content
stringlengths 1
1.04M
| input_ids
sequencelengths 1
774k
| ratio_char_token
float64 0.38
22.9
| token_count
int64 1
774k
|
|---|---|---|---|
from django.shortcuts import render, redirect
from .forms import RegistrationForm
from .models import Account
from django.contrib import messages, auth
from django.contrib.auth.decorators import login_required
from django.http import HttpResponse
from carts.models import Cart, CartItem
from carts.views import _cart_id
import requests
# verification imports
from django.contrib.sites.shortcuts import get_current_site
from django.template.loader import render_to_string
from django.utils.http import urlsafe_base64_encode, urlsafe_base64_decode
from django.utils.encoding import force_bytes
from django.contrib.auth.tokens import default_token_generator
from django.core.mail import EmailMessage
# Create your views here.
@login_required(login_url='login')
@login_required(login_url='login')
| [
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
11,
18941,
198,
6738,
764,
23914,
1330,
24610,
8479,
198,
6738,
764,
27530,
1330,
10781,
198,
6738,
42625,
14208,
13,
3642,
822,
1330,
6218,
11,
6284,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
12501,
273,
2024,
1330,
17594,
62,
35827,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
6738,
44355,
13,
27530,
1330,
13690,
11,
13690,
7449,
198,
6738,
44355,
13,
33571,
1330,
4808,
26674,
62,
312,
198,
11748,
7007,
198,
198,
2,
19637,
17944,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
49315,
13,
19509,
23779,
1330,
651,
62,
14421,
62,
15654,
198,
6738,
42625,
14208,
13,
28243,
13,
29356,
1330,
8543,
62,
1462,
62,
8841,
198,
6738,
42625,
14208,
13,
26791,
13,
4023,
1330,
2956,
7278,
8635,
62,
8692,
2414,
62,
268,
8189,
11,
2956,
7278,
8635,
62,
8692,
2414,
62,
12501,
1098,
198,
6738,
42625,
14208,
13,
26791,
13,
12685,
7656,
1330,
2700,
62,
33661,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
83,
482,
641,
1330,
4277,
62,
30001,
62,
8612,
1352,
198,
6738,
42625,
14208,
13,
7295,
13,
4529,
1330,
9570,
12837,
198,
198,
2,
13610,
534,
5009,
994,
13,
628,
198,
198,
31,
38235,
62,
35827,
7,
38235,
62,
6371,
11639,
38235,
11537,
628,
198,
198,
31,
38235,
62,
35827,
7,
38235,
62,
6371,
11639,
38235,
11537,
628,
628
] | 3.480519 | 231 |
begin_unit
comment|'# Copyright 2010 United States Government as represented by the'
nl|'\n'
comment|'# Administrator of the National Aeronautics and Space Administration.'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n'
comment|'# a copy of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT'
nl|'\n'
comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the'
nl|'\n'
comment|'# License for the specific language governing permissions and limitations'
nl|'\n'
comment|'# under the License.'
nl|'\n'
nl|'\n'
name|'from'
name|'oslo_log'
name|'import'
name|'log'
name|'as'
name|'logging'
newline|'\n'
name|'from'
name|'oslo_log'
name|'import'
name|'versionutils'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
op|'.'
name|'i18n'
name|'import'
name|'_LW'
newline|'\n'
nl|'\n'
DECL|variable|LOG
name|'LOG'
op|'='
name|'logging'
op|'.'
name|'getLogger'
op|'('
name|'__name__'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|CloudController
name|'class'
name|'CloudController'
op|'('
name|'object'
op|')'
op|':'
newline|'\n'
DECL|member|__init__
indent|' '
name|'def'
name|'__init__'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'versionutils'
op|'.'
name|'report_deprecated_feature'
op|'('
nl|'\n'
name|'LOG'
op|','
nl|'\n'
name|'_LW'
op|'('
string|"'The in tree EC2 API has been removed in Mitaka. '"
nl|'\n'
string|"'Please remove entries from api-paste.ini and use '"
nl|'\n'
string|"'the OpenStack ec2-api project '"
nl|'\n'
string|"'http://git.openstack.org/cgit/openstack/ec2-api/'"
op|')'
nl|'\n'
op|')'
newline|'\n'
dedent|''
dedent|''
endmarker|''
end_unit
| [
27471,
62,
20850,
198,
23893,
91,
6,
2,
15069,
3050,
1578,
1829,
5070,
355,
7997,
416,
262,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
22998,
286,
262,
2351,
15781,
261,
2306,
873,
290,
4687,
8694,
2637,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
1439,
6923,
33876,
2637,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
345,
743,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
921,
743,
7330,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
257,
4866,
286,
262,
13789,
379,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
220,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
42881,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
4091,
262,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
11247,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
23893,
91,
6,
2,
220,
220,
220,
739,
262,
13789,
2637,
198,
21283,
91,
6,
59,
77,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
3672,
91,
6,
6738,
6,
198,
3672,
91,
6,
418,
5439,
62,
6404,
6,
198,
3672,
91,
6,
11748,
6,
198,
3672,
91,
6,
6404,
6,
198,
3672,
91,
6,
292,
6,
198,
3672,
91,
6,
6404,
2667,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
3672,
91,
6,
6738,
6,
198,
3672,
91,
6,
418,
5439,
62,
6404,
6,
198,
3672,
91,
6,
11748,
6,
198,
3672,
91,
6,
9641,
26791,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
3672,
91,
6,
6738,
6,
198,
3672,
91,
6,
38438,
6,
198,
404,
91,
6,
2637,
198,
3672,
91,
6,
72,
1507,
77,
6,
198,
3672,
91,
6,
11748,
6,
198,
3672,
91,
6,
62,
43,
54,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
41374,
43,
91,
45286,
91,
25294,
198,
3672,
91,
6,
25294,
6,
198,
404,
91,
6,
11639,
198,
3672,
91,
6,
6404,
2667,
6,
198,
404,
91,
6,
2637,
198,
3672,
91,
6,
1136,
11187,
1362,
6,
198,
404,
91,
6,
10786,
198,
3672,
91,
6,
834,
3672,
834,
6,
198,
404,
91,
11537,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
41374,
43,
91,
4871,
91,
18839,
22130,
198,
3672,
91,
6,
4871,
6,
198,
3672,
91,
6,
18839,
22130,
6,
198,
404,
91,
6,
10786,
198,
3672,
91,
6,
15252,
6,
198,
404,
91,
11537,
6,
198,
404,
91,
10354,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
41374,
43,
91,
19522,
91,
834,
15003,
834,
198,
521,
298,
91,
6,
220,
220,
220,
705,
198,
3672,
91,
6,
4299,
6,
198,
3672,
91,
6,
834,
15003,
834,
6,
198,
404,
91,
6,
10786,
198,
3672,
91,
6,
944,
6,
198,
404,
91,
11537,
6,
198,
404,
91,
10354,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
521,
298,
91,
6,
220,
220,
220,
220,
220,
220,
220,
705,
198,
3672,
91,
6,
9641,
26791,
6,
198,
404,
91,
6,
2637,
198,
3672,
91,
6,
13116,
62,
10378,
31023,
62,
30053,
6,
198,
404,
91,
6,
10786,
198,
21283,
91,
6,
59,
77,
6,
198,
3672,
91,
6,
25294,
6,
198,
404,
91,
41707,
198,
21283,
91,
6,
59,
77,
6,
198,
3672,
91,
6,
62,
43,
54,
6,
198,
404,
91,
6,
10786,
198,
8841,
91,
30543,
464,
287,
5509,
13182,
17,
7824,
468,
587,
4615,
287,
11707,
8130,
13,
705,
1,
198,
21283,
91,
6,
59,
77,
6,
198,
8841,
91,
30543,
5492,
4781,
12784,
422,
40391,
12,
34274,
13,
5362,
290,
779,
705,
1,
198,
21283,
91,
6,
59,
77,
6,
198,
8841,
91,
30543,
1169,
4946,
25896,
9940,
17,
12,
15042,
1628,
705,
1,
198,
21283,
91,
6,
59,
77,
6,
198,
8841,
91,
30543,
4023,
1378,
18300,
13,
9654,
25558,
13,
2398,
14,
66,
18300,
14,
9654,
25558,
14,
721,
17,
12,
15042,
14,
29653,
198,
404,
91,
11537,
6,
198,
21283,
91,
6,
59,
77,
6,
198,
404,
91,
11537,
6,
198,
3605,
1370,
91,
6,
59,
77,
6,
198,
9395,
298,
91,
7061,
198,
9395,
298,
91,
7061,
198,
437,
4102,
263,
91,
7061,
198,
437,
62,
20850,
198
] | 2.262136 | 927 |
import io
from google.cloud import vision
# Prepare image to be classified
# Get the labels for an image
| [
11748,
33245,
198,
6738,
23645,
13,
17721,
1330,
5761,
628,
220,
220,
220,
1303,
43426,
2939,
284,
307,
10090,
628,
220,
220,
220,
1303,
3497,
262,
14722,
329,
281,
2939,
198
] | 3.709677 | 31 |
from django.db import models
from django.db.models.signals import pre_save
from user.models import CustomUser
# Signals
pre_save.connect(caculate_university_overall_score, sender=UniversityRate)
pre_save.connect(caculate_professor_overall_score, sender=ProfessorRate)
| [
6738,
42625,
14208,
13,
9945,
1330,
4981,
198,
6738,
42625,
14208,
13,
9945,
13,
27530,
13,
12683,
874,
1330,
662,
62,
21928,
198,
6738,
2836,
13,
27530,
1330,
8562,
12982,
628,
628,
628,
628,
628,
198,
2,
5865,
874,
628,
198,
198,
3866,
62,
21928,
13,
8443,
7,
66,
330,
5039,
62,
403,
1608,
62,
2502,
439,
62,
26675,
11,
29788,
28,
21009,
32184,
8,
198,
3866,
62,
21928,
13,
8443,
7,
66,
330,
5039,
62,
5577,
5987,
62,
2502,
439,
62,
26675,
11,
29788,
28,
25031,
32184,
8,
198
] | 3.122222 | 90 |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import json
import logging
import sys
from argparse import ArgumentParser
from six import PY2
import yaml
from . import (
__url__,
__version__,
api,
)
from .provider import ProviderError
from .serializer import (
get_json_encoder,
get_yaml_dumper,
)
from .utils import recurse_paths
logging.basicConfig(stream=sys.stdout, format='%(message)s')
logging.getLogger('CONSOLE').setLevel(logging.INFO)
logging.getLogger('knowit').setLevel(logging.ERROR)
console = logging.getLogger('CONSOLE')
logger = logging.getLogger('knowit')
def build_argument_parser():
"""Build the argument parser.
:return: the argument parser
:rtype: ArgumentParser
"""
opts = ArgumentParser()
opts.add_argument(dest='videopath', help='Path to the video to introspect', nargs='*')
provider_opts = opts.add_argument_group('Providers')
provider_opts.add_argument('-p', '--provider', dest='provider',
help='The provider to be used: mediainfo, ffmpeg or enzyme.')
output_opts = opts.add_argument_group('Output')
output_opts.add_argument('--debug', action='store_true', dest='debug',
help='Print useful information for debugging knowit and for reporting bugs.')
output_opts.add_argument('--report', action='store_true', dest='report',
help='Parse media and report all non-detected values')
output_opts.add_argument('-y', '--yaml', action='store_true', dest='yaml',
help='Display output in yaml format')
output_opts.add_argument('-N', '--no-units', action='store_true', dest='no_units',
help='Display output without units')
output_opts.add_argument('-P', '--profile', dest='profile',
help='Display values according to specified profile: code, default, human, technical')
conf_opts = opts.add_argument_group('Configuration')
conf_opts.add_argument('--mediainfo', dest='mediainfo',
help='The location to search for MediaInfo binaries')
conf_opts.add_argument('--ffmpeg', dest='ffmpeg',
help='The location to search for FFmpeg (ffprobe) binaries')
information_opts = opts.add_argument_group('Information')
information_opts.add_argument('--version', dest='version', action='store_true',
help='Display knowit version.')
return opts
def knowit(video_path, options, context):
"""Extract video metadata."""
context['path'] = video_path
if not options.report:
console.info('For: %s', video_path)
else:
console.info('Parsing: %s', video_path)
info = api.know(video_path, context)
if not options.report:
console.info('Knowit %s found: ', __version__)
console.info(dump(info, options, context))
return info
def dump(info, options, context):
"""Convert info to string using json or yaml format."""
if options.yaml:
data = {info['path']: info} if 'path' in info else info
result = yaml.dump(data, Dumper=get_yaml_dumper(context),
default_flow_style=False, allow_unicode=True)
if PY2:
result = result.decode('utf-8')
else:
result = json.dumps(info, cls=get_json_encoder(context), indent=4, ensure_ascii=False)
return result
def main(args=None):
"""Execute main function for entry point."""
argument_parser = build_argument_parser()
args = args or sys.argv[1:]
options = argument_parser.parse_args(args)
if options.debug:
logger.setLevel(logging.DEBUG)
logging.getLogger('enzyme').setLevel(logging.INFO)
else:
logger.setLevel(logging.WARNING)
paths = recurse_paths(options.videopath)
if paths:
report = {}
for i, videopath in enumerate(paths):
try:
context = dict(vars(options))
if options.report:
context['report'] = report
else:
del context['report']
knowit(videopath, options, context)
except ProviderError:
logger.exception('Error when processing video')
except OSError:
logger.exception('OS error when processing video')
except UnicodeError:
logger.exception('Character encoding error when processing video')
except api.KnowitException as e:
logger.error(e)
if options.report and i % 20 == 19 and report:
console.info('Unknown values so far:')
console.info(dump(report, options, vars(options)))
if options.report:
if report:
console.info('Knowit %s found unknown values:', __version__)
console.info(dump(report, options, vars(options)))
console.info('Please report them at %s', __url__)
else:
console.info('Knowit %s knows everything. :-)', __version__)
elif options.version:
console.info(api.debug_info())
else:
argument_parser.print_help()
if __name__ == '__main__':
main(sys.argv[1:])
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
11748,
33918,
198,
11748,
18931,
198,
11748,
25064,
198,
6738,
1822,
29572,
1330,
45751,
46677,
198,
198,
6738,
2237,
1330,
350,
56,
17,
198,
11748,
331,
43695,
198,
198,
6738,
764,
1330,
357,
198,
220,
220,
220,
11593,
6371,
834,
11,
198,
220,
220,
220,
11593,
9641,
834,
11,
198,
220,
220,
220,
40391,
11,
198,
8,
198,
6738,
764,
15234,
1304,
1330,
32549,
12331,
198,
6738,
764,
46911,
7509,
1330,
357,
198,
220,
220,
220,
651,
62,
17752,
62,
12685,
12342,
11,
198,
220,
220,
220,
651,
62,
88,
43695,
62,
67,
15829,
11,
198,
8,
198,
6738,
764,
26791,
1330,
664,
12321,
62,
6978,
82,
198,
198,
6404,
2667,
13,
35487,
16934,
7,
5532,
28,
17597,
13,
19282,
448,
11,
5794,
11639,
4,
7,
20500,
8,
82,
11537,
198,
6404,
2667,
13,
1136,
11187,
1362,
10786,
10943,
15821,
2538,
27691,
2617,
4971,
7,
6404,
2667,
13,
10778,
8,
198,
6404,
2667,
13,
1136,
11187,
1362,
10786,
16275,
270,
27691,
2617,
4971,
7,
6404,
2667,
13,
24908,
8,
198,
198,
41947,
796,
18931,
13,
1136,
11187,
1362,
10786,
10943,
15821,
2538,
11537,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
10786,
16275,
270,
11537,
628,
198,
4299,
1382,
62,
49140,
62,
48610,
33529,
198,
220,
220,
220,
37227,
15580,
262,
4578,
30751,
13,
628,
220,
220,
220,
1058,
7783,
25,
262,
4578,
30751,
198,
220,
220,
220,
1058,
81,
4906,
25,
45751,
46677,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2172,
82,
796,
45751,
46677,
3419,
198,
220,
220,
220,
2172,
82,
13,
2860,
62,
49140,
7,
16520,
11639,
85,
485,
18569,
3256,
1037,
11639,
15235,
284,
262,
2008,
284,
18951,
4443,
3256,
299,
22046,
11639,
9,
11537,
628,
220,
220,
220,
10131,
62,
404,
912,
796,
2172,
82,
13,
2860,
62,
49140,
62,
8094,
10786,
15946,
4157,
11537,
198,
220,
220,
220,
10131,
62,
404,
912,
13,
2860,
62,
49140,
10786,
12,
79,
3256,
705,
438,
15234,
1304,
3256,
2244,
11639,
15234,
1304,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
464,
10131,
284,
307,
973,
25,
16957,
391,
6513,
11,
31246,
43913,
393,
27679,
2637,
8,
628,
220,
220,
220,
5072,
62,
404,
912,
796,
2172,
82,
13,
2860,
62,
49140,
62,
8094,
10786,
26410,
11537,
198,
220,
220,
220,
5072,
62,
404,
912,
13,
2860,
62,
49140,
10786,
438,
24442,
3256,
2223,
11639,
8095,
62,
7942,
3256,
2244,
11639,
24442,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
18557,
4465,
1321,
329,
28769,
760,
270,
290,
329,
6447,
11316,
2637,
8,
198,
220,
220,
220,
5072,
62,
404,
912,
13,
2860,
62,
49140,
10786,
438,
13116,
3256,
2223,
11639,
8095,
62,
7942,
3256,
2244,
11639,
13116,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
10044,
325,
2056,
290,
989,
477,
1729,
12,
15255,
11197,
3815,
11537,
198,
220,
220,
220,
5072,
62,
404,
912,
13,
2860,
62,
49140,
10786,
12,
88,
3256,
705,
438,
88,
43695,
3256,
2223,
11639,
8095,
62,
7942,
3256,
2244,
11639,
88,
43695,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
23114,
5072,
287,
331,
43695,
5794,
11537,
198,
220,
220,
220,
5072,
62,
404,
912,
13,
2860,
62,
49140,
10786,
12,
45,
3256,
705,
438,
3919,
12,
41667,
3256,
2223,
11639,
8095,
62,
7942,
3256,
2244,
11639,
3919,
62,
41667,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
23114,
5072,
1231,
4991,
11537,
198,
220,
220,
220,
5072,
62,
404,
912,
13,
2860,
62,
49140,
10786,
12,
47,
3256,
705,
438,
13317,
3256,
2244,
11639,
13317,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
23114,
3815,
1864,
284,
7368,
7034,
25,
2438,
11,
4277,
11,
1692,
11,
6276,
11537,
628,
220,
220,
220,
1013,
62,
404,
912,
796,
2172,
82,
13,
2860,
62,
49140,
62,
8094,
10786,
38149,
11537,
198,
220,
220,
220,
1013,
62,
404,
912,
13,
2860,
62,
49140,
10786,
438,
2379,
391,
6513,
3256,
2244,
11639,
2379,
391,
6513,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
464,
4067,
284,
2989,
329,
6343,
12360,
38640,
11537,
198,
220,
220,
220,
1013,
62,
404,
912,
13,
2860,
62,
49140,
10786,
438,
487,
43913,
3256,
2244,
11639,
487,
43913,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
464,
4067,
284,
2989,
329,
18402,
43913,
357,
487,
1676,
1350,
8,
38640,
11537,
628,
220,
220,
220,
1321,
62,
404,
912,
796,
2172,
82,
13,
2860,
62,
49140,
62,
8094,
10786,
21918,
11537,
198,
220,
220,
220,
1321,
62,
404,
912,
13,
2860,
62,
49140,
10786,
438,
9641,
3256,
2244,
11639,
9641,
3256,
2223,
11639,
8095,
62,
7942,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
23114,
760,
270,
2196,
2637,
8,
628,
220,
220,
220,
1441,
2172,
82,
628,
198,
4299,
760,
270,
7,
15588,
62,
6978,
11,
3689,
11,
4732,
2599,
198,
220,
220,
220,
37227,
11627,
974,
2008,
20150,
526,
15931,
198,
220,
220,
220,
4732,
17816,
6978,
20520,
796,
2008,
62,
6978,
198,
220,
220,
220,
611,
407,
3689,
13,
13116,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
1890,
25,
4064,
82,
3256,
2008,
62,
6978,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
47,
945,
278,
25,
4064,
82,
3256,
2008,
62,
6978,
8,
198,
220,
220,
220,
7508,
796,
40391,
13,
16275,
7,
15588,
62,
6978,
11,
4732,
8,
198,
220,
220,
220,
611,
407,
3689,
13,
13116,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
23812,
270,
4064,
82,
1043,
25,
46083,
11593,
9641,
834,
8,
198,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
7,
39455,
7,
10951,
11,
3689,
11,
4732,
4008,
628,
220,
220,
220,
1441,
7508,
628,
198,
4299,
10285,
7,
10951,
11,
3689,
11,
4732,
2599,
198,
220,
220,
220,
37227,
3103,
1851,
7508,
284,
4731,
1262,
33918,
393,
331,
43695,
5794,
526,
15931,
198,
220,
220,
220,
611,
3689,
13,
88,
43695,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
796,
1391,
10951,
17816,
6978,
6,
5974,
7508,
92,
611,
705,
6978,
6,
287,
7508,
2073,
7508,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
331,
43695,
13,
39455,
7,
7890,
11,
360,
15829,
28,
1136,
62,
88,
43695,
62,
67,
15829,
7,
22866,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
62,
11125,
62,
7635,
28,
25101,
11,
1249,
62,
46903,
1098,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
350,
56,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
1255,
13,
12501,
1098,
10786,
40477,
12,
23,
11537,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
33918,
13,
67,
8142,
7,
10951,
11,
537,
82,
28,
1136,
62,
17752,
62,
12685,
12342,
7,
22866,
828,
33793,
28,
19,
11,
4155,
62,
292,
979,
72,
28,
25101,
8,
628,
220,
220,
220,
1441,
1255,
628,
198,
4299,
1388,
7,
22046,
28,
14202,
2599,
198,
220,
220,
220,
37227,
23002,
1133,
1388,
2163,
329,
5726,
966,
526,
15931,
198,
220,
220,
220,
4578,
62,
48610,
796,
1382,
62,
49140,
62,
48610,
3419,
198,
220,
220,
220,
26498,
796,
26498,
393,
25064,
13,
853,
85,
58,
16,
47715,
198,
220,
220,
220,
3689,
796,
4578,
62,
48610,
13,
29572,
62,
22046,
7,
22046,
8,
628,
220,
220,
220,
611,
3689,
13,
24442,
25,
198,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
2617,
4971,
7,
6404,
2667,
13,
30531,
8,
198,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
1136,
11187,
1362,
10786,
268,
24266,
27691,
2617,
4971,
7,
6404,
2667,
13,
10778,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
2617,
4971,
7,
6404,
2667,
13,
31502,
8,
628,
220,
220,
220,
13532,
796,
664,
12321,
62,
6978,
82,
7,
25811,
13,
85,
485,
18569,
8,
628,
220,
220,
220,
611,
13532,
25,
198,
220,
220,
220,
220,
220,
220,
220,
989,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
11,
18784,
18569,
287,
27056,
378,
7,
6978,
82,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4732,
796,
8633,
7,
85,
945,
7,
25811,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
3689,
13,
13116,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4732,
17816,
13116,
20520,
796,
989,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1619,
4732,
17816,
13116,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
760,
270,
7,
85,
485,
18569,
11,
3689,
11,
4732,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
32549,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
1069,
4516,
10786,
12331,
618,
7587,
2008,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
440,
5188,
81,
1472,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
1069,
4516,
10786,
2640,
4049,
618,
7587,
2008,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
34371,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
1069,
4516,
10786,
27275,
21004,
4049,
618,
7587,
2008,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
40391,
13,
23812,
270,
16922,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
18224,
7,
68,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
3689,
13,
13116,
290,
1312,
4064,
1160,
6624,
678,
290,
989,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
20035,
3815,
523,
1290,
25,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
7,
39455,
7,
13116,
11,
3689,
11,
410,
945,
7,
25811,
22305,
628,
220,
220,
220,
220,
220,
220,
220,
611,
3689,
13,
13116,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
989,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
23812,
270,
4064,
82,
1043,
6439,
3815,
25,
3256,
11593,
9641,
834,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
7,
39455,
7,
13116,
11,
3689,
11,
410,
945,
7,
25811,
22305,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
5492,
989,
606,
379,
4064,
82,
3256,
11593,
6371,
834,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
10786,
23812,
270,
4064,
82,
4206,
2279,
13,
47226,
3256,
11593,
9641,
834,
8,
628,
220,
220,
220,
1288,
361,
3689,
13,
9641,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8624,
13,
10951,
7,
15042,
13,
24442,
62,
10951,
28955,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4578,
62,
48610,
13,
4798,
62,
16794,
3419,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
7,
17597,
13,
853,
85,
58,
16,
25,
12962,
198
] | 2.338028 | 2,272 |
from unittest import TestCase
from string_utils.generation import roman_range
| [
6738,
555,
715,
395,
1330,
6208,
20448,
198,
198,
6738,
4731,
62,
26791,
13,
20158,
1330,
374,
5185,
62,
9521,
628
] | 3.809524 | 21 |
"""
Copyright (C) 2011
Mads Chr. Olesen <[email protected]>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>. """
#-----------------------------------------------------------------
# Based on pycparser: _build_tables.py, Copyright (C) 2008-2011, Eli Bendersky
#
# A dummy for generating the lexing/parsing tables and and
# compiling them into .pyc for faster execution in optimized mode.
# Should be called from the installation directory.
#
#-----------------------------------------------------------------
# Generate c_ast.py
#
#from pyuppaal.ulp
import systemdec_parser
# Generates the tables
#
systemdec_parser.SystemDeclarationParser('',
lex_optimize=True,
yacc_debug=False,
yacc_optimize=True)
# Load to compile into .pyc
#
#import lextab
import systemdec_parser_yacctab
| [
37811,
220,
198,
220,
220,
220,
15069,
357,
34,
8,
2813,
198,
220,
220,
220,
4627,
82,
49369,
13,
440,
829,
268,
1279,
76,
354,
305,
31,
6359,
13,
64,
559,
13,
34388,
29,
628,
220,
220,
220,
770,
1430,
318,
1479,
3788,
25,
345,
460,
17678,
4163,
340,
290,
14,
273,
13096,
198,
220,
220,
220,
340,
739,
262,
2846,
286,
262,
22961,
3611,
5094,
13789,
355,
3199,
416,
198,
220,
220,
220,
262,
3232,
10442,
5693,
11,
2035,
2196,
513,
286,
262,
13789,
11,
393,
198,
220,
220,
220,
357,
265,
534,
3038,
8,
597,
1568,
2196,
13,
628,
220,
220,
220,
770,
1430,
318,
9387,
287,
262,
2911,
326,
340,
481,
307,
4465,
11,
198,
220,
220,
220,
475,
42881,
15529,
34764,
56,
26,
1231,
772,
262,
17142,
18215,
286,
198,
220,
220,
220,
34482,
3398,
1565,
5603,
25382,
393,
376,
46144,
7473,
317,
16652,
2149,
37232,
33079,
48933,
13,
220,
4091,
262,
198,
220,
220,
220,
22961,
3611,
5094,
13789,
329,
517,
3307,
13,
628,
220,
220,
220,
921,
815,
423,
2722,
257,
4866,
286,
262,
22961,
3611,
5094,
13789,
198,
220,
220,
220,
1863,
351,
428,
1430,
13,
220,
1002,
407,
11,
766,
1279,
4023,
1378,
2503,
13,
41791,
13,
2398,
14,
677,
4541,
15913,
13,
37227,
198,
198,
2,
10097,
12,
198,
2,
13403,
319,
12972,
13155,
28198,
25,
4808,
11249,
62,
83,
2977,
13,
9078,
11,
15069,
357,
34,
8,
3648,
12,
9804,
11,
25204,
347,
7338,
2584,
198,
2,
198,
2,
317,
31548,
329,
15453,
262,
31191,
278,
14,
79,
945,
278,
8893,
290,
290,
220,
198,
2,
33393,
606,
656,
764,
9078,
66,
329,
5443,
9706,
287,
23392,
4235,
13,
198,
2,
10358,
307,
1444,
422,
262,
9988,
8619,
13,
198,
2,
198,
2,
10097,
12,
198,
198,
2,
2980,
378,
269,
62,
459,
13,
9078,
198,
2,
198,
198,
2,
6738,
12972,
7211,
64,
282,
13,
29528,
220,
198,
11748,
1080,
12501,
62,
48610,
198,
198,
2,
2980,
689,
262,
8893,
198,
2,
198,
10057,
12501,
62,
48610,
13,
11964,
37835,
10186,
46677,
10786,
3256,
198,
220,
220,
220,
31191,
62,
40085,
1096,
28,
17821,
11,
220,
198,
220,
220,
220,
331,
4134,
62,
24442,
28,
25101,
11,
220,
198,
220,
220,
220,
331,
4134,
62,
40085,
1096,
28,
17821,
8,
198,
198,
2,
8778,
284,
17632,
656,
764,
9078,
66,
198,
2,
198,
2,
11748,
443,
742,
397,
198,
11748,
1080,
12501,
62,
48610,
62,
88,
330,
310,
397,
198
] | 3.428224 | 411 |
from org.nsclient4j import NSClient4j, NSClient4JException
| [
6738,
8745,
13,
5907,
16366,
19,
73,
1330,
10896,
11792,
19,
73,
11,
10896,
11792,
19,
41,
16922,
201
] | 3.105263 | 19 |
import string
import random
import time
from flask import Flask, Response
from flask.json import jsonify
app = Flask(__name__)
@app.route('/')
if __name__ == '__main__':
app.run()
| [
11748,
4731,
198,
11748,
4738,
198,
11748,
640,
198,
198,
6738,
42903,
1330,
46947,
11,
18261,
198,
6738,
42903,
13,
17752,
1330,
33918,
1958,
198,
198,
1324,
796,
46947,
7,
834,
3672,
834,
8,
628,
198,
220,
220,
220,
220,
220,
220,
220,
220,
628,
198,
31,
1324,
13,
38629,
10786,
14,
11537,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
598,
13,
5143,
3419,
198
] | 2.716216 | 74 |
from fastapi.testclient import TestClient
from dogapp.app import app
client = TestClient(app) | [
6738,
3049,
15042,
13,
9288,
16366,
1330,
6208,
11792,
198,
198,
6738,
3290,
1324,
13,
1324,
1330,
598,
198,
16366,
796,
6208,
11792,
7,
1324,
8
] | 3.615385 | 26 |
import math
# Import appropriate version of tkinter
try:
import Tkinter as tk
except ImportError:
import tkinter as tk
import numpy as np
import matplotlib as mpl
import matplotlib.backends.backend_tkagg as backend_tkagg
import faraday_numerics
import entry_boxes
import options
if __name__ == '__main__':
main()
| [
11748,
10688,
198,
198,
2,
17267,
5035,
2196,
286,
256,
74,
3849,
198,
28311,
25,
198,
220,
220,
220,
1330,
309,
74,
3849,
355,
256,
74,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1330,
256,
74,
3849,
355,
256,
74,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
355,
285,
489,
198,
11748,
2603,
29487,
8019,
13,
1891,
2412,
13,
1891,
437,
62,
30488,
9460,
355,
30203,
62,
30488,
9460,
198,
11748,
1290,
43593,
62,
77,
6975,
873,
198,
11748,
5726,
62,
29305,
198,
11748,
3689,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.955357 | 112 |
comanda = ""
while comanda != "quit":
comanda = input("> ").lower()
if comanda == "start":
print("Masina a pornit")
elif comanda == "stop":
print("Masina sa oprit")
elif comanda == "help":
print('''
Start - Masina porneste
Stop - Masina se opreste
quit - A iesi
''')
else:
print('Nu intaleg asta')
| [
785,
5282,
796,
13538,
198,
4514,
401,
5282,
14512,
366,
47391,
1298,
198,
220,
220,
401,
5282,
796,
5128,
7,
5320,
366,
737,
21037,
3419,
198,
220,
220,
611,
401,
5282,
6624,
366,
9688,
1298,
198,
220,
220,
220,
220,
220,
220,
3601,
7203,
38224,
1437,
257,
8483,
270,
4943,
198,
220,
220,
1288,
361,
401,
5282,
6624,
366,
11338,
1298,
198,
220,
220,
220,
220,
220,
220,
3601,
7203,
38224,
1437,
473,
1034,
799,
4943,
198,
220,
220,
1288,
361,
401,
5282,
6624,
366,
16794,
1298,
198,
220,
220,
220,
220,
220,
220,
3601,
7,
7061,
6,
220,
198,
220,
220,
220,
220,
220,
220,
7253,
532,
11066,
1437,
8483,
29872,
198,
220,
220,
220,
220,
220,
220,
13707,
532,
11066,
1437,
384,
1034,
2118,
68,
198,
220,
220,
220,
220,
220,
220,
11238,
532,
317,
220,
444,
72,
198,
220,
220,
220,
220,
220,
220,
705,
7061,
8,
198,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
3601,
10786,
45,
84,
493,
1000,
70,
6468,
64,
11537,
628,
198
] | 2.137931 | 174 |
# -*- coding: utf-8 -*-
# global import
from xlwt import *
# local import
# global vars
header_names = [
u"影片名称",
u"片长",
u"语言",
u"开映时间",
u"结束时间",
u"场间",
]
## HEADER STYLE
header_pat = Pattern()
header_pat.pattern = header_pat.SOLID_PATTERN
header_pat.pattern_fore_colour = 1
header_pat.pattern_back_colour = 1
# header alignment
header_align = Alignment()
header_align.horz = header_align.HORZ_CENTER
header_align.vert = header_align.VERT_CENTER
# header border
header_border = Borders()
header_border.top = header_border.MEDIUM
header_border.left = header_border.MEDIUM
header_border.right = header_border.MEDIUM
header_border.bottom = header_border.MEDIUM
header_style = XFStyle()
header_style.pattern = header_pat
header_style.alignment = header_align
header_style.borders = header_border
## LEFT STYLE
left_border = Borders()
left_border.left = left_border.MEDIUM
left_style = XFStyle()
left_style.borders = left_border
## RIGHT STYLE
right_border = Borders()
right_border.right = right_border.MEDIUM
right_style = XFStyle()
right_style.borders = right_border
## BOTTOM LEFT STYLE
bottom_border = Borders()
bottom_border.left = bottom_border.MEDIUM
bottom_border.bottom = bottom_border.MEDIUM
bottolleft_style = XFStyle()
bottolleft_style.borders = bottom_border
## BOTTOM RIGHT STYLE
bottom_border = Borders()
bottom_border.right = bottom_border.MEDIUM
bottom_border.bottom = bottom_border.MEDIUM
bottomright_style = XFStyle()
bottomright_style.borders = bottom_border
## BOTTOM CENTER STYLE
bottom_border = Borders()
bottom_border.bottom = bottom_border.MEDIUM
bottomcenter_style = XFStyle()
bottomcenter_style.borders = bottom_border
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
2,
3298,
1330,
198,
6738,
2124,
75,
46569,
1330,
1635,
198,
198,
2,
1957,
1330,
198,
198,
2,
3298,
410,
945,
198,
25677,
62,
14933,
796,
685,
198,
220,
220,
220,
334,
1,
37605,
109,
31965,
229,
28938,
235,
163,
100,
108,
1600,
198,
220,
220,
220,
334,
1,
31965,
229,
165,
243,
123,
1600,
198,
220,
220,
220,
334,
1,
46237,
255,
164,
101,
222,
1600,
198,
220,
220,
220,
334,
1,
28156,
222,
23626,
254,
33768,
114,
29785,
112,
1600,
198,
220,
220,
220,
334,
1,
163,
119,
241,
30266,
253,
33768,
114,
29785,
112,
1600,
198,
220,
220,
220,
334,
1,
28839,
118,
29785,
112,
1600,
198,
60,
628,
198,
2235,
39837,
1137,
3563,
56,
2538,
198,
25677,
62,
8071,
796,
23939,
3419,
198,
25677,
62,
8071,
13,
33279,
796,
13639,
62,
8071,
13,
50,
3535,
2389,
62,
47,
1404,
31800,
198,
25677,
62,
8071,
13,
33279,
62,
754,
62,
49903,
796,
352,
198,
25677,
62,
8071,
13,
33279,
62,
1891,
62,
49903,
796,
352,
198,
2,
13639,
19114,
198,
25677,
62,
31494,
796,
978,
16747,
3419,
198,
25677,
62,
31494,
13,
17899,
89,
796,
13639,
62,
31494,
13,
39,
1581,
57,
62,
43960,
1137,
198,
25677,
62,
31494,
13,
1851,
796,
13639,
62,
31494,
13,
15858,
62,
43960,
1137,
198,
2,
13639,
4865,
198,
25677,
62,
20192,
796,
40934,
3419,
198,
25677,
62,
20192,
13,
4852,
796,
13639,
62,
20192,
13,
30733,
41796,
198,
25677,
62,
20192,
13,
9464,
796,
13639,
62,
20192,
13,
30733,
41796,
198,
25677,
62,
20192,
13,
3506,
796,
13639,
62,
20192,
13,
30733,
41796,
198,
25677,
62,
20192,
13,
22487,
796,
13639,
62,
20192,
13,
30733,
41796,
198,
25677,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
25677,
62,
7635,
13,
33279,
796,
13639,
62,
8071,
198,
25677,
62,
7635,
13,
282,
16747,
796,
13639,
62,
31494,
198,
25677,
62,
7635,
13,
65,
6361,
796,
13639,
62,
20192,
198,
198,
2235,
12509,
9792,
3563,
56,
2538,
198,
9464,
62,
20192,
796,
40934,
3419,
198,
9464,
62,
20192,
13,
9464,
796,
1364,
62,
20192,
13,
30733,
41796,
198,
9464,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
9464,
62,
7635,
13,
65,
6361,
796,
1364,
62,
20192,
198,
198,
2235,
33621,
3563,
56,
2538,
198,
3506,
62,
20192,
796,
40934,
3419,
198,
3506,
62,
20192,
13,
3506,
796,
826,
62,
20192,
13,
30733,
41796,
198,
3506,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
3506,
62,
7635,
13,
65,
6361,
796,
826,
62,
20192,
198,
198,
2235,
347,
29089,
2662,
12509,
9792,
3563,
56,
2538,
198,
22487,
62,
20192,
796,
40934,
3419,
198,
22487,
62,
20192,
13,
9464,
796,
4220,
62,
20192,
13,
30733,
41796,
198,
22487,
62,
20192,
13,
22487,
796,
4220,
62,
20192,
13,
30733,
41796,
198,
10985,
349,
9464,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
10985,
349,
9464,
62,
7635,
13,
65,
6361,
796,
4220,
62,
20192,
198,
198,
2235,
347,
29089,
2662,
33621,
3563,
56,
2538,
198,
22487,
62,
20192,
796,
40934,
3419,
198,
22487,
62,
20192,
13,
3506,
796,
4220,
62,
20192,
13,
30733,
41796,
198,
22487,
62,
20192,
13,
22487,
796,
4220,
62,
20192,
13,
30733,
41796,
198,
22487,
3506,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
22487,
3506,
62,
7635,
13,
65,
6361,
796,
4220,
62,
20192,
198,
2235,
347,
29089,
2662,
33269,
1137,
3563,
56,
2538,
198,
22487,
62,
20192,
796,
40934,
3419,
198,
22487,
62,
20192,
13,
22487,
796,
4220,
62,
20192,
13,
30733,
41796,
198,
22487,
16159,
62,
7635,
796,
1395,
10652,
774,
293,
3419,
198,
22487,
16159,
62,
7635,
13,
65,
6361,
796,
4220,
62,
20192,
198
] | 2.704362 | 619 |
import _dk_core as core
# interpolation type
CATMULL_ROM = 0
UNIFORM_CUBIC = 1
HERMITE = 2
BEZIER = 3
Spline = core.Spline
class Spline2:
'''spline for Vector2'''
class Spline3:
'''spline for Vector3'''
class Spline4:
'''spline for Vector4'''
| [
11748,
4808,
34388,
62,
7295,
355,
4755,
198,
198,
2,
39555,
341,
2099,
198,
34,
1404,
44,
9994,
62,
33676,
796,
657,
198,
4944,
5064,
1581,
44,
62,
34,
10526,
2149,
796,
352,
198,
16879,
44,
12709,
796,
362,
198,
12473,
57,
38311,
796,
513,
628,
198,
26568,
500,
796,
4755,
13,
26568,
500,
198,
198,
4871,
13341,
500,
17,
25,
198,
220,
220,
220,
705,
7061,
22018,
500,
329,
20650,
17,
7061,
6,
198,
198,
4871,
13341,
500,
18,
25,
198,
220,
220,
220,
705,
7061,
22018,
500,
329,
20650,
18,
7061,
6,
198,
198,
4871,
13341,
500,
19,
25,
198,
220,
220,
220,
705,
7061,
22018,
500,
329,
20650,
19,
7061,
6,
628
] | 2.278261 | 115 |
# Lint as: python3
"""LIT wrappers for T5, supporting both HuggingFace and SavedModel formats."""
import re
from typing import List
import attr
from lit_nlp.api import model as lit_model
from lit_nlp.api import types as lit_types
from lit_nlp.examples.models import model_utils
from lit_nlp.lib import utils
import tensorflow as tf
# tensorflow_text is required for T5 SavedModel
import tensorflow_text # pylint: disable=unused-import
import transformers
from rouge_score import rouge_scorer
JsonDict = lit_types.JsonDict
def masked_token_mean(vectors, masks):
"""Mean over tokens.
Args:
vectors: <tf.float32>[batch_size, num_tokens, emb_dim]
masks: <tf.int32>[batch_size, num_tokens]
Returns:
<tf.float32>[batch_size, emb_dim]
"""
masks = tf.cast(masks, tf.float32)
weights = masks / tf.reduce_sum(masks, axis=1, keepdims=True)
return tf.reduce_sum(vectors * tf.expand_dims(weights, axis=-1), axis=1)
@attr.s(auto_attribs=True, kw_only=True)
class T5ModelConfig(object):
"""Config options for a T5 generation model."""
# Input options
inference_batch_size: int = 4
# Generation options
beam_size: int = 4
max_gen_length: int = 50
num_to_generate: int = 1
# Decoding options
token_top_k: int = 10
output_attention: bool = False
def validate_t5_model(model: lit_model.Model) -> lit_model.Model:
"""Validate that a given model looks like a T5 model.
This checks the model spec at runtime; it is intended to be used before server
start, such as in the __init__() method of a wrapper class.
Args:
model: a LIT model
Returns:
model: the same model
Raises:
AssertionError: if the model's spec does not match that expected for a T5
model.
"""
# Check inputs
ispec = model.input_spec()
assert "input_text" in ispec
assert isinstance(ispec["input_text"], lit_types.TextSegment)
if "target_text" in ispec:
assert isinstance(ispec["target_text"], lit_types.TextSegment)
# Check outputs
ospec = model.output_spec()
assert "output_text" in ospec
assert isinstance(
ospec["output_text"],
(lit_types.GeneratedText, lit_types.GeneratedTextCandidates))
assert ospec["output_text"].parent == "target_text"
return model
class T5SavedModel(lit_model.Model):
"""T5 from a TensorFlow SavedModel, for black-box access.
To create a SavedModel from a regular T5 checkpoint, see
https://github.com/google-research/text-to-text-transfer-transformer#export
"""
##
# LIT API implementations
def predict_minibatch(self, inputs):
"""Predict on a single minibatch of examples."""
model_inputs = tf.constant([ex["input_text"] for ex in inputs])
model_outputs = self.model.signatures["serving_default"](model_inputs)
return [{
"output_text": m.decode("utf-8")
} for m in model_outputs["outputs"].numpy()]
class T5HFModel(lit_model.Model):
"""T5 using HuggingFace Transformers and Keras.
This version supports embeddings, attention, and force-decoding of the target
text, as well as more options to control decoding (such as beam search).
"""
@property
def _force_decode(self, encoded_inputs, encoded_targets):
"""Get predictions for a batch of tokenized examples.
Each forward pass produces the following:
logits: batch_size x dec_len x vocab_size
decoder_past_key_value_states: tuple with cached outputs.
dec_states: tuple[len:dec_layers]:
batch_size x dec_len x hid_size
dec_attn: [optional] tuple[len:dec_layers+1]
batch_size x num_heads x dec_len x dec_len
enc_final_state: batch_size x enc_len x hid_size
enc_states: tuple[len:enc_layers]:
batch_size x enc_len x hid_size
enc_attn: [optional] tuple[len:enc_layers+1]
batch_size x num_heads x enc_len x enc_len
The two optional attention fields are only returned if
config.output_attention is set.
Args:
encoded_inputs: Dict as returned from Tokenizer for inputs.
encoded_targets: Dict as returned from Tokenizer for outputs
Returns:
batched_outputs: Dict[str, tf.Tensor]
"""
results = self.model(
input_ids=encoded_inputs["input_ids"],
decoder_input_ids=encoded_targets["input_ids"],
attention_mask=encoded_inputs["attention_mask"],
decoder_attention_mask=encoded_targets["attention_mask"])
model_probs = tf.nn.softmax(results.logits, axis=-1)
top_k = tf.math.top_k(
model_probs, k=self.config.token_top_k, sorted=True, name=None)
batched_outputs = {
"input_ids": encoded_inputs["input_ids"],
"input_ntok": tf.reduce_sum(encoded_inputs["attention_mask"], axis=1),
"target_ids": encoded_targets["input_ids"],
"target_ntok": tf.reduce_sum(encoded_targets["attention_mask"], axis=1),
"top_k_indices": top_k.indices,
"top_k_probs": top_k.values,
}
# encoder_last_hidden_state is <float>[batch_size, num_tokens, emb_dim]
# take the mean over real tokens to get <float>[batch_size, emb_dim]
batched_outputs["encoder_final_embedding"] = masked_token_mean(
results.encoder_last_hidden_state, encoded_inputs["attention_mask"])
if self.config.output_attention:
for i in range(len(results.decoder_attentions)):
batched_outputs[
f"decoder_layer_{i+1:d}_attention"] = results.decoder_attentions[i]
for i in range(len(results.encoder_attentions)):
batched_outputs[
f"encoder_layer_{i+1:d}_attention"] = results.encoder_attentions[i]
return batched_outputs
def _postprocess(self, preds):
"""Post-process single-example preds. Operates on numpy arrays."""
# Return tokenization for input text.
input_ntok = preds.pop("input_ntok")
input_ids = preds.pop("input_ids")[:input_ntok]
preds["input_tokens"] = self.tokenizer.convert_ids_to_tokens(input_ids)
# Return tokenization for target text.
target_ntok = preds.pop("target_ntok")
target_ids = preds.pop("target_ids")[:target_ntok]
preds["target_tokens"] = self.tokenizer.convert_ids_to_tokens(target_ids)
# Decode predicted top-k tokens.
# token_topk_preds will be a List[List[(word, prob)]]
# Initialize prediction for 0th token as N/A.
token_topk_preds = [[("N/A", 1.)]]
pred_ids = preds.pop("top_k_indices")[:target_ntok] # <int>[num_tokens, k]
pred_probs = preds.pop(
"top_k_probs")[:target_ntok] # <float32>[num_tokens, k]
for token_pred_ids, token_pred_probs in zip(pred_ids, pred_probs):
token_pred_words = self.tokenizer.convert_ids_to_tokens(token_pred_ids)
token_topk_preds.append(list(zip(token_pred_words, token_pred_probs)))
preds["pred_tokens"] = token_topk_preds
# Decode generated ids
candidates = [
self.tokenizer.decode(ids, skip_special_tokens=True)
for ids in preds.pop("generated_ids")
]
if self.config.num_to_generate > 1:
preds["output_text"] = [(s, None) for s in candidates]
else:
preds["output_text"] = candidates[0]
# Process attention fields, if present.
for key in preds:
if not re.match(r"\w+_layer_(\d+)/attention", key):
continue
if key.startswith("encoder_"):
ntok = input_ntok
elif key.startswith("decoder_"):
ntok = target_ntok
else:
raise ValueError(f"Invalid attention key: '{key}'")
# Select only real tokens, since most of this matrix is padding.
# <float32>[num_heads, max_seq_length, max_seq_length]
# -> <float32>[num_heads, num_tokens, num_tokens]
preds[key] = preds[key][:, :ntok, :ntok].transpose((0, 2, 1))
# Make a copy of this array to avoid memory leaks, since NumPy otherwise
# keeps a pointer around that prevents the source array from being GCed.
preds[key] = preds[key].copy()
return preds
##
# LIT API implementations
def predict_minibatch(self, inputs):
"""Run model on a single batch.
Args:
inputs: List[Dict] with fields as described by input_spec()
Returns:
outputs: List[Dict] with fields as described by output_spec()
"""
# Text as sequence of sentencepiece ID"s.
encoded_inputs = self._encode_texts([ex["input_text"] for ex in inputs])
encoded_targets = self._encode_texts(
[ex.get("target_text", "") for ex in inputs])
##
# Force-decode on target text, and also get encoder embs and attention.
batched_outputs = self._force_decode(encoded_inputs, encoded_targets)
# Get the conditional generation from the model.
# Workaround for output_hidden not being compatible with generate.
# See https://github.com/huggingface/transformers/issues/8361
self.model.config.output_hidden_states = False
generated_ids = self.model.generate(
encoded_inputs.input_ids,
num_beams=self.config.beam_size,
attention_mask=encoded_inputs.attention_mask,
max_length=self.config.max_gen_length,
num_return_sequences=self.config.num_to_generate)
# [batch_size*num_return_sequences, num_steps]
# -> [batch_size, num_return_sequences, num_steps]
batched_outputs["generated_ids"] = tf.reshape(
generated_ids,
[-1, self.config.num_to_generate, generated_ids.shape[-1]])
self.model.config.output_hidden_states = True
# Convert to numpy for post-processing.
detached_outputs = {k: v.numpy() for k, v in batched_outputs.items()}
# Split up batched outputs, then post-process each example.
unbatched_outputs = utils.unbatch_preds(detached_outputs)
return list(map(self._postprocess, unbatched_outputs))
##
# Task-specific wrapper classes.
class TranslationWrapper(lit_model.ModelWrapper):
"""Wrapper class for machine translation."""
# Mapping from generic T5 fields to this task
FIELD_RENAMES = {
"input_text": "source",
"target_text": "target",
"output_text": "translation",
}
# From Appendix D of https://arxiv.org/pdf/1910.10683.pdf.
# Add more of these if your model supports them.
LANGCODE_TO_NAME = {
"en": "English",
"de": "German",
"fr": "French",
"ro": "Romanian",
}
INPUT_TEMPLATE = "translate {source_language} to {target_language}: {source}"
##
# LIT API implementation
# TODO(b/170662608): remove these after batching API is cleaned up.
def predict(self, inputs):
"""Predict on a single minibatch of examples."""
model_inputs = (self.preprocess(ex) for ex in inputs)
outputs = self.wrapped.predict(model_inputs)
return (utils.remap_dict(mo, self.FIELD_RENAMES) for mo in outputs)
def predict_with_metadata(self, indexed_inputs):
"""As predict(), but inputs are IndexedInput."""
return self.predict((ex["data"] for ex in indexed_inputs))
class SummarizationWrapper(lit_model.ModelWrapper):
"""Wrapper class to perform a summarization task."""
