content
stringlengths 1
1.04M
| input_ids
sequencelengths 1
774k
| ratio_char_token
float64 0.38
22.9
| token_count
int64 1
774k
|
|---|---|---|---|
import sys, os
pykin_path = os.path.abspath(os.path.dirname(__file__)+"/../../" )
sys.path.append(pykin_path)
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var x = x < 0 ? -x: x
var arr: [Int] = Array<Int>()
var result = 0
while true {
// 最后一位
let temp = x % 10
arr.append(temp)
x = x / 10
if x == 0 {
break
}
}
for (index, value) in arr.enumerated() {
result += value * Int(pow(10.0, Double(arr.count - index - 1)))
}
if result > Int(pow(2.0, 31.0)) {
return 0;
}
result = result * sign
return result
}
}
var s = Solution()
var result = s.reverse(-123)
print(result) | [
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] | 1.723464 | 358 |
# Copyright 2020 Google LLC and Stanford University
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .laikago import LaikagoBullet
from pybullet_utils import bullet_client
import pybullet
import pybullet_data
import time
import gym, gym.utils.seeding, gym.spaces
import numpy as np
from my_pybullet_envs import utils
from collections import deque
import os
import inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
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7,
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628
] | 3.523466 | 277 |
# -*- encode: utf-8 -*-
from typing import List, Tuple, Callable
import numpy as np
from models import Aircraft, Airport, City, Time
from settings import time_limit, time_limit, distance_to_weights
# Phantom class
if __name__ == '__main__':
from data import cities
airline = Airline(cities, time_limit, distance_to_weights)
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] | 3.12844 | 109 |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name='django_sourcerer',
version='2.1',
author='Cem Arslan, Kadir Kocak, Ugur Dogus Hamarat, Cagatay Em, Farid Murmadov, Burak Karaca',
author_email="cmarslan06@gmail.com",
description="Django app that import and correlating data from external sources.",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/nokia-wroclaw/innovativeproject-django-sourcerer",
packages=setuptools.find_packages(),
install_requires=[
'django == 3.0.7',
'djangorestframework == 3.11.0',
'requests == 2.23.0',
'pyyaml == 5.3.1',
'pandas == 1.0.3',
'pytest == 5.4.1',
'requests-mock == 1.7.0',
],
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
python_requires='>=3.6',
)
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62,
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29,
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198,
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] | 2.334842 | 442 |
from __future__ import division
import os
import sys
import time
import threading
import re
import signal
from ..runtime import min_version, runtime_info
from ..profiler_scheduler import ProfilerScheduler
from ..metric import Metric
from ..metric import Breakdown
from ..frame import Frame
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#!/usr/bin/env python
"""
Generalised class: Displays data sources for a class
"""
import os
import sys
import lib_util
import lib_common
try:
import lib_wbem
wbemOk = True
except ImportError:
wbemOk = False
import lib_wmi
from lib_properties import pc
# Now, adds the base classes of this one, at least one one level.
# Adds the list of base classes. Returns the list of pairs (name node),
# so it can be matched againt another inheritance tree.
# Adds a WMI node and other stuff, for the class name.
# entity_type = "CIM_Process", "Win32_Service" etc...
# This might happen at an intermediary level, with inheritance (To be implemented).
if __name__ == '__main__':
Main()
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705,
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198,
197,
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] | 3.309179 | 207 |
import websocket
import threading
import time
import requests
from bs4 import BeautifulSoup
import pygame
import pyperclip
import settings
new_id = -1
poe_trade_url = None
if __name__ == "__main__":
poe_trade_url_ini = input("Please enter your poe.trade URL: ")
poe_trade_url_split = poe_trade_url_ini.split("search/", 1)[1]
poe_trade_url = poe_trade_url_split.split("/live",1)[0]
websocket.enableTrace(False)
ws = websocket.WebSocketApp(settings.WS_URL + poe_trade_url,
on_message = on_message,
on_error = on_error,
on_close = on_close)
ws.run_forever() | [
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] | 2.126582 | 316 |
# -*- coding: utf-8 -*- #
# Copyright 2021 Google LLC. 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.
"""Implementation of create command for notifications."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
import textwrap
from googlecloudsdk.calliope import base
@base.Hidden
class Create(base.Command):
"""Create a notification config on a bucket."""
detailed_help = {
'DESCRIPTION':
"""
*{command}* creates a notification config on a bucket,
establishing a flow of event notifications from Cloud Storage to a
Cloud Pub/Sub topic. As part of creating this flow, it also verifies
that the destination Cloud Pub/Sub topic exists, creating it if necessary,
and verifies that the Cloud Storage bucket has permission to publish
events to that topic, granting the permission if necessary.
If a destination Cloud Pub/Sub topic is not specified with the `-t` flag,
Cloud Storage chooses a topic name in the default project whose ID is
the same as the bucket name. For example, if the default project ID
specified is `default-project` and the bucket being configured is
`gs://example-bucket`, the create command uses the Cloud Pub/Sub topic
`projects/default-project/topics/example-bucket`.
In order to enable notifications, your project's
[Cloud Storage service agent](https://cloud.google.com/storage/docs/projects#service-accounts)
must have the IAM permission "pubsub.topics.publish".
This command checks to see if the destination Cloud Pub/Sub topic grants
the service agent this permission.
If not, the create command attempts to grant it.
A bucket can have up to 100 total notification configurations and up to
10 notification configurations set to trigger for a specific event.
""",
'EXAMPLES':
"""
Begin sending notifications of all changes to the bucket
`example-bucket` to the Cloud Pub/Sub topic
`projects/default-project/topics/example-bucket`:
$ {command} -f json gs://example-bucket
The same as above, but specifies the destination topic ID
`files-to-process` in the default project:
$ {command} -f json -t files-to-process gs://example-bucket
The same as above, but specifies a Cloud Pub/Sub topic belonging
to the specific cloud project `example-project`:
$ {command} -f json \
-t projects/example-project/topics/files-to-process gs://example-bucket
Create a notification config that only sends an event when a new object
has been created:
$ {command} -f json -e OBJECT_FINALIZE gs://example-bucket
Create a topic and notification config that only sends an event when an
object beginning with `photos/` is affected:
$ {command} -p photos/ gs://example-bucket
""",
}
@staticmethod
| [
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198
] | 3.265728 | 1,065 |
"""
Copyright 2020 InfAI (CC SES)
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.
"""
__all__ = ("getLogger", "initLogger")
from .configuration import conf
import simple_env_var
import logging
logging_levels = {
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL,
'debug': logging.DEBUG
}
msg_fmt = '%(asctime)s - %(levelname)s: [%(name)s] %(message)s'
date_fmt = '%m.%d.%Y %I:%M:%S %p'
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter(fmt=msg_fmt, datefmt=date_fmt))
conf_logger = logging.getLogger("simple-env-var")
conf_logger.addHandler(handler)
conf_logger.setLevel(logging.INFO)
kvs_logger = logging.getLogger("snorkels")
kvs_logger.addHandler(handler)
kvs_logger.setLevel(logging.INFO)
simple_env_var.loadConfig(conf)
logger = logging.getLogger("job-manager")
logger.propagate = False
logger.addHandler(handler)
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] | 2.883768 | 499 |
from boa3.builtin.interop.contract import GAS
from boa3.builtin.type import UInt160
| [
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# -*- coding: utf-8 -*-
"""
Created on Fri Nov 14 18:53:38 2014
% TESTS :
% Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6];
% fY = [2 5 1 3 2 6];
% [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 0, 1, 1, 1e15 );
% Z = QZ*RZ;
% [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ...
% fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 )
% [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ...
% fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 )
% norm( Z - QZ*RZ)
% should give something very small.
%
% The same holds for the scaled version:
% Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6];
% fY = [2 5 1 3 2 6];
% [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 1, 1, 1, 1e15 );
% Z = QZ*RZ;
% [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ...
% fY, [], [], xbase, 0, scale, 1, 1, 1, 1e15 )
% [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ...
% fY, [],[],xbase, 0, scale, 1, 1, 1, 1e15 )
% norm( Z - QZ*RZ)
@author: jaco_da
"""
import unittest
from sqpdfo.sqpdfo_swap_in_Y import *
from sqpdfo.bcdfo_build_QR_of_Y import *
from numpy import array
class Test_sqpdfo_swap_in_Y(unittest.TestCase):
"""
Reminder :
This class is a test for sqpdfo_swap_in_Y which swaps the position of interpolation points i and j in Y, and updates the
factorization of Z(Y) accordingly.
"""
def test_sqpdfo_swap_in_Y(self):
"""
Matlab test
"""
QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 0, 1, 1, 1e15 )
Z = QZ.dot(RZ)
#
ceY = array([])
ciY = array([])
QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y,
self.fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 )
QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y,
fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 )
ret = norm_( Z - QZ.dot(RZ))
self.assertTrue(ret < 1e-15)
#
# #Scaled version :
QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 1, 1, 1, 1e15 )
Z = QZ.dot(RZ)
ceY = array([])
ciY = array([])
QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y,
self.fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 )
QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y,
fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 )
ret = norm_( Z - QZ.dot(RZ))
self.assertTrue(ret < 1e-15)
if __name__ == '__main__':
unittest.main() | [
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7,
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220,
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220,
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2116,
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7,
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834,
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198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419
] | 1.751302 | 1,536 |
# Generated by Django 2.0.6 on 2018-06-30 15:59
from django.db import migrations
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] | 2.766667 | 30 |
'''
Filename: word_embeding.py
Project: models
File Created: Sunday, 2nd December 2018 2:38:45 pm
Author: xiaofeng (sxf1052566766@163.com)
--------------------------
Last Modified: Sunday, 2nd December 2018 2:39:14 pm
Modified By: xiaofeng (sxf1052566766@163.com)
---------------------------
: 2018.06 - 2018 .
'''
import tensorflow as tf
def Embedding(name, vocab_embeding, input_sequence):
"""
Creates an embedding matrix of dimensions n_symbols x embeding_dim upon first use.
Looks up embedding vector for each input symbol
:parameters:
name: name of embedding matrix tensor variable
vocab_embeding: full vocabulary embedings
input_sequence: input symbols tensor
return:
word embeding for current input_sequence tensor
shape is (batch_size,1+input_sequence_length,embeding_dim)
"""
with tf.device("/cpu:0"), tf.variable_scope(name):
label_embeding = tf.nn.embedding_lookup(vocab_embeding, input_sequence)
return label_embeding
def embedding_initializer():
"""Returns initializer for embeddings"""
return _initializer
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################################################################################
#
# Originally based on http://djangosnippets.org/snippets/1016/
# with small modifications
#
################################################################################
import re
from django.contrib import admin
from django.conf.urls import patterns, url
from django.http import HttpResponseRedirect
class ButtonableModelAdmin(admin.ModelAdmin):
"""
A subclass of this admin will let you add buttons (like history) in the
change view of an entry.
"""
buttons = []
| [
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] | 3.932886 | 149 |
# -*- coding: utf-8 -*-
from django.conf import settings
from cms.tests.base import CMSTestCase
from cms.utils.plugins import get_placeholders
from cms.exceptions import DuplicatePlaceholderWarning
import sys
import warnings
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#!/usr/bin/env python3
# -*- Coding: utf-8 -*-
import subprocess
from subprocess import PIPE
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from config import database
from pymongo import MongoClient
from mongoengine import *
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import glob
folder = '/data03/shared/lehhou/lym_project/svs_tiles/TCGA-38-4629-01Z-00-DX1.d00cc280-5370-4b9f-9655-6c35deb94647.svs/';
outfile = folder + 'list.txt';
filevar = open(outfile, 'w');
filelist = [];
for filename in glob.glob(folder + '/*.png'):
name = filename[len(folder):-4];
filevar.write("%s\n" % name);
filevar.close();
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13,
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198
] | 2.22293 | 157 |
import pytube
from bs4 import BeautifulSoup
import urllib.request
import threading
from collections.abc import Sequence
from spotdl.metadata import StreamsBase
from spotdl.metadata import ProviderBase
from spotdl.metadata.exceptions import YouTubeMetadataNotFoundError
import spotdl.util
import spotdl.patch
spotdl.patch.youtube.apply_patches()
import logging
logger = logging.getLogger(__name__)
BASE_SEARCH_URL = "https://www.youtube.com/results?sp=EgIQAQ%253D%253D&q={}"
HEADERS = [('Range', 'bytes=0-'),]
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] | 3.089286 | 168 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2018, WSO2 Inc. (http://wso2.org) All Rights Reserved.
#
# WSO2 Inc. licenses this file to you under the Apache License,
# Version 2.0 (the "License"); you may not use this file except
# in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
# ----------------------------------------------------------------------------
# Create AWS CloudFormation template
# ----------------------------------------------------------------------------
import argparse
import csv
import json
import os
from jinja2 import Environment, FileSystemLoader
PATH = os.path.dirname(os.path.abspath(__file__))
TEMPLATE_ENVIRONMENT = Environment(
autoescape=False,
loader=FileSystemLoader(os.path.join(PATH, 'templates')),
trim_blocks=False,
keep_trailing_newline=True)
if __name__ == "__main__":
main()
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34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
198,
2,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
220,
4091,
262,
13789,
329,
262,
198,
2,
2176,
3303,
15030,
21627,
290,
11247,
198,
2,
739,
262,
13789,
13,
198,
2,
198,
2,
16529,
10541,
198,
2,
13610,
30865,
10130,
8479,
341,
11055,
198,
2,
16529,
10541,
198,
198,
11748,
1822,
29572,
198,
11748,
269,
21370,
198,
11748,
33918,
198,
11748,
28686,
198,
6738,
474,
259,
6592,
17,
1330,
9344,
11,
9220,
11964,
17401,
198,
198,
34219,
796,
28686,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
397,
2777,
776,
7,
834,
7753,
834,
4008,
198,
51,
3620,
6489,
6158,
62,
1677,
53,
4663,
1340,
10979,
796,
9344,
7,
198,
220,
220,
220,
1960,
3028,
36435,
28,
25101,
11,
198,
220,
220,
220,
40213,
28,
8979,
11964,
17401,
7,
418,
13,
6978,
13,
22179,
7,
34219,
11,
705,
11498,
17041,
11537,
828,
198,
220,
220,
220,
15797,
62,
27372,
28,
25101,
11,
198,
220,
220,
220,
1394,
62,
9535,
4386,
62,
3605,
1370,
28,
17821,
8,
628,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 3.488889 | 360 |
# -*- coding: utf-8 -*-
from openerp import tools
from openerp import models,fields,api
from openerp.tools.translate import _
import datetime
import pytz
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
201,
198,
201,
198,
6738,
21996,
79,
1330,
4899,
201,
198,
6738,
21996,
79,
1330,
4981,
11,
25747,
11,
15042,
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6738,
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79,
13,
31391,
13,
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11748,
12972,
22877,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198
] | 2.615385 | 65 |
BASIC_AUTH = "basic"
DIGEST_AUTH = "digest"
OAUTH1 = "oauth1"
BEARER_AUTH = "bearer"
