content
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1.04M
| input_ids
sequencelengths 1
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| ratio_char_token
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int64 1
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|---|---|---|---|
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
data = np.genfromtxt('example-log.csv', delimiter = ',', skip_header = 4, names = ['t', 'T'])
plt.plot(data['t'] / 1e3, data['T'])
plt.ylabel('T/°C')
plt.xlabel('t/s')
plt.show()
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] | 2.256637 | 113 |
from collections import defaultdict
from pycoingecko import CoinGeckoAPI
from net_worth_tracker.utils import euro_per_dollar
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from __future__ import absolute_import
from __future__ import print_function
import argparse
import os
import sys
from mimic3benchmark.subject import read_stays, read_diagnoses, read_events, get_events_for_stay, add_hours_elpased_to_events
from mimic3benchmark.subject import convert_events_to_timeseries, get_first_valid_from_timeseries
from mimic3benchmark.preprocessing import read_itemid_to_variable_map, map_itemids_to_variables, read_variable_ranges, clean_events
from mimic3benchmark.preprocessing import transform_gender, transform_ethnicity, assemble_episodic_data
parser = argparse.ArgumentParser(description='Extract episodes from per-subject data.')
parser.add_argument('subjects_root_path', type=str, help='Directory containing subject sub-directories.')
parser.add_argument('--variable_map_file', type=str,
default=os.path.join(os.path.dirname(__file__), '../resources/itemid_to_variable_map.csv'),
help='CSV containing ITEMID-to-VARIABLE map.')
parser.add_argument('--reference_range_file', type=str,
default=os.path.join(os.path.dirname(__file__), '../resources/variable_ranges.csv'),
help='CSV containing reference ranges for VARIABLEs.')
parser.add_argument('--verbose', '-v', type=int, help='Level of verbosity in output.', default=1)
args, _ = parser.parse_known_args()
var_map = read_itemid_to_variable_map(args.variable_map_file)
variables = var_map.VARIABLE.unique()
for subject_dir in os.listdir(args.subjects_root_path):
dn = os.path.join(args.subjects_root_path, subject_dir)
try:
subject_id = int(subject_dir)
if not os.path.isdir(dn):
raise Exception
except:
continue
sys.stdout.write('Subject {}: '.format(subject_id))
sys.stdout.flush()
try:
sys.stdout.write('reading...')
sys.stdout.flush()
stays = read_stays(os.path.join(args.subjects_root_path, subject_dir))
diagnoses = read_diagnoses(os.path.join(args.subjects_root_path, subject_dir))
events = read_events(os.path.join(args.subjects_root_path, subject_dir))
except:
sys.stdout.write('error reading from disk!\n')
continue
else:
sys.stdout.write('got {0} stays, {1} diagnoses, {2} events...'.format(stays.shape[0], diagnoses.shape[0], events.shape[0]))
sys.stdout.flush()
episodic_data = assemble_episodic_data(stays, diagnoses)
sys.stdout.write('cleaning and converting to time series...')
sys.stdout.flush()
events = map_itemids_to_variables(events, var_map)
events = clean_events(events)
if events.shape[0] == 0:
sys.stdout.write('no valid events!\n')
continue
timeseries = convert_events_to_timeseries(events, variables=variables)
sys.stdout.write('extracting separate episodes...')
sys.stdout.flush()
for i in range(stays.shape[0]):
stay_id = stays.ICUSTAY_ID.iloc[i]
sys.stdout.write(' {}'.format(stay_id))
sys.stdout.flush()
intime = stays.INTIME.iloc[i]
outtime = stays.OUTTIME.iloc[i]
episode = get_events_for_stay(timeseries, stay_id, intime, outtime)
if episode.shape[0] == 0:
sys.stdout.write(' (no data!)')
sys.stdout.flush()
continue
episode = add_hours_elpased_to_events(episode, intime).set_index('HOURS').sort_index(axis=0)
episodic_data.Weight.loc[stay_id] = get_first_valid_from_timeseries(episode, 'Weight')
episodic_data.Height.loc[stay_id] = get_first_valid_from_timeseries(episode, 'Height')
episodic_data.loc[episodic_data.index==stay_id].to_csv(os.path.join(args.subjects_root_path, subject_dir, 'episode{}.csv'.format(i+1)), index_label='Icustay')
columns = list(episode.columns)
columns_sorted = sorted(columns, key=(lambda x: "" if x == "Hours" else x))
episode = episode[columns_sorted]
episode.to_csv(os.path.join(args.subjects_root_path, subject_dir, 'episode{}_timeseries.csv'.format(i+1)), index_label='Hours')
sys.stdout.write(' DONE!\n')
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] | 2.470836 | 1,663 |
""" Main module to start the catsleep tool """
import os
import sys
from catsleep.cat import catsleep as ct
def start_catsleep():
""" Starting point of catsleep """
catsp = ct.CatSleep()
catsp.catsleep_control()
if __name__ == '__main__':
start_catsleep()
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###################################################################
# Copyright (c) 2016 by TAOS Technologies, Inc.
# All rights reserved.
#
# This file is proprietary and confidential to TAOS Technologies.
# No part of this file may be reproduced, stored, transmitted,
# disclosed or used in any form or by any means other than as
# expressly provided by the written permission from Jianhui Tao
#
###################################################################
# -*- coding: utf-8 -*-
import sys
import os
import time
import datetime
import inspect
import psutil
import shutil
import pandas as pd
from util.log import *
tdSql = TDSql() | [
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# Generated by Django 2.2.4 on 2020-04-04 15:19
from django.db import migrations, models
import django.db.models.deletion
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from __future__ import unicode_literals
import nose
from django.core.files.uploadedfile import SimpleUploadedFile
from kgb import SpyAgency
from reviewboard.admin.import_utils import has_module
from reviewboard.diffviewer.diffutils import (get_original_file,
get_patched_file,
patch)
from reviewboard.diffviewer.forms import UploadDiffForm
from reviewboard.scmtools.models import Repository, Tool
from reviewboard.testing import TestCase
class UploadDiffFormTests(SpyAgency, TestCase):
"""Unit tests for UploadDiffForm."""
fixtures = ['test_scmtools']
def test_create(self):
"""Testing UploadDiffForm.create"""
diff_file = SimpleUploadedFile('diff', self.DEFAULT_GIT_FILEDIFF_DATA,
content_type='text/x-patch')
repository = self.create_repository(tool_name='Test')
self.spy_on(repository.get_file_exists,
call_fake=lambda *args, **kwargs: True)
form = UploadDiffForm(
repository=repository,
data={
'basedir': '/',
'base_commit_id': '1234',
},
files={
'path': diff_file,
})
self.assertTrue(form.is_valid())
diffset = form.create(diff_file)
self.assertEqual(diffset.files.count(), 1)
self.assertEqual(diffset.basedir, '/')
self.assertEqual(diffset.base_commit_id, '1234')
def test_create_filters_parent_diffs(self):
"""Testing UploadDiffForm.create filters parent diff files"""
saw_file_exists = {}
parent_diff_1 = (
b'diff --git a/README b/README\n'
b'index d6613f4..5b50865 100644\n'
b'--- README\n'
b'+++ README\n'
b'@@ -2 +2 @@\n'
b'-blah..\n'
b'+blah blah\n'
)
parent_diff_2 = (
b'diff --git a/UNUSED b/UNUSED\n'
b'index 1234567..5b50866 100644\n'
b'--- UNUSED\n'
b'+++ UNUSED\n'
b'@@ -1,1 +1,1 @@\n'
b'-foo\n'
b'+bar\n'
)
parent_diff = parent_diff_1 + parent_diff_2
diff_file = SimpleUploadedFile('diff', self.DEFAULT_GIT_FILEDIFF_DATA,
content_type='text/x-patch')
parent_diff_file = SimpleUploadedFile('parent_diff', parent_diff,
content_type='text/x-patch')
repository = self.create_repository(tool_name='Test')
self.spy_on(repository.get_file_exists, call_fake=get_file_exists)
form = UploadDiffForm(
repository=repository,
data={
'basedir': '/',
},
files={
'path': diff_file,
'parent_diff_path': parent_diff_file,
})
self.assertTrue(form.is_valid())
diffset = form.create(diff_file, parent_diff_file)
self.assertEqual(diffset.files.count(), 1)
filediff = diffset.files.get()
self.assertEqual(filediff.diff, self.DEFAULT_GIT_FILEDIFF_DATA)
self.assertEqual(filediff.parent_diff, parent_diff_1)
self.assertIn(('/README', 'd6613f4'), saw_file_exists)
self.assertNotIn(('/UNUSED', '1234567'), saw_file_exists)
self.assertEqual(len(saw_file_exists), 1)
def test_create_with_parser_get_orig_commit_id(self):
"""Testing UploadDiffForm.create uses correct base revision returned
by DiffParser.get_orig_commit_id
"""
diff = (
b'# Node ID a6fc203fee9091ff9739c9c00cd4a6694e023f48\n'
b'# Parent 7c4735ef51a7c665b5654f1a111ae430ce84ebbd\n'
b'diff --git a/doc/readme b/doc/readme\n'
b'--- a/doc/readme\n'
b'+++ b/doc/readme\n'
b'@@ -1,3 +1,3 @@\n'
b' Hello\n'
b'-\n'
b'+...\n'
b' goodbye\n'
)
parent_diff = (
b'# Node ID 7c4735ef51a7c665b5654f1a111ae430ce84ebbd\n'
b'# Parent 661e5dd3c4938ecbe8f77e2fdfa905d70485f94c\n'
b'diff --git a/doc/newfile b/doc/newfile\n'
b'new file mode 100644\n'
b'--- /dev/null\n'
b'+++ b/doc/newfile\n'
b'@@ -0,0 +1,1 @@\n'
b'+Lorem ipsum\n'
)
if not has_module('mercurial'):
raise nose.SkipTest("Hg is not installed")
diff_file = SimpleUploadedFile('diff', diff,
content_type='text/x-patch')
parent_diff_file = SimpleUploadedFile('parent_diff', parent_diff,
content_type='text/x-patch')
repository = Repository.objects.create(
name='Test HG',
path='scmtools/testdata/hg_repo',
tool=Tool.objects.get(name='Mercurial'))
form = UploadDiffForm(
repository=repository,
files={
'path': diff_file,
'parent_diff_path': parent_diff_file,
})
self.assertTrue(form.is_valid())
diffset = form.create(diff_file, parent_diff_file)
self.assertEqual(diffset.files.count(), 1)
filediff = diffset.files.get()
self.assertEqual(filediff.source_revision,
'661e5dd3c4938ecbe8f77e2fdfa905d70485f94c')
def test_create_with_parent_filediff_with_move_and_no_change(self):
"""Testing UploadDiffForm.create with a parent diff consisting only
of a move/rename without content change
"""
revisions = [
b'93e6b3e8944c48737cb11a1e52b046fa30aea7a9',
b'4839fc480f47ca59cf05a9c39410ea744d1e17a2',
]
parent_diff = SimpleUploadedFile(
'parent_diff',
(b'diff --git a/foo b/bar\n'
b'similarity index 100%%\n'
b'rename from foo\n'
b'rename to bar\n'),
content_type='text/x-patch')
diff = SimpleUploadedFile(
'diff',
(b'diff --git a/bar b/bar\n'
b'index %s..%s 100644\n'
b'--- a/bar\n'
b'+++ b/bar\n'
b'@@ -1,2 +1,3 @@\n'
b' Foo\n'
b'+Bar\n') % (revisions[0], revisions[1]),
content_type='text/x-patch')
repository = self.create_repository(tool_name='Test')
self.spy_on(repository.get_file_exists,
call_fake=lambda *args, **kwargs: True)
# We will only be making one call to get_file and we can fake it out.
self.spy_on(repository.get_file,
call_fake=lambda *args, **kwargs: b'Foo\n')
self.spy_on(patch)
form = UploadDiffForm(
repository=repository,
data={
'basedir': '/',
},
files={
'path': diff,
'parent_diff_path': parent_diff,
})
self.assertTrue(form.is_valid())
diffset = form.create(diff, parent_diff)
self.assertEqual(diffset.files.count(), 1)
f = diffset.files.get()
self.assertEqual(f.source_revision, revisions[0])
self.assertEqual(f.dest_detail, revisions[1])
# We shouldn't call out to patch because the parent diff is just a
# rename.
original_file = get_original_file(f, None, ['ascii'])
self.assertEqual(original_file, b'Foo\n')
self.assertFalse(patch.spy.called)
patched_file = get_patched_file(original_file, f, None)
self.assertEqual(patched_file, b'Foo\nBar\n')
self.assertTrue(patch.spy.called)
def test_create_with_parent_filediff_with_move_and_change(self):
"""Testing UploadDiffForm.create with a parent diff consisting of a
move/rename with content change
"""
revisions = [
b'93e6b3e8944c48737cb11a1e52b046fa30aea7a9',
b'4839fc480f47ca59cf05a9c39410ea744d1e17a2',
b'04861c126cfebd7e7cb93045ab0bff4a7acc4cf2',
]
parent_diff = SimpleUploadedFile(
'parent_diff',
(b'diff --git a/foo b/bar\n'
b'similarity index 55%%\n'
b'rename from foo\n'
b'rename to bar\n'
b'index %s..%s 100644\n'
b'--- a/foo\n'
b'+++ b/bar\n'
b'@@ -1,2 +1,3 @@\n'
b' Foo\n'
b'+Bar\n') % (revisions[0], revisions[1]),
content_type='text/x-patch')
diff = SimpleUploadedFile(
'diff',
(b'diff --git a/bar b/bar\n'
b'index %s..%s 100644\n'
b'--- a/bar\n'
b'+++ b/bar\n'
b'@@ -1,3 +1,4 @@\n'
b' Foo\n'
b' Bar\n'
b'+Baz\n') % (revisions[1], revisions[2]),
content_type='text/x-patch')
repository = self.create_repository(tool_name='Test')
self.spy_on(repository.get_file_exists,
call_fake=lambda *args, **kwargs: True)
# We will only be making one call to get_file and we can fake it out.
self.spy_on(repository.get_file,
call_fake=lambda *args, **kwargs: b'Foo\n')
self.spy_on(patch)
form = UploadDiffForm(
repository=repository,
data={
'basedir': '/',
},
files={
'path': diff,
'parent_diff_path': parent_diff,
})
self.assertTrue(form.is_valid())
diffset = form.create(diff, parent_diff)
self.assertEqual(diffset.files.count(), 1)
f = diffset.files.get()
self.assertEqual(f.source_revision, revisions[0])
self.assertEqual(f.dest_detail, revisions[2])
original_file = get_original_file(f, None, ['ascii'])
self.assertEqual(original_file, b'Foo\nBar\n')
self.assertTrue(patch.spy.called)
patched_file = get_patched_file(original_file, f, None)
self.assertEqual(patched_file, b'Foo\nBar\nBaz\n')
self.assertEqual(len(patch.spy.calls), 2)
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] | 1.846278 | 5,562 |
from django.contrib.auth.models import Permission
from graphene import ID, ClientIDMutation, Field, ResolveInfo, String
from graphql import GraphQLError
from graphql_jwt.decorators import login_required, permission_required, staff_member_required
from graphql_relay import from_global_id
from .models import Article, Publication, Reporter
from .types import ArticleNode, PublicationNode, ReporterNode
# Reporter
# ^^^^^^^^
class UpdateReporter(ClientIDMutation):
"""
A reporter can only update his/her own details if he/she has `Can change reporter` permission
"""
reporter = Field(ReporterNode)
@classmethod
@permission_required('starter.change_reporter')
# Publication
# ^^^^^^^^^^^
# Article
# ^^^^^^^
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] | 3.39726 | 219 |
import unittest
from TestUtils import TestChecker
from AST import *
from StaticError import *
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] | 3.62963 | 27 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Implements grpc modules"""
import time
import grpc
import service.service_pb2 as bot_pb
from service import service_pb2_grpc
from EshebaBot.esheba import EshebaBot
from concurrent.futures import ThreadPoolExecutor
# end class
def run_server():
'''Runs the grpc server'''
port = '5000'
server = grpc.server(ThreadPoolExecutor(max_workers=10))
service_pb2_grpc.add_BotServiceServicer_to_server(BotService(), server)
server.add_insecure_port('[::]:' + port)
server.start()
print('Server running at http://localhost:%s' % port)
while True:
time.sleep(100)
# end white
input('Press enter to stop the server...')
server.stop(True)
# end def
if __name__ == '__main__':
run_server()
# end if
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#!/usr/bin/env python
"""
date2dec : Converts calendar dates into decimal dates.
This module was written by Arndt Piayda and then enhanced and
maintained by Matthias Cuntz while at Department of Computational
Hydrosystems, Helmholtz Centre for Environmental Research - UFZ,
Leipzig, Germany, and continued by Matthias Cuntz while at Institut
National de Recherche pour l'Agriculture, l'Alimentation et
l'Environnement (INRAE), Nancy, France.
Copyright (c) 2010-2020 Matthias Cuntz - mc (at) macu (dot) de
Released under the MIT License; see LICENSE file for details.
* Written Jun 2010 by Arndt Piayda
* Input can be scalar, list, array, or mix of it, Feb 2012, Matthias Cuntz
* Changed checks, added calendars decimal and decimal360, Feb 2012, Matthias Cuntz
* Changed units of proleptic_gregorian calendar from days since 0001-01-01 00:00:00 to days since 0001-01-00 00:00:00, Dec 2010, Matthias Cuntz
* Deal with Excel leap year error, Feb 2013, Matthias Cuntz
* Ported to Python 3, Feb 2013, Matthias Cuntz
* ascii/eng without time defaults to 00:00:00, Jul 2013, Matthias Cuntz
* Excel starts at 1 not at 0 on 01 January 1900 or 1904, Oct 2013, Matthias Cuntz
* Bug: 01.01.0001 was substracted if Julian calendar even with units given, Oct 2013, Matthias Cuntz
* Removed remnant of time treatment before time check in eng keyword, Nov 2013, Matthias Cuntz
* Adapted to new netCDF4/netcdftime (>= v1.0) and datetime (>= Python v2.7.9), Jun 2015, Matthias Cuntz
* Call date2num with list instead of single netCDF4.datetime objects, Oct 2015, Matthias Cuntz
* mo for months always integer, Oct 2016, Matthias Cuntz
* 00, 01, etc. for integers not accepted by Python 3, removed from examples and code, Nov 2016, Matthias Cuntz
* Using numpy docstring format, May 2020, Matthias Cuntz
* Succeed eng by en keyword as in ascii2ascii and dec2date, Jul 2020, Matthias Cuntz
* proleptic_gregorian instead of gregorian calendar for Excel dates, Jul 2020, Matthias Cuntz
.. moduleauthor:: Matthias Cuntz, Arndt Piayda
The following functions are provided
.. autosummary::
date2dec
"""
from __future__ import division, absolute_import, print_function
import numpy as np
__all__ = ['date2dec']
def date2dec(calendar = 'standard', units=None,
excelerr = True, yr=1,
mo=1, dy=1, hr=0, mi=0, sc=0,
ascii=None, en=None, eng=None):
"""
Convert scalar and array_like with calendar dates into decimal
dates. Supported calendar formats are standard, gregorian, julian,
proleptic_gregorian, excel1900, excel1904, 365_day, noleap, 366_day,
all_leap, 360_day, decimal, or decimal360.
Input is year, month day, hour, minute, second or a combination of them.
Input as date string is possible.
Output is decimal date with day as unit.
Parameters
----------
yr : array_like, optional
years (default: 1)
mo : array_like, optional
month (default: 1)
dy : array_like, optional
days (default: 1)
hr : array_like, optional
hours (default: 0)
mi : array_like, optional
minutes (default: 0)
sc : array_like, optional
seconds (default: 0)
ascii : array_like, optional
strings of the format 'dd.mm.yyyy hh:mm:ss'.
Missing hour, minutes and/or seconds are set
to their default values (0).
`ascii` overwrites all other keywords.
`ascii` and `eng` are mutually exclusive.
en : array_like, optional
strings of the format 'yyyy-mm-dd hh:mm:ss'.
Missing hour, minutes and/or seconds are set
to their default values (0).
`en` overwrites all other keywords.
`en` and `ascii` are mutually exclusive.
eng : array_like, optional
Same as en: obsolete.
calendar : str, optional
Calendar of output dates (default: 'standard').
Possible values are:
'standard', 'gregorian' = julian calendar from
01.01.-4712 12:00:00 (BC) until 05.03.1583 00:00:00 and
gregorian calendar from 15.03.1583 00:00:00 until now.
Missing 10 days do not exsist.
'julian' = julian calendar from 01.01.-4712 12:00:00 (BC)
until now.
'proleptic_gregorian' = gregorian calendar from
01.01.0001 00:00:00 until now.
'excel1900' = Excel dates with origin at
01.01.1900 00:00:00.
'excel1904' = Excel 1904 (Lotus) format.
Same as excel1904 but with origin at
01.01.1904 00:00:00.
'365_day', 'noleap' = 365 days format,
i.e. common years only (no leap years)
with origin at 01.01.0001 00:00:00.
'366_day', 'all_leap' = 366 days format,
i.e. leap years only (no common years)
with origin at 01.01.0001 00:00:00.
'360_day' = 360 days format,
i.e. years with only 360 days (30 days per month)
with origin at 01.01.0001 00:00:00.
'decimal' = decimal year instead of decimal days.
'decimal360' = decimal year with a year of 360 days, i.e. 12 month with 30 days each.
units : str, optional
User set units of output dates. Must be a
string in the format 'days since yyyy-mm-dd hh:mm:ss'.
Default values are set automatically depending on `calendar`.
excelerr : bool, optional
In Excel, the year 1900 is normally considered a leap year,
which it was not. By default, this error is taken into account
if `calendar=='excel1900'` (default: True).
1900 is not considered a leap year if `excelerr==False`.
Returns
-------
array_like
array_like with decimal dates. The type of output will be the same as the input type.
Notes
-----
Most versions of `datetime` do not support negative years,
i.e. Julian days < 1721423.5 = 01.01.0001 00:00:00.
There is an issue in `netcdftime` version < 0.9.5 in proleptic_gregorian for dates before year 301:
dec2date(date2dec(ascii='01.01.0300 00:00:00', calendar='proleptic_gregorian'), calendar='proleptic_gregorian')
[300, 1, 2, 0, 0, 0]
dec2date(date2dec(ascii='01.01.0301 00:00:00', calendar='proleptic_gregorian'), calendar='proleptic_gregorian')
[301, 1, 1, 0, 0, 0]
List input is only supported up to 2 dimensions.
Requires `netcdftime.py` from module `netcdftime` available at:
http://netcdf4-python.googlecode.com
Examples
--------
# Some implementations of datetime do not support negative years
>>> import datetime
>>> if datetime.MINYEAR > 0:
... print('The minimum year in your datetime implementation is ', datetime.MINYEAR)
... print('i.e. it does not support negative years (BC).')
The minimum year in your datetime implementation is 1
i.e. it does not support negative years (BC).
>>> if datetime.MINYEAR > 0:
... year = np.array([2000, 1810, 1630, 1510, 1271, 619, 2, 1])
... else:
... year = np.array([2000, 1810, 1630, 1510, 1271, 619, -1579, -4712])
>>> month = np.array([1, 4, 7, 9, 3, 8, 8, 1])
>>> day = np.array([5, 24, 15, 20, 18, 27, 23, 1])
>>> hour = np.array([12, 16, 10, 14, 19, 11, 20, 12])
>>> minute = np.array([30, 15, 20, 35, 41, 8, 3, 0])
>>> second = np.array([15, 10, 40, 50, 34, 37, 41, 0])
>>> decimal = date2dec(calendar = 'standard', yr=year, mo=month, dy=day, hr=hour, mi=minute, sc=second)
>>> nn = year.size
>>> print('{:.14e} {:.14e} {:.14e} {:.14e}'.format(*decimal[:nn//2]))
2.45154902100695e+06 2.38226217719907e+06 2.31660093101852e+06 2.27284810821759e+06
>>> print('{:.14e} {:.14e}'.format(*decimal[nn//2:nn-2]))
2.18536732053241e+06 1.94738596431713e+06
>>> decimal = date2dec(calendar='standard', yr=year, mo=6, dy=15, hr=12, mi=minute, sc=second)
>>> print('{:.14e} {:.14e} {:.14e} {:.14e}'.format(*decimal[:nn//2]))
2.45171102100695e+06 2.38231401053241e+06 2.31657101435185e+06 2.27275102488426e+06
>>> print('{:.14e} {:.14e}'.format(*decimal[nn//2:nn-2]))
2.18545602886574e+06 1.94731300598380e+06
# ascii input
>>> if datetime.MINYEAR > 0:
... a = np.array(['05.01.2000 12:30:15', '24.04.1810 16:15:10', '15.07.1630 10:20:40', '20.09.1510 14:35:50',
... '18.03.1271 19:41:34', '27.08. 619 11:08:37', '23.08.0002 20:03:41', '01.01.0001 12:00:00'])
... else:
... a = np.array(['05.01.2000 12:30:15', '24.04.1810 16:15:10', '15.07.1630 10:20:40', '20.09.1510 14:35:50',
... '18.03.1271 19:41:34', '27.08. 619 11:08:37', '23.08.-1579 20:03:41', '01.01.-4712 12:00:00'])
>>> decimal = date2dec(calendar='standard', ascii=a)
>>> nn = a.size
>>> print('{:.14e} {:.14e} {:.14e} {:.14e}'.format(*decimal[:nn//2]))
2.45154902100695e+06 2.38226217719907e+06 2.31660093101852e+06 2.27284810821759e+06
>>> print('{:.14e} {:.14e}'.format(*decimal[nn//2:nn-2]))
2.18536732053241e+06 1.94738596431713e+06
# calendar = 'julian'
>>> decimal = date2dec(calendar='julian', ascii=a)
>>> print('{:.14e} {:.14e} {:.14e} {:.14e}'.format(*decimal[:nn//2]))
2.45156202100695e+06 2.38227417719907e+06 2.31661093101852e+06 2.27284810821759e+06
>>> print('{:.14e} {:.14e}'.format(*decimal[nn//2:nn-2]))
2.18536732053241e+06 1.94738596431713e+06
# calendar = 'proleptic_gregorian'
>>> decimal = date2dec(calendar='proleptic_gregorian', ascii=a)
>>> print('{:.7f} {:.7f} {:.7f} {:.7f}'.format(*decimal[:nn//2]))
730123.5210069 660836.6771991 595175.4310185 551412.6082176
>>> print('{:.7f} {:.7f}'.format(*decimal[nn//2:nn-2]))
463934.8205324 225957.4643171
# calendar = 'excel1900' WITH excelerr=True -> 1900 considered as leap year
>>> d = np.array(['05.01.2000 12:30:15', '27.05.1950 16:25:10', '13.08.1910 10:40:55',
... '01.03.1900 00:00:00', '29.02.1900 00:00:00', '28.02.1900 00:00:00',
... '01.01.1900 00:00:00'])
>>> decimal = date2dec(calendar='excel1900', ascii=d)
>>> nn = d.size
>>> print('{:.7f} {:.7f} {:.7f}'.format(*decimal[:nn//2]))
36530.5210069 18410.6841435 3878.4450810
>>> print('{:.1f} {:.1f} {:.1f} {:.1f}'.format(*decimal[nn//2:]))
61.0 60.0 59.0 1.0
# calendar = 'excel1900' WITH excelerr = False -> 1900 is NO leap year
>>> decimal = date2dec(calendar='excel1900', ascii=d, excelerr=False)
>>> print('{:.7f} {:.7f} {:.7f}'.format(*decimal[:nn//2]))
36529.5210069 18409.6841435 3877.4450810
>>> print('{:.1f} {:.1f} {:.1f} {:.1f}'.format(*decimal[nn//2:]))
60.0 60.0 59.0 1.0
# calendar = 'excel1904'
>>> decimal = date2dec(calendar='excel1904', ascii=d[:nn//2])
>>> print('{:.7f} {:.7f} {:.7f}'.format(*decimal[:nn//2]))
35069.5210069 16949.6841435 2417.4450810
# calendar = '365_day'
>>> g = np.array(['18.08.1972 12:30:15', '25.10.0986 12:30:15', '28.11.0493 22:20:40', '01.01.0001 00:00:00'])
>>> decimal = date2dec(calendar='365_day', ascii=g)
>>> nn = g.size
>>> print('{:.7f} {:.7f} {:.7f} {:.7f}'.format(*decimal[:nn]))
719644.5210069 359822.5210069 179911.9310185 0.0000000
# calendar = '366_day'
>>> decimal = date2dec(calendar='366_day', ascii=g)
>>> print('{:.7f} {:.7f} {:.7f} {:.7f}'.format(*decimal[:nn]))
721616.5210069 360808.5210069 180404.9310185 0.0000000
# 360_day does not work with netcdftime.py version equal or below 0.9.2
# calendar = '360_day'
>>> decimal = date2dec(calendar='360_day', ascii=g)
>>> print('{:.7f} {:.7f} {:.7f} {:.7f}'.format(*decimal[:nn]))
709787.5210069 354894.5210069 177447.9310185 0.0000000
>>> print('{:.7f}'.format(date2dec(yr=1992, mo=1, dy=26, hr=2, mi=0, sc=0, calendar='decimal')))
1992.0685337
>>> print('{:.7f}'.format(date2dec(ascii='26.01.1992 02:00', calendar='decimal360')))
1992.0696759
>>> print('{:.7f} {:.7f}'.format(*date2dec(ascii=['26.01.1992 02:00','26.01.1992 02:00'], calendar='decimal360')))
1992.0696759 1992.0696759
>>> print('{:.7f} {:.7f}'.format(*date2dec(yr=[1992,1992], mo=1, dy=26, hr=2, mi=0, sc=0, calendar='decimal360')))
1992.0696759 1992.0696759
>>> print('{:.7f} {:.7f}'.format(*date2dec(yr=np.array([1992,1992]), mo=1, dy=26, hr=2, mi=0, sc=0, calendar='decimal360')))
1992.0696759 1992.0696759
>>> decimal = date2dec(ascii=[['26.01.1992 02:00','26.01.1992 02:00'],
... ['26.01.1992 02:00','26.01.1992 02:00'],
... ['26.01.1992 02:00','26.01.1992 02:00']],
... calendar='decimal360')
>>> print('{:.7f} {:.7f}'.format(*decimal[0]))
1992.0696759 1992.0696759
>>> print('{:.7f} {:.7f}'.format(*decimal[2]))
1992.0696759 1992.0696759
>>> print((date2dec(ascii='01.03.2003 00:00:00') - date2dec(ascii='01.03.2003')) == 0.)
True
# en
>>> decimal = date2dec(en='1992-01-26 02:00', calendar='decimal360')
>>> print('{:.7f}'.format(decimal))
1992.0696759
>>> decimal = date2dec(eng='1992-01-26 02:00', calendar='decimal360')
>>> print('{:.7f}'.format(decimal))
1992.0696759
History
-------
Written Arndt Piayda, Jun 2010
Modified Matthias Cuntz, Feb 2012 - All input can be scalar, list or array, also a mix
- Changed checks for easier extension
- decimal, decimal360
Matthias Cuntz, Dec 2012 - change unit of proleptic_gregorian
from 'days since 0001-01-01 00:00:00'
to 'days since 0001-01-00 00:00:00'
Matthias Cuntz, Feb 2013 - solved Excel leap year problem.
Matthias Cuntz, Feb 2013 - ported to Python 3
Matthias Cuntz, Jul 2013 - ascii/eng without time defaults to 00:00:00
Matthias Cuntz, Oct 2013 - Excel starts at 1 not at 0
Matthias Cuntz, Oct 2013 - units bugs, e.g. 01.01.0001 was substracted if Julian calendar even with units
Matthias Cuntz, Nov 2013 - removed remnant of time treatment before time check in eng keyword
Matthias Cuntz, Jun 2015 - adapted to new netCDF4/netcdftime (>= v1.0) and datetime (>= Python v2.7.9)
Matthias Cuntz, Oct 2015 - call date2num with list instead of single netCDF4.datetime objects
Matthias Cuntz, Oct 2016 - netcdftime provided even with netCDF4 > 1.0.0; make mo for months always integer
Matthias Cuntz, Nov 2016 - 00, 01, etc. for integers not accepted by Python3
Matthias Cuntz, May 2020 - numpy docstring format
Matthias Cuntz, Jul 2020 - en for eng
Matthias Cuntz, Jul 2020 - use proleptic_gregorian for Excel dates
Matthias Cuntz, May 2021 - rm np.int and np.float
- (almost) flake8 compatible
"""
#
# Checks
calendars = ['standard', 'gregorian', 'julian', 'proleptic_gregorian',
'excel1900', 'excel1904', '365_day', 'noleap', '366_day',
'all_leap', '360_day', 'decimal', 'decimal360']
# add little epsilon to julian dates for better reconversion
muleps = np.finfo(float).eps
try:
import cftime as nt
if (nt.__version__ <= '1.0.4'):
muleps = 0. # before 1.0.5, cftime used eps
except:
import netCDF4 as nt
try:
tst = nt.date2num
tst = nt.datetime
except:
try:
import netcdftime as nt
if ((nt.__version__ <= '0.9.2') & (calendar == '360_day')):
raise ValueError(
"date2dec error: Your version of netcdftime.py is equal"
" or below 0.9.2. The 360_day calendar does not work with"
" arrays here. Please download a newer one.")
except:
raise ImportError('Could not determine netcdf time library.')