# Mapping from generic T5 fields to this task
FIELD_RENAMES = {
"input_text": "document",
"target_text": "reference",
}
##
# LIT API implementation
# TODO(b/170662608): remove these after batching API is cleaned up.
def predict(self, inputs):
"""Predict on a single minibatch of examples."""
inputs = list(inputs) # needs to be referenced below, so keep full list
model_inputs = (self.preprocess(ex) for ex in inputs)
outputs = self.wrapped.predict(model_inputs)
outputs = (utils.remap_dict(mo, self.FIELD_RENAMES) for mo in outputs)
# TODO(gehrmann): temp solution to get ROUGE scores in data table.
for ex, mo in zip(inputs, outputs):
score = self._scorer.score(
target=ex["reference"],
prediction=self._get_pred_string(mo["output_text"]))
mo["rougeL"] = float(score["rougeL"].fmeasure)
yield mo
def predict_with_metadata(self, indexed_inputs):
"""As predict(), but inputs are IndexedInput."""
return self.predict((ex["data"] for ex in indexed_inputs))
| [
2,
406,
600,
355,
25,
21015,
18,
198,
37811,
43,
2043,
7917,
11799,
329,
309,
20,
11,
6493,
1111,
12905,
2667,
32388,
290,
8858,
276,
17633,
17519,
526,
15931,
198,
11748,
302,
198,
6738,
19720,
1330,
7343,
198,
198,
11748,
708,
81,
198,
6738,
6578,
62,
21283,
79,
13,
15042,
1330,
2746,
355,
6578,
62,
19849,
198,
6738,
6578,
62,
21283,
79,
13,
15042,
1330,
3858,
355,
6578,
62,
19199,
198,
6738,
6578,
62,
21283,
79,
13,
1069,
12629,
13,
27530,
1330,
2746,
62,
26791,
198,
6738,
6578,
62,
21283,
79,
13,
8019,
1330,
3384,
4487,
198,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
2,
11192,
273,
11125,
62,
5239,
318,
2672,
329,
309,
20,
8858,
276,
17633,
198,
11748,
11192,
273,
11125,
62,
5239,
220,
1303,
279,
2645,
600,
25,
15560,
28,
403,
1484,
12,
11748,
198,
11748,
6121,
364,
198,
198,
6738,
13805,
469,
62,
26675,
1330,
13805,
469,
62,
1416,
11934,
198,
198,
41,
1559,
35,
713,
796,
6578,
62,
19199,
13,
41,
1559,
35,
713,
628,
198,
4299,
29229,
62,
30001,
62,
32604,
7,
303,
5217,
11,
20680,
2599,
198,
220,
37227,
5308,
272,
625,
16326,
13,
628,
220,
943,
14542,
25,
198,
220,
220,
220,
30104,
25,
1279,
27110,
13,
22468,
2624,
36937,
43501,
62,
7857,
11,
997,
62,
83,
482,
641,
11,
4072,
62,
27740,
60,
198,
220,
220,
220,
20680,
25,
1279,
27110,
13,
600,
2624,
36937,
43501,
62,
7857,
11,
997,
62,
83,
482,
641,
60,
628,
220,
16409,
25,
198,
220,
220,
220,
1279,
27110,
13,
22468,
2624,
36937,
43501,
62,
7857,
11,
4072,
62,
27740,
60,
198,
220,
37227,
198,
220,
20680,
796,
48700,
13,
2701,
7,
5356,
591,
11,
48700,
13,
22468,
2624,
8,
198,
220,
19590,
796,
20680,
1220,
48700,
13,
445,
7234,
62,
16345,
7,
5356,
591,
11,
16488,
28,
16,
11,
1394,
67,
12078,
28,
17821,
8,
198,
220,
1441,
48700,
13,
445,
7234,
62,
16345,
7,
303,
5217,
1635,
48700,
13,
11201,
392,
62,
67,
12078,
7,
43775,
11,
16488,
10779,
16,
828,
16488,
28,
16,
8,
628,
198,
31,
35226,
13,
82,
7,
23736,
62,
1078,
822,
82,
28,
17821,
11,
479,
86,
62,
8807,
28,
17821,
8,
198,
4871,
309,
20,
17633,
16934,
7,
15252,
2599,
198,
220,
37227,
16934,
3689,
329,
257,
309,
20,
5270,
2746,
526,
15931,
198,
220,
1303,
23412,
3689,
198,
220,
32278,
62,
43501,
62,
7857,
25,
493,
796,
604,
198,
220,
1303,
16588,
3689,
198,
220,
15584,
62,
7857,
25,
493,
796,
604,
198,
220,
3509,
62,
5235,
62,
13664,
25,
493,
796,
2026,
198,
220,
997,
62,
1462,
62,
8612,
378,
25,
493,
796,
352,
198,
220,
1303,
4280,
7656,
3689,
198,
220,
11241,
62,
4852,
62,
74,
25,
493,
796,
838,
198,
220,
5072,
62,
1078,
1463,
25,
20512,
796,
10352,
628,
198,
4299,
26571,
62,
83,
20,
62,
19849,
7,
19849,
25,
6578,
62,
19849,
13,
17633,
8,
4613,
6578,
62,
19849,
13,
17633,
25,
198,
220,
37227,
7762,
20540,
326,
257,
1813,
2746,
3073,
588,
257,
309,
20,
2746,
13,
628,
220,
770,
8794,
262,
2746,
1020,
379,
19124,
26,
340,
318,
5292,
284,
307,
973,
878,
4382,
198,
220,
923,
11,
884,
355,
287,
262,
11593,
15003,
834,
3419,
2446,
286,
257,
29908,
1398,
13,
628,
220,
943,
14542,
25,
198,
220,
220,
220,
2746,
25,
257,
406,
2043,
2746,
628,
220,
16409,
25,
198,
220,
220,
220,
2746,
25,
262,
976,
2746,
628,
220,
7567,
2696,
25,
198,
220,
220,
220,
2195,
861,
295,
12331,
25,
611,
262,
2746,
338,
1020,
857,
407,
2872,
326,
2938,
329,
257,
309,
20,
198,
220,
220,
220,
2746,
13,
198,
220,
37227,
198,
220,
1303,
6822,
17311,
198,
220,
318,
43106,
796,
2746,
13,
15414,
62,
16684,
3419,
198,
220,
6818,
366,
15414,
62,
5239,
1,
287,
318,
43106,
198,
220,
6818,
318,
39098,
7,
271,
43106,
14692,
15414,
62,
5239,
33116,
6578,
62,
19199,
13,
8206,
41030,
434,
8,
198,
220,
611,
366,
16793,
62,
5239,
1,
287,
318,
43106,
25,
198,
220,
220,
220,
6818,
318,
39098,
7,
271,
43106,
14692,
16793,
62,
5239,
33116,
6578,
62,
19199,
13,
8206,
41030,
434,
8,
628,
220,
1303,
6822,
23862,
198,
220,
267,
16684,
796,
2746,
13,
22915,
62,
16684,
3419,
198,
220,
6818,
366,
22915,
62,
5239,
1,
287,
267,
16684,
198,
220,
6818,
318,
39098,
7,
198,
220,
220,
220,
220,
220,
267,
16684,
14692,
22915,
62,
5239,
33116,
198,
220,
220,
220,
220,
220,
357,
18250,
62,
19199,
13,
8645,
515,
8206,
11,
6578,
62,
19199,
13,
8645,
515,
8206,
41572,
37051,
4008,
198,
220,
6818,
267,
16684,
14692,
22915,
62,
5239,
1,
4083,
8000,
6624,
366,
16793,
62,
5239,
1,
628,
220,
1441,
2746,
628,
198,
4871,
309,
20,
50,
9586,
17633,
7,
18250,
62,
19849,
13,
17633,
2599,
198,
220,
37227,
51,
20,
422,
257,
309,
22854,
37535,
8858,
276,
17633,
11,
329,
2042,
12,
3524,
1895,
13,
628,
220,
1675,
2251,
257,
8858,
276,
17633,
422,
257,
3218,
309,
20,
26954,
11,
766,
198,
220,
3740,
1378,
12567,
13,
785,
14,
13297,
12,
34033,
14,
5239,
12,
1462,
12,
5239,
12,
39437,
12,
7645,
16354,
2,
39344,
198,
220,
37227,
628,
220,
22492,
198,
220,
1303,
406,
2043,
7824,
25504,
628,
220,
825,
4331,
62,
1084,
571,
963,
7,
944,
11,
17311,
2599,
198,
220,
220,
220,
37227,
47,
17407,
319,
257,
2060,
949,
571,
963,
286,
6096,
526,
15931,
198,
220,
220,
220,
2746,
62,
15414,
82,
796,
48700,
13,
9979,
415,
26933,
1069,
14692,
15414,
62,
5239,
8973,
329,
409,
287,
17311,
12962,
198,
220,
220,
220,
2746,
62,
22915,
82,
796,
2116,
13,
19849,
13,
12683,
6691,
14692,
31293,
62,
12286,
8973,
7,
19849,
62,
15414,
82,
8,
198,
220,
220,
220,
1441,
685,
90,
198,
220,
220,
220,
220,
220,
220,
220,
366,
22915,
62,
5239,
1298,
285,
13,
12501,
1098,
7203,
40477,
12,
23,
4943,
198,
220,
220,
220,
1782,
329,
285,
287,
2746,
62,
22915,
82,
14692,
22915,
82,
1,
4083,
77,
32152,
3419,
60,
628,
198,
4871,
309,
20,
29567,
17633,
7,
18250,
62,
19849,
13,
17633,
2599,
198,
220,
37227,
51,
20,
1262,
12905,
2667,
32388,
39185,
290,
17337,
292,
13,
628,
220,
770,
2196,
6971,
11525,
67,
654,
11,
3241,
11,
290,
2700,
12,
12501,
7656,
286,
262,
2496,
198,
220,
2420,
11,
355,
880,
355,
517,
3689,
284,
1630,
39938,
357,
10508,
355,
15584,
2989,
737,
198,
220,
37227,
628,
220,
2488,
26745,
628,
220,
825,
4808,
3174,
62,
12501,
1098,
7,
944,
11,
30240,
62,
15414,
82,
11,
30240,
62,
83,
853,
1039,
2599,
198,
220,
220,
220,
37227,
3855,
16277,
329,
257,
15458,
286,
11241,
1143,
6096,
13,
628,
220,
220,
220,
5501,
2651,
1208,
11073,
262,
1708,
25,
198,
220,
220,
220,
220,
220,
2604,
896,
25,
15458,
62,
7857,
2124,
875,
62,
11925,
2124,
12776,
397,
62,
7857,
198,
220,
220,
220,
220,
220,
875,
12342,
62,
30119,
62,
2539,
62,
8367,
62,
27219,
25,
46545,
351,
39986,
23862,
13,
198,
220,
220,
220,
220,
220,
875,
62,
27219,
25,
46545,
58,
11925,
25,
12501,
62,
75,
6962,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15458,
62,
7857,
2124,
875,
62,
11925,
2124,
24519,
62,
7857,
198,
220,
220,
220,
220,
220,
875,
62,
1078,
77,
25,
685,
25968,
60,
46545,
58,
11925,
25,
12501,
62,
75,
6962,
10,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15458,
62,
7857,
2124,
997,
62,
16600,
2124,
875,
62,
11925,
2124,
875,
62,
11925,
198,
220,
220,
220,
220,
220,
2207,
62,
20311,
62,
5219,
25,
15458,
62,
7857,
2124,
2207,
62,
11925,
2124,
24519,
62,
7857,
198,
220,
220,
220,
220,
220,
2207,
62,
27219,
25,
46545,
58,
11925,
25,
12685,
62,
75,
6962,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15458,
62,
7857,
2124,
2207,
62,
11925,
2124,
24519,
62,
7857,
198,
220,
220,
220,
220,
220,
2207,
62,
1078,
77,
25,
685,
25968,
60,
46545,
58,
11925,
25,
12685,
62,
75,
6962,
10,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15458,
62,
7857,
2124,
997,
62,
16600,
2124,
2207,
62,
11925,
2124,
2207,
62,
11925,
628,
220,
220,
220,
383,
734,
11902,
3241,
7032,
389,
691,
4504,
611,
198,
220,
220,
220,
4566,
13,
22915,
62,
1078,
1463,
318,
900,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
30240,
62,
15414,
82,
25,
360,
713,
355,
4504,
422,
29130,
7509,
329,
17311,
13,
198,
220,
220,
220,
220,
220,
30240,
62,
83,
853,
1039,
25,
360,
713,
355,
4504,
422,
29130,
7509,
329,
23862,
628,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
7365,
1740,
62,
22915,
82,
25,
360,
713,
58,
2536,
11,
48700,
13,
51,
22854,
60,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2482,
796,
2116,
13,
19849,
7,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
2340,
28,
12685,
9043,
62,
15414,
82,
14692,
15414,
62,
2340,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
875,
12342,
62,
15414,
62,
2340,
28,
12685,
9043,
62,
83,
853,
1039,
14692,
15414,
62,
2340,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
3241,
62,
27932,
28,
12685,
9043,
62,
15414,
82,
14692,
1078,
1463,
62,
27932,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
875,
12342,
62,
1078,
1463,
62,
27932,
28,
12685,
9043,
62,
83,
853,
1039,
14692,
1078,
1463,
62,
27932,
8973,
8,
628,
220,
220,
220,
2746,
62,
1676,
1443,
796,
48700,
13,
20471,
13,
4215,
9806,
7,
43420,
13,
6404,
896,
11,
16488,
10779,
16,
8,
198,
220,
220,
220,
1353,
62,
74,
796,
48700,
13,
11018,
13,
4852,
62,
74,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2746,
62,
1676,
1443,
11,
479,
28,
944,
13,
11250,
13,
30001,
62,
4852,
62,
74,
11,
23243,
28,
17821,
11,
1438,
28,
14202,
8,
198,
220,
220,
220,
7365,
1740,
62,
22915,
82,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
366,
15414,
62,
2340,
1298,
30240,
62,
15414,
82,
14692,
15414,
62,
2340,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
366,
15414,
62,
429,
482,
1298,
48700,
13,
445,
7234,
62,
16345,
7,
12685,
9043,
62,
15414,
82,
14692,
1078,
1463,
62,
27932,
33116,
16488,
28,
16,
828,
198,
220,
220,
220,
220,
220,
220,
220,
366,
16793,
62,
2340,
1298,
30240,
62,
83,
853,
1039,
14692,
15414,
62,
2340,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
366,
16793,
62,
429,
482,
1298,
48700,
13,
445,
7234,
62,
16345,
7,
12685,
9043,
62,
83,
853,
1039,
14692,
1078,
1463,
62,
27932,
33116,
16488,
28,
16,
828,
198,
220,
220,
220,
220,
220,
220,
220,
366,
4852,
62,
74,
62,
521,
1063,
1298,
1353,
62,
74,
13,
521,
1063,
11,
198,
220,
220,
220,
220,
220,
220,
220,
366,
4852,
62,
74,
62,
1676,
1443,
1298,
1353,
62,
74,
13,
27160,
11,
198,
220,
220,
220,
1782,
198,
220,
220,
220,
1303,
2207,
12342,
62,
12957,
62,
30342,
62,
5219,
318,
1279,
22468,
36937,
43501,
62,
7857,
11,
997,
62,
83,
482,
641,
11,
4072,
62,
27740,
60,
198,
220,
220,
220,
1303,
1011,
262,
1612,
625,
1103,
16326,
284,
651,
1279,
22468,
36937,
43501,
62,
7857,
11,
4072,
62,
27740,
60,
198,
220,
220,
220,
7365,
1740,
62,
22915,
82,
14692,
12685,
12342,
62,
20311,
62,
20521,
12083,
8973,
796,
29229,
62,
30001,
62,
32604,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2482,
13,
12685,
12342,
62,
12957,
62,
30342,
62,
5219,
11,
30240,
62,
15414,
82,
14692,
1078,
1463,
62,
27932,
8973,
8,
628,
220,
220,
220,
611,
2116,
13,
11250,
13,
22915,
62,
1078,
1463,
25,
198,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
11925,
7,
43420,
13,
12501,
12342,
62,
1078,
298,
507,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
7365,
1740,
62,
22915,
82,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
1,
12501,
12342,
62,
29289,
23330,
72,
10,
16,
25,
67,
92,
62,
1078,
1463,
8973,
796,
2482,
13,
12501,
12342,
62,
1078,
298,
507,
58,
72,
60,
198,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
11925,
7,
43420,
13,
12685,
12342,
62,
1078,
298,
507,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
7365,
1740,
62,
22915,
82,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
1,
12685,
12342,
62,
29289,
23330,
72,
10,
16,
25,
67,
92,
62,
1078,
1463,
8973,
796,
2482,
13,
12685,
12342,
62,
1078,
298,
507,
58,
72,
60,
628,
220,
220,
220,
1441,
7365,
1740,
62,
22915,
82,
628,
220,
825,
4808,
7353,
14681,
7,
944,
11,
2747,
82,
2599,
198,
220,
220,
220,
37227,
6307,
12,
14681,
2060,
12,
20688,
2747,
82,
13,
6564,
689,
319,
299,
32152,
26515,
526,
15931,
198,
220,
220,
220,
1303,
8229,
11241,
1634,
329,
5128,
2420,
13,
198,
220,
220,
220,
5128,
62,
429,
482,
796,
2747,
82,
13,
12924,
7203,
15414,
62,
429,
482,
4943,
198,
220,
220,
220,
5128,
62,
2340,
796,
2747,
82,
13,
12924,
7203,
15414,
62,
2340,
4943,
58,
25,
15414,
62,
429,
482,
60,
198,
220,
220,
220,
2747,
82,
14692,
15414,
62,
83,
482,
641,
8973,
796,
2116,
13,
30001,
7509,
13,
1102,
1851,
62,
2340,
62,
1462,
62,
83,
482,
641,
7,
15414,
62,
2340,
8,
198,
220,
220,
220,
1303,
8229,
11241,
1634,
329,
2496,
2420,
13,
198,
220,
220,
220,
2496,
62,
429,
482,
796,
2747,
82,
13,
12924,
7203,
16793,
62,
429,
482,
4943,
198,
220,
220,
220,
2496,
62,
2340,
796,
2747,
82,
13,
12924,
7203,
16793,
62,
2340,
4943,
58,
25,
16793,
62,
429,
482,
60,
198,
220,
220,
220,
2747,
82,
14692,
16793,
62,
83,
482,
641,
8973,
796,
2116,
13,
30001,
7509,
13,
1102,
1851,
62,
2340,
62,
1462,
62,
83,
482,
641,
7,
16793,
62,
2340,
8,
628,
220,
220,
220,
1303,
4280,
1098,
11001,
1353,
12,
74,
16326,
13,
198,
220,
220,
220,
1303,
11241,
62,
4852,
74,
62,
28764,
82,
481,
307,
257,
7343,
58,
8053,
58,
7,
4775,
11,
1861,
8,
11907,
198,
220,
220,
220,
1303,
20768,
1096,
17724,
329,
657,
400,
11241,
355,
399,
14,
32,
13,
198,
220,
220,
220,
11241,
62,
4852,
74,
62,
28764,
82,
796,
16410,
7203,
45,
14,
32,
1600,
352,
2014,
11907,
198,
220,
220,
220,
2747,
62,
2340,
796,
2747,
82,
13,
12924,
7203,
4852,
62,
74,
62,
521,
1063,
4943,
58,
25,
16793,
62,
429,
482,
60,
220,
1303,
1279,
600,
36937,
22510,
62,
83,
482,
641,
11,
479,
60,
198,
220,
220,
220,
2747,
62,
1676,
1443,
796,
2747,
82,
13,
12924,
7,
198,
220,
220,
220,
220,
220,
220,
220,
366,
4852,
62,
74,
62,
1676,
1443,
4943,
58,
25,
16793,
62,
429,
482,
60,
220,
1303,
1279,
22468,
2624,
36937,
22510,
62,
83,
482,
641,
11,
479,
60,
198,
220,
220,
220,
329,
11241,
62,
28764,
62,
2340,
11,
11241,
62,
28764,
62,
1676,
1443,
287,
19974,
7,
28764,
62,
2340,
11,
2747,
62,
1676,
1443,
2599,
198,
220,
220,
220,
220,
220,
11241,
62,
28764,
62,
10879,
796,
2116,
13,
30001,
7509,
13,
1102,
1851,
62,
2340,
62,
1462,
62,
83,
482,
641,
7,
30001,
62,
28764,
62,
2340,
8,
198,
220,
220,
220,
220,
220,
11241,
62,
4852,
74,
62,
28764,
82,
13,
33295,
7,
4868,
7,
13344,
7,
30001,
62,
28764,
62,
10879,
11,
11241,
62,
28764,
62,
1676,
1443,
22305,
198,
220,
220,
220,
2747,
82,
14692,
28764,
62,
83,
482,
641,
8973,
796,
11241,
62,
4852,
74,
62,
28764,
82,
628,
220,
220,
220,
1303,
4280,
1098,
7560,
220,
2340,
198,
220,
220,
220,
5871,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30001,
7509,
13,
12501,
1098,
7,
2340,
11,
14267,
62,
20887,
62,
83,
482,
641,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
220,
2340,
287,
2747,
82,
13,
12924,
7203,
27568,
62,
2340,
4943,
198,
220,
220,
220,
2361,
198,
220,
220,
220,
611,
2116,
13,
11250,
13,
22510,
62,
1462,
62,
8612,
378,
1875,
352,
25,
198,
220,
220,
220,
220,
220,
2747,
82,
14692,
22915,
62,
5239,
8973,
796,
47527,
82,
11,
6045,
8,
329,
264,
287,
5871,
60,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
2747,
82,
14692,
22915,
62,
5239,
8973,
796,
5871,
58,
15,
60,
628,
220,
220,
220,
1303,
10854,
3241,
7032,
11,
611,
1944,
13,
198,
220,
220,
220,
329,
1994,
287,
2747,
82,
25,
198,
220,
220,
220,
220,
220,
611,
407,
302,
13,
15699,
7,
81,
1,
59,
86,
10,
62,
29289,
62,
38016,
67,
10,
20679,
1078,
1463,
1600,
1994,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
611,
1994,
13,
9688,
2032,
342,
7203,
12685,
12342,
62,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
299,
83,
482,
796,
5128,
62,
429,
482,
198,
220,
220,
220,
220,
220,
1288,
361,
1994,
13,
9688,
2032,
342,
7203,
12501,
12342,
62,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
299,
83,
482,
796,
2496,
62,
429,
482,
198,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7,
69,
1,
44651,
3241,
1994,
25,
705,
90,
2539,
92,
6,
4943,
198,
220,
220,
220,
220,
220,
1303,
9683,
691,
1103,
16326,
11,
1201,
749,
286,
428,
17593,
318,
24511,
13,
198,
220,
220,
220,
220,
220,
1303,
1279,
22468,
2624,
36937,
22510,
62,
16600,
11,
3509,
62,
41068,
62,
13664,
11,
3509,
62,
41068,
62,
13664,
60,
198,
220,
220,
220,
220,
220,
1303,
4613,
1279,
22468,
2624,
36937,
22510,
62,
16600,
11,
997,
62,
83,
482,
641,
11,
997,
62,
83,
482,
641,
60,
198,
220,
220,
220,
220,
220,
2747,
82,
58,
2539,
60,
796,
2747,
82,
58,
2539,
7131,
45299,
1058,
429,
482,
11,
1058,
429,
482,
4083,
7645,
3455,
19510,
15,
11,
362,
11,
352,
4008,
198,
220,
220,
220,
220,
220,
1303,
6889,
257,
4866,
286,
428,
7177,
284,
3368,
4088,
17316,
11,
1201,
31835,
20519,
4306,
198,
220,
220,
220,
220,
220,
1303,
7622,
257,
17562,
1088,
326,
15174,
262,
2723,
7177,
422,
852,
20145,
276,
13,
198,
220,
220,
220,
220,
220,
2747,
82,
58,
2539,
60,
796,
2747,
82,
58,
2539,
4083,
30073,
3419,
628,
220,
220,
220,
1441,
2747,
82,
628,
220,
22492,
198,
220,
1303,
406,
2043,
7824,
25504,
628,
220,
825,
4331,
62,
1084,
571,
963,
7,
944,
11,
17311,
2599,
198,
220,
220,
220,
37227,
10987,
2746,
319,
257,
2060,
15458,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
17311,
25,
7343,
58,
35,
713,
60,
351,
7032,
355,
3417,
416,
5128,
62,
16684,
3419,
628,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
23862,
25,
7343,
58,
35,
713,
60,
351,
7032,
355,
3417,
416,
5072,
62,
16684,
3419,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
8255,
355,
8379,
286,
6827,
12239,
4522,
1,
82,
13,
198,
220,
220,
220,
30240,
62,
15414,
82,
796,
2116,
13557,
268,
8189,
62,
5239,
82,
26933,
1069,
14692,
15414,
62,
5239,
8973,
329,
409,
287,
17311,
12962,
198,
220,
220,
220,
30240,
62,
83,
853,
1039,
796,
2116,
13557,
268,
8189,
62,
5239,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
685,
1069,
13,
1136,
7203,
16793,
62,
5239,
1600,
366,
4943,
329,
409,
287,
17311,
12962,
628,
220,
220,
220,
22492,
198,
220,
220,
220,
1303,
5221,
12,
12501,
1098,
319,
2496,
2420,
11,
290,
635,
651,
2207,
12342,
795,
1443,
290,
3241,
13,
198,
220,
220,
220,
7365,
1740,
62,
22915,
82,
796,
2116,
13557,
3174,
62,
12501,
1098,
7,
12685,
9043,
62,
15414,
82,
11,
30240,
62,
83,
853,
1039,
8,
198,
220,
220,
220,
1303,
3497,
262,
26340,
5270,
422,
262,
2746,
13,
198,
220,
220,
220,
1303,
5521,
14145,
329,
5072,
62,
30342,
407,
852,
11670,
351,
7716,
13,
198,
220,
220,
220,
1303,
4091,
3740,
1378,
12567,
13,
785,
14,
71,
1018,
2667,
2550,
14,
35636,
364,
14,
37165,
14,
23,
35195,
198,
220,
220,
220,
2116,
13,
19849,
13,
11250,
13,
22915,
62,
30342,
62,
27219,
796,
10352,
198,
220,
220,
220,
7560,
62,
2340,
796,
2116,
13,
19849,
13,
8612,
378,
7,
198,
220,
220,
220,
220,
220,
220,
220,
30240,
62,
15414,
82,
13,
15414,
62,
2340,
11,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
1350,
4105,
28,
944,
13,
11250,
13,
40045,
62,
7857,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3241,
62,
27932,
28,
12685,
9043,
62,
15414,
82,
13,
1078,
1463,
62,
27932,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
13664,
28,
944,
13,
11250,
13,
9806,
62,
5235,
62,
13664,
11,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
7783,
62,
3107,
3007,
28,
944,
13,
11250,
13,
22510,
62,
1462,
62,
8612,
378,
8,
198,
220,
220,
220,
1303,
685,
43501,
62,
7857,
9,
22510,
62,
7783,
62,
3107,
3007,
11,
997,
62,
20214,
60,
198,
220,
220,
220,
1303,
4613,
685,
43501,
62,
7857,
11,
997,
62,
7783,
62,
3107,
3007,
11,
997,
62,
20214,
60,
198,
220,
220,
220,
7365,
1740,
62,
22915,
82,
14692,
27568,
62,
2340,
8973,
796,
48700,
13,
3447,
1758,
7,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
62,
2340,
11,
198,
220,
220,
220,
220,
220,
220,
220,
25915,
16,
11,
2116,
13,
11250,
13,
22510,
62,
1462,
62,
8612,
378,
11,
7560,
62,
2340,
13,
43358,
58,
12,
16,
11907,
8,
198,
220,
220,
220,
2116,
13,
19849,
13,
11250,
13,
22915,
62,
30342,
62,
27219,
796,
6407,
628,
220,
220,
220,
1303,
38240,
284,
299,
32152,
329,
1281,
12,
36948,
13,
198,
220,
220,
220,
30795,
62,
22915,
82,
796,
1391,
74,
25,
410,
13,
77,
32152,
3419,
329,
479,
11,
410,
287,
7365,
1740,
62,
22915,
82,
13,
23814,
3419,
92,
198,
220,
220,
220,
1303,
27758,
510,
7365,
1740,
23862,
11,
788,
1281,
12,
14681,
1123,
1672,
13,
198,
220,
220,
220,
555,
8664,
1740,
62,
22915,
82,
796,
3384,
4487,
13,
403,
43501,
62,
28764,
82,
7,
15255,
2317,
62,
22915,
82,
8,
198,
220,
220,
220,
1441,
1351,
7,
8899,
7,
944,
13557,
7353,
14681,
11,
555,
8664,
1740,
62,
22915,
82,
4008,
628,
198,
2235,
198,
2,
15941,
12,
11423,
29908,
6097,
13,
628,
198,
4871,
33322,
36918,
2848,
7,
18250,
62,
19849,
13,
17633,
36918,
2848,
2599,
198,
220,
37227,
36918,
2848,
1398,
329,
4572,
11059,
526,
15931,
628,
220,
1303,
337,
5912,
422,
14276,
309,
20,
7032,
284,
428,
4876,
198,
220,
18930,
24639,
62,
49,
1677,
29559,
796,
1391,
198,
220,
220,
220,
220,
220,
366,
15414,
62,
5239,
1298,
366,
10459,
1600,
198,
220,
220,
220,
220,
220,
366,
16793,
62,
5239,
1298,
366,
16793,
1600,
198,
220,
220,
220,
220,
220,
366,
22915,
62,
5239,
1298,
366,
41519,
1600,
198,
220,
1782,
628,
220,
1303,
3574,
30378,
360,
286,
3740,
1378,
283,
87,
452,
13,
2398,
14,
12315,
14,
1129,
940,
13,
940,
47521,
13,
12315,
13,
198,
220,
1303,
3060,
517,
286,
777,
611,
534,
2746,
6971,
606,
13,
198,
220,
406,
15567,
34,
16820,
62,
10468,
62,
20608,
796,
1391,
198,
220,
220,
220,
220,
220,
366,
268,
1298,
366,
15823,
1600,
198,
220,
220,
220,
220,
220,
366,
2934,
1298,
366,
16010,
1600,
198,
220,
220,
220,
220,
220,
366,
8310,
1298,
366,
24111,
1600,
198,
220,
220,
220,
220,
220,
366,
305,
1298,
366,
32454,
666,
1600,
198,
220,
1782,
628,
220,
3268,
30076,
62,
51,
3620,
6489,
6158,
796,
366,
7645,
17660,
1391,
10459,
62,
16129,
92,
284,
1391,
16793,
62,
16129,
38362,
1391,
10459,
36786,
628,
220,
22492,
198,
220,
1303,
406,
2043,
7824,
7822,
628,
220,
1303,
16926,
46,
7,
65,
14,
17279,
2791,
21719,
23,
2599,
4781,
777,
706,
15458,
278,
7824,
318,
20750,
510,
13,
628,
220,
825,
4331,
7,
944,
11,
17311,
2599,
198,
220,
220,
220,
37227,
47,
17407,
319,
257,
2060,
949,
571,
963,
286,
6096,
526,
15931,
198,
220,
220,
220,
2746,
62,
15414,
82,
796,
357,
944,
13,
3866,
14681,
7,
1069,
8,
329,
409,
287,
17311,
8,
198,
220,
220,
220,
23862,
796,
2116,
13,
29988,
1496,
13,
79,
17407,
7,
19849,
62,
15414,
82,
8,
198,
220,
220,
220,
1441,
357,
26791,
13,
2787,
499,
62,
11600,
7,
5908,
11,
2116,
13,
44603,
62,
49,
1677,
29559,
8,
329,
6941,
287,
23862,
8,
628,
220,
825,
4331,
62,
4480,
62,
38993,
7,
944,
11,
41497,
62,
15414,
82,
2599,
198,
220,
220,
220,
37227,
1722,
4331,
22784,
475,
17311,
389,
12901,
276,
20560,
526,
15931,
198,
220,
220,
220,
1441,
2116,
13,
79,
17407,
19510,
1069,
14692,
7890,
8973,
329,
409,
287,
41497,
62,
15414,
82,
4008,
628,
198,
4871,
5060,
3876,
1634,
36918,
2848,
7,
18250,
62,
19849,
13,
17633,
36918,
2848,
2599,
198,
220,
37227,
36918,
2848,
1398,
284,
1620,
257,
15676,
1634,
4876,
526,
15931,
628,
220,
1303,
337,
5912,
422,
14276,
309,
20,
7032,
284,
428,
4876,
198,
220,
18930,
24639,
62,
49,
1677,
29559,
796,
1391,
198,
220,
220,
220,
220,
220,
366,
15414,
62,
5239,
1298,
366,
22897,
1600,
198,
220,
220,
220,
220,
220,
366,
16793,
62,
5239,
1298,
366,
35790,
1600,
198,
220,
1782,
628,
220,
22492,
198,
220,
1303,
406,
2043,
7824,
7822,
628,
220,
1303,
16926,
46,
7,
65,
14,
17279,
2791,
21719,
23,
2599,
4781,
777,
706,
15458,
278,
7824,
318,
20750,
510,
13,
628,
220,
825,
4331,
7,
944,
11,
17311,
2599,
198,
220,
220,
220,
37227,
47,
17407,
319,
257,
2060,
949,
571,
963,
286,
6096,
526,
15931,
198,
220,
220,
220,
17311,
796,
1351,
7,
15414,
82,
8,
220,
1303,
2476,
284,
307,
20717,
2174,
11,
523,
1394,
1336,
1351,
198,
220,
220,
220,
2746,
62,
15414,
82,
796,
357,
944,
13,
3866,
14681,
7,
1069,
8,
329,
409,
287,
17311,
8,
198,
220,
220,
220,
23862,
796,
2116,
13,
29988,
1496,
13,
79,
17407,
7,
19849,
62,
15414,
82,
8,
198,
220,
220,
220,
23862,
796,
357,
26791,
13,
2787,
499,
62,
11600,
7,
5908,
11,
2116,
13,
44603,
62,
49,
1677,
29559,
8,
329,
6941,
287,
23862,
8,
628,
220,
220,
220,
1303,
16926,
46,
7,
469,
11840,
9038,
2599,
20218,
4610,
284,
651,
371,
2606,
8264,
8198,
287,
1366,
3084,
13,
198,
220,
220,
220,
329,
409,
11,
6941,
287,
19974,
7,
15414,
82,
11,
23862,
2599,
198,
220,
220,
220,
220,
220,
4776,
796,
2116,
13557,
1416,
11934,
13,
26675,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2496,
28,
1069,
14692,
35790,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17724,
28,
944,
13557,
1136,
62,
28764,
62,
8841,
7,
5908,
14692,
22915,
62,
5239,
8973,
4008,
198,
220,
220,
220,
220,
220,
6941,
14692,
472,
469,
43,
8973,
796,
12178,
7,
26675,
14692,
472,
469,
43,
1,
4083,
69,
1326,
5015,
8,
198,
220,
220,
220,
220,
220,
7800,
6941,
628,
220,
825,
4331,
62,
4480,
62,
38993,
7,
944,
11,
41497,
62,
15414,
82,
2599,
198,
220,
220,
220,
37227,
1722,
4331,
22784,
475,
17311,
389,
12901,
276,
20560,
526,
15931,
198,
220,
220,
220,
1441,
2116,
13,
79,
17407,
19510,
1069,
14692,
7890,
8973,
329,
409,
287,
41497,
62,
15414,
82,
4008,
198
] | 2.585776 | 4,640 |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.4 on 2017-01-18 14:49
from __future__ import unicode_literals
from django.db import migrations, models
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
2980,
515,
416,
37770,
352,
13,
940,
13,
19,
319,
2177,
12,
486,
12,
1507,
1478,
25,
2920,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.736842 | 57 |
from .methods import Randomizer
from .plots import oned, twod
from .utils import *
__version__ = "0.1.4"
| [
6738,
764,
24396,
82,
1330,
14534,
7509,
198,
6738,
764,
489,
1747,
1330,
319,
276,
11,
665,
375,
198,
6738,
764,
26791,
1330,
1635,
628,
198,
834,
9641,
834,
796,
366,
15,
13,
16,
13,
19,
1,
198
] | 2.815789 | 38 |
##Script to prepare data for pollination analyses
##Before running, you must have the NLCD and CDL rasters for your year(s) of analysis and the states raster in one folder
# Import modules, reset environments
import arcpy
arcpy.CheckOutExtension("spatial")
arcpy.ResetEnvironments()
import tkFileDialog
# Select geodatabase where input datasets (NLCD, CDL, and state rasters) are stored
inputFolder = tkFileDialog.askdirectory(initialdir="/", title='Please select the geodatabase where the NLCD, CDL, and state rasters are stored.')
#Set input folder as working directory
arcpy.env.workspace = inputFolder
# Set years of analysis
years = raw_input("Enter years of analysis separated by spaces:")
years_list = years.split()
#Get states dataset
states = inputFolder+"/studystates"
#Loop rest of processing through each year of analysis
for year in years_list:
# Set input datasets
rawCDL = inputFolder+"/CDL_" + year
rawNLCD = inputFolder+"/NLCD_" + year
#Resample NLCD to 56 m, using states as snap raster
arcpy.env.snapRaster = states
NLCD = arcpy.Resample_management(rawNLCD, "NLCD_56m_" + year, 56, "MAJORITY")
#Resample CDL to 56 m, using states as snap raster
arcpy.env.snapRaster = states
CDL = arcpy.Resample_management(rawCDL, "CDL_56m_" + year, 56, "MAJORITY")
| [
2235,
7391,
284,
8335,
1366,
329,
3278,
1883,
13523,
201,
198,
2235,
8421,
2491,
11,
345,
1276,
423,
262,
399,
5639,
35,
290,
6458,
43,
374,
7060,
329,
534,
614,
7,
82,
8,
286,
3781,
290,
262,
2585,
374,
1603,
287,
530,
9483,
201,
198,
201,
198,
2,
17267,
13103,
11,
13259,
12493,
201,
198,
11748,
10389,
9078,
201,
198,
5605,
9078,
13,
9787,
7975,
11627,
3004,
7203,
2777,
34961,
4943,
201,
198,
5605,
9078,
13,
4965,
316,
4834,
12103,
3419,
201,
198,
201,
198,
11748,
256,
74,
8979,
44204,
201,
198,
201,
198,
2,
9683,
4903,
375,
265,
5754,
810,
5128,
40522,
357,
45,
5639,
35,
11,
6458,
43,
11,
290,
1181,
374,
7060,
8,
389,
8574,
201,
198,
15414,
41092,
796,
256,
74,
8979,
44204,
13,
2093,
34945,
7,
36733,
15908,
35922,
1600,
3670,
11639,
5492,
2922,
262,
4903,
375,
265,
5754,
810,
262,
399,
5639,
35,
11,
6458,
43,
11,
290,
1181,
374,
7060,
389,
8574,
2637,
8,
201,
198,
201,
198,
2,
7248,
5128,
9483,
355,
1762,
8619,
201,
198,
5605,
9078,
13,
24330,
13,
5225,
10223,
796,
5128,
41092,
201,
198,
201,
198,
2,
5345,
812,
286,
3781,
201,
198,
19002,
796,
8246,
62,
15414,
7203,
17469,
812,
286,
3781,
11266,
416,
9029,
25,
4943,
201,
198,
19002,
62,
4868,
796,
812,
13,
35312,
3419,
201,
198,
201,
198,
2,
3855,
2585,
27039,
201,
198,
27219,
796,
5128,
41092,
10,
1,
14,
44517,
27219,
1,
201,
198,
201,
198,
2,
39516,
1334,
286,
7587,
832,
1123,
614,
286,
3781,
201,
198,
1640,
614,
287,
812,
62,
4868,
25,
201,
198,
220,
220,
220,
1303,
5345,
5128,
40522,
201,
198,
220,
220,
220,
8246,
8610,
43,
796,
5128,
41092,
10,
1,
14,
8610,
43,
62,
1,
1343,
614,
201,
198,
220,
220,
220,
8246,
45,
5639,
35,
796,
5128,
41092,
10,
1,
14,
45,
5639,
35,
62,
1,
1343,
614,
201,
198,
201,
198,
220,
220,
220,
1303,
4965,
1403,
399,
5639,
35,
284,
7265,
285,
11,
1262,
2585,
355,
11495,
374,
1603,
201,
198,
220,
220,
220,
10389,
9078,
13,
24330,
13,
45380,
49,
1603,
796,
2585,
201,
198,
220,
220,
220,
399,
5639,
35,
796,
10389,
9078,
13,
4965,
1403,
62,
27604,
7,
1831,
45,
5639,
35,
11,
366,
45,
5639,
35,
62,
3980,
76,
62,
1,
1343,
614,
11,
7265,
11,
366,
5673,
41,
1581,
9050,
4943,
201,
198,
201,
198,
220,
220,
220,
1303,
4965,
1403,
6458,
43,
284,
7265,
285,
11,
1262,
2585,
355,
11495,
374,
1603,
201,
198,
220,
220,
220,
10389,
9078,
13,
24330,
13,
45380,
49,
1603,
796,
2585,
201,
198,
220,
220,
220,
6458,
43,
796,
10389,
9078,
13,
4965,
1403,
62,
27604,
7,
1831,
8610,
43,
11,
366,
8610,
43,
62,
3980,
76,
62,
1,
1343,
614,
11,
7265,
11,
366,
5673,
41,
1581,
9050,
4943,
201,
198,
201,
198,
220,
220,
220,
201,
198
] | 2.832985 | 479 |
from keprekars_constant import find_keprekars_constant_steps
import unittest
if __name__ == "__main__":
unittest.main()
| [
6738,
885,
3866,
74,
945,
62,
9979,
415,
1330,
1064,
62,
365,
3866,
74,
945,
62,
9979,
415,
62,
20214,
198,
11748,
555,
715,
395,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.591837 | 49 |
import cv2
from qualipy.utils.focus_measure import *
IMAGE = cv2.imread('tests/images/lama.jpg', 0)
BLURRED = cv2.blur(IMAGE, (10, 10))
| [
11748,
269,
85,
17,
198,
198,
6738,
4140,
541,
88,
13,
26791,
13,
37635,
62,
1326,
5015,
1330,
1635,
198,
198,
3955,
11879,
796,
269,
85,
17,
13,
320,
961,
10786,
41989,
14,
17566,
14,
75,
1689,
13,
9479,
3256,
657,
8,
198,
9148,
4261,
22083,
796,
269,
85,
17,
13,
2436,
333,
7,
3955,
11879,
11,
357,
940,
11,
838,
4008,
628,
628,
198
] | 2.184615 | 65 |
from .api import API
| [
6738,
764,
15042,
1330,
7824,
628
] | 3.666667 | 6 |
from utils import cpp, table_reader
if __name__ == "__main__":
main()
| [
6738,
3384,
4487,
1330,
269,
381,
11,
3084,
62,
46862,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.566667 | 30 |
"""Send file for not5oclock_bot"""
import argparse
from os import path
import botskeleton
if __name__ == "__main__":
SECRETS_DIR = path.join(path.abspath(path.dirname(__file__)), "SECRETS")
botskeleton = botskeleton.BotSkeleton(SECRETS_DIR, bot_name="not5oclock_bot")
# Get arg.
# Could probably do it more simply - this is doing it properly but half-assed.
parser = argparse.ArgumentParser(description="Send a tweet.")
parser.add_argument("text", metavar="TWEET", type=str,
help="The tweet to send")
args = parser.parse_args()
tweet = vars(args)["text"]
botskeleton.send(tweet)
| [
37811,
25206,
2393,
329,
407,
20,
420,
5354,
62,
13645,
37811,
198,
198,
11748,
1822,
29572,
198,
6738,
28686,
1330,
3108,
198,
198,
11748,
29641,
38800,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
10729,
2200,
4694,
62,
34720,
796,
3108,
13,
22179,
7,
6978,
13,
397,
2777,
776,
7,
6978,
13,
15908,
3672,
7,
834,
7753,
834,
36911,
366,
23683,
2200,
4694,
4943,
198,
220,
220,
220,
29641,
38800,
796,
29641,
38800,
13,
20630,
50,
38800,
7,
23683,
2200,
4694,
62,
34720,
11,
10214,
62,
3672,
2625,
1662,
20,
420,
5354,
62,
13645,
4943,
628,
220,
220,
220,
1303,
3497,
1822,
13,
198,
220,
220,
220,
1303,
10347,
2192,
466,
340,
517,
2391,
532,
428,
318,
1804,
340,
6105,
475,
2063,
12,
21390,
13,
198,
220,
220,
220,
30751,
796,
1822,
29572,
13,
28100,
1713,
46677,
7,
11213,
2625,
25206,
257,
6126,
19570,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
7203,
5239,
1600,
1138,
615,
283,
2625,
51,
8845,
2767,
1600,
2099,
28,
2536,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
464,
6126,
284,
3758,
4943,
198,
220,
220,
220,
26498,
796,
30751,
13,
29572,
62,
22046,
3419,
198,
220,
220,
220,
6126,
796,
410,
945,
7,
22046,
8,
14692,
5239,
8973,
628,
220,
220,
220,
29641,
38800,
13,
21280,
7,
83,
7277,
8,
198
] | 2.617886 | 246 |
"""
stanCode Breakout Project
Adapted from Eric Roberts's Breakout by
Sonja Johnson-Yu, Kylie Jue, Nick Bowman,
and Jerry Liao.
This is a breakout game with loading animation, two levels of games, and a score board
"""
from campy.gui.events.timer import pause
from breakoutgraphics import BreakoutGraphics
FRAME_RATE = 1000 / 120 # 120 frames per second
if __name__ == '__main__':
main()
| [
37811,
198,
14192,
10669,
12243,
448,
4935,
198,
48003,
276,
422,
7651,
10918,
338,
12243,
448,
416,
198,
31056,
6592,
5030,
12,
40728,
11,
39859,
494,
449,
518,
11,
8047,
38774,
11,
198,
392,
13075,
406,
13481,
13,
198,
198,
1212,
318,
257,
31661,
983,
351,
11046,
11034,
11,
734,
2974,
286,
1830,
11,
290,
257,
4776,
3096,
198,
37811,
198,
198,
6738,
1413,
88,
13,
48317,
13,
31534,
13,
45016,
1330,
14985,
198,
6738,
31661,
70,
11549,
1330,
12243,
448,
18172,
198,
198,
10913,
10067,
62,
49,
6158,
796,
8576,
1220,
7982,
220,
1303,
7982,
13431,
583,
1218,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 3.352941 | 119 |
import os.path as osp
import mmcv
from tools_yuan.convert_data.utils import parse_xml
from tools_yuan.convert_data.utils import track_progress_yuan
import getpass
"""
Author: Yuan Yuan
Date:2018/12/16
Location:SCU
"""
if __name__ == '__main__':
main()
| [
11748,
28686,
13,
6978,
355,
267,
2777,
198,
11748,
8085,
33967,
198,
6738,
4899,
62,
88,
7258,
13,
1102,
1851,
62,
7890,
13,
26791,
1330,
21136,
62,
19875,
198,
6738,
4899,
62,
88,
7258,
13,
1102,
1851,
62,
7890,
13,
26791,
1330,
2610,
62,
33723,
62,
88,
7258,
198,
11748,
651,
6603,
198,
37811,
198,
13838,
25,
34071,
34071,
198,
10430,
25,
7908,
14,
1065,
14,
1433,
198,
14749,
25,
6173,
52,
198,
37811,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.755319 | 94 |
#!/usr/bin/env python
from control.msg import heaveFeedback, heaveAction, heaveResult
import rospy
import time
import actionlib
if __name__ == '__main__':
rospy.init_node('heaveServer')
server = Heave(rospy.get_name())
rospy.spin()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
6738,
1630,
13,
19662,
1330,
339,
1015,
18332,
1891,
11,
339,
1015,
12502,
11,
339,
1015,
23004,
198,
11748,
686,
2777,
88,
198,
11748,
640,
198,
11748,
2223,
8019,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
686,
2777,
88,
13,
15003,
62,
17440,
10786,
258,
1015,
10697,
11537,
198,
220,
220,
220,
4382,
796,
679,
1015,
7,
305,
2777,
88,
13,
1136,
62,
3672,
28955,
198,
220,
220,
220,
686,
2777,
88,
13,
39706,
3419,
198
] | 2.606383 | 94 |
import numpy as np
from net_utils import net_catalogue
from net_utils.local_settings import gpu_available
from utils import resize_image
| [
11748,
299,
32152,
355,
45941,
198,
6738,
2010,
62,
26791,
1330,
2010,
62,
9246,
30326,
198,
6738,
2010,
62,
26791,
13,
12001,
62,
33692,
1330,
308,
19944,
62,
15182,
198,
6738,
3384,
4487,
1330,
47558,
62,
9060,
628,
628,
628
] | 3.55 | 40 |
from itertools import product as it_product
import tqdm
from scipy import sparse
from provided_code.constants_class import ModelParameters
from provided_code.data_loader import DataLoader
from provided_code.general_functions import get_paths, get_predictions_to_optimize
from provided_code.optimizer import PlanningModel
from provided_code.resources import Patient
if __name__ == '__main__':
# Define project constants
cs = ModelParameters()
# Run extra inverse planning experiments
inverse_planning_experiments = False
# Prepare data loader for optimization
testing_plan_paths = get_paths(cs.reference_data_dir, ext='') # gets the path of each patient's directory
data_loader = DataLoader(testing_plan_paths, mode_name='optimization')
# Select the set of predictions to plan for
predictions_to_optimize, _ = get_predictions_to_optimize(cs)
predictions_to_optimize = predictions_to_optimize[0:13]
# Iterate through each set of predictions
for prediction_path in predictions_to_optimize:
# Define hold out set
hold_out_plan_paths = get_paths(prediction_path, ext='') # list of paths used for held out validation
prediction_name = prediction_path.split('/')[-1]
# Predict dose for the held out set
dose_loader = DataLoader(hold_out_plan_paths, mode_name='predicted_dose')
# Prepare files
for idx in tqdm.tqdm(range(dose_loader.number_of_batches())):
print('Patient {} of {}'.format(idx + 1, dose_loader.number_of_batches()))
# Get other patient info
pat_data = data_loader.get_batch(idx)
# Load prediction data
all_predicted_data = dose_loader.get_batch(patient_list=pat_data['patient_list'])
predicted_dose = all_predicted_data[dose_loader.mode_name]
# Build a patient object with the predicted dose
patient = Patient(cs,
pat_data['patient_list'][0], # Patient ID
pat_data['patient_path_list'][0], # Path where patient data is stored
predicted_dose.squeeze(), # Dose for patient
pat_data['structure_masks'][0], # Structure mask
sparse.csr_matrix(pat_data['dij'][0]), # Full dose influence matrix
pat_data['voxel_dimensions'][0], # Dimensions of a voxel (in units of mm)
pat_data['beamlet_indices'][0].values, # Beamlet indices on fluence map
)
cs.set_patient(patient.identifier)
for rel_or_abs, max_or_mean in it_product(['relative', 'absolute'], ['mean', 'max']):
cs.set_directories_for_new_io(prediction_name, opt_name=f'{rel_or_abs}_{max_or_mean}')
# Optimize if dose not already present
if not cs.check_patient():
model = PlanningModel(patient, cs, relative_or_absolute=rel_or_abs, mean_or_max=max_or_mean)
model.solve(quick_test=False)
model.save_fluence_and_dose()
# Generate an inverse planning plan with the weights generated above (based on theory from paper)
cs.set_directories_for_new_io(prediction_name, opt_name=f'inverse_{rel_or_abs}_{max_or_mean}')
if inverse_planning_experiments and not cs.check_patient():
patient.update_weights()
inverse_model = PlanningModel(patient, cs, relative_or_absolute=rel_or_abs,
mean_or_max=max_or_mean, inverse_plan=True)
inverse_model.solve()
inverse_model.save_fluence_and_dose()
| [
6738,
340,
861,
10141,
1330,
1720,
355,
340,
62,
11167,
198,
198,
11748,
256,
80,
36020,
198,
6738,
629,
541,
88,
1330,
29877,
198,
198,
6738,
2810,
62,
8189,
13,
9979,
1187,
62,
4871,
1330,
9104,
48944,
198,
6738,
2810,
62,
8189,
13,
7890,
62,
29356,
1330,
6060,
17401,
198,
6738,
2810,
62,
8189,
13,
24622,
62,
12543,
2733,
1330,
651,
62,
6978,
82,
11,
651,
62,
28764,
9278,
62,
1462,
62,
40085,
1096,
198,
6738,
2810,
62,
8189,
13,
40085,
7509,
1330,
21913,
17633,
198,
6738,
2810,
62,
8189,
13,
37540,
1330,
35550,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
628,
220,
220,
220,
1303,
2896,
500,
1628,
38491,
198,
220,
220,
220,
50115,
796,
9104,
48944,
3419,
628,
220,
220,
220,
1303,
5660,
3131,
34062,
5410,
10256,
198,
220,
220,
220,
34062,
62,
11578,
768,
62,
23100,
6800,
796,
10352,
628,
220,
220,
220,
1303,
43426,
1366,
40213,
329,
23989,
198,
220,
220,
220,
4856,
62,
11578,
62,
6978,
82,
796,
651,
62,
6978,
82,
7,
6359,
13,
35790,
62,
7890,
62,
15908,
11,
1070,
28,
7061,
8,
220,
1303,
3011,
262,
3108,
286,
1123,
5827,
338,
8619,
198,
220,
220,
220,
1366,
62,
29356,
796,
6060,
17401,
7,
33407,
62,
11578,
62,
6978,
82,
11,
4235,
62,
3672,
11639,
40085,
1634,
11537,
628,
220,
220,
220,
1303,
9683,
262,
900,
286,
16277,
284,
1410,
329,
198,
220,
220,
220,
16277,
62,
1462,
62,
40085,
1096,
11,
4808,
796,
651,
62,
28764,
9278,
62,
1462,
62,
40085,
1096,
7,
6359,
8,
198,
220,
220,
220,
16277,
62,
1462,
62,
40085,
1096,
796,
16277,
62,
1462,
62,
40085,
1096,
58,
15,
25,
1485,
60,
198,
220,
220,
220,
1303,
40806,
378,
832,
1123,
900,
286,
16277,
198,
220,
220,
220,
329,
17724,
62,
6978,
287,
16277,
62,
1462,
62,
40085,
1096,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2896,
500,
1745,
503,
900,
198,
220,
220,
220,
220,
220,
220,
220,
1745,
62,
448,
62,
11578,
62,
6978,
82,
796,
651,
62,
6978,
82,
7,
28764,
2867,
62,
6978,
11,
1070,
28,
7061,
8,
220,
1303,
1351,
286,
13532,
973,
329,
2714,
503,
21201,
198,
220,
220,
220,
220,
220,
220,
220,
17724,
62,
3672,
796,
17724,
62,
6978,
13,
35312,
10786,
14,
11537,
58,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
49461,
10742,
329,
262,
2714,
503,
900,
198,
220,
220,
220,
220,
220,
220,
220,
10742,
62,
29356,
796,
6060,
17401,
7,
2946,
62,
448,
62,
11578,
62,
6978,
82,
11,
4235,
62,
3672,
11639,
28764,
5722,
62,
34436,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
43426,
3696,
198,
220,
220,
220,
220,
220,
220,
220,
329,
4686,
87,
287,
256,
80,
36020,
13,
83,
80,
36020,
7,
9521,
7,
34436,
62,
29356,
13,
17618,
62,
1659,
62,
8664,
2052,
28955,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
12130,
1153,
23884,
286,
23884,
4458,
18982,
7,
312,
87,
1343,
352,
11,
10742,
62,
29356,
13,
17618,
62,
1659,
62,
8664,
2052,
3419,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3497,
584,
5827,
7508,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
796,
1366,
62,
29356,
13,
1136,
62,
43501,
7,
312,
87,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
8778,
17724,
1366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
477,
62,
28764,
5722,
62,
7890,
796,
10742,
62,
29356,
13,
1136,
62,
43501,
7,
26029,
62,
4868,
28,
8071,
62,
7890,
17816,
26029,
62,
4868,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11001,
62,
34436,
796,
477,
62,
28764,
5722,
62,
7890,
58,
34436,
62,
29356,
13,
14171,
62,
3672,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
10934,
257,
5827,
2134,
351,
262,
11001,
10742,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5827,
796,
35550,
7,
6359,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
17816,
26029,
62,
4868,
6,
7131,
15,
4357,
220,
1303,
35550,
4522,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
17816,
26029,
62,
6978,
62,
4868,
6,
7131,
15,
4357,
220,
1303,
10644,
810,
5827,
1366,
318,
8574,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11001,
62,
34436,
13,
16485,
1453,
2736,
22784,
220,
1303,
360,
577,
329,
5827,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
17816,
301,
5620,
62,
5356,
591,
6,
7131,
15,
4357,
220,
1303,
32522,
9335,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29877,
13,
6359,
81,
62,
6759,
8609,
7,
8071,
62,
7890,
17816,
67,
2926,
6,
7131,
15,
46570,
220,
1303,
6462,
10742,
4588,
17593,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
17816,
85,
1140,
417,
62,
27740,
5736,
6,
7131,
15,
4357,
220,
1303,
41265,
286,
257,
410,
1140,
417,
357,
259,
4991,
286,
8085,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1458,
62,
7890,
17816,
40045,
1616,
62,
521,
1063,
6,
7131,
15,
4083,
27160,
11,
220,
1303,
25855,
1616,
36525,
319,
6562,
594,
3975,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
50115,
13,
2617,
62,
26029,
7,
26029,
13,
738,
7483,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
823,
62,
273,
62,
8937,
11,
3509,
62,
273,
62,
32604,
287,
340,
62,
11167,
7,
17816,
43762,
3256,
705,
48546,
6,
4357,
37250,
32604,
3256,
705,
9806,
20520,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
50115,
13,
2617,
62,
12942,
1749,
62,
1640,
62,
3605,
62,
952,
7,
28764,
2867,
62,
3672,
11,
2172,
62,
3672,
28,
69,
6,
90,
2411,
62,
273,
62,
8937,
92,
23330,
9806,
62,
273,
62,
32604,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
30011,
1096,
611,
10742,
407,
1541,
1944,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
50115,
13,
9122,
62,
26029,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2746,
796,
21913,
17633,
7,
26029,
11,
50115,
11,
3585,
62,
273,
62,
48546,
28,
2411,
62,
273,
62,
8937,
11,
1612,
62,
273,
62,
9806,
28,
9806,
62,
273,
62,
32604,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2746,
13,
82,
6442,
7,
24209,
62,
9288,
28,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2746,
13,
21928,
62,
69,
23079,
62,
392,
62,
34436,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2980,
378,
281,
34062,
5410,
1410,
351,
262,
19590,
7560,
2029,
357,
3106,
319,
4583,
422,
3348,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
50115,
13,
2617,
62,
12942,
1749,
62,
1640,
62,
3605,
62,
952,
7,
28764,
2867,
62,
3672,
11,
2172,
62,
3672,
28,
69,
6,
259,
4399,
23330,
2411,
62,
273,
62,
8937,
92,
23330,
9806,
62,
273,
62,
32604,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
34062,
62,
11578,
768,
62,
23100,
6800,
290,
407,
50115,
13,
9122,
62,
26029,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5827,
13,
19119,
62,
43775,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34062,
62,
19849,
796,
21913,
17633,
7,
26029,
11,
50115,
11,
3585,
62,
273,
62,
48546,
28,
2411,
62,
273,
62,
8937,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1612,
62,
273,
62,
9806,
28,
9806,
62,
273,
62,
32604,
11,
34062,
62,
11578,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34062,
62,
19849,
13,
82,
6442,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34062,
62,
19849,
13,
21928,
62,
69,
23079,
62,
392,
62,
34436,
3419,
628
] | 2.259524 | 1,680 |
"""Implementation of ALI-G in tensorflow 1."""
import tensorflow as tf
def minimize(optimizer, loss, global_step=None, var_list=None,
gate_gradients=tf.compat.v1.train.Optimizer.GATE_OP, aggregation_method=None,
colocate_gradients_with_ops=False, name=None,
grad_loss=None):
"""
Re-write of tf.train.Optimizer.minimize
"""
# first part of method is identical to tf
grads_and_vars = optimizer.compute_gradients(
loss, var_list=var_list, gate_gradients=gate_gradients,
aggregation_method=aggregation_method,
colocate_gradients_with_ops=colocate_gradients_with_ops,
grad_loss=grad_loss)
vars_with_grad = [v for g, v in grads_and_vars if g is not None]
if not vars_with_grad:
raise ValueError(
"No gradients provided for any variable, check your graph for ops"
" that do not support gradients, between variables %s and loss %s." %
([str(v) for _, v in grads_and_vars], loss))
# compute step-size here
grad_sqrd_norm = sum(tf.norm(grad) ** 2 for grad, _ in grads_and_vars)
optimizer._learning_rate = loss / (grad_sqrd_norm + optimizer.eps)
if optimizer._max_lr is not None:
optimizer._learning_rate = tf.clip_by_value(optimizer._learning_rate, clip_value_min=0,
clip_value_max=optimizer._max_lr)
return optimizer.apply_gradients(grads_and_vars, global_step=global_step,
name=name)
class AliGwithMomentum(tf.compat.v1.train.MomentumOptimizer):
"""Optimizer that implements the AliG algorithm.
"""
class AliGwithoutMomentum(tf.compat.v1.train.GradientDescentOptimizer):
"""Optimizer that implements the AliG algorithm.
"""
| [
37811,
3546,
32851,
286,
8355,
40,
12,
38,
287,
11192,
273,
11125,
352,
526,
15931,
198,
11748,
11192,
273,
11125,
355,
48700,
628,
198,
4299,
17775,
7,
40085,
7509,
11,
2994,
11,
3298,
62,
9662,
28,
14202,
11,
1401,
62,
4868,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8946,
62,
9744,
2334,
28,
27110,
13,
5589,
265,
13,
85,
16,
13,
27432,
13,
27871,
320,
7509,
13,
38,
6158,
62,
3185,
11,
46500,
62,
24396,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
951,
13369,
62,
9744,
2334,
62,
4480,
62,
2840,
28,
25101,
11,
1438,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3915,
62,
22462,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
797,
12,
13564,
286,
48700,
13,
27432,
13,
27871,
320,
7509,
13,
1084,
48439,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
717,
636,
286,
2446,
318,
10411,
284,
48700,
198,
220,
220,
220,
3915,
82,
62,
392,
62,
85,
945,
796,
6436,
7509,
13,
5589,
1133,
62,
9744,
2334,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2994,
11,
1401,
62,
4868,
28,
7785,
62,
4868,
11,
8946,
62,
9744,
2334,
28,
10494,
62,
9744,
2334,
11,
198,
220,
220,
220,
220,
220,
220,
220,
46500,
62,
24396,
28,
9460,
43068,
62,
24396,
11,
198,
220,
220,
220,
220,
220,
220,
220,
951,
13369,
62,
9744,
2334,
62,
4480,
62,
2840,
28,
4033,
13369,
62,
9744,
2334,
62,
4480,
62,
2840,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3915,
62,
22462,
28,
9744,
62,
22462,
8,
628,
220,
220,
220,
410,
945,
62,
4480,
62,
9744,
796,
685,
85,
329,
308,
11,
410,
287,
3915,
82,
62,
392,
62,
85,
945,
611,
308,
318,
407,
6045,
60,
198,
220,
220,
220,
611,
407,
410,
945,
62,
4480,
62,
9744,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
2949,
3915,
2334,
2810,
329,
597,
7885,
11,
2198,
534,
4823,
329,
39628,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
326,
466,
407,
1104,
3915,
2334,
11,
1022,
9633,
4064,
82,
290,
2994,
4064,
82,
526,
4064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29565,
2536,
7,
85,
8,
329,
4808,
11,
410,
287,
3915,
82,
62,
392,
62,
85,
945,
4357,
2994,
4008,
628,
220,
220,
220,
1303,
24061,
2239,
12,
7857,
994,
198,
220,
220,
220,
3915,
62,
31166,
4372,
62,
27237,
796,
2160,
7,
27110,
13,
27237,
7,
9744,
8,
12429,
362,
329,
3915,
11,
4808,
287,
3915,
82,
62,
392,
62,
85,
945,
8,
198,
220,
220,
220,
6436,
7509,
13557,
40684,
62,
4873,
796,
2994,
1220,
357,
9744,
62,
31166,
4372,
62,
27237,
1343,
6436,
7509,
13,
25386,
8,
198,
220,
220,
220,
611,
6436,
7509,
13557,
9806,
62,
14050,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
13557,
40684,
62,
4873,
796,
48700,
13,
15036,
62,
1525,
62,
8367,
7,
40085,
7509,
13557,
40684,
62,
4873,
11,
10651,
62,
8367,
62,
1084,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10651,
62,
8367,
62,
9806,
28,
40085,
7509,
13557,
9806,
62,
14050,
8,
628,
220,
220,
220,
1441,
6436,
7509,
13,
39014,
62,
9744,
2334,
7,
2164,
5643,
62,
392,
62,
85,
945,
11,
3298,
62,
9662,
28,
20541,
62,
9662,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
3672,
8,
628,
198,
4871,
12104,
38,
4480,
29252,
298,
388,
7,
27110,
13,
5589,
265,
13,
85,
16,
13,
27432,
13,
29252,
298,
388,
27871,
320,
7509,
2599,
198,
220,
220,
220,
37227,
27871,
320,
7509,
326,
23986,
262,
12104,
38,
11862,
13,
198,
220,
220,
220,
37227,
628,
198,
4871,
12104,
38,
19419,
29252,
298,
388,
7,
27110,
13,
5589,
265,
13,
85,
16,
13,
27432,
13,
42731,
1153,
5960,
1087,
27871,
320,
7509,
2599,
198,
220,
220,
220,
37227,
27871,
320,
7509,
326,
23986,
262,
12104,
38,
11862,
13,
198,
220,
220,
220,
37227,
628
] | 2.310567 | 776 |
from . trace_form import Trace
from . average_form import Average
from . extension_form import Extension
from . restriction_form import Restriction
from . injection_form import Injection
from . point_trace_form import PointTrace
from . xii_assembly import assemble as ii_assemble
from . average_shape import Square, SquareRim, Circle, Disk
from . block_form import block_form
| [
6738,
764,
12854,
62,
687,
1330,
34912,
198,
6738,
764,
2811,
62,
687,
1330,
13475,
198,
6738,
764,
7552,
62,
687,
1330,
27995,
198,
6738,
764,
17504,
62,
687,
1330,
37163,
295,
198,
6738,
764,
16954,
62,
687,
1330,
554,
29192,
198,
6738,
764,
966,
62,
40546,
62,
687,
1330,
6252,
2898,
558,
198,
6738,
764,
2124,
4178,
62,
41873,
1330,
25432,
355,
21065,
62,
292,
15140,
198,
6738,
764,
2811,
62,
43358,
1330,
9276,
11,
9276,
49,
320,
11,
16291,
11,
31664,
198,
6738,
764,
2512,
62,
687,
1330,
2512,
62,
687,
198
] | 4 | 94 |
#!/bin/python3
# https://www.DIVD.nl
# Developed by Hidde Smit & Wietse Boonstra
# Usage: cat ips.txt | python3 ip-whois-mail.py
# ips.txt 1 ip per line
# Debugging: sys.stdin = ['1.1.1.1', '8.8.8.8']
from ipwhois import IPWhois
import sys
for line in sys.stdin:
try:
ip = line.strip('\n')
obj = IPWhois(ip)
rdap = obj.lookup_rdap(depth=2)
result = rdap['objects']
abusemails = []
for key, value in result.items():
if value['roles'] and 'abuse' in value['roles']:
for abusemail in value['contact']['email']:
abusemails.append(abusemail['value'])
abusemails = list(dict.fromkeys(abusemails))
print (ip,str(abusemails)[1:-1].replace(' ', ''),sep=',')
except Exception as e:
print ("Failed with ip: {}; error {}".format(ip, e))
pass
| [
2,
48443,
8800,
14,
29412,
18,
198,
2,
3740,
1378,
2503,
13,
33569,
35,
13,
21283,
198,
2,
6013,
276,
416,
367,
1638,
68,
2439,
270,
1222,
370,
1155,
325,
347,
2049,
12044,
198,
2,
29566,
25,
3797,
220,
2419,
13,
14116,
930,
21015,
18,
20966,
12,
8727,
271,
12,
4529,
13,
9078,
198,
2,
220,
2419,
13,
14116,
352,
20966,
583,
1627,
198,
2,
31687,
2667,
25,
25064,
13,
19282,
259,
796,
37250,
16,
13,
16,
13,
16,
13,
16,
3256,
705,
23,
13,
23,
13,
23,
13,
23,
20520,
198,
198,
6738,
20966,
8727,
271,
1330,
6101,
8241,
271,
198,
11748,
25064,
198,
198,
1640,
1627,
287,
25064,
13,
19282,
259,
25,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
20966,
796,
1627,
13,
36311,
10786,
59,
77,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
26181,
796,
6101,
8241,
271,
7,
541,
8,
198,
220,
220,
220,
220,
220,
220,
220,
374,
67,
499,
796,
26181,
13,
5460,
929,
62,
4372,
499,
7,
18053,
28,
17,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
374,
67,
499,
17816,
48205,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
5076,
26165,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
11,
1988,
287,
1255,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
17816,
305,
829,
20520,
290,
705,
47158,
6,
287,
1988,
17816,
305,
829,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
5076,
4529,
287,
1988,
17816,
32057,
6,
7131,
6,
12888,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5076,
26165,
13,
33295,
7,
47158,
4529,
17816,
8367,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
5076,
26165,
796,
1351,
7,
11600,
13,
6738,
13083,
7,
47158,
26165,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
357,
541,
11,
2536,
7,
47158,
26165,
38381,
16,
21912,
16,
4083,
33491,
10786,
46083,
10148,
828,
325,
79,
28,
3256,
11537,
198,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
5855,
37,
6255,
351,
20966,
25,
1391,
19629,
4049,
23884,
1911,
18982,
7,
541,
11,
304,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198
] | 2.127451 | 408 |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# ProDy: A Python Package for Protein Dynamics Analysis
#
# Copyright (C) 2010-2012 Ahmet Bakan
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
"""ProDy test suite. Usage::
from prody import *
prody.test()
Testing will use :mod:`nose` if it is available, otherwise it will use
:mod:`unittest`."""
