STUDENTS_REQUEST = 'ALL_STUDENTS_GRADES'
| [
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220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
628,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198
] | 2.489627 | 241 |
# Copyright 2019 Google LLC
#
# 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.
"""Tests for the crash_access library."""
# pylint: disable=protected-access
import unittest
import mock
from clusterfuzz._internal.tests.test_libs import helpers as test_helpers
from libs import crash_access
from libs import helpers
from libs.query import base
class AddScopeTest(unittest.TestCase):
"""Test add_scope."""
def test_forbidden(self):
"""Test when user is forbidden."""
self.mock.has_access.return_value = False
with self.assertRaises(helpers.EarlyExitException):
crash_access.add_scope(self.query, self.params, 'security_flag',
'job_type', 'fuzzer_name')
def test_default_global_privileged(self):
"""Test the default filter for globally privileged users."""
self.mock.has_access.return_value = True
crash_access.add_scope(self.query, self.params, 'security_flag', 'job_type',
'fuzzer_name')
self.assertTrue(self.params['permissions']['everything'])
self.assertTrue(self.params['permissions']['isPrivileged'])
self.assertEqual([], self.params['permissions']['jobs'])
self.assertFalse([], self.params['permissions']['fuzzers'])
self.query.union.assert_has_calls([])
self.query.filter.assert_has_calls([])
def test_default_domain(self):
"""Test the default filter for domain users."""
self.mock.has_access.side_effect = _has_access
crash_access.add_scope(self.query, self.params, 'security_flag', 'job_type',
'fuzzer_name')
self.assertTrue(self.params['permissions']['everything'])
self.assertFalse(self.params['permissions']['isPrivileged'])
self.assertEqual([], self.params['permissions']['jobs'])
self.assertFalse([], self.params['permissions']['fuzzers'])
self.query.filter.assert_has_calls([])
self.query.union.assert_called_once_with(mock.ANY)
q = self.query.union.call_args[0][0]
q.union.assert_has_calls([])
q.filter.assert_has_calls([mock.call('security_flag', False)])
def test_domain_with_job_and_fuzzer(self):
"""Test domain user with job and fuzzer."""
self.mock.has_access.side_effect = _has_access
self.mock.get_user_job_type.return_value = 'job'
self.mock._allowed_entities_for_user.side_effect = [['job2'], ['fuzzer']]
self.mock.get_permission_names.side_effect = [['perm'], ['perm1']]
crash_access.add_scope(self.query, self.params, 'security_flag', 'job_type',
'fuzzer_name')
self.assertTrue(self.params['permissions']['everything'])
self.assertFalse(self.params['permissions']['isPrivileged'])
self.assertListEqual(['perm', 'job'], self.params['permissions']['jobs'])
self.assertListEqual(['perm1'], self.params['permissions']['fuzzers'])
self.query.union.assert_has_calls([])
self.query.union.assert_called_once_with(mock.ANY, mock.ANY, mock.ANY)
everything_query = self.query.union.call_args[0][0]
job_query = self.query.union.call_args[0][1]
fuzzer_query = self.query.union.call_args[0][2]
everything_query.union.assert_has_calls([])
job_query.union.assert_has_calls([])
fuzzer_query.union.assert_has_calls([])
everything_query.filter.assert_has_calls(
[mock.call('security_flag', False)])
job_query.filter_in.assert_has_calls([
mock.call('job_type', ['job2', 'job']),
])
fuzzer_query.filter_in.assert_has_calls([
mock.call('fuzzer_name', ['fuzzer']),
])
| [
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] | 2.619792 | 1,536 |
import csv
import os
import shutil
from random import randint
from uuid import uuid4
import cherrypy
import numpy as np
from cherrypy.lib.static import serve_file
from ics.classifier.classifier import NO_LABEL, YES_LABEL
from ics.db.sqlalchemydb import SQLAlchemyDB, Job, ClassificationMode, LabelSource
from ics.util.util import get_fully_portable_file_name, bool_to_string
__author__ = 'Andrea Esuli'
MAX_BATCH_SIZE = 1000
CSV_LARGE_FIELD = 1024 * 1024 * 10
QUICK_CLASSIFICATION_BATCH_SIZE = 100
| [
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] | 2.947674 | 172 |
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe import _
from datetime import datetime,timedelta
from dateutil.relativedelta import relativedelta
from frappe.utils import flt, getdate, today
| [
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] | 3.731183 | 93 |
import ctypes # used for accessing the dynamic library
import graph_partitioning.partitioners.utils as putils # used for some of the utilities functions
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3911,
653,
364,
13,
26791,
355,
1234,
4487,
1303,
973,
329,
617,
286,
262,
20081,
5499,
628
] | 4.305556 | 36 |
# coding: UTF-8
import sys
import os
import numpy as np
# unit is [us].
if __name__ == "__main__":
argc = len(sys.argv)
# 単位はus
dirname = sys.argv[1]
mu = int(sys.argv[2])
M = int(sys.argv[3])
N = int(sys.argv[4])
for trial in range(N):
print(run(dirname, mu, M, trial))
pass
| [
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220,
220,
220,
220,
1208,
198,
220,
220,
220,
220,
198
] | 1.923977 | 171 |
#Django
from django.apps import AppConfig
class EncuestasAppConfig(AppConfig):
"""Encuestas app config"""
name = 'encuestas.encuesta'
verbose_name = 'Encuestas' | [
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] | 2.521739 | 69 |
#!/usr/bin/env python3
# encoding: utf-8
#
# Copyright (c) 2008 Doug Hellmann All rights reserved.
#
"""Manipulating the order of items in a deque.
"""
#end_pymotw_header
import collections
d = collections.deque(range(10))
print('Normal :', d)
d = collections.deque(range(10))
d.rotate(2)
print('Right rotation:', d)
d = collections.deque(range(10))
d.rotate(-2)
print('Left rotation :', d)
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8,
198
] | 2.61039 | 154 |
import numpy as np
import scipy
import scipy.optimize
import argparse
import sklearn.metrics
import matplotlib.pyplot as plt
import autograd.scipy
import autograd.numpy as ag_np
import autograd
import pandas as pd
## TODO:
# - Need a mapping from timesteps to dates
################## Functions for fitting data ########################
#####################################################################
############## loss calculation ###############
#####################################################################
FUNCTIONS = {'erf': erf, 'ag_erf': ag_erf}
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--function', default='ag_erf')
parser.add_argument('--fit_type', default='cumulative')
parser.add_argument('--lower_bound', default='0.0')
parser.add_argument('--inputfile', default='input_example_mass_positives.csv')
parser.add_argument('--outputfile', default='output_example_mass_positives.csv')
args = parser.parse_args()
fun = FUNCTIONS[args.function]
fit_type = args.fit_type
lower_bound = float(args.lower_bound)
num_params = 3
seed_list = ag_np.arange(5)
x, dates, y = load_data(args.inputfile, fit_type)
best_loss = ag_np.inf
best_seed = 0
def calc_loss(params):
'''
Default loss is MSE.
'''
yhat = fun(x, *params)
loss = MSE(y, yhat)
return loss
for seed in seed_list:
ag_np.random.seed(seed)
initial_guess = ag_np.random.random(num_params)
result = scipy.optimize.minimize(
calc_loss,
initial_guess,
jac=autograd.grad(calc_loss),
method='l-bfgs-b',
constraints={},
# changing the lower bounds shifts the peak, we can explore
# this for the sake of confidence intervals.
bounds=[(0, ag_np.inf), (0, ag_np.inf), (np.max(y)*lower_bound, ag_np.inf)])
params = result.x
loss = calc_loss(params)
if loss < best_loss:
best_loss = loss
best_seed = seed
ag_np.random.seed(best_seed)
initial_guess = ag_np.random.random(num_params)
result = scipy.optimize.minimize(
calc_loss,
initial_guess,
jac=autograd.grad(calc_loss),
method='l-bfgs-b',
constraints={},
bounds=[(0, ag_np.inf), (0, ag_np.inf), (np.max(y)*lower_bound, ag_np.inf)])
params = result.x
save_results(x, y, fun, params, fit_type, dates, args.outputfile)
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330,
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220,
220,
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220,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2446,
11639,
75,
12,
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65,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17778,
34758,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22303,
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62,
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8,
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198,
220,
220,
220,
42287,
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13,
87,
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220,
220,
220,
3613,
62,
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7,
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11,
331,
11,
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11,
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11,
4197,
62,
4906,
11,
9667,
11,
26498,
13,
22915,
7753,
8,
628,
198
] | 2.199675 | 1,232 |
import numpy as np
from numba.core import types
from numba.extending import overload
@overload(np.where)
def where(cond, x, y):
"""
Implement np.where().
"""
# Choose implementation based on argument types.
if isinstance(cond, types.Array):
# Array where() => return an array of the same shape
if all(ty.layout == 'C' for ty in (cond, x, y)):
def where_impl(cond, x, y):
"""
Fast implementation for C-contiguous arrays
"""
shape = cond.shape
if x.shape != shape or y.shape != shape:
raise ValueError("all inputs should have the same shape")
res = np.empty_like(x)
cf = cond.flat
xf = x.flat
yf = y.flat
rf = res.flat
for i in range(cond.size):
rf[i] = xf[i] if cf[i] else yf[i]
return res
else:
def where_impl(cond, x, y):
"""
Generic implementation for other arrays
"""
shape = cond.shape
if x.shape != shape or y.shape != shape:
raise ValueError("all inputs should have the same shape")
res = np.empty_like(x)
for idx, c in np.ndenumerate(cond):
res[idx] = x[idx] if c else y[idx]
return res
else:
def where_impl(cond, x, y):
"""
Scalar where() => return a 0-dim array
"""
scal = x if cond else y
return np.full_like(scal, scal)
return where_impl
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8,
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1441,
810,
62,
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198
] | 1.868943 | 908 |
import os
import cv2
import itertools
import numpy as np
def dump_images(
names, pil_images, annotations, detections, stats,
labelmap, dir):
"""
Dumps images with bbox overlays to disk.
:param names: batch of sample names
:param pil_images: batch of original PIL images
:param annotations: batch of annotations
:param detections: batch of detections from NN
:param stats: batch of debug info from a network. Keeps number of anchors that match particular GT box.
:param labelmap: names of classes
:param dir: destination directory to save images
:return: None
"""
det_color = (0, 255, 0)
anno_color = (255, 0, 0)
if annotations is None: annotations = []
if detections is None: detections = []
if stats is None: stats = []
try:
for ib, (name, pil_img, anno, detection, stat) in \
enumerate(itertools.zip_longest(names, pil_images, annotations, detections, stats)):
img = np.asarray(pil_img).copy()
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
scale = [img.shape[1], img.shape[0], img.shape[1], img.shape[0]]
if detection is not None:
for icls, cls_det in enumerate(detection):
for det in cls_det:
conf = det[0]
if conf > 0.0:
bbox = det[1:]
bbox_pix = bbox * scale
type = labelmap[icls]
cv2.rectangle(
img,
(int(bbox_pix[0]), int(bbox_pix[1])),
(int(bbox_pix[2]), int(bbox_pix[3])),
det_color, 1)
cv2.putText(
img,
'{} {:.2f}'.format(type, conf),
(int(bbox_pix[0]), int(bbox_pix[1])+10),
cv2.FONT_HERSHEY_SIMPLEX,
0.4,
det_color)
if anno is not None and stat is not None:
for obj, num_matches in zip(anno, stat):
bbox = obj['bbox']
bbox_pix = bbox * scale
cv2.rectangle(
img,
(int(bbox_pix[0]), int(bbox_pix[1])),
(int(bbox_pix[2]), int(bbox_pix[3])),
anno_color, 1)
cv2.putText(
img,
obj['type'] + " M{}".format(num_matches), # M - number of matching anchors
(int(bbox_pix[0]), int(bbox_pix[1])+10),
cv2.FONT_HERSHEY_SIMPLEX,
0.4,
anno_color)
filename = name + '.png'
cv2.imwrite(os.path.join(dir, filename), img)
pass
except Exception as e:
pass
pass
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] | 1.681693 | 1,819 |
from peewee import *
from playhouse.gfk import *
from playhouse.tests.base import database_initializer
from playhouse.tests.base import ModelTestCase
db = database_initializer.get_in_memory_database()
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] | 3.433333 | 60 |
from discord.ext import commands
import requests
from discord import Embed
from disputils import BotEmbedPaginator
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] | 4.142857 | 28 |
import typer
app = typer.Typer()
@app.callback('example_plugin')
def check_cmd_group():
"""Example plugin."""
@app.command("first_command")
def _first_command():
"""Example command."""
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] | 2.84058 | 69 |
#!/usr/bin/env python3
# coding: utf-8
import pytest # type: ignore
from state import Board, Piece, GameState, GameMove
import dataclasses, json
def test_2_players_board_init(monkeypatch):
"""Make sure if we have just two players in a 4 corner board for them
to be at the opposite corners instead of next to each other.
"""
board = Board.create([1, 3])
# Redundant asserts
assert board.players == [1, 3]
# Defaults asserts
assert board.pieces_per_player == 4
assert board.board_sides == 4
assert board.board_side_length == 14
assert board.finish_zone_length == 5
# Consistency asserts
assert board.player_shift == board.board_side_length * board.board_sides // len(
board.players
)
assert board.path_zone_length == len(board.players) * board.player_shift
assert (
board.end_progress
== board.player_shift * len(board.players) + board.finish_zone_length + 1
)
assert len(board.pieces) == len(board.players) * board.pieces_per_player
# Explicit asserts
assert board.pieces == [
Piece(0, 1, 0),
Piece(1, 1, 0),
Piece(2, 1, 0),
Piece(3, 1, 0),
Piece(0, 3, 0),
Piece(1, 3, 0),
Piece(2, 3, 0),
Piece(3, 3, 0),
]
def test_3_players_6_corner_board_init(monkeypatch):
"""Make sure if we have just 3 players in a 5 corner board for them
to be at the opposite corners instead of next to each other.
"""
board = Board.create([0, 2, 3], board_sides=6, board_side_length=9)
# Redundant asserts
assert board.players == [0, 2, 3]
assert board.board_sides == 6
assert board.board_side_length == 9
# Defaults asserts
assert board.finish_zone_length == 5
assert board.pieces_per_player == 4
# Consistency asserts
assert board.player_shift == board.board_side_length * board.board_sides // len(
board.players
)
assert board.path_zone_length == len(board.players) * board.player_shift
# end_progress == path_zone_length + finish_zone_length + 1 THAT IS
# end_progress == (board_sides * board_side_length) + finish_zone_length + 1
assert (
board.end_progress
== board.player_shift * len(board.players) + board.finish_zone_length + 1
)
assert len(board.pieces) == len(board.players) * board.pieces_per_player
# Explicit asserts
assert board.pieces == [
Piece(0, 0, 0),
Piece(1, 0, 0),
Piece(2, 0, 0),
Piece(3, 0, 0),
Piece(0, 2, 0),
Piece(1, 2, 0),
Piece(2, 2, 0),
Piece(3, 2, 0),
Piece(0, 3, 0),
Piece(1, 3, 0),
Piece(2, 3, 0),
Piece(3, 3, 0),
]
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] | 2.41218 | 1,133 |
__all__ = [
'MultiLayerAtmosphere',
'AtmosphericLayer',
'phase_covariance_von_karman',
'phase_structure_function_von_karman',
'power_spectral_density_von_karman',
'Cn_squared_from_fried_parameter',
'fried_parameter_from_Cn_squared',
'seeing_to_fried_parameter',
'fried_parameter_to_seeing',
'FiniteAtmosphericLayer',
'InfiniteAtmosphericLayer',
'ModalAdaptiveOpticsLayer',
'make_standard_atmospheric_layers',
'make_las_campanas_atmospheric_layers'
]
from .atmospheric_model import *
from .finite_atmospheric_layer import *
from .infinite_atmospheric_layer import *
from .modal_adaptive_optics_layer import *
from .standard_atmosphere import *
| [
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] | 2.525362 | 276 |
# ---------------------------------------------------------------------------
#
# Copyright (c) 2014, Enthought, Inc.
# All rights reserved.
#
# This software is provided without warranty under the terms of the BSD
# license included in /LICENSE.txt and may be redistributed only
# under the conditions described in the aforementioned license. The license
# is also available online at http://www.enthought.com/licenses/BSD.txt
#
# Thanks for using Enthought open source!
#
# ---------------------------------------------------------------------------
from __future__ import unicode_literals
from sphinx.ext.autodoc import (
ModuleLevelDocumenter, ModuleDocumenter, annotation_option, SUPPRESS)
from .util import get_trait_definition, DefinitionError
class ModuleTraitDocumenter(ModuleLevelDocumenter):
""" Specialised Documenter subclass for module level traits.
The class defines a new documenter that recovers the trait definition
signature of class level traits.
"""
objtype = 'data'
member_order = 40
option_spec = dict(ModuleLevelDocumenter.option_spec)
option_spec["annotation"] = annotation_option
# must be higher than other data documenters
priority = -5
@classmethod
def can_document_member(cls, member, membername, isattr, parent):
""" Check that the documented member is a trait instance.
"""
return (
isattr and
hasattr(member, 'as_ctrait') and
isinstance(parent, ModuleDocumenter))
def document_members(self, all_members=False):
""" Trait attributes have no members """
def add_directive_header(self, sig):
""" Add the sphinx directives.
Add the 'attribute' directive with the annotation option
set to the trait definition.