PASSWORD_PLACEHOLDER = '*' * 16
CONNECT_TIMEOUT = 60
# If any remote service does not respond within 5 minutes, time out.
# (Some OpenMRS reports can take a long time. Cut them a little slack,
# but not too much.)
READ_TIMEOUT = 5 * 60
REQUEST_TIMEOUT = (CONNECT_TIMEOUT, READ_TIMEOUT)
ALGO_AES = 'aes'
DATA_TYPE_UNKNOWN = None
COMMCARE_DATA_TYPE_TEXT = 'cc_text'
COMMCARE_DATA_TYPE_INTEGER = 'cc_integer'
COMMCARE_DATA_TYPE_DECIMAL = 'cc_decimal'
COMMCARE_DATA_TYPE_BOOLEAN = 'cc_boolean'
COMMCARE_DATA_TYPE_DATE = 'cc_date'
COMMCARE_DATA_TYPE_DATETIME = 'cc_datetime'
COMMCARE_DATA_TYPE_TIME = 'cc_time'
COMMCARE_DATA_TYPES = (
COMMCARE_DATA_TYPE_TEXT,
COMMCARE_DATA_TYPE_INTEGER,
COMMCARE_DATA_TYPE_DECIMAL,
COMMCARE_DATA_TYPE_BOOLEAN,
COMMCARE_DATA_TYPE_DATE,
COMMCARE_DATA_TYPE_DATETIME,
COMMCARE_DATA_TYPE_TIME,
)
COMMCARE_DATA_TYPES_AND_UNKNOWN = COMMCARE_DATA_TYPES + (DATA_TYPE_UNKNOWN,)
DIRECTION_IMPORT = 'in'
DIRECTION_EXPORT = 'out'
DIRECTION_BOTH = None
DIRECTIONS = (
DIRECTION_IMPORT,
DIRECTION_EXPORT,
DIRECTION_BOTH,
)
| [
33,
1921,
2149,
62,
32,
24318,
796,
366,
35487,
1,
198,
35,
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32,
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366,
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12203,
62,
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62,
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62,
33,
6684,
2538,
1565,
796,
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535,
62,
2127,
21052,
6,
198,
9858,
9655,
12203,
62,
26947,
62,
25216,
62,
35,
6158,
796,
705,
535,
62,
4475,
6,
198,
9858,
9655,
12203,
62,
26947,
62,
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62,
35,
1404,
2767,
12789,
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535,
62,
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8079,
6,
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62,
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220,
220,
9440,
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62,
26947,
62,
25216,
62,
32541,
11,
198,
220,
220,
220,
9440,
9655,
12203,
62,
26947,
62,
25216,
62,
12394,
7156,
1137,
11,
198,
220,
220,
220,
9440,
9655,
12203,
62,
26947,
62,
25216,
62,
41374,
3955,
1847,
11,
198,
220,
220,
220,
9440,
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62,
26947,
62,
25216,
62,
33,
6684,
2538,
1565,
11,
198,
220,
220,
220,
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62,
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62,
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62,
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220,
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62,
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62,
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62,
35,
1404,
2767,
12789,
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220,
220,
220,
9440,
9655,
12203,
62,
26947,
62,
25216,
62,
34694,
11,
198,
8,
198,
9858,
9655,
12203,
62,
26947,
62,
9936,
47,
1546,
62,
6981,
62,
4944,
44706,
796,
9440,
9655,
12203,
62,
26947,
62,
9936,
47,
1546,
1343,
357,
26947,
62,
25216,
62,
4944,
44706,
35751,
198,
198,
17931,
23988,
2849,
62,
3955,
15490,
796,
705,
259,
6,
198,
17931,
23988,
2849,
62,
6369,
15490,
796,
705,
448,
6,
198,
17931,
23988,
2849,
62,
33,
26946,
796,
6045,
198,
17931,
23988,
11053,
796,
357,
198,
220,
220,
220,
42242,
2849,
62,
3955,
15490,
11,
198,
220,
220,
220,
42242,
2849,
62,
6369,
15490,
11,
198,
220,
220,
220,
42242,
2849,
62,
33,
26946,
11,
198,
8,
198
] | 2.254826 | 518 |
from random import randint
numeros = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10))
print('os numeros sorteados são: ', end='')
for n in numeros:
print(f'{n}', end=' ')
print(f'\no maior numero foi {max(numeros)}')
print(f'O menor numero foi {min(numeros)}')
| [
6738,
4738,
1330,
43720,
600,
198,
77,
6975,
418,
796,
357,
25192,
600,
7,
16,
11,
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828,
43720,
600,
7,
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7,
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6,
59,
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17266,
1504,
997,
3529,
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72,
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9806,
7,
77,
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418,
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198,
4798,
7,
69,
6,
46,
1450,
273,
997,
3529,
11511,
72,
1391,
1084,
7,
77,
6975,
418,
38165,
11537,
628,
628
] | 2.325581 | 129 |
import numpy as np
import pandas as pd
import scrape_data
import csv
team_data = pd.read_csv('data/cbb19.csv')
team_data = team_data.drop(columns=['POSTSEASON', 'SEED'])
t = list(team_data['TEAM'])
all_games = scrape_data.all_games
winners = scrape_data.winners
name_mappings = {'UNC': 'North Carolina', 'Citadel': 'The Citadel', 'Purdue-Fort Wayne': 'Fort Wayne',
'Arkansas-Pine Bluff': 'Arkansas Pine Bluff', 'UT-Martin': 'Tennessee Martin', 'ETSU':
'East Tennessee St.', 'Gardner-Webb': 'Gardner Webb', 'UIC': 'Illinois Chicago', 'Louisiana-Monroe':
'Louisiana Monroe', 'Ole Miss': 'Mississippi', 'Prairie View': 'Prairie View A&M', "St. John's (NY)":
"St. John's", 'Miami (FL)': 'Miami FL', 'Miami (OH)': 'Miami OH', "Loyola (IL)": "Loyola Chicago",
"Loyola (MD)": "Loyola MD", "Pitt": "Pittsburgh", "Texas-Arlington": "UT Arlington",
"Alabama-Birmingham": "UAB", "St. Joseph's": "Saint Joseph's", 'Louisiana': 'Louisiana Lafayette',
'Omaha': 'Nebraska Omaha', 'California Baptist': 'Cal Baptist', 'Texas-Rio Grande Valley':
'UT Rio Grande Valley', 'Florida International': 'FIU', 'William ': 'William & Mary', 'UMass':
'Massachusetts', 'Saint Francis (PA)': 'St. Francis PA', 'LIU': 'LIU Brooklyn', 'Albany (NY)':
'Albany', 'St. Francis (NY)': 'St. Francis NY', 'Grambling': 'Grambling St.', 'Texas A&M-Corpus':
'Texas A&M Corpus Chris', 'UMass-Lowell': 'UMass Lowell', 'Bethune-Cookman': 'Bethune Cookman',
"St. Peter's": "Saint Peter's", "Maryland-Eastern Shore": "Maryland Eastern Shore", "SIU-Edwardsville":
"SIU Edwardsville"}
for i in range(len(all_games)):
for j in range(len(all_games[0])):
if('UC' in all_games[i][j]):
if(all_games[i][j] == 'UCSB'):
all_games[i][j] = 'UC Santa Barbara'
elif(all_games[i][j] == "UConn"):
all_games[i][j] = 'Connecticut'
else:
pos = all_games[i][j].find('-')
if(pos != -1):
all_games[i][j] = all_games[i][j][:pos] + \
' ' + all_games[i][j][pos+1:]
elif('cal state' in all_games[i][j].lower()):
pos = all_games[i][j].lower().find('state')
all_games[i][j] = all_games[i][j][:pos] + \
'St. ' + all_games[i][j][pos + 6:]
elif('state' in all_games[i][j].lower()):
if(all_games[i][j] == 'NC State'):
all_games[i][j] = 'North Carolina St.'
elif(all_games[i][j] == 'Bowling Green State'):
all_games[i][j] = 'Bowling Green'
elif(all_games[i][j] != "USC Upstate"):
all_games[i][j] = all_games[i][j][:-3] + '.'
elif(all_games[i][j] in name_mappings.keys()):
all_games[i][j] = name_mappings[all_games[i][j]]
for i in range(len(winners)):
if('UC' in winners[i]):
if(winners[i] == 'UCSB'):
winners[i] = 'UC Santa Barbara'
elif(winners[i] == "UConn"):
winners[i] = 'Connecticut'
else:
pos = winners[i].find('-')
if(pos != -1):
winners[i] = winners[i][:pos] + ' ' + winners[i][pos+1:]
elif('cal state' in winners[i].lower()):
pos = winners[i].lower().find('state')
winners[i] = winners[i][:pos] + 'St. ' + winners[i][pos + 6:]
elif('state' in winners[i].lower()):
if(winners[i] == 'NC State'):
winners[i] = 'North Carolina St.'
elif(winners[i] == 'Bowling Green State'):
winners[i] = 'Bowling Green'
elif(winners[i] != "USC Upstate"):
winners[i] = winners[i][:-3] + '.'
elif(winners[i] in name_mappings.keys()):
winners[i] = name_mappings[winners[i]]
games = pd.DataFrame(all_games, columns=['Away Team', 'Home Team'])
games['Winner'] = winners
games_to_drop = []
for i in range(len(games)):
if(not(games['Away Team'][i] in t and games['Home Team'][i] in t)):
games_to_drop.append(i)
games = games.drop(games_to_drop)
games = games.reset_index()
games = games.drop(columns=['index'])
with open('data/all_games_19.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter=',')
writer.writerow(['Away Team', 'Home Team', 'Winner'])
for i in range(len(games)):
writer.writerow(
[games['Away Team'][i], games['Home Team'][i], games['Winner'][i]])
| [
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8,
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220,
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220,
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220,
220,
220,
220,
220,
220,
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220,
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220,
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13,
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8,
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357,
12096,
8,
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705,
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18723,
3256,
366,
43,
726,
5708,
357,
4146,
8,
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366,
43,
726,
5708,
4842,
1600,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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366,
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12,
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1298,
366,
3843,
30379,
1600,
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] | 2.003873 | 2,324 |
import datetime, pytz
def getEventStartEnd(event):
'''returns start time & end time as datetime objects from an event struct'''
start_string = event['start'].get('dateTime',event['start'].get('date'))
start_time = str2time(start_string)
end_string = event['end'].get('dateTime',0)
whole_day_event = 0
if not end_string:
end_time = start_time + datetime.timedelta(days = 1)
whole_day_event = 1
else:
end_time = str2time(end_string)
return start_time,end_time,whole_day_event
def daily_insert(service,event,time_begin,duration,
effective_days,date_start = datetime.datetime.today(),
repeat_on_day_of_week = {0,1,2,3,4,5,6}):
"""
service: googleCalendar API connection. See connection.py
event: event struct. Can be created from eventCreator()
***Note that event does not need to contain start and end dates. If it
does, then it is going to overwritten***
repeat_on_day_of_week: an integer list with len 1~7 and values 0-6 each integer
value represent a day of week. e.g. 0 is Monday, 2 is Wednesday, etc. This determines
on what day of the week the event shall repeat
time_start: datetime.time() object. When the event take place on each day
even_duartion: datetime.timedelta() object. Duration of the event
effective_days: over how many days do you want the event repeated? e.g. 365 days (1 year)
date_start (optional) : when do you want the event to start repeating? By default it is
going to be the date when this function is executed. Note that if the day is not
one of the day specified in repeat_day_of_week, the next closest date meeting the
criterial is when the event going to start.
"""
datetime_begin = datetime.datetime.combine(date_start,time_begin)
datetime_end = datetime_begin + duration
for days in range(effective_days):
datetime_begin = datetime_begin + datetime.timedelta(days = 1)
datetime_end = datetime_end + datetime.timedelta(days = 1)
#check if right weekday
if not datetime_begin.weekday() in repeat_on_day_of_week:
continue
start_string = time2str(datetime_begin)
end_string = time2str(datetime_end)
event['start']['dateTime'] = start_string
event['end']['dateTime'] = end_string
service.events().insert(calendarId = "primary",body = event).execute()
def getFreeTime(service,start_datetime = datetime.datetime.now(),check_ndays = 14,min_free_len_mins = 10):
"""returns a list of free time psuedo-events starting from start_date for
n effective_days
service: googleCalendar API connection. See connection.py
start_date: datetime.datetime obj
effective_days: datetime.timedelta obj
check_ndays: how many days from the start date to check for
min_free_len_mins: minumn lenth of free time. Any free time shorter will be ignored
"""
calendar_result = service.calendarList().list().execute()
calendars = calendar_result.get('items',[])
all_events = []
for calendar in calendars:
cal_id = calendar['id']
events = getEvents(service,cal_id,start_datetime,check_ndays)
all_events = all_events + events
#now we remove all day events
remove_list = list()
for event in all_events:
if not event['start'].get('dateTime',0):
remove_list.append(event)
for event in remove_list:
all_events.remove(event)
#now we sort all events by their start time
all_events = sorted(all_events, key = lambda t: t['start'].get('dateTime'))
#we set the first end time to be start_time
end_datetime = start_datetime
#create a list holder of free_time events
free_times = []
for event in all_events:
start_string = event['start']['dateTime']
start_datetime = str2time(start_string)
duration_timedelta = start_datetime - end_datetime #we calculate duration by using the start time of the second event minus the end time of the first event
duration = divmod(duration_timedelta.total_seconds(),60)
duration = duration[0]
if duration < min_free_len_mins:
# if duration is too short skip
end_datetime = str2time(event['end']['dateTime'])
continue
else:
#if duration is good, create free time event
free_time = eventCreator(end_datetime,start_datetime,-2,0,'free event',0,0,'Free Time',0) #not the start_datetime field is actually filled by the end_datetime vairable, and vice versa
free_times.append(free_time)
#update end_datetime for next loop
end_datetime = str2time(event['end']['dateTime'])
return free_times
def getCalendarId(service,calendar_summary):
'''returns a calendar_Id from a calendar_summary. Always returns the
first one found. If none found, return -1'''
calendar_result = service.calendarList().list().execute()
calendars = calendar_result.get('items',[])
for calendar in calendars:
if calendar['summary'] == calendar_summary:
return calendar['id']
return -1
def getEvents(service,calId,start_datetime,search_for_ndays):
'''do not use this unless you intend to pull only raw Google Calendar Events from
the server. This is intended to be used as a component for methods such as getAllEvents()'''
end_datetime = start_datetime.date() + datetime.timedelta(days = int(search_for_ndays) + 1) #+1 here because timeMax is exclusive
end_datetime = datetime.datetime.combine(end_datetime, datetime.time(0,0)) #note the end time always at 0:00
start_datetime = utcFormat(start_datetime)
end_datetime = utcFormat(end_datetime)
events_result = service.events().list(calendarId= calId,
timeMin=start_datetime,
maxResults= 1000, singleEvents=True,
timeMax= end_datetime,
orderBy='startTime').execute()
events = events_result.get('items', [])
return events
def createRecurringEvent(event,by_day ='MO,TU,WE,TH,FR,SA,SU',until = 0):
'''until needs to be a string in the formta "YYYYMMDD" '''
'''needs more work'''
event['recurrence'] = list()
if until:
until_statement = 'UNTIL=' + until + ';'
else:
until_statement = ''
event['recurrence'].append( 'RRULE:FREQ=WEEKLY;'+ until_statement+'BYDAY=' + by_day)
return event
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198,
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628,
220,
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220,
220,
628,
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] | 2.428369 | 2,827 |
# Generated by Django 4.0.2 on 2022-02-19 16:35
from django.db import migrations, models
| [
2,
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416,
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] | 2.84375 | 32 |
# coding: mixt
from mixt import Element, NotProvided, Required, html
from mixt.contrib.css import css_vars
from ... import datatypes
from ..doc import DocPart, DocHeader
from ..generic import Details
from . import Code, DocString, NamedValue, UnnamedValue
</Details>
</if>
</DocPart>
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] | 2.637097 | 124 |
from math import sqrt, ceil
if __name__ == "__main__":
from aocd import get_data
data = get_data(year=2021, day=17)
print(part1(data))
print(part2(data))
| [
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] | 2.324675 | 77 |
# Generated by Django 2.2.6 on 2020-11-14 23:01
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
| [
2,
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] | 3.019231 | 52 |
from __future__ import unicode_literals
import sys
import logging
from datetime import datetime
from framework.mongo import database
from website.app import init_app
from scripts import utils as script_utils
from framework.transactions.context import TokuTransaction
logger = logging.getLogger(__name__)
# 2015 Sept 18
CUT_OFF_DATE = (2015, 9, 18)
BACKUP_COLLECTION = 'zzz20151009pagecounters'
NEW_COLLECTION = '20151009pagecountersmigrated'
if __name__ == '__main__':
dry = 'dry' in sys.argv
if not dry:
script_utils.add_file_logger(logger, __file__)
# Allow setting the log level just by appending the level to the command
if 'debug' in sys.argv:
logger.setLevel(logging.DEBUG)
elif 'warning' in sys.argv:
logger.setLevel(logging.WARNING)
elif 'info' in sys.argv:
logger.setLevel(logging.INFO)
elif 'error' in sys.argv:
logger.setLevel(logging.ERROR)
main(dry=dry)
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] | 2.648045 | 358 |
import json
import trustlab.lab.config as config
import time
from trustlab.consumers.chunk_consumer import ChunkAsyncJsonWebsocketConsumer
from trustlab.models import *
from trustlab.serializers.scenario_serializer import ScenarioSerializer
from trustlab.lab.director import Director
class LabConsumer(ChunkAsyncJsonWebsocketConsumer):
"""
LabConsumer class, with sequential process logic of the Director in its receive_json method.
It is therewith the main interface between User Agent and Director.
"""
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] | 3.737589 | 141 |
from telegapi.reqs import reqs as reqs
from telegapi.telapi import telapi
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import bilby
import numpy as np
from bilby.core.likelihood import (
AnalyticalMultidimensionalBimodalCovariantGaussian,
AnalyticalMultidimensionalCovariantGaussian,
)
logger = bilby.core.utils.logger
cov = [
[
0.045991865933182365,
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0.0020087713726603213,
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0.005260905282822458,
0.0013607957548231718,
0.001970785895702776,
0.006708452591621081,
-0.005107684668720825,
0.004402554308030673,
-0.00334987648531921,
],
[
-0.005489748382557152,
0.05478640427684032,
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0.004858466255616657,
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0.003169780190169035,
0.006761345004654851,
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0.005571796842520162,
-0.0071098291510566895,
-0.004477773540640284,
-0.011250694688474672,
0.007465228985669282,
],
[
-0.01025067223674548,
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0.044324704403674524,
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0.0025107211483955676,
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0.01153595152487264,
0.005773054728678472,
0.005286558230422045,
-0.0055438798694137734,
0.0044772210361854765,
-0.00620416958073918,
],
[
0.0020087713726603213,
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0.029861342087731065,
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0.009925736654597632,
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0.003885350572544307,
0.00022362281488693097,
0.006609741178005571,
-0.003292722856107429,
-0.005873218251875897,
],
[
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0.0538403407841302,
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0.004499568241334517,
0.009591034277125177,
0.00008612746932654223,
0.003386296829505543,
-0.002600737873367083,
0.000621148057330571,
-0.006603857049454523,
-0.009241221870695395,
],
[
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0.004858466255616657,
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0.0033303577606412765,
],
[
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],
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0.011126783289057604,
],
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],
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],
[
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],
[
0.006708452591621083,
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0.005286558230422046,
0.00022362281488693216,
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0.0019732354732442886,
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0.04762367868805726,
0.0008818947598625008,
-0.0007262691465810616,
-0.006482422704208912,
],
[
-0.005107684668720825,
-0.0044777735406402895,
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0.006609741178005571,
0.0006211480573305693,
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0.0057186369973531905,
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0.0008818947598624995,
0.042639958466440225,
0.0010194948614718209,
0.0033872675386130637,
],
[
0.004402554308030674,
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0.004477221036185477,
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0.0003370445313891318,
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-0.0007262691465810616,
0.0010194948614718226,
0.05244900188599414,
-0.000256550861960499,
],
[
-0.00334987648531921,
0.007465228985669282,
-0.006204169580739178,
-0.005873218251875899,
-0.009241221870695395,
0.003330357760641278,
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0.011126783289057604,
-0.0031735521631824654,
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-0.007137012700864866,
-0.006482422704208912,
0.0033872675386130632,
-0.000256550861960499,
0.05380987317762257,
],
]
dim = 15
mean = np.zeros(dim)
label = "multidim_gaussian_unimodal"
outdir = "outdir"
likelihood = AnalyticalMultidimensionalCovariantGaussian(mean, cov)
priors = bilby.core.prior.PriorDict()
priors.update(
{
"x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i))
for i in range(dim)
}
)
result = bilby.run_sampler(
likelihood=likelihood,
priors=priors,
sampler="dynesty",
outdir=outdir,
label=label,
check_point_plot=True,
resume=True,
)
result.plot_corner(parameters={"x{0}".format(i): mean[i] for i in range(dim)})