__author__ = 'Ahmet Bakan'
__copyright__ = 'Copyright (C) 2010-2012 Ahmet Bakan'
from glob import glob
from os.path import abspath, split, join, relpath, splitext
from os.path import sep as dirsep
import inspect
import tempfile
try:
import unittest2 as unittest
from unittest2 import TestCase, skipIf, skipUnless
except ImportError:
import unittest
from unittest import TestCase, skipIf, skipUnless
from prody.utilities import PLATFORM
from prody import LOGGER
from prody.utilities import which
NOPRODYCMD = which('prody') is None
WINDOWS = PLATFORM == 'Windows'
try:
import matplotlib
matplotlib.use('Agg')
except ImportError:
MATPLOTLIB = False
else:
try:
from matplotlib import pyplot
except ImportError:
MATPLOTLIB = False
else:
MATPLOTLIB = True
TESTDIR = abspath(split(inspect.getfile(inspect.currentframe()))[0])
TEMPDIR = tempfile.gettempdir()
MODULES = dict()
PREFIX = 'prody.tests.'
for pyfile in glob(join(TESTDIR, '*', '*.py')):
pyfile = splitext(relpath(pyfile, TESTDIR))[0]
items = pyfile.split(dirsep)
if items[-1] == '__init__':
items = items[:-1]
if items[-1].startswith('test_'):
MODULES['.'.join([i[5:] for i in items])] = PREFIX + '.'.join(items)
if __name__ == '__main__':
runTests()
| [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
1041,
35,
88,
25,
317,
11361,
15717,
329,
31702,
33806,
14691,
198,
2,
198,
2,
15069,
357,
34,
8,
3050,
12,
6999,
7900,
4164,
17466,
272,
198,
2,
198,
2,
770,
1430,
318,
1479,
3788,
25,
345,
460,
17678,
4163,
340,
290,
14,
273,
13096,
198,
2,
340,
739,
262,
2846,
286,
262,
22961,
3611,
5094,
13789,
355,
3199,
416,
198,
2,
262,
3232,
10442,
5693,
11,
2035,
2196,
513,
286,
262,
13789,
11,
393,
198,
2,
357,
265,
534,
3038,
8,
597,
1568,
2196,
13,
198,
2,
198,
2,
770,
1430,
318,
9387,
287,
262,
2911,
326,
340,
481,
307,
4465,
11,
198,
2,
475,
42881,
15529,
34764,
56,
26,
1231,
772,
262,
17142,
18215,
286,
198,
2,
34482,
3398,
1565,
5603,
25382,
393,
376,
46144,
7473,
317,
16652,
2149,
37232,
33079,
48933,
13,
220,
4091,
262,
198,
2,
22961,
3611,
5094,
13789,
329,
517,
3307,
13,
198,
2,
198,
2,
921,
815,
423,
2722,
257,
4866,
286,
262,
22961,
3611,
5094,
13789,
198,
2,
1863,
351,
428,
1430,
13,
220,
1002,
407,
11,
766,
1279,
4023,
1378,
2503,
13,
41791,
13,
2398,
14,
677,
4541,
15913,
198,
198,
37811,
2964,
35,
88,
1332,
18389,
13,
220,
29566,
3712,
628,
220,
422,
386,
9892,
1330,
1635,
198,
220,
386,
9892,
13,
9288,
3419,
198,
198,
44154,
481,
779,
1058,
4666,
25,
63,
77,
577,
63,
611,
340,
318,
1695,
11,
4306,
340,
481,
779,
198,
25,
4666,
25,
63,
403,
715,
395,
63,
526,
15931,
198,
198,
834,
9800,
834,
796,
705,
10910,
4164,
17466,
272,
6,
198,
834,
22163,
4766,
834,
796,
705,
15269,
357,
34,
8,
3050,
12,
6999,
7900,
4164,
17466,
272,
6,
628,
198,
6738,
15095,
1330,
15095,
198,
6738,
28686,
13,
6978,
1330,
2352,
6978,
11,
6626,
11,
4654,
11,
823,
6978,
11,
4328,
578,
742,
198,
6738,
28686,
13,
6978,
1330,
41767,
355,
26672,
325,
79,
198,
11748,
10104,
198,
11748,
20218,
7753,
198,
198,
28311,
25,
198,
220,
220,
220,
1330,
555,
715,
395,
17,
355,
555,
715,
395,
198,
220,
220,
220,
422,
555,
715,
395,
17,
1330,
6208,
20448,
11,
14267,
1532,
11,
14267,
28042,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1330,
555,
715,
395,
198,
220,
220,
220,
422,
555,
715,
395,
1330,
6208,
20448,
11,
14267,
1532,
11,
14267,
28042,
198,
198,
6738,
386,
9892,
13,
315,
2410,
1330,
9297,
1404,
21389,
198,
6738,
386,
9892,
1330,
41605,
30373,
198,
198,
6738,
386,
9892,
13,
315,
2410,
1330,
543,
198,
45,
3185,
49,
33076,
34,
12740,
796,
543,
10786,
1676,
9892,
11537,
318,
6045,
198,
198,
33207,
796,
9297,
1404,
21389,
6624,
705,
11209,
6,
198,
198,
28311,
25,
198,
220,
220,
220,
1330,
2603,
29487,
8019,
198,
220,
220,
220,
2603,
29487,
8019,
13,
1904,
10786,
46384,
11537,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
36775,
6489,
2394,
40347,
796,
10352,
198,
17772,
25,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
422,
2603,
29487,
8019,
1330,
12972,
29487,
198,
220,
220,
220,
2845,
17267,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
36775,
6489,
2394,
40347,
796,
10352,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
36775,
6489,
2394,
40347,
796,
6407,
198,
198,
51,
6465,
34720,
796,
2352,
6978,
7,
35312,
7,
1040,
806,
13,
1136,
7753,
7,
1040,
806,
13,
14421,
14535,
3419,
4008,
58,
15,
12962,
198,
51,
3620,
5760,
4663,
796,
20218,
7753,
13,
1136,
29510,
15908,
3419,
198,
198,
33365,
6239,
1546,
796,
8633,
3419,
198,
47,
31688,
10426,
796,
705,
1676,
9892,
13,
41989,
2637,
198,
198,
1640,
12972,
7753,
287,
15095,
7,
22179,
7,
51,
6465,
34720,
11,
705,
9,
3256,
705,
24620,
9078,
11537,
2599,
198,
220,
220,
220,
12972,
7753,
796,
4328,
578,
742,
7,
2411,
6978,
7,
9078,
7753,
11,
43001,
34720,
4008,
58,
15,
60,
628,
220,
220,
220,
3709,
796,
12972,
7753,
13,
35312,
7,
15908,
325,
79,
8,
198,
220,
220,
220,
611,
3709,
58,
12,
16,
60,
6624,
705,
834,
15003,
834,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
3709,
796,
3709,
58,
21912,
16,
60,
628,
220,
220,
220,
611,
3709,
58,
12,
16,
4083,
9688,
2032,
342,
10786,
9288,
62,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
19164,
6239,
1546,
17816,
2637,
13,
22179,
26933,
72,
58,
20,
47715,
329,
1312,
287,
3709,
12962,
60,
796,
22814,
47084,
1343,
705,
2637,
13,
22179,
7,
23814,
8,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1057,
51,
3558,
3419,
198
] | 2.838791 | 794 |
# https://atcoder.jp/contests/abc202/tasks/abc202_d
A, B, K = map(int, input().split())
# memo[a][b] aがa個, bがb個の時の場合の数
memo = [[0 for _ in range(31)] for _ in range(31)]
memo[0][0] = 1
for i in range(A + 1):
for j in range(B + 1):
if i == 0:
memo[i][j] = 1
continue
if j == 0:
memo[i][j] = 1
continue
memo[i][j] += memo[i][j - 1] + memo[i - 1][j]
print(get_S(A, B, K))
| [
2,
3740,
1378,
265,
66,
12342,
13,
34523,
14,
3642,
3558,
14,
39305,
19004,
14,
83,
6791,
14,
39305,
19004,
62,
67,
198,
32,
11,
347,
11,
509,
796,
3975,
7,
600,
11,
5128,
22446,
35312,
28955,
198,
198,
2,
16155,
58,
64,
7131,
65,
60,
257,
35585,
64,
161,
222,
233,
11,
275,
35585,
65,
161,
222,
233,
27032,
25081,
15474,
254,
112,
28938,
230,
27032,
243,
108,
198,
11883,
78,
796,
16410,
15,
329,
4808,
287,
2837,
7,
3132,
15437,
329,
4808,
287,
2837,
7,
3132,
15437,
198,
11883,
78,
58,
15,
7131,
15,
60,
796,
352,
198,
1640,
1312,
287,
2837,
7,
32,
1343,
352,
2599,
198,
220,
220,
220,
329,
474,
287,
2837,
7,
33,
1343,
352,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16155,
58,
72,
7131,
73,
60,
796,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
611,
474,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16155,
58,
72,
7131,
73,
60,
796,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
16155,
58,
72,
7131,
73,
60,
15853,
16155,
58,
72,
7131,
73,
532,
352,
60,
1343,
16155,
58,
72,
532,
352,
7131,
73,
60,
628,
198,
198,
4798,
7,
1136,
62,
50,
7,
32,
11,
347,
11,
509,
4008,
198
] | 1.71374 | 262 |
# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for tf.MatMul JIT compilation."""
import numpy as np
import unittest
from tensorflow.compiler.mlir.tfrt.jit.python_binding import tf_cpurt
cpurt = tf_cpurt.TfCpurtExecutor()
# Matmul: [1, k] x [k, 1]
# Matmul: [1, k] x [k, n]
# Matmul: [n, k] x [k, 1]
# Matmul: [m, k] x [k, n]
if __name__ == "__main__":
np.random.seed(0)
googletest.main()
| [
2,
15069,
33448,
383,
309,
22854,
37535,
46665,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
2,
38093,
25609,
28,
198,
37811,
51,
3558,
329,
48700,
13,
19044,
44,
377,
449,
2043,
23340,
526,
15931,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
11748,
555,
715,
395,
198,
6738,
11192,
273,
11125,
13,
5589,
5329,
13,
4029,
343,
13,
83,
8310,
83,
13,
45051,
13,
29412,
62,
30786,
1330,
48700,
62,
13155,
3325,
628,
198,
198,
13155,
3325,
796,
48700,
62,
13155,
3325,
13,
51,
69,
34,
79,
3325,
23002,
38409,
3419,
628,
628,
220,
1303,
6550,
76,
377,
25,
685,
16,
11,
479,
60,
2124,
685,
74,
11,
352,
60,
628,
220,
1303,
6550,
76,
377,
25,
685,
16,
11,
479,
60,
2124,
685,
74,
11,
299,
60,
628,
220,
1303,
6550,
76,
377,
25,
685,
77,
11,
479,
60,
2124,
685,
74,
11,
352,
60,
628,
220,
1303,
6550,
76,
377,
25,
685,
76,
11,
479,
60,
2124,
685,
74,
11,
299,
60,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
45941,
13,
25120,
13,
28826,
7,
15,
8,
198,
220,
467,
519,
1616,
395,
13,
12417,
3419,
198
] | 3.147929 | 338 |
from util import Util
| [
6738,
7736,
1330,
7273,
346,
198
] | 3.666667 | 6 |
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Manage automatic weight adjustments."""
import collections
import datetime
from base import utils
from datastore import data_handler
from datastore import data_types
from datastore import ndb_utils
from google_cloud_utils import big_query
from handlers import base_handler
from libs import handler
from metrics import fuzzer_stats
from metrics import logs
QuerySpecification = collections.namedtuple(
'QuerySpecification',
['adjusted_weight', 'threshold', 'query_format', 'formatter', 'reason'])
# Formatters for query specifications.
def _past_day_formatter(query_format, dataset):
"""Simple formatter to get stats for the past day."""
end_time = utils.utcnow().date()
start_time = end_time - datetime.timedelta(days=1)
return query_format.format(
dataset=dataset, start_time=start_time, end_time=end_time)
def _new_fuzzer_formatter(query_format, dataset):
"""Prepare a query to check for new fuzzers from the past week."""
now = utils.utcnow().date()
cutoff_time = now - datetime.timedelta(days=7)
return query_format.format(dataset=dataset, cutoff_time=cutoff_time)
def _coverage_formatter(query_format, dataset):
"""Prepare a query to check for changes in coverage week over week."""
end_date = utils.utcnow().date() - datetime.timedelta(days=1)
middle_date = end_date - datetime.timedelta(days=7)
start_date = end_date - datetime.timedelta(days=14)
return query_format.format(
dataset=dataset,
start_date=start_date,
middle_date=middle_date,
end_date=end_date)
# Most of our queries should simply average a field name to get a ratio showing
# how often some behavior occurs.
GENERIC_QUERY_FORMAT = """
SELECT
fuzzer,
job,
AVG({field_name}) AS ratio
FROM
{{dataset}}.TestcaseRun
WHERE
_PARTITIONTIME BETWEEN TIMESTAMP('{{start_time}}')
AND TIMESTAMP('{{end_time}}')
GROUP BY
fuzzer,
job
"""
# Heavily reduce the weight for fuzzers which frequently crash on startup. This
# is indicitave of a very serious problem that makes it highly unlikely that
# we'll find anything during fuzzing.
STARTUP_CRASH_SPECIFICATION = QuerySpecification(
adjusted_weight=0.10,
threshold=0.80,
query_format=GENERIC_QUERY_FORMAT.format(field_name='startup_crash_count'),
formatter=_past_day_formatter,
reason='frequent startup crashes')
# Reduce weight somewhat for fuzzers with many slow units. If a particular unit
# runs for so long that we detect it as a slow unit, it usually means that the
# fuzzer is not making good use of its cycles while running or needs a fix.
SLOW_UNIT_SPECIFICATION = QuerySpecification(
adjusted_weight=0.50,
threshold=0.80,
query_format=GENERIC_QUERY_FORMAT.format(field_name='slow_unit_count'),
formatter=_past_day_formatter,
reason='frequent slow units')
# This should end up being very similar to the slow unit specification, and is
# included for the same reason.
TIMEOUT_SPECIFICATION = QuerySpecification(
adjusted_weight=0.50,
threshold=0.80,
query_format=GENERIC_QUERY_FORMAT.format(field_name='timeout_count'),
formatter=_past_day_formatter,
reason='frequent timeouts')
# Fuzzers which are crashing frequently may not be making full use of their
# allotted time for fuzzing, and may end up being more effective once the known
# issues are fixed.
CRASH_SPECIFICATION = QuerySpecification(
adjusted_weight=0.50,
threshold=0.90,
query_format=GENERIC_QUERY_FORMAT.format(field_name='crash_count'),
formatter=_past_day_formatter,
reason='frequent crashes')
# Fuzzers with extremely frequent OOMs may contain leaks or other issues that
# signal that they need some improvement. Run with a slightly reduced weight
# until the issues are fixed.
OOM_SPECIFICATION = QuerySpecification(
adjusted_weight=0.50,
threshold=0.90,
query_format=GENERIC_QUERY_FORMAT.format(field_name='oom_count'),
formatter=_past_day_formatter,
reason='frequent OOMs')
# New fuzzers/jobs should run much more frequently than others. In this case, we
# test the fraction of days for which we have no stats for this fuzzer/job pair
# and increase if it's nonzero.
NEW_FUZZER_FORMAT = """
SELECT
fuzzer,
job,
1 as ratio,
MIN(_PARTITIONTIME) as first_time
FROM
{dataset}.TestcaseRun
GROUP BY
fuzzer,
job
HAVING
first_time >= TIMESTAMP('{cutoff_time}')
"""
NEW_FUZZER_SPECIFICATION = QuerySpecification(
adjusted_weight=5.0,
threshold=1.0,
query_format=NEW_FUZZER_FORMAT,
formatter=_new_fuzzer_formatter,
reason='new fuzzer')
# Format to query for fuzzers with minimal change in week to week coverage.
COVERAGE_UNCHANGED_FORMAT = """
SELECT
recent.fuzzer AS fuzzer,
recent.job AS job,
1 as ratio
FROM (
SELECT
fuzzer,
job,
MAX(edge_coverage / edges_total) AS coverage
FROM
{dataset}.TestcaseRun
WHERE
_PARTITIONTIME BETWEEN TIMESTAMP('{middle_date}')
AND TIMESTAMP('{end_date}')
AND edges_total > 0
AND edge_coverage > 0
GROUP BY
fuzzer,
job
HAVING
coverage <= 1.0) AS recent
JOIN (
SELECT
fuzzer,
job,
MAX(edge_coverage / edges_total) AS coverage
FROM
{dataset}.TestcaseRun
WHERE
_PARTITIONTIME BETWEEN TIMESTAMP('{start_date}')
AND TIMESTAMP('{middle_date}')
AND edges_total > 0
AND edge_coverage > 0
GROUP BY
fuzzer,
job
HAVING
coverage <= 1.0) AS older
ON
recent.fuzzer = older.fuzzer
AND recent.job = older.job
WHERE
ABS((recent.coverage - older.coverage) / recent.coverage) < 0.01
"""
COVERAGE_UNCHANGED_SPECIFICATION = QuerySpecification(
adjusted_weight=0.5,
threshold=1.0,
query_format=COVERAGE_UNCHANGED_FORMAT,
formatter=_coverage_formatter,
reason='coverage flat over past 2 weeks')
# Mappings for which specifications to use for which
LIBFUZZER_SPECIFICATIONS = [
COVERAGE_UNCHANGED_SPECIFICATION,
CRASH_SPECIFICATION,
NEW_FUZZER_SPECIFICATION,
OOM_SPECIFICATION,
SLOW_UNIT_SPECIFICATION,
STARTUP_CRASH_SPECIFICATION,
TIMEOUT_SPECIFICATION,
]
AFL_SPECIFICATIONS = [
CRASH_SPECIFICATION,
NEW_FUZZER_SPECIFICATION,
STARTUP_CRASH_SPECIFICATION,
]
# Special specification used to modify previously altered weights to their
# default values when they no longer match any other specifications.
RESTORE_DEFAULT_SPECIFICATION = QuerySpecification(
adjusted_weight=1.0,
threshold=None,
query_format=None,
formatter=None,
reason='no longer matches any weight adjustment specifications')
def _query_helper(client, query):
"""Helper function to get fuzzer stats."""
return client.query(query=query).rows
def _update_match(matched_specifications, fuzzer, job, specification):
"""Update the weight for a fuzzer/job."""
key = (fuzzer, job)
old_match = matched_specifications.get(key, RESTORE_DEFAULT_SPECIFICATION)
new_weight = specification.adjusted_weight
old_weight = old_match.adjusted_weight
# Always update the weight if the previous value is the default. This is
# required to deal with specifications that are meant to set the weight above
# 1.0. Otherwise, prioritize only the most penalizing match for this pairing.
if old_match == RESTORE_DEFAULT_SPECIFICATION or new_weight < old_weight:
matched_specifications[key] = specification
def update_weight_for_target(fuzz_target_name, job, specification):
"""Set the weight for a particular target."""
target_job = data_handler.get_fuzz_target_job(fuzz_target_name, job)
if not target_job:
logs.log_error('FuzzTargetJob for target %s and job %s does not exist.' %
(fuzz_target_name, job))
return
weight = specification.adjusted_weight
logs.log('Adjusted weight to %f for target %s and job %s (%s).' %
(weight, fuzz_target_name, job, specification.reason))
target_job.weight = weight
target_job.put()
def update_matches_for_specification(specification, client, engine,
matched_specifications, run_set):
"""Run a query and adjust weights based on a given query specification."""
query = specification.formatter(specification.query_format,
fuzzer_stats.dataset_name(engine))
results = _query_helper(client, query)
for result in results:
fuzzer = result['fuzzer']
job = result['job']
ratio = result['ratio']
run_set.add((fuzzer, job))
if ratio >= specification.threshold:
_update_match(matched_specifications, fuzzer, job, specification)
def update_target_weights_for_engine(client, engine, specifications):
"""Update all fuzz target weights for the specified engine."""
matched_specifications = {}
run_set = set()
# All fuzzers with non-default weights must be tracked with a special
# specification. This ensures that they will be restored to normal weight
# once conditions causing adjustments are no longer met.
target_jobs = data_types.FuzzTargetJob.query(
data_types.FuzzTarget.engine == engine).filter(
data_types.FuzzTargetJob.weight != 1.0)
for target_job in target_jobs:
matched_specifications[(target_job.fuzz_target_name,
target_job.job)] = RESTORE_DEFAULT_SPECIFICATION
for specification in specifications:
update_matches_for_specification(specification, client, engine,
matched_specifications, run_set)
for (fuzzer, job), specification in matched_specifications.iteritems():
if (fuzzer, job) not in run_set:
# This ensures that we don't reset weights for fuzzers with problems if
# they didn't run in the time covered by our queries.
continue
update_weight_for_target(fuzzer, job, specification)
logs.log('Weight adjustments complete for engine %s.' % engine)
def store_current_weights_in_bigquery():
"""Update a bigquery table containing the daily stats."""
rows = []
target_jobs = ndb_utils.get_all_from_model(data_types.FuzzTargetJob)
for target_job in target_jobs:
row = {
'fuzzer': target_job.fuzz_target_name,
'job': target_job.job,
'weight': target_job.weight
}
rows.append(big_query.Insert(row=row, insert_id=None))
client = big_query.Client(dataset_id='main', table_id='fuzzer_weights')
client.insert(rows)
class Handler(base_handler.Handler):
"""Handler to periodically update fuzz target weights based on performance."""
@handler.check_cron()
def get(self):
"""Process all fuzz targets and update FuzzTargetJob weights."""
client = big_query.Client()
update_target_weights_for_engine(client, 'libFuzzer',
LIBFUZZER_SPECIFICATIONS)
update_target_weights_for_engine(client, 'afl', AFL_SPECIFICATIONS)
store_current_weights_in_bigquery()
| [
2,
15069,
13130,
3012,
11419,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
37811,
5124,
496,
11353,
3463,
16895,
526,
15931,
198,
198,
11748,
17268,
198,
11748,
4818,
8079,
198,
198,
6738,
2779,
1330,
3384,
4487,
198,
6738,
4818,
459,
382,
1330,
1366,
62,
30281,
198,
6738,
4818,
459,
382,
1330,
1366,
62,
19199,
198,
6738,
4818,
459,
382,
1330,
299,
9945,
62,
26791,
198,
6738,
23645,
62,
17721,
62,
26791,
1330,
1263,
62,
22766,
198,
6738,
32847,
1330,
2779,
62,
30281,
198,
6738,
9195,
82,
1330,
21360,
198,
6738,
20731,
1330,
26080,
263,
62,
34242,
198,
6738,
20731,
1330,
17259,
198,
198,
20746,
22882,
2649,
796,
17268,
13,
13190,
83,
29291,
7,
198,
220,
220,
220,
705,
20746,
22882,
2649,
3256,
198,
220,
220,
220,
37250,
29117,
62,
6551,
3256,
705,
400,
10126,
3256,
705,
22766,
62,
18982,
3256,
705,
687,
1436,
3256,
705,
41181,
6,
12962,
628,
198,
2,
18980,
1010,
329,
12405,
20640,
13,
198,
4299,
4808,
30119,
62,
820,
62,
687,
1436,
7,
22766,
62,
18982,
11,
27039,
2599,
198,
220,
37227,
26437,
1296,
1436,
284,
651,
9756,
329,
262,
1613,
1110,
526,
15931,
198,
220,
886,
62,
2435,
796,
3384,
4487,
13,
315,
66,
2197,
22446,
4475,
3419,
198,
220,
923,
62,
2435,
796,
886,
62,
2435,
532,
4818,
8079,
13,
16514,
276,
12514,
7,
12545,
28,
16,
8,
198,
220,
1441,
12405,
62,
18982,
13,
18982,
7,
198,
220,
220,
220,
220,
220,
27039,
28,
19608,
292,
316,
11,
923,
62,
2435,
28,
9688,
62,
2435,
11,
886,
62,
2435,
28,
437,
62,
2435,
8,
628,
198,
4299,
4808,
3605,
62,
69,
4715,
263,
62,
687,
1436,
7,
22766,
62,
18982,
11,
27039,
2599,
198,
220,
37227,
37534,
533,
257,
12405,
284,
2198,
329,
649,
26080,
364,
422,
262,
1613,
1285,
526,
15931,
198,
220,
783,
796,
3384,
4487,
13,
315,
66,
2197,
22446,
4475,
3419,
198,
220,
45616,
62,
2435,
796,
783,
532,
4818,
8079,
13,
16514,
276,
12514,
7,
12545,
28,
22,
8,
198,
220,
1441,
12405,
62,
18982,
13,
18982,
7,
19608,
292,
316,
28,
19608,
292,
316,
11,
45616,
62,
2435,
28,
8968,
2364,
62,
2435,
8,
628,
198,
4299,
4808,
1073,
1857,
62,
687,
1436,
7,
22766,
62,
18982,
11,
27039,
2599,
198,
220,
37227,
37534,
533,
257,
12405,
284,
2198,
329,
2458,
287,
5197,
1285,
625,
1285,
526,
15931,
198,
220,
886,
62,
4475,
796,
3384,
4487,
13,
315,
66,
2197,
22446,
4475,
3419,
532,
4818,
8079,
13,
16514,
276,
12514,
7,
12545,
28,
16,
8,
198,
220,
3504,
62,
4475,
796,
886,
62,
4475,
532,
4818,
8079,
13,
16514,
276,
12514,
7,
12545,
28,
22,
8,
198,
220,
923,
62,
4475,
796,
886,
62,
4475,
532,
4818,
8079,
13,
16514,
276,
12514,
7,
12545,
28,
1415,
8,
198,
220,
1441,
12405,
62,
18982,
13,
18982,
7,
198,
220,
220,
220,
220,
220,
27039,
28,
19608,
292,
316,
11,
198,
220,
220,
220,
220,
220,
923,
62,
4475,
28,
9688,
62,
4475,
11,
198,
220,
220,
220,
220,
220,
3504,
62,
4475,
28,
27171,
62,
4475,
11,
198,
220,
220,
220,
220,
220,
886,
62,
4475,
28,
437,
62,
4475,
8,
628,
198,
2,
4042,
286,
674,
20743,
815,
2391,
2811,
257,
2214,
1438,
284,
651,
257,
8064,
4478,
198,
2,
703,
1690,
617,
4069,
8833,
13,
198,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
796,
37227,
198,
46506,
198,
220,
26080,
263,
11,
198,
220,
1693,
11,
198,
220,
35224,
15090,
3245,
62,
3672,
30072,
7054,
8064,
198,
10913,
2662,
198,
220,
22935,
19608,
292,
316,
11709,
13,
14402,
7442,
10987,
198,
47357,
198,
220,
4808,
30709,
17941,
34694,
38651,
8845,
1677,
31742,
6465,
23518,
10786,
27007,
9688,
62,
2435,
11709,
11537,
198,
220,
5357,
31742,
6465,
23518,
10786,
27007,
437,
62,
2435,
11709,
11537,
198,
46846,
11050,
198,
220,
26080,
263,
11,
198,
220,
1693,
198,
37811,
198,
198,
2,
679,
615,
813,
4646,
262,
3463,
329,
26080,
364,
543,
6777,
7014,
319,
13693,
13,
770,
198,
2,
318,
2699,
270,
1015,
286,
257,
845,
2726,
1917,
326,
1838,
340,
4047,
7485,
326,
198,
2,
356,
1183,
1064,
1997,
1141,
26080,
278,
13,
198,
2257,
7227,
8577,
62,
9419,
11211,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
940,
11,
198,
220,
220,
220,
11387,
28,
15,
13,
1795,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
13,
18982,
7,
3245,
62,
3672,
11639,
9688,
929,
62,
6098,
1077,
62,
9127,
33809,
198,
220,
220,
220,
1296,
1436,
28,
62,
30119,
62,
820,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
69,
46018,
13693,
17616,
11537,
198,
198,
2,
44048,
3463,
6454,
329,
26080,
364,
351,
867,
3105,
4991,
13,
1002,
257,
1948,
4326,
198,
2,
4539,
329,
523,
890,
326,
356,
4886,
340,
355,
257,
3105,
4326,
11,
340,
3221,
1724,
326,
262,
198,
2,
26080,
263,
318,
407,
1642,
922,
779,
286,
663,
16006,
981,
2491,
393,
2476,
257,
4259,
13,
198,
8634,
3913,
62,
4944,
2043,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
1120,
11,
198,
220,
220,
220,
11387,
28,
15,
13,
1795,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
13,
18982,
7,
3245,
62,
3672,
11639,
38246,
62,
20850,
62,
9127,
33809,
198,
220,
220,
220,
1296,
1436,
28,
62,
30119,
62,
820,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
69,
46018,
3105,
4991,
11537,
198,
198,
2,
770,
815,
886,
510,
852,
845,
2092,
284,
262,
3105,
4326,
20855,
11,
290,
318,
198,
2,
3017,
329,
262,
976,
1738,
13,
198,
34694,
12425,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
1120,
11,
198,
220,
220,
220,
11387,
28,
15,
13,
1795,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
13,
18982,
7,
3245,
62,
3672,
11639,
48678,
62,
9127,
33809,
198,
220,
220,
220,
1296,
1436,
28,
62,
30119,
62,
820,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
69,
46018,
640,
5269,
11537,
198,
198,
2,
376,
4715,
364,
543,
389,
21899,
6777,
743,
407,
307,
1642,
1336,
779,
286,
511,
198,
2,
44554,
640,
329,
26080,
278,
11,
290,
743,
886,
510,
852,
517,
4050,
1752,
262,
1900,
198,
2,
2428,
389,
5969,
13,
198,
9419,
11211,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
1120,
11,
198,
220,
220,
220,
11387,
28,
15,
13,
3829,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
13,
18982,
7,
3245,
62,
3672,
11639,
6098,
1077,
62,
9127,
33809,
198,
220,
220,
220,
1296,
1436,
28,
62,
30119,
62,
820,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
69,
46018,
17616,
11537,
198,
198,
2,
376,
4715,
364,
351,
4457,
10792,
440,
2662,
82,
743,
3994,
17316,
393,
584,
2428,
326,
198,
2,
6737,
326,
484,
761,
617,
9025,
13,
5660,
351,
257,
4622,
5322,
3463,
198,
2,
1566,
262,
2428,
389,
5969,
13,
198,
46,
2662,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
1120,
11,
198,
220,
220,
220,
11387,
28,
15,
13,
3829,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
35353,
1137,
2149,
62,
10917,
19664,
62,
21389,
1404,
13,
18982,
7,
3245,
62,
3672,
11639,
4207,
62,
9127,
33809,
198,
220,
220,
220,
1296,
1436,
28,
62,
30119,
62,
820,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
69,
46018,
440,
2662,
82,
11537,
198,
198,
2,
968,
26080,
364,
14,
43863,
815,
1057,
881,
517,
6777,
621,
1854,
13,
554,
428,
1339,
11,
356,
198,
2,
1332,
262,
13390,
286,
1528,
329,
543,
356,
423,
645,
9756,
329,
428,
26080,
263,
14,
21858,
5166,
198,
2,
290,
2620,
611,
340,
338,
1729,
22570,
13,
198,
13965,
62,
38989,
30148,
1137,
62,
21389,
1404,
796,
37227,
198,
46506,
198,
220,
26080,
263,
11,
198,
220,
1693,
11,
198,
220,
352,
355,
8064,
11,
198,
220,
20625,
28264,
30709,
17941,
34694,
8,
355,
717,
62,
2435,
198,
10913,
2662,
198,
220,
1391,
19608,
292,
316,
27422,
14402,
7442,
10987,
198,
46846,
11050,
198,
220,
26080,
263,
11,
198,
220,
1693,
198,
7801,
53,
2751,
198,
220,
717,
62,
2435,
18189,
31742,
6465,
23518,
10786,
90,
8968,
2364,
62,
2435,
92,
11537,
198,
37811,
198,
198,
13965,
62,
38989,
30148,
1137,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
20,
13,
15,
11,
198,
220,
220,
220,
11387,
28,
16,
13,
15,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
13965,
62,
38989,
30148,
1137,
62,
21389,
1404,
11,
198,
220,
220,
220,
1296,
1436,
28,
62,
3605,
62,
69,
4715,
263,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
3605,
26080,
263,
11537,
198,
198,
2,
18980,
284,
12405,
329,
26080,
364,
351,
10926,
1487,
287,
1285,
284,
1285,
5197,
13,
198,
8220,
5959,
11879,
62,
47461,
15567,
1961,
62,
21389,
1404,
796,
37227,
198,
46506,
198,
220,
2274,
13,
69,
4715,
263,
7054,
26080,
263,
11,
198,
220,
2274,
13,
21858,
7054,
1693,
11,
198,
220,
352,
355,
8064,
198,
10913,
2662,
357,
198,
220,
33493,
198,
220,
220,
220,
26080,
263,
11,
198,
220,
220,
220,
1693,
11,
198,
220,
220,
220,
25882,
7,
14907,
62,
1073,
1857,
1220,
13015,
62,
23350,
8,
7054,
5197,
198,
220,
16034,
198,
220,
220,
220,
1391,
19608,
292,
316,
27422,
14402,
7442,
10987,
198,
220,
33411,
198,
220,
220,
220,
4808,
30709,
17941,
34694,
38651,
8845,
1677,
31742,
6465,
23518,
10786,
90,
27171,
62,
4475,
92,
11537,
198,
220,
220,
220,
5357,
31742,
6465,
23518,
10786,
90,
437,
62,
4475,
92,
11537,
198,
220,
220,
220,
5357,
13015,
62,
23350,
1875,
657,
198,
220,
220,
220,
5357,
5743,
62,
1073,
1857,
1875,
657,
198,
220,
44441,
11050,
198,
220,
220,
220,
26080,
263,
11,
198,
220,
220,
220,
1693,
198,
220,
367,
10116,
2751,
198,
220,
220,
220,
5197,
19841,
352,
13,
15,
8,
7054,
2274,
198,
45006,
1268,
357,
198,
220,
33493,
198,
220,
220,
220,
26080,
263,
11,
198,
220,
220,
220,
1693,
11,
198,
220,
220,
220,
25882,
7,
14907,
62,
1073,
1857,
1220,
13015,
62,
23350,
8,
7054,
5197,
198,
220,
16034,
198,
220,
220,
220,
1391,
19608,
292,
316,
27422,
14402,
7442,
10987,
198,
220,
33411,
198,
220,
220,
220,
4808,
30709,
17941,
34694,
38651,
8845,
1677,
31742,
6465,
23518,
10786,
90,
9688,
62,
4475,
92,
11537,
198,
220,
220,
220,
5357,
31742,
6465,
23518,
10786,
90,
27171,
62,
4475,
92,
11537,
198,
220,
220,
220,
5357,
13015,
62,
23350,
1875,
657,
198,
220,
220,
220,
5357,
5743,
62,
1073,
1857,
1875,
657,
198,
220,
44441,
11050,
198,
220,
220,
220,
26080,
263,
11,
198,
220,
220,
220,
1693,
198,
220,
367,
10116,
2751,
198,
220,
220,
220,
5197,
19841,
352,
13,
15,
8,
7054,
4697,
198,
1340,
198,
220,
2274,
13,
69,
4715,
263,
796,
4697,
13,
69,
4715,
263,
198,
220,
5357,
2274,
13,
21858,
796,
4697,
13,
21858,
198,
47357,
198,
220,
29950,
19510,
49921,
13,
1073,
1857,
532,
4697,
13,
1073,
1857,
8,
1220,
2274,
13,
1073,
1857,
8,
1279,
657,
13,
486,
198,
37811,
198,
198,
8220,
5959,
11879,
62,
47461,
15567,
1961,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
15,
13,
20,
11,
198,
220,
220,
220,
11387,
28,
16,
13,
15,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
8220,
5959,
11879,
62,
47461,
15567,
1961,
62,
21389,
1404,
11,
198,
220,
220,
220,
1296,
1436,
28,
62,
1073,
1857,
62,
687,
1436,
11,
198,
220,
220,
220,
1738,
11639,
1073,
1857,
6228,
625,
1613,
362,
2745,
11537,
198,
198,
2,
337,
39242,
329,
543,
20640,
284,
779,
329,
543,
198,
40347,
38989,
30148,
1137,
62,
48451,
30643,
18421,
796,
685,
198,
220,
220,
220,
47902,
11879,
62,
47461,
15567,
1961,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
8740,
11211,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
12682,
62,
38989,
30148,
1137,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
440,
2662,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
12419,
3913,
62,
4944,
2043,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
33303,
8577,
62,
9419,
11211,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
20460,
12425,
62,
48451,
30643,
6234,
11,
198,
60,
198,
198,
32,
3697,
62,
48451,
30643,
18421,
796,
685,
198,
220,
220,
220,
8740,
11211,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
12682,
62,
38989,
30148,
1137,
62,
48451,
30643,
6234,
11,
198,
220,
220,
220,
33303,
8577,
62,
9419,
11211,
62,
48451,
30643,
6234,
11,
198,
60,
198,
198,
2,
6093,
20855,
973,
284,
13096,
4271,
14294,
19590,
284,
511,
198,
2,
4277,
3815,
618,
484,
645,
2392,
2872,
597,
584,
20640,
13,
198,
49,
6465,
6965,
62,
7206,
38865,
62,
48451,
30643,
6234,
796,
43301,
22882,
2649,
7,
198,
220,
220,
220,
12328,
62,
6551,
28,
16,
13,
15,
11,
198,
220,
220,
220,
11387,
28,
14202,
11,
198,
220,
220,
220,
12405,
62,
18982,
28,
14202,
11,
198,
220,
220,
220,
1296,
1436,
28,
14202,
11,
198,
220,
220,
220,
1738,
11639,
3919,
2392,
7466,
597,
3463,
15068,
20640,
11537,
628,
198,
4299,
4808,
22766,
62,
2978,
525,
7,
16366,
11,
12405,
2599,
198,
220,
37227,
47429,
2163,
284,
651,
26080,
263,
9756,
526,
15931,
198,
220,
1441,
5456,
13,
22766,
7,
22766,
28,
22766,
737,
8516,
628,
198,
4299,
4808,
19119,
62,
15699,
7,
31409,
62,
16684,
6637,
11,
26080,
263,
11,
1693,
11,
20855,
2599,
198,
220,
37227,
10260,
262,
3463,
329,
257,
26080,
263,
14,
21858,
526,
15931,
198,
220,
1994,
796,
357,
69,
4715,
263,
11,
1693,
8,
198,
220,
1468,
62,
15699,
796,
14451,
62,
16684,
6637,
13,
1136,
7,
2539,
11,
30617,
6965,
62,
7206,
38865,
62,
48451,
30643,
6234,
8,
628,
220,
649,
62,
6551,
796,
20855,
13,
29117,
62,
6551,
198,
220,
1468,
62,
6551,
796,
1468,
62,
15699,
13,
29117,
62,
6551,
628,
220,
1303,
16622,
4296,
262,
3463,
611,
262,
2180,
1988,
318,
262,
4277,
13,
770,
318,
198,
220,
1303,
2672,
284,
1730,
351,
20640,
326,
389,
4001,
284,
900,
262,
3463,
2029,
198,
220,
1303,
352,
13,
15,
13,
15323,
11,
32980,
691,
262,
749,
23634,
2890,
2872,
329,
428,
27356,
13,
198,
220,
611,
1468,
62,
15699,
6624,
30617,
6965,
62,
7206,
38865,
62,
48451,
30643,
6234,
393,
649,
62,
6551,
1279,
1468,
62,
6551,
25,
198,
220,
220,
220,
14451,
62,
16684,
6637,
58,
2539,
60,
796,
20855,
628,
198,
4299,
4296,
62,
6551,
62,
1640,
62,
16793,
7,
69,
4715,
62,
16793,
62,
3672,
11,
1693,
11,
20855,
2599,
198,
220,
37227,
7248,
262,
3463,
329,
257,
1948,
2496,
526,
15931,
198,
220,
2496,
62,
21858,
796,
1366,
62,
30281,
13,
1136,
62,
69,
4715,
62,
16793,
62,
21858,
7,
69,
4715,
62,
16793,
62,
3672,
11,
1693,
8,
628,
220,
611,
407,
2496,
62,
21858,
25,
198,
220,
220,
220,
17259,
13,
6404,
62,
18224,
10786,
37,
4715,
21745,
33308,
329,
2496,
4064,
82,
290,
1693,
4064,
82,
857,
407,
2152,
2637,
4064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
69,
4715,
62,
16793,
62,
3672,
11,
1693,
4008,
198,
220,
220,
220,
1441,
628,
220,
3463,
796,
20855,
13,
29117,
62,
6551,
198,
220,
17259,
13,
6404,
10786,
39668,
276,
3463,
284,
4064,
69,
329,
2496,
4064,
82,
290,
1693,
4064,
82,
37633,
82,
737,
6,
4064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
6551,
11,
26080,
62,
16793,
62,
3672,
11,
1693,
11,
20855,
13,
41181,
4008,
628,
220,
2496,
62,
21858,
13,
6551,
796,
3463,
198,
220,
2496,
62,
21858,
13,
1996,
3419,
628,
198,
4299,
4296,
62,
6759,
2052,
62,
1640,
62,
16684,
2649,
7,
16684,
2649,
11,
5456,
11,
3113,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14451,
62,
16684,
6637,
11,
1057,
62,
2617,
2599,
198,
220,
37227,
10987,
257,
12405,
290,
4532,
19590,
1912,
319,
257,
1813,
12405,
20855,
526,
15931,
198,
220,
12405,
796,
20855,
13,
687,
1436,
7,
16684,
2649,
13,
22766,
62,
18982,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26080,
263,
62,
34242,
13,
19608,
292,
316,
62,
3672,
7,
18392,
4008,
198,
220,
2482,
796,
4808,
22766,
62,
2978,
525,
7,
16366,
11,
12405,
8,
198,
220,
329,
1255,
287,
2482,
25,
198,
220,
220,
220,
26080,
263,
796,
1255,
17816,
69,
4715,
263,
20520,
198,
220,
220,
220,
1693,
796,
1255,
17816,
21858,
20520,
198,
220,
220,
220,
8064,
796,
1255,
17816,
10366,
952,
20520,
628,
220,
220,
220,
1057,
62,
2617,
13,
2860,
19510,
69,
4715,
263,
11,
1693,
4008,
198,
220,
220,
220,
611,
8064,
18189,
20855,
13,
400,
10126,
25,
198,
220,
220,
220,
220,
220,
4808,
19119,
62,
15699,
7,
31409,
62,
16684,
6637,
11,
26080,
263,
11,
1693,
11,
20855,
8,
628,
198,
4299,
4296,
62,
16793,
62,
43775,
62,
1640,
62,
18392,
7,
16366,
11,
3113,
11,
20640,
2599,
198,
220,
37227,
10260,
477,
26080,
2496,
19590,
329,
262,
7368,
3113,
526,
15931,
198,
220,
14451,
62,
16684,
6637,
796,
23884,
198,
220,
1057,
62,
2617,
796,
900,
3419,
628,
220,
1303,
1439,
26080,
364,
351,
1729,
12,
12286,
19590,
1276,
307,
18283,
351,
257,
2041,
198,
220,
1303,
20855,
13,
770,
19047,
326,
484,
481,
307,
15032,
284,
3487,
3463,
198,
220,
1303,
1752,
3403,
6666,
16895,
389,
645,
2392,
1138,
13,
198,
220,
2496,
62,
43863,
796,
1366,
62,
19199,
13,
37,
4715,
21745,
33308,
13,
22766,
7,
198,
220,
220,
220,
220,
220,
1366,
62,
19199,
13,
37,
4715,
21745,
13,
18392,
6624,
3113,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
19199,
13,
37,
4715,
21745,
33308,
13,
6551,
14512,
352,
13,
15,
8,
628,
220,
329,
2496,
62,
21858,
287,
2496,
62,
43863,
25,
198,
220,
220,
220,
14451,
62,
16684,
6637,
58,
7,
16793,
62,
21858,
13,
69,
4715,
62,
16793,
62,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2496,
62,
21858,
13,
21858,
15437,
796,
30617,
6965,
62,
7206,
38865,
62,
48451,
30643,
6234,
628,
220,
329,
20855,
287,
20640,
25,
198,
220,
220,
220,
4296,
62,
6759,
2052,
62,
1640,
62,
16684,
2649,
7,
16684,
2649,
11,
5456,
11,
3113,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14451,
62,
16684,
6637,
11,
1057,
62,
2617,
8,
628,
220,
329,
357,
69,
4715,
263,
11,
1693,
828,
20855,
287,
14451,
62,
16684,
6637,
13,
2676,
23814,
33529,
198,
220,
220,
220,
611,
357,
69,
4715,
263,
11,
1693,
8,
407,
287,
1057,
62,
2617,
25,
198,
220,
220,
220,
220,
220,
1303,
770,
19047,
326,
356,
836,
470,
13259,
19590,
329,
26080,
364,
351,
2761,
611,
198,
220,
220,
220,
220,
220,
1303,
484,
1422,
470,
1057,
287,
262,
640,
5017,
416,
674,
20743,
13,
198,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
4296,
62,
6551,
62,
1640,
62,
16793,
7,
69,
4715,
263,
11,
1693,
11,
20855,
8,
628,
220,
17259,
13,
6404,
10786,
25844,
16895,
1844,
329,
3113,
4064,
82,
2637,
4064,
3113,
8,
628,
198,
4299,
3650,
62,
14421,
62,
43775,
62,
259,
62,
14261,
22766,
33529,
198,
220,
37227,
10260,
257,
1263,
22766,
3084,
7268,
262,
4445,
9756,
526,
15931,
198,
220,
15274,
796,
17635,
198,
220,
2496,
62,
43863,
796,
299,
9945,
62,
26791,
13,
1136,
62,
439,
62,
6738,
62,
19849,
7,
7890,
62,
19199,
13,
37,
4715,
21745,
33308,
8,
198,
220,
329,
2496,
62,
21858,
287,
2496,
62,
43863,
25,
198,
220,
220,
220,
5752,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
705,
69,
4715,
263,
10354,
2496,
62,
21858,
13,
69,
4715,
62,
16793,
62,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
705,
21858,
10354,
2496,
62,
21858,
13,
21858,
11,
198,
220,
220,
220,
220,
220,
220,
220,
705,
6551,
10354,
2496,
62,
21858,
13,
6551,
198,
220,
220,
220,
1782,
198,
220,
220,
220,
15274,
13,
33295,
7,
14261,
62,
22766,
13,
44402,
7,
808,
28,
808,
11,
7550,
62,
312,
28,
14202,
4008,
628,
220,
5456,
796,
1263,
62,
22766,
13,
11792,
7,
19608,
292,
316,
62,
312,
11639,
12417,
3256,
3084,
62,
312,
11639,
69,
4715,
263,
62,
43775,
11537,
198,
220,
5456,
13,
28463,
7,
8516,
8,
628,
198,
4871,
32412,
7,
8692,
62,
30281,
13,
25060,
2599,
198,
220,
37227,
25060,
284,
26034,
4296,
26080,
2496,
19590,
1912,
319,
2854,
526,
15931,
628,
220,
2488,
30281,
13,
9122,
62,
66,
1313,
3419,
198,
220,
825,
651,
7,
944,
2599,
198,
220,
220,
220,
37227,
18709,
477,
26080,
6670,
290,
4296,
376,
4715,
21745,
33308,
19590,
526,
15931,
198,
220,
220,
220,
5456,
796,
1263,
62,
22766,
13,
11792,
3419,
198,
220,
220,
220,
4296,
62,
16793,
62,
43775,
62,
1640,
62,
18392,
7,
16366,
11,
705,
8019,
37,
4715,
263,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45651,
38989,
30148,
1137,
62,
48451,
30643,
18421,
8,
198,
220,
220,
220,
4296,
62,
16793,
62,
43775,
62,
1640,
62,
18392,
7,
16366,
11,
705,
1878,
75,
3256,
25363,
62,
48451,
30643,
18421,
8,
628,
220,
220,
220,
3650,
62,
14421,
62,
43775,
62,
259,
62,
14261,
22766,
3419,
198
] | 2.910929 | 3,907 |
from __future__ import (
unicode_literals,
absolute_import,
print_function,
division,
)
import sys
from PySide2 import QtCore
import avb
if str is not bytes:
unicode = str
if __name__ == "__main__":
from PySide2 import QtWidgets
from optparse import OptionParser
parser = OptionParser()
parser.add_option('-m','--mobs',action="store_true", default=False)
parser.add_option('-t','--toplevel',action="store_true", default=False)
(options, args) = parser.parse_args()
if not args:
parser.error("not enough arguments")
file_path = args[0]
f = avb.open(file_path)
root = f.content
if options.toplevel:
root = list(f.content.toplevel())
if options.mobs:
root = list(f.content.mobs)
app = QtWidgets.QApplication(sys.argv)
model = AVBModel(root)
use_column = False
if use_column:
tree = QtWidgets.QColumnView()
tree.setModel(model)
else:
tree = QtWidgets.QTreeView()
tree.setModel(model)
tree.setUniformRowHeights(True)
tree.expandToDepth(1)
tree.resizeColumnToContents(0)
tree.resizeColumnToContents(1)
tree.resize(700,600)
tree.setAlternatingRowColors(True)
tree.show()
sys.exit(app.exec_())
| [
6738,
11593,
37443,
834,
1330,
357,
198,
220,
220,
220,
28000,
1098,
62,
17201,
874,
11,
198,
220,
220,
220,
4112,
62,
11748,
11,
198,
220,
220,
220,
3601,
62,
8818,
11,
198,
220,
220,
220,
7297,
11,
198,
220,
220,
220,
1267,
198,
11748,
25064,
198,
6738,
9485,
24819,
17,
1330,
33734,
14055,
198,
198,
11748,
1196,
65,
198,
198,
361,
965,
318,
407,
9881,
25,
198,
220,
220,
220,
28000,
1098,
796,
965,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
628,
220,
220,
220,
422,
9485,
24819,
17,
1330,
33734,
54,
312,
11407,
198,
220,
220,
220,
422,
2172,
29572,
1330,
16018,
46677,
628,
220,
220,
220,
30751,
796,
16018,
46677,
3419,
198,
220,
220,
220,
30751,
13,
2860,
62,
18076,
10786,
12,
76,
41707,
438,
76,
8158,
3256,
2673,
2625,
8095,
62,
7942,
1600,
4277,
28,
25101,
8,
198,
220,
220,
220,
30751,
13,
2860,
62,
18076,
10786,
12,
83,
41707,
438,
83,
643,
626,
3256,
2673,
2625,
8095,
62,
7942,
1600,
4277,
28,
25101,
8,
628,
220,
220,
220,
357,
25811,
11,
26498,
8,
796,
30751,
13,
29572,
62,
22046,
3419,
628,
220,
220,
220,
611,
407,
26498,
25,
198,
220,
220,
220,
220,
220,
220,
220,
30751,
13,
18224,
7203,
1662,
1576,
7159,
4943,
628,
220,
220,
220,
2393,
62,
6978,
796,
26498,
58,
15,
60,
628,
220,
220,
220,
277,
796,
1196,
65,
13,
9654,
7,
7753,
62,
6978,
8,
628,
220,
220,
220,
6808,
796,
277,
13,
11299,
198,
220,
220,
220,
611,
3689,
13,
83,
643,
626,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6808,
796,
1351,
7,
69,
13,
11299,
13,
83,
643,
626,
28955,
198,
220,
220,
220,
611,
3689,
13,
76,
8158,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6808,
796,
1351,
7,
69,
13,
11299,
13,
76,
8158,
8,
628,
220,
220,
220,
598,
796,
33734,
54,
312,
11407,
13,
48,
23416,
7,
17597,
13,
853,
85,
8,
628,
220,
220,
220,
2746,
796,
14661,
33,
17633,
7,
15763,
8,
628,
220,
220,
220,
779,
62,
28665,
796,
10352,
628,
220,
220,
220,
611,
779,
62,
28665,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
33734,
54,
312,
11407,
13,
48,
39470,
7680,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
2617,
17633,
7,
19849,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
33734,
54,
312,
11407,
13,
48,
27660,
7680,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
2617,
17633,
7,
19849,
8,
628,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
2617,
3118,
6933,
25166,
1544,
2337,
7,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
11201,
392,
2514,
48791,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
411,
1096,
39470,
2514,
15842,
7,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
411,
1096,
39470,
2514,
15842,
7,
16,
8,
628,
220,
220,
220,
5509,
13,
411,
1096,
7,
9879,
11,
8054,
8,
198,
220,
220,
220,
5509,
13,
2617,
23081,
803,
25166,
5216,
669,
7,
17821,
8,
628,
220,
220,
220,
5509,
13,
12860,
3419,
628,
220,
220,
220,
25064,
13,
37023,
7,
1324,
13,
18558,
62,
28955,
198
] | 2.343525 | 556 |
from pytensor.network.variable import *
from pytensor.network.parameter import *
from pytensor.network.operation import *
| [
6738,
12972,
83,
22854,
13,
27349,
13,
45286,
1330,
1635,
198,
6738,
12972,
83,
22854,
13,
27349,
13,
17143,
2357,
1330,
1635,
198,
6738,
12972,
83,
22854,
13,
27349,
13,
27184,
1330,
1635,
198
] | 3.588235 | 34 |
"""Common shell interaction logic shared between different shells"""
from __future__ import print_function
import os
import sys
import inspect
import subprocess
import pyparsing as pp
from six.moves import input
from friendlyshell.command_parsers import default_line_parser
# Path where configuration data is stored for friendly shells
CONFIG_FOLDER = os.path.expanduser(os.path.join("~", ".friendlyshell"))
# pylint: disable=no-member
class BaseShell(object):
"""Common base class for all Friendly Shells
Defines basic IO and interactive shell logic common to all Friendly Shells
"""
@property
def return_code(self):
"""error / return code generated by operations run by this shell
:rtype: :class:`int`
"""
return self._return_code
@property
def _config_folder(self):
"""Gets the folder where config and log files should be stored
:rtype: :class:`str`
"""
# Create our config folder with restricted access to everyone but the
# owner. This is just in case we write secrets to a log / history file
# by accident then only the current user can see it.
if not os.path.exists(CONFIG_FOLDER):
os.makedirs(CONFIG_FOLDER, 0o700)
return CONFIG_FOLDER
def _process_error(self, err_code):
"""Helper method used to track error codes
When running in batch mode this helper method with terminate the running
shell session under the assumption that any subsequent operations that
may be performed by the shell will likely fail as a result of the first
failure anyway.
:param int err_code: return code to set in the shell instance"""
self._return_code = err_code
# See if we're running in batch mode and terminate the shell if we are
if self._input_stream:
self.do_exit()
def _get_input(self):
"""Gets input to be processed from the appropriate source
:returns: the input line retrieved from the source
:rtype: :class:`str`
"""
try:
if self._input_stream:
line = self._input_stream.readline()
if not line:
self._input_stream = None
else:
line = line.strip()
self.info(self.prompt + line)
else:
line = input(self.prompt)
if line:
line = line.strip()
return line
except KeyboardInterrupt:
# When the user enters CTRL+C to terminate the shell, we just
# terminate the currently running shell. That way if there is
# a parent shell in play control can be returned to it so the
# user can attempt to recover from whatever operation they
# tried to abort
self._done = True
return None
except Exception as err: # pylint: disable=broad-except
self.error(
'Unexpected error during input sequence: %s',
err
)
# Reserve the detailed debug info / stack trace to the debug
# output only. This avoids spitting out lots of technical
# garbage to the user
self.debug(err, exc_info=True)
self._done = True
self._process_error(1)
return None
def _execute_command(self, func, parser):
"""Calls a command function with a set of parsed parameters
:param func: the command function to execute
:param parser: The parsed command parameters to pass to the command
"""
try:
if not parser.params:
func()
return
params_to_pass = parser.params
num_params_total = self._count_params(func)
if len(params_to_pass) > num_params_total:
# If we have more tokens than parameters on the command function
# we concatenate the extraneous tokens with the last parameter
# assuming the command function is going to parse the tokens
# itself or otherwise perform it's logic on the unparsed
# input
self.debug("too many tokens - concatenating extras")
num_params_to_compress = \
len(params_to_pass) - num_params_total + 1
self.debug("params to compress %s", num_params_to_compress)
compressed = " ".join(params_to_pass[-num_params_to_compress:])
self.debug("compressed params: %s", compressed)
params_to_pass = params_to_pass[:-num_params_to_compress]
params_to_pass.append(compressed)
func(*params_to_pass)
except Exception as err: # pylint: disable=broad-except
# Log summary info about the error to standard error output
self.error('Unknown error detected: %s', err)
# Reserve the detailed debug info / stack trace to the debug
# output only. This avoids spitting out lots of technical
# garbage to the user
self.debug(str(err), exc_info=True)
self._process_error(1)
except KeyboardInterrupt:
self.debug("User interrupted operation...")
