content
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sequencelengths 1
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| token_count
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|
|---|---|---|---|
import hashlib
import os
| [
11748,
12234,
8019,
198,
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198
] | 3.571429 | 7 |
# baleen.utils.timez
# Utility functions for Baleen
#
# Author: Benjamin Bengfort <[email protected]>
# Created: Mon Sep 22 10:14:57 2014 -0400
#
# Copyright (C) 2014 Bengfort.com
# For license information, see LICENSE.txt
#
# ID: utils.py [] [email protected] $
"""
Utility functions for Baleenc
"""
##########################################################################
## Imports
##########################################################################
import re
import time
from dateutil.tz import tzlocal, tzutc
from datetime import date, datetime, timedelta
from dateutil.relativedelta import relativedelta
##########################################################################
## Format constants
##########################################################################
HUMAN_DATETIME = "%a %b %d %H:%M:%S %Y %z"
HUMAN_DATE = "%b %d, %Y"
HUMAN_TIME = "%I:%M:%S %p"
JSON_DATETIME = "%Y-%m-%dT%H:%M:%S.%fZ" # Must be UTC
ISO8601_DATETIME = "%Y-%m-%dT%H:%M:%S%z"
ISO8601_DATE = "%Y-%m-%d"
ISO8601_TIME = "%H:%M:%S"
COMMON_DATETIME = "%d/%b/%Y:%H:%M:%S %z"
##########################################################################
## Module helper function
##########################################################################
zre = re.compile(r'([\-\+]\d{4})')
def strptimez(dtstr, dtfmt):
"""
Helper function that performs the timezone calculation to correctly
compute the '%z' format that is not added by default in Python 2.7.
"""
if '%z' not in dtfmt:
return datetime.strptime(dtstr, dtfmt)
dtfmt = dtfmt.replace('%z', '')
offset = int(zre.search(dtstr).group(1))
dtstr = zre.sub('', dtstr)
delta = timedelta(hours = offset/100)
utctsp = datetime.strptime(dtstr, dtfmt) - delta
return utctsp.replace(tzinfo=tzutc())
def humanizedelta(*args, **kwargs):
"""
Wrapper around dateutil.relativedelta (same construtor args) and returns
a humanized string representing the detla in a meaningful way.
"""
if 'milliseconds' in kwargs:
sec = kwargs.get('seconds', 0)
msec = kwargs.pop('milliseconds')
kwargs['seconds'] = sec + (float(msec) / 1000.0)
delta = relativedelta(*args, **kwargs)
attrs = ('years', 'months', 'days', 'hours', 'minutes', 'seconds')
parts = [
'%d %s' % (getattr(delta, attr), getattr(delta, attr) > 1 and attr or attr[:-1])
for attr in attrs if getattr(delta, attr)
]
return " ".join(parts)
##########################################################################
## Timer functions
##########################################################################
class Timer(object):
"""
A context object timer. Usage:
>>> with Timer() as timer:
... do_something()
>>> print timer.elapsed
"""
def __init__(self, wall_clock=True):
"""
If wall_clock is True then use time.time() to get the number of
actually elapsed seconds. If wall_clock is False, use time.clock to
get the process time instead.
"""
self.wall_clock = wall_clock
self.time = time.time if wall_clock else time.clock
# Stubs for serializing an empty timer.
self.started = None
self.finished = None
self.elapsed = 0.0
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# 插入排序
if __name__ == '__main__':
print(Solution().insertSort([1,8,3,2,6,9])) | [
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"""
Tests for the genetic maps management.
"""
import unittest
from unittest import mock
import tarfile
import tempfile
import os.path
import shutil
import urllib.request
import pathlib
import msprime
import stdpopsim
from stdpopsim import genetic_maps
import tests
# Infrastructure for keeping a local cache of the downloaded tarballs that
# which we 'download' from when we're running tests below.
def download_map_tarballs(destination):
"""
Download the tarballs for all genetic maps to the specified destination.
Used mainly for testing, where we want to download the maps repeatedly
to the cache and we wish to avoid the cost of downloading multiple times
from the remote location.
"""
for key, genetic_map in genetic_maps.registered_maps.items():
local_file = destination / (key + ".tar.gz")
if not local_file.exists():
cache_dir = local_file.parent
cache_dir.mkdir(exist_ok=True)
urllib.request.urlretrieve(genetic_map.url, local_file)
saved_urls = {}
# TODO add some parameters here to check different compression options,
# number of chromosomes etc.
def get_genetic_map_tarball():
"""
Returns a genetic map in hapmap format in a tarball as a bytes object.
"""
with tempfile.TemporaryDirectory() as map_dir:
for j in range(1, 10):
# TODO Have a way to put in different maps??
with open(os.path.join(map_dir, "prefix_chr{}.txt".format(j)), "w") as f:
print("Chromosome Position(bp) Rate(cM/Mb) Map(cM)", file=f)
print("chr1 55550 2.981822 0.000000", file=f)
print("chr1 82571 2.082414 0.080572", file=f)
print("chr1 88169 0 0.092229", file=f)
# For the tarfile to be in the right format, we must be in the right directory.
with genetic_maps.cd(map_dir):
# Now tar up this map_directory
with tempfile.TemporaryFile('wb+') as tmp_file:
with tarfile.open(fileobj=tmp_file, mode="w:gz") as tar_file:
for filename in os.listdir("."):
tar_file.add(filename)
# Read back the tarball
tmp_file.seek(0)
tarball = tmp_file.read()
return tarball
class TestGeneticMapTarball(unittest.TestCase):
"""
Tests that we correctly encode a genetic map in the tarball test function.
"""
class TestGeneticMap(tests.CacheWritingTest):
"""
Tests for the basic functionality of the genetic map class.
"""
class TestGeneticMapDownload(tests.CacheWritingTest):
"""
Tests downloading code for the genetic maps.
"""
class TestAllGeneticMaps(tests.CacheReadingTest):
"""
Tests if the all_genetic_maps() function works correctly.
"""
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] | 2.479381 | 1,164 |
"""
Copyright 2017 ARM 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.
ReportBase module, contains the base class for other report types.
"""
import os
from datetime import timedelta
import icetea_lib.LogManager as LogManager
#pylint: disable=no-self-use
class ReportBase(object):
"""
ReportBase is the baseclass of all other report types. It implements helpers related to
reporting as well as the abstract generate-method.
"""
def get_latest_filename(self, extension, basename="../latest."):
"""
Generate filename with 'latest.' prefix.
:param extension: Extension for file
:param basename: Base file name
:return: path to latest.basename.extension.
"""
return os.path.join(LogManager.get_base_dir(), basename+extension)
def get_current_filename(self, extension, basename="result."):
"""
Generate filename for a report.
:param extension: Extension for file name
:param basename: Base file name
:return: path to basename.extension
"""
return os.path.join(LogManager.get_base_dir(), basename+extension)
def generate(self, *args, **kwargs):
"""
Abstract generate-method.
"""
raise NotImplementedError("generate function missing")
def duration_to_string(self, seconds):
"""
Converts time in seconds to a timedelta and represents it as string.
:param seconds: Time in seconds
:return: str(datetime.timedelta)
"""
delta = timedelta(seconds=seconds)
return str(delta)
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] | 2.947814 | 709 |
import dash_html_components as html
import dash_core_components as dcc
def simple_bubble_chart(id_, title):
"""Generates simple bubble chart component
Args:
id (str): Component id
title (str): Component title
Returns:
obj: Html div object
"""
return html.Div(
className="main-card mb-4",
children=[
html.Div(
title,
className="title-bold title-centered",
),
html.Hr(),
dcc.Graph(id=id_),
],
)
| [
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] | 2.02952 | 271 |
# -*- coding:UTF-8 -*-
#! /usr/bin/python3
print('''for循环使用格式：
for <variable> in <sequence>:
<statements>
else:
<statements>\n''')
# 以下 for 实例中使用了 break 语句，break 语句用于跳出当前循环体
for a in [1,2,3,4,5,5,6,7,7,8,8,9,9,10,12,13,14,56,78]:
if a == 8:
print('a = 8 了')
break # 直接结束循环
print('a：',a,end= ';')
print( )
# continue语句被用来告诉Python跳过当前循环块中的剩余语句，然后继续进行下一轮循环。
for a in [1,2,3,4,5,5,6,7,7,8,8,9,9,10,12,13,14,56,78]:
if a == 8:
print('|a = 8| ',end=';')
continue # 跳出本次循环
print('a:',a,end= ';')
print( )
# 如果你需要遍历数字序列，可以使用内置range()函数。它会生成数列
for a in range(10):
print(a,end=" ")
print( )
for a in range(5,10):
print(a,end=' ')
print( )
for a in range(0,-15,-3):
print(a,end=' ') # 第三个变量表示步长
print( )
list1 = list(range(10,1000,99)) # 可用于创建列表
print(list1)
# 循环语句可以有 else 子句，它在穷尽列表(以for循环)或条件变为 false (以while循环)导致循环终止时被执行,但循环被break终止时不执行。
for a in range(6):
print(a)
else:
print('here is the end')
# 例如
for n in range(2, 20):
for x in range(2, n):
if n % x == 0:
print(n, '=', x, '*', n//x)
break
else:
# 循环中没有找到元素
print(n, '是质数')
while a in range(5):
pass # Python pass是空语句，是为了保持程序结构的完整性，pass不做任何事情，一般用做占位语句. | [
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13
] | 1.202614 | 1,071 |
# Copyright 2014 Google Inc. 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 packaging.utils
from caniuseonlywheels import pypi
from test import skip_pypi_timeouts, unittest
| [
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72,
62,
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5269,
11,
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395,
628,
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] | 3.77957 | 186 |
import logging
import socket
import time
from collections import defaultdict
| [
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] | 4.9375 | 16 |
import numpy as np
import cv2
import matplotlib.pyplot as plt
from pathlib import Path
import glob2 as glob
import os
import sys
savedir = "./output/"
# Add main support to run file from terminal directly
if __name__ == '__main__':
args = sys.argv
# args[0] = current file
# args[1] = function name
# args[2:] = function args : (*unpacked)
globals()[args[1]](*args[2:]) | [
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58,
22046,
58,
16,
11907,
46491,
22046,
58,
17,
25,
12962
] | 2.731034 | 145 |
#-------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#--------------------------------------------------------------------------
from datetime import datetime, timedelta
import logging
import pytest
import sys
import time
from azure.servicebus import ServiceBusClient, AutoLockRenewer
from azure.servicebus._common.constants import ReceiveMode
from devtools_testutils import AzureMgmtTestCase, CachedResourceGroupPreparer
from servicebus_preparer import ServiceBusNamespacePreparer, ServiceBusQueuePreparer
from stress_tests.stress_test_base import StressTestRunner, ReceiveType
LOGGING_ENABLE = False
| [
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] | 4.543353 | 173 |
import logging
from healthtools.scrapers.base_scraper import Scraper
from healthtools.config import SITES
from datetime import datetime
class DoctorsScraper(Scraper):
'''
Scraper for regular doctors on the medical board website
'''
def elasticsearch_format(self, entry):
"""
Format entry into elasticsearch ready document
:param entry: the data to be formatted
:return: dictionaries of the entry's metadata and the formatted entry
"""
date_obj = self.parse_date(entry["reg_date"])
entry["reg_date"] = datetime.strftime(date_obj, "%Y-%m-%d")
entry["facility"] = entry["practice_type"] = "-"
entry["doctor_type"] = "local_doctor"
# all bulk data need meta data describing the data
meta_dict = {
"index": {
"_index": self.es_index,
"_type": self.es_doc,
"_id": entry["id"]
}
}
return meta_dict, entry
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] | 2.383693 | 417 |
from bisect import bisect
def lis(seq, indices=False):
'''longest increasing subsequence
>>> lis([1, 2, 5, 3, 4])
[1, 2, 3, 4]
'''
if not seq:
return []
# prevs[i] is the index of the previous element in the longest subsequence
# containing element i
prevs = [None] * len(seq)
# tails[i] is the pair (elem, index) of the lowest element of any
# subsequence with length i + 1
tails = [(seq[0], 0)]
for i, elem in enumerate(seq[1:], start=1):
if elem > tails[-1][0]:
prevs[i] = tails[-1][1]
tails.append((elem, i))
continue
# let's find a tail that we can extend
k = bisect(tails, (elem, -1))
if tails[k][0] > elem:
tails[k] = (elem, i)
if k > 0:
prevs[i] = tails[k - 1][1]
_, i = tails[-1]
subseq = []
while i is not None:
subseq.append(i if indices else seq[i])
i = prevs[i]
return subseq[::-1]
| [
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220,
1441,
850,
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198
] | 2.041068 | 487 |
'''A collection of auxiliary functions that might be useful.'''
from obscurator import Obscurator
from common import Similarity
def showcase(s):
'''Showcase all tiers of characters on a given sentence.'''
print(s)
for tiers in [
[Similarity.HIGH],
[Similarity.MEDIUM],
[Similarity.LOW],
]:
o = Obscurator(similarities=tiers)
print(o.substitute(s, chance=1))
| [
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198
] | 2.515152 | 165 |
from SmartAnno.utils.ConfigReader import ConfigReader
from SmartAnno.gui.PreviousNextWidgets import PreviousNextHTML
from SmartAnno.gui.Workflow import Workflow
from SmartAnno.utils.IntroStep import IntroStep
ConfigReader('../conf/smartanno_conf2.json')
intro=IntroStep('<h2>Welcome to SmartAnno!</h2><h4>First, let's import txt data from a directory. </h4>',
name='intro')
wf = Workflow([intro,
PreviousNextHTML(name='finish',
description='<h3>Well done!</h3><h4>Now you have finished reviewing all the samples. ')
])
wf.start()
intro.navigate(intro.branch_buttons[0]) | [
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7,
600,
305,
13,
1671,
3702,
62,
4360,
27288,
58,
15,
12962
] | 2.674009 | 227 |
import os, sys
file = os.path.join(sys.path[0],"txt/2.txt")
print(printText(file))
| [
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] | 1.960784 | 51 |
import aiomeasures
import logging
from functools import wraps
log = logging.getLogger('discord')
| [
11748,
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"""
Copyright (c) 2015 Red Hat, Inc
All rights reserved.
This software may be modified and distributed under the terms
of the BSD license. See the LICENSE file for details.
Add arbitrary yum repo, specified by URL of repo file, to a list of
repos which should be injected into built image by the inject_yum_repo
plugin.
This plugin has to run _BEFORE_ the inject_yum_repo plugin, which
actually places the repo file in the build environment.
Example configuration to add content of repo file at URL:
{
"name": "add_yum_repo_by_url",
"args": {
"repourls": ["http://example.com/myrepo/myrepo.repo"]
}
}
"""
from atomic_reactor.plugin import PreBuildPlugin
from atomic_reactor.yum_util import YumRepo
| [
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13,
88,
388,
62,
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575,
388,
6207,
78,
628
] | 3.142857 | 231 |
import final_strategy_train
import baseline_strategy
import test
import time
import submissions
from os import path
TRAIN_START_NAME = submissions.STRATEGY_NAME
TRAIN_EPOCH_NUM = submissions.EPOCH_NUM
FILENAME = 'savedStrats/' + TRAIN_START_NAME + "_" + str(TRAIN_EPOCH_NUM) + ".pkl"
if path.exists(FILENAME):
print("Strategy File", FILENAME, "Already Exists!")
exit()
print("Loading Trainned Results to hit data")
startTime = time.time()
withHistWinningChanceFileName = TRAIN_START_NAME + "_historyChance.pkl"
hitRateFileName = TRAIN_START_NAME + "_hitRate.pkl"
final_strategy_train.readWinningChanceWithHistoryResults(withHistWinningChanceFileName)
final_strategy_train.readWinnningHitResults(hitRateFileName)
readFinishTime = time.time()
print("it took",(readFinishTime - startTime),"to read from pre-trained data")
final_strategy_train.final_strategy.producing_actual_result = True
final_strategy_train.saveStrategy(FILENAME,final_strategy_train.final_strategy)
endTime = time.time()
timeDiff = endTime - startTime
print("Generation Finished in",timeDiff,"seconds") | [
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4798,
7203,
8645,
341,
42931,
287,
1600,
2435,
28813,
553,
43012,
4943
] | 2.961957 | 368 |
from ..base_internode import BaseInternode
__all__ = ['NormCoor']
| [
6738,
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] | 3.136364 | 22 |
#!/usr/bin/python2.7
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setup(14, GPIO.OUT)
GPIO.output(14, GPIO.HIGH)
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2,
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] | 2.033333 | 60 |
import pytest
from txtble import IndeterminateWidthError, Txtble
BAD_STRING = "\x01"
ERRMSG = repr(BAD_STRING) + ": string has indeterminate width"
@pytest.mark.parametrize(
"s",
[
"\x0E",
"\x0F", # altcharset on/off
"\033[17;23H", # move cursor
"\a", # bell
"\b", # backspace
"!\b!",
"_\bx", # overstruck printing
"\x7F", # delete
"\033[H\033[J", # clear screen
"\033[?1049h", # altscreen on
"\033[?1049l", # altscreen off
],
)
| [
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220,
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30,
940,
2920,
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220,
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435,
912,
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319,
198,
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220,
220,
220,
220,
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220,
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58,
30,
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1303,
435,
912,
32060,
572,
198,
220,
220,
220,
16589,
198,
8,
628,
628,
628
] | 1.909091 | 286 |
from flask import Flask, render_template, jsonify, redirect
import pymongo
import scrape_mars
# Establish Flask app & mongodb connection
app = Flask(__name__)
conn = "mongodb://localhost:27017"
client = pymongo.MongoClient(conn)
# Connect to mongo db and mars_info collection
db = client.mars
collection = db.mars_info
@app.route("/")
@app.route("/scrape")
if __name__ == "__main__":
app.run(debug=True)
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] | 2.849315 | 146 |
import sys
import os.path
import re
buttonFileName = 'Button/gpio-keys'
print "Checking " + buttonFileName
if os.path.isfile(buttonFileName):
try:
print "Setting proper permissions on " + buttonFileName
os.chmod(buttonFileName, 0744)
except:
pass
apikeysFileName = 'Clock/ApiKeys.py'
wuapi_re = re.compile('\\s*wuapi\\s*=')
dsapi_re = re.compile('\\s*dsapi\\s*=')
print "Checking " + apikeysFileName
if (os.path.isfile(apikeysFileName)):
altered = False
foundds = False
newfile = ''
apikeys = open(apikeysFileName, "r")
for aline in apikeys:
if dsapi_re.match(aline):
foundds = True
if wuapi_re.match(aline):
print "Removing wuapi key from " + apikeysFileName
altered = True
else:
newfile += aline
apikeys.close()
if not foundds:
print "This version of PiClock requires a DarkSky api key."
print "https://darksky.net/dev"
print "Enter your DarkSky api key."
print "key:",
k = sys.stdin.readline()
k = k.strip()
if len(k) > 1:
newfile += "dsapi = '" + k + "'"
altered = True
if altered:
print "Writing Updated " + apikeysFileName
apikeys = open(apikeysFileName, "w")
apikeys.write(newfile)
apikeys.close()
else:
print "No changes made to " + apikeysFileName
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7,
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8,
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220,
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220,
220,
220,
220,
220,
2471,
522,
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13,
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3419,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
366,
2949,
2458,
925,
284,
366,
1343,
2471,
522,
893,
8979,
5376,
198
] | 2.148036 | 662 |
from typing import NamedTuple
## Security
class ChallengeInfo(NamedTuple):
"""
Attributes:
id (int): The id of the challenge
challenge (str): The challenge to complete
"""
id: int
challenge: str
| [
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4427,
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] | 2.785714 | 84 |
import prctl
import signal
import subprocess
from .output import Output
class FfmpegOutput(Output):
"""
The FfmpegOutput class allows an encoded video stream to be passed to FFmpeg for output,
meaning we can take advantange of FFmpeg's wide support for different output formats.
Optionally audio recording may be included, where this is handled entirely by FFmpeg.
Because we are prepared to accept whatever parameters and values that FFmpeg supports,
there is generally no checking up at this level. That may change over time as we
develop better expectations as to what can and cannot work.
For example, to record an mp4 file use FfmpegOutput("test.mp4")
To include audio in the recording, use FfmpegOutput("test.mp4", audio=True)
To record an MPEG2 transport stream, use FfmpegOutput("test.ts")
In fact, the output filename may include any string of options and an output
destination so long as these are meaningful to FFmpeg. So you might even try something
like FfmpegOutput("-f mpegts udp://<ip-addr>:<port>").
When audio recording is enabled, the following optional parameters are available:
audio_device - the name of the Pulse audio device ("default" is usually OK)
audio_sync - time offset (in seconds) to add to the audio stream to ensure
synchronisation with the video. So making this more negative will make the
audio earlier. In general this may need tweaking depending on the hardware
and configuration being used.
audio_samplerate, audio_codec, audio_bitrate - the usual audio parameters.
"""
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532,
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6678,
6597,
10007,
13,
628,
220,
220,
220,
37227,
198
] | 3.663636 | 440 |
from pathlib import Path
from pytest import fixture
from ..factset import Factset
from ..jinja_renderer import JinjaRenderer
@fixture
@fixture
| [
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] | 3.333333 | 45 |
import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
| [
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# PATH interpreter
# Copyright (c) 2003-04 Francis Rogers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
import sys
import os
class Path:
"""Implementation of the PATH programming language in Python."""
# This class uses the following data attributes:
# x: current x position
# y: current y position
# p: current memory cell pointer
# d: current direction
# s: whether the next cell is being skipped
# mem: array of memory cells
# prog: 2-dimensional array of characters that make up the program
# plugins: array of plug-in objects for the interpreter to use
# func_in: function to use for input
# func_out: function to use for output
# plug_lock: plugin the interpreter is locked on
# verbose: if true, enable debug messages
def __init__(self):
"""Initialize the class."""
self.PATH_DIRECTION_RIGHT = 1
self.PATH_DIRECTION_DOWN = 2
self.PATH_DIRECTION_LEFT = 3
self.PATH_DIRECTION_UP = 4
self.func_in = sys.stdin.read
self.func_out = sys.stdout.write
self.plug_lock = None
self.plugins = []
def __add__(self, x):
"""Step thru x symbols. Return false if end of program encountered."""
ret = 0
for i in range(x):
ret = self.step()
if not ret:
return ret
return ret
def addplugin(self, plugin):
"""This method is called internally by plugins.
(To add a plugin to the interpreter: 'execfile(plugin, {"glob_path":prog})') """
self.plugins.append(plugin)
def debug(self, msg):
"""Print a debug message."""
if self.verbose:
self.errprint("({},{}) {}".format(self.x, self.y, msg))
def dir2string(self, d):
"""Get the string representation of a direction id."""
if d == self.PATH_DIRECTION_RIGHT:
return "right"
elif d == self.PATH_DIRECTION_DOWN:
return "down"
elif d == self.PATH_DIRECTION_LEFT:
return "left"
elif d == self.PATH_DIRECTION_UP:
return "up"
def errprint(self, msg):
"""Print a message to stderr."""
sys.stderr.write(os.path.basename(sys.argv[0]) + ": " + msg + "\n")
def load_prog_file(self, filename):
"""Load a new program file into the interpreter."""
try:
with open(filename) as f:
self.prog = f.readlines()
if self.prog[0].startswith("#!"):
self.prog = self.prog[1:]
self.normalize_line_length()
except IOError:
self.errprint("can't open file '{}'".format(filename))
sys.exit(1)
self.reset()
def load_prog_array(self, progarray):
"""Load a new program directly into the interpreter."""
self.prog = progarray
self.normalize_line_length()
self.reset()
def lock(self, plugin):
"""Lock the interpreter on a specific plugin. (Use path.lock(None) to unlock.)"""
self.plug_lock = plugin
def redefine_io(self, infunc, outfunc):
"""Redefine the input and output functions used by the , and . symbols.
(Defaults are sys.stdin.read for input and sys.stdout.write for output."""
self.func_in = infunc
self.func_out = outfunc
def reset(self):
"""Reset the program state and restart the program."""
self.x = 0
self.y = 0
self.p = 0
self.d = self.PATH_DIRECTION_RIGHT
self.s = False
self.mem = [0]
self.verbose = False
for ny in range(len(self.prog)):
for nx in range(len(self.prog[ny])):
if self.prog[ny][nx] == '$':
self.y = ny
self.x = nx
def run(self):
"""Run the entire program."""
while not self.step():
pass
def runplugins(self):
"""Run all the loaded plugins on the current symbol."""
for plugin in self.plugins:
if not plugin.call(self):
return False
return True
def step(self):
"""
Step through a single symbol of the program.
Returns True if end of program encountered, False if
another step should be executed.