# The prior is constant and flat, and the likelihood is normalised such that the area under it is one.
# The analytical evidence is then given as 1/(prior volume)
log_prior_vol = np.sum(
np.log([prior.maximum - prior.minimum for key, prior in priors.items()])
)
log_evidence = -log_prior_vol
sampled_std = [
np.std(result.posterior[param]) for param in result.search_parameter_keys
]
logger.info("Analytic log evidence: " + str(log_evidence))
logger.info(
"Sampled log evidence: "
+ str(result.log_evidence)
+ " +/- "
+ str(result.log_evidence_err)
)
for i, search_parameter_key in enumerate(result.search_parameter_keys):
logger.info(search_parameter_key)
logger.info("Expected posterior standard deviation: " + str(likelihood.sigma[i]))
logger.info("Sampled posterior standard deviation: " + str(sampled_std[i]))
# BIMODAL distribution
label = "multidim_gaussian_bimodal"
dim = len(cov[0])
mean_1 = 4 * np.sqrt(np.diag(cov))
mean_2 = -4 * np.sqrt(np.diag(cov))
likelihood = AnalyticalMultidimensionalBimodalCovariantGaussian(mean_1, mean_2, cov)
priors = bilby.core.prior.PriorDict()
priors.update(
{
"x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i))
for i in range(dim)
}
)
result = bilby.run_sampler(
likelihood=likelihood,
priors=priors,
sampler="dynesty",
outdir=outdir,
label=label,
check_point_plot=True,
resume=True,
)
result.plot_corner(
parameters={"x{0}".format(i): mean_1[i] for i in range(dim)},
filename=outdir + "/multidim_gaussian_bimodal_mode_1",
)
result.plot_corner(
parameters={"x{0}".format(i): mean_2[i] for i in range(dim)},
filename=outdir + "/multidim_gaussian_bimodal_mode_2",
)
log_prior_vol = np.sum(
np.log([prior.maximum - prior.minimum for key, prior in priors.items()])
)
log_evidence = -log_prior_vol
sampled_std_1 = []
sampled_std_2 = []
for param in result.search_parameter_keys:
samples = np.array(result.posterior[param])
samples_1 = samples[np.where(samples < 0)]
samples_2 = samples[np.where(samples > 0)]
sampled_std_1.append(np.std(samples_1))
sampled_std_2.append(np.std(samples_2))
logger.info("Analytic log evidence: " + str(log_evidence))
logger.info(
"Sampled log evidence: "
+ str(result.log_evidence)
+ " +/- "
+ str(result.log_evidence_err)
)
for i, search_parameter_key in enumerate(result.search_parameter_keys):
logger.info(search_parameter_key)
logger.info(
"Expected posterior standard deviation both modes: " + str(likelihood.sigma[i])
)
logger.info(
"Sampled posterior standard deviation first mode: " + str(sampled_std_1[i])
)
logger.info(
"Sampled posterior standard deviation second mode: " + str(sampled_std_2[i])
)
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13,
22544,
2780,
5607,
2780,
2548,
1495,
3553,
17827,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2713,
2857,
4521,
26429,
1983,
3104,
1821,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2857,
4521,
1238,
1959,
14656,
27412,
3510,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3720,
1270,
33372,
1821,
2425,
486,
25022,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
3270,
2231,
940,
2425,
1314,
18741,
20219,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2780,
3365,
42199,
1495,
3980,
1433,
37680,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
1433,
30924,
27301,
1433,
2154,
18638,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
11245,
22172,
3695,
30484,
486,
35844,
2327,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
42548,
1485,
2231,
22914,
2996,
2780,
4349,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
2425,
2079,
4304,
21395,
2075,
3104,
32576,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
41948,
21738,
3104,
32114,
1264,
5237,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
940,
4089,
1959,
1314,
13348,
35809,
3865,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2598,
3324,
3324,
2327,
29703,
1821,
30336,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
1065,
1120,
45214,
34427,
2857,
24669,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
4524,
2996,
23815,
42250,
36657,
32568,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
2999,
1120,
3134,
1828,
27824,
2231,
2780,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2857,
4521,
1238,
1959,
14656,
27412,
2598,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
43977,
33916,
2154,
25644,
27824,
2231,
1731,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
37187,
3553,
2078,
22745,
23721,
27037,
2231,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28694,
44230,
3388,
2327,
26200,
27203,
1415,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2780,
2624,
1065,
2713,
5607,
27696,
2682,
2414,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2231,
4304,
1507,
3388,
2791,
25674,
23195,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
1495,
940,
4761,
1157,
2780,
2670,
2816,
42548,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
486,
2075,
6420,
1129,
1485,
3553,
1157,
6659,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
486,
1314,
2327,
3865,
1314,
1731,
5774,
18897,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
22544,
3324,
22515,
2857,
2078,
30924,
37856,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
22544,
27033,
2816,
6469,
1270,
3682,
1238,
2231,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2816,
43704,
43240,
3388,
44103,
3324,
2682,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2598,
3324,
1828,
940,
2623,
21652,
2857,
2996,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
18638,
1433,
3865,
36928,
2670,
1507,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
11528,
3324,
19708,
2075,
1899,
2624,
1485,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3720,
1270,
33372,
1821,
2425,
486,
25022,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
37187,
3553,
2078,
22745,
23721,
27037,
2623,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
48891,
4521,
19880,
21315,
3324,
26717,
2996,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
1795,
2682,
3324,
19880,
26598,
35447,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
16562,
36657,
2598,
10232,
2425,
1899,
2481,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2079,
28676,
2623,
2996,
33459,
4304,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
4304,
29173,
19707,
3682,
1238,
2154,
4349,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
22544,
38314,
2670,
3553,
1821,
1954,
1238,
27203,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
1983,
23045,
1954,
2327,
4790,
1983,
2999,
1433,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
30460,
4310,
1120,
3553,
1495,
2598,
22996,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
1828,
2623,
23815,
1415,
3459,
3388,
1270,
5607,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
28041,
31751,
4524,
1157,
3695,
405,
2816,
4869,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
1959,
1983,
23815,
3980,
940,
4524,
1959,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
44617,
2624,
1507,
1495,
1507,
2425,
4531,
22,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
2075,
33646,
40486,
2857,
4089,
1959,
5774,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
3270,
2231,
940,
2425,
1314,
18741,
21599,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28694,
44230,
3388,
2327,
26200,
27203,
1415,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
1795,
2682,
3324,
19880,
26598,
35667,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2713,
2548,
1821,
23601,
3695,
3901,
22709,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
2598,
2791,
4051,
2425,
33690,
2091,
1433,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1495,
20666,
20,
2682,
24339,
1558,
486,
4310,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2598,
33438,
3104,
1731,
16945,
2231,
1558,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
28694,
3270,
940,
2682,
27019,
11623,
22413,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2388,
4521,
1065,
4524,
3388,
39195,
4051,
22047,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2091,
4521,
1959,
3104,
1959,
1120,
2816,
3559,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2075,
25816,
2718,
5774,
29211,
2154,
5999,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
5237,
16562,
1795,
3553,
26073,
42875,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
1899,
27203,
2154,
2920,
2231,
2231,
1954,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28694,
1731,
18376,
1507,
2154,
37381,
31010,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2682,
28727,
2075,
23188,
1157,
2231,
18897,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2780,
3365,
42199,
1495,
3980,
1433,
37680,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2780,
2624,
1065,
2713,
5607,
27696,
30995,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
16562,
36657,
2598,
10232,
38219,
25150,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
2598,
2791,
4051,
2425,
33690,
2091,
1507,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
3023,
2718,
3510,
38605,
1485,
2548,
2996,
13464,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
48712,
1983,
12952,
26912,
25191,
2996,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
940,
2079,
2996,
18638,
27988,
1433,
1485,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
2791,
1238,
1731,
486,
1558,
5892,
1433,
3104,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1065,
3270,
1314,
6200,
2718,
2154,
1795,
3365,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3104,
2079,
4089,
1959,
4309,
17657,
26276,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
40220,
22370,
37804,
25707,
2078,
3695,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1731,
2231,
3134,
3134,
2857,
405,
3559,
1731,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
2231,
2857,
3695,
36928,
3682,
1507,
1433,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2091,
1270,
2327,
3324,
1899,
2414,
16799,
2996,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2718,
1558,
2682,
29159,
27203,
29334,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
1433,
30924,
27301,
1433,
2154,
22136,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2231,
4304,
1507,
3388,
2791,
25674,
27367,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2079,
28676,
2623,
2996,
33459,
4304,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1495,
20666,
20,
2682,
24339,
1558,
486,
4310,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
48712,
1983,
12952,
26912,
25191,
2996,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
32459,
29334,
23195,
3104,
25838,
6469,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
5824,
36809,
25270,
1983,
2078,
7029,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
5237,
1485,
4524,
22172,
2920,
2231,
13348,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
25816,
1157,
5774,
2425,
3865,
2598,
5705,
27696,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
3134,
39226,
2718,
2079,
3023,
21652,
2075,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
8054,
31496,
2920,
3553,
49087,
28567,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
3553,
25096,
2623,
39647,
33319,
23362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
47785,
940,
3865,
1495,
2857,
23906,
3324,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
5705,
36879,
2791,
3695,
1065,
2091,
21261,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
3388,
35890,
3324,
1314,
3134,
4089,
3553,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
11245,
22172,
3695,
30484,
486,
35844,
30995,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
1495,
940,
4761,
1157,
2780,
2670,
2816,
2791,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
4304,
29173,
19707,
3682,
1238,
2154,
3270,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2598,
33438,
3104,
1731,
16945,
2231,
1314,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
940,
2079,
2996,
18638,
27988,
1433,
1558,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
5824,
36809,
25270,
1983,
2078,
21844,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2713,
3324,
2682,
2075,
35402,
1795,
3459,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2816,
24591,
27970,
44688,
3865,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
9879,
1795,
2780,
28256,
26598,
23237,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
3134,
2920,
3388,
26895,
3312,
24,
3365,
5824,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
28978,
3510,
486,
15711,
4089,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3695,
3720,
1731,
2857,
1983,
3104,
1129,
1731,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
22544,
2624,
17430,
2548,
32128,
1238,
27260,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
486,
14686,
3134,
5999,
27693,
43526,
31916,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
4309,
31751,
2713,
2078,
2078,
24137,
3365,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
42548,
1485,
2231,
22914,
2996,
2780,
31654,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
486,
2075,
6420,
1129,
1485,
3553,
1157,
6659,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
22544,
38314,
2670,
3553,
1821,
1954,
18638,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
28694,
3270,
940,
2682,
27019,
11623,
22413,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
2791,
1238,
1731,
486,
1558,
5892,
1433,
3104,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
5237,
1485,
4524,
22172,
2920,
2231,
15801,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2816,
24591,
27970,
44688,
3865,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
3023,
39132,
3134,
405,
23362,
3388,
48564,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
3023,
1983,
486,
2919,
12762,
41544,
2791,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
49087,
21599,
12762,
29796,
27301,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
39121,
1899,
1238,
2670,
3270,
38073,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
32128,
23195,
27800,
19891,
1731,
5332,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
2091,
32869,
2231,
25838,
4531,
12952,
6052,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
1558,
2327,
4309,
24136,
1507,
1731,
3134,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
1485,
1899,
3720,
36189,
2780,
1954,
1558,
2598,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
2425,
2079,
4304,
21395,
2075,
3104,
32576,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
486,
1314,
2327,
3865,
1314,
1731,
5774,
18897,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
1983,
23045,
1954,
2327,
4790,
2075,
42250,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2388,
4521,
1065,
4524,
48528,
22980,
29703,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1065,
3270,
1314,
6200,
2718,
2154,
1795,
5237,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
25816,
1157,
5774,
2425,
3865,
2598,
5705,
27696,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
9879,
1795,
2780,
28256,
26598,
1558,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
3023,
1983,
486,
2919,
12762,
41544,
3104,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
2713,
44675,
1065,
31654,
1495,
5999,
34808,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
21601,
1129,
1495,
29334,
1433,
31010,
22579,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1238,
3553,
3134,
1828,
2718,
1983,
3324,
2718,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2780,
25150,
24839,
1415,
29334,
17059,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
1821,
2996,
2624,
1899,
2075,
2791,
2075,
4761,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3980,
1129,
486,
1238,
3324,
1157,
2920,
1485,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
30986,
3695,
3365,
3865,
2154,
1983,
49641,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
41948,
21738,
3104,
32114,
1264,
5237,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
22544,
3324,
22515,
2857,
2078,
30924,
37856,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
30460,
4310,
1120,
3553,
1495,
2598,
26895,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2091,
4521,
1959,
3104,
1959,
1120,
2816,
3682,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3104,
2079,
4089,
1959,
4309,
17657,
29807,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
3134,
39226,
2718,
2079,
3023,
21652,
1828,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
3134,
2920,
3388,
26895,
3312,
24,
3365,
6052,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
49087,
21599,
12762,
29796,
14315,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
21601,
1129,
1495,
29334,
1433,
31010,
1959,
3459,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
25707,
22413,
1314,
4304,
1731,
1433,
41948,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1270,
2718,
24136,
2598,
4304,
405,
25061,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
17657,
2623,
4524,
31020,
2548,
1983,
2623,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
23,
24943,
16799,
30120,
2481,
1065,
2670,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
19708,
486,
1983,
25257,
34287,
2791,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
28041,
32583,
2231,
25191,
1433,
21536,
5999,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
25816,
940,
4089,
1959,
1314,
13348,
35809,
3865,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
22544,
27033,
2816,
6469,
1270,
3682,
1238,
3510,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
1828,
2623,
23815,
1415,
3459,
3388,
2624,
1433,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2075,
25816,
2718,
5774,
29211,
2154,
37988,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
40220,
22370,
37804,
25707,
2078,
4521,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
8054,
31496,
2920,
3553,
49087,
33394,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
28978,
3510,
486,
940,
4531,
22,
17032,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
39121,
1899,
1238,
2670,
3270,
38073,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1238,
3553,
3134,
1828,
2718,
1983,
3324,
2718,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1270,
2718,
24136,
2598,
4304,
405,
24136,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
35435,
1954,
30924,
3104,
1795,
3553,
2075,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
3459,
1507,
5824,
2425,
4089,
26704,
25257,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
22,
2075,
26276,
1415,
38431,
15801,
1433,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
34287,
1731,
1828,
2154,
27211,
4531,
1065,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
22544,
15982,
41580,
2791,
5774,
21315,
1495,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2598,
3324,
3324,
2327,
29703,
1821,
2078,
3865,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2816,
43704,
43240,
3388,
44103,
43571,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
28041,
31751,
4524,
1157,
3695,
405,
2816,
4869,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
5237,
16562,
1795,
48638,
22515,
48528,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
1731,
2231,
3134,
3134,
2857,
405,
3559,
1731,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
3553,
25096,
2623,
39647,
33319,
1129,
2713,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
3695,
3720,
1731,
2857,
1983,
3104,
17477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
32128,
23195,
27800,
19891,
23753,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
405,
2780,
25150,
24839,
1415,
29334,
19708,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
17657,
2623,
4524,
31020,
2548,
1983,
2623,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
3459,
1507,
5824,
2425,
49087,
1731,
33438,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
3023,
2075,
28771,
3365,
3510,
2414,
1821,
18182,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
8298,
30484,
2920,
34251,
20198,
1507,
22567,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2091,
5774,
2075,
2425,
2548,
5333,
20548,
2718,
11,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
22914,
1821,
1495,
4051,
1270,
1795,
1270,
45385,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
486,
1065,
1120,
45214,
34427,
2857,
3510,
2425,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
405,
2598,
3324,
1828,
940,
2623,
21652,
32883,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
11245,
1959,
1983,
23815,
3980,
940,
4524,
1959,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
1899,
27203,
2154,
2920,
2231,
2231,
1954,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
28041,
2231,
2857,
3695,
36928,
3682,
1507,
1314,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
830,
47785,
940,
3865,
1495,
2857,
23906,
4761,
11,
198,
220,
220,
220,
220,
220,
220,
220,
532,
15,
13,
22544,
2624,
17430,
2548,
32128,
1238,
27260,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
830,
2091,
32869,
2231,
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] | 1.786332 | 6,014 |
import re
| [
11748,
302,
628,
198
] | 3 | 4 |
from datetime import timedelta
import logging
from homeassistant.core import callback
from homeassistant.components.sensor import SensorEntity
from homeassistant.helpers.entity import DeviceInfo
from homeassistant.helpers.update_coordinator import (
DataUpdateCoordinator,
)
from homeassistant.const import (
CONF_NAME,
CONF_UNIT_OF_MEASUREMENT,
)
from .const import (
DOMAIN,
PROMETHEUS_METRIC_KEY,
PROMETHEUS_VALUE_KEY,
PROMETHEUS_JOB_KEY,
PROMETHEUS_INSTANCE_KEY,
)
from . import requestData
_LOGGER = logging.getLogger(__name__)
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# coding: utf-8
from __future__ import unicode_literals
import pytest
@pytest.mark.parametrize('text', ["ca.", "m.a.o.", "Jan.", "Dec."])
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'''This is my first class in python'''
p1 = Product()
p1.display()
# print(p1.name)
# print(p1.description)
# print(p1.price)
p2 = Product()
p2.display()
# print(p2.name)
# print(p2.description)
# print(p2.price) | [
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# Dungeon Crawler
import asciiart
import level1
import level2
import time # timer
import hero
#def test():
# print(asciiart.baby_dragon())
# print(asciiart.big_skull())
# print(asciiart.dragon())
# print(asciiart.samurai())
# print(asciiart.skull_cross())
# print(asciiart.warrior())
# print(asciiart.chicken())
global my_hero = hero.Hero("Bob")
start_dungeon()
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from distutils.core import setup
setup(
name='mepfinder',
version='0.1',
packages=['mepfinder'],
url='',
license='MIT',
author='Theodros Zelleke',
author_email='',
description=''
)
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# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('pokemonchg.csv')
X = dataset.iloc[:, [19,20,21,22,23,25,28,35]].values
y = dataset.iloc[:, 40].values
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)
# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)
#accuracy
from sklearn.metrics import accuracy_score
# Fitting Random Forest Classification to the Training set
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_randomforest = confusion_matrix(y_test, y_pred)
acc_randomforest=accuracy_score(y_test,y_pred)*100
# Fitting Kernel SVM to the Training set
from sklearn.svm import SVC
classifier = SVC(kernel = 'rbf', random_state = 0)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_svmkernel = confusion_matrix(y_test, y_pred)
acc_svmkernel=accuracy_score(y_test,y_pred)*100
# Fitting K-NN to the Training set
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_knn = confusion_matrix(y_test, y_pred)
acc_knn=accuracy_score(y_test,y_pred)*100
# Fitting Naive Bayes to the Training set
from sklearn.naive_bayes import GaussianNB
classifier = GaussianNB()
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_naivebayes = confusion_matrix(y_test, y_pred)
acc_naivebayes=accuracy_score(y_test,y_pred)*100
# Fitting Decision Tree Classification to the Training set
from sklearn.tree import DecisionTreeClassifier
classifier = DecisionTreeClassifier(criterion = 'entropy', random_state = 0)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_decisiontree = confusion_matrix(y_test, y_pred)
acc_decisiontree=accuracy_score(y_test,y_pred)*100
# Fitting SVM to the Training set
from sklearn.svm import SVC
classifier = SVC(kernel = 'linear', random_state = 0)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_svm = confusion_matrix(y_test, y_pred)
acc_svm=accuracy_score(y_test,y_pred)*100
# Fitting Logistic Regression to the Training set
from sklearn.linear_model import LogisticRegression
classifier = LogisticRegression(random_state = 0)
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_logistic = confusion_matrix(y_test, y_pred)
acc_logistic=accuracy_score(y_test,y_pred)*100
# Importing the Keras libraries and packages
import keras
from keras.models import Sequential
from keras.layers import Dense
from tensorflow.python.keras import backend as k
# Initialising the ANN
classifier = Sequential()
# Adding the input layer and the first hidden layer
classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu', input_dim = 8))
# Adding the second hidden layer
classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu'))
# Adding the third hidden layer
classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu'))
# Adding the fourth hidden layer
classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu'))
# Adding the output layer
classifier.add(Dense(output_dim = 1, init = 'uniform', activation = 'sigmoid'))
# Compiling the ANN
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
# Fitting the ANN to the Training set
classifier.fit(X_train, y_train, batch_size = 10, nb_epoch = 100)
# Part 3 - Making the predictions and evaluating the model
# Predicting the Test set results
y_pred = classifier.predict(X_test)
y_pred = (y_pred > 0.5)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm_ann = confusion_matrix(y_test, y_pred)
acc_ann=accuracy_score(y_test,y_pred)*100
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] | 2.811547 | 1,836 |
########################################################################
################# Importing packages #######################
########################################################################
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask_login import LoginManager
# init SQLAlchemy so we can use it later in our models
db = SQLAlchemy() | [
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] | 5.184211 | 76 |
# Copyright (c) 2021 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.
import os
from paddle.utils.cpp_extension import load
from .adamw import AdamW
from .AdamwOptimizer import AdamwOptimizer
from .adamwdl import AdamWDL
__all__ = [
'_jit_compile',
'AdamW',
'AdamwOptimizer',
'AdamWDL',
]
| [
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] | 3.290698 | 258 |
##################################################
# Copyright (c) INRIA (France) 2011, 2012, 2013
#
# This file is part of inria-mvs. You can redistribute it and/or
# modify it under the terms of the GNU General Public License.
#
# This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
# WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
#
# Author: Jean-Paul CHIEZE <jean-paul.chieze@inria.fr>
#
##################################################
import sys, os, re, string
from scipy import weave
import numpy as np
class MyException(Exception):
"""Bad parameter or file.