# Typically, when a user cancels an operation there will be at
# least some partial output generated by the command so we
# write out a blank to ensure the interactive prompt appears on
# the line below
self.info("")
def do_native_shell(self, cmd):
"""Executes a shell command within the Friendly Shell environment"""
self.debug("Running shell command %s", cmd)
try:
output = subprocess.check_output(
cmd,
shell=True,
stderr=subprocess.STDOUT)
self.info(output.decode("utf-8"))
except subprocess.CalledProcessError as err:
self.info("Failed to run command %s: %s", err.cmd, err.returncode)
self.info(err.output)
self._process_error(1)
except KeyboardInterrupt:
self.debug("User interrupted operation...")
# Typically, when a user cancels an operation there will be at
# least some partial output generated by the command so we
# write out a blank to ensure the interactive prompt appears on
# the line below
self.info("")
@staticmethod
def alias_native_shell():
"""Gets the shorthand character for the 'native_shell' command
:rtype: :class:`str`
"""
return "!"
def run_subshell(self, subshell):
"""Launches a child process for another shell under this one
:param subshell: the new Friendly Shell to be launched"""
subshell.run(input_stream=self._input_stream, parent=self)
# save the return code from our child shell here in the parent so it
# may be propagated back to the shell if needed
self._return_code = subshell.return_code
def run(self, *_args, **kwargs):
"""Main entry point function that launches our command line interpreter
This method will wait for input to be given via the command line, and
process each command provided until a request to terminate the shell is
given.
:param input_stream:
optional Python input stream object where commands should be loaded
from. Typically this will be a file-like object containing commands
to be run, but any input stream object should work.
If not provided, input will be read from stdin using :meth:`input`
:param parent:
Optional parent shell which owns this shell. If none provided this
shell is assumed to be a parent or first level shell session with
no ancestry
"""
self._input_stream = \
kwargs.pop("input_stream") if "input_stream" in kwargs else None
self._parent = kwargs.pop("parent") if "parent" in kwargs else None
if self.banner_text:
self.info(self.banner_text)
while not self._done:
line = self._get_input()
if not line:
continue
if line.startswith(self.comment_delimiter):
self.debug("Skipping comment line %s", line)
continue
# Before we process our command input, see if we need to
# substitute any environment variables that may be used
line = os.path.expandvars(line)
parser = self._parse_line(line)
if parser is None:
self._process_error(1)
continue
func = self._find_command(parser.command)
if not func:
self.error("Command not found: %s", parser.command)
self._process_error(1)
continue
if not self._check_params(func, parser):
self._process_error(1)
continue
self._execute_command(func, parser)
def _check_params(self, func, parser):
"""Are there sufficient tokens to populate command parameters
:param func: command function to be called
:param parser: parsed tokens rom the shell
:returns:
true if there are sufficient parameters to call the command, false
if not
:rtype: :class:`bool`
"""
num_tokens = len(parser.params) if parser.params else 0
num_required_params = self._count_required_params(func)
total_num_params = self._count_params(func)
if total_num_params == 0 and num_tokens != 0:
msg = "Command %s accepts no parameters but %s provided."
self.error(
msg,
func.__name__.replace("do_", ""),
num_tokens
)
return False
if num_tokens < num_required_params:
msg = 'Command %s requires %s parameters but %s provided.'
self.error(
msg,
func.__name__.replace("do_", ""),
num_required_params,
num_tokens)
return False
return True
def _count_required_params(self, cmd_method):
"""Gets the number of required parameters from a command method
:param cmd_method:
:class:`inspect.Signature` for method to analyse
:returns:
Number of required parameters (ie: parameters without default
values) for the given method
:rtype: :class:`int`
"""
if sys.version_info < (3, 3):
params = inspect.getargspec(cmd_method) # pylint: disable=deprecated-method
self.debug(
'Command %s params are: %s',
cmd_method.__name__,
params)
tmp = params.args
if 'self' in tmp:
tmp.remove('self')
return len(tmp) - (len(params.defaults) if params.defaults else 0)
func_sig = inspect.signature(cmd_method) # pylint: disable=no-member
retval = 0
for cur_param in func_sig.parameters.values():
if cur_param.default is inspect.Parameter.empty: # pylint: disable=no-member
retval += 1
return retval
def _count_params(self, cmd_method):
"""Gets the total number of parameters from a command method
:param cmd_method:
:class:`inspect.Signature` for method to analyse
:returns:
Number of parameters supported by the given method
:rtype: :class:`int`
"""
if sys.version_info < (3, 3):
params = inspect.getargspec(cmd_method) # pylint: disable=deprecated-method
self.debug(
'Command %s params are: %s',
cmd_method.__name__,
params)
tmp = params.args
if 'self' in tmp:
tmp.remove('self')
return len(tmp)
func_sig = inspect.signature(cmd_method) # pylint: disable=no-member
return len(func_sig.parameters)
def _parse_line(self, line):
"""Parses a single line of command text and returns the parsed output
:param str line: line of command text to be parsed
:returns: Parser object describing all of the parsed command tokens
:rtype: :class:`pyparsing.ParseResults`"""
self.debug('Parsing command input "%s"...', line)
try:
retval = self._parser.parseString(line, parseAll=True)
except pp.ParseException as err:
self.error('Parsing error:')
self.error('\t%s', err.pstr)
self.error('\t%s^', ' ' * (err.col-1))
self.debug('Details: %s', err)
return None
self.debug('Parsed command line is "%s"', retval)
return retval
def _find_command(self, command_name):
"""Attempts to locate the command handler for a given command
:param str command_name: The name of the command to find the handler for
:returns: Reference to the method to be called to execute the command
Returns None if no command method found
:rtype: :class:`meth`
"""
self.debug("looking for command method...")
# Gather all class methods, including static methods
all_methods = inspect.getmembers(self, inspect.ismethod)
all_methods.extend(inspect.getmembers(self, inspect.isfunction))
# See if we can find a 'do_' method for our command...
for cur_method in all_methods:
self.debug("Processing %s", cur_method)
if cur_method[0] == 'do_' + command_name:
self.debug("command method found: %s", cur_method[0])
return cur_method[1]
# if no command method can be found for the specified token,
# try looking up an alias for the command as well:
self.debug("Looking for alias...")
for cur_method in all_methods:
if not cur_method[0].startswith("alias_"):
continue
self.debug("Found alias method %s", cur_method[0])
if cur_method[1]() == command_name:
orig_cmd_name = cur_method[0][len("alias_"):]
self.debug("Recursing to find alias command %s", orig_cmd_name)
return self._find_command(orig_cmd_name)
self.debug("No command found with name " + command_name)
return None
def do_exit(self):
"""Terminates the command interpreter"""
self.debug('Terminating interpreter...')
self._done = True
# See if our shell has any parents, and force them to quit too
if self._parent:
self._parent.do_exit()
def do_close(self):
"""Terminates the currently running shell"""
self.debug(
'Closing shell %s (%s)',
self.__class__.__name__,
self.prompt)
# Return control back to the parent Friendly Shell or the console,
# whichever comes next in the shell's ancestry
self._done = True
@staticmethod
def help_close():
"""Extended help for close method"""
return """If the current shell is a sub-shell spawned by another """\
"""Friendly Shell instance, control will return to the """\
"""parent shell which will continue running"""
@staticmethod
def info(message, *args, **_kwargs):
"""Displays an info message to the default output stream
Default implementation just directs output to stdout. Use a logging
mixin class to customize this behavior.
See :class:`friendlyshell.basic_logger_mixin.BasicLoggerMixin` for
examples.
:param str message: text to be displayed"""
print(message % args)
@staticmethod
def warning(message, *args, **_kwargs):
"""Displays a non-critical warning message to the default output stream
Default implementation just directs output to stdout. Use a logging
mixin class to customize this behavior.
See :class:`friendlyshell.basic_logger_mixin.BasicLoggerMixin` for
examples.
:param str message: text to be displayed"""
print(message % args)
@staticmethod
def error(message, *args, **_kwargs):
"""Displays a critical error message to the default output stream
Default implementation just directs output to stdout. Use a logging
mixin class to customize this behavior.
See :class:`friendlyshell.basic_logger_mixin.BasicLoggerMixin` for
examples.
:param str message: text to be displayed"""
print(message % args)
@staticmethod
def debug(message, *args, **_kwargs):
"""Displays an internal-use-only debug message to verbose log file
Default implementation hides all debug output. Use a logging mixin
class to customize this behavior.
See :class:`friendlyshell.basic_logger_mixin.BasicLoggerMixin` for
examples.
:param str message: text to be displayed"""
if __name__ == "__main__":
pass
| [
37811,
17227,
7582,
10375,
9156,
4888,
1022,
1180,
19679,
37811,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
10104,
198,
11748,
850,
14681,
198,
11748,
279,
4464,
945,
278,
355,
9788,
198,
6738,
2237,
13,
76,
5241,
1330,
5128,
198,
6738,
8030,
29149,
13,
21812,
62,
79,
945,
364,
1330,
4277,
62,
1370,
62,
48610,
198,
198,
2,
10644,
810,
8398,
1366,
318,
8574,
329,
8030,
19679,
198,
10943,
16254,
62,
37,
3535,
14418,
796,
28686,
13,
6978,
13,
11201,
392,
7220,
7,
418,
13,
6978,
13,
22179,
7203,
93,
1600,
27071,
13120,
29149,
48774,
628,
198,
2,
279,
2645,
600,
25,
15560,
28,
3919,
12,
19522,
198,
4871,
7308,
23248,
7,
15252,
2599,
198,
220,
220,
220,
37227,
17227,
2779,
1398,
329,
477,
38683,
17537,
82,
628,
220,
220,
220,
2896,
1127,
4096,
24418,
290,
14333,
7582,
9156,
2219,
284,
477,
38683,
17537,
82,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
1441,
62,
8189,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
18224,
1220,
1441,
2438,
7560,
416,
4560,
1057,
416,
428,
7582,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
600,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
7783,
62,
8189,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
4808,
11250,
62,
43551,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
9483,
810,
4566,
290,
2604,
3696,
815,
307,
8574,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
2536,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
13610,
674,
4566,
9483,
351,
10770,
1895,
284,
2506,
475,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4870,
13,
770,
318,
655,
287,
1339,
356,
3551,
13141,
284,
257,
2604,
1220,
2106,
2393,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
416,
5778,
788,
691,
262,
1459,
2836,
460,
766,
340,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
10943,
16254,
62,
37,
3535,
14418,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
10943,
16254,
62,
37,
3535,
14418,
11,
657,
78,
9879,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
25626,
62,
37,
3535,
14418,
628,
220,
220,
220,
825,
4808,
14681,
62,
18224,
7,
944,
11,
11454,
62,
8189,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
47429,
2446,
973,
284,
2610,
4049,
12416,
628,
220,
220,
220,
220,
220,
220,
220,
1649,
2491,
287,
15458,
4235,
428,
31904,
2446,
351,
23654,
262,
2491,
198,
220,
220,
220,
220,
220,
220,
220,
7582,
6246,
739,
262,
13196,
326,
597,
8840,
4560,
326,
198,
220,
220,
220,
220,
220,
220,
220,
743,
307,
6157,
416,
262,
7582,
481,
1884,
2038,
355,
257,
1255,
286,
262,
717,
198,
220,
220,
220,
220,
220,
220,
220,
5287,
6949,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
493,
11454,
62,
8189,
25,
1441,
2438,
284,
900,
287,
262,
7582,
4554,
37811,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
7783,
62,
8189,
796,
11454,
62,
8189,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
4091,
611,
356,
821,
2491,
287,
15458,
4235,
290,
23654,
262,
7582,
611,
356,
389,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13557,
15414,
62,
5532,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
4598,
62,
37023,
3419,
628,
220,
220,
220,
825,
4808,
1136,
62,
15414,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
5128,
284,
307,
13686,
422,
262,
5035,
2723,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
262,
5128,
1627,
29517,
422,
262,
2723,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
2536,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13557,
15414,
62,
5532,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
2116,
13557,
15414,
62,
5532,
13,
961,
1370,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1627,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
15414,
62,
5532,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
1627,
13,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7,
944,
13,
16963,
457,
1343,
1627,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
5128,
7,
944,
13,
16963,
457,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1627,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
1627,
13,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1627,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
31973,
9492,
3622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1649,
262,
2836,
14170,
45249,
10,
34,
284,
23654,
262,
7582,
11,
356,
655,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
23654,
262,
3058,
2491,
7582,
13,
1320,
835,
611,
612,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
257,
2560,
7582,
287,
711,
1630,
460,
307,
4504,
284,
340,
523,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2836,
460,
2230,
284,
8551,
422,
4232,
4905,
484,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3088,
284,
15614,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
28060,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
11454,
25,
220,
1303,
279,
2645,
600,
25,
15560,
28,
36654,
12,
16341,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
52,
42072,
4049,
1141,
5128,
8379,
25,
4064,
82,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11454,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
12224,
262,
6496,
14257,
7508,
1220,
8931,
12854,
284,
262,
14257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
5072,
691,
13,
770,
30940,
46266,
503,
6041,
286,
6276,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
15413,
284,
262,
2836,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7,
8056,
11,
2859,
62,
10951,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
28060,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
628,
220,
220,
220,
825,
4808,
41049,
62,
21812,
7,
944,
11,
25439,
11,
30751,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
34,
5691,
257,
3141,
2163,
351,
257,
900,
286,
44267,
10007,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
25439,
25,
262,
3141,
2163,
284,
12260,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
30751,
25,
383,
44267,
3141,
10007,
284,
1208,
284,
262,
3141,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
30751,
13,
37266,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
62,
1462,
62,
6603,
796,
30751,
13,
37266,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
37266,
62,
23350,
796,
2116,
13557,
9127,
62,
37266,
7,
20786,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
37266,
62,
1462,
62,
6603,
8,
1875,
997,
62,
37266,
62,
23350,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1002,
356,
423,
517,
16326,
621,
10007,
319,
262,
3141,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
356,
1673,
36686,
378,
262,
22820,
11655,
16326,
351,
262,
938,
11507,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
13148,
262,
3141,
2163,
318,
1016,
284,
21136,
262,
16326,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2346,
393,
4306,
1620,
340,
338,
9156,
319,
262,
8593,
945,
276,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
5128,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
18820,
867,
16326,
532,
1673,
36686,
803,
33849,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
37266,
62,
1462,
62,
5589,
601,
796,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18896,
7,
37266,
62,
1462,
62,
6603,
8,
532,
997,
62,
37266,
62,
23350,
1343,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
37266,
284,
27413,
4064,
82,
1600,
997,
62,
37266,
62,
1462,
62,
5589,
601,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25388,
796,
366,
27071,
22179,
7,
37266,
62,
1462,
62,
6603,
58,
12,
22510,
62,
37266,
62,
1462,
62,
5589,
601,
25,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
5589,
2790,
42287,
25,
4064,
82,
1600,
25388,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
62,
1462,
62,
6603,
796,
42287,
62,
1462,
62,
6603,
58,
21912,
22510,
62,
37266,
62,
1462,
62,
5589,
601,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
62,
1462,
62,
6603,
13,
33295,
7,
5589,
2790,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
46491,
37266,
62,
1462,
62,
6603,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
11454,
25,
220,
1303,
279,
2645,
600,
25,
15560,
28,
36654,
12,
16341,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
5972,
10638,
7508,
546,
262,
4049,
284,
3210,
4049,
5072,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
10786,
20035,
4049,
12326,
25,
4064,
82,
3256,
11454,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
12224,
262,
6496,
14257,
7508,
1220,
8931,
12854,
284,
262,
14257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
5072,
691,
13,
770,
30940,
46266,
503,
6041,
286,
6276,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
15413,
284,
262,
2836,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7,
2536,
7,
8056,
828,
2859,
62,
10951,
28,
17821,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
31973,
9492,
3622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
12982,
19072,
4905,
9313,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
27095,
11,
618,
257,
2836,
14241,
82,
281,
4905,
612,
481,
307,
379,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1551,
617,
13027,
5072,
7560,
416,
262,
3141,
523,
356,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3551,
503,
257,
9178,
284,
4155,
262,
14333,
6152,
3568,
319,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
262,
1627,
2174,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7203,
4943,
628,
220,
220,
220,
825,
466,
62,
30191,
62,
29149,
7,
944,
11,
23991,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
23002,
1769,
257,
7582,
3141,
1626,
262,
38683,
17537,
2858,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
28768,
7582,
3141,
4064,
82,
1600,
23991,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
850,
14681,
13,
9122,
62,
22915,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
23991,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7582,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
336,
1082,
81,
28,
7266,
14681,
13,
36886,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7,
22915,
13,
12501,
1098,
7203,
40477,
12,
23,
48774,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
850,
14681,
13,
34,
4262,
18709,
12331,
355,
11454,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7203,
37,
6255,
284,
1057,
3141,
4064,
82,
25,
4064,
82,
1600,
11454,
13,
28758,
11,
11454,
13,
7783,
8189,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7,
8056,
13,
22915,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
31973,
9492,
3622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
12982,
19072,
4905,
9313,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
27095,
11,
618,
257,
2836,
14241,
82,
281,
4905,
612,
481,
307,
379,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1551,
617,
13027,
5072,
7560,
416,
262,
3141,
523,
356,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3551,
503,
257,
9178,
284,
4155,
262,
14333,
6152,
3568,
319,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
262,
1627,
2174,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7203,
4943,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
16144,
62,
30191,
62,
29149,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
45883,
2095,
329,
262,
705,
30191,
62,
29149,
6,
3141,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
2536,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
2474,
628,
220,
220,
220,
825,
1057,
62,
7266,
29149,
7,
944,
11,
6352,
12758,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
46182,
2052,
257,
1200,
1429,
329,
1194,
7582,
739,
428,
530,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
6352,
12758,
25,
262,
649,
38683,
17537,
284,
307,
5611,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
6352,
12758,
13,
5143,
7,
15414,
62,
5532,
28,
944,
13557,
15414,
62,
5532,
11,
2560,
28,
944,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3613,
262,
1441,
2438,
422,
674,
1200,
7582,
994,
287,
262,
2560,
523,
340,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
743,
307,
8928,
515,
736,
284,
262,
7582,
611,
2622,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
7783,
62,
8189,
796,
6352,
12758,
13,
7783,
62,
8189,
628,
220,
220,
220,
825,
1057,
7,
944,
11,
1635,
62,
22046,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13383,
5726,
966,
2163,
326,
18617,
674,
3141,
1627,
28846,
628,
220,
220,
220,
220,
220,
220,
220,
770,
2446,
481,
4043,
329,
5128,
284,
307,
1813,
2884,
262,
3141,
1627,
11,
290,
198,
220,
220,
220,
220,
220,
220,
220,
1429,
1123,
3141,
2810,
1566,
257,
2581,
284,
23654,
262,
7582,
318,
198,
220,
220,
220,
220,
220,
220,
220,
1813,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
5128,
62,
5532,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11902,
11361,
5128,
4269,
2134,
810,
9729,
815,
307,
9639,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
422,
13,
27095,
428,
481,
307,
257,
2393,
12,
2339,
2134,
7268,
9729,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
307,
1057,
11,
475,
597,
5128,
4269,
2134,
815,
670,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
407,
2810,
11,
5128,
481,
307,
1100,
422,
14367,
259,
1262,
1058,
76,
2788,
25,
63,
15414,
63,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
2560,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32233,
2560,
7582,
543,
12216,
428,
7582,
13,
1002,
4844,
2810,
428,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7582,
318,
9672,
284,
307,
257,
2560,
393,
717,
1241,
7582,
6246,
351,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
29171,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
15414,
62,
5532,
796,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
479,
86,
22046,
13,
12924,
7203,
15414,
62,
5532,
4943,
611,
366,
15414,
62,
5532,
1,
287,
479,
86,
22046,
2073,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
8000,
796,
479,
86,
22046,
13,
12924,
7203,
8000,
4943,
611,
366,
8000,
1,
287,
479,
86,
22046,
2073,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
3820,
1008,
62,
5239,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10951,
7,
944,
13,
3820,
1008,
62,
5239,
8,
628,
220,
220,
220,
220,
220,
220,
220,
981,
407,
2116,
13557,
28060,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
2116,
13557,
1136,
62,
15414,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1627,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1627,
13,
9688,
2032,
342,
7,
944,
13,
23893,
62,
12381,
320,
2676,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
50,
4106,
2105,
2912,
1627,
4064,
82,
1600,
1627,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7413,
356,
1429,
674,
3141,
5128,
11,
766,
611,
356,
761,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
15373,
597,
2858,
9633,
326,
743,
307,
973,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
28686,
13,
6978,
13,
11201,
392,
85,
945,
7,
1370,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30751,
796,
2116,
13557,
29572,
62,
1370,
7,
1370,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
30751,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
796,
2116,
13557,
19796,
62,
21812,
7,
48610,
13,
21812,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
25439,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
7203,
21575,
407,
1043,
25,
4064,
82,
1600,
30751,
13,
21812,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
2116,
13557,
9122,
62,
37266,
7,
20786,
11,
30751,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
14681,
62,
18224,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
41049,
62,
21812,
7,
20786,
11,
30751,
8,
628,
220,
220,
220,
825,
4808,
9122,
62,
37266,
7,
944,
11,
25439,
11,
30751,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
8491,
612,
6751,
16326,
284,
48040,
3141,
10007,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
25439,
25,
3141,
2163,
284,
307,
1444,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
30751,
25,
44267,
16326,
9267,
262,
7582,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2081,
611,
612,
389,
6751,
10007,
284,
869,
262,
3141,
11,
3991,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
30388,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
83,
482,
641,
796,
18896,
7,
48610,
13,
37266,
8,
611,
30751,
13,
37266,
2073,
657,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
35827,
62,
37266,
796,
2116,
13557,
9127,
62,
35827,
62,
37266,
7,
20786,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2472,
62,
22510,
62,
37266,
796,
2116,
13557,
9127,
62,
37266,
7,
20786,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2472,
62,
22510,
62,
37266,
6624,
657,
290,
997,
62,
83,
482,
641,
14512,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
796,
366,
21575,
4064,
82,
18178,
645,
10007,
475,
4064,
82,
2810,
526,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
13,
834,
3672,
834,
13,
33491,
7203,
4598,
62,
1600,
366,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
83,
482,
641,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
10352,
628,
220,
220,
220,
220,
220,
220,
220,
611,
997,
62,
83,
482,
641,
1279,
997,
62,
35827,
62,
37266,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
796,
705,
21575,
4064,
82,
4433,
4064,
82,
10007,
475,
4064,
82,
2810,
2637,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
13,
834,
3672,
834,
13,
33491,
7203,
4598,
62,
1600,
366,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
35827,
62,
37266,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
83,
482,
641,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6407,
628,
220,
220,
220,
825,
4808,
9127,
62,
35827,
62,
37266,
7,
944,
11,
23991,
62,
24396,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
1271,
286,
2672,
10007,
422,
257,
3141,
2446,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
23991,
62,
24396,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
63,
1040,
806,
13,
11712,
1300,
63,
329,
2446,
284,
39552,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7913,
286,
2672,
10007,
357,
494,
25,
10007,
1231,
4277,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
8,
329,
262,
1813,
2446,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
600,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
25064,
13,
9641,
62,
10951,
1279,
357,
18,
11,
513,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
796,
10104,
13,
1136,
853,
16684,
7,
28758,
62,
24396,
8,
220,
1303,
279,
2645,
600,
25,
15560,
28,
10378,
31023,
12,
24396,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
21575,
4064,
82,
42287,
389,
25,
4064,
82,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
23991,
62,
24396,
13,
834,
3672,
834,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45218,
796,
42287,
13,
22046,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
944,
6,
287,
45218,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45218,
13,
28956,
10786,
944,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
18896,
7,
22065,
8,
532,
357,
11925,
7,
37266,
13,
12286,
82,
8,
611,
42287,
13,
12286,
82,
2073,
657,
8,
628,
220,
220,
220,
220,
220,
220,
220,
25439,
62,
82,
328,
796,
10104,
13,
12683,
1300,
7,
28758,
62,
24396,
8,
220,
1303,
279,
2645,
600,
25,
15560,
28,
3919,
12,
19522,
198,
220,
220,
220,
220,
220,
220,
220,
1005,
2100,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1090,
62,
17143,
287,
25439,
62,
82,
328,
13,
17143,
7307,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1090,
62,
17143,
13,
12286,
318,
10104,
13,
36301,
13,
28920,
25,
220,
1303,
279,
2645,
600,
25,
15560,
28,
3919,
12,
19522,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1005,
2100,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1005,
2100,
628,
220,
220,
220,
825,
4808,
9127,
62,
37266,
7,
944,
11,
23991,
62,
24396,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
2472,
1271,
286,
10007,
422,
257,
3141,
2446,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
23991,
62,
24396,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
63,
1040,
806,
13,
11712,
1300,
63,
329,
2446,
284,
39552,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7913,
286,
10007,
4855,
416,
262,
1813,
2446,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
600,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
25064,
13,
9641,
62,
10951,
1279,
357,
18,
11,
513,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
796,
10104,
13,
1136,
853,
16684,
7,
28758,
62,
24396,
8,
220,
1303,
279,
2645,
600,
25,
15560,
28,
10378,
31023,
12,
24396,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
21575,
4064,
82,
42287,
389,
25,
4064,
82,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
23991,
62,
24396,
13,
834,
3672,
834,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42287,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45218,
796,
42287,
13,
22046,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
944,
6,
287,
45218,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45218,
13,
28956,
10786,
944,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
18896,
7,
22065,
8,
628,
220,
220,
220,
220,
220,
220,
220,
25439,
62,
82,
328,
796,
10104,
13,
12683,
1300,
7,
28758,
62,
24396,
8,
220,
1303,
279,
2645,
600,
25,
15560,
28,
3919,
12,
19522,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
18896,
7,
20786,
62,
82,
328,
13,
17143,
7307,
8,
628,
220,
220,
220,
825,
4808,
29572,
62,
1370,
7,
944,
11,
1627,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
47,
945,
274,
257,
2060,
1627,
286,
3141,
2420,
290,
5860,
262,
44267,
5072,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
1627,
25,
1627,
286,
3141,
2420,
284,
307,
44267,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
23042,
263,
2134,
12059,
477,
286,
262,
44267,
3141,
16326,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
79,
4464,
945,
278,
13,
10044,
325,
25468,
63,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
10786,
47,
945,
278,
3141,
5128,
36521,
82,
26214,
3256,
1627,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1005,
2100,
796,
2116,
13557,
48610,
13,
29572,
10100,
7,
1370,
11,
21136,
3237,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
9788,
13,
10044,
325,
16922,
355,
11454,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
10786,
47,
945,
278,
4049,
25,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
10786,
59,
83,
4,
82,
3256,
11454,
13,
79,
2536,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
18224,
10786,
59,
83,
4,
82,
61,
3256,
705,
705,
1635,
357,
8056,
13,
4033,
12,
16,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
10786,
24259,
25,
4064,
82,
3256,
11454,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
10786,
47,
945,
276,
3141,
1627,
318,
36521,
82,
1,
3256,
1005,
2100,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1005,
2100,
628,
220,
220,
220,
825,
4808,
19796,
62,
21812,
7,
944,
11,
3141,
62,
3672,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
48452,
284,
17276,
262,
3141,
21360,
329,
257,
1813,
3141,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
3141,
62,
3672,
25,
383,
1438,
286,
262,
3141,
284,
1064,
262,
21360,
329,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
7783,
82,
25,
20984,
284,
262,
2446,
284,
307,
1444,
284,
12260,
262,
3141,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16409,
6045,
611,
645,
3141,
2446,
1043,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1058,
4871,
25,
63,
76,
2788,
63,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
11534,
329,
3141,
2446,
9313,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
402,
1032,
477,
1398,
5050,
11,
1390,
9037,
5050,
198,
220,
220,
220,
220,
220,
220,
220,
477,
62,
24396,
82,
796,
10104,
13,
1136,
30814,
7,
944,
11,
10104,
13,
1042,
316,
2065,
8,
198,
220,
220,
220,
220,
220,
220,
220,
477,
62,
24396,
82,
13,
2302,
437,
7,
1040,
806,
13,
1136,
30814,
7,
944,
11,
10104,
13,
4468,
4575,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
4091,
611,
356,
460,
1064,
257,
705,
4598,
62,
6,
2446,
329,
674,
3141,
986,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1090,
62,
24396,
287,
477,
62,
24396,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
18709,
278,
4064,
82,
1600,
1090,
62,
24396,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1090,
62,
24396,
58,
15,
60,
6624,
705,
4598,
62,
6,
1343,
3141,
62,
3672,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
21812,
2446,
1043,
25,
4064,
82,
1600,
1090,
62,
24396,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1090,
62,
24396,
58,
16,
60,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
611,
645,
3141,
2446,
460,
307,
1043,
329,
262,
7368,
11241,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1949,
2045,
510,
281,
16144,
329,
262,
3141,
355,
880,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
15784,
329,
16144,
9313,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1090,
62,
24396,
287,
477,
62,
24396,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1090,
62,
24396,
58,
15,
4083,
9688,
2032,
342,
7203,
26011,
62,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
21077,
16144,
2446,
4064,
82,
1600,
1090,
62,
24396,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1090,
62,
24396,
58,
16,
60,
3419,
6624,
3141,
62,
3672,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1796,
62,
28758,
62,
3672,
796,
1090,
62,
24396,
58,
15,
7131,
11925,
7203,
26011,
62,
1,
2599,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
6690,
1834,
278,
284,
1064,
16144,
3141,
4064,
82,
1600,
1796,
62,
28758,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
19796,
62,
21812,
7,
11612,
62,
28758,
62,
3672,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7203,
2949,
3141,
1043,
351,
1438,
366,
1343,
3141,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
628,
220,
220,
220,
825,
466,
62,
37023,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
44798,
689,
262,
3141,
28846,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
10786,
44798,
803,
28846,
986,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
28060,
796,
6407,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
4091,
611,
674,
7582,
468,
597,
3397,
11,
290,
2700,
606,
284,
11238,
1165,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13557,
8000,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
8000,
13,
4598,
62,
37023,
3419,
628,
220,
220,
220,
825,
466,
62,
19836,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
44798,
689,
262,
3058,
2491,
7582,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2601,
2752,
7582,
4064,
82,
37633,
82,
8,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
4871,
834,
13,
834,
3672,
834,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
16963,
457,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
8229,
1630,
736,
284,
262,
2560,
38683,
17537,
393,
262,
8624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
26204,
2058,
1306,
287,
262,
7582,
338,
29171,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
28060,
796,
6407,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
1037,
62,
19836,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
11627,
1631,
1037,
329,
1969,
2446,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
37227,
1532,
262,
1459,
7582,
318,
257,
850,
12,
29149,
29013,
416,
1194,
37227,
59,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37227,
23331,
306,
17537,
4554,
11,
1630,
481,
1441,
284,
262,
37227,
59,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37227,
8000,
7582,
543,
481,
2555,
2491,
37811,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
7508,
7,
20500,
11,
1635,
22046,
11,
12429,
62,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7279,
26024,
281,
7508,
3275,
284,
262,
4277,
5072,
4269,
628,
220,
220,
220,
220,
220,
220,
220,
15161,
7822,
655,
32254,
5072,
284,
14367,
448,
13,
5765,
257,
18931,
198,
220,
220,
220,
220,
220,
220,
220,
5022,
259,
1398,
284,
24184,
428,
4069,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
1058,
4871,
25,
63,
13120,
29149,
13,
35487,
62,
6404,
1362,
62,
19816,
259,
13,
26416,
11187,
1362,
35608,
259,
63,
329,
198,
220,
220,
220,
220,
220,
220,
220,
6096,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
3275,
25,
2420,
284,
307,
9066,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
20500,
4064,
26498,
8,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
6509,
7,
20500,
11,
1635,
22046,
11,
12429,
62,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7279,
26024,
257,
1729,
12,
34666,
6509,
3275,
284,
262,
4277,
5072,
4269,
628,
220,
220,
220,
220,
220,
220,
220,
15161,
7822,
655,
32254,
5072,
284,
14367,
448,
13,
5765,
257,
18931,
198,
220,
220,
220,
220,
220,
220,
220,
5022,
259,
1398,
284,
24184,
428,
4069,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
1058,
4871,
25,
63,
13120,
29149,
13,
35487,
62,
6404,
1362,
62,
19816,
259,
13,
26416,
11187,
1362,
35608,
259,
63,
329,
198,
220,
220,
220,
220,
220,
220,
220,
6096,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
3275,
25,
2420,
284,
307,
9066,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
20500,
4064,
26498,
8,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
4049,
7,
20500,
11,
1635,
22046,
11,
12429,
62,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7279,
26024,
257,
4688,
4049,
3275,
284,
262,
4277,
5072,
4269,
628,
220,
220,
220,
220,
220,
220,
220,
15161,
7822,
655,
32254,
5072,
284,
14367,
448,
13,
5765,
257,
18931,
198,
220,
220,
220,
220,
220,
220,
220,
5022,
259,
1398,
284,
24184,
428,
4069,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
1058,
4871,
25,
63,
13120,
29149,
13,
35487,
62,
6404,
1362,
62,
19816,
259,
13,
26416,
11187,
1362,
35608,
259,
63,
329,
198,
220,
220,
220,
220,
220,
220,
220,
6096,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
3275,
25,
2420,
284,
307,
9066,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
20500,
4064,
26498,
8,
628,
220,
220,
220,
2488,
12708,
24396,
198,
220,
220,
220,
825,
14257,
7,
20500,
11,
1635,
22046,
11,
12429,
62,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7279,
26024,
281,
5387,
12,
1904,
12,
8807,
14257,
3275,
284,
15942,
577,
2604,
2393,
628,
220,
220,
220,
220,
220,
220,
220,
15161,
7822,
30768,
477,
14257,
5072,
13,
5765,
257,
18931,
5022,
259,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
284,
24184,
428,
4069,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
1058,
4871,
25,
63,
13120,
29149,
13,
35487,
62,
6404,
1362,
62,
19816,
259,
13,
26416,
11187,
1362,
35608,
259,
63,
329,
198,
220,
220,
220,
220,
220,
220,
220,
6096,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
965,
3275,
25,
2420,
284,
307,
9066,
37811,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1208,
198
] | 2.364155 | 7,365 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#-----------------------------------------------------------------------------
# Copyright (c) 2015, IBM Corp.
# All rights reserved.
#
# Distributed under the terms of the BSD Simplified License.
#
# The full license is in the LICENSE file, distributed with this software.
#-----------------------------------------------------------------------------
"""
Test module for IdaGeoSeries
"""
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
import pandas
import pytest
import six
from ibmdbpy import IdaSeries
from ibmdbpy import IdaGeoSeries
from ibmdbpy.exceptions import IdaGeoDataFrameError
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
10097,
32501,
198,
2,
15069,
357,
66,
8,
1853,
11,
19764,
11421,
13,
198,
2,
1439,
2489,
10395,
13,
198,
2,
198,
2,
4307,
6169,
739,
262,
2846,
286,
262,
347,
10305,
45157,
1431,
13789,
13,
198,
2,
198,
2,
383,
1336,
5964,
318,
287,
262,
38559,
24290,
2393,
11,
9387,
351,
428,
3788,
13,
198,
2,
10097,
32501,
198,
198,
37811,
198,
14402,
8265,
329,
5121,
64,
10082,
78,
27996,
198,
37811,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
6738,
2003,
1330,
3210,
62,
32016,
198,
20307,
62,
32016,
13,
17350,
62,
7344,
1386,
3419,
198,
198,
11748,
19798,
292,
198,
11748,
12972,
9288,
198,
11748,
2237,
198,
198,
6738,
24283,
9132,
65,
9078,
1330,
5121,
64,
27996,
198,
6738,
24283,
9132,
65,
9078,
1330,
5121,
64,
10082,
78,
27996,
198,
6738,
24283,
9132,
65,
9078,
13,
1069,
11755,
1330,
5121,
64,
10082,
78,
6601,
19778,
12331,
628,
198,
220,
220,
220,
220
] | 3.9375 | 208 |
import os
import wandb
import pytorch_lightning as pl
import argparse
from thanos.trainers.lit_detector import LitGestureTransformer
from thanos.trainers import load_config
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("config", type=str, help="Path to config py file")
args = parser.parse_args()
config = load_config(args.config)
lit_model = LitGestureTransformer(config)
trainer = pl.Trainer(**config.trainer_config())
trainer.fit(lit_model, config.train_dataloader(), config.val_dataloader())
# save the config file to wandb cloud
wandb.save(config.config_path) | [
11748,
28686,
198,
11748,
11569,
65,
198,
11748,
12972,
13165,
354,
62,
2971,
768,
355,
458,
198,
11748,
1822,
29572,
198,
198,
6738,
621,
418,
13,
27432,
364,
13,
18250,
62,
15255,
9250,
1330,
25659,
38,
395,
495,
8291,
16354,
198,
6738,
621,
418,
13,
27432,
364,
1330,
3440,
62,
11250,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
30751,
796,
1822,
29572,
13,
28100,
1713,
46677,
3419,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
7203,
11250,
1600,
2099,
28,
2536,
11,
1037,
2625,
15235,
284,
4566,
12972,
2393,
4943,
198,
220,
220,
220,
26498,
796,
30751,
13,
29572,
62,
22046,
3419,
198,
220,
220,
220,
4566,
796,
3440,
62,
11250,
7,
22046,
13,
11250,
8,
198,
220,
220,
220,
6578,
62,
19849,
796,
25659,
38,
395,
495,
8291,
16354,
7,
11250,
8,
198,
220,
220,
220,
21997,
796,
458,
13,
2898,
10613,
7,
1174,
11250,
13,
2213,
10613,
62,
11250,
28955,
198,
220,
220,
220,
21997,
13,
11147,
7,
18250,
62,
19849,
11,
4566,
13,
27432,
62,
67,
10254,
1170,
263,
22784,
4566,
13,
2100,
62,
67,
10254,
1170,
263,
28955,
198,
220,
220,
220,
1303,
3613,
262,
4566,
2393,
284,
11569,
65,
6279,
198,
220,
220,
220,
11569,
65,
13,
21928,
7,
11250,
13,
11250,
62,
6978,
8
] | 2.895928 | 221 |
# Rotate String
if __name__ == "__main__":
sol = Solution()
s = "abcde"
goal = "cdeab"
s = "abcde"
goal = "abced"
s = "bbbacddceeb"
goal = "ceebbbbacdd"
print(sol.rotateString(s, goal))
| [
2,
18481,
378,
10903,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1540,
796,
28186,
3419,
198,
220,
220,
220,
264,
796,
366,
39305,
2934,
1,
198,
220,
220,
220,
3061,
796,
366,
66,
2934,
397,
1,
198,
220,
220,
220,
264,
796,
366,
39305,
2934,
1,
198,
220,
220,
220,
3061,
796,
366,
397,
771,
1,
198,
220,
220,
220,
264,
796,
366,
11848,
65,
330,
1860,
344,
1765,
1,
198,
220,
220,
220,
3061,
796,
366,
344,
1765,
11848,
65,
330,
1860,
1,
198,
220,
220,
220,
3601,
7,
34453,
13,
10599,
378,
10100,
7,
82,
11,
3061,
4008,
198
] | 1.990909 | 110 |
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
import numpy as np
import mindspore.context as context
import mindspore.nn as nn
from mindspore import Tensor
from mindspore.common import dtype as mstype
from mindspore.ops import operations as P
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
| [
2,
15069,
12131,
43208,
21852,
1766,
1539,
12052,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
2,
38093,
2559,
18604,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
11748,
2000,
2777,
382,
13,
22866,
355,
4732,
198,
11748,
2000,
2777,
382,
13,
20471,
355,
299,
77,
198,
6738,
2000,
2777,
382,
1330,
309,
22854,
198,
6738,
2000,
2777,
382,
13,
11321,
1330,
288,
4906,
355,
285,
301,
2981,
198,
6738,
2000,
2777,
382,
13,
2840,
1330,
4560,
355,
350,
198,
198,
22866,
13,
2617,
62,
22866,
7,
14171,
28,
22866,
13,
10761,
31300,
62,
49058,
11,
3335,
62,
16793,
11639,
36037,
11537,
628,
198
] | 3.961864 | 236 |
"""bugfix: correct active to is_active
Revision ID: cb98a72750ab
Revises: 7685fd00e696
Create Date: 2021-12-03 12:16:09.979253
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = 'cb98a72750ab'
down_revision = '7685fd00e696'
branch_labels = None
depends_on = None
| [
37811,
25456,
13049,
25,
3376,
4075,
284,
318,
62,
5275,
198,
198,
18009,
1166,
4522,
25,
269,
65,
4089,
64,
47760,
1120,
397,
198,
18009,
2696,
25,
767,
35978,
16344,
405,
68,
38205,
198,
16447,
7536,
25,
33448,
12,
1065,
12,
3070,
1105,
25,
1433,
25,
2931,
13,
24,
3720,
28592,
198,
198,
37811,
198,
6738,
31341,
2022,
291,
1330,
1034,
198,
11748,
44161,
282,
26599,
355,
473,
628,
198,
2,
18440,
42814,
11,
973,
416,
9300,
2022,
291,
13,
198,
260,
10178,
796,
705,
21101,
4089,
64,
47760,
1120,
397,
6,
198,
2902,
62,
260,
10178,
796,
705,
30610,
20,
16344,
405,
68,
38205,
6,
198,
1671,
3702,
62,
23912,
1424,
796,
6045,
198,
10378,
2412,
62,
261,
796,
6045,
628,
198
] | 2.609756 | 123 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import codecs
from unidecode import unidecode
from itertools import product
SUBSTITUTIONS = {
u'a': u'áảàãạâấẩẫầậăắẳẵằặ',
u'á': u'aảàãạâấẩẫầậăắẳẵằặ',
u'ả': u'aáàãạâấẩẫầậăắẳẵằặ',
u'à': u'aáảãạâấẩẫầậăắẳẵằặ',
u'ã': u'aáảàạâấẩẫầậăắẳẵằặ',
u'ạ': u'aáảàãâấẩẫầậăắẳẵằặ',
u'â': u'aáảàãạấẩẫầậăắẳẵằặ',
u'ấ': u'aáảàãạâẩẫầậăắẳẵằặ',
u'ẩ': u'aáảàãạâấẫầậăắẳẵằặ',
u'ẫ': u'aáảàãạâấẩầậăắẳẵằặ',
u'ầ': u'aáảàãạâấẩẫậăắẳẵằặ',
u'ậ': u'aáảàãạâấẩẫầăắẳẵằặ',
u'ă': u'aáảàãạâấẩẫầậắẳẵằặ',
u'ắ': u'aáảàãạâấẩẫầậăẳẵằặ',
u'ẳ': u'aáảàãạâấẩẫầậăắẵằặ',
u'ẵ': u'aáảàãạâấẩẫầậăắẳằặ',
u'ằ': u'aáảàãạâấẩẫầậăắẳẵặ',
u'ặ': u'aáảàãạâấẩẫầậăắẳẵằ',
u'd': u'đ',
u'đ': u'd',
u'e': u'ẹẻèéẽêệểềếễ',
u'ẹ': u'eẻèéẽêệểềếễ',
u'ẻ': u'eẹèéẽêệểềếễ',
u'è': u'eẹẻéẽêệểềếễ',
u'é': u'eẹẻèẽêệểềếễ',
u'ẽ': u'eẹẻèéêệểềếễ',
u'ê': u'eẹẻèéẽệểềếễ',
u'ệ': u'eẹẻèéẽêểềếễ',
u'ể': u'eẹẻèéẽêệềếễ',
u'ề': u'eẹẻèéẽêệểếễ',
u'ế': u'eẹẻèéẽêệểềễ',
u'ễ': u'eẹẻèéẽêệểềế',
u'i': u'ịỉìíĩ',
u'ị': u'iỉìíĩ',
u'ỉ': u'iịìíĩ',
u'ì': u'iịỉíĩ',
u'í': u'iịỉìĩ',
u'ĩ': u'iịỉìí',
u'o': u'ọỏòóõơợởờớỡôổốồỗộ',
u'ọ': u'oỏòóõơợởờớỡôổốồỗộ',
u'ỏ': u'oọòóõơợởờớỡôổốồỗộ',
u'ò': u'oọỏóõơợởờớỡôổốồỗộ',
u'ó': u'oọỏòõơợởờớỡôổốồỗộ',
u'õ': u'oọỏòóơợởờớỡôổốồỗộ',
u'ơ': u'oọỏòóõợởờớỡôổốồỗộ',
u'ợ': u'oọỏòóõơợờớỡôổốồỗộ',
u'ở': u'oọỏòóõơợờớỡôổốồỗộ',
u'ờ': u'oọỏòóõơợởớỡôổốồỗộ',
u'ớ': u'oọỏòóõơợởờỡôổốồỗộ',
u'ỡ': u'oọỏòóõơợởờớôổốồỗộ',
u'ô': u'oọỏòóõơợởờớỡổốồỗộ',
u'ổ': u'oọỏòóõơợởờớỡôốồỗộ',
u'ố': u'oọỏòóõơợởờớỡôổồỗộ',
u'ồ': u'oọỏòóõơợởờớỡôổốỗộ',
u'ỗ': u'oọỏòóõơợởờớỡôổốồộ',
u'ộ': u'oọỏòóõơợởờớỡôổốồỗ',
u'u': u'ụủùúũưựửừứữ',
u'ụ': u'uủùúũưựửừứữ',
u'ủ': u'uụùúũưựửừứữ',
u'ù': u'uụủúũưựửừứữ',
u'ú': u'uụủùũưựửừứữ',
u'ũ': u'uụủùúưựửừứữ',
u'ư': u'uụủùúũựửừứữ',
u'ự': u'uụủùúũưửừứữ',
u'ử': u'uụủùúũưựừứữ',
u'ừ': u'uụủùúũưựửứữ',
u'ứ': u'uụủùúũưựửừữ',
u'ữ': u'uụủùúũưựửừứ',
u'y': u'ỵỷỳýỹ',
u'ỵ': u'yỷỳýỹ',
u'ỷ': u'yỵỳýỹ',
u'ỳ': u'yỵỷýỹ',
u'ý': u'yỵỷỳỹ',
u'ỹ': u'yỵỷỳý'
}
VN_LOWERCASE = u'aạảàáã' \
u'âậẩầấẫ' \
u'ăặẳằắẵ' \
u'bcdđ' \
u'eẹẻèéẽ' \
u'êệểềếễ' \
u'fgh' \
u'iịỉìíĩ' \
u'jklmn' \
u'oọỏòóõ' \
u'ôộổồốỗ' \
u'ơợởờớỡ' \
u'pqrst' \
u'uụủùúũ' \
u'ưựửừứữ' \
u'vwx' \
u'yỵỷỳýỹ' \
u'z'
VN_UPPERCASE = u'AẠẢÀÁÃ' \
u'ÂẬẨẦẤẪ' \
u'ĂẶẮẰẮẴ' \
u'BCDĐ' \
u'EẸẺÈÉẼ' \
u'ÊỆỂỀẾỄ' \
u'FGH' \
u'IỊỈÌÍĨ' \
u'JKLMN' \
u'OỌỎÒÓÕ' \
u'ÔỘỔỒỐỖ' \
u'ƠỢỞỜỚỠ' \
u'PQRST' \
u'UỤỦÙÚŨ' \
u'ƯỰỬỪỨỮ' \
u'VWX' \
u'YỴỶỲÝỸ' \
u'Z'
VN_COMBINE_ACCENT_REPLACE = {
u'à': u'à',
u'á': u'á',
u'ã': u'ã',
u'ả': u'ả',
u'ạ': u'ạ',
u'è': u'è',
u'é': u'é',
u'ẽ': u'ẽ',
u'ẻ': u'ẻ',
u'ẹ': u'ẹ',
u'ì': u'ì',
u'í': u'í',
u'ĩ': u'ĩ',
u'ỉ': u'ỉ',
u'ị': u'ị',
u'ò': u'ò',
u'ó': u'ó',
u'õ': u'õ',
u'ỏ': u'ỏ',
u'ọ': u'ọ',
u'ờ': u'ờ',
u'ớ': u'ớ',
u'ỡ': u'ỡ',
u'ở': u'ở',
u'ợ': u'ợ',
u'ù': u'ù',
u'ú': u'ú',
u'ũ': u'ũ',
u'ủ': u'ủ',
u'ụ': u'ụ',
u'ỳ': u'ỳ',
u'ý': u'ý',
u'ỹ': u'ỹ',
u'ỷ': u'ỷ',
u'ỵ': u'ỵ',
u'â': u'â',
u'ầ': u'ầ',
u'ấ': u'ấ',
u'ẫ': u'ẫ',
u'ẩ': u'ẩ',
u'ậ': u'ậ',
u'ằ': u'ằ',
u'ắ': u'ắ',
u'ẵ': u'ẵ',
u'ẳ': u'ẳ',
u'ặ': u'ặ',
u'ừ': u'ừ',
u'ứ': u'ứ',
u'ữ': u'ữ',
u'ử': u'ử',
u'ự': u'ự',
u'ê': u'ê',
u'ề': u'ề',
u'ế': u'ế',
u'ễ': u'ễ',
u'ể': u'ể',
u'ệ': u'ệ',
u'ô': u'ô',
u'ồ': u'ồ',
u'ố': u'ố',
u'ỗ': u'ỗ',
u'ổ': u'ổ',
u'ộ': u'ộ'
}
VN_CHARACTERS = VN_LOWERCASE + VN_UPPERCASE
DIGIT = u'0123456789'
SPEC_CHARACTERS = u'`~!@$%^&*()_=\|]}[{"\';:/?.>,<“”‘’…'
ADDITIONAL_CHARACTERS = u'`~!@#$%^&*()-_=+\|]}[{"\';:/?.>,<“”‘’…'
_DIGIT = set([x for x in DIGIT])
_ADDITIONAL_CHARACTERS = set([x for x in ADDITIONAL_CHARACTERS])
_VN_LOWERCASE = set([x for x in VN_LOWERCASE])
def vn_islowercase(char):
"""Check is lowercase for a vn character
:param char: a unicode character
:return:
"""
if char in _DIGIT or char in _ADDITIONAL_CHARACTERS:
return True
return char in VN_LOWERCASE
def vn_isuppercase(char):
"""Check is uppercase for a vn character
:param char: a unicode character
:return:
"""
if char in DIGIT or char in ADDITIONAL_CHARACTERS:
return True
return char in VN_UPPERCASE
def vn_tolowercase(s):
"""To lower case a vn string
:param s: a unicode vn string
:return:
"""
ls = list(s)
for c in range(0, len(ls)):
if ls[c] in _DIGIT or ls[c] in _ADDITIONAL_CHARACTERS:
continue
if vn_isuppercase(ls[c]):
ic = VN_UPPERCASE.index(ls[c])
ls[c] = VN_LOWERCASE[ic]
return u''.join(ls)
def vn_touppercase(s):
"""To upper case a vn string
:param s: a unicode vn string
:return:
"""
ls = list(s)
for c in range(0, len(ls)):
if ls[c] in _DIGIT or ls[c] in _ADDITIONAL_CHARACTERS:
continue
if vn_isuppercase(ls[c]):
ic = VN_LOWERCASE.index(ls[c])
ls[c] = VN_UPPERCASE[ic]
return u''.join(ls)
def vn_combine_accent_replace(s):
"""
convert ascii+combine_accent -> unicode_char
:param s:
:return:
"""
ss = set([x for x in s])
for k, v in VN_COMBINE_ACCENT_REPLACE.items():
if k in ss:
s = s.replace(k, v)
return s
def load_vocab(vocab_path):
""" Loading a vocabulary file
:param vocab_path: Path to vocabulary file
:return: Array contains words
"""
with codecs.open(vocab_path, encoding="utf-8") as fobj:
vocab = fobj.readlines()
return vocab
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
40481,
82,
198,
6738,
555,
485,
8189,
1330,
555,
485,
8189,
198,
6738,
340,
861,
10141,
1330,
1720,
628,
198,
50,
10526,
2257,
2043,
3843,
11053,
796,
1391,
198,
220,
220,
220,
334,
6,
64,
10354,
334,
6,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
6557,
10354,
334,
6,
64,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
96,
10354,
334,
6,
64,
6557,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
24247,
10354,
334,
6,
64,
6557,
157,
118,
96,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
26102,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
94,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
22940,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
98,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
102,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
104,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
100,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
255,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
107,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
111,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
111,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
113,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
113,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
109,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
109,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
115,
10354,
334,
6,
64,
6557,
157,
118,
96,
24247,
26102,
157,
118,
94,
22940,
157,
118,
98,
157,
118,
102,
157,
118,
104,
157,
118,
100,
157,
118,
255,
128,
225,
157,
118,
107,
157,
118,
111,
157,
118,
113,
157,
118,
109,
3256,
198,
220,
220,
220,
334,
1549,
10354,
334,
6,
128,
239,
3256,
198,
220,
220,
220,
334,
6,
128,
239,
10354,
334,
1549,
3256,
198,
220,
220,
220,
334,
6,
68,
10354,
334,
6,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
117,
10354,
334,
6,
68,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
119,
10354,
334,
6,
68,
157,
118,
117,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
14064,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
2634,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
121,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
25792,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
229,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
225,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
223,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
223,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
118,
123,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
118,
123,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
227,
10354,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
3256,
198,
220,
220,
220,
334,
6,
72,
10354,
334,
6,
157,
119,
233,
157,
119,
231,
127,
105,
8836,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
233,
10354,
334,
6,
72,
157,
119,
231,
127,
105,
8836,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
231,
10354,
334,
6,
72,
157,
119,
233,
127,
105,
8836,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
127,
105,
10354,
334,
6,
72,
157,
119,
233,
157,
119,
231,
8836,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
8836,
10354,
334,
6,
72,
157,
119,
233,
157,
119,
231,
127,
105,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
128,
102,
10354,
334,
6,
72,
157,
119,
233,
157,
119,
231,
127,
105,
8836,
3256,
198,
220,
220,
220,
334,
6,
78,
10354,
334,
6,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
235,
10354,
334,
6,
78,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
237,
10354,
334,
6,
78,
157,
119,
235,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
127,
110,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
10205,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
127,
113,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
96,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
253,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
251,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
249,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
94,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
27083,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
243,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
239,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
239,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
241,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
241,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
245,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
245,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
247,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
247,
10354,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
27083,
157,
119,
243,
157,
119,
239,
157,
119,
241,
157,
119,
245,
3256,
198,
220,
220,
220,
334,
6,
84,
10354,
334,
6,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
98,
10354,
334,
6,
84,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
100,
10354,
334,
6,
84,
157,
119,
98,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
127,
117,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
21356,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
129,
102,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
109,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
255,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
104,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
104,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
102,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
102,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
107,
10354,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
3256,
198,
220,
220,
220,
334,
6,
88,
10354,
334,
6,
157,
119,
113,
157,
119,
115,
157,
119,
111,
127,
121,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
113,
10354,
334,
6,
88,
157,
119,
115,
157,
119,
111,
127,
121,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
115,
10354,
334,
6,
88,
157,
119,
113,
157,
119,
111,
127,
121,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
111,
10354,
334,
6,
88,
157,
119,
113,
157,
119,
115,
127,
121,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
127,
121,
10354,
334,
6,
88,
157,
119,
113,
157,
119,
115,
157,
119,
111,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
157,
119,
117,
10354,
334,
6,
88,
157,
119,
113,
157,
119,
115,
157,
119,
111,
127,
121,
6,
198,
92,
198,
198,
53,
45,
62,
43,
36048,
34,
11159,
796,
334,
6,
64,
157,
118,
94,
157,
118,
96,
24247,
6557,
26102,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
22940,
157,
118,
255,
157,
118,
102,
157,
118,
100,
157,
118,
98,
157,
118,
104,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
128,
225,
157,
118,
115,
157,
118,
111,
157,
118,
109,
157,
118,
107,
157,
118,
113,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
65,
10210,
128,
239,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
68,
157,
118,
117,
157,
118,
119,
14064,
2634,
157,
118,
121,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
25792,
157,
119,
229,
157,
119,
225,
157,
119,
223,
157,
118,
123,
157,
119,
227,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
69,
456,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
72,
157,
119,
233,
157,
119,
231,
127,
105,
8836,
128,
102,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
73,
41582,
10295,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
78,
157,
119,
235,
157,
119,
237,
127,
110,
10205,
127,
113,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
27083,
157,
119,
247,
157,
119,
243,
157,
119,
241,
157,
119,
239,
157,
119,
245,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
130,
94,
157,
119,
96,
157,
119,
253,
157,
119,
251,
157,
119,
249,
157,
119,
94,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
79,
80,
81,
301,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
84,
157,
119,
98,
157,
119,
100,
127,
117,
21356,
129,
102,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
130,
108,
157,
119,
109,
157,
119,
255,
157,
119,
104,
157,
119,
102,
157,
119,
107,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
85,
49345,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
88,
157,
119,
113,
157,
119,
115,
157,
119,
111,
127,
121,
157,
119,
117,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
89,
6,
198,
198,
53,
45,
62,
8577,
18973,
34,
11159,
796,
334,
6,
32,
157,
118,
254,
157,
118,
95,
127,
222,
127,
223,
5746,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
5523,
157,
118,
105,
157,
118,
101,
157,
118,
99,
157,
118,
97,
157,
118,
103,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
128,
224,
157,
118,
114,
157,
118,
106,
157,
118,
108,
157,
118,
106,
157,
118,
112,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
2749,
35,
128,
238,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
36,
157,
118,
116,
157,
118,
118,
127,
230,
38351,
157,
118,
120,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
127,
232,
157,
119,
228,
157,
119,
224,
157,
119,
222,
157,
118,
122,
157,
119,
226,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
37,
17511,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
40,
157,
119,
232,
157,
119,
230,
127,
234,
38638,
128,
101,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
41,
42,
31288,
45,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
46,
157,
119,
234,
157,
119,
236,
127,
240,
127,
241,
127,
243,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
127,
242,
157,
119,
246,
157,
119,
242,
157,
36596,
157,
119,
238,
157,
119,
244,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
130,
254,
157,
119,
95,
157,
119,
252,
157,
119,
250,
157,
119,
248,
157,
119,
254,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
47,
48,
49,
2257,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
52,
157,
119,
97,
157,
119,
99,
127,
247,
127,
248,
129,
101,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
130,
107,
157,
119,
108,
157,
119,
105,
157,
119,
103,
157,
119,
101,
157,
119,
106,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
30133,
55,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
56,
157,
119,
112,
157,
119,
114,
157,
119,
110,
127,
251,
157,
119,
116,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
334,
6,
57,
6,
198,
198,
53,
45,
62,
9858,
33,
8881,
62,
26861,
3525,
62,
2200,
6489,
11598,
796,
1391,
198,
220,
220,
220,
334,
6,
64,
136,
222,
10354,
334,
6,
24247,
3256,
198,
220,
220,
220,
334,
6,
64,
136,
223,
10354,
334,
6,
6557,
3256,
198,
220,
220,
220,
334,
6,
64,
136,
225,
10354,
334,
6,
26102,
3256,
198,
220,
220,
220,
334,
6,
64,
136,
231,
10354,
334,
6,
157,
118,
96,
3256,
198,
220,
220,
220,
334,
6,
64,
136,
96,
10354,
334,
6,
157,
118,
94,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
222,
10354,
334,
6,
14064,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
223,
10354,
334,
6,
2634,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
225,
10354,
334,
6,
157,
118,
121,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
231,
10354,
334,
6,
157,
118,
119,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
96,
10354,
334,
6,
157,
118,
117,
3256,
198,
220,
220,
220,
334,
6,
72,
136,
222,
10354,
334,
6,
127,
105,
3256,
198,
220,
220,
220,
334,
6,
72,
136,
223,
10354,
334,
6,
8836,
3256,
198,
220,
220,
220,
334,