"""
cursym = self.prog[self.y][self.x]
if self.s:
self.s = False
elif self.plug_lock is not None:
self.plug_lock.call(self)
elif not self.runplugins():
pass
elif cursym == '$':
self.debug("Start")
elif cursym == '#':
self.debug("End")
return True
elif cursym == '!':
self.s = True
self.debug("Skip next symbol")
elif cursym == '}':
self.p += 1
if self.p > len(self.mem) - 1:
self.mem.append(0)
self.debug("New memory cell: {}".format(self.p))
elif cursym == '{':
if self.p > 0:
self.p -= 1
self.debug("New memory cell: {}".format(self.p))
elif cursym == '/':
if self.d == self.PATH_DIRECTION_RIGHT:
self.d = self.PATH_DIRECTION_UP
elif self.d == self.PATH_DIRECTION_DOWN:
self.d = self.PATH_DIRECTION_LEFT
elif self.d == self.PATH_DIRECTION_LEFT:
self.d = self.PATH_DIRECTION_DOWN
elif self.d == self.PATH_DIRECTION_UP:
self.d = self.PATH_DIRECTION_RIGHT
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == '\\':
if self.d == self.PATH_DIRECTION_RIGHT:
self.d = self.PATH_DIRECTION_DOWN
elif self.d == self.PATH_DIRECTION_DOWN:
self.d = self.PATH_DIRECTION_RIGHT
elif self.d == self.PATH_DIRECTION_LEFT:
self.d = self.PATH_DIRECTION_UP
elif self.d == self.PATH_DIRECTION_UP:
self.d = self.PATH_DIRECTION_LEFT
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == '>':
if self.mem[self.p] != 0:
self.d = self.PATH_DIRECTION_RIGHT
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == 'v':
if self.mem[self.p] != 0:
self.d = self.PATH_DIRECTION_DOWN
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == '<':
if self.mem[self.p] != 0:
self.d = self.PATH_DIRECTION_LEFT
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == '^':
if self.mem[self.p] != 0:
self.d = self.PATH_DIRECTION_UP
self.debug("New direction: {}".format(self.dir2string(self.d)))
elif cursym == '+':
self.mem[self.p] += 1
if self.mem[self.p] == 256:
self.mem[self.p] = 0
self.debug("Incremented memory cell {} to {}".format(self.p, self.mem[self.p]))
elif cursym == '-':
self.mem[self.p] -= 1
if self.mem[self.p] == -1:
self.mem[self.p] = 255
self.debug("Decremented memory cell {} to {}".format(self.p, self.mem[self.p]))
elif cursym == ',':
self.mem[self.p] = ord(self.func_in(1))
self.debug("Inputted {} to memory cell {}".format(self.mem[self.p], self.p))
elif cursym == '.':
self.func_out(chr(self.mem[self.p]))
self.debug("Outputted {} from memory cell {}".format(self.mem[self.p], self.p))
if self.d == self.PATH_DIRECTION_RIGHT:
self.x += 1
elif self.d == self.PATH_DIRECTION_DOWN:
self.y += 1
elif self.d == self.PATH_DIRECTION_LEFT:
self.x -= 1
elif self.d == self.PATH_DIRECTION_UP:
self.y -= 1
try:
self.prog[self.y][self.x]
if self.x < 0:
raise IndexError
if self.y < 0:
raise IndexError
except IndexError:
self.debug("Ran off the side")
return True
return False
| [
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1441,
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] | 2.140331 | 4,354 |
# Generated by Django 3.0.6 on 2020-05-28 19:33
from django.db import migrations, models
| [
2,
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"""Tests for 'layout' filters."""
from flask_extras.filters import layout
class TestBs3Col:
"""All tests for bs3 col function."""
def test_returns_right_width(self):
"""Test the return value for a valid type."""
assert layout.bs3_cols(1) == 12
assert layout.bs3_cols(2) == 6
assert layout.bs3_cols(3) == 4
assert layout.bs3_cols(4) == 3
assert layout.bs3_cols(5) == 2
assert layout.bs3_cols(6) == 2
def test_returns_right_width_bad_data(self):
"""Test the return value for an invalid type."""
assert layout.bs3_cols(None) == 12
assert layout.bs3_cols('foo') == 12
assert layout.bs3_cols(dict()) == 12
| [
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] | 2.28479 | 309 |
# -*- coding: utf-8 -*-
from nose.tools import *
import sys
import logging
from rainbow_logging_handler import RainbowLoggingHandler
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] | 3.292683 | 41 |
from Resources.required_modules import pymodules
pymodules.install(pymodules.presets.modules("mailer"))
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import smtplib
import ssl
# Repeated mailing to a single address
def mail_repeated_address(message_object, data_object, reciever_address, repeat_amount=1):
"""
:param message_object - mailman_message("test subject", "test body", Mailman.plain)
:param data_object - mailman_data("[email protected]", "password", repeated_amount=5)
:param reciever_address - The address to send the mail to
:param repeat_amount - The amount of times the email will be sent
"""
mailer = Mailman(data_object.sender, data_object.password, data_object.content_type)
for index in range(0, repeat_amount, 1):
mailer.send(reciever_address, \
mailer.format_mail(message_object.subject, message_object.message, reciever_address, message_object.content_type)) | [
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] | 3.03125 | 320 |
from graphSearch import GraphSearch
from DeepFeatures import DeepFeatures
import os
import glob
import json
<<<<<<< HEAD
=======
<<<<<<< HEAD
=======
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
import argparse
import numpy as np
import scipy
from skimage import transform
<<<<<<< HEAD
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
file_list_name = 'image_index_file.json'
file_list_path = os.path.join(os.getcwd(), file_list_name)
<<<<<<< HEAD
# TODO convert this to argument and move defaults to the parameters
# file.
self.feature_gen = DeepFeatures(feature_type={
'model': 'custom', 'input_layer': 'default', 'output_layer': 'fc2'})
=======
self.feature_gen = DeepFeatures(feature_type={
'model': 'custom', 'input_layer': 'default', 'output_layer': 'fc2'})
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
self.folder_name = image_folder_name
self.files = glob.glob(os.path.join(self.folder_name, '**/*.jpg'))
self.num_files = len(self.files)
print("Number of files", len(self.files))
<<<<<<< HEAD
=======
<<<<<<< HEAD
self.index_file_generator(self.files, force_generation=True)
self.feature_gen = DeepFeatures(feature_type={
'model': 'custom', 'input_layer': 'default', 'output_layer': 'fc2'})
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
def create_index(self, create_new=False):
""" Loads the image index from disk if it is available.
Args - create_new : If True creates a new index using images in input folder.
"""
self.feature_store = []
if create_new:
# Create the index file before creating the features and generating
# the index.
self.index_file_generator(self.files, force_generation=True)
for idx, file_name in enumerate(self.files):
image = self.feature_gen.read_image(file_name)
feature = self.feature_gen.get_feature(image)
self.feature_store.append(feature.ravel())
self.gs.create_index(np.array(feature_store, np.float32),
np.arange(len(self.num_files)))
self.gs.save_index()
else:
# Load index from disk if available.
self.gs.load_index()
def get_match(self, image_file):
""" Retrieve closest matching image given an input image_file
Args - image_file : Query image file.
return - match_idx : Index id of matched image.
self.files[match_idx[0]] : Filename of Matched image.
"""
image = self.feature_gen.read_image(image_file)
feature = self.feature_gen.get_feature(image)
<<<<<<< HEAD
match_idx = self.gs.knn(feature.ravel())[0][0]
print("Match id", match_idx)
return match_idx, self.files[match_idx[0]]
def index_file_loader(self):
""" Loads the image file list index from disk.
Image list index ensures that file modifications do not affect indexing.
Index files need to be generated.
"""
with open(file_list_path) as file:
self.file_list = json.loads(file.read())
=======
<<<<<<< HEAD
return self.gs.knn(feature.ravel())[0][0]
=======
match_idx = self.gs.knn(feature.ravel())[0][0]
print("Match id", match_idx)
return match_idx, self.files[match_idx[0]]
>>>>>>> Adding changes
<<<<<<< HEAD
=======
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
self.files = [os.path.join(self.folder_name, self.file_list['index'][
str(idx)]) for idx, i in enumerate(self.file_list['index'])]
self.num_files = len(self.files)
<<<<<<< HEAD
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
''' Function creates a json file to keep track of index keys that
correspond to particular images that are indexed. This is nesseary
to ensure that indexes created on one host can be reused on another
where the file structure is modified or has been tampered with. As long
as folder structure remains the same this indexing will hold. Missing
files can then be restructured. This index can later be moved to a datbase
entry.
Args :
filenames -> Names of the input files
force_generation -> force a new index file creation even if an
index file exists.
'''
if os.path.isfile(file_list_path) and not force_generation:
print('Index File found skipping file generation')
exit()
print('Generating file list.')
<<<<<<< HEAD
=======
<<<<<<< HEAD
file_list = {}
file_list['index'] = []
=======
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
if filenames == None:
filenames = self.files
file_list = {}
file_list['index'] = {}
<<<<<<< HEAD
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
for idx, i in enumerate(filenames):
''' Strip filepath to only classname and file id.
This will keep things sane when working across multiple systems.
As long as the file structure is maintained we should be good '''
<<<<<<< HEAD
file_list['index'][str(idx)] = '/'.join(i.split('/')[-2:])
=======
<<<<<<< HEAD
file_list['index'].append(
"{'" + str(idx) + "':'" + '/'.join(i.split('/')[-2:]) + "'}")
=======
file_list['index'][str(idx)] = '/'.join(i.split('/')[-2:])
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
with open(file_list_path, 'w') as outfile:
# save to Json file
json.dump(file_list, outfile)
print('File List saved to ' + file_list_path)
<<<<<<< HEAD
def batch_feature_store(self):
""" Function performs batch feature generation for indexing.
"""
=======
<<<<<<< HEAD
=======
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
self.index_file_loader()
gs = GraphSearch()
# TODO Remove all hard links.
print(len(self.files))
feature_store = []
# TODO Remove hardcoded value.
file_indexes = np.random.choice(len(self.files), self.num_files)
<<<<<<< HEAD
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
print(file_indexes.size)
# TODO Move batchsize to properties file.
batch_size = 128
image_batch = []
for idx, filenumber in enumerate(file_indexes):
print(idx)
image_decoded = scipy.ndimage.imread(
<<<<<<< HEAD
self.files[filenumber], flatten=False, mode=None)
=======
<<<<<<< HEAD
files[filenumber], flatten=False, mode=None)
=======
self.files[filenumber], flatten=False, mode=None)
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
# TODO Move hardcoded values to properties file.
image_decoded = transform.resize(image_decoded, [224, 224, 3])
image_decoded = np.expand_dims(image_decoded, axis=0)
if image_batch == []:
image_batch = image_decoded
else:
image_batch = np.concatenate(
(image_batch, image_decoded), axis=0)
if (not (idx) % (batch_size)) or (idx >= len(file_indexes) - 1):
print(image_batch.shape)
feature_store.extend(self.feature_gen.get_feature(image_batch))
image_batch = []
print('feature_store shape', np.array(feature_store).shape)
gs.create_index(np.array(feature_store, np.float32), file_indexes)
gs.save_index()
<<<<<<< HEAD
=======
query = gs.knn(feature_store[0])
print(query)
<<<<<<< HEAD
=======
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Split images from folder into test and validation')
parser.add_argument('--dataset_folder', dest='folder_name',
help='Folder with dataset')
parser.add_argument(
'--create_index_file', action='store_true', dest='create_index')
parser.add_argument(
'--generate_image_index', action='store_true', dest='generate_features')
args = parser.parse_args()
folder_name = args.folder_name
print(folder_name)
ig = ImageRetrieval(folder_name)
if args.create_index:
ig.index_file_generator(force_generation=True)
if args.generate_features:
ig.batch_feature_store()
ig.index_file_loader()
<<<<<<< HEAD
=======
>>>>>>> Adding changes
>>>>>>> c5b3a9dac6d0789cc8005df728bc69dff4b455b3
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25,
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220,
220,
220,
220,
220,
220,
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62,
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8,
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27,
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15630,
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67,
487,
19,
65,
30505,
65,
18,
198
] | 2.236683 | 3,980 |
import unittest
from selenium.common.exceptions import TimeoutException
from manga_py.base_classes.web_driver import make_driver, get_display
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# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'simple_threshold.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
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import re
| [
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] | 2.166667 | 6 |
import discord
from discord.ext import commands
from discord_slash import cog_ext
from discord_slash.utils.manage_commands import create_option | [
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"""Auth command."""
from .base import Base
from .. import settings, spotify
import spotipy
class Auth(Base):
"""Authenticate user"""
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import pysolr
from django.conf import settings
from django.template import Template, Context
from django.test import TestCase
from haystack import connections, connection_router
from haystack import indexes
from haystack.utils.loading import UnifiedIndex
from core.models import MockModel
from solr_tests.tests.solr_backend import clear_solr_index
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import tensorflow as tf
import numpy as np
class PositionalEncoding(object):
"""
In https://rubikscode.net/2019/08/05/transformer-with-python-and-tensorflow-2-0-attention-layers/,
he uses [sin(w*0), sin(w*1), ..., cos(w*0), cos(w*1), ...]
but in tensorflow tutorial https://www.tensorflow.org/tutorials/text/transformer
the vector is [sin(w*0), cos(w*0), sin(w*1), cos(w*1), ...]
The both are equivalent but we choose the second one, because the original paper proposes in this way
"""
if __name__ == '__main__':
positionalEncoding = PositionalEncoding(8,4)
print(positionalEncoding.get_positional_encoding()) | [
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361,
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834,
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220,
220,
220,
45203,
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18574,
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7,
23,
11,
19,
8,
198,
220,
220,
220,
3601,
7,
1930,
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27195,
7656,
13,
1136,
62,
1930,
1859,
62,
12685,
7656,
28955
] | 2.539924 | 263 |
#
# Copyright (c) 2021-2022, Alden Torres
#
# Licensed under the terms of the MIT license.
# Copy of the license at https://opensource.org/licenses/MIT
#
import json
import re
import subprocess
ecc_headers = ["util", "hash", "mac", "kdf", "ed25519", "ristretto255", "bls12_381",
"h2c", "oprf", "opaque", "sign", "pre"]
ecc_ignore = ["ecc_memzero", "ecc_bin2hex", "ecc_hex2bin", "ecc_malloc", "ecc_free",
"ecc_sign_bls12_381_Aggregate"]
gen_code(ecc_headers, ecc_ignore)
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198,
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220,
220,
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220,
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366,
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62,
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628,
628,
628,
198,
5235,
62,
8189,
7,
68,
535,
62,
50145,
11,
21399,
62,
46430,
8,
198
] | 2.297778 | 225 |
from enum import Enum
from typing import Dict, List, NewType
from palantir.clock import Clock
from palantir.types import Timestamp
Metrics = NewType("Metrics", Dict[Metric, Dict[Timestamp, List[float]]])
| [
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#
# ESnet Network Operating System (ENOS) Copyright (c) 2015, The Regents
# of the University of California, through Lawrence Berkeley National
# Laboratory (subject to receipt of any required approvals from the
# U.S. Dept. of Energy). All rights reserved.
#
# If you have questions about your rights to use or distribute this
# software, please contact Berkeley Lab's Innovation & Partnerships
# Office at [email protected].
#
# NOTICE. This Software was developed under funding from the
# U.S. Department of Energy and the U.S. Government consequently retains
# certain rights. As such, the U.S. Government has been granted for
# itself and others acting on its behalf a paid-up, nonexclusive,
# irrevocable, worldwide license in the Software to reproduce,
# distribute copies to the public, prepare derivative works, and perform
# publicly and display publicly, and to permit other to do so.
#
__author__ = 'lomax'
"""
This package provides generic type and basic implementation of OpenFlow support. Note tha it currently
does not provide any level of security, nor it is thread safe. This will have to be addressed in the future.
"""
from array import array
from layer2.common.utils import generateId
from layer2.common.api import Properties, Node
from layer2.common.mac import MACAddress
from layer2.common.utils import Logger
import binascii
import sys
debug = False
class Match(Properties):
"""
This is the class defining an OpenFlow match. It is a wrapper of Properties.
The base class defines the following key / values:
Layer2:
"in_port": Port ingress port on the swith
"dl_dst" : array('B') destination MAC
"vlan" : int VLAN
Other layers are TBD
"""
class Action(Properties):
"""
This class is the class defining an OpenFlow action. It is a wrapper of Properties.
The base class defines the following key / values:
Layer 2:
"dl_dst": array('B') rewrite the destination MAC with the provided MAC
"vlan": int rewrite the VLAN with the provided vlan
"out_port": Port egress ports
Other layers are TBD
"""
class FlowEntry:
"""
A 3-tuple consisting of a MAC address, VLAN, and port. This data structure is used for
various purposes such as indexing. It is similar to (but conceptually separate from) the
Match data structure.
"""
@staticmethod
class FlowMod(Properties):
"""
This class uniquely represent a flow mod.
"""
def __init__(self,scope,switch,match=None,name="",actions=[]):
"""
:param scope: Scope owner
:param switch: common.api.Node
:param match: Match
:param actions: Action
"""
Properties.__init__(self,name)
self.scope = scope
self.scopeowner = scope.owner
self.switch = switch
self.actions = actions
self.match = match
self.props['priority'] = 1 # only configured in TapEntryWithSrcMac
self.id = generateId()
if not name:
self.name = str(self.id)
@staticmethod
class Scope(Properties):
"""
This class is a Properties wrapper. The key/value pairs in the property is used to define the scope of control
an application wishes to have on a given network element.
"""
def __init__(self,name,switch,owner,props={}):
"""
:param name: str human readable name of the scope
:param switch: common.api.Node
:param owner: ScopeController controller that owns this scope
:param props: dict optional properties of the scope, such as ports, vlan, etc. See Layer2Scope for example.
"""
Properties.__init__(self,name,props)
self.owner = owner
self.id = generateId()
self.switch = switch
def overlaps(self, scope):
"""
Check if this scopes overlaps with the provided scope. It is expected that Scope implements will overwrite
this method.
:param scope: Scope
:returns True if scopes overlap, False otherwise
"""
return True
def isValidFlowMod(self, flowMod):
"""
Verifies if a flowMod is valid within the scope
:param flowMod: FlowMod
"""
return False
def includes(self,port):
"""
Returns True if the provided port is within the Scope. False otherwise
:param port: Port
:returns boolean
"""
return False
class ScopeEvent(Properties):
"""
This class define an event related to a scope sent by the controller to the application. Scope implementation
are responsible for implementing ScopeEvent as well. A ScopeEvent is a Properties, i.e. a dict of objects.
For instance, an OpenFlow event could countain a key "packet-in" matching an object containing the relevant
data. Implementing scopes freely define their own key/value pairs. All keys must be strings.
This base class defines basic keys as well as their meaning. Value definition is let to the implementation.
However the semantic of the key must be followed. This allow the consumer of the
event to understand what the event means without understand the actual details, or the opposite.
"closed": the scope has closed. If there is no "error" key/value in the event, the scope is gracefully closed.
"error": the event is the result of an error that affected the scope.
"changed": something has changed in the scope.
"""
def __init__(self,name,scope,props={}):
"""
:param name: str human readable name of the event
:param scope: Scope scope that is generating the event
:param props: properties of the event
"""
Properties.__init__(self,name,props={})
self.id = generateId()
class PacketInEvent(ScopeEvent):
"""
This class defines a PACKET_IN event. It adds the following key / value's to the ScopeEvent
"in_port": common.api.Port
"payload": opaque type, payload of the packet (Ethernet payload, minus Ethernet and 802.1q headers)
Layer 2
"dl_src": common.mac.MACAddress
"dl_dst": common.mac.MACAddress
"vlan" ": int VLAN
Although the payload is an opaque object, it is (in the common case) an object of a subclass of
org.opendaylight.controller.sal.packet.Packet or (if the higher layers cannot be parsed) an array
of unsigned bytes.
Other layers are TBD
"""
class PacketOut(Properties):
"""
This class implements a packet out.
"""
def __init__(self, scope, port, dl_src, dl_dst, etherType, vlan, payload, name=""):
"""
:param scope: Scope
:param port: Port
:param vlan: int
:param payload: opaque type, contents starting from the Ethernet frame payload (not including Ethernet or 802.1q headers)
In reality, payload is either an array of unsigned bytes or a subclass of
org.opendaylight.controller.sal.packet.Packet.
"""
super(PacketOut, self).__init__(name)
self.scope = scope
self.port = port
self.dl_src = dl_src
self.dl_dst = dl_dst
self.etherType = etherType
self.vlan = vlan
self.payload = payload
class ScopeOwner(Properties):
"""
This class must be extended by any application that controls a scope.
"""
def eventListener(self,event):
"""
The implementation of this class is expected to overwrite this method if it desires
to receive events from the controller such as PACKET_IN
:param event: ScopeEvent
"""
class OpenFlowSwitch(Node):
"""
This class represents an OpenFlowSwitch. It contains the list of flowmods that is set on the switch.
"""
def __init__(self, name, dpid, controller = None, builder = None, props = {}):
"""
Creates an OpenFlowSwitch instance.
:param controller (Controller) of this switch
:return:
"""
Node.__init__(self, name, builder, props)
self.dpid = dpid
self.controller = controller
self.props['controller'] = controller
self.flowMods = {}
self.scopes = {}
class Controller(object):
"""
This class defined the generic API of the client of an OpenFlow controller.
API for packet in and out not yet defined.
"""
def requestControl(self,scope):
"""
Request the control over the specified scope.
:param scope:
:return: True up success, False otherwise
"""
return False
def send(selfs,packet):
"""
:param packet: PacketOut
"""
class SimpleController(Controller):
"""
This class implements a simple controller. It implements some basic controller function but does not
implement the actual interaction with the switch or controller.
IMPORTANT: this currentl implementation relies on having static state. In otherwords, only one
controller extending SimpleController may run at the same time. This limitation should be fixed later.
"""
logger = Logger('SimpleController')
scopes = None
forbiddenScopes = None
switches = None
id = None
instance = None
def addSwitch(self,switch):
"""
Adds a switch to the list of switches this controller can manage
:param switch: OpenFlowSwitch
:return:
"""
SimpleController.switches[switch.dpid] = switch
def addScope(self, scope):
"""
Adds the scopes to the authorized set of scopes. In order to be accepted, a scope must not overlap
with any of the forbiden scopes, and not overlap with any of existing, authorized, scopes.
:param scope:
:return:
"""
for (x,s) in SimpleController.forbiddenScopes.items():
if s.overlaps(scope):
print "addScope error: ", scope
print "Overlaps with a forbidden port/vlan:"
print s
return False
for s in self.scopes.values():
if s.overlaps(scope):
print "addScope error: ", scope
print "Overlaps with a port/vlan that is already in another scope:"
print s
return False
if scope.id in self.scopes:
print "addScope error: ", scope
print "this scope has been already added"
return False
self.scopes[scope.id] = scope
return True
def addForbiddenScope(self,scope):
"""
Adds a scope that is forbidden to authorize any request
:param scope:
:return:
"""
print "not implemented yet"
def removeForbiddenScope(self,scope):
"""
Adds a scope that is forbidden scope
:param scope:
:return:
"""
print "not implemented yet"
def addFlowMod(self, flowMod):
"""
Implementation of SimpleController must implement this method
:param flowMod:
:return:
"""
return False
def delFlowMod(self, flowMod):
"""
Implementation of SimpleController must implement this method
:param flowMod:
:return:
"""
return False
def send(self,packet):
"""
Implementation of SimpleController must implement this method
:param self:
:param packet:
:return:
"""
return False
def getScope(self, port, vlan, mac):
"""
Here we hack by using (port, vid) instead of (port, vlan) as the index
for some specific ports ('SrcToDst.WAN' ports on HwSwitch) to fix the
issue that VPNs with different vids should have their own separated
scopes but share the same port and vlan.
"""
if port.props['type'].endswith('.WAN'):
key = '%s.%s.%d' % (port.props['node'].name, port.name, mac.getVid())
else:
key = '%s.%s.%d' % (port.props['node'].name, port.name, vlan)
if not key in self.scopeIndex:
# try to check if the port includes all vlans
key = port.name
if not key in self.scopeIndex:
SimpleController.logger.warning('(%s, %d, %r) not found in %r.scopeIndex' % (port.name, vlan, mac, self))
return None
return self.scopeIndex[key]
def dispatchPacketIn(self,packetIn):
"""
:param packetIn: PacketIn
:return:
"""
port = packetIn.props['in_port'].props['enosPort']
vlan = packetIn.props['vlan']
dl_dst = packetIn.props['dl_dst']
if vlan == 0:
SimpleController.logger.debug('vlan == 0 not interested...')
return
SimpleController.logger.info('recv packet %r' % packetIn)
scope = self.getScope(port, vlan, dl_dst)
print " prepare to dispatch to " + scope.name
if scope and scope.switch == port.get('enosNode') and scope.includes(packetIn):
scope.owner.eventListener(packetIn)
else:
SimpleController.logger.warning('No scope for %r', packetIn)
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] | 2.663033 | 4,953 |
from bme280 import Bme280
import busio
try:
import adafruit_dht
except ImportError:
print ("\033[91mError importing DHT code -- Are you running on an IoT device?\033[0m")
try:
import board
except NotImplementedError:
print ("\033[91mError importing board -- Are you running on an IoT device?\033[0m")
from adafruit_seesaw.seesaw import Seesaw
from gpiozero import LED
from gpiozero.pins.pigpio import PiGPIOFactory
from gpio_frequency import FrequencySignal
from iotdevice import IotDevice
from time import sleep
# TODO Brian: Add attributes for light sensor.
class RaspberryPi(IotDevice):
""" Class to interface with Raspberry Pi for
an Automated Irrigation System. This Raspberry Pi
setup actuates a solenoid valve that is collecting
a variety of sensor data (Moisture, Flow,
Humidity, Temperature).
Args:
gpio_relay: Integer. Indicates GPIO pin on Raspberry Pi
for relay to actuate solenoid valve or an LED for testing.
gpio_flow: Integer. Indicates GPIO pin on Raspberry Pi for flow sensor.
ip_address: Optional. A string. Indicates IP Address of Raspberry Pi.
By default None. If provided, then use PiGPIOFactory package
for remote GPIO control.
use_dht_11: Optional. A boolean. When set to True a DHT11 will be used
instead of the DHT22. By default False.
moisture: Optional. A String. "I2C" or "SIM" (for simulated device).
By default "I2C".
Attributes:
dht_sensor: DHT22 sensor to measure humidity and temperature. connected
to pin 18 for now.
moisture_sensor: connected to pin 3 and pin 2 for now
"""
def get_humidity_and_temperature(self):
""" Function to retrieve humidity and temperature data and then update model. """
temperature_f, humidity = None, None
while humidity is None and temperature_f is None:
try:
temperature_c = self.ht_sensor.temperature
temperature_f = temperature_c * (9 / 5) + 32
humidity = self.ht_sensor.humidity
except RuntimeError as err:
# DHT's are hard to read, keep going
sleep(2.0)
continue
except Exception as e:
print('Encountered error while trying to retrieve humidity and temeperature data: {0}'.format(e))
return (None, None)
# update model
self.set_humidity_and_temperature(humidity, temperature_f)
return super().get_humidity_and_temperature()
def get_moisture(self):
""" Function to retrieve moisture data and then update model """
try:
moist_val = self.moisture_sensor.moisture_read()
moist_val -= 300
moist_val *= 0.014
if moist_val < 0:
moist_val = 0
if moist_val > 10:
moist_val = 10
# upate model
self.set_moisture(moist_val)
except Exception as e:
print('Encountered error while trying to retrieve moisture data: {0}'.format(e))
return super().get_moisture()
def get_flow(self):
""" Funtion to retrieve flow data and then update model """
try:
# For our device you get 3.1Hz for each Liter/minute of water
rate = 3.1 # Adjust this based on testing your device.
self.set_flow(self.gpio_flow.measure_frequency() / rate)
except Exception as e:
print('Encountered error while trying to retrieve flow data: {0}'.format(e))
return super().get_flow()
def turn_valve_on(self):
""" Function to turn relay/LED on. """
try:
self.gpio_relay.on()
except Exception as e:
print('Encountered error while trying to turn relay on: {0}'.format(e))
# update model
super().turn_valve_on()
def turn_valve_off(self):
""" Function to turn relay/LED off. """
try:
self.gpio_relay.off()
except Exception as e:
print('Encountered error while trying to turn relay off: {0}'.format(e))
# update model
super().turn_valve_off()
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] | 2.403608 | 1,774 |
from pyabc.transition import NotEnoughParticles, LocalTransition, Transition
from pyabc import MultivariateNormalTransition
import pandas as pd
import numpy as np
import pytest
from pyabc import GridSearchCV
@pytest.fixture(params=[LocalTransition, MultivariateNormalTransition])
def test_argument_order(transition: Transition):
"""
Dataframes passed to the transition kernels are generated from dicts.
Order of parameter names is no guaranteed.
The Transition kernel has to take care of the correct sorting.