"""
ModuleLevelDocumenter.add_directive_header(self, sig)
if hasattr(self, 'get_sourcename'):
sourcename = self.get_sourcename()
else:
sourcename = '<autodoc>'
if not self.options.annotation:
try:
definition = get_trait_definition(
self.parent, self.object_name)
except DefinitionError as error:
self.directive.warn(error.args[0])
return
self.add_line(
' :annotation: = {0}'.format(definition), sourcename)
elif self.options.annotation is SUPPRESS:
pass
else:
self.add_line(
' :annotation: %s' % self.options.annotation, sourcename)
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13,
1236,
14221,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6770,
796,
651,
62,
9535,
270,
62,
46758,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8000,
11,
2116,
13,
15252,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
30396,
12331,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12942,
425,
13,
40539,
7,
18224,
13,
22046,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2860,
62,
1370,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
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1058,
1236,
14221,
25,
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15,
92,
4458,
18982,
7,
46758,
828,
11348,
66,
12453,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2116,
13,
25811,
13,
1236,
14221,
318,
19549,
32761,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2860,
62,
1370,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
220,
220,
1058,
1236,
14221,
25,
4064,
82,
6,
4064,
2116,
13,
25811,
13,
1236,
14221,
11,
11348,
66,
12453,
8,
198
] | 2.708159 | 956 |
from django.shortcuts import render
from django.http import HttpResponse
from .models import Image
# Create your views here.
| [
6738,
42625,
14208,
13,
19509,
23779,
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14208,
13,
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1330,
7412,
198,
198,
2,
13610,
534,
5009,
994,
13,
198
] | 3.818182 | 33 |
#! /usr/bin/env python
from wordfreq import word_frequency, iter_wordlist
import regex
iter = iter_wordlist('en', 'large')
re_nonlatin = regex.compile('[^-_\p{Latin}\d\.\']')
re_alphabet = regex.compile('[a-z]', regex.IGNORECASE)
re_underscore = regex.compile('_')
last_freq = -1
position = 0
current_line = 0
for word in iter:
current_line += 1
# skip non english words, emoji, etc.
if re_nonlatin.search(word):
continue
# skip '123.45', 'ŭ', etc.
if not re_alphabet.search(word):
continue
# skip 'x_x', 'r_e_t_w_e_e_t', etc.
if re_underscore.search(word):
continue
freq = word_frequency(word, 'en', 'large')
if freq != last_freq:
last_freq = freq
position = current_line
print("%d\t%s\t%f" % (position, word, freq * 1e6))
| [
2,
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62,
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25,
198,
220,
220,
220,
220,
220,
220,
220,
938,
62,
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80,
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2030,
80,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
796,
1459,
62,
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198,
220,
220,
220,
3601,
7203,
4,
67,
59,
83,
4,
82,
59,
83,
4,
69,
1,
4064,
357,
9150,
11,
1573,
11,
2030,
80,
1635,
352,
68,
21,
4008,
198
] | 2.258333 | 360 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import ast
import codecs
import os.path
import re
import subprocess
import sys
from codecs import open
from distutils import log
from distutils.errors import DistutilsError
from setuptools import find_packages, setup
from setuptools.command.install import install
from setuptools.command.sdist import sdist as BaseSDistCommand
ROOT = os.path.realpath(os.path.dirname(__file__))
init = os.path.join(ROOT, 'src', 'etools_permissions', '__init__.py')
_version_re = re.compile(r'__version__\s+=\s+(.*)')
_name_re = re.compile(r'NAME\s+=\s+(.*)')
sys.path.insert(0, os.path.join(ROOT, 'src'))
with open(init, 'rb') as f:
content = f.read().decode('utf-8')
VERSION = str(ast.literal_eval(_version_re.search(content).group(1)))
NAME = str(ast.literal_eval(_name_re.search(content).group(1)))
class VerifyTagVersion(install):
"""Verify that the git tag matches version"""
setup(name=NAME,
version=VERSION,
url='https://github.com/unicef/etools-permissions',
author='UNICEF',
author_email='[email protected]',
license="Apache 2 License",
description='Django package that handles permissions',
long_description=codecs.open('README.rst').read(),
package_dir={'': 'src'},
packages=find_packages(where='src'),
include_package_data=True,
install_requires=read('install.pip'),
extras_require={
'test': read('install.pip', 'testing.pip'),
},
platforms=['any'],
classifiers=[
'Environment :: Web Environment',
'Programming Language :: Python :: 3.6',
'Framework :: Django',
'Intended Audience :: Developers'],
scripts=[],
cmdclass={
'sdist': SDistCommand,
"verify": VerifyTagVersion,
}
)
| [
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28,
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62,
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2721,
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220,
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220,
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220,
220,
220,
220,
705,
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2229,
15417,
7904,
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513,
13,
21,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
21055,
6433,
7904,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5317,
1631,
7591,
1240,
7904,
34152,
6,
4357,
198,
220,
220,
220,
220,
220,
14750,
41888,
4357,
198,
220,
220,
220,
220,
220,
23991,
4871,
34758,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
82,
17080,
10354,
9834,
396,
21575,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
332,
1958,
1298,
49899,
24835,
14815,
11,
198,
220,
220,
220,
220,
220,
1782,
198,
8,
198
] | 2.500688 | 727 |
# Rotate Sprite
# Demonstrates rotating a sprite
from livewires import games
games.init(screen_width = 640, screen_height = 480, fps = 50)
class Ship(games.Sprite):
""" A rotating ship. """
def update(self):
""" Rotate based on keys pressed. """
if games.keyboard.is_pressed(games.K_RIGHT):
self.angle += 1
if games.keyboard.is_pressed(games.K_LEFT):
self.angle -= 1
if games.keyboard.is_pressed(games.K_1):
self.angle = 0
if games.keyboard.is_pressed(games.K_2):
self.angle = 90
if games.keyboard.is_pressed(games.K_3):
self.angle = 180
if games.keyboard.is_pressed(games.K_4):
self.angle = 270
main()
| [
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12417,
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] | 2.151429 | 350 |
__all__ = ['get_bond_yields','get_company','get_fund','get_manager','get_stock_holders','return_rate_dao'] | [
834,
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] | 2.717949 | 39 |
# -*- coding: utf-8 -*-
import numpy as np
from matplotlib import pyplot as plt
from anaflow import ext_thiem_3d, ext_grf_steady
from anaflow.tools.coarse_graining import K_CG
rad = np.geomspace(0.05, 4) # radius from the pumping well in [0, 4]
r_ref = 2.0 # reference radius
var = 0.5 # variance of the log-transmissivity
len_scale = 10.0 # correlation length of the log-transmissivity
KG = 1e-4 # the geometric mean of the transmissivity
anis = 0.7 # aniso ratio
rate = -1e-4 # pumping rate
head1 = ext_thiem_3d(rad, r_ref, KG, var, len_scale, anis, 1, rate)
head2 = ext_grf_steady(rad, r_ref, K_CG, rate=rate, cond_gmean=KG, var=var, len_scale=len_scale, anis=anis)
plt.plot(rad, head1, label="Ext Thiem 3D")
plt.plot(rad, head2, label="grf(K_CG)", linestyle="--")
plt.xlabel("r in [m]")
plt.ylabel("h in [m]")
plt.legend()
plt.tight_layout()
plt.show()
| [
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] | 2.08658 | 462 |
from os.path import join, isdir
from os import makedirs
from matplotlib.backends.backend_pdf import PdfPages
from source.model.structure_model import StraightBeam
from source.auxiliary.validate_and_assign_defaults import validate_and_assign_defaults
from source.auxiliary.other_utilities import get_adjusted_path_string
from source.auxiliary import global_definitions as GD
class AnalysisController(object):
"""
Dervied class for the dynamic analysis of a given structure model
"""
POSSIBLE_ANALYSES = ['eigenvalue_analysis',
'dynamic_analysis',
'static_analysis']
# using these as default or fallback settings
DEFAULT_SETTINGS = {
"global_output_folder": "some/path",
"model_properties": {},
"report_options": {},
"runs": [],
"skin_model_parameters": {}}
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] | 2.615385 | 338 |
import trodesnetwork.socket as socket
import trodesnetwork.trodes as trodes
import threading
'''
Use this class to subscribe to analog sources
Requires input of a channel map object. The channel map is just
a JSON-like dictionary of the XML HardwareConfiguration node
in the `.trodesconfig` file.
Requires a server_address to connect to the server.
It can be used like this:
subscriber = trodes.DigitalClient(
server_address=self.network_address,
channel_map=config.channel_map,
channel_name='ECU_Din8')
'''
'''
Subscriber wraps subscription in a thread and callback
Callback can be used to call a Qt signal
''' | [
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] | 3.28934 | 197 |
class MockRequest(object):
'''
This is a mocked Request object containing only an url,
as this is the only attribute accessed during the tests.
There is a default value for it, but it can also be passed.
'''
class MockSolrResponse(object):
'''
This is a mocked Response object (can be used to replace
a response from any call to "requests.get" or
"request.put" or "request.delete", ...).
It contains a request, a status code and some JSON content.
For all of these, there is default values, but they can also
be passed.
Some standard cases are available, e.g. or "handle not found",
which has a specific combination of HTTP status code, handle
response code and content.
'''
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] | 3.273128 | 227 |
# -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
# pylint: disable=invalid-name
"""
A pass implementing the legacy swapper.
Based on Sergey Bravyi's algorithm.
"""
import sys
import numpy as np
from qiskit.transpiler.basepasses import TransformationPass
from qiskit.dagcircuit import DAGCircuit
from qiskit.transpiler.exceptions import TranspilerError
from qiskit.circuit import QuantumRegister
from qiskit.extensions.standard import SwapGate
class LegacySwap(TransformationPass):
"""
Maps a DAGCircuit onto a `coupling_map` adding swap gates.
"""
def __init__(self,
coupling_map,
initial_layout=None,
trials=20,
seed=None):
"""
Maps a DAGCircuit onto a `coupling_map` using swap gates.
Args:
coupling_map (CouplingMap): Directed graph represented a coupling map.
initial_layout (Layout): initial layout of qubits in mapping
trials (int): the number of attempts the randomized algorithm makes.
seed (int): initial seed.
"""
super().__init__()
self.coupling_map = coupling_map
self.initial_layout = initial_layout
self.trials = trials
self.seed = seed
def run(self, dag):
"""Map a DAGCircuit onto a CouplingGraph using swap gates.
Args:
dag (DAGCircuit): input DAG circuit
Returns:
DAGCircuit: object containing a circuit equivalent to
circuit_graph that respects couplings in coupling_map, and
a layout dict mapping qubits of circuit_graph into qubits
of coupling_map. The layout may differ from the initial_layout
if the first layer of gates cannot be executed on the
initial_layout.
Raises:
TranspilerError: if there was any error during the mapping or with the
parameters.
"""
if dag.width() > self.coupling_map.size():
raise TranspilerError("Not enough qubits in CouplingGraph")
# Schedule the input circuit
layerlist = list(dag.layers())
if self.initial_layout is None and self.property_set["layout"]:
self.initial_layout = self.property_set["layout"]
if self.initial_layout is not None:
# update initial_layout from a user given dict{(regname,idx): (regname,idx)}
# to an expected dict{(reg,idx): (reg,idx)}
virtual_qubits = self.initial_layout.get_virtual_bits()
self.initial_layout = {(v.register.name, v.index): ('q', self.initial_layout[v]) for v
in virtual_qubits}
device_register = QuantumRegister(self.coupling_map.size(), 'q')
initial_layout = {dag.qregs[k[0]][k[1]]: device_register[v[1]]
for k, v in self.initial_layout.items()}
# Check the input layout
circ_qubits = dag.qubits()
coup_qubits = [(QuantumRegister(self.coupling_map.size(), 'q'), wire) for wire in
self.coupling_map.physical_qubits]
qubit_subset = []
for k, v in initial_layout.items():
qubit_subset.append(v)
if k not in circ_qubits:
raise TranspilerError("initial_layout qubit %s[%d] not in input "
"DAGCircuit" % (k[0].name, k[1]))
if v not in coup_qubits:
raise TranspilerError("initial_layout qubit %s[%d] not in input "
"CouplingGraph" % (v[0].name, v[1]))
else:
# Supply a default layout
qubit_subset = [QuantumRegister(self.coupling_map.size(), 'q')[wire] for wire in
self.coupling_map.physical_qubits]
qubit_subset = qubit_subset[0:dag.width()]
initial_layout = {a: b for a, b in zip(dag.qubits(), qubit_subset)}
# Find swap circuit to preceed to each layer of input circuit
layout = initial_layout.copy()
# Construct an empty DAGCircuit with one qreg "q"
# and the same set of cregs as the input circuit
dagcircuit_output = DAGCircuit()
dagcircuit_output.name = dag.name
dagcircuit_output.add_qreg(QuantumRegister(self.coupling_map.size(), "q"))
for creg in dag.cregs.values():
dagcircuit_output.add_creg(creg)
# Make a trivial wire mapping between the subcircuits
# returned by swap_mapper_layer_update and the circuit
# we are building
identity_wire_map = {}
q = QuantumRegister(self.coupling_map.size(), 'q')
for j in range(self.coupling_map.size()):
identity_wire_map[q[j]] = q[j]
for creg in dag.cregs.values():
for j in range(creg.size):
identity_wire_map[creg[j]] = creg[j]
first_layer = True # True until first layer is output
# Iterate over layers
for i, layer in enumerate(layerlist):
# Attempt to find a permutation for this layer
success_flag, best_circ, best_d, best_layout, trivial_flag \
= self.layer_permutation(layer["partition"], layout, qubit_subset)
# If this fails, try one gate at a time in this layer
if not success_flag:
serial_layerlist = list(layer["graph"].serial_layers())
# Go through each gate in the layer
for j, serial_layer in enumerate(serial_layerlist):
success_flag, best_circ, best_d, best_layout, trivial_flag \
= self.layer_permutation(serial_layer["partition"], layout, qubit_subset)
# Give up if we fail again
if not success_flag:
raise TranspilerError("swap_mapper failed: " +
"layer %d, sublayer %d" % (i, j))
# If this layer is only single-qubit gates,
# and we have yet to see multi-qubit gates,
# continue to the next inner iteration
if trivial_flag and first_layer:
continue
# Update the record of qubit positions for each inner iteration
layout = best_layout
# Update the QASM
dagcircuit_output.compose_back(
self.swap_mapper_layer_update(j,
first_layer,
best_layout,
best_d,
best_circ,
serial_layerlist),
identity_wire_map)
# Update initial layout
if first_layer:
initial_layout = layout
first_layer = False
else:
# Update the record of qubit positions for each iteration
layout = best_layout
# Update the QASM
dagcircuit_output.compose_back(
self.swap_mapper_layer_update(i,
first_layer,
best_layout,
best_d,
best_circ,
layerlist),
identity_wire_map)
# Update initial layout
if first_layer:
initial_layout = layout
first_layer = False
# If first_layer is still set, the circuit only has single-qubit gates
# so we can use the initial layout to output the entire circuit
if first_layer:
layout = initial_layout
for i, layer in enumerate(layerlist):
dagcircuit_output.compose_back(layer["graph"], layout)
return dagcircuit_output
def layer_permutation(self, layer_partition, layout, qubit_subset):
"""Find a swap circuit that implements a permutation for this layer.
The goal is to swap qubits such that qubits in the same two-qubit gates
are adjacent.
Based on Sergey Bravyi's algorithm.
The layer_partition is a list of (qu)bit lists and each qubit is a
tuple (qreg, index).
The layout is a dict mapping qubits in the circuit to qubits in the
coupling graph and represents the current positions of the data.
The qubit_subset is the subset of qubits in the coupling graph that
we have chosen to map into.
The coupling is a CouplingGraph.
TRIALS is the number of attempts the randomized algorithm makes.
Returns: success_flag, best_circ, best_d, best_layout, trivial_flag
If success_flag is True, then best_circ contains a DAGCircuit with
the swap circuit, best_d contains the depth of the swap circuit, and
best_layout contains the new positions of the data qubits after the
swap circuit has been applied. The trivial_flag is set if the layer
has no multi-qubit gates.
"""
if self.seed is None:
self.seed = np.random.randint(0, np.iinfo(np.int32).max)
rng = np.random.RandomState(self.seed)
rev_layout = {b: a for a, b in layout.items()}
gates = []
for layer in layer_partition:
if len(layer) > 2:
raise TranspilerError("Layer contains >2 qubit gates")
if len(layer) == 2:
gates.append(tuple(layer))
# Can we already apply the gates?
dist = sum(
[self.coupling_map.distance(layout[g[0]].index, layout[g[1]].index) for g in gates])
if dist == len(gates):
circ = DAGCircuit()
circ.add_qreg(QuantumRegister(self.coupling_map.size(), "q"))
return True, circ, 0, layout, bool(gates)
# Begin loop over trials of randomized algorithm
n = self.coupling_map.size()
best_d = sys.maxsize # initialize best depth
best_circ = None # initialize best swap circuit
best_layout = None # initialize best final layout
QR = QuantumRegister(self.coupling_map.size(), "q")
for _ in range(self.trials):
trial_layout = layout.copy()
rev_trial_layout = rev_layout.copy()
# SWAP circuit constructed this trial
trial_circ = DAGCircuit()
trial_circ.add_qreg(QR)
# Compute Sergey's randomized distance
xi = {}
for i in self.coupling_map.physical_qubits:
xi[(QR, i)] = {}
for i in self.coupling_map.physical_qubits:
i = (QR, i)
for j in self.coupling_map.physical_qubits:
j = (QR, j)
scale = 1 + rng.normal(0, 1 / n)
xi[i][j] = scale * self.coupling_map.distance(i[1], j[1]) ** 2
xi[j][i] = xi[i][j]
# Loop over depths d up to a max depth of 2n+1
d = 1
# Circuit for this swap slice
circ = DAGCircuit()
circ.add_qreg(QR)
# Identity wire-map for composing the circuits
identity_wire_map = {QR[j]: QR[j] for j in range(n)}
while d < 2 * n + 1:
# Set of available qubits
qubit_set = set(qubit_subset)
# While there are still qubits available
while qubit_set:
# Compute the objective function
min_cost = sum([xi[trial_layout[g[0]]][trial_layout[g[1]]]
for g in gates])
# Try to decrease objective function
progress_made = False
# Loop over edges of coupling graph
for e in self.coupling_map.get_edges():
e = [QR[edge] for edge in e]
# Are the qubits available?
if e[0] in qubit_set and e[1] in qubit_set:
# Try this edge to reduce the cost
new_layout = trial_layout.copy()
new_layout[rev_trial_layout[e[0]]] = e[1]
new_layout[rev_trial_layout[e[1]]] = e[0]
rev_new_layout = rev_trial_layout.copy()
rev_new_layout[e[0]] = rev_trial_layout[e[1]]
rev_new_layout[e[1]] = rev_trial_layout[e[0]]
# Compute the objective function
new_cost = sum([xi[new_layout[g[0]]][new_layout[g[1]]]
for g in gates])
# Record progress if we succeed
if new_cost < min_cost:
progress_made = True
min_cost = new_cost
opt_layout = new_layout
rev_opt_layout = rev_new_layout
opt_edge = e
# Were there any good choices?
if progress_made:
qubit_set.remove(opt_edge[0])
qubit_set.remove(opt_edge[1])
trial_layout = opt_layout
rev_trial_layout = rev_opt_layout
circ.apply_operation_back(
SwapGate(),
[opt_edge[0], opt_edge[1]],
[])
else:
break
# We have either run out of qubits or failed to improve
# Compute the coupling graph distance_qubits
dist = sum([self.coupling_map.distance(trial_layout[g[0]].index,
trial_layout[g[1]].index) for g in gates])
# If all gates can be applied now, we are finished
# Otherwise we need to consider a deeper swap circuit
if dist == len(gates):
trial_circ.compose_back(circ, identity_wire_map)
break
# Increment the depth
d += 1
# Either we have succeeded at some depth d < dmax or failed
dist = sum([self.coupling_map.distance(trial_layout[g[0]].index,
trial_layout[g[1]].index) for g in gates])
if dist == len(gates):
if d < best_d:
best_circ = trial_circ
best_layout = trial_layout
best_d = min(best_d, d)
if best_circ is None:
return False, None, None, None, False
return True, best_circ, best_d, best_layout, False
def swap_mapper_layer_update(self, i, first_layer, best_layout, best_d,
best_circ, layer_list):
"""Update the QASM string for an iteration of swap_mapper.
i = layer number
first_layer = True if this is the first layer with multi-qubit gates
best_layout = layout returned from swap algorithm
best_d = depth returned from swap algorithm
best_circ = swap circuit returned from swap algorithm
layer_list = list of circuit objects for each layer
Return DAGCircuit object to append to the output DAGCircuit.