6,
72,
136,
225,
10354,
334,
6,
128,
102,
3256,
198,
220,
220,
220,
334,
6,
72,
136,
231,
10354,
334,
6,
157,
119,
231,
3256,
198,
220,
220,
220,
334,
6,
72,
136,
96,
10354,
334,
6,
157,
119,
233,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
222,
10354,
334,
6,
127,
110,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
223,
10354,
334,
6,
10205,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
225,
10354,
334,
6,
127,
113,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
231,
10354,
334,
6,
157,
119,
237,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
96,
10354,
334,
6,
157,
119,
235,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
136,
222,
10354,
334,
6,
157,
119,
251,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
136,
223,
10354,
334,
6,
157,
119,
249,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
136,
225,
10354,
334,
6,
157,
119,
94,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
136,
231,
10354,
334,
6,
157,
119,
253,
3256,
198,
220,
220,
220,
334,
6,
130,
94,
136,
96,
10354,
334,
6,
157,
119,
96,
3256,
198,
220,
220,
220,
334,
6,
84,
136,
222,
10354,
334,
6,
127,
117,
3256,
198,
220,
220,
220,
334,
6,
84,
136,
223,
10354,
334,
6,
21356,
3256,
198,
220,
220,
220,
334,
6,
84,
136,
225,
10354,
334,
6,
129,
102,
3256,
198,
220,
220,
220,
334,
6,
84,
136,
231,
10354,
334,
6,
157,
119,
100,
3256,
198,
220,
220,
220,
334,
6,
84,
136,
96,
10354,
334,
6,
157,
119,
98,
3256,
198,
220,
220,
220,
334,
6,
88,
136,
222,
10354,
334,
6,
157,
119,
111,
3256,
198,
220,
220,
220,
334,
6,
88,
136,
223,
10354,
334,
6,
127,
121,
3256,
198,
220,
220,
220,
334,
6,
88,
136,
225,
10354,
334,
6,
157,
119,
117,
3256,
198,
220,
220,
220,
334,
6,
88,
136,
231,
10354,
334,
6,
157,
119,
115,
3256,
198,
220,
220,
220,
334,
6,
88,
136,
96,
10354,
334,
6,
157,
119,
113,
3256,
198,
220,
220,
220,
334,
6,
64,
136,
224,
10354,
334,
6,
22940,
3256,
198,
220,
220,
220,
334,
6,
22940,
136,
222,
10354,
334,
6,
157,
118,
100,
3256,
198,
220,
220,
220,
334,
6,
22940,
136,
223,
10354,
334,
6,
157,
118,
98,
3256,
198,
220,
220,
220,
334,
6,
22940,
136,
225,
10354,
334,
6,
157,
118,
104,
3256,
198,
220,
220,
220,
334,
6,
22940,
136,
231,
10354,
334,
6,
157,
118,
102,
3256,
198,
220,
220,
220,
334,
6,
22940,
136,
96,
10354,
334,
6,
157,
118,
255,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
136,
222,
10354,
334,
6,
157,
118,
109,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
136,
223,
10354,
334,
6,
157,
118,
107,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
136,
225,
10354,
334,
6,
157,
118,
113,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
136,
231,
10354,
334,
6,
157,
118,
111,
3256,
198,
220,
220,
220,
334,
6,
128,
225,
136,
96,
10354,
334,
6,
157,
118,
115,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
136,
222,
10354,
334,
6,
157,
119,
104,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
136,
223,
10354,
334,
6,
157,
119,
102,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
136,
225,
10354,
334,
6,
157,
119,
107,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
136,
231,
10354,
334,
6,
157,
119,
255,
3256,
198,
220,
220,
220,
334,
6,
130,
108,
136,
96,
10354,
334,
6,
157,
119,
109,
3256,
198,
220,
220,
220,
334,
6,
68,
136,
224,
10354,
334,
6,
25792,
3256,
198,
220,
220,
220,
334,
6,
25792,
136,
222,
10354,
334,
6,
157,
119,
223,
3256,
198,
220,
220,
220,
334,
6,
25792,
136,
223,
10354,
334,
6,
157,
118,
123,
3256,
198,
220,
220,
220,
334,
6,
25792,
136,
225,
10354,
334,
6,
157,
119,
227,
3256,
198,
220,
220,
220,
334,
6,
25792,
136,
231,
10354,
334,
6,
157,
119,
225,
3256,
198,
220,
220,
220,
334,
6,
25792,
136,
96,
10354,
334,
6,
157,
119,
229,
3256,
198,
220,
220,
220,
334,
6,
78,
136,
224,
10354,
334,
6,
27083,
3256,
198,
220,
220,
220,
334,
6,
27083,
136,
222,
10354,
334,
6,
157,
119,
241,
3256,
198,
220,
220,
220,
334,
6,
27083,
136,
223,
10354,
334,
6,
157,
119,
239,
3256,
198,
220,
220,
220,
334,
6,
27083,
136,
225,
10354,
334,
6,
157,
119,
245,
3256,
198,
220,
220,
220,
334,
6,
27083,
136,
231,
10354,
334,
6,
157,
119,
243,
3256,
198,
220,
220,
220,
334,
6,
27083,
136,
96,
10354,
334,
6,
157,
119,
247,
6,
198,
92,
198,
198,
53,
45,
62,
38019,
10659,
4877,
796,
569,
45,
62,
43,
36048,
34,
11159,
1343,
569,
45,
62,
8577,
18973,
34,
11159,
198,
35,
3528,
2043,
796,
334,
6,
486,
1954,
2231,
3134,
4531,
6,
198,
48451,
62,
38019,
10659,
4877,
796,
334,
6,
63,
93,
0,
31,
3,
4,
61,
5,
9,
3419,
62,
28,
59,
91,
48999,
58,
4895,
59,
17020,
14079,
30,
13,
22330,
27,
447,
250,
447,
251,
447,
246,
447,
247,
1399,
6,
198,
29266,
17941,
1847,
62,
38019,
10659,
4877,
796,
334,
6,
63,
93,
0,
31,
29953,
4,
61,
5,
9,
3419,
12,
62,
28,
10,
59,
91,
48999,
58,
4895,
59,
17020,
14079,
30,
13,
22330,
27,
447,
250,
447,
251,
447,
246,
447,
247,
1399,
6,
198,
198,
62,
35,
3528,
2043,
796,
900,
26933,
87,
329,
2124,
287,
360,
3528,
2043,
12962,
198,
62,
29266,
17941,
1847,
62,
38019,
10659,
4877,
796,
900,
26933,
87,
329,
2124,
287,
27841,
17941,
1847,
62,
38019,
10659,
4877,
12962,
198,
62,
53,
45,
62,
43,
36048,
34,
11159,
796,
900,
26933,
87,
329,
2124,
287,
569,
45,
62,
43,
36048,
34,
11159,
12962,
628,
198,
4299,
410,
77,
62,
3044,
789,
7442,
7,
10641,
2599,
198,
220,
220,
220,
37227,
9787,
318,
2793,
7442,
329,
257,
410,
77,
2095,
628,
220,
220,
220,
1058,
17143,
1149,
25,
257,
28000,
1098,
2095,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1149,
287,
4808,
35,
3528,
2043,
393,
1149,
287,
4808,
29266,
17941,
1847,
62,
38019,
10659,
4877,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6407,
628,
220,
220,
220,
1441,
1149,
287,
569,
45,
62,
43,
36048,
34,
11159,
628,
198,
4299,
410,
77,
62,
271,
7211,
2798,
589,
7,
10641,
2599,
198,
220,
220,
220,
37227,
9787,
318,
334,
39921,
589,
329,
257,
410,
77,
2095,
628,
220,
220,
220,
1058,
17143,
1149,
25,
257,
28000,
1098,
2095,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1149,
287,
360,
3528,
2043,
393,
1149,
287,
27841,
17941,
1847,
62,
38019,
10659,
4877,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6407,
628,
220,
220,
220,
1441,
1149,
287,
569,
45,
62,
8577,
18973,
34,
11159,
628,
198,
4299,
410,
77,
62,
83,
349,
789,
7442,
7,
82,
2599,
198,
220,
220,
220,
37227,
2514,
2793,
1339,
257,
410,
77,
4731,
628,
220,
220,
220,
1058,
17143,
264,
25,
257,
28000,
1098,
410,
77,
4731,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
43979,
796,
1351,
7,
82,
8,
198,
220,
220,
220,
329,
269,
287,
2837,
7,
15,
11,
18896,
7,
7278,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
43979,
58,
66,
60,
287,
4808,
35,
3528,
2043,
393,
43979,
58,
66,
60,
287,
4808,
29266,
17941,
1847,
62,
38019,
10659,
4877,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
611,
410,
77,
62,
271,
7211,
2798,
589,
7,
7278,
58,
66,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14158,
796,
569,
45,
62,
8577,
18973,
34,
11159,
13,
9630,
7,
7278,
58,
66,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43979,
58,
66,
60,
796,
569,
45,
62,
43,
36048,
34,
11159,
58,
291,
60,
628,
220,
220,
220,
1441,
334,
35384,
22179,
7,
7278,
8,
628,
198,
4299,
410,
77,
62,
83,
280,
39921,
589,
7,
82,
2599,
198,
220,
220,
220,
37227,
2514,
6727,
1339,
257,
410,
77,
4731,
628,
220,
220,
220,
1058,
17143,
264,
25,
257,
28000,
1098,
410,
77,
4731,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
43979,
796,
1351,
7,
82,
8,
198,
220,
220,
220,
329,
269,
287,
2837,
7,
15,
11,
18896,
7,
7278,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
43979,
58,
66,
60,
287,
4808,
35,
3528,
2043,
393,
43979,
58,
66,
60,
287,
4808,
29266,
17941,
1847,
62,
38019,
10659,
4877,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
611,
410,
77,
62,
271,
7211,
2798,
589,
7,
7278,
58,
66,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14158,
796,
569,
45,
62,
43,
36048,
34,
11159,
13,
9630,
7,
7278,
58,
66,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43979,
58,
66,
60,
796,
569,
45,
62,
8577,
18973,
34,
11159,
58,
291,
60,
628,
220,
220,
220,
1441,
334,
35384,
22179,
7,
7278,
8,
628,
198,
4299,
410,
77,
62,
24011,
500,
62,
330,
1087,
62,
33491,
7,
82,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10385,
355,
979,
72,
10,
24011,
500,
62,
330,
1087,
4613,
28000,
1098,
62,
10641,
198,
220,
220,
220,
1058,
17143,
264,
25,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
37786,
796,
900,
26933,
87,
329,
2124,
287,
264,
12962,
198,
220,
220,
220,
329,
479,
11,
410,
287,
569,
45,
62,
9858,
33,
8881,
62,
26861,
3525,
62,
2200,
6489,
11598,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
611,
479,
287,
37786,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
796,
264,
13,
33491,
7,
74,
11,
410,
8,
198,
220,
220,
220,
1441,
264,
628,
198,
4299,
3440,
62,
18893,
397,
7,
18893,
397,
62,
6978,
2599,
198,
220,
220,
220,
37227,
12320,
257,
25818,
2393,
628,
220,
220,
220,
1058,
17143,
12776,
397,
62,
6978,
25,
10644,
284,
25818,
2393,
198,
220,
220,
220,
1058,
7783,
25,
15690,
4909,
2456,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
351,
40481,
82,
13,
9654,
7,
18893,
397,
62,
6978,
11,
21004,
2625,
40477,
12,
23,
4943,
355,
277,
26801,
25,
198,
220,
220,
220,
220,
220,
220,
220,
12776,
397,
796,
277,
26801,
13,
961,
6615,
3419,
198,
220,
220,
220,
1441,
12776,
397,
628,
628,
198
] | 1.016159 | 6,374 |
"""Dataloaders for MNIST, FashionMNIST, CIFAR10"""
from typing import Tuple
import torchvision
from torch.utils.data import DataLoader
from opacus.utils.uniform_sampler import UniformWithReplacementSampler
| [
37811,
35,
10254,
1170,
364,
329,
29060,
8808,
11,
30958,
39764,
8808,
11,
327,
5064,
1503,
940,
37811,
198,
198,
6738,
19720,
1330,
309,
29291,
198,
11748,
28034,
10178,
198,
6738,
28034,
13,
26791,
13,
7890,
1330,
6060,
17401,
198,
6738,
1034,
48628,
13,
26791,
13,
403,
6933,
62,
37687,
20053,
1330,
35712,
3152,
39232,
5592,
16305,
20053,
628,
628,
198
] | 3.459016 | 61 |
import logging
from django.db import models
from django.template.defaultfilters import floatformat
from django.urls import reverse
from django.utils import timezone
from django.contrib.auth.models import User
from django.contrib.postgres.fields import JSONField
from django_rq import get_connection, job
from iso639 import languages
from rq.job import Job, NoSuchJobError
from lemmatization.lemmatizer import Lemmatizer
@job("default", timeout=600)
# this is for representing the lemmatized text
| [
11748,
18931,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
4981,
198,
6738,
42625,
14208,
13,
28243,
13,
12286,
10379,
1010,
1330,
5530,
3390,
265,
198,
6738,
42625,
14208,
13,
6371,
82,
1330,
9575,
198,
6738,
42625,
14208,
13,
26791,
1330,
640,
11340,
198,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
27530,
1330,
11787,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
7353,
34239,
13,
25747,
1330,
19449,
15878,
198,
198,
6738,
42625,
14208,
62,
81,
80,
1330,
651,
62,
38659,
11,
1693,
198,
6738,
47279,
21,
2670,
1330,
8950,
198,
6738,
374,
80,
13,
21858,
1330,
15768,
11,
1400,
16678,
33308,
12331,
198,
198,
6738,
443,
3020,
265,
1634,
13,
293,
3020,
265,
7509,
1330,
20607,
6759,
7509,
628,
198,
198,
31,
21858,
7203,
12286,
1600,
26827,
28,
8054,
8,
628,
198,
2,
428,
318,
329,
10200,
262,
443,
3020,
265,
1143,
2420,
628
] | 3.418919 | 148 |
#! /usr/bin/env python
"""
the html test reporter
"""
import sys, os, re
import pprint
import py
from pypy.tool.pytest import result
from pypy.tool.pytest.overview import ResultCache
#
# various interesting path objects
#
html = py.xml.html
NBSP = py.xml.raw(" ")
#
# rendering
#
# generate html files
#
mydir = py.path.local(__file__).dirpath()
| [
2,
0,
1220,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
37811,
198,
1169,
27711,
1332,
9095,
220,
198,
198,
37811,
198,
11748,
25064,
11,
28686,
11,
302,
198,
11748,
279,
4798,
198,
11748,
12972,
220,
198,
6738,
279,
4464,
88,
13,
25981,
13,
9078,
9288,
1330,
1255,
198,
6738,
279,
4464,
88,
13,
25981,
13,
9078,
9288,
13,
2502,
1177,
1330,
25414,
30562,
220,
198,
198,
2,
220,
198,
2,
2972,
3499,
3108,
5563,
220,
198,
2,
198,
198,
6494,
796,
12972,
13,
19875,
13,
6494,
198,
32819,
4303,
796,
12972,
13,
19875,
13,
1831,
7203,
5,
77,
24145,
26,
4943,
628,
220,
220,
220,
1303,
220,
198,
220,
220,
220,
1303,
14837,
220,
198,
220,
220,
220,
1303,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
7716,
27711,
3696,
220,
198,
220,
220,
220,
1303,
198,
198,
1820,
15908,
796,
12972,
13,
6978,
13,
12001,
7,
834,
7753,
834,
737,
15908,
6978,
3419,
198
] | 2.459119 | 159 |
from simpleWebServer import SimpleWebServer
#---------------------------------------------------
usersCount = 0
estonianPopulation = {
"tallinn" : 441000,
"tartu" : 94000,
"narva" : 58000,
"parnu" : 41000
}
#---------------------------------------------------
SimpleWebServer().serve(8088, getPopulation) | [
6738,
2829,
13908,
10697,
1330,
17427,
13908,
10697,
198,
198,
2,
47232,
6329,
198,
198,
18417,
12332,
796,
657,
198,
198,
19115,
666,
45251,
796,
1391,
198,
220,
220,
220,
366,
35429,
3732,
1,
1058,
604,
3901,
830,
11,
198,
220,
220,
220,
366,
83,
433,
84,
1,
1058,
10048,
830,
11,
198,
220,
220,
220,
366,
23955,
6862,
1,
1058,
7618,
830,
11,
198,
220,
220,
220,
366,
79,
1501,
84,
1,
1058,
6073,
830,
198,
92,
628,
198,
2,
47232,
6329,
198,
198,
26437,
13908,
10697,
22446,
2655,
303,
7,
1795,
3459,
11,
651,
45251,
8
] | 3.326531 | 98 |
import logging
import _thread
from threading import Timer
from . import hpim_globals
from .metric import AssertMetric, Metric
from .tree_interface import TreeInterface
from .non_root_state_machine import SFMRNonRootState
from .assert_state import AssertState, SFMRAssertABC
from .downstream_state import SFMRPruneState, SFMRDownstreamStateABC
| [
11748,
18931,
198,
11748,
4808,
16663,
198,
6738,
4704,
278,
1330,
5045,
263,
198,
198,
6738,
764,
1330,
27673,
320,
62,
4743,
672,
874,
198,
6738,
764,
4164,
1173,
1330,
2195,
861,
9171,
1173,
11,
3395,
1173,
198,
6738,
764,
21048,
62,
39994,
1330,
12200,
39317,
198,
6738,
764,
13159,
62,
15763,
62,
5219,
62,
30243,
1330,
14362,
13599,
15419,
30016,
9012,
198,
6738,
764,
30493,
62,
5219,
1330,
2195,
861,
9012,
11,
14362,
44,
3861,
824,
861,
24694,
198,
6738,
764,
2902,
5532,
62,
5219,
1330,
14362,
13599,
6836,
1726,
9012,
11,
14362,
13599,
8048,
5532,
9012,
24694,
198
] | 3.44 | 100 |
from Automator import Automator
position_dictionary = {
"skill_1": (54, 432),
"skill_2": (123, 432),
"skill_3": (192, 432),
"skill_4": (291, 432),
"skill_5": (362, 432),
"skill_6": (432, 432),
"skill_7": (530, 432),
"skill_8": (600, 432),
"skill_9": (672, 432),
"master_skill_option": (896, 273),
"skill_master_1": (680, 230),
"skill_master_2": (747, 230),
"skill_master_3": (813, 230),
"change_3": (400, 400),
"change_4": (550, 400),
"change_confirm": (482, 473),
"skill_select_1": (240, 350),
"skill_select_2": (480, 350),
"skill_select_3": (710, 350),
"noble_fantasy_1": (300, 150),
"noble_fantasy_2": (480, 150),
"noble_fantasy_3": (660, 150),
"arbitrary_command_card_1": (300, 380),
"arbitrary_command_card_2": (490, 380),
"return": (10, 10),
"attack": (850, 450),
}
wait_select = 0.6
wait_effect = 0.6
wait_loading_fight = 10
ctl = Automator()
| [
6738,
17406,
1352,
1330,
17406,
1352,
201,
198,
201,
198,
9150,
62,
67,
14188,
796,
1391,
201,
198,
220,
220,
220,
366,
42401,
62,
16,
1298,
357,
4051,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
17,
1298,
357,
10163,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
18,
1298,
357,
17477,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
19,
1298,
357,
33551,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
20,
1298,
357,
35667,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
21,
1298,
357,
45331,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
22,
1298,
357,
38612,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
23,
1298,
357,
8054,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
24,
1298,
357,
43864,
11,
46393,
828,
201,
198,
220,
220,
220,
366,
9866,
62,
42401,
62,
18076,
1298,
357,
48712,
11,
38549,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
9866,
62,
16,
1298,
357,
37397,
11,
18395,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
9866,
62,
17,
1298,
357,
48882,
11,
18395,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
9866,
62,
18,
1298,
357,
23,
1485,
11,
18395,
828,
201,
198,
220,
220,
220,
366,
3803,
62,
18,
1298,
357,
7029,
11,
7337,
828,
201,
198,
220,
220,
220,
366,
3803,
62,
19,
1298,
357,
22730,
11,
7337,
828,
201,
198,
220,
220,
220,
366,
3803,
62,
10414,
2533,
1298,
357,
40149,
11,
604,
4790,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
19738,
62,
16,
1298,
357,
16102,
11,
13803,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
19738,
62,
17,
1298,
357,
22148,
11,
13803,
828,
201,
198,
220,
220,
220,
366,
42401,
62,
19738,
62,
18,
1298,
357,
43147,
11,
13803,
828,
201,
198,
220,
220,
220,
366,
34952,
293,
62,
69,
34921,
62,
16,
1298,
357,
6200,
11,
6640,
828,
201,
198,
220,
220,
220,
366,
34952,
293,
62,
69,
34921,
62,
17,
1298,
357,
22148,
11,
6640,
828,
201,
198,
220,
220,
220,
366,
34952,
293,
62,
69,
34921,
62,
18,
1298,
357,
39885,
11,
6640,
828,
201,
198,
220,
220,
220,
366,
283,
2545,
11619,
62,
21812,
62,
9517,
62,
16,
1298,
357,
6200,
11,
29101,
828,
201,
198,
220,
220,
220,
366,
283,
2545,
11619,
62,
21812,
62,
9517,
62,
17,
1298,
357,
31503,
11,
29101,
828,
201,
198,
220,
220,
220,
366,
7783,
1298,
357,
940,
11,
838,
828,
201,
198,
220,
220,
220,
366,
20358,
1298,
357,
25764,
11,
18523,
828,
201,
198,
201,
198,
92,
201,
198,
17077,
62,
19738,
796,
657,
13,
21,
201,
198,
17077,
62,
10760,
796,
657,
13,
21,
201,
198,
17077,
62,
25138,
62,
15481,
796,
838,
201,
198,
34168,
796,
17406,
1352,
3419,
201,
198
] | 2.047521 | 484 |
from counterfit_connection import CounterFitConnection
CounterFitConnection.init('127.0.0.1', 5000)
import time
from counterfit_shims_rpi_vl53l0x.vl53l0x import VL53L0X
distance_sensor = VL53L0X()
distance_sensor.begin()
while True:
distance_sensor.wait_ready()
print(f'Distance = {distance_sensor.get_distance()} mm')
time.sleep(1) | [
6738,
3753,
11147,
62,
38659,
1330,
15034,
31805,
32048,
198,
31694,
31805,
32048,
13,
15003,
10786,
16799,
13,
15,
13,
15,
13,
16,
3256,
23336,
8,
198,
198,
11748,
640,
198,
198,
6738,
3753,
11147,
62,
1477,
12078,
62,
81,
14415,
62,
19279,
4310,
75,
15,
87,
13,
19279,
4310,
75,
15,
87,
1330,
569,
43,
4310,
43,
15,
55,
198,
198,
30246,
62,
82,
22854,
796,
569,
43,
4310,
43,
15,
55,
3419,
198,
30246,
62,
82,
22854,
13,
27471,
3419,
198,
198,
4514,
6407,
25,
198,
220,
220,
220,
5253,
62,
82,
22854,
13,
17077,
62,
1493,
3419,
198,
220,
220,
220,
3601,
7,
69,
6,
45767,
796,
1391,
30246,
62,
82,
22854,
13,
1136,
62,
30246,
3419,
92,
8085,
11537,
198,
220,
220,
220,
640,
13,
42832,
7,
16,
8
] | 2.616541 | 133 |
from Database import DatabaseContext | [
6738,
24047,
1330,
24047,
21947
] | 7.2 | 5 |
import re | [
11748,
302
] | 4.5 | 2 |
# -*- coding: utf-8 -*-
"""Active user in game.
Greyd Rule: 1xx
"""
import logging
from datetime import datetime, timedelta
from greyd.db import session
from greyd.models.user import User
from greyd.models.lobby import Lobby
from greyd.models.user_to_lobby import UserToLobby
from greyd.models.chat import Chat
from greyd.models.user_location import UserLocation
class ActiveUser():
"""Active game greyd rules handler.
This class contains user transaction on game.
Decide of game rotation (continue, finish) with request data.
If game finish regular ways then find winnner user.
"""
logger = logging.getLogger(__name__)
def entry(self):
"""Decide of the game request way. Response json.
Greyd Rule - Entry Style
101 - User on a game.
102 - User wait in the lobby.
"""
greyd_rule = self.request["greydRule"]
if greyd_rule == 101:
response = self._refresh_game()
elif greyd_rule == 102:
response = self._refresh_lobby()
else:
error_type = "Wrong greyRule Game request."
response = {"success": False, "errorType": error_type}
self.logger.error("%s GreydId: %s", error_type,
self.request["greydId"])
return response
def _refresh_game(self):
"""Use user location, is taken bait or not?
If user is lobby owner then check is game end?
Return other lobby users information(chat, users.id etc.) in game.
"""
self._add_chat()
if self.lobby.is_bait_taken(self.request["location"]):
self._points_inc_dec()
bait_taken = True
else:
bait_taken = False
location = UserLocation(session_id=self.session_id,
location=self.request["location"],
time=self.time_now,
bait_location=self.lobby.bait_location,
is_bait_taken=bait_taken)
session.add(location)
session.commit()
# Check game is end or continue.
self._is_game_end()
return {"success": True,
"greydRule": self.request["greydRule"],
"greydId": self.request["greydId"],
"lobbyId": self.lobby.id,
"currentBaitLocation": self.lobby.bait_location,
"lobbyStatus": self.lobby.status,
"users": self._user_info_same_lobby()}
def _refresh_lobby(self):
"""Use Chat request and return other users chat information."""
self._add_chat()
if self.lobby.bait_location is None:
bait_location = ""
else:
bait_location = self.lobby.bait_location
return {"success": True,
"greydRule": self.request["greydRule"],
"greydId": self.request["greydId"],
"lobbyId": self.request["lobbyId"],
"lobbyStatus": self.lobby.status,
"baitLocation": bait_location,
"users": self._user_info_same_lobby()}
def _get_lobby(self):
"""Return lobby."""
return session.query(Lobby).filter(
Lobby.id == self.request["lobbyId"]).first()
def _get_session_id(self):
"""Return session id."""
return session.query(UserToLobby.id).filter(
UserToLobby.lobby_id == self.request["lobbyId"]).filter(
UserToLobby.user_id == self.request["greydId"]).first()[0]
def _add_chat(self):
"""Add database chat content."""
if "lobbyChat" in self.request.keys():
for chat_content in self.request["lobbyChat"]:
chat = Chat(session_id=self.session_id,
content=chat_content,
time=self.time_now)
session.add(chat)
session.commit()
def _user_info_same_lobby(self):
"""Get other users info and chat info."""
lobby_users = session.query(UserToLobby).join(UserToLobby.user).filter(
UserToLobby.lobby_id == self.request["lobbyId"]).all()
user_list = []
for lobby_user in lobby_users:
# Find how many taken bait in this lobby.
user_taken_bait = session.query(UserLocation).filter(
UserLocation.session_id == lobby_user.id).filter(
UserLocation.is_bait_taken).count()
user_info = {"userGreydId": lobby_user.user.id,
"userFacebookId": lobby_user.user.facebook_id,
"userFullName": lobby_user.user.full_name,
"userScore": lobby_user.user.total_score,
"userLocation": lobby_user.user.location,
"userTotalBait": user_taken_bait}
# Add chat data in response
chats = session.query(Chat).filter(
Chat.session_id == lobby_user.id).filter(
Chat.id > self.request["lastSeenChatId"]).all()
user_chat = []
for chat in chats:
chat_info = {"chatId": chat.id,
"chatTime": chat.time,
"chatContent": chat.content}
user_chat.append(chat_info)
user_list.append(user_info)
return user_list
def _game_result(self):
"""Game Result. Find winner user."""
self.lobby.end_game()
winner_session = session.query(UserToLobby).order_by(
UserToLobby.collected_bait.desc()).first()
winner_session.is_game_won = True
session.commit()
def _is_game_end(self):
"""Control of game. Control authorization only lobby creator."""
if self.lobby.creator_id != self.request["greydId"]:
return
# Check time ending
start_time = datetime.strptime(self.lobby.start_time, '%m/%d/%Y %H:%M')
expecting_end_time = start_time + \
timedelta(minutes=self.lobby.max_time)
if expecting_end_time <= datetime.now():
self._game_result()
# Check life ending
# How many user have more than 0 life
user_still_playing = session.query(UserToLobby).filter(
UserToLobby.lobby_id == self.lobby.id).filter(
UserToLobby.remaining_life > 0).count()
if user_still_playing < 0:
self._game_result()
def _points_inc_dec(self):
"""Add 1 point for bait taken user and other user lost 1 life."""
user = session.query(User).filter(
User.id == self.request["greydId"]).first()
user.add_point()
users_session = session.query(UserToLobby).filter(
UserToLobby.lobby_id == self.lobby.id).filter(
UserToLobby.remaining_life > 0).all()
for user_session in users_session:
# User is won the bait then increase the collected bait
# else then user lose the life.
if user_session.id == self.session_id:
user_session.collected_bait = user_session.collected_bait + 1
else:
user_session.remaining_life = user_session.remaining_life - 1
session.commit()
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
37811,
13739,
2836,
287,
983,
13,
198,
49141,
67,
14330,
25,
352,
5324,
198,
37811,
198,
198,
11748,
18931,
198,
6738,
4818,
8079,
1330,
4818,
8079,
11,
28805,
12514,
198,
198,
6738,
13791,
67,
13,
9945,
1330,
6246,
198,
6738,
13791,
67,
13,
27530,
13,
7220,
1330,
11787,
198,
6738,
13791,
67,
13,
27530,
13,
75,
11369,
1330,
35068,
198,
6738,
13791,
67,
13,
27530,
13,
7220,
62,
1462,
62,
75,
11369,
1330,
11787,
2514,
43,
11369,
198,
6738,
13791,
67,
13,
27530,
13,
17006,
1330,
24101,
198,
6738,
13791,
67,
13,
27530,
13,
7220,
62,
24886,
1330,
11787,
14749,
628,
198,
4871,
14199,
12982,
33529,
198,
220,
220,
220,
37227,
13739,
983,
13791,
67,
3173,
21360,
13,
198,
220,
220,
220,
770,
1398,
4909,
2836,
8611,
319,
983,
13,
198,
220,
220,
220,
4280,
485,
286,
983,
13179,
357,
43043,
11,
5461,
8,
351,
2581,
1366,
13,
198,
220,
220,
220,
1002,
983,
5461,
3218,
2842,
788,
1064,
1592,
77,
1008,
2836,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
49706,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
628,
220,
220,
220,
825,
5726,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10707,
485,
286,
262,
983,
2581,
835,
13,
18261,
33918,
13,
628,
220,
220,
220,
220,
220,
220,
220,
13980,
67,
14330,
220,
532,
220,
220,
21617,
17738,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8949,
220,
220,
220,
220,
532,
220,
220,
11787,
319,
257,
983,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15143,
220,
220,
220,
220,
532,
220,
220,
11787,
4043,
287,
262,
10866,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
13791,
67,
62,
25135,
796,
2116,
13,
25927,
14692,
49502,
67,
31929,
8973,
198,
220,
220,
220,
220,
220,
220,
220,
611,
13791,
67,
62,
25135,
6624,
8949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
2116,
13557,
5420,
3447,
62,
6057,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
13791,
67,
62,
25135,
6624,
15143,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
2116,
13557,
5420,
3447,
62,
75,
11369,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4049,
62,
4906,
796,
366,
39213,
506,
13791,
31929,
3776,
2581,
526,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
19779,
13138,
1298,
10352,
11,
366,
18224,
6030,
1298,
4049,
62,
4906,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6404,
1362,
13,
18224,
7203,
4,
82,
13980,
67,
7390,
25,
4064,
82,
1600,
4049,
62,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25927,
14692,
49502,
67,
7390,
8973,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2882,
628,
220,
220,
220,
825,
4808,
5420,
3447,
62,
6057,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
11041,
2836,
4067,
11,
318,
2077,
26536,
393,
407,
30,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
2836,
318,
10866,
4870,
788,
2198,
318,
983,
886,
30,
198,
220,
220,
220,
220,
220,
220,
220,
8229,
584,
10866,
2985,
1321,
7,
17006,
11,
2985,
13,
312,
3503,
2014,
287,
983,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
2860,
62,
17006,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
75,
11369,
13,
271,
62,
65,
4548,
62,
83,
1685,
7,
944,
13,
25927,
14692,
24886,
8973,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
13033,
62,
1939,
62,
12501,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26536,
62,
83,
1685,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26536,
62,
83,
1685,
796,
10352,
628,
220,
220,
220,
220,
220,
220,
220,
4067,
796,
11787,
14749,
7,
29891,
62,
312,
28,
944,
13,
29891,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4067,
28,
944,
13,
25927,
14692,
24886,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
28,
944,
13,
2435,
62,
2197,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26536,
62,
24886,
28,
944,
13,
75,
11369,
13,
65,
4548,
62,
24886,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
65,
4548,
62,
83,
1685,
28,
65,
4548,
62,
83,
1685,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
2860,
7,
24886,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
41509,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
6822,
983,
318,
886,
393,
2555,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
271,
62,
6057,
62,
437,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
19779,
13138,
1298,
6407,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49502,
67,
31929,
1298,
2116,
13,
25927,
14692,
49502,
67,
31929,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49502,
67,
7390,
1298,
2116,
13,
25927,
14692,
49502,
67,
7390,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
75,
11369,
7390,
1298,
2116,
13,
75,
11369,
13,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
14421,
33,
4548,
14749,
1298,
2116,
13,
75,
11369,
13,
65,
4548,
62,
24886,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
75,
11369,
19580,
1298,
2116,
13,
75,
11369,
13,
13376,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
18417,
1298,
2116,
13557,
7220,
62,
10951,
62,
31642,
62,
75,
11369,
3419,
92,
628,
220,
220,
220,
825,
4808,
5420,
3447,
62,
75,
11369,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
11041,
24101,
2581,
290,
1441,
584,
2985,
8537,
1321,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
2860,
62,
17006,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
75,
11369,
13,
65,
4548,
62,
24886,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26536,
62,
24886,
796,
13538,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26536,
62,
24886,
796,
2116,
13,
75,
11369,
13,
65,
4548,
62,
24886,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
19779,
13138,
1298,
6407,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49502,
67,
31929,
1298,
2116,
13,
25927,
14692,
49502,
67,
31929,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49502,
67,
7390,
1298,
2116,
13,
25927,
14692,
49502,
67,
7390,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
75,
11369,
7390,
1298,
2116,
13,
25927,
14692,
75,
11369,
7390,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
75,
11369,
19580,
1298,
2116,
13,
75,
11369,
13,
13376,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
65,
4548,
14749,
1298,
26536,
62,
24886,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
18417,
1298,
2116,
13557,
7220,
62,
10951,
62,
31642,
62,
75,
11369,
3419,
92,
628,
220,
220,
220,
825,
4808,
1136,
62,
75,
11369,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
10866,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6246,
13,
22766,
7,
43,
11369,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35068,
13,
312,
6624,
2116,
13,
25927,
14692,
75,
11369,
7390,
8973,
737,
11085,
3419,
628,
220,
220,
220,
825,
4808,
1136,
62,
29891,
62,
312,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
6246,
4686,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6246,
13,
22766,
7,
12982,
2514,
43,
11369,
13,
312,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
75,
11369,
62,
312,
6624,
2116,
13,
25927,
14692,
75,
11369,
7390,
8973,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
7220,
62,
312,
6624,
2116,
13,
25927,
14692,
49502,
67,
7390,
8973,
737,
11085,
3419,
58,
15,
60,
628,
220,
220,
220,
825,
4808,
2860,
62,
17006,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
4550,
6831,
8537,
2695,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
611,
366,
75,
11369,
30820,
1,
287,
2116,
13,
25927,
13,
13083,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
8537,
62,
11299,
287,
2116,
13,
25927,
14692,
75,
11369,
30820,
1,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8537,
796,
24101,
7,
29891,
62,
312,
28,
944,
13,
29891,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2695,
28,
17006,
62,
11299,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
28,
944,
13,
2435,
62,
2197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
2860,
7,
17006,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
41509,
3419,
628,
220,
220,
220,
825,
4808,
7220,
62,
10951,
62,
31642,
62,
75,
11369,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
3855,
584,
2985,
7508,
290,
8537,
7508,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
10866,
62,
18417,
796,
6246,
13,
22766,
7,
12982,
2514,
43,
11369,
737,
22179,
7,
12982,
2514,
43,
11369,
13,
7220,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
75,
11369,
62,
312,
6624,
2116,
13,
25927,
14692,
75,
11369,
7390,
8973,
737,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
4868,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
10866,
62,
7220,
287,
10866,
62,
18417,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
9938,
703,
867,
2077,
26536,
287,
428,
10866,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
83,
1685,
62,
65,
4548,
796,
6246,
13,
22766,
7,
12982,
14749,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
14749,
13,
29891,
62,
312,
6624,
10866,
62,
7220,
13,
312,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
14749,
13,
271,
62,
65,
4548,
62,
83,
1685,
737,
9127,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
10951,
796,
19779,
7220,
49141,
67,
7390,
1298,
10866,
62,
7220,
13,
7220,
13,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7220,
12025,
7390,
1298,
10866,
62,
7220,
13,
7220,
13,
19024,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7220,
13295,
5376,
1298,
10866,
62,
7220,
13,
7220,
13,
12853,
62,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7220,
26595,
1298,
10866,
62,
7220,
13,
7220,
13,
23350,
62,
26675,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7220,
14749,
1298,
10866,
62,
7220,
13,
7220,
13,
24886,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7220,
14957,
33,
4548,
1298,
2836,
62,
83,
1685,
62,
65,
4548,
92,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
8537,
1366,
287,
2882,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40815,
796,
6246,
13,
22766,
7,
30820,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24101,
13,
29891,
62,
312,
6624,
10866,
62,
7220,
13,
312,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24101,
13,
312,
1875,
2116,
13,
25927,
14692,
12957,
4653,
268,
30820,
7390,
8973,
737,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
17006,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
8537,
287,
40815,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8537,
62,
10951,
796,
19779,
17006,
7390,
1298,
8537,
13,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17006,
7575,
1298,
8537,
13,
2435,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17006,
19746,
1298,
8537,
13,
11299,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
17006,
13,
33295,
7,
17006,
62,
10951,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
4868,
13,
33295,
7,
7220,
62,
10951,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2836,
62,
4868,
628,
220,
220,
220,
825,
4808,
6057,
62,
20274,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
8777,
25414,
13,
9938,
8464,
2836,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
75,
11369,
13,
437,
62,
6057,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
8464,
62,
29891,
796,
6246,
13,
22766,
7,
12982,
2514,
43,
11369,
737,
2875,
62,
1525,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
4033,
12609,
62,
65,
4548,
13,
20147,
3419,
737,
11085,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
8464,
62,
29891,
13,
271,
62,
6057,
62,
26502,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
41509,
3419,
628,
220,
220,
220,
825,
4808,
271,
62,
6057,
62,
437,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
15988,
286,
983,
13,
6779,
19601,
691,
10866,
13172,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
75,
11369,
13,
45382,
62,
312,
14512,
2116,
13,
25927,
14692,
49502,
67,
7390,
1,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
6822,
640,
7464,
198,
220,
220,
220,
220,
220,
220,
220,
923,
62,
2435,
796,
4818,
8079,
13,
2536,
457,
524,
7,
944,
13,
75,
11369,
13,
9688,
62,
2435,
11,
705,
4,
76,
14,
4,
67,
14,
4,
56,
4064,
39,
25,
4,
44,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
12451,
62,
437,
62,
2435,
796,
923,
62,
2435,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28805,
12514,
7,
1084,
1769,
28,
944,
13,
75,
11369,
13,
9806,
62,
2435,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
12451,
62,
437,
62,
2435,
19841,
4818,
8079,
13,
2197,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
6057,
62,
20274,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
6822,
1204,
7464,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1374,
867,
2836,
423,
517,
621,
657,
1204,
198,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
24219,
62,
17916,
796,
6246,
13,
22766,
7,
12982,
2514,
43,
11369,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
75,
11369,
62,
312,
6624,
2116,
13,
75,
11369,
13,
312,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
2787,
1397,
62,
6042,
1875,
657,
737,
9127,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2836,
62,
24219,
62,
17916,
1279,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
6057,
62,
20274,
3419,
628,
220,
220,
220,
825,
4808,
13033,
62,
1939,
62,
12501,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
4550,
352,
966,
329,
26536,
2077,
2836,
290,
584,
2836,
2626,
352,
1204,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2836,
796,
6246,
13,
22766,
7,
12982,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
13,
312,
6624,
2116,
13,
25927,
14692,
49502,
67,
7390,
8973,
737,
11085,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2836,
13,
2860,
62,
4122,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
2985,
62,
29891,
796,
6246,
13,
22766,
7,
12982,
2514,
43,
11369,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
75,
11369,
62,
312,
6624,
2116,
13,
75,
11369,
13,
312,
737,
24455,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11787,
2514,
43,
11369,
13,
2787,
1397,
62,
6042,
1875,
657,
737,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
329,
2836,
62,
29891,
287,
2985,
62,
29891,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
11787,
318,
1839,
262,
26536,
788,
2620,
262,
7723,
26536,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2073,
788,
2836,
4425,
262,
1204,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2836,
62,
29891,
13,
312,
6624,
2116,
13,
29891,
62,
312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
29891,
13,
4033,
12609,
62,
65,
4548,
796,
2836,
62,
29891,
13,
4033,
12609,
62,
65,
4548,
1343,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2836,
62,
29891,
13,
2787,
1397,
62,
6042,
796,
2836,
62,
29891,
13,
2787,
1397,
62,
6042,
532,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6246,
13,
41509,
3419,
198
] | 2.081916 | 3,528 |
#!/usr/bin/env python
from argparse import ArgumentParser
import sys
if __name__ == '__main__':
arg_parser = ArgumentParser(description='compute primes')
arg_parser.add_argument('implmentation', choices=['python', 'numba'
'python_array',
'numba_array'],
default='python', nargs='?',
help='implementation to run')
arg_parser.add_argument('--n', type=int, default=10,
help='number of primes')
options = arg_parser.parse_args()
if options.implmentation == 'python':
from primes_vanilla import primes
elif options.implmentation == 'numba':
from primes_numba import primes
results = primes(options.n)
print(', '.join(map(str, results)))
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
6738,
1822,
29572,
1330,
45751,
46677,
198,
11748,
25064,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1822,
62,
48610,
796,
45751,
46677,
7,
11213,
11639,
5589,
1133,
778,
999,
11537,
198,
220,
220,
220,
1822,
62,
48610,
13,
2860,
62,
49140,
10786,
23928,
14374,
3256,
7747,
28,
17816,
29412,
3256,
705,
77,
2178,
64,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
29412,
62,
18747,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
77,
2178,
64,
62,
18747,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
11639,
29412,
3256,
299,
22046,
11639,
30,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
320,
32851,
284,
1057,
11537,
198,
220,
220,
220,
1822,
62,
48610,
13,
2860,
62,
49140,
10786,
438,
77,
3256,
2099,
28,
600,
11,
4277,
28,
940,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
11639,
17618,
286,
778,
999,
11537,
198,
220,
220,
220,
3689,
796,
1822,
62,
48610,
13,
29572,
62,
22046,
3419,
198,
220,
220,
220,
611,
3689,
13,
23928,
14374,
6624,
705,
29412,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
422,
778,
999,
62,
10438,
5049,
1330,
778,
999,
198,
220,
220,
220,
1288,
361,
3689,
13,
23928,
14374,
6624,
705,
77,
2178,
64,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
422,
778,
999,
62,
77,
2178,
64,
1330,
778,
999,
198,
220,
220,
220,
2482,
796,
778,
999,
7,
25811,
13,
77,
8,
198,
220,
220,
220,
3601,
7,
3256,
45302,
22179,
7,
8899,
7,
2536,
11,
2482,
22305,
198
] | 2.020785 | 433 |
# Generated by Django 3.1.7 on 2021-04-08 07:14
from django.db import migrations, models
import django.db.models.deletion
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
22,
319,
33448,
12,
3023,
12,
2919,
8753,
25,
1415,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
198,
11748,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
628
] | 2.818182 | 44 |
from django.db.models.query import QuerySet
from rest_framework import generics, mixins, viewsets
from rest_framework import filters
import django_filters.rest_framework
from django.http import JsonResponse
from rest_framework.renderers import JSONRenderer
from django.shortcuts import get_object_or_404
from fiche_produit.models import Employee, Product, ProductCard, Order, Facture, ProductCardAnnexe5, Project, Specification, Declaration, Tds, Coo, Routage, \
OrderItem, FactureItem, Lot
from .serializers import FPModelSerializer, ProductModelSerializer, OrderModelSerializer, FactureModelSerializer, \
SpecificationModelSerializer, DeclarationModelSerializer, TdsModelSerializer, CooModelSerializer, RoutageModelSerializer, \
RoutageModelSerializer, OrderItemModelSerializer, FactureItemModelSerializer, FPNewNumberSerializer, \
ProductCardAnnexe5ModelSerializer
class EnablePartialUpdateMixin:
"""Enable partial updates
Override partial kwargs in UpdateModelMixin class
https://github.com/encode/django-rest-framework/blob/91916a4db14cd6a06aca13fb9a46fc667f6c0682/rest_framework/mixins.py#L64
"""
| [
6738,
42625,
14208,
13,
9945,
13,
27530,
13,
22766,
1330,
43301,
7248,
198,
6738,
1334,
62,
30604,
1330,
1152,
873,
11,
5022,
1040,
11,
5009,
1039,
198,
6738,
1334,
62,
30604,
1330,
16628,
198,
11748,
42625,
14208,
62,
10379,
1010,
13,
2118,
62,
30604,
198,
6738,
42625,
14208,
13,
4023,
1330,
449,
1559,
31077,
198,
6738,
1334,
62,
30604,
13,
10920,
19288,
1330,
19449,
49,
437,
11882,
198,
6738,
42625,
14208,
13,
19509,
23779,
1330,
651,
62,
15252,
62,
273,
62,
26429,
198,
198,
6738,
277,
14234,
62,
18230,
270,
13,
27530,
1330,
36824,
11,
8721,
11,
8721,
16962,
11,
8284,
11,
19020,
495,
11,
8721,
16962,
2025,
12413,
68,
20,
11,
4935,
11,
18291,
2649,
11,
24720,
11,
309,
9310,
11,
1766,
78,
11,
39602,
496,
11,
3467,
198,
220,
220,
220,
8284,
7449,
11,
19020,
495,
7449,
11,
15099,
198,
6738,
764,
46911,
11341,
1330,
31459,
17633,
32634,
7509,
11,
8721,
17633,
32634,
7509,
11,
8284,
17633,
32634,
7509,
11,
19020,
495,
17633,
32634,
7509,
11,
3467,
198,
220,
220,
220,
18291,
2649,
17633,
32634,
7509,
11,
24720,
17633,
32634,
7509,
11,
309,
9310,
17633,
32634,
7509,
11,
1766,
78,
17633,
32634,
7509,
11,
39602,
496,
17633,
32634,
7509,
11,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
39602,
496,
17633,
32634,
7509,
11,
8284,
7449,
17633,
32634,
7509,
11,
19020,
495,
7449,
17633,
32634,
7509,
11,
31459,
3791,
15057,
32634,
7509,
11,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8721,
16962,
2025,
12413,
68,
20,
17633,
32634,
7509,
628,
198,
4871,
27882,
7841,
498,
10260,
35608,
259,
25,
198,
220,
220,
220,
37227,
36695,
13027,
5992,
628,
220,
220,
220,
3827,
13154,
13027,
479,
86,
22046,
287,
10133,
17633,
35608,
259,
1398,
198,
220,
220,
220,
3740,
1378,
12567,
13,
785,
14,
268,
8189,
14,
28241,
14208,
12,
2118,
12,
30604,
14,
2436,
672,
14,
24,
1129,
1433,
64,
19,
9945,
1415,
10210,
21,
64,
3312,
22260,
1485,
21855,
24,
64,
3510,
16072,
28933,
69,
21,
66,
15,
43950,
14,
2118,
62,
30604,
14,
19816,
1040,
13,
9078,
2,
43,
2414,
198,
220,
220,
220,
37227,
628,
628,
628,
628,
628,
628,
198
] | 3.203857 | 363 |
# flake8: noqa
import warnings
from .drf_urls import *
warnings.warn(
"drf-urls.py is not a valid module name and will be "
"removed in a future version, use drf_urls.py instead",
PendingDeprecationWarning
)
| [
2,
781,
539,
23,
25,
645,
20402,
198,
11748,
14601,
198,
6738,
764,
7109,
69,
62,
6371,
82,
1330,
1635,
198,
198,
40539,
654,
13,
40539,
7,
198,
220,
220,
220,
366,
7109,
69,
12,
6371,
82,
13,
9078,
318,
407,
257,
4938,
8265,
1438,
290,
481,
307,
366,
198,
220,
220,
220,
366,
2787,
2668,
287,
257,
2003,
2196,
11,
779,
1553,
69,
62,
6371,
82,
13,
9078,
2427,
1600,
198,
220,
220,
220,
350,
1571,
12156,
8344,
341,
20361,
198,
8,
198
] | 2.630952 | 84 |
import logging
import socket
from concurrent.futures import Executor
from time import time
import cv2
import numpy as np
from adbutils import AdbDevice
from .raw_socket import send_raw
logger = logging.getLogger(__name__)
| [
11748,
18931,
198,
11748,
17802,
198,
6738,
24580,
13,
69,
315,
942,
1330,
8393,
38409,
198,
6738,
640,
1330,
640,
198,
198,
11748,
269,
85,
17,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
512,
4360,
4487,
1330,
1215,
65,
24728,
198,
198,
6738,
764,
1831,
62,
44971,
1330,
3758,
62,
1831,
198,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
628,
628
] | 3.304348 | 69 |
# Test of phase Module (Manual)
import numpy as np
import math as math
import data as data
import phase as phase
import matplotlib.pyplot as plt
import statistics
##########################################################
# Test Difference of identical phase # 1
##########################################################
# Generate data to be passed through phase
data_em_test_1 = data.EMdata()
x1 = np.linspace(0, 255, 256)
y1 = np.linspace(0, 255, 256)
mx1, my1 = np.meshgrid(x1, y1)
data_em_test_1.holo_1 = np.sin(mx1 * 2 * np.pi / 16)
data_em_test_1.holo_2_aligned = data_em_test_1.holo_1
data_em_test_1.holo_ref = data_em_test_1.holo_1
# Circle of radius 1 centered around coordinate (192, 128)
r1 = 1
center1 = (144, 128)
# Pass through phase
phase.phase(center1, r1, data_em_test_1)
# Display results
fig_test_1_2d = plt.figure()
fig_test_1_2d_ax1 = fig_test_1_2d.add_subplot(2, 2, 1)
fig_test_1_2d_ax2 = fig_test_1_2d.add_subplot(2, 2, 2)
fig_test_1_2d_ax3 = fig_test_1_2d.add_subplot(2, 2, 3)
fig_test_1_2d_ax4 = fig_test_1_2d.add_subplot(2, 2, 4)
fig_test_1_2d_ax1.imshow(data_em_test_1.phase_1)
fig_test_1_2d_ax2.imshow(data_em_test_1.phase_2)
fig_test_1_2d_ax3.imshow(data_em_test_1.phase_ref)
fig_test_1_2d_ax4.imshow(data_em_test_1.diff_2_1_not_cor)
fig_test_1_2d_ax1.set_title('Unwrap-1')
fig_test_1_2d_ax2.set_title('Unwrap-2')
fig_test_1_2d_ax3.set_title('Unwrap-Ref')
fig_test_1_2d_ax4.set_title('2-1-uncor')
fig_test_1_1d = plt.figure()
fig_test_1_1d_ax1 = fig_test_1_1d.add_subplot(2, 2, 1)
fig_test_1_1d_ax2 = fig_test_1_1d.add_subplot(2, 2, 2)
fig_test_1_1d_ax3 = fig_test_1_1d.add_subplot(2, 2, 3)
fig_test_1_1d_ax4 = fig_test_1_1d.add_subplot(2, 2, 4)
fig_test_1_1d_ax1.plot(data_em_test_1.diff_1_ref[128, :])
# fig_test_1_1d_ax1.set_ylim(-np.pi, np.pi)
fig_test_1_1d_ax2.plot(data_em_test_1.diff_2_ref[128, :])
# fig_test_1_1d_ax2.set_ylim(-np.pi, np.pi)
fig_test_1_1d_ax3.plot(data_em_test_1.diff_2_1_cor[128, :])
# fig_test_1_1d_ax3.set_ylim(-np.pi, np.pi)
fig_test_1_1d_ax4.plot(data_em_test_1.diff_2_1_not_cor[128, :])
# fig_test_1_1d_ax4.set_ylim(-np.pi, np.pi)
fig_test_1_1d_ax1.set_title('1-Ref')
fig_test_1_1d_ax2.set_title('2-Ref')
fig_test_1_1d_ax3.set_title('2-1-cor')
fig_test_1_1d_ax4.set_title('2-1-uncor')
plt.show()
##########################################################
# Test Difference of known phase images # 2
##########################################################
# Generate data to be passed through phase
data_em_test_2 = data.EMdata()
x2 = np.linspace(0, 255, 256)
y2 = np.linspace(0, 255, 256)
mx2, my2 = np.meshgrid(x2, y2)
a2 = 4
b2 = 4.5
data_em_test_2.holo_1 = np.sin(mx2 * 2 * np.pi / a2)
data_em_test_2.holo_2_aligned = np.sin(mx2 * 2 * np.pi / b2)
data_em_test_2.holo_ref = data_em_test_2.holo_1
# Circle of radius 1 centered around coordinate (192, 128)
r2 = 20
center2 = (192, 128)
# Pass through phase
phase.phase(center2, r2, data_em_test_2)
# Display results
fig_test_2_2d = plt.figure()
fig_test_2_2d_ax1 = fig_test_2_2d.add_subplot(2, 2, 1)
fig_test_2_2d_ax2 = fig_test_2_2d.add_subplot(2, 2, 2)
fig_test_2_2d_ax3 = fig_test_2_2d.add_subplot(2, 2, 3)
fig_test_2_2d_ax4 = fig_test_2_2d.add_subplot(2, 2, 4)
fig_test_2_2d_ax1.imshow(data_em_test_2.phase_1)
fig_test_2_2d_ax2.imshow(data_em_test_2.phase_2)
fig_test_2_2d_ax3.imshow(data_em_test_2.phase_ref)
fig_test_2_2d_ax4.imshow(data_em_test_2.diff_2_1_not_cor)
fig_test_2_2d_ax1.set_title('Unwrap-1')
fig_test_2_2d_ax2.set_title('Unwrap-2')
fig_test_2_2d_ax3.set_title('Unwrap-Ref')
fig_test_2_2d_ax4.set_title('2-1-uncor')
fig_test_2_1d = plt.figure()
fig_test_2_1d_ax1 = fig_test_2_1d.add_subplot(2, 2, 1)
fig_test_2_1d_ax2 = fig_test_2_1d.add_subplot(2, 2, 2)
fig_test_2_1d_ax3 = fig_test_2_1d.add_subplot(2, 2, 3)
fig_test_2_1d_ax4 = fig_test_2_1d.add_subplot(2, 2, 4)
fig_test_2_1d_ax1.plot(data_em_test_2.diff_1_ref[128, :])
# fig_test_1_1d_ax1.set_ylim(-np.pi, np.pi)
fig_test_2_1d_ax2.plot(data_em_test_2.diff_2_ref[128, :])
# fig_test_1_1d_ax2.set_ylim(-np.pi, np.pi)
fig_test_2_1d_ax3.plot(data_em_test_2.diff_2_1_cor[128, :])
# fig_test_1_1d_ax3.set_ylim(-np.pi, np.pi)
fig_test_2_1d_ax4.plot(data_em_test_2.diff_2_1_not_cor[128, :])
# fig_test_1_1d_ax4.set_ylim(-np.pi, np.pi)
fig_test_2_1d_ax1.set_title('1-Ref')
fig_test_2_1d_ax2.set_title('2-Ref')
fig_test_2_1d_ax3.set_title('2-1-cor')
fig_test_2_1d_ax4.set_title('2-1-uncor')
slope_th = (2 * np.pi / b2) - (2 * np.pi / a2)
slope_exp = (data_em_test_2.diff_2_1_not_cor[128, 253] - data_em_test_2.diff_2_1_not_cor[128, 2]) / 251
error_slope = abs(slope_th - slope_exp)
print('Theoretical slope ', slope_th)
print('Experimental slope ', slope_exp)
print('Slope error ', error_slope)
plt.show() | [
2,
6208,
286,
7108,
19937,
357,
5124,
723,
8,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
10688,
355,
10688,
198,
11748,
1366,
355,
1366,
198,
11748,
7108,
355,
7108,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
7869,
198,
198,
29113,
14468,
7804,
2235,
198,
2,
6208,
43795,
286,
10411,
7108,
1303,
352,
198,
29113,
14468,
7804,
2235,
198,
198,
2,
2980,
378,
1366,
284,
307,
3804,
832,
7108,
198,
7890,
62,
368,
62,
9288,
62,
16,
796,
1366,
13,
3620,
7890,
3419,
198,
198,
87,
16,
796,
45941,
13,
21602,
10223,
7,
15,
11,
14280,
11,
17759,
8,
198,
88,
16,
796,
45941,
13,
21602,
10223,
7,
15,
11,
14280,
11,
17759,
8,
198,
36802,
16,
11,
616,
16,
796,
45941,
13,
76,
5069,
25928,
7,
87,
16,
11,
331,
16,
8,
198,
7890,
62,
368,
62,
9288,
62,
16,
13,
3937,
78,
62,
16,
796,
45941,
13,
31369,
7,
36802,
16,
1635,
362,
1635,
45941,
13,
14415,
1220,
1467,
8,
198,
7890,
62,
368,
62,
9288,
62,
16,
13,
3937,
78,
62,
17,
62,
41634,
796,
1366,
62,
368,
62,
9288,
62,
16,
13,
3937,
78,
62,
16,
198,
7890,
62,
368,
62,
9288,
62,
16,
13,
3937,
78,
62,
5420,
796,
1366,
62,
368,
62,
9288,
62,
16,
13,
3937,
78,
62,
16,
198,
198,
2,
16291,
286,
16874,
352,
19254,
1088,
20435,
357,
17477,
11,
13108,
8,
198,
81,
16,
796,
352,
198,
16159,
16,
796,
357,
18444,
11,
13108,
8,
198,
198,
2,
6251,
832,
7108,
198,
40715,
13,
40715,
7,
16159,
16,
11,
374,
16,
11,
1366,
62,
368,
62,
9288,
62,
16,
8,
198,
198,
2,
16531,
2482,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
796,
458,
83,
13,
26875,
3419,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
16,
796,
2336,
62,
9288,
62,
16,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
352,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
17,
796,
2336,
62,
9288,
62,
16,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
362,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
18,
796,
2336,
62,
9288,
62,
16,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
513,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
19,
796,
2336,
62,
9288,
62,
16,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
604,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
16,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
40715,
62,
16,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
17,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
40715,
62,
17,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
18,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
40715,
62,
5420,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
19,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
8,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
16,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
16,
11537,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
17,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
17,
11537,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
18,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
16,
62,
17,
67,
62,
897,
19,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
403,
10215,
11537,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
796,
458,
83,
13,
26875,
3419,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
16,
796,
2336,
62,
9288,
62,
16,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
352,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
17,
796,
2336,
62,
9288,
62,
16,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
362,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
18,
796,
2336,
62,
9288,
62,
16,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
513,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
19,
796,
2336,
62,
9288,
62,
16,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
604,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
16,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
26069,
62,
16,
62,
5420,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
16,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
17,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
26069,
62,
17,
62,
5420,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
17,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
18,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
26069,
62,
17,
62,
16,
62,
10215,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
18,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
19,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
16,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
19,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
16,
13,
2617,
62,
7839,
10786,
16,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
17,
13,
2617,
62,
7839,
10786,
17,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
18,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
10215,
11537,
198,
5647,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
19,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
403,
10215,
11537,
198,
198,
489,
83,
13,
12860,
3419,
198,
198,
29113,
14468,
7804,
2235,
198,
2,
6208,
43795,
286,
1900,
7108,
4263,
1303,
362,
198,
29113,
14468,
7804,
2235,
198,
198,
2,
2980,
378,
1366,
284,
307,
3804,
832,
7108,
198,
7890,
62,
368,
62,
9288,
62,
17,
796,
1366,
13,
3620,
7890,
3419,
198,
198,
87,
17,
796,
45941,
13,
21602,
10223,
7,
15,
11,
14280,
11,
17759,
8,
198,
88,
17,
796,
45941,
13,
21602,
10223,
7,
15,
11,
14280,
11,
17759,
8,
198,
36802,
17,
11,
616,
17,
796,
45941,
13,
76,
5069,
25928,
7,
87,
17,
11,
331,
17,
8,
198,
64,
17,
796,
604,
198,
65,
17,
796,
604,
13,
20,
198,
7890,
62,
368,
62,
9288,
62,
17,
13,
3937,
78,
62,
16,
796,
45941,
13,
31369,
7,
36802,
17,
1635,
362,
1635,
45941,
13,
14415,
1220,
257,
17,
8,
198,
7890,
62,
368,
62,
9288,
62,
17,
13,
3937,
78,
62,
17,
62,
41634,
796,
45941,
13,
31369,
7,
36802,
17,
1635,
362,
1635,
45941,
13,
14415,
1220,
275,
17,
8,
198,
7890,
62,
368,
62,
9288,
62,
17,
13,
3937,
78,
62,
5420,
796,
1366,
62,
368,
62,
9288,
62,
17,
13,
3937,
78,
62,
16,
198,
198,
2,
16291,
286,
16874,
352,
19254,
1088,
20435,
357,
17477,
11,
13108,
8,
198,
81,
17,
796,
1160,
198,
16159,
17,
796,
357,
17477,
11,
13108,
8,
198,
198,
2,
6251,
832,
7108,
198,
40715,
13,
40715,
7,
16159,
17,
11,
374,
17,
11,
1366,
62,
368,
62,
9288,
62,
17,
8,
198,
198,
2,
16531,
2482,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
796,
458,
83,
13,
26875,
3419,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
16,
796,
2336,
62,
9288,
62,
17,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
352,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
17,
796,
2336,
62,
9288,
62,
17,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
362,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
18,
796,
2336,
62,
9288,
62,
17,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
513,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
19,
796,
2336,
62,
9288,
62,
17,
62,
17,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
604,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
16,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
40715,
62,
16,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
17,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
40715,
62,
17,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
18,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
40715,
62,
5420,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
19,
13,
320,
12860,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
8,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
16,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
16,
11537,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
17,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
17,
11537,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
18,
13,
2617,
62,
7839,
10786,
3118,
37150,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
17,
62,
17,
67,
62,
897,
19,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
403,
10215,
11537,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
796,
458,
83,
13,
26875,
3419,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
16,
796,
2336,
62,
9288,
62,
17,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
352,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
17,
796,
2336,
62,
9288,
62,
17,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
362,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
18,
796,
2336,
62,
9288,
62,
17,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
513,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
19,
796,
2336,
62,
9288,
62,
17,
62,
16,
67,
13,
2860,
62,
7266,
29487,
7,
17,
11,
362,
11,
604,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
16,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
16,
62,
5420,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
16,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
17,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
5420,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
17,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
18,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
16,
62,
10215,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
18,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
19,
13,
29487,
7,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
58,
12762,
11,
1058,
12962,
198,
2,
2336,
62,
9288,
62,
16,
62,
16,
67,
62,
897,
19,
13,
2617,
62,
88,
2475,
32590,
37659,
13,
14415,
11,
45941,
13,
14415,
8,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
16,
13,
2617,
62,
7839,
10786,
16,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
17,
13,
2617,
62,
7839,
10786,
17,
12,
8134,
11537,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
18,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
10215,
11537,
198,
5647,
62,
9288,
62,
17,
62,
16,
67,
62,
897,
19,
13,
2617,
62,
7839,
10786,
17,
12,
16,
12,
403,
10215,
11537,
198,
198,
6649,
3008,
62,
400,
796,
357,
17,
1635,
45941,
13,
14415,
1220,
275,
17,
8,
532,
357,
17,
1635,
45941,
13,
14415,
1220,
257,
17,
8,
198,
6649,
3008,
62,
11201,
796,
357,
7890,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
58,
12762,
11,
32056,
60,
532,
1366,
62,
368,
62,
9288,
62,
17,
13,
26069,
62,
17,
62,
16,
62,
1662,
62,
10215,
58,
12762,
11,
362,
12962,
1220,
34489,
198,
18224,
62,
6649,
3008,
796,
2352,
7,
6649,
3008,
62,
400,
532,
22638,
62,
11201,
8,
198,
4798,
10786,
464,
9997,
605,
22638,
46083,
22638,
62,
400,
8,
198,
4798,
10786,
20468,
9134,
22638,
46083,
22638,
62,
11201,
8,
198,
4798,
10786,
11122,
3008,
4049,
46083,
4049,
62,
6649,
3008,
8,
198,
198,
489,
83,
13,
12860,
3419
] | 1.991946 | 2,359 |
#!/usr/bin/python3
import sys
import os
sys.path.append( os.path.dirname( os.path.realpath(__file__) ) + '/../..' )
from shared import Ipv4Validator
from common import Parameter
import unittest
import mock
if __name__ == '__main__':
unittest.main()
| [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
198,
11748,
25064,
198,
11748,
28686,
198,
17597,
13,
6978,
13,
33295,
7,
28686,
13,
6978,
13,
15908,
3672,
7,
28686,
13,
6978,
13,
5305,
6978,
7,
834,
7753,
834,
8,
1267,
1343,
31051,
40720,
492,
6,
1267,
198,
6738,
4888,
1330,
314,
79,
85,
19,
47139,
1352,
198,
6738,
2219,
1330,
25139,
2357,
220,
198,
11748,
555,
715,
395,
198,
11748,
15290,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.712766 | 94 |
"""
@brief test log(time=1s)
"""
import sys
import os
import unittest
from datetime import datetime
from pyquickhelper.loghelper import fLOG
try:
import src
except ImportError:
path = os.path.normpath(
os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"..",
"..")))