"""
df, w = data(20)
transition.fit(df, w)
test = df.iloc[0]
reversed_ = test[::-1]
# works b/c of even nr of parameters
assert (np.array(test) != np.array(reversed_)).all()
assert transition.pdf(test) == transition.pdf(reversed_)
def test_grid_search_two_samples_multivariate_normal():
"""
Supposed to run into problems b/c nr splits > then nr_samples
"""
cv = 5
m = MultivariateNormalTransition()
m_grid = GridSearchCV(m, {"scaling": np.logspace(-5, 1.5, 5)}, cv=cv,
n_jobs=1)
df, w = data(2)
m_grid.fit(df, w)
assert m_grid.cv == cv
def test_grid_search_single_sample_multivariate_normal():
"""
Supposed to run into problems b/c nr splits > then nr_samples
"""
cv = 5
m = MultivariateNormalTransition()
m_grid = GridSearchCV(m, {"scaling": np.logspace(-5, 1.5, 5)}, cv=cv,
n_jobs=1)
df, w = data(1)
m_grid.fit(df, w)
assert m_grid.cv == cv
def test_mean_coefficient_of_variation_sample_not_full_rank(
transition: Transition):
"""
This is a test created after I encountered this kind of bug
"""
n = 13
df = pd.DataFrame({"a": np.ones(n) * 2,
"b": np.ones(n)})
w = np.ones(len(df)) / len(df)
transition.fit(df, w)
transition.mean_cv()
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8,
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220,
220,
220,
6801,
13,
32604,
62,
33967,
3419,
198
] | 2.424396 | 787 |
import pytest
from sessionista.store import store
MY_ACTION = 'my_action'
| [
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] | 3.26087 | 23 |
import torch
def reg_loss_interaction(A, reg_lambda = 0.001, order=2):
""" Regularization loss for the off-diag elements of interaction matrix A """
mask = ~torch.eye(A.shape[0], dtype=torch.bool)
return reg_lambda * torch.linalg.norm(A[mask], order)
def reg_loss_r(r, reg_lambda = 0.001, order=2):
""" Regularization loss for the growth rate r """
return reg_lambda * torch.linalg.norm(r, order)
def reg_loss_eps(eps, reg_lambda = 0.001, order=2):
""" Regularization loss for the susceptibility eps """
return reg_lambda * torch.linalg.norm(eps, order) | [
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] | 2.898477 | 197 |
raio = float(input())
area = (raio * raio) * 3.14159
print("A=%0.4f" %area) | [
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# Copyright (c) Meta Platforms, Inc. and affiliates. All rights reserved.
from datetime import datetime
"""
Develop an experiment that measures and combination of the following features:
spatial_frequency
temporal_frequency
mean_luminance
eccentricity
field_angle
orientation
"""
constants = dict(
savefolder="./databases/",
timestamp=datetime.now().strftime("%Y-%m-%d_%H-%M-%S"),
config_path="./config_8d.ini",
seed=1,
)
base_params = {
"spatial_frequency": 2,
"orientation": 0,
"pedestal": 0.5,
"contrast": 0.75,
"temporal_frequency": 0,
"size": 10,
"angle_dist":0,
"eccentricity": 0,
}
psychopy_vars = dict(
setSizePix=[1680, 1050],
setWidth=47.475,
setDistance=57,
pre_duration_s=0.0,
stim_duration_s=5.0,
post_duration_s=1,
response_wait=2,
iti=0,
)
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11,
198,
220,
220,
220,
340,
72,
28,
15,
11,
198,
8,
198
] | 2.354749 | 358 |
from dataclasses import dataclass, field
from typing import List
__NAMESPACE__ = "urn:test"
@dataclass
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"""
********************************************************************************
* Name: model_file_database_connection_base.py
* Author: nswain
* Created On: June 05, 2018
* Copyright: (c) Aquaveo 2018
********************************************************************************
"""
class ModelDatabaseConnectionBase(object):
"""
Represents a Model Database.
"""
db_name = None
db_dir = None
db_id = None
def get_id(self):
"""
DB id getter.
"""
return self.db_id
def get_name(self):
"""
DB name getter.
"""
return self.db_name
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2116,
13,
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] | 2.856502 | 223 |
from .selection import selection_counter
| [
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] | 5.125 | 8 |
import anndata as ad
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import random
import warnings
from warnings import warn
def cluster_composition(adata, cluster, condition, xlabel='cell cluster',
ylabel='cell count', title=None, save=False):
"""
Deprecated. Use epi.pl.cell_composition instead.
"""
warnings.warn("Deprecated. Use epi.pl.cell_composition instead.")
contingency_table = pd.crosstab(
adata.obs[condition],
adata.obs[cluster],
margins = True
)
counts = []
p_part = []
index = 0
categories = sorted(list(set(adata.obs[cluster])))
for n in sorted(set(adata.obs[condition])):
#counts.append()
p_part.append(plt.bar(categories, contingency_table.iloc[index][0:-1].values))
index += 1
#Plots the bar chart
#plt.figsize(figsize=[6.4, 4.8])
plt.legend(tuple([p[0] for p in p_part]), tuple(sorted(set(adata.obs[condition]))))
plt.xlabel(xlabel, )
plt.ylabel(ylabel)
plt.title(title)
if save!=False:
if (save==True) or (save.split('.')[-1] not in ['png', 'pdf']):
plt.savefig('cluster_composition.png', dpi=300, bbox_inches="tight")
else:
plt.savefig('_'.join(['cluster_composition',save]), #format=save.split('.')[-1],
dpi=300, bbox_inches="tight")
plt.show()
def cell_composition(adata, obs_1, obs_2,
title='Cell composition per sample',
xlabel="",
ylabel="Number of cells",
loc_legend = 'best',
location_bbox=(1, 0, 0, 1),
save=None):
"""
Bar plots displaying the cell composition division between two Anndata obs categories.
adata : AnnData objct
obs_1 : adata.obs key 1
obs_2 : adata.obs key 2
title : [optional] title of the plot
loc_legend : location of the legend. Available are ``'upper left', 'upper right', 'lower left', 'lower right'``
or ``'upper center', 'lower center', 'center left', 'center right'``
bbox_to_anchor : tuple containing the location of the figure. Default (1, 0, 0, 1)
save : if not None, str corresponding to the output file name
"""
# create dataframe
df = pd.crosstab(adata.obs[obs_1], adata.obs[obs_2])
array = np.array(df)
x = df.columns.tolist()
y = df.index.tolist()
#colors for the plot
if obs_1+"_colors" in adata.uns.keys():
colors=adata.uns[obs_1+"_colors"]
else:
# select random colors
no_of_colors=len(y)
colors=["#"+''.join([random.choice('0123456789ABCDEF') for i in range(6)])
for j in range(no_of_colors)]
# plot bars in stack manner
previous_value = 0
index = 0
for n in range(len(y)):
plt.bar(x, array[index], bottom=previous_value, color=colors[index])
previous_value += array[index]
index += 1
# The strings
# ``'upper left', 'upper right', 'lower left', 'lower right'``
# place the legend at the corresponding corner of the axes/figure.
# The strings
# ``'upper center', 'lower center', 'center left', 'center right'``
# place the legend at the center of the corresponding edge of the
# axes/figure.
plt.xticks(x, rotation=90)
plt.legend(y, loc=loc_legend, bbox_to_anchor=location_bbox)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
if save != None :
plt.savefig(save, bbox_inches='tight')
plt.show() | [
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] | 2.227189 | 1,633 |
import sys
import os
import shutil
import subprocess
import multiprocessing
from multiprocessing import Pool
import pickle as pkl
import itertools
import numpy as np
from scipy import stats
import tensorflow as tf
# mute tensorflow information
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR) # or any {DEBUG, INFO, WARN, ERROR, FATAL}
if __name__ == '__main__':
for jump_prior in [-10]:
# Data specific variables
# Options of `(vocab_size, dim)`: (30000, 100), (3000, 10), (10000, 20)
MAX_VOCAB_SIZE = 30000
DIM = 100
DIFFUSION = 2 #
RAND_VOCAB = False
BEAM_SIZE = 1 # 8
JUMP_BIAS = jump_prior #-10
DATA_FOLDER = "./data-n-ckpt/gbooks"
IN_DATAPATH_TEMPLATE = DATA_FOLDER + '/train/npos_year%4d.bin.gz'
VAL_DATAPATH_TEMPLATE = DATA_FOLDER + '/test/npos_year%4d.bin.gz'
CHECKPOINT_FOLDER = (
'./v%d_d%d_b%d_p%d_diff%f_gbooks/' % (MAX_VOCAB_SIZE,
DIM,
BEAM_SIZE,
JUMP_BIAS,
DIFFUSION))
OUT_DIR_TEMPLATE = CHECKPOINT_FOLDER + 'gbooks%4d_b%s_s%s/' # year, beam_id, s_t
PREV_PARAM_PATH_TEMPLATE = CHECKPOINT_FOLDER + '%s_%4d.npy' # beam_mu/beam_std, year
BEAM_VAR_FOLDER = CHECKPOINT_FOLDER + '/beam_results/'
CONTEXT_VECTOR_CKPT_PATH = (
'./data-n-ckpt/gbooks' #### MODIFY
'/gbooks_entire_timesteps_v%d_d%d_subsample/checkpoint-10000' % (MAX_VOCAB_SIZE, DIM))
FIRST_GPU = 0
MAX_GPU = 2
os.mkdir(CHECKPOINT_FOLDER)
os.mkdir(BEAM_VAR_FOLDER)
def test_procedure(year):
'''Compute the predictive likelihood for each beam.
'''
proc = multiprocessing.current_process()
gpu_id = FIRST_GPU
out_file_path = BEAM_VAR_FOLDER + 'likelihood.txt'
mu_path = PREV_PARAM_PATH_TEMPLATE % ('beam_mu', year)
log_s_path = BEAM_VAR_FOLDER + 'beam_log_s_v%d_d%d_b%d_y%d.npy' % (MAX_VOCAB_SIZE, DIM, BEAM_SIZE, year)
context_vector_ckpt_path = CONTEXT_VECTOR_CKPT_PATH
val_datapath = VAL_DATAPATH_TEMPLATE % year
comargs = ['env', 'CUDA_VISIBLE_DEVICES=%d' % gpu_id,
'python', 'dsg_filtering_test.py',
'--rng_seed=123',
# '--rand_vocab',
# '--norm_npos',
'--vocab_size=%d' % MAX_VOCAB_SIZE,
'--dim=%d' % DIM,
'--context_vector_ckpt=%s' % context_vector_ckpt_path,
'--mu_path=%s' % mu_path,
'--log_s_path=%s' % log_s_path,
val_datapath, out_file_path]
rs = subprocess.run(comargs, check=True, stderr=subprocess.STDOUT)
def find_optimal_beam(scores, beam_size, discard_fraction = 1.0 / 3.0):
'''Return the indices of the `beam_size` optimal hypotheses.
Args:
scores: vector of scores (e.g., log probabilities or ELBOs) of each
hypothesis. Must have an even length and the two hypotheses with the
same parent always have to come together, i.e.,
scores = [
score of the first child of the first parent,
score of the first child of the second parent,
score of the first child of the third parent,
score of the second child of the first parent,
score of the second child of the second parent,
score of the second child of the third parent,
]
beam_size: the number of hyptheses that can be selected from candidates.
discard fraction: fraction of the lowest scroed hypotheses that will be
discarded before we even try to maximize diversity. More precisely,
this is the fraction that will be discarded *in the steady state*,
i.e., once `len(scores) == 2 * beam_size`. Must be between 0 and 0.5.
Returns:
An array of indices into argument `scores` that defines the optimal beam.
'''
assert 0 < discard_fraction
assert discard_fraction < 0.5
if beam_size >= len(scores):
return np.arange(len(scores))
num_parents = len(scores) // 2
assert scores.shape == (2 * num_parents,)
assert num_parents <= beam_size
# Keep track of the hypotheses' parents
parents = np.array(list(range(num_parents)) * 2).flatten()
# Discard `discard_fraction` of the hypotheses (except that we don't have to discard
# any hypothesis in the first few steps when there are only few hypotheses)
# num_keep = min(len(scores), round((1.0 - discard_fraction) * (2 * beam_size)))
num_keep = len(scores) - 2
candidate_indices = np.argsort(-scores)[:num_keep]
candidate_scores = scores[candidate_indices]
candidate_parents = parents[candidate_indices]
# Find out how many different parents are among the candidates (but at most `beam_size`).
max_num_parents = min(beam_size, len(set(candidate_parents)))
# Out of all ways to choose `beam_size` candidates, consider only the ones with
# `max_num_parents` different parents, and then take the one with maximum total score.
best_indices = None
best_score = float('-Inf')
resulting_beam_size = min(beam_size, len(candidate_scores))
for indices in itertools.combinations(range(len(candidate_scores)), resulting_beam_size):
indices = np.array(np.array(indices))
if len(set(candidate_parents[indices])) == max_num_parents:
score = candidate_scores[indices].sum()
if score > best_score:
best_indices = indices
best_score = score
return candidate_indices[best_indices]
def update_mu_std(ind, dir_1, dir_0, beam_mu, beam_std, beam_size):
"""dir_1 = ... # template with beam id as indicator
dir_0 = ...
"""
mu_1, std_1 = [], []
mu_0, std_0 = [], []
for b in range(beam_size):
checkpoint_path = tf.train.latest_checkpoint(dir_1 % b)
reader = tf.train.NewCheckpointReader(checkpoint_path)
_mean_1, _std_1 = reader.get_tensor('q/mean_u'), np.exp(reader.get_tensor('q/log_std_u'))
mu_1.append(_mean_1)
std_1.append(_std_1)
checkpoint_path = tf.train.latest_checkpoint(dir_0 % b)
reader = tf.train.NewCheckpointReader(checkpoint_path)
_mean_0, _std_0 = reader.get_tensor('q/mean_u'), np.exp(reader.get_tensor('q/log_std_u'))
mu_0.append(_mean_0)
std_0.append(_std_0)
mu_1, std_1 = np.asarray(mu_1, dtype=np.float32), np.asarray(std_1, dtype=np.float32) # (beam_size, vocab_size, emb_size)
mu_0, std_0 = np.asarray(mu_0, dtype=np.float32), np.asarray(std_0, dtype=np.float32)
extended_candidate_mu = np.concatenate((mu_1, mu_0), axis=0) # (2*beam_size, vocab_size, emb_size)
extended_beam_mu = np.tile(beam_mu, (2, 1, 1, 1)) # (2*beam_size, vocab_size, emb_size, T-1)
# process for each word
_beam_mu = []
for (extended_beam_mu_i, extended_candidate_mu_i, ind_i) in zip(extended_beam_mu.transpose(1, 0, 2, 3), extended_candidate_mu.transpose(1, 0, 2), ind.transpose()):
_beam_mu.append(np.expand_dims(np.concatenate((extended_beam_mu_i[ind_i, :, :], np.expand_dims(extended_candidate_mu_i[ind_i, :], axis=-1)), axis=-1), axis=1))
beam_mu = np.concatenate(_beam_mu, axis=1)
extended_candidate_std = np.concatenate((std_1, std_0), axis=0) # (2*beam_size, vocab_size, emb_size)
extended_beam_std = np.tile(beam_std, (2, 1, 1, 1)) # (2*beam_size, vocab_size, emb_size, T-1)
# process for each word
_beam_std = []
for (extended_beam_std_i, extended_candidate_std_i, ind_i) in zip(extended_beam_std.transpose(1, 0, 2, 3), extended_candidate_std.transpose(1, 0, 2), ind.transpose()):
_beam_std.append(np.expand_dims(np.concatenate((extended_beam_std_i[ind_i, :, :], np.expand_dims(extended_candidate_std_i[ind_i, :], axis=-1)), axis=-1), axis=1))
beam_std = np.concatenate(_beam_std, axis=1)
return beam_mu, beam_std
year_list = range(1900, 2000 + 1)
# Training
_, _ = dsg_beam_search(year_list, s_dim=MAX_VOCAB_SIZE, beam_size=BEAM_SIZE, jump_bias=JUMP_BIAS)
# Test procedure
# for year in year_list:
# print('Computing predictive likelihood for heldout data.')
# test_args = [[year]]
# with Pool(1) as p:
# p.starmap(test_procedure, test_args)
# p.close()
# print('Year %d done.' % year)
# sys.stdout.flush()
# tools
def delayed_update_procedure(beam_decision, beam_mu, num_years, update=True, beam_id=0, vocab_size=30000, emb_dim=100):
'''`beam_decision` should be a numpy ndarray of shape
`(beam_size, vocab_size, num_steps)`.
`beam_mu` is the inferred embeddings of shape
`(beam_size, vocab_size, emb_dim, num_steps)`.
`num_years` is `num_steps`.
It returns word embeddings of shape `(num_steps, vocab_size, emb_dim)`.
'''
embs = beam_mu[beam_id, ...].transpose(0, 2, 1)
if update:
embeddings = np.zeros((vocab_size, num_years, emb_dim))
# process each word
for i in range(vocab_size):
beam_decision_i = beam_decision[beam_id, i, :]
stay_start = 0
for j, d_i in enumerate(beam_decision_i):
if d_i == 1 and j > 0:
embeddings[i, stay_start:j, :] = np.tile(embs[i, j-1, :],
(j - stay_start, 1))
stay_start = j
embeddings[i, stay_start:, :] = np.tile(embs[i, -1, :],
(num_years - stay_start, 1))
embeddings = np.transpose(embeddings, (1, 0, 2))
else:
embeddings = embs
return embeddings
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# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import math
import statistics
from sktime.transformations.base import _PanelToPanelTransformer
from sktime.datatypes._panel._convert import from_nested_to_2d_array
from sktime.utils.validation.panel import check_X
class SlopeTransformer(_PanelToPanelTransformer):
"""
Class to perform the Slope transformation on a time series
dataframe. It splits a time series into num_intervals segments.
Then within each segment, it performs a total least
squares regression to extract the gradient of the segment.
Parameters
----------
num_intervals : int, number of approx equal segments
to split the time series into.
"""
def transform(self, X, y=None):
"""
Parameters
----------
X : a pandas dataframe of shape = [n_samples, num_dims]
The training input samples.
Returns
-------
df: a pandas data frame of shape = [num_intervals, num_dims]
"""
# Check the data
self.check_is_fitted()
X = check_X(X, coerce_to_pandas=True)
# Get information about the dataframe
n_timepoints = len(X.iloc[0, 0])
num_instances = X.shape[0]
col_names = X.columns
self._check_parameters(n_timepoints)
df = pd.DataFrame()
for x in col_names:
# Convert one of the columns in the dataframe to numpy array
arr = from_nested_to_2d_array(pd.DataFrame(X[x]), return_numpy=True)
# Calculate gradients
transformedData = []
for y in range(num_instances):
res = self._get_gradients_of_lines(arr[y])
transformedData.append(res)
# Convert to Numpy array
transformedData = np.asarray(transformedData)
# Add it to the dataframe
colToAdd = []
for i in range(len(transformedData)):
inst = transformedData[i]
colToAdd.append(pd.Series(inst))
df[x] = colToAdd
return df
def _get_gradients_of_lines(self, X):
"""
Function to get the gradients of the line of best fits
given a time series.
Parameters
----------
X : a numpy array of shape = [time_series_length]
Returns
-------
gradients : a numpy array of shape = [num_intervals].
It contains the gradients of the line of best fit
for each interval in a time series.
"""
# Firstly, split the time series into approx equal length intervals
splitTimeSeries = self._split_time_series(X)
gradients = []
for x in range(len(splitTimeSeries)):
gradients.append(self._get_gradient(splitTimeSeries[x]))
return gradients
def _get_gradient(self, Y):
"""
Function to get the gradient of the line of best fit given a
section of a time series.
Equation adopted from:
real-statistics.com/regression/total-least-squares
Parameters
----------
Y : a numpy array of shape = [interval_size]
Returns
-------
m : an int corresponding to the gradient of the best fit line.
"""
# Create a list that contains 1,2,3,4,...,len(Y) for the x coordinates.
X = [(i + 1) for i in range(len(Y))]
# Calculate the mean of both lists
meanX = statistics.mean(X)
meanY = statistics.mean(Y)
# Calculate the list (yi-mean(y))^2
yminYbar = [(y - meanY) ** 2 for y in Y]
# Calculate the list (xi-mean(x))^2
xminXbar = [(x - meanX) ** 2 for x in X]
# Sum them to produce w.
w = sum(yminYbar) - sum(xminXbar)
# Calculate the list (xi-mean(x))*(yi-mean(y))
temp = []
for x in range(len(X)):
temp.append((X[x] - meanX) * (Y[x] - meanY))
# Sum it and multiply by 2 to calculate r
r = 2 * sum(temp)
if r == 0:
# remove nans
m = 0
else:
# Gradient is defined as (w+sqrt(w^2+r^2))/r
m = (w + math.sqrt(w ** 2 + r ** 2)) / r
return m
def _split_time_series(self, X):
"""
Function to split a time series into approximately equal intervals.
Adopted from = https://stackoverflow.com/questions/2130016/
splitting-a-list-into-n-parts-of-approximately
-equal-length
Parameters
----------
X : a numpy array of shape = [time_series_length]
Returns
-------
output : a numpy array of shape = [num_intervals,interval_size]
"""
avg = len(X) / float(self.num_intervals)
output = []
beginning = 0.0
while beginning < len(X):
output.append(X[int(beginning) : int(beginning + avg)])
beginning += avg
return output
def _check_parameters(self, n_timepoints):
"""
Function for checking the values of parameters inserted into Slope.
Throws
------
ValueError or TypeError if a parameters input is invalid.
"""
if isinstance(self.num_intervals, int):
if self.num_intervals <= 0:
raise ValueError(
"num_intervals must have the value \
of at least 1"
)
if self.num_intervals > n_timepoints:
raise ValueError(
"num_intervals cannot be higher than \
subsequence_length"
)
else:
raise TypeError(
"num_intervals must be an 'int'. Found '"
+ type(self.num_intervals).__name__
+ "'instead."