The execution cannot continue
"""
def draw_point(buf,ix,iy,size,color,cross = False):
"""
draw a colored square around point (ix,iy)
"""
code = """
struct pts {
int y;
int nbx;
int x[5];
};
struct pts rpoints[] = {
{-1,3,-1,0,1},
{0,2,-1,1,0},
{1,3,-1,0,1},
};
struct pts cpoints[] = {
{-2,1,0},
{-1,1,0},
{0,5,-2,-1,0,1,2},
{1,1,0},
{2,1,0},
};
#define NBLR sizeof(rpoints) / sizeof(struct pts)
#define NBLC sizeof(cpoints) / sizeof(struct pts)
#include <stdio.h>
int nbl;
struct pts *points;
if(cross == 0) {
nbl = NBLR;
points = rpoints;
} else {
nbl = NBLC;
points = cpoints;
}
int i, j, k, ky, kx, k0;
int rdimx = 3 * dimx;
for(j=0;j<nbl;j++) {
ky = points[j].y + iy;
if(ky < 0 || ky >= dimy) continue;
k0 = ky * rdimx;
for(i=0;i<points[j].nbx;i++) {
kx = points[j].x[i] + ix;
//printf("i,j = %d,%d, kx= %d, k0 = %d\\n",i,j,kx,k0);
if(kx < 0 || kx >= dimx) continue;
k = k0 + 3 * kx;
*(buf+k++) = color[0];
*(buf+k++) = color[1];
*(buf+k) = color[2];
}
}
"""
(dimx,dimy) = (size[0],size[1])
weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color','cross'])
def draw_color_rect(buf,ix,iy,size,wrect,color):
"""
draw a square centerd on x,y filled with color
"""
code = """
int nd = %d;
int x, y, i, j;
int ny = 1 + 2 * nd;
int nx = ny;
y = iy - nd;
if (y < 0) {
ny += y;
y = 0;
} else
if ((y + ny) > dimy) ny -= y + ny - dimy;
x = ix - nd;
if (x < 0) {
nx += x;
x = 0;
} else
if ((x + nx) > dimx) nx -= x + nx - dimx;
int k = y * dimx * 3 + 3 * x;
int deltak = 3 * (dimx - nx);
for (i = 0;i < ny;i++) {
for (j = 0;j < nx;j++) {
#if 1
*(buf+k++) = color[0];
*(buf+k++) = color[1];
*(buf+k++) = color[2];
#else
*(buf+k) = (*(buf+k) / 2) + (color[0] / 2);
k++;
*(buf+k) = (*(buf+k) / 2) + (color[1] / 2);
k++;
*(buf+k) = (*(buf+k) / 2) + (color[2] / 2);
k++;
#endif
}
k += deltak;
}
""" %wrect
(dimx,dimy) = (size[0],size[1])
#ll lqprint "XX %d %d" %(ix,iy)
if(ix < 0 or iy < 0 or ix >= dimx or iy >= dimy): return()
weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color'])
def c_projection(matr,pts3d,pts2d):
"""
fills pts2d (2xn array) with projection of pts3d (3xn array)
"""
code = """
int jj = 0;
int i;
float X[3];
float x;
int ki, kj;
for( i =0;i < npts;i++) {
double *mat = matr;
for(ki = 0;ki < 3; ki++) {
x = 0;
for(kj = 0;kj < 3;kj++)
x += *(mat+kj) * *(pts3d + jj + kj);
x += *(mat + 3);
X[ki] = x;
mat += 4;
}
x = X[2];
*(pts2d + jj) = X[0] / x;
*(pts2d + jj + 1) = X[1] / x;
*(pts2d + jj + 2) = x;
jj += 3;
}
"""
npts = pts3d.shape[1]
weave.inline(code,['matr','pts3d','pts2d','npts'])
def decode_line(s,l,func = float):
"""
split a string and convert each token with <func>
and append the result to list <l>
"""
x = s.split()
for v in x:
l.append(func(v))
return(l)
def get_bundle_header(bundler_file,num = None):
"""
reads header of <dir>/pmvs/bundle.rd.out
output : file handle (pointing to the 1st point), nb of points
+ if num is given >= 0 : focal length and 3x4 Rotation-translation matrix of camera
if num < 0 : array of focals and array of matrices for all cameras
"""
matPs = []
focals = []
f = open(bundler_file,'r')
s = f.readline()
s = f.readline()
s = s.strip()
l = s.split()
if len(l) != 2:
raise Exception, "Bad 1st line <%s> in bundle file" %s
nbcam = int(l[0])
nbpts = int(l[1])
if num != None and num >= nbcam:
raise Exception, "Only %d cameras" %nbcam
for i in xrange(0,nbcam):
(f,focal,m) = get_bundle_cam(f)
if num < 0 or i == num:
focals.append(focal)
matPs.append(m)
if num < 0:
return(f,nbpts,focals,matPs)
else:
return(f,nbpts,focals[0],matPs[0])
def read_projmatrx(file,return_coef = False,return_pairs = False):
"""
return the 3x4 projection matrix read from the given pmvs .txt file
"""
mat = []
with open(file,'r') as f:
lines = f.readlines()
s = lines[0].strip()
if (s != 'CONTOUR'):
raise Exception, "Bad format <%s> for projection file" %s
for i in range(1,4):
s = lines[i].strip()
l = s.split()
for j in range(0,4):
mat.append(float(l[j]))
if return_coef or return_pairs:
coef = None
pairs = []
if(len(lines) >= 6):
if(lines[4].strip() == 'COEF'):
coef = float(lines[5].strip())
if return_pairs:
if (len(lines) >= 10) and (lines[8].strip() == 'PAIRS'):
nbp = int(lines[9].strip())
if (len(lines) >= (10 + nbp)):
for i in xrange(0,nbp):
xl = map(lambda x : int(x) ,lines[10 + i].strip().split())
pairs.append(xl)
return(np.array(mat).reshape(3,4),coef,pairs)
return(np.array(mat).reshape(3,4),coef)
else:
return(np.array(mat).reshape(3,4))
def get_bundle_points(f,nbpts,numcam):
"""
input : filehandle to bundle file (ready to read 1st point)
nb of points, and num of picture
output (lists): - 3d coordinates of all points (numcam == None)
of points matched in camera numcam
- corresponding 2d coordinates if numcam is specified
(origine au centre de l'image)
- colors of returned points
"""
pts3d = []
pts2d = []
ptscol = []
for k in xrange(0,nbpts):
l = []
s = (f.readline()).strip()
decode_line(s,l)
l.append(1.)
X = np.array(l)
s = (f.readline()).strip()
cols = []
decode_line(s,cols,int)
if (numcam == None):
pts3d.append(X)
ptscol.append(np.array(cols))
f.readline()
else:
keys = []
s = (f.readline()).strip()
decode_line(s,keys)
n = int(keys[0])
i = 1
for j in xrange(0,n):
if(int(keys[i]) != numcam):
i += 4
continue
rx = keys[i+2]
ry = keys[i+3]
i += 4
pts2d.append((rx,ry))
pts3d.append(X)
ptscol.append(np.array(cols))
break
return(pts3d,pts2d,ptscol)
def get_ply_array(ptsfile):
"""
read the ply file and return the points coord as a 3xn array
"""
nbpts = 0
with open(ptsfile,'r') as f:
s = f.readline()
if s.strip() != 'ply':
raise Exception, "Not a ply file!"
while True:
s = f.readline().strip()
l = s.split()
if (len(l) == 3 and l[0] == 'element' and l[1] == 'vertex'):
nbpts = int(l[2])
continue
if(s.strip() == 'end_header'):
break
if (s == ''):
break
# start with points
kk = 0
pts3d = np.empty((3,nbpts),dtype=np.float,order="F")
while True:
s = (f.readline()).strip()
if (s == ''):
break
l = s.split()
n = len(l)
if(n < 3):
continue
ln = [float(l[i]) for i in range(0,n)]
pts3d[0,kk] = ln[0]
pts3d[1,kk] = ln[1]
pts3d[2,kk] = ln[2]
kk += 1
return pts3d
def get_ply_points(ptsfile,return_normals = False):
"""
read the ply file and return the lists of points and colors
"""
pts3d = []
ptscol = []
ptsnorm = []
with open(ptsfile,'r') as f:
s = f.readline()
if s.strip() != 'ply':
raise Exception, "Not a ply file!"
while True:
s = f.readline()
if(s.strip() == 'end_header'):
break
if (s == ''):
break
# start with points
while True:
s = (f.readline()).strip()
if (s == ''):
break
l = s.split()
n = len(l)
if(n < 3):
continue
ln = [float(l[i]) for i in range(0,n)]
pts3d.append(np.array([ln[0],ln[1],ln[2],1.]))
if (n > 3):
ptscol.append(np.array([ln[n-3],ln[n-2],ln[n-1]]))
if (n > 6 and return_normals):
ptsnorm.append(np.array([ln[3],ln[4],ln[5]]))
if return_normals:
return(pts3d,ptscol,ptsnorm)
else:
return(pts3d,ptscol)
def projection(matrx,pts3d):
"""
returns the list of projections of <pts3d> points (origin at the image center).
<matrx> is the projection matrix of camera and <size> the image width and height
"""
ptsxy = []
n = len(pts3d)
## print "MATR %s" %str(matrx)
for i in xrange(0,n):
X = pts3d[i]
Y = np.dot(matrx,X)
x = int(0.5 + Y[0] / Y[2])
y = int(0.5 + Y[1] / Y[2])
ptsxy.append((x,y))
return(ptsxy)
color = np.array([0,255,0])
color2 = np.array([255,0,0])
color3 = np.array([255,255,0])
def draw_projection(ptsxy,refpts,ptscol,obuf,size,wrect,cross = False):
"""
input : 2d projections list (ptsxy), original 2d points (refpts)
colors of points (ptscol), image buffer (obuf), image size
drawing options (wrect,cross)
Points are in image coordinates (0,0 = top left corner)
writes 2d points (ptsxy) in the image buffer <obuf>;
if wrect is None : a litle green square (cross = False) or
cross (cross = True) is drawn centered on each point
and if refpts is non empty, a red square or croos
is drawn on these points
If refpts[i] == ptsxy[i] : draw in yellow
if wrect is given : at each point, fill a square of (2*wrect +1) size with the point color
"""
(nx,ny) = size
## nx2 = 0.5 + (float(nx) / 2)
## ny2 = .5 + (float(ny) / 2)
n2d = len(refpts)
ncol = len(ptscol)
n = len(ptsxy)
for i in xrange(0,n):
(x,y) = ptsxy[i]
if(wrect != None):
draw_color_rect(obuf,x,y,size,wrect,ptscol[i])
else:
draw_point(obuf,x,y,size,color)
if n2d > 0:
(rx,ry) = refpts[i]
## rx = int(rx + nx2)
## ry = ny - int(ny2 + ry)
#print "XXX %d %d (%d %d)" %(x,y,rx,ry)
if (rx == x and ry == y):
col2 = color3
else:
col2 = color2
draw_point(obuf,rx,ry,size,col2,cross)
def calc_camparams(m,tzsign,verb=False):
"""
calculate intrinsics and extrinsics parameter of camera from 3x4 projection matrix m
NB : tzsign is ignored and will be removed in a next release
"""
a1 = m[0,0:3]
a2 = m[1,0:3]
a3 = m[2,0:3]
b = np.array([[m[0,3]],[m[1,3]],[m[2,3]]])
eps = 1
rho=eps / np.linalg.norm(a3)
r3 = rho * a3
x0 = rho * rho * np.dot(a1.T, a3)
y0 = rho * rho * np.dot(a2.T,a3)
b1 = np.cross(a1,a3)
b2 = np.cross(a2,a3);
theta = np.arccos(- np.dot(b1.T,b2) / (np.linalg.norm(b1)*np.linalg.norm(b2)))
# The magnifications are assumed to be positive..
alpha = rho * rho * np.linalg.norm(b1) * np.sin(theta)
beta = rho * rho * np.linalg.norm(b2) * np.sin(theta)
b23 = np.cross(a2,a3)
r1 = (1. / np.linalg.norm(b23)) * b23
r2 = np.cross(r3,r1)
K = np.array([[alpha, -alpha * np.cos(theta) / np.sin(theta), x0],
[ 0, beta/np.sin(theta), y0], [0, 0, 1]])
t = rho * np.linalg.solve(K,b)
# The sign of the solution is unknow : the last element in
# original and recalculated projection matrices must be the same
R = np.array([r1.T, r2.T, r3.T])
M = m
M2 = np.dot(K,np.concatenate((R,t),1))
tzsign = M[0,0] * M2[0,0] * M[2,3] * M2[2,3]
if tzsign < 0:
r3 = -r3
r2 = -r2
t = -t
R = np.array([r1.T, r2.T, r3.T])
M2 = np.dot(K,np.concatenate((R,t),1))
rho =M[0,0] / M2[0,0]
M2 = rho * M2
intrins = np.array([alpha,beta,180 * theta / np.pi])
if verb:
print "\nrho %f\nM= %s\nM2= %s" %(rho,str(M),str(M2))
print "R= %s\nt= %s\nintrinsic= %s" %(str(R),str(t),str(intrins))
print "x0,y0 %s %s" %(x0,y0)
X = np.array([[0.,0.,0.,1.],[t[0,0],t[1,0],-1.,1.]])
pts = projection(m,X)
pts2 = projection(M2,X)
(x,y) = pts[0];(x1,y1) = pts2[0]
print "Proj de 0 : %.3f %.3f, %.3f %.3f" %(x,y,x1,y1)
(x,y) = pts[1];(x1,y1) = pts2[1]
print "Proj de C : %.3f %.3f, %.3f %.3f\n" %(x,y,x1,y1)
return (K,R,t,M2)
def calc_transform(pts3d1,pts3d2,cmn_pts):
"""
renvoie la matrice de transformation pour passer du repere 1 au repere 2
input : pts3d1 pts3d2, liste d'arrays de dim 4
cmn_pts : liste de couples d'indices dans pts3d1 pts3d2
"""
nb = len(cmn_pts)
if (nb < 6):
print "Not enough (%d) common points!" %nb
return None
# if(nb > 25):
# nb = 25
print "-- %d common projections" %nb
A = np.zeros((3*nb,12))
zer = np.zeros((4,))
b = np.zeros((3*nb,))
for i in xrange(0,nb):
(i1,i2) = cmn_pts[i]
A[3 * i,:] = np.concatenate((pts3d1[i1],zer,zer))
A[3 * i + 1,:] = np.concatenate((zer,pts3d1[i1],zer))
A[3 * i + 2,:] = np.concatenate((zer,zer,pts3d1[i1]))
b[3*i:3*(i+1)] = pts3d2[i2][0:3]
x = np.linalg.lstsq(A,b)[0]
x = np.concatenate((x,np.array([0.,0.,0.,1.])))
matr = x.reshape((4,4))
## print "M= %s" %str(matr)
emoy = 0.
emax = 0.
for i in xrange(0,nb):
(i1,i2) = cmn_pts[i]
p1 = pts3d1[i1]
p2 = pts3d2[i2]
y = np.dot(matr,p1)
e = np.linalg.norm(y - p2)
if e > emax:
emax = e
emoy += e
emoy /= nb
print "ERR max %f, moy %f" %(emax,emoy)
return matr
def print_matrix(M,file= None):
"""
print matrix m*n as m lines of n floats
"""
(m,n) = M.shape
for i in xrange(0,m):
l = map(lambda x : str(x),M[i,:])
s = ' '.join(l)
if file == None:
print s
else:
print >>file, s
def mk_KRt(mat,focal,w,h):
"""
makes matrix in pmvs2 format from bundler camera data
"""
K = np.array([[-focal,0, 0.5 * w - 0.5],
[0,focal,0.5 * h - 0.5],
[0,0,1]])
M = np.dot(K,mat)
return ( - np.concatenate((M,np.array([0,0,0,1],ndmin=2)),0))
def read_metis_graph(file):
"""
reads the metis graph (1st line = nb-img 2*nb-edges,
other lines : neighbours of each image
Output : list of lists (list[i] = neighbours of i)
"""
graph = []
try:
f = open(file,'r')
s = f.readline().strip()
l = s.split()
with_weights = False
if len(l) == 3:
with_weights = True
while True:
s = f.readline()
if s == '':
break
l = []
if with_weights:
x = s.strip().split()
for i in xrange(0,len(x),2):
l.append(int(x[i]) - 1)
else:
l = map(lambda x : int(x) - 1,s.strip().split())
graph.append(l)
f.close()
except Exception:
raise MyException("%s open error" %file)
return graph
def read_adj_matrix(file):
"""
reads the adjacency matrix (values = nb of matched points)
Output : list of lists (list[i] = list of (j, nb-match) where j is a neighbour of i)
list[i] is ordered according to nb-match
"""
adj = []
try:
f = open(file,'r')
lines = f.readlines()
f.close()
except Exception:
raise MyException("%s open error" %file)
for s in lines:
l = []
decode_line(s.strip(),l,func = int)
neighbours = []
for i in xrange(0,len(l)):
if l[i] != 0:
neighbours.append((i,l[i]))
neighbours = sorted(neighbours,cmp = lambda (i1,nb1),(i2,nb2) : nb1 - nb2)
adj.append(neighbours)
return adj
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220,
220,
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1441,
9224,
198
] | 1.830541 | 9,371 |
# Managed by bumpversion
__version__ = "1.33.0"
| [
2,
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9641,
834,
796,
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13,
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1,
198
] | 2.526316 | 19 |
import numpy as np
inputs = [[1.0, 2.0, 3.0, 2.5],
[2.0, 5.0, -1.0, 2.0],
[-1.5, 2.7, 3.3, -0.8]]
weights = [[0.2, 0.8, -0.5, 1.0],
[0.5, -0.91, 0.26, -0.5],
[-0.26, -0.27, 0.17, 0.87]]
biases = [2.0, 3.0, 0.5]
outputs = np.dot(inputs, np.array(weights).T) + biases
print(outputs)
# https://nnfs.io/crq
# https://nnfs.io/gjw
# https://nnfs.io/ch2
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] | 1.604082 | 245 |
from datetime import datetime, timedelta
import os
import tempfile
import torch
import logging
log = logging.getLogger(__name__)
__all__ = ["FlexibleModelCheckpoint"]
"""
Copied from https://github.com/pytorch/ignite/blob/v0.2.1/ignite/handlers/checkpoint.py
due to the change in ignite v0.3.0
"""
class ModelCheckpoint(object):
""" ModelCheckpoint handler can be used to periodically save objects to disk.