#
calendar = calendar.lower()
if (calendar not in calendars):
raise ValueError(
"date2dec error: Wrong calendar!" +
" Choose: " + ''.join([i + ' ' for i in calendars]))
# obsolete eng
if (eng is not None):
if (en is not None):
raise ValueError("date2dec error: 'eng' was succeeded by 'en'. Only one can be given.")
else:
en = eng
# if ascii input is given by user, other input will be neglected
# calculation of input size and shape
if (ascii is not None) and (en is not None):
raise ValueError("date2dec error: 'ascii' and 'en' mutually exclusive")
if (ascii is not None):
islist = type(ascii) != type(np.array(ascii))
isarr = np.ndim(ascii)
if (islist & (isarr > 2)):
raise ValueError("date2dec error: ascii input is list > 2D; Use array input")
if isarr == 0:
ascii = np.array([ascii])
else:
ascii = np.array(ascii)
insize = ascii.size
outsize = insize
outshape = ascii.shape
asciifl = ascii.flatten()
timeobj = np.zeros(insize, dtype=object)
# slicing of ascii strings to implement in datetime object. missing times
# will be set to 0.
yr = np.zeros(insize, dtype=int)
mo = np.zeros(insize, dtype=int)
dy = np.zeros(insize, dtype=int)
hr = np.zeros(insize, dtype=int)
mi = np.zeros(insize, dtype=int)
sc = np.zeros(insize, dtype=int)
for i in range(insize):
aa = asciifl[i].split('.')
dy[i] = int(aa[0])
mo[i] = int(aa[1])
tail = aa[2].split()
yr[i] = int(tail[0])
if len(tail) > 1:
tim = tail[1].split(':')
hr[i] = int(tim[0])
if len(tim) > 1:
mi[i] = int(tim[1])
else:
mi[i] = 0
if len(tim) > 2:
sc[i] = int(tim[2])
else:
sc[i] = 0
else:
hr[i] = 0
mi[i] = 0
sc[i] = 0
if ((yr[i] == 1900) & (mo[i] == 2) & (dy[i] == 29)):
timeobj[i] = nt.datetime(yr[i], 3, 1, hr[i], mi[i], sc[i])
else:
timeobj[i] = nt.datetime(yr[i], mo[i], dy[i], hr[i], mi[i],
sc[i])
if (en is not None):
islist = type(en) != type(np.array(en))
isarr = np.ndim(en)
if isarr == 0:
en = np.array([en])
else:
en = np.array(en)
if (islist & (isarr > 2)):
raise ValueError("date2dec error: en input is list > 2D; Use array input")
en = np.array(en)
insize = en.size
outsize = insize
outshape = en.shape
enfl = en.flatten()
timeobj = np.zeros(insize, dtype=object)
# slicing of en strings to implement in datetime object. missing times
# will be set to 0.
yr = np.zeros(insize, dtype=int)
mo = np.zeros(insize, dtype=int)
dy = np.zeros(insize, dtype=int)
hr = np.zeros(insize, dtype=int)
mi = np.zeros(insize, dtype=int)
sc = np.zeros(insize, dtype=int)
for i in range(insize):
ee = enfl[i].split('-')
yr[i] = int(ee[0])
mo[i] = int(ee[1])
tail = ee[2].split()
dy[i] = int(tail[0])
if len(tail) > 1:
tim = tail[1].split(':')
hr[i] = int(tim[0])
if len(tim) > 1:
mi[i] = int(tim[1])
else:
mi[i] = 0
if len(tim) > 2:
sc[i] = int(tim[2])
else:
sc[i] = 0
else:
hr[i] = 0
mi[i] = 0
sc[i] = 0
if ((yr[i] == 1900) & (mo[i] == 2) & (dy[i] == 29)):
timeobj[i] = nt.datetime(yr[i], 3, 1, hr[i], mi[i], sc[i])
else:
timeobj[i] = nt.datetime(yr[i], mo[i], dy[i], hr[i], mi[i],
sc[i])
# if no ascii input, other inputs will be concidered
# calculation of input sizes, shapes and number of axis
if (ascii is None) and (en is None):
isnlist1 = type(yr) == type(np.array(yr))
isarr1 = np.ndim(yr)
if isarr1 == 0:
yr = np.array([yr])
else:
yr = np.array(yr)
isnlist2 = type(mo) == type(np.array(mo))
isarr2 = np.ndim(mo)
if isarr2 == 0:
mo = np.array([mo], dtype=int)
else:
mo = np.array(mo, dtype=int)
isnlist3 = type(dy) == type(np.array(dy))
isarr3 = np.ndim(dy)
if isarr3 == 0:
dy = np.array([dy])
else:
dy = np.array(dy)
isnlist4 = type(hr) == type(np.array(hr))
isarr4 = np.ndim(hr)
if isarr4 == 0:
hr = np.array([hr])
else:
hr = np.array(hr)
isnlist5 = type(mi) == type(np.array(mi))
isarr5 = np.ndim(mi)
if isarr5 == 0:
mi = np.array([mi])
else:
mi = np.array(mi)
isnlist6 = type(sc) == type(np.array(sc))
isarr6 = np.ndim(sc)
if isarr6 == 0:
sc = np.array([sc])
else:
sc = np.array(sc)
islist = not (isnlist1 | isnlist2 | isnlist3 | isnlist4 | isnlist5 |
isnlist6)
isarr = isarr1 + isarr2 + isarr3 + isarr4 + isarr5 + isarr6
shapes = [np.shape(yr), np.shape(mo), np.shape(dy), np.shape(hr),
np.shape(mi), np.shape(sc)]
nyr = np.size(yr)
nmo = np.size(mo)
ndy = np.size(dy)
nhr = np.size(hr)
nmi = np.size(mi)
nsc = np.size(sc)
sizes = [nyr, nmo, ndy, nhr, nmi, nsc]
nmax = np.amax(sizes)
ii = np.argmax(sizes)
outshape = shapes[ii]
if (islist & (np.size(outshape) > 2)):
raise ValueError("date2dec error: input is list > 2D; Use array input.")
if nyr < nmax:
if nyr == 1:
yr = np.ones(outshape, dtype=int) * yr
else:
raise ValueError("date2dec error: size of yr != max input or 1.")
if nmo < nmax:
if nmo == 1:
mo = np.ones(outshape, dtype=int) * mo
else:
raise ValueError("date2dec error: size of mo != max input or 1.")
if ndy < nmax:
if ndy == 1:
dy = np.ones(outshape, dtype=int) * dy
else:
raise ValueError("date2dec error: size of dy != max input or 1.")
if nhr < nmax:
if nhr == 1:
hr = np.ones(outshape, dtype=int) * hr
else:
raise ValueError("date2dec error: size of hr != max input or 1.")
if nmi < nmax:
if nmi == 1:
mi = np.ones(outshape, dtype=int) * mi
else:
raise ValueError("date2dec error: size of mi != max input or 1.")
if nsc < nmax:
if nsc == 1:
sc = np.ones(outshape, dtype=int) * sc
else:
raise ValueError("date2dec error: size of sc != max input or 1.")
indate = [yr, mo, dy, hr, mi, sc]
insize = [np.size(i) for i in indate]
inshape = [np.shape(i) for i in indate]
dimnum = [len(i) for i in inshape]
# calculation of maximum input size and maximum number of axis for
# reshaping the output
indate = [i.flatten() for i in indate]
outsize = max(insize)
timeobj = np.zeros(outsize, dtype=object)
# datetime object is constructed
for i in range(outsize):
iyr = int(indate[0][i])
imo = int(indate[1][i])
idy = int(indate[2][i])
ihr = int(indate[3][i])
imi = int(indate[4][i])
isc = int(indate[5][i])
if ((iyr == 1900) & (imo == 2) & (idy == 29)):
timeobj[i] = nt.datetime(iyr, 3, 1, ihr, imi, isc)
else:
timeobj[i] = nt.datetime(iyr, imo, idy, ihr, imi, isc)
# depending on chosen calendar and optional set of the time units
# decimal date is calculated
output = np.zeros(outsize)
try:
t0 = nt.datetime(1582, 10, 4, 23, 59, 59, 999999)
except:
t0 = nt.datetime(1582, 10, 4, 23, 59, 59)
t1 = nt.datetime(1582, 10, 15, 0, 0, 0)
is121 = True if (min(timeobj) <= t0) and (max(timeobj) >= t1) else False
if (calendar == 'standard') or (calendar == 'gregorian'):
if not units:
units = 'days since 0001-01-01 12:00:00'
dec0 = 1721424
else:
dec0 = 0
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units,
calendar='gregorian') + dec0
else:
output = nt.date2num(timeobj, units,
calendar='gregorian').astype(float) + dec0
output += np.abs(output) * muleps
elif calendar == 'julian':
if not units:
units = 'days since 0001-01-01 12:00:00'
dec0 = 1721424
else:
dec0 = 0
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units,
calendar='julian') + dec0
else:
output = nt.date2num(timeobj, units,
calendar='julian').astype(float) + dec0
output += np.abs(output) * muleps
elif calendar == 'proleptic_gregorian':
if not units:
units = 'days since 0001-01-01 00:00:00'
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units,
calendar='proleptic_gregorian')
else:
output = nt.date2num(timeobj, units,
calendar='proleptic_gregorian').astype(float)
output += np.abs(output) * muleps
elif calendar == 'excel1900':
doerr = False
if not units:
units = 'days since 1899-12-31 00:00:00'
if excelerr:
doerr = True
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units,
calendar='proleptic_gregorian')
else:
output = nt.date2num(timeobj, units,
calendar='proleptic_gregorian').astype(float)
if doerr:
output = np.where(output >= 60., output + 1., output)
# date2num treats 29.02.1900 as 01.03.1990,
# i.e. is the same decimal number
if np.any((output >= 61.) & (output < 62.)):
for i in range(outsize):
# if (timeobj[i].year==1900) & (timeobj[i].month==2) &
# (timeobj[i].day==29):
# output[i] -= 1.
if (yr[i] == 1900) & (mo[i] == 2) & (dy[i] == 29):
output[i] -= 1.
output += np.abs(output) * muleps
elif calendar == 'excel1904':
if not units:
units = 'days since 1903-12-31 00:00:00'
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units,
calendar='proleptic_gregorian')
else:
output = nt.date2num(timeobj, units,
calendar='proleptic_gregorian').astype(float)
output += np.abs(output) * muleps
elif (calendar == '365_day') or (calendar == 'noleap'):
if not units:
units = 'days since 0001-01-01 00:00:00'
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units, calendar='365_day')
else:
output = nt.date2num(timeobj, units,
calendar='365_day').astype(float)
output += np.abs(output) * muleps
elif (calendar == '366_day') or (calendar == 'all_leap'):
if not units:
units = 'days since 0001-01-01 00:00:00'
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units, calendar='366_day')
else:
output = nt.date2num(timeobj, units,
calendar='366_day').astype(float)
output += np.abs(output) * muleps
elif calendar == '360_day':
if not units:
units = 'days since 0001-01-01 00:00:00'
if is121 and (nt.__version__ < '1.2.2'):
for ii, tt in enumerate(timeobj):
output[ii] = nt.date2num(tt, units, calendar='360_day')
else:
output = nt.date2num(timeobj, units,
calendar='360_day').astype(float)
output += np.abs(output) * muleps
elif calendar == 'decimal':
ntime = np.size(yr)
leap = np.array((((yr % 4) == 0) & ((yr % 100) != 0)) |
((yr % 400) == 0)).astype(int)
tdy = np.array(dy, dtype=float)
diy = np.array([ [-9, 0, 31, 59, 90, 120, 151, 181, 212,
243, 273, 304, 334, 365],
[-9, 0, 31, 60, 91, 121, 152, 182, 213,
244, 274, 305, 335, 366] ])
for i in range(ntime):
tdy[i] = tdy[i] + np.array(diy[leap[i], mo[i]], dtype=float)
days_year = 365.
output = ( np.array(yr, dtype=float) +
((tdy - 1.) * 24. + np.array(hr, dtype=float) +
np.array(mi, dtype=float) / 60. +
np.array(sc, dtype=float) / 3600.) /
((days_year + np.array(leap, dtype=float)) * 24.) )
# for numerical stability, i.e. back and forth transforms
output += 1e-08 # 1/3 sec
elif calendar == 'decimal360':
ntime = np.size(yr)
tdy = np.array(dy, dtype=float)
diy = np.array([-9, 0, 30, 60, 90, 120, 150, 180, 210, 240, 270,
300, 330, 360])
for i in range(ntime):
tdy[i] = tdy[i] + np.array(diy[mo[i]], dtype=float)
days_year = 360.
output = ( np.array(yr, dtype=float) +
((tdy - 1.) * 24. + np.array(hr, dtype=float) +
np.array(mi, dtype=float) / 60. +
np.array(sc, dtype=float) / 3600.) /
(days_year * 24.) )
# for numerical stability, i.e. back and forth transforms
output += 1e-08 # 1/3 sec
else:
raise ValueError("date2dec error: calendar not implemented; should have been catched before.")
# return of reshaped output
output = np.reshape(output, outshape)
if isarr == 0:
output = float(output)
else:
if islist:
ns = np.size(outshape)
if ns == 1:
output = [i for i in output]
else:
loutput = [ i for i in output[:, 0]]
for i in range(np.size(output[:, 0])):
loutput[i] = list(np.squeeze(output[i, :]))
output = loutput
return output
if __name__ == '__main__':
import doctest
doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
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88,
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12,
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25,
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3815,
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6906,
319,
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81,
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11,
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198,
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554,
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262,
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318,
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198,
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220,
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220,
220,
543,
340,
373,
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13,
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428,
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318,
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656,
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198,
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220,
220,
220,
220,
611,
4600,
9948,
9239,
855,
6,
1069,
5276,
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6,
63,
357,
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25,
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737,
628,
220,
220,
220,
220,
220,
220,
21489,
318,
407,
3177,
257,
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614,
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4600,
1069,
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81,
855,
25101,
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198,
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13,
68,
13,
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13,
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13,
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13,
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25,
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25,
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13,
628,
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1318,
318,
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2071,
287,
4600,
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10210,
31387,
63,
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13,
24,
13,
20,
287,
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62,
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329,
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878,
614,
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25,
198,
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220,
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17,
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7,
4475,
17,
12501,
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292,
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13,
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13,
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25,
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25,
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62,
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198,
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11,
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1378,
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66,
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12,
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13,
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13,
785,
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21066,
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24200,
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1104,
4633,
812,
198,
220,
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220,
13163,
1330,
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198,
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220,
220,
13163,
611,
4818,
8079,
13,
23678,
56,
17133,
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657,
25,
198,
220,
220,
220,
2644,
220,
220,
220,
220,
3601,
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464,
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614,
287,
534,
4818,
8079,
7822,
318,
46083,
4818,
8079,
13,
23678,
56,
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8,
198,
220,
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220,
2644,
220,
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220,
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3601,
10786,
72,
13,
68,
13,
340,
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1104,
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2749,
737,
11537,
198,
220,
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220,
383,
5288,
614,
287,
534,
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7822,
318,
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1312,
13,
68,
13,
340,
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220,
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13,
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56,
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25,
198,
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220,
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220,
220,
796,
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13,
18747,
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11024,
11,
1248,
940,
11,
1467,
1270,
11,
1315,
940,
11,
1105,
4869,
11,
718,
1129,
11,
362,
11,
352,
12962,
198,
220,
220,
220,
2644,
2073,
25,
198,
220,
220,
220,
2644,
220,
220,
220,
220,
614,
220,
220,
796,
45941,
13,
18747,
26933,
11024,
11,
1248,
940,
11,
1467,
1270,
11,
1315,
940,
11,
1105,
4869,
11,
718,
1129,
11,
532,
1314,
3720,
11,
532,
2857,
1065,
12962,
198,
220,
220,
220,
13163,
1227,
220,
796,
45941,
13,
18747,
26933,
16,
11,
604,
11,
767,
11,
860,
11,
513,
11,
807,
11,
807,
11,
352,
12962,
198,
220,
220,
220,
13163,
1110,
220,
220,
220,
796,
45941,
13,
18747,
26933,
20,
11,
1987,
11,
1315,
11,
1160,
11,
1248,
11,
2681,
11,
2242,
11,
352,
12962,
198,
220,
220,
220,
13163,
1711,
220,
220,
796,
45941,
13,
18747,
26933,
1065,
11,
1467,
11,
838,
11,
1478,
11,
678,
11,
1367,
11,
1160,
11,
1105,
12962,
198,
220,
220,
220,
13163,
5664,
796,
45941,
13,
18747,
26933,
1270,
11,
1315,
11,
1160,
11,
3439,
11,
6073,
11,
807,
11,
513,
11,
657,
12962,
198,
220,
220,
220,
13163,
1218,
796,
45941,
13,
18747,
26933,
1314,
11,
838,
11,
2319,
11,
2026,
11,
4974,
11,
5214,
11,
6073,
11,
657,
12962,
198,
220,
220,
220,
13163,
32465,
796,
3128,
17,
12501,
7,
9948,
9239,
796,
705,
20307,
3256,
42635,
28,
1941,
11,
6941,
28,
8424,
11,
20268,
28,
820,
11,
39436,
28,
9769,
11,
21504,
28,
11374,
11,
629,
28,
12227,
8,
198,
220,
220,
220,
13163,
299,
77,
796,
614,
13,
7857,
198,
220,
220,
220,
13163,
3601,
10786,
90,
25,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
4458,
18982,
46491,
12501,
4402,
58,
25,
20471,
1003,
17,
60,
4008,
198,
220,
220,
220,
362,
13,
2231,
1314,
31503,
2481,
405,
37381,
68,
10,
3312,
362,
13,
2548,
1828,
5237,
22413,
19104,
2998,
68,
10,
3312,
362,
13,
33400,
8054,
24,
3132,
29159,
4309,
68,
10,
3312,
362,
13,
1983,
2078,
2780,
940,
6469,
1558,
3270,
68,
10,
3312,
198,
220,
220,
220,
13163,
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25,
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17,
60,
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220,
220,
362,
13,
21652,
2623,
4790,
1238,
4310,
28872,
68,
10,
3312,
352,
13,
24,
2857,
2548,
3270,
2414,
34125,
1485,
68,
10,
3312,
198,
220,
220,
220,
13163,
32465,
796,
3128,
17,
12501,
7,
9948,
9239,
11639,
20307,
3256,
42635,
28,
1941,
11,
6941,
28,
21,
11,
20268,
28,
1314,
11,
39436,
28,
1065,
11,
21504,
28,
11374,
11,
629,
28,
12227,
8,
198,
220,
220,
220,
13163,
3601,
10786,
90,
25,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
4458,
18982,
46491,
12501,
4402,
58,
25,
20471,
1003,
17,
60,
4008,
198,
220,
220,
220,
362,
13,
2231,
1558,
11442,
2481,
405,
37381,
68,
10,
3312,
362,
13,
2548,
1954,
1415,
486,
2713,
18,
28872,
68,
10,
3312,
362,
13,
33400,
3553,
8784,
40064,
21652,
68,
10,
3312,
362,
13,
1983,
23195,
35500,
40353,
2075,
68,
10,
3312,
198,
220,
220,
220,
13163,
3601,
10786,
90,
25,
13,
1415,
68,
92,
46110,
13,
1415,
68,
92,
4458,
18982,
46491,
12501,
4402,
58,
20471,
1003,
17,
25,
20471,
12,
17,
60,
4008,
198,
220,
220,
220,
362,
13,
21652,
2231,
1899,
25270,
2996,
4524,
68,
10,
3312,
352,
13,
24,
2857,
25838,
405,
3270,
5999,
1795,
68,
10,
3312,
628,
220,
220,
220,
1303,
355,
979,
72,
5128,
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73,
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6,
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220,
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2014,
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220,
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2010,
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2010,
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220,
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2010,
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13,
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2010,
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1330,
2010,
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13,
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19841,
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15,
13,
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13,
17,
11537,
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357,
9948,
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705,
15277,
62,
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198,
220,
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220,
220,
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] | 1.978679 | 16,181 |
from __future__ import print_function
import sys
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from datetime import datetime
MINUTES_IN_DAY = 60 * 24
SECONDS_IN_MINUTE = 60
class Slice(object):
"""
A period of time with a start and an end
"""
DT_FMT = "%Y-%m-%d %H:%M"
@property
@property
@property
@property
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"""
Copyright (C) 2016 Interactive Brokers LLC. All rights reserved. This code is
subject to the terms and conditions of the IB API Non-Commercial License or the
IB API Commercial License, as applicable.
"""
"""
Simple enum implementation
"""
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# -*- coding: utf-8 -*-
# @Time : 2021-12-03 1:12 p.m.
# @Author : young wang
# @FileName: geoCorrection.py
# @Software: PyCharm
import pydicom
import numpy as np
from OssiviewBufferReader import OssiviewBufferReader
from os.path import join, isfile
from pydicom.uid import generate_uid
import os
from matplotlib import pyplot as plt
from scipy.interpolate import griddata
def load_from_oct_file(oct_file):
"""
read .oct file uising OssiviewBufferReader
export an array in the shape of [512,512,330]
the aarry contains pixel intensity data(20log) in float16 format
"""
obr = OssiviewBufferReader(oct_file)
data_fp16 = np.squeeze(obr.data)
data = imag2uint(data_fp16)
clean_data = clean(data)
return clean_data
def imag2uint(data):
"""
convert pixel data from the 255 range to unit16 range(0-65535)
"""
# remove the low and high bounds of the pixel intensity data points
# 45 and 130dB are heuristically chosen
data = np.clip(data, 50, np.max(data))
# pixel intensity normalization
# for detail, please see wiki page
# https://en.wikipedia.org/wiki/Normalization_(image_processing)
# 446 is the maximum pixel in the MRI template
data = (data - np.min(data)) * 446 / (np.max(data) - np.min(data))
return np.uint16(np.around(data, 0))
def oct_to_dicom(oct_file,PatientName, seriesdescription,
dicom_folder, dicom_prefix):
"""
convert pixel array [512,512,330] to DICOM format
using MRI template, this template will be deprecated
in the future once OCT template is received
"""
data = load_from_oct_file(oct_file)
dss = []
template_file = '../template data/template.dcm'
ds = pydicom.dcmread(template_file)
# SeriesInstanceUID refers to each series, and should be
# unqie for each sesssion, and generate_uid() provides an unique
# identifier
ds.SeriesInstanceUID = generate_uid()
all_files_exist = False
# looping through all 330 slice of images with [512(row) x 512(column)]
for i in range(data.shape[2]):
# UID used for indexing slices
ds.SOPInstanceUID = generate_uid()
# update row and column numbers to be 512
ds.Rows = data.shape[0]
ds.Columns = data.shape[1]
# define the bottom(assuming the middle plane to be zero,
# that -165 * 30um(axial resolution) = -4.95 mm)
# DICOM assumes physical dimension to be in mm unit
bottom = -4.95
# elevate the z by its axial resolution at a time
z = bottom + (i * 0.03)
# update meta properties
ds.PixelSpacing = [0.02, 0.02] # pixel spacing in x, y planes [mm]
ds.SliceThickness = 0.03 # slice thickness in axial(z) direction [mm]
ds.SpacingBetweenSlices = 0.03 # slice spacing in axial(z) direction [mm]
ds.SliceLocation = '%0.2f' % z # slice location in axial(z) direction
ds.InstanceNumber = '%0d' % (i + 1,) # instance number, 330 in total
ds.ImagePositionPatient = [z, 0, 0] # patient physical location
ds.Manufacturer = 'Audioptics Medical Inc'
ds.InstitutionName = 'Audioptics Medical'
ds.InstitutionAddress = '1344 Summer St., #55, Halifax, NS, Canada'
ds.StudyDescription = 'Example DICOM export'
ds.StationName = 'Unit 1'
ds.SeriesDescription = seriesdescription
ds.PhysiciansOfRecord = ''
ds.PerformingPhysicianName = ''
ds.InstitutionalDepartmentName = ''
ds.ManufacturerModelName = 'Mark II'
ds.PatientName = PatientName
ds.PatientBirthDate = '20201123'
ds.PatientAddress = ''
# setting the dynamic range with WindowCenter and WindowWidth
# lowest_visible_value = window_center — window_width / 2
# highest_visible_value = window_center + window_width / 2
ds.WindowCenter = '248'
ds.WindowWidth = '396'
# # set highest and lowest pixel values
ds.LargestImagePixelValue = 446
ds.SmallestImagePixelValue = 50
dicom_file = join(dicom_folder, "%s%05d.dcm" % (dicom_prefix, i))
pixel_data = data[:, :, i]
pixel_data[pixel_data <= 50] = 0
ds.PixelData = pixel_data.tobytes()
ds.save_as(dicom_file)
dss.append(ds)
all_files_exist = all_files_exist and isfile(dicom_file)
return all_files_exist
if __name__ == '__main__':
oct_files = []
directory = '/Users/youngwang/Desktop/GeoCorrection'
import glob
for filepath in glob.iglob(r'/Users/youngwang/Desktop/GeoCorrection/*.oct'):
oct_files.append(filepath)
oct_files.sort()
raw_data = load_from_oct_file(oct_files[0])
test_slice = np.rot90(raw_data[256,:,:])
plt.imshow(test_slice)
plt.show()
#
import polarTransform
#
# # imagec = plt.imread('/Users/youngwang/Desktop/a109560e-fa1e-4bb2-916b-d5a851de7051.jpeg')
# # image=np.mean(imagec,axis=2)
#
# opening_angle= 10 #deg
# polarImage, ptSettings = polarTransform.convertToCartesianImage(test_slice.T,
# initialRadius=0,
# finalRadius=330,
# initialAngle= -opening_angle*np.pi/360,
# finalAngle= opening_angle*np.pi/360,
# imageSize=(512,330))
#
# fig,ax = plt.subplots(1,2)
# ax[0].imshow(test_slice.T)
# ax[1].imshow(polarImage.T)
# # #
# plt.show()
# #
opening_angle = 10 # deg
polarImage, ptSettings = polarTransform.convertToCartesianImage(test_slice.T,
initialRadius=0,
finalRadius=660,
initialAngle=-opening_angle * np.pi / 360,
finalAngle=opening_angle * np.pi / 360,
)
fig, ax = plt.subplots(1, 2)
ax[0].imshow(test_slice.T)
ax[1].imshow(polarImage.T)
plt.show()
# #
# # plt.show()
#
# # dicom_prefix = 'Phantom'
# # seriesdescription = 'Corrected'
# #
# # export_path = '/Users/youngwang/Desktop/GeoCorrection/After'
# #
# # if not os.path.exists(export_path):
# # os.mkdir(export_path)
# # else:
# # pass
# #
# # PatientName = 'Phantom'
# # oct_to_dicom(oct_file = oct_files[0],PatientName = PatientName,
# # seriesdescription = seriesdescription,
# # dicom_folder =export_path,
# # dicom_prefix = dicom_prefix)
# #
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] | 2.103822 | 3,323 |
# -*- coding: utf-8 -*-
# *****************************************************************************
# NICOS, the Networked Instrument Control System of the MLZ
# Copyright (c) 2009-2021 by the NICOS contributors (see AUTHORS)
#
# This program is free software; you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation; either version 2 of the License, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# this program; if not, write to the Free Software Foundation, Inc.,
# 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#
# Module authors:
# Georg Brandl <[email protected]>
#
# *****************************************************************************
"""
Python interface to the _pyctl module, to control the execution of Python
code via a C trace function.
"""
import threading
import traceback
from nicos.protocols.daemon import STATUS_INBREAK, STATUS_RUNNING
try:
from nicospyctl.pyctl import ControlStop, Controller as _Controller
except ImportError:
ControlStop = BaseException
__all__ = ['LINENO_ALL', 'LINENO_TOPLEVEL', 'LINENO_NAME',
'Controller', 'ControlStop']
# defines from the C module
LINENO_ALL = 0 # trace all line numbers
LINENO_TOPLEVEL = 1 # trace only line numbers in toplevel frame
LINENO_NAME = 2 # trace only line numbers in frames with the
# filename given by break_only_in_filename
class Controller(_Controller):
"""
The Controller object allows to execute Python code in a controlled
environment using the Python tracing mechanism (using a C trace function
instead of a Python one for speed).
The running code can therefore be halted and stopped from another thread.
Additionally, the currently executed line and Python frame can be observed.
Halting works by calling a custom function ("break function") from the trace
function -- until this function returns the execution is halted.
Stopping works by throwing an exception from the trace function into the
frame executing code, where it should be allowed to propagate to the
toplevel and exit excecution. The exception (ControlStop) inherits from
BaseException. This works nicely together with "finally:" clauses, but
requires that bare "except:" clauses are replaced by "except Exception:".
There are various options to control breaking behavior. By default, a break
can occur everywhere. "break_only_in_toplevel" limits breaking so that a
break can only occur between two lines of code in the toplevel code.
"break_only_in_filename" works similar, but if it is set, breaks can occur
in all frames whose code has the given filename. Using this, breakpoints in
non-toplevel code are implemented.
Using an "observer" callable, changes in the line number and execution need
not be polled: each time the status or line number changes, the observer is
called as observer(status, lineno).
The external interface is usually used like this:
In the executing thread:
* instantiate the Controller object
* call set_observer() to add an observer
* call start()/start_exec()
In the controlling thread:
* when halting is wanted, call set_break()
* when continuing is wanted, call set_continue()
* when stopping is wanted, call set_stop()
Signature of the C class:
Controller(breakfunc, # break function
break_only_in_toplevel=False, # see above
break_only_in_filename=None, # see above
lineno_behavior) # which line numbers to trace
Methods of the C class:
- start(callable): start execution, calling the given callable as toplevel
- start_exec(code, globals[, locals]): start execution of the given code
object with the global and local scopes
- set_break(arg): request a break, the breakfunc will be called at the
next trace function run, the arg is given to the breakfunc; a not-None
arg is supposed to mean "stop"
- set_stop(arg): request a stop, the arg will be used as an intializer
argument to the ControlStop exception
- set_observer(observer): attach an observer to the instance
Attributes of the C class:
- status: execution status
- currentframe: current execution frame
- toplevelframe: first and topmost execution frame
- lineno: current line number (in which frame, see lineno_behavior)
"""
def _breakfunc(self, frame, arg):
"""Called when execution has been halted."""
flag = self.wait_for_continue()
if flag is not None:
self.set_stop(flag)
def wait_for_continue(self):
"""Called from the break func: wait for set_continue() to be called."""
self.__continue.wait()
self.__continue.clear()
return self.__continue_arg
def set_continue(self, arg):
"""Allow continuation of a halted execution."""
self.__continue_arg = arg
self.__continue.set()
def stop(self, arg):
"""Called from outside: stop execution."""
if arg is None:
arg = 'stop method called'
# if execution is running, we set a stop flag ourselves
if self.status == STATUS_RUNNING:
self.set_stop(arg)
# else we let wait_for_continue() return the arg, and the breakfunc
# must call set_stop()
elif self.status == STATUS_INBREAK:
self.set_continue(arg)
def get_stacktrace(self, limit=None):
"""Return a stacktrace of the currently executed code."""
frame = self.currentframe
if frame is None:
return None
return ''.join(traceback.format_stack(frame, limit)[2:])
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] | 3.111392 | 1,975 |
import numpy as np
import pandas as pd
import spacy
# %% Load spaCy model
nlp = spacy.load("en_core_web_lg")
# %% Load cleaned data
df = pd.read_csv('./data/interim/Corpus_Cleaned.csv')
# %% Extract document vectors
df['Vector'] = df.loc[:, 'Top1':'Top25'].apply(lambda x: nlp(' '.join([str(s) for s in x])).vector, axis=1)
matrix = np.zeros((len(df), df['Vector'][0].shape[0]))
for i, r in df.iterrows():
matrix[i, ] = r['Vector']
# %% Prepare file with so many columns as in Doc2Vec vectors plus one more (for a label)
df_out = pd.DataFrame(data=matrix)
df_out['Class'] = df['Class']
df_out.to_csv(path_or_buf='./data/processed/GloVe.csv', index=False) | [
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] | 2.51711 | 263 |
import numpy as np
import scipy.sparse as sparse
from typing import Any
from torch.utils.checkpoint import checkpoint
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_scatter import scatter_max
from .. import register_model, BaseModel
from cogdl.utils import mul_edge_softmax, spmm, get_activation
from cogdl.trainers.deepergcn_trainer import DeeperGCNTrainer
class DeepGCNLayer(nn.Module):
"""
Implementation of DeeperGCN in paper `"DeeperGCN: All You Need to Train Deeper GCNs"` <https://arxiv.org/abs/2006.07739>
Parameters
-----------
in_feat : int
Size of each input sample
out_feat : int
Size of each output sample
conv : class
Base convolution layer.
connection : str
Residual connection type, `res` or `res+`.
activation : str
dropout : float
checkpoint_grad : bool
"""
@register_model("deepergcn")
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] | 2.568063 | 382 |
# This code is part of Qiskit.
#
# (C) Copyright IBM 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Runtime REST adapter."""
import logging
from typing import Dict, Any, Union, Optional
import json
from concurrent import futures
from .base import RestAdapterBase
from ..session import RetrySession
from ...runtime.utils import RuntimeEncoder
logger = logging.getLogger(__name__)
class Runtime(RestAdapterBase):
"""Rest adapter for Runtime base endpoints."""
URL_MAP = {
'programs': '/programs',
'jobs': '/jobs',
'logout': '/logout'
}
def program(self, program_id: str) -> 'Program':
"""Return an adapter for the program.
Args:
program_id: ID of the program.
Returns:
The program adapter.
"""
return Program(self.session, program_id)
def program_job(self, job_id: str) -> 'ProgramJob':
"""Return an adapter for the job.
Args:
job_id: Job ID.
Returns:
The program job adapter.
"""
return ProgramJob(self.session, job_id)
def list_programs(self, limit: int = None, skip: int = None) -> Dict[str, Any]:
"""Return a list of runtime programs.
Args:
limit: The number of programs to return.
skip: The number of programs to skip.
Returns:
A list of runtime programs.
"""
url = self.get_url('programs')
payload: Dict[str, int] = {}
if limit:
payload['limit'] = limit
if skip:
payload['offset'] = skip
return self.session.get(url, params=payload).json()
def create_program(
self,
program_data: str,
name: str,
description: str,
max_execution_time: int,
is_public: Optional[bool] = False,
spec: Optional[Dict] = None
) -> Dict:
"""Upload a new program.
Args:
program_data: Program data (base64 encoded).
name: Name of the program.
description: Program description.
max_execution_time: Maximum execution time.
is_public: Whether the program should be public.
spec: Backend requirements, parameters, interim results, return values, etc.
Returns:
JSON response.
"""
url = self.get_url('programs')
payload = {'name': name,
'data': program_data,
'cost': max_execution_time,
'description': description,
'is_public': is_public}
if spec is not None:
payload['spec'] = spec
data = json.dumps(payload)
return self.session.post(url, data=data).json()
def program_run(
self,
program_id: str,
hub: str,
group: str,
project: str,
backend_name: str,
params: Dict,
image: str,
log_level: Optional[str] = None
) -> Dict:
"""Execute the program.