)
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] | 2.141472 | 2,785 |
from .tracc import *
from .functions import *
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] | 3.285714 | 14 |
#!/usr/bin/env python
# TODO: description of this script
# BOB = controller
# CAB = cable
# COM = misc
# DEV = controller
# GPS = sensor
# LCD = actuator
# ROB = actuator
# SEN = sensor
# TOL = tool
# WRL = wireless
# KIT = (drop)
# LAB = (drop)
# PRT = misc
import flask_sqlalchemy
from iot_lab_inventory import db
from iot_lab_inventory.models import Part
sku_category = {'BOB': 'controller',\
'CAB': 'cable',\
'COM': 'misc',\
'DEV': 'controller',\
'GPS': 'sensor',\
'LCD': 'actuator',\
'KIT': 'kit',
'PRT': 'misc',\
'ROB': 'actuator',\
'SEN': 'sensor',\
'TOL': 'tool',\
'WRL': 'wireless'}
parts = Part.query.all()
for part in parts:
sku = part.sparkfun_id.split('-')[0]
if sku == 'LAB':
print('ignoring ' + part.name)
else:
print(part.name + ': ' + sku_category[sku])
part.category = sku_category[sku]
db.session.commit()
#sku = 'KIT' or 'LAB', drop from table
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__title__ = "stockist"
__description__ = ""
__version__ = "0.1.1"
__author__ = "Maina Nick"
__license__ = "DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE 2.0"
__copyright__ = "Copyright (C) 2018-Present Maina Nick"
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# coding: utf-8
# flake8: noqa
"""
Sunshine Conversations API
The version of the OpenAPI document: 9.4.5
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
__version__ = "9.4.6"
# import apis into sdk package
from sunshine_conversations_client.api.activities_api import ActivitiesApi
from sunshine_conversations_client.api.app_keys_api import AppKeysApi
from sunshine_conversations_client.api.apps_api import AppsApi
from sunshine_conversations_client.api.attachments_api import AttachmentsApi
from sunshine_conversations_client.api.clients_api import ClientsApi
from sunshine_conversations_client.api.conversations_api import ConversationsApi
from sunshine_conversations_client.api.custom_integration_api_keys_api import CustomIntegrationApiKeysApi
from sunshine_conversations_client.api.integrations_api import IntegrationsApi
from sunshine_conversations_client.api.messages_api import MessagesApi
from sunshine_conversations_client.api.o_auth_endpoints_api import OAuthEndpointsApi
from sunshine_conversations_client.api.participants_api import ParticipantsApi
from sunshine_conversations_client.api.switchboard_actions_api import SwitchboardActionsApi
from sunshine_conversations_client.api.switchboard_integrations_api import SwitchboardIntegrationsApi
from sunshine_conversations_client.api.switchboards_api import SwitchboardsApi
from sunshine_conversations_client.api.users_api import UsersApi
from sunshine_conversations_client.api.webhooks_api import WebhooksApi
# import ApiClient
from sunshine_conversations_client.api_client import ApiClient
from sunshine_conversations_client.configuration import Configuration
from sunshine_conversations_client.exceptions import OpenApiException
from sunshine_conversations_client.exceptions import ApiTypeError
from sunshine_conversations_client.exceptions import ApiValueError
from sunshine_conversations_client.exceptions import ApiKeyError
from sunshine_conversations_client.exceptions import ApiException
# import models into sdk package
from sunshine_conversations_client.model.accept_control_body import AcceptControlBody
from sunshine_conversations_client.model.action import Action
from sunshine_conversations_client.model.action_subset import ActionSubset
from sunshine_conversations_client.model.activity import Activity
from sunshine_conversations_client.model.activity_all_of import ActivityAllOf
from sunshine_conversations_client.model.activity_post import ActivityPost
from sunshine_conversations_client.model.activity_post_all_of import ActivityPostAllOf
from sunshine_conversations_client.model.activity_types import ActivityTypes
from sunshine_conversations_client.model.android import Android
from sunshine_conversations_client.model.android_all_of import AndroidAllOf
from sunshine_conversations_client.model.android_update import AndroidUpdate
from sunshine_conversations_client.model.android_update_all_of import AndroidUpdateAllOf
from sunshine_conversations_client.model.api_key import ApiKey
from sunshine_conversations_client.model.app import App
from sunshine_conversations_client.model.app_create_body import AppCreateBody
from sunshine_conversations_client.model.app_key import AppKey
from sunshine_conversations_client.model.app_key_create_body import AppKeyCreateBody
from sunshine_conversations_client.model.app_key_list_response import AppKeyListResponse
from sunshine_conversations_client.model.app_key_response import AppKeyResponse
from sunshine_conversations_client.model.app_list_filter import AppListFilter
from sunshine_conversations_client.model.app_list_response import AppListResponse
from sunshine_conversations_client.model.app_response import AppResponse
from sunshine_conversations_client.model.app_settings import AppSettings
from sunshine_conversations_client.model.app_sub_schema import AppSubSchema
from sunshine_conversations_client.model.app_update_body import AppUpdateBody
from sunshine_conversations_client.model.apple import Apple
from sunshine_conversations_client.model.apple_all_of import AppleAllOf
from sunshine_conversations_client.model.apple_update import AppleUpdate
from sunshine_conversations_client.model.attachment_delete_body import AttachmentDeleteBody
from sunshine_conversations_client.model.attachment_media_token_body import AttachmentMediaTokenBody
from sunshine_conversations_client.model.attachment_media_token_response import AttachmentMediaTokenResponse
from sunshine_conversations_client.model.attachment_response import AttachmentResponse
from sunshine_conversations_client.model.attachment_schema import AttachmentSchema
from sunshine_conversations_client.model.attachment_upload_body import AttachmentUploadBody
from sunshine_conversations_client.model.author import Author
from sunshine_conversations_client.model.author_webhook import AuthorWebhook
from sunshine_conversations_client.model.buy import Buy
from sunshine_conversations_client.model.carousel_message import CarouselMessage
from sunshine_conversations_client.model.carousel_message_display_settings import CarouselMessageDisplaySettings
from sunshine_conversations_client.model.client import Client
from sunshine_conversations_client.model.client_add_event import ClientAddEvent
from sunshine_conversations_client.model.client_add_event_all_of import ClientAddEventAllOf
from sunshine_conversations_client.model.client_add_event_all_of_payload import ClientAddEventAllOfPayload
from sunshine_conversations_client.model.client_association import ClientAssociation
from sunshine_conversations_client.model.client_create import ClientCreate
from sunshine_conversations_client.model.client_list_response import ClientListResponse
from sunshine_conversations_client.model.client_remove_event import ClientRemoveEvent
from sunshine_conversations_client.model.client_remove_event_all_of import ClientRemoveEventAllOf
from sunshine_conversations_client.model.client_remove_event_all_of_payload import ClientRemoveEventAllOfPayload
from sunshine_conversations_client.model.client_response import ClientResponse
from sunshine_conversations_client.model.client_type import ClientType
from sunshine_conversations_client.model.client_update_event import ClientUpdateEvent
from sunshine_conversations_client.model.client_update_event_all_of import ClientUpdateEventAllOf
from sunshine_conversations_client.model.client_update_event_all_of_payload import ClientUpdateEventAllOfPayload
from sunshine_conversations_client.model.confirmation import Confirmation
from sunshine_conversations_client.model.content import Content
from sunshine_conversations_client.model.conversation import Conversation
from sunshine_conversations_client.model.conversation_all_of import ConversationAllOf
from sunshine_conversations_client.model.conversation_create_body import ConversationCreateBody
from sunshine_conversations_client.model.conversation_create_event import ConversationCreateEvent
from sunshine_conversations_client.model.conversation_create_event_all_of import ConversationCreateEventAllOf
from sunshine_conversations_client.model.conversation_create_event_all_of_payload import ConversationCreateEventAllOfPayload
from sunshine_conversations_client.model.conversation_join_event import ConversationJoinEvent
from sunshine_conversations_client.model.conversation_join_event_all_of import ConversationJoinEventAllOf
from sunshine_conversations_client.model.conversation_join_event_all_of_payload import ConversationJoinEventAllOfPayload
from sunshine_conversations_client.model.conversation_leave_event import ConversationLeaveEvent
from sunshine_conversations_client.model.conversation_leave_event_all_of import ConversationLeaveEventAllOf
from sunshine_conversations_client.model.conversation_leave_event_all_of_payload import ConversationLeaveEventAllOfPayload
from sunshine_conversations_client.model.conversation_list_filter import ConversationListFilter
from sunshine_conversations_client.model.conversation_list_response import ConversationListResponse
from sunshine_conversations_client.model.conversation_message_delivery_channel_event import ConversationMessageDeliveryChannelEvent
from sunshine_conversations_client.model.conversation_message_delivery_channel_event_all_of import ConversationMessageDeliveryChannelEventAllOf
from sunshine_conversations_client.model.conversation_message_delivery_failure_event import ConversationMessageDeliveryFailureEvent
from sunshine_conversations_client.model.conversation_message_delivery_failure_event_all_of import ConversationMessageDeliveryFailureEventAllOf
from sunshine_conversations_client.model.conversation_message_delivery_payload import ConversationMessageDeliveryPayload
from sunshine_conversations_client.model.conversation_message_delivery_payload_destination import ConversationMessageDeliveryPayloadDestination
from sunshine_conversations_client.model.conversation_message_delivery_payload_external_messages import ConversationMessageDeliveryPayloadExternalMessages
from sunshine_conversations_client.model.conversation_message_delivery_payload_message import ConversationMessageDeliveryPayloadMessage
from sunshine_conversations_client.model.conversation_message_delivery_user_event import ConversationMessageDeliveryUserEvent
from sunshine_conversations_client.model.conversation_message_event import ConversationMessageEvent
from sunshine_conversations_client.model.conversation_message_event_all_of import ConversationMessageEventAllOf
from sunshine_conversations_client.model.conversation_message_event_all_of_payload import ConversationMessageEventAllOfPayload
from sunshine_conversations_client.model.conversation_postback_event import ConversationPostbackEvent
from sunshine_conversations_client.model.conversation_postback_event_all_of import ConversationPostbackEventAllOf
from sunshine_conversations_client.model.conversation_postback_event_all_of_payload import ConversationPostbackEventAllOfPayload
from sunshine_conversations_client.model.conversation_read_event import ConversationReadEvent
from sunshine_conversations_client.model.conversation_read_event_all_of import ConversationReadEventAllOf
from sunshine_conversations_client.model.conversation_read_event_all_of_payload import ConversationReadEventAllOfPayload
from sunshine_conversations_client.model.conversation_remove_event import ConversationRemoveEvent
from sunshine_conversations_client.model.conversation_remove_event_all_of import ConversationRemoveEventAllOf
from sunshine_conversations_client.model.conversation_remove_event_all_of_payload import ConversationRemoveEventAllOfPayload
from sunshine_conversations_client.model.conversation_response import ConversationResponse
from sunshine_conversations_client.model.conversation_truncated import ConversationTruncated
from sunshine_conversations_client.model.conversation_type import ConversationType
from sunshine_conversations_client.model.conversation_typing_event import ConversationTypingEvent
from sunshine_conversations_client.model.conversation_typing_event_all_of import ConversationTypingEventAllOf
from sunshine_conversations_client.model.conversation_typing_event_all_of_payload import ConversationTypingEventAllOfPayload
from sunshine_conversations_client.model.conversation_update_body import ConversationUpdateBody
from sunshine_conversations_client.model.custom import Custom
from sunshine_conversations_client.model.custom_all_of import CustomAllOf
from sunshine_conversations_client.model.custom_update import CustomUpdate
from sunshine_conversations_client.model.destination import Destination
from sunshine_conversations_client.model.device import Device
from sunshine_conversations_client.model.event_sub_schema import EventSubSchema
from sunshine_conversations_client.model.extra_channel_options import ExtraChannelOptions
from sunshine_conversations_client.model.extra_channel_options_messenger import ExtraChannelOptionsMessenger
from sunshine_conversations_client.model.field import Field
from sunshine_conversations_client.model.file_message import FileMessage
from sunshine_conversations_client.model.form_message import FormMessage
from sunshine_conversations_client.model.form_response_message import FormResponseMessage
from sunshine_conversations_client.model.image_message import ImageMessage
from sunshine_conversations_client.model.inline_object import InlineObject
from sunshine_conversations_client.model.instagram import Instagram
from sunshine_conversations_client.model.instagram_all_of import InstagramAllOf
from sunshine_conversations_client.model.instagram_update import InstagramUpdate
from sunshine_conversations_client.model.instagram_update_all_of import InstagramUpdateAllOf
from sunshine_conversations_client.model.integration import Integration
from sunshine_conversations_client.model.integration_api_key import IntegrationApiKey
from sunshine_conversations_client.model.integration_api_key_list_response import IntegrationApiKeyListResponse
from sunshine_conversations_client.model.integration_api_key_response import IntegrationApiKeyResponse
from sunshine_conversations_client.model.integration_id import IntegrationId
from sunshine_conversations_client.model.integration_list_filter import IntegrationListFilter
from sunshine_conversations_client.model.integration_list_response import IntegrationListResponse
from sunshine_conversations_client.model.integration_response import IntegrationResponse
from sunshine_conversations_client.model.integration_type import IntegrationType
from sunshine_conversations_client.model.integration_update import IntegrationUpdate
from sunshine_conversations_client.model.integration_update_base import IntegrationUpdateBase
from sunshine_conversations_client.model.ios import Ios
from sunshine_conversations_client.model.ios_all_of import IosAllOf
from sunshine_conversations_client.model.ios_update import IosUpdate
from sunshine_conversations_client.model.ios_update_all_of import IosUpdateAllOf
from sunshine_conversations_client.model.item import Item
from sunshine_conversations_client.model.line import Line
from sunshine_conversations_client.model.line_all_of import LineAllOf
from sunshine_conversations_client.model.line_update import LineUpdate
from sunshine_conversations_client.model.link import Link
from sunshine_conversations_client.model.links import Links
from sunshine_conversations_client.model.list_message import ListMessage
from sunshine_conversations_client.model.location_message import LocationMessage
from sunshine_conversations_client.model.location_message_coordinates import LocationMessageCoordinates
from sunshine_conversations_client.model.location_message_location import LocationMessageLocation
from sunshine_conversations_client.model.location_request import LocationRequest
from sunshine_conversations_client.model.mailgun import Mailgun
from sunshine_conversations_client.model.mailgun_all_of import MailgunAllOf
from sunshine_conversations_client.model.mailgun_update import MailgunUpdate
from sunshine_conversations_client.model.mailgun_update_all_of import MailgunUpdateAllOf
from sunshine_conversations_client.model.match_criteria import MatchCriteria
from sunshine_conversations_client.model.match_criteria_base import MatchCriteriaBase
from sunshine_conversations_client.model.match_criteria_mailgun import MatchCriteriaMailgun
from sunshine_conversations_client.model.match_criteria_mailgun_all_of import MatchCriteriaMailgunAllOf
from sunshine_conversations_client.model.match_criteria_messagebird import MatchCriteriaMessagebird
from sunshine_conversations_client.model.match_criteria_messagebird_all_of import MatchCriteriaMessagebirdAllOf
from sunshine_conversations_client.model.match_criteria_twilio import MatchCriteriaTwilio
from sunshine_conversations_client.model.match_criteria_twilio_all_of import MatchCriteriaTwilioAllOf
from sunshine_conversations_client.model.match_criteria_whatsapp import MatchCriteriaWhatsapp
from sunshine_conversations_client.model.match_criteria_whatsapp_all_of import MatchCriteriaWhatsappAllOf
from sunshine_conversations_client.model.message import Message
from sunshine_conversations_client.model.message_bird_update import MessageBirdUpdate
from sunshine_conversations_client.model.message_list_response import MessageListResponse
from sunshine_conversations_client.model.message_override import MessageOverride
from sunshine_conversations_client.model.message_override_apple import MessageOverrideApple
from sunshine_conversations_client.model.message_override_line import MessageOverrideLine
from sunshine_conversations_client.model.message_override_messenger import MessageOverrideMessenger
from sunshine_conversations_client.model.message_override_payload import MessageOverridePayload
from sunshine_conversations_client.model.message_override_whatsapp import MessageOverrideWhatsapp
from sunshine_conversations_client.model.message_post import MessagePost
from sunshine_conversations_client.model.message_post_response import MessagePostResponse
from sunshine_conversations_client.model.message_webhook import MessageWebhook
from sunshine_conversations_client.model.messagebird import Messagebird
from sunshine_conversations_client.model.messagebird_all_of import MessagebirdAllOf
from sunshine_conversations_client.model.messenger import Messenger
from sunshine_conversations_client.model.messenger_all_of import MessengerAllOf
from sunshine_conversations_client.model.messenger_update import MessengerUpdate
from sunshine_conversations_client.model.meta import Meta
from sunshine_conversations_client.model.offer_control_body import OfferControlBody
from sunshine_conversations_client.model.page import Page
from sunshine_conversations_client.model.participant import Participant
from sunshine_conversations_client.model.participant_join_body import ParticipantJoinBody
from sunshine_conversations_client.model.participant_leave_body import ParticipantLeaveBody
from sunshine_conversations_client.model.participant_leave_body_participant_id import ParticipantLeaveBodyParticipantId
from sunshine_conversations_client.model.participant_leave_body_user_external_id import ParticipantLeaveBodyUserExternalId
from sunshine_conversations_client.model.participant_leave_body_user_id import ParticipantLeaveBodyUserId
from sunshine_conversations_client.model.participant_list_response import ParticipantListResponse
from sunshine_conversations_client.model.participant_response import ParticipantResponse
from sunshine_conversations_client.model.participant_sub_schema import ParticipantSubSchema
from sunshine_conversations_client.model.participant_with_user_external_id import ParticipantWithUserExternalId
from sunshine_conversations_client.model.participant_with_user_id import ParticipantWithUserId
from sunshine_conversations_client.model.pass_control_body import PassControlBody
from sunshine_conversations_client.model.postback import Postback
from sunshine_conversations_client.model.postback_webhook import PostbackWebhook
from sunshine_conversations_client.model.prechat_capture import PrechatCapture
from sunshine_conversations_client.model.profile import Profile
from sunshine_conversations_client.model.quoted_message import QuotedMessage
from sunshine_conversations_client.model.quoted_message_external_message_id import QuotedMessageExternalMessageId
from sunshine_conversations_client.model.quoted_message_message import QuotedMessageMessage
from sunshine_conversations_client.model.referral import Referral
from sunshine_conversations_client.model.referral_details import ReferralDetails
from sunshine_conversations_client.model.reply import Reply
from sunshine_conversations_client.model.source import Source
from sunshine_conversations_client.model.source_webhook import SourceWebhook
from sunshine_conversations_client.model.status import Status
from sunshine_conversations_client.model.switchboard import Switchboard
from sunshine_conversations_client.model.switchboard_accept_control import SwitchboardAcceptControl
from sunshine_conversations_client.model.switchboard_accept_control_all_of import SwitchboardAcceptControlAllOf
from sunshine_conversations_client.model.switchboard_accept_control_all_of_payload import SwitchboardAcceptControlAllOfPayload
from sunshine_conversations_client.model.switchboard_accept_control_failure import SwitchboardAcceptControlFailure
from sunshine_conversations_client.model.switchboard_accept_control_failure_all_of import SwitchboardAcceptControlFailureAllOf
from sunshine_conversations_client.model.switchboard_accept_control_failure_all_of_payload import SwitchboardAcceptControlFailureAllOfPayload
from sunshine_conversations_client.model.switchboard_integration import SwitchboardIntegration
from sunshine_conversations_client.model.switchboard_integration_create_body import SwitchboardIntegrationCreateBody
from sunshine_conversations_client.model.switchboard_integration_list_response import SwitchboardIntegrationListResponse
from sunshine_conversations_client.model.switchboard_integration_response import SwitchboardIntegrationResponse
from sunshine_conversations_client.model.switchboard_integration_update_body import SwitchboardIntegrationUpdateBody
from sunshine_conversations_client.model.switchboard_integration_webhook import SwitchboardIntegrationWebhook
from sunshine_conversations_client.model.switchboard_list_response import SwitchboardListResponse
from sunshine_conversations_client.model.switchboard_offer_control import SwitchboardOfferControl
from sunshine_conversations_client.model.switchboard_offer_control_all_of import SwitchboardOfferControlAllOf
from sunshine_conversations_client.model.switchboard_offer_control_all_of_payload import SwitchboardOfferControlAllOfPayload
from sunshine_conversations_client.model.switchboard_offer_control_failure import SwitchboardOfferControlFailure
from sunshine_conversations_client.model.switchboard_pass_control import SwitchboardPassControl
from sunshine_conversations_client.model.switchboard_pass_control_all_of import SwitchboardPassControlAllOf
from sunshine_conversations_client.model.switchboard_pass_control_all_of_payload import SwitchboardPassControlAllOfPayload
from sunshine_conversations_client.model.switchboard_pass_control_failure import SwitchboardPassControlFailure
from sunshine_conversations_client.model.switchboard_response import SwitchboardResponse
from sunshine_conversations_client.model.switchboard_update_body import SwitchboardUpdateBody
from sunshine_conversations_client.model.target import Target
from sunshine_conversations_client.model.telegram import Telegram
from sunshine_conversations_client.model.telegram_all_of import TelegramAllOf
from sunshine_conversations_client.model.telegram_update import TelegramUpdate
from sunshine_conversations_client.model.template_message import TemplateMessage
from sunshine_conversations_client.model.text_message import TextMessage
from sunshine_conversations_client.model.twilio import Twilio
from sunshine_conversations_client.model.twilio_all_of import TwilioAllOf
from sunshine_conversations_client.model.twilio_update import TwilioUpdate
from sunshine_conversations_client.model.twitter import Twitter
from sunshine_conversations_client.model.twitter_all_of import TwitterAllOf
from sunshine_conversations_client.model.twitter_update import TwitterUpdate
from sunshine_conversations_client.model.user import User
from sunshine_conversations_client.model.user_all_of import UserAllOf
from sunshine_conversations_client.model.user_create_body import UserCreateBody
from sunshine_conversations_client.model.user_merge_event import UserMergeEvent
from sunshine_conversations_client.model.user_merge_event_all_of import UserMergeEventAllOf
from sunshine_conversations_client.model.user_merge_event_all_of_payload import UserMergeEventAllOfPayload
from sunshine_conversations_client.model.user_merge_event_all_of_payload_merged_clients import UserMergeEventAllOfPayloadMergedClients
from sunshine_conversations_client.model.user_merge_event_all_of_payload_merged_conversations import UserMergeEventAllOfPayloadMergedConversations
from sunshine_conversations_client.model.user_merge_event_all_of_payload_merged_users import UserMergeEventAllOfPayloadMergedUsers
from sunshine_conversations_client.model.user_response import UserResponse
from sunshine_conversations_client.model.user_truncated import UserTruncated
from sunshine_conversations_client.model.user_update_body import UserUpdateBody
from sunshine_conversations_client.model.viber import Viber
from sunshine_conversations_client.model.viber_all_of import ViberAllOf
from sunshine_conversations_client.model.viber_update import ViberUpdate
from sunshine_conversations_client.model.web import Web
from sunshine_conversations_client.model.web_all_of import WebAllOf
from sunshine_conversations_client.model.web_update import WebUpdate
from sunshine_conversations_client.model.web_update_all_of import WebUpdateAllOf
from sunshine_conversations_client.model.webhook import Webhook
from sunshine_conversations_client.model.webhook_body import WebhookBody
from sunshine_conversations_client.model.webhook_create_body import WebhookCreateBody
from sunshine_conversations_client.model.webhook_list_response import WebhookListResponse
from sunshine_conversations_client.model.webhook_response import WebhookResponse
from sunshine_conversations_client.model.webhook_sub_schema import WebhookSubSchema
from sunshine_conversations_client.model.webview import Webview
from sunshine_conversations_client.model.whats_app_update import WhatsAppUpdate
from sunshine_conversations_client.model.whats_app_update_all_of import WhatsAppUpdateAllOf
from sunshine_conversations_client.model.whatsapp import Whatsapp
from sunshine_conversations_client.model.whatsapp_all_of import WhatsappAllOf
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1324,
62,
439,
62,
1659,
1330,
28556,
1324,
3237,
5189,
628
] | 3.843559 | 6,699 |
__version__ = "1.021"
try:
from .client import Client
from .order import Order
except ImportError:
pass
# OANDA API URLS
SANDBOX = (
"http://api-sandbox.oanda.com",
"http://stream-sandbox.oanda.com"
)
PRACTICE = (
"https://api-fxpractice.oanda.com",
"https://stream-fxpractice.oanda.com"
)
TRADE = (
"https://api-fxtrade.oanda.com",
"https://stream-fxtrade.oanda.com"
)
| [
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5532,
12,
69,
742,
27585,
13,
78,
5282,
13,
785,
1,
198,
8,
198
] | 2.303371 | 178 |
import sys
if __name__ == "__main__":
if len(sys.argv) == 2:
print(max_number(n=sys.argv[1]))
else:
sys.exit(1) | [
11748,
25064,
628,
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8,
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25,
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220,
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220,
220,
220,
220,
220,
220,
220,
25064,
13,
37023,
7,
16,
8
] | 1.864865 | 74 |
import random
import re
import pandas as pd
from sklearn.model_selection import train_test_split
"""
Translate txt into json
"""
# Lowercase, trim, and remove non-letter characters
if __name__ == "__main__":
src_path, trg_path = 'data/hard_pc_src.txt', 'data/hard_pc_tar.txt'
raw_data = processData(src_path, trg_path, 'ISO-8859-1')
df = pd.DataFrame(raw_data, columns=['Src', 'Trg'])
# split train and test
# In 2019, using 20% for test, using 80% for 5 fold cross-validation
train_data, test_data = train_test_split(df, test_size=0.2)
# save the data in json type
train_data.to_json('data/train.json', orient='records', lines=True)
test_data.to_json('data/test.json', orient='records', lines=True)
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62,
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3256,
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3256,
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13,
1462,
62,
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14,
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13,
17752,
3256,
11367,
11639,
8344,
3669,
3256,
3951,
28,
17821,
8,
198
] | 2.62807 | 285 |
from custom.ilsgateway.comparison_reports import ProductsCompareReport, LocationsCompareReport, \
WebUsersCompareReport, SMSUsersCompareReport
from custom.ilsgateway.tanzania.reports.alerts import AlertReport
from custom.ilsgateway.tanzania.reports.dashboard_report import DashboardReport
from custom.ilsgateway.tanzania.reports.delivery import DeliveryReport
from custom.ilsgateway.tanzania.reports.randr import RRreport
from custom.ilsgateway.tanzania.reports.facility_details import FacilityDetailsReport
from custom.ilsgateway.tanzania.reports.stock_on_hand import StockOnHandReport
from custom.ilsgateway.tanzania.reports.supervision import SupervisionReport
CUSTOM_REPORTS = (
('Custom reports', (
DashboardReport,
AlertReport,
StockOnHandReport,
RRreport,
FacilityDetailsReport,
DeliveryReport,
SupervisionReport,
ProductsCompareReport,
LocationsCompareReport,
WebUsersCompareReport,
SMSUsersCompareReport
)),
)
# For QA purposes it should be set to true.
TEST = True
| [
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900,
284,
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198
] | 3.011173 | 358 |
import sys
import pickle
from tqdm import tqdm
sys.path.append(sys.path[0].rsplit('/', 1)[0])
from elementary_step_om.chem import Fragment
from elementary_step_om.external_calculation.xtb_calculations import xTBCalculator
from elementary_step_om.external_calculation.gaussian_calculations import GaussianCalculator
if __name__ == "__main__":
exteral_xtb_in_g16 = "/home/koerstz/github/elementary_step_om/scripts/gaussian_xtb_external.py"
ts_calc = GaussianCalculator(
kwds="opt=(ts,calcall,noeigentest) pm3",
properties=['structure', 'energy', 'frequencies'],
external_script=None,
charge=0,
spin=1
)
irc_calc = GaussianCalculator(
kwds="irc=(calcfc, recalc=10, maxpoints=50, stepsize=5) pm3",
properties=['irc_structure', 'energy'],
external_script=None,
charge=0,
spin=1
)
refine_calc = xTBCalculator(
xtb_kwds="--opt loose",
charge=0,
spin=1
)
input_file = sys.argv[1]
with open(input_file, "rb") as f:
reactions = pickle.load(f)
print(f"Total number of reactions: {len(reactions)} \n")
for reaction in tqdm(reactions):
#print("new")
reaction.irc_check_ts(ts_calc, irc_calc, refine_calc)
#print(reaction.__dict__)
#print()
#print()
with open(input_file.split('.')[0] + "_output.pkl", 'wb') as f:
pickle.dump(reactions, f)
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220,
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3419,
198,
220,
220,
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7,
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62,
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2637,
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15,
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355,
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25,
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220,
220,
220,
220,
2298,
293,
13,
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7,
260,
4658,
11,
277,
8,
198
] | 2.109843 | 701 |
# Copyright (c) 2021 Microsoft
#
# This software is released under the MIT License.
# https://opensource.org/licenses/MIT
import json
import logging
import os
import tempfile
from enum import Enum
from pathlib import Path
from typing import Literal, Tuple, Union
import lightgbm
import mlflow
import numpy as np
import pandas as pd
import typer
from azureml.core import Model, Run, Workspace
from azureml.exceptions import ModelNotFoundException, WebserviceException
from sklearn import metrics
METADATA_JSON = "metadata.json"
RESOURCE_DOES_NOT_EXIST = "RESOURCE_DOES_NOT_EXIST"
logger = logging.getLogger("evaluate.py")
logger.setLevel(logging.INFO)
logger.addHandler(logging.StreamHandler())
def read_dataframe(input_path: Path) -> pd.DataFrame:
"""
Read a file (CSV or Parquet) and return a dataframe.