This handler expects two arguments:
- an :class:`~ignite.engine.Engine` object
- a `dict` mapping names (`str`) to objects that should be saved to disk.
See Notes and Examples for further details.
Args:
dirname (str):
Directory path where objects will be saved.
filename_prefix (str):
Prefix for the filenames to which objects will be saved. See Notes
for more details.
save_interval (int, optional):
if not None, objects will be saved to disk every `save_interval` calls to the handler.
Exactly one of (`save_interval`, `score_function`) arguments must be provided.
score_function (callable, optional):
if not None, it should be a function taking a single argument,
an :class:`~ignite.engine.Engine` object,
and return a score (`float`). Objects with highest scores will be retained.
Exactly one of (`save_interval`, `score_function`) arguments must be provided.
score_name (str, optional):
if `score_function` not None, it is possible to store its absolute value using `score_name`. See Notes for
more details.
n_saved (int, optional):
Number of objects that should be kept on disk. Older files will be removed.
atomic (bool, optional):
If True, objects are serialized to a temporary file,
and then moved to final destination, so that files are
guaranteed to not be damaged (for example if exception occures during saving).
require_empty (bool, optional):
If True, will raise exception if there are any files starting with `filename_prefix`
in the directory 'dirname'.
create_dir (bool, optional):
If True, will create directory 'dirname' if it doesnt exist.
save_as_state_dict (bool, optional):
If True, will save only the `state_dict` of the objects specified, otherwise the whole object will be saved.
Note:
This handler expects two arguments: an :class:`~ignite.engine.Engine` object and a `dict`
mapping names to objects that should be saved.
These names are used to specify filenames for saved objects.
Each filename has the following structure:
`{filename_prefix}_{name}_{step_number}.pth`.
Here, `filename_prefix` is the argument passed to the constructor,
`name` is the key in the aforementioned `dict`, and `step_number`
is incremented by `1` with every call to the handler.
If `score_function` is provided, user can store its absolute value using `score_name` in the filename.
Each filename can have the following structure:
`{filename_prefix}_{name}_{step_number}_{score_name}={abs(score_function_result)}.pth`.
For example, `score_name="val_loss"` and `score_function` that returns `-loss` (as objects with highest scores
will be retained), then saved models filenames will be `model_resnet_10_val_loss=0.1234.pth`.
Examples:
>>> import os
>>> from ignite.engine import Engine, Events
>>> from ignite.handlers import ModelCheckpoint
>>> from torch import nn
>>> trainer = Engine(lambda batch: None)
>>> handler = ModelCheckpoint('/tmp/models', 'myprefix', save_interval=2, n_saved=2, create_dir=True)
>>> model = nn.Linear(3, 3)
>>> trainer.add_event_handler(Events.EPOCH_COMPLETED, handler, {'mymodel': model})
>>> trainer.run([0], max_epochs=6)
>>> os.listdir('/tmp/models')
['myprefix_mymodel_4.pth', 'myprefix_mymodel_6.pth']
"""
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1,
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28,
15,
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13,
79,
400,
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198,
220,
220,
220,
21066,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13163,
1330,
28686,
198,
220,
220,
220,
220,
220,
220,
220,
13163,
422,
44794,
13,
18392,
1330,
7117,
11,
18715,
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220,
220,
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13163,
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25,
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220,
220,
220,
220,
13163,
21360,
796,
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9787,
4122,
10786,
14,
22065,
14,
27530,
3256,
705,
1820,
40290,
3256,
3613,
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28,
17,
11,
299,
62,
82,
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28,
17,
11,
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62,
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28,
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8,
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220,
220,
220,
220,
220,
220,
220,
13163,
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796,
299,
77,
13,
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7,
18,
11,
513,
8,
198,
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220,
220,
220,
220,
220,
220,
13163,
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7,
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13,
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11,
21360,
11,
1391,
6,
1820,
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2746,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
13163,
21997,
13,
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15,
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62,
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5374,
82,
28,
21,
8,
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220,
220,
220,
220,
220,
220,
13163,
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14,
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14,
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62,
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62,
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21,
13,
79,
400,
20520,
198,
220,
220,
220,
37227,
628,
198
] | 2.690306 | 1,537 |
lista = [1, 2, 3]
try:
numero = int(input(f'Digite um número entre 0 e {len(lista)-1}: '))
print(lista[numero])
except ValueError:
print('Não foi digitado um número')
except IndexError:
print('O número digitado está fora da faixa aceita')
#https://pt.stackoverflow.com/q/451936/101
| [
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] | 2.238806 | 134 |
from urllib import response
from django.http import HttpResponse,HttpResponseForbidden, HttpResponseRedirect
from teproj.models import TestModel
from django.urls import reverse
from django.conf import settings
from django.core.cache import cache
from django.contrib.auth.models import Group
| [
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220,
220,
220,
220,
220,
220,
220
] | 3.301075 | 93 |
#!/usr/bin/env python3
#
# Licensed under BSD 2-Clause License.
#
# This is a really crude script. This spits out shell-escaped wget
# commands to download the images of the chapters.
#
# Each image is downloaded into "VOLUME_CHAPTER/XXX.png" where VOLUME
# and CHAPTER are the volume and chapter names respectively. If DRY
# environmental variable is not empty, then this script does not
# create the needed directories beforehand.
#
# Chapter or series URL may be given as arguments to the script.
#
# To read the chapter in zathura(1), use the following command
#
# zip CHAPTER.zip CHAPTER_IMAGES/*
import json
from os import mkdir, getenv
from os.path import splitext, basename
from os.path import exists as file_exists_p
from shlex import quote as shell_quote
from sys import argv
import re
import urllib.request as req
import bs4
DYNASTY_IMAGE_RE = re.compile(r"//<!\[CDATA\[")
BATOTO_IMAGE_RE_1 = re.compile(r"(?:const|var) images = \[")
BATOTO_IMAGE_RE_2 = re.compile(r"(?:const|var) imgHttpLis = \[")
JS_CTXT = None
UA = { "User-Agent": "Chrome/96.0.4664.110" }
MKDIRP = not getenv("DRY")
def request(url):
"""Request URL."""
return req.urlopen(req.Request(url, headers=UA))
def dynasty_get_chapter_list(url):
"""Get the list of chapters in URL.
Returned value is a dictionary { VOLUME: CHAPTERS } where VOLUME
is the name of the volume and CHAPTERS is a tuple (NAME, URL)
where NAME is the name of the chapter and URL is the link to the
chapter. If the manga is not divided by volumes, then VOLUME is
an empty string.
"""
soup = bs4.BeautifulSoup(request(url), "html.parser")
ret = {}
vol = ""
chs = []
chp = soup.find("dl", class_="chapter-list")
for i in chp:
if not isinstance(i, bs4.element.Tag):
continue
if i.name == "dt":
if chs: ret[vol] = chs
vol = i.string
chs = []
elif i.name == "dd":
chs.append((i.a.string, "https://dynasty-scans.com" + i.a["href"]))
if chs:
ret[vol] = chs
return ret
def dynasty_get_images(ch):
"""Get list of image URLs for the chapter with URL CH."""
soup = bs4.BeautifulSoup(request(ch), "html.parser")
if r := re.search(r"var pages = (\[.*\])", soup.find("script", string=DYNASTY_IMAGE_RE).string):
return [ "https://dynasty-scans.com" + i["image"]
for i in json.loads(r.group(1)) ]
return []
def batoto_get_chapter_list(url):
"""Get the list of chapters in URL.
Returned value is a list of (NAME, URL) where NAME is the name of
chapter and URL is the link to the chapter.
"""
chs = []
# User-Agent is need to be set otherwise cloudfare pops up.
soup = bs4.BeautifulSoup(request(url), "html.parser")
for i in soup.find_all("a", class_="visited chapt"):
# The name of the chapter is surrounded by newlines for some
# reason.
chs.append((i.text.strip(), "https://bato.to" + i["href"]))
chs.reverse()
return chs
def batoto_get_images(ch):
"""Get list of image URLs for the chapter CH.
I came to know of duktape thanks to the Tachiyomi bato.to
extension.
"""
def js_eval(string):
"""Evalulate JavaScript code in the string STRING."""
import pyduktape
global JS_CTXT
if not JS_CTXT:
JS_CTXT = pyduktape.DuktapeContext()
if not file_exists_p("./crypto.js"):
# The same URL tachiyomi uses.
cryptojs = request("https://cdnjs.cloudflare.com/ajax/libs/crypto-js/4.0.0/crypto-js.min.js")
with open("./crypto.js", "w") as f:
f.write(cryptojs.read().decode("utf-8"))
JS_CTXT.eval_js_file("./crypto.js")
return JS_CTXT.eval_js(string)
soup = bs4.BeautifulSoup(request(ch), "html.parser")
if js := soup.find("script", text=BATOTO_IMAGE_RE_1):
# Most of this magic can be figured out by reading the JavaScript
# sources in a chapter page. Alternatively, refer to
# https://github.com/tachiyomiorg/tachiyomi-extensions/blob/master/src/all/batoto/src/eu/kanade/tachiyomi/extension/all/batoto/BatoTo.kt
js = js.string
server = re.search(r"(?:const|var) server = ([^;]+);", js).group(1)
batojs = re.search(r"(?:const|var) batojs = ([^;]+);", js).group(1)
base = js_eval(f"CryptoJS.AES.decrypt({server} ,{batojs}).toString(CryptoJS.enc.Utf8);").strip("\"")
return [ base + i for i in json.loads(re.search(r"(?:const|var) images = (\[.*\]);", js).group(1)) ]
elif js := soup.find("script", text=BATOTO_IMAGE_RE_2):
# Again, thanks to tachiyomi for showing the light. It is
# also easy enough to figure out if you read the JS files.
js = js.string
img = re.search(r"(?:const|var) imgHttpLis = ([^;]+);", js).group(1)
img = json.loads(img)
batoword = re.search(r"(?:const|var) batoWord = ([^;]+);", js).group(1)
batopass = re.search(r"(?:const|var) batoPass = ([^;]+);", js).group(1)
passwd = json.loads(js_eval(f"CryptoJS.AES.decrypt({batoword}, {batopass}).toString(CryptoJS.enc.Utf8);"))
if len(passwd) != len(img):
return [ ]
return [ i + "?" + passwd[n] for n, i in enumerate(img) ]
return []
if __name__ == "__main__":
for i in argv[1:]:
do(i)
| [
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7,
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198,
220,
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220,
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220,
220,
220,
220,
220,
220,
1441,
685,
2361,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
1312,
1343,
366,
1701,
1343,
1208,
16993,
58,
77,
60,
329,
299,
11,
1312,
287,
27056,
378,
7,
9600,
8,
2361,
628,
220,
220,
220,
1441,
17635,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
329,
1312,
287,
1822,
85,
58,
16,
25,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
466,
7,
72,
8,
198
] | 2.309022 | 2,372 |
from dataclasses import dataclass
from bindings.gmd.abstract_crstype import AbstractCoordinateOperationType
__NAMESPACE__ = "http://www.opengis.net/gml"
@dataclass
| [
6738,
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] | 2.929825 | 57 |
from .Bassin import Bassin | [
6738,
764,
33,
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1330,
19829,
259
] | 3.714286 | 7 |
# -*- coding: utf-8 -*-
# Global variables
_HEADER = {"Content-Type": "application/json"}
_PAYLOAD = {"stmt": None}
| [
2,
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] | 2.543478 | 46 |
from django.contrib.auth.models import User
from django.shortcuts import render, redirect
from zero_ilumi_agenda_core.models import Evento_Agendado
from django.contrib.auth.decorators import login_required
from django.contrib.auth import authenticate, login, logout
from django.contrib import messages
from datetime import datetime, timedelta
from django.http.response import Http404, JsonResponse
# Create your views here.
# def index(request):
# return redirect('/agenda/')
@login_required(login_url='/login/')
@login_required(login_url='/login/')
@login_required(login_url='/login/')
@login_required(login_url='/login/')
@login_required(login_url='/login/')
| [
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6371,
11639,
14,
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14,
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628,
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] | 3.086364 | 220 |
"""
Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution.
SPDX-License-Identifier: Apache-2.0 OR MIT
"""
"""
C13767841 - All Gradient Modifier nodes can be added to a graph
C18055051 - All Gradient Modifier nodes can be removed from a graph
"""