Args:
program_id: Program ID.
hub: Hub to be used.
group: Group to be used.
project: Project to be used.
backend_name: Name of the backend.
params: Program parameters.
image: Runtime image.
log_level: Log level to use.
Returns:
JSON response.
"""
url = self.get_url('jobs')
payload = {
'program_id': program_id,
'hub': hub,
'group': group,
'project': project,
'backend': backend_name,
'params': params,
'runtime': image
}
if log_level:
payload["log_level"] = log_level
data = json.dumps(payload, cls=RuntimeEncoder)
return self.session.post(url, data=data).json()
def jobs_get(
self,
limit: int = None,
skip: int = None,
pending: bool = None,
program_id: str = None
) -> Dict:
"""Get a list of job data.
Args:
limit: Number of results to return.
skip: Number of results to skip.
pending: Returns 'QUEUED' and 'RUNNING' jobs if True,
returns 'DONE', 'CANCELLED' and 'ERROR' jobs if False.
program_id: Filter by Program ID.
Returns:
JSON response.
"""
url = self.get_url('jobs')
payload: Dict[str, Union[int, str]] = {}
if limit:
payload['limit'] = limit
if skip:
payload['offset'] = skip
if pending is not None:
payload['pending'] = 'true' if pending else 'false'
if program_id:
payload['program'] = program_id
return self.session.get(url, params=payload).json()
def logout(self) -> None:
"""Clear authorization cache."""
url = self.get_url('logout')
self.session.post(url)
class Program(RestAdapterBase):
"""Rest adapter for program related endpoints."""
URL_MAP = {
'self': '',
'data': '/data',
'run': '/jobs',
'private': '/private',
'public': '/public'
}
_executor = futures.ThreadPoolExecutor()
def __init__(self, session: RetrySession, program_id: str, url_prefix: str = '') -> None:
"""Job constructor.
Args:
session: Session to be used in the adapter.
program_id: ID of the runtime program.
url_prefix: Prefix to use in the URL.
"""
super().__init__(session, '{}/programs/{}'.format(url_prefix, program_id))
def get(self) -> Dict[str, Any]:
"""Return program information.
Returns:
JSON response.
"""
url = self.get_url('self')
return self.session.get(url).json()
def make_public(self) -> None:
"""Sets a runtime program's visibility to public."""
url = self.get_url('public')
self.session.put(url)
def make_private(self) -> None:
"""Sets a runtime program's visibility to private."""
url = self.get_url('private')
self.session.put(url)
def delete(self) -> None:
"""Delete this program.
Returns:
JSON response.
"""
url = self.get_url('self')
self.session.delete(url)
def update_data(self, program_data: str) -> None:
"""Update program data.
Args:
program_data: Program data (base64 encoded).
"""
url = self.get_url("data")
self.session.put(url, data=program_data,
headers={'Content-Type': 'application/octet-stream'})
def update_metadata(
self,
name: str = None,
description: str = None,
max_execution_time: int = None,
spec: Optional[Dict] = None
) -> None:
"""Update program metadata.
Args:
name: Name of the program.
description: Program description.
max_execution_time: Maximum execution time.
spec: Backend requirements, parameters, interim results, return values, etc.
"""
url = self.get_url("self")
payload: Dict = {}
if name:
payload["name"] = name
if description:
payload["description"] = description
if max_execution_time:
payload["cost"] = max_execution_time
if spec:
payload["spec"] = spec
self.session.patch(url, json=payload)
class ProgramJob(RestAdapterBase):
"""Rest adapter for program job related endpoints."""
URL_MAP = {
'self': '',
'results': '/results',
'cancel': '/cancel',
'logs': '/logs'
}
def __init__(
self,
session: RetrySession,
job_id: str,
url_prefix: str = ''
) -> None:
"""ProgramJob constructor.
Args:
session: Session to be used in the adapter.
job_id: ID of the program job.
url_prefix: Prefix to use in the URL.
"""
super().__init__(session, '{}/jobs/{}'.format(
url_prefix, job_id))
def get(self) -> Dict:
"""Return program job information.
Returns:
JSON response.
"""
return self.session.get(self.get_url('self')).json()
def delete(self) -> None:
"""Delete program job."""
self.session.delete(self.get_url('self'))
def results(self) -> str:
"""Return program job results.
Returns:
Job results.
"""
response = self.session.get(self.get_url('results'))
return response.text
def cancel(self) -> None:
"""Cancel the job."""
self.session.post(self.get_url('cancel'))
def logs(self) -> str:
"""Retrieve job logs.
Returns:
Job logs.
"""
return self.session.get(self.get_url('logs')).text
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19746,
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] | 2.158432 | 4,412 |
# uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]
# Embedded file name: T:\InGame\Gameplay\Scripts\Server\sims\outfits\outfit_picker_interactions.py
# Compiled at: 2017-06-14 00:32:50
# Size of source mod 2**32: 16347 bytes
import operator
from business.business_enums import BusinessEmployeeType
from filters.tunable import TunableSimFilter
from interactions import ParticipantType
from interactions.base.picker_interaction import PickerSuperInteraction
from interactions.context import QueueInsertStrategy
from interactions.utils.tunable import TunableContinuation
from sims.outfits.outfit_enums import OutfitCategory, TODDLER_PROHIBITED_OUTFIT_CATEGORIES
from sims.sim_info_types import Gender
from sims4.localization import TunableLocalizedStringFactory
from sims4.tuning.tunable import TunableEnumEntry, TunableVariant, HasTunableSingletonFactory, AutoFactoryInit, OptionalTunable, TunableList
from sims4.tuning.tunable_base import GroupNames
from sims4.utils import flexmethod
from ui.ui_dialog_picker import TunableUiOutfitPickerSnippet, OutfitPickerRow, UiSimPicker, SimPickerRow
import services | [
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class PathData:
"""
data structure contain open api scheme (sub scheme) and the variable define in the parents of the current scheme
"""
def __init__(self, scheme: dict, args: dict):
"""
:param scheme: open api scheme (sub scheme)
:param args: the variable define in the parents of the current scheme
"""
self.scheme: dict = scheme
self.args: dict = args
class SchemePath:
"""
this class should assist complex path calculations
"""
#TODO relative Path in the scheme
def getPath(self, scheme: dict, args:dict={}):
"""
calculate the path of self.path in the open api scheme
:param scheme: the open api scheme
:param args: the variable define in the path
:return: PathData | list[PathData] or None
if the path point to list return list[PathData]
if the path point to specific element return PathData
else if the epath not exist return None
"""
self.__result = []
if(self.path.endswith('%')):
self.__result_is_value = True
self.path = self.path[:-1]
path_items = self.path.split(".")
self.__getPathRec(path_items, scheme, args)#TODO handle errors
if len(self.__result) > 0:
return self.__result if self.__result_is_list else self.__result[0]
return None
def __getPathRec(self, path: list, scheme: dict, args:dict={}):
"""
recursive function used by getPath
:param path: list of element in the path
:param scheme: the current sub scheme of the open api
:param args: the variable define in the path
:return:
"""
while len(path) > 0:
if scheme is None:
return
if isinstance(scheme,list):
for sub_scheme in scheme:
sub_path = path.copy()
self.__result_is_list = True
self.__getPathRec(sub_path,sub_scheme,args)
return
item:str = path.pop(0)
if isinstance(scheme,str) and len(path) == 0 and item.startswith("#"):
sub_args = args.copy()
sub_args[item[1:]] = scheme
self.__result.append(PathData(None, sub_args))
return
if(item.startswith("#")):#variable definition
var = item[1:]
for item in scheme.keys():
sub_path = path.copy()
sub_args = args.copy()
sub_args[var] = item
self.__result_is_list = True
self.__getPathRec(sub_path,scheme[item],sub_args)
return
if(item.startswith("$")):#var Value
item = args[item[1:]]
if(item in scheme):
scheme = scheme[item]
else:
return
if(isinstance(scheme,list) and not self.__result_is_value):
self.__result_is_list = True
for item in scheme:
self.__result.append(PathData(item, args))
else:
self.__result.append(PathData(scheme, args)) | [
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"""
This file deals with preprocessing the images for the featurizer.
It gives the user 3 options:
1. Upload a CSV with URL pointers.
2. Upload an image directory with no CSV. The featurizer will generate a CSV automatically.
3. Upload a CSV with an image directory. The CSV will contain pointers to image in the directory.
The integrated function is the preprocess_data function, which takes in the input and
generates a 4D tensor containing the vectorized representations of the image to be featurized.
"""
from PIL import Image, ImageFile
import logging
import os
try:
from urllib import urlretrieve
except ImportError:
from urllib.request import urlretrieve
import re
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.DEBUG = 0
import numpy as np # noqa: E402
import pandas as pd # noqa: E402
import trafaret as t # noqa: E402
import keras.applications as ka # noqa: E402
from keras.preprocessing.image import load_img, img_to_array # noqa: E402
##############################################
# FUNCTIONS FOR BUILDING LIST OF IMAGE PATHS #
##############################################
# Dictionary for preprocessing algorithms
# Unnecessary 'size' entry, but leaving in case of future use...
preprocessing_dict = {
'squeezenet': {
'preprocess': ka.imagenet_utils.preprocess_input,
'size': (227, 227)
},
'vgg16': {
'preprocess': ka.vgg16.preprocess_input,
'size': (224, 224)
},
'vgg19': {
'preprocess': ka.vgg19.preprocess_input,
'size': (224, 224)
},
'resnet50': {
'preprocess': ka.resnet50.preprocess_input,
'size': (224, 224)
},
'inceptionv3': {
'preprocess': ka.inception_v3.preprocess_input,
'size': (299, 299)
},
'xception': {
'preprocess': ka.xception.preprocess_input,
'size': (299, 299)
},
}
def _create_df_with_image_paths(list_of_images, image_column_header):
"""
Take in a list of image names, and return a DataFrame where each
image name is a new row.
Parameters:
----------
list_of_images: list of str
Full paths to images in a directory
image_column_header : str
The name of the header for the column of image paths
Returns:
-------
df : pandas.DataFrame
The dataframe containing the full list of image names.
"""
df = pd.DataFrame(list_of_images, columns=[image_column_header])
return df
def natural_key(string_):
"""See http://www.codinghorror.com/blog/archives/001018.html"""
return [int(s) if s.isdigit() else s for s in re.split(r'(\d+)', string_)]
def _find_directory_image_paths(image_directory):
"""
Take in a directory and parse which files in it are valid images for
loading into the featurizer.
List ordering explanation for directory-only featurization:
The list will be sorted in order to create a deterministic file order for
the generated csv, regardless of filesystem ordering. The CSV will then be
used as the canonical order for all data preprocessing, featurizing, and
eventually writing the features back into the csv.
Parameters:
----------
image_directory : str
The filepath to the directory containing the images
Returns:
-------
list_of_images : list of str
A sorted list of full paths to each valid image contained in the directory
"""
image_list = os.listdir(image_directory)
valid = ['JPEG', 'BMP', 'PNG']
list_of_images = []
for fichier in image_list:
try:
if Image.open(image_directory + fichier).format in valid:
list_of_images.append(fichier)
Image.close()
except Exception:
pass
return sorted(list_of_images, key=natural_key)
def _find_csv_image_paths(csv_path, image_column_header):
"""
Find the image paths in a csv without an image directory.
List ordering explanation for csv-included featurization:
The list does not need to be sorted, as it is already in a set order in the csv.
The csv will be used as the canonical order for all data preprocessing,
featurizing, and eventually writing the features back into the csv.
Parameters:
----------
csv_path : str
Full path to the csv
image_column_header : str
Name of the column containing the image paths
Returns:
-------
list_of_images: list of str
Full paths to each valid image contained in the csv
"""
# Create the dataframe from the csv
df = pd.read_csv(csv_path, error_bad_lines=False)
# -------------- #
# ERROR CHECKING #
# Raise an error if the image column header isn't in the dataframe
if image_column_header not in df.columns:
raise ValueError('image_column_header error: {} does not exist as a '
'column in the csv file.'.format(image_column_header))
# -------------- #
# Create the list of image paths from the column in the dataframe
list_of_images = df[image_column_header].tolist()
return list_of_images, df
def _find_combined_image_paths(image_path, csv_path, image_column_header):
"""
Find the image paths of a csv combined with a directory: take only the overlap
to avoid errors.
List ordering explanation for csv-included featurization:
See docstring for _find_csv_image_paths() method.
Parameters:
----------
image_path : str
Full path to the provided image directory
csv_path : str
Full path to the provided csv
image_column_header : str
Name of the column in the csv containing image paths
Returns:
-------
list_of_images: list of str
Full paths to each valid image contained in both the csv and directory
"""
# Find the list of image paths in the csv
csv_list, df = _find_csv_image_paths(csv_path, image_column_header)
# Find the list of image paths in the directory
directory_list = _find_directory_image_paths(image_path)
list_of_images = []
# Create the list of image paths by finding the overlap between the two,
# keeping the order in the csv
for path in csv_list:
if path in directory_list:
list_of_images.append(path)
# If the image is in the csv but not the directory, input an empty string
# as a placeholder. This image will eventually get vectorized to zeros.
else:
list_of_images.append('')
# -------------- #
# ERROR CHECKING #
# Raise error if there are no shared images between the csv and the directory
if all(path == '' for path in list_of_images):
raise ValueError('Something is wrong. There are no shared images in the'
' csv and the image directory. Check formatting or files.')
# -------------- #
return list_of_images, df
def _image_paths_finder(image_path, csv_path, image_column_header):
"""
Given an image column header, and either a csv path or an image directory,
find the list of image paths. If just a csv, it's pulled from the column.
If it's just a directory, it's pulled from the directory. If it's both,
the list is checked from the overlap between the directory and the csv.
Parameters:
----------
image_path : str
Path to the image directory, if it exists
csv_path : str
Path to the csv, if it exists
image_column_header : str
Name of column header holding image information
Returns:
-------
list_of_images : list of str
a list of the paths to all the images being featurized
"""
# CASE 1: They only give an image directory with no CSV
if csv_path == '':
# Find list of images from the image directory
list_of_images = _find_directory_image_paths(image_path)
# Create the new csv in a folder called 'featurizer_csv/'
df = _create_df_with_image_paths(list_of_images,
image_column_header=image_column_header)
# CASE 2: They only give a CSV with no directory
elif image_path == '':
# Create the list_of_images from the csv
list_of_images, df = _find_csv_image_paths(csv_path, image_column_header)
logging.info('Found image paths from csv.')
# CASE 3: They give both a CSV and a directory
else:
list_of_images, df = _find_combined_image_paths(image_path, csv_path, image_column_header)
logging.info('Found image paths that overlap between both the directory and the csv.\n')
return list_of_images, df
#####################################
# FUNCTION FOR IMAGE VECTORIZATION #
####################################
def _convert_single_image(image_source, model_str, image_path, target_size=(299, 299),
grayscale=False):
"""
Take in a path to an image (either by URL or in a native directory)
and convert the image to a preprocessed 4D numpy array, ready to be plugged
into the featurizer.
Parameters:
----------
image_source : str
Flag for either url or directory source for image
model_str : str
Name of the model converting the image
image_path : str
Either the URL or the full path to the image
target size : tuple of ints
The desired size of the image
grayscale : bool
Boolean indicating whether the image is grayscale or not
Returns:
-------
image_array : np.ndarray
a numpy array that represents the loaded and preprocessed image
"""
# Retrieve the image, either from a given url or from a directory
try:
if image_source == 'url':
image_file = urlretrieve(image_path)[0]
elif image_source == 'directory':
image_file = image_path
# If the image can't be retrieved, return a zeros vector of the appropriate size
except (IOError, ValueError):
# The channel dimension for a missing image is 3 if not grayscale, or 1 if grayscale
im_size = target_size + (3 - 2 * grayscale,)
logging.error('ERROR: Could not load/convert image to numpy array: {}'.format(image_path))
return np.zeros(im_size)
# Load the image, and convert it to a numpy array with the target size
image = load_img(image_file, target_size=target_size, grayscale=grayscale)
image_array = img_to_array(image)
# Expand the dimension for keras preprocessing, and preprocess the data
# according to the InceptionV3 training that they performed.
image_array = np.expand_dims(image_array, axis=0)
image_array = preprocessing_dict[model_str]['preprocess'](image_array)
# Return the image array
return image_array
################################################
# FUNCTION FOR END-TO-END DATA PREPROCESSING #
################################################
@t.guard(image_column_header=t.String(allow_blank=False),
model_str=t.String(allow_blank=False),
list_of_images=t.List(t.String(allow_blank=True)),
image_path=t.String(allow_blank=True),
csv_path=t.String(allow_blank=True),
target_size=t.Tuple(t.Int, t.Int),
grayscale=t.Bool)
def preprocess_data(image_column_header,
model_str,
list_of_images,
image_path='',
csv_path='',
target_size=(299, 299),
grayscale=False):
"""
Receive the data (some combination of image directory + csv), find
the list of valid images, and then convert each to an array and adds
them to the full batch.
Parameters:
----------
image_path : str
The path to the image directory, if it is being passed
csv_path : str
The path to the csv, if it is being passed
image_column_header : str
The name of the column that contains the image paths in the csv
target_size : tuple of ints
The size that the images will be scaled to
grayscale : bool
Boolean indicating whether the images are grayscale or not
Returns:
-------
image_data : np.ndarray
a 4D numpy tensor containing the (full or batched) vectorized images,
ready to be pushed through the featurizer
list_of_images : list of str
the list of image paths in the same order as the batches
of the numpy tensor. This will allow us to add the
features to the correct row of the csv.
"""
# -------------- #
# ERROR CHECKING #
# -------------- #
# If there is no image directory or csv, then something is wrong.
if image_path == '' and csv_path == '':
raise ValueError('Need to load either an image directory or a CSV with'
' URLs, if no image directory included.')
# Raise an error if the image_path doesn't point to a directory
if image_path and not os.path.isdir(image_path):
raise TypeError('image_path must lead to a directory if '
'it is initialized. It is where the images are stored.')
if model_str not in preprocessing_dict.keys():
raise ValueError('model_str must be one the following: {}'.format(preprocessing_dict.keys))
# ------------------------------------------------------ #
# BUILDING IMAGE PATH LIST #
num_images = len(list_of_images)
image_source = _find_image_source(image_path)
# Set number of grayscale channels (3 if color, 1 if grayscale)
channels = 3 - (2 * grayscale)
# Initialize the full batch
image_data = np.ones((num_images, target_size[0], target_size[1], channels))
# Create the full image tensor
logging.info('Converting images.')
image_dict = {}
index = 0
# Iterate through each image in the list of image names
for image in list_of_images:
# If the image is in the csv, but not in the directory, set it to all zeros
# This allows the featurizer to correctly append features when there is
# mismatch between the csv and the directory. Otherwise it would lose rows
if image == '':
image_data[index, :, :, :] = 0
index += 1
continue
# If the image has already been vectorized before, just copy that slice
if image in image_dict:
image_data[index, :, :, :] = image_data[image_dict[image], :, :, :]
# Otherwise, vectorize the image
else:
# Add the index to the dictionary to check in the future
image_dict[image] = index
# Append the image path to the image name. If there's none, nothing will change
image = '{}{}'.format(image_path, image)
# Place the vectorized image into the image data
image_data[index, :, :, :] = _convert_single_image(image_source, model_str, image,
target_size=target_size,
grayscale=grayscale)
# Progress report at set intervals
if num_images < 1000:
report_step = 100
elif num_images < 5000:
report_step = 500
else:
report_step = 1000
if not index % report_step:
logging.info('Converted {} images in batch. Only {} images left to go.'.format(
index, num_images - index))
index += 1
return image_data, list_of_images
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] | 2.598162 | 6,092 |
class Rule:
"""Represents a single production rule of a grammar.
Rules are usually written using some sort of BNF-like notation,
for example, 'list ::= list item' would be a valid rule. A rule
always has a single non-terminal symbol on the left and a list
(possibly empty) of arbitrary symbols on the right. The above rule
would be constructed as follows.
>>> r = Rule('list', ('list', 'item'))
>>> print(r)
'list' = 'list', 'item';
The symbols can be arbitrary objects, not just strings. They must,
however, be hashable. (Hashability is not enforced by the Rule class
directly.)
>>> print(Rule(0, (1, 2)))
0 = 1, 2;
Occasionaly, you must pass a one-tuple.
>>> print(Rule('root', ('list',)))
'root' = 'list';
Note that terminal and non-terminal symbols are written
using the same syntax -- the differentiation only occurs
at the grammar level. The symbols standing on the left side of some rule
are considered non-terminal.
A rule can have no symbols on the right, such rules produce empty strings.
>>> print(Rule('e', ()))
'e' = ;
The left and right symbols can be accessed via 'left' and 'right' members.
>>> r.left, r.right
('list', ('list', 'item'))
A rule can have an associated semantic action. The action is not interpreted in any
way, but can be used to carry additional information in the rule. The default is None.
>>> repr(r.action)
'None'
A custom semantic action is associated in constructor.
>>> def concat_list(self, list, item):
... list.append(item)
... return list
>>> r = Rule('list', ('list', 'item'), action=concat_list)
>>> r.action(None, [], 1)
[1]
"""
def __init__(self, left, right, action=None):
"""
Constructs a rule from the left symbol, an iterable of right symbols
and an associated semantic action.
"""
self.left = left
self.right = tuple(right)
self.action = action
def __str__(self):
"""
>>> print(Rule('a', ('b', 'c')))
'a' = 'b', 'c';
>>> print(Rule('a', ()))
'a' = ;
>>> def _custom_action(ctx): pass
>>> print(Rule('a', (), _custom_action))
'a' = ; {_custom_action}
>>> print(Rule('a', (), lambda x: x))
'a' = ; {<lambda>}
"""
r = [repr(self.left), ' = ', ', '.join(repr(symbol) for symbol in self.right), ';']
if self.action is not None:
r.extend((' {', getattr(self.action, '__name__', ''), '}'))
return ''.join(r)
def __repr__(self):
"""
>>> print(repr(Rule('a', ('b', 'c'))))
Rule('a', ('b', 'c'))
>>> print(repr(Rule('a', ())))
Rule('a', ())
>>> def _my_action(ctx): return None
>>> print(repr(Rule('a', (), action=_my_action))) # doctest: +ELLIPSIS
Rule('a', (), <function _my_action...>)
>>> print(repr(Rule('a', (), action=lambda x: x))) # doctest: +ELLIPSIS
Rule('a', (), <function <lambda>...>)
"""
if self.action is not None:
args = (self.left, self.right, self.action)
else:
args = (self.left, self.right)
return 'Rule(%s)' % ', '.join((repr(arg) for arg in args))
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] | 2.391519 | 1,415 |
"""
Use previous output catalogs to investigate correct and incorrect images
"""
import logging
import os
import json
import pandas as pd
import numpy as np
from astropy.io import fits
from PIL import Image
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
from tidalclassifier.utils import custom_image_utils
from tidalclassifier.cnn.individual_cnn.meta_CNN import define_parameters
def visualise_error_by_class(df, save_loc):
"""Show performance on each pure tidal class based on predictions
Args:
df (pd.DataFrame): rows of galaxies, cols of picture_id, FEAT, true_label, and prediction
save_loc (str): path to save performance figure
"""
for n in range(len(df)):
df.at[n, 'log_loss'] = log_loss(df.iloc[n]['true_label'], df.iloc[n]['prediction'])
df.at[n, 'abs_error'] = absolute_error(df.iloc[n]['true_label'], df.iloc[n]['prediction'])
single_tidal_feature = {'L', 'M', 'A', 'S', 'F'}
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(16, 6))
ax1 = sns.boxplot(x="FEAT", y="log_loss", data=df[df['FEAT'].isin(single_tidal_feature)], ax=ax1)
ax1.set_xlabel('Tidal Class')
ax1.set_ylabel('Log Binary Cross-Entropy')
ax2 = sns.violinplot(x="FEAT", y="log_loss", data=df[df['FEAT'].isin(single_tidal_feature)], inner="stick", ax=ax2)
ax2.set_xlabel('Tidal Class')
ax2.set_ylabel('Log Binary Cross-Entropy')
ax3 = sns.boxplot(x="FEAT", y="abs_error", data=df[df['FEAT'].isin(single_tidal_feature)], ax=ax3)
ax3.set_xlabel('Tidal Class')
ax3.set_ylabel('Absolute Error')
ax3.set_ylim([0, 1])
ax4 = sns.violinplot(x="FEAT", y="abs_error", data=df[df['FEAT'].isin(single_tidal_feature)], inner="stick", ax=ax4)
ax4.set_xlabel('Tidal Class')
ax4.set_ylabel('Absolute Error')
ax4.set_ylim([0, 1])
plt.tight_layout()
plt.savefig(save_loc)
if __name__ == '__main__':
get_performance('/Data/repos/tidalclassifier/results/cnn_runs/oxford_first_run_80_epochs')
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] | 2.390498 | 863 |
'''
1. complete the missing data
2. convert the continous feature into discrete feature
3. one-hot encondes the discrete feature generated by the continous feature
4. one-hot encode all discrete feature
'''
import csv
import numpy as np
from numpy import fabs, random
from numpy.lib.function_base import percentile, sort_complex
from numpy.lib.shape_base import split
import pandas as pd
from BoostingTrees import process_training_data
MISSING_DATA = ['?']
CONTINUOUS_ATTR = ['fnlwgt']
INTEGER_ATTR = ['age', 'education.num', 'hours.per.week', 'capital.gain', 'capital.loss']
# process the missing data of the data
# mode, median and average
# write the data into csv file
# get the discrete rules
# transform the data from continous to discrete ones
if __name__ == '__main__':
training_data = pd.read_csv('./Data/train_final_full.csv', na_values=MISSING_DATA)
test_data = pd.read_csv('./Data/test_final.csv', na_values=MISSING_DATA)
processor = dProcessor(training_data, test_data) | [
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] | 2.935211 | 355 |
import sys
#operator precedence table
Precedence = {
'|' : 0, #NFA Union Operator
'.' : 1, #NFA Concat Operator
'?' : 2, #NFA zero or one Operator
'*' : 2, #NFA Closure Operator
'+' : 2 #NFA one or more Operator
}
| [
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] | 2.563218 | 87 |
import converter
import tkinter as tk
from tkinter import messagebox as tkm
import tkinter.font as tkf
if __name__ == '__main__':
# 创建主窗口
window = tk.Tk()
window.title('B站 AV/BV号转换器')
window.geometry('450x300')
window.iconbitmap('BVid2Aid.ico')
window.resizable(width=False, height=False)
# 常量&变量
font_main = tkf.Font(family="Lucida Grande", size=20)
var_input = tk.StringVar()
var_result = tk.StringVar()
# 顶部LOGO图片
canvas = tk.Canvas(window, height=200, width=450)
image_file = tk.PhotoImage(file='welcome.gif')
image = canvas.create_image(0, 0, anchor='nw', image=image_file)
canvas.pack(side=tk.TOP)
# 输入
tk.Label(window, text='AV/BVid: ', font=font_main).place(x=30, y=150)
entry_input = tk.Entry(window, textvariable=var_input,
width=16, highlightcolor='red', highlightthickness=1, font=font_main)
entry_input.place(x=160, y=150)
entry_input.bind("<Return>", lambda x: convert())
# 输出
tk.Label(window, text='Result: ', font=font_main).place(x=30, y=190)
output_result = tk.Entry(window, textvariable=var_result, state='readonly',
width=16, highlightcolor='red', highlightthickness=1, font=font_main)
output_result.place(x=160, y=190)
# 转换按钮
btn_login = tk.Button(window, text='Convert', command=convert, font=font_main)
btn_login.place(relx=0.5, y=260, relwidth=0.3, anchor=tk.CENTER)
window.mainloop()
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1137,
8,
628,
220,
220,
220,
4324,
13,
12417,
26268,
3419,
198
] | 2.113798 | 703 |
import requests
from usecases.screen.exceptions import UnknownResponseFormat
STATUS_OK = "OK"
STATUS_FAILED = "KO"
INFORMATION_MISSING = "N/A"
| [
11748,
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] | 2.862745 | 51 |
import os
import uproot3 as uproot
import torch
import torch.nn as nn
import numpy as np
from torch.utils.data import Dataset, DataLoader, Sampler
from datetime import datetime
from tqdm import tqdm
data_dir = 'data/'
node_features_list = ['trk_d0', 'trk_z0', 'trk_phi', 'trk_ctgtheta', 'trk_pt', 'trk_charge']
jet_features_list = ['jet_pt', 'jet_eta', 'jet_phi', 'jet_M']
node_features_list_real_data = ['Track_dxy', 'Track_dz', 'Track_phi', 'Track_eta', 'Track_pt', 'Track_charge']
jet_features_list_real_data = ['Jet_pt', 'Jet_eta', 'Jet_phi', 'Jet_mass']
track_vertex_key = b'trk_vtx_index'
track_vertex_key_real_data = b'Jet_SV_multi'
jet_flav_key = b'jet_flav'
jet_flav_key_real_data = b'Jet_hadronFlavour'
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628,
628,
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] | 2.403333 | 300 |
# Adapted from: https://github.com/rxn4chemistry/rxnfp/blob/master/nbs/10_results_uspto_1k_tpl.ipynb
import pickle
import click
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from sklearn.neural_network import MLPClassifier
import numpy as np
from pathlib import Path
from typing import Optional
from collections import Counter
from pycm import ConfusionMatrix
from sklearn.preprocessing import LabelEncoder
def get_pred(
train_X: np.array, train_y: np.array, eval_X: np.array, n_classes: int
) -> list:
"""
Get predictaions using a simple MLP.
"""
model = keras.models.Sequential(
[
keras.layers.Dense(1664, input_dim=len(train_X[0]), activation=tf.nn.tanh),
keras.layers.Dense(n_classes, activation=tf.nn.softmax),
]
)
model.compile(
loss="sparse_categorical_crossentropy",
optimizer=keras.optimizers.Adam(learning_rate=0.0001),
metrics=["accuracy"],
)
model.fit(
train_X,
train_y,
epochs=10,
batch_size=64,
)
return np.argmax(model.predict(eval_X), axis=-1)
def get_cache_confusion_matrix(
name: str, actual_vector: list, predict_vector: list
) -> ConfusionMatrix:
"""
Make confusion matrix and save it.
"""
cm = ConfusionMatrix(actual_vector=actual_vector, predict_vector=predict_vector)
cm.save_html(name)
with open(f"{name}.pickle", "wb") as f:
pickle.dump(cm, f)
return cm
@click.command()
@click.argument("input_train_filepath", type=click.Path(exists=True))
@click.argument("input_test_filepath", type=click.Path(exists=True))
if __name__ == "__main__":
main()
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366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.444921 | 699 |
from django.conf.urls import url, include
urlpatterns = [
url(r'', include("iiif_api_services.urls")),
]
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] | 2.571429 | 42 |
import os
import logging
import requests
import json
from string import Formatter, Template
from datetime import datetime
import satsearch.utils as utils
import satsearch.config as config
import traceback
logger = logging.getLogger(__name__)
class Scenes(object):
""" A collection of Scene objects """
def __init__(self, scenes, properties={}):
""" Initialize with a list of Scene objects """
self.scenes = sorted(scenes, key=lambda s: s.date)
self.properties = properties
for p in properties:
if isinstance(properties[p], str):
try:
_p = json.loads(properties[p])
self.properties[p] = _p
except:
self.properties[p] = properties[p]
# check if FeatureCollection and get just first Feature
if p == 'intersects':
if self.properties[p]['type'] == 'FeatureCollection':
self.properties[p] = self.properties[p]['features'][0]
self.collections
def __len__(self):
""" Number of scenes """
return len(self.scenes)
def dates(self):
""" Get sorted list of dates for all scenes """
return sorted(list(set([s.date for s in self.scenes])))
def collections(self):
""" Get collection records for this list of scenes """
return self.collections
def bbox(self):
""" Get bounding box of search """
if 'intersects' in self.properties:
coords = self.properties['intersects']['geometry']['coordinates']
lats = [c[1] for c in coords[0]]
lons = [c[0] for c in coords[0]]
return [min(lons), min(lats), max(lons), max(lats)]
else:
return []
def platforms(self, date=None):
""" List of all available sensors across scenes """
if date is None:
return list(set([s['eo:platform'] for s in self.scenes]))
else:
return list(set([s['eo:platform'] for s in self.scenes if s.date == date]))
def print_scenes(self, params=[]):
""" Print summary of all scenes """
if len(params) == 0:
params = ['date', 'id']
txt = 'Scenes (%s):\n' % len(self.scenes)
txt += ''.join(['{:<20}'.format(p) for p in params]) + '\n'
for s in self.scenes:
# NOTE - the string conversion is because .date returns a datetime obj
txt += ''.join(['{:<20}'.format(str(s[p])) for p in params]) + '\n'
print(txt)
def text_calendar(self):
""" Get calendar for dates """
date_labels = {}
dates = self.dates()
if len(dates) == 0:
return ''
for d in self.dates():
sensors = self.platforms(d)
if len(sensors) > 1:
date_labels[d] = 'Multiple'
else:
date_labels[d] = sensors[0]
return utils.get_text_calendar(date_labels)
def save(self, filename):
""" Save scene metadata """
with open(filename, 'w') as f:
f.write(json.dumps(self.geojson()))
def geojson(self):
""" Get all metadata as GeoJSON """
features = [s.feature for s in self.scenes]
return {
'type': 'FeatureCollection',
'features': features,
'properties': self.properties
}
@classmethod
def load(cls, filename):
""" Load a collections class from a GeoJSON file of metadata """
with open(filename) as f:
geoj = json.loads(f.read())
scenes = [Scene(feature) for feature in geoj['features']]
return Scenes(scenes, properties=geoj.get('properties', {}))
def filter(self, key, values):
""" Filter scenes on key matching value """
scenes = []
for val in values:
scenes += list(filter(lambda x: x[key] == val, self.scenes))
self.scenes = scenes
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220,
220,
220,
220,
220,
220,
220,
8188,
15853,
1351,
7,
24455,
7,
50033,
2124,
25,
2124,
58,
2539,
60,
6624,
1188,
11,
2116,
13,
28123,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
28123,
796,
8188,
198
] | 2.249434 | 1,768 |
#!/usr/bin/env python
import json
from vc3master.task import VC3Task
| [
2,
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] | 2.342857 | 35 |
import asyncio
from fastapi_mail import FastMail, MessageSchema
from app.core.celery_app import celery_app
from app.core.config import settings
@celery_app.task
| [
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] | 3.173077 | 52 |
"""
62 / 62 test cases passed.