"""
layout = best_layout
dagcircuit_output = DAGCircuit()
QR = QuantumRegister(self.coupling_map.size(), 'q')
dagcircuit_output.add_qreg(QR)
# Identity wire-map for composing the circuits
identity_wire_map = {QR[j]: QR[j] for j in range(self.coupling_map.size())}
# If this is the first layer with multi-qubit gates,
# output all layers up to this point and ignore any
# swap gates. Set the initial layout.
if first_layer:
# Output all layers up to this point
for j in range(i + 1):
dagcircuit_output.compose_back(layer_list[j]["graph"], layout)
# Otherwise, we output the current layer and the associated swap gates.
else:
# Output any swaps
if best_d > 0:
dagcircuit_output.compose_back(best_circ, identity_wire_map)
# Output this layer
dagcircuit_output.compose_back(layer_list[i]["graph"], layout)
return dagcircuit_output
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] | 1.985046 | 8,760 |
"""
Module:
unicon.plugins.ironware.settings
Author:
James Di Trapani <[email protected]> - https://github.com/jamesditrapani
Description:
Define/Override Generic Settings specific to the Ironware NOS
"""
from unicon.plugins.generic.settings import GenericSettings
__author__ = "James Di Trapani <[email protected]>"
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] | 3.017544 | 114 |
#!/usr/bin/python
#import sys
# sys.path.append('/home/ruben/leaf/pycarwings2/pycarwings2')
import pycarwings2
import time
from ConfigParser import SafeConfigParser
import logging
import sys
import pprint
logging.basicConfig(stream=sys.stdout, level=logging.ERROR)
parser = SafeConfigParser()
candidates = ['config.ini', 'my_config.ini']
found = parser.read(candidates)
username = parser.get('get-leaf-info', 'username')
password = parser.get('get-leaf-info', 'password')
logging.debug("login = %s , password = %s" % (username, password))
print "Prepare Session"
s = pycarwings2.Session(username, password, "NE")
print "Login..."
l = s.get_leaf()
print "request_location"
result_key = l.request_location()
while True:
location_status = l.get_status_from_location(result_key)
if location_status is None:
print "Waiting for response (sleep 10)"
time.sleep(10)
else:
lat = location_status.latitude
lon = location_status.longitude
print("lat: {} long: {}".format(lat, lon))
# OpenStreetMap url, ctrl click in terminal to open browser,
# for example, my parking lot ;)
# http://www.openstreetmap.org/search?query=52.37309+4.89217#map=19/52.37310/4.89220
z = 19 # zoom level, lower is bigger area
print("http://www.openstreetmap.org/search?query={}%20{}#map={}/{}/{}".format(lat,lon,z,lat,lon))
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198,
220,
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2270
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from pypy.translator.oosupport.constant import is_primitive
from pypy.rpython.ootypesystem import ootype
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628
] | 3.028571 | 35 |
from ml100k import recommenderMl100k
import time as tm
from distances import recommender
s = recommender(0)
s.readMovies()
'''
s = recommender(0,k=3,metric='manhattan')
s.readBooks()
#print(s.jaccard(s.data['Stephen'],s.data['Amy']))
print(s.ProjectedRanting('Patrick C','Scarface'))
'''
'''
r = recommenderMl100k(0,metric='cosine')
r.loadMovieLens('../datasets/ml-100k/')
#print(r.cosine(r.data['278833"'],r.data['278858"']))
#print(r.jaccard(r.data['278804'],r.data['211']))
print(r.computeNearestNeighbor("100"))
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] | 2.368182 | 220 |
import os
import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
from textwrap import wrap
### NOTE: `conda install basemap`
import conda
conda_file_dir = conda.__file__
conda_dir = conda_file_dir.split('lib')[0]
proj_lib = os.path.join(os.path.join(conda_dir, 'share'), 'proj')
os.environ["PROJ_LIB"] = proj_lib
from mpl_toolkits.basemap import Basemap
from matplotlib import ticker
def vertical_bar_chart(df, x, y, label, sort, figsize=(13, 9), ascending=True):
"""
This customize vertical bar chart from seaborn(sns as aliased above)
Args:
df: dataframe
x: x-axis column
y: y-axis column
label: string to label the graph
figsize: figure size to make chart small or big
ascending: ascending order from smallest to biggest
sort: which column to sort by
Returns:
None
"""
sns.set(style="whitegrid")
fig, ax = plt.subplots(figsize=figsize)
#sns.set_color_codes(sns.color_palette(["#0088c0"]))
# Text on the top of each barplot
ax = sns.barplot(x=x, y=y, data=df.sort_values(sort, ascending=ascending),
label=label, color="b", palette=["#0088c0"])
total = df[y].sum()
for p in ax.patches:
ax.annotate(str(format(p.get_height()/total * 100, '.2f')) + '%' + ' (' + str(int(p.get_height())) + ')',
(p.get_x() + p.get_width() / 2., p.get_height()),
ha = 'center', va = 'center',
xytext = (0, 10), textcoords = 'offset points')
y_value=['{:,.0f}'.format(x/total * 100) + '%' for x in ax.get_yticks()]
plt.yticks(list(plt.yticks()[0]) + [10])
ax.set_yticklabels(y_value)
plt.xlabel('')
plt.ylabel('')
sns.despine(left=True, bottom=True)
def horizontal_bar_chart(df, x, y, label, figsize=(16, 16)):
"""
This customize horizontal bar chart from seaborn(sns as aliased above)
Args:
df: dataframe
x: x-axis column
y: y-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
sns.set(style="whitegrid")
fig, ax = plt.subplots(figsize=figsize)
ax = sns.barplot(x=x, y=y, data=df,
label=label, color="b", palette=["#0088c0"])
total = df.values[:, 1].sum()
for i, v in enumerate(df.values[:, 1]):
ax.text(v + 0.1, i + .25, str(format(v / total * 100, '.2f')) + '% (' + str(v) + ')')
labels = [ '\n'.join(wrap(l, 20)) for l in df.values[:, 0]]
ax.set_yticklabels(labels)
x_value=['{:,.0f}'.format(x/total * 100) + '%' for x in ax.get_xticks()]
plt.xticks(list(plt.xticks()[0]) + [10])
ax.set_xticklabels(x_value)
plt.ylabel('')
plt.xlabel('')
sns.despine(left=True, bottom=True)
def line_graph(df, column, figsize=(12, 8)):
"""
This customize line chart from matplotlib(plt as aliased above)
Args:
df: dataframe
column: x-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
fig, ax = plt.subplots(figsize=figsize)
line_data = df[column].value_counts().reset_index().sort_values(by='index')
line_data['Cumulative Frequency'] = line_data[column].cumsum()
line_data.plot(x='index', y=column, style='o-', ax=ax, label='Daily Infection')
line_data.plot(x='index', y='Cumulative Frequency', style='ro-', ax=ax)
plt.xticks(rotation=90)
plt.xlabel('')
def general_line_graph(df, x, y, figsize=(12, 8)):
"""
This customize line chart from matplotlib(plt as aliased above)
Args:
df: dataframe
column: x-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
fig, ax = plt.subplots(figsize=figsize)
df.plot(x=x, y=y, style='o-', ax=ax, label='Daily Tests')
plt.xticks(rotation=90)
plt.xlabel('')
def pie_chart(df, column):
"""
This customize pie chart from matplotlib(plt as aliased above)
Args:
df: dataframe
column: x-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
X = df[column].value_counts()
colors = ['#0088C0', '#82DAFF']
plt.pie(X.values, labels=X.index, colors=colors,
startangle=90,
explode = (0, 0),
textprops={'fontsize': 14},
autopct = '%1.2f%%')
plt.axis('equal')
plt.show()
def flat_globe(travel, colors):
"""
This customize map chart from Basemap(plt as aliased above)
Args:
df: dataframe
column: x-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
plt.figure(figsize = (30,30))
m = Basemap(projection='gall')
m.fillcontinents(color="#61993b",lake_color="#008ECC")
m.drawmapboundary(fill_color="#5D9BFF")
m.drawcountries(color='#585858',linewidth = 1)
m.drawstates(linewidth = 0.2)
m.drawcoastlines(linewidth=1)
countries = list(travel.Source.unique())
for item in countries:
for index, row in travel[travel.Source == item].drop_duplicates().iterrows():
x2, y2 = m.gcpoints( row["Source_Lat"], row["Source_Lon"], row["Dest_Lat"], row["Dest_Lon"], 20)
plt.plot(x2,y2,color=colors[countries.index(item)],linewidth=0.8)
plt.show()
def globe(travel, colors):
"""
This customize map chart from Basemap(plt as aliased above)
Args:
df: dataframe
column: x-axis column
label: string to label the graph
figsize: figure size to make chart small or big
Returns:
None
"""
plt.figure(figsize=(16,16))
m = Basemap(projection='ortho', lat_0=0, lon_0=0)
m.drawmapboundary(fill_color='#5D9BFF')
m.fillcontinents(color='#0D9C29',lake_color='#008ECC')
m.drawcountries(color='#585858',linewidth=1)
m.drawcoastlines()
countries = list(travel.Source.unique())
for item in countries:
for index, row in travel[travel.Source == item].drop_duplicates().iterrows():
x2, y2 = m.gcpoints( row["Source_Lat"], row["Source_Lon"], row["Dest_Lat"], row["Dest_Lon"], 20)
plt.plot(x2,y2,color=colors[countries.index(item)],linewidth=0.8)
plt.show()
def plot_covid19za_grouwth(df, provinces, min_cases=100, ls='-', figsize=(12, 8)):
"""
This shows covid19za growth since the first case was reported
from each province
"""
fig, ax = plt.subplots(figsize=figsize)
df = (df.set_index('date'))
df.index = pd.to_datetime(df.index, dayfirst=True)
for province in provinces:
df1 = df.loc[(df.province == province)].groupby(['date']).agg({'country': ['count']})
df1.columns = ['new cases']
df1['cummulative'] = df1['new cases'].cumsum()
(df1.reset_index()['cummulative']
.plot(label=province, ls=ls))
x = np.linspace(0, plt.xlim()[1])
plt.plot(x,x+(1.33), ls='--', color='k', label='33% daily growth')
plt.title('Data up to {}'.format(df.index.max().strftime('%B %d, %Y')))
plt.xlabel('Days from first confirmed case')
plt.ylabel('Confirmed cases')
ax.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
ax.set_xticks(range(0,int(plt.xlim()[1])+1))
plt.legend(bbox_to_anchor=(1.0, 1.0))
sns.despine()
plt.annotate('Based on Coronavirus COVID-19 (2019-nCoV) Data Repository for South Africa \
[Hosted by DSFSI group at University of Pretoria]',
(0.1, 0.01), xycoords='figure fraction', fontsize=10)
def flat_mutipath_globe(df_travel, path_route, colors, all_starting_countries):
"""
This is flat structure for multistop
"""
plt.figure(figsize = (30,30))
m = Basemap(projection='gall')
m.fillcontinents(color="#61993b",lake_color="#008ECC")
m.drawmapboundary(fill_color="#5D9BFF")
m.drawcountries(color='#585858',linewidth = 1)
m.drawstates(linewidth = 0.2)
m.drawcoastlines(linewidth=1)
for path_rout in path_route:
if path_rout[0][0] == 'USA;Mexico':
point_a = df_travel[df_travel.country_or_province_travelled == path_rout[0][0].split(';')[0]]
point_b = df_travel[df_travel.country_or_province_travelled == path_rout[0][0].split(';')[1]]
point_c = df_travel[df_travel.country_or_province_travelled == path_rout[0][1]]
point_d = df_travel[df_travel.country_or_province_travelled == path_rout[1]]
x2, y2 = m.gcpoints(point_a["latitude"],point_a["longitude"],point_b["latitude"],point_b["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0].split(';')[0])],linewidth=3)
# m.scatter(point_a["latitude"],point_a["longitude"], marker='^',color="#EC7063", s=500,zorder=5)
# plt.text(point_a["latitude"],point_a["longitude"]+10000,path_rout[0][0].split(';')[0].replace('the ', ''),fontsize=20,fontweight='bold',ha='center',va='bottom',color="black")
x2, y2 = m.gcpoints(point_b["latitude"],point_b["longitude"],point_c["latitude"],point_c["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0].split(';')[0])],linewidth=3)
x2, y2 = m.gcpoints(point_c["latitude"],point_c["longitude"],point_d["latitude"],point_d["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0].split(';')[0])],linewidth=3)
elif len(path_rout[0]) == 2:
point_a = df_travel[df_travel.country_or_province_travelled == path_rout[0][0].replace('the ', '')]
point_b = df_travel[df_travel.country_or_province_travelled == path_rout[0][1].replace('the ', '')]
point_c = df_travel[df_travel.country_or_province_travelled == path_rout[1].replace('LP', 'LIM')]
x2, y2 = m.gcpoints(point_a["latitude"],point_a["longitude"],point_b["latitude"],point_b["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0].replace('the ', ''))],linewidth=3)
# m.scatter(x2, y2, marker='^',color="#EC7063", s=500,zorder=5)
# plt.text(x2,y2,path_rout[0][0].replace('the ', ''),fontsize=20,fontweight='bold',ha='center',va='bottom',color="black")
x2, y2 = m.gcpoints(point_b["latitude"],point_b["longitude"],point_c["latitude"],point_c["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0].replace('the ', ''))],linewidth=3)
elif len(path_rout[0]) == 3:
point_a = df_travel[df_travel.country_or_province_travelled == path_rout[0][0]]
point_b = df_travel[df_travel.country_or_province_travelled == path_rout[0][1]]
point_c = df_travel[df_travel.country_or_province_travelled == path_rout[0][2]]
point_d = df_travel[df_travel.country_or_province_travelled == path_rout[1]]
x2, y2 = m.gcpoints(point_a["latitude"],point_a["longitude"],point_b["latitude"],point_b["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=0.8)
# m.scatter(x2, y2, marker='^',color="#EC7063", s=500,zorder=5)
# plt.text(x2,y2,path_rout[0][0],fontsize=20,fontweight='bold',ha='center',va='bottom',color="black")
x2, y2 = m.gcpoints(point_b["latitude"],point_b["longitude"],point_c["latitude"],point_c["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=0.8)
x2, y2 = m.gcpoints(point_c["latitude"],point_c["longitude"],point_d["latitude"],point_d["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=3)
elif len(path_rout[0]) == 4:
point_a = df_travel[df_travel.country_or_province_travelled == path_rout[0][0]]
point_b = df_travel[df_travel.country_or_province_travelled == path_rout[0][1]]
point_c = df_travel[df_travel.country_or_province_travelled == path_rout[0][2]]
point_d = df_travel[df_travel.country_or_province_travelled == path_rout[0][3]]
point_e = df_travel[df_travel.country_or_province_travelled == path_rout[1]]
x2, y2 = m.gcpoints(point_a["latitude"],point_a["longitude"],point_b["latitude"],point_b["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=3)
# m.scatter(x2, y2, marker='^',color="#EC7063", s=500,zorder=5)
# plt.text(x2,y2,path_rout[0][0],fontsize=20,fontweight='bold',ha='center',va='bottom',color="black")
x2, y2 = m.gcpoints(point_b["latitude"],point_b["longitude"],point_c["latitude"],point_c["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=3)
x2, y2 = m.gcpoints(point_c["latitude"],point_c["longitude"],point_d["latitude"],point_d["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=3)
x2, y2 = m.gcpoints(point_d["latitude"],point_d["longitude"],point_e["latitude"],point_e["longitude"], 20)
plt.plot(x2,y2,color = colors[all_starting_countries.index(path_rout[0][0])],linewidth=3)
plt.show()
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18,
8,
198,
220,
220,
220,
458,
83,
13,
12860,
3419,
198
] | 2.139079 | 6,428 |
"""
Вывести в порядке возрастания все простые числа, расположенные между n и m (включая сами числа n и m),
а также количество x этих чисел.
"""
start_number = int(input("Enter start number:"))
end_number = int(input("Enter end number:"))
# Generate elements from start_number to end_number (including)
my_count = 0
for element in range(start_number, end_number + 1):
# Check if this element is the prime number
is_prime = True
for divider in range(2, element):
# If we've found any divider the remainder of which is zero
# So current element is not the prime number
if divider > 1 and element % divider == 0:
is_prime = False
break
# Current element is the prime number
if is_prime:
print(element)
my_count += 1
print("Total count of prime numbers")
print(my_count)
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286,
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62,
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8,
198
] | 2.13217 | 401 |
import pandas as pd
import smtplib
import imghdr
from email.message import EmailMessage
SenderAddress = "[email protected]"
password = "ndXX@XX3$#XXX"
e = pd.read_excel("email.xlsx")
emails = e['Emails'].values
names = e["Names"].values
file = "banner.jpg"
msg = EmailMessage()
msg['Subject'] = "Hello world - dynamic"
msg['From'] = SenderAddress
print(f"The receiver's mail ids are : \n\n{emails}")
with smtplib.SMTP("smtp.gmail.com", 587, timeout=15) as server:
server.starttls()
server.login(SenderAddress, password)
# msg = f"Hello {this is an email form python"
# subject = "Hello world"
# body = "Subject: {}\n\n{}".format(subject,msg)
with open(file, 'rb') as f:
file_data = f.read()
file_type = imghdr.what(f.name)
file_name = f.name
for email,name in zip(emails,names):
msg['To'] = email
body = f"Hello {name};\n\n\nThis is an email from python"
# msg = "Subject: {}\n\n{}".format(subject,body)
msg.set_content(body)
msg.add_attachment(file_data, maintype='image', subtype=file_type, filename=file_name)
server.send_message(msg)
# server.sendmail(SenderAddress, email, msg)
server.quit()
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1,
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2,
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7,
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13,
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7,
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11,
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9060,
3256,
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4906,
28,
7753,
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11,
3053,
11,
31456,
8,
198,
197,
15388,
13,
47391,
3419,
198
] | 2.524554 | 448 |
def set_points(self, points):
"""
Set coordinate polygon by given string.
Moreover, invalidate the parent's ``pc:AlternativeImage``s
(because they will have been cropped with a bbox
of the previous polygon).
"""
if hasattr(self, 'parent_object_'):
parent = self.parent_object_
if hasattr(parent, 'invalidate_AlternativeImage'):
# RegionType, TextLineType, WordType, GlyphType:
parent.invalidate_AlternativeImage()
elif hasattr(parent, 'parent_object_') and hasattr(parent.parent_object_, 'invalidate_AlternativeImage'):
# BorderType:
parent.parent_object_.invalidate_AlternativeImage(feature_selector='cropped')
self.points = points
| [
4299,
900,
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220,
220,
220,
1303,
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25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2560,
13,
8000,
62,
15252,
44807,
259,
12102,
378,
62,
49788,
5159,
7,
30053,
62,
19738,
273,
11639,
19915,
1496,
11537,
198,
220,
220,
220,
2116,
13,
13033,
796,
2173,
198
] | 2.651079 | 278 |
"""This module provides functions that make sure environment to be compatible with RLlib. If Rllib is not used, please
directly use the wrapper in comm_channel.py."""
import numpy as np
from pettingzoo.utils.conversions import to_parallel_wrapper
from pettingzoo.utils.wrappers import AssertOutOfBoundsWrapper, OrderEnforcingWrapper
from ray.rllib.env import PettingZooEnv
from ray.rllib.env.wrappers.pettingzoo_env import ParallelPettingZooEnv
from supersuit import pad_action_space_v0, pad_observations_v0
from comm_channel import ParallelCommWrapper, CommWrapper
def main_comm_env(base_env, comm_dict):
"""Wrap the communication channel into Pettingzoo main environment, and padding the environment."""
return comm_env
def main_env(base_env):
"""Padding the environment."""
return env
def parallel_comm_env(base_env, comm_dict):
"""Wrap the communication channel into Pettingzoo parallel environment, and padding the environment."""
return comm_env
def parallel_env(base_env):
"""Padding the parallel environment."""
return env
| [
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47,
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262,
2858,
526,
15931,
198,
220,
220,
220,
1441,
17365,
628,
198,
4299,
10730,
62,
9503,
62,
24330,
7,
8692,
62,
24330,
11,
725,
62,
11600,
2599,
198,
220,
220,
220,
37227,
54,
2416,
262,
6946,
6518,
656,
4767,
889,
89,
2238,
10730,
2858,
11,
290,
24511,
262,
2858,
526,
15931,
198,
220,
220,
220,
1441,
725,
62,
24330,
628,
198,
4299,
10730,
62,
24330,
7,
8692,
62,
24330,
2599,
198,
220,
220,
220,
37227,
47,
26872,
262,
10730,
2858,
526,
15931,
198,
220,
220,
220,
1441,
17365,
628,
628,
198
] | 3.283537 | 328 |
import abc
import random
import string
from typing import Generator, Iterable, Mapping, Optional, Tuple
| [
11748,
450,
66,
198,
11748,
4738,
198,
11748,
4731,
198,
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1330,
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11,
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540,
11,
337,
5912,
11,
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11,
309,
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628,
628,
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] | 3.892857 | 28 |
# 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.
"""
Implementations of abstract role interfaces. Test cases can get objects from
here via the testbed attribute. The `get_role` method queries the implementation
field of an equipment, that should point to something in here. But it could be
in another package.