import os
import pytest
# Bail on the test if ly_test_tools doesn't exist.
pytest.importorskip('ly_test_tools')
import ly_test_tools.environment.file_system as file_system
import editor_python_test_tools.hydra_test_utils as hydra
test_directory = os.path.join(os.path.dirname(__file__), 'EditorScripts')
@pytest.mark.parametrize('project', ['AutomatedTesting'])
@pytest.mark.parametrize('level', ['tmp_level'])
@pytest.mark.usefixtures("automatic_process_killer")
@pytest.mark.parametrize("launcher_platform", ['windows_editor'])
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31,
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69,
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2044,
62,
24254,
1600,
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62,
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6,
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] | 3.145907 | 281 |
from setuptools import setup
from torch.utils.cpp_extension import CUDAExtension, BuildExtension
from pathlib import Path
# Usage:
# python setup.py install (or python setup.py bdist_wheel)
# NB: Windows: run from VS2017 x64 Native Tool Command Prompt
rootdir = (Path(__file__).parent / '..' / 'op').resolve()
setup(
name='upfirdn2d',
ext_modules=[
CUDAExtension('upfirdn2d_op',
[str(rootdir / 'upfirdn2d.cpp'), str(rootdir / 'upfirdn2d_kernel.cu')],
)
],
cmdclass={
'build_ext': BuildExtension
}
)
setup(
name='fused',
ext_modules=[
CUDAExtension('fused',
[str(rootdir / 'fused_bias_act.cpp'), str(rootdir / 'fused_bias_act_kernel.cu')],
)
],
cmdclass={
'build_ext': BuildExtension
}
) | [
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62,
2302,
10354,
10934,
11627,
3004,
198,
220,
220,
220,
1782,
198,
8
] | 2.227778 | 360 |
import requests
from bs4 import BeautifulSoup
import sys
import datetime
mainPageUrl = 'https://pcgames-download.com/'
mainFilePath = './loading/mainPage.html'
pagePath = './loading/'
def loadGameData():
"Loads computer games data"
print ('Loading number of pages')
response = requests.get(mainPageUrl)
with open(mainFilePath, 'wb') as f:
f.write(response.content)
soup = BeautifulSoup(open(mainFilePath, encoding="utf8"), 'html.parser')
for lastPage in soup.find_all(class_='last'):
lastPageText = lastPage.get('href').strip()
lastPageNumber = getLastPageNumber(lastPageText)
print ('Last available page: ' + lastPageText)
continue
data = []
for currentPageNumber in range(1, lastPageNumber + 1):
print('Loading page ' + str(currentPageNumber))
titleTexts, titleLinks = checkLoadPageData(currentPageNumber)
for index in range(len(titleTexts)):
data.append(str(titleTexts[index]) + '; ' + str(titleLinks[index]) + '\n')
fileName = getCurrentDateTimeFormatted() + '.csv'
print('Writing data to csv file: ' + fileName)
with open('./savedData/' + fileName, 'w') as f:
f.write(''.join(data))
print ("Done")
def getLastPageNumber(lastPage):
"Gets the last page number of the computer game website"
#https://pcgames-download.com/page/271/ --> 271
lastPage = lastPage.replace(mainPageUrl + 'page/', "").replace("/", "")
return int(lastPage)
def checkLoadPageData(currentPage):
"Loads the page data for the given page number"
if currentPage == 1:
print (mainPageUrl)
return loadPageData(mainPageUrl, currentPage)
else:
pageUrl = mainPageUrl + 'page/' + str(currentPage)
print (pageUrl)
return loadPageData(pageUrl, currentPage)
def loadPageData(pageUrl, currentPage):
"Loads the page data for the given page url"
response = requests.get(pageUrl)
pageFile = pagePath + str(currentPage) + '.html'
with open(pageFile, 'wb') as f:
f.write(response.content)
soup = BeautifulSoup(open(pageFile, encoding="utf8"), 'html.parser')
titleTexts = []
titleLinks = []
for posts in soup.find_all(class_='post-title'):
for post in posts:
titleTexts.append(post.get('title'))
titleLinks.append(post.get('href'))
return (titleTexts, titleLinks)
def getCurrentDateTimeFormatted():
"Returns a string for the json output file with the current date and time"
return datetime.datetime.now().isoformat().replace(":", "-").replace(".", "-")
loadGameData() | [
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] | 2.918689 | 824 |
import sys
import os
from scipy import stats
import tenseal as ts
import numpy as np
from scipy.stats import t
sys.path.append(os.path.abspath('../../tensealstat'))
from tensealstat.tools_context import ToolsContext as tc
from tensealstat.algebra.algebra_numpy import AlgebraNumpy
from tensealstat.algebra.algebra_tenseal import AlgebraTenseal
from tensealstat.statistic.student_t_repeated_measures import StudentTRepeatedMeasures
statistic_generator = StudentTRepeatedMeasures()
#
# This test follows Larsen Marc 4Th edition P790
#
# 1 done by the key holder
context = tc.get_context_default()
algebra_tenseal = AlgebraTenseal(context)
algebra_numpy = AlgebraNumpy()
# 2 done by the data holders
sample_0 = np.array([14.6, 17.3, 10.9, 12.8, 16.6, 12.2, 11.2, 15.4, 14.8, 16.2])
sample_1 = np.array([13.8, 15.4, 11.3, 11.6, 16.4, 12.6, 11.8, 15.0, 14.4, 15.0])
list_sample = [sample_0, sample_1]
list_sample_encrypted = [algebra_tenseal.encrypt_vector(sample) for sample in list_sample]
# 3 done by the agregator
statistic_encrypted = statistic_generator.encrypt_statistic(algebra_tenseal, list_sample_encrypted)
# 4 done by the key holder
t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_tenseal, statistic_encrypted)
p_value = t.cdf(t_statistic, degrees_of_freedom)
# p value should be between about 0.94 and 0.95
print('via tensealstat')
print('t_statistic: ' + str(t_statistic))
print('p_value: ' + str(p_value))
# Test version
statistic_encrypted = statistic_generator.encrypt_statistic(algebra_numpy, list_sample)
t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_numpy, statistic_encrypted)
p_value = t.cdf(t_statistic, degrees_of_freedom)
print('')
print('via tensealstattest')
print('t_statistic: ' + str(t_statistic))
print('p_value: ' + str(p_value))
# Scipy version
t_statistic, p_value = stats.ttest_rel(sample_0 ,sample_1)
print('')
print('via scipy')
print('t_statistic: ' + str(t_statistic))
print('p_value: ' + str(1 - (p_value / 2)))
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362,
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198
] | 2.727763 | 742 |
import os
from django.db import models
from django.contrib.auth.models import User
from easy_thumbnails.fields import ThumbnailerImageField
import uuid
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"""
@author: magician
@file: confirm_subclass.py
@date: 2020/1/14
"""
class Meta(type):
"""
Meta
"""
class MyClass(object, metaclass=Meta):
"""
MyClass
"""
stuff = 3
class ValidatePolygon(type):
"""
ValidatePolygon
"""
def __new__(meta, name, bases, class_dict):
"""
Don't validate the abstract Polygon class
@param name:
@param bases:
@param class_dict:
"""
if bases != (object,):
if class_dict['sides'] < 3:
raise ValueError('Polygons need 3+ sides')
return type.__new__(meta, name, bases, class_dict)
class Polygon(object, metaclass=ValidatePolygon):
"""
Polygon
"""
# Specified by subclasses
sides = None
@classmethod
class Triangle(Polygon):
"""
Triangle
"""
sides = 3
if __name__ == '__main__':
print('Before Class')
try:
class Line(Polygon):
"""
Line
"""
print('Before sides')
sides = 1
print('After sides')
except Exception as e:
print(e)
print('After Class')
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] | 2.131627 | 547 |
import FWCore.ParameterSet.Config as cms
XMLIdealGeometryESSource = cms.ESSource("XMLIdealGeometryESSource",
geomXMLFiles = cms.vstring(
'Geometry/CMSCommonData/data/materials/2021/v3/materials.xml',
'Geometry/CMSCommonData/data/rotations.xml',
'Geometry/CMSCommonData/data/extend/v3/cmsextent.xml',
'Geometry/CMSCommonData/data/cavernData/2021/v1/cavernData.xml',
'Geometry/CMSCommonData/data/cms/2021/v3/cms.xml',
'Geometry/CMSCommonData/data/cmsMother.xml',
'Geometry/CMSCommonData/data/eta3/etaMax.xml',
'Geometry/TrackerCommonData/data/pixfwdCommon.xml',
'Geometry/ForwardCommonData/data/pixfwd/2021/v1/pixfwd.xml',
'Geometry/HcalCommonData/data/average/hcalforwardmaterial.xml',
'Geometry/ForwardCommonData/data/forward/2021/v1/forward.xml',
'Geometry/ForwardCommonData/data/totemt2/2021/v1/totemt2.xml',
'Geometry/ForwardCommonData/data/forwardshield/2021/v1/forwardshield.xml',
'Geometry/ForwardCommonData/data/bhm.xml',
'Geometry/ForwardCommonData/data/pltbcm/2021/v1/pltbcm.xml',
'Geometry/ForwardCommonData/data/bcm1f/2021/v1/bcm1f.xml',
'Geometry/ForwardCommonData/data/plt/2021/v1/plt.xml',
'Geometry/ForwardSimData/data/bcm1fsens.xml',
'Geometry/ForwardCommonData/data/zdcmaterials/2021/v1/zdcmaterials.xml',
'Geometry/ForwardCommonData/data/lumimaterials.xml',
'Geometry/ForwardCommonData/data/zdcrotations.xml',
'Geometry/ForwardCommonData/data/lumirotations.xml',
'Geometry/ForwardCommonData/data/zdc/2021/v1/zdc.xml',
'Geometry/ForwardCommonData/data/zdclumi/2021/v2/zdclumi.xml',
'Geometry/ForwardCommonData/data/cmszdc.xml',
'Geometry/ForwardSimData/data/pltsens.xml',
'Geometry/ForwardSimData/data/bcm1fsens.xml',
'Geometry/ForwardSimData/data/totemsensT2/2021/totemsensT2.xml',
'Geometry/ForwardSimData/data/zdcsens.xml',
'Geometry/ForwardSimData/data/bhmProdCuts/2021/v1/bhmProdCuts.xml',
'Geometry/ForwardSimData/data/zdcProdCuts/2021/v2/zdcProdCuts.xml',
'Geometry/ForwardSimData/data/ForwardShieldProdCuts.xml',
'Geometry/CMSCommonData/data/FieldParameters.xml',
),
rootNodeName = cms.string('cms:OCMS')
)
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10082,
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6601,
14,
7890,
14,
15878,
48944,
13,
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3256,
198,
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220,
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10612,
198,
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6808,
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5376,
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8841,
10786,
46406,
25,
4503,
5653,
11537,
198,
8,
198
] | 2.137963 | 1,080 |
"""
MIT License
Copyright (c) 2021 TheHamkerCat
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
"""
from wbb import db
from typing import Dict, List, Union
notesdb = db.notes
filtersdb = db.filters
warnsdb = db.warns
karmadb = db.karma
chatsdb = db.chats
gbansdb = db.gban
coupledb = db.couple
captchadb = db.captcha
antiservicedb = db.antiservice
pmpermitdb = db.pmpermit
""" Notes functions """
""" Filters funcions """
""" Warn functions """
""" Karma functions """
""" Chats log functions """
""" Gban functions """
# Couple Chooser
# Captcha
"""Anti Service System"""
""" PM PERMIT """
| [
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2,
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198,
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3122,
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628,
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] | 3.398747 | 479 |
# -*- coding: utf-8 -*-
"""
@author: nicolas.posocco
"""
from sklearn.calibration import calibration_curve
import numpy as np
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] | 2.666667 | 48 |
# coding: utf-8
#
# File name "sac" means "SHCNE_ASSOCCHANGED" used at 4xc5k9H.
#
from __future__ import absolute_import
import sys
#/
if __name__ == '__main__':
sys.exit(main())
| [
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] | 2.367089 | 79 |
import Grabber
gauge_grabber = Grabber.grabb_serial_values()
gauge_grabber.init()
gauge_grabber.grabb(10)
gauge_grabber.convert_grabbed_to_numpy()
gauge_grabber.plot_grabbed_data()
gauge_grabber.clean_numpy_dict()
gauge_grabber.save_cleaned_dict_numpy('test_saving')
gauge_grabber.save_cleaned_dict_numpy_csv('test_saving')
| [
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] | 2.295775 | 142 |
# Copyright (c) 2014, Tomohiro Kusumi
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
# ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
from . import filebytes
from . import ncurses
from . import setting
from . import terminal
from . import util
Error = Exception
_count = 0
A_NONE = 0
A_BOLD = 1
A_REVERSE = 2
A_STANDOUT = 4
A_UNDERLINE = 8
A_COLOR_FB = 0
A_COLOR_CURRENT = 0
A_COLOR_ZERO = 0
A_COLOR_FF = 0
A_COLOR_PRINT = 0
A_COLOR_DEFAULT = 0
A_COLOR_VISUAL = 0
A_COLOR_OFFSET = 0
BUTTON1_CLICKED = 0
BUTTON1_PRESSED = 0
BUTTON1_RELEASED = 0
BUTTON1_DOUBLE_CLICKED = 0
BUTTON1_TRIPLE_CLICKED = 0
BUTTON2_CLICKED = 0
BUTTON2_PRESSED = 0
BUTTON2_RELEASED = 0
BUTTON2_DOUBLE_CLICKED = 0
BUTTON2_TRIPLE_CLICKED = 0
BUTTON3_CLICKED = 0
BUTTON3_PRESSED = 0
BUTTON3_RELEASED = 0
BUTTON3_DOUBLE_CLICKED = 0
BUTTON3_TRIPLE_CLICKED = 0
BUTTON4_CLICKED = 0
BUTTON4_PRESSED = 0
BUTTON4_RELEASED = 0
BUTTON4_DOUBLE_CLICKED = 0
BUTTON4_TRIPLE_CLICKED = 0
REPORT_MOUSE_POSITION = 0
# APIs must be compatible with
# https://docs.python.org/3/library/curses.html
| [
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220,
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220,
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] | 2.562766 | 940 |
import sublime, sublime_plugin
import sys
import re
import os | [
11748,
41674,
11,
41674,
62,
33803,
198,
198,
11748,
25064,
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] | 3.875 | 16 |
#!/usr/bin/env python3
import argparse
from glob import glob
from skimage import exposure
from PIL import Image
import colour
import numpy as np
import pandas as pd
import os
from colour_demosaicing import (
demosaicing_CFA_Bayer_bilinear,
demosaicing_CFA_Bayer_Malvar2004,
demosaicing_CFA_Bayer_Menon2007,
mosaicing_CFA_Bayer)
cctf_encoding = colour.cctf_encoding
parser = argparse.ArgumentParser(description='Process quality series of Permacam images and generate error measurements')
parser.add_argument('save_dir', help='Optional save detected images to file in dir')
args = parser.parse_args()
jpegs = glob(args.save_dir + '/image_mono*.jpeg')
raws = glob(args.save_dir + '/image_raw*.npy')
manifest_fname = args.save_dir + '/manifest.pkl'
data = None
if not os.path.isfile(manifest_fname) :
print('Generating')
data = {}
data['filename'] = []
data['id'] = []
data['quality'] = []
data['size'] = []
data['raw'] = []
data['time'] = []
data['image_array'] = []
d = None
fname = None
for f in jpegs:
data['filename'].append(f)
i = int(f.split('_')[-1].split('.')[0])
data['id'].append(i)
q = int(f.split('_')[2])
data['quality'].append(q)
data['size'].append(os.path.getsize(f))
data['raw'].append(0)
time_fname = args.save_dir + '/time_to_send_' + str(q) + '_' + str(i) + '.txt'
time_to_send = 0
with open(time_fname, 'r') as tf:
time_to_send = float(tf.read());
data['time'].append(time_to_send)
jpeg = Image.open(f)
d = np.array(jpeg.getdata()).reshape(jpeg.size[0], jpeg.size[1]) / 0xff
d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR'))
d = exposure.rescale_intensity(d, (0,1))
d = exposure.adjust_gamma(d, 1.5)
#d = (d * 255).astype(np.uint8)
fname = f.replace('mono', 'jpeg_demosaiced').replace('.jpeg', '.npy')
np.save(fname, d)
data['image_array'].append(fname)
result = Image.fromarray((d * 255).astype(np.uint8))
result.save(fname.replace('npy','jpeg'), format='JPEG')
for f in raws:
data['filename'].append(f)
i = int(f.split('_')[-1].split('.')[0])
data['id'].append(i)
data['quality'].append(100)
data['raw'].append(1)
data['size'].append(d.shape[0] * d.shape[1])
time_fname = args.save_dir + '/time_to_send_0_' + str(i) + '.txt'
time_to_send = 0
with open(time_fname, 'r') as tf:
time_to_send = float(tf.read());
data['time'].append(time_to_send)
d = np.load(f) / float(0xff)
d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR'))
d = exposure.rescale_intensity(d, (0,1))
d = exposure.adjust_gamma(d, 1.5)
#d = (d * 255).astype(np.uint8)
fname = f.replace('raw', 'demosaiced')
np.save(fname, d)
data['image_array'].append(fname)
result = Image.fromarray((d * 255).astype(np.uint8))
result.save(fname.replace('npy','jpeg'), format='JPEG')
data = pd.DataFrame(data)
qualities = set(np.unique(data['quality']).flatten())
for i in data['id']:
avail_qual = set(data[data['id'] == i]['quality'])
if (avail_qual != qualities):
data = data[data['id'] != i]
data.to_pickle(manifest_fname)
else:
data = pd.read_pickle(manifest_fname)
print(data)
print(len(np.unique(data['id'])))
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17816,
312,
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22305,
198
] | 2.135086 | 1,636 |
# Generated by Django 2.1.7 on 2020-10-22 12:55
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
| [
2,
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] | 3.065574 | 61 |
# coding=utf-8
# Copyright 2015 Brave Labs sp. z o.o.
# All rights reserved.
#
# This source code and all resulting intermediate files are CONFIDENTIAL and
# PROPRIETY TRADE SECRETS of Brave Labs sp. z o.o.
# Use is subject to license terms. See NOTICE file of this project for details.
import json
import logging
from smtplib import SMTPAuthenticationError, SMTPServerDisconnected
import html2text
from django.conf import settings
from django.core.mail import EmailMultiAlternatives
from django.core.mail import send_mail as django_send_mail
from django.template.exceptions import TemplateDoesNotExist
from django.template.loader import render_to_string
from sparkpost.exceptions import SparkPostAPIException
def send_mail(template_path, ctx, to):
"""Simplifies message rendering"""
ctx.setdefault('BASE_URL', settings.BASE_URL)
message = render_to_string(template_path + '.jinja2', ctx)
html_message = render_to_string(template_path + '.html', ctx)
subject, message = message.split("\n", 1)
if not isinstance(to, list):
to = [to]
django_send_mail(
subject=subject,
message=message,
html_message=html_message,
from_email=settings.DEFAULT_FROM_EMAIL,
recipient_list=to
)
def send_mail_template(template, ctx, subject, to=None, **kwargs):
"""Simplifies message rendering"""
ctx.setdefault('BASE_URL', settings.BASE_URL)
html_message = render_to_string(template, ctx)
try:
text_message = render_to_string(template.replace(".html", ".jinja2"), ctx)
except TemplateDoesNotExist:
text_message = html2text.html2text(html_message)
if not isinstance(to, list):
to = [to]
kwargs.setdefault('from_email', settings.DEFAULT_FROM_EMAIL)
kwargs.setdefault('reply_to', [settings.DEFAULT_REPLY_TO_EMAIL])
message = EmailMultiAlternatives(subject, body=text_message, to=to, **kwargs)
if html_message:
message.attach_alternative(html_message, 'text/html')
logging.debug("to: %s", to)
if 'unsubscribe' in ctx:
message.extra_headers['List-Unsubscribe'] = "<{}>".format(ctx['unsubscribe'])
message.extra_headers['X-MSYS-API'] = json.dumps({'options': {'transactional': True}})
try:
return message.send()
except SparkPostAPIException as ex:
if ex.status == 1902 or not settings.FAIL_ON_EMAIL_SUPPRESSION:
logging.error("Email suppression: %s", to, exc_info=ex)
else:
raise
except (SMTPServerDisconnected, SMTPAuthenticationError) as ex:
logging.error("", exc_info=ex)
# Retry once
return message.send()
| [
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] | 2.641791 | 1,005 |
import random
import matplotlib.pyplot as plt
from setting import *
from field import Field
from qvalue import Hunter
if __name__ == "__main__":
h0 = Hunter(0)
h1 = Hunter(1)
epi_itern_l = []
for i in range(EPISODE_N):
f = Field()
itern = 0
while True:
fin = qlearn_step(f, h0, h1)
itern += 1
if fin:
break
epi_itern_l.append(itern)
print(i, itern)
plt.plot(list(range(EPISODE_N)), epi_itern_l, linewidth=1)
plt.xlabel("Number of Trials")
plt.ylabel("Steps to Catch")
plt.savefig("figure")
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220,
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83,
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5647,
7203,
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198
] | 1.974522 | 314 |
import multiprocessing as mp
import time
import torch.distributed
from rlpyt.runners.minibatch_rl import MinibatchRl
from rlpyt.runners.minibatch_rl_eval import MinibatchRlEval
from rlpyt.utils.seed import make_seed
from rlpyt.utils.collections import AttrDict
from rlpyt.utils.quick_args import save__init__args
###############################################################################
# Master
###############################################################################
###############################################################################
# Worker
###############################################################################
# Helpers
| [
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] | 4.447368 | 152 |
# Copyright 2018 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
import os
from dataclasses import dataclass
from textwrap import dedent
from typing import Optional, Tuple
from pants.backend.python.rules.pex import Pex
from pants.backend.python.rules.pex_from_target_closure import CreatePexFromTargetClosure
from pants.backend.python.rules.prepare_chrooted_python_sources import ChrootedPythonSources
from pants.backend.python.subsystems.pytest import PyTest
from pants.backend.python.subsystems.python_setup import PythonSetup
from pants.backend.python.subsystems.subprocess_environment import SubprocessEncodingEnvironment
from pants.build_graph.address import Address
from pants.engine.addressable import BuildFileAddresses
from pants.engine.fs import Digest, DirectoriesToMerge, FileContent, InputFilesContent
from pants.engine.interactive_runner import InteractiveProcessRequest
from pants.engine.isolated_process import ExecuteProcessRequest, FallibleExecuteProcessResult
from pants.engine.legacy.graph import HydratedTargets, TransitiveHydratedTargets
from pants.engine.legacy.structs import PythonTestsAdaptor
from pants.engine.rules import UnionRule, rule, subsystem_rule
from pants.engine.selectors import Get
from pants.option.global_options import GlobalOptions
from pants.rules.core.strip_source_root import SourceRootStrippedSources
from pants.rules.core.test import TestDebugRequest, TestOptions, TestResult, TestTarget
DEFAULT_COVERAGE_CONFIG = dedent(f"""
[run]
branch = True
timid = False
relative_files = True
""")
def calculate_timeout_seconds(
*,
timeouts_enabled: bool,
target_timeout: Optional[int],
timeout_default: Optional[int],
timeout_maximum: Optional[int],
) -> Optional[int]:
"""Calculate the timeout for a test target.
If a target has no timeout configured its timeout will be set to the default timeout.