Runtime: 32 ms
Memory Usage: 15 MB
"""
| [
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#!/usr/bin/env python3
# encoding: utf-8
#
# Copyright (c) 2009 Doug Hellmann All rights reserved.
#
"""
"""
# flake8: noqa
#end_pymotw_header
import gettext
gettext.install(
'example',
'locale',
names=['ngettext'],
)
print(_('This message is in the script.'))
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] | 2.464286 | 112 |
from setuptools import setup, find_packages
setup(
name="spaceship",
version="0.8.2",
packages=find_packages(),
install_requires=[
'netifaces'
],
url = 'https://github.com/antoan-angelov/spaceship/',
author="Antoan Angelov",
author_email="[email protected]",
description="Python utility for chat and streaming files across machines in the same network",
license="MIT",
keywords="spaceship python terminal chat stream files same network",
classifiers=[
"Development Status :: 4 - Beta",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Communications :: Chat",
"Topic :: Utilities",
"Programming Language :: Python :: 3.4",
"Operating System :: POSIX :: Linux",
"Natural Language :: English",
"Environment :: Console",
"Intended Audience :: End Users/Desktop",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License"
],
entry_points={
'console_scripts': [
'spaceship = spaceship.__main__:main'
]
}
) | [
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8
] | 2.626424 | 439 |
# simplest case: takes a single line and convert it to binary
import sys
import re
# 15 bit addresses
predefined_symbols = {
'THAT': '000000000000100',
'R14': '000000000001110',
'R15': '000000000001111',
'R12': '000000000001100',
'R13': '000000000001101',
'R10': '000000000001010',
'R11': '000000000001011',
'KBD': '110000000000000',
'R4': '000000000000100',
'R5': '000000000000101',
'R6': '000000000000110',
'R7': '000000000000111',
'R0': '000000000000000',
'R1': '000000000000001',
'R2': '000000000000010',
'R3': '000000000000011',
'SCREEN': '100000000000000',
'R8': '000000000001000',
'R9': '000000000001001',
'THIS': '000000000000011',
'SP': '000000000000000',
'ARG': '000000000000010',
'LCL': '000000000000001'
}
comp_map = {
"0": "0101010",
"1": "0111111",
"-1": "0111010",
"D": "0001100",
"A": "0110000",
"!D": "0001101",
"!A": "0110001",
"-D": "0001111",
"-A": "0110011",
"D+1": "0011111",
"A+1": "0110111",
"D-1": "0001110",
"A-1": "0110010",
"D+A": "0000010",
"D-A": "0010011",
"A-D": "0000111",
"D&A": "0000000",
"D|A": "0010101",
"M": "1110000",
"!M": "1110001",
"-M": "1110011",
"M+1": "1110111",
"M-1": "1110010",
"D+M": "1000010",
"D-M": "1010011",
"M-D": "1000111",
"D&M": "1000000",
"D|M": "1010101"
}
dest_map = {
"": "000",
"M": "001",
"D": "010",
"MD": "011",
"A": "100",
"AM": "101",
"AD": "110",
"AMD": "111"
}
jump_map = {
"": "000",
"JGT": "001",
"JEQ": "010",
"JGE": "011",
"JLT": "100",
"JNE": "101",
"JLE": "110",
"JMP": "111"
}
if __name__ == '__main__':
if len(sys.argv) < 3:
raise Exception("You need to supply a hack asm file and target")
file_name = sys.argv[1]
target_name = sys.argv[2]
output = assemble(file_name)
with open(target_name, "w") as f:
f.write(output)
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220,
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13,
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7,
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8,
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] | 1.99503 | 1,006 |
# 使用import方式进行导入时，只能跟包名或模块名称
# import 包名
import calc2
# import 模块名
import package.module_a
# import 包名+取别名
import package.module_b as mb
# from 包名 import 模块名
# 使用from...import方式可以导入包、模块、函数、变量
from package import module_a
print(package.module_a.a)
print(mb.b)
print(module_a.a)
print(calc2.add(10, 20))
| [
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] | 1.470874 | 206 |
import functools
import time
from django.db import connection, reset_queries
from django.utils.deprecation import MiddlewareMixin
| [
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] | 3.540541 | 37 |
# Copyright 2021 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function, division, absolute_import
from numba import types
from numba.core.typing.npydecl import register_number_classes, parse_dtype, parse_shape
from numba.core.typing.templates import (
AttributeTemplate,
ConcreteTemplate,
AbstractTemplate,
CallableTemplate,
signature,
Registry,
)
import numba_dppy, numba_dppy as dppy
from numba_dppy import target
from numba_dppy.dppy_array_type import DPPYArray
registry = Registry()
intrinsic = registry.register
intrinsic_attr = registry.register_attr
intrinsic_global = registry.register_global
# register_number_classes(intrinsic_global)
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
@intrinsic
# dppy.atomic submodule -------------------------------------------------------
@intrinsic
@intrinsic
@intrinsic_attr
intrinsic_global(dppy.atomic.add, types.Function(Ocl_atomic_add))
intrinsic_global(dppy.atomic.sub, types.Function(Ocl_atomic_sub))
# dppy.local submodule -------------------------------------------------------
@intrinsic
@intrinsic_attr
# OpenCL module --------------------------------------------------------------
@intrinsic_attr
# intrinsic
# intrinsic_global(dppy, types.Module(dppy))
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31,
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2,
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62,
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7,
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14097,
11,
3858,
13,
26796,
7,
67,
14097,
4008,
198
] | 3.215385 | 585 |
#!/usr/bin/env python
try:
from setuptools import setup, find_packages
except ImportError:
raise RuntimeError('setuptools is required')
DESCRIPTION = ('pvops is a python library for the analysis of ' +
'field collected operational data for photovoltaic systems.')
LONG_DESCRIPTION = """
pvops is a python package for PV operators & researchers. It is
a collection of functions for working with text-based data
from photovoltaic power systems. The library includes functions for
processing text data as well as fusion of the text information with
time series data for visualization of contextual details for data
analysis.
Documentation: https://pvops.readthedocs.io/en/latest/index.html
Source code: https://github.com/sandialabs/pvOps
"""
DISTNAME = 'pvops'
MAINTAINER = "Thushara Gunda"
MAINTAINER_EMAIL = '[email protected]'
LICENSE = 'Revised BSD'
URL = 'https://github.com/sandialabs/pvops'
TESTS_REQUIRE = [
'pytest',
]
INSTALL_REQUIRES = [
'numpy >= 1.15.0',
'pandas >= 0.23.0',
'scipy >= 1.2.0',
'scikit-learn',
'nltk',
'datefinder',
'matplotlib',
'seaborn',
'plotly',
'gensim',
'networkx',
'pvlib',
'pvanalytics',
'timezonefinder'
]
DOCS_REQUIRE = [
'sphinx == 2.2.0'
]
EXTRAS_REQUIRE = {
'optional': ['ruptures'],
'test': TESTS_REQUIRE,
'doc': DOCS_REQUIRE
}
EXTRAS_REQUIRE['all'] = sorted(set(sum(EXTRAS_REQUIRE.values(), [])))
SETUP_REQUIRES = ['setuptools_scm']
CLASSIFIERS = [
'Development Status :: 2 - Pre-Alpha',
'Operating System :: OS Independent',
'Intended Audience :: Science/Research',
'Programming Language :: Python :: 3',
'Topic :: Scientific/Engineering'
]
PACKAGES = find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"])
setup(
name=DISTNAME,
use_scm_version=True,
packages=PACKAGES,
install_requires=INSTALL_REQUIRES,
extras_require=EXTRAS_REQUIRE,
tests_require=TESTS_REQUIRE,
setup_requires=SETUP_REQUIRES,
ext_modules=[],
description=DESCRIPTION,
long_description=LONG_DESCRIPTION,
maintainer=MAINTAINER,
maintainer_email=MAINTAINER_EMAIL,
license=LICENSE,
classifiers=CLASSIFIERS,
url=URL
)
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1137,
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11,
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5064,
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4877,
11,
198,
220,
220,
220,
19016,
28,
21886,
198,
8,
198
] | 2.527149 | 884 |
from __future__ import print_function
import os
import sys
import getopt
from os import path
from textwrap import dedent
from retrying import retry
from awsudo.config import CredentialResolver
from awsudo.main import cleanEnvironment
from boto.iam.connection import IAMConnection
from boto.exception import BotoServerError
ACCESS_KEY_DOCS = 'http://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html'
try:
from configparser import RawConfigParser
except ImportError:
from ConfigParser import RawConfigParser
@retry(
stop_max_delay=60*1000,
wait_exponential_multiplier=250,
wait_exponential_max=10*1000,
retry_on_exception=lambda e: isinstance(e, BotoServerError))
def deactivateKey(iam, oldKey, userName):
"""Set the given key as inactive.
I'll retry a few times if necessary because AWS's API is eventually
consistent, and it can take a few seconds for new access keys to start
working.
"""
iam.update_access_key(oldKey, 'Inactive', userName)
def deleteOldKeys(iam, currentKeyId, userName):
"""Delete all keys except the currentKeyId.
I'll only delete inactive keys. If I find any that are active, I'll abort
the program.
We must delete old keys because each user can have a maximum of two.
"""
response = iam.get_all_access_keys(userName)['list_access_keys_response']
allKeys = response['list_access_keys_result']['access_key_metadata']
oldKeys = [k for k in allKeys if k['access_key_id'] != currentKeyId]
if len(oldKeys) == len(allKeys):
abort(
"Very odd: current key %s is not listed" %
(currentKeyId,)
)
for key in oldKeys:
if key['status'] == 'Active':
abort(dedent('''
%s is still active: will not automatically delete it.
Please delete it manually if it is safe to do so.
%s
''' % (key['access_key_id'], ACCESS_KEY_DOCS)).strip())
for key in oldKeys:
iam.delete_access_key(key['access_key_id'], user_name=userName)
if __name__ == '__main__':
main()
| [
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834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.712452 | 779 |
import os
import sys
import subprocess
import traceback
import pexpect
if False:
# This is just needed so mypy will work; it's never executed.
from typing import Optional # NOQA
MY_DIR = os.path.abspath(os.path.dirname(__file__))
SAUCE_CONNECT_SH_PATH = os.path.join(MY_DIR, 'sauce_connect.sh')
LOAD_SAUCE_CONNECT = 'source {}'.format(SAUCE_CONNECT_SH_PATH)
PROMPT = "BASH IS READY > "
TIMEOUT = 30 # In seconds.
if __name__ == '__main__':
if len(sys.argv) <= 2:
print("usage: {} <command>".format(sys.argv[0]))
sys.exit(maybe_run_with_tunnel(sys.argv[1:]))
| [
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] | 2.407258 | 248 |
from __future__ import absolute_import, division, print_function
from six.moves import range
# -*- Mode: Python; c-basic-offset: 2; indent-tabs-mode: nil; tab-width: 8 -*-
#
# LIBTBX_SET_DISPATCHER_NAME cctbx.xfel.stripe_experiment
#
# Given an LCLS experiment results directory and a trial, group results by
# run group and then distrbute each run group's results into subgroups and run
# dials.combine_experiments (optionally with clustering and selecting clusters).
#
from dials.util import show_mail_on_error
from libtbx.phil import parse
from libtbx.utils import Sorry
from libtbx import easy_run
from xfel.util.dials_file_matcher import match_dials_files
from xfel.util.mp import mp_phil_str as multiprocessing_str
from xfel.util.mp import get_submit_command_chooser
import sys
import os, math
import six
multiprocessing_override_str = '''
mp {
use_mpi = False
}
'''
striping_str = '''
striping {
results_dir = None
.type = path
.help = "LCLS results directory containint runs starting with r."
rungroup = None
.type = int
.multiple = True
.help = "Selected rungroups to stripe. If None, all rungroups are accepted."
run = None
.type = str
.multiple = True
.help = "Selected runs to stripe. If None, all runs are accepted."
trial = None
.type = int
.help = "Trial identifier for an XFEL GUI formatted processing trial."
stripe = False
.type = bool
.help = "Enable to select results evenly spaced across each rungroup"
"(stripes) as opposed to contiguous chunks."
chunk_size = 1000
.type = float
.help = "Maximum number of images per chunk or stripe."
respect_rungroup_barriers = True
.type = bool
.help = "Enforce separation by rungroup at time of striping (default)."
"Turn off to allow multiple rungroups to share a detector model."
dry_run = False
.type = bool
.help = "Only set up jobs but do not execute them"
output_folder = None
.type = path
.help = "Path for output data. If None, use current directory"
}
'''
combining_str = '''
combine_experiments {
clustering {
dendrogram = False
.type = bool
.help = "Overrides any multiprocessing parameters to allow interactive"
.help = "run. Clustering dendrograms can only be displayed in this mode."
}
keep_integrated = False
.type = bool
.help = "Combine refined.expt and integrated.refl files."
.help = "If False, ignore integrated.refl files in favor of"
.help = "indexed.refl files in preparation for reintegrating."
include scope dials.command_line.combine_experiments.phil_scope
}
'''
combining_override_str = '''
combine_experiments {
output {
experiments_filename = FILENAME_combined.expt
reflections_filename = FILENAME_combined.refl
delete_shoeboxes = False
}
reference_from_experiment {
detector = 0
}
clustering {
use = True
}
}
'''
# future feature: filter experiments by rmsd after combining/clustering
filtering_str = '''
filtering {
enable = False
}
'''
refinement_str = '''
refinement {
include scope dials.command_line.refine.phil_scope
input {
experiments = None
reflections = None
}
}
'''
refinement_override_str = '''
refinement {
output {
experiments = FILENAME_refined_CLUSTER.expt
reflections = FILENAME_refined_CLUSTER.refl
include_unused_reflections = False
log = FILENAME_refine_CLUSTER.log
debug_log = FILENAME_refine_CLUSTER.debug.log
}
refinement {
parameterisation {
auto_reduction {
action = remove
}
beam {
fix = all
}
}
refinery {
engine = SparseLevMar
}
reflections {
outlier {
algorithm = sauter_poon
minimum_number_of_reflections = 3
separate_experiments = False
separate_panels = False
}
}
}
input {
experiments = FILENAME_combined_CLUSTER.expt
reflections = FILENAME_combined_CLUSTER.refl
}
}
'''
recompute_mosaicity_str = '''
recompute_mosaicity {
include scope xfel.command_line.recompute_mosaicity.phil_scope
input {
experiments = None
reflections = None
}
}
'''
recompute_mosaicity_override_str = '''
recompute_mosaicity {
input {
experiments = FILENAME_refined_CLUSTER.expt
reflections = FILENAME_refined_CLUSTER.refl
}
output {
experiments = FILENAME_refined_CLUSTER.expt
reflections = FILENAME_refined_CLUSTER.refl
}
}
'''
# reintegration after dials refinement
reintegration_str = '''
reintegration {
enable = True
include scope xfel.merging.command_line.mpi_integrate.phil_scope
input {
experiments = None
reflections = None
}
}
'''
reintegration_override_str = '''
reintegration{
dispatch {
step_list = input balance integrate
}
output {
prefix = FILENAME_reintegrated_CLUSTER
save_experiments_and_reflections = True
}
input {
path = .
experiments_suffix = FILENAME_refined_CLUSTER.expt
reflections_suffix = FILENAME_refined_CLUSTER.refl
}
}
'''
# split results and coerce to integration pickle for merging
postprocessing_str = '''
postprocessing {
enable = True
include scope xfel.command_line.frame_extractor.phil_scope
}
'''
postprocessing_override_str = """
postprocessing {
input {
experiments = FILENAME_reintegrated_CLUSTER*.expt
reflections = FILENAME_reintegrated_CLUSTER*.refl
}
output {
filename = FILENAME_CLUSTER_ITER_extracted.refl
dirname = %s
}
}
"""
master_defaults_str = multiprocessing_str + striping_str + combining_str + filtering_str + \
refinement_str + recompute_mosaicity_str + reintegration_str + postprocessing_str
# initialize a master scope from the multiprocessing phil string
master_defaults_scope = parse(master_defaults_str, process_includes=True)
# update master scope with customized and local phil scopes
phil_scope = master_defaults_scope.fetch(parse(postprocessing_override_str, process_includes=True))
phil_scope = phil_scope.fetch(parse(reintegration_override_str, process_includes=True))
phil_scope = phil_scope.fetch(parse(recompute_mosaicity_override_str, process_includes=True))
phil_scope = phil_scope.fetch(parse(refinement_override_str, process_includes=True))
phil_scope = phil_scope.fetch(parse(combining_override_str, process_includes=True))
phil_scope = phil_scope.fetch(parse(multiprocessing_override_str, process_includes=True))
helpstring = """cctbx.xfel.stripe_experiment: parallel processing of an XFEL UI-generated trial.
usage: cctbx.xfel.stripe_experiment striping.results_dir=/path/to/results striping.trial=000
for interactive unit cell clustering, use combine_experiments.clustering.dendrogram=True
"""
def script_to_expand_over_clusters(clustered_json_name,
phil_template_name, command, location):
"""
Write a bash script to find results of a clustering step and produce customized
phils and commands to run with each of them. For example, run the command
dials.refine ...cluster8.expt ...cluster8.refl ...cluster8.phil followed by
dials.refine ...cluster9.expt ...cluster9.refl ...cluster9.phil.
clustered_json_name, clustered_refl_name and phil_template_name must each
contain an asterisk, and substitution in phil_template itself will occur at
each instance of CLUSTER.
"""
clj_part_first, clj_part_last = clustered_json_name.split("CLUSTER")
clustered_template_name = clj_part_first + "*" + clj_part_last
ph_part_first, ph_part_last = phil_template_name.split("CLUSTER")
bash_str = '''
#! /bin/sh
for file in `ls {clname}`
do export cluster=`echo $file | sed "s:{cljfirst}::; s:{cljlast}::"`
export philname="{phfirst}${cluster}{phlast}"
export outname=`echo $philname | sed "s:.phil:.out:"`
sed "s:CLUSTER:${cluster}:g" {phtempl} > $philname
{command} $philname > $outname
done
'''.format(clname=clustered_template_name, phtempl=phil_template_name,
cljfirst=clj_part_first, cljlast=clj_part_last,
phfirst=ph_part_first, phlast=ph_part_last,
command=command, cluster="{cluster}")
bash_name = "generator".join([ph_part_first, ph_part_last]).split(".phil")[0] + ".sh"
with open(os.path.join(location, bash_name), "wb") as script:
script.write(bash_str)
return bash_name
if __name__ == "__main__":
import sys
if "-h" in sys.argv[1:] or "--help" in sys.argv[1:]:
print(helpstring)
exit()
if "-c" in sys.argv[1:]:
expert_level = int(sys.argv[sys.argv.index("-e") + 1]) if "-e" in sys.argv[1:] else 0
attr_level = int(sys.argv[sys.argv.index("-a") + 1]) if "-a" in sys.argv[1:] else 0
phil_scope.show(expert_level=expert_level, attributes_level=attr_level)
with open("striping_defaults.phil", "wb") as defaults:
defaults.write(phil_scope.as_str())
exit()
with show_mail_on_error():
script = Script()
script.run()
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] | 2.697328 | 3,294 |
from django.conf.urls import url
from todos.views import TodoListCreateAPIView, TodoDetailAPIView
urlpatterns = [
url(r'^$', TodoListCreateAPIView.as_view(), name="list"),
url(r'^(?P<pk>[0-9]+)/$', TodoDetailAPIView.as_view(), name="detail"),
] | [
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from typing import Optional
from fastapi_camelcase import CamelModel
from .common._unit_validators import dB_unit_check_validator, power_unit_validator
from .signals.frequency import Frequency
class GainFrequency(Gain):
"""[Gain at a single frequency]
Arguments:
f {Frequency} -- Single Frequency
gain {Gain} -- Gain in dB
"""
f: Frequency
class GainTransfer(CamelModel):
"""[Input Power vs. Output Power Base Model]
Arguments:
input_power {Power} -- Input power in dBm
output_power {Power} -- Output power in dBm
"""
input_power: Power
output_power: Power
gain: Optional[Gain]
class GainTransferFrequency(GainTransfer):
"""[Input Power vs. Output Power at a single frequency]
Arguments:
f {Frequency} -- Single Frequency
input_power {Power} -- Input power in dBm
output_power {Power} -- Output power in dBm
"""
f: Frequency
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] | 2.822485 | 338 |
# DATA TYPES, NUMBERS, OPERATIONS, TYPE CONVERSION, f-Strings
# 1. Data Types
# a. String
# pulling out an element from the string = subscripting
# the index starts from 0 to length-1
print("Hello"[3])
# b. Integer
# large integers can be separated with _
print(199_000) # show 199000, but it makes it more readable for us
# c. Float = floating point number
print(3.41231231)
# d. Boolean = True or False
print(True)
# 2. Type Error, Type Checking, Type Conversion
# Type Error -> when we give the wrong type to the function
print(type("aPPLE")) # CHECK THE TYPE OF THE VALUE/VARIABLE
# TYPE CASTING -> CONVERT INTO ANOTHER VALUE
num_str = str(100)
print("My Wishful Score is "+ num_str)
# DATA TYPE EXERCISE
two_digit_number = input("Type a two digit number: ")
if len(two_digit_number)!=2:
print("Invalid input")
print(int(two_digit_number[0]) + int(two_digit_number[1]))
# 3. Mathematical Operators
# '-' Substraction
# '*' Multiplication
# '**' Exponent
# '/' Division -> float result
# '//' Division -> number result
# '%' Modulus
# Priorities -> (), **, * / , + -
# MATHEMATICAL OPERATOR EXERCISE -> BMI CALCULATOR
# Count Body Mass Index with formula = weight/(height^2)
weight = float(input("Input your Weight (kg): "))
height = float(input("Input your Height (m): "))
print("Your BMI index (simplified) is "+ str(int(weight/(height**2))))
# Number Manipulation and F Strings
print(round(10/3,2)) # round function -> how many decimal places
# shorthand => symbol + '='
# f-string
score = 86
print(f'Your score is {score}')
# MATHEMATICAL MANIPULATION EXERCISE -> LIFE IN WEEKS
# Count how many days, weeks, and months left if you live until 90
age = int(input("What is your current age? "))
days = (90-age)*365
weeks = (90-age)*52
months = (90-age)*12
print(f"You have {days} days, {weeks} weeks, and {months} months left.") | [
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] | 2.985554 | 623 |
# Generated by Django 2.0.7 on 2018-08-14 12:53
from django.db import migrations, models
| [
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#!/usr/bin/python
# Standard library imports
from datetime import datetime
from optparse import OptionParser
import os
import sys
import time
from xml.sax.saxutils import escape as h
# Some global variables
svn_sep = "------------------------------------------------------------------------"
cvs_sep = "----------------------------"
# Event to hold all of the separate events as we parse them from the logs.
def parse_args(argv):
""" Parses command line arguments and returns an options object
along with any extra arguments.
"""
p = OptionParser()
p.add_option("-s", "--svn-log", dest="svn_log",
metavar="<log file>",
help="input svn log to convert to standard event xml")
p.add_option("-c", "--cvs-log", dest="cvs_log",
metavar="<log file>",
help="input cvs log to convert to standard event xml")
p.add_option("-g", "--git-log", dest="git_log",
metavar="<log file>",
help="input git log to convert to standard event xml")
p.add_option("-v", "--vss-log", dest="vss_log",
metavar="<log file>",
help="input vss report to convert to standard event xml")
p.add_option("-t", "--starteam-log", dest="starteam_log",
metavar="<log file>",
help="input starteam log to convert to standard event xml")
p.add_option("-w", "--wikiswarm-log", dest="wikiswarm_log",
metavar="<log file>",
help="input wikiswarm log to convert to standard event xml")
p.add_option("-m", "--mercurial-log", dest="mercurial_log",
metavar="<log file>",
help="input mercurial log to convert to standard event xml")
p.add_option( "-d", "--darcs-log", dest="darcs_log",
metavar="<log file>",
help="input darcs log to convert to standard event xml")
p.add_option( "-o", "--output-log", dest="output_log",
metavar="<log file>",
help="specify standard log output file")
p.add_option( "-p", "--perforce-path", dest="perforce_path",
metavar="<log file>",
help="get data from perforce and save it to standard event xml")
(options, args) = p.parse_args(argv)
return (options, args)
def main():
""" Calls the parse_args function based on the
command-line inputs and handles parsed arguments.
"""
(opts, args) = parse_args(sys.argv)
# Handle parsed options.
if opts.svn_log or opts.git_log:
# Grab the correct log file based on what was specified.
log_file = opts.svn_log
if opts.git_log:
print "Parsing Git log..."
log_file = opts.git_log
else:
print "Parsing SVN log..."
# Check to be sure the specified log path exists.
if os.path.exists(log_file):
# Iterate through log file lines to parse out the revision history, adding Event
# entries to a list as we go.
commits = 0
event_list = []
file_handle = open(log_file, 'r')
line = file_handle.readline()
while len(line) > 0:
# The svn_sep indicates a new revision history to parse.
if line.startswith(svn_sep):
# Extract author and date from revision line. Here is a sample revision line:
# r9 | michael.ogawa | 2008-06-19 10:23:25 -0500 (Thu, 19 Jun 2008) | 3 lines.
rev_line = file_handle.readline()
# The last line of the file is an svn_sep line, so if we try to retreive the
# revision line and get an empty string, we know we are at the end of the file
# and can break out of the loop.
# "" is EOF condition
if rev_line == "":
break;
rev_parts = rev_line.split(' | ')
# line containing committer info is malformed
if len(rev_parts) < 4:
continue
author = rev_parts[1]
date_parts = rev_parts[2].split(" ")
date = date_parts[0] + " " + date_parts[1]
date = time.strptime(date, '%Y-%m-%d %H:%M:%S')
date = int(time.mktime(date))*1000
# Skip the 'Changed paths:' line and start reading in the changed filenames.
nextLine = file_handle.readline()
# malformed log
if nextLine.lower()[:14] != "changed paths:":
continue;
commits += 1
path = file_handle.readline()
while len(path) > 1:
ch_path = None
if opts.svn_log:
ch_path = path[5:].split(" (from")[0].replace("\n", "")
else:
# git uses quotes if filename contains unprintable characters
ch_path = path[2:].replace("\n", "").replace("\"", "")
event_list.append(Event(ch_path, date, author))
path = file_handle.readline()
line = file_handle.readline()
file_handle.close()
print "Parsed %i commits" % ( commits )
# Generate standard event xml file from event_list.
create_event_xml(event_list, log_file, opts.output_log)
else:
print "Please specify an existing path."
if opts.cvs_log:
log_file = opts.cvs_log
print "Parsing CVS log..."
# Check to be sure the specified log path exists.
if os.path.exists(log_file):
event_list = []
filename = ""
file_handle = open(log_file, 'r')
line = file_handle.readline()
while len(line) > 0:
# The cvs_sep indicates a new revision history to parse.
if line.startswith(cvs_sep):
#Read the revision number
rev_line = file_handle.readline()
# Extract author and date from revision line.
rev_line = file_handle.readline()
if(rev_line.lower().find("date:") == 0):
rev_parts = rev_line.split('; ')
date_parts = rev_parts[0].split(": ")
date_no_tz = ' '.join(date_parts[1].split(' ')[0:2]).strip()
for fmts in ['%Y-%m-%d %H:%M:%S', '%Y/%m/%d %H:%M:%S']:
try:
date = time.strptime(date_no_tz, fmts)
except:
pass
else:
break
date = int(time.mktime(date))*1000
author = rev_parts[1].split(": ")[1]
event_list.append(Event(filename, date, author))
line = file_handle.readline()
if(str(line) == ""):
break
elif(line.lower().find("rcs file: ") >= 0):
rev_line = line.split(": ");
filename = rev_line[1].strip().split(',')[0]
file_handle.close()
# Generate standard event xml file from event_list.
create_event_xml(event_list, log_file, opts.output_log)
else:
print "Please specify an existing path."
if opts.vss_log:
log_file = opts.vss_log
print "Parsing VSS log..."
if os.path.exists(log_file):
event_list = []
file_handle = open(log_file, 'r')
filename = ""
author = ""
mdy = ""
t = ""
# The VSS report can have multiple lines for each entry, where the values
# are continued within a column range.
for line in file_handle.readlines():
if line.startswith(' '):
# Handle a continuation line
filename += line[0:20].strip()
author += line[22:31].strip()
else:
if mdy:
filename = filename.replace("$", "")
date = datetime.strptime(mdy + ' ' + t[:-1]+t[-1].upper()+'M', "%m/%d/%y %I:%M%p")
date = int(time.mktime(date.timetuple())*1000)
event_list.append(Event(filename, date, author.lower()))
filename = line[0:20].strip()
author = line[21:31].strip()
mdy = line[32:40].strip()
t = line[42:48].strip()
create_event_xml(event_list, log_file, opts.output_log)
if opts.starteam_log:
log_file = opts.starteam_log
print "Parsing starteam log..."
if os.path.exists(log_file):
import re
event_list = []
file_handle = open(log_file, 'r')
folder = None
filename = None
# The Starteam log can have multiple lines for each entry
for line in file_handle.readlines():
m = re.compile("^Folder: (\w*) \(working dir: (.*)\)$").match(line)
if m:
folder = m.group(2)
#print "parsing folder %s @ %s" % (m.group(1), folder)
continue
m = re.compile("^History for: (.*)$").match(line)
if m:
filename = m.group(1)
#print "parsing file %s" % filename
continue
m = re.compile("^Author: (.*) Date: (.*) \w+$").match(line)
if m:
author = m.group(1)
date = datetime.strptime(m.group(2), "%m/%d/%y %I:%M:%S %p")
date = int(time.mktime(date.timetuple())*1000)
event_list.append(Event(os.path.join(folder, filename), date, author))
#print "%s check in at %s" % (author, date)
continue
create_event_xml(event_list, log_file, opts.output_log)
if opts.wikiswarm_log:
log_file = opts.wikiswarm_log
print "Parsing wikiswarm log..."
# Check to be sure the specified log path exists.
if os.path.exists(log_file):
event_list = []
file_handle = open(log_file, 'r')
line = file_handle.readline()
for rev_line in file_handle.readlines():
if rev_line is '':
continue
rev_parts = rev_line.split('|')
#rev_id = rev_parts[0].strip()# Don't really need this, it's mainly for the ouputter
filename = rev_parts[1].strip()
author = rev_parts[2].strip()
date = rev_parts[3].strip()+'000' # Padd to convert seconds into milliseconds
event_list.append(Event(filename, date, author))
continue
# Generate standard event xml file from event_list.
create_event_xml(event_list, log_file, opts.output_log)
if opts.mercurial_log:
# author: Stefan Scherfke
# contact: stefan.scherfke at uni-oldenburg.de
log_file = opts.mercurial_log
print "Parsing mercurial log..."
if os.path.exists(log_file):
event_list = []
file_handle = open(log_file, 'r')
state = 0
user = ''
date = ''
files = []
for line in file_handle.readlines():
if state == 0:
author = line[:-1]
state += 1
elif state == 1:
date = line[:line.find('.')] + '000'
state += 1
elif state == 2:
files = line[:-1].split(' ')
for filename in files:
event_list.append(Event(filename, date, author.lower()))
state += 1
elif state == 3:
state = 0
else:
print 'Error: undifined state'
create_event_xml(event_list, log_file, opts.output_log)
if opts.darcs_log:
log_file = opts.darcs_log
print "Parsing darcs log..."
if os.path.exists(log_file):
event_list = []
file_handle = open(log_file, 'r')
user = ''
date = ''
for line in file_handle.readlines():
line = line.rstrip()
if len(line) == 0:
continue
elif line[0] != ' ':
date = line[:29].strip()
author = line[30:].strip()
if date[7:9] == ' ':
date = date.replace(' ', ' 0')
date = int(time.mktime(time.strptime(date, '%a %b %d %H:%M:%S %Z %Y')))*1000
parts = author.split('<')
if len(parts) == 2:
author = parts[0].strip()
elif line[0] == ' ' and len(line) > 4:
if line[4:8] == 'M ./' or line[4:8] == 'A ./' or line[4:8] == 'R ./':
filename = line.lstrip('MAR ./')
filename = filename.rstrip(' +-123456789')
event_list.append(Event(filename, date, author))
continue
else:
continue
else:
continue
create_event_xml(event_list, log_file, opts.output_log)
if opts.perforce_path:
import re
print "Parsing perforce log..."
event_list = []
changelists = run_marshal('p4 -G changelists "' + opts.perforce_path + '"')
file_key_re = re.compile("^depotFile")
for changelist in changelists:
files = run_marshal('p4 -G describe -s "' + changelist['change'] + '"')
for file in files:
for key_name, file_name in file.iteritems():
if file_key_re.match(key_name):
event_list.append(Event(file_name, int(changelist['time'] + '000'), changelist['user']))
create_event_xml(event_list, 'depot', opts.output_log)
def create_event_xml(events, base_log, output_log=None):
""" Write out the final XML output log file based on an input
list of events and input log files.