if path not in sys.path:
sys.path.append(path)
import src
from src.ensae_teaching_cs.td_1a.classiques import racine_carree, commentaire_accentues, dix_entiers_carre
from src.ensae_teaching_cs.td_1a.classiques import repetition_a_eviter, str2date
if __name__ == "__main__":
unittest.main()
| [
37811,
198,
31,
65,
3796,
220,
220,
220,
220,
220,
1332,
2604,
7,
2435,
28,
16,
82,
8,
198,
37811,
628,
198,
11748,
25064,
198,
11748,
28686,
198,
11748,
555,
715,
395,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
6738,
12972,
24209,
2978,
525,
13,
6404,
2978,
525,
1330,
277,
25294,
628,
198,
28311,
25,
198,
220,
220,
220,
1330,
12351,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
27237,
6978,
7,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
397,
2777,
776,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
35312,
7,
834,
7753,
834,
38381,
15,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
492,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
492,
1,
22305,
198,
220,
220,
220,
611,
3108,
407,
287,
25064,
13,
6978,
25,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
6978,
13,
33295,
7,
6978,
8,
198,
220,
220,
220,
1330,
12351,
198,
198,
6738,
12351,
13,
641,
3609,
62,
660,
8103,
62,
6359,
13,
8671,
62,
16,
64,
13,
4871,
6368,
1330,
3444,
500,
62,
7718,
631,
11,
2912,
7626,
62,
330,
1087,
947,
11,
288,
844,
62,
298,
3183,
62,
7718,
260,
198,
6738,
12351,
13,
641,
3609,
62,
660,
8103,
62,
6359,
13,
8671,
62,
16,
64,
13,
4871,
6368,
1330,
29693,
62,
64,
62,
1990,
2676,
11,
965,
17,
4475,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.163987 | 311 |
from dataclasses import dataclass
from typing import List, Generic
from datetime import datetime
import Adafruit_ADS1x15
from app.sensors.sensor import Sensor
@dataclass
| [
6738,
4818,
330,
28958,
1330,
4818,
330,
31172,
198,
6738,
19720,
1330,
7343,
11,
42044,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
11748,
1215,
1878,
4872,
62,
47149,
16,
87,
1314,
198,
198,
6738,
598,
13,
82,
641,
669,
13,
82,
22854,
1330,
35367,
628,
198,
31,
19608,
330,
31172,
628
] | 3.301887 | 53 |
import pygame
from pygame.sprite import Sprite | [
11748,
12972,
6057,
198,
6738,
12972,
6057,
13,
34975,
578,
1330,
33132
] | 3.833333 | 12 |
############################################################################################
#
# Project: Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research Project
# Repository: ALL Detection System 2019
# Project: Facial Authentication Server
#
# Author: Adam Milton-Barker (AdamMiltonBarker.com)
# Contributors:
# Title: Data Class
# Description: Data class for the ALL Detection System 2019 NCS1 Classifier.
# License: MIT License
# Last Modified: 2020-07-16
#
############################################################################################
import cv2, glob, json, math, os, pathlib, random, sys, time
import numpy as np
import tensorflow as tf
from datetime import datetime
from PIL import Image
from sys import argv
from Classes.Helpers import Helpers
class Data():
""" Data Helper Class
Core data management class for the ALL Detection System 2019 NCS1 Classifier
"""
def __init__(self):
""" Initializes the Data Class. """
self.Helpers = Helpers("DataProcessor")
self.confs = self.Helpers.confs
self.Helpers.logger.info("Data helper class initialization complete.")
def getLabelsAndDirectories(self):
""" Returns a list of classes/labels and directories. """
labels = [name for name in os.listdir(self.confs["Classifier"]["DatasetDir"]) if os.path.isdir(
os.path.join(self.confs["Classifier"]["DatasetDir"], name)) and name != '.ipynb_checkpoints']
directories = []
for dirName in os.listdir(self.confs["Classifier"]["DatasetDir"]):
if dirName != '.ipynb_checkpoints':
path = os.path.join(
self.confs["Classifier"]["DatasetDir"], dirName)
if os.path.isdir(path):
directories.append(path)
return labels, directories
def processFilesAndClasses(self):
""" Returns a list of filenames and classes/labels. """
labels, directories = self.getLabelsAndDirectories()
data = []
for directory in directories:
for filename in os.listdir(directory):
if filename.endswith('.jpg') or filename.endswith('.jpeg') or filename.endswith('.png') or filename.endswith('.gif'):
data.append(os.path.join(directory, filename))
else:
continue
return data, sorted(labels)
def writeLabels(self, labels_to_labels):
"""
Writes a file with the list of class names.
Args:
labels_to_labels: A map of (integer) labels to class names.
filename: The filename where the class names are written.
"""
labelsFile = os.path.join(
self.confs["Classifier"]["DatasetDir"], self.confs["Classifier"]["Labels"])
classesFile = os.path.join(
self.confs["Classifier"]["DatasetDir"], self.confs["Classifier"]["Classes"])
with tf.gfile.Open(classesFile, 'w') as f:
for label in labels_to_labels:
f.write('%s\n' % (label))
with tf.gfile.Open(labelsFile, 'w') as f:
for label in labels_to_labels:
class_name = labels_to_labels[label]
f.write('%d:%s\n' % (label, class_name))
def convertToTFRecord(self, split_name, filenames, labels_to_ids):
""" Converts the given filenames to a TFRecord dataset. """
assert split_name in ['train', 'validation']
num_per_shard = int(
math.ceil(len(filenames) / float(self.confs["Classifier"]["Shards"])))
self.Helpers.logger.info("Files: " + str(len(filenames)))
self.Helpers.logger.info("Files per shard: " + str(num_per_shard))
with tf.Graph().as_default():
image_reader = ImageReader()
with tf.Session('') as sess:
for shard_id in range(self.confs["Classifier"]["Shards"]):
output_filename = self.getDatasetFilename(
split_name, shard_id)
self.Helpers.logger.info(
"Saving shard: " + output_filename)
with tf.python_io.TFRecordWriter(output_filename) as tfrecord_writer:
start_ndx = shard_id * num_per_shard
end_ndx = min(
(shard_id+1) * num_per_shard, len(filenames))
for i in range(start_ndx, end_ndx):
sys.stdout.write('\r>> Converting image %d/%d shard %d' % (
i+1, len(filenames), shard_id))
sys.stdout.flush()
image_data = tf.gfile.FastGFile(
filenames[i], 'rb').read()
height, width = image_reader.read_image_dims(
sess, image_data)
class_name = os.path.basename(
os.path.dirname(filenames[i]))
class_id = labels_to_ids[class_name]
example = self.imageToTFExample(
image_data, b'jpg', height, width, class_id)
tfrecord_writer.write(example.SerializeToString())
sys.stdout.write('\n')
sys.stdout.flush()
def getDatasetFilename(self, split_name, shard_id):
""" Gets the model TFRecordFile. """
output_filename = '%s_%s_%05d-of-%05d.tfrecord' % (
self.confs["Classifier"]["TFRecordFile"], split_name, shard_id, self.confs["Classifier"]["Shards"])
return os.path.join(self.confs["Classifier"]["DatasetDir"], output_filename)
def int64Feature(self, values):
"""
Returns a TF-Feature of int64s.
Args:
values: A scalar or list of values.
Returns:
a TF-Feature.
"""
if not isinstance(values, (tuple, list)):
values = [values]
return tf.train.Feature(int64_list=tf.train.Int64List(value=values))
def bytesFeature(self, values):
"""
Returns a TF-Feature of bytes.
Args:
values: A string.
Returns:
a TF-Feature.
"""
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[values]))
def cropTestDataset(self):
""" Crops the testing dataset. """
data_dir = pathlib.Path(
self.confs["Classifier"]["TestImagePath"])
data = list(data_dir.glob('*.jpg'))
for ipath in data:
fpath = str(ipath)
image = Image.open(fpath)
image = image.resize((600, 600))
image.save(fpath)
self.Helpers.logger.info("Test data resized.")
class ImageReader(object):
""" ImageReader Helper Class
Provides TensorFlow image coding utilities
"""
def __init__(self):
""" Initializes ImageReader Class """
self._decode_jpeg_data = tf.placeholder(dtype=tf.string)
self._decode_jpeg = tf.image.decode_image(
self._decode_jpeg_data, channels=3)
def read_image_dims(self, sess, image_data):
""" Gets the dimensions of image_data """
image = self.decode_jpeg(sess, image_data)
return image.shape[0], image.shape[1]
def decode_jpeg(self, sess, image_data):
""" Decodes image_data (jpeg)"""
image = sess.run(self._decode_jpeg, feed_dict={
self._decode_jpeg_data: image_data})
assert len(image.shape) == 3
assert image.shape[2] == 3
return image
| [
29113,
29113,
14468,
7804,
4242,
198,
2,
198,
2,
4935,
25,
220,
220,
220,
220,
220,
220,
5613,
19935,
4013,
1133,
2011,
417,
1868,
1222,
406,
20896,
45292,
3477,
1004,
43505,
9552,
4992,
4935,
198,
2,
1432,
13264,
25,
220,
220,
220,
11096,
46254,
4482,
13130,
198,
2,
4935,
25,
220,
220,
220,
220,
220,
220,
13585,
498,
48191,
9652,
198,
2,
198,
2,
6434,
25,
220,
220,
220,
220,
220,
220,
220,
7244,
30979,
12,
33,
668,
263,
357,
23159,
44,
9044,
33,
668,
263,
13,
785,
8,
198,
2,
25767,
669,
25,
198,
2,
11851,
25,
220,
220,
220,
220,
220,
220,
220,
220,
6060,
5016,
198,
2,
12489,
25,
220,
220,
6060,
1398,
329,
262,
11096,
46254,
4482,
13130,
399,
7902,
16,
5016,
7483,
13,
198,
2,
13789,
25,
220,
220,
220,
220,
220,
220,
17168,
13789,
198,
2,
4586,
40499,
25,
12131,
12,
2998,
12,
1433,
198,
2,
198,
29113,
29113,
14468,
7804,
4242,
198,
198,
11748,
269,
85,
17,
11,
15095,
11,
33918,
11,
10688,
11,
28686,
11,
3108,
8019,
11,
4738,
11,
25064,
11,
640,
220,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
6738,
350,
4146,
1330,
7412,
198,
6738,
25064,
1330,
1822,
85,
198,
198,
6738,
38884,
13,
12621,
19276,
1330,
10478,
364,
628,
198,
4871,
6060,
33529,
198,
220,
220,
220,
37227,
6060,
5053,
525,
5016,
628,
220,
220,
220,
7231,
1366,
4542,
1398,
329,
262,
11096,
46254,
4482,
13130,
399,
7902,
16,
5016,
7483,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
20768,
4340,
262,
6060,
5016,
13,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
796,
10478,
364,
7203,
6601,
18709,
273,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
796,
2116,
13,
12621,
19276,
13,
1102,
9501,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
13,
6404,
1362,
13,
10951,
7203,
6601,
31904,
1398,
37588,
1844,
19570,
628,
220,
220,
220,
825,
651,
17822,
1424,
1870,
13470,
1749,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16409,
257,
1351,
286,
6097,
14,
23912,
1424,
290,
29196,
13,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
14722,
796,
685,
3672,
329,
1438,
287,
28686,
13,
4868,
15908,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
8973,
8,
611,
28686,
13,
6978,
13,
9409,
343,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
33116,
1438,
4008,
290,
1438,
14512,
45302,
541,
2047,
65,
62,
9122,
13033,
20520,
628,
220,
220,
220,
220,
220,
220,
220,
29196,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
26672,
5376,
287,
28686,
13,
4868,
15908,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
8973,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
26672,
5376,
14512,
45302,
541,
2047,
65,
62,
9122,
13033,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
33116,
26672,
5376,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
28686,
13,
6978,
13,
9409,
343,
7,
6978,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29196,
13,
33295,
7,
6978,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
14722,
11,
29196,
628,
220,
220,
220,
825,
1429,
25876,
1870,
9487,
274,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16409,
257,
1351,
286,
1226,
268,
1047,
290,
6097,
14,
23912,
1424,
13,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
14722,
11,
29196,
796,
2116,
13,
1136,
17822,
1424,
1870,
13470,
1749,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1366,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
8619,
287,
29196,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
29472,
287,
28686,
13,
4868,
15908,
7,
34945,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
29472,
13,
437,
2032,
342,
7,
4458,
9479,
11537,
393,
29472,
13,
437,
2032,
342,
7,
4458,
73,
22071,
11537,
393,
29472,
13,
437,
2032,
342,
7,
4458,
11134,
11537,
393,
29472,
13,
437,
2032,
342,
7,
4458,
27908,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
13,
33295,
7,
418,
13,
6978,
13,
22179,
7,
34945,
11,
29472,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1366,
11,
23243,
7,
23912,
1424,
8,
628,
220,
220,
220,
825,
3551,
17822,
1424,
7,
944,
11,
14722,
62,
1462,
62,
23912,
1424,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
12257,
274,
257,
2393,
351,
262,
1351,
286,
1398,
3891,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14722,
62,
1462,
62,
23912,
1424,
25,
317,
3975,
286,
357,
41433,
8,
14722,
284,
1398,
3891,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29472,
25,
383,
29472,
810,
262,
1398,
3891,
389,
3194,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
14722,
8979,
796,
28686,
13,
6978,
13,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
33116,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
17822,
1424,
8973,
8,
628,
220,
220,
220,
220,
220,
220,
220,
6097,
8979,
796,
28686,
13,
6978,
13,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
33116,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
9487,
274,
8973,
8,
628,
220,
220,
220,
220,
220,
220,
220,
351,
48700,
13,
70,
7753,
13,
11505,
7,
37724,
8979,
11,
705,
86,
11537,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
6167,
287,
14722,
62,
1462,
62,
23912,
1424,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
13,
13564,
10786,
4,
82,
59,
77,
6,
4064,
357,
18242,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
351,
48700,
13,
70,
7753,
13,
11505,
7,
23912,
1424,
8979,
11,
705,
86,
11537,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
6167,
287,
14722,
62,
1462,
62,
23912,
1424,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
62,
3672,
796,
14722,
62,
1462,
62,
23912,
1424,
58,
18242,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
13,
13564,
10786,
4,
67,
25,
4,
82,
59,
77,
6,
4064,
357,
18242,
11,
1398,
62,
3672,
4008,
628,
220,
220,
220,
825,
10385,
2514,
10234,
23739,
7,
944,
11,
6626,
62,
3672,
11,
1226,
268,
1047,
11,
14722,
62,
1462,
62,
2340,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
1482,
24040,
262,
1813,
1226,
268,
1047,
284,
257,
24958,
23739,
27039,
13,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
6818,
6626,
62,
3672,
287,
37250,
27432,
3256,
705,
12102,
341,
20520,
628,
220,
220,
220,
220,
220,
220,
220,
997,
62,
525,
62,
1477,
446,
796,
493,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10688,
13,
344,
346,
7,
11925,
7,
10379,
268,
1047,
8,
1220,
12178,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
2484,
1371,
8973,
22305,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
13,
6404,
1362,
13,
10951,
7203,
25876,
25,
366,
1343,
965,
7,
11925,
7,
10379,
268,
1047,
22305,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
13,
6404,
1362,
13,
10951,
7203,
25876,
583,
427,
446,
25,
366,
1343,
965,
7,
22510,
62,
525,
62,
1477,
446,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
351,
48700,
13,
37065,
22446,
292,
62,
12286,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
62,
46862,
796,
7412,
33634,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
351,
48700,
13,
36044,
7,
7061,
8,
355,
264,
408,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
427,
446,
62,
312,
287,
2837,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
2484,
1371,
8973,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
62,
34345,
796,
2116,
13,
1136,
27354,
292,
316,
35063,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6626,
62,
3672,
11,
427,
446,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
13,
6404,
1362,
13,
10951,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
50,
2703,
427,
446,
25,
366,
1343,
5072,
62,
34345,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
351,
48700,
13,
29412,
62,
952,
13,
10234,
23739,
34379,
7,
22915,
62,
34345,
8,
355,
48700,
22105,
62,
16002,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
923,
62,
358,
87,
796,
427,
446,
62,
312,
1635,
997,
62,
525,
62,
1477,
446,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
886,
62,
358,
87,
796,
949,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
1477,
446,
62,
312,
10,
16,
8,
1635,
997,
62,
525,
62,
1477,
446,
11,
18896,
7,
10379,
268,
1047,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
9688,
62,
358,
87,
11,
886,
62,
358,
87,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
13564,
10786,
59,
81,
4211,
35602,
889,
2939,
4064,
67,
14,
4,
67,
427,
446,
4064,
67,
6,
4064,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1312,
10,
16,
11,
18896,
7,
10379,
268,
1047,
828,
427,
446,
62,
312,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
62,
7890,
796,
48700,
13,
70,
7753,
13,
22968,
38,
8979,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1226,
268,
1047,
58,
72,
4357,
705,
26145,
27691,
961,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6001,
11,
9647,
796,
2939,
62,
46862,
13,
961,
62,
9060,
62,
67,
12078,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
408,
11,
2939,
62,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
62,
3672,
796,
28686,
13,
6978,
13,
12093,
12453,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
15908,
3672,
7,
10379,
268,
1047,
58,
72,
60,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
62,
312,
796,
14722,
62,
1462,
62,
2340,
58,
4871,
62,
3672,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1672,
796,
2116,
13,
9060,
2514,
10234,
16281,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
62,
7890,
11,
275,
6,
9479,
3256,
6001,
11,
9647,
11,
1398,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48700,
22105,
62,
16002,
13,
13564,
7,
20688,
13,
32634,
1096,
2514,
10100,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
13564,
10786,
59,
77,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
628,
220,
220,
220,
825,
651,
27354,
292,
316,
35063,
7,
944,
11,
6626,
62,
3672,
11,
427,
446,
62,
312,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
29620,
262,
2746,
24958,
23739,
8979,
13,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
62,
34345,
796,
705,
4,
82,
62,
4,
82,
62,
4,
2713,
67,
12,
1659,
12,
4,
2713,
67,
13,
27110,
22105,
6,
4064,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
10234,
23739,
8979,
33116,
6626,
62,
3672,
11,
427,
446,
62,
312,
11,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
2484,
1371,
8973,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
28686,
13,
6978,
13,
22179,
7,
944,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
27354,
292,
316,
35277,
33116,
5072,
62,
34345,
8,
628,
220,
220,
220,
825,
493,
2414,
38816,
7,
944,
11,
3815,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
257,
24958,
12,
38816,
286,
493,
2414,
82,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
25,
317,
16578,
283,
393,
1351,
286,
3815,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
24958,
12,
38816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
318,
39098,
7,
27160,
11,
357,
83,
29291,
11,
1351,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
685,
27160,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
48700,
13,
27432,
13,
38816,
7,
600,
2414,
62,
4868,
28,
27110,
13,
27432,
13,
5317,
2414,
8053,
7,
8367,
28,
27160,
4008,
628,
220,
220,
220,
825,
9881,
38816,
7,
944,
11,
3815,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
257,
24958,
12,
38816,
286,
9881,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
25,
317,
4731,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
24958,
12,
38816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
48700,
13,
27432,
13,
38816,
7,
33661,
62,
4868,
28,
27110,
13,
27432,
13,
45992,
8053,
7,
8367,
41888,
27160,
60,
4008,
628,
220,
220,
220,
825,
13833,
14402,
27354,
292,
316,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
9325,
862,
262,
4856,
27039,
13,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
15908,
796,
3108,
8019,
13,
15235,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
9501,
14692,
9487,
7483,
1,
7131,
1,
14402,
5159,
15235,
8973,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
796,
1351,
7,
7890,
62,
15908,
13,
4743,
672,
10786,
24620,
9479,
6,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
329,
20966,
776,
287,
1366,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
6978,
796,
965,
7,
541,
776,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
796,
7412,
13,
9654,
7,
69,
6978,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
796,
2939,
13,
411,
1096,
19510,
8054,
11,
10053,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
13,
21928,
7,
69,
6978,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12621,
19276,
13,
6404,
1362,
13,
10951,
7203,
14402,
1366,
581,
1143,
19570,
628,
198,
4871,
7412,
33634,
7,
15252,
2599,
198,
220,
220,
220,
37227,
7412,
33634,
5053,
525,
5016,
628,
220,
220,
220,
47081,
309,
22854,
37535,
2939,
19617,
20081,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
20768,
4340,
7412,
33634,
5016,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
12501,
1098,
62,
73,
22071,
62,
7890,
796,
48700,
13,
5372,
13829,
7,
67,
4906,
28,
27110,
13,
8841,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
12501,
1098,
62,
73,
22071,
796,
48700,
13,
9060,
13,
12501,
1098,
62,
9060,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
12501,
1098,
62,
73,
22071,
62,
7890,
11,
9619,
28,
18,
8,
628,
220,
220,
220,
825,
1100,
62,
9060,
62,
67,
12078,
7,
944,
11,
264,
408,
11,
2939,
62,
7890,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
29620,
262,
15225,
286,
2939,
62,
7890,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2939,
796,
2116,
13,
12501,
1098,
62,
73,
22071,
7,
82,
408,
11,
2939,
62,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2939,
13,
43358,
58,
15,
4357,
2939,
13,
43358,
58,
16,
60,
628,
220,
220,
220,
825,
36899,
62,
73,
22071,
7,
944,
11,
264,
408,
11,
2939,
62,
7890,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
4280,
4147,
2939,
62,
7890,
357,
73,
22071,
8,
37811,
628,
220,
220,
220,
220,
220,
220,
220,
2939,
796,
264,
408,
13,
5143,
7,
944,
13557,
12501,
1098,
62,
73,
22071,
11,
3745,
62,
11600,
34758,
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,
2116,
13557,
12501,
1098,
62,
73,
22071,
62,
7890,
25,
2939,
62,
7890,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
18896,
7,
9060,
13,
43358,
8,
6624,
513,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2939,
13,
43358,
58,
17,
60,
6624,
513,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2939,
198
] | 2.115942 | 3,657 |
# File content is auto-generated. Do not modify.
# pylint: skip-file
from ._internal import NDArrayBase
from ..base import _Null
def ElementWiseSum(*args, **kwargs):
r"""Adds all input arguments element-wise.
.. math::
add\_n(a_1, a_2, ..., a_n) = a_1 + a_2 + ... + a_n
``add_n`` is potentially more efficient than calling ``add`` by `n` times.
The storage type of ``add_n`` output depends on storage types of inputs
- add_n(row_sparse, row_sparse, ..) = row_sparse
- otherwise, ``add_n`` generates output with default storage
Defined in src/operator/tensor/elemwise_sum.cc:L123
Parameters
----------
args : NDArray[]
Positional input arguments
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def abs(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise absolute value of the input.
Example::
abs([-2, 0, 3]) = [2, 0, 3]
The storage type of ``abs`` output depends upon the input storage type:
- abs(default) = default
- abs(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L385
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def adam_update(weight=None, grad=None, mean=None, var=None, lr=_Null, beta1=_Null, beta2=_Null, epsilon=_Null, wd=_Null, rescale_grad=_Null, clip_gradient=_Null, out=None, name=None, **kwargs):
r"""Update function for Adam optimizer. Adam is seen as a generalization
of AdaGrad.
Adam update consists of the following steps, where g represents gradient and m, v
are 1st and 2nd order moment estimates (mean and variance).
.. math::
g_t = \nabla J(W_{t-1})\\
m_t = \beta_1 m_{t-1} + (1 - \beta_1) g_t\\
v_t = \beta_2 v_{t-1} + (1 - \beta_2) g_t^2\\
W_t = W_{t-1} - \alpha \frac{ m_t }{ \sqrt{ v_t } + \epsilon }
It updates the weights using::
m = beta1*m + (1-beta1)*grad
v = beta2*v + (1-beta2)*(grad**2)
w += - learning_rate * m / (sqrt(v) + epsilon)
If w, m and v are all of ``row_sparse`` storage type,
only the row slices whose indices appear in grad.indices are updated (for w, m and v)::
for row in grad.indices:
m[row] = beta1*m[row] + (1-beta1)*grad[row]
v[row] = beta2*v[row] + (1-beta2)*(grad[row]**2)
w[row] += - learning_rate * m[row] / (sqrt(v[row]) + epsilon)
Defined in src/operator/optimizer_op.cc:L383
Parameters
----------
weight : NDArray
Weight
grad : NDArray
Gradient
mean : NDArray
Moving mean
var : NDArray
Moving variance
lr : float, required
Learning rate
beta1 : float, optional, default=0.9
The decay rate for the 1st moment estimates.
beta2 : float, optional, default=0.999
The decay rate for the 2nd moment estimates.
epsilon : float, optional, default=1e-08
A small constant for numerical stability.
wd : float, optional, default=0
Weight decay augments the objective function with a regularization term that penalizes large weights. The penalty scales with the square of the magnitude of each weight.
rescale_grad : float, optional, default=1
Rescale gradient to grad = rescale_grad*grad.
clip_gradient : float, optional, default=-1
Clip gradient to the range of [-clip_gradient, clip_gradient] If clip_gradient <= 0, gradient clipping is turned off. grad = max(min(grad, clip_gradient), -clip_gradient).
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def add_n(*args, **kwargs):
r"""Adds all input arguments element-wise.
.. math::
add\_n(a_1, a_2, ..., a_n) = a_1 + a_2 + ... + a_n
``add_n`` is potentially more efficient than calling ``add`` by `n` times.
The storage type of ``add_n`` output depends on storage types of inputs
- add_n(row_sparse, row_sparse, ..) = row_sparse
- otherwise, ``add_n`` generates output with default storage
Defined in src/operator/tensor/elemwise_sum.cc:L123
Parameters
----------
args : NDArray[]
Positional input arguments
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arccos(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise inverse cosine of the input array.
The input should be in range `[-1, 1]`.
The output is in the closed interval :math:`[0, \pi]`
.. math::
arccos([-1, -.707, 0, .707, 1]) = [\pi, 3\pi/4, \pi/2, \pi/4, 0]
The storage type of ``arccos`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L123
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arccosh(data=None, out=None, name=None, **kwargs):
r"""Returns the element-wise inverse hyperbolic cosine of the input array, \
computed element-wise.
The storage type of ``arccosh`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L264
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arcsin(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise inverse sine of the input array.
The input should be in the range `[-1, 1]`.
The output is in the closed interval of [:math:`-\pi/2`, :math:`\pi/2`].
.. math::
arcsin([-1, -.707, 0, .707, 1]) = [-\pi/2, -\pi/4, 0, \pi/4, \pi/2]
The storage type of ``arcsin`` output depends upon the input storage type:
- arcsin(default) = default
- arcsin(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L104
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arcsinh(data=None, out=None, name=None, **kwargs):
r"""Returns the element-wise inverse hyperbolic sine of the input array, \
computed element-wise.
The storage type of ``arcsinh`` output depends upon the input storage type:
- arcsinh(default) = default
- arcsinh(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L250
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arctan(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise inverse tangent of the input array.
The output is in the closed interval :math:`[-\pi/2, \pi/2]`
.. math::
arctan([-1, 0, 1]) = [-\pi/4, 0, \pi/4]
The storage type of ``arctan`` output depends upon the input storage type:
- arctan(default) = default
- arctan(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L144
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def arctanh(data=None, out=None, name=None, **kwargs):
r"""Returns the element-wise inverse hyperbolic tangent of the input array, \
computed element-wise.
The storage type of ``arctanh`` output depends upon the input storage type:
- arctanh(default) = default
- arctanh(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L281
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def cast_storage(data=None, stype=_Null, out=None, name=None, **kwargs):
r"""Casts tensor storage type to the new type.
When an NDArray with default storage type is cast to csr or row_sparse storage,
the result is compact, which means:
- for csr, zero values will not be retained
- for row_sparse, row slices of all zeros will not be retained
The storage type of ``cast_storage`` output depends on stype parameter:
- cast_storage(csr, 'default') = default
- cast_storage(row_sparse, 'default') = default
- cast_storage(default, 'csr') = csr
- cast_storage(default, 'row_sparse') = row_sparse
Example::
dense = [[ 0., 1., 0.],
[ 2., 0., 3.],
[ 0., 0., 0.],
[ 0., 0., 0.]]
# cast to row_sparse storage type
rsp = cast_storage(dense, 'row_sparse')
rsp.indices = [0, 1]
rsp.values = [[ 0., 1., 0.],
[ 2., 0., 3.]]
# cast to csr storage type
csr = cast_storage(dense, 'csr')
csr.indices = [1, 0, 2]
csr.values = [ 1., 2., 3.]
csr.indptr = [0, 1, 3, 3, 3]
Defined in src/operator/tensor/cast_storage.cc:L69
Parameters
----------
data : NDArray
The input.
stype : {'csr', 'default', 'row_sparse'}, required
Output storage type.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def ceil(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise ceiling of the input.
The ceil of the scalar x is the smallest integer i, such that i >= x.
Example::
ceil([-2.1, -1.9, 1.5, 1.9, 2.1]) = [-2., -1., 2., 2., 3.]
The storage type of ``ceil`` output depends upon the input storage type:
- ceil(default) = default
- ceil(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L463
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def clip(data=None, a_min=_Null, a_max=_Null, out=None, name=None, **kwargs):
r"""Clips (limits) the values in an array.
Given an interval, values outside the interval are clipped to the interval edges.
Clipping ``x`` between `a_min` and `a_x` would be::
clip(x, a_min, a_max) = max(min(x, a_max), a_min))
Example::
x = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
clip(x,1,8) = [ 1., 1., 2., 3., 4., 5., 6., 7., 8., 8.]
The storage type of ``clip`` output depends on storage types of inputs and the a_min, a_max \
parameter values:
- clip(default) = default
- clip(row_sparse, a_min <= 0, a_max >= 0) = row_sparse
- clip(csr, a_min <= 0, a_max >= 0) = csr
- clip(row_sparse, a_min < 0, a_max < 0) = default
- clip(row_sparse, a_min > 0, a_max > 0) = default
- clip(csr, a_min < 0, a_max < 0) = csr
- clip(csr, a_min > 0, a_max > 0) = csr
Defined in src/operator/tensor/matrix_op.cc:L486
Parameters
----------
data : NDArray
Input array.
a_min : float, required
Minimum value
a_max : float, required
Maximum value
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def cos(data=None, out=None, name=None, **kwargs):
r"""Computes the element-wise cosine of the input array.
The input should be in radians (:math:`2\pi` rad equals 360 degrees).
.. math::
cos([0, \pi/4, \pi/2]) = [1, 0.707, 0]
The storage type of ``cos`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L63
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def cosh(data=None, out=None, name=None, **kwargs):
r"""Returns the hyperbolic cosine of the input array, computed element-wise.
.. math::
cosh(x) = 0.5\times(exp(x) + exp(-x))
The storage type of ``cosh`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L216
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def degrees(data=None, out=None, name=None, **kwargs):
r"""Converts each element of the input array from radians to degrees.
.. math::
degrees([0, \pi/2, \pi, 3\pi/2, 2\pi]) = [0, 90, 180, 270, 360]
The storage type of ``degrees`` output depends upon the input storage type:
- degrees(default) = default
- degrees(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L163
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def dot(lhs=None, rhs=None, transpose_a=_Null, transpose_b=_Null, out=None, name=None, **kwargs):
r"""Dot product of two arrays.
``dot``'s behavior depends on the input array dimensions:
- 1-D arrays: inner product of vectors
- 2-D arrays: matrix multiplication
- N-D arrays: a sum product over the last axis of the first input and the first
axis of the second input
For example, given 3-D ``x`` with shape `(n,m,k)` and ``y`` with shape `(k,r,s)`, the
result array will have shape `(n,m,r,s)`. It is computed by::
dot(x,y)[i,j,a,b] = sum(x[i,j,:]*y[:,a,b])
Example::
x = reshape([0,1,2,3,4,5,6,7], shape=(2,2,2))
y = reshape([7,6,5,4,3,2,1,0], shape=(2,2,2))
dot(x,y)[0,0,1,1] = 0
sum(x[0,0,:]*y[:,1,1]) = 0
The storage type of ``dot`` output depends on storage types of inputs and transpose options:
- dot(csr, default) = default
- dot(csr.T, default) = row_sparse
- dot(csr, row_sparse) = default
- dot(default, csr) = csr
- otherwise, ``dot`` generates output with default storage
Defined in src/operator/tensor/dot.cc:L62
Parameters
----------
lhs : NDArray
The first input
rhs : NDArray
The second input
transpose_a : boolean, optional, default=0
If true then transpose the first input before dot.
transpose_b : boolean, optional, default=0
If true then transpose the second input before dot.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def elemwise_add(lhs=None, rhs=None, out=None, name=None, **kwargs):
r"""Adds arguments element-wise.
The storage type of ``elemwise_add`` output depends on storage types of inputs
- elemwise_add(row_sparse, row_sparse) = row_sparse
- elemwise_add(csr, csr) = csr
- otherwise, ``elemwise_add`` generates output with default storage
Parameters
----------
lhs : NDArray
first input
rhs : NDArray
second input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def elemwise_div(lhs=None, rhs=None, out=None, name=None, **kwargs):
r"""Divides arguments element-wise.
The storage type of ``elemwise_div`` output is always dense
Parameters
----------
lhs : NDArray
first input
rhs : NDArray
second input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def elemwise_mul(lhs=None, rhs=None, out=None, name=None, **kwargs):
r"""Multiplies arguments element-wise.
The storage type of ``elemwise_mul`` output depends on storage types of inputs
- elemwise_mul(default, default) = default
- elemwise_mul(row_sparse, row_sparse) = row_sparse
- elemwise_mul(default, row_sparse) = default
- elemwise_mul(row_sparse, default) = default
- elemwise_mul(csr, csr) = csr
- otherwise, ``elemwise_mul`` generates output with default storage
Parameters
----------
lhs : NDArray
first input
rhs : NDArray
second input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def elemwise_sub(lhs=None, rhs=None, out=None, name=None, **kwargs):
r"""Subtracts arguments element-wise.
The storage type of ``elemwise_sub`` output depends on storage types of inputs
- elemwise_sub(row_sparse, row_sparse) = row_sparse
- elemwise_sub(csr, csr) = csr
- otherwise, ``elemwise_sub`` generates output with default storage
Parameters
----------
lhs : NDArray
first input
rhs : NDArray
second input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def exp(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise exponential value of the input.
.. math::
exp(x) = e^x \approx 2.718^x
Example::
exp([0, 1, 2]) = [1., 2.71828175, 7.38905621]
The storage type of ``exp`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L641
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def expm1(data=None, out=None, name=None, **kwargs):
r"""Returns ``exp(x) - 1`` computed element-wise on the input.
This function provides greater precision than ``exp(x) - 1`` for small values of ``x``.
The storage type of ``expm1`` output depends upon the input storage type:
- expm1(default) = default
- expm1(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L720
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def fix(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise rounded value to the nearest \
integer towards zero of the input.
Example::
fix([-2.1, -1.9, 1.9, 2.1]) = [-2., -1., 1., 2.]
The storage type of ``fix`` output depends upon the input storage type:
- fix(default) = default
- fix(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L520
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def floor(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise floor of the input.
The floor of the scalar x is the largest integer i, such that i <= x.
Example::
floor([-2.1, -1.9, 1.5, 1.9, 2.1]) = [-3., -2., 1., 1., 2.]
The storage type of ``floor`` output depends upon the input storage type:
- floor(default) = default
- floor(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L482
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def ftrl_update(weight=None, grad=None, z=None, n=None, lr=_Null, lamda1=_Null, beta=_Null, wd=_Null, rescale_grad=_Null, clip_gradient=_Null, out=None, name=None, **kwargs):
r"""Update function for Ftrl optimizer.
Referenced from *Ad Click Prediction: a View from the Trenches*, available at
http://dl.acm.org/citation.cfm?id=2488200.
It updates the weights using::
rescaled_grad = clip(grad * rescale_grad, clip_gradient)
z += rescaled_grad - (sqrt(n + rescaled_grad**2) - sqrt(n)) * weight / learning_rate
n += rescaled_grad**2
w = (sign(z) * lamda1 - z) / ((beta + sqrt(n)) / learning_rate + wd) * (abs(z) > lamda1)
If w, z and n are all of ``row_sparse`` storage type,
only the row slices whose indices appear in grad.indices are updated (for w, z and n)::
for row in grad.indices:
rescaled_grad[row] = clip(grad[row] * rescale_grad, clip_gradient)
z[row] += rescaled_grad[row] - (sqrt(n[row] + rescaled_grad[row]**2) - sqrt(n[row])) * weight[row] / learning_rate
n[row] += rescaled_grad[row]**2
w[row] = (sign(z[row]) * lamda1 - z[row]) / ((beta + sqrt(n[row])) / learning_rate + wd) * (abs(z[row]) > lamda1)
Defined in src/operator/optimizer_op.cc:L520
Parameters
----------
weight : NDArray
Weight
grad : NDArray
Gradient
z : NDArray
z
n : NDArray
Square of grad
lr : float, required
Learning rate
lamda1 : float, optional, default=0.01
The L1 regularization coefficient.
beta : float, optional, default=1
Per-Coordinate Learning Rate beta.
wd : float, optional, default=0
Weight decay augments the objective function with a regularization term that penalizes large weights. The penalty scales with the square of the magnitude of each weight.
rescale_grad : float, optional, default=1
Rescale gradient to grad = rescale_grad*grad.
clip_gradient : float, optional, default=-1
Clip gradient to the range of [-clip_gradient, clip_gradient] If clip_gradient <= 0, gradient clipping is turned off. grad = max(min(grad, clip_gradient), -clip_gradient).
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def gamma(data=None, out=None, name=None, **kwargs):
r"""Returns the gamma function (extension of the factorial function \
to the reals), computed element-wise on the input array.
The storage type of ``gamma`` output is always dense
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def gammaln(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise log of the absolute value of the gamma function \
of the input.
The storage type of ``gammaln`` output is always dense
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def log(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise Natural logarithmic value of the input.
The natural logarithm is logarithm in base *e*, so that ``log(exp(x)) = x``
The storage type of ``log`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L653
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def log10(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise Base-10 logarithmic value of the input.
``10**log10(x) = x``
The storage type of ``log10`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L665
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def log1p(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise ``log(1 + x)`` value of the input.
This function is more accurate than ``log(1 + x)`` for small ``x`` so that
:math:`1+x\approx 1`
The storage type of ``log1p`` output depends upon the input storage type:
- log1p(default) = default
- log1p(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L702
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def log2(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise Base-2 logarithmic value of the input.
``2**log2(x) = x``
The storage type of ``log2`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L677
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def make_loss(data=None, out=None, name=None, **kwargs):
r"""Make your own loss function in network construction.
This operator accepts a customized loss function symbol as a terminal loss and
the symbol should be an operator with no backward dependency.
The output of this function is the gradient of loss with respect to the input data.
For example, if you are a making a cross entropy loss function. Assume ``out`` is the
predicted output and ``label`` is the true label, then the cross entropy can be defined as::
cross_entropy = label * log(out) + (1 - label) * log(1 - out)
loss = make_loss(cross_entropy)
We will need to use ``make_loss`` when we are creating our own loss function or we want to
combine multiple loss functions. Also we may want to stop some variables' gradients
from backpropagation. See more detail in ``BlockGrad`` or ``stop_gradient``.
The storage type of ``make_loss`` output depends upon the input storage type:
- make_loss(default) = default
- make_loss(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L199
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def mean(data=None, axis=_Null, keepdims=_Null, exclude=_Null, out=None, name=None, **kwargs):
r"""Computes the mean of array elements over given axes.
Defined in src/operator/tensor/broadcast_reduce_op_value.cc:L101
Parameters
----------
data : NDArray
The input
axis : Shape(tuple), optional, default=[]
The axis or axes along which to perform the reduction.
The default, `axis=()`, will compute over all elements into a
scalar array with shape `(1,)`.
If `axis` is int, a reduction is performed on a particular axis.
If `axis` is a tuple of ints, a reduction is performed on all the axes
specified in the tuple.
If `exclude` is true, reduction will be performed on the axes that are
NOT in axis instead.
Negative values means indexing from right to left.
keepdims : boolean, optional, default=0
If this is set to `True`, the reduced axes are left in the result as dimension with size one.
exclude : boolean, optional, default=0
Whether to perform reduction on axis that are NOT in axis instead.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def negative(data=None, out=None, name=None, **kwargs):
r"""Numerical negative of the argument, element-wise.
The storage type of ``negative`` output depends upon the input storage type:
- negative(default) = default
- negative(row_sparse) = row_sparse
- negative(csr) = csr
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def norm(data=None, out=None, name=None, **kwargs):
r"""Flattens the input array and then computes the l2 norm.
Examples::
x = [[1, 2],
[3, 4]]
norm(x) = [5.47722578]
rsp = x.cast_storage('row_sparse')
norm(rsp) = [5.47722578]
csr = x.cast_storage('csr')
norm(csr) = [5.47722578]
Defined in src/operator/tensor/broadcast_reduce_op_value.cc:L266
Parameters
----------
data : NDArray
Source input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def radians(data=None, out=None, name=None, **kwargs):
r"""Converts each element of the input array from degrees to radians.
.. math::
radians([0, 90, 180, 270, 360]) = [0, \pi/2, \pi, 3\pi/2, 2\pi]
The storage type of ``radians`` output depends upon the input storage type:
- radians(default) = default
- radians(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L182
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def relu(data=None, out=None, name=None, **kwargs):
r"""Computes rectified linear.
.. math::
max(features, 0)
The storage type of ``relu`` output depends upon the input storage type:
- relu(default) = default
- relu(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L83
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def retain(data=None, indices=None, out=None, name=None, **kwargs):
r"""pick rows specified by user input index array from a row sparse matrix
and save them in the output sparse matrix.
Example::
data = [[1, 2], [3, 4], [5, 6]]
indices = [0, 1, 3]
shape = (4, 2)
rsp_in = row_sparse(data, indices)
to_retain = [0, 3]
rsp_out = retain(rsp_in, to_retain)
rsp_out.values = [[1, 2], [5, 6]]
rsp_out.indices = [0, 3]
The storage type of ``retain`` output depends on storage types of inputs
- retain(row_sparse, default) = row_sparse
- otherwise, ``retain`` is not supported
Defined in src/operator/tensor/sparse_retain.cc:L53
Parameters
----------
data : NDArray
The input array for sparse_retain operator.
indices : NDArray
The index array of rows ids that will be retained.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def rint(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise rounded value to the nearest integer of the input.
.. note::
- For input ``n.5`` ``rint`` returns ``n`` while ``round`` returns ``n+1``.
- For input ``-n.5`` both ``rint`` and ``round`` returns ``-n-1``.
Example::
rint([-1.5, 1.5, -1.9, 1.9, 2.1]) = [-2., 1., -2., 2., 2.]
The storage type of ``rint`` output depends upon the input storage type:
- rint(default) = default
- rint(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L444
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def round(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise rounded value to the nearest integer of the input.
Example::
round([-1.5, 1.5, -1.9, 1.9, 2.1]) = [-2., 2., -2., 2., 2.]
The storage type of ``round`` output depends upon the input storage type:
- round(default) = default
- round(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L423
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def rsqrt(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise inverse square-root value of the input.
.. math::
rsqrt(x) = 1/\sqrt{x}
Example::
rsqrt([4,9,16]) = [0.5, 0.33333334, 0.25]
The storage type of ``rsqrt`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L584
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sgd_mom_update(weight=None, grad=None, mom=None, lr=_Null, momentum=_Null, wd=_Null, rescale_grad=_Null, clip_gradient=_Null, out=None, name=None, **kwargs):
r"""Momentum update function for Stochastic Gradient Descent (SDG) optimizer.
Momentum update has better convergence rates on neural networks. Mathematically it looks
like below:
.. math::
v_1 = \alpha * \nabla J(W_0)\\
v_t = \gamma v_{t-1} - \alpha * \nabla J(W_{t-1})\\
W_t = W_{t-1} + v_t
It updates the weights using::
v = momentum * v - learning_rate * gradient
weight += v
Where the parameter ``momentum`` is the decay rate of momentum estimates at each epoch.
If weight and grad are both of ``row_sparse`` storage type and momentum is of ``default`` storage type,
standard update is applied.
If weight, grad and momentum are all of ``row_sparse`` storage type,
only the row slices whose indices appear in grad.indices are updated (for both weight and momentum)::
for row in gradient.indices:
v[row] = momentum[row] * v[row] - learning_rate * gradient[row]
weight[row] += v[row]
Defined in src/operator/optimizer_op.cc:L265
Parameters
----------
weight : NDArray
Weight
grad : NDArray
Gradient
mom : NDArray
Momentum
lr : float, required
Learning rate
momentum : float, optional, default=0
The decay rate of momentum estimates at each epoch.
wd : float, optional, default=0
Weight decay augments the objective function with a regularization term that penalizes large weights. The penalty scales with the square of the magnitude of each weight.
rescale_grad : float, optional, default=1
Rescale gradient to grad = rescale_grad*grad.
clip_gradient : float, optional, default=-1
Clip gradient to the range of [-clip_gradient, clip_gradient] If clip_gradient <= 0, gradient clipping is turned off. grad = max(min(grad, clip_gradient), -clip_gradient).
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sgd_update(weight=None, grad=None, lr=_Null, wd=_Null, rescale_grad=_Null, clip_gradient=_Null, out=None, name=None, **kwargs):
r"""Update function for Stochastic Gradient Descent (SDG) optimizer.
It updates the weights using::
weight = weight - learning_rate * gradient
If weight is of ``row_sparse`` storage type,
only the row slices whose indices appear in grad.indices are updated::
for row in gradient.indices:
weight[row] = weight[row] - learning_rate * gradient[row]
Defined in src/operator/optimizer_op.cc:L222
Parameters
----------
weight : NDArray
Weight
grad : NDArray
Gradient
lr : float, required
Learning rate
wd : float, optional, default=0
Weight decay augments the objective function with a regularization term that penalizes large weights. The penalty scales with the square of the magnitude of each weight.
rescale_grad : float, optional, default=1
Rescale gradient to grad = rescale_grad*grad.
clip_gradient : float, optional, default=-1
Clip gradient to the range of [-clip_gradient, clip_gradient] If clip_gradient <= 0, gradient clipping is turned off. grad = max(min(grad, clip_gradient), -clip_gradient).
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sigmoid(data=None, out=None, name=None, **kwargs):
r"""Computes sigmoid of x element-wise.
.. math::
y = 1 / (1 + exp(-x))
The storage type of ``sigmoid`` output is always dense
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L102
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sign(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise sign of the input.
Example::
sign([-2, 0, 3]) = [-1, 0, 1]
The storage type of ``sign`` output depends upon the input storage type:
- sign(default) = default
- sign(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L404
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sin(data=None, out=None, name=None, **kwargs):
r"""Computes the element-wise sine of the input array.
The input should be in radians (:math:`2\pi` rad equals 360 degrees).
.. math::
sin([0, \pi/4, \pi/2]) = [0, 0.707, 1]
The storage type of ``sin`` output depends upon the input storage type:
- sin(default) = default
- sin(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L46
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sinh(data=None, out=None, name=None, **kwargs):
r"""Returns the hyperbolic sine of the input array, computed element-wise.
.. math::
sinh(x) = 0.5\times(exp(x) - exp(-x))
The storage type of ``sinh`` output depends upon the input storage type:
- sinh(default) = default
- sinh(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L201
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def slice(data=None, begin=_Null, end=_Null, step=_Null, out=None, name=None, **kwargs):
r"""Slices a region of the array.
.. note:: ``crop`` is deprecated. Use ``slice`` instead.
This function returns a sliced array between the indices given
by `begin` and `end` with the corresponding `step`.
For an input array of ``shape=(d_0, d_1, ..., d_n-1)``,
slice operation with ``begin=(b_0, b_1...b_m-1)``,
``end=(e_0, e_1, ..., e_m-1)``, and ``step=(s_0, s_1, ..., s_m-1)``,
where m <= n, results in an array with the shape
``(|e_0-b_0|/|s_0|, ..., |e_m-1-b_m-1|/|s_m-1|, d_m, ..., d_n-1)``.
The resulting array's *k*-th dimension contains elements
from the *k*-th dimension of the input array starting
from index ``b_k`` (inclusive) with step ``s_k``
until reaching ``e_k`` (exclusive).
If the *k*-th elements are `None` in the sequence of `begin`, `end`,
and `step`, the following rule will be used to set default values.
If `s_k` is `None`, set `s_k=1`. If `s_k > 0`, set `b_k=0`, `e_k=d_k`;
else, set `b_k=d_k-1`, `e_k=-1`.
The storage type of ``slice`` output depends on storage types of inputs
- slice(csr) = csr
- otherwise, ``slice`` generates output with default storage
.. note:: When input data storage type is csr, it only supports
step=(), or step=(None,), or step=(1,) to generate a csr output.
For other step parameter values, it falls back to slicing
a dense tensor.
Example::
x = [[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]]
slice(x, begin=(0,1), end=(2,4)) = [[ 2., 3., 4.],
[ 6., 7., 8.]]
slice(x, begin=(None, 0), end=(None, 3), step=(-1, 2)) = [[9., 11.],
[5., 7.],
[1., 3.]]
Defined in src/operator/tensor/matrix_op.cc:L355
Parameters
----------
data : NDArray
Source input
begin : Shape(tuple), required
starting indices for the slice operation, supports negative indices.
end : Shape(tuple), required
ending indices for the slice operation, supports negative indices.
step : Shape(tuple), optional, default=[]
step for the slice operation, supports negative values.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sqrt(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise square-root value of the input.
.. math::
\textrm{sqrt}(x) = \sqrt{x}
Example::
sqrt([4, 9, 16]) = [2, 3, 4]
The storage type of ``sqrt`` output depends upon the input storage type:
- sqrt(default) = default
- sqrt(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L564
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def square(data=None, out=None, name=None, **kwargs):
r"""Returns element-wise squared value of the input.
.. math::
square(x) = x^2
Example::
square([2, 3, 4]) = [4, 9, 16]
The storage type of ``square`` output depends upon the input storage type:
- square(default) = default
- square(row_sparse) = row_sparse
- square(csr) = csr
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L541
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def stop_gradient(data=None, out=None, name=None, **kwargs):
r"""Stops gradient computation.
Stops the accumulated gradient of the inputs from flowing through this operator
in the backward direction. In other words, this operator prevents the contribution
of its inputs to be taken into account for computing gradients.
Example::
v1 = [1, 2]
v2 = [0, 1]
a = Variable('a')
b = Variable('b')
b_stop_grad = stop_gradient(3 * b)
loss = MakeLoss(b_stop_grad + a)
executor = loss.simple_bind(ctx=cpu(), a=(1,2), b=(1,2))
executor.forward(is_train=True, a=v1, b=v2)
executor.outputs
[ 1. 5.]
executor.backward()
executor.grad_arrays
[ 0. 0.]
[ 1. 1.]
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L166
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def sum(data=None, axis=_Null, keepdims=_Null, exclude=_Null, out=None, name=None, **kwargs):
r"""Computes the sum of array elements over given axes.