"""
if not timeouts_enabled:
return None
if target_timeout is None:
if timeout_default is None:
return None
target_timeout = timeout_default
if timeout_maximum is not None:
return min(target_timeout, timeout_maximum)
return target_timeout
@dataclass(frozen=True)
@rule
@rule(name="Run pytest")
async def run_python_test(
test_target: PythonTestsAdaptor,
test_setup: TestTargetSetup,
python_setup: PythonSetup,
subprocess_encoding_environment: SubprocessEncodingEnvironment,
global_options: GlobalOptions,
test_options: TestOptions,
) -> TestResult:
"""Runs pytest for one target."""
colors = global_options.colors
env = {"PYTEST_ADDOPTS": f"--color={'yes' if colors else 'no'}"}
request = test_setup.requirements_pex.create_execute_request(
python_setup=python_setup,
subprocess_encoding_environment=subprocess_encoding_environment,
pex_path=f'./{test_setup.requirements_pex.output_filename}',
pex_args=test_setup.args,
input_files=test_setup.input_files_digest,
output_directories=('.coverage',) if test_options.values.run_coverage else None,
description=f'Run Pytest for {test_target.address.reference()}',
timeout_seconds=test_setup.timeout_seconds if test_setup.timeout_seconds is not None else 9999,
env=env,
)
result = await Get[FallibleExecuteProcessResult](ExecuteProcessRequest, request)
return TestResult.from_fallible_execute_process_result(result)
@rule(name="Run pytest in an interactive process")
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7,
3672,
2625,
10987,
12972,
9288,
287,
281,
14333,
1429,
4943,
628
] | 3.3343 | 1,035 |
from sciencebeam_utils.utils.string import (
parse_list
)
| [
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# coding: utf-8 -*-
# TITLE / SUBTITLE / AUTHOR
# The title, subtitle, and author of the blog
TITLE = "Misa Montes"
SUBTITLE = "blog"
AUTHOR = "Misa"
METADATA_TAGS = ['title', 'author']
# POSTS_PER_PAGE
# The number of posts that will appear on each page of index.html
POSTS_PER_PAGE = 3
# SUMMARY_DELIMITOR
# Used to specify a breaking point from the beginning of the document to the
# end of the summary.
SUMMARY_DELIMITER = "~~"
# USE_HEROKU
# Toggled as True/False if the system will or will not be deployed as a Heroku
# app, respectively.
USE_HEROKU = True
# DISQUS_SHORTNAME
# Disqus is a free system used to manage comments at the bottom of blog posts.
# After signing up, you will be issued a shortname -- put it here. By default
# developer mode of the script is enabled.
DISQUS_SHORTNAME = "misalabs"
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198
] | 2.928315 | 279 |
'''
Description: Problem 2 (rearrange the code)
Version: 1.0.2.20210118
Author: Arvin Zhao
Date: 2021-01-14 22:35:43
Last Editors: Arvin Zhao
LastEditTime: 2021-01-18 18:11:03
'''
line = input('Enter a string: ')
i = 0
is_palindrome = True
while i < len(line) / 2 and is_palindrome:
if line[i] != line[len(line) - i - 1]:
is_palindrome = False
else:
is_palindrome = True
i += 1
if is_palindrome:
print(line, 'is a palindrome.')
else:
print(line, 'is not a palindrome.') | [
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] | 2.292793 | 222 |
"""
name - jméno
pozition - pozice (x, y)
can_train - čísla pro trening jednotky (integer) - pokud je má jednotka alespoň jedno z těchto čísel může budova trénovat tuto jednotku (čím víc společných čísel tím kratší doba tréningu)
defend_power - sílá obrany integer - 0 neučastní se obrany
lifes - počet životů (integer, integer) - aktuálně, maximalně | 0 v maximalně zničení při zničení města, -1 v maximalně zničení při útoku na město, ostantí kladná čísla v maximalně zničení při dosažení 0
income - vydělá za čas (integer, integer, integer) - vydělá, za, posledně
"""
from time import time | [
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] | 1.571429 | 518 |
##
## Demonstrate some of the operations of the Deck and Card classes
##
import cards
# Seed the random number generator to a specific value so every execution
# of the program uses the same sequence of random numbers (for testing).
import random
random.seed( 100 )
# Create a deck of cards
my_deck = cards.Deck()
# Shuffle the deck, then display it in 13 columns
my_deck.shuffle()
print( "===== shuffled deck =====" )
my_deck.display()
# Deal five cards to each player (alternating)
print( "Dealt five cards to each player (alternating)" )
print()
player1_list=[]
player2_list=[]
for i in range( 5 ):
player1_list.append( my_deck.deal() )
player2_list.append( my_deck.deal() )
# Display each player's cards and the cards still in the deck
print( "===== player #1 =====" )
print()
print( player1_list )
print()
print( "===== player #2 =====" )
print()
print( player2_list )
print()
print( "===== remaining cards in deck =====" )
my_deck.display()
hand(0,'First')
hand(0,'Second')
hand(-1,'Last') | [
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from __future__ import absolute_import
import os
import socket
from ur_online_control.ur_direct.mixins.airpick_mixins import AirpickMixins
__all__ = [
'URCommandScript'
]
class URCommandScript(AirpickMixins):
"""Class containing commands for the UR Robot system"""
def start(self):
"""To build the start of the script"""
self.add_lines(["def program():",
"\ttextmsg(\">> Entering program.\")",
"\t# open line for airpick commands"])
def end(self, feedback=None):
"""To build the end of the script"""
if feedback:
self.socket_send_line('"Done"')
self.add_lines(["\ttextmsg(\"<< Exiting program.\")",
"end",
"program()\n\n\n"])
def generate(self):
"""Translate the dictionary to a long string"""
self.script = '\n'.join(self.commands_dict.values())
return self.script
# Dictionary building
def add_line(self, line, i=None):
"""Add a single line to the script"""
if i is None:
i = len(self.commands_dict)
else:
pass
self.commands_dict[i] = line
def add_lines(self, lines):
"""Add a multiple lines to the script"""
i = len(self.commands_dict)
[self.add_line(line, i+line_nr) for (line_nr, line) in zip(range(len(lines)), lines)]
# Feedback functionality
def get_current_pose_cartesian(self, send=False):
"""Get the current cartesian pose"""
self.get_current_pose("cartesian", send)
def get_current_pose_joints(self, send=False):
"""Get the current joints pose"""
self.get_current_pose("joints", send)
def get_current_pose(self, get_type, send):
"""Create get pose code"""
pose_type = {
"cartesian": "get_forward_kin()",
"joints": "get_actual_joint_positions()"
}
self.add_lines(["\tcurrent_pose = {}".format(pose_type[get_type]),
"\ttextmsg(current_pose)"])
if send:
self.socket_send_line('current_pose')
#self.add_line("\ttextmsg('sending done')")
# Connectivity
def is_available(self):
"""Ping the network, to check for availability"""
system_call = "ping -r 1 -n 1 {}".format(self.ur_ip)
response = os.system(system_call)
if response == 0:
return True
else:
return False
# Geometric effects
def set_tcp(self, tcp):
"""Set the tcp"""
#tcp = [tcp[i]/1000 if i < 3 else tcp[i] for i in range(len(tcp))]
tcp = [tcp[i] for i in range(len(tcp))]
self.add_line("\tset_tcp(p{})".format(tcp))
def add_move_linear(self, move_command, feedback=None):
"""Add a move command to the script"""
#move = [cmd / 1000 if c not in [3, 4, 5] else cmd for c, cmd in zip(range(len(move_command)), move_command)]
move = [cmd for c, cmd in zip(range(len(move_command)), move_command)]
[x, y, z, dx, dy, dz, v, r] = move
self.add_line("\tmovel(p[{}, {}, {}, {}, {}, {}], v={}, r={})".format(x, y, z, dx, dy, dz, v, r))
if feedback == "Full":
self.get_current_pose_cartesian(True)
elif feedback == "UR_only":
self.get_current_pose_cartesian(False)
else:
pass
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] | 2.15856 | 1,583 |
import os
import contextlib
filepath = os.path.dirname(os.path.abspath(__file__))
def remove_installed_data_files():
"""
Removes some of the files that are downloaded during install.
Args:
None
Returns:
None
"""
# remove the GO file
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'go-basic.obo'))
# remove the GO annotations
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'goa_human.gaf.gz'))
# remove the housekeeping genes file
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'HK_genes.txt'))
# remove the transcription factors genes file
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'TFCheckpoint_download_180515.txt'))
# remove the GTEx Rdata file
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'gtex', 'rse_gene.Rdata'))
# remove the GTEx expression file
with contextlib.suppress(FileNotFoundError):
os.remove(os.path.join(filepath, 'gtex', 'expression_data.csv')) | [
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62,
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13,
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] | 2.567033 | 455 |
#
if aaa:
# ...
elif bbb:
# ...
#
| [
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220,
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198,
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198
] | 1.555556 | 27 |
"""
Copyright (c) Microsoft Corporation.
Licensed under the MIT license.
HERO for Video Question Answering Tasks, shared by:
1. TVQA
2. How2QA
3. VLEP
4. VIOLIN
copied/modified from HERO
(https://github.com/linjieli222/HERO)
"""
from collections import defaultdict
import copy
import torch
from torch import nn
from torch.nn import functional as F
from .model import HeroModel
from .layers import MLPLayer
from .modeling_utils import mask_logits
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] | 3.176056 | 142 |
import logging
from channels.test import ChannelTestCase, WSClient
from .game_logic import add_player_to_game
from .models import Player, Game, CardGamePlayer, Card
LOGGER = logging.getLogger("cardgame_channels_app")
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# pyt_utilities.py (python3)
# utilities for CNN training with pytorch; data preparation, training, evaluation
# added saving checkpoint
# FEB 2020 / 21
# sources:
# https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html#load-data
# https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html
#updated normalization mean and std:
#mean [0.4597244970012637, 0.4887084808460421, 0.46925360649661096]
#std [0.20728858675971737, 0.2048932794469992, 0.21645177513430724]
#-------------------------------------------------------------------------------
import os, sys, time, random, itertools
import torch, torchvision
from torch.optim import lr_scheduler
from torch.autograd import Variable
from torchvision import models, datasets, transforms
import torch.nn.functional as F
from torch import utils
import torch.optim as optim
from PIL import Image
import numpy
import array
import urllib, glob, shutil
from shutil import copyfile, copy
from copy import deepcopy
import matplotlib.pyplot as plt
from plot_helper import *
from utilities import *
bali26_class_names = ['aroid', 'bamboo', 'banana', 'cacao', 'cinnamon', 'coffeearabica', 'dragonfruit', 'durian', 'frangipani', 'guava', \
'jackfruit', 'lychee', 'mango', 'mangosteen', 'nilam', 'papaya', 'passiflora', \
'sawo', 'snakefruit', 'starfruit', 'sugarpalm', 'taro', 'vanilla', 'waterguava', 'whitepepper', 'zodia']
#files on pCloud
bali26_alexnet = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_alexnet.pth'
bali26_resnet152 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnet152.pth'
bali26_rexnext50 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnext50.pth'
bali26_samples_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali26samples.zip'
bali3_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3.zip'
bali3B_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3B.zip'
bali3C_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3C.zip'
bali3D_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3D.zip'
tests_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/tests.zip'
bali_mixedplants_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali_mixedplants.zip'
#-------------------------------------------------------------------------------
data_transforms = {
'train': transforms.Compose([
transforms.RandomResizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26
#transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
'val': transforms.Compose([
transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26
#transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
}
predict_transform = transforms.Compose([
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26
#transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
#-------------------------------------------------------------------------------
#simple three layer CNN for 224 x 224 input; reduced alexnet; untrained by default
#https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#def train_model(checkpointname, model, criterion, optimizer, scheduler, num_epochs, output):
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
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198,
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2,
10097,
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2,
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24305,
198
] | 2.838411 | 1,510 |
import mysql.connector
import yaml
from os import path, listdir
import shutil
import datetime
db_connection = mysql.connector.connect(
host="localhost",
port=3308,
user="root",
passwd="",
database="ipldata"
)
# Global Variable
player_data = {}
# Query Team details by name
# Add new player to DB.
# Get Player details by name
# Read data from YAML file
# Read files from folders
# Upload data into MySQL DB
# Parse Innings data
###### Main Program ######
# Read files to load from directory
files = readFilesInFolder()
# Read Data from the file.
for file in files:
print("Processing file: " + file)
match_data = readDataFromFile(file)
#print(match_data['info'])
# Upload into DB
parseAndUploadDataToDB(match_data)
shutil.move(path.dirname(__file__) + "/to_load/" + file, path.dirname(__file__) + "/done/" + file)
print("I'm done here !") | [
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] | 2.908197 | 305 |
#
#
#
#
#
#
#$Id: groParser.py,v 1.11 2006/12/15 19:53:29 annao Exp $
#
"""
Module Gromacs Parser.
"""
import os,types
from MolKit.moleculeParser import MoleculeParser
from MolKit.protein import Protein, Chain, ChainSet, Residue, ResidueSet, ProteinSet
from MolKit.molecule import Atom, AtomSet, Bond, BondSet, HydrogenBond
from PyBabel.babelElements import babel_elements
if __name__ == '__main__':
parser = groParser( filename='/usr/share/gromacs/tutor/methanol/conf.gro' )
print "Reading molecule"
mol = parser.parse()
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796,
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198
] | 2.591549 | 213 |
# Copyright 2012-2013 Eric Ptak - trouch.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import time
import subprocess
from webiopi.utils.logger import debug, info
BUSLIST = {
"I2C": {"enabled": False, "gpio": {0:"SDA", 1:"SCL", 2:"SDA", 3:"SCL"}, "modules": ["i2c-bcm2708", "i2c-dev"]},
"SPI": {"enabled": False, "gpio": {7:"CE1", 8:"CE0", 9:"MISO", 10:"MOSI", 11:"SCLK"}, "modules": ["spi-bcm2708", "spidev"]},
"UART": {"enabled": False, "gpio": {14:"TX", 15:"RX"}},
"ONEWIRE": {"enabled": False, "gpio": {4:"DATA"}, "modules": ["w1-gpio"], "wait": 2}
}
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] | 2.735294 | 408 |
import datetime
from clover.common import get_system_info
from clover.common import friendly_datetime
from clover.report.service import ReportService
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] | 3.825 | 40 |
class asyncGwEvent(object):
"""Basic async event."""