If a directory is passed, look for parquet, if not available, look for CSV
(Based on file extension)
"""
if input_path.is_dir():
parquet_files = list(input_path.glob("*.parquet"))
csv_files = list(input_path.glob("*.csv"))
if len(parquet_files) > 0:
input_path = parquet_files[0]
elif len(csv_files) > 0:
input_path = csv_files[0]
else:
raise FileNotFoundError("No CSV or Parquet files found")
file_suffix = input_path.suffix
if file_suffix == ".parquet":
df = pd.read_parquet(input_path)
elif file_suffix == ".csv":
df = pd.read_csv(input_path)
else:
raise FileNotFoundError("File is not CSV or Parquet")
return df
def write_indicator_file(
output_folder: str,
register_model: bool
) -> None:
"""Write an empty file in the output path to indicated if the model should be registered"""
output_path = Path(output_folder)
filename = "REGISTER" if register_model else "SKIP"
(output_path / filename).touch()
def get_model_metrics(model: lightgbm.Booster, data: lightgbm.Dataset, model_name: str) -> dict:
"""Construct a dictionary of metrics for the model"""
predictions = model.predict(data.data)
fpr, tpr, thresholds = metrics.roc_curve(data.label, predictions)
best_threshold = predict_best_threshold(fpr, tpr, thresholds)
f1_score = metrics.f1_score(data.label, np.where(
predictions < best_threshold, 0, 1))
model_metrics = {"auc": metrics.auc(fpr, tpr),
"f1-score": f1_score}
logger.info(f"{model_name} Metrics {model_metrics}")
return model_metrics
def compare_models(
champion_model: lightgbm.Booster,
challenger_model: lightgbm.Booster,
valid_df: pd.DataFrame,
comparison_metric: Literal["any", "all", "f1_score", "auc"] = "any"
) -> bool:
"""
A function to compare the performance of the Champion and Challenger models
on the validation dataset comparison metrics
"""
comparison_metrics_directions = {"f1-score": ModelDirection.HIGHER_BETTER,
"auc": ModelDirection.HIGHER_BETTER,
"accuracy": ModelDirection.HIGHER_BETTER}
# Prep datasets
features = valid_df.drop(['target', 'id'], axis=1, errors="ignore")
labels = np.array(valid_df['target'])
valid_dataset = lightgbm.Dataset(data=features, label=labels)
# Calculate Champion and Challenger metrics for each
champion_metrics = get_model_metrics(champion_model, valid_dataset, "Champion")
challenger_metrics = get_model_metrics(challenger_model, valid_dataset, "Challenger")
if comparison_metric not in ['any', 'all']:
logger.info(f"Champion performance for {comparison_metric}: {champion_metrics[comparison_metric]}")
logger.info(f"Challenger performance for {comparison_metric}: {challenger_metrics[comparison_metric]}")
register_model = challenger_metric_better(champ_metrics=champion_metrics,
challenger_metrics=challenger_metrics,
metric_name=comparison_metric,
direction=comparison_metrics_directions[comparison_metric])
else:
comparison_results = {metric: challenger_metric_better(champ_metrics=champion_metrics,
challenger_metrics=challenger_metrics,
metric_name=metric,
direction=comparison_metrics_directions[metric])
for metric in champion_metrics.keys()}
if comparison_metric == "any":
register_model = any(comparison_results.values())
if register_model:
positive_results = [metric for metric, result in comparison_results.items() if result]
for metric in positive_results:
logger.info(f"Challenger Model performed better for '{metric}' on validation data")
else:
logger.info("Champion model performed better for all metrics on validation data")
else:
register_model = all(comparison_results.values())
if register_model:
logger.info("Challenger model performed better on all metrics on validation data")
else:
negative_ressults = [metric for metric, result in comparison_results.items() if not result]
for metric in negative_ressults:
logger.info(f"Champion Model performed better for '{metric}' on validation data")
return register_model
def load_champion_model(
model_name: str,
register_model: bool
) -> Tuple[Union[lightgbm.Booster, None], bool]:
"""
Load the champion model as the currently registered model of 'model_name' and the highest version number
"""
run = Run.get_context()
ws: Workspace = run.experiment.workspace
# Load Champion Model
# If the champion model doesn't exist, recommend register model
try:
champ_temp_dir = tempfile.mkdtemp()
champion_model = Model(ws, model_name)
champion_model.download(target_dir=champ_temp_dir)
champion_model = mlflow.lightgbm.load_model(os.path.join(champ_temp_dir, "model"))
except (WebserviceException, ModelNotFoundException) as exp:
logger.info(f"No model named '{model_name}' currently in registry - recommending model registration")
logger.info(f"Exception Raised: {exp.message}")
register_model = True
champion_model = None
return champion_model, register_model
def load_challenger_model(
model_name: str,
run_id: str
) -> lightgbm.Booster:
"""Load challenger model from this Pipeline"""
challenger_model_uri = f"runs:/{run_id}/model"
challenger_model = mlflow.lightgbm.load_model(challenger_model_uri)
return challenger_model
def main(
model_metadata: Path = typer.Option(..., exists=True, dir_okay=True, file_okay=False),
recommendation_folder: Path = typer.Option(..., exists=False, dir_okay=True, file_okay=False),
validation_data_path: Path = typer.Option(..., exists=True, dir_okay=True, file_okay=True),
):
"""
Download the currently registered model from AML Model Registry and compare the model performance
on a standard dataset.
The "Champion" model - is the model currently registered and in production. The "Challenger" model is the model
currently
If the challenger model wins, then promote the model to production.
Otherwise, keep the champion model in production.
"""
# TODO: Implement OpenCensus and Shell logging
recommendation_folder.mkdir(parents=True, exist_ok=True)
register_model = False
# Load the RunID and Model name from the model training step
run_id, model_name = load_model_metadata(model_metadata)
# Load champion model from the Model Registry
champion_model, register_model = load_champion_model(model_name, register_model)
# Load the challenger model from 'Train Model' step
challenger_model = load_challenger_model(model_name, run_id)
valid_df = read_dataframe(validation_data_path)
# If the champion model exists, then run the compare model function
if champion_model is not None:
register_model = compare_models(champion_model=champion_model,
challenger_model=challenger_model,
valid_df=valid_df,
comparison_metric="all")
logger.info(f"Is Model Registration Recommended?: {register_model}")
# Write the indicator file to pass along to the "Register Model" step.
# The folder will either contain an empty file that says "REGISTER" or an empty file that says "SKIP"
write_indicator_file(output_folder=recommendation_folder, register_model=register_model)
if __name__ == "__main__":
typer.run(main)
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7,
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198
] | 2.484873 | 3,636 |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import asyncio
import importlib.resources
import logging
import os
import shlex
import subprocess
import sys
import tempfile
from contextlib import asynccontextmanager, contextmanager
from dataclasses import dataclass
from itertools import chain
from pathlib import Path
from typing import AsyncContextManager, ContextManager, Iterable, Optional, Union
from fs_image.vm.guest_agent import QemuError, QemuGuestAgent
from fs_image.vm.share import Share, process_shares
logger = logging.getLogger("vm")
@dataclass(frozen=True)
@contextmanager
@asynccontextmanager
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] | 3.525114 | 219 |
## All icons in Laelaps package.
__all__ = [
'BotBwdIcon.png',
'BotFwdIcon.png',
'BotLeftIcon.png',
'BotRightIcon.png',
'BotStopIcon.png',
'LaelapsAlarmsIcon.png',
'LaelapsCamIcon.png',
'LaelapsImuIcon.png',
'LaelapsPanelIcon.png',
'LaelapsRangeIcon.png',
'LaelapsTwistIcon.png',
'ROSIcon.png',
'icon_alarm.png',
'icon_camera.png',
'icon_close.png',
'icon_close_32.png',
'icon_bot_back.png',
'icon_bot_brake.png',
'icon_bot_forward.png',
'icon_bot_range.png',
'icon_bot_spin_left.png',
'icon_bot_spin_right.png',
'icon_bot_twist.png',
'icon_estop.png',
'icon_estop_reset.png',
'icon_exit.png',
'icon_info.png',
'icon_laelaps_logo.png',
'icon_led_dark_16.png',
'icon_led_green_16.png',
'icon_led_red_16.png',
'icon_led_yellow_16.png',
'icon_pause.png',
'icon_settings.png',
]
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] | 2.174807 | 389 |
from flask import Flask
from flask import render_template
from api.user_api import user_api
from api.audit_api import audit_api
from api.sns_api import sns_api
from errors import ParameterError, DataError
from utilities import response
from constants import APIStatus
from batch.notification import apns_push
app = Flask(__name__)
app.config.from_pyfile('settings.cfg')
app.register_blueprint(user_api)
app.register_blueprint(audit_api)
app.register_blueprint(sns_api)
@app.route('/')
@app.route('/policy')
@app.route('/terms')
@app.route('/api/version/')
@app.route('/api/notification/')
@app.errorhandler(404)
@app.errorhandler(ParameterError)
@app.errorhandler(DataError) | [
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] | 3.017467 | 229 |
from doubles import InstanceDouble, allow
from pytest import fixture
from staticpy.category import Category
@fixture
@fixture
| [
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# liste methotları listelerimiz üzerine methotlar sayesinde işlemler yapmamızı sağlar
numbers = [5,2,1,7,4]
# listeye öğe eklemek için append methodundan yararlanırız
numbers.append(20)
print(numbers)
# listeye indeks numarasına göre öge eklemek
numbers.insert(2,10)
print(numbers)
# listemizde bir öğeyi silmek için remove methodundan yararlanırız
numbers.remove(5)
print(numbers)
# listemizdeki tüm ögeleri silmek için clear() methodundan yararlanırız
numbers.clear()
print(numbers) # []
number = [1,2,3,4,3,5]
# listenin son ögesini silmek için pop() methoundan yararlanırız
number.pop()
print(number) # [1,2,3,4]
# listedeki ögelerin varlığını ögrenmek için methotlardan yararlanabiliriz
# index() methodu sayesinde öğenin listedeki indeks sayısını öğrenmiş olduk
print(number.index(2)) #1
# index() methoduna listede bulunmayan bir öğeyi yazarsak ValueError hatası alırız
# bir değerin listede bulunup bulunmadığını in kelimesini kullanarak bulabiliriz
print(2 in number) # 2 değeri number listesinde bulunduğu için değer True oldu
print(100 in number) # 100 değeri number listesinde bulunduğu için değer False oldu
# bir değerin listenin içinde kaç tane bulunduğunu kontrol etmek için count() methodunu kullanırız
print(number.count(3)) #2
print(number.count(4)) # 1
print(number.count(40)) # bulunmadığı için 0
# listeleri küçükten büyüğe sıralamak için sort() methodundan yararlanabiliriz
number.sort()
print(number) # [1,2,3,3,4]
# listeleri büyükten küçüğe sıralamak için reverse() methodundan yararlanırız
number.reverse()
print(number) # [4,3,3,2,1]
# listemizin bir kopyasını almak için copy() methodundan yararlanırız
number2 = number.copy()
number.append(10)
print(number) # [4,3,3,2,1,10]
print(number2) # [4,3,3,2,1]
# listemizin bir kopyasını almak, listeye sonradan ekleyeceğimiz, çıkartacağımız vb.
# gibi değişikliklerden etkilenmemesi için en doğru yoldur
"""
EGZERSİZ
"""
# bir listemiz var bu listenin içinde aynı değere sahip 1 den fazla öge var
# bu ögelerin kopyalarını nasıl silebiliriz
numbersOne = [2,2,4,6,3,4,6,1]
uniques = [] # boş bir liste
for numberTwo in numbersOne: # numbersOne listesindeki her bir ögeye numberTwo adını verdik:
if numberTwo not in uniques: # eğer öge uniques listesinde yok ise:
uniques.append(numberTwo) # uniques listesine o ögeyi ekle
print(uniques) # [2,4,6,3,1] # uniques listesini yazdır
"""
numbersOne adlı değişkenin içinde kopyalarıda bulunan karışık değerli bir listemiz var
bu listedeki kopyalardan arınmış halini uniques listesinde toplayacağız
bu yüzden boş bir liste yarattık
numberOne daki her bir ögeyi ele aldık
eğer dedik numberTwo ögeleri uniques içinde yok ise bu listeye ögeyi ekle dedik
not in dememizin sebebi eğer 1 uniques in içinde ise bir daha birin yazılmasını engellemek
bu sayede listenin kopyalardan arınmış halini oluşturduk
"""
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5362,
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46481,
36590,
646,
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628,
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] | 2.20216 | 1,296 |
from PIL import Image
from pdf2image import convert_from_bytes
import os
import math
import random
# | [
6738,
350,
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28686,
201,
198,
11748,
10688,
201,
198,
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4738,
201,
198,
2
] | 3.28125 | 32 |
import cv2
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
from numpy import pi
from utils import stripes, get_gradation_2d,\
get_gradation_3d, checkerboard, radial_gradient
from utils.filters import gau_kern, circ_mask
from skimage.color import rgb2gray
from skimage import img_as_float
if __name__ == "__main__":
cmask = circ_mask(70, (35, 35), 35, 0)
im1 = stripes(32, 45, 256, 256, horizontal=False)
im2 = get_gradation_2d(256, 256, 0, 255, is_horizontal=False)
im3 = checkerboard(256, 64)
im4 = stripes(32, 45, 256, 256, horizontal=True)
im5 = rgb2gray(radial_gradient(70, 70))
fig = plt.figure()
grid = ImageGrid(fig, 111, # similar to subplot(111)
nrows_ncols=(1, 5), # creates 2x2 grid of axes
axes_pad=0.1, # pad between axes in inch.
)
for ax, im in zip(grid, [im1, im2, im3, im4, im5]):
# Iterating over the grid returns the Axes.
ax.imshow(im, cmap='gray')
ax.set_axis_off()
plt.imsave('vstripes.tiff', im1)
plt.imsave('gradient_2d.tiff', im2)
plt.imsave('checkerboard.tiff', im3)
plt.imsave('hstripes.tiff', im4)
plt.imsave('gradient_3d.tiff', im5)
plt.show()
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8,
628,
220,
220,
220,
458,
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198
] | 2.205085 | 590 |
import os
import pprint
import argparse
import time
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
from torch.utils.data import DataLoader
import sys
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
import lib.models as models
from lib.config import config, update_config
from lib.utils import utils
from lib.datasets import get_dataset
from lib.core import function
test_files = {
"WFLW":None,
"300W":None,
"AFLW":None,
"COFW":None
}
test_files["WFLW"] = [
"data/wflw/face_landmarks_wflw_test.csv",
"data/wflw/face_landmarks_wflw_test_blur.csv",
"data/wflw/face_landmarks_wflw_test_expression.csv",
"data/wflw/face_landmarks_wflw_test_illumination.csv",
"data/wflw/face_landmarks_wflw_test_largepose.csv",
"data/wflw/face_landmarks_wflw_test_makeup.csv",
"data/wflw/face_landmarks_wflw_test_occlusion.csv"
]
test_files["300W"] = [
"data/300w/face_landmarks_300w_valid_challenge.csv",
"data/300w/face_landmarks_300w_valid_common.csv",
"data/300w/face_landmarks_300w_valid.csv",
"data/300w/face_landmarks_300w_test.csv"
]
test_files["AFLW"] = [
"data/aflw/face_landmarks_aflw_test.csv",
"data/aflw/face_landmarks_aflw_test_frontal.csv"
]
test_files["COFW"] = [
"data/cofw/COFW_test_color.mat"
]
if __name__ == '__main__':
main()
| [
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10354,
198,
220,
220,
220,
1388,
3419,
628
] | 2.250412 | 607 |
#!/bin/env python2
"""
Script for running annotation on the document files.
"""
from sys import argv as _argv
import logging
from ConfigParser import ConfigParser
from os import path, listdir
from typing import List
from srl_nlp.framenet.adapter import PARSERS_AVAILABLE, DocumentAdapter
from srl_nlp.framenet.corpus import Paragraph, Document
from srl_nlp.fsparsing import Annotator, SemaforAnnotator
from srl_nlp.rule_utils import list_doc_files
logger = logging.getLogger(__name__)
config = ConfigParser()
_package_directory = path.dirname(__file__)
config.read(path.join(_package_directory, "external.conf"))
if __name__ == '__main__':
import argparse
from logger_config import add_logger_args as _add_logger_args, config_logger, timeit
@timeit
try:
main(_argv)
except KeyboardInterrupt:
logger.info('Halted by the user')
except OSError as e:
logger.critical('Problem reading/writing files')
logger.critical(e)
raise e
| [
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] | 2.775623 | 361 |
# This script takes a list of project directories and find the owner info from "_infra/project.yml"
import os
import sys
import yaml
if __name__ == '__main__':
main()
| [
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] | 3.240741 | 54 |
from __future__ import absolute_import
import logging
import argparse
import apache_beam as beam
import apache_beam.transforms.window as window
'''Normalize pubsub string to json object'''
# Lines look like this:
# {'datetime': '2017-07-13T21:15:02Z', 'mac': 'FC:FC:48:AE:F6:94', 'status': 1}
def run(argv=None):
"""Build and run the pipeline."""
parser = argparse.ArgumentParser()
parser.add_argument(
'--input_topic', required=True,
help='Input PubSub topic of the form "/topics/<PROJECT>/<TOPIC>".')
parser.add_argument(
'--output_table', required=True,
help=
('Output BigQuery table for results specified as: PROJECT:DATASET.TABLE '
'or DATASET.TABLE.'))
known_args, pipeline_args = parser.parse_known_args(argv)
with beam.Pipeline(argv=pipeline_args) as p:
# Read the pubsub topic into a PCollection.
lines = ( p | beam.io.ReadStringsFromPubSub(known_args.input_topic)
| beam.Map(parse_pubsub)
| beam.Map(lambda (mac_bq, status_bq, datetime_bq): {'mac': mac_bq, 'status': status_bq, 'datetime': datetime_bq})
| beam.io.WriteToBigQuery(
known_args.output_table,
schema=' mac:STRING, status:INTEGER, datetime:TIMESTAMP',
create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND)
)
if __name__ == '__main__':
logging.getLogger().setLevel(logging.INFO)
run() | [
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1136,
11187,
1362,
22446,
2617,
4971,
7,
6404,
2667,
13,
10778,
8,
198,
220,
1057,
3419
] | 2.315234 | 663 |
#!/usr/bin/python
"""Simple VLAN topology example
Linear Topology,
Switch1-----Switch2
Switch1-----a1, a2, b1, b2
Switch2-----a3, a4 ,b3, b4
objective:
1. a1,a2,a3,a4, belongs to VLAN 100
2. b1, b2, b3, b4 belongs to VLAN 200
Switch1 to Switch2 connected with 802.1Q TRUNK Links
"""
from mininet.topo import Topo
from mininet.net import Mininet
from mininet.log import setLogLevel
from mininet.cli import CLI
from mininet.node import OVSSwitch, Controller, RemoteController
from time import sleep
class SingleSwitchTopo(Topo):
"Single switch connected to n hosts."
if __name__ == '__main__':
setLogLevel('info')
topo = SingleSwitchTopo()
c1 = RemoteController('c1', ip='127.0.0.1')
net = Mininet(topo=topo, controller=c1)
net.start()
CLI(net)
net.stop()
| [
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526,
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198,
198,
361,
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3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
900,
11187,
4971,
10786,
10951,
11537,
198,
220,
220,
220,
1353,
78,
796,
14206,
38978,
9126,
78,
3419,
198,
220,
220,
220,
269,
16,
796,
21520,
22130,
10786,
66,
16,
3256,
20966,
11639,
16799,
13,
15,
13,
15,
13,
16,
11537,
198,
220,
220,
220,
2010,
796,
1855,
42504,
7,
4852,
78,
28,
4852,
78,
11,
10444,
28,
66,
16,
8,
198,
220,
220,
220,
2010,
13,
9688,
3419,
198,
220,
220,
220,
43749,
7,
3262,
8,
198,
220,
220,
220,
2010,
13,
11338,
3419,
198
] | 2.580645 | 310 |
# web.responder.strategy.base
import json
"""
Base class for strategies returning JSON responses
"""
| [
2,
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] | 3.678571 | 28 |
import keras
# import tensorflow.keras as keras
# from keras.models import Sequential
from keras.layers import LSTM,Dense,Activation,SimpleRNN,Conv1D,MaxPool1D,Flatten,Reshape,Dropout,MaxPooling1D,Masking
from keras.metrics import categorical_accuracy
# from keras.callbacks import EarlyStopping
# from keras.metrics import categorical_accuracy
# from keras.optimizers import RMSprop
| [
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] | 3.015504 | 129 |
# -*- coding: utf-8 -*-
import numpy as np
import math
import cv2
__all__ = ['_energy', '_entropy', '_next_power_of_two', '_pad_image_power_2',
'pad_image', '_zero_runs']
| [
2,
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62,
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3256,
705,
62,
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62,
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201
] | 2.053763 | 93 |
import math
import torch
from torch.optim import Optimizer
| [
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] | 3.647059 | 17 |
"""
* Written by the Trapdoor-NX team, May 8, 2018.
* Licensing information can found in the 'LICENSE' file.
* Injector based on reswitched/fusee-launcher.
"""
CURR_VERSION = '0.1' | [
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] | 2.787879 | 66 |
from docs_snippets_crag.intro_tutorial.basics.connecting_solids.complex_pipeline import diamond
from docs_snippets_crag.intro_tutorial.test_util import patch_cereal_requests
@patch_cereal_requests
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] | 2.802817 | 71 |
from pysh import pysh
a = 1
b = 2
pysh(s['echo $HOME {a} {b}']) | [
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from setuptools import find_packages, setup
requirements = ["slackclient==2.5.0"]
setup(
name="slackhermes",
version="1.0.0",
description="A message notifier for Slack",
author="mdcg",
url="https://github.com/mdcg/slack-hermes",
packages=find_packages(exclude=["tests"]),
install_requires=requirements,
include_package_data=True,
zip_safe=False,
)
| [
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220,
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220,
220,
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28,
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] | 2.556291 | 151 |
import re
from typing import Any
import pendulum
from timezonefinder import TimezoneFinder
from crimsobot.exceptions import LocationNotFound
from crimsobot.utils.astronomy import where_are_you
from crimsobot.utils.tools import clib_path_join
# This any param is a bummer but it's the only way I can see to make make mypy work the way we want.
# Everything is terrible.
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] | 3.523364 | 107 |
""" Lambda, let, let*
Examples:
(let
(
(a 6))
(* a 1))
"""
from typing import List
import copy
import concurrent.futures
from mplisp.structures import env, tree
from mplisp import evaluator
def lambda_expression(args: List, node):
"""Return lambda expression"""
if len(args) != 2:
evaluator.error("(special_forms.lambda_expression.lambda) 2 parameters expected, {} given".format(len(args)), node)
return create_lambda(args, node)
def let_expression(args: List, node):
"""Return let expression"""
with concurrent.futures.ThreadPoolExecutor() as executor:
for name, value in executor.map(set_env, args[0].children):
node.getenv().symbols[name.children[0].value] = value
return evaluator.evaluate_node(args[1])
def let_star_expression(args: List, node):
"""Return let expression"""
for param in args[0].children:
node.getenv().symbols[param.children[0].value] = evaluator.evaluate_node(
param.children[1])
return evaluator.evaluate_node(args[1])
def create_lambda(args, node: tree.SyntaxTreeNode):
"""Generate lambda function"""
params = [arg.value for arg in args[0].children]
def func(local_args: List, _):
"""Callable object"""
new_node = copy.copy(node.children[2])
if new_node.local_env is None:
new_node.local_env = env.EnvNode({})
for arg, value in zip(params, local_args):
new_node.local_env.symbols[arg] = evaluator.evaluate_node(value)
return evaluator.evaluate_node(new_node)
return func
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] | 2.57767 | 618 |
#!/usr/bin/env python3
import glob
from PIL import Image
for file in glob.glob("./rgb/*.jpg"):
im1 = Image.open(file)
try:
im2 = Image.open(file.replace('rgb', 'averaged'))
except:
im2 = Image.open(file.replace('rgb', 'depth'))
get_concat_v(im1, im2).save(file.replace('rgb', 'merged'))
#print("Merged: " + file)
print('Done.') | [
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] | 2.29932 | 147 |
#!/usr/bin/env python3
import sys, time, colorsys, threading
from enum import Enum
try:
import numpy
except ImportError:
sys.exit("This script requires the numpy module\nInstall with: sudo pip3 install numpy")
from lib.logger import Level, Logger
from lib.feature import Feature
from lib.enums import Color
from rgbmatrix5x5 import RGBMatrix5x5
# ..............................................................................
# ..............................................................................
class RgbMatrix(Feature):
'''
This class provides access to a pair of Pimoroni 5x5 RGB LED Matrix displays,
labeled port and starboard. It also includes several canned demonstrations,
which can be used to indicate behaviours in progress.
'''
# ..........................................................................
# ..........................................................................
# ..........................................................................
# ..........................................................................
# ..........................................................................
# ..........................................................................
# ..........................................................................
def _rainbow(self, rgbmatrix5x5):
'''
Display a rainbow pattern.
'''
global enabled
self._log.info('starting rainbow...')
_spacing = 360.0 / 5.0
_hue = 0
while enabled:
for x in range(self._width):
for y in range(self._height):
_hue = int(time.time() * 100) % 360
offset = (x * y) / 25.0 * _spacing
h = ((_hue + offset) % 360) / 360.0
r, g, b = [int(c * 255) for c in colorsys.hsv_to_rgb(h, 1.0, 1.0)]
rgbmatrix5x5.set_pixel(x, y, r, g, b)
# r, g, b = [int(c * 255) for c in colorsys.hsv_to_rgb(h + 0.5, 1.0, 1.0)]
# rainbow2.set_pixel(x, y, r, g, b)
if not enabled:
break
rgbmatrix5x5.show()
# rainbow2.show()
time.sleep(0.0001)
self._clear(rgbmatrix5x5)
self._log.info('rainbow ended.')
# ..........................................................................
def _sworl(self, rgbmatrix5x5):
'''
Display a sworl pattern, whatever that is.
'''
global enabled
self._log.info('starting sworl...')
target = Color.LIGHT_BLUE
self.set_color(target)
# for r in numpy.arange(0.0, target.red):
# for g in numpy.arange(0.0, target.green):
# for b in numpy.arange(0.0, target.blue):
# rgbmatrix5x5.set_all(r, g, b)
# rgbmatrix5x5.show()
# time.sleep(0.01)
# if not enabled:
# break
# for r in numpy.arange(target.red, 0.0, -1.0):
# for g in numpy.arange(target.green, 0.0, -1.0):
# for b in numpy.arange(target.blue, 0.0, -1.0):
# rgbmatrix5x5.set_all(r, g, b)
# rgbmatrix5x5.show()
# time.sleep(0.01)
# if not enabled:
# break
self._clear(rgbmatrix5x5)
self._log.info('sworl ended.')
# ..........................................................................
def _dark(self, rgbmatrix5x5):
'''
Display a dark static color.
'''
global enabled
self._log.info('starting dark...')
self.set_color(Color.BLACK)
while enabled:
time.sleep(0.2)
# ..........................................................................
@staticmethod
# ..........................................................................
def _blinky(self, rgbmatrix5x5):
'''
Display a pair of blinky spots.
'''
global enabled
self._log.info('starting blinky...')
if self._height == self._width:
_delta = 0
else:
_delta = 2
while enabled:
for i in range(3):
for z in list(range(1, 10)[::-1]) + list(range(1, 10)):
fwhm = 5.0/z
gauss = RgbMatrix.make_gaussian(fwhm)
start = time.time()
for y in range(self._height):
for x in range(self._width):
h = 0.5
s = 0.8
if self._height <= self._width:
v = gauss[x, y]
# v = gauss[x, y + _delta]
else:
v = gauss[x, y]
# v = gauss[x + _delta, y]
rgb = colorsys.hsv_to_rgb(h, s, v)
r = int(rgb[0]*255.0)
g = int(rgb[1]*255.0)
b = int(rgb[2]*255.0)
rgbmatrix5x5.set_pixel(x, y, r, g, b)
rgbmatrix5x5.show()
end = time.time()
t = end - start
if t < 0.04:
time.sleep(0.04 - t)
pass
if not enabled:
break
self._clear(rgbmatrix5x5)
self._log.info('blinky ended.')
# ..........................................................................
def _scan(self, rgbmatrix5x5):
'''
KITT- or Cylon-like eyeball scanning.
'''
global enabled
self._log.info('starting scan...')
r = int(255.0)
g = int(64.0)
b = int(0.0)
# start = time.time()
# for x in range(self._width):
x = 2
_delay = 0.25
while enabled:
# for i in range(count):
for y in range(0,self._height):
rgbmatrix5x5.clear()
rgbmatrix5x5.set_pixel(x, y, r, g, b)
rgbmatrix5x5.show()
time.sleep(_delay)
for y in range(self._height-1,0,-1):
rgbmatrix5x5.clear()
rgbmatrix5x5.set_pixel(x, y, r, g, b)
rgbmatrix5x5.show()
time.sleep(_delay)
if not enabled:
break
self._clear(rgbmatrix5x5)
self._log.debug('scan ended.')
# ..........................................................................
def _random(self, rgbmatrix5x5):
'''
Display an ever-changing random pattern.