"""
# By default, the generated xml file will be the same name as the input log file
# but with an '.xml' extension.
log_file_path = os.path.abspath(base_log)
dest_dir = os.path.dirname(log_file_path)
log_file_base = os.path.basename(log_file_path)
xml_filename = os.path.splitext(log_file_base)[0] + '.xml'
xml_path = os.path.join(dest_dir, xml_filename)
# If the user specified an output log file, then use that.
if output_log:
xml_path = output_log
print "Generating XML from %i events..." % ( len( events ) )
# Create new empty xml file.
xml_handle = open(xml_path, 'w')
xml_handle.write('<?xml version="1.0"?>\n')
xml_handle.write('<file_events>\n')
# Make sure the events are sorted in ascending order by date, then
# write the events into the xml file.
events.sort()
for event in events:
try:
xml_handle.write('<event date="%s" filename="%s" author="%s" />\n' % \
(event.date, h(event.filename), h(event.author)))
except:
print "Error when writing this file: " + str(event)
xml_handle.write('</file_events>\n')
xml_handle.close()
if __name__ == "__main__":
""" Main entry point."""
main()
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] | 1.858954 | 8,834 |
"""Packaging settings."""
import sys
import os
from codecs import open
from subprocess import call
from setuptools import Command, find_packages, setup
from pf9 import __version__
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
# set env_vars for python intpretor that was used for install
py_env = sys.prefix
os.environ["EXPRESS_CLI_PYTHON"] = str(sys.executable)
os.environ["EXPRESS_CLI_VENV"] = str(py_env)
os.environ["EXPRESS_CLI_VENV_ACTIVATE"] = "{}/bin/activate".format(py_env)
# The above values should be written to a config file in ~/pf9/bin/
# sym links to the venv/activate and entry points should be created there
# User's PATH should be updated to include ~/pf9/bin/ with entry in ~/.bashrc or ~/.bash_profile
class RunTests(Command):
"""Run all tests."""
description = 'run tests'
user_options = []
def run(self):
"""Run all tests!"""
errno = call('py.test')
raise SystemExit(errno)
setup(
name='express-cli',
version=__version__,
description='Platform9 CLI.',
long_description=open('README.md').read(),
long_description_content_type='text/markdown',
url='https://github.com/platform9/express-cli',
author='Jeremy Brooks',
author_email='[email protected]',
license='Apache 2.0',
classifiers=[
'Intended Audience :: System Administrators',
'Intended Audience :: End Users/Desktop',
'Intended Audience :: Developers',
'Topic :: Utilities',
'License :: OSI Approved :: Apache Software License',
'Natural Language :: English',
'Operating System :: OS Independent',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3.5',
],
include_package_data=True,
zip_safe=False,
keywords='cli',
packages=find_packages(exclude=['docs', 'tests*']),
install_requires=['click==7.1.2',
'cryptography==3.2.1',
'prettytable',
'requests',
'netifaces',
'colorama',
'urllib3',
'paramiko',
'fabric',
'invoke',
'ansible==2.9.13',
'analytics-python'
],
extras_require={
'test': ['coverage', 'pytest', 'pytest-cov', 'mock'],
},
entry_points={
'console_scripts': [
'express=pf9.express:cli',
],
},
cmdclass={'test': RunTests},
)
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] | 2.262226 | 1,186 |
memo = {0:0, 1:1}
if __name__ == "__main__":
print(f"\n0: {fib(0)}")
print(f"\n1: {fib(1)}")
print(f"\n5: {fib(5)}")
print(f"\n10: {fib(10)}")
#for k,v in memo.items(): print(f"{k}: {v}")
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] | 1.669291 | 127 |
# badges.py
#
# Application responds to users in the scene and updates the user avatar with name and badge updates.
import argparse
import yaml
from arena import *
from gstable import GoogleSheetTable
DFT_CONFIG_FILENAME = './config.yaml'
ACTUSERS = {} # actual users by camera id
config = {}
data = []
# parse args and config
init_args()
# establish shared Sheets auth
gst = GoogleSheetTable()
# establish shared ARENA auth
kwargs = {}
if 'namespace' in config['arena']:
kwargs["namespace"] = config['arena']['namespace']
scene = Scene(
host=config['arena']['host'],
realm=config['arena']['realm'],
scene=config['arena']['scenename'],
on_msg_callback=scene_callback,
user_join_callback=user_join_callback,
user_left_callback=user_left_callback,
**kwargs)
# TODO: launch separate threads for each scene
scene.run_tasks()
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] | 2.880399 | 301 |
# -*- coding: utf-8 -*-
"""
legit.cli
~~~~~~~~~
This module povides the CLI interface to legit.
"""
import os
import sys
from subprocess import call
from time import sleep
import clint.resources
from clint import args
from clint.eng import join as eng_join
from clint.textui import colored, puts, columns
from .core import __version__
from .settings import settings
from .helpers import is_lin, is_osx, is_win
from .scm import *
# --------
# Dispatch
# --------
def main():
"""Primary Legit command dispatch."""
command = Command.lookup(args.get(0))
if command:
arg = args.get(0)
args.remove(arg)
command.__call__(args)
sys.exit()
elif args.contains(('-h', '--help')):
display_help()
sys.exit(1)
elif args.contains(('-v', '--version')):
display_version()
sys.exit(1)
else:
if settings.git_transparency:
# Send everything to git
git_args = list(sys.argv)
if settings.git_transparency is True:
settings.git_transparency = os.environ.get("GIT_PYTHON_GIT_EXECUTABLE", 'git')
git_args[0] = settings.git_transparency
sys.exit(call(' '.join(git_args), shell=True))
else:
show_error(colored.red('Unknown command {0}'.format(args.get(0))))
display_info()
sys.exit(1)
# -------
# Helpers
# -------
def status_log(func, message, *args, **kwargs):
"""Executes a callable with a header message."""
print message
log = func(*args, **kwargs)
if log:
out = []
for line in log.split('\n'):
if not line.startswith('#'):
out.append(line)
print black('\n'.join(out))
def switch_to(branch):
"""Runs the cmd_switch command with given branch arg."""
switch_args = args.copy
switch_args._args = [branch]
return cmd_switch(switch_args)
# --------
# Commands
# --------
def cmd_switch(args):
"""Legit Switch command."""
to_branch = args.get(0)
to_branch = fuzzy_match_branch(to_branch)
if not to_branch:
print 'Please specify a branch to switch to:'
display_available_branches()
sys.exit()
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.')
status_log(checkout_branch, 'Switching to {0}.'.format(
colored.yellow(to_branch)), to_branch)
if unstash_index():
status_log(unstash_it, 'Restoring local changes.')
def cmd_sync(args):
"""Stashes unstaged changes, Fetches remote data, Performs smart
pull+merge, Pushes local commits up, and Unstashes changes.
Defaults to current branch.
"""
if args.get(0):
# Optional branch specifier.
branch = fuzzy_match_branch(args.get(0))
if branch:
is_external = True
original_branch = repo.head.ref.name
else:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(args.get(0)))
sys.exit(1)
else:
# Sync current branch.
branch = repo.head.ref.name
is_external = False
if branch in get_branch_names(local=False):
if is_external:
switch_to(branch)
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.', sync=True)
status_log(smart_pull, 'Pulling commits from the server.')
status_log(push, 'Pushing commits to the server.', branch)
if unstash_index(sync=True):
status_log(unstash_it, 'Restoring local changes.', sync=True)
if is_external:
switch_to(original_branch)
else:
print '{0} has not been published yet.'.format(
colored.yellow(branch))
sys.exit(1)
#############################
##### CozyGit functions #####
#############################
def cmd_update(args):
"""Stashes unstaged changes, does a pull no-ff and Unstashes changes.
Defaults to current branch.
"""
# check if the branch exists and is pushed to the central repo
if args.get(0):
# Optional branch specifier.
branch = fuzzy_match_branch(args.get(0))
if branch:
is_external = True
original_branch = repo.head.ref.name
else:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(args.get(0)))
sys.exit(1)
else:
# Sync current branch.
branch = repo.head.ref.name
is_external = False
if branch in get_branch_names(local=False):
if is_external:
switch_to(branch)
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.', sync=True)
status_log(pull_noff, 'Pulling commits from the server.')
if unstash_index(sync=True):
status_log(unstash_it, 'Restoring local changes.', sync=True)
if is_external:
switch_to(original_branch)
else:
print '{0} has not been published yet.'.format(
colored.yellow(branch))
sys.exit(1)
def cmd_merge_master(args):
"""Stashes unstaged changes, merge current branch with master
and Unstashes changes.
Defaults to current branch.
"""
if args.get(0):
# Optional branch specifier.
branch = fuzzy_match_branch(args.get(0))
if branch:
is_external = True
original_branch = repo.head.ref.name
else:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(args.get(0)))
sys.exit(1)
else:
print 'please specify a branch name'
sys.exit(1)
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.', sync=True)
switch_to("master")
status_log(merge_noff , 'Merging master with the branch', branch_name=branch)
if unstash_index(sync=True):
status_log(unstash_it, 'Restoring local changes.', sync=True)
switch_to(branch)
def cmd_dev_merge(args):
"""Stashes unstaged changes, updates developement,
merge it with current branch and Unstashes changes.
Defaults to current branch.
"""
# get the branch's name
branch = repo.head.ref.name
if branch in get_branch_names(local=False):
# stash changes if needed
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.', sync=True)
# update development
status_log(update_branch,'Updating development',branch_name='development')
# switch to original branch
switch_to(branch)
# merge development in the branch
status_log(merge_noff, 'Merging development in the branch', branch_name="development")
# unstash the changes
if unstash_index(sync=True):
status_log(unstash_it, 'Restoring local changes.', sync=True)
else:
print branch + ' has not been published yet.'.format(
colored.yellow(branch))
sys.exit(1)
def cmd_merge_close(args):
"""merge current branch in dev and close it
Defaults to current branch.
"""
b = repo.head.ref.name
branch = b
if repo.is_dirty():
print 'you have unpushed changes, please commit/checkout and push them before deleting the branch'
elif b=='development':
print 'you cannot delete the branch "development" with this function'
elif b=='master':
print 'you cannont delete the branch "master"'
else:
switch_to("development")
status_log(merge_noff, 'Merging current branch in dev',branch_name=branch)
status_log(close_branch, 'Closing current branch',branch_name=branch)
##################################################
##### See at the end for the rest of CozyGit #####
##################################################
def cmd_sprout(args):
"""Creates a new branch of given name from given branch.
Defaults to current branch.
"""
off_branch = args.get(0)
new_branch = args.get(1)
if new_branch is None:
new_branch = off_branch
off_branch = repo.head.ref.name
else:
off_branch = fuzzy_match_branch(off_branch)
if not off_branch:
print 'Please specify branch to sprout:'
display_available_branches()
sys.exit()
branch_names = get_branch_names()
if off_branch not in branch_names:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(off_branch))
sys.exit(1)
if new_branch in branch_names:
print "{0} already exists. Use a unique name.".format(
colored.yellow(new_branch))
sys.exit(1)
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.')
status_log(sprout_branch, 'Branching {0} to {1}.'.format(
colored.yellow(off_branch), colored.yellow(new_branch)),
off_branch, new_branch)
def cmd_graft(args):
"""Merges an unpublished branch into the given branch, then deletes it."""
branch = fuzzy_match_branch(args.get(0))
into_branch = args.get(1)
if not branch:
print 'Please specify a branch to graft:'
display_available_branches()
sys.exit()
if not into_branch:
into_branch = repo.head.ref.name
else:
into_branch = fuzzy_match_branch(into_branch)
branch_names = get_branch_names(local=True, remote_branches=False)
remote_branch_names = get_branch_names(local=False, remote_branches=True)
if branch not in branch_names:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(branch))
sys.exit(1)
if branch in remote_branch_names:
print "{0} is published. To graft it, unpublish it first.".format(
colored.yellow(branch))
sys.exit(1)
if into_branch not in branch_names:
print "{0} doesn't exist. Use a branch that does.".format(
colored.yellow(into_branch))
sys.exit(1)
# Go to new branch.
switch_to(into_branch)
status_log(graft_branch, 'Grafting {0} into {1}.'.format(
colored.yellow(branch), colored.yellow(into_branch)), branch)
def cmd_publish(args):
"""Pushes an unpublished branch to a remote repository."""
branch = fuzzy_match_branch(args.get(0))
if not branch:
branch = repo.head.ref.name
display_available_branches()
print "Branch {0} not found, using current branch {1}".format(colored.red(args.get(0)),colored.yellow(branch))
branch_names = get_branch_names(local=False)
if branch in branch_names:
print "{0} is already published. Use a branch that isn't.".format(
colored.yellow(branch))
sys.exit(1)
status_log(publish_branch, 'Publishing {0}.'.format(
colored.yellow(branch)), branch)
def cmd_unpublish(args):
"""Removes a published branch from the remote repository."""
branch = fuzzy_match_branch(args.get(0))
if not branch:
print 'Please specify a branch to unpublish:'
display_available_branches()
sys.exit()
branch_names = get_branch_names(local=False)
if branch not in branch_names:
print "{0} isn't published. Use a branch that is.".format(
colored.yellow(branch))
sys.exit(1)
status_log(unpublish_branch, 'Unpublishing {0}.'.format(
colored.yellow(branch)), branch)
def cmd_harvest(args):
"""Syncs a branch with given branch. Defaults to current."""
from_branch = fuzzy_match_branch(args.get(0))
to_branch = fuzzy_match_branch(args.get(1))
if not from_branch:
print 'Please specify a branch to harvest commits from:'
display_available_branches()
sys.exit()
if to_branch:
original_branch = repo.head.ref.name
is_external = True
else:
is_external = False
branch_names = get_branch_names(local=True, remote_branches=False)
if from_branch not in branch_names:
print "{0} isn't an available branch. Use a branch that is.".format(
colored.yellow(from_branch))
sys.exit(1)
if is_external:
switch_to(to_branch)
if repo.is_dirty():
status_log(stash_it, 'Saving local changes.')
status_log(smart_merge, 'Grafting commits from {0}.'.format(
colored.yellow(from_branch)), from_branch, allow_rebase=False)
if is_external:
switch_to(original_branch)
if unstash_index():
status_log(unstash_it, 'Restoring local changes.')
#
def cmd_branches(args):
"""Displays available branches."""
display_available_branches()
def cmd_settings(args):
"""Opens legit settings in editor."""
path = clint.resources.user.open('config.ini').name
print 'Legit Settings:\n'
for (option, _, description) in settings.config_defaults:
print columns([colored.yellow(option), 25], [description, None])
print '\nSee {0} for more details.'.format(settings.config_url)
sleep(0.35)
if is_osx:
editor = os.environ.get('EDITOR') or os.environ.get('VISUAL') or 'open'
os.system("{0} '{1}'".format(editor, path))
elif is_lin:
editor = os.environ.get('EDITOR') or os.environ.get('VISUAL') or 'pico'
os.system("{0} '{1}'".format(editor, path))
elif is_win:
os.system("'{0}'".format(path))
else:
print "Edit '{0}' to manage Legit settings.\n".format(path)
sys.exit()
####################################################################
##### Edit this function to be able to install the new aliases #####
##### Syntax : #####
##### '\'!cozygit <cmd name> <"$@" if cmd take an arg>\'' #####
####################################################################
def cmd_install(args):
"""Installs legit git aliases."""
aliases = {
'branches': '\'!cozygit branches\'',
'graft': '\'!cozygit graft "$@"\'',
'harvest': '\'!cozygit harvest "$@"\'',
'publish': '\'!cozygit publish "$@"\'',
'unpublish': '\'!cozygit unpublish "$@"\'',
'sprout': '\'!cozygit sprout "$@"\'',
'sync': '\'!cozygit sync "$@"\'',
'switch': '\'!cozygit switch "$@"\'',
'update': '\'!cozygit update "$@"\'',
'mergemaster': '\'!cozygit mergemaster\'',
'devmerge': '\'!cozygit devmerge\'',
'newbranch': '\'!cozygit newbranch "$@"\'',
'mergeclose': '\'!cozygit mergeclose\''
}
print 'The following git aliases have been installed:\n'
for (ak, av) in aliases.items():
os.system('git config --global --replace-all alias.{0} {1}'.format(ak, av))
print columns(['', 1], [colored.yellow('git ' + ak), 14], [av, None])
sys.exit()
def cmd_help(args):
"""Display help for individual commands."""
command = args.get(0)
help(command)
# -----
# Views
# -----
def display_available_branches():
"""Displays available branches."""
branches = get_branches()
branch_col = len(max([b.name for b in branches], key=len)) + 1
for branch in branches:
try:
branch_is_selected = (branch.name == repo.head.ref.name)
except TypeError:
branch_is_selected = False
marker = '*' if branch_is_selected else ' '
color = colored.green if branch_is_selected else colored.yellow
pub = '(published)' if branch.is_published else '(unpublished)'
print columns(
[colored.red(marker), 2],
[color(branch.name), branch_col],
[black(pub), 14]
)
def display_info():
"""Displays Legit informatics."""
puts('{0}. {1}\n'.format(
colored.red('legit'),
black(u'A Kenneth Reitz Project™')
))
puts('Usage: {0}'.format(colored.blue('legit <command>')))
puts('Commands:\n')
for command in Command.all_commands():
usage = command.usage or command.name
help = command.help or ''
puts('{0:40} {1}'.format(
colored.green(usage),
first_sentence(help)))
def display_help():
"""Displays Legit help."""
display_info()
def display_version():
"""Displays Legit version/release."""
puts('{0} v{1}'.format(
colored.yellow('legit'),
__version__
))
settings.abort_handler = handle_abort
def_cmd(
name='branches',
fn=cmd_branches,
usage='branches',
help='Get a nice pretty list of branches.')
def_cmd(
name='graft',
short=['gr'],
fn=cmd_graft,
usage='graft <branch> <into-branch>',
help=('Merges specified branch into the second branch, and removes it. '
'You can only graft unpublished branches.'))
def_cmd(
name='harvest',
short=['ha', 'hv', 'har'],
usage='harvest [<branch>] <into-branch>',
help=('Auto-Merge/Rebase of specified branch changes into the second '
'branch.'),
fn=cmd_harvest)
def_cmd(
name='help',
short=['h'],
fn=cmd_help,
usage='help <command>',
help='Display help for legit command.')
def_cmd(
name='install',
fn=cmd_install,
usage='install',
help='Installs legit git aliases.')
def_cmd(
name='publish',
short=['pub'],
fn=cmd_publish,
usage='publish <branch>',
help='Publishes specified branch to the remote.')
def_cmd(
name='settings',
fn=cmd_settings,
usage='settings',
help='Opens legit settings in a text editor.')
def_cmd(
name='sprout',
short=['sp'],
fn=cmd_sprout,
usage='sprout [<branch>] <new-branch>',
help=('Creates a new branch off of the specified branch. Defaults to '
'current branch. Switches to it immediately.'))
def_cmd(
name='switch',
short=['sw'],
fn=cmd_switch,
usage='switch <branch>',
help=('Switches to specified branch. Automatically stashes and unstashes '
'any changes.'))
def_cmd(
name='sync',
short=['sy'],
fn=cmd_sync,
usage='sync <branch>',
help=('Syncronizes the given branch. Defaults to current branch. Stash, '
'Fetch, Auto-Merge/Rebase, Push, and Unstash.'))
def_cmd(
name='unpublish',
short=['unp'],
fn=cmd_unpublish,
usage='unpublish <branch>',
help='Removes specified branch from the remote.')
###########################################
##### Definition of CozyGit's command #####
###########################################
def_cmd(
name='update',
short=['updt'],
fn=cmd_update,
usage='update <branch>',
help='Pull the changes of the branch from the server. By default it executes on current branch')
def_cmd(
name='mergemaster',
short=['mmstr'],
fn=cmd_merge_master,
usage='mergemaster',
help='Merge current branch in master')
def_cmd(
name='devmerge',
short=['dmrg'],
fn=cmd_dev_merge,
usage='devmerge',
help='Update dev and merge it in current branch')
def_cmd(
name='mergeclose',
short=['mcls'],
fn=cmd_merge_close,
usage='mergeclose',
help='Merge current branch in dev and close it')
def_cmd(
name='newbranch',
short=['nbrch'],
fn=cmd_new_branch,
usage='newbranch <branch>',
help='Create a new branch, push it to the server and link both branches')
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] | 2.37555 | 8,180 |
#!/usr/bin/env python
import sys
import netsnmp
import re
import memcache
import datetime
import MySQLdb
import time
if __name__ == '__main__':
mc = memcache.Client(['10.30.22.49:11216'], debug=0)
timestamp = int(time.time())
# year = datetime.datetime.now().strftime("%y")
# month = datetime.datetime.now().strftime("%m")
# day = datetime.datetime.now().strftime("%d")
# hour = datetime.datetime.now().strftime("%H")
# minute = datetime.datetime.now().strftime("%M")
serverlist = open("server.lst")
for line in serverlist.readlines():
community_string = line.strip().split(" ")[-1]
ip = line.strip().split(" ")[0]
getsnmpinfo(ip, community_string)
serverlist.close()
sys.exit(0)
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] | 2.498339 | 301 |
import numpy as np
import numpy.testing as npt
import test_utils as tu
| [
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] | 3.272727 | 22 |
#!/usr/bin/env python
"""Non-Pedantic Time
=================
.. moduleauthor:: Thomas Grenfell Smith <[email protected]>
Python's :mod:`datetime` module has many uses, but it has a difficulty: you
can't do any arithmetic with :class:`datetime.time`. Only with
:class:`datetime.datetime`. Now, there are good reasons for this: "What time
will it be, 24 hours from now" has a lot of corner cases, including daylight
savings time, leap seconds, historical timezone changes, and so on. But
sometimes you really *do* need the simple case. Sometimes the perfect is the
enemy of the good. And that's why you have this module. This module will allow
you to cocoon yourself in the comforting illusion that, in 24 hours, it will be
the same time as it is right now.
And what freedom this illusion gives you! You can add a
:class:`datetime.timedelta` object to an :mod:`nptime` object, and it works! It
will cycle around 24 hours, like modular arithmetic. You can ask "what time
comes 1 day and 36 minutes after 12:24 pm?" and it will let you know: 1:00 pm.
How lovely!
>>> from nptime import nptime
>>> from datetime import timedelta, date, datetime
>>> afternoon = nptime(12, 24) + timedelta(days=1, minutes=36)
>>> afternoon
nptime(13, 0)
>>> str(afternoon)
'13:00:00'
Maybe we're talking about the afternoon of Guido van Rossum's birthday. Lucky,
we can combine ``nptime`` objects with ``date`` objects:
>>> datetime.combine(date(1956, 1, 31), afternoon)
datetime.datetime(1956, 1, 31, 13, 0, 0)
You can also ask "How long is it between 9:00 AM and 5:00 PM? It sure
feels like a million years!"
>>> workday = nptime(hour=17) - nptime(hour=9)
>>> workday
datetime.timedelta(0, 28800)
>>> print workday
8:00:00
Nope, only 8 hours, how strange. Anyway, please use this module. It will
be convenient. But don't use it when talking about concrete time, time in
a particular place, or anything like that. In fact, it doesn't even notice
:class:`datetime.tzinfo` objects right now. Good luck.
.. note::
You can find the newest version at https://github.com/tgs/nptime . You can
find online documentation at http://tgs.github.com/nptime/ . The package
is available for download from PyPi: `easy_install nptime`
"""
from datetime import *
class nptime(time):
"""nptime - a non-pedantic time object
Inherits from :class:`datetime.time`. You can't do arithmetic with that
class, but with ``nptime`` you can:
* Add a :class:`datetime.timedelta` to an :class:`nptime` (commutative),
resulting in another ``nptime``
* Subtract a ``timedelta`` from an ``nptime``, resulting in a
``timedelta``
* Subtract an ``nptime`` from another ``nptime``, resulting in a
``timedelta``
You can use the class methods :func:`from_timedelta` and :func:`from_time`
to construct an ``nptime`` from those ``datetime`` classes. You can use the
:func:`to_timedelta` instance method to construct a ``timedelta`` from an
``nptime``.
I can't figure out a reason you'd want to add two times together without
using ``timedelta`` objects, but if someone requests that, I'm happy to
include it.
``nptime`` is `naive` about time zones. I think this is the only way that
makes sense, since days are only 24 hours long in an abstract sense. But
if you want to see a different system, pull requests are welcome..."""
_std_date = date(year=1000, month=1, day=1)
@classmethod
def from_time(cls, other):
"""Construct an :class:`nptime` object from a :class:`datetime.time`
.. note::
This *ignores* the :class:`datetime.tzinfo` that may be part
of the ``time`` object.
"""
return cls(other.hour, other.minute, other.second, other.microsecond)
@classmethod
def from_timedelta(cls, other):
"""Construct an :class:`nptime` object from a :class:`datetime.timedelta`.
The ``timedelta`` is taken to be the amount of time since midnight."""
return cls() + other
def to_timedelta(self):
"""Construct a :class:`timedelta` object from an :class:`nptime`. The
timedelta gives the number of seconds (and microseconds) since
midnight."""
return timedelta(hours=self.hour, minutes=self.minute,
seconds=self.second, microseconds=self.microsecond)
def __add__(self, other):
"""Add nptime and timedelta, returning an nptime"""
self_dt = datetime.combine(self._std_date, self)
sum = self_dt + other
return nptime.from_time(sum.time())
def __radd__(self, other):
"""Add timedelta and nptime"""
return self + other
def __sub__(self, other):
"""Subtract timedelta or nptime from nptime, returning a timedelta"""
if isinstance(other, self.__class__):
diff = self.to_timedelta() - other.to_timedelta()
else:
diff = self.to_timedelta() - other
return diff
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198
] | 2.802241 | 1,785 |
#!/usr/bin/env python
# coding=utf-8
'''
Author: BATU1579
Date: 2021-08-11 15:20:04
LastEditors: BATU1579
LastEditTime: 2021-08-16 22:33:54
Description: file content
'''
import logging
import library.const as g
from time import sleep
# 加载不同浏览器的驱动
if g.BROWSER == "edge":
# edge驱动设置
from msedge.selenium_tools import Edge as Driver
from library.webdriver_manager.microsoft import EdgeChromiumDriverManager as Manager
from msedge.selenium_tools import EdgeOptions
options = EdgeOptions()
options.use_chromium = True
options.add_experimental_option("excludeSwitches", ["enable-logging"]) # 不显示日志
elif g.BROWSER == "chrome":
# chrome驱动设置
from selenium.webdriver import Chrome as Driver
from library.webdriver_manager.chrome import ChromeDriverManager as Manager
from selenium.webdriver import ChromeOptions
options = ChromeOptions()
options.add_experimental_option("excludeSwitches", ["enable-logging"]) # 不显示日志
elif g.BROWSER == "firefox":
# firefox驱动设置
from selenium.webdriver import Firefox as Driver
from library.webdriver_manager.firefox import GeckoDriverManager as Manager
from selenium.webdriver import FirefoxOptions
options = FirefoxOptions()
set_github_token()
else:
g.LOG.error("暂不支持 %s 浏览器" % g.BROWSER)
exit()
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8,
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220,
220,
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8420,
3419,
628,
628
] | 2.485822 | 529 |
import os
import sys
import glob
import re
from kivy.lang import Builder
from kivy.event import EventDispatcher
def resource_path():
"""
PyInstaller対策。
"""
if hasattr(sys, '_MEIPASS'):
return os.path.join(sys._MEIPASS)
return os.path.join(os.path.dirname(os.path.abspath(__file__)))
def load_style(dir_path):
"""
指定したディレクトリに存在するkvファイルを読み込む
"""
style_files = glob.glob(dir_path)
for style in style_files:
Builder.load_file(style)
def register_event(handler):
"""
'on_'で始まるメソッドを探してイベントとして登録する
__init__メソッドに付けるデコレータ
"""
excludes = [
'on_opacity',
'on_touch_down',
'on_touch_move',
'on_touch_up'
]
return wrapper
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] | 1.785219 | 433 |
import os
import sys
import boto
from nose.tools import assert_in, assert_not_in, raises
from moto import mock_s3
from radula import RadulaProxy, _parse_args, Radula, RadulaError
TEST_BUCKET = "tests"
here = os.path.dirname(os.path.realpath(__file__))
TEST_FILE = os.path.join(here, "testdata.txt")
REMOTE_FILE = os.path.join(TEST_BUCKET, os.path.basename(TEST_FILE))
PRIMARY_USER = 'test-user'
ALT_USER = 'alt-user'
aws_url = "http://acs.amazonaws.com/groups/global"
aws_auth = aws_url + "/AuthenticatedUsers"
aws_all = aws_url + "/AllUsers"
@mock_s3
@mock_s3
@mock_s3
@raises(RadulaError)
@mock_s3
@mock_s3
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# coding=utf-8
# Copyright 2021 The Trax Authors.
#
# 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.
# Lint as: python3
"""Policy network training tasks.
Policy tasks encapsulate the training process of a policy network into a simple,
replaceable component. To implement a policy-based Agent using policy tasks:
1. Subclass the base Agent class.
2. In __init__(), initialize the policy training and evaluation tasks, and
a trax.supervised.training.Loop instance using them.
3. In train_epoch(), call the Loop to train the network.
4. In policy(), call network_policy() defined in this module.
"""
import numpy as np
from trax import layers as tl
from trax.fastmath import numpy as jnp
from trax.rl import distributions
from trax.supervised import training
class PolicyTrainTask(training.TrainTask):
"""Task for policy training.
Trains the policy based on action advantages.
"""
def __init__(
self,
trajectory_batch_stream,
optimizer,
lr_schedule,
policy_distribution,
advantage_estimator,
value_fn,
weight_fn=(lambda x: x),
advantage_normalization=True,
advantage_normalization_epsilon=1e-5,
head_selector=(),
):
"""Initializes PolicyTrainTask.
Args:
trajectory_batch_stream: Generator of trax.rl.task.TimeStepBatch.
optimizer: Optimizer for network training.
lr_schedule: Learning rate schedule for network training.
policy_distribution: Distribution over actions.
advantage_estimator: Function
(rewards, returns, values, dones) -> advantages, created by one of the
functions from trax.rl.advantages.
value_fn: Function TimeStepBatch -> array (batch_size, seq_len)
calculating the baseline for advantage calculation. Can be used to
implement actor-critic algorithms, by substituting a call to the value
network as value_fn.
weight_fn: Function float -> float to apply to advantages. Examples:
- A2C: weight_fn = id
- AWR: weight_fn = exp
- behavioral cloning: weight_fn(_) = 1
advantage_normalization: Whether to normalize advantages.
advantage_normalization_epsilon: Epsilon to use then normalizing
advantages.
head_selector: Layer to apply to the network output to select the value
head. Only needed in multitask training. By default, use a no-op layer,
signified by an empty sequence of layers, ().
"""
self.trajectory_batch_stream = trajectory_batch_stream
self._value_fn = value_fn
self._advantage_estimator = advantage_estimator
self._weight_fn = weight_fn
self._advantage_normalization = advantage_normalization
self._advantage_normalization_epsilon = advantage_normalization_epsilon
self.policy_distribution = policy_distribution
labeled_data = map(self.policy_batch, trajectory_batch_stream)
sample_batch = self.policy_batch(
next(trajectory_batch_stream), shape_only=True
)
loss_layer = distributions.LogLoss(distribution=policy_distribution)
loss_layer = tl.Serial(head_selector, loss_layer)
super().__init__(
labeled_data, loss_layer, optimizer,
sample_batch=sample_batch,
lr_schedule=lr_schedule,
loss_name='policy_loss',
)
def calculate_weights(self, advantages):
"""Calculates advantage-based weights for log loss in policy training."""
if self._advantage_normalization:
# Normalize advantages.
advantages -= jnp.mean(advantages)
advantage_std = jnp.std(advantages)
advantages /= advantage_std + self._advantage_normalization_epsilon
weights = self._weight_fn(advantages)
assert weights.shape == advantages.shape
return weights
def policy_batch(self, trajectory_batch, shape_only=False):
"""Computes a policy training batch based on a trajectory batch.
Args:
trajectory_batch: trax.rl.task.TimeStepBatch with a batch of trajectory
slices. Elements should have shape (batch_size, seq_len, ...).
shape_only: Whether to return dummy zero arrays of correct shape. Useful
for initializing models.
Returns:
Triple (observations, actions, weights), where weights are the
advantage-based weights for the policy loss. Shapes:
- observations: (batch_size, seq_len) + observation_shape
- actions: (batch_size, seq_len) + action_shape
- weights: (batch_size, seq_len)
"""
advantages = self.calculate_advantages(
trajectory_batch, shape_only=shape_only
)
(observations, actions, mask) = self.trim_batch(
trajectory_batch, advantages
)
weights = self.calculate_weights(advantages) * mask / jnp.sum(mask)
return (observations, actions, weights)
class PolicyEvalTask(training.EvalTask):
"""Task for policy evaluation."""
def __init__(self, train_task, n_eval_batches=1, head_selector=()):
"""Initializes PolicyEvalTask.
Args:
train_task: PolicyTrainTask used to train the policy network.
n_eval_batches: Number of batches per evaluation.
head_selector: Layer to apply to the network output to select the value
head. Only needed in multitask training.