class asyncClEvent(object):
"""Basic async event.""" | [
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wt1_2_7 = {'192.168.122.112': [6.0527, 8.4551, 7.8479, 7.6681, 7.4932, 6.4745, 6.4198, 8.2644, 10.7811, 10.3783, 9.9412, 9.5791, 9.2604, 9.4337, 9.2044, 8.9888, 8.8576, 8.6938, 8.5687, 8.4276, 8.3159, 8.203, 8.3446, 8.2226, 8.127, 8.0167, 7.9279, 7.8576, 7.9614, 7.9092, 7.8796, 7.8118, 7.747, 7.8486, 7.7813, 7.8853, 7.8253, 7.7668, 7.8695, 7.8173, 7.7653, 7.7128, 7.6701, 7.7426, 7.811, 7.8762, 7.8196, 7.7081, 7.6705, 7.6261, 7.4933, 7.4535, 7.4443, 7.4345, 7.3984, 7.3828, 7.7321, 7.6903, 7.6519, 7.6141, 7.5784, 7.928, 7.9189, 7.9659, 7.944, 7.9437, 7.913, 7.8772, 7.85, 7.8308, 7.8185, 7.792, 7.7742, 7.7612, 7.7356, 7.766, 7.7373, 7.713, 7.6905, 7.6612, 7.6402, 7.6118, 7.6528, 7.6491, 7.6283, 7.6693, 7.6482, 7.6321, 7.6127, 7.6098, 7.591, 7.5769, 7.552, 7.5301, 7.599, 7.5916, 7.5948, 7.5769, 7.5614, 7.5986, 7.6272, 7.6068, 7.5859, 7.5649, 7.5449, 7.5254, 7.5584, 7.5457, 7.5256, 7.507, 7.4923, 7.4765, 7.4653, 7.4491, 7.4337, 7.4291, 7.4144, 7.3997, 7.3822, 7.367, 7.3764, 7.3622, 7.3563, 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cpu1_2_7 = [19.4, 29.2, 0.1, 2.2, 1.0, 0.3, 0.1, 1.7, 0.5, 0.5, 0.1, 1.8, 1.3, 0.6, 0.8, 2.2, 0.3, 2.0, 2.3, 1.6, 0.3, 1.1, 0.8, 0.1, 0.4, 1.1, 1.9, 0.4, 0.4, 0.4, 0.8, 0.3, 0.9, 0.7, 0.9, 0.2, 0.2, 0.2, 0.8, 0.7, 0.6, 0.7, 0.8, 0.5, 0.3, 3.3, 3.5, 1.2, 1.4, 0.6, 0.1, 0.3, 0.5, 0.4, 0.2, 0.3, 0.6, 0.2, 0.6, 0.3, 1.6, 1.4, 0.4, 1.7, 0.7, 0.5, 0.9, 0.7, 0.5, 1.1, 0.8, 6.3, 5.9, 0.2, 0.6, 0.2, 0.4, 0.3, 0.7, 0.1, 0.2, 0.4, 0.2, 0.2, 0.6, 1.2, 0.1, 1.7, 2.0, 0.5, 1.3, 1.2, 0.0, 0.8, 0.2, 0.3, 0.3, 1.1, 1.4, 0.6, 0.2, 0.4, 1.1, 1.2, 0.4, 0.4, 0.6, 1.1, 0.3, 0.1, 0.5, 0.6, 0.2, 0.4, 1.2, 0.1, 0.5, 1.1, 0.6, 1.0, 1.4, 0.2, 1.0, 0.4, 0.7, 0.2, 0.5, 0.5, 1.1, 2.6, 1.0, 0.1, 3.3, 4.3, 0.4, 0.7, 1.4, 0.9, 1.7, 4.7, 2.4, 1.3, 0.8, 1.6, 1.8, 0.7, 0.7, 0.5, 0.2, 1.3, 4.5, 5.9, 0.4, 5.0, 4.7, 0.0, 1.1, 1.3, 0.8, 0.9, 4.9, 4.5, 0.8, 1.1, 1.5, 1.9, 0.2, 1.0, 4.4, 6.0, 0.4, 1.2, 0.4, 0.8, 0.2, 1.6, 0.3, 0.3, 0.7, 0.1, 0.7, 0.2, 0.0, 0.4, 0.0, 0.1, 1.0, 0.2, 0.3, 0.3, 0.6, 0.1, 3.2, 3.7, 0.3, 4.8, 4.6, 3.9, 4.0, 0.1, 5.0, 2.3, 2.7, 0.5, 1.2, 0.0, 1.6, 0.9, 0.9, 0.5, 0.0, 1.7, 1.3, 0.3, 1.0, 1.9, 0.8, 0.1, 0.7, 1.7, 0.6, 0.5, 0.2, 1.3, 1.0, 0.3, 1.7, 1.1, 1.1, 0.4, 1.1, 0.9, 1.2, 0.2, 0.5, 0.5, 0.6, 0.8, 0.7, 1.0, 0.2, 0.3, 0.3, 0.9, 0.9, 0.3, 1.0, 2.2, 1.0, 1.4, 0.3, 1.1, 0.3, 0.7, 0.7, 0.6, 2.1, 1.0, 1.0, 0.1, 0.0, 0.0, 1.2, 2.3, 1.0, 0.3, 0.0, 0.2, 2.2, 1.9, 0.3, 1.2, 0.6, 1.1, 2.6, 2.6, 2.4, 2.4, 1.0, 2.0, 0.9, 4.9, 0.3, 3.9, 0.6, 0.8, 0.6, 2.1, 2.6, 1.4, 1.7, 1.6, 1.2, 0.9, 0.8, 1.0, 1.4, 0.7, 0.8, 0.9, 1.4, 0.1, 1.5, 0.1, 4.8, 1.6, 2.7, 0.4, 2.4, 2.3, 1.2, 1.0, 2.3, 1.4, 0.8, 0.2, 0.7, 0.3, 0.3, 0.1, 1.8, 5.2, 3.2, 2.8, 1.7, 0.2, 0.0, 1.6, 1.0, 1.6, 2.2, 1.8, 1.9, 0.3, 1.2, 0.0, 0.4, 0.3, 2.2, 1.3, 3.8, 3.5, 1.2, 2.3, 0.9, 1.0, 0.1, 1.5, 0.2, 1.4, 0.4, 0.3, 0.7, 0.9, 0.3, 4.0, 4.5, 0.0, 0.1, 5.9, 5.2, 1.7, 0.9, 0.4, 0.0, 1.3, 0.1, 0.5, 1.6, 0.4, 0.3]
off_mec1_2_7 = 284
off_cloud1_2_7 = 392
inward_mec1_2_7 = 222
loc1_2_7 = 635
deadlock1_2_7 = [7]
memory1_2_7 = [0.2175, 0.2178, 0.2179, 0.218, 0.2182, 0.2182, 0.2182, 0.2182, 0.2183, 0.2184, 0.2184, 0.2184, 0.2184, 0.2184, 0.2188, 0.2189, 0.2189, 0.219, 0.219, 0.219, 0.219, 0.219, 0.219, 0.2191, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2193, 0.2193, 0.2193, 0.2193, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2196, 0.2196, 0.2196, 0.2197, 0.2197, 0.2198, 0.2198, 0.2199, 0.2199, 0.2199, 0.2199, 0.2199, 0.2199, 0.22, 0.2201, 0.2201, 0.2201, 0.2201, 0.2201, 0.2201, 0.2201, 0.2201, 0.2202, 0.2202, 0.2203, 0.2204, 0.2204, 0.2205, 0.2205, 0.2205, 0.2205, 0.2205, 0.2205, 0.2205, 0.2206, 0.2206, 0.2207, 0.2207, 0.2208, 0.2209, 0.2209, 0.2209, 0.2209, 0.2209, 0.2209, 0.221, 0.221, 0.221, 0.2211, 0.2211, 0.2211, 0.2213, 0.2213, 0.2213, 0.2214, 0.2214, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2215, 0.2216, 0.2217, 0.2217, 0.2217, 0.2217, 0.2218, 0.2218, 0.2218, 0.2218, 0.2218, 0.2218, 0.2219, 0.2219, 0.2219, 0.2219, 0.2219, 0.2219, 0.222, 0.222, 0.222, 0.222, 0.222, 0.2221, 0.2221, 0.2222, 0.2222, 0.2222, 0.2222, 0.2223, 0.2223, 0.2223, 0.2223, 0.2223, 0.2224, 0.2224, 0.2224, 0.2224, 0.2225, 0.2225, 0.2225, 0.2225, 0.2225, 0.2225, 0.2225, 0.2226, 0.2226, 0.2227, 0.2227, 0.2229, 0.2229, 0.223, 0.223, 0.223, 0.223, 0.223, 0.223, 0.223, 0.2231, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2232, 0.2233, 0.2233, 0.2233, 0.2234, 0.2234, 0.2234, 0.2234, 0.2234, 0.2235, 0.2235, 0.2235, 0.2235, 0.2235, 0.2236, 0.2236, 0.2237, 0.2237, 0.2237, 0.2238, 0.2238, 0.2238, 0.2239, 0.2239, 0.2239, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.2241, 0.2241, 0.2241, 0.2241, 0.2242, 0.2242, 0.2242, 0.2242, 0.2245, 0.2245, 0.2245, 0.2246, 0.2246, 0.2246, 0.2246, 0.2246, 0.2246, 0.2246, 0.2246, 0.2246, 0.2247, 0.2247, 0.2247, 0.2247, 0.2248, 0.2248, 0.2248, 0.2248, 0.2249, 0.2249, 0.2249, 0.225, 0.225, 0.225, 0.2251, 0.2251, 0.2251, 0.2251, 0.2252, 0.2252, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2253, 0.2254, 0.2255, 0.2255, 0.2255, 0.2255, 0.2258, 0.2258, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.2259, 0.226, 0.226, 0.226, 0.2261, 0.2261, 0.2261, 0.2261, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2262, 0.2263, 0.2263, 0.2263, 0.2263, 0.2264, 0.2264, 0.2264, 0.2264, 0.2265, 0.2265, 0.2267, 0.2268, 0.2268, 0.2269, 0.2269, 0.2269, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2273, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2276, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2278, 0.2278, 0.2278, 0.2279, 0.2279, 0.228, 0.228, 0.228, 0.228, 0.228, 0.228, 0.2283, 0.2283, 0.2283, 0.2283, 0.2284, 0.2284, 0.2284]
task_received1_2_7 = 1311
sent_t1_2_7 = {'125': 375, '124': 449, '126': 487}
cooperate1_2_7 = {'mec': 284, 'cloud': 392}
task_record1_2_7 = {}
outward_mec1_2_7 = 244
offload_check1_2_7 = [197, 42]
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1983,
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1983,
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1983,
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18,
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11,
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1983,
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5705,
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23,
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18,
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20,
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3980,
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24940,
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24,
48768,
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13,
24,
33372,
11,
838,
13,
24,
28857,
11,
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13,
1983,
5999,
11,
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13,
2780,
5999,
11,
1367,
13,
2780,
3510,
11,
838,
13,
3459,
3132,
11,
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13,
4089,
2598,
11,
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2231,
11,
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13,
2414,
1558,
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13,
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5066,
11,
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3365,
1157,
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22,
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11,
1105,
13,
33660,
11,
1367,
13,
1485,
2624,
11,
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11,
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1821,
5332,
11,
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22,
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2327,
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2548,
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2857,
1065,
11,
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1983,
3459,
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29088,
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30610,
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1433,
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21,
11,
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13,
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2598,
11,
642,
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62,
448,
62,
83,
6791,
16,
62,
17,
62,
22,
796,
657
] | 1.616278 | 214,009 |
import numpy as np
import random
import json
import hdbscan
import numba
import sys
from sklearn.neighbors import KDTree
from pyclustering.cluster.xmeans import xmeans
from helpers import distance_matrix as dm
from helpers import hparam_functions as hp
from helpers import visualization as vis
from concurrent.futures import ThreadPoolExecutor
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] | 2.902985 | 134 |
"""
Copyright 2012 Ali Ok (aliokATapacheDOTorg)
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from __future__ import division
from trnltk.morphology.contextful.likelihoodmetrics.hidden.querykeyappender import _word_parse_result_appender, _word_surface_appender
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] | 3.706468 | 201 |
import numpy as np
| [
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# encoding:utf-8
class Position(object):
"""
Basic position class.
Attributes
----------
symbol : str
List of securities.
side : str
("Long", "Short"). Positions of different sides will not be merged.
cost_price : float
Average cost price of current net position.
close_pnl : float
float_pnl : float
trading_pnl : float
holding_pnl : float
init_size : int
Position at the start of the day.
enable_size : int
Position that can be closed.
frozen_size : int
Positions to be closed.
want_size : int
Positions to be opened.
pre_size : int
Last day's position.
today_size : int
Today's position.
current_size : int
Current position.
Methods
-------
"""
'''
__slots__ = ['symbol', 'side', 'cost_price',
'close_pnl', 'float_pnl', 'trading_pnl', 'holding_pnl',
'enable_size', 'frozen_size', 'want_size',
'today_size', 'pre_size', 'current_size', 'init_size',
'commission']
'''
@classmethod
@classmethod
class GoalPosition(object):
"""
Used in goal_portfolio function to generate orders.
Attributes
----------
symbol : str
ref_price : float
Reference price, used by risk management, not by order.
size : int
Target position size.
urgency : int
The urgency to adjust position, used to determine trading algorithm.
"""
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5004,
7313,
11862,
13,
628,
220,
220,
220,
37227,
198
] | 2.424723 | 631 |
#
# -------------------------------------------------------------------------
# Copyright (c) 2015-2017 AT&T Intellectual Property
# Copyright (C) 2020 Wipro Limited.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# -------------------------------------------------------------------------
#
import socket
import time
import cotyledon
import futurist
from oslo_config import cfg
from oslo_log import log
from conductor.common.config_loader import load_config_file
from conductor.common import db_backend
from conductor.common.music import messaging as music_messaging
from conductor.common.utils import conductor_logging_util as log_util
from conductor.controller.generic_objective_translator import GenericObjectiveTranslator
from conductor.controller.translator import Translator
from conductor.controller.translator_utils import TranslatorException
from conductor.controller.translator_utils import VERSIONS
from conductor.i18n import _LE
from conductor.i18n import _LI
from conductor import messaging
LOG = log.getLogger(__name__)
CONF = cfg.CONF
CONTROLLER_OPTS = [
cfg.IntOpt('polling_interval',
default=1,
min=1,
help='Time between checking for new plans. '
'Default value is 1.'),
cfg.IntOpt('max_translation_counter',
default=1,
min=1),
cfg.StrOpt('opt_schema_file',
default='opt_schema.json',
help='json schema file which will be used to validate the '
'optimization object for the new template version'),
]
CONF.register_opts(CONTROLLER_OPTS, group='controller')
class TranslatorService(cotyledon.Service):
"""Template Translator service.
This service looks for untranslated templates and
preps them for solving by the Solver service.
"""
# This will appear in 'ps xaf'
name = "Template Translator"
def __init__(self, worker_id, conf, **kwargs):
"""Initializer"""
LOG.debug("{}".format(self.__class__.__name__))
super(TranslatorService, self).__init__(worker_id)
self._init(conf, **kwargs)
self.running = True
def _gracefully_stop(self):
"""Gracefully stop working on things"""
pass
def millisec_to_sec(self, millisec):
"""Convert milliseconds to seconds"""
return millisec / 1000
def _reset_template_status(self):
"""Reset plans being templated so they are translated again.
Use this only when the translator service is not running concurrently.
"""
plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING)
for the_plan in plans:
the_plan.status = self.Plan.TEMPLATE
# Use only in active-passive mode, so don't have to be atomic
the_plan.update()
def _restart(self):
"""Prepare to restart the service"""
pass
def current_time_seconds(self):
"""Current time in milliseconds."""
return int(round(time.time()))
def setup_rpc(self, conf, topic):
"""Set up the RPC Client"""
# TODO(jdandrea): Put this pattern inside music_messaging?
transport = messaging.get_transport(conf=conf)
target = music_messaging.Target(topic=topic)
client = music_messaging.RPCClient(conf=conf,
transport=transport,
target=target)
return client
def translate(self, plan):
"""Translate the plan to a format the solver can use"""
# Update the translation field and set status to TRANSLATED.
try:
LOG.info(_LI("Requesting plan {} translation").format(
plan.id))
template_version = plan.template.get("homing_template_version")
if template_version in VERSIONS['BASE']:
trns = Translator(self.conf, plan.name, plan.id, plan.template)
elif template_version in VERSIONS['GENERIC']:
trns = GenericObjectiveTranslator(self.conf, plan.name, plan.id, plan.template, self.opt_schema)
else:
raise TranslatorException(
"conductor_template_version must be one "
"of: {}".format(', '.join([x for v in VERSIONS.values() for x in v])))
trns.translate()
if trns.ok:
plan.translation = trns.translation
plan.status = self.Plan.TRANSLATED
LOG.info(_LI(
"Plan {} translated. Ready for solving").format(
plan.id))
LOG.info(_LI(
"Plan name: {}").format(
plan.name))
else:
plan.message = trns.error_message
plan.status = self.Plan.ERROR
LOG.error(_LE(
"Plan {} translation error encountered").format(
plan.id))
except Exception as ex:
template = "An exception of type {0} occurred, arguments:\n{1!r}"
plan.message = template.format(type(ex).__name__, ex.args)
plan.status = self.Plan.ERROR
_is_success = 'FAILURE'
while 'FAILURE' in _is_success and (self.current_time_seconds() - self.millisec_to_sec(plan.updated)) \
<= self.conf.messaging_server.timeout:
_is_success = plan.update(condition=self.translation_owner_condition)
LOG.info(_LI("Changing the template status from translating to {}, "
"atomic update response from MUSIC {}").format(plan.status, _is_success))
def __check_for_templates(self):
"""Wait for the polling interval, then do the real template check."""
# Wait for at least poll_interval sec
polling_interval = self.conf.controller.polling_interval
time.sleep(polling_interval)
# Look for plans with the status set to TEMPLATE
# Instead of using the query.all() method, now creating an index for 'status'
# field in conductor.plans table, and query plans by status columns
template_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TEMPLATE)
translating_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING)
# combine the plans with status = 'template' and 'translating' together
plans = template_plans + translating_plans
for plan in plans:
# If there's a template to be translated, do it!
if plan.status == self.Plan.TEMPLATE:
if plan.translation_counter >= self.conf.controller.max_translation_counter:
message = _LE("Tried {} times. Plan {} is unable to translate") \
.format(self.conf.controller.max_translation_counter, plan.id)
plan.message = message
plan.status = self.Plan.ERROR
plan.update(condition=self.template_status_condition)
LOG.error(message)
break
else:
# change the plan status to "translating" and assign the current machine as translation owner
plan.status = self.Plan.TRANSLATING
plan.translation_counter += 1
plan.translation_owner = socket.gethostname()
plan.translation_begin_timestamp = int(round(time.time() * 1000))
_is_updated = plan.update(condition=self.template_status_condition)
log_util.setLoggerFilter(LOG, self.conf.keyspace, plan.id)
LOG.info(_LE("Plan {} is trying to update the status from 'template' to 'translating',"
" get {} response from MUSIC").format(plan.id, _is_updated))
if not _is_updated:
break
if _is_updated and 'SUCCESS' in _is_updated:
self.translate(plan)
break
# TODO(larry): sychronized clock among Conducotr VMs, or use an offset
elif plan.status == self.Plan.TRANSLATING and (self.current_time_seconds()
- self.millisec_to_sec(plan.updated)) \
> self.conf.messaging_server.timeout:
plan.status = self.Plan.TEMPLATE
plan.update(condition=self.translating_status_condition)
break
elif plan.timedout:
# TODO(jdandrea): How to tell all involved to stop working?
# Not enough to just set status.
continue
def run(self):
"""Run"""
LOG.debug("{}".format(self.__class__.__name__))
# Look for templates to translate from within a thread
executor = futurist.ThreadPoolExecutor()
while self.running:
fut = executor.submit(self.__check_for_templates)
fut.result()
executor.shutdown()
def terminate(self):
"""Terminate"""
LOG.debug("{}".format(self.__class__.__name__))
self.running = False
self._gracefully_stop()
super(TranslatorService, self).terminate()
def reload(self):
"""Reload"""
LOG.debug("{}".format(self.__class__.__name__))
self._restart()
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2116,
13557,
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] | 2.311106 | 4,304 |
#!/bin/python3
enum = {}
previousValue = None
with open("rosecommon/include/epackettype.h", "r") as f:
for i in range(46):
f.readline()
for line in f:
if "};" in line:
break
name, value = parse(line)
if value:
enum[name] = value
while True:
value = input("Enter the hex value of the packet: ")
for name, v in enum.items():
if int(value, 16) == v:
if "PAKCS" in name:
print("Sent by client :", name)
else:
print("Sent by server :", name)
| [
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1600,
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8,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
31837,
416,
4382,
1058,
1600,
1438,
8,
198
] | 2.024648 | 284 |
'''
Copyright (C) 2021 CG Cookie
http://cgcookie.com
hello@cgcookie.com
Created by Jonathan Denning, Jonathan Williamson
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
'''
import os
import re
import sys
import glob
import inspect
import operator
import itertools
import importlib
import bpy
from mathutils import Vector, Matrix
from .blender import get_preferences
from .profiler import profiler
from .debug import dprint, debugger
from .maths import (
Point, Direction, Normal, Frame,
Point2D, Vec2D, Direction2D,
Ray, XForm, BBox, Plane
)
##################################################
# find functions of object that has key attribute
# returns list of (attribute value, fn)
##################################################
StructRNA = bpy.types.bpy_struct
registered_objects = {}
#################################################
#########################################################
#########################################################
#########################################################
#################################################
#################################################
def join(sep, iterable, preSep='', postSep='', toStr=str):
'''
this function adds features on to sep.join(iterable)
if iterable is not empty, preSep is prepended and postSep is appended
also, all items of iterable are turned to strings using toStr, which can be customized
ex: join(', ', [1,2,3]) => '1, 2, 3'
ex: join('.', ['foo', 'bar'], preSep='.') => '.foo.bar'
'''
s = sep.join(map(toStr, iterable))
if not s: return ''
return f'{preSep}{s}{postSep}'
def get_matrices(ob):
''' obtain blender object matrices '''
mx = ob.matrix_world
imx = mx.inverted()
return [mx, imx]
class Dict():
'''
a fancy dictionary object
''' | [
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307,
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25,
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7,
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685,
16,
11,
17,
11,
18,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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16,
11,
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220,
220,
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277,
6,
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82,
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92,
6,
628,
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62,
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7,
672,
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220,
220,
220,
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2603,
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198,
220,
220,
220,
285,
87,
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909,
13,
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8609,
62,
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198,
220,
220,
220,
545,
87,
796,
285,
87,
13,
259,
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3419,
198,
220,
220,
220,
1441,
685,
36802,
11,
545,
87,
60,
628,
628,
198,
198,
4871,
360,
713,
33529,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
257,
14996,
22155,
2134,
198,
220,
220,
220,
705,
7061
] | 3.389646 | 734 |
import torch
import torch.nn as nn
import torch.nn.functional as f
| [
11748,
28034,
201,
198,
11748,
28034,
13,
20471,
355,
299,
77,
201,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
277,
201,
198,
201,
198,
201,
198
] | 2.740741 | 27 |
import json
from django import template
from django.utils.html import mark_safe
register = template.Library()
@register.simple_tag
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import factory
from django.contrib.auth import get_user_model
from organisations.models import Organisation, OrganisationProposal, Person
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