"""
import abc
from .. import importlib
from .. import config
class BaseRole(metaclass=abc.ABCMeta):
"""Base, abstract, role for equipment role controllers."""
class SoftwareRole(metaclass=abc.ABCMeta):
"""Base, abstract, role for software objects.
Usually, this is an emulator of some kind."""
def get_role(classpath):
"""Get a role implementation by its path name."""
return importlib.get_class(classpath, __name__)
# vim:ts=4:sw=4:softtabstop=4:smarttab:expandtab:fileencoding=utf-8
| [
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7,
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11,
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8,
628,
198,
2,
43907,
25,
912,
28,
19,
25,
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28,
19,
25,
4215,
8658,
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28,
19,
25,
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8658,
25,
11201,
392,
8658,
25,
7753,
12685,
7656,
28,
40477,
12,
23,
198
] | 3.594005 | 367 |
import brownie
YEAR = 86400 * 365
| [
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198,
198,
56,
17133,
796,
807,
2414,
405,
1635,
21268,
628,
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] | 2.533333 | 15 |
from ta.momentum import rsi
if __name__ == "__main__":
_rsi14 = rsi(Closes, 14)
| [
6738,
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13,
32542,
298,
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] | 2.179487 | 39 |
import lib1 as iks
| [
11748,
9195,
16,
355,
1312,
591,
198
] | 2.714286 | 7 |
#------------------------------------------------------------------------------
# Copyright (c) 2013, Nucleic Development Team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
#------------------------------------------------------------------------------
import sys
from setuptools import setup, find_packages, Extension
ext_modules = [
Extension(
'enaml.weakmethod',
['enaml/src/weakmethod.cpp'],
language='c++',
),
Extension(
'enaml.callableref',
['enaml/src/callableref.cpp'],
language='c++',
),
Extension(
'enaml.signaling',
['enaml/src/signaling.cpp'],
language='c++',
),
Extension(
'enaml.core.funchelper',
['enaml/src/funchelper.cpp'],
language='c++',
),
Extension(
'enaml.colorext',
['enaml/src/colorext.cpp'],
language='c++',
),
Extension(
'enaml.fontext',
['enaml/src/fontext.cpp'],
language='c++',
),
Extension(
'enaml.core.dynamicscope',
['enaml/src/dynamicscope.cpp'],
language='c++',
),
Extension(
'enaml.core.alias',
['enaml/src/alias.cpp'],
language='c++',
)
]
if sys.platform == 'win32':
ext_modules.append(
Extension(
'enaml.winutil',
['enaml/src/winutil.cpp'],
libraries=['user32', 'gdi32'],
language='c++'
)
)
setup(
name='enaml',
version='0.8.8',
author='The Nucleic Development Team',
author_email='[email protected]',
url='https://github.com/nucleic/enaml',
description='Declarative DSL for building rich user interfaces in Python',
long_description=open('README.md').read(),
requires=['atom', 'PyQt', 'ply', 'casuarius'],
install_requires=['distribute'],
packages=find_packages(),
package_data={
'enaml.applib': ['*.enaml'],
'enaml.stdlib': ['*.enaml'],
'enaml.qt.docking': [
'dock_images/*.png',
'dock_images/*.py',
'enaml_dock_resources.qrc'
],
},
entry_points={'console_scripts': ['enaml-run = enaml.runner:main']},
ext_modules=ext_modules,
)
| [
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__author__='administrator'
# -*- coding:utf-8 -*-
import unittest
import time
# if __name__=="__main__":
# unittest.main()
# tester=Test()
# tester.setUp()
# tester.test01()
# tester.test02()
# tester.test03()
# tester.tearDown() | [
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from scipy import fftpack, ndimage, signal
import numpy as np
import threading
#from scipy._lib._version import NumpyVersion
_rfft_mt_safe = True # (NumpyVersion(np.__version__) >= '1.9.0.dev-e24486e')
_rfft_lock = threading.Lock()
import lenstronomy.Util.kernel_util as kernel_util
import lenstronomy.Util.util as util
import lenstronomy.Util.image_util as image_util
from lenstronomy.Util.package_util import exporter
export, __all__ = exporter()
@export
class PixelKernelConvolution(object):
"""
class to compute convolutions for a given pixelized kernel (fft, grid)
"""
def __init__(self, kernel, convolution_type='fft_static'):
"""
:param kernel: 2d array, convolution kernel
:param convolution_type: string, 'fft', 'grid', 'fft_static' mode of 2d convolution
"""
self._kernel = kernel
if convolution_type not in ['fft', 'grid', 'fft_static']:
raise ValueError('convolution_type %s not supported!' % convolution_type)
self._type = convolution_type
self._pre_computed = False
def pixel_kernel(self, num_pix=None):
"""
access pixelated kernel
:param num_pix: size of returned kernel (odd number per axis). If None, return the original kernel.
:return: pixel kernel centered
"""
if num_pix is not None:
return kernel_util.cut_psf(self._kernel, num_pix)
return self._kernel
def copy_transpose(self):
"""
:return: copy of the class with kernel set to the transpose of original one
"""
return PixelKernelConvolution(self._kernel.T, convolution_type=self._type)
def convolution2d(self, image):
"""
:param image: 2d array (image) to be convolved
:return: fft convolution
"""
if self._type == 'fft':
image_conv = signal.fftconvolve(image, self._kernel, mode='same')
elif self._type == 'fft_static':
image_conv = self._static_fft(image, mode='same')
elif self._type == 'grid':
image_conv = signal.convolve2d(image, self._kernel, mode='same')
else:
raise ValueError('convolution_type %s not supported!' % self._type)
return image_conv
def _static_fft(self, image, mode='same'):
"""
scipy fft convolution with saved static fft kernel
:param image: 2d numpy array to be convolved
:return:
"""
in1 = image
in1 = np.asarray(in1)
if self._pre_computed is False:
self._s1, self._s2, self._complex_result, self._shape, self._fshape, self._fslice, self._sp2 = self._static_pre_compute(image)
self._pre_computed = True
s1, s2, complex_result, shape, fshape, fslice, sp2 = self._s1, self._s2, self._complex_result, self._shape, self._fshape, self._fslice, self._sp2
#if in1.ndim == in2.ndim == 0: # scalar inputs
# return in1 * in2
#elif not in1.ndim == in2.ndim:
# raise ValueError("in1 and in2 should have the same dimensionality")
#elif in1.size == 0 or in2.size == 0: # empty arrays
# return np.array([])
# Check that input sizes are compatible with 'valid' mode
#if _inputs_swap_needed(mode, s1, s2):
# Convolution is commutative; order doesn't have any effect on output
# only applicable for 'valid' mode
# in1, s1, in2, s2 = in2, s2, in1, s1
# Pre-1.9 NumPy FFT routines are not threadsafe. For older NumPys, make
# sure we only call rfftn/irfftn from one thread at a time.
if not complex_result and (_rfft_mt_safe or _rfft_lock.acquire(False)):
try:
sp1 = np.fft.rfftn(in1, fshape)
ret = (np.fft.irfftn(sp1 * sp2, fshape)[fslice].copy())
finally:
if not _rfft_mt_safe:
_rfft_lock.release()
else:
# If we're here, it's either because we need a complex result, or we
# failed to acquire _rfft_lock (meaning rfftn isn't threadsafe and
# is already in use by another thread). In either case, use the
# (threadsafe but slower) SciPy complex-FFT routines instead.
sp1 = fftpack.fftn(in1, fshape)
ret = fftpack.ifftn(sp1 * sp2)[fslice].copy()
if not complex_result:
ret = ret.real
if mode == "full":
return ret
elif mode == "same":
return _centered(ret, s1)
elif mode == "valid":
return _centered(ret, s1 - s2 + 1)
else:
raise ValueError("Acceptable mode flags are 'valid',"
" 'same', or 'full'.")
def _static_pre_compute(self, image):
"""
pre-compute Fourier transformed kernel and shape quantities to speed up convolution
:param image: 2d numpy array
:return:
"""
in1 = image
in2 = self._kernel
s1 = np.array(in1.shape)
s2 = np.array(in2.shape)
complex_result = (np.issubdtype(in1.dtype, np.complexfloating) or
np.issubdtype(in2.dtype, np.complexfloating))
shape = s1 + s2 - 1
# Check that input sizes are compatible with 'valid' mode
# if _inputs_swap_needed(mode, s1, s2):
# Convolution is commutative; order doesn't have any effect on output
# only applicable for 'valid' mode
# in1, s1, in2, s2 = in2, s2, in1, s1
# Speed up FFT by padding to optimal size for FFTPACK
fshape = [fftpack.helper.next_fast_len(int(d)) for d in shape]
fslice = tuple([slice(0, int(sz)) for sz in shape])
# Pre-1.9 NumPy FFT routines are not threadsafe. For older NumPys, make
# sure we only call rfftn/irfftn from one thread at a time.
if not complex_result and (_rfft_mt_safe or _rfft_lock.acquire(False)):
try:
sp2 = np.fft.rfftn(in2, fshape)
finally:
if not _rfft_mt_safe:
_rfft_lock.release()
else:
# If we're here, it's either because we need a complex result, or we
# failed to acquire _rfft_lock (meaning rfftn isn't threadsafe and
# is already in use by another thread). In either case, use the
# (threadsafe but slower) SciPy complex-FFT routines instead.
sp2 = fftpack.fftn(in2, fshape)
return s1, s2, complex_result, shape, fshape, fslice, sp2
def re_size_convolve(self, image_low_res, image_high_res=None):
"""
:param image_high_res: supersampled image/model to be convolved on a regular pixel grid
:return: convolved and re-sized image
"""
return self.convolution2d(image_low_res)
@export
class SubgridKernelConvolution(object):
"""
class to compute the convolution on a supersampled grid with partial convolution computed on the regular grid
"""
def __init__(self, kernel_supersampled, supersampling_factor, supersampling_kernel_size=None, convolution_type='fft_static'):
"""
:param kernel_supersampled: kernel in supersampled pixels
:param supersampling_factor: supersampling factor relative to the image pixel grid
:param supersampling_kernel_size: number of pixels (in units of the image pixels) that are convolved with the
supersampled kernel
"""
n_high = len(kernel_supersampled)
self._supersampling_factor = supersampling_factor
numPix = int(n_high / self._supersampling_factor)
#if self._supersampling_factor % 2 == 0:
# self._kernel = kernel_util.averaging_even_kernel(kernel_supersampled, self._supersampling_factor)
#else:
# self._kernel = util.averaging(kernel_supersampled, numGrid=n_high, numPix=numPix)
if supersampling_kernel_size is None:
kernel_low_res, kernel_high_res = np.zeros((3, 3)), kernel_supersampled
self._low_res_convolution = False
else:
kernel_low_res, kernel_high_res = kernel_util.split_kernel(kernel_supersampled, supersampling_kernel_size,
self._supersampling_factor)
self._low_res_convolution = True
self._low_res_conv = PixelKernelConvolution(kernel_low_res, convolution_type=convolution_type)
self._high_res_conv = PixelKernelConvolution(kernel_high_res, convolution_type=convolution_type)
def convolution2d(self, image):
"""
:param image: 2d array (high resoluton image) to be convolved and re-sized
:return: convolved image
"""
image_high_res_conv = self._high_res_conv.convolution2d(image)
image_resized_conv = image_util.re_size(image_high_res_conv, self._supersampling_factor)
if self._low_res_convolution is True:
image_resized = image_util.re_size(image, self._supersampling_factor)
image_resized_conv += self._low_res_conv.convolution2d(image_resized)
return image_resized_conv
def re_size_convolve(self, image_low_res, image_high_res):
"""
:param image_high_res: supersampled image/model to be convolved on a regular pixel grid
:return: convolved and re-sized image
"""
image_high_res_conv = self._high_res_conv.convolution2d(image_high_res)
image_resized_conv = image_util.re_size(image_high_res_conv, self._supersampling_factor)
if self._low_res_convolution is True:
image_resized_conv += self._low_res_conv.convolution2d(image_low_res)
return image_resized_conv
@export
class MultiGaussianConvolution(object):
"""
class to perform a convolution consisting of multiple 2d Gaussians
This is aimed to lead to a speed-up without significant loss of accuracy do to the simplified convolution kernel
relative to a pixelized kernel.
"""
def __init__(self, sigma_list, fraction_list, pixel_scale, supersampling_factor=1, supersampling_convolution=False,
truncation=2):
"""
:param sigma_list: list of std value of Gaussian kernel
:param fraction_list: fraction of flux to be convoled with each Gaussian kernel
:param pixel_scale: scale of pixel width (to convert sigmas into units of pixels)
:param truncation: float. Truncate the filter at this many standard deviations.
Default is 4.0.
"""
self._num_gaussians = len(sigma_list)
self._sigmas_scaled = np.array(sigma_list) / pixel_scale
if supersampling_convolution is True:
self._sigmas_scaled *= supersampling_factor
self._fraction_list = fraction_list / np.sum(fraction_list)
assert len(self._sigmas_scaled) == len(self._fraction_list)
self._truncation = truncation
self._pixel_scale = pixel_scale
self._supersampling_factor = supersampling_factor
self._supersampling_convolution = supersampling_convolution
def convolution2d(self, image):
"""
2d convolution
:param image: 2d numpy array, image to be convolved
:return: convolved image, 2d numpy array
"""
image_conv = None
for i in range(self._num_gaussians):
if image_conv is None:
image_conv = ndimage.filters.gaussian_filter(image, self._sigmas_scaled[i], mode='nearest',
truncate=self._truncation) * self._fraction_list[i]
else:
image_conv += ndimage.filters.gaussian_filter(image, self._sigmas_scaled[i], mode='nearest',
truncate=self._truncation) * self._fraction_list[i]
return image_conv
def re_size_convolve(self, image_low_res, image_high_res):
"""
:param image_high_res: supersampled image/model to be convolved on a regular pixel grid
:return: convolved and re-sized image
"""
if self._supersampling_convolution is True:
image_high_res_conv = self.convolution2d(image_high_res)
image_resized_conv = image_util.re_size(image_high_res_conv, self._supersampling_factor)
else:
image_resized_conv = self.convolution2d(image_low_res)
return image_resized_conv
def pixel_kernel(self, num_pix):
"""
computes a pixelized kernel from the MGE parameters
:param num_pix: int, size of kernel (odd number per axis)
:return: pixel kernel centered
"""
from lenstronomy.LightModel.Profiles.gaussian import MultiGaussian
mg = MultiGaussian()
x, y = util.make_grid(numPix=num_pix, deltapix=self._pixel_scale)
kernel = mg.function(x, y, amp=self._fraction_list, sigma=self._sigmas_scaled)
kernel = util.array2image(kernel)
return kernel / np.sum(kernel)
@export
class FWHMGaussianConvolution(object):
"""
uses a two-dimensional Gaussian function with same FWHM of given kernel as approximation
"""
def __init__(self, kernel, truncation=4):
"""
:param kernel: 2d kernel
:param truncation: sigma scaling of kernel truncation
"""
fwhm = kernel_util.fwhm_kernel(kernel)
self._sigma = util.fwhm2sigma(fwhm)
self._truncation = truncation
def convolution2d(self, image):
"""
2d convolution
:param image: 2d numpy array, image to be convolved
:return: convolved image, 2d numpy array
"""
image_conv = ndimage.filters.gaussian_filter(image, self._sigma, mode='nearest', truncate=self._truncation)
return image_conv
@export
class MGEConvolution(object):
"""
approximates a 2d kernel with an azimuthal Multi-Gaussian expansion
"""
def __init__(self, kernel, pixel_scale, order=1):
"""
:param kernel: 2d convolution kernel (centered, odd axis number)
:param order: order of Multi-Gaussian Expansion
"""
#kernel_util.fwhm_kernel(kernel)
amps, sigmas, norm = kernel_util.mge_kernel(kernel, order=order)
# make instance o MultiGaussian convolution kernel
self._mge_conv = MultiGaussianConvolution(sigma_list=sigmas*pixel_scale, fraction_list=np.array(amps) / np.sum(amps),
pixel_scale=pixel_scale, truncation=4)
self._kernel = kernel
# store difference between MGE approximation and real kernel
def convolution2d(self, image):
"""
:param image:
:return:
"""
return self._mge_conv.convolution2d(image)
def kernel_difference(self):
"""
:return: difference between true kernel and MGE approximation
"""
kernel_mge = self._mge_conv.pixel_kernel(num_pix=len(self._kernel))
return self._kernel - kernel_mge
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1441,
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] | 2.278181 | 6,618 |
import plistlib
filename = "/Applications/Safari.app/Contents/Info.plist"
info = plistlib.readPlist(filename)
info["CFBundleGetInfoString"]
version = info["CFBundleShortVersionString"]
print version
print info["CFBundleURLTypes"]
print info["CFBundleURLTypes"][0]
print info["CFBundleURLTypes"][0]["CFBundleURLSchemes"]
print info["CFBundleURLTypes"][0]["CFBundleURLSchemes"][0]
filename = "/Library/Preferences/com.apple.loginwindow.plist"
plistinfo = plistlib.readPlist(filename)
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] | 2.83237 | 173 |
# Generated by Django 4.0 on 2022-03-28 09:59
from django.db import migrations, models
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# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
from django.db.models import Q
from django.http import Http404
from django.shortcuts import render, get_object_or_404, redirect
from .forms import QuestionForm, AnswerForm
from .models import Category, Question, Answer, SendNotification
# Create your views here.
@login_required()
@login_required()
@login_required()
@login_required()
@login_required()
@login_required()
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] | 3.322581 | 186 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
HTTP Protocol Binding implementation.
.. autosummary::
:toctree: _http
wotpy.protocols.http.handlers
wotpy.protocols.http.client
wotpy.protocols.http.enums
wotpy.protocols.http.server
"""
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] | 2.289474 | 114 |
from dwave_networkx.utils import binary_quadratic_model_sampler
__all__ = ["maximum_independent_set", "is_independent_set"]
@binary_quadratic_model_sampler(1)
def maximum_independent_set(G, sampler=None, **sampler_args):
"""Returns an approximate maximum independent set.
Defines a QUBO with ground states corresponding to a
maximum independent set and uses the sampler to sample from
it.
An independent set is a set of nodes such that the subgraph
of G induced by these nodes contains no edges. A maximum
independent set is an independent set of largest possible size.
Parameters
----------
G : NetworkX graph
sampler
A binary quadratic model sampler. A sampler is a process that
samples from low energy states in models defined by an Ising
equation or a Quadratic Unconstrained Binary Optimization
Problem (QUBO). A sampler is expected to have a 'sample_qubo'
and 'sample_ising' method. A sampler is expected to return an
iterable of samples, in order of increasing energy. If no
sampler is provided, one must be provided using the
`set_default_sampler` function.
sampler_args
Additional keyword parameters are passed to the sampler.
Returns
-------
indep_nodes : list
List of nodes that the form a maximum independent set, as
determined by the given sampler.
Examples
--------
>>> G = nx.path_graph(5)
>>> dnx.maximum_independent_set(G, sampler)
[0, 2, 4]
Notes
-----
Samplers by their nature may not return the optimal solution. This
function does not attempt to confirm the quality of the returned
sample.
https://en.wikipedia.org/wiki/Independent_set_(graph_theory)
https://en.wikipedia.org/wiki/Quadratic_unconstrained_binary_optimization
References
----------
.. [AL] Lucas, A. (2014). Ising formulations of many NP problems.