.. Note::
`sum` and `sum_axis` are equivalent.
For ndarray of csr storage type summation along axis 0 and axis 1 is supported.
Setting keepdims or exclude to True will cause a fallback to dense operator.
Example::
data = [[[1,2],[2,3],[1,3]],
[[1,4],[4,3],[5,2]],
[[7,1],[7,2],[7,3]]]
sum(data, axis=1)
[[ 4. 8.]
[ 10. 9.]
[ 21. 6.]]
sum(data, axis=[1,2])
[ 12. 19. 27.]
data = [[1,2,0],
[3,0,1],
[4,1,0]]
csr = cast_storage(data, 'csr')
sum(csr, axis=0)
[ 8. 3. 1.]
sum(csr, axis=1)
[ 3. 4. 5.]
Defined in src/operator/tensor/broadcast_reduce_op_value.cc:L85
Parameters
----------
data : NDArray
The input
axis : Shape(tuple), optional, default=[]
The axis or axes along which to perform the reduction.
The default, `axis=()`, will compute over all elements into a
scalar array with shape `(1,)`.
If `axis` is int, a reduction is performed on a particular axis.
If `axis` is a tuple of ints, a reduction is performed on all the axes
specified in the tuple.
If `exclude` is true, reduction will be performed on the axes that are
NOT in axis instead.
Negative values means indexing from right to left.
keepdims : boolean, optional, default=0
If this is set to `True`, the reduced axes are left in the result as dimension with size one.
exclude : boolean, optional, default=0
Whether to perform reduction on axis that are NOT in axis instead.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def tan(data=None, out=None, name=None, **kwargs):
r"""Computes the element-wise tangent of the input array.
The input should be in radians (:math:`2\pi` rad equals 360 degrees).
.. math::
tan([0, \pi/4, \pi/2]) = [0, 1, -inf]
The storage type of ``tan`` output depends upon the input storage type:
- tan(default) = default
- tan(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L83
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def tanh(data=None, out=None, name=None, **kwargs):
r"""Returns the hyperbolic tangent of the input array, computed element-wise.
.. math::
tanh(x) = sinh(x) / cosh(x)
The storage type of ``tanh`` output depends upon the input storage type:
- tanh(default) = default
- tanh(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_trig.cc:L234
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def trunc(data=None, out=None, name=None, **kwargs):
r"""Return the element-wise truncated value of the input.
The truncated value of the scalar x is the nearest integer i which is closer to
zero than x is. In short, the fractional part of the signed number x is discarded.
Example::
trunc([-2.1, -1.9, 1.5, 1.9, 2.1]) = [-2., -1., 1., 1., 2.]
The storage type of ``trunc`` output depends upon the input storage type:
- trunc(default) = default
- trunc(row_sparse) = row_sparse
Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L502
Parameters
----------
data : NDArray
The input array.
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
def zeros_like(data=None, out=None, name=None, **kwargs):
r"""Return an array of zeros with the same shape and type
as the input array.
The storage type of ``zeros_like`` output depends on the storage type of the input
- zeros_like(row_sparse) = row_sparse
- zeros_like(csr) = csr
- zeros_like(default) = default
Examples::
x = [[ 1., 1., 1.],
[ 1., 1., 1.]]
zeros_like(x) = [[ 0., 0., 0.],
[ 0., 0., 0.]]
Parameters
----------
data : NDArray
The input
out : NDArray, optional
The output NDArray to hold the result.
Returns
-------
out : NDArray or list of NDArrays
The output of this function.
"""
return (0,)
__all__ = ['ElementWiseSum', 'abs', 'adam_update', 'add_n', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctanh', 'cast_storage', 'ceil', 'clip', 'cos', 'cosh', 'degrees', 'dot', 'elemwise_add', 'elemwise_div', 'elemwise_mul', 'elemwise_sub', 'exp', 'expm1', 'fix', 'floor', 'ftrl_update', 'gamma', 'gammaln', 'log', 'log10', 'log1p', 'log2', 'make_loss', 'mean', 'negative', 'norm', 'radians', 'relu', 'retain', 'rint', 'round', 'rsqrt', 'sgd_mom_update', 'sgd_update', 'sigmoid', 'sign', 'sin', 'sinh', 'slice', 'sqrt', 'square', 'stop_gradient', 'sum', 'tan', 'tanh', 'trunc', 'zeros_like'] | [
2,
9220,
2695,
318,
8295,
12,
27568,
13,
2141,
407,
13096,
13,
198,
2,
279,
2645,
600,
25,
14267,
12,
7753,
198,
6738,
47540,
32538,
1330,
25524,
19182,
14881,
198,
6738,
11485,
8692,
1330,
4808,
35067,
198,
198,
4299,
11703,
54,
786,
13065,
46491,
22046,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
46245,
477,
5128,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
751,
59,
62,
77,
7,
64,
62,
16,
11,
257,
62,
17,
11,
2644,
11,
257,
62,
77,
8,
796,
257,
62,
16,
1343,
257,
62,
17,
1343,
2644,
1343,
257,
62,
77,
628,
220,
220,
220,
7559,
2860,
62,
77,
15506,
318,
6196,
517,
6942,
621,
4585,
7559,
2860,
15506,
416,
4600,
77,
63,
1661,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
2860,
62,
77,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
532,
751,
62,
77,
7,
808,
62,
82,
29572,
11,
5752,
62,
82,
29572,
11,
11485,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
532,
4306,
11,
7559,
2860,
62,
77,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
16345,
13,
535,
25,
43,
10163,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
26498,
1058,
25524,
19182,
21737,
198,
220,
220,
220,
220,
220,
220,
220,
18574,
1859,
5128,
7159,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2352,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
4112,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
2352,
26933,
12,
17,
11,
657,
11,
513,
12962,
796,
685,
17,
11,
657,
11,
513,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
8937,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
2352,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
2352,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
27203,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
23197,
62,
19119,
7,
6551,
28,
14202,
11,
3915,
28,
14202,
11,
1612,
28,
14202,
11,
1401,
28,
14202,
11,
300,
81,
28,
62,
35067,
11,
12159,
16,
28,
62,
35067,
11,
12159,
17,
28,
62,
35067,
11,
304,
862,
33576,
28,
62,
35067,
11,
266,
67,
28,
62,
35067,
11,
6811,
1000,
62,
9744,
28,
62,
35067,
11,
10651,
62,
49607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
10260,
2163,
329,
7244,
6436,
7509,
13,
7244,
318,
1775,
355,
257,
2276,
1634,
198,
220,
220,
220,
286,
47395,
42731,
13,
628,
220,
220,
220,
7244,
4296,
10874,
286,
262,
1708,
4831,
11,
810,
308,
6870,
31312,
290,
285,
11,
410,
198,
220,
220,
220,
389,
352,
301,
290,
362,
358,
1502,
2589,
7746,
357,
32604,
290,
24198,
737,
628,
220,
220,
220,
11485,
10688,
3712,
628,
220,
220,
220,
220,
308,
62,
83,
796,
3467,
77,
397,
5031,
449,
7,
54,
23330,
83,
12,
16,
30072,
6852,
198,
220,
220,
220,
220,
285,
62,
83,
796,
3467,
31361,
62,
16,
285,
23330,
83,
12,
16,
92,
1343,
357,
16,
532,
3467,
31361,
62,
16,
8,
308,
62,
83,
6852,
198,
220,
220,
220,
220,
410,
62,
83,
796,
3467,
31361,
62,
17,
410,
23330,
83,
12,
16,
92,
1343,
357,
16,
532,
3467,
31361,
62,
17,
8,
308,
62,
83,
61,
17,
6852,
198,
220,
220,
220,
220,
370,
62,
83,
796,
370,
23330,
83,
12,
16,
92,
532,
3467,
26591,
3467,
31944,
90,
285,
62,
83,
1782,
90,
3467,
31166,
17034,
90,
410,
62,
83,
1782,
1343,
3467,
538,
18217,
261,
1782,
628,
220,
220,
220,
632,
5992,
262,
19590,
1262,
3712,
628,
220,
220,
220,
220,
285,
796,
12159,
16,
9,
76,
1343,
357,
16,
12,
31361,
16,
27493,
9744,
198,
220,
220,
220,
220,
410,
796,
12159,
17,
9,
85,
1343,
357,
16,
12,
31361,
17,
27493,
7,
9744,
1174,
17,
8,
198,
220,
220,
220,
220,
266,
15853,
532,
4673,
62,
4873,
1635,
285,
1220,
357,
31166,
17034,
7,
85,
8,
1343,
304,
862,
33576,
8,
628,
220,
220,
220,
1002,
266,
11,
285,
290,
410,
389,
477,
286,
7559,
808,
62,
82,
29572,
15506,
6143,
2099,
11,
198,
220,
220,
220,
691,
262,
5752,
24314,
3025,
36525,
1656,
287,
3915,
13,
521,
1063,
389,
6153,
357,
1640,
266,
11,
285,
290,
410,
2599,
25,
628,
220,
220,
220,
220,
329,
5752,
287,
3915,
13,
521,
1063,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
285,
58,
808,
60,
796,
12159,
16,
9,
76,
58,
808,
60,
1343,
357,
16,
12,
31361,
16,
27493,
9744,
58,
808,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
410,
58,
808,
60,
796,
12159,
17,
9,
85,
58,
808,
60,
1343,
357,
16,
12,
31361,
17,
27493,
7,
9744,
58,
808,
60,
1174,
17,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
266,
58,
808,
60,
15853,
532,
4673,
62,
4873,
1635,
285,
58,
808,
60,
1220,
357,
31166,
17034,
7,
85,
58,
808,
12962,
1343,
304,
862,
33576,
8,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
40085,
7509,
62,
404,
13,
535,
25,
43,
34741,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
3463,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
198,
220,
220,
220,
3915,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
17701,
1153,
198,
220,
220,
220,
1612,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
26768,
1612,
198,
220,
220,
220,
1401,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
26768,
24198,
198,
220,
220,
220,
300,
81,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
18252,
2494,
198,
220,
220,
220,
12159,
16,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
13,
24,
198,
220,
220,
220,
220,
220,
220,
220,
383,
22119,
2494,
329,
262,
352,
301,
2589,
7746,
13,
198,
220,
220,
220,
12159,
17,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
13,
17032,
198,
220,
220,
220,
220,
220,
220,
220,
383,
22119,
2494,
329,
262,
362,
358,
2589,
7746,
13,
198,
220,
220,
220,
304,
862,
33576,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
68,
12,
2919,
198,
220,
220,
220,
220,
220,
220,
220,
317,
1402,
6937,
329,
29052,
10159,
13,
198,
220,
220,
220,
266,
67,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
22119,
16339,
902,
262,
9432,
2163,
351,
257,
3218,
1634,
3381,
326,
23634,
4340,
1588,
19590,
13,
383,
7389,
16252,
351,
262,
6616,
286,
262,
14735,
286,
1123,
3463,
13,
198,
220,
220,
220,
6811,
1000,
62,
9744,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1874,
38765,
31312,
284,
3915,
796,
6811,
1000,
62,
9744,
9,
9744,
13,
198,
220,
220,
220,
10651,
62,
49607,
1058,
12178,
11,
11902,
11,
4277,
10779,
16,
198,
220,
220,
220,
220,
220,
220,
220,
42512,
31312,
284,
262,
2837,
286,
25915,
15036,
62,
49607,
11,
10651,
62,
49607,
60,
1002,
10651,
62,
49607,
19841,
657,
11,
31312,
45013,
318,
2900,
572,
13,
3915,
796,
3509,
7,
1084,
7,
9744,
11,
10651,
62,
49607,
828,
532,
15036,
62,
49607,
737,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
751,
62,
77,
46491,
22046,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
46245,
477,
5128,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
751,
59,
62,
77,
7,
64,
62,
16,
11,
257,
62,
17,
11,
2644,
11,
257,
62,
77,
8,
796,
257,
62,
16,
1343,
257,
62,
17,
1343,
2644,
1343,
257,
62,
77,
628,
220,
220,
220,
7559,
2860,
62,
77,
15506,
318,
6196,
517,
6942,
621,
4585,
7559,
2860,
15506,
416,
4600,
77,
63,
1661,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
2860,
62,
77,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
532,
751,
62,
77,
7,
808,
62,
82,
29572,
11,
5752,
62,
82,
29572,
11,
11485,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
532,
4306,
11,
7559,
2860,
62,
77,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
16345,
13,
535,
25,
43,
10163,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
26498,
1058,
25524,
19182,
21737,
198,
220,
220,
220,
220,
220,
220,
220,
18574,
1859,
5128,
7159,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
610,
535,
418,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
34062,
8615,
500,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5128,
815,
307,
287,
2837,
4600,
58,
12,
16,
11,
352,
60,
44646,
198,
220,
220,
220,
383,
5072,
318,
287,
262,
4838,
16654,
1058,
11018,
25,
63,
58,
15,
11,
3467,
14415,
60,
63,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
610,
535,
418,
26933,
12,
16,
11,
532,
13,
24038,
11,
657,
11,
764,
24038,
11,
352,
12962,
796,
685,
59,
14415,
11,
513,
59,
14415,
14,
19,
11,
3467,
14415,
14,
17,
11,
3467,
14415,
14,
19,
11,
657,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
283,
535,
418,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
10163,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
610,
535,
3768,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
5002,
12,
3083,
34062,
8718,
65,
4160,
8615,
500,
286,
262,
5128,
7177,
11,
3467,
198,
220,
220,
220,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
283,
535,
3768,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
18897,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
44606,
259,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
34062,
264,
500,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5128,
815,
307,
287,
262,
2837,
4600,
58,
12,
16,
11,
352,
60,
44646,
198,
220,
220,
220,
383,
5072,
318,
287,
262,
4838,
16654,
286,
685,
25,
11018,
25,
63,
12,
59,
14415,
14,
17,
47671,
1058,
11018,
25,
63,
59,
14415,
14,
17,
63,
4083,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
44606,
259,
26933,
12,
16,
11,
532,
13,
24038,
11,
657,
11,
764,
24038,
11,
352,
12962,
796,
25915,
59,
14415,
14,
17,
11,
532,
59,
14415,
14,
19,
11,
657,
11,
3467,
14415,
14,
19,
11,
3467,
14415,
14,
17,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
5605,
31369,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
44606,
259,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
44606,
259,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
13464,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
44606,
259,
71,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
5002,
12,
3083,
34062,
8718,
65,
4160,
264,
500,
286,
262,
5128,
7177,
11,
3467,
198,
220,
220,
220,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
5605,
31369,
71,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
44606,
259,
71,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
44606,
259,
71,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
9031,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
610,
310,
272,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
34062,
13875,
298,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5072,
318,
287,
262,
4838,
16654,
1058,
11018,
25,
63,
58,
12,
59,
14415,
14,
17,
11,
3467,
14415,
14,
17,
60,
63,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
610,
310,
272,
26933,
12,
16,
11,
657,
11,
352,
12962,
796,
25915,
59,
14415,
14,
19,
11,
657,
11,
3467,
14415,
14,
19,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
283,
310,
272,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
610,
310,
272,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
610,
310,
272,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
18444,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
610,
310,
272,
71,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
5002,
12,
3083,
34062,
8718,
65,
4160,
13875,
298,
286,
262,
5128,
7177,
11,
3467,
198,
220,
220,
220,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
283,
310,
272,
71,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
610,
310,
272,
71,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
610,
310,
272,
71,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
30368,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
3350,
62,
35350,
7,
7890,
28,
14202,
11,
336,
2981,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
34,
5773,
11192,
273,
6143,
2099,
284,
262,
649,
2099,
13,
628,
220,
220,
220,
1649,
281,
25524,
19182,
351,
4277,
6143,
2099,
318,
3350,
284,
269,
27891,
393,
5752,
62,
82,
29572,
6143,
11,
198,
220,
220,
220,
262,
1255,
318,
16001,
11,
543,
1724,
25,
628,
220,
220,
220,
532,
329,
269,
27891,
11,
6632,
3815,
481,
407,
307,
17383,
198,
220,
220,
220,
532,
329,
5752,
62,
82,
29572,
11,
5752,
24314,
286,
477,
1976,
27498,
481,
407,
307,
17383,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
2701,
62,
35350,
15506,
5072,
8338,
319,
336,
2981,
11507,
25,
628,
220,
220,
220,
532,
3350,
62,
35350,
7,
6359,
81,
11,
705,
12286,
11537,
796,
4277,
198,
220,
220,
220,
532,
3350,
62,
35350,
7,
808,
62,
82,
29572,
11,
705,
12286,
11537,
796,
4277,
198,
220,
220,
220,
532,
3350,
62,
35350,
7,
12286,
11,
705,
6359,
81,
11537,
796,
269,
27891,
198,
220,
220,
220,
532,
3350,
62,
35350,
7,
12286,
11,
705,
808,
62,
82,
29572,
11537,
796,
5752,
62,
82,
29572,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
15715,
796,
16410,
657,
1539,
220,
352,
1539,
220,
657,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
362,
1539,
220,
657,
1539,
220,
513,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
657,
1539,
220,
657,
1539,
220,
657,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
657,
1539,
220,
657,
1539,
220,
657,
8183,
60,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3350,
284,
5752,
62,
82,
29572,
6143,
2099,
198,
220,
220,
220,
220,
220,
220,
220,
374,
2777,
796,
3350,
62,
35350,
7,
67,
1072,
11,
705,
808,
62,
82,
29572,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
374,
2777,
13,
521,
1063,
796,
685,
15,
11,
352,
60,
198,
220,
220,
220,
220,
220,
220,
220,
374,
2777,
13,
27160,
796,
16410,
657,
1539,
220,
352,
1539,
220,
657,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
362,
1539,
220,
657,
1539,
220,
513,
8183,
60,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3350,
284,
269,
27891,
6143,
2099,
198,
220,
220,
220,
220,
220,
220,
220,
269,
27891,
796,
3350,
62,
35350,
7,
67,
1072,
11,
705,
6359,
81,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
269,
27891,
13,
521,
1063,
796,
685,
16,
11,
657,
11,
362,
60,
198,
220,
220,
220,
220,
220,
220,
220,
269,
27891,
13,
27160,
796,
685,
352,
1539,
220,
362,
1539,
220,
513,
8183,
198,
220,
220,
220,
220,
220,
220,
220,
269,
27891,
13,
521,
20692,
796,
685,
15,
11,
352,
11,
513,
11,
513,
11,
513,
60,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
2701,
62,
35350,
13,
535,
25,
43,
3388,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
13,
198,
220,
220,
220,
336,
2981,
1058,
1391,
6,
6359,
81,
3256,
705,
12286,
3256,
705,
808,
62,
82,
29572,
6,
5512,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
25235,
6143,
2099,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2906,
346,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
13387,
286,
262,
5128,
13,
628,
220,
220,
220,
383,
2906,
346,
286,
262,
16578,
283,
2124,
318,
262,
18197,
18253,
1312,
11,
884,
326,
1312,
18189,
2124,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
2906,
346,
26933,
12,
17,
13,
16,
11,
532,
16,
13,
24,
11,
352,
13,
20,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
17,
1539,
532,
16,
1539,
220,
362,
1539,
220,
362,
1539,
220,
513,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
344,
346,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
2906,
346,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
2906,
346,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
38380,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
10651,
7,
7890,
28,
14202,
11,
257,
62,
1084,
28,
62,
35067,
11,
257,
62,
9806,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
2601,
2419,
357,
49196,
8,
262,
3815,
287,
281,
7177,
13,
628,
220,
220,
220,
11259,
281,
16654,
11,
3815,
2354,
262,
16654,
389,
49305,
284,
262,
16654,
13015,
13,
198,
220,
220,
220,
1012,
4501,
7559,
87,
15506,
1022,
4600,
64,
62,
1084,
63,
290,
4600,
64,
62,
87,
63,
561,
307,
3712,
628,
220,
220,
220,
220,
220,
220,
10651,
7,
87,
11,
257,
62,
1084,
11,
257,
62,
9806,
8,
796,
3509,
7,
1084,
7,
87,
11,
257,
62,
9806,
828,
257,
62,
1084,
4008,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
2124,
796,
685,
15,
11,
352,
11,
362,
11,
513,
11,
604,
11,
642,
11,
718,
11,
767,
11,
807,
11,
860,
60,
628,
220,
220,
220,
220,
220,
220,
220,
10651,
7,
87,
11,
16,
11,
23,
8,
796,
685,
352,
1539,
220,
352,
1539,
220,
362,
1539,
220,
513,
1539,
220,
604,
1539,
220,
642,
1539,
220,
718,
1539,
220,
767,
1539,
220,
807,
1539,
220,
807,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
15036,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
290,
262,
257,
62,
1084,
11,
257,
62,
9806,
3467,
198,
220,
220,
220,
11507,
3815,
25,
628,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
808,
62,
82,
29572,
11,
257,
62,
1084,
19841,
657,
11,
257,
62,
9806,
18189,
657,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
6359,
81,
11,
257,
62,
1084,
19841,
657,
11,
257,
62,
9806,
18189,
657,
8,
796,
269,
27891,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
808,
62,
82,
29572,
11,
257,
62,
1084,
1279,
657,
11,
257,
62,
9806,
1279,
657,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
808,
62,
82,
29572,
11,
257,
62,
1084,
1875,
657,
11,
257,
62,
9806,
1875,
657,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
6359,
81,
11,
257,
62,
1084,
1279,
657,
11,
257,
62,
9806,
1279,
657,
8,
796,
269,
27891,
198,
220,
220,
220,
220,
220,
220,
532,
10651,
7,
6359,
81,
11,
257,
62,
1084,
1875,
657,
11,
257,
62,
9806,
1875,
657,
8,
796,
269,
27891,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
6759,
8609,
62,
404,
13,
535,
25,
43,
34251,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
23412,
7177,
13,
198,
220,
220,
220,
257,
62,
1084,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
26265,
1988,
198,
220,
220,
220,
257,
62,
9806,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
22246,
1988,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
8615,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
262,
5002,
12,
3083,
8615,
500,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5128,
815,
307,
287,
2511,
1547,
357,
25,
11018,
25,
63,
17,
59,
14415,
63,
2511,
21767,
11470,
7370,
737,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
8615,
26933,
15,
11,
3467,
14415,
14,
19,
11,
3467,
14415,
14,
17,
12962,
796,
685,
16,
11,
657,
13,
24038,
11,
657,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6966,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
5066,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
269,
3768,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
8718,
65,
4160,
8615,
500,
220,
286,
262,
5128,
7177,
11,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
269,
3768,
7,
87,
8,
796,
657,
13,
20,
59,
22355,
7,
11201,
7,
87,
8,
1343,
1033,
32590,
87,
4008,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
66,
3768,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
20666,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
7370,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
3103,
24040,
1123,
5002,
286,
262,
5128,
7177,
422,
2511,
1547,
284,
7370,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
7370,
26933,
15,
11,
3467,
14415,
14,
17,
11,
3467,
14415,
11,
513,
59,
14415,
14,
17,
11,
362,
59,
14415,
12962,
796,
685,
15,
11,
4101,
11,
11546,
11,
20479,
11,
11470,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
13500,
6037,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
7370,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
7370,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
24136,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
16605,
7,
75,
11994,
28,
14202,
11,
9529,
82,
28,
14202,
11,
1007,
3455,
62,
64,
28,
62,
35067,
11,
1007,
3455,
62,
65,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35,
313,
1720,
286,
734,
26515,
13,
628,
220,
220,
220,
7559,
26518,
15506,
6,
82,
4069,
8338,
319,
262,
5128,
7177,
15225,
25,
628,
220,
220,
220,
532,
352,
12,
35,
26515,
25,
8434,
1720,
286,
30104,
198,
220,
220,
220,
532,
362,
12,
35,
26515,
25,
17593,
48473,
198,
220,
220,
220,
532,
399,
12,
35,
26515,
25,
257,
2160,
1720,
625,
262,
938,
16488,
286,
262,
717,
5128,
290,
262,
717,
198,
220,
220,
220,
220,
220,
16488,
286,
262,
1218,
5128,
628,
220,
220,
220,
220,
220,
1114,
1672,
11,
1813,
513,
12,
35,
7559,
87,
15506,
351,
5485,
4600,
7,
77,
11,
76,
11,
74,
8,
63,
290,
7559,
88,
15506,
351,
5485,
4600,
7,
74,
11,
81,
11,
82,
8,
47671,
262,
198,
220,
220,
220,
220,
220,
1255,
7177,
481,
423,
5485,
4600,
7,
77,
11,
76,
11,
81,
11,
82,
8,
44646,
632,
318,
29231,
416,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
16605,
7,
87,
11,
88,
38381,
72,
11,
73,
11,
64,
11,
65,
60,
796,
2160,
7,
87,
58,
72,
11,
73,
11,
47715,
9,
88,
58,
45299,
64,
11,
65,
12962,
628,
220,
220,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
2124,
796,
27179,
1758,
26933,
15,
11,
16,
11,
17,
11,
18,
11,
19,
11,
20,
11,
21,
11,
22,
4357,
5485,
16193,
17,
11,
17,
11,
17,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
331,
796,
27179,
1758,
26933,
22,
11,
21,
11,
20,
11,
19,
11,
18,
11,
17,
11,
16,
11,
15,
4357,
5485,
16193,
17,
11,
17,
11,
17,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
16605,
7,
87,
11,
88,
38381,
15,
11,
15,
11,
16,
11,
16,
60,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
2160,
7,
87,
58,
15,
11,
15,
11,
47715,
9,
88,
58,
45299,
16,
11,
16,
12962,
796,
657,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
26518,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
290,
1007,
3455,
3689,
25,
628,
220,
220,
220,
532,
16605,
7,
6359,
81,
11,
4277,
8,
796,
4277,
198,
220,
220,
220,
532,
16605,
7,
6359,
81,
13,
51,
11,
4277,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
532,
16605,
7,
6359,
81,
11,
5752,
62,
82,
29572,
8,
796,
4277,
198,
220,
220,
220,
532,
16605,
7,
12286,
11,
269,
27891,
8,
796,
269,
27891,
198,
220,
220,
220,
532,
4306,
11,
7559,
26518,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
26518,
13,
535,
25,
43,
5237,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
300,
11994,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
717,
5128,
198,
220,
220,
220,
9529,
82,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
1218,
5128,
198,
220,
220,
220,
1007,
3455,
62,
64,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
2081,
788,
1007,
3455,
262,
717,
5128,
878,
16605,
13,
198,
220,
220,
220,
1007,
3455,
62,
65,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
2081,
788,
1007,
3455,
262,
1218,
5128,
878,
16605,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
9766,
76,
3083,
62,
2860,
7,
75,
11994,
28,
14202,
11,
9529,
82,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
46245,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
68,
10671,
3083,
62,
2860,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
2860,
7,
808,
62,
82,
29572,
11,
5752,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
2860,
7,
6359,
81,
11,
269,
27891,
8,
796,
269,
27891,
198,
220,
220,
220,
220,
220,
220,
532,
4306,
11,
7559,
68,
10671,
3083,
62,
2860,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
300,
11994,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
717,
5128,
198,
220,
220,
220,
9529,
82,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
1218,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
9766,
76,
3083,
62,
7146,
7,
75,
11994,
28,
14202,
11,
9529,
82,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
24095,
1460,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
68,
10671,
3083,
62,
7146,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
300,
11994,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
717,
5128,
198,
220,
220,
220,
9529,
82,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
1218,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
9766,
76,
3083,
62,
76,
377,
7,
75,
11994,
28,
14202,
11,
9529,
82,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
15205,
24705,
444,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
68,
10671,
3083,
62,
76,
377,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
76,
377,
7,
12286,
11,
4277,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
76,
377,
7,
808,
62,
82,
29572,
11,
5752,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
76,
377,
7,
12286,
11,
5752,
62,
82,
29572,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
76,
377,
7,
808,
62,
82,
29572,
11,
4277,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
76,
377,
7,
6359,
81,
11,
269,
27891,
8,
796,
269,
27891,
198,
220,
220,
220,
220,
220,
220,
532,
4306,
11,
7559,
68,
10671,
3083,
62,
76,
377,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
300,
11994,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
717,
5128,
198,
220,
220,
220,
9529,
82,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
1218,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
9766,
76,
3083,
62,
7266,
7,
75,
11994,
28,
14202,
11,
9529,
82,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7004,
83,
974,
82,
7159,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
68,
10671,
3083,
62,
7266,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
7266,
7,
808,
62,
82,
29572,
11,
5752,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
9766,
76,
3083,
62,
7266,
7,
6359,
81,
11,
269,
27891,
8,
796,
269,
27891,
198,
220,
220,
220,
220,
220,
220,
532,
4306,
11,
7559,
68,
10671,
3083,
62,
7266,
15506,
18616,
5072,
351,
4277,
6143,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
300,
11994,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
717,
5128,
198,
220,
220,
220,
9529,
82,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
1218,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
1033,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
39682,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
1033,
7,
87,
8,
796,
304,
61,
87,
3467,
1324,
13907,
362,
13,
45720,
61,
87,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
1033,
26933,
15,
11,
352,
11,
362,
12962,
796,
685,
16,
1539,
362,
13,
45720,
2078,
17430,
11,
767,
13,
29769,
2713,
21,
2481,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
11201,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
42759,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
1033,
76,
16,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
7559,
11201,
7,
87,
8,
532,
352,
15506,
29231,
5002,
12,
3083,
319,
262,
5128,
13,
628,
220,
220,
220,
770,
2163,
3769,
3744,
15440,
621,
7559,
11201,
7,
87,
8,
532,
352,
15506,
329,
1402,
3815,
286,
7559,
87,
15506,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
1069,
4426,
16,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
1033,
76,
16,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
1033,
76,
16,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
23906,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
4259,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
19273,
1988,
284,
262,
16936,
3467,
198,
220,
220,
220,
18253,
3371,
6632,
286,
262,
5128,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
4259,
26933,
12,
17,
13,
16,
11,
532,
16,
13,
24,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
17,
1539,
532,
16,
1539,
220,
352,
1539,
362,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
13049,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
4259,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
4259,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
31211,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
4314,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
4314,
286,
262,
5128,
13,
628,
220,
220,
220,
383,
4314,
286,
262,
16578,
283,
2124,
318,
262,
4387,
18253,
1312,
11,
884,
326,
1312,
19841,
2124,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
4314,
26933,
12,
17,
13,
16,
11,
532,
16,
13,
24,
11,
352,
13,
20,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
18,
1539,
532,
17,
1539,
220,
352,
1539,
220,
352,
1539,
220,
362,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
28300,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
4314,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
4314,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
40149,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
277,
14859,
62,
19119,
7,
6551,
28,
14202,
11,
3915,
28,
14202,
11,
1976,
28,
14202,
11,
299,
28,
14202,
11,
300,
81,
28,
62,
35067,
11,
30592,
6814,
16,
28,
62,
35067,
11,
12159,
28,
62,
35067,
11,
266,
67,
28,
62,
35067,
11,
6811,
1000,
62,
9744,
28,
62,
35067,
11,
10651,
62,
49607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
10260,
2163,
329,
376,
14859,
6436,
7509,
13,
198,
220,
220,
220,
6524,
14226,
771,
422,
1635,
2782,
6914,
46690,
25,
257,
3582,
422,
262,
309,
33650,
25666,
1695,
379,
198,
220,
220,
220,
2638,
1378,
25404,
13,
330,
76,
13,
2398,
14,
66,
3780,
13,
12993,
76,
30,
312,
28,
1731,
3459,
2167,
13,
628,
220,
220,
220,
632,
5992,
262,
19590,
1262,
3712,
628,
220,
220,
220,
220,
6811,
3021,
62,
9744,
796,
10651,
7,
9744,
1635,
6811,
1000,
62,
9744,
11,
10651,
62,
49607,
8,
198,
220,
220,
220,
220,
1976,
15853,
6811,
3021,
62,
9744,
532,
357,
31166,
17034,
7,
77,
1343,
6811,
3021,
62,
9744,
1174,
17,
8,
532,
19862,
17034,
7,
77,
4008,
1635,
3463,
1220,
4673,
62,
4873,
198,
220,
220,
220,
220,
299,
15853,
6811,
3021,
62,
9744,
1174,
17,
198,
220,
220,
220,
220,
266,
796,
357,
12683,
7,
89,
8,
1635,
30592,
6814,
16,
532,
1976,
8,
1220,
14808,
31361,
1343,
19862,
17034,
7,
77,
4008,
1220,
4673,
62,
4873,
1343,
266,
67,
8,
1635,
357,
8937,
7,
89,
8,
1875,
30592,
6814,
16,
8,
628,
220,
220,
220,
1002,
266,
11,
1976,
290,
299,
389,
477,
286,
7559,
808,
62,
82,
29572,
15506,
6143,
2099,
11,
198,
220,
220,
220,
691,
262,
5752,
24314,
3025,
36525,
1656,
287,
3915,
13,
521,
1063,
389,
6153,
357,
1640,
266,
11,
1976,
290,
299,
2599,
25,
628,
220,
220,
220,
220,
329,
5752,
287,
3915,
13,
521,
1063,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
6811,
3021,
62,
9744,
58,
808,
60,
796,
10651,
7,
9744,
58,
808,
60,
1635,
6811,
1000,
62,
9744,
11,
10651,
62,
49607,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
58,
808,
60,
15853,
6811,
3021,
62,
9744,
58,
808,
60,
532,
357,
31166,
17034,
7,
77,
58,
808,
60,
1343,
6811,
3021,
62,
9744,
58,
808,
60,
1174,
17,
8,
532,
19862,
17034,
7,
77,
58,
808,
60,
4008,
1635,
3463,
58,
808,
60,
1220,
4673,
62,
4873,
198,
220,
220,
220,
220,
220,
220,
220,
220,
299,
58,
808,
60,
15853,
6811,
3021,
62,
9744,
58,
808,
60,
1174,
17,
198,
220,
220,
220,
220,
220,
220,
220,
220,
266,
58,
808,
60,
796,
357,
12683,
7,
89,
58,
808,
12962,
1635,
30592,
6814,
16,
532,
1976,
58,
808,
12962,
1220,
14808,
31361,
1343,
19862,
17034,
7,
77,
58,
808,
60,
4008,
1220,
4673,
62,
4873,
1343,
266,
67,
8,
1635,
357,
8937,
7,
89,
58,
808,
12962,
1875,
30592,
6814,
16,
8,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
40085,
7509,
62,
404,
13,
535,
25,
43,
31211,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
3463,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
198,
220,
220,
220,
3915,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
17701,
1153,
198,
220,
220,
220,
1976,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
1976,
198,
220,
220,
220,
299,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
9276,
286,
3915,
198,
220,
220,
220,
300,
81,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
18252,
2494,
198,
220,
220,
220,
30592,
6814,
16,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
13,
486,
198,
220,
220,
220,
220,
220,
220,
220,
383,
406,
16,
3218,
1634,
35381,
13,
198,
220,
220,
220,
12159,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
198,
220,
220,
220,
220,
220,
220,
220,
2448,
12,
7222,
45480,
18252,
14806,
12159,
13,
198,
220,
220,
220,
266,
67,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
22119,
16339,
902,
262,
9432,
2163,
351,
257,
3218,
1634,
3381,
326,
23634,
4340,
1588,
19590,
13,
383,
7389,
16252,
351,
262,
6616,
286,
262,
14735,
286,
1123,
3463,
13,
198,
220,
220,
220,
6811,
1000,
62,
9744,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1874,
38765,
31312,
284,
3915,
796,
6811,
1000,
62,
9744,
9,
9744,
13,
198,
220,
220,
220,
10651,
62,
49607,
1058,
12178,
11,
11902,
11,
4277,
10779,
16,
198,
220,
220,
220,
220,
220,
220,
220,
42512,
31312,
284,
262,
2837,
286,
25915,
15036,
62,
49607,
11,
10651,
62,
49607,
60,
1002,
10651,
62,
49607,
19841,
657,
11,
31312,
45013,
318,
2900,
572,
13,
3915,
796,
3509,
7,
1084,
7,
9744,
11,
10651,
62,
49607,
828,
532,
15036,
62,
49607,
737,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
34236,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
34236,
2163,
357,
2302,
3004,
286,
262,
1109,
5132,
2163,
3467,
198,
220,
220,
220,
284,
262,
302,
874,
828,
29231,
5002,
12,
3083,
319,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
28483,
2611,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
308,
6475,
282,
77,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
2604,
286,
262,
4112,
1988,
286,
262,
34236,
2163,
3467,
198,
220,
220,
220,
286,
262,
5128,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
70,
6475,
282,
77,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2604,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
12068,
2604,
283,
342,
9383,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
383,
3288,
2604,
283,
342,
76,
318,
2604,
283,
342,
76,
287,
2779,
1635,
68,
25666,
523,
326,
7559,
6404,
7,
11201,
7,
87,
4008,
796,
2124,
15506,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6404,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
46435,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2604,
940,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
7308,
12,
940,
2604,
283,
342,
9383,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
7559,
940,
1174,
6404,
940,
7,
87,
8,
796,
2124,
15506,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6404,
940,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
36879,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2604,
16,
79,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
7559,
6404,
7,
16,
1343,
2124,
8,
15506,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
770,
2163,
318,
517,
7187,
621,
7559,
6404,
7,
16,
1343,
2124,
8,
15506,
220,
329,
1402,
7559,
87,
15506,
523,
326,
198,
220,
220,
220,
1058,
11018,
25,
63,
16,
10,
87,
59,
1324,
13907,
352,
63,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6404,
16,
79,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
2604,
16,
79,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
2604,
16,
79,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
36680,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2604,
17,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
7308,
12,
17,
2604,
283,
342,
9383,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
7559,
17,
1174,
6404,
17,
7,
87,
8,
796,
2124,
15506,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6404,
17,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
40179,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
787,
62,
22462,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
12050,
534,
898,
2994,
2163,
287,
3127,
5103,
13,
628,
220,
220,
220,
770,
10088,
18178,
257,
27658,
2994,
2163,
6194,
355,
257,
12094,
2994,
290,
198,
220,
220,
220,
262,
6194,
815,
307,
281,
10088,
351,
645,
19528,
20203,
13,
198,
220,
220,
220,
383,
5072,
286,
428,
2163,
318,
262,
31312,
286,
2994,
351,
2461,
284,
262,
5128,
1366,
13,
628,
220,
220,
220,
1114,
1672,
11,
611,
345,
389,
257,
1642,
257,
3272,
40709,
2994,
2163,
13,
2195,
2454,
7559,
448,
15506,
318,
262,
198,
220,
220,
220,
11001,
5072,
290,
7559,
18242,
15506,
318,
262,
2081,
6167,
11,
788,
262,
3272,
40709,
460,
307,
5447,
355,
3712,
628,
220,
220,
220,
220,
220,
3272,
62,
298,
28338,
796,
6167,
1635,
2604,
7,
448,
8,
1343,
357,
16,
532,
6167,
8,
1635,
2604,
7,
16,
532,
503,
8,
198,
220,
220,
220,
220,
220,
2994,
796,
787,
62,
22462,
7,
19692,
62,
298,
28338,
8,
628,
220,
220,
220,
775,
481,
761,
284,
779,
7559,
15883,
62,
22462,
15506,
618,
356,
389,
4441,
674,
898,
2994,
2163,
393,
356,
765,
284,
198,
220,
220,
220,
12082,
3294,
2994,
5499,
13,
4418,
356,
743,
765,
284,
2245,
617,
9633,
6,
3915,
2334,
198,
220,
220,
220,
422,
736,
22930,
363,
341,
13,
4091,
517,
3703,
287,
7559,
12235,
42731,
15506,
393,
7559,
11338,
62,
49607,
15506,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
15883,
62,
22462,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
787,
62,
22462,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
787,
62,
22462,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
19104,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
1612,
7,
7890,
28,
14202,
11,
16488,
28,
62,
35067,
11,
1394,
67,
12078,
28,
62,
35067,
11,
19607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
262,
1612,
286,
7177,
4847,
625,
1813,
34197,
13,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
36654,
2701,
62,
445,
7234,
62,
404,
62,
8367,
13,
535,
25,
43,
8784,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
198,
220,
220,
220,
16488,
1058,
25959,
7,
83,
29291,
828,
11902,
11,
4277,
28,
21737,
198,
220,
220,
220,
220,
220,
220,
220,
383,
16488,
393,
34197,
1863,
543,
284,
1620,
262,
7741,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
4277,
11,
4600,
22704,
28,
3419,
47671,
481,
24061,
625,
477,
4847,
656,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16578,
283,
7177,
351,
5485,
4600,
7,
16,
35751,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
22704,
63,
318,
493,
11,
257,
7741,
318,
6157,
319,
257,
1948,
16488,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
22704,
63,
318,
257,
46545,
286,
493,
82,
11,
257,
7741,
318,
6157,
319,
477,
262,
34197,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7368,
287,
262,
46545,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
1069,
9152,
63,
318,
2081,
11,
7741,
481,
307,
6157,
319,
262,
34197,
326,
389,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5626,
287,
16488,
2427,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
36183,
3815,
1724,
6376,
278,
422,
826,
284,
1364,
13,
198,
220,
220,
220,
1394,
67,
12078,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
428,
318,
900,
284,
4600,
17821,
47671,
262,
5322,
34197,
389,
1364,
287,
262,
1255,
355,
15793,
351,
2546,
530,
13,
198,
220,
220,
220,
19607,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
10127,
284,
1620,
7741,
319,
16488,
326,
389,
5626,
287,
16488,
2427,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
4633,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
45,
6975,
605,
4633,
286,
262,
4578,
11,
5002,
12,
3083,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
31591,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
4633,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
4633,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
4633,
7,
6359,
81,
8,
796,
269,
27891,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2593,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7414,
1078,
641,
262,
5128,
7177,
290,
788,
552,
1769,
262,
300,
17,
2593,
13,
628,
220,
220,
220,
21066,
3712,
628,
220,
220,
220,
220,
220,
2124,
796,
16410,
16,
11,
362,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
18,
11,
604,
11907,
628,
220,
220,
220,
220,
220,
2593,
7,
87,
8,
796,
685,
20,
13,
2857,
4761,
1495,
3695,
60,
628,
220,
220,
220,
220,
220,
374,
2777,
796,
2124,
13,
2701,
62,
35350,
10786,
808,
62,
82,
29572,
11537,
628,
220,
220,
220,
220,
220,
2593,
7,
81,
2777,
8,
796,
685,
20,
13,
2857,
4761,
1495,
3695,
60,
628,
220,
220,
220,
220,
220,
269,
27891,
796,
2124,
13,
2701,
62,
35350,
10786,
6359,
81,
11537,
628,
220,
220,
220,
220,
220,
2593,
7,
6359,
81,
8,
796,
685,
20,
13,
2857,
4761,
1495,
3695,
60,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
36654,
2701,
62,
445,
7234,
62,
404,
62,
8367,
13,
535,
25,
43,
25540,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
8090,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2511,
1547,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
3103,
24040,
1123,
5002,
286,
262,
5128,
7177,
422,
7370,
284,
2511,
1547,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
2511,
1547,
26933,
15,
11,
4101,
11,
11546,
11,
20479,
11,
11470,
12962,
796,
685,
15,
11,
3467,
14415,
14,
17,
11,
3467,
14415,
11,
513,
59,
14415,
14,
17,
11,
362,
59,
14415,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
6335,
1547,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
2511,
1547,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
2511,
1547,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
24294,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
823,
84,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
13621,
1431,
14174,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
3509,
7,
40890,
11,
657,
8,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
260,
2290,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
823,
84,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
823,
84,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
5999,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
12377,
7,
7890,
28,
14202,
11,
36525,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
27729,
15274,
7368,
416,
2836,
5128,
6376,
7177,
422,
257,
5752,
29877,
17593,
198,
220,
220,
220,
290,
3613,
606,
287,
262,
5072,
29877,
17593,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
1366,
796,
16410,
16,
11,
362,
4357,
685,
18,
11,
604,
4357,
685,
20,
11,
718,
11907,
198,
220,
220,
220,
220,
220,
36525,
796,
685,
15,
11,
352,
11,
513,
60,
198,
220,
220,
220,
220,
220,
5485,
796,
357,
19,
11,
362,
8,
198,
220,
220,
220,
220,
220,
374,
2777,
62,
259,
796,
5752,
62,
82,
29572,
7,
7890,
11,
36525,
8,
198,
220,
220,
220,
220,
220,
284,
62,
1186,
391,
796,
685,
15,
11,
513,
60,
198,
220,
220,
220,
220,
220,
374,
2777,
62,
448,
796,
12377,
7,
81,
2777,
62,
259,
11,
284,
62,
1186,
391,
8,
198,
220,
220,
220,
220,
220,
374,
2777,
62,
448,
13,
27160,
796,
16410,
16,
11,
362,
4357,
685,
20,
11,
718,
11907,
198,
220,
220,
220,
220,
220,
374,
2777,
62,
448,
13,
521,
1063,
796,
685,
15,
11,
513,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
1186,
391,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
532,
12377,
7,
808,
62,
82,
29572,
11,
4277,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
532,
4306,
11,
7559,
1186,
391,
15506,
318,
407,
4855,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
82,
29572,
62,
1186,
391,
13,
535,
25,
43,
4310,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
329,
29877,
62,
1186,
391,
10088,
13,
198,
220,
220,
220,
36525,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
6376,
7177,
286,
15274,
220,
2340,
326,
481,
307,
17383,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
374,
600,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
19273,
1988,
284,
262,
16936,
18253,
286,
262,
5128,
13,
628,
220,
220,
220,
11485,
3465,
3712,
198,
220,
220,
220,
220,
220,
220,
532,
1114,
5128,
7559,
77,
13,
20,
15506,
7559,
22272,
15506,
5860,
7559,
77,
15506,
981,
7559,
744,
15506,
5860,
7559,
77,
10,
16,
15506,
13,
198,
220,
220,
220,
220,
220,
220,
532,
1114,
5128,
7559,
12,
77,
13,
20,
15506,
1111,
7559,
22272,
15506,
290,
7559,
744,
15506,
5860,
7559,
12,
77,
12,
16,
15506,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
374,
600,
26933,
12,
16,
13,
20,
11,
352,
13,
20,
11,
532,
16,
13,
24,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
17,
1539,
220,
352,
1539,
532,
17,
1539,
220,
362,
1539,
220,
362,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
22272,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
374,
600,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
374,
600,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
30272,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2835,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