"""
self._train_task = train_task
self._policy_dist = train_task.policy_distribution
labeled_data = map(self._eval_batch, train_task.trajectory_batch_stream)
sample_batch = self._eval_batch(
next(train_task.trajectory_batch_stream), shape_only=True
)
# TODO(pkozakowski): Implement more metrics.
metrics = {
'policy_entropy': self.entropy_metric,
}
metrics.update(self.advantage_metrics)
metrics.update(self.weight_metrics)
metrics = {
name: tl.Serial(head_selector, metric)
for (name, metric) in metrics.items()
}
(metric_names, metric_layers) = zip(*metrics.items())
# Select the appropriate head for evaluation.
super().__init__(
labeled_data, metric_layers,
sample_batch=sample_batch,
metric_names=metric_names,
n_eval_batches=n_eval_batches,
)
@property
@property
@property
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] | 2.895197 | 2,290 |
import datetime as dt
import BitcoinNewsProcessor as bitcoin_news
import pandas as pd
from matplotlib import pyplot as plt
from sklearn import linear_model
from sklearn.metrics import mean_absolute_error, explained_variance_score
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import Imputer
# read data
path = "/Users/shankarganesh/files/bitcoin/bitcoin_dataset.csv"
data = pd.read_csv(path, parse_dates=["Date"])
# get the news dataframe - shape : sentiment_date, sentiment
news_df = bitcoin_news.get_sentiment_by_date()
# merge with left join - left on index, right on sentiment_date
data = data.reset_index()
merge_df = pd.DataFrame(pd.merge(data, news_df, how='left', left_on='Date', right_on='sentiment_date'))
# sentiment not available for all dates. Replacing missing sentiments with neutral 0
merge_df['sentiment'].fillna(0, inplace=True)
# init imputer for handling missing values
imputer = Imputer()
# extract date out of merge, since date cannot be imputed
date_df = pd.DataFrame(pd.to_datetime(merge_df['Date']))
merge_df = merge_df.drop(['Date', 'sentiment_date'], axis=1)
# get all columns, so that col headers can be added after imputing
cols = merge_df.columns
# fill missing values
merge_df = pd.DataFrame(imputer.fit_transform(merge_df), columns=cols)
# add date back to the mix
merge_df = merge_df.assign(Date=date_df['Date'].map(dt.datetime.toordinal))
# prediction target
y = pd.DataFrame(merge_df.btc_market_price)
# predictors - removed sentiment date since it's already present in the index of original data
X = merge_df[merge_df.columns.difference(['btc_market_price', 'sentiment_date'])]
# split into train and test data
train_X, val_X, train_y, val_y = train_test_split(X, y, random_state=0)
# print evaluation metrics
evaluate_performance(train_X, val_X, train_y, val_y)
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] | 3.006504 | 615 |
import tensorflow as tf
import numpy as np
import os
import csv
from tensorflow.python.framework import ops
import warnings
from sklearn.model_selection import train_test_split
import loadCleanup
warnings.filterwarnings("ignore")
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
ops.reset_default_graph()
tf.flags.DEFINE_boolean("allow_soft_placement", True, "Allow device soft device placement")
tf.flags.DEFINE_boolean("log_device_placement", False, "Log placement of ops on devices")
tf.flags.DEFINE_string("checkpointDir", "layer3min16reg1", "Checkpoint directory")
FLAGS = tf.flags.FLAGS
train, unknown = loadCleanup.getTrainTestDFs()
Y = loadCleanup.getValueColumn()
Y = np.array(Y.values).reshape((-1, 1))
trainX, testX, trainY, testY = train_test_split(train, Y, test_size=0.3, random_state=43)
out_dir = os.path.abspath(os.path.join(os.path.curdir, "runs", FLAGS.checkpointDir, "checkpoints"))
checkpoint_file = tf.train.latest_checkpoint(out_dir)
graph = tf.Graph()
with graph.as_default():
session_conf = tf.ConfigProto(
allow_soft_placement=FLAGS.allow_soft_placement,
log_device_placement=FLAGS.log_device_placement)
sess = tf.Session(config=session_conf)
with sess.as_default():
# Load the saved meta graph and restore variables
saver = tf.train.import_meta_graph("{}.meta".format(checkpoint_file))
saver.restore(sess, checkpoint_file)
w1 = graph.get_operation_by_name("W1").outputs[0]
w2 = graph.get_operation_by_name("W2").outputs[0]
wOut = graph.get_operation_by_name("WOut").outputs[0]
b1 = graph.get_operation_by_name("b1").outputs[0]
b2 = graph.get_operation_by_name("b2").outputs[0]
bOut = graph.get_operation_by_name("bOut").outputs[0]
l1 = tf.nn.relu(tf.nn.xw_plus_b(tf.convert_to_tensor(unknown, dtype=tf.float32), w1, b1), name="l1")
l2 = tf.nn.relu(tf.nn.xw_plus_b(l1, w2, b2), name="l2")
pred = tf.nn.xw_plus_b(l2, wOut, bOut, name="prediction")
predictions = sess.run(pred)
# predictions = np.column_stack((sess.run(pred)))
out_path = os.path.join(os.path.curdir, "submit.csv")
print("Saving evaluation to {0}".format(out_path))
with open(out_path, 'w') as f:
csv.writer(f).writerows(predictions)
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13,
16002,
7,
69,
737,
16002,
1666,
7,
28764,
9278,
8,
198
] | 2.386528 | 965 |
from datetime import timedelta as dt
import numpy as np
import matplotlib.pyplot as plt
from irise import convert, grid
from irise.diagnostics import rossby_waves
from myscripts.models.um import case_studies
def main(cubes, xbins, ybins, xlabel, ylabel, **kwargs):
"""
"""
# Load variables
thetapv2 = convert.calc('air_potential_temperature', cubes,
levels=('ertel_potential_vorticity', [2]))[0]
z_bl = convert.calc('atmosphere_boundary_layer_thickness', cubes)
# Create a ridge trough mask
theta_b = rossby_waves.nae_map(grid.get_datetime(thetapv2)[0])
dtheta = thetapv2.data - theta_b.data
# Calculate the pdf for ridges/troughs vs bl height
colourplot(z_bl.data.flatten(), dtheta.flatten(), xbins, ybins, **kwargs)
# Calculate the individual pdf for bl height
lineplot(z_bl.data, xbins, xlabel)
# Calculate the individual pdf for ridges/troughs
lineplot(dtheta, ybins, ylabel)
plt.show()
if __name__ == '__main__':
forecast = case_studies.iop5()
cubes = forecast.set_lead_time(dt(hours=36))
xbins = np.linspace(0, 4000, 9)
xlabel = 'Boundary Layer Height (m)'
ybins = np.linspace(-50, 50, 21)
ylabel = r'$\theta - \theta_b$ (K)'
main(cubes, xbins, ybins, xlabel, ylabel, vmin=0, vmax=10, cmap='plasma')
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13,
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11,
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11,
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8,
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220,
331,
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374,
6,
3,
59,
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8326,
532,
3467,
1169,
8326,
62,
65,
3,
357,
42,
33047,
198,
220,
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220,
1388,
7,
66,
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65,
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11,
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11,
331,
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28,
15,
11,
410,
9806,
28,
940,
11,
269,
8899,
11639,
489,
11797,
11537,
198
] | 2.371886 | 562 |
from itertools import *
X = []
X.extend(list(map(int,input().split())))
X.extend(list(map(int,input().split())))
X.extend(list(map(int,input().split())))
Ans = 81
for P in permutations(range(1,10)):
if sum(P[0:3]) == 15 and sum(P[3:6]) == 15 and sum(P[0::3]) == 15 and sum(P[1::3]) == 15 and P[0] + P[4] + P[8] == 15 and (P[2] + P[4] + P[6] == 15):
Ans = min(Ans, sum(abs(P[i] - X[i]) for i in range(0,9)))
print(Ans)
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7,
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58,
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58,
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287,
2837,
7,
15,
11,
24,
22305,
198,
4798,
7,
2025,
82,
8,
198
] | 2.057143 | 210 |
##############################################################################
# Copyright (c) 2013-2017, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
#
# This file is part of Spack.
# Created by Todd Gamblin, [email protected], All rights reserved.
# LLNL-CODE-647188
#
# For details, see https://github.com/spack/spack
# Please also see the NOTICE and LICENSE files for our notice and the LGPL.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License (as
# published by the Free Software Foundation) version 2.1, February 1999.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
# conditions of the GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
##############################################################################
import sys
from spack import *
from distutils.dir_util import copy_tree
class Git(AutotoolsPackage):
"""Git is a free and open source distributed version control
system designed to handle everything from small to very large
projects with speed and efficiency.
"""
homepage = "http://git-scm.com"
url = "https://github.com/git/git/archive/v2.12.0.tar.gz"
# In order to add new versions here, add a new list entry with:
# * version: {version}
# * md5: the md5sum of the v{version}.tar.gz
# * md5_manpages: the md5sum of the corresponding manpage from
# https://www.kernel.org/pub/software/scm/git/git-manpages-{version}.tar.xz
releases = [
{
'version': '2.14.1',
'md5': 'e965a37b3d277f2e7e78f5b04de28e2a',
'md5_manpages': 'da2e75ea3972b9e93fb47023e3bf1401',
},
{
'version': '2.13.0',
'md5': 'd0f14da0ef1d22f1ce7f7876fadcb39f',
'md5_manpages': 'fda8d6d5314eb5a47e315405830f9970',
},
{
'version': '2.12.2',
'md5': 'f1a50c09ce8b5dd197f3c6c6d5ea8e75',
'md5_manpages': '9358777e9a67e57427b03884c82311bd',
},
{
'version': '2.12.1',
'md5': 'a05c614c80ecd41e50699f1562e1130c',
'md5_manpages': '8dfba0c9f51c6c23fb135d136c061c78',
},
{
'version': '2.12.0',
'md5': '11a440ce0ed02098adf554c797facfd3',
'md5_manpages': '4d11e05068231e37d7e42935e9cc43a1',
},
{
'version': '2.11.1',
'md5': '2cf960f19e56f27248816809ae896794',
'md5_manpages': 'ade1e458a34a89d03dda9a6de85976bd',
},
{
'version': '2.11.0',
'md5': 'c63fb83b86431af96f8e9722ebb3ca01',
'md5_manpages': '72718851626e5b2267877cc2194a1ac9',
},
{
'version': '2.9.3',
'md5': 'b0edfc0f3cb046aec7ed68a4b7282a75',
'md5_manpages': '337165a3b2bbe4814c73075cb6854ca2',
},
{
'version': '2.9.2',
'md5': '3ff8a9b30fd5c99a02e6d6585ab543fc',
'md5_manpages': 'c4f415b4fc94cf75a1deb651ba769594',
},
{
'version': '2.9.1',
'md5': 'a5d806743a992300b45f734d1667ddd2',
'md5_manpages': '2aa797ff70c704a563c910e04c0f620a',
},
{
'version': '2.9.0',
'md5': 'bf33a13c2adc05bc9d654c415332bc65',
'md5_manpages': 'c840c968062251b768ba9852fd29054c',
},
{
'version': '2.8.4',
'md5': '86afb10254c3803894c9863fb5896bb6',
'md5_manpages': '8340e772d60ccd04a5da88fa9c976dad',
},
{
'version': '2.8.3',
'md5': '0e19f31f96f9364fd247b8dc737dacfd',
'md5_manpages': '553827e1b6c422ecc485499c1a1ae28d',
},
{
'version': '2.8.2',
'md5': '3d55550880af98f6e35c7f1d7c5aecfe',
'md5_manpages': '33330463af27eb1238cbc2b4ca100b3a',
},
{
'version': '2.8.1',
'md5': '1308448d95afa41a4135903f22262fc8',
'md5_manpages': '87bc202c6f6ae32c1c46c2dda3134ed1',
},
{
'version': '2.8.0',
'md5': 'eca687e46e9750121638f258cff8317b',
'md5_manpages': 'd67a7db0f363e8c3b2960cd84ad0373f',
},
{
'version': '2.7.3',
'md5': 'fa1c008b56618c355a32ba4a678305f6',
'md5_manpages': '97a525cca7fe38ff6bd7aaa4f0438896',
},
{
'version': '2.7.1',
'md5': 'bf0706b433a8dedd27a63a72f9a66060',
'md5_manpages': '19881ca231f73dec91fb456d74943950',
},
]
for release in releases:
version(release['version'], release['md5'])
resource(
name='git-manpages',
url="https://www.kernel.org/pub/software/scm/git/git-manpages-{0}.tar.xz".format(
release['version']),
md5=release['md5_manpages'],
placement='git-manpages',
when='@{0}'.format(release['version']))
depends_on('curl')
depends_on('expat')
depends_on('gettext')
depends_on('libiconv')
depends_on('openssl')
depends_on('pcre', when='@:2.13')
depends_on('pcre+jit', when='@2.14:')
depends_on('perl')
depends_on('zlib')
depends_on('autoconf', type='build')
depends_on('automake', type='build')
depends_on('libtool', type='build')
depends_on('m4', type='build')
@run_after('configure')
@run_after('install')
@run_after('install')
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] | 1.926094 | 3,085 |
import fasttext
import os
| [
11748,
3049,
5239,
198,
11748,
28686,
198
] | 3.714286 | 7 |
import logging
from discord import RawReactionActionEvent as ReactionEvent
from discord.ext import commands
from discord.utils import get
from cationbot.core.bot import Bot
from cationbot.core.env import env
class AutoRole(commands.Cog):
"""Add/Remove the tech/misc roles."""
@commands.Cog.listener()
async def on_raw_reaction_add(self, event: ReactionEvent):
"""Handle the event to add a role to member."""
await self._toggle(event)
@commands.Cog.listener()
async def on_raw_reaction_remove(self, event: ReactionEvent):
"""Handle the event to remove a role from member."""
await self._toggle(event)
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220,
220,
220,
30351,
825,
319,
62,
1831,
62,
260,
2673,
62,
28956,
7,
944,
11,
1785,
25,
39912,
9237,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37508,
262,
1785,
284,
4781,
257,
2597,
422,
2888,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
25507,
2116,
13557,
44256,
7,
15596,
8,
628
] | 2.968468 | 222 |
#!/usr/bin/env python3
import os
import gzip
import sys
filename_vcf = sys.argv[1]
gnomAD_list = dict()
dirname_gnomAD = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'..', 'data')
for tmp_filename in os.listdir(dirname_gnomAD):
if not tmp_filename.endswith('vcf.gz'):
continue
if tmp_filename.find('gnomad') < 0:
continue
filename_gnomAD = os.path.join(dirname_gnomAD, tmp_filename)
f_gnomAD = gzip.open(filename_gnomAD, 'rt')
sys.stderr.write('Read %s\n' % filename_gnomAD)
for line in f_gnomAD:
tokens = line.strip().split("\t")
for tmp_alt in tokens[4].split(','):
var_id = '%s:%s:%s-%s' % (tokens[0], tokens[1], tokens[3], tmp_alt)
var_name = tokens[2]
gnomAD_list[var_id] = var_name
f_gnomAD.close()
f_vcf = open(filename_vcf, 'r')
if filename_vcf.endswith('.gz'):
f_vcf = gzip.open(filename_vcf, 'rt')
count_total = 0
count_filtered = 0
filename_out = filename_vcf.replace('.vcf', '+NoGnomAD.vcf')
if filename_vcf.endswith('.gz'):
filename_out = filename_vcf.replace('.vcf.gz', '+NoGnomAD.vcf')
f_out = open(filename_out, 'w')
for line in f_vcf:
if line.startswith('#'):
f_out.write("%s\n" % line.strip())
continue
tokens = line.strip().split("\t")
tmp_ref = tokens[3]
tmp_alt = tokens[4]
tmp_var_id = '%s:%s:%s-%s' % (tokens[0], tokens[1], tokens[3], tokens[4])
count_total += 1
if tokens[0].startswith('Mm'):
continue
if tmp_var_id not in gnomAD_list:
count_filtered += 1
f_out.write("%s\n" % line.strip())
f_out.close()
sys.stderr.write('Total Vars: %d\n' % count_total)
sys.stderr.write('Filtered Vars: %d\n' % count_filtered)
| [
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220,
220,
220,
220,
220,
954,
62,
10379,
4400,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
277,
62,
448,
13,
13564,
7203,
4,
82,
59,
77,
1,
4064,
1627,
13,
36311,
28955,
198,
69,
62,
448,
13,
19836,
3419,
198,
198,
17597,
13,
301,
1082,
81,
13,
13564,
10786,
14957,
569,
945,
25,
4064,
67,
59,
77,
6,
4064,
954,
62,
23350,
8,
198,
17597,
13,
301,
1082,
81,
13,
13564,
10786,
11928,
4400,
569,
945,
25,
4064,
67,
59,
77,
6,
4064,
954,
62,
10379,
4400,
8,
198
] | 2.046296 | 864 |
with open("day04.txt") as f:
data = [line for line in f]
identity = lambda s: s
anagram = lambda s: "".join(sorted(s))
print("2017 day 4 part 1: %d" % count_good_passwords(data, identity))
print("2017 day 4 part 2: %d" % count_good_passwords(data, anagram))
| [
198,
4480,
1280,
7203,
820,
3023,
13,
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355,
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25,
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62,
11274,
62,
6603,
10879,
7,
7890,
11,
281,
6713,
4008,
198
] | 2.536364 | 110 |
import os
from flask import Flask, got_request_exception
from flask_jwt_extended.exceptions import JWTExtendedException
from jwt.exceptions import PyJWTError
from werkzeug.exceptions import HTTPException
from sqlalchemy.exc import OperationalError
from .apis import urls
from .config.celery_config import CeleryConfig
from .config.default_config import DefaultConfig
from .exceptions.service_exception import ServiceException
from .exceptions.system_exception import SystemException
from .extensions import (
cache, celery, cors, db, jwt_manager, migrate, # noqa
redis_store, swagger,
)
from .logger import log, init as log_init
_default_instance_path = '%(instance_path)s/instance' % \
{'instance_path': os.path.dirname(os.path.realpath(__file__))}
| [
11748,
28686,
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198,
6738,
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6,
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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,
1391,
6,
39098,
62,
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10354,
28686,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
5305,
6978,
7,
834,
7753,
834,
4008,
92,
628,
628,
628,
628
] | 3.019011 | 263 |
from setuptools import setup
setup(
name='k8s-deploy-external-dns',
version='1.0.0',
packages=['provider'],
url='',
license='',
author='Filippo Ferrazini',
author_email='[email protected]',
description=''
)
| [
6738,
900,
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3256,
198,
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43085,
11639,
3256,
198,
197,
9800,
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5362,
31,
14816,
13,
785,
3256,
198,
197,
11213,
28,
7061,
198,
8,
198
] | 2.456522 | 92 |
import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
from ...bbox.iou_calculators.iou2d_calculator import bbox_overlaps
@BBOX_ASSIGNERS.register_module()
class ATSSCostAssignerCenterAllTopk(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
Each proposals will be assigned with `0` or a positive integer
indicating the ground truth index.
- 0: negative sample, no assigned gt
- positive integer: positive sample, index (1-based) of assigned gt
Args:
topk (float): number of bbox selected in each level
"""
# https://github.com/sfzhang15/ATSS/blob/master/atss_core/modeling/rpn/atss/loss.py
def assign(self,
bboxes,
num_level_bboxes,
cls_scores,
bbox_preds, # NOTE prediction instead of pre-defined
bbox_coder, # NOTE bbox_coder
gt_bboxes,
gt_bboxes_ignore=None,
gt_labels=None):
"""Assign gt to bboxes.
The assignment is done in following steps
1. compute iou between all bbox (bbox of all pyramid levels) and gt
2. compute center distance between all bbox and gt
3. on each pyramid level, for each gt, select k bbox whose center
are closest to the gt center, so we total select k*l bbox as
candidates for each gt
4. get corresponding iou for the these candidates, and compute the
mean and std, set mean + std as the iou threshold
5. select these candidates whose iou are greater than or equal to
the threshold as postive
6. limit the positive sample's center in gt
Args:
bboxes (Tensor): Bounding boxes to be assigned, shape(n, 4).
num_level_bboxes (List): num of bboxes in each level
gt_bboxes (Tensor): Groundtruth boxes, shape (k, 4).
gt_bboxes_ignore (Tensor, optional): Ground truth bboxes that are
labelled as `ignored`, e.g., crowd boxes in COCO.
gt_labels (Tensor, optional): Label of gt_bboxes, shape (k, ).
Returns:
:obj:`AssignResult`: The assign result.
"""
INF = 100000000
bboxes = bboxes[:, :4]
bbox_preds = bbox_preds.detach()
cls_scores = cls_scores.detach()
num_gt, num_bboxes, num_bbox_preds = gt_bboxes.size(0), bboxes.size(0), bbox_preds.size(0)
assert num_bboxes == num_bbox_preds
# assign 0 by default
assigned_gt_inds = cls_scores.new_full((num_bboxes, ),
0,
dtype=torch.long)
if num_gt == 0 or num_bboxes == 0:
# No ground truth or boxes, return empty assignment
max_overlaps = cls_scores.new_zeros((num_bboxes, ))
if num_gt == 0:
# No truth, assign everything to background
assigned_gt_inds[:] = 0
if gt_labels is None:
assigned_labels = None
else:
assigned_labels = cls_scores.new_full((num_bboxes, ),
-1,
dtype=torch.long)
return AssignResult(num_gt, assigned_gt_inds, max_overlaps, labels=assigned_labels)
if (self.ignore_iof_thr > 0 and gt_bboxes_ignore is not None
and gt_bboxes_ignore.numel() > 0 and bboxes.numel() > 0):
ignore_overlaps = self.iou_calculator(
bboxes, gt_bboxes_ignore, mode='iof')
ignore_max_overlaps, _ = ignore_overlaps.max(dim=1)
ignore_idxs = ignore_max_overlaps > self.ignore_iof_thr
assigned_gt_inds[ignore_idxs] = -1
assert True==False
bbox_repeat = bboxes.unsqueeze(1).repeat(1, num_gt, 1).view(-1, 4)
bbox_preds_repeat = bbox_preds.unsqueeze(1).repeat(1, num_gt, 1)
gt_bboxes_repeat = gt_bboxes.unsqueeze(0).repeat(num_bbox_preds, 1, 1)
bbox_preds_decode = bbox_coder.decode(bbox_repeat, bbox_preds_repeat.view(-1,4)).view(num_bbox_preds, num_gt, 4)
gt_bboxes_decode = gt_bboxes_repeat
bbox_preds_encode = bbox_preds_repeat
gt_bboxes_encode = bbox_coder.encode(bbox_repeat, gt_bboxes_repeat.view(-1,4)).view(num_bbox_preds, num_gt, 4)
bbox_preds_x = (bbox_preds_decode[:, :, 0] + bbox_preds_decode[:, :, 2]) * 0.5
bbox_preds_y = (bbox_preds_decode[:, :, 1] + bbox_preds_decode[:, :, 3]) * 0.5
bbox_preds_center = torch.stack([bbox_preds_x, bbox_preds_y], dim=-1)
bboxes_repeat = bboxes.unsqueeze(1).repeat(1, num_gt, 1)
bboxes_x = (bboxes_repeat[:, :, 0] + bboxes_repeat[:, :, 2]) * 0.5
bboxes_y = (bboxes_repeat[:, :, 1] + bboxes_repeat[:, :, 3]) * 0.5
bboxes_w = (bboxes_repeat[:, :, 2] - bboxes_repeat[:, :, 0])
bboxes_h = (bboxes_repeat[:, :, 3] - bboxes_repeat[:, :, 1])
bboxes_center = torch.stack([bboxes_x, bboxes_y], dim=-1)
bboxes_wh = torch.stack([bboxes_w, bboxes_h], dim=-1)
gt_center_x = (gt_bboxes_decode[:, :, 0] + gt_bboxes_decode[:, :, 2]) * 0.5
gt_center_y = (gt_bboxes_decode[:, :, 1] + gt_bboxes_decode[:, :, 3]) * 0.5
gt_center = torch.stack([gt_center_x, gt_center_y], dim=-1)
# cls_cost只对每个gt取对应的gt_label进行计算
cls_scores_repeat = cls_scores[:, gt_labels].sigmoid()
# giou loss
cost_bbox_num = bbox_overlaps(bbox_preds_decode, gt_bboxes_decode, mode='giou', is_aligned=True, eps=1e-7)
cost_bbox_num = 1 - cost_bbox_num
# l1 loss
cost_bbox2_num = torch.abs(bbox_preds_encode - gt_bboxes_encode) * 0.5
cost_bbox2_num = cost_bbox2_num.mean(dim=2)
# focal loss
gamma = 2.0
cost_cls_num = 0.5 * ((1 - cls_scores_repeat) ** gamma) * (-(cls_scores_repeat + 1e-8).log())
# print('cost_bbox_num :', cost_bbox_num)
# print('cost_bbox2_num :', cost_bbox2_num)
# print('cost_cls_num :', cost_cls_num)
assert cost_bbox2_num.shape == cost_cls_num.shape
assert torch.all(cost_bbox_num >= 0)
assert torch.all(cost_bbox2_num >= 0)
assert torch.all(cost_cls_num >= 0)
overlaps = cost_bbox_num + cost_bbox2_num + cost_cls_num
anchor_distance_cost = torch.abs(bbox_preds_center - bboxes_center) * 0.5
# NOTE:对anchor_distance_cost进行归一化（按bbox的wh大小分别对xy归一化）
anchor_distance_cost = anchor_distance_cost / (bboxes_wh / 8)
# print('anchor_distance_cost :', anchor_distance_cost)
# 计算L2距离
anchor_distance_cost = pow(anchor_distance_cost[:, :, 0], 2) + pow(anchor_distance_cost[:, :, 1], 2)
anchor_distance_cost = pow(anchor_distance_cost, 0.5)
anchor_distance_ratio = (0.5 * anchor_distance_cost + torch.full_like(anchor_distance_cost, 1))
assert torch.all(anchor_distance_ratio >= 0)
overlaps = overlaps * anchor_distance_ratio
# print('anchor_distance_ratio :', anchor_distance_ratio)
# NOTE: 确保predicted和anchor的shape，并在索引时一一对应，因为overlap是根据predicted排序的，而assign的时候是根据overlap的顺序assign给anchor
assert overlaps.shape[0] == assigned_gt_inds.shape[0]
overlaps_thr_per_gt = overlaps.topk(self.topk, dim=0, largest=False)[0][self.topk - 1]
is_pos = overlaps <= overlaps_thr_per_gt[None, :]
bboxes_cx = (bboxes[:, 0] + bboxes[:, 2]) / 2.0
bboxes_cy = (bboxes[:, 1] + bboxes[:, 3]) / 2.0
# limit the positive sample's center in gt
ep_bboxes_cx = bboxes_cx.view(-1, 1).expand(
num_bboxes, num_gt).contiguous()
ep_bboxes_cy = bboxes_cy.view(-1, 1).expand(
num_bboxes, num_gt).contiguous()
# calculate the left, top, right, bottom distance between positive
# bbox center and gt side
l_ = ep_bboxes_cx - gt_bboxes[:, 0]
t_ = ep_bboxes_cy - gt_bboxes[:, 1]
r_ = gt_bboxes[:, 2] - ep_bboxes_cx
b_ = gt_bboxes[:, 3] - ep_bboxes_cy
is_in_gts = torch.stack([l_, t_, r_, b_], dim=1).min(dim=1)[0] > 0.01
is_pos = is_pos & is_in_gts
overlaps_inf = torch.full_like(overlaps,
INF).contiguous().view(-1)
index = is_pos.view(-1)
overlaps_inf[index] = overlaps.contiguous().view(-1)[index]
overlaps_inf = overlaps_inf.view(-1, num_gt)
# NOTE: 第一次assign，用于计算第一次的rank
max_overlaps, argmax_overlaps = overlaps_inf.min(dim=1)
assigned_gt_inds[
max_overlaps != INF] = argmax_overlaps[max_overlaps != INF] + 1
# get the cost ranks of bboxes
ranked_values, indices = overlaps_inf.topk(k=num_bboxes, dim=0, largest=False)
assert torch.all(ranked_values >= 0)
ranked_values = ranked_values % INF
ranks = torch.full_like(overlaps_inf ,-1).contiguous()
for i in range(num_gt):
ranks[indices[:, i], i] = torch.arange(num_bboxes).type_as(overlaps_inf)
assert torch.all(ranks != -1)
sort_dim0 = torch.where(assigned_gt_inds > 0)[0]
conflict_num = (overlaps_inf != INF).sum(dim=1)
conflict_sort_dim0 = (conflict_num > 1) # 有冲突的anchor的dim0索引
sort_dim1 = torch.full_like(assigned_gt_inds, -1)
sort_dim1[sort_dim0] = argmax_overlaps[sort_dim0]
# NOTE: 如果一个anchor分配给多个gt，取rank最高的那个gt
if len(conflict_sort_dim0) > 0 :
ranks_inf = torch.full_like(ranks, INF).contiguous().view(-1)
overlaps_conflict = torch.full_like(overlaps_inf, -INF)
overlaps_conflict[conflict_sort_dim0] = overlaps_inf[conflict_sort_dim0]
dim0, dim1 = torch.where(overlaps_conflict > 0)
index = dim0 * num_gt + dim1
ranks_inf[index] = ranks.view(-1)[index]
ranks_inf = ranks_inf.view(num_bboxes, num_gt)
_, conflict_valid_dim1 = torch.min(ranks_inf, dim=1)
sort_dim1[conflict_sort_dim0] = conflict_valid_dim1[conflict_sort_dim0]
sort_dim1 = sort_dim1[sort_dim0]
assert torch.all(sort_dim1 != -1)
assert sort_dim0.shape == sort_dim1.shape
# NOTE: 第二次assign，根据rank排序后得到
assigned_gt_inds[sort_dim0] = sort_dim1 + 1
max_overlaps[sort_dim0] = overlaps_inf[sort_dim0, sort_dim1]
if gt_labels is not None:
assigned_labels = assigned_gt_inds.new_full((num_bboxes, ), -1)
pos_inds = torch.nonzero(
assigned_gt_inds > 0, as_tuple=False).squeeze()
if pos_inds.numel() > 0:
assigned_labels[pos_inds] = gt_labels[
assigned_gt_inds[pos_inds] - 1]
else:
assigned_labels = None
return AssignResult(num_gt, assigned_gt_inds, max_overlaps, labels=assigned_labels)
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28,
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3916,
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8,
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] | 1.932343 | 5,720 |
#Programa Principal
escreva('Gustavo Guanabará')
escreva('Curso de Python no YouTube')
escreva('CeV') | [
198,
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from application import app
from application import decorators
from flask import Blueprint, render_template
from flask import request, session, redirect, url_for
from run import gt
from config import BOT_TOKEN
from push_notifications import notification
import gorbin_tools2
page = Blueprint('reg', __name__,
template_folder='templates')
@page.route('/reg', methods = ['GET', 'POST'])
def reg():
'''
Registration function
'''
if 'login' in session:
#If such user already logged in, then redirect him to home page
return redirect(url_for('home.home'))
if request.method == "POST":
#get information from registarion form
result = request.form
with app.app_context():
#check if such login and email already taken or not
if (not gt.check_login(result['login'])) and (not gt.check_email(result['email'])):
#if not, then add information about new user in database
if result['login'] == 'user':
return render_template("reg.html",
error_flag=True,
error_message='This login is already taken')
gt.add_user(login = result['login'],
pas = gorbin_tools2.hash(result['password']),
email = result['email'])
if BOT_TOKEN:
notification(user = result['login'], type_message = 'user', users = gt.get_telegrams())
#log in user in session
session['login'] = result['login']
session['current_password'] = gorbin_tools2.hash(result['password'])
#redirect to home page
return redirect(url_for('home.home'))
else:
# if current login taken
if gt.check_login(result['login']):
#print error msg
return render_template("reg.html",
error_flag = True,
error_message = 'This login is already taken')
#if current email taken
elif gt.check_email(result['email']):
#print error msg
return render_template("reg.html",
error_flag = True,
error_message = 'This email is already taken')
return render_template("reg.html", error_flag = False)
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13,
6494,
1600,
4049,
62,
32109,
796,
10352,
8,
198
] | 2.725543 | 736 |
#A generator is a programming object that produces (that is, generates) a sequence of values
if __name__ == '__main__':
main() | [
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] | 3.540541 | 37 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from os.path import join, dirname, abspath
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import matplotlib.pyplot as plt
from matplotlib import rcParams
import numpy as np
| [
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from ocp_resources.resource import NamespacedResource
| [
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] | 4.583333 | 12 |
import pygame
import sys
from pygame.sprite import Group
from pygame.sprite import Sprite
class Settings():
"""A class that stores all settings."""
def __init__(self):
"""Initialize the game's settings."""
# Screen settings
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
class Star(Sprite):
"""A class to represent a single star."""
def __init__(self, settings, screen):
"""Initialize star and set its starting position."""
super().__init__()
self.settings = settings
self.screen = screen
# load star image and set its rect attribute.
self.image = pygame.image.load('images/star.bmp')
self.rect = self.image.get_rect()
# Start each new star near the top left of the screen.
self.rect.x = self.rect.width
self.rect.y = self.rect.height
def blitme(self):
"""Draw the start at its current location."""
self.screen.blit(self.image, self.rect)
def check_keydown_events(event, settings, screen):
"""Respond to key presses."""
if event.key == pygame.K_q:
sys.exit()
def check_keyup_events(event):
"""Respond to key releases."""
pass
def check_events(settings, screen):
"""Respond to key presses and mouse events."""
for event in pygame.event.get():
if event.type == pygame.QUIT:
sys.exit()
elif event.type == pygame.KEYDOWN:
check_keydown_events(event, settings, screen)
elif event.type == pygame.KEYUP:
check_keyup_events(event)
def update_screen(settings, screen, stars):
"""Update images on the screen and flip to the new screen."""
# Redraw the screen during each pass through the loop.
screen.fill(settings.bg_color)
# Redraw all stars.
stars.draw(screen)
# Make the most recently drawn screen visible.
pygame.display.flip()
def get_number_rows(settings, star_height):
"""Determine the number of rows of stars that fit on the screen."""
avaiable_space_y = (settings.screen_height - star_height)
number_rows = int(avaiable_space_y / (2 * star_height))
return number_rows
def get_number_stars_x(settings, star_width):
"""Determine the number of stars that fit in a row."""
avaiable_space_x = settings.screen_width - star_width
number_stars_x = int(avaiable_space_x / (2 * star_width))
return number_stars_x
def create_star(settings, screen, stars, star_number, row_number):
"""Create a star and place it in the row."""
star = Star(settings, screen)
star_width = star.rect.width
star_height = star.rect.height
star.x = star_width + 2 * star_width * star_number
star.rect.x = star.x
star.rect.y = star_height + 2 * star_height * row_number
stars.add(star)
def create_stars(settings, screen, stars):
"""Create a full group of stars."""
# Create a star and find the number of stars in a row.
star = Star(settings, screen)
number_stars_x = get_number_stars_x(settings, star.rect.width)
number_rows = get_number_rows(settings, star.rect.height)
# Create group of stars.
for row_number in range(number_rows):
for star_number in range(number_stars_x):
create_star(settings, screen, stars, star_number, row_number)
def run():
"""Initialize pygame, settings and screen objects."""
pygame.init()
settings = Settings()
screen = pygame.display.set_mode(
(settings.screen_width, settings.screen_height))
pygame.display.set_caption('Stars')
# Make a group to store stars.
stars = Group()
# Create group of start.
create_stars(settings, screen, stars)
# Main loop
while True:
check_events(settings, screen)
update_screen(settings, screen, stars)
run()
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8,
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] | 2.657713 | 1,452 |
from dataclasses import dataclass
from datetime import datetime
from typing import Optional
@dataclass
| [
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330,
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] | 3.888889 | 27 |
"""
时间：2020/9/22
作者：lurui
功能：k8s集群GPU节点打标签
"""
import os
import sys
basedir = os.path.abspath('.')
a = sys.argv[1]
b = sys.argv[2]
start_label_gpu(a, b)
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# -*- coding: utf-8 -*-
"""
`USGS Emergency Data Distribution Network`_ services
.. _USGS Emergency Data Distribution Network: http://eddn.usgs.gov/
"""
from .core import decode, get_data
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import itertools
from typing import Tuple, Union
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
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11748,
299,
32152,
355,
45941,
198,
11748,
384,
397,
1211,
355,
3013,
82,
628,
628
] | 3.15 | 40 |
from __future__ import print_function
import argparse
import time
import json
import grpc
import helloworld_pb2
import helloworld_pb2_grpc
service_config_json = json.dumps({
"methodConfig": [{
"name": [{
"service": "helloworld.Greeter",
"method": "SayHello"
}],
"retryPolicy": {
"maxAttempts": 5,
"initialBackoff": "1s",
"maxBackoff": "10s",
"backoffMultiplier": 2,
"retryableStatusCodes": ["UNAVAILABLE"],
},
}]
})
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='grpc test tool command')
parser.add_argument('-i', '--ip', type=str,
help='grpc server ip', required=True)
parser.add_argument('-p', '--port', type=str,
help='grpc server port', required=True)
parser.add_argument('-n', '--host_name', type=str,
help='grpc server host name', required=True)
args = parser.parse_args()
run(args.ip, args.port, args.host_name)
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220,
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220,
220,
220,
220,
220,
220,
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220,
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11,
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13,
634,
11,
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13,
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62,
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8,
198
] | 2.151329 | 489 |
from .api import AdflyApi
__all__ = ['AdflyApi']
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] | 2.380952 | 21 |
from __main__ import (
app,
session,
redirect,
render_template,
request,
jsonify,
uuid4,
USERS,
)
from json import (
dumps,
) # https://stackoverflow.com/questions/11994325/how-to-divide-flask-app-into-multiple-py-files
### LOGIN ###
@app.route("/login")
@app.route("/login", methods=["POST"])
### LOGIN end ###
### REGISTER ###
@app.route("/register")
@app.route("/register", methods=["POST"])
### REGISTER end ###
@app.route("/logout")
| [
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628,
198,
31,
1324,
13,
38629,
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30238,
1600,
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28,
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32782,
8973,
8,
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886,
44386,
628,
198,
31,
1324,
13,
38629,
7203,
14,
6404,
448,
4943,
198
] | 2.44 | 200 |
"""
A queue is a data structure whose primary purpose is to store and
return elements in First In First Out order.