Frontiers in Physics, Volume 2, Article 5.
"""
# We assume that the sampler can handle an unstructured QUBO problem, so let's set one up.
# Let us define the largest independent set to be S.
# For each node n in the graph, we assign a boolean variable v_n, where v_n = 1 when n
# is in S and v_n = 0 otherwise.
# We call the matrix defining our QUBO problem Q.
# On the diagnonal, we assign the linear bias for each node to be -1. This means that each
# node is biased towards being in S
# On the off diagnonal, we assign the off-diagonal terms of Q to be 2. Thus, if both
# nodes are in S, the overall energy is increased by 2.
Q = {(node, node): -1 for node in G}
Q.update({edge: 2 for edge in G.edges})
# use the sampler to find low energy states
response = sampler.sample_qubo(Q, **sampler_args)
# we want the lowest energy sample
sample = next(iter(response))
# nodes that are spin up or true are exactly the ones in S.
return [node for node in sample if sample[node] > 0]
def is_independent_set(G, indep_nodes):
"""Determines whether the given nodes form an independent set.
An independent set is a set of nodes such that the subgraph
of G induced by these nodes contains no edges.
Parameters
----------
G : NetworkX graph
indep_nodes : list
List of nodes that the form a maximum independent set, as
determined by the given sampler.
Returns
-------
is_independent : bool
True if indep_nodes form an independent set.
"""
return not bool(G.subgraph(indep_nodes).edges)
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] | 3.020202 | 1,188 |
#!/usr/bin/env python3
"""
Launcher for AoC 2016 puzzles.
Handles puzzle selection and puzzle input.
"""
import day_1_no_time_for_a_taxicab as d1
import day_2_bathroom_security as d2
if __name__ == '__main__':
AVAILABLE_PUZZLES = {1: run_taxicab, 2:run_keypad}
print('Welcome to inifinity! Try an available solution to AoC 2016 puzzles in', \
list(AVAILABLE_PUZZLES.keys()), 'or enter EOF to quit!')
while True:
puzzle = None
try:
puzzle = int(input('Please select a puzzle: '))
if puzzle not in AVAILABLE_PUZZLES:
print('That puzzle\'s solution is not available! Try one of', \
list(AVAILABLE_PUZZLES.keys()))
puzzle = None
else:
AVAILABLE_PUZZLES[puzzle]()
except ValueError:
print('Please input an integer!')
except EOFError:
print('\nThanks for playing, happy holidays!')
break
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] | 2.143478 | 460 |
from django import forms
from models import Student
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] | 3.928571 | 14 |
from django.db import models
from django.contrib.auth.models import User
| [
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] | 2.925926 | 27 |
from _thread import *
import threading
import socket
import json
# team: PWA
# member: 0870508 Tyas van de Spree
# member: 0966770 Maarten de Goede
# class: DINF2
BYTE_SIZE = 1024
TEAMNAME = "PWA" # programmers with attitude
CLASSNAME = "DINF2"
TEAMMATESTUDENTNR = ''
STUDENTNR = input("Please provide your student number")
if STUDENTNR == "0870508" or STUDENTNR == "":
if STUDENTNR == "":
STUDENTNR = "0870508"
TEAMMATESTUDENTNR = '0966770'
elif STUDENTNR == '0966770':
TEAMMATESTUDENTNR = '0870508'
SERVERIP = '145.24.238.191'
MYIP = socket.gethostbyname(socket.gethostbyname("localhost"))
peerIp = input("Please provide the ip of the peer client you wish to connect with. If left blank will run as both clients")
if peerIp == '':
peerIp = MYIP
print_lock = threading.Lock()
# create a peerListenerSocket object
serverSocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
peerConnectionSocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
messageReceived = False
if __name__ == '__main__':
Main()
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7,
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62,
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13,
50,
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62,
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8,
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10352,
628,
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198,
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6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
8774,
3419,
198
] | 2.75 | 384 |
from typing import Callable, Optional
from airflow.decorators.base import task_decorator_factory
from astro.sql.operators.sql_dataframe import SqlDataframeOperator
def dataframe(
python_callable: Optional[Callable] = None,
multiple_outputs: Optional[bool] = None,
conn_id: str = "",
database: Optional[str] = None,
schema: Optional[str] = None,
warehouse: Optional[str] = None,
task_id: Optional[str] = None,
identifiers_as_lower: Optional[bool] = True,
):
"""
This function allows a user to run python functions in Airflow but with the huge benefit that SQL files
will automatically be turned into dataframes and resulting dataframes can automatically used in astro.sql functions
"""
param_map = {
"conn_id": conn_id,
"database": database,
"schema": schema,
"warehouse": warehouse,
"identifiers_as_lower": identifiers_as_lower,
}
if task_id:
param_map["task_id"] = task_id
return task_decorator_factory(
python_callable=python_callable,
multiple_outputs=multiple_outputs,
decorated_operator_class=SqlDataframeOperator, # type: ignore
**param_map,
)
| [
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220,
12429,
17143,
62,
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11,
198,
220,
220,
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198
] | 2.685268 | 448 |
from django.urls import path
from . import views
urlpatterns = [
path(r'classroom/', views.classroom, name='classroom'),
path(r'synopsis/', views.UnitGroupListView.as_view(), name='synopsis'),
path(r'unit/problems/<int:pk>/', views.unit_problems, name='view-problems'),
path(r'unit/tex/<int:pk>/', views.unit_tex, name='view-tex'),
path(r'unit/solutions/<int:pk>/', views.unit_solutions, name='view-solutions'),
]
| [
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] | 2.536145 | 166 |
import numpy as np
from annoy import AnnoyIndex
import yaml
import os
import threading
import queue
import time
model_location = '/data/model_ha' | [
11748,
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] | 3.418605 | 43 |
# -*- coding: utf-8 -*-
'''
Returners Directory
'''
| [
2,
532,
9,
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] | 2.166667 | 24 |
#----------------------------------------------------------------------------#
# Imports
#----------------------------------------------------------------------------#
from flask import Flask, render_template, request, jsonify, redirect, url_for
import random
from datetime import datetime
from flask_cors import CORS
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import math
# from flask.ext.sqlalchemy import SQLAlchemy
import logging
from logging import Formatter, FileHandler
from forms import *
import os
from Aaron_Lib import *
import io
# Imports the Google Cloud client library
from google.cloud import speech
from google.cloud.speech import enums
from google.cloud.speech import types
# Instantiates a client
client = speech.SpeechClient()
#----------------------------------------------------------------------------#
# App Config.
#----------------------------------------------------------------------------#
app = Flask(__name__)
CORS(app)
app.config.from_object('config')
#db = SQLAlchemy(app)
# Automatically tear down SQLAlchemy.
'''
@app.teardown_request
def shutdown_session(exception=None):
db_session.remove()
'''
# Login required decorator.
'''
def login_required(test):
@wraps(test)
def wrap(*args, **kwargs):
if 'logged_in' in session:
return test(*args, **kwargs)
else:
flash('You need to login first.')
return redirect(url_for('login'))
return wrap
'''
# Create list of calls
calls = [
{
'time': str(datetime.now().strftime('%Y-%m-%d %H:%M:%S')),
'text': 'Help!',
'sentiment': 6,
'confidence': 8
}
]
#----------------------------------------------------------------------------#
# Controllers.
#----------------------------------------------------------------------------#
@app.route('/')
@app.route('/about')
@app.route('/login')
@app.route('/register')
@app.route('/forgot')
@app.route('/recorder')
@app.route('/recorder_mobile')
# Error handlers.
@app.errorhandler(500)
@app.errorhandler(404)
if not app.debug:
file_handler = FileHandler('error.log')
file_handler.setFormatter(
Formatter('%(asctime)s %(levelname)s: %(message)s [in %(pathname)s:%(lineno)d]')
)
app.logger.setLevel(logging.INFO)
file_handler.setLevel(logging.INFO)
app.logger.addHandler(file_handler)
app.logger.info('errors')
# List for request from client
@app.route('/api/newcall', methods = ['POST'])
#----------------------------------------------------------------------------#
# Launch.
#----------------------------------------------------------------------------#
# Default port:
# if __name__ == '__main__':
# app.run()
# Or specify port manually:
if __name__ == '__main__':
port = int(os.environ.get('PORT', 3000))
app.run(host='0.0.0.0', port=port)
| [
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2393,
62,
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8479,
1436,
7,
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5178,
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4,
7,
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310,
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25,
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7,
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8,
82,
685,
259,
4064,
7,
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3672,
8,
82,
25,
4,
7,
2815,
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8,
67,
60,
11537,
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220,
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1267,
198,
220,
220,
220,
598,
13,
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1362,
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14,
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3256,
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37250,
32782,
6,
12962,
198,
2,
10097,
10541,
2,
198,
2,
21225,
13,
198,
2,
10097,
10541,
2,
198,
198,
2,
15161,
2493,
25,
198,
2,
611,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
2,
220,
220,
220,
220,
598,
13,
5143,
3419,
198,
198,
2,
1471,
11986,
2493,
14500,
25,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
2493,
796,
493,
7,
418,
13,
268,
2268,
13,
1136,
10786,
15490,
3256,
20343,
4008,
198,
220,
220,
220,
598,
13,
5143,
7,
4774,
11639,
15,
13,
15,
13,
15,
13,
15,
3256,
2493,
28,
634,
8,
628
] | 3.134426 | 915 |
from typing import List, Dict, Optional
from pyspark.sql import DataFrame, Column
from spark_auto_mapper.automappers.check_schema_result import CheckSchemaResult
class AutoMapperBase:
"""
Abstract Base class for AutoMappers
"""
def transform_with_data_frame(
self, df: DataFrame, source_df: Optional[DataFrame], keys: List[str]
) -> DataFrame:
"""
Internal function called by base class to transform the data frame
:param df: destination data frame
:param source_df: source data frame
:param keys: key columns
:return data frame after the transform
"""
# implement in subclasses
raise NotImplementedError
def get_column_specs(self, source_df: Optional[DataFrame]) -> Dict[str, Column]:
"""
Gets column specs (Spark expressions)
:param source_df: source data frame
:return: dictionary of column name, column expression
"""
raise NotImplementedError
def check_schema(
self, parent_column: Optional[str], source_df: Optional[DataFrame]
) -> Optional[CheckSchemaResult]:
"""
Checks the schema
:param parent_column: parent column
:param source_df: source data frame
:return: result of checking schema
"""
return None
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220,
220,
220,
220,
220,
220,
220,
1058,
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2723,
62,
7568,
25,
2723,
1366,
5739,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
25,
1255,
286,
10627,
32815,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198
] | 2.65748 | 508 |
from bokeh.models import Panel, Tabs
from bokeh.io import output_file, show
from bokeh.plotting import figure
output_file("slider.html")
p1 = figure(plot_width=300, plot_height=300)
p1.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5)
tab1 = Panel(child=p1, title="circle")
p2 = figure(plot_width=300, plot_height=300)
p2.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], line_width=3, color="navy", alpha=0.5)
tab2 = Panel(child=p2, title="line")
tabs = Tabs(tabs=[ tab1, tab2 ])
show(tabs)
| [
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16,
11,
7400,
17,
33761,
198,
198,
12860,
7,
8658,
82,
8,
198
] | 2.28125 | 224 |
# @return a list of strings, [s1, s2]
# test
digits = "23"
print(Solution().letterCombinations(digits)) | [
220,
220,
220,
1303,
2488,
7783,
257,
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286,
13042,
11,
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7,
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896,
4008
] | 2.634146 | 41 |
from typing import *
import velocyto as vcy
| [
6738,
19720,
1330,
1635,
198,
11748,
11555,
13733,
1462,
355,
410,
948,
628
] | 3.461538 | 13 |
from plastron import ldp, ore, rdf
from plastron.namespaces import dcterms, dcmitype, ebucore, fabio, pcdm, pcdmuse, premis
from plastron.files import LocalFileSource, RepositoryFileSource
from PIL import Image
# alias the rdflib Namespace
ns = pcdm
@rdf.object_property('members', pcdm.hasMember)
@rdf.object_property('member_of', pcdm.memberOf)
@rdf.object_property('files', pcdm.hasFile)
@rdf.object_property('related', pcdm.hasRelatedObject)
@rdf.object_property('related_of', pcdm.relatedObjectOf)
@rdf.data_property('title', dcterms.title)
@rdf.rdf_class(pcdm.Object)
# recursively create an object and components and that don't yet exist
@rdf.object_property('file_of', pcdm.fileOf)
@rdf.data_property('mimetype', ebucore.hasMimeType)
@rdf.data_property('filename', ebucore.filename)
@rdf.data_property('size', premis.hasSize)
@rdf.data_property('width', ebucore.width)
@rdf.data_property('height', ebucore.height)
@rdf.object_property('dcmitype', dcterms.type)
@rdf.data_property('title', dcterms.title)
@rdf.rdf_class(pcdm.File)
@rdf.rdf_class(pcdmuse.PreservationMasterFile)
@rdf.rdf_class(pcdmuse.IntermediateFile)
@rdf.rdf_class(pcdmuse.ServiceFile)
@rdf.rdf_class(pcdmuse.ExtractedText)
@rdf.rdf_class(pcdm.Collection)
@rdf.data_property('number', fabio.hasSequenceIdentifier)
@rdf.rdf_class(fabio.Page)
class Page(Object):
"""One page of an item-level resource"""
pass
FILE_CLASS_FOR = {
'.tif': PreservationMasterFile,
'.jpg': IntermediateFile,
'.txt': ExtractedText,
'.xml': ExtractedText,
}
| [
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] | 2.521036 | 618 |
from os import path
import json
| [
6738,
28686,
1330,
3108,
198,
11748,
33918,
198
] | 4 | 8 |
import numpy as np
import gpustats.kernels as kernels
import gpustats.codegen as codegen
import gpustats.util as util
import pycuda.driver as drv
from pycuda.gpuarray import GPUArray, to_gpu
from pycuda.gpuarray import empty as gpu_empty
from pycuda.curandom import rand as curand
# reload(kernels)
# reload(codegen)
cu_module = codegen.get_full_cuda_module()
def sample_discrete(densities, logged=False,
return_gpuarray=False):
"""
Takes a categorical sample from the unnormalized univariate
densities defined in the rows of 'densities'
Parameters
---------
densities : ndarray or gpuarray (n, k)
logged: boolean indicating whether densities is on the
log scale ...
Returns
-------
indices : ndarray or gpuarray (if return_gpuarray=True)
of length n and dtype = int32
"""
from gpustats.util import info
n, k = densities.shape
# prep data
if isinstance(densities, GPUArray):
if densities.flags.f_contiguous:
gpu_densities = util.transpose(densities)
else:
gpu_densities = densities
else:
densities = util.prep_ndarray(densities)
gpu_densities = to_gpu(densities)
# get gpu function
cu_func = cu_module.get_function('sample_discrete')
# setup GPU data
gpu_random = to_gpu(np.asarray(np.random.rand(n), dtype=np.float32))
gpu_dest = gpu_empty(n, dtype=np.int32)
dims = np.array([n,k,logged],dtype=np.int32)
if info.max_block_threads<1024:
x_block_dim = 16
else:
x_block_dim = 32
y_block_dim = 16
# setup GPU call
block_design = (x_block_dim, y_block_dim, 1)
grid_design = (int(n/y_block_dim) + 1, 1)
shared_mem = 4 * ( (x_block_dim+1)*y_block_dim +
2 * y_block_dim )
cu_func(gpu_densities, gpu_random, gpu_dest,
dims[0], dims[1], dims[2],
block=block_design, grid=grid_design, shared=shared_mem)
gpu_random.gpudata.free()
if return_gpuarray:
return gpu_dest
else:
res = gpu_dest.get()
gpu_dest.gpudata.free()
return res
## depreciated
def sample_discrete_old(in_densities, logged=False, pad=False,
return_gpuarray=False):
"""
Takes a categorical sample from the unnormalized univariate
densities defined in the rows of 'densities'
Parameters
---------
densities : ndarray or gpuarray (n, k)
logged: boolean indicating whether densities is on the
log scale ...
Returns
-------
indices : ndarray or gpuarray (if return_gpuarray=True)
of length n and dtype = int32
"""
if pad:
if logged:
densities = util.pad_data_mult16(in_densities, fill=1)
else:
densities = util.pad_data_mult16(in_densities, fill=0)
else:
densities = in_densities
n, k = densities.shape
if logged:
cu_func = cu_module.get_function('sample_discrete_logged_old')
else:
cu_func = cu_module.get_function('sample_discrete_old')
if isinstance(densities, GPUArray):
if densities.flags.f_contiguous:
gpu_densities = util.transpose(densities)
else:
gpu_densities = densities
else:
densities = util.prep_ndarray(densities)
gpu_densities = to_gpu(densities)
# setup GPU data
#gpu_random = curand(n)
gpu_random = to_gpu(np.asarray(np.random.rand(n), dtype=np.float32))
#gpu_dest = to_gpu(np.zeros(n, dtype=np.float32))
gpu_dest = gpu_empty(n, dtype=np.float32)
stride = gpu_densities.shape[1]
if stride % 2 == 0:
stride += 1
dims = np.array([n,k, gpu_densities.shape[1], stride],dtype=np.int32)
# optimize design ...
grid_design, block_design = _tune_sfm(n, stride, cu_func.num_regs)
shared_mem = 4 * (block_design[0] * stride +
1 * block_design[0])
cu_func(gpu_densities, gpu_random, gpu_dest,
dims[0], dims[1], dims[2], dims[3],
block=block_design, grid=grid_design, shared=shared_mem)
gpu_random.gpudata.free()
if return_gpuarray:
return gpu_dest
else:
res = gpu_dest.get()
gpu_dest.gpudata.free()
return res
def _tune_sfm(n, stride, func_regs):
"""
Outputs the 'opimal' block and grid configuration
for the sample discrete kernel.
"""
from gpustats.util import info
#info = DeviceInfo()
comp_cap = info.compute_cap
max_smem = info.shared_mem * 0.8
max_threads = int(info.max_block_threads * 0.5)
max_regs = 0.9 * info.max_registers
# We want smallest dim possible in x dimsension while
# still reading mem correctly
if comp_cap[0] == 1:
xdim = 16
else:
xdim = 32
ydim = 2
while sfm_config_ok(xdim, ydim, stride, func_regs, max_regs, max_smem, max_threads):
ydim += 1
ydim -= 1
nblocks = int(n/xdim) + 1
return (nblocks,1), (xdim,ydim,1)
if __name__ == '__main__':
n = 100
k = 5
dens = np.log(np.abs(np.random.randn(k))) - 200
densities = [dens.copy() for _ in range(n)]
dens = np.exp(dens + 200)
densities = np.asarray(densities)
labels = sample_discrete(densities, logged=True)
mu = np.dot(dens / dens.sum(), np.arange(k))
print mu, labels.mean()
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220,
220,
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3601,
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11,
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] | 2.216172 | 2,424 |
import os
from typing import Any, Dict, Optional, Sequence, Type, TYPE_CHECKING, Union
from .. import _dtypes
from ..base_types.media import Media
if TYPE_CHECKING: # pragma: no cover
from wandb.apis.public import Artifact as PublicArtifact
from ...wandb_artifacts import Artifact as LocalArtifact
from ...wandb_run import Run as LocalRun
_dtypes.TypeRegistry.add(_ClassesIdType)
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] | 3.174603 | 126 |
import unittest, json
from comodit_client.rest.client import HttpClient
from comodit_client.rest.exceptions import ApiException
from test.mock.urllib_mocks import RequestWithMethodMock, RequestResult
# Create tests
# Delete tests
# Read tests
# Update tests
# Helpers
if __name__ == '__main__':
unittest.main()
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220,
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555,
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] | 2.829268 | 123 |
# terrascript/chef/__init__.py
import terrascript
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2,
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from .environment import EnvironmentConf
from ..tools import secret_hash
class SecurityConf(EnvironmentConf):
"""
Security options.