'''
global enabled
self._log.info('starting random...')
count = 0
while enabled:
rand_hue = numpy.random.uniform(0.1, 0.9)
rand_mat = numpy.random.rand(self._width,self._height)
for y in range(self._height):
for x in range(self._width):
# h = 0.1 * rand_mat[x, y]
h = rand_hue * rand_mat[x, y]
s = 0.8
v = rand_mat[x, y]
rgb = colorsys.hsv_to_rgb(h, s, v)
r = int(rgb[0]*255.0)
g = int(rgb[1]*255.0)
b = int(rgb[2]*255.0)
rgbmatrix5x5.set_pixel(x, y, r, g, b)
if not enabled:
break
rgbmatrix5x5.show()
time.sleep(0.01)
self._clear(rgbmatrix5x5)
self._log.info('random ended.')
# ..........................................................................
def set_color(self, color):
'''
Set the color of both RGB Matrix displays.
'''
self._set_color(self._rgbmatrix5x5_PORT, color)
self._set_color(self._rgbmatrix5x5_STBD, color)
# ..........................................................................
def _set_color(self, rgbmatrix5x5, color):
'''
Set the color of the RGB Matrix.
'''
rgbmatrix5x5.set_all(color.red, color.green, color.blue)
rgbmatrix5x5.show()
# ..........................................................................
def _clear(self, rgbmatrix5x5):
'''
Clears the RGB Matrix by setting its color to black.
'''
self._set_color(rgbmatrix5x5, Color.BLACK)
# ..........................................................................
# ..........................................................................
#EOF
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220,
220,
220,
1303,
220,
23193,
2109,
492,
198,
198,
2,
4720,
37,
198
] | 1.995692 | 4,410 |
from djchoices import ChoiceItem, DjangoChoices
| [
6738,
42625,
6679,
1063,
1330,
18502,
7449,
11,
37770,
22164,
1063,
628
] | 4.083333 | 12 |
# flake8: noqa
__all__ = []
| [
2,
781,
539,
23,
25,
645,
20402,
198,
834,
439,
834,
796,
17635,
198
] | 2 | 14 |
from os import system
| [
6738,
28686,
1330,
1080,
220,
198
] | 3.833333 | 6 |
"""
vaenet.py
PyTorch implementation of a Convolutional Neural Network Variational Autoencoder ( VaeNet )
Author : Abhishek .
"""
# PyTorch Imports
import torch.nn as nn
# VaeNet class
# Initializer for the ConvNetVAE model
# Method for the forward pass
# Method for the encoder layers
# Method for the reparameterization
# Method for the decoder layers | [
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220,
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] | 2.5875 | 160 |
# Import di flask e degli operatori di templating
from flask import Flask, render_template
from flask_mail import Mail
# Definizione oggetto WSGI
app = Flask(__name__)
mail = Mail(app)
# Configurazioni
app.config.from_object('config')
app.secret_key = app.config['CSRF_SESSION_KEY']
# HTTP error handling
@app.errorhandler(404)
# Import a module / component using its blueprint handler variable (mod_auth)
from app.main.controller import main
# Register blueprint(s)
app.register_blueprint(main)
| [
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62,
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7,
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8,
198
] | 3.23871 | 155 |
"""
PyOO - Pythonic interface to Apache OpenOffice API (UNO)
Copyright (c) 2016-2017 Seznam.cz, a.s.
Copyright (c) 2017-2019 Miloslav Pojman
"""
from __future__ import division
import datetime
import functools
import itertools
import numbers
import os
import sys
import uno
# Filters used when saving document.
FILTER_PDF_EXPORT = 'writer_pdf_Export'
FILTER_WRITER_PDF_EXPORT = 'writer_pdf_Export'
FILTER_CALC_PDF_EXPORT = 'calc_pdf_Export'
FILTER_EXCEL_97 = 'MS Excel 97'
FILTER_EXCEL_2007 = 'Calc MS Excel 2007 XML'
# Number format choices
FORMAT_TEXT = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.TEXT')
FORMAT_INT = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.NUMBER_INT')
FORMAT_FLOAT = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.NUMBER_DEC2')
FORMAT_INT_SEP = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.NUMBER_1000INT')
FORMAT_FLOAT_SEP = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.NUMBER_1000DEC2')
FORMAT_PERCENT_INT = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.PERCENT_INT')
FORMAT_PERCENT_FLOAT = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.PERCENT_DEC2')
FORMAT_DATE = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.DATE_SYSTEM_SHORT')
FORMAT_TIME = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.TIME_HHMM')
FORMAT_DATETIME = uno.getConstantByName('com.sun.star.i18n.NumberFormatIndex.DATETIME_SYSTEM_SHORT_HHMM')
# Font weight choices
FONT_WEIGHT_DONTKNOW = uno.getConstantByName('com.sun.star.awt.FontWeight.DONTKNOW')
FONT_WEIGHT_THIN = uno.getConstantByName('com.sun.star.awt.FontWeight.THIN')
FONT_WEIGHT_ULTRALIGHT = uno.getConstantByName('com.sun.star.awt.FontWeight.ULTRALIGHT')
FONT_WEIGHT_LIGHT = uno.getConstantByName('com.sun.star.awt.FontWeight.LIGHT')
FONT_WEIGHT_SEMILIGHT = uno.getConstantByName('com.sun.star.awt.FontWeight.SEMILIGHT')
FONT_WEIGHT_NORMAL = uno.getConstantByName('com.sun.star.awt.FontWeight.NORMAL')
FONT_WEIGHT_SEMIBOLD = uno.getConstantByName('com.sun.star.awt.FontWeight.SEMIBOLD')
FONT_WEIGHT_BOLD = uno.getConstantByName('com.sun.star.awt.FontWeight.BOLD')
FONT_WEIGHT_ULTRABOLD = uno.getConstantByName('com.sun.star.awt.FontWeight.ULTRABOLD')
FONT_WEIGHT_BLACK = uno.getConstantByName('com.sun.star.awt.FontWeight.BLACK')
# Text underline choices (only first three are present here)
UNDERLINE_NONE = uno.getConstantByName('com.sun.star.awt.FontUnderline.NONE')
UNDERLINE_SINGLE = uno.getConstantByName('com.sun.star.awt.FontUnderline.SINGLE')
UNDERLINE_DOUBLE = uno.getConstantByName('com.sun.star.awt.FontUnderline.DOUBLE')
# Text alignment choices
TEXT_ALIGN_STANDARD = 'STANDARD'
TEXT_ALIGN_LEFT = 'LEFT'
TEXT_ALIGN_CENTER = 'CENTER'
TEXT_ALIGN_RIGHT = 'RIGHT'
TEXT_ALIGN_BLOCK = 'BLOCK'
TEXT_ALIGN_REPEAT = 'REPEAT'
# Axis choices
AXIS_PRIMARY = uno.getConstantByName('com.sun.star.chart.ChartAxisAssign.PRIMARY_Y')
AXIS_SECONDARY = uno.getConstantByName('com.sun.star.chart.ChartAxisAssign.SECONDARY_Y')
# Exceptions thrown by UNO.
# We try to catch them and re-throw Python standard exceptions.
_IndexOutOfBoundsException = uno.getClass('com.sun.star.lang.IndexOutOfBoundsException')
_NoSuchElementException = uno.getClass('com.sun.star.container.NoSuchElementException')
_IOException = uno.getClass('com.sun.star.io.IOException')
_NoConnectException = uno.getClass('com.sun.star.connection.NoConnectException')
_ConnectionSetupException = uno.getClass('com.sun.star.connection.ConnectionSetupException')
UnoException = uno.getClass('com.sun.star.uno.Exception')
PY2 = sys.version_info[0] == 2
PY3 = sys.version_info[0] == 3
if PY3:
string_types = str,
integer_types = int,
text_type = str
else:
string_types = basestring,
integer_types = (int, long)
text_type = unicode
range = xrange
def str_repr(klass):
"""
Implements string conversion methods for the given class.
The given class must implement the __str__ method. This decorat
will add __repr__ and __unicode__ (for Python 2).
"""
if PY2:
klass.__unicode__ = klass.__str__
klass.__str__ = lambda self: self.__unicode__().encode('utf-8')
klass.__repr__ = lambda self: '<%s: %r>' % (self.__class__.__name__, str(self))
return klass
def _clean_slice(key, length):
"""
Validates and normalizes a cell range slice.
>>> _clean_slice(slice(None, None), 10)
(0, 10)
>>> _clean_slice(slice(-10, 10), 10)
(0, 10)
>>> _clean_slice(slice(-11, 11), 10)
(0, 10)
>>> _clean_slice(slice('x', 'y'), 10)
Traceback (most recent call last):
...
TypeError: Cell indices must be integers, str given.
>>> _clean_slice(slice(0, 10, 2), 10)
Traceback (most recent call last):
...
NotImplementedError: Cell slice with step is not supported.
>>> _clean_slice(slice(5, 5), 10)
Traceback (most recent call last):
...
ValueError: Cell slice can not be empty.
"""
if key.step is not None:
raise NotImplementedError('Cell slice with step is not supported.')
start, stop = key.start, key.stop
if start is None:
start = 0
if stop is None:
stop = length
if not isinstance(start, integer_types):
raise TypeError('Cell indices must be integers, %s given.' % type(start).__name__)
if not isinstance(stop, integer_types):
raise TypeError('Cell indices must be integers, %s given.' % type(stop).__name__)
if start < 0:
start = start + length
if stop < 0:
stop = stop + length
start, stop = max(0, start), min(length, stop)
if start == stop:
raise ValueError('Cell slice can not be empty.')
return start, stop
def _clean_index(key, length):
"""
Validates and normalizes a cell range index.
>>> _clean_index(0, 10)
0
>>> _clean_index(-10, 10)
0
>>> _clean_index(10, 10)
Traceback (most recent call last):
...
IndexError: Cell index out of range.
>>> _clean_index(-11, 10)
Traceback (most recent call last):
...
IndexError: Cell index out of range.
>>> _clean_index(None, 10)
Traceback (most recent call last):
...
TypeError: Cell indices must be integers, NoneType given.
"""
if not isinstance(key, integer_types):
raise TypeError('Cell indices must be integers, %s given.' % type(key).__name__)
if -length <= key < 0:
return key + length
elif 0 <= key < length:
return key
else:
raise IndexError('Cell index out of range.')
def _row_name(index):
"""
Converts a row index to a row name.
>>> _row_name(0)
'1'
>>> _row_name(10)
'11'
"""
return '%d' % (index + 1)
def _col_name(index):
"""
Converts a column index to a column name.
>>> _col_name(0)
'A'
>>> _col_name(26)
'AA'
"""
for exp in itertools.count(1):
limit = 26 ** exp
if index < limit:
return ''.join(chr(ord('A') + index // (26 ** i) % 26) for i in range(exp-1, -1, -1))
index -= limit
@str_repr
class SheetPosition(object):
"""
Position of a rectangular are in a spreadsheet.
This class represent physical position in 100/th mm,
see SheetAddress class for a logical address of cells.
>>> position = SheetPosition(1000, 2000)
>>> print position
x=1000, y=2000
>>> position = SheetPosition(1000, 2000, 3000, 4000)
>>> print position
x=1000, y=2000, width=3000, height=4000
"""
__slots__ = ('x', 'y', 'width', 'height')
@classmethod
@str_repr
class SheetAddress(object):
"""
Address of a cell or a rectangular range of cells in a spreadsheet.
This class represent logical address of cells, see SheetPosition
class for physical location.
>>> address = SheetAddress(1, 2)
>>> print address
$C$2
>>> address = SheetAddress(1, 2, 3, 4)
>>> print address
$C$2:$F$4
"""
__slots__ = ('row', 'col', 'row_count', 'col_count')
@property
@property
def formula(self, row_abs=False, col_abs=False):
"""
Returns this address as a string to be used in formulas.
"""
if row_abs and col_abs:
fmt = u'$%s$%s'
elif row_abs:
fmt = u'%s$%s'
elif col_abs:
fmt = u'$%s%s'
else:
fmt = u'%s%s'
start = fmt % (_col_name(self.col), _row_name(self.row))
if self.row_count == self.col_count == 1:
return start
end = fmt % (_col_name(self.col_end), _row_name(self.row_end))
return '%s:%s' % (start, end)
def replace(self, row=None, col=None, row_count=None, col_count=None):
"""
Returns a new address which the specified fields replaced.
"""
row = row if row is not None else self.row
col = col if col is not None else self.col
row_count = row_count if row_count is not None else self.row_count
col_count = col_count if col_count is not None else self.col_count
return self.__class__(row, col, row_count, col_count)
@classmethod
class _UnoProxy(object):
"""
Abstract base class for objects which act as a proxy to UNO objects.
"""
__slots__ = ('_target',)
class NamedCollection(_UnoProxy):
"""
Base class for collections accessible by both index and name.
"""
# Target must implement both of:
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/container/XIndexAccess.html
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/container/XNameAccess.html
__slots__ = ()
# Internal:
class DiagramSeries(_UnoProxy):
"""
Diagram series.
This class allows to control how one sequence of values (typically
one table column) is displayed in a chart (for example appearance
of one line).
"""
__slots__ = ()
def __get_axis(self):
"""
Gets to which axis this series are assigned.
"""
return self._target.getPropertyValue('Axis')
def __set_axis(self, value):
"""
Sets to which axis this series are assigned.
"""
self._target.setPropertyValue('Axis', value)
axis = property(__get_axis, __set_axis)
def __get_line_color(self):
"""
Gets line color.
"""
return self._target.getPropertyValue('LineColor')
def __set_line_color(self, value):
"""
Sets line color.
Be aware that this call is sometimes ignored by OpenOffice.
"""
self._target.setPropertyValue('LineColor', value)
line_color = property(__get_line_color, __set_line_color)
def __get_fill_color(self):
"""
Gets fill color.
"""
return self._target.getPropertyValue('FillColor')
def __set_fill_color(self, value):
"""
Sets fill color.
"""
self._target.setPropertyValue('FillColor', value)
fill_color = property(__get_fill_color, __set_fill_color)
class DiagramSeriesCollection(_UnoProxy):
"""
Provides access to individual diagram series.
Instance of this class is returned when series property of
the Diagram class is accessed.
"""
__slots__ = ()
# It seems that length of series can not be easily determined so
# here is no __len__ method.
class Axis(_UnoProxy):
"""
Chart axis
"""
__slots__ = ()
def __get_visible(self):
"""
Gets whether this axis is visible.
"""
# Getting target.HasXAxis is a lot of faster then accessing
# target.XAxis.Visible property.
return self._target.getPropertyValue(self._has_axis_property)
def __set_visible(self, value):
"""
Sets whether this axis is visible.
"""
return self._target.setPropertyValue(self._has_axis_property, value)
visible = property(__get_visible, __set_visible)
def __get_title(self):
"""
Gets title of this axis.
"""
target = self._get_title_target()
return target.getPropertyValue('String')
def __set_title(self, value):
"""
Sets title of this axis.
"""
# OpenOffice on Debian "squeeze" ignore value of target.XAxis.String
# unless target.HasXAxisTitle is set to True first. (Despite the
# fact that target.HasXAxisTitle is reported to be False until
# target.XAxis.String is set to non empty value.)
self._target.setPropertyValue(self._has_axis_title_property, True)
target = self._get_title_target()
target.setPropertyValue('String', text_type(value))
title = property(__get_title, __set_title)
def __get_logarithmic(self):
"""
Gets whether this axis has an logarithmic scale.
"""
target = self._get_axis_target()
return target.getPropertyValue('Logarithmic')
def __set_logarithmic(self, value):
"""
Sets whether this axis has an logarithmic scale.
"""
target = self._get_axis_target()
target.setPropertyValue('Logarithmic', value)
logarithmic = property(__get_logarithmic, __set_logarithmic)
def __get_reversed(self):
"""
Gets whether this axis is reversed
"""
target = self._get_axis_target()
return target.getPropertyValue('ReverseDirection')
def __set_reversed(self, value):
"""
Sets whether this axis is reversed
"""
target = self._get_axis_target()
return target.setPropertyValue('ReverseDirection', value)
reversed = property(__get_reversed, __set_reversed)
# The _target property of this class does not hold the axis itself but
# the owner diagram instance. So following methods and properties has
# to be overridden in order to access appropriate UNO objects.
_has_axis_property = None
_has_axis_title_property = None
class Diagram(_UnoProxy):
"""
Diagram - inner content of a chart.
Each chart has a diagram which specifies how data are rendered.
The inner diagram can be changed or replaced while the
the outer chart instance is still the same.
"""
__slots__ = ()
@property
def series(self):
"""
Collection of diagram series.
"""
return DiagramSeriesCollection(self._target)
# Following code is specific to 2D diagrams. If support for another
# diagram types is added (e.g. pie) then a new class should
# be probably introduced.
@property
def x_axis(self):
"""
X (bottom) axis
"""
return XAxis(self._target)
@property
def y_axis(self):
"""
Y (left) axis
"""
return YAxis(self._target)
@property
def secondary_x_axis(self):
"""
Secondary X (top) axis
"""
return SecondaryXAxis(self._target)
@property
def secondary_y_axis(self):
"""
Secondary Y (right) axis
"""
return SecondaryYAxis(self._target)
def __get_is_stacked(self):
"""
Gets whether series of the diagram are stacked.
"""
return self._target.getPropertyValue('Stacked')
def __set_is_stacked(self, value):
"""
Sets whether series of the diagram are stacked.
"""
self._target.setPropertyValue('Stacked', value)
is_stacked = property(__get_is_stacked, __set_is_stacked)
class BarDiagram(Diagram):
"""
Bar or column diagram.
Type of diagram can be changed using Chart.change_type method.
"""
__slots__ = ()
_type = 'com.sun.star.chart.BarDiagram'
def __get_lines(self):
"""
Gets count of series which are rendered as lines instead of lines.
"""
return self._target.getPropertyValue('NumberOfLines')
def __set_lines(self, value):
"""
Sets count of series which are rendered as lines instead of lines
"""
return self._target.setPropertyValue('NumberOfLines', value)
lines = property(__get_lines, __set_lines)
def __get_is_horizontal(self):
"""
Gets whether this diagram is rendered with horizontal bars.
If value is False then you get vertical columns.
"""
# Be aware - this call is translated to UNO "Vertical" property.
#
# UNO API claims that if vertical is false then we get a column chart
# rather than a bar chart -- which describes OpenOffice behavior.
#
# But the words "horizontal" and "vertical" simply mean opposite
# of the UNO semantics. If you don't believe me then try to google
# for "horizontal bar chart" and "vertical bar chart" images.
return self._target.getPropertyValue('Vertical')
def __set_is_horizontal(self, value):
"""
Sets whether this diagram is rendered with horizontal bars.
"""
return self._target.setPropertyValue('Vertical', value)
is_horizontal = property(__get_is_horizontal, __set_is_horizontal)
def __get_is_grouped(self):
"""
Gets whether to group columns attached to different axis.
If bars of a bar or column chart are attached to different axis,
this property determines how to display those. If true, the bars
are grouped together in one block for each axis, thus they are
painted one group over the other.
"""
return self._target.getPropertyValue('GroupBarsPerAxis')
def __set_is_grouped(self, value):
"""
Sets whether to group columns attached to different axis.
"""
return self._target.setPropertyValue('GroupBarsPerAxis', value)
is_grouped = property(__get_is_grouped, __set_is_grouped)
class LineDiagram(Diagram):
"""
Line, spline or symbol diagram.
Type of diagram can be changed using Chart.change_type method.
"""
__slots__ = ()
_type = 'com.sun.star.chart.LineDiagram'
spline = property(__get_spline, __set_spline)
# Registry of supported diagram types.
_DIAGRAM_TYPES = {
BarDiagram._type: BarDiagram,
LineDiagram._type: LineDiagram,
}
class Chart(_UnoProxy):
"""
Chart
"""
__slots__ = ('sheet', '_embedded')
@property
def name(self):
"""
Chart name which can be used as a key for accessing this chart.
"""
return self._target.getName()
@property
def has_row_header(self):
"""
Returns whether the first row is used for header
"""
return self._target.getHasRowHeaders()
@property
def has_col_header(self):
"""
Returns whether the first column is used for header
"""
return self._target.getHasColumnHeaders()
@property
def ranges(self):
"""
Returns a list of addresses with source data.
"""
ranges = self._target.getRanges()
return map(SheetAddress._from_uno, ranges)
@property
def diagram(self):
"""
Diagram - inner content of this chart.
The diagram can be replaced by another type using change_type method.
"""
target = self._embedded.getDiagram()
target_type = target.getDiagramType()
cls = _DIAGRAM_TYPES.get(target_type, Diagram)
return cls(target)
def change_type(self, cls):
"""
Change type of diagram in this chart.
Accepts one of classes which extend Diagram.
"""
target_type = cls._type
target = self._embedded.createInstance(target_type)
self._embedded.setDiagram(target)
return cls(target)
class ChartCollection(NamedCollection):
"""
Collection of charts in one sheet.
"""
__slots__ = ('sheet',)
def create(self, name, position, ranges=(), col_header=False, row_header=False):
"""
Creates and inserts a new chart.
"""
rect = self._uno_rect(position)
ranges = self._uno_ranges(ranges)
self._create(name, rect, ranges, col_header, row_header)
return self[name]
# Internal:
class SheetCursor(_UnoProxy):
"""
Cursor in spreadsheet sheet.
Most of spreadsheet operations are done using this cursor
because cursor movement is much faster then cell range selection.
"""
__slots__ = ('row', 'col', 'row_count', 'col_count',
'max_row_count', 'max_col_count')
def get_target(self, row, col, row_count, col_count):
"""
Moves cursor to the specified position and returns in.
"""
# This method is called for almost any operation so it should
# be maximally optimized.
#
# Any comparison here is negligible compared to UNO call. So we do all
# possible checks which can prevent an unnecessary cursor movement.
#
# Generally we need to expand or collapse selection to the desired
# size and move it to the desired position. But both of these actions
# can fail if there is not enough space. For this reason we must
# determine which of the actions has to be done first. In some cases
# we must even move the cursor twice (cursor movement is faster than
# selection change).
#
target = self._target
# If we cannot resize selection now then we must move cursor first.
if self.row + row_count > self.max_row_count or self.col + col_count > self.max_col_count:
# Move cursor to the desired position if possible.
row_delta = row - self.row if row + self.row_count <= self.max_row_count else 0
col_delta = col - self.col if col + self.col_count <= self.max_col_count else 0
target.gotoOffset(col_delta, row_delta)
self.row += row_delta
self.col += col_delta
# Resize selection
if (row_count, col_count) != (self.row_count, self.col_count):
target.collapseToSize(col_count, row_count)
self.row_count = row_count
self.col_count = col_count
# Move cursor to the desired position
if (row, col) != (self.row, self.col):
target.gotoOffset(col - self.col, row - self.row)
self.row = row
self.col = col
return target
@str_repr
class CellRange(object):
"""
Range of cells in one sheet.
This is an abstract base class implements cell manipulation functionality.
"""
# Does not extend _UnoProxy because it uses sheet cursor internally
# instead of direct reference to UNO object.
__slots__ = ('sheet', 'address')
@property
def position(self):
"""
Physical position of this cells.
"""
target = self._get_target()
position, size = target.getPropertyValues(('Position', 'Size'))
return SheetPosition._from_uno(position, size)
def __get_is_merged(self):
"""
Gets whether cells are merged.
"""
return self._get_target().getIsMerged()
def __set_is_merged(self, value):
"""
Sets whether cells are merged.
"""
self._get_target().merge(value)
is_merged = property(__get_is_merged, __set_is_merged)
def __get_number_format(self):
"""
Gets format of numbers in this cells.
"""
return self._get_target().getPropertyValue('NumberFormat')
def __set_number_format(self, value):
"""
Sets format of numbers in this cells.
"""
self._get_target().setPropertyValue('NumberFormat', value)
number_format = property(__get_number_format, __set_number_format)
def __get_text_align(self):
"""
Gets horizontal alignment.
Returns one of TEXT_ALIGN_* constants.
"""
return self._get_target().getPropertyValue('HoriJustify').value
def __set_text_align(self, value):
"""
Sets horizontal alignment.
Accepts TEXT_ALIGN_* constants.
"""
# The HoriJustify property contains is a struct.
# We need to get it, update value and then set it back.
target = self._get_target()
struct = target.getPropertyValue('HoriJustify')
struct.value = value
target.setPropertyValue('HoriJustify', struct)
text_align = property(__get_text_align, __set_text_align)
def __get_font_size(self):
"""
Gets font size.
"""
return self._get_target().getPropertyValue('CharHeight')
def __set_font_size(self, value):
"""
Sets font size.
"""
return self._get_target().setPropertyValue('CharHeight', value)
font_size = property(__get_font_size, __set_font_size)
def __get_font_weight(self):
"""
Gets font weight.
"""
return self._get_target().getPropertyValue('CharWeight')
def __set_font_weight(self, value):
"""
Sets font weight.
"""
return self._get_target().setPropertyValue('CharWeight', value)
font_weight = property(__get_font_weight, __set_font_weight)
def __get_underline(self):
"""
Gets text underline.
Returns UNDERLINE_* constants.
"""
return self._get_target().getPropertyValue('CharUnderline')
def __set_underline(self, value):
"""
Sets text weight.
Accepts UNDERLINE_* constants.
"""
return self._get_target().setPropertyValue('CharUnderline', value)
underline = property(__get_underline, __set_underline)
def __get_text_color(self):
"""
Gets text color.
Color is returned as integer in format 0xAARRGGBB.
Returns None if no the text color is not set.
"""
value = self._get_target().getPropertyValue('CharColor')
if value == -1:
value = None
return value
def __set_text_color(self, value):
"""
Sets text color.
Color should be given as an integer in format 0xAARRGGBB.
Unsets the text color if None value is given.
"""
if value is None:
value = -1
return self._get_target().setPropertyValue('CharColor', value)
text_color = property(__get_text_color, __set_text_color)
def __get_background_color(self):
"""
Gets cell background color.
Color is returned as integer in format 0xAARRGGBB.
Returns None if the background color is not set.
"""
value = self._get_target().getPropertyValue('CellBackColor')
if value == -1:
value = None
return value
def __set_background_color(self, value):
"""
Sets cell background color.
Color should be given as an integer in format 0xAARRGGBB.
Unsets the background color if None value is given.
"""
if value is None:
value = -1
return self._get_target().setPropertyValue('CellBackColor', value)
background_color = property(__get_background_color, __set_background_color)
def __get_border_width(self):
"""
Gets width of all cell borders (in 1/100 mm).
Returns 0 if cell borders are different.
"""
target = self._get_target()
# Get four borders and test if all of them have same width.
keys = ('TopBorder', 'RightBorder', 'BottomBorder', 'LeftBorder')
lines = target.getPropertyValues(keys)
values = [line.OuterLineWidth for line in lines]
if any(value != values[0] for value in values):
return 0
return values[0]
def __set_border_width(self, value):
"""
Sets width of all cell borders (in 1/100 mm).
"""
target = self._get_target()
line = uno.createUnoStruct('com.sun.star.table.BorderLine2')
line.OuterLineWidth = value
# Set all four borders using one call - this can save even a few seconds
keys = ('TopBorder', 'RightBorder', 'BottomBorder', 'LeftBorder')
lines = (line, line, line, line)
target.setPropertyValues(keys, lines)
border_width = property(__get_border_width, __set_border_width)
def __get_one_border_width(self, key):
"""
Gets width of one border.