1. [X] Implement the Queue class using an array as the underlying storage structure.
Make sure the Queue tests pass.
2. [X] Re-implement the Queue class, this time using the linked list implementation
as the underlying storage structure.
Make sure the Queue tests pass.
3. [X] What is the difference between using an array vs. a linked list when
implementing a Queue?
Major difference is, arrays are index-based data structure and each element of the array is associated with an index. With a linked list, it relies on pointers; each node has the data and then pointers to both previous and next elements. You use binary or linear searches to traverse arrays; linear to traverse linked lists. Arrays are directly or randomly accessed and you can access any element in them; queues are accessed via first pointer only.
Stretch: [X] What if you could only use instances of your Stack class to implement the Queue? What would that look like?
You'd need one for one direction and one for the opposite direction.
[X] How many Stacks would you need?
Two
[X] Try it!
doubly linked list?
"""
from singly_linked_list import LinkedList
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284,
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262,
4670,
518,
30,
220,
1867,
561,
326,
804,
588,
30,
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220,
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220,
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921,
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198,
198,
6738,
1702,
306,
62,
25614,
62,
4868,
1330,
7502,
276,
8053,
628
] | 3.69382 | 356 |
from django.apps import AppConfig
| [
6738,
42625,
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13,
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1330,
2034,
16934,
628
] | 3.888889 | 9 |
"""
Follow up for N-Queens problem.
Now, instead outputting board configurations, return the total number of distinct solutions.
"""
# @return an integer
# First remember this is diff to a normal cheesboard,
# placing a n*n chess board
# input 1, expect 1 but not 8
# Keep in mind the way to use self.ret as global
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355,
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198
] | 3.40404 | 99 |
"""Contains all classes related to the Character Bazaar sections in Tibia.com"""
import datetime
import logging
import re
import urllib.parse
from typing import Dict, List, Optional
import bs4
from tibiapy import InvalidContent, Sex, Vocation, abc
from tibiapy.abc import BaseCharacter
from tibiapy.enums import (AuctionOrder, AuctionOrderBy, AuctionSearchType, AuctionStatus, BattlEyeTypeFilter,
BazaarType, BidType, PvpTypeFilter, SkillFilter, VocationAuctionFilter)
from tibiapy.utils import (convert_line_breaks, get_tibia_url, parse_form_data, parse_integer, parse_pagination,
parse_tibia_datetime, parse_tibiacom_content, try_enum)
__all__ = (
"AchievementEntry",
"Auction",
"AuctionFilters",
"CharacterBazaar",
"CharmEntry",
"BestiaryEntry",
"BlessingEntry",
"DisplayItem",
"DisplayMount",
"DisplayOutfit",
"DisplayFamiliar",
"ItemSummary",
"AuctionEntry",
"Outfits",
"OutfitImage",
"Mounts",
"Familiars",
"SalesArgument",
"SkillEntry",
)
results_pattern = re.compile(r'Results: (\d+)')
char_info_regex = re.compile(r'Level: (\d+) \| Vocation: ([\w\s]+)\| (\w+) \| World: (\w+)')
id_addon_regex = re.compile(r'(\d+)_(\d)\.gif')
id_regex = re.compile(r'(\d+).(?:gif|png)')
description_regex = re.compile(r'"(?:an?\s)?([^"]+)"')
amount_regex = re.compile(r'([\d,]+)x')
log = logging.getLogger("tibiapy")
class AchievementEntry(abc.Serializable):
"""An unlocked achievement by the character.
Attributes
----------
name: :class:`str`
The name of the achievement.
secret: :class:`bool`
Whether the achievement is secret or not.
"""
__slots__ = (
"name",
"secret",
)
class AuctionFilters(abc.Serializable):
"""The auction filters available in the auctions section.
All attributes are optional.
Attributes
----------
world: :class:`str`
The character's world to show characters for.
pvp_type: :class:`PvpTypeFilter`
The PvP type of the character's worlds to show.
battleye: :class:`BattlEyeTypeFilter`
The type of BattlEye protection of the character's worlds to show.
vocation: :class:`VocationAuctionFilter`
The character vocation to show results for.
min_level: :class:`int`
The minimum level to display.
max_level: :class:`int`
The maximum level to display.
skill: :class:`SkillFilter`
The skill to filter by its level range.
min_skill_level: :class:`int`
The minimum skill level of the selected :attr:`skill` to display.
max_skill_level: :class:`int`
The maximum skill level of the selected :attr:`skill` to display.
search_string: :class:`str`
The search term to filter out auctions.
search_type: :class:`AuctionSearchType`
The type of search to use. Defines the behaviour of :py:attr:`search_string`.
available_worlds: :class:`list` of :class:`str`
The list of available worlds to select to filter.
"""
__slots__ = (
"world",
"pvp_type",
"battleye",
"vocation",
"min_level",
"max_level",
"skill",
"min_skill_level",
"max_skill_level",
"order_by",
"order",
"search_string",
"search_type",
"available_worlds",
)
@property
def query_params(self):
""":class:`dict`: The query parameters representing this filter."""
params = {
"filter_profession": self.vocation.value if self.vocation else None,
"filter_levelrangefrom": self.min_level,
"filter_levelrangeto": self.max_level,
"filter_world": self.world,
"filter_worldpvptype": self.pvp_type.value if self.pvp_type else None,
"filter_worldbattleyestate": self.battleye.value if self.battleye else None,
"filter_skillid": self.skill.value if self.skill else None,
"filter_skillrangefrom": self.min_skill_level,
"filter_skillrangeto": self.max_skill_level,
"order_column": self.order_by.value if self.order_by else None,
"order_direction": self.order.value if self.order else None,
"searchstring": self.search_string,
"searchtype": self.search_type.value if self.search_type else None,
}
return {k: v for k, v in params.items() if v is not None}
@classmethod
def _parse_filter_table(cls, table):
"""Parse the filters table to extract its values.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the filters.
Returns
-------
:class:`AuctionFilters`
The currently applied filters.
"""
filters = AuctionFilters()
forms = table.find_all("form")
data = parse_form_data(forms[0], include_options=True)
data_search = parse_form_data(forms[1], include_options=True)
filters.world = data["filter_world"]
filters.available_worlds = [w for w in data.get("__options__", {}).get("filter_world", []) if "(" not in w]
filters.pvp_type = try_enum(PvpTypeFilter, parse_integer(data.get("filter_worldpvptype"), None))
filters.battleye = try_enum(BattlEyeTypeFilter, parse_integer(data.get("filter_worldbattleyestate"), None))
filters.vocation = try_enum(VocationAuctionFilter, parse_integer(data.get("filter_profession"), None))
filters.min_level = parse_integer(data.get("filter_levelrangefrom"), None)
filters.max_level = parse_integer(data.get("filter_levelrangeto"), None)
filters.skill = try_enum(SkillFilter, parse_integer(data.get("filter_skillid"), None))
filters.min_skill_level = parse_integer(data.get("filter_skillrangefrom"), None)
filters.max_skill_level = parse_integer(data.get("filter_skillrangeto"), None)
filters.order_by = try_enum(AuctionOrderBy, parse_integer(data.get("order_column"), None))
filters.order = try_enum(AuctionOrder, parse_integer(data.get("order_direction"), None))
filters.search_string = data_search.get("searchstring")
filters.search_type = try_enum(AuctionSearchType, parse_integer(data_search.get("searchtype"), None))
return filters
class BestiaryEntry(abc.Serializable):
"""The bestiary progress for a specific creature.
Attributes
----------
name: :class:`str`
The name of the creature.
kills: :class:`int`
The number of kills of this creature the player has done.
step: :class:`int`
The current step to unlock this creature the character is in, where 4 is fully unlocked.
"""
__slots__ = (
"name",
"kills",
"step",
)
@property
def completed(self):
""":class:`bool`: Whether the entry is completed or not."""
return self.step == 4
class BlessingEntry(abc.Serializable):
"""A character's blessings.
Attributes
----------
name: :class:`str`
The name of the blessing.
amount: :class:`int`
The amount of blessing charges the character has.
"""
__slots__ = (
"name",
"amount",
)
class CharacterBazaar(abc.Serializable):
"""Represents the char bazaar.
Attributes
----------
page: :class:`int`
The page being currently viewed.
total_pages: :class:`int`
The total number of pages available.
results_count: :class:`int`
The number of auctions listed.
entries: :class:`list` of :class:`AuctionEntry`
The auctions displayed.
type: :class:`BazaarType`
The type of auctions being displayed, either current or auction history.
filters: :class:`AuctionFilters`
The currently set filtering options.
"""
__slots__ = (
"type",
"filters",
"page",
"total_pages",
"results_count",
"entries",
)
# region Properties
@property
def url(self):
""":class:`str`: Get the URL to the bazaar."""
return self.get_auctions_history_url(self.page) if self.type == BazaarType.HISTORY else \
self.get_current_auctions_url(self.page, self.filters)
# endregion
# region Public Methods
@classmethod
def get_current_auctions_url(cls, page=1, filters=None):
"""Get the URL to the list of current auctions in Tibia.com.
Parameters
----------
page: :class:`int`
The page to show the URL for.
filters: :class:`AuctionFilters`
The filtering criteria to use.
Returns
-------
:class:`str`
The URL to the current auctions section in Tibia.com
"""
filters = filters or AuctionFilters()
return get_tibia_url("charactertrade", "currentcharactertrades", currentpage=page, **filters.query_params)
@classmethod
def get_auctions_history_url(cls, page=1, filters=None):
"""Get the URL to the auction history in Tibia.com.
Parameters
----------
page: :class:`int`
The page to show the URL for.
filters: :class:`AuctionFilters`
The filtering criteria to use.
Returns
-------
:class:`str`
The URL to the auction history section in Tibia.com
"""
filters = filters or AuctionFilters()
return get_tibia_url("charactertrade", "pastcharactertrades", currentpage=page, **filters.query_params)
@classmethod
def from_content(cls, content):
"""Get the bazaar's information and list of auctions from Tibia.com.
Parameters
----------
content: :class:`str`
The HTML content of the bazaar section at Tibia.com.
Returns
-------
:class:`CharacterBazaar`
The character bazaar with the entries found.
"""
try:
parsed_content = parse_tibiacom_content(content, builder='html5lib')
content_table = parsed_content.find("div", attrs={"class": "BoxContent"})
tables = content_table.find_all("div", attrs={"class": "TableContainer"})
filter_table = None
if len(tables) == 1:
auctions_table = tables[0]
else:
filter_table, auctions_table, *_ = tables
bazaar = cls()
bazaar.type = BazaarType.CURRENT if filter_table else BazaarType.HISTORY
if filter_table:
bazaar.filters = AuctionFilters._parse_filter_table(filter_table)
page_navigation_row = parsed_content.find("td", attrs={"class": "PageNavigation"})
if page_navigation_row:
bazaar.page, bazaar.total_pages, bazaar.results_count = parse_pagination(page_navigation_row)
auction_rows = auctions_table.find_all("div", attrs={"class": "Auction"})
for auction_row in auction_rows:
auction = AuctionEntry._parse_auction(auction_row)
bazaar.entries.append(auction)
return bazaar
except ValueError as e:
raise InvalidContent("content does not belong to the bazaar at Tibia.com", original=e)
# endregion
class CharmEntry(abc.Serializable):
"""An unlocked charm by the character.
Attributes
----------
name: :class:`str`
The name of the charm.
cost: :class:`int`
The cost of the charm in charm points.
"""
__slots__ = (
"name",
"cost",
)
class DisplayImage(abc.Serializable):
"""An image displayed in the auction.
Attributes
----------
image_url: :class:`str`
The URL to the image.
name: :class:`str`
The element's name.
"""
__slots__ = (
"image_url",
"name",
)
@classmethod
class DisplayItem(abc.Serializable):
"""Represents an item displayed on an auction, or the character's items in the auction detail.
Attributes
----------
image_url: :class:`str`
The URL to the item's image.
name: :class:`str`
The item's name.
description: :class:`str`
The item's description, if any.
count: :class:`int`
The item's count.
item_id: :class:`int`
The item's client id.
"""
__slots__ = (
"image_url",
"name",
"description",
"count",
"item_id",
)
@classmethod
class DisplayMount(DisplayImage):
"""Represents a mount owned or unlocked by the character.
Attributes
----------
image_url: :class:`str`
The URL to the image.
name: :class:`str`
The mount's name.
mount_id: :class:`int`
The internal ID of the mount.
"""
__slots__ = (
"mount_id",
)
@classmethod
class DisplayOutfit(DisplayImage):
"""Represents an outfit owned or unlocked by the character.
Attributes
----------
image_url: :class:`str`
The URL to the image.
name: :class:`str`
The outfit's name.
outfit_id: :class:`int`
The internal ID of the outfit.
addons: :class:`int`
The unlocked or owned addons for this outfit.
"""
__slots__ = (
"outfit_id",
"addons",
)
@classmethod
class DisplayFamiliar(DisplayImage):
"""Represents a familiar owned or unlocked by the character.
Attributes
----------
image_url: :class:`str`
The URL to the image.
name: :class:`str`
The familiar's name.
familiar_id: :class:`int`
The internal ID of the familiar.
"""
__slots__ = (
"familiar_id",
)
@classmethod
class AuctionEntry(BaseCharacter, abc.Serializable):
"""Represents an auction in the list, containing the summary.
Attributes
----------
auction_id: :class:`int`
The internal id of the auction.
name: :class:`str`
The name of the character.
level: :class:`int`
The level of the character.
world: :class:`str`
The world the character is in.
vocation: :class:`Vocation`
The vocation of the character.
sex: :class:`Sex`
The sex of the character.
outfit: :class:`OutfitImage`
The current outfit selected by the user.
displayed_items: :class:`list` of :class:`DisplayItem`
The items selected to be displayed.
sales_arguments: :class:`list` of :class:`SalesArgument`
The sale arguments selected for the auction.
auction_start: :class:`datetime.datetime`
The date when the auction started.
auction_end: :class:`datetime.datetime`
The date when the auction ends.
bid: :class:`int`
The current bid in Tibia Coins.
bid_type: :class:`BidType`
The type of the auction's bid.
status: :class:`AuctionStatus`
The current status of the auction.
"""
__slots__ = (
"auction_id",
"name",
"level",
"world",
"vocation",
"sex",
"outfit",
"displayed_items",
"sales_arguments",
"auction_start",
"auction_end",
"bid",
"bid_type",
"status",
)
# region Properties
@property
def character_url(self):
""":class:`str`: The URL of the character's information page on Tibia.com."""
return BaseCharacter.get_url(self.name)
@property
def url(self):
""":class:`str`: The URL to this auction's detail page on Tibia.com."""
return self.get_url(self.auction_id)
# endregion
# region Public Methods
@classmethod
def get_url(cls, auction_id):
"""Get the URL to the Tibia.com detail page of an auction with a given id.
Parameters
----------
auction_id: :class:`int`
The ID of the auction.
Returns
-------
:class:`str`
The URL to the auction's detail page.
"""
return get_tibia_url("charactertrade", "currentcharactertrades", page="details", auctionid=auction_id)
# endregion
# region Private Methods
@classmethod
def _parse_auction(cls, auction_row, auction_id=0):
"""Parse an auction's table, extracting its data.
Parameters
----------
auction_row: :class:`bs4.Tag`
The row containing the auction's information.
auction_id: :class:`int`
The ID of the auction.
Returns
-------
:class:`AuctionEntry`
The auction contained in the table.
"""
header_container = auction_row.find("div", attrs={"class": "AuctionHeader"})
char_name_container = header_container.find("div", attrs={"class": "AuctionCharacterName"})
char_link = char_name_container.find("a")
if char_link:
url = urllib.parse.urlparse(char_link["href"])
query = urllib.parse.parse_qs(url.query)
auction_id = int(query["auctionid"][0])
name = char_link.text
else:
name = char_name_container.text
auction = cls(name=name, auction_id=auction_id)
char_name_container.replaceWith('')
m = char_info_regex.search(header_container.text)
if m:
auction.level = int(m.group(1))
auction.vocation = try_enum(Vocation, m.group(2).strip())
auction.sex = try_enum(Sex, m.group(3).strip().lower())
auction.world = m.group(4)
outfit_img = auction_row.find("img", {"class": "AuctionOutfitImage"})
m = id_addon_regex.search(outfit_img["src"])
if m:
auction.outfit = OutfitImage(image_url=outfit_img["src"], outfit_id=int(m.group(1)), addons=int(m.group(2)))
item_boxes = auction_row.find_all("div", attrs={"class": "CVIcon"})
for item_box in item_boxes:
item = DisplayItem._parse_image_box(item_box)
if item:
auction.displayed_items.append(item)
dates_containers = auction_row.find("div", {"class": "ShortAuctionData"})
start_date_tag, end_date_tag, *_ = dates_containers.find_all("div", {"class": "ShortAuctionDataValue"})
auction.auction_start = parse_tibia_datetime(start_date_tag.text.replace('\xa0', ' '))
auction.auction_end = parse_tibia_datetime(end_date_tag.text.replace('\xa0', ' '))
bids_container = auction_row.find("div", {"class": "ShortAuctionDataBidRow"})
bid_tag = bids_container.find("div", {"class", "ShortAuctionDataValue"})
bid_type_tag = bids_container.find_all("div", {"class", "ShortAuctionDataLabel"})[0]
bid_type_str = bid_type_tag.text.replace(":", "").strip()
auction.bid_type = try_enum(BidType, bid_type_str)
auction.bid = parse_integer(bid_tag.text)
auction_body_block = auction_row.find("div", {"class", "CurrentBid"})
auction_info_tag = auction_body_block.find("div", {"class": "AuctionInfo"})
status = ""
if auction_info_tag:
convert_line_breaks(auction_info_tag)
status = auction_info_tag.text.replace("\n", " ").replace(" ", " ")
auction.status = try_enum(AuctionStatus, status, AuctionStatus.IN_PROGRESS)
argument_entries = auction_row.find_all("div", {"class": "Entry"})
for entry in argument_entries:
img = entry.find("img")
img_url = img["src"]
category_id = 0
m = id_regex.search(img_url)
if m:
category_id = parse_integer(m.group(1))
auction.sales_arguments.append(SalesArgument(content=entry.text, category_image=img_url,
category_id=category_id))
return auction
# endregion
class Auction(AuctionEntry):
"""The details of an auction.
Attributes
----------
auction_id: :class:`int`
The internal id of the auction.
name: :class:`str`
The name of the character.
level: :class:`int`
The level of the character.
world: :class:`str`
The world the character is in.
vocation: :class:`Vocation`
The vocation of the character.
sex: :class:`Sex`
The sex of the character.
outfit: :class:`OutfitImage`
The current outfit selected by the user.
displayed_items: :class:`list` of :class:`DisplayItem`
The items selected to be displayed.
sales_arguments: :class:`list` of :class:`SalesArgument`
The sale arguments selected for the auction.
auction_start: :class:`datetime.datetime`
The date when the auction started.
auction_end: :class:`datetime.datetime`
The date when the auction ends.
bid: :class:`int`
The current bid in Tibia Coins.
bid_type: :class:`BidType`
The type of the auction's bid.
status: :class:`AuctionStatus`
The current status of the auction.
hit_points: :class:`int`
The hit points of the character.
mana: :class:`int`
The mana points of the character.
capacity: :class:`int`
The character's capacity in ounces.
speed: :class:`int`
The character's speed.
blessings_count: :class:`int`
The number of blessings the character has.
outfits_count: :class:`int`
The number of outfits the character has.
titles_count: :class:`int`
The number of titles the character has.
skills: :class:`list` of :class:`SkillEntry`
The current skills of the character.
creation_date: :class:`datetime.datetime`
The date when the character was created.
experience: :class:`int`
The total experience of the character.
gold: :class:`int`
The total amount of gold the character has.
achievement_points: :class:`int`
The number of achievement points of the character.
regular_world_transfer_available_date: :class:`datetime.datetmie`
The date after regular world transfers will be available to purchase and use.
:obj:`None` indicates it is available immediately.
charm_expansion: :class:`bool`
Whether the character has a charm expansion or not.
available_charm_points: :class:`int`
The amount of charm points the character has available to spend.
spent_charm_points: :class:`int`
The total charm points the character has spent.
prey_wildcards: :class:`int`
The number of Prey Wildcards the character has.
daly_reward_streak: :class:`int`
The current daily reward streak.
permanent_hunting_task_slots: :class:`int`
The number of hunting task slots.
permanent_prey_slots: :class:`int`
The number of prey slots.
hirelings: :class:`int`
The number of hirelings the character has.
hireling_jobs: :class:`int`
The number of hireling jobs the character has.
hireling_outfits: :class:`int`
The number of hireling outfits the character has.
items: :class:`ItemSummary`
The items the character has across inventory, depot and item stash.
store_items: :class:`ItemSummary`
The store items the character has.
mounts: :class:`Mounts`
The mounts the character has unlocked.
store_mounts: :class:`Mounts`
The mounts the character has purchased from the store.
outfits: :class:`Outfits`
The outfits the character has unlocked.
store_outfits: :class:`Outfits`
The outfits the character has purchased from the store.
familiars: :class:`Familiars`
The familiars the character has purchased or unlocked.
blessings: :class:`list` of :class:`BlessingEntry`
The blessings the character has.
imbuements: :class:`list` of :class:`str`
The imbuements the character has unlocked access to.
charms: :class:`list` of :class:`CharmEntry`
The charms the character has unlocked.
completed_cyclopedia_map_areas: :class:`list` of :class:`str`
The cyclopedia map areas that the character has fully discovered.
completed_quest_lines: :class:`list` of :class:`str`
The quest lines the character has fully completed.
titles: :class:`list` of :class:`str`
The titles the character has unlocked.
achievements: :class:`list` of :class:`AchievementEntry`
The achievements the character has unlocked.
bestiary_progress: :class:`list` of :class:`BestiaryEntry`
The bestiary progress of the character.
"""
__slots__ = (
"hit_points",
"mana",
"capacity",
"speed",
"blessings_count",
"mounts_count",
"outfits_count",
"titles_count",
"skills",
"creation_date",
"experience",
"gold",
"achievement_points",
"regular_world_transfer_available_date",
"charm_expansion",
"available_charm_points",
"spent_charm_points",
"daily_reward_streak",
"hunting_task_points",
"permanent_hunting_task_slots",
"permanent_prey_slots",
"prey_wildcards",
"hirelings",
"hireling_jobs",
"hireling_outfits",
"items",
"store_items",
"mounts",
"store_mounts",
"outfits",
"store_outfits",
"familiars",
"blessings",
"imbuements",
"charms",
"completed_cyclopedia_map_areas",
"completed_quest_lines",
"titles",
"achievements",
"bestiary_progress",
)
# region Properties
@property
def completed_bestiary_entries(self):
""":class:`list` of :class:`BestiaryEntry`: Get a list of completed bestiary entries."""
return [e for e in self.bestiary_progress if e.completed]
@property
def regular_world_transfer_available(self):
""":class:`bool`: Whether regular world transfers are available immediately for this character."""
return self.regular_world_transfer_available_date is None
@property
def skills_map(self) -> Dict[str, 'SkillEntry']:
""":class:`dict` of :class:`str`, :class:`SkillEntry`: A mapping of skills by their name."""
return {skill.name: skill for skill in self.skills}
# endregion
# region Public Methods
@classmethod
def from_content(cls, content, auction_id=0, skip_details=False):
"""Parse an auction detail page from Tibia.com and extracts its data.
Parameters
----------
content: :class:`str`
The HTML content of the auction detail page in Tibia.com
auction_id: :class:`int`, optional
The ID of the auction.
It is not possible to extract the ID from the page's content, so it may be passed to assign it manually.
skip_details: :class:`bool`, optional
Whether to skip parsing the entire auction and only parse the information shown in lists. False by default.
This allows fetching basic information like name, level, vocation, world, bid and status, shaving off some
parsing time.
Returns
-------
:class:`Auction`
The auction details if found, :obj:`None` otherwise.
Raises
------
InvalidContent
If the content does not belong to a auction detail's page.
"""
parsed_content = parse_tibiacom_content(content, builder='html5lib' if not skip_details else 'lxml')
auction_row = parsed_content.find("div", attrs={"class": "Auction"})
if not auction_row:
if "internal error" in content:
return None
raise InvalidContent("content does not belong to a auction details page in Tibia.com")
auction = cls._parse_auction(auction_row)
auction.auction_id = auction_id
if skip_details:
return auction
details_tables = cls._parse_tables(parsed_content)
if "General" in details_tables:
auction._parse_general_table(details_tables["General"])
if "ItemSummary" in details_tables:
auction.items = ItemSummary._parse_table(details_tables["ItemSummary"])
if "StoreItemSummary" in details_tables:
auction.store_items = ItemSummary._parse_table(details_tables["StoreItemSummary"])
if "Mounts" in details_tables:
auction.mounts = Mounts._parse_table(details_tables["Mounts"])
if "StoreMounts" in details_tables:
auction.store_mounts = Mounts._parse_table(details_tables["StoreMounts"])
if "Outfits" in details_tables:
auction.outfits = Outfits._parse_table(details_tables["Outfits"])
if "StoreOutfits" in details_tables:
auction.store_outfits = Outfits._parse_table(details_tables["StoreOutfits"])
if "Familiars" in details_tables:
auction.familiars = Familiars._parse_table(details_tables["Familiars"])
if "Blessings" in details_tables:
auction._parse_blessings_table(details_tables["Blessings"])
if "Imbuements" in details_tables:
auction.imbuements = cls._parse_single_column_table(details_tables["Imbuements"])
if "Charms" in details_tables:
auction._parse_charms_table(details_tables["Charms"])
if "CompletedCyclopediaMapAreas" in details_tables:
auction.completed_cyclopedia_map_areas = cls._parse_single_column_table(
details_tables["CompletedCyclopediaMapAreas"])
if "CompletedQuestLines" in details_tables:
auction.completed_quest_lines = cls._parse_single_column_table(details_tables["CompletedQuestLines"])
if "Titles" in details_tables:
auction.titles = cls._parse_single_column_table(details_tables["Titles"])
if "Achievements" in details_tables:
auction._parse_achievements_table(details_tables["Achievements"])
if "BestiaryProgress" in details_tables:
auction._parse_bestiary_table(details_tables["BestiaryProgress"])
return auction
# endregion
# region Private Methods
@classmethod
def _parse_tables(cls, parsed_content) -> Dict[str, bs4.Tag]:
"""Parse the character details tables.
Parameters
----------
parsed_content: :class:`bs4.Tag`
The parsed content of the auction.
Returns
-------
:class:`dict`
A dictionary of the tables, grouped by their id.
"""
details_tables = parsed_content.find_all("div", {"class": "CharacterDetailsBlock"})
return {table["id"]: table for table in details_tables}
@classmethod
def _parse_data_table(cls, table) -> Dict[str, str]:
"""Parse a simple data table into a key value mapping.
Parameters
----------
table: :class:`bs4.Tag`
The table to be parsed.
Returns
-------
:class:`dict`
A mapping containing the table's data.
"""
rows = table.find_all("tr")
data = {}
for row in rows:
name = row.find("span").text
value = row.find("div").text
name = name.lower().strip().replace(" ", "_").replace(":", "")
data[name] = value
return data
def _parse_skills_table(self, table):
"""Parse the skills table.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the character's skill.
"""
rows = table.find_all("tr")
skills = []
for row in rows:
cols = row.find_all("td")
name_c, level_c, progress_c = [c.text for c in cols]
level = int(level_c)
progress = float(progress_c.replace("%", ""))
skills.append(SkillEntry(name=name_c, level=level, progress=progress))
self.skills = skills
def _parse_blessings_table(self, table):
"""Parse the blessings table.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the character's blessings.
"""
table_content = table.find("table", attrs={"class": "TableContent"})
_, *rows = table_content.find_all("tr")
for row in rows:
cols = row.find_all("td")
amount_c, name_c = [c.text for c in cols]
amount = int(amount_c.replace("x", ""))
self.blessings.append(BlessingEntry(name_c, amount))
@classmethod
def _parse_single_column_table(cls, table):
"""Parse a table with a single column into an array.
Parameters
----------
table: :class:`bs4.Tag`
A table with a single column.
Returns
-------
:class:`list` of :class:`str`
A list with the contents of each row.
"""
table_content = table.find_all("table", attrs={"class": "TableContent"})[-1]
_, *rows = table_content.find_all("tr")
ret = []
for row in rows:
col = row.find("td")
text = col.text
if "more entries" in text:
continue
ret.append(text)
return ret
def _parse_charms_table(self, table):
"""Parse the charms table and extracts its information.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the charms.
"""
table_content = table.find("table", attrs={"class": "TableContent"})
_, *rows = table_content.find_all("tr")
for row in rows:
cols = row.find_all("td")
if len(cols) != 2:
continue
cost_c, name_c = [c.text for c in cols]
cost = parse_integer(cost_c.replace("x", ""))
self.charms.append(CharmEntry(name_c, cost))
def _parse_achievements_table(self, table):
"""Parse the achievements table and extracts its information.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the achievements.
"""
table_content = table.find("table", attrs={"class": "TableContent"})
_, *rows = table_content.find_all("tr")
for row in rows:
col = row.find("td")
text = col.text.strip()
if "more entries" in text:
continue
secret = col.find("img") is not None
self.achievements.append(AchievementEntry(text, secret))
def _parse_bestiary_table(self, table):
"""Parse the bestiary table and extracts its information.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the bestiary information.
"""
table_content = table.find("table", attrs={"class": "TableContent"})
_, *rows = table_content.find_all("tr")
for row in rows:
cols = row.find_all("td")
if len(cols) != 3:
continue
step_c, kills_c, name_c = [c.text for c in cols]
kills = parse_integer(kills_c.replace("x", ""))
step = int(step_c)
self.bestiary_progress.append(BestiaryEntry(name_c, kills, step))
@classmethod
def _parse_page_items(cls, content, entry_class):
"""Parse the elements of a page in the items, mounts and outfits.
Attributes
----------
content: :class:`str`
The HTML content in the page.
entry_class:
The class defining the elements.
Returns
-------
The entries contained in the page.
"""
parsed_content = parse_tibiacom_content(content, builder='html5lib')
item_boxes = parsed_content.find_all("div", attrs={"class": "CVIcon"})
entries = []
for item_box in item_boxes:
item = entry_class._parse_image_box(item_box)
if item:
entries.append(item)
return entries
def _parse_general_table(self, table):
"""Parse the general information table and assigns its values.
Parameters
----------
table: :class:`bs4.Tag`
The table with general information.
"""
content_containers = table.find_all("table", {"class": "TableContent"})
general_stats = self._parse_data_table(content_containers[0])
self.hit_points = parse_integer(general_stats.get("hit_points", "0"))
self.mana = parse_integer(general_stats.get("mana", "0"))
self.capacity = parse_integer(general_stats.get("capacity", "0"))
self.speed = parse_integer(general_stats.get("speed", "0"))
self.mounts_count = parse_integer(general_stats.get("mounts", "0"))
self.outfits_count = parse_integer(general_stats.get("outfits", "0"))
self.titles_count = parse_integer(general_stats.get("titles", "0"))
self.blessings_count = parse_integer(re.sub(r"/d+", "", general_stats.get("blessings", "0")))
self._parse_skills_table(content_containers[1])
additional_stats = self._parse_data_table(content_containers[2])
self.creation_date = parse_tibia_datetime(additional_stats.get("creation_date", "").replace("\xa0", " "))
self.experience = parse_integer(additional_stats.get("experience", "0"))
self.gold = parse_integer(additional_stats.get("gold", "0"))
self.achievement_points = parse_integer(additional_stats.get("achievement_points", "0"))
transfer_data = self._parse_data_table(content_containers[3])
transfer_text = transfer_data.get("regular_world_transfer")
if "after" in transfer_text:
date_string = transfer_text.split("after ")[1]
self.regular_world_transfer_available_date = parse_tibia_datetime(date_string)
charms_data = self._parse_data_table(content_containers[4])
self.charm_expansion = "yes" in charms_data.get("charm_expansion", "")
self.available_charm_points = parse_integer(charms_data.get("available_charm_points"))
self.spent_charm_points = parse_integer(charms_data.get("spent_charm_points"))
daily_rewards_data = self._parse_data_table(content_containers[5])
self.daily_reward_streak = parse_integer(daily_rewards_data.popitem()[1])
hunting_data = self._parse_data_table(content_containers[6])
self.hunting_task_points = parse_integer(hunting_data.get("hunting_task_points", ""))
self.permanent_hunting_task_slots = parse_integer(hunting_data.get("permanent_hunting_task_slots", ""))
self.permanent_prey_slots = parse_integer(hunting_data.get("permanent_prey_slots", ""))
self.prey_wildcards = parse_integer(hunting_data.get("prey_wildcards", ""))
hirelings_data = self._parse_data_table(content_containers[7])
self.hirelings = parse_integer(hirelings_data.get("hirelings", ""))
self.hireling_jobs = parse_integer(hirelings_data.get("hireling_jobs", ""))
self.hireling_outfits = parse_integer(hirelings_data.get("hireling_outfits", ""))
# endregion
class OutfitImage(abc.Serializable):
"""The image of the outfit currently being worn by the character.