"""
def get_secret_key(self):
"""
WARNING: keep the secret key used in production secret! We generate a
secret from a hash of the current settings during the .finalize() phase.
this is ok for local development, but may be insecure/inconvenient for
"""
value = self.env.str("DJANGO_SECRET_KEY", default=None)
if not value:
if self.ENVIRONMENT in ("local", "test"):
return self.ENVIRONMENT
else:
return None
return value
# https://docs.djangoproject.com/en/2.0/ref/settings/#auth-password-validators
def get_auth_password_validators(self):
"""
Password validation
"""
prefix = "django.contrib.auth.password_validation"
validators = [
"UserAttributeSimilarityValidator",
"MinimumLengthValidator",
"CommonPasswordValidator",
"NumericPasswordValidator",
]
return [{"NAME": f"{prefix}.{x}"} for x in validators]
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] | 2.370518 | 502 |
# # !/usr/bin/python3
# # -*- coding: utf-8 -*-
import logging, os
SETTINGS_PRIORITY = 100
# THESE SETTINGS ARE NEEDED FOR PYSETTINGS
APP_LOG_FILENAME = 'app.log'
APP_LOG_HANDLER_CONSOLE_LEVEL = logging.WARNING
APP_LOG_HANDLER_FILE_LEVEL = logging.WARNING
CONTROL_EVENTS_GRAPH_DEFAULT_SCALE = 100
BOARD_LOG_WINDOW_REFRESH_RATE = 1000
USE_MULTIPROCESSING = True
PYFORMS_MAINWINDOW_MARGIN = 0
PYFORMS_STYLESHEET = ''
PYFORMS_STYLESHEET_DARWIN = ''
PYFORMS_SILENT_PLUGINS_FINDER = True
#PYFORMS_STYLESHEET = os.path.join(os.path.dirname(__file__), 'resources', 'css', 'default.css')
PYFORMS_MATPLOTLIB_ENABLED = True
PYFORMS_WEB_ENABLED = True
PYFORMS_GL_ENABLED = True
PYFORMS_VISVIS_ENABLED = False
GENERIC_EDITOR_PLUGINS_PATH = None
GENERIC_EDITOR_PLUGINS_LIST = [
'pybpodgui_plugin',
'pybpodgui_plugin_timeline',
'pybpodgui_plugin_trial_timeline',
'pybpod_alyx_plugin',
'pybpodgui_plugin_session_history',
# 'pge_welcome_plugin',
]
#WELCOME_PLUGIN_URL = 'http://pybpod.readthedocs.io'
############ BPODGUI PLUGIN SETTINGS ############
#DEFAULT_PROJECT_PATH = '/home/ricardo/bitbucket/pybpod/pybpod-gui-plugin/projects/Untitled project 1'
BOARD_LOG_WINDOW_REFRESH_RATE = 2000
SESSIONLOG_PLUGIN_REFRESH_RATE = 1000
TIMELINE_PLUGIN_REFRESH_RATE = 1000
PYBOARD_COMMUNICATION_THREAD_REFRESH_TIME = 2 # timer for thread look for events (seconds)
PYBOARD_COMMUNICATION_PROCESS_REFRESH_TIME = 2 # timer for process look for events (seconds)
PYBOARD_COMMUNICATION_PROCESS_TIME_2_LIVE = 0 # wait before killing process (seconds)
GENERIC_EDITOR_TITLE = 'PyBpod'
PYBPOD_REPOSITORIES_TXT_LIST = 'repositories.yml' | [
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] | 2.197368 | 760 |
from io import BytesIO
from pdfmajor.execptions import FontError, UnicodeNotDefined, CMapNotFound
from pdfmajor.parser.PSStackParser import literal_name
from pdfmajor.parser.PDFStream import int_value
from pdfmajor.parser.PDFStream import num_value
from pdfmajor.parser.PDFStream import list_value
from pdfmajor.parser.PDFStream import dict_value
from pdfmajor.parser.PDFStream import PDFStream
from pdfmajor.parser.PDFStream import resolve1
from pdfmajor.parser.cmapdb import CMap, CMapDB, CMapParser
from pdfmajor.parser.cmapdb import FileUnicodeMap
from pdfmajor.utils import settings, apply_matrix_norm
from .PDFFont import PDFFont, PDFSimpleFont
from .util import FontMetricsDB, get_widths, get_widths2
from .Type1FontHeaderParser import Type1FontHeaderParser
from .TrueTypeFont import TrueTypeFont
# PDFType1Font
# PDFTrueTypeFont
# PDFType3Font
# PDFCIDFont
| [
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] | 3.400778 | 257 |
import mixer
import pygame
soun_obj=pygame.mixer.Sound("Star Wars Main Theme (Full).mp3")
soun_obj.play()
soun_obj.stop() | [
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from functools import wraps
from importlib.util import find_spec
from jinja2 import Environment, FileSystemLoader
from pathlib import Path
from rdkit import Chem
import pandas as pd
env = Environment(loader=FileSystemLoader(Path(__file__).parent / 'templates'),
autoescape=False)
def tooltip_formatter(s, subset, fmt, style, transform):
"""Function to generate tooltips from a pandas Series
Parameters
----------
s : pandas.Series
Row in the internal pandas DataFrame
subset : list
Subset of columns that are used for the tooltip
fmt : str
Format string for each key-value pair of the tooltip
style : dict
CSS styling applied to each item independently
transform : dict
Functions applied to each value before rendering
"""
items = []
for k, v in s[subset].to_dict().items():
v = transform[k](v) if transform.get(k) else v
v = f'<span style="{style[k](v)}">{v}</span>' if style.get(k) else v
items.append(fmt.format(key=k, value=v))
return "<br>".join(items)
def mol_to_smiles(mol):
"""Returns a SMILES from an RDKit molecule, or None if not an RDKit mol"""
return Chem.MolToSmiles(mol) if mol else None
def mol_to_record(mol, mol_col="mol"):
"""Function to create a dict of data from an RDKit molecule"""
return {"SMILES": Chem.MolToSmiles(mol),
**mol.GetPropsAsDict(includePrivate=True),
mol_col: mol} if mol else {}
def sdf_to_dataframe(sdf_path, mol_col="mol"):
"""Returns a dataframe of molecules from an SDF file"""
return pd.DataFrame([mol_to_record(mol, mol_col)
for mol in Chem.SDMolSupplier(sdf_path)])
def remove_coordinates(mol):
"""Removes the existing coordinates from the molecule. The molecule is
modified inplace"""
mol.RemoveAllConformers()
return mol
def make_popup_callback(title, html, js="", style=""):
"""Creates a JavaScript callback that displays a popup window
Parameters
----------
title : str
Title of the popup. Use `title='${data["Name"]}'` to use the value
of the column "Name" as a title
html : str
Content of the popup window
js : str
JavaScript code executed before making the content of the popup window.
This allows you to create variables and reuse them later in the `html`
content of the popup, using the `${my_variable}` syntax
style : str
CSS style assigned to the popup window
"""
return (env.get_template('js/popup.js')
.render(js=js,
html=html,
title=title,
style=style))
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] | 2.555764 | 1,067 |
"""The builtin str implementation"""
from rpython.rlib import jit
from rpython.rlib.jit import we_are_jitted
from rpython.rlib.objectmodel import (
compute_hash, compute_unique_id, import_from_mixin)
from rpython.rlib.buffer import StringBuffer
from rpython.rlib.rstring import StringBuilder, replace
from pypy.interpreter.baseobjspace import W_Root
from pypy.interpreter.buffer import SimpleView
from pypy.interpreter.error import OperationError, oefmt
from pypy.interpreter.gateway import (
WrappedDefault, interp2app, interpindirect2app, unwrap_spec)
from pypy.interpreter.typedef import TypeDef
from pypy.objspace.std import newformat
from pypy.objspace.std.basestringtype import basestring_typedef
from pypy.objspace.std.formatting import mod_format
from pypy.objspace.std.stringmethods import StringMethods
from pypy.objspace.std.unicodeobject import (
decode_object, unicode_from_encoded_object,
unicode_from_string, getdefaultencoding)
from pypy.objspace.std.util import IDTAG_SPECIAL, IDTAG_SHIFT
W_BytesObject.EMPTY = W_BytesObject('')
W_BytesObject.typedef = TypeDef(
"pal", basestring_typedef, None, "read",
__new__ = interp2app(W_BytesObject.descr_new),
__doc__ = """pal(objeto='') -> palabra
Vuelve una representación palabra del objeto. Si el argumento es
una palabra, lo que vuelve es el objeto mismo.
""",
__repr__ = interpindirect2app(W_AbstractBytesObject.descr_repr),
__pal__ = interpindirect2app(W_AbstractBytesObject.descr_str),
__str__ = interpindirect2app(W_AbstractBytesObject.descr_str),
__hash__ = interpindirect2app(W_AbstractBytesObject.descr_hash),
__ig__ = interpindirect2app(W_AbstractBytesObject.descr_eq),
__eq__ = interpindirect2app(W_AbstractBytesObject.descr_eq),
__ni__ = interpindirect2app(W_AbstractBytesObject.descr_ne),
__ne__ = interpindirect2app(W_AbstractBytesObject.descr_ne),
__meq__ = interpindirect2app(W_AbstractBytesObject.descr_lt),
__lt__ = interpindirect2app(W_AbstractBytesObject.descr_lt),
__mei__ = interpindirect2app(W_AbstractBytesObject.descr_le),
__le__ = interpindirect2app(W_AbstractBytesObject.descr_le),
__maq__ = interpindirect2app(W_AbstractBytesObject.descr_gt),
__gt__ = interpindirect2app(W_AbstractBytesObject.descr_gt),
__mai__ = interpindirect2app(W_AbstractBytesObject.descr_ge),
__ge__ = interpindirect2app(W_AbstractBytesObject.descr_ge),
__tam__ = interpindirect2app(W_AbstractBytesObject.descr_len),
__len__ = interpindirect2app(W_AbstractBytesObject.descr_len),
__contiene__ = interpindirect2app(W_AbstractBytesObject.descr_contains),
__contains__ = interpindirect2app(W_AbstractBytesObject.descr_contains),
__mas__ = interpindirect2app(W_AbstractBytesObject.descr_add),
__add__ = interpindirect2app(W_AbstractBytesObject.descr_add),
__mul__ = interpindirect2app(W_AbstractBytesObject.descr_mul),
__dmul__ = interpindirect2app(W_AbstractBytesObject.descr_rmul),
__rmul__ = interpindirect2app(W_AbstractBytesObject.descr_rmul),
__sacaartic__ = interpindirect2app(W_AbstractBytesObject.descr_getitem),
__getitem__ = interpindirect2app(W_AbstractBytesObject.descr_getitem),
__sacaparte__ = interpindirect2app(W_AbstractBytesObject.descr_getslice),
__getslice__ = interpindirect2app(W_AbstractBytesObject.descr_getslice),
mayuscular = interpindirect2app(W_AbstractBytesObject.descr_capitalize),
capitalize = interpindirect2app(W_AbstractBytesObject.descr_capitalize),
centro = interpindirect2app(W_AbstractBytesObject.descr_center),
center = interpindirect2app(W_AbstractBytesObject.descr_center),
total = interpindirect2app(W_AbstractBytesObject.descr_count),
count = interpindirect2app(W_AbstractBytesObject.descr_count),
decodificar = interpindirect2app(W_AbstractBytesObject.descr_decode),
decode = interpindirect2app(W_AbstractBytesObject.descr_decode),
codificar = interpindirect2app(W_AbstractBytesObject.descr_encode),
encode = interpindirect2app(W_AbstractBytesObject.descr_encode),
expandtabs = interpindirect2app(W_AbstractBytesObject.descr_expandtabs),
encontrar = interpindirect2app(W_AbstractBytesObject.descr_find),
find = interpindirect2app(W_AbstractBytesObject.descr_find),
dencontrar = interpindirect2app(W_AbstractBytesObject.descr_rfind),
rfind = interpindirect2app(W_AbstractBytesObject.descr_rfind),
indice = interpindirect2app(W_AbstractBytesObject.descr_index),
index = interpindirect2app(W_AbstractBytesObject.descr_index),
dindice = interpindirect2app(W_AbstractBytesObject.descr_rindex),
rindex = interpindirect2app(W_AbstractBytesObject.descr_rindex),
esalnum = interpindirect2app(W_AbstractBytesObject.descr_isalnum),
isalnum = interpindirect2app(W_AbstractBytesObject.descr_isalnum),
esalfa = interpindirect2app(W_AbstractBytesObject.descr_isalpha),
isalpha = interpindirect2app(W_AbstractBytesObject.descr_isalpha),
esdig = interpindirect2app(W_AbstractBytesObject.descr_isdigit),
isdigit = interpindirect2app(W_AbstractBytesObject.descr_isdigit),
esminusc = interpindirect2app(W_AbstractBytesObject.descr_islower),
islower = interpindirect2app(W_AbstractBytesObject.descr_islower),
esespac = interpindirect2app(W_AbstractBytesObject.descr_isspace),
isspace = interpindirect2app(W_AbstractBytesObject.descr_isspace),
estitulo = interpindirect2app(W_AbstractBytesObject.descr_istitle),
istitle = interpindirect2app(W_AbstractBytesObject.descr_istitle),
esmayusc = interpindirect2app(W_AbstractBytesObject.descr_isupper),
isupper = interpindirect2app(W_AbstractBytesObject.descr_isupper),
juntar = interpindirect2app(W_AbstractBytesObject.descr_join),
join = interpindirect2app(W_AbstractBytesObject.descr_join),
ijust = interpindirect2app(W_AbstractBytesObject.descr_ljust),
ljust = interpindirect2app(W_AbstractBytesObject.descr_ljust),
djust = interpindirect2app(W_AbstractBytesObject.descr_rjust),
rjust = interpindirect2app(W_AbstractBytesObject.descr_rjust),
minusc = interpindirect2app(W_AbstractBytesObject.descr_lower),
lower = interpindirect2app(W_AbstractBytesObject.descr_lower),
particion = interpindirect2app(W_AbstractBytesObject.descr_partition),
partition = interpindirect2app(W_AbstractBytesObject.descr_partition),
dparticion = interpindirect2app(W_AbstractBytesObject.descr_rpartition),
rpartition = interpindirect2app(W_AbstractBytesObject.descr_rpartition),
reemplazar = interpindirect2app(W_AbstractBytesObject.descr_replace),
replace = interpindirect2app(W_AbstractBytesObject.descr_replace),
quebrar = interpindirect2app(W_AbstractBytesObject.descr_split),
split = interpindirect2app(W_AbstractBytesObject.descr_split),
dquebrar = interpindirect2app(W_AbstractBytesObject.descr_rsplit),
rsplit = interpindirect2app(W_AbstractBytesObject.descr_rsplit),
quebrarlineas = interpindirect2app(W_AbstractBytesObject.descr_splitlines),
splitlines = interpindirect2app(W_AbstractBytesObject.descr_splitlines),
empcon = interpindirect2app(W_AbstractBytesObject.descr_startswith),
startswith = interpindirect2app(W_AbstractBytesObject.descr_startswith),
terminacon = interpindirect2app(W_AbstractBytesObject.descr_endswith),
endswith = interpindirect2app(W_AbstractBytesObject.descr_endswith),
decapar = interpindirect2app(W_AbstractBytesObject.descr_strip),
strip = interpindirect2app(W_AbstractBytesObject.descr_strip),
idecapar = interpindirect2app(W_AbstractBytesObject.descr_lstrip),
lstrip = interpindirect2app(W_AbstractBytesObject.descr_lstrip),
ddecapar = interpindirect2app(W_AbstractBytesObject.descr_rstrip),
rstrip = interpindirect2app(W_AbstractBytesObject.descr_rstrip),
minmayusc = interpindirect2app(W_AbstractBytesObject.descr_swapcase),
swapcase = interpindirect2app(W_AbstractBytesObject.descr_swapcase),
titulo = interpindirect2app(W_AbstractBytesObject.descr_title),
title = interpindirect2app(W_AbstractBytesObject.descr_title),
traducir = interpindirect2app(W_AbstractBytesObject.descr_translate),
translate = interpindirect2app(W_AbstractBytesObject.descr_translate),
mayusc = interpindirect2app(W_AbstractBytesObject.descr_upper),
upper = interpindirect2app(W_AbstractBytesObject.descr_upper),
cllenar = interpindirect2app(W_AbstractBytesObject.descr_zfill),
zfill = interpindirect2app(W_AbstractBytesObject.descr_zfill),
__bufer__ = interp2app(W_BytesObject.descr_getbuffer),
__buffer__ = interp2app(W_BytesObject.descr_getbuffer),
formato = interpindirect2app(W_BytesObject.descr_format),
format = interpindirect2app(W_BytesObject.descr_format),
__formato__ = interpindirect2app(W_BytesObject.descr__format__),
__format__ = interpindirect2app(W_BytesObject.descr__format__),
__mod__ = interpindirect2app(W_BytesObject.descr_mod),
__dmod__ = interpindirect2app(W_BytesObject.descr_rmod),
__rmod__ = interpindirect2app(W_BytesObject.descr_rmod),
__sacanuevosargs__ = interpindirect2app(
W_AbstractBytesObject.descr_getnewargs),
__getnewargs__ = interpindirect2app(
W_AbstractBytesObject.descr_getnewargs),
_formatter_parser = interp2app(W_BytesObject.descr_formatter_parser),
_formatter_field_name_split =
interp2app(W_BytesObject.descr_formatter_field_name_split),
)
W_BytesObject.typedef.flag_sequence_bug_compat = True
@jit.elidable
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] | 2.650153 | 3,593 |
from sqlalchemy import Column, Integer, String, Date
from sqlalchemy.orm import relationship
from sqlalchemy.sql.schema import ForeignKey
from configuration import Base
from datetime import * | [
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1330,
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220,
198,
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1635
] | 4.173913 | 46 |
from rest_framework.response import Response
from rest_framework.views import APIView
from rest_framework import status
from rest_framework.permissions import IsAdminUser
from common.views import ResponseInfo, MyPageNumber
from .models import File
from .serializers import FileSerializer
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] | 4.279412 | 68 |
#!/usr/bin/env python
"""
recursive search and deinit (disconnection) for drive-google directories
"""
from pathlib import Path
from gdrivepublic import isgdrive
from subprocess import call
from argparse import ArgumentParser
p = ArgumentParser()
p.add_argument('rdir',help='root directory to search for active drive-google connections',nargs='?',default='~')
p = p.parse_args()
rdir = Path(p.rdir).expanduser()
#%%
for d in rdir.rglob('.gd'):
try:
if isgdrive(d):
call(['drive','deinit'],cwd=str(d))
except PermissionError:
pass
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220,
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220,
220,
220,
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220,
220,
869,
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41707,
2934,
15003,
6,
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66,
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28,
2536,
7,
67,
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198,
220,
220,
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2448,
3411,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198
] | 2.762136 | 206 |
import json
import os
from argparse import Namespace, _SubParsersAction
from cloudfoundry_client.client import CloudFoundryClient
from cloudfoundry_client.json_object import JsonObject
from cloudfoundry_client.main.command_domain import CommandDomain, Command
| [
11748,
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198,
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62,
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1330,
9455,
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11,
9455,
628
] | 3.852941 | 68 |
from numpy import random
import gc
import numpy as np
import pdb
import cv2
import os
import sys
import matplotlib.pyplot as plt
dataset_name = sys.argv[1]
data_dir = './quickdraw/' + dataset_name + '/r128/'
save_dir = './quickdraw/' + dataset_name + '/obj-in-image/'
os.makedirs(save_dir + 'test/' , exist_ok=True)
os.makedirs(save_dir + 'train/' , exist_ok=True)
list_files = os.listdir(data_dir)
test_num = int(len(list_files) / 5)
mode = ''
for count , file in enumerate(list_files):
if count < test_num:
mode = 'test/'
else:
mode = 'train/'
obj_img = cv2.imread(data_dir + file , 0)
obj_img = cv2.resize(obj_img , (32,32))
_,obj_img = cv2.threshold(obj_img,127,255,cv2.THRESH_BINARY)
file , ext = os.path.splitext(file)
for i in range(5):
bkg_img = np.zeros((128,128))
tx = random.randint(0,64)
ty = random.randint(0,64)
bkg_img[tx:tx+32,ty:ty+32] = obj_img
cv2.imwrite(save_dir + mode + file + '_' + str(i) + ext , bkg_img)
# pdb.set_trace()
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] | 2.205418 | 443 |
# Use true division operator always even in old python 2.x (used in `_get_case_getter_s`)
from __future__ import division
from distutils.version import LooseVersion
from enum import Enum
from inspect import isgeneratorfunction, getmodule, currentframe
from itertools import product
from warnings import warn
from decopatch import function_decorator, DECORATED
from makefun import with_signature, add_signature_parameters, remove_signature_parameters, wraps
import pytest
try: # python 3.3+
from inspect import signature, Parameter
except ImportError:
from funcsigs import signature, Parameter
try:
from typing import Type
except ImportError:
# on old versions of typing module the above does not work. Since our code below has all Type hints quoted it's ok
pass
try: # type hints, python 3+
from typing import Callable, Union, Optional, Any, Tuple, List, Dict, Iterable
from pytest_cases.case_funcs import CaseData, ExpectedError
from types import ModuleType
# Type hint for the simple functions
CaseFunc = Callable[[], CaseData]
# Type hint for generator functions
GeneratedCaseFunc = Callable[[Any], CaseData]
except ImportError:
pass
from pytest_cases.common import yield_fixture, get_pytest_parametrize_marks, get_test_ids_from_param_values, \
make_marked_parameter_value, extract_parameterset_info, get_fixture_name, get_param_argnames_as_list, \
get_fixture_scope, remove_duplicates
from pytest_cases.main_params import cases_data
def unpack_fixture(argnames, fixture):
"""
Creates several fixtures with names `argnames` from the source `fixture`. Created fixtures will correspond to
elements unpacked from `fixture` in order. For example if `fixture` is a tuple of length 2, `argnames="a,b"` will
create two fixtures containing the first and second element respectively.