"""
target = self._get_target()
line = target.getPropertyValue(key)
return line.OuterLineWidth
def __set_one_border_width(self, value, key):
"""
Sets width of one border.
"""
target = self._get_target()
line = uno.createUnoStruct('com.sun.star.table.BorderLine2')
line.OuterLineWidth = value
target.setPropertyValue(key, line)
border_left_width = property(functools.partial(__get_one_border_width, key='LeftBorder'),
functools.partial(__set_one_border_width, key='LeftBorder'))
border_right_width = property(functools.partial(__get_one_border_width, key='RightBorder'),
functools.partial(__set_one_border_width, key='RightBorder'))
border_top_width = property(functools.partial(__get_one_border_width, key='TopBorder'),
functools.partial(__set_one_border_width, key='TopBorder'))
border_bottom_width = property(functools.partial(__get_one_border_width, key='BottomBorder'),
functools.partial(__set_one_border_width, key='BottomBorder'))
def __get_border_color(self):
"""
Gets color of all cell borders
Returns 0 if cell borders are different.
"""
target = self._get_target()
# Get four borders and test if all of them have same color.
keys = ('TopBorder', 'RightBorder', 'BottomBorder', 'LeftBorder')
lines = target.getPropertyValues(keys)
values = [line.Color for line in lines]
if any(value != values[0] for value in values):
return 0
return values[0]
def __set_border_color(self, value):
"""
Sets color of all cell borders
"""
target = self._get_target()
keys = ('TopBorder', 'RightBorder', 'BottomBorder', 'LeftBorder')
#Get current values of lines - required to save width
oldLines = target.getPropertyValues(keys)
#Change colour of all lines to value - Value is hex value of colour 0xFF00FF
for line in oldLines:
line.Color = value
lines = (oldLines[0], oldLines[1], oldLines[2], oldLines[3])
target.setPropertyValues(keys, lines)
border_color = property(__get_border_color, __set_border_color)
def __get_inner_border_width(self):
"""
Gets with of inner border between cells (in 1/100 mm).
Returns 0 if cell borders are different.
"""
target = self._get_target()
tb = target.getPropertyValue('TableBorder')
horizontal = tb.HorizontalLine.OuterLineWidth
vertical = tb.VerticalLine.OuterLineWidth
if horizontal != vertical:
return 0
return horizontal
def __set_inner_border_width(self, value):
"""
Sets with of inner border between cells (in 1/100 mm).
"""
target = self._get_target()
# Inner borders are saved in a TableBorder struct.
line = uno.createUnoStruct('com.sun.star.table.BorderLine2')
line.OuterLineWidth = value
tb = target.getPropertyValue('TableBorder')
tb.HorizontalLine = tb.VerticalLine = line
target.setPropertyValue('TableBorder', tb)
inner_border_width = property(__get_inner_border_width,
__set_inner_border_width)
# Internal methods:
def _get_target(self):
"""
Returns cursor which can be used for most of operations.
"""
address = self.address
cursor = self.sheet.cursor
return cursor.get_target(address.row, address.col,
address.row_count, address.col_count)
def _clean_value(self, value):
"""
Validates and converts value before assigning it to a cell.
"""
if value is None:
return value
return self._convert(value)
def _clean_formula(self, value):
"""
Validates and converts formula before assigning it to a cell.
"""
if value is None:
return ''
return self._convert(value)
class Cell(CellRange):
"""
One cell in a spreadsheet.
Cells are returned when a sheet (or any other tabular cell range)
is indexed by two integer numbers.
"""
__slots__ = ()
def __get_value(self):
"""
Gets cell value with as a string or number based on cell type.
"""
array = self._get_target().getDataArray()
return array[0][0]
def __set_value(self, value):
"""
Sets cell value to a string or number based on the given value.
"""
array = ((self._clean_value(value),),)
return self._get_target().setDataArray(array)
value = property(__get_value, __set_value)
def __get_formula(self):
"""
Gets a formula in this cell.
If this cell contains actual formula then the returned value starts
with an equal sign but any cell value is returned.
"""
array = self._get_target().getFormulaArray()
return array[0][0]
def __set_formula(self, formula):
"""
Sets a formula in this cell.
Any cell value can be set using this method. Actual formulas must
start with an equal sign.
"""
array = ((self._clean_formula(formula),),)
return self._get_target().setFormulaArray(array)
formula = property(__get_formula, __set_formula)
@property
def date(self):
"""
Returns date value in this cell.
Converts value from number to datetime.datetime instance.
"""
return self.sheet.document.date_from_number(self.value)
@property
def time(self):
"""
Returns time value in this cell.
Converts value from number to datetime.time instance.
"""
return self.sheet.document.time_from_number(self.value)
class TabularCellRange(CellRange):
"""
Tabular range of cells.
Individual cells can be accessed by (row, column) index and
slice notation can be used for retrieval of sub ranges.
Instances of this class are returned when a sheet (or any other tabular
cell range) is sliced in both axes.
"""
__slots__ = ()
def __get_values(self):
"""
Gets values in this cell range as a tuple of tuples.
"""
array = self._get_target().getDataArray()
return array
def __set_values(self, values):
"""
Sets values in this cell range from an iterable of iterables.
"""
# Tuple of tuples is required
array = tuple(tuple(self._clean_value(col) for col in row) for row in values)
self._get_target().setDataArray(array)
values = property(__get_values, __set_values)
def __get_formulas(self):
"""
Gets formulas in this cell range as a tuple of tuples.
If cells contain actual formulas then the returned values start
with an equal sign but all values are returned.
"""
return self._get_target().getFormulaArray()
def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable of iterables.
Any cell values can be set using this method. Actual formulas must
start with an equal sign.
"""
# Tuple of tuples is required
array = tuple(tuple(self._clean_formula(col) for col in row) for row in formulas)
self._get_target().setFormulaArray(array)
formulas = property(__get_formulas, __set_formulas)
class HorizontalCellRange(CellRange):
"""
Range of cells in one row.
Individual cells can be accessed by integer index or subranges
can be retrieved using slice notation.
Instances of this class are returned if a sheet (or any other tabular
cell range) is indexed by a row number but columns are sliced.
"""
__slots__ = ()
def __get_values(self):
"""
Gets values in this cell range as a tuple.
"""
array = self._get_target().getDataArray()
return array[0]
def __set_values(self, values):
"""
Sets values in this cell range from an iterable.
"""
array = (tuple(self._clean_value(v) for v in values),)
self._get_target().setDataArray(array)
values = property(__get_values, __set_values)
def __get_formulas(self):
"""
Gets formulas in this cell range as a tuple.
If cells contain actual formulas then the returned values start
with an equal sign but all values are returned.
"""
array = self._get_target().getFormulaArray()
return array[0]
def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable.
Any cell values can be set using this method. Actual formulas must
start with an equal sign.
"""
array = (tuple(self._clean_formula(v) for v in formulas),)
return self._get_target().setFormulaArray(array)
formulas = property(__get_formulas, __set_formulas)
class VerticalCellRange(CellRange):
"""
Range of cells in one column.
Individual cells can be accessed by integer index or or subranges
can be retrieved using slice notation.
Instances of this class are returned if a sheet (or any other tabular
cell range) is indexed by a column number but rows are sliced.
"""
__slots__ = ()
def __get_values(self):
"""
Gets values in this cell range as a tuple.
This is much more effective than reading cell values one by one.
"""
array = self._get_target().getDataArray()
return tuple(itertools.chain.from_iterable(array))
def __set_values(self, values):
"""
Sets values in this cell range from an iterable.
This is much more effective than writing cell values one by one.
"""
array = tuple((self._clean_value(v),) for v in values)
self._get_target().setDataArray(array)
values = property(__get_values, __set_values)
def __get_formulas(self):
"""
Gets formulas in this cell range as a tuple.
If cells contain actual formulas then the returned values start
with an equal sign but all values are returned.
"""
array = self._get_target().getFormulaArray()
return tuple(itertools.chain.from_iterable(array))
def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable.
Any cell values can be set using this method. Actual formulas must
start with an equal sign.
"""
array = tuple((self._clean_formula(v),) for v in formulas)
self._get_target().setFormulaArray(array)
formulas = property(__get_formulas, __set_formulas)
@str_repr
class Sheet(TabularCellRange):
"""
One sheet in a spreadsheet document.
This class extends TabularCellRange which means that cells can
be accessed using index or slice notation.
Sheet instances can be accessed using sheets property
of a SpreadsheetDocument class.
"""
__slots__ = ('document', '_target', 'cursor')
@property
def index(self):
"""
Index of this sheet in the document.
"""
# This should be cached if used more often.
return self._target.getRangeAddress().Sheet
def __get_name(self):
"""
Gets a name of this sheet.
"""
# This should be cached if used more often.
return self._target.getName();
def __set_name(self, value):
"""
Sets a name of this sheet.
"""
return self._target.setName(value);
name = property(__get_name, __set_name)
@property
class SpreadsheetCollection(NamedCollection):
"""
Collection of spreadsheets in a spreadsheet document.
Instance of this class is returned via sheets property of
the SpreadsheetDocument class.
"""
__slots__ = ('document',)
def create(self, name, index=None):
"""
Creates a new sheet with the given name.
If an optional index argument is not provided then the created
sheet is appended at the end. Returns the new sheet.
"""
if index is None:
index = len(self)
self._create(name, index)
return self[name]
def copy(self, old_name, new_name, index=None):
"""
Copies an old sheet with the old_name to a new sheet with new_name.
If an optional index argument is not provided then the created
sheet is appended at the end. Returns the new sheet.
"""
if index is None:
index = len(self)
self._copy(old_name, new_name, index)
return self[new_name]
# Internal:
class Locale(object):
"""
Document locale.
Provides locale number formats. Instances of this class can be
retrieved from SpreadsheetDocument using get_locale method.
"""
__slots__ = ('_locale', '_formats')
def format(self, code):
"""
Returns one of predefined formats.
Accepts FORMAT_* constants.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/util/XNumberFormatTypes.html#getFormatIndex
return self._formats.getFormatIndex(code, self._locale)
class SpreadsheetDocument(_UnoProxy):
"""
Spreadsheet document.
"""
def save(self, path=None, filter_name=None):
"""
Saves this document to a local file system.
The optional first argument defaults to the document's path.
Accept optional second argument which defines type of
the saved file. Use one of FILTER_* constants or see list of
available filters at http://wakka.net/archives/7 or
http://www.oooforum.org/forum/viewtopic.phtml?t=71294.
"""
if path is None:
try:
self._target.store()
except _IOException as e:
raise IOError(e.Message)
return
# UNO requires absolute paths
url = uno.systemPathToFileUrl(os.path.abspath(path))
if filter_name:
format_filter = uno.createUnoStruct('com.sun.star.beans.PropertyValue')
format_filter.Name = 'FilterName'
format_filter.Value = filter_name
filters = (format_filter,)
else:
filters = ()
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/frame/XStorable.html#storeToURL
try:
self._target.storeToURL(url, filters)
except _IOException as e:
raise IOError(e.Message)
def close(self):
"""
Closes this document.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/util/XCloseable.html#close
self._target.close(True)
def get_locale(self, language=None, country=None, variant=None):
"""
Returns locale which can be used for access to number formats.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/lang/Locale.html
locale = uno.createUnoStruct('com.sun.star.lang.Locale')
if language:
locale.Language = language
if country:
locale.Country = country
if variant:
locale.Variant = variant
formats = self._target.getNumberFormats()
return Locale(locale, formats)
@property
def sheets(self):
"""
Collection of sheets in this document.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/sheet/XSpreadsheetDocument.html#getSheets
try:
return self._sheets
except AttributeError:
target = self._target.getSheets()
self._sheets = SpreadsheetCollection(self, target)
return self._sheets
def date_from_number(self, value):
"""
Converts a float value to corresponding datetime instance.
"""
if not isinstance(value, numbers.Real):
return None
delta = datetime.timedelta(days=value)
return self._null_date + delta
def date_to_number(self, date):
"""
Converts a date or datetime instance to a corresponding float value.
"""
if isinstance(date, datetime.datetime):
delta = date - self._null_date
elif isinstance(date, datetime.date):
delta = date - self._null_date.date()
else:
raise TypeError(date)
return delta.days + delta.seconds / (24.0 * 60 * 60)
def time_from_number(self, value):
"""
Converts a float value to corresponding time instance.
"""
if not isinstance(value, numbers.Real):
return None
delta = datetime.timedelta(days=value)
minutes, second = divmod(delta.seconds, 60)
hour, minute = divmod(minutes, 60)
return datetime.time(hour, minute, second)
def time_to_number(self, time):
"""
Converts a time instance to a corresponding float value.
"""
if not isinstance(time, datetime.time):
raise TypeError(time)
return ((time.second / 60.0 + time.minute) / 60.0 + time.hour) / 24.0
# Internal:
@property
def _null_date(self):
"""
Returns date which is represented by a integer 0.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/util/NumberFormatSettings.html#NullDate
try:
return self.__null_date
except AttributeError:
number_settings = self._target.getNumberFormatSettings()
d = number_settings.getPropertyValue('NullDate')
self.__null_date = datetime.datetime(d.Year, d.Month, d.Day)
return self.__null_date
class Desktop(_UnoProxy):
"""
Access to a running to an OpenOffice.org program.
Allows to create and open of spreadsheet documents.
Opens a connection to a running OpenOffice.org program when Desktop
instance is initialized. If the program OpenOffice.org is restarted
then the connection is lost all subsequent method calls will fail.
"""
def create_spreadsheet(self):
"""
Creates a new spreadsheet document.
"""
url = 'private:factory/scalc'
document = self._open_url(url)
return SpreadsheetDocument(document)
def open_spreadsheet(self, path, as_template=False, read_only=False):
"""
Opens an exiting spreadsheet document on the local file system.
"""
extra = ()
if as_template:
pv = uno.createUnoStruct('com.sun.star.beans.PropertyValue')
pv.Name = 'AsTemplate'
pv.Value = True
extra += (pv,)
if read_only:
pv = uno.createUnoStruct('com.sun.star.beans.PropertyValue')
pv.Name = 'ReadOnly'
pv.Value = True
extra += (pv,)
# UNO requires absolute paths
url = uno.systemPathToFileUrl(os.path.abspath(path))
document = self._open_url(url, extra)
return SpreadsheetDocument(document)
class LazyDesktop(object):
"""
Lazy access to a running to Open Office program.
Provides same interface as a Desktop class but creates connection
to OpenOffice program when necessary. The advantage of this approach
is that a LazyDesktop instance can recover from a restart of
the OpenOffice.org program.
"""
cls = Desktop
def create_spreadsheet(self):
"""
Creates a new spreadsheet document.
"""
desktop = self.cls(self.hostname, self.port, self.pipe)
return desktop.create_spreadsheet()
def open_spreadsheet(self, path, as_template=False):
"""
Opens an exiting spreadsheet document on the local file system.
"""
desktop = self.cls(self.hostname, self.port)
return desktop.open_spreadsheet(path, as_template=as_template)
class NameGenerator(object):
"""
Generates valid names for Open Office.
Keeps track of used names and does not return one value twice.
Names must not contain characters []*?:\/.
Names (in older versions of OO) must have length of 31 chars maximum.
Names must be unique (case insensitive).
"""
max_length = 31
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36525,
1276,
307,
37014,
11,
4064,
82,
1813,
2637,
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7,
2539,
737,
834,
3672,
834,
8,
198,
220,
220,
220,
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1994,
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1994,
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257,
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340,
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7,
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12,
16,
11,
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11,
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16,
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48185,
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31,
2536,
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7,
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13,
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7,
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2779,
1398,
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543,
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355,
257,
15741,
284,
4725,
46,
5563,
13,
198,
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220,
220,
37227,
198,
220,
220,
220,
11593,
6649,
1747,
834,
796,
19203,
62,
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3256,
8,
628,
198,
4871,
34441,
36307,
28264,
3118,
78,
44148,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7308,
1398,
329,
17268,
9857,
416,
1111,
6376,
290,
1438,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1303,
12744,
1276,
3494,
1111,
286,
25,
198,
220,
220,
220,
1303,
2638,
1378,
2503,
13,
9654,
31810,
13,
2398,
14,
15042,
14,
31628,
14,
11321,
14,
5420,
14,
785,
14,
19155,
14,
7364,
14,
34924,
14,
55,
15732,
15457,
13,
6494,
198,
220,
220,
220,
1303,
2638,
1378,
2503,
13,
9654,
31810,
13,
2398,
14,
15042,
14,
31628,
14,
11321,
14,
5420,
14,
785,
14,
19155,
14,
7364,
14,
34924,
14,
55,
5376,
15457,
13,
6494,
628,
220,
220,
220,
11593,
6649,
1747,
834,
796,
7499,
628,
220,
220,
220,
1303,
18628,
25,
628,
198,
4871,
6031,
6713,
27996,
28264,
3118,
78,
44148,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6031,
6713,
2168,
13,
628,
220,
220,
220,
770,
1398,
3578,
284,
1630,
703,
530,
8379,
286,
3815,
357,
48126,
198,
220,
220,
220,
530,
3084,
5721,
8,
318,
9066,
287,
257,
8262,
357,
1640,
1672,
5585,
198,
220,
220,
220,
286,
530,
1627,
737,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
11593,
6649,
1747,
834,
796,
7499,
628,
220,
220,
220,
825,
11593,
1136,
62,
22704,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
284,
543,
16488,
428,
2168,
389,
8686,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
16793,
13,
1136,
21746,
11395,
10786,
31554,
271,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
22704,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
284,
543,
16488,
428,
2168,
389,
8686,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
16793,
13,
2617,
21746,
11395,
10786,
31554,
271,
3256,
1988,
8,
198,
220,
220,
220,
16488,
796,
3119,
7,
834,
1136,
62,
22704,
11,
11593,
2617,
62,
22704,
8,
628,
220,
220,
220,
825,
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1136,
62,
1370,
62,
8043,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
1627,
3124,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
16793,
13,
1136,
21746,
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10786,
13949,
10258,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
1370,
62,
8043,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
1627,
3124,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1355,
3910,
326,
428,
869,
318,
3360,
9514,
416,
4946,
27743,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
16793,
13,
2617,
21746,
11395,
10786,
13949,
10258,
3256,
1988,
8,
198,
220,
220,
220,
1627,
62,
8043,
796,
3119,
7,
834,
1136,
62,
1370,
62,
8043,
11,
11593,
2617,
62,
1370,
62,
8043,
8,
628,
220,
220,
220,
825,
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1136,
62,
20797,
62,
8043,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
6070,
3124,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
16793,
13,
1136,
21746,
11395,
10786,
33762,
10258,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
20797,
62,
8043,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
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220,
220,
220,
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13,
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7,
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62,
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2617,
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62,
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78,
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220,
47081,
1895,
284,
1981,
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13,
628,
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2262,
590,
286,
428,
1398,
318,
4504,
618,
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262,
6031,
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13,
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8,
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220,
220,
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318,
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13,
198,
220,
220,
220,
220,
220,
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220,
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198,
220,
220,
220,
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62,
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62,
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1988,
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7,
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62,
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220,
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220,
220,
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220,
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198,
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220,
220,
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220,
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29620,
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286,
428,
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13,
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198,
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220,
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1303,
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27743,
319,
26062,
366,
16485,
1453,
2736,
1,
8856,
1988,
286,
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13,
55,
31554,
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13,
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13,
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31554,
271,
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318,
2098,
284,
307,
10352,
1566,
198,
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220,
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220,
220,
220,
220,
1303,
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13,
55,
31554,
271,
13,
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284,
1729,
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1988,
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7,
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62,
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342,
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7,
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198,
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2604,
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220,
220,
220,
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283,
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7,
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1988,
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220,
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198,
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220,
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220,
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2496,
13,
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21746,
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283,
342,
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3256,
1988,
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198,
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220,
2604,
283,
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796,
3119,
7,
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11,
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8,
628,
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825,
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1136,
62,
260,
690,
276,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
1771,
428,
16488,
318,
17687,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
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198,
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7,
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1988,
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220,
220,
220,
220,
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198,
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220,
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220,
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1441,
2496,
13,
2617,
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49,
964,
325,
35,
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1988,
8,
198,
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220,
17687,
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3119,
7,
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11,
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62,
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690,
276,
8,
628,
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428,
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857,
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2346,
475,
198,
220,
220,
220,
1303,
262,
4870,
16362,
4554,
13,
1406,
1708,
5050,
290,
6608,
468,
198,
220,
220,
220,
1303,
284,
307,
23170,
4651,
287,
1502,
284,
1895,
5035,
4725,
46,
5563,
13,
628,
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220,
4808,
10134,
62,
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62,
26745,
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62,
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28264,
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543,
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13,
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198,
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6713,
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36307,
7,
944,
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8,
628,
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220,
220,
1303,
14207,
2438,
318,
2176,
284,
362,
35,
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13,
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318,
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13,
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220,
220,
220,
220,
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198,
220,
220,
220,
220,
220,
220,
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31554,
271,
7,
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8,
628,
220,
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220,
2488,
26745,
198,
220,
220,
220,
825,
331,
62,
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7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
575,
357,
9464,
8,
16488,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
575,
31554,
271,
7,
944,
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8,
628,
220,
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220,
2488,
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198,
220,
220,
220,
825,
9233,
62,
87,
62,
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7,
944,
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198,
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220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29521,
1395,
357,
4852,
8,
16488,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
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1441,
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55,
31554,
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7,
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8,
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220,
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26745,
198,
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825,
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62,
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62,
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7,
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220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
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220,
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29521,
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357,
3506,
8,
16488,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
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1441,
29521,
56,
31554,
271,
7,
944,
13557,
16793,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
271,
62,
301,
6021,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
1771,
2168,
286,
262,
16362,
389,
24167,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
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21746,
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10786,
1273,
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11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
271,
62,
301,
6021,
7,
944,
11,
1988,
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198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
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2116,
13557,
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13,
2617,
21746,
11395,
10786,
1273,
6021,
3256,
1988,
8,
198,
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220,
220,
318,
62,
301,
6021,
796,
3119,
7,
834,
1136,
62,
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62,
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6021,
11,
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2617,
62,
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62,
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6021,
8,
628,
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4871,
2409,
18683,
6713,
7,
18683,
6713,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2409,
393,
5721,
16362,
13,
628,
220,
220,
220,
5994,
286,
16362,
460,
307,
3421,
1262,
22086,
13,
3803,
62,
4906,
2446,
13,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
808,
62,
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3256,
705,
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62,
4033,
62,
9127,
11537,
628,
220,
220,
220,
825,
651,
62,
16793,
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11,
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11,
951,
11,
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62,
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11,
951,
62,
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2599,
198,
220,
220,
220,
220,
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198,
220,
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284,
262,
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290,
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287,
13,
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220,
220,
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198,
220,
220,
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1303,
770,
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318,
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329,
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597,
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198,
220,
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220,
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281,
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13,
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220,
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468,
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198,
220,
220,
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356,
1276,
772,
1445,
262,
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357,
66,
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3356,
318,
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198,
220,
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1487,
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198,
220,
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198,
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1002,
356,
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13,
198,
220,
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220,
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220,
611,
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13,
808,
1343,
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62,
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1875,
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13,
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62,
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62,