Attributes
----------
image_url: :class:`str`
The URL of the image.
outfit_id: :class:`int`
The ID of the outfit.
addons: :class:`int`
The addons displayed in the outfit.
"""
__slots__ = (
"image_url",
"outfit_id",
"addons",
)
class PaginatedSummary(abc.Serializable):
"""Represents a paginated summary in the character auction section.
Attributes
----------
page: :class:`int`
The current page being displayed.
total_pages: :class:`int`
The total number of pages.
results: :class:`int`
The total number of results.
entries: :class:`list`
The entries.
fully_fetched: :class:`bool`
Whether the summary was fetched completely, including all other pages.
"""
entry_class = None
__slots__ = (
"page",
"total_pages",
"results",
"fully_fetched",
"entries",
)
# region Public Methods
def get_by_name(self, name):
"""Get an entry by its name.
Parameters
----------
name: :class:`str`
The name of the entry, case insensitive.
Returns
-------
:class:`object`:
The entry matching the name.
"""
return next((e for e in self.entries if e.name.lower() == name.lower()), None)
def search(self, value):
"""Search an entry by its name.
Parameters
----------
value: :class:`str`
The value to look for.
Returns
-------
:class:`list`
A list of entries with names containing the search term.
"""
return [e for e in self.entries if value.lower() in e.name.lower()]
def get_by_id(self, name):
"""Get an entry by its id.
Parameters
----------
name: :class:`str`
The name of the entry, case insensitive.
Returns
-------
:class:`object`:
The entry matching the name.
"""
return NotImplemented
# endregion
# region Private Methods
# endregion
class ItemSummary(PaginatedSummary):
"""Items in a character's inventory and depot.
Attributes
----------
page: :class:`int`
The current page being displayed.
total_pages: :class:`int`
The total number of pages.
results: :class:`int`
The total number of results.
entries: :class:`list` of :class:`DisplayItem`
The character's items.
fully_fetched: :class:`bool`
Whether the summary was fetched completely, including all other pages.
"""
entries: List[DisplayItem]
entry_class = DisplayItem
def get_by_id(self, entry_id):
"""Get an item by its item id.
Parameters
----------
entry_id: :class:`int`
The ID of the item.
Returns
-------
:class:`DisplayItem`
The item matching the id.
"""
return next((e for e in self.entries if e.item_id == entry_id), None)
@classmethod
def _parse_table(cls, table):
"""Parse the item summary table.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the item summary.
Returns
-------
:class:`ItemSummary`
The item summary contained in the table.
"""
summary = cls()
summary._parse_pagination(table)
item_boxes = table.find_all("div", attrs={"class": "CVIcon"})
for item_box in item_boxes:
item = DisplayItem._parse_image_box(item_box)
if item:
summary.entries.append(item)
return summary
class Mounts(PaginatedSummary):
"""The mounts a character has unlocked or purchased.
Attributes
----------
page: :class:`int`
The current page being displayed.
total_pages: :class:`int`
The total number of pages.
results: :class:`int`
The total number of results.
entries: :class:`list` of :class:`DisplayMount`
The character's mounts.
fully_fetched: :class:`bool`
Whether the summary was fetched completely, including all other pages.
"""
entries: List[DisplayMount]
entry_class = DisplayMount
def get_by_id(self, entry_id):
"""Get a mount by its mount id.
Parameters
----------
entry_id: :class:`int`
The ID of the mount.
Returns
-------
:class:`DisplayMount`
The mount matching the id.
"""
return next((e for e in self.entries if e.mount_id == entry_id), None)
@classmethod
class Familiars(PaginatedSummary):
"""The familiars the character has unlocked or purchased.
Attributes
----------
page: :class:`int`
The current page being displayed.
total_pages: :class:`int`
The total number of pages.
results: :class:`int`
The total number of results.
entries: :class:`list` of :class:`DisplayFamiliar`
The familiars the character has unlocked or purchased.
fully_fetched: :class:`bool`
Whether the summary was fetched completely, including all other pages.
"""
entries: List[DisplayFamiliar]
entry_class = DisplayFamiliar
def get_by_id(self, entry_id):
"""Get an outfit by its familiar id.
Parameters
----------
entry_id: :class:`int`
The ID of the outfit.
Returns
-------
:class:`DisplayOutfit`
The outfit matching the id.
"""
return next((e for e in self.entries if e.familiar_id == entry_id), None)
@classmethod
def _parse_table(cls, table):
"""Parse the outfits table.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the character outfits.
Returns
-------
:class:`Outfits`
The outfits contained in the table.
"""
summary = cls()
summary._parse_pagination(table)
item_boxes = table.find_all("div", attrs={"class": "CVIcon"})
for item_box in item_boxes:
item = DisplayFamiliar._parse_image_box(item_box)
if item:
summary.entries.append(item)
return summary
class Outfits(PaginatedSummary):
"""The outfits the character has unlocked or purchased.
Attributes
----------
page: :class:`int`
The current page being displayed.
total_pages: :class:`int`
The total number of pages.
results: :class:`int`
The total number of results.
entries: :class:`list` of :class:`DisplayOutfit`
The outfits the character has unlocked or purchased.
fully_fetched: :class:`bool`
Whether the summary was fetched completely, including all other pages.
"""
entries: List[DisplayOutfit]
entry_class = DisplayOutfit
def get_by_id(self, entry_id):
"""Get an outfit by its outfit id.
Parameters
----------
entry_id: :class:`int`
The ID of the outfit.
Returns
-------
:class:`DisplayOutfit`
The outfit matching the id.
"""
return next((e for e in self.entries if e.outfit_id == entry_id), None)
@classmethod
def _parse_table(cls, table):
"""Parse the outfits table.
Parameters
----------
table: :class:`bs4.Tag`
The table containing the character outfits.
Returns
-------
:class:`Outfits`
The outfits contained in the table.
"""
summary = cls()
summary._parse_pagination(table)
item_boxes = table.find_all("div", attrs={"class": "CVIcon"})
for item_box in item_boxes:
item = DisplayOutfit._parse_image_box(item_box)
if item:
summary.entries.append(item)
return summary
class SalesArgument(abc.Serializable):
"""Represents a sales argument.
Sales arguments can be selected when creating an auction, and allow the user to highlight certain
character features in the auction listing.
Attributes
----------
category_image: :class:`str`
The URL to the category icon.
content: :class:`str`
The content of the sales argument.
"""
__slots__ = (
"category_id",
"category_image",
"content",
)
class SkillEntry(abc.Serializable):
"""Represents the character's skills.
Attributes
----------
name: :class:`name`
The name of the skill.
level: :class:`int`
The current level.
progress: :class:`float`
The percentage of progress for the next level.
"""
__slots__ = (
"name",
"level",
"progress",
)
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198,
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220,
220,
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1,
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37227,
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40117,
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35656,
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317,
22155,
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37227,
10044,
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2829,
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13,
628,
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33491,
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220,
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60,
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40117,
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24200,
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13,
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19796,
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66,
8,
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220,
220,
220,
220,
220,
220,
220,
220,
4371,
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12178,
7,
33723,
62,
66,
13,
33491,
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4,
1600,
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4008,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4678,
13,
33295,
7,
35040,
30150,
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3672,
28,
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62,
66,
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654,
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220,
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220,
220,
220,
37227,
10044,
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40117,
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220,
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13,
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63,
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220,
220,
220,
220,
220,
220,
220,
220,
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220,
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13,
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37227,
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19796,
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28,
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4871,
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198,
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220,
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220,
220,
4808,
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1635,
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19796,
62,
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2033,
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66,
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220,
220,
220,
2116,
13,
65,
1203,
654,
13,
33295,
7,
33,
1203,
278,
30150,
7,
3672,
62,
66,
11,
2033,
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220,
2488,
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220,
825,
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29572,
62,
29762,
62,
28665,
62,
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7,
565,
82,
11,
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2599,
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220,
220,
220,
220,
220,
220,
220,
37227,
10044,
325,
257,
3084,
351,
257,
2060,
5721,
656,
281,
7177,
13,
628,
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220,
220,
220,
220,
220,
220,
40117,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
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220,
220,
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3084,
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13,
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317,
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13,
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220,
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16409,
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35656,
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4868,
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286,
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317,
1351,
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10154,
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19746,
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38381,
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16,
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4808,
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19796,
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220,
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220,
220,
220,
611,
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3549,
12784,
1,
287,
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25,
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220,
220,
220,
220,
220,
220,
220,
220,
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2555,
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220,
220,
220,
37227,
10044,
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41700,
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290,
32139,
663,
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13,
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40117,
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220,
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220,
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220,
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220,
220,
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262,
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19796,
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4808,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
4033,
82,
8,
14512,
362,
25,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
1575,
796,
21136,
62,
41433,
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220,
220,
220,
220,
220,
4445,
62,
260,
2017,
62,
7890,
796,
2116,
13557,
29572,
62,
7890,
62,
11487,
7,
11299,
62,
3642,
50221,
58,
20,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
29468,
62,
260,
904,
62,
22853,
461,
796,
21136,
62,
41433,
7,
29468,
62,
260,
2017,
62,
7890,
13,
12924,
9186,
3419,
58,
16,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
10988,
62,
7890,
796,
2116,
13557,
29572,
62,
7890,
62,
11487,
7,
11299,
62,
3642,
50221,
58,
21,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
20088,
889,
62,
35943,
62,
13033,
796,
21136,
62,
41433,
7,
20088,
889,
62,
7890,
13,
1136,
7203,
20088,
889,
62,
35943,
62,
13033,
1600,
13538,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
525,
44172,
62,
20088,
889,
62,
35943,
62,
6649,
1747,
796,
21136,
62,
41433,
7,
20088,
889,
62,
7890,
13,
1136,
7203,
525,
44172,
62,
20088,
889,
62,
35943,
62,
6649,
1747,
1600,
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198,
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13,
525,
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796,
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796,
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13,
198,
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220,
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287,
262,
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13,
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220,
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198,
220,
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220,
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281,
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416,
663,
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13,
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220,
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198,
220,
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198,
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286,
262,
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11,
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41246,
13,
628,
220,
220,
220,
220,
220,
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198,
220,
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220,
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198,
220,
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25,
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25,
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220,
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383,
5726,
12336,
262,
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13,
198,
220,
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220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1306,
19510,
68,
329,
304,
287,
2116,
13,
298,
1678,
611,
304,
13,
3672,
13,
21037,
3419,
6624,
1438,
13,
21037,
3419,
828,
6045,
8,
628,
220,
220,
220,
825,
2989,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
18243,
281,
5726,
416,
663,
1438,
13,
628,
220,
220,
220,
220,
220,
220,
220,
40117,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
25,
1058,
4871,
25,
63,
2536,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1988,
284,
804,
329,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
198,
220,
220,
220,
220,
220,
220,
220,
35656,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
63,
4868,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
317,
1351,
286,
12784,
351,
3891,
7268,
262,
2989,
3381,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
68,
329,
304,
287,
2116,
13,
298,
1678,
611,
1988,
13,
21037,
3419,
287,
304,
13,
3672,
13,
21037,
3419,
60,
628,
220,
220,
220,
825,
651,
62,
1525,
62,
312,
7,
944,
11,
1438,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
3855,
281,
5726,
416,
663,
4686,
13,
628,
220,
220,
220,
220,
220,
220,
220,
40117,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
1058,
4871,
25,
63,
2536,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1438,
286,
262,
5726,
11,
1339,
41246,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
198,
220,
220,
220,
220,
220,
220,
220,
35656,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
63,
15252,
63,
25,
198,
220,
220,
220,
220,
220,
220,
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220,
220,
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220,
383,
5726,
12336,
262,
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13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1892,
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1154,
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198,
220,
220,
220,
1303,
886,
36996,
628,
220,
220,
220,
1303,
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15348,
25458,
198,
220,
220,
220,
1303,
886,
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628,
198,
4871,
9097,
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7,
47,
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198,
220,
220,
220,
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23022,
287,
257,
2095,
338,
13184,
290,
43369,
13,
628,
220,
220,
220,
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198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
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25,
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25,
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600,
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198,
220,
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220,
220,
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220,
383,
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852,
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13,
198,
220,
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198,
220,
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286,
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13,
198,
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25,
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198,
220,
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286,
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13,
198,
220,
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12784,
25,
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25,
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286,
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25,
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198,
220,
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198,
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10127,
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373,
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11,
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477,
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13,
198,
220,
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628,
220,
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25,
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60,
198,
220,
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16531,
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628,
220,
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312,
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11,
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312,
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198,
220,
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220,
37227,
3855,
281,
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416,
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13,
628,
220,
220,
220,
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220,
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40117,
198,
220,
220,
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438,
198,
220,
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312,
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198,
220,
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383,
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286,
262,
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13,
628,
220,
220,
220,
220,
220,
220,
220,
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198,
220,
220,
220,
220,
220,
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220,
35656,
198,
220,
220,
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220,
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1058,
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25,
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63,
198,
220,
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12336,
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13,
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198,
220,
220,
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220,
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1441,
1306,
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287,
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13,
298,
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611,
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13,
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312,
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312,
828,
6045,
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628,
220,
220,
220,
2488,
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24396,
198,
220,
220,
220,
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4808,
29572,
62,
11487,
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565,
82,
11,
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198,
220,
220,
220,
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220,
220,
37227,
10044,
325,
262,
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10638,
3084,
13,
628,
220,
220,
220,
220,
220,
220,
220,
40117,
198,
220,
220,
220,
220,
220,
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438,
198,
220,
220,
220,
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3084,
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25,
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63,
198,
220,
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262,
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10638,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
198,
220,
220,
220,
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220,
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220,
35656,
198,
220,
220,
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1058,
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25,
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63,
198,
220,
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10638,
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287,
262,
3084,
13,
198,
220,
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220,
220,
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37227,
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220,
220,
366,
33723,
1600,
198,
220,
220,
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1267,
198
] | 2.343844 | 20,614 |
num = list()
pos = 0
while True:
num.append(int(input("Digite um valor: ")))
option = " "
while option not in "SN":
option = str(input("Quer continuar? [S/N]: ")).upper().strip()[0]
if option == "N":
break
print("="*30)
print(f"Você digitou a seguinte lista {num}")
print(f"Foram digitados {len(num)} termos")
if 5 in num:
print("O número 5 está na lista, ", end="")
for pos, n in enumerate(num):
if n == 5:
print(f"{pos}...", end="")
pos += 1
else:
print("\nO número 5 não esta na lista")
num.sort(reverse=True)
print(f"\nA lista em ordem decrescente é {num}")
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] | 2.107143 | 308 |
"""
Django settings for myproject project.
Generated by 'django-admin startproject' using Django 2.2.
For more information on this file, see
https://docs.djangoproject.com/en/2.2/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/2.2/ref/settings/
"""
import os
import datetime
import environ
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
root = environ.Path(__file__) - 3
env = environ.Env(DEBUG=(bool, False), ) # set default values and casting
env.read_env(
os.path.join(BASE_DIR,
'myproject/envs/env.%s' % env.str('PROJECT_ENV', 'local'))
) # 在envs文件夹下有env.dev/ env.prod/ env.qa/ env.local文件
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'u5_2uvq7vu#24&4s(d*^96r4=e3!o3qh81m01c#lb@vzzc8f@a'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = env('DEBUG')
ALLOWED_HOSTS = env.list('ALLOWED_HOSTS')
CORS_ORIGIN_WHITELIST = env.list('CORS_ORIGIN_WHITELIST')
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'corsheaders',
'rest_framework',
'rest_framework.authtoken',
'user.apps.UserConfig',
]
MIDDLEWARE = [
'corsheaders.middleware.CorsMiddleware',
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'myproject.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'myproject.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.2/ref/settings/#databases
DATABASES = {'default': env.db()}
# Password validation
# https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME':
'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME':
'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME':
'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME':
'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
REST_FRAMEWORK = {
# Use Django's standard `django.contrib.auth` permissions,
# or allow read-only access for unauthenticated users.
'DEFAULT_PERMISSION_CLASSES': [],
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework_jwt.authentication.JSONWebTokenAuthentication',
'rest_framework.authentication.SessionAuthentication',
'rest_framework.authentication.BasicAuthentication',
),
'DEFAULT_PAGINATION_CLASS':
'rest_framework.pagination.LimitOffsetPagination',
'PAGE_SIZE':
15,
'DATETIME_FORMAT':
'%Y-%m-%d %H:%M:%S',
'TIME_ZONE':
'Asia/Shanghai',
'EXCEPTION_HANDLER':
'utils.custom_exception_handler.custom_exception_handler',
}
REST_FRAMEWORK_DOCS = {'HIDE_DOCS': False}
JWT_AUTH = {
'JWT_ALLOW_REFRESH': True,
'JWT_EXPIRATION_DELTA': datetime.timedelta(days=30),
}
LOGGING = {
'version': 1,
'disable_existing_loggers': False,
'formatters': {
'verbose': {
'format':
'%(levelname)s %(asctime)s %(module)s %(process)d %(thread)d %(message)s'
},
'simple': {
'format': '%(levelname)s %(message)s'
},
},
'handlers': {
'console': {
'level': 'INFO',
'class': 'logging.StreamHandler',
'formatter': 'simple'
},
'file': {
'level': 'INFO',
'class': 'logging.FileHandler',
'filename': '/var/log/myproject_uwsgi.log',
'formatter': 'verbose'
},
},
'loggers': {
'django': {
'handlers': ['console', 'file'],
'level': 'INFO',
'propagate': True,
},
'myproject': {
'handlers': ['console', 'file'],
'level': 'INFO',
'propagate': True,
}
},
}
# Internationalization
# https://docs.djangoproject.com/en/2.2/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.2/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, "static")
STATICFILES_DIRS = (os.path.join(BASE_DIR, "web/static"), )
# Absolute filesystem path to the directory that will hold user-uploaded files.
# Example: "/home/media/media.lawrence.com/media/"
MEDIA_ROOT = os.path.join(BASE_DIR, "static/media")
# URL that handles the media served from MEDIA_ROOT. Make sure to use a
# trailing slash.
# Examples: "http://media.lawrence.com/media/", "http://example.com/media/"
MEDIA_URL = '/media/'
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13,
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2,
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7,
33,
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198,
2,
10289,
326,
17105,
262,
2056,
4983,
422,
26112,
3539,
62,
13252,
2394,
13,
6889,
1654,
284,
779,
257,
198,
2,
25462,
24632,
13,
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2,
21066,
25,
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6270,
6784,
13,
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14,
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14,
1600,
366,
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20688,
13,
785,
14,
11431,
30487,
198,
30733,
3539,
62,
21886,
796,
31051,
11431,
14,
6,
198
] | 2.232346 | 2,634 |
"""
Evaluate min. no. train examples to edit to flip test prediction.
"""
import os
import sys
import time
import hashlib
import argparse
import resource
from datetime import datetime
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import sem
from sklearn.metrics import log_loss
here = os.path.abspath(os.path.dirname(__file__))
sys.path.insert(0, here + '/../')
import util
from experiments import util as exp_util
from config import post_args
if __name__ == '__main__':
main(post_args.get_counterfactual_args().parse_args())
| [
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62,
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198,
6738,
4566,
1330,
1281,
62,
22046,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
7,
7353,
62,
22046,
13,
1136,
62,
24588,
22584,
723,
62,
22046,
22446,
29572,
62,
22046,
28955,
198
] | 3.135135 | 185 |
#!/usr/bin/env python3
import json
import time
from env import env
from run_common import AWSCli
from run_common import print_message
from run_common import print_session
options, args = dict(), list()
if __name__ == "__main__":
from run_common import parse_args
options, args = parse_args()
################################################################################
#
# start
#
################################################################################
print_session('create sqs')
target_name = None
region = options.get('region')
is_target_exists = False
for settings in env.get('sqs', list()):
if target_name and settings['NAME'] != target_name:
continue
if region and settings['AWS_REGION'] != region:
continue
is_target_exists = True
run_create_queue(settings['NAME'], settings)
if is_target_exists is False:
mm = list()
if target_name:
mm.append(target_name)
if region:
mm.append(region)
mm = ' in '.join(mm)
print(f'sqs: {mm} is not found in config.json')
| [
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220,
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7,
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8,
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220,
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25,
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220,
220,
220,
220,
220,
220,
220,
8085,
13,
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7,
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8,
198,
220,
220,
220,
8085,
796,
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287,
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7,
3020,
8,
198,
220,
220,
220,
3601,
7,
69,
338,
48382,
25,
1391,
3020,
92,
318,
407,
1043,
287,
4566,
13,
17752,
11537,
198
] | 3.093023 | 344 |
import Sofa
import particle
# optionnally, script can create a graph...
| [
11748,
1406,
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198,
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198,
197,
2,
3038,
77,
453,
11,
4226,
460,
2251,
257,
4823,
986,
628,
198
] | 3.5 | 22 |
import abc
import numpy as np
__all__ = ['LeafLineSearcher']
| [
11748,
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] | 2.64 | 25 |
import pytest
import spacy
from replacy import ReplaceMatcher
nlp = spacy.load("en_core_web_sm")
# They read us the stories they themselves had written.
match_dict = {
"match-1": {
"patterns": [[
{"LOWER": {"IN": ["they", "she"]}},
{"LEMMA": "read", "TEMPLATE_ID": 1},
{"LOWER": "us"},
{"LOWER": "the"},
{"LEMMA": "story", "TEMPLATE_ID": 1},
{"LOWER": {"IN": ["they", "she"]}},
{"LOWER": {"IN": ["themselves", "herself"]}},
{"LEMMA": "have", "OP": "*"},
{"LEMMA": {"IN": ["write", "made"]}},
]],
"suggestions": [
[
{"PATTERN_REF": 0},
{"TEXT": {"IN": ["sing", "give"]}, "FROM_TEMPLATE_ID": 1},
{"PATTERN_REF": 2},
{"TEXT": {"IN": ["a", "the", "some"]}},
{"TEXT": "story", "INFLECTION": "NOUN"},
{"PATTERN_REF": 5, "REPLACY_OP": "UPPER"},
{"PATTERN_REF": 6},
{"TEXT": {"IN": ["write", "made", "create"]}, "INFLECTION": "VBD"},
]
],
"test": {"positive": [], "negative": []},
}
}
outputs = [
"They sang us a stories THEY themselves wrote",
"They sang us a stories THEY themselves made",
"They sang us a stories THEY themselves created",
"They gave us a stories THEY themselves wrote",
"They gave us a stories THEY themselves made",
"They gave us a stories THEY themselves created",
"They sang us the story THEY themselves wrote",
"They sang us the story THEY themselves made",
"They sang us the story THEY themselves created",
"They gave us the story THEY themselves wrote",
"They gave us the story THEY themselves made",
"They gave us the story THEY themselves created",
]
output_default_max_count_1 = [
"They sang us a stories THEY themselves wrote",
"They sang us a story THEY themselves made",
"They gave us a stories THEY themselves made",
"They gave us a story THEY themselves wrote",
"They sang us the stories THEY themselves made",
"They sang us the story THEY themselves wrote",
"They gave us the stories THEY themselves wrote",
"They gave us the story THEY themselves made",
"They sang us some stories THEY themselves created",
"They gave us some story THEY themselves created",
]
r_matcher1 = ReplaceMatcher(
nlp,
match_dict=match_dict,
lm_path="./replacy/resources/test.arpa",
filter_suggestions=True,
)
spans = r_matcher1("They read us the stories they themselves had written.")
suggestions = spans[0]._.suggestions
r_matcher_max_count_1 = ReplaceMatcher(
nlp,
match_dict=match_dict,
lm_path="./replacy/resources/test.arpa",
filter_suggestions=True,
default_max_count=1,
)
spans_max_count_1 = r_matcher_max_count_1(
"They read us the stories they themselves had written."
)
suggestions_max_count_1 = spans_max_count_1[0]._.suggestions
short_match_dict_2_sugg = {
"match-1": {
"patterns": [[
{"LOWER": {"IN": ["they", "she"]}},
{"LEMMA": "read", "TEMPLATE_ID": 1},
]],
"suggestions": [
[
{"PATTERN_REF": 0},
{"FROM_TEMPLATE_ID": 1, "TEXT": {"IN": ["sing", "give"]}},
],
[{"PATTERN_REF": 0}, {"FROM_TEMPLATE_ID": 1, "TEXT": "dance"},],
],
"test": {"negative": [], "positive": []},
}
}
short_match_dict = {
"match-1": {
"patterns": [[
{"LOWER": {"IN": ["they", "she"]}},
{"LEMMA": "read", "TEMPLATE_ID": 1},
]],
"suggestions": [
[
{"PATTERN_REF": 0},
{"FROM_TEMPLATE_ID": 1, "TEXT": {"IN": ["sing", "give"]}},
]
],
"test": {"negative": [], "positive": []},
}
}
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37,
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53,
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220,
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220,
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220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
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9288,
1298,
19779,
24561,
1298,
685,
4357,
366,
31591,
1298,
17635,
5512,
198,
220,
220,
220,
1782,
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92,
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25889,
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] | 2.200792 | 1,768 |
#!/usr/bin/env python3
"""
Module to compute positive exons in the bloom filter as follos:
- abyss-bloom kmers to get bed coordinates of each transcriptomic kmer in the BF
- bedtools merge to join overlapping consecutive intervals by k-1bases
- awk to throw away too short intervales (to avoid FPs)
- bedtools merge to join overlapping consecutive intervals by k-max_overlap bases
"""
import logging
from subprocess import Popen, PIPE
import pandas as pd
from exfi.io.bed import BED3_COLS, BED3_DTYPES
def process_output(process):
"""Get lines in BED3 format from the output of a Popen.
:param Popen process: Popen object.
"""
bed3 = pd.DataFrame(
data=[
stdout_line.decode().strip().split()
for stdout_line in iter(process.stdout.readline, b'')
],
columns=BED3_COLS
).astype(BED3_DTYPES)
process.stdout.close()
process.wait()
return bed3
def get_fasta(transcriptome_dict, iterable_of_bed):
"""Extract subsequences in trancriptome_fn according to locis.
:param dict transcriptome_dict: FastaDict of the transcriptome
:param iterable iterable_of_bed: iterable of Bed3Records.
"""
for bed in iterable_of_bed:
chromosome, start, end = bed
if chromosome in transcriptome_dict:
seq = transcriptome_dict[chromosome][start:end]
identifier = f"{chromosome}:{start}-{end}"
yield (identifier, seq)
def find_exons(args):
"""Find exons according to the Bloom filter -> BED3
Main pipeline:
- Check every kmer,
- merge if there is an overlap of k-1 bases,
- Throw away too short exons (k + max_fp_bases; FP of the BF),
- merge consecutive exons if they have an ovelap of max_fp_bases
args = {
"kmer": int,
"bloom": str,
"fasta": str,
"max_overlap": int,
"max_fp_bases": int
}
:param dict args: arguments for abyss-bloom kmers, bedtools merge and awk
"""
logging.info("Running the find exons pipeline")
# Prepare the commands
c_kmers = [
"abyss-bloom", "kmers", "--kmer", str(
args["kmer"]), "--verbose", "--bed",
args["bloom"], args["fasta"]
]
c_merge1 = ["bedtools", "merge", "-d", str(-args["kmer"] + 2)]
c_filter = ["awk", "$3 - $2 >= {min_length}".format(
min_length=args["kmer"] + args["max_fp_bases"]
)]
c_merge2 = ["bedtools", "merge", "-d", str(-args["max_overlap"])]
# Run all of them streamlined
p_kmers = Popen(c_kmers, stdout=PIPE)
p_merge1 = Popen(c_merge1, stdin=p_kmers.stdout, stdout=PIPE)
p_filter = Popen(c_filter, stdin=p_merge1.stdout, stdout=PIPE)
p_merge2 = Popen(c_merge2, stdin=p_filter.stdout, stdout=PIPE)
p_kmers.stdout.close()
logging.info('Done')
return process_output(p_merge2)
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] | 2.394449 | 1,189 |
from typing import List, Optional
from littlelambocoin.consensus.block_record import BlockRecord
from littlelambocoin.consensus.blockchain_interface import BlockchainInterface
from littlelambocoin.consensus.constants import ConsensusConstants
from littlelambocoin.types.blockchain_format.classgroup import ClassgroupElement
from littlelambocoin.types.blockchain_format.sized_bytes import bytes32
from littlelambocoin.types.end_of_slot_bundle import EndOfSubSlotBundle
from littlelambocoin.util.ints import uint64, uint128
def get_signage_point_vdf_info(
constants: ConsensusConstants,
finished_sub_slots: List[EndOfSubSlotBundle],
overflow: bool,
prev_b: Optional[BlockRecord],
blocks: BlockchainInterface,
sp_total_iters: uint128,
sp_iters: uint64,
):
"""
Returns the following information, for the VDF of the signage point at sp_total_iters.
cc and rc challenge hash
cc and rc input
cc and rc iterations
"""
new_sub_slot: bool = len(finished_sub_slots) > 0
genesis_block: bool = prev_b is None
if new_sub_slot and not overflow:
# Case 1: start from start of this slot. Case of no overflow slots. Also includes genesis block after empty
# slot(s), but not overflowing
rc_vdf_challenge: bytes32 = finished_sub_slots[-1].reward_chain.get_hash()
cc_vdf_challenge = finished_sub_slots[-1].challenge_chain.get_hash()
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
elif new_sub_slot and overflow and len(finished_sub_slots) > 1:
# Case 2: start from start of prev slot. This is a rare case of empty prev slot. Includes genesis block after
# 2 empty slots
rc_vdf_challenge = finished_sub_slots[-2].reward_chain.get_hash()
cc_vdf_challenge = finished_sub_slots[-2].challenge_chain.get_hash()
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
elif genesis_block:
# Case 3: Genesis block case, first challenge
rc_vdf_challenge = constants.GENESIS_CHALLENGE
cc_vdf_challenge = constants.GENESIS_CHALLENGE
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
elif new_sub_slot and overflow and len(finished_sub_slots) == 1:
# Case 4: Starting at prev will put us in the previous, sub-slot, since case 2 handled more empty slots
assert prev_b is not None
curr: BlockRecord = prev_b
while not curr.first_in_sub_slot and curr.total_iters > sp_total_iters:
curr = blocks.block_record(curr.prev_hash)
if curr.total_iters < sp_total_iters:
sp_vdf_iters = uint64(sp_total_iters - curr.total_iters)
cc_vdf_input = curr.challenge_vdf_output
rc_vdf_challenge = curr.reward_infusion_new_challenge
else:
assert curr.finished_reward_slot_hashes is not None
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
rc_vdf_challenge = curr.finished_reward_slot_hashes[-1]
while not curr.first_in_sub_slot:
curr = blocks.block_record(curr.prev_hash)
assert curr.finished_challenge_slot_hashes is not None
cc_vdf_challenge = curr.finished_challenge_slot_hashes[-1]
elif not new_sub_slot and overflow:
# Case 5: prev is in the same sub slot and also overflow. Starting at prev does not skip any sub slots
assert prev_b is not None
curr = prev_b
# Collects the last two finished slots
if curr.first_in_sub_slot:
assert curr.finished_challenge_slot_hashes is not None
assert curr.finished_reward_slot_hashes is not None
found_sub_slots = list(
reversed(
list(
zip(
curr.finished_challenge_slot_hashes,
curr.finished_reward_slot_hashes,
)
)
)
)
else:
found_sub_slots = []
sp_pre_sb: Optional[BlockRecord] = None
while len(found_sub_slots) < 2 and curr.height > 0:
if sp_pre_sb is None and curr.total_iters < sp_total_iters:
sp_pre_sb = curr
curr = blocks.block_record(curr.prev_hash)
if curr.first_in_sub_slot:
assert curr.finished_challenge_slot_hashes is not None
assert curr.finished_reward_slot_hashes is not None
found_sub_slots += list(
reversed(
list(
zip(
curr.finished_challenge_slot_hashes,
curr.finished_reward_slot_hashes,
)
)
)
)
if sp_pre_sb is None and curr.total_iters < sp_total_iters:
sp_pre_sb = curr
if sp_pre_sb is not None:
sp_vdf_iters = uint64(sp_total_iters - sp_pre_sb.total_iters)
cc_vdf_input = sp_pre_sb.challenge_vdf_output
rc_vdf_challenge = sp_pre_sb.reward_infusion_new_challenge
else:
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
rc_vdf_challenge = found_sub_slots[1][1]
cc_vdf_challenge = found_sub_slots[1][0]
elif not new_sub_slot and not overflow:
# Case 6: prev is in the same sub slot. Starting at prev does not skip any sub slots. We do not need
# to go back another sub slot, because it's not overflow, so the VDF to signage point is this sub-slot.
assert prev_b is not None
curr = prev_b
while not curr.first_in_sub_slot and curr.total_iters > sp_total_iters:
curr = blocks.block_record(curr.prev_hash)
if curr.total_iters < sp_total_iters:
sp_vdf_iters = uint64(sp_total_iters - curr.total_iters)
cc_vdf_input = curr.challenge_vdf_output
rc_vdf_challenge = curr.reward_infusion_new_challenge
else:
assert curr.finished_reward_slot_hashes is not None
sp_vdf_iters = sp_iters
cc_vdf_input = ClassgroupElement.get_default_element()
rc_vdf_challenge = curr.finished_reward_slot_hashes[-1]
while not curr.first_in_sub_slot:
curr = blocks.block_record(curr.prev_hash)
assert curr.finished_challenge_slot_hashes is not None
cc_vdf_challenge = curr.finished_challenge_slot_hashes[-1]
else:
# All cases are handled above
assert False
return (
cc_vdf_challenge,
rc_vdf_challenge,
cc_vdf_input,
ClassgroupElement.get_default_element(),
sp_vdf_iters,
sp_vdf_iters,
)
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1267,
198
] | 2.11549 | 3,273 |
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