The created fixtures are automatically registered into the callers' module, but you may wish to assign them to
variables for convenience. In that case make sure that you use the same names,
e.g. `a, b = unpack_fixture('a,b', 'c')`.
```python
import pytest
from pytest_cases import unpack_fixture, pytest_fixture_plus
@pytest_fixture_plus
@pytest.mark.parametrize("o", ['hello', 'world'])
def c(o):
return o, o[0]
a, b = unpack_fixture("a,b", c)
def test_function(a, b):
assert a[0] == b
```
:param argnames: same as `@pytest.mark.parametrize` `argnames`.
:param fixture: a fixture name string or a fixture symbol. If a fixture symbol is provided, the created fixtures
will have the same scope. If a name is provided, they will have scope='function'. Note that in practice the
performance loss resulting from using `function` rather than a higher scope is negligible since the created
fixtures' body is a one-liner.
:return: the created fixtures.
"""
# get caller module to create the symbols
caller_module = get_caller_module()
return _unpack_fixture(caller_module, argnames, fixture)
def _unpack_fixture(caller_module, argnames, fixture):
"""
:param caller_module:
:param argnames:
:param fixture:
:return:
"""
# unpack fixture names to create if needed
argnames_lst = get_param_argnames_as_list(argnames)
# possibly get the source fixture name if the fixture symbol was provided
if not isinstance(fixture, str):
source_f_name = get_fixture_name(fixture)
scope = get_fixture_scope(fixture)
else:
source_f_name = fixture
# we dont have a clue about the real scope, so lets use function scope
scope = 'function'
# finally create the sub-fixtures
created_fixtures = []
for value_idx, argname in enumerate(argnames_lst):
# create the fixture
# To fix late binding issue with `value_idx` we add an extra layer of scope: a factory function
# See https://stackoverflow.com/questions/3431676/creating-functions-in-a-loop
# create it
fix = _create_fixture(value_idx)
# add to module
check_name_available(caller_module, argname, if_name_exists=WARN, caller=unpack_fixture)
setattr(caller_module, argname, fix)
# collect to return the whole list eventually
created_fixtures.append(fix)
return created_fixtures
def param_fixture(argname, argvalues, autouse=False, ids=None, scope="function", **kwargs):
"""
Identical to `param_fixtures` but for a single parameter name, so that you can assign its output to a single
variable.
```python
import pytest
from pytest_cases import param_fixtures, param_fixture
# create a single parameter fixture
my_parameter = param_fixture("my_parameter", [1, 2, 3, 4])
@pytest.fixture
def fixture_uses_param(my_parameter):
...
def test_uses_param(my_parameter, fixture_uses_param):
...
```
:param argname: see fixture `name`
:param argvalues: see fixture `params`
:param autouse: see fixture `autouse`
:param ids: see fixture `ids`
:param scope: see fixture `scope`
:param kwargs: any other argument for 'fixture'
:return: the create fixture
"""
if "," in argname:
raise ValueError("`param_fixture` is an alias for `param_fixtures` that can only be used for a single "
"parameter name. Use `param_fixtures` instead - but note that it creates several fixtures.")
elif len(argname.replace(' ', '')) == 0:
raise ValueError("empty argname")
caller_module = get_caller_module()
return _param_fixture(caller_module, argname, argvalues, autouse=autouse, ids=ids, scope=scope, **kwargs)
def _param_fixture(caller_module, argname, argvalues, autouse=False, ids=None, scope="function", **kwargs):
""" Internal method shared with param_fixture and param_fixtures """
# create the fixture
fix = pytest_fixture_plus(name=argname, scope=scope, autouse=autouse, params=argvalues, ids=ids,
**kwargs)(__param_fixture)
# Dynamically add fixture to caller's module as explained in https://github.com/pytest-dev/pytest/issues/2424
check_name_available(caller_module, argname, if_name_exists=WARN, caller=param_fixture)
setattr(caller_module, argname, fix)
return fix
class ExistingFixtureNameError(ValueError):
"""
Raised by `add_fixture_to_callers_module` when a fixture already exists in a module
"""
RAISE = 0
WARN = 1
CHANGE = 2
def check_name_available(module,
name, # type: str
if_name_exists=RAISE, # type: int
caller=None, # type: Callable[[Any], Any]
):
"""
Routine to
:param module:
:param name:
:param if_name_exists:
:param caller:
:return: a name that might be different if policy was CHANGE
"""
if name in dir(module):
if caller is None:
caller = ''
# Name already exists: act according to policy
if if_name_exists is RAISE:
raise ExistingFixtureNameError(module, name, caller)
elif if_name_exists is WARN:
warn("%s Overriding symbol %s in module %s" % (caller, name, module))
elif if_name_exists is CHANGE:
# find a non-used name in that module
i = 1
name2 = name + '_%s' % i
while name2 in dir(module):
i += 1
name2 = name + '_%s' % i
name = name2
else:
raise ValueError("invalid value for `if_name_exists`: %s" % if_name_exists)
return name
def param_fixtures(argnames, argvalues, autouse=False, ids=None, scope="function", **kwargs):
"""
Creates one or several "parameters" fixtures - depending on the number or coma-separated names in `argnames`. The
created fixtures are automatically registered into the callers' module, but you may wish to assign them to
variables for convenience. In that case make sure that you use the same names, e.g.
`p, q = param_fixtures('p,q', [(0, 1), (2, 3)])`.
Note that the (argnames, argvalues, ids) signature is similar to `@pytest.mark.parametrize` for consistency,
see https://docs.pytest.org/en/latest/reference.html?highlight=pytest.param#pytest-mark-parametrize
```python
import pytest
from pytest_cases import param_fixtures, param_fixture
# create a 2-tuple parameter fixture
arg1, arg2 = param_fixtures("arg1, arg2", [(1, 2), (3, 4)])
@pytest.fixture
def fixture_uses_param2(arg2):
...
def test_uses_param2(arg1, arg2, fixture_uses_param2):
...
```
:param argnames: same as `@pytest.mark.parametrize` `argnames`.
:param argvalues: same as `@pytest.mark.parametrize` `argvalues`.
:param autouse: see fixture `autouse`
:param ids: same as `@pytest.mark.parametrize` `ids`
:param scope: see fixture `scope`
:param kwargs: any other argument for the created 'fixtures'
:return: the created fixtures
"""
created_fixtures = []
argnames_lst = get_param_argnames_as_list(argnames)
caller_module = get_caller_module()
if len(argnames_lst) < 2:
return _param_fixture(caller_module, argnames, argvalues, autouse=autouse, ids=ids, scope=scope, **kwargs)
# create the root fixture that will contain all parameter values
# note: we sort the list so that the first in alphabetical order appears first. Indeed pytest uses this order.
root_fixture_name = "%s__param_fixtures_root" % ('_'.join(sorted(argnames_lst)))
# Dynamically add fixture to caller's module as explained in https://github.com/pytest-dev/pytest/issues/2424
root_fixture_name = check_name_available(caller_module, root_fixture_name, if_name_exists=CHANGE, caller=param_fixtures)
@pytest_fixture_plus(name=root_fixture_name, autouse=autouse, scope=scope, **kwargs)
@pytest.mark.parametrize(argnames, argvalues, ids=ids)
@with_signature("(%s)" % argnames)
# Override once again the symbol with the correct contents
setattr(caller_module, root_fixture_name, _root_fixture)
# finally create the sub-fixtures
for param_idx, argname in enumerate(argnames_lst):
# create the fixture
# To fix late binding issue with `param_idx` we add an extra layer of scope: a factory function
# See https://stackoverflow.com/questions/3431676/creating-functions-in-a-loop
# create it
fix = _create_fixture(param_idx)
# add to module
check_name_available(caller_module, argname, if_name_exists=WARN, caller=param_fixtures)
setattr(caller_module, argname, fix)
# collect to return the whole list eventually
created_fixtures.append(fix)
return created_fixtures
@function_decorator
def cases_fixture(cases=None, # type: Union[Callable[[Any], Any], Iterable[Callable[[Any], Any]]]
module=None, # type: Union[ModuleType, Iterable[ModuleType]]
case_data_argname='case_data', # type: str
has_tag=None, # type: Any
filter=None, # type: Callable[[List[Any]], bool]
f=DECORATED,
**kwargs
):
"""
DEPRECATED - use double annotation `@pytest_fixture_plus` + `@cases_data` instead
```python
@pytest_fixture_plus
@cases_data(module=xxx)
def my_fixture(case_data)
```
Decorates a function so that it becomes a parametrized fixture.
The fixture will be automatically parametrized with all cases listed in module `module`, or with
all cases listed explicitly in `cases`.
Using it with a non-None `module` argument is equivalent to
* extracting all cases from `module`
* then decorating your function with @pytest.fixture(params=cases) with all the cases
So
```python
from pytest_cases import cases_fixture, CaseData
# import the module containing the test cases
import test_foo_cases
@cases_fixture(module=test_foo_cases)
def foo_fixture(case_data: CaseData):
...
```
is equivalent to:
```python
import pytest
from pytest_cases import get_all_cases, CaseData
# import the module containing the test cases
import test_foo_cases
# manually list the available cases
cases = get_all_cases(module=test_foo_cases)
# parametrize the fixture manually
@pytest.fixture(params=cases)
def foo_fixture(request):
case_data = request.param # type: CaseData
...
```
Parameters (cases, module, has_tag, filter) can be used to perform explicit listing, or filtering. See
`get_all_cases()` for details.
:param cases: a single case or a hardcoded list of cases to use. Only one of `cases` and `module` should be set.
:param module: a module or a hardcoded list of modules to use. You may use `THIS_MODULE` to indicate that the
module is the current one. Only one of `cases` and `module` should be set.
:param case_data_argname: the optional name of the function parameter that should receive the `CaseDataGetter`
object. Default is 'case_data'.
:param has_tag: an optional tag used to filter the cases. Only cases with the given tag will be selected. Only
cases with the given tag will be selected.
:param filter: an optional filtering function taking as an input a list of tags associated with a case, and
returning a boolean indicating if the case should be selected. It will be used to filter the cases in the
`module`. It both `has_tag` and `filter` are set, both will be applied in sequence.
:return:
"""
# apply @cases_data (that will translate to a @pytest.mark.parametrize)
parametrized_f = cases_data(cases=cases, module=module,
case_data_argname=case_data_argname, has_tag=has_tag, filter=filter)(f)
# apply @pytest_fixture_plus
return pytest_fixture_plus(**kwargs)(parametrized_f)
@function_decorator
def pytest_fixture_plus(scope="function",
autouse=False,
name=None,
unpack_into=None,
fixture_func=DECORATED,
**kwargs):
""" decorator to mark a fixture factory function.
Identical to `@pytest.fixture` decorator, except that
- it supports multi-parametrization with `@pytest.mark.parametrize` as requested in
https://github.com/pytest-dev/pytest/issues/3960. As a consequence it does not support the `params` and `ids`
arguments anymore.
- it supports a new argument `unpack_into` where you can provide names for fixtures where to unpack this fixture
into.
:param scope: the scope for which this fixture is shared, one of
"function" (default), "class", "module" or "session".
:param autouse: if True, the fixture func is activated for all tests that
can see it. If False (the default) then an explicit
reference is needed to activate the fixture.
:param name: the name of the fixture. This defaults to the name of the
decorated function. Note: If a fixture is used in the same module in
which it is defined, the function name of the fixture will be
shadowed by the function arg that requests the fixture; one way
to resolve this is to name the decorated function
``fixture_<fixturename>`` and then use
``@pytest.fixture(name='<fixturename>')``.
:param unpack_into: an optional iterable of names, or string containing coma-separated names, for additional
fixtures to create to represent parts of this fixture. See `unpack_fixture` for details.
:param kwargs: other keyword arguments for `@pytest.fixture`
"""
if name is not None:
# Compatibility for the 'name' argument
if LooseVersion(pytest.__version__) >= LooseVersion('3.0.0'):
# pytest version supports "name" keyword argument
kwargs['name'] = name
elif name is not None:
# 'name' argument is not supported in this old version, use the __name__ trick.
fixture_func.__name__ = name
# if unpacking is requested, do it first
if unpack_into is not None:
# get the future fixture name if needed
if name is None:
name = fixture_func.__name__
# get caller module to create the symbols
caller_module = get_caller_module(frame_offset=2)
_unpack_fixture(caller_module, unpack_into, name)
# (1) Collect all @pytest.mark.parametrize markers (including those created by usage of @cases_data)
parametrizer_marks = get_pytest_parametrize_marks(fixture_func)
if len(parametrizer_marks) < 1:
return _create_fixture_without_marks(fixture_func, scope, autouse, **kwargs)
else:
if 'params' in kwargs:
raise ValueError(
"With `pytest_fixture_plus` you cannot mix usage of the keyword argument `params` and of "
"the pytest.mark.parametrize marks")
# (2) create the huge "param" containing all params combined
# --loop (use the same order to get it right)
params_names_or_name_combinations = []
params_values = []
params_ids = []
params_marks = []
for pmark in parametrizer_marks:
# check number of parameter names in this parameterset
if len(pmark.param_names) < 1:
raise ValueError("Fixture function '%s' decorated with '@pytest_fixture_plus' has an empty parameter "
"name in a @pytest.mark.parametrize mark")
# remember
params_names_or_name_combinations.append(pmark.param_names)
# extract all parameters that have a specific configuration (pytest.param())
_pids, _pmarks, _pvalues = extract_parameterset_info(pmark.param_names, pmark)
# Create the proper id for each test
if pmark.param_ids is not None:
# overridden at global pytest.mark.parametrize level - this takes precedence.
try: # an explicit list of ids ?
paramids = list(pmark.param_ids)
except TypeError: # a callable to apply on the values
paramids = list(pmark.param_ids(v) for v in _pvalues)
else:
# default: values-based...
paramids = get_test_ids_from_param_values(pmark.param_names, _pvalues)
# ...but local pytest.param takes precedence
for i, _id in enumerate(_pids):
if _id is not None:
paramids[i] = _id
# Finally store the ids, marks, and values for this parameterset
params_ids.append(paramids)
params_marks.append(tuple(_pmarks))
params_values.append(tuple(_pvalues))
# (3) generate the ids and values, possibly reapplying marks
if len(params_names_or_name_combinations) == 1:
# we can simplify - that will be more readable
final_ids = params_ids[0]
final_marks = params_marks[0]
final_values = list(params_values[0])
# reapply the marks
for i, marks in enumerate(final_marks):
if marks is not None:
final_values[i] = make_marked_parameter_value(final_values[i], marks=marks)
else:
final_values = list(product(*params_values))
final_ids = get_test_ids_from_param_values(params_names_or_name_combinations, product(*params_ids))
final_marks = tuple(product(*params_marks))
# reapply the marks
for i, marks in enumerate(final_marks):
ms = [m for mm in marks if mm is not None for m in mm]
if len(ms) > 0:
final_values[i] = make_marked_parameter_value(final_values[i], marks=ms)
if len(final_values) != len(final_ids):
raise ValueError("Internal error related to fixture parametrization- please report")
# (4) wrap the fixture function so as to remove the parameter names and add 'request' if needed
all_param_names = tuple(v for l in params_names_or_name_combinations for v in l)
# --create the new signature that we want to expose to pytest
old_sig = signature(fixture_func)
for p in all_param_names:
if p not in old_sig.parameters:
raise ValueError("parameter '%s' not found in fixture signature '%s%s'"
"" % (p, fixture_func.__name__, old_sig))
new_sig = remove_signature_parameters(old_sig, *all_param_names)
# add request if needed
func_needs_request = 'request' in old_sig.parameters
if not func_needs_request:
new_sig = add_signature_parameters(new_sig, first=Parameter('request', kind=Parameter.POSITIONAL_OR_KEYWORD))
# --common routine used below. Fills kwargs with the appropriate names and values from fixture_params
# --Finally create the fixture function, a wrapper of user-provided fixture with the new signature
if not isgeneratorfunction(fixture_func):
# normal function with return statement
@wraps(fixture_func, new_sig=new_sig)
# transform the created wrapper into a fixture
fixture_decorator = pytest.fixture(scope=scope, params=final_values, autouse=autouse, ids=final_ids, **kwargs)
return fixture_decorator(wrapped_fixture_func)
else:
# generator function (with a yield statement)
@wraps(fixture_func, new_sig=new_sig)
# transform the created wrapper into a fixture
fixture_decorator = yield_fixture(scope=scope, params=final_values, autouse=autouse, ids=final_ids, **kwargs)
return fixture_decorator(wrapped_fixture_func)
def _create_fixture_without_marks(fixture_func, scope, autouse, **kwargs):
"""
creates a fixture for decorated fixture function `fixture_func`.