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393,
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13,
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1343,
951,
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1875,
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13,
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62,
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62,
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25,
198,
220,
220,
220,
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1303,
10028,
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284,
262,
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611,
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13,
198,
220,
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67,
12514,
796,
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532,
2116,
13,
808,
611,
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1343,
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13,
808,
62,
9127,
19841,
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13,
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62,
808,
62,
9127,
2073,
657,
198,
220,
220,
220,
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220,
951,
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67,
12514,
796,
951,
532,
2116,
13,
4033,
611,
951,
1343,
2116,
13,
4033,
62,
9127,
19841,
2116,
13,
9806,
62,
4033,
62,
9127,
2073,
657,
198,
220,
220,
220,
220,
220,
220,
220,
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220,
220,
220,
2496,
13,
70,
2069,
34519,
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4033,
62,
67,
12514,
11,
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62,
67,
12514,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
808,
15853,
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62,
67,
12514,
198,
220,
220,
220,
220,
220,
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220,
220,
220,
220,
220,
2116,
13,
4033,
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951,
62,
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12514,
198,
220,
220,
220,
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220,
220,
220,
1303,
1874,
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198,
220,
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11,
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13,
808,
62,
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11,
2116,
13,
4033,
62,
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2599,
198,
220,
220,
220,
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220,
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13,
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11,
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9127,
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198,
220,
220,
220,
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13,
808,
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198,
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13,
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62,
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796,
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198,
220,
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1303,
10028,
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11,
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13,
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198,
220,
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11,
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13,
808,
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198,
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220,
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198,
31,
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198,
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7,
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198,
220,
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198,
220,
220,
220,
13667,
286,
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287,
530,
9629,
13,
628,
220,
220,
220,
770,
318,
281,
12531,
2779,
1398,
23986,
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17512,
11244,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
8314,
407,
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4808,
3118,
78,
44148,
780,
340,
3544,
9629,
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20947,
198,
220,
220,
220,
1303,
2427,
286,
1277,
4941,
284,
4725,
46,
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13,
628,
220,
220,
220,
11593,
6649,
1747,
834,
796,
19203,
21760,
3256,
705,
21975,
11537,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
2292,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
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198,
220,
220,
220,
220,
220,
220,
220,
16331,
2292,
286,
428,
4778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
11,
2546,
796,
2496,
13,
1136,
21746,
40161,
7,
10786,
26545,
3256,
705,
10699,
6,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
21616,
26545,
13557,
6738,
62,
36909,
7,
9150,
11,
2546,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
271,
62,
647,
2004,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
1771,
4778,
389,
23791,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
3792,
13102,
2004,
3419,
198,
220,
220,
220,
825,
11593,
2617,
62,
271,
62,
647,
2004,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
1771,
4778,
389,
23791,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
1136,
62,
16793,
22446,
647,
469,
7,
8367,
8,
198,
220,
220,
220,
318,
62,
647,
2004,
796,
3119,
7,
834,
1136,
62,
271,
62,
647,
2004,
11,
11593,
2617,
62,
271,
62,
647,
2004,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
17618,
62,
18982,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
5794,
286,
3146,
287,
428,
4778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
15057,
26227,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
17618,
62,
18982,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
5794,
286,
3146,
287,
428,
4778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
15057,
26227,
3256,
1988,
8,
198,
220,
220,
220,
1271,
62,
18982,
796,
3119,
7,
834,
1136,
62,
17618,
62,
18982,
11,
11593,
2617,
62,
17618,
62,
18982,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
5239,
62,
31494,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
16021,
19114,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
530,
286,
40383,
62,
1847,
16284,
62,
9,
38491,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
39,
10145,
5703,
1958,
27691,
8367,
198,
220,
220,
220,
825,
11593,
2617,
62,
5239,
62,
31494,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
16021,
19114,
13,
628,
220,
220,
220,
220,
220,
220,
220,
21699,
82,
40383,
62,
1847,
16284,
62,
9,
38491,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
383,
6075,
72,
5703,
1958,
3119,
4909,
318,
257,
2878,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
775,
761,
284,
651,
340,
11,
4296,
1988,
290,
788,
900,
340,
736,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2878,
796,
2496,
13,
1136,
21746,
11395,
10786,
39,
10145,
5703,
1958,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
2878,
13,
8367,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
13,
2617,
21746,
11395,
10786,
39,
10145,
5703,
1958,
3256,
2878,
8,
198,
220,
220,
220,
2420,
62,
31494,
796,
3119,
7,
834,
1136,
62,
5239,
62,
31494,
11,
11593,
2617,
62,
5239,
62,
31494,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
10331,
62,
7857,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
10369,
2546,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
12441,
23106,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
10331,
62,
7857,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
10369,
2546,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
12441,
23106,
3256,
1988,
8,
198,
220,
220,
220,
10369,
62,
7857,
796,
3119,
7,
834,
1136,
62,
10331,
62,
7857,
11,
11593,
2617,
62,
10331,
62,
7857,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
10331,
62,
6551,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
10369,
3463,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
12441,
25844,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
10331,
62,
6551,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
10369,
3463,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
12441,
25844,
3256,
1988,
8,
198,
220,
220,
220,
10369,
62,
6551,
796,
3119,
7,
834,
1136,
62,
10331,
62,
6551,
11,
11593,
2617,
62,
10331,
62,
6551,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
4625,
1370,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
2420,
739,
1370,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
35219,
24027,
62,
9,
38491,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
12441,
9203,
1370,
11537,
198,
220,
220,
220,
825,
11593,
2617,
62,
4625,
1370,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
2420,
3463,
13,
628,
220,
220,
220,
220,
220,
220,
220,
21699,
82,
35219,
24027,
62,
9,
38491,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
12441,
9203,
1370,
3256,
1988,
8,
198,
220,
220,
220,
739,
1370,
796,
3119,
7,
834,
1136,
62,
4625,
1370,
11,
11593,
2617,
62,
4625,
1370,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
5239,
62,
8043,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
2420,
3124,
13,
628,
220,
220,
220,
220,
220,
220,
220,
5315,
318,
4504,
355,
18253,
287,
5794,
657,
87,
32,
26465,
38,
4579,
33,
13,
198,
220,
220,
220,
220,
220,
220,
220,
16409,
6045,
611,
645,
262,
2420,
3124,
318,
407,
900,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
12441,
10258,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
6624,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
198,
220,
220,
220,
825,
11593,
2617,
62,
5239,
62,
8043,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
2420,
3124,
13,
628,
220,
220,
220,
220,
220,
220,
220,
5315,
815,
307,
1813,
355,
281,
18253,
287,
5794,
657,
87,
32,
26465,
38,
4579,
33,
13,
198,
220,
220,
220,
220,
220,
220,
220,
791,
28709,
262,
2420,
3124,
611,
6045,
1988,
318,
1813,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
532,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
12441,
10258,
3256,
1988,
8,
198,
220,
220,
220,
2420,
62,
8043,
796,
3119,
7,
834,
1136,
62,
5239,
62,
8043,
11,
11593,
2617,
62,
5239,
62,
8043,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
25249,
62,
8043,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
2685,
4469,
3124,
13,
628,
220,
220,
220,
220,
220,
220,
220,
5315,
318,
4504,
355,
18253,
287,
5794,
657,
87,
32,
26465,
38,
4579,
33,
13,
198,
220,
220,
220,
220,
220,
220,
220,
16409,
6045,
611,
262,
4469,
3124,
318,
407,
900,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
2116,
13557,
1136,
62,
16793,
22446,
1136,
21746,
11395,
10786,
28780,
7282,
10258,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
6624,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
198,
220,
220,
220,
825,
11593,
2617,
62,
25249,
62,
8043,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
2685,
4469,
3124,
13,
628,
220,
220,
220,
220,
220,
220,
220,
5315,
815,
307,
1813,
355,
281,
18253,
287,
5794,
657,
87,
32,
26465,
38,
4579,
33,
13,
198,
220,
220,
220,
220,
220,
220,
220,
791,
28709,
262,
4469,
3124,
611,
6045,
1988,
318,
1813,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
532,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
21746,
11395,
10786,
28780,
7282,
10258,
3256,
1988,
8,
198,
220,
220,
220,
4469,
62,
8043,
796,
3119,
7,
834,
1136,
62,
25249,
62,
8043,
11,
11593,
2617,
62,
25249,
62,
8043,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
20192,
62,
10394,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
9647,
286,
477,
2685,
11637,
357,
259,
352,
14,
3064,
8085,
737,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
657,
611,
2685,
11637,
389,
1180,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3497,
1440,
11637,
290,
1332,
611,
477,
286,
606,
423,
976,
9647,
13,
198,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
19203,
9126,
34189,
3256,
705,
11028,
34189,
3256,
705,
34104,
34189,
3256,
705,
18819,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
2496,
13,
1136,
21746,
40161,
7,
13083,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
685,
1370,
13,
7975,
263,
13949,
30916,
329,
1627,
287,
3951,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
597,
7,
8367,
14512,
3815,
58,
15,
60,
329,
1988,
287,
3815,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
3815,
58,
15,
60,
198,
220,
220,
220,
825,
11593,
2617,
62,
20192,
62,
10394,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
9647,
286,
477,
2685,
11637,
357,
259,
352,
14,
3064,
8085,
737,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
555,
78,
13,
17953,
3118,
78,
44909,
10786,
785,
13,
19155,
13,
7364,
13,
11487,
13,
34189,
13949,
17,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
13,
7975,
263,
13949,
30916,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
477,
1440,
11637,
1262,
530,
869,
532,
428,
460,
3613,
772,
257,
1178,
4201,
198,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
19203,
9126,
34189,
3256,
705,
11028,
34189,
3256,
705,
34104,
34189,
3256,
705,
18819,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
357,
1370,
11,
1627,
11,
1627,
11,
1627,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
13,
2617,
21746,
40161,
7,
13083,
11,
3951,
8,
198,
220,
220,
220,
4865,
62,
10394,
796,
3119,
7,
834,
1136,
62,
20192,
62,
10394,
11,
11593,
2617,
62,
20192,
62,
10394,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
505,
62,
20192,
62,
10394,
7,
944,
11,
1994,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
9647,
286,
530,
4865,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
2496,
13,
1136,
21746,
11395,
7,
2539,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1627,
13,
7975,
263,
13949,
30916,
198,
220,
220,
220,
825,
11593,
2617,
62,
505,
62,
20192,
62,
10394,
7,
944,
11,
1988,
11,
1994,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
9647,
286,
530,
4865,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
555,
78,
13,
17953,
3118,
78,
44909,
10786,
785,
13,
19155,
13,
7364,
13,
11487,
13,
34189,
13949,
17,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
13,
7975,
263,
13949,
30916,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
13,
2617,
21746,
11395,
7,
2539,
11,
1627,
8,
628,
220,
220,
220,
4865,
62,
9464,
62,
10394,
796,
3119,
7,
12543,
310,
10141,
13,
47172,
7,
834,
1136,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
18819,
34189,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
834,
2617,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
18819,
34189,
6,
4008,
198,
220,
220,
220,
4865,
62,
3506,
62,
10394,
796,
3119,
7,
12543,
310,
10141,
13,
47172,
7,
834,
1136,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
11028,
34189,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
834,
2617,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
11028,
34189,
6,
4008,
198,
220,
220,
220,
4865,
62,
4852,
62,
10394,
796,
3119,
7,
12543,
310,
10141,
13,
47172,
7,
834,
1136,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
9126,
34189,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
834,
2617,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
9126,
34189,
6,
4008,
198,
220,
220,
220,
4865,
62,
22487,
62,
10394,
796,
3119,
7,
12543,
310,
10141,
13,
47172,
7,
834,
1136,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
34104,
34189,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
834,
2617,
62,
505,
62,
20192,
62,
10394,
11,
1994,
11639,
34104,
34189,
6,
4008,
628,
220,
220,
220,
825,
11593,
1136,
62,
20192,
62,
8043,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
3124,
286,
477,
2685,
11637,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
657,
611,
2685,
11637,
389,
1180,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3497,
1440,
11637,
290,
1332,
611,
477,
286,
606,
423,
976,
3124,
13,
198,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
19203,
9126,
34189,
3256,
705,
11028,
34189,
3256,
705,
34104,
34189,
3256,
705,
18819,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
2496,
13,
1136,
21746,
40161,
7,
13083,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
685,
1370,
13,
10258,
329,
1627,
287,
3951,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
597,
7,
8367,
14512,
3815,
58,
15,
60,
329,
1988,
287,
3815,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
3815,
58,
15,
60,
628,
220,
220,
220,
825,
11593,
2617,
62,
20192,
62,
8043,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
3124,
286,
477,
2685,
11637,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
19203,
9126,
34189,
3256,
705,
11028,
34189,
3256,
705,
34104,
34189,
3256,
705,
18819,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3855,
1459,
3815,
286,
3951,
532,
2672,
284,
3613,
9647,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
43,
1127,
796,
2496,
13,
1136,
21746,
40161,
7,
13083,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
19400,
9568,
286,
477,
3951,
284,
1988,
532,
11052,
318,
17910,
1988,
286,
9568,
657,
87,
5777,
405,
5777,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1627,
287,
1468,
43,
1127,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
13,
10258,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
357,
727,
43,
1127,
58,
15,
4357,
1468,
43,
1127,
58,
16,
4357,
1468,
43,
1127,
58,
17,
4357,
1468,
43,
1127,
58,
18,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
13,
2617,
21746,
40161,
7,
13083,
11,
3951,
8,
198,
220,
220,
220,
4865,
62,
8043,
796,
3119,
7,
834,
1136,
62,
20192,
62,
8043,
11,
11593,
2617,
62,
20192,
62,
8043,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
5083,
62,
20192,
62,
10394,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
351,
286,
8434,
4865,
1022,
4778,
357,
259,
352,
14,
3064,
8085,
737,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
657,
611,
2685,
11637,
389,
1180,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
256,
65,
796,
2496,
13,
1136,
21746,
11395,
10786,
10962,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
16021,
796,
256,
65,
13,
27991,
38342,
13949,
13,
7975,
263,
13949,
30916,
198,
220,
220,
220,
220,
220,
220,
220,
11723,
796,
256,
65,
13,
42369,
605,
13949,
13,
7975,
263,
13949,
30916,
198,
220,
220,
220,
220,
220,
220,
220,
611,
16021,
14512,
11723,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
16021,
198,
220,
220,
220,
825,
11593,
2617,
62,
5083,
62,
20192,
62,
10394,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
351,
286,
8434,
4865,
1022,
4778,
357,
259,
352,
14,
3064,
8085,
737,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
2116,
13557,
1136,
62,
16793,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
24877,
11637,
389,
7448,
287,
257,
8655,
34189,
2878,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
555,
78,
13,
17953,
3118,
78,
44909,
10786,
785,
13,
19155,
13,
7364,
13,
11487,
13,
34189,
13949,
17,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
13,
7975,
263,
13949,
30916,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
256,
65,
796,
2496,
13,
1136,
21746,
11395,
10786,
10962,
34189,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
256,
65,
13,
27991,
38342,
13949,
796,
256,
65,
13,
42369,
605,
13949,
796,
1627,
198,
220,
220,
220,
220,
220,
220,
220,
2496,
13,
2617,
21746,
11395,
10786,
10962,
34189,
3256,
256,
65,
8,
198,
220,
220,
220,
8434,
62,
20192,
62,
10394,
796,
3119,
7,
834,
1136,
62,
5083,
62,
20192,
62,
10394,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11593,
2617,
62,
5083,
62,
20192,
62,
10394,
8,
628,
220,
220,
220,
1303,
18628,
5050,
25,
628,
220,
220,
220,
825,
4808,
1136,
62,
16793,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
16409,
23493,
543,
460,
307,
973,
329,
749,
286,
4560,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2209,
796,
2116,
13,
21975,
198,
220,
220,
220,
220,
220,
220,
220,
23493,
796,
2116,
13,
21760,
13,
66,
21471,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
23493,
13,
1136,
62,
16793,
7,
21975,
13,
808,
11,
2209,
13,
4033,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2209,
13,
808,
62,
9127,
11,
2209,
13,
4033,
62,
9127,
8,
628,
220,
220,
220,
825,
4808,
27773,
62,
8367,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3254,
37051,
290,
26161,
1988,
878,
38875,
340,
284,
257,
2685,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1102,
1851,
7,
8367,
8,
628,
220,
220,
220,
825,
4808,
27773,
62,
687,
4712,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3254,
37051,
290,
26161,
10451,
878,
38875,
340,
284,
257,
2685,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
10148,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1102,
1851,
7,
8367,
8,
628,
198,
4871,
12440,
7,
28780,
17257,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1881,
2685,
287,
257,
30117,
13,
628,
220,
220,
220,
39794,
389,
4504,
618,
257,
9629,
357,
273,
597,
584,
7400,
934,
2685,
2837,
8,
198,
220,
220,
220,
318,
41497,
416,
734,
18253,
3146,
13,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
11593,
6649,
1747,
834,
796,
7499,
628,
220,
220,
220,
825,
11593,
1136,
62,
8367,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
2685,
1988,
351,
355,
257,
4731,
393,
1271,
1912,
319,
2685,
2099,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
796,
2116,
13557,
1136,
62,
16793,
22446,
1136,
6601,
19182,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
7177,
58,
15,
7131,
15,
60,
198,
220,
220,
220,
825,
11593,
2617,
62,
8367,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
2685,
1988,
284,
257,
4731,
393,
1271,
1912,
319,
262,
1813,
1988,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
796,
14808,
944,
13557,
27773,
62,
8367,
7,
8367,
828,
828,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
6601,
19182,
7,
18747,
8,
198,
220,
220,
220,
1988,
796,
3119,
7,
834,
1136,
62,
8367,
11,
11593,
2617,
62,
8367,
8,
628,
220,
220,
220,
825,
11593,
1136,
62,
687,
4712,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29620,
257,
10451,
287,
428,
2685,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1002,
428,
2685,
4909,
4036,
10451,
788,
262,
4504,
1988,
4940,
198,
220,
220,
220,
220,
220,
220,
220,
351,
281,
4961,
1051,
475,
597,
2685,
1988,
318,
4504,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
796,
2116,
13557,
1136,
62,
16793,
22446,
1136,
8479,
4712,
19182,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
7177,
58,
15,
7131,
15,
60,
198,
220,
220,
220,
825,
11593,
2617,
62,
687,
4712,
7,
944,
11,
10451,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
21394,
257,
10451,
287,
428,
2685,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4377,
2685,
1988,
460,
307,
900,
1262,
428,
2446,
13,
33520,
32126,
1276,
198,
220,
220,
220,
220,
220,
220,
220,
923,
351,
281,
4961,
1051,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
796,
14808,
944,
13557,
27773,
62,
687,
4712,
7,
687,
4712,
828,
828,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
1136,
62,
16793,
22446,
2617,
8479,
4712,
19182,
7,
18747,
8,
198,
220,
220,
220,
10451,
796,
3119,
7,
834,
1136,
62,
687,
4712,
11,
11593,
2617,
62,
687,
4712,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3128,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
16409,
3128,
1988,
287,
428,
2685,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1482,
24040,
1988,
422,
1271,
284,
4818,
8079,
13,
19608,
8079,
4554,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
21760,
13,
22897,
13,
4475,
62,
6738,
62,
17618,
7,
944,
13,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
640,
7,
944,
2599,
198,
220,
220,
220,
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] | 2.485603 | 19,691 |
# Author: Zi Wang
import cPickle as pickle
import os
import active_learners.helper as helper
from active_learners.active_learner import run_ActiveLearner
def gen_data(expid, exp, n_data, save_fnm):
'''
Generate initial data for a function associated the experiment.
Args:
expid: ID of the experiment; e.g. 0, 1, 2, ...
exp: name of the experiment; e.g. 'pour', 'scoop'.
n_data: number of data points to generate.
save_fnm: a file name string where the initial data will be
saved.
'''
print('Generating data...')
func = helper.get_func_from_exp(exp)
xx, yy = helper.gen_data(func, n_data)
pickle.dump((xx, yy), open(save_fnm, 'wb'))
def run_exp(expid, exp, method, n_init_data, iters):
'''
Run the active learning experiment.
Args:
expid: ID of the experiment; e.g. 0, 1, 2, ...
exp: name of the experiment; e.g. 'pour', 'scoop'.
method: learning method, including
'nn_classification': a classification neural network
based learning algorithm that queries the input that has
the largest output.
'nn_regression': a regression neural network based
learning algorithm that queries the input that has
the largest output.
'gp_best_prob': a Gaussian process based learning algorithm
that queries the input that has the highest probability of
having a positive function value.
'gp_lse': a Gaussian process based learning algorithm called
straddle algorithm. See B. Bryan, R. C. Nichol, C. R. Genovese,
J. Schneider, C. J. Miller, and L. Wasserman, "Active learning for
identifying function threshold boundaries," in NIPS, 2006.
'random': an algorithm that query uniformly random samples.
n_data: number of data points to generate.
save_fnm: a file name string where the initial data will be
saved.
'''
dirnm = 'data/'
if not os.path.isdir(dirnm):
os.mkdir(dirnm)
init_fnm = os.path.join(
dirnm, '{}_init_data_{}.pk'.format(exp, expid))
gen_data(expid, exp, n_init_data, init_fnm)
initx, inity = pickle.load(open(init_fnm, 'rb'))
func = helper.get_func_from_exp(exp)
active_learner = helper.get_learner_from_method(method, initx, inity, func)
# file name for saving the learning results
learn_fnm = os.path.join(
dirnm, '{}_{}_{}.pk'.format(exp, method, expid))
# get a context
context = helper.gen_context(func)
# start running the learner
print('Start running the learning experiment...')
run_ActiveLearner(active_learner, context, learn_fnm, iters)
def sample_exp(expid, exp, method):
'''
Sample from the learned model.
Args:
expid: ID of the experiment; e.g. 0, 1, 2, ...
exp: name of the experiment; e.g. 'pour', 'scoop'.
method: see run_exp.
'''
func = helper.get_func_from_exp(exp)
xx, yy, c = helper.get_xx_yy(expid, method, exp=exp)
active_learner = helper.get_learner_from_method(method, xx, yy, func)
active_learner.retrain()
# Enable gui
func.do_gui = True
while raw_input('Continue? [y/n]') == 'y':
x = active_learner.sample(c)
func(x)
if __name__ == '__main__':
exp = 'scoop'
method = 'gp_lse'
expid = 0
n_init_data = 10
iters = 50
run_exp(expid, exp, method, n_init_data, iters)
sample_exp(expid, exp, method)
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] | 2.364418 | 1,512 |
import pybullet as p
import time
import pybullet_data
from math import sin, cos
import random
physicsClient= p.connect(p.GUI)#or p.DIRECTfor non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId= p.loadURDF("plane.urdf")
robotStartPos= [0,0,1]
robotStartOrientation= p.getQuaternionFromEuler([0,0,0])
robotId= p.loadURDF("dumbo_color.urdf", robotStartPos, robotStartOrientation)
mode = p.POSITION_CONTROL
jointIndex = [i for i in range(8)]
jointIndex= 0 # 2 motor leg thigh (1)
jointIndex1= 1 # 2 motor leg calf (1)
jointIndex2= 2 # 2 motor leg thigh (2)
jointIndex3= 3 # 2 motor leg calf (2)
jointIndex4= 4 # 1 motor leg calf (1)
jointIndex5= 5 # 1 motor leg calf (2)
jointIndex6= 6 # 1 motor leg calf (3)
jointIndex7= 7 # 1 motor leg calf (4)
# original test parameters
w = 0.1 # beat parameter chould increase/decrease with 1% based on picked up beat
a = 0.4
b = 0.8
c = 0.6
# # our first walking parameters
# w = 0.02 # 2/100 # beat parameter chould increase/decrease with 1% based on picked up beat
# a = 0.5 # 120/240
# b = 0.2 # 50/240
# c = 0 # 0/240
# random.seed(8)
# assume a, c
# print(a)
# print(c)
# w = 0.2 # beat parameter chould increase/decrease with 1% based on picked up beat
# a = 0
# b = 1 #1
# c = 0 # change phase
# other continuous functions
for i in range (10000):
p.stepSimulation()
# if (i % 10 == 0):
# a = [random.random() for j in range(8)]
# b = [random.random() for j in range(8)]
# c = [random.random() for j in range(8)]
# if i >= 200:
# num_motors = random.randrange(1,8)
# motors = random.sample(range(8), num_motors)
# print(num_motors, motors)
# for n in motors:
# p.setJointMotorControl2(robotId, jointIndex[n], controlMode=mode, targetPosition=(a[n]+b[n]*sin(i*w+c[n])))
# time.sleep(1./20.)
# 2 motor leg thigh (1)
# p.setJointMotorControl2(robotId, jointIndex, controlMode=mode, targetPosition=0.4+0.8*sin(i*0.01+0.6))
# p.setJointMotorControl2(robotId, jointIndex1, controlMode=mode, targetPosition=(a+b*sin(i*w+c))) # 2 motor leg calf (1)
# p.setJointMotorControl2(robotId, jointIndex2, controlMode=mode, targetPosition=(a+b*cos(i*w+c))) # 2 motor leg thigh (2)
# p.setJointMotorControl2(robotId, jointIndex3, controlMode=mode, targetPosition=(a+b*cos(i*w+c))) # 2 motor leg calf (2)
p.setJointMotorControl2(robotId, jointIndex4, controlMode=mode, targetPosition=(a+b*sin(i*w+c))) # 1 motor leg calf (1)
p.setJointMotorControl2(robotId, jointIndex5, controlMode=mode, targetPosition=(a+b*cos(i*w+c))) # 1 motor leg calf (2)
p.setJointMotorControl2(robotId, jointIndex6, controlMode=mode, targetPosition=(a+b*sin(i*w+c))) # 1 motor leg calf (3)
p.setJointMotorControl2(robotId, jointIndex7, controlMode=mode, targetPosition=(a+b*cos(i*w+c))) # 1 motor leg calf (4)
time.sleep(1./100.) # make this dependent on song
# change dance speed with the beat
#time.sleep(w)
robotPos, robotOrn= p.getBasePositionAndOrientation(robotId)
print(robotPos, robotOrn)
p.disconnect()
# print(p.getNumJoints(robotId)) | [
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# -*- coding: utf-8 -*-
#
# Dell EMC OpenManage Ansible Modules
# Version 2.1.3
# Copyright (C) 2020 Dell Inc. or its subsidiaries. All Rights Reserved.
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
#
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import pytest
import json
from ansible_collections.dellemc.openmanage.plugins.modules import ome_network_vlan_info
from ansible_collections.dellemc.openmanage.tests.unit.plugins.modules.common import FakeAnsibleModule, Constants
from ansible.module_utils.six.moves.urllib.error import URLError, HTTPError
from ansible.module_utils.urls import ConnectionError, SSLValidationError
from io import StringIO
from ansible.module_utils._text import to_text
MODULE_PATH = 'ansible_collections.dellemc.openmanage.plugins.modules.'
response = {
'@odata.context': '/api/$metadata#Collection(NetworkConfigurationService.Network)',
'@odata.count': 1,
'value': [
{
'@odata.type': '#NetworkConfigurationService.Network',
'@odata.id': '/api/NetworkConfigurationService/Networks(20057)',
'Id': 20057,
'Name': 'Logical Network - 1',
'Description': 'Description of Logical Network - 1',
'VlanMaximum': 111,
'VlanMinimum': 111,
"Type": 1,
'CreatedBy': 'admin',
'CreationTime': '2020-09-02 18:48:42.129',
'UpdatedBy': None,
'UpdatedTime': '2020-09-02 18:48:42.129',
'InternalRefNWUUId': '42b9903d-93f8-4184-adcf-0772e4492f71'
}
]
}
network_type_qos_type_dict_reponse = {1: {'Id': 1, 'Name': 'General Purpose (Bronze)',
'Description':
'This is the network for general purpose traffic. QOS Priority : Bronze.',
'VendorCode': 'GeneralPurpose', 'NetworkTrafficType': 'Ethernet',
'QosType': {'Id': 4, 'Name': 'Bronze'}}}
network_type_dict_response = {1: {'Id': 1, 'Name': 'General Purpose (Bronze)',
'Description':
'This is the network for general purpose traffic. QOS Priority : Bronze.',
'VendorCode': 'GeneralPurpose', 'NetworkTrafficType': 'Ethernet',
'QosType': 4}}
qos_type_dict_response = {4: {'Id': 4, 'Name': 'Bronze'}}
type_dict_ome_reponse = {'@odata.context': '/api/$metadata#Collection(NetworkConfigurationService.Network)',
'@odata.count': 1,
'value': [
{'@odata.type': '#NetworkConfigurationService.NetworkType',
'@odata.id': '/api/NetworkConfigurationService/NetworkTypes(1)',
'Id': 1,
'Name': 'General Purpose (Bronze)',
'Description': 'This is the network for general purpose traffic. QOS Priority : Bronze.',
'VendorCode': 'GeneralPurpose', 'NetworkTrafficType': 'Ethernet',
'QosType': 4}]}
class TestOmeNetworkVlanInfo(FakeAnsibleModule):
"""Pytest class for ome_network_vlan_info module."""
module = ome_network_vlan_info
@pytest.fixture
@pytest.mark.parametrize("exc_type", [URLError, HTTPError, SSLValidationError, ConnectionError,
TypeError, ValueError])
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] | 2.070326 | 1,749 |
# <<BEGIN-copyright>>
# Copyright 2021, Lawrence Livermore National Security, LLC.
# See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: BSD-3-Clause
# <<END-copyright>>
from math import sqrt
from brownies.legacy.toENDF6 import endfFormats as endfFormatsModule
from brownies.legacy.converting.ENDFToGNDS import ENDF_ITYPE_4
from PoPs.decays import decayData as decayDataModule
from PoPs.decays import spectrum as spectrumModule
RTYPdict = {}
for key, value in ENDF_ITYPE_4.decayType.items():
RTYPdict[value] = key
STYPdict = {}
for key, value in ENDF_ITYPE_4.STYPProduct.items():
STYPdict[value] = key
decayDataModule.decayData.toENDF6 = toENDF6
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12964,
8068,
62,
9050,
11401,
62,
19,
13,
12501,
323,
6030,
13,
23814,
33529,
198,
220,
220,
220,
371,
9936,
47,
11600,
58,
8367,
60,
796,
1994,
198,
198,
2257,
48232,
11600,
796,
23884,
198,
1640,
1994,
11,
1988,
287,
12964,
8068,
62,
9050,
11401,
62,
19,
13,
2257,
56,
10246,
2076,
310,
13,
23814,
33529,
198,
220,
220,
220,
3563,
48232,
11600,
58,
8367,
60,
796,
1994,
628,
198,
12501,
323,
6601,
26796,
13,
12501,
323,
6601,
13,
1462,
1677,
8068,
21,
796,
284,
1677,
8068,
21,
198
] | 2.762097 | 248 |
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