:param fixture_func:
:param scope:
:param autouse:
:param kwargs:
:return:
"""
# IMPORTANT: even if 'params' is not in kwargs, the fixture
# can be used in a fixture union and therefore a param will be received
# on some calls (and the fixture will be called several times - only once for real)
# - we have to handle the NOT_USED.
# --create a wrapper where we will be able to auto-detect
# TODO we could put this in a dedicated wrapper 'ignore_unsused'..
old_sig = signature(fixture_func)
# add request if needed
func_needs_request = 'request' in old_sig.parameters
if not func_needs_request:
new_sig = add_signature_parameters(old_sig,
first=Parameter('request', kind=Parameter.POSITIONAL_OR_KEYWORD))
else:
new_sig = old_sig
if not isgeneratorfunction(fixture_func):
# normal function with return statement
@wraps(fixture_func, new_sig=new_sig)
# transform the created wrapper into a fixture
fixture_decorator = pytest.fixture(scope=scope, autouse=autouse, **kwargs)
return fixture_decorator(wrapped_fixture_func)
else:
# generator function (with a yield statement)
@wraps(fixture_func, new_sig=new_sig)
# transform the created wrapper into a fixture
fixture_decorator = yield_fixture(scope=scope, autouse=autouse, **kwargs)
return fixture_decorator(wrapped_fixture_func)
NOT_USED = _NotUsed()
"""Object representing a fixture value when the fixture is not used"""
class UnionFixtureAlternative(object):
"""A special class that should be used to wrap a fixture name"""
# def __str__(self):
# that is maybe too dangerous...
# return self.fixture_name
@staticmethod
class IdStyle(Enum):
"""
The enum defining all possible id styles.
"""
none = None
explicit = 'explicit'
compact = 'compact'
def apply_id_style(id, union_fixture_name, idstyle):
"""
Applies the id style defined in `idstyle` to the given id.
See https://github.com/smarie/python-pytest-cases/issues/41
:param id:
:param union_fixture_name:
:param idstyle:
:return:
"""
if idstyle is IdStyle.none:
return id
elif idstyle is IdStyle.explicit:
return "%s_is_%s" % (union_fixture_name, id)
elif idstyle is IdStyle.compact:
return "U%s" % id
else:
raise ValueError("Invalid id style")
class InvalidParamsList(Exception):
"""
Exception raised when users attempt to provide a non-iterable `argvalues` in pytest parametrize.
See https://docs.pytest.org/en/latest/reference.html#pytest-mark-parametrize-ref
"""
__slots__ = 'params',
def is_fixture_union_params(params):
"""
Internal helper to quickly check if a bunch of parameters correspond to a union fixture.
:param params:
:return:
"""
try:
return len(params) >= 1 and isinstance(params[0], UnionFixtureAlternative)
except TypeError:
raise InvalidParamsList(params)
def is_used_request(request):
"""
Internal helper to check if a given request for fixture is active or not. Inactive fixtures
happen when a fixture is not used in the current branch of a UNION fixture.
This helper is used in all fixtures created in this module.
:param request:
:return:
"""
return getattr(request, 'param', None) is not NOT_USED
def fixture_union(name,
fixtures,
scope="function",
idstyle='explicit',
ids=fixture_alternative_to_str,
unpack_into=None,
autouse=False,
**kwargs):
"""
Creates a fixture that will take all values of the provided fixtures in order. That fixture is automatically
registered into the callers' module, but you may wish to assign it to a variable for convenience. In that case
make sure that you use the same name, e.g. `a = fixture_union('a', ['b', 'c'])`
The style of test ids corresponding to the union alternatives can be changed with `idstyle`. Three values are
allowed:
- `'explicit'` (default) favors readability,
- `'compact'` adds a small mark so that at least one sees which parameters are union parameters and which others
are normal parameters,
- `None` does not change the ids.
:param name: the name of the fixture to create
:param fixtures: an array-like containing fixture names and/or fixture symbols
:param scope: the scope of the union. Since the union depends on the sub-fixtures, it should be smaller than the
smallest scope of fixtures referenced.
:param idstyle: The style of test ids corresponding to the union alternatives. One of `'explicit'` (default),
`'compact'`, or `None`.
:param ids: as in pytest. The default value returns the correct fixture
:param unpack_into: an optional iterable of names, or string containing coma-separated names, for additional
fixtures to create to represent parts of this fixture. See `unpack_fixture` for details.
:param autouse: as in pytest
:param kwargs: other pytest fixture options. They might not be supported correctly.
:return: the new fixture. Note: you do not need to capture that output in a symbol, since the fixture is
automatically registered in your module. However if you decide to do so make sure that you use the same name.
"""
caller_module = get_caller_module()
return _fixture_union(caller_module, name, fixtures, scope=scope, idstyle=idstyle, ids=ids, autouse=autouse,
unpack_into=unpack_into, **kwargs)
def _fixture_union(caller_module, name, fixtures, idstyle, scope="function", ids=fixture_alternative_to_str,
unpack_into=None, autouse=False, **kwargs):
"""
Internal implementation for fixture_union
:param caller_module:
:param name:
:param fixtures:
:param idstyle:
:param scope:
:param ids:
:param unpack_into:
:param autouse:
:param kwargs:
:return:
"""
# test the `fixtures` argument to avoid common mistakes
if not isinstance(fixtures, (tuple, set, list)):
raise TypeError("fixture_union: the `fixtures` argument should be a tuple, set or list")
# validate the idstyle
idstyle = IdStyle(idstyle)
# first get all required fixture names
f_names = []
for f in fixtures:
# possibly get the fixture name if the fixture symbol was provided
f_names.append(get_fixture_name(f) if not isinstance(f, str) else f)
if len(f_names) < 1:
raise ValueError("Empty fixture unions are not permitted")
# then generate the body of our union fixture. It will require all of its dependent fixtures and receive as
# a parameter the name of the fixture to use
@with_signature("(%s, request)" % ', '.join(f_names))
_new_fixture.__name__ = name
# finally create the fixture per se.
# WARNING we do not use pytest.fixture but pytest_fixture_plus so that NOT_USED is discarded
f_decorator = pytest_fixture_plus(scope=scope,
params=[UnionFixtureAlternative(_name, idstyle) for _name in f_names],
autouse=autouse, ids=ids, **kwargs)
fix = f_decorator(_new_fixture)
# Dynamically add fixture to caller's module as explained in https://github.com/pytest-dev/pytest/issues/2424
check_name_available(caller_module, name, if_name_exists=WARN, caller=param_fixture)
setattr(caller_module, name, fix)
# if unpacking is requested, do it here
if unpack_into is not None:
_unpack_fixture(caller_module, argnames=unpack_into, fixture=name)
return fix
def _fixture_product(caller_module, name, fixtures_or_values, fixture_positions,
scope="function", ids=fixture_alternative_to_str,
unpack_into=None, autouse=False, **kwargs):
"""
Internal implementation for fixture products created by pytest parametrize plus.
:param caller_module:
:param name:
:param fixtures_or_values:
:param fixture_positions:
:param idstyle:
:param scope:
:param ids:
:param unpack_into:
:param autouse:
:param kwargs:
:return:
"""
# test the `fixtures` argument to avoid common mistakes
if not isinstance(fixtures_or_values, (tuple, set, list)):
raise TypeError("fixture_product: the `fixtures_or_values` argument should be a tuple, set or list")
_tuple_size = len(fixtures_or_values)
# first get all required fixture names
f_names = [None] * _tuple_size
for f_pos in fixture_positions:
# possibly get the fixture name if the fixture symbol was provided
f = fixtures_or_values[f_pos]
# and remember the position in the tuple
f_names[f_pos] = get_fixture_name(f) if not isinstance(f, str) else f
# remove duplicates by making it an ordered set
all_names = remove_duplicates((n for n in f_names if n is not None))
if len(all_names) < 1:
raise ValueError("Empty fixture products are not permitted")
# then generate the body of our product fixture. It will require all of its dependent fixtures
@with_signature("(%s)" % ', '.join(all_names))
_new_fixture.__name__ = name
# finally create the fixture per se.
# WARNING we do not use pytest.fixture but pytest_fixture_plus so that NOT_USED is discarded
f_decorator = pytest_fixture_plus(scope=scope, autouse=autouse, ids=ids, **kwargs)
fix = f_decorator(_new_fixture)
# Dynamically add fixture to caller's module as explained in https://github.com/pytest-dev/pytest/issues/2424
check_name_available(caller_module, name, if_name_exists=WARN, caller=param_fixture)
setattr(caller_module, name, fix)
# if unpacking is requested, do it here
if unpack_into is not None:
_unpack_fixture(caller_module, argnames=unpack_into, fixture=name)
return fix
class fixture_ref:
"""
A reference to a fixture, to be used in `pytest_parametrize_plus`.
You can create it from a fixture name or a fixture object (function).
"""
__slots__ = 'fixture',
def pytest_parametrize_plus(argnames, argvalues, indirect=False, ids=None, scope=None, **kwargs):
"""
Equivalent to `@pytest.mark.parametrize` but also supports the fact that in argvalues one can include references to
fixtures with `fixture_ref(<fixture>)` where <fixture> can be the fixture name or fixture function.
When such a fixture reference is detected in the argvalues, a new function-scope fixture will be created with a
unique name, and the test function will be wrapped so as to be injected with the correct parameters. Special test
ids will be created to illustrate the switching between normal parameters and fixtures.
:param argnames:
:param argvalues:
:param indirect:
:param ids:
:param scope:
:param kwargs:
:return:
"""
# make sure that we do not destroy the argvalues if it is provided as an iterator
try:
argvalues = list(argvalues)
except TypeError:
raise InvalidParamsList(argvalues)
# get the param names
all_param_names = get_param_argnames_as_list(argnames)
nb_params = len(all_param_names)
# find if there are fixture references in the values provided
fixture_indices = []
if nb_params == 1:
for i, v in enumerate(argvalues):
if isinstance(v, fixture_ref):
fixture_indices.append((i, None))
elif nb_params > 1:
for i, v in enumerate(argvalues):
try:
j = 0
fix_pos = []
for j, _pval in enumerate(v):
if isinstance(_pval, fixture_ref):
fix_pos.append(j)
if len(fix_pos) > 0:
fixture_indices.append((i, fix_pos))
if j+1 != nb_params:
raise ValueError("Invalid parameter values containing %s items while the number of parameters is %s: "
"%s." % (j+1, nb_params, v))
except TypeError:
# a fixture ref is
if isinstance(v, fixture_ref):
fixture_indices.append((i, None))
else:
raise ValueError(
"Invalid parameter values containing %s items while the number of parameters is %s: "
"%s." % (1, nb_params, v))
if len(fixture_indices) == 0:
# no fixture reference: do as usual
return pytest.mark.parametrize(argnames, argvalues, indirect=indirect, ids=ids, scope=scope, **kwargs)
else:
# there are fixture references: we have to create a specific decorator
caller_module = get_caller_module()
def _create_param_fixture(from_i, to_i, p_fix_name):
""" Routine that will be used to create a parameter fixture for argvalues between prev_i and i"""
selected_argvalues = argvalues[from_i:to_i]
try:
# an explicit list of ids
selected_ids = ids[from_i:to_i]
except TypeError:
# a callable to create the ids
selected_ids = ids
# default behaviour is not the same betwee pytest params and pytest fixtures
if selected_ids is None:
# selected_ids = ['-'.join([str(_v) for _v in v]) for v in selected_argvalues]
selected_ids = get_test_ids_from_param_values(all_param_names, selected_argvalues)
if to_i == from_i + 1:
p_fix_name = "%s_is_%s" % (p_fix_name, from_i)
else:
p_fix_name = "%s_is_%sto%s" % (p_fix_name, from_i, to_i - 1)
p_fix_name = check_name_available(caller_module, p_fix_name, if_name_exists=CHANGE,
caller=pytest_parametrize_plus)
param_fix = _param_fixture(caller_module, argname=p_fix_name, argvalues=selected_argvalues,
ids=selected_ids)
return param_fix
# then create the decorator
def parametrize_plus_decorate(test_func):
"""
A decorator that wraps the test function so that instead of receiving the parameter names, it receives the
new fixture. All other decorations are unchanged.
:param test_func:
:return:
"""
# first check if the test function has the parameters as arguments
old_sig = signature(test_func)
for p in all_param_names:
if p not in old_sig.parameters:
raise ValueError("parameter '%s' not found in test function signature '%s%s'"
"" % (p, test_func.__name__, old_sig))
# The base name for all fixtures that will be created below
# style_template = "%s_param__%s"
style_template = "%s_%s"
base_name = style_template % (test_func.__name__, argnames.replace(' ', '').replace(',', '_'))
base_name = check_name_available(caller_module, base_name, if_name_exists=CHANGE, caller=pytest_parametrize_plus)
# Retrieve (if ref) or create (for normal argvalues) the fixtures that we will union
# TODO important note: we could either wish to create one fixture for parameter value or to create one for
# each consecutive group as shown below. This should not lead to different results but perf might differ.
# maybe add a parameter in the signature so that users can test it ?
fixtures_to_union = []
fixtures_to_union_names_for_ids = []
prev_i = -1
for i, j_list in fixture_indices:
if i > prev_i + 1:
# there was a non-empty group of 'normal' parameters before this fixture_ref.
# create a new fixture parametrized with all of that consecutive group.
param_fix = _create_param_fixture(prev_i + 1, i, base_name)
fixtures_to_union.append(param_fix)
fixtures_to_union_names_for_ids.append(get_fixture_name(param_fix))
if j_list is None:
# add the fixture referenced with `fixture_ref`
referenced_fixture = argvalues[i].fixture
fixtures_to_union.append(referenced_fixture)
id_for_fixture = apply_id_style(get_fixture_name(referenced_fixture), base_name, IdStyle.explicit)
fixtures_to_union_names_for_ids.append(id_for_fixture)
else:
# create a fixture refering to all the fixtures required in the tuple
prod_fix = _create_fixture_product(i, j_list, base_name)
fixtures_to_union.append(prod_fix)
id_for_fixture = apply_id_style(get_fixture_name(prod_fix), base_name, IdStyle.explicit)
fixtures_to_union_names_for_ids.append(id_for_fixture)
prev_i = i
# handle last consecutive group of normal parameters, if any
i = len(argvalues)
if i > prev_i + 1:
param_fix = _create_param_fixture(prev_i + 1, i, base_name)
fixtures_to_union.append(param_fix)
fixtures_to_union_names_for_ids.append(get_fixture_name(param_fix))
# Finally create a "main" fixture with a unique name for this test function
# note: the function automatically registers it in the module
# note 2: idstyle is set to None because we provide an explicit enough list of ids
big_param_fixture = _fixture_union(caller_module, base_name, fixtures_to_union, idstyle=None,
ids=fixtures_to_union_names_for_ids)
# --create the new test function's signature that we want to expose to pytest
# it is the same than existing, except that we want to replace all parameters with the new fixture
new_sig = remove_signature_parameters(old_sig, *all_param_names)
new_sig = add_signature_parameters(new_sig, Parameter(base_name, kind=Parameter.POSITIONAL_OR_KEYWORD))
# --Finally create the fixture function, a wrapper of user-provided fixture with the new signature
if not isgeneratorfunction(test_func):
# normal test function with return statement
@wraps(test_func, new_sig=new_sig)
else:
# generator test function (with one or several yield statement)
@wraps(test_func, new_sig=new_sig)
# move all pytest marks from the test function to the wrapper
# not needed because the __dict__ is automatically copied when we use @wraps
# move_all_pytest_marks(test_func, wrapped_test_func)
# With this hack we will be ordered correctly by pytest https://github.com/pytest-dev/pytest/issues/4429
wrapped_test_func.place_as = test_func
# return the new test function
return wrapped_test_func
return parametrize_plus_decorate
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] | 2.52071 | 16,514 |
from pydpi.pypro import PyPro
import logging
AA_MODIFICATIONS = {
"Benzoylphenylalanine": "F",
"C-term amidation": "",
"Sulfotyrosine": "Y",
"4-Hydroxyproline": "P",
"Pyroglutamic acid": "E",
"Gamma carboxylic glutamic acid": "E",
"Any": "G",
"D-leucine": "L",
"D-phenylalanine": "F",
"D-methionine": "M",
"D-tryptophan": "W",
"D-tyrosine": "Y",
"Bromotryptophan": "W",
"glycosylated serine": "S",
"2_2-dimethylthiazolidine": "G",
"glycosylated threonine": "T",
"Oxomethionine": "M",
"Selenocystine (half)": "C",
"gamma-hydroxy-D-valine": "V",
"5-hydroxy-lysine": "K",
"Norleucine": "L",
"N-Acetate (on N-terminus)": "",
"3-iodotyrosine": "Y",
"5-amino-3-oxo-pentanoic acid": "G",
"2-amino-DL-dodecanoic acid": "G",
"Carbabridge [C2 unsaturated] (half)": "G",
"alpha-aminobutyric acid": "G",
"Asymmetric dimethylarginine": "R",
"4-(R)-amino-proline": "P",
"4-(S)-amino-proline": "P",
"4-(R)-guanidino-proline": "P",
"4-(R)-betainamidyl-proline": "P",
"4-(R)-fluoro-proline": "P",
"4-(S)-fluoro-proline": "P",
"4-(R)-phenyl-proline": "P",
"4-(S)-phenyl-proline": "P",
"4-(R)-benzyl-proline": "P",
"4-(S)-benzyl-proline": "P",
"4-(R)-1-naphtylmehyl-proline": "P",
"4-(S)-1-naphtylmehyl-proline": "P",
"3-(R)-phenyl-proline": "P",
"3-(S)-phenyl-proline": "P",
"5-(R)-phenyl-proline": "P",
"5-(S)-phenyl-proline": "P",
"Diiodotyrosine": "Y",
"D-alanine": "A",
"Carbabridge [C4 unsaturated] (half)": "G",
"Carbabridge [C4 saturated] (half)": "G",
"Carbabridge [C7 unsaturated] (half)": "G",
" L-4,5-dithiolnorvaline": "V",
}
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220,
366,
18683,
2101,
313,
88,
4951,
500,
1298,
366,
56,
1600,
198,
220,
220,
220,
366,
35,
12,
25786,
500,
1298,
366,
32,
1600,
198,
220,
220,
220,
366,
9914,
65,
397,
12818,
685,
34,
19,
5576,
30192,
60,
357,
13959,
8,
1298,
366,
38,
1600,
198,
220,
220,
220,
366,
9914,
65,
397,
12818,
685,
34,
19,
24725,
60,
357,
13959,
8,
1298,
366,
38,
1600,
198,
220,
220,
220,
366,
9914,
65,
397,
12818,
685,
34,
22,
5576,
30192,
60,
357,
13959,
8,
1298,
366,
38,
1600,
198,
220,
220,
220,
366,
406,
12,
19,
11,
20,
12,
67,
342,
1669,
13099,
2100,
500,
1298,
366,
53,
1600,
198,
92,
628
] | 1.906977 | 903 |
v = int(input('Digite a velocidade do carro: '))
if v<=80:
print('Dirija com segurança. Boa viagem.')
else:
print('Você foi multado por exeder o limite de 80km/h.')
m = (v - 80) * 7
print('A multa vai custar {:.2f} reais'.format(m)) | [
85,
796,
493,
7,
15414,
10786,
19511,
578,
257,
11555,
420,
312,
671,
466,
1097,
305,
25,
705,
4008,
198,
361,
410,
27,
28,
1795,
25,
198,
220,
220,
3601,
10786,
35277,
34655,
401,
384,
70,
42211,
50041,
13,
3248,
64,
25357,
363,
368,
2637,
8,
198,
17772,
25,
198,
220,
220,
220,
3601,
10786,
53,
420,
25792,
11511,
72,
1963,
4533,
16964,
409,
5702,
267,
1761,
578,
390,
4019,
13276,
14,
71,
2637,
8,
198,
220,
220,
220,
285,
796,
357,
85,
532,
4019,
8,
1635,
767,
198,
220,
220,
220,
3601,
10786,
32,
1963,
64,
410,
1872,
9378,
283,
46110,
13,
17,
69,
92,
302,
15152,
4458,
18982,
7,
76,
4008
] | 2.185841 | 113 |
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