19273,
1988,
284,
262,
16936,
18253,
286,
262,
5128,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
2835,
26933,
12,
16,
13,
20,
11,
352,
13,
20,
11,
532,
16,
13,
24,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
17,
1539,
220,
362,
1539,
532,
17,
1539,
220,
362,
1539,
220,
362,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
744,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
532,
2835,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
532,
2835,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
43356,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
374,
31166,
17034,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
34062,
6616,
12,
15763,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
374,
31166,
17034,
7,
87,
8,
796,
352,
14,
59,
31166,
17034,
90,
87,
92,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
374,
31166,
17034,
26933,
19,
11,
24,
11,
1433,
12962,
796,
685,
15,
13,
20,
11,
657,
13,
24840,
2091,
2682,
11,
657,
13,
1495,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
3808,
80,
17034,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
46352,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
264,
21287,
62,
32542,
62,
19119,
7,
6551,
28,
14202,
11,
3915,
28,
14202,
11,
1995,
28,
14202,
11,
300,
81,
28,
62,
35067,
11,
12858,
28,
62,
35067,
11,
266,
67,
28,
62,
35067,
11,
6811,
1000,
62,
9744,
28,
62,
35067,
11,
10651,
62,
49607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
29252,
298,
388,
4296,
2163,
329,
520,
5374,
3477,
17701,
1153,
2935,
1087,
357,
10305,
38,
8,
6436,
7509,
13,
628,
220,
220,
220,
29278,
388,
4296,
468,
1365,
40826,
3965,
319,
17019,
7686,
13,
6550,
46558,
340,
3073,
198,
220,
220,
220,
588,
2174,
25,
628,
220,
220,
220,
11485,
10688,
3712,
628,
220,
220,
220,
220,
220,
410,
62,
16,
796,
3467,
26591,
1635,
3467,
77,
397,
5031,
449,
7,
54,
62,
15,
8,
6852,
198,
220,
220,
220,
220,
220,
410,
62,
83,
796,
3467,
28483,
2611,
410,
23330,
83,
12,
16,
92,
532,
3467,
26591,
1635,
3467,
77,
397,
5031,
449,
7,
54,
23330,
83,
12,
16,
30072,
6852,
198,
220,
220,
220,
220,
220,
370,
62,
83,
796,
370,
23330,
83,
12,
16,
92,
1343,
410,
62,
83,
628,
220,
220,
220,
632,
5992,
262,
19590,
1262,
3712,
628,
220,
220,
220,
220,
220,
410,
796,
12858,
1635,
410,
532,
4673,
62,
4873,
1635,
31312,
198,
220,
220,
220,
220,
220,
3463,
15853,
410,
628,
220,
220,
220,
6350,
262,
11507,
7559,
32542,
298,
388,
15506,
318,
262,
22119,
2494,
286,
12858,
7746,
379,
1123,
36835,
13,
628,
220,
220,
220,
1002,
3463,
290,
3915,
389,
1111,
286,
7559,
808,
62,
82,
29572,
15506,
6143,
2099,
290,
12858,
318,
286,
7559,
12286,
15506,
6143,
2099,
11,
198,
220,
220,
220,
3210,
4296,
318,
5625,
13,
628,
220,
220,
220,
1002,
3463,
11,
3915,
290,
12858,
389,
477,
286,
7559,
808,
62,
82,
29572,
15506,
6143,
2099,
11,
198,
220,
220,
220,
691,
262,
5752,
24314,
3025,
36525,
1656,
287,
3915,
13,
521,
1063,
389,
6153,
357,
1640,
1111,
3463,
290,
12858,
2599,
25,
628,
220,
220,
220,
220,
220,
329,
5752,
287,
31312,
13,
521,
1063,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
58,
808,
60,
796,
12858,
58,
808,
60,
1635,
410,
58,
808,
60,
532,
4673,
62,
4873,
1635,
31312,
58,
808,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3463,
58,
808,
60,
15853,
410,
58,
808,
60,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
40085,
7509,
62,
404,
13,
535,
25,
43,
22980,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
3463,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
198,
220,
220,
220,
3915,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
17701,
1153,
198,
220,
220,
220,
1995,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
29278,
388,
198,
220,
220,
220,
300,
81,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
18252,
2494,
198,
220,
220,
220,
12858,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
383,
22119,
2494,
286,
12858,
7746,
379,
1123,
36835,
13,
198,
220,
220,
220,
266,
67,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
22119,
16339,
902,
262,
9432,
2163,
351,
257,
3218,
1634,
3381,
326,
23634,
4340,
1588,
19590,
13,
383,
7389,
16252,
351,
262,
6616,
286,
262,
14735,
286,
1123,
3463,
13,
198,
220,
220,
220,
6811,
1000,
62,
9744,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1874,
38765,
31312,
284,
3915,
796,
6811,
1000,
62,
9744,
9,
9744,
13,
198,
220,
220,
220,
10651,
62,
49607,
1058,
12178,
11,
11902,
11,
4277,
10779,
16,
198,
220,
220,
220,
220,
220,
220,
220,
42512,
31312,
284,
262,
2837,
286,
25915,
15036,
62,
49607,
11,
10651,
62,
49607,
60,
1002,
10651,
62,
49607,
19841,
657,
11,
31312,
45013,
318,
2900,
572,
13,
3915,
796,
3509,
7,
1084,
7,
9744,
11,
10651,
62,
49607,
828,
532,
15036,
62,
49607,
737,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
264,
21287,
62,
19119,
7,
6551,
28,
14202,
11,
3915,
28,
14202,
11,
300,
81,
28,
62,
35067,
11,
266,
67,
28,
62,
35067,
11,
6811,
1000,
62,
9744,
28,
62,
35067,
11,
10651,
62,
49607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
10260,
2163,
329,
520,
5374,
3477,
17701,
1153,
2935,
1087,
357,
10305,
38,
8,
6436,
7509,
13,
628,
220,
220,
220,
632,
5992,
262,
19590,
1262,
3712,
628,
220,
220,
220,
220,
3463,
796,
3463,
532,
4673,
62,
4873,
1635,
31312,
628,
220,
220,
220,
1002,
3463,
318,
286,
7559,
808,
62,
82,
29572,
15506,
6143,
2099,
11,
198,
220,
220,
220,
691,
262,
5752,
24314,
3025,
36525,
1656,
287,
3915,
13,
521,
1063,
389,
6153,
3712,
628,
220,
220,
220,
220,
329,
5752,
287,
31312,
13,
521,
1063,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
3463,
58,
808,
60,
796,
3463,
58,
808,
60,
532,
4673,
62,
4873,
1635,
31312,
58,
808,
60,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
40085,
7509,
62,
404,
13,
535,
25,
43,
23148,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
3463,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
198,
220,
220,
220,
3915,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
17701,
1153,
198,
220,
220,
220,
300,
81,
1058,
12178,
11,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
18252,
2494,
198,
220,
220,
220,
266,
67,
1058,
12178,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
14331,
22119,
16339,
902,
262,
9432,
2163,
351,
257,
3218,
1634,
3381,
326,
23634,
4340,
1588,
19590,
13,
383,
7389,
16252,
351,
262,
6616,
286,
262,
14735,
286,
1123,
3463,
13,
198,
220,
220,
220,
6811,
1000,
62,
9744,
1058,
12178,
11,
11902,
11,
4277,
28,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1874,
38765,
31312,
284,
3915,
796,
6811,
1000,
62,
9744,
9,
9744,
13,
198,
220,
220,
220,
10651,
62,
49607,
1058,
12178,
11,
11902,
11,
4277,
10779,
16,
198,
220,
220,
220,
220,
220,
220,
220,
42512,
31312,
284,
262,
2837,
286,
25915,
15036,
62,
49607,
11,
10651,
62,
49607,
60,
1002,
10651,
62,
49607,
19841,
657,
11,
31312,
45013,
318,
2900,
572,
13,
3915,
796,
3509,
7,
1084,
7,
9744,
11,
10651,
62,
49607,
828,
532,
15036,
62,
49607,
737,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
264,
17225,
1868,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
264,
17225,
1868,
286,
2124,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
331,
796,
352,
1220,
357,
16,
1343,
1033,
32590,
87,
4008,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
82,
17225,
1868,
15506,
5072,
318,
1464,
15715,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
15377,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
1051,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
1051,
286,
262,
5128,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
1051,
26933,
12,
17,
11,
657,
11,
513,
12962,
796,
25915,
16,
11,
657,
11,
352,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
12683,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
1051,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
1051,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
26429,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
7813,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
262,
5002,
12,
3083,
264,
500,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5128,
815,
307,
287,
2511,
1547,
357,
25,
11018,
25,
63,
17,
59,
14415,
63,
2511,
21767,
11470,
7370,
737,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
7813,
26933,
15,
11,
3467,
14415,
14,
19,
11,
3467,
14415,
14,
17,
12962,
796,
685,
15,
11,
657,
13,
24038,
11,
352,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
31369,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
7813,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
7813,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
3510,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
7813,
71,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
8718,
65,
4160,
264,
500,
286,
262,
5128,
7177,
11,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
7813,
71,
7,
87,
8,
796,
657,
13,
20,
59,
22355,
7,
11201,
7,
87,
8,
532,
1033,
32590,
87,
4008,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
31369,
71,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
7813,
71,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
7813,
71,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
1264,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
16416,
7,
7890,
28,
14202,
11,
2221,
28,
62,
35067,
11,
886,
28,
62,
35067,
11,
2239,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
50,
677,
274,
257,
3814,
286,
262,
7177,
13,
628,
220,
220,
220,
11485,
3465,
3712,
7559,
31476,
15506,
318,
39224,
13,
5765,
7559,
48369,
15506,
2427,
13,
628,
220,
220,
220,
770,
2163,
5860,
257,
26790,
7177,
1022,
262,
36525,
1813,
198,
220,
220,
220,
416,
4600,
27471,
63,
290,
4600,
437,
63,
351,
262,
11188,
4600,
9662,
44646,
628,
220,
220,
220,
1114,
281,
5128,
7177,
286,
7559,
43358,
16193,
67,
62,
15,
11,
288,
62,
16,
11,
2644,
11,
288,
62,
77,
12,
16,
8,
15506,
11,
198,
220,
220,
220,
16416,
4905,
351,
7559,
27471,
16193,
65,
62,
15,
11,
275,
62,
16,
986,
65,
62,
76,
12,
16,
8,
15506,
11,
198,
220,
220,
220,
7559,
437,
16193,
68,
62,
15,
11,
304,
62,
16,
11,
2644,
11,
304,
62,
76,
12,
16,
8,
15506,
11,
290,
7559,
9662,
16193,
82,
62,
15,
11,
264,
62,
16,
11,
2644,
11,
264,
62,
76,
12,
16,
8,
15506,
11,
198,
220,
220,
220,
810,
285,
19841,
299,
11,
2482,
287,
281,
7177,
351,
262,
5485,
198,
220,
220,
220,
11592,
91,
68,
62,
15,
12,
65,
62,
15,
91,
14,
91,
82,
62,
15,
91,
11,
2644,
11,
930,
68,
62,
76,
12,
16,
12,
65,
62,
76,
12,
16,
91,
14,
91,
82,
62,
76,
12,
16,
91,
11,
288,
62,
76,
11,
2644,
11,
288,
62,
77,
12,
16,
8,
15506,
13,
628,
220,
220,
220,
383,
7186,
7177,
338,
1635,
74,
9,
12,
400,
15793,
4909,
4847,
198,
220,
220,
220,
422,
262,
1635,
74,
9,
12,
400,
15793,
286,
262,
5128,
7177,
3599,
198,
220,
220,
220,
422,
6376,
7559,
65,
62,
74,
15506,
357,
259,
5731,
8,
351,
2239,
7559,
82,
62,
74,
15506,
198,
220,
220,
220,
1566,
8978,
7559,
68,
62,
74,
15506,
357,
41195,
737,
628,
220,
220,
220,
1002,
262,
1635,
74,
9,
12,
400,
4847,
389,
4600,
14202,
63,
287,
262,
8379,
286,
4600,
27471,
47671,
4600,
437,
47671,
198,
220,
220,
220,
290,
4600,
9662,
47671,
262,
1708,
3896,
481,
307,
973,
284,
900,
4277,
3815,
13,
198,
220,
220,
220,
1002,
4600,
82,
62,
74,
63,
318,
4600,
14202,
47671,
900,
4600,
82,
62,
74,
28,
16,
44646,
1002,
4600,
82,
62,
74,
1875,
657,
47671,
900,
4600,
65,
62,
74,
28,
15,
47671,
4600,
68,
62,
74,
28,
67,
62,
74,
63,
26,
198,
220,
220,
220,
2073,
11,
900,
4600,
65,
62,
74,
28,
67,
62,
74,
12,
16,
47671,
4600,
68,
62,
74,
10779,
16,
44646,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
48369,
15506,
5072,
8338,
319,
6143,
3858,
286,
17311,
628,
220,
220,
220,
532,
16416,
7,
6359,
81,
8,
796,
269,
27891,
198,
220,
220,
220,
532,
4306,
11,
7559,
48369,
15506,
18616,
5072,
351,
4277,
6143,
628,
220,
220,
220,
11485,
3465,
3712,
1649,
5128,
1366,
6143,
2099,
318,
269,
27891,
11,
340,
691,
6971,
198,
220,
220,
220,
2239,
16193,
828,
393,
2239,
16193,
14202,
11,
828,
393,
2239,
16193,
16,
35751,
284,
7716,
257,
269,
27891,
5072,
13,
198,
220,
220,
220,
1114,
584,
2239,
11507,
3815,
11,
340,
8953,
736,
284,
49289,
198,
220,
220,
220,
257,
15715,
11192,
273,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
2124,
796,
16410,
220,
352,
1539,
220,
220,
362,
1539,
220,
220,
513,
1539,
220,
220,
604,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
220,
642,
1539,
220,
220,
718,
1539,
220,
220,
767,
1539,
220,
220,
807,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
220,
860,
1539,
220,
838,
1539,
220,
1367,
1539,
220,
1105,
8183,
60,
628,
220,
220,
220,
220,
220,
16416,
7,
87,
11,
2221,
16193,
15,
11,
16,
828,
886,
16193,
17,
11,
19,
4008,
796,
16410,
362,
1539,
220,
513,
1539,
220,
604,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
718,
1539,
220,
767,
1539,
220,
807,
8183,
60,
198,
220,
220,
220,
220,
220,
16416,
7,
87,
11,
2221,
16193,
14202,
11,
657,
828,
886,
16193,
14202,
11,
513,
828,
2239,
16193,
12,
16,
11,
362,
4008,
796,
16410,
24,
1539,
1367,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
20,
1539,
220,
767,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
16,
1539,
220,
513,
8183,
60,
628,
198,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
6759,
8609,
62,
404,
13,
535,
25,
43,
28567,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
8090,
5128,
198,
220,
220,
220,
2221,
1058,
25959,
7,
83,
29291,
828,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
3599,
36525,
329,
262,
16416,
4905,
11,
6971,
4633,
36525,
13,
198,
220,
220,
220,
886,
1058,
25959,
7,
83,
29291,
828,
2672,
198,
220,
220,
220,
220,
220,
220,
220,
7464,
36525,
329,
262,
16416,
4905,
11,
6971,
4633,
36525,
13,
198,
220,
220,
220,
2239,
1058,
25959,
7,
83,
29291,
828,
11902,
11,
4277,
28,
21737,
198,
220,
220,
220,
220,
220,
220,
220,
2239,
329,
262,
16416,
4905,
11,
6971,
4633,
3815,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
19862,
17034,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
6616,
12,
15763,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
3467,
5239,
26224,
90,
31166,
17034,
92,
7,
87,
8,
796,
3467,
31166,
17034,
90,
87,
92,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
19862,
17034,
26933,
19,
11,
860,
11,
1467,
12962,
796,
685,
17,
11,
513,
11,
604,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
31166,
17034,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
19862,
17034,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
19862,
17034,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
20,
2414,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
6616,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
5002,
12,
3083,
44345,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
6616,
7,
87,
8,
796,
2124,
61,
17,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
6616,
26933,
17,
11,
513,
11,
604,
12962,
796,
685,
19,
11,
860,
11,
1467,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
23415,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
6616,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
6616,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
220,
220,
220,
532,
6616,
7,
6359,
81,
8,
796,
269,
27891,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
20,
3901,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2245,
62,
49607,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
1273,
2840,
31312,
29964,
13,
628,
220,
220,
220,
520,
2840,
262,
22425,
31312,
286,
262,
17311,
422,
17609,
832,
428,
10088,
198,
220,
220,
220,
287,
262,
19528,
4571,
13,
554,
584,
2456,
11,
428,
10088,
15174,
262,
10156,
198,
220,
220,
220,
286,
663,
17311,
284,
307,
2077,
656,
1848,
329,
14492,
3915,
2334,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
410,
16,
796,
685,
16,
11,
362,
60,
198,
220,
220,
220,
220,
220,
410,
17,
796,
685,
15,
11,
352,
60,
198,
220,
220,
220,
220,
220,
257,
796,
35748,
10786,
64,
11537,
198,
220,
220,
220,
220,
220,
275,
796,
35748,
10786,
65,
11537,
198,
220,
220,
220,
220,
220,
275,
62,
11338,
62,
9744,
796,
2245,
62,
49607,
7,
18,
1635,
275,
8,
198,
220,
220,
220,
220,
220,
2994,
796,
6889,
43,
793,
7,
65,
62,
11338,
62,
9744,
1343,
257,
8,
628,
220,
220,
220,
220,
220,
3121,
273,
796,
2994,
13,
36439,
62,
21653,
7,
49464,
28,
36166,
22784,
257,
16193,
16,
11,
17,
828,
275,
16193,
16,
11,
17,
4008,
198,
220,
220,
220,
220,
220,
3121,
273,
13,
11813,
7,
271,
62,
27432,
28,
17821,
11,
257,
28,
85,
16,
11,
275,
28,
85,
17,
8,
198,
220,
220,
220,
220,
220,
3121,
273,
13,
22915,
82,
198,
220,
220,
220,
220,
220,
685,
352,
13,
220,
642,
8183,
628,
220,
220,
220,
220,
220,
3121,
273,
13,
1891,
904,
3419,
198,
220,
220,
220,
220,
220,
3121,
273,
13,
9744,
62,
3258,
592,
198,
220,
220,
220,
220,
220,
685,
657,
13,
220,
657,
8183,
198,
220,
220,
220,
220,
220,
685,
352,
13,
220,
352,
8183,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
23055,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
2160,
7,
7890,
28,
14202,
11,
16488,
28,
62,
35067,
11,
1394,
67,
12078,
28,
62,
35067,
11,
19607,
28,
62,
35067,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
262,
2160,
286,
7177,
4847,
625,
1813,
34197,
13,
628,
220,
220,
220,
11485,
5740,
3712,
628,
220,
220,
220,
220,
220,
4600,
16345,
63,
290,
4600,
16345,
62,
22704,
63,
389,
7548,
13,
198,
220,
220,
220,
220,
220,
1114,
299,
67,
18747,
286,
269,
27891,
6143,
2099,
30114,
341,
1863,
16488,
657,
290,
16488,
352,
318,
4855,
13,
198,
220,
220,
220,
220,
220,
25700,
1394,
67,
12078,
393,
19607,
284,
6407,
481,
2728,
257,
2121,
1891,
284,
15715,
10088,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
1366,
796,
16410,
58,
16,
11,
17,
38430,
17,
11,
18,
38430,
16,
11,
18,
60,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16410,
16,
11,
19,
38430,
19,
11,
18,
38430,
20,
11,
17,
60,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16410,
22,
11,
16,
38430,
22,
11,
17,
38430,
22,
11,
18,
11907,
60,
628,
220,
220,
220,
220,
220,
2160,
7,
7890,
11,
16488,
28,
16,
8,
198,
220,
220,
220,
220,
220,
16410,
220,
604,
13,
220,
220,
807,
8183,
198,
220,
220,
220,
220,
220,
220,
685,
838,
13,
220,
220,
860,
8183,
198,
220,
220,
220,
220,
220,
220,
685,
2310,
13,
220,
220,
718,
8183,
60,
628,
220,
220,
220,
220,
220,
2160,
7,
7890,
11,
16488,
41888,
16,
11,
17,
12962,
198,
220,
220,
220,
220,
220,
685,
1105,
13,
220,
678,
13,
220,
2681,
8183,
628,
220,
220,
220,
220,
220,
1366,
796,
16410,
16,
11,
17,
11,
15,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
18,
11,
15,
11,
16,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
19,
11,
16,
11,
15,
11907,
628,
220,
220,
220,
220,
220,
269,
27891,
796,
3350,
62,
35350,
7,
7890,
11,
705,
6359,
81,
11537,
628,
220,
220,
220,
220,
220,
2160,
7,
6359,
81,
11,
16488,
28,
15,
8,
198,
220,
220,
220,
220,
220,
685,
807,
13,
220,
513,
13,
220,
352,
8183,
628,
220,
220,
220,
220,
220,
2160,
7,
6359,
81,
11,
16488,
28,
16,
8,
198,
220,
220,
220,
220,
220,
685,
513,
13,
220,
604,
13,
220,
642,
8183,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
36654,
2701,
62,
445,
7234,
62,
404,
62,
8367,
13,
535,
25,
43,
5332,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
198,
220,
220,
220,
16488,
1058,
25959,
7,
83,
29291,
828,
11902,
11,
4277,
28,
21737,
198,
220,
220,
220,
220,
220,
220,
220,
383,
16488,
393,
34197,
1863,
543,
284,
1620,
262,
7741,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
4277,
11,
4600,
22704,
28,
3419,
47671,
481,
24061,
625,
477,
4847,
656,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16578,
283,
7177,
351,
5485,
4600,
7,
16,
35751,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
22704,
63,
318,
493,
11,
257,
7741,
318,
6157,
319,
257,
1948,
16488,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
22704,
63,
318,
257,
46545,
286,
493,
82,
11,
257,
7741,
318,
6157,
319,
477,
262,
34197,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7368,
287,
262,
46545,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
1069,
9152,
63,
318,
2081,
11,
7741,
481,
307,
6157,
319,
262,
34197,
326,
389,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5626,
287,
16488,
2427,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
36183,
3815,
1724,
6376,
278,
422,
826,
284,
1364,
13,
198,
220,
220,
220,
1394,
67,
12078,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
428,
318,
900,
284,
4600,
17821,
47671,
262,
5322,
34197,
389,
1364,
287,
262,
1255,
355,
15793,
351,
2546,
530,
13,
198,
220,
220,
220,
19607,
1058,
25131,
11,
11902,
11,
4277,
28,
15,
198,
220,
220,
220,
220,
220,
220,
220,
10127,
284,
1620,
7741,
319,
16488,
326,
389,
5626,
287,
16488,
2427,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
25706,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
7293,
1769,
262,
5002,
12,
3083,
13875,
298,
286,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
5128,
815,
307,
287,
2511,
1547,
357,
25,
11018,
25,
63,
17,
59,
14415,
63,
2511,
21767,
11470,
7370,
737,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
25706,
26933,
15,
11,
3467,
14415,
14,
19,
11,
3467,
14415,
14,
17,
12962,
796,
685,
15,
11,
352,
11,
532,
10745,
60,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
38006,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
25706,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
25706,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
5999,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
25706,
71,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
35561,
262,
8718,
65,
4160,
13875,
298,
286,
262,
5128,
7177,
11,
29231,
5002,
12,
3083,
13,
628,
220,
220,
220,
11485,
10688,
3712,
198,
220,
220,
220,
220,
220,
220,
25706,
71,
7,
87,
8,
796,
7813,
71,
7,
87,
8,
1220,
269,
3768,
7,
87,
8,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
38006,
71,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
25706,
71,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
25706,
71,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
2213,
328,
13,
535,
25,
43,
24409,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
40122,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
13615,
262,
5002,
12,
3083,
40122,
515,
1988,
286,
262,
5128,
13,
628,
220,
220,
220,
383,
40122,
515,
1988,
286,
262,
16578,
283,
2124,
318,
262,
16936,
18253,
1312,
543,
318,
5699,
284,
198,
220,
220,
220,
6632,
621,
2124,
318,
13,
554,
1790,
11,
262,
13390,
282,
636,
286,
262,
4488,
1271,
2124,
318,
25148,
13,
628,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
40122,
26933,
12,
17,
13,
16,
11,
532,
16,
13,
24,
11,
352,
13,
20,
11,
352,
13,
24,
11,
362,
13,
16,
12962,
796,
25915,
17,
1539,
532,
16,
1539,
220,
352,
1539,
220,
352,
1539,
220,
362,
8183,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
2213,
19524,
15506,
5072,
8338,
2402,
262,
5128,
6143,
2099,
25,
628,
220,
220,
220,
220,
220,
220,
532,
40122,
7,
12286,
8,
796,
4277,
198,
220,
220,
220,
220,
220,
220,
532,
40122,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
628,
628,
220,
220,
220,
2896,
1389,
287,
12351,
14,
46616,
14,
83,
22854,
14,
68,
10671,
3083,
62,
403,
560,
62,
404,
62,
35487,
13,
535,
25,
43,
35126,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
7177,
13,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
4299,
1976,
27498,
62,
2339,
7,
7890,
28,
14202,
11,
503,
28,
14202,
11,
1438,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
374,
37811,
13615,
281,
7177,
286,
1976,
27498,
351,
262,
976,
5485,
290,
2099,
198,
220,
220,
220,
355,
262,
5128,
7177,
13,
628,
220,
220,
220,
383,
6143,
2099,
286,
7559,
9107,
418,
62,
2339,
15506,
5072,
8338,
319,
262,
6143,
2099,
286,
262,
5128,
628,
220,
220,
220,
532,
1976,
27498,
62,
2339,
7,
808,
62,
82,
29572,
8,
796,
5752,
62,
82,
29572,
198,
220,
220,
220,
532,
1976,
27498,
62,
2339,
7,
6359,
81,
8,
796,
269,
27891,
198,
220,
220,
220,
532,
1976,
27498,
62,
2339,
7,
12286,
8,
796,
4277,
628,
220,
220,
220,
21066,
3712,
628,
220,
220,
220,
220,
220,
2124,
796,
16410,
352,
1539,
220,
352,
1539,
220,
352,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
352,
1539,
220,
352,
1539,
220,
352,
8183,
60,
628,
220,
220,
220,
220,
220,
1976,
27498,
62,
2339,
7,
87,
8,
796,
16410,
657,
1539,
220,
657,
1539,
220,
657,
13,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
657,
1539,
220,
657,
1539,
220,
657,
8183,
60,
628,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1366,
1058,
25524,
19182,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5128,
628,
220,
220,
220,
503,
1058,
25524,
19182,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
25524,
19182,
284,
1745,
262,
1255,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
503,
1058,
25524,
19182,
393,
1351,
286,
25524,
3163,
20477,
198,
220,
220,
220,
220,
220,
220,
220,
383,
5072,
286,
428,
2163,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
357,
15,
35751,
198,
198,
834,
439,
834,
796,
37250,
20180,
54,
786,
13065,
3256,
705,
8937,
3256,
705,
324,
321,
62,
19119,
3256,
705,
2860,
62,
77,
3256,
705,
283,
535,
418,
3256,
705,
283,
535,
3768,
3256,
705,
5605,
31369,
3256,
705,
5605,
31369,
71,
3256,
705,
283,
310,
272,
3256,
705,
283,
310,
272,
71,
3256,
705,
2701,
62,
35350,
3256,
705,
344,
346,
3256,
705,
15036,
3256,
705,
6966,
3256,
705,
66,
3768,
3256,
705,
13500,
6037,
3256,
705,
26518,
3256,
705,
68,
10671,
3083,
62,
2860,
3256,
705,
68,
10671,
3083,
62,
7146,
3256,
705,
68,
10671,
3083,
62,
76,
377,
3256,
705,
68,
10671,
3083,
62,
7266,
3256,
705,
11201,
3256,
705,
1069,
4426,
16,
3256,
705,
13049,
3256,
705,
28300,
3256,
705,
701,
45895,
62,
19119,
3256,
705,
28483,
2611,
3256,
705,
70,
6475,
282,
77,
3256,
705,
6404,
3256,
705,
6404,
940,
3256,
705,
6404,
16,
79,
3256,
705,
6404,
17,
3256,
705,
15883,
62,
22462,
3256,
705,
32604,
3256,
705,
31591,
3256,
705,
27237,
3256,
705,
6335,
1547,
3256,
705,
260,
2290,
3256,
705,
1186,
391,
3256,
705,
22272,
3256,
705,
744,
3256,
705,
3808,
80,
17034,
3256,
705,
82,
21287,
62,
32542,
62,
19119,
3256,
705,
82,
21287,
62,
19119,
3256,
705,
82,
17225,
1868,
3256,
705,
12683,
3256,
705,
31369,
3256,
705,
31369,
71,
3256,
705,
48369,
3256,
705,
31166,
17034,
3256,
705,
23415,
3256,
705,
11338,
62,
49607,
3256,
705,
16345,
3256,
705,
38006,
3256,
705,
38006,
71,
3256,
705,
2213,
19524,
3256,
705,
9107,
418,
62,
2339,
20520
] | 2.514054 | 21,311 |
# Module for platform specific stuff.
from . import map_platform_specifics
| [
2,
19937,
329,
3859,
2176,
3404,
13,
198,
6738,
764,
1330,
3975,
62,
24254,
62,
11423,
82,
628
] | 4.222222 | 18 |
from rest_framework import viewsets
from rest_framework import filters
from rest_framework.permissions import IsAuthenticated
from rest_framework.pagination import PageNumberPagination
from .serializers import ItemSerializer
from .models import Item
class CustomSearchFilter(filters.SearchFilter):
"""
Filter that only allows users to see their own objects.
"""
class ItemViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows organizations to be viewed or edited.
"""
queryset = Item.objects.all().order_by('_id')
serializer_class = ItemSerializer
permission_classes = [IsAuthenticated]
http_method_names = ['get']
# pagination
pagination_class = ItemResultsSetPagination
# search and filter
filter_backends = [filters.SearchFilter, CustomSearchFilter]
search_fields = ['Location', 'Zone', 'Plant', 'Part_Number', 'Part_Description',
'Serial_Number', 'Condition', 'Category', 'Owner', 'Unit_of_Measure']
| [
6738,
1334,
62,
30604,
1330,
5009,
1039,
198,
6738,
1334,
62,
30604,
1330,
16628,
198,
6738,
1334,
62,
30604,
13,
525,
8481,
1330,
1148,
47649,
3474,
198,
6738,
1334,
62,
30604,
13,
79,
363,
1883,
1330,
7873,
15057,
47,
363,
1883,
198,
198,
6738,
764,
46911,
11341,
1330,
9097,
32634,
7509,
198,
6738,
764,
27530,
1330,
9097,
628,
628,
198,
4871,
8562,
18243,
22417,
7,
10379,
1010,
13,
18243,
22417,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
25853,
326,
691,
3578,
2985,
284,
766,
511,
898,
5563,
13,
198,
220,
220,
220,
37227,
628,
198,
4871,
9097,
7680,
7248,
7,
1177,
28709,
13,
17633,
7680,
7248,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7824,
36123,
326,
3578,
5745,
284,
307,
9569,
393,
13012,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
42517,
893,
316,
796,
9097,
13,
48205,
13,
439,
22446,
2875,
62,
1525,
10786,
62,
312,
11537,
198,
220,
220,
220,
11389,
7509,
62,
4871,
796,
9097,
32634,
7509,
198,
220,
220,
220,
7170,
62,
37724,
796,
685,
3792,
47649,
3474,
60,
198,
220,
220,
220,
2638,
62,
24396,
62,
14933,
796,
37250,
1136,
20520,
198,
220,
220,
220,
1303,
42208,
1883,
198,
220,
220,
220,
42208,
1883,
62,
4871,
796,
9097,
25468,
7248,
47,
363,
1883,
198,
220,
220,
220,
1303,
2989,
290,
8106,
198,
220,
220,
220,
8106,
62,
1891,
2412,
796,
685,
10379,
1010,
13,
18243,
22417,
11,
8562,
18243,
22417,
60,
198,
220,
220,
220,
2989,
62,
25747,
796,
37250,
14749,
3256,
705,
26961,
3256,
705,
3646,
415,
3256,
705,
7841,
62,
15057,
3256,
705,
7841,
62,
11828,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
32634,
62,
15057,
3256,
705,
48362,
3256,
705,
27313,
3256,
705,
42419,
3256,
705,
26453,
62,
1659,
62,
47384,
20520,
198
] | 3.171429 | 315 |
#!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
import argparse
from textwrap import dedent
from glob import glob
import matlab2cpp
hstring = "*** Matlab2cpp version " + str(matlab2cpp.__version__) + " ***\n\n" + """\
The toolbox frontend of the Matlab2cpp library. Use this to try to do automatic
and semi-automatic translation. The program will create files with the same
name as the input, but with various extra extensions. Scripts will receive the
extension `.cpp`, headers and modules `.hpp`. A file containing data type and
header information will be stored in a `.py` file. Any errors will be stored in
`.log`.
"""
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description=dedent(hstring))
parser.add_argument("filename",
help="File containing valid Matlab code.").completer=\
lambda prefix, **kws: glob("*.m")
parser.add_argument("-o", '--original', action="store_true",
help="Include original Matlab code line as comment before the C++ translation of the code line")
parser.add_argument("-c", '--comments', action="store_true",
help="""\
Include Matlab comments in the generated C++ files.""")
parser.add_argument("-s", '--suggest', action="store_true",
help="""\
Automatically populate the `<filename>.py` file with datatype with suggestions
if possible.""")
parser.add_argument("-S", '--matlab-suggest', action="store_true",
help="""Creates a folder m2cpp_temp. In the folder the matlab file(s) to be translated are also put. \
These matlab file(s) are slightly modified so that they output data-type information of the variables \
to file(s). This output can then be used to set the datatypes for the translation.""")
parser.add_argument("-r", '--reset', action="store_true",
help="""\
Ignore the content of `<filename>.py` and make a fresh translation.""")
parser.add_argument("-t", '--tree', action="store_true",
help="""\
Print the underlying node tree. Each line in the output represents a node and
is formated as follows:
`<codeline> <position> <class> <backend> <datatype> <name> <translation>`
The indentation represents the tree structure.
""")
parser.add_argument("-T", "--tree-full", action="store_true",
help="""\
Same as -t, but the full node tree, but include meta-nodes.""")
parser.add_argument("-d", '--disp', action="store_true",
help="""\
Print out the progress of the translation process.""")
parser.add_argument("-p", "--paths_file", type=str, dest="paths_file",
help="""\
Flag and paths_file (-p path_to_pathsfile). m2cpp will look for matlab files in the location specified \
in the paths_file""")
parser.add_argument("-omp", '--enable-omp', action="store_true",
help="""\
OpenMP code is inserted for Parfor and loops marked with the pragma %%#PARFOR (in Matlab code) when this \
flag is set.""")
parser.add_argument("-tbb", '--enable-tbb', action="store_true",
help="""\
TBB code is inserted for Parfor and loops marked with the pragma %%#PARFOR (in Matlab code) when this flag is set.""")
parser.add_argument("-ref", '--reference', action="store_true",
help="""\
For the generated C++ code, function input parameters are "copied by value" as default. With this flag some \
input parameters in the generated code can be const references. There can be some performance advantage of using
const references instead of "copied by value". Note that Matlab "copies by value". \
The Matlab code you try to translate to C++ code could try read as well as write to this input variable. \
The code generator doesn't perform an analysis to detect this and then "copy by value" for this variable.""")
parser.add_argument("-l", '--line', type=int, dest="line",
help="Only display code related to code line number `<line>`.")
parser.add_argument("-n", '--nargin', action="store_true",
help="Don't remove if and switch branches which use nargin variable.")
try:
import argcomplete
argcomplete.autocomplete(parser)
except:
pass
if __name__ == "__main__":
args = parser.parse_args()
matlab2cpp.main(args)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
350,
56,
4221,
1340,
62,
1503,
38,
41335,
9328,
62,
11380,
198,
198,
11748,
1822,
29572,
198,
6738,
2420,
37150,
1330,
4648,
298,
198,
6738,
15095,
1330,
15095,
198,
11748,
2603,
23912,
17,
20322,
198,
198,
71,
8841,
796,
366,
8162,
6550,
23912,
17,
20322,
2196,
366,
1343,
965,
7,
6759,
23912,
17,
20322,
13,
834,
9641,
834,
8,
1343,
366,
17202,
59,
77,
59,
77,
1,
1343,
37227,
59,
198,
464,
2891,
3524,
2166,
437,
286,
262,
6550,
23912,
17,
20322,
5888,
13,
220,
5765,
428,
284,
1949,
284,
466,
11353,
198,
392,
10663,
12,
37800,
11059,
13,
220,
383,
1430,
481,
2251,
3696,
351,
262,
976,
198,
3672,
355,
262,
5128,
11,
475,
351,
2972,
3131,
18366,
13,
220,
12327,
82,
481,
3328,
262,
198,
2302,
3004,
4600,
13,
20322,
47671,
24697,
290,
13103,
4600,
13,
71,
381,
44646,
220,
317,
2393,
7268,
1366,
2099,
290,
198,
25677,
1321,
481,
307,
8574,
287,
257,
4600,
13,
9078,
63,
2393,
13,
4377,
8563,
481,
307,
8574,
287,
198,
44646,
6404,
44646,
198,
37811,
628,
198,
48610,
796,
1822,
29572,
13,
28100,
1713,
46677,
7,
198,
220,
220,
220,
1296,
1436,
62,
4871,
28,
853,
29572,
13,
27369,
11828,
22087,
8479,
1436,
11,
198,
220,
220,
220,
6764,
28,
9395,
298,
7,
71,
8841,
4008,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
34345,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
8979,
7268,
4938,
6550,
23912,
2438,
526,
737,
785,
1154,
353,
28,
59,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37456,
21231,
11,
12429,
74,
18504,
25,
15095,
7203,
24620,
76,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
78,
1600,
705,
438,
14986,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
818,
9152,
2656,
6550,
23912,
2438,
1627,
355,
2912,
878,
262,
327,
4880,
11059,
286,
262,
2438,
1627,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
66,
1600,
705,
438,
15944,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
818,
9152,
6550,
23912,
3651,
287,
262,
7560,
327,
4880,
3696,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
82,
1600,
705,
438,
47811,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
38062,
4142,
48040,
262,
4600,
27,
34345,
28401,
9078,
63,
2393,
351,
4818,
265,
2981,
351,
11776,
198,
361,
1744,
32203,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
50,
1600,
705,
438,
6759,
23912,
12,
47811,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
16719,
274,
257,
9483,
285,
17,
20322,
62,
29510,
13,
554,
262,
9483,
262,
2603,
23912,
2393,
7,
82,
8,
284,
307,
14251,
389,
635,
1234,
13,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
2312,
2603,
23912,
2393,
7,
82,
8,
389,
4622,
9518,
523,
326,
484,
5072,
1366,
12,
4906,
1321,
286,
262,
9633,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
284,
2393,
7,
82,
737,
770,
5072,
460,
788,
307,
973,
284,
900,
262,
4818,
265,
9497,
329,
262,
11059,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
81,
1600,
705,
438,
42503,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
32916,
382,
262,
2695,
286,
4600,
27,
34345,
28401,
9078,
63,
290,
787,
257,
4713,
11059,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
83,
1600,
705,
438,
21048,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
18557,
262,
10238,
10139,
5509,
13,
5501,
1627,
287,
262,
5072,
6870,
257,
10139,
290,
198,
271,
1296,
515,
355,
5679,
25,
198,
198,
63,
27,
19815,
4470,
29,
1279,
9150,
29,
1279,
4871,
29,
1279,
1891,
437,
29,
1279,
19608,
265,
2981,
29,
1279,
3672,
29,
1279,
41519,
29,
63,
198,
198,
464,
33793,
341,
6870,
262,
5509,
4645,
13,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
51,
1600,
366,
438,
21048,
12,
12853,
1600,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
30556,
355,
532,
83,
11,
475,
262,
1336,
10139,
5509,
11,
475,
2291,
13634,
12,
77,
4147,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
67,
1600,
705,
438,
6381,
79,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
18557,
503,
262,
4371,
286,
262,
11059,
1429,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
79,
1600,
366,
438,
6978,
82,
62,
7753,
1600,
2099,
28,
2536,
11,
2244,
2625,
6978,
82,
62,
7753,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
34227,
290,
13532,
62,
7753,
13841,
79,
3108,
62,
1462,
62,
6978,
82,
7753,
737,
285,
17,
20322,
481,
804,
329,
2603,
23912,
3696,
287,
262,
4067,
7368,
3467,
198,
259,
262,
13532,
62,
7753,
15931,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
3361,
1600,
705,
438,
21633,
12,
3361,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
11505,
7378,
2438,
318,
18846,
329,
2547,
1640,
290,
23607,
7498,
351,
262,
23864,
2611,
43313,
2,
27082,
13775,
357,
259,
6550,
23912,
2438,
8,
618,
428,
3467,
198,
32109,
318,
900,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
83,
11848,
1600,
705,
438,
21633,
12,
83,
11848,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
51,
15199,
2438,
318,
18846,
329,
2547,
1640,
290,
23607,
7498,
351,
262,
23864,
2611,
43313,
2,
27082,
13775,
357,
259,
6550,
23912,
2438,
8,
618,
428,
6056,
318,
900,
32203,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
5420,
1600,
705,
438,
35790,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
15931,
59,
198,
1890,
262,
7560,
327,
4880,
2438,
11,
2163,
5128,
10007,
389,
366,
22163,
798,
416,
1988,
1,
355,
4277,
13,
2080,
428,
6056,
617,
3467,
198,
15414,
10007,
287,
262,
7560,
2438,
460,
307,
1500,
10288,
13,
1318,
460,
307,
617,
2854,
4621,
286,
1262,
198,
9979,
10288,
2427,
286,
366,
22163,
798,
416,
1988,
1911,
5740,
326,
6550,
23912,
366,
22163,
444,
416,
1988,
1911,
3467,
198,
464,
6550,
23912,
2438,
345,
1949,
284,
15772,
284,
327,
4880,
2438,
714,
1949,
1100,
355,
880,
355,
3551,
284,
428,
5128,
7885,
13,
3467,
198,
464,
2438,
17301,
1595,
470,
1620,
281,
3781,
284,
4886,
428,
290,
788,
366,
30073,
416,
1988,
1,
329,
428,
7885,
32203,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
75,
1600,
705,
438,
1370,
3256,
2099,
28,
600,
11,
2244,
2625,
1370,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
10049,
3359,
2438,
3519,
284,
2438,
1627,
1271,
4600,
27,
1370,
29,
63,
19570,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
12,
77,
1600,
705,
438,
77,
853,
259,
3256,
2223,
2625,
8095,
62,
7942,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1037,
2625,
3987,
470,
4781,
611,
290,
5078,
13737,
543,
779,
299,
853,
259,
7885,
19570,
628,
628,
198,
28311,
25,
198,
220,
220,
220,
1330,
1822,
20751,
198,
220,
220,
220,
1822,
20751,
13,
2306,
42829,
6677,
7,
48610,
8,
198,
16341,
25,
198,
220,
220,
220,
1208,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
26498,
796,
30751,
13,
29572,
62,
22046,
3419,
198,
220,
220,
220,
2603,
23912,
17,
20322,
13,
12417,
7,
22046,
8,
628
] | 3.037464 | 1,388 |
import torch
def rademacher(shape, gpu=True):
"""
Creates a random tensor of size [shape] under the Rademacher distribution (P(x=1) == P(x=-1) == 0.5)
"""
x = torch.empty(shape)
if gpu:
x = x.cuda()
x.random_(0, 2)
x[x == 0] = -1
return x
def second_directional_derivative(G, z, c, x, G_z, epsilon, w=None, Q=None):
"""
Computes the second directional derivative of G w.r.t. its input at z in the direction x
"""
if w is None: # Apply the Hessian Penalty in Z-space
return (G(z + x, c, Q=Q) - 2 * G_z + G(z - x, c, Q=Q)) / (epsilon ** 2)
else: # Apply it in W-space
return (G(z, c, w=w+x, Q=Q) - 2 * G_z + G(z, c, w=w-x, Q=Q)) / (epsilon ** 2)
def multi_layer_second_directional_derivative(G, z, c, x, G_z, epsilon, w=None, Q=None):
"""
Same as second_directional_derivative, but assumes G returns multiple outputs in a list
"""
if w is None:
_, G_to_x = G(z + x, c, return_bn=True, Q=Q)
_, G_from_x = G(z - x, c, return_bn=True, Q=Q)
else:
_, G_to_x = G(z, c, w=w+x, return_bn=True, Q=Q)
_, G_from_x = G(z, c, w=w-x, return_bn=True, Q=Q)
eps_sqr = epsilon ** 2
sdd = [(G2x - 2 * G_z_base + Gfx) / eps_sqr for G2x, G_z_base, Gfx in zip(G_to_x, G_z, G_from_x)]
return sdd
def hessian_penalty(G, z, c, w=None, G_z=None, k=2, epsilon=0.1, reduction=torch.mean,
multiple_layers=True, return_separately=False, Q=None):
"""
Version of the Hessian Penalty that allows taking the Hessian w.r.t. the w input instead of z
Note: w here refers to the coefficients for the learned directions in Q, it has nothing to do with W-space
as in StyleGAN, etc.
:param G: Function that maps z to either a tensor or a size-N list of tensors (activations)
:param z: (N, dim_z) input to G
:param c: Class label input to G (not regularized in this version of hessian penalty)
:param w: (N, ndirs) tensor that represents how far to move z in each of the ndirs directions stored in Q.
If specified, Hessian is taken w.r.t. w instead of w.r.t. z.
:param k: Number of Hessian directions to sample (must be >= 2)
:param G_z: Pre-cached G(z) computation (i.e., a size-N list)
:param epsilon: Amount to blur G before estimating Hessian (must be > 0)
:param reduction: Many-to-one function to reduce each pixel's individual hessian penalty into a final loss
:param multiple_layers: If True, G is expected to return a list of tensors that are all regularized jointly
:param return_separately: If True, returns hessian penalty for each layer separately, rather than combining them
:param Q: (ndirs, nz) matrix of directions (rows correspond to directions)
:return: A differentiable scalar (the hessian penalty), or a list of hessian penalties if return_separately is True
"""
if G_z is None:
G_z = G(z, c, w=w, return_bn=multiple_layers, Q=Q)
if multiple_layers:
G_z = G_z[1]
if w is not None:
xs = rademacher(torch.Size((k, *w.size()))) * epsilon
else:
xs = rademacher(torch.Size((k, *z.size()))) * epsilon
second_orders = []
for i in range(k):
x = xs[i]
if multiple_layers:
central_second_order = multi_layer_second_directional_derivative(G, z, c, x, G_z, epsilon, w=w, Q=Q)
else:
central_second_order = second_directional_derivative(G, z, c, x, G_z, epsilon, w=w, Q=Q)
second_orders.append(central_second_order)
if multiple_layers:
penalty = multi_stack_var_and_reduce(second_orders, reduction, return_separately)
else:
penalty = stack_var_and_reduce(second_orders, reduction)
return penalty
| [
11748,
28034,
628,
198,
4299,
2511,
368,
3493,
7,
43358,
11,
308,
19944,
28,
17821,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7921,
274,
257,
4738,
11192,
273,
286,
2546,
685,
43358,
60,
739,
262,
5325,
368,
3493,
6082,
357,
47,
7,
87,
28,
16,
8,
6624,
350,
7,
87,
10779,
16,
8,
6624,
657,
13,
20,
8,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2124,
796,
28034,
13,
28920,
7,
43358,
8,
198,
220,
220,
220,
611,
308,
19944,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
796,
2124,
13,
66,
15339,
3419,
198,
220,
220,
220,
2124,
13,
25120,
41052,
15,
11,
362,
8,
198,
220,
220,
220,
2124,
58,
87,
6624,
657,
60,
796,
532,
16,
198,
220,
220,
220,
1441,
2124,
628,
198,
4299,
1218,
62,
37295,
282,
62,
1082,
452,
876,
7,
38,
11,
1976,
11,
269,
11,
2124,
11,
402,
62,
89,
11,
304,
862,
33576,
11,
266,
28,
14202,
11,
1195,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3082,
1769,
262,
1218,
47424,
27255,
286,
402,
266,
13,
81,
13,
83,
13,
663,
5128,
379,
1976,
287,
262,
4571,
2124,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
266,
318,
6045,
25,
220,
1303,
27967,
262,
46305,
666,
41676,
287,
1168,
12,
13200,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
357,
38,
7,
89,
1343,
2124,
11,
269,
11,
1195,
28,
48,
8,
532,
362,
1635,
402,
62,
89,
1343,
402,
7,
89,
532,
2124,
11,
269,
11,
1195,
28,
48,
4008,
1220,
357,
538,
18217,
261,
12429,
362,
8,
198,
220,
220,
220,
2073,
25,
220,
1303,
27967,
340,
287,
370,
12,
13200,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
357,
38,
7,
89,
11,
269,
11,
266,
28,
86,
10,
87,
11,
1195,
28,
48,
8,
532,
362,
1635,
402,
62,
89,
1343,
402,
7,
89,
11,
269,
11,
266,
28,
86,
12,
87,
11,
1195,
28,
48,
4008,
1220,
357,
538,
18217,
261,
12429,
362,
8,
628,
198,
4299,
5021,
62,
29289,
62,
12227,
62,
37295,
282,
62,
1082,
452,
876,
7,
38,
11,
1976,
11,
269,
11,
2124,
11,
402,
62,
89,
11,
304,
862,
33576,
11,
266,
28,
14202,
11,
1195,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16766,
355,
1218,
62,
37295,
282,
62,
1082,
452,
876,
11,
475,
18533,
402,
5860,
3294,
23862,
287,
257,
1351,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
266,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
402,
62,
1462,
62,
87,
796,
402,
7,
89,
1343,
2124,
11,
269,
11,
1441,
62,
9374,
28,
17821,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
402,
62,
6738,
62,
87,
796,
402,
7,
89,
532,
2124,
11,
269,
11,
1441,
62,
9374,
28,
17821,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
402,
62,
1462,
62,
87,
796,
402,
7,
89,
11,
269,
11,
266,
28,
86,
10,
87,
11,
1441,
62,
9374,
28,
17821,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
402,
62,
6738,
62,
87,
796,
402,
7,
89,
11,
269,
11,
266,
28,
86,
12,
87,
11,
1441,
62,
9374,
28,
17821,
11,
1195,
28,
48,
8,
628,
220,
220,
220,
304,
862,
62,
31166,
81,
796,
304,
862,
33576,
12429,
362,
198,
220,
220,
220,
264,
1860,
796,
47527,
38,
17,
87,
532,
362,
1635,
402,
62,
89,
62,
8692,
1343,
402,
21373,
8,
1220,
304,
862,
62,
31166,
81,
329,
402,
17,
87,
11,
402,
62,
89,
62,
8692,
11,
402,
21373,
287,
19974,
7,
38,
62,
1462,
62,
87,
11,
402,
62,
89,
11,
402,
62,
6738,
62,
87,
15437,
198,
220,
220,
220,
1441,
264,
1860,
628,
628,
198,
4299,
339,
824,
666,
62,
3617,
6017,
7,
38,
11,
1976,
11,
269,
11,
266,
28,
14202,
11,
402,
62,
89,
28,
14202,
11,
479,
28,
17,
11,
304,
862,
33576,
28,
15,
13,
16,
11,
7741,
28,
13165,
354,
13,
32604,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3294,
62,
75,
6962,
28,
17821,
11,
1441,
62,
25512,
1286,
28,
25101,
11,
1195,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10628,
286,
262,
46305,
666,
41676,
326,
3578,
2263,
262,
46305,
666,
266,
13,
81,
13,
83,
13,
262,
266,
5128,
2427,
286,
1976,
198,
220,
220,
220,
5740,
25,
266,
994,
10229,
284,
262,
44036,
329,
262,
4499,
11678,
287,
1195,
11,
340,
468,
2147,
284,
466,
351,
370,
12,
13200,
198,
220,
220,
220,
355,
287,
17738,
45028,
11,
3503,
13,
628,
220,
220,
220,
1058,
17143,
402,
25,
15553,
326,
8739,
1976,
284,
2035,
257,
11192,
273,
393,
257,
2546,
12,
45,
1351,
286,
11192,
669,
357,
15791,
602,
8,
198,
220,
220,
220,
1058,
17143,
1976,
25,
357,
45,
11,
5391,
62,
89,
8,
5128,
284,
402,
198,
220,
220,
220,
1058,
17143,
269,
25,
5016,
6167,
5128,
284,
402,
357,
1662,
3218,
1143,
287,
428,
2196,
286,
339,
824,
666,
7389,
8,
198,
220,
220,
220,
1058,
17143,
266,
25,
357,
45,
11,
299,
15908,
82,
8,
11192,
273,
326,
6870,
703,
1290,
284,
1445,
1976,
287,
1123,
286,
262,
299,
15908,
82,
11678,
8574,
287,
1195,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
7368,
11,
46305,
666,
318,
2077,
266,
13,
81,
13,
83,
13,
266,
2427,
286,
266,
13,
81,
13,
83,
13,
1976,
13,
198,
220,
220,
220,
1058,
17143,
479,
25,
7913,
286,
46305,
666,
11678,
284,
6291,
357,
27238,
307,
18189,
362,
8,
198,
220,
220,
220,
1058,
17143,
402,
62,
89,
25,
3771,
12,
66,
2317,
402,
7,
89,
8,
29964,
357,
72,
13,
68,
1539,
257,
2546,
12,
45,
1351,
8,
198,
220,
220,
220,
1058,
17143,
304,
862,
33576,
25,
26308,
284,
23671,
402,
878,
39539,
46305,
666,
357,
27238,
307,
1875,
657,
8,
198,
220,
220,
220,
1058,
17143,
7741,
25,
4650,
12,
1462,
12,
505,
2163,
284,
4646,
1123,
17465,
338,
1981,
339,
824,
666,
7389,
656,
257,
2457,
2994,
198,
220,
220,
220,
1058,
17143,
3294,
62,
75,
6962,
25,
1002,
6407,
11,
402,
318,
2938,
284,
1441,
257,
1351,
286,
11192,
669,
326,
389,
477,
3218,
1143,
26913,
198,
220,
220,
220,
1058,
17143,
1441,
62,
25512,
1286,
25,
1002,
6407,
11,
5860,
339,
824,
666,
7389,
329,
1123,
7679,
13869,
11,
2138,
621,
19771,
606,
198,
220,
220,
220,
1058,
17143,
1195,
25,
357,
358,
17062,
11,
299,
89,
8,
17593,
286,
11678,
357,
8516,
6053,
284,
11678,
8,
628,
220,
220,
220,
1058,
7783,
25,
317,
1180,
3379,
16578,
283,
357,
1169,
339,
824,
666,
7389,
828,
393,
257,
1351,
286,
339,
824,
666,
12970,
611,
1441,
62,
25512,
1286,
318,
6407,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
402,
62,
89,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
402,
62,
89,
796,
402,
7,
89,
11,
269,
11,
266,
28,
86,
11,
1441,
62,
9374,
28,
48101,
62,
75,
6962,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3294,
62,
75,
6962,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
402,
62,
89,
796,
402,
62,
89,
58,
16,
60,
198,
220,
220,
220,
611,
266,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
82,
796,
2511,
368,
3493,
7,
13165,
354,
13,
10699,
19510,
74,
11,
1635,
86,
13,
7857,
3419,
22305,
1635,
304,
862,
33576,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
82,
796,
2511,
368,
3493,
7,
13165,
354,
13,
10699,
19510,
74,
11,
1635,
89,
13,
7857,
3419,
22305,
1635,
304,
862,
33576,
198,
220,
220,
220,
1218,
62,
6361,
796,
17635,
198,
220,
220,
220,
329,
1312,
287,
2837,
7,
74,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
796,
2124,
82,
58,
72,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3294,
62,
75,
6962,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4318,
62,
12227,
62,
2875,
796,
5021,
62,
29289,
62,
12227,
62,
37295,
282,
62,
1082,
452,
876,
7,
38,
11,
1976,
11,
269,
11,
2124,
11,
402,
62,
89,
11,
304,
862,
33576,
11,
266,
28,
86,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4318,
62,
12227,
62,
2875,
796,
1218,
62,
37295,
282,
62,
1082,
452,
876,
7,
38,
11,
1976,
11,
269,
11,
2124,
11,
402,
62,
89,
11,
304,
862,
33576,
11,
266,
28,
86,
11,
1195,
28,
48,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1218,
62,
6361,
13,
33295,
7,
31463,
62,
12227,
62,
2875,
8,
198,
220,
220,
220,
611,
3294,
62,
75,
6962,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7389,
796,
5021,
62,
25558,
62,
7785,
62,
392,
62,
445,
7234,
7,
12227,
62,
6361,
11,
7741,
11,
1441,
62,
25512,
1286,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7389,
796,
8931,
62,
7785,
62,
392,
62,
445,
7234,
7,
12227,
62,
6361,
11,
7741,
8,
198,
220,
220,
220,
1441,
7389,
628
] | 2.331269 | 1,615 |
from __future__ import annotations
from io import BytesIO
from unittest.mock import Mock
import pytest
from vine import promise
import t.skip
from kombu.asynchronous import http
from kombu.asynchronous.http.base import BaseClient, normalize_header
from kombu.exceptions import HttpError
from t.mocks import PromiseMock
@pytest.mark.usefixtures('hub')
@pytest.mark.usefixtures('hub')
@t.skip.if_pypy
| [
6738,
11593,
37443,
834,
1330,
37647,
198,
198,
6738,
33245,
1330,
2750,
4879,
9399,
198,
6738,
555,
715,
395,
13,
76,
735,
1330,
44123,
198,
198,
11748,
12972,
9288,
198,
6738,
17793,
1330,
6991,
198,
198,
11748,
256,
13,
48267,
198,
6738,
479,
2381,
84,
13,
292,
31301,
1330,
2638,
198,
6738,
479,
2381,
84,
13,
292,
31301,
13,
4023,
13,
8692,
1330,
7308,
11792,
11,
3487,
1096,
62,
25677,
198,
6738,
479,
2381,
84,
13,
1069,
11755,
1330,
367,
29281,
12331,
198,
6738,
256,
13,
76,
3320,
1330,
34920,
44,
735,
628,
198,
198,
31,
9078,
9288,
13,
4102,
13,
1904,
69,
25506,
10786,
40140,
11537,
628,
198,
31,
9078,
9288,
13,
4102,
13,
1904,
69,
25506,
10786,
40140,
11537,
628,
198,
198,
31,
83,
13,
48267,
13,
361,
62,
79,
4464,
88,
198
] | 3.037037 | 135 |
#!/usr/bin/env python
# -*- coding: utf8 -*-
"""
Copyright (c) 2011 Tyler Kenendy <[email protected]>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
try:
import json
except ImportError:
import simplejson as json
import traceback
import six
import six.moves.urllib.request
from burger import website
from .topping import Topping
from jawa.constants import *
RESOURCES_SITE = "http://resources.download.minecraft.net/%(short_hash)s/%(hash)s"
def get_sounds(asset_index, resources_site=RESOURCES_SITE):
"""Downloads the sounds.json file from the assets index"""
hash = asset_index["objects"]["minecraft/sounds.json"]["hash"]
short_hash = hash[0:2]
sounds_url = resources_site % {'hash': hash, 'short_hash': short_hash}
sounds_file = six.moves.urllib.request.urlopen(sounds_url)
try:
return json.load(sounds_file)
finally:
sounds_file.close()
class SoundTopping(Topping):
"""Finds all named sound effects which are both used in the server and
available for download."""
PROVIDES = [
"sounds"
]
DEPENDS = [
"identify.sounds.list",
"identify.sounds.event",
"version.name",
"language"
]
@staticmethod
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
23,
532,
9,
12,
198,
37811,
198,
15269,
357,
66,
8,
2813,
14886,
7148,
437,
88,
1279,
30488,
31,
30488,
660,
13,
354,
29,
198,
198,
5990,
3411,
318,
29376,
7520,
11,
1479,
286,
3877,
11,
284,
597,
1048,
16727,
257,
4866,
198,
1659,
428,
3788,
290,
3917,
10314,
3696,
357,
1169,
366,
25423,
12340,
284,
1730,
198,
259,
262,
10442,
1231,
17504,
11,
1390,
1231,
17385,
262,
2489,
198,
1462,
779,
11,
4866,
11,
13096,
11,
20121,
11,
7715,
11,
14983,
11,
850,
43085,
11,
290,
14,
273,
3677,
198,
22163,
444,
286,
262,
10442,
11,
290,
284,
8749,
6506,
284,
4150,
262,
10442,
318,
198,
69,
700,
1348,
284,
466,
523,
11,
2426,
284,
262,
1708,
3403,
25,
198,
198,
464,
2029,
6634,
4003,
290,
428,
7170,
4003,
2236,
307,
3017,
287,
198,
439,
9088,
393,
8904,
16690,
286,
262,
10442,
13,
198,
198,
10970,
47466,
3180,
36592,
2389,
1961,
366,
1921,
3180,
1600,
42881,
34764,
56,
3963,
15529,
509,
12115,
11,
7788,
32761,
6375,
198,
3955,
49094,
11,
47783,
2751,
21728,
5626,
40880,
5390,
3336,
34764,
11015,
3963,
34482,
3398,
1565,
5603,
25382,
11,
198,
37,
46144,
7473,
317,
16652,
2149,
37232,
33079,
48933,
5357,
44521,
1268,
10913,
2751,
12529,
13,
3268,
8005,
49261,
50163,
3336,
198,
32,
24318,
20673,
6375,
27975,
38162,
9947,
367,
15173,
4877,
9348,
43031,
19146,
7473,
15529,
47666,
3955,
11,
29506,
25552,
6375,
25401,
198,
43,
3539,
25382,
11,
7655,
2767,
16879,
3268,
3537,
40282,
3963,
27342,
10659,
11,
309,
9863,
6375,
25401,
54,
24352,
11,
5923,
1797,
2751,
16034,
11,
198,
12425,
3963,
6375,
3268,
7102,
45,
24565,
13315,
3336,
47466,
6375,
3336,
23210,
6375,
25401,
5550,
1847,
20754,
3268,
198,
10970,
47466,
13,
198,
37811,
198,
198,
28311,
25,
198,
220,
220,
220,
1330,
33918,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1330,
2829,
17752,
355,
33918,
198,
198,
11748,
12854,
1891,
198,
198,
11748,
2237,
198,
11748,
2237,
13,
76,
5241,
13,
333,
297,
571,
13,
25927,
198,
198,
6738,
26593,
1330,
3052,
198,
6738,
764,
1462,
2105,
1330,
1675,
2105,
198,
198,
6738,
474,
6909,
13,
9979,
1187,
1330,
1635,
198,
198,
19535,
2606,
7397,
1546,
62,
50,
12709,
796,
366,
4023,
1378,
37540,
13,
15002,
13,
17761,
13,
3262,
14,
4,
7,
19509,
62,
17831,
8,
82,
14,
4,
7,
17831,
8,
82,
1,
198,
198,
4299,
651,
62,
82,
3733,
7,
562,
316,
62,
9630,
11,
4133,
62,
15654,
28,
19535,
2606,
7397,
1546,
62,
50,
12709,
2599,
198,
220,
220,
220,
37227,
10002,
82,
262,
5238,
13,
17752,
2393,
422,
262,
6798,
6376,
37811,
198,
220,
220,
220,
12234,
796,
11171,
62,
9630,
14692,
48205,
1,
7131,
1,
17761,
14,
82,
3733,
13,
17752,
1,
7131,
1,
17831,
8973,
198,
220,
220,
220,
1790,
62,
17831,
796,
12234,
58,
15,
25,
17,
60,
198,
220,
220,
220,
5238,
62,
6371,
796,
4133,
62,
15654,
4064,
1391,
6,
17831,
10354,
12234,
11,
705,
19509,
62,
17831,
10354,
1790,
62,
17831,
92,
628,
220,
220,
220,
5238,
62,
7753,
796,
2237,
13,
76,
5241,
13,
333,
297,
571,
13,
25927,
13,
6371,
9654,
7,
82,
3733,
62,
6371,
8,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
33918,
13,
2220,
7,
82,
3733,
62,
7753,
8,
198,
220,
220,
220,
3443,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5238,
62,
7753,
13,
19836,
3419,
198,
198,
4871,
9506,
2514,
2105,
7,
2514,
2105,
2599,
198,
220,
220,
220,
37227,
16742,
82,
477,
3706,
2128,
3048,
543,
389,
1111,
973,
287,
262,
4382,
290,
198,
220,
220,
220,
220,
220,
220,
1695,
329,
4321,
526,
15931,
628,
220,
220,
220,
36592,
42538,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
82,
3733,
1,
198,
220,
220,
220,
2361,
628,
220,
220,
220,
5550,
47,
1677,
5258,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
738,
1958,
13,
82,
3733,
13,
4868,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
738,
1958,
13,
82,
3733,
13,
15596,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
9641,
13,
3672,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
16129,
1,
198,
220,
220,
220,
2361,
628,
220,
220,
220,
2488,
12708,
24396,
198
] | 3.010929 | 732 |
#!/usr/bin/env python3
# Copyright (c) 2015-2020 by the parties listed in the AUTHORS file.
# All rights reserved. Use of this source code is governed by
# a BSD-style license that can be found in the LICENSE file.
"""
Simpler version of the ground simulation script
"""
import argparse
import dateutil.parser
import os
import pickle
import sys
import traceback
import numpy as np
from toast.mpi import get_world, Comm
from toast.dist import distribute_uniform, Data
from toast.utils import Logger, Environment, memreport
from toast.timing import function_timer, GlobalTimers, Timer, gather_timers
from toast.timing import dump as dump_timing
import toast.qarray as qa
from toast.tod import OpCacheCopy, plot_focalplane, OpCacheClear
from toast.todmap import TODGround
from toast.pipeline_tools import (
add_dist_args,
add_debug_args,
get_time_communicators,
get_comm,
add_polyfilter_args,
apply_polyfilter,
add_groundfilter_args,
apply_groundfilter,
add_atmosphere_args,
add_noise_args,
simulate_noise,
add_gainscrambler_args,
scramble_gains,
add_pointing_args,
expand_pointing,
add_madam_args,
setup_madam,
apply_madam,
add_sky_map_args,
add_pysm_args,
scan_sky_signal,
simulate_sky_signal,
copy_signal,
add_tidas_args,
output_tidas,
add_spt3g_args,
output_spt3g,
add_todground_args,
get_breaks,
Focalplane,
load_schedule,
add_mc_args,
add_binner_args,
init_binner,
apply_binner,
)
def create_observations(args, comm, schedule):
""" Simulate constant elevation scans.
Simulate constant elevation scans at "site" matching entries in
"all_ces". Each operational day is assigned to a different
process group to allow making day maps.
"""
timer = Timer()
log = Logger.get()
data = Data(comm)
telescope = schedule.telescope
site = telescope.site
focalplane = telescope.focalplane
all_ces = schedule.ceslist
nces = len(all_ces)
breaks = get_breaks(comm, all_ces, args)
nbreak = len(breaks)
groupdist = distribute_uniform(nces, comm.ngroups, breaks=breaks)
group_firstobs = groupdist[comm.group][0]
group_numobs = groupdist[comm.group][1]
if comm.comm_group is not None:
ndetrank = comm.comm_group.size
else:
ndetrank = 1
for ices in range(group_firstobs, group_firstobs + group_numobs):
ces = all_ces[ices]
totsamples = int((ces.stop_time - ces.start_time) * args.sample_rate)
# create the single TOD for this observation
try:
tod = TODGround(
comm.comm_group,
focalplane.detquats,
totsamples,
detranks=ndetrank,
firsttime=ces.start_time,
rate=args.sample_rate,
site_lon=site.lon,
site_lat=site.lat,
site_alt=site.alt,
azmin=ces.azmin,
azmax=ces.azmax,
el=ces.el,
scanrate=args.scan_rate,
scan_accel=args.scan_accel,
cosecant_modulation=args.scan_cosecant_modulate,
CES_start=None,
CES_stop=None,
sun_angle_min=args.sun_angle_min,
coord=args.coord,
sampsizes=None,
report_timing=args.debug,
)
except RuntimeError as e:
raise RuntimeError("Failed to create the CES scan: {}".format(e))
# Create the (single) observation
ob = {}
ob["name"] = "CES-{}-{}-{}".format(ces.name, ces.scan, ces.subscan)
ob["tod"] = tod
if len(tod.subscans) > 0:
ob["intervals"] = tod.subscans
else:
raise RuntimeError("{} has no valid intervals".format(ob["name"]))
ob["baselines"] = None
ob["noise"] = focalplane.noise
ob["id"] = int(ces.mjdstart * 10000)
data.obs.append(ob)
for ob in data.obs:
tod = ob["tod"]
tod.free_azel_quats()
if comm.comm_world is None or comm.comm_group.rank == 0:
log.info("Group # {:4} has {} observations.".format(comm.group, len(data.obs)))
if len(data.obs) == 0:
raise RuntimeError(
"Too many tasks. Every MPI task must "
"be assigned to at least one observation."
)
if comm.world_rank == 0:
timer.report_clear("Simulate scans")
return data
def setup_sigcopy(args, comm, signalname):
""" Setup for copying the signal so we can run filter+bin and Madam.
"""
if args.use_madam:
signalname_madam = "signal_madam"
sigcopy_madam = OpCacheCopy(signalname, signalname_madam)
sigclear = OpCacheClear(signalname)
else:
signalname_madam = signalname
sigcopy_madam = None
sigclear = None
return signalname_madam, sigcopy_madam, sigclear
def copy_signal_madam(args, comm, data, sigcopy_madam):
""" Make a copy of the TOD for Madam.
"""
if sigcopy_madam is not None:
if comm.world_rank == 0:
print("Making a copy of the TOD for Madam", flush=args.flush)
sigcopy_madam.exec(data)
return
if __name__ == "__main__":
try:
main()
except Exception:
# We have an unhandled exception on at least one process. Print a stack
# trace for this process and then abort so that all processes terminate.
mpiworld, procs, rank = get_world()
if procs == 1:
raise
exc_type, exc_value, exc_traceback = sys.exc_info()
lines = traceback.format_exception(exc_type, exc_value, exc_traceback)
lines = ["Proc {}: {}".format(rank, x) for x in lines]
print("".join(lines), flush=True)
if mpiworld is not None:
mpiworld.Abort(6)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
2,
15069,
357,
66,
8,
1853,
12,
42334,
416,
262,
4671,
5610,
287,
262,
37195,
20673,
2393,
13,
198,
2,
1439,
2489,
10395,
13,
220,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
198,
2,
257,
347,
10305,
12,
7635,
5964,
326,
460,
307,
1043,
287,
262,
38559,
24290,
2393,
13,
198,
198,
37811,
198,
8890,
20053,
2196,
286,
262,
2323,
18640,
4226,
198,
37811,
198,
198,
11748,
1822,
29572,
198,
11748,
3128,
22602,
13,
48610,
198,
11748,
28686,
198,
11748,
2298,
293,
198,
11748,
25064,
198,
11748,
12854,
1891,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
27805,
13,
3149,
72,
1330,
651,
62,
6894,
11,
1520,
198,
198,
6738,
27805,
13,
17080,
1330,
14983,
62,
403,
6933,
11,
6060,
198,
198,
6738,
27805,
13,
26791,
1330,
5972,
1362,
11,
9344,
11,
1066,
13116,
198,
198,
6738,
27805,
13,
16514,
278,
1330,
2163,
62,
45016,
11,
8060,
14967,
364,
11,
5045,
263,
11,
6431,
62,
16514,
364,
198,
6738,
27805,
13,
16514,
278,
1330,
10285,
355,
10285,
62,
16514,
278,
198,
198,
11748,
27805,
13,
80,
18747,
355,
10662,
64,
198,
6738,
27805,
13,
83,
375,
1330,
8670,
30562,
29881,
11,
7110,
62,
69,
4374,
14382,
11,
8670,
30562,
19856,
198,
6738,
27805,
13,
83,
375,
8899,
1330,
16926,
35539,
198,
198,
6738,
27805,
13,
79,
541,
4470,
62,
31391,
1330,
357,
198,
220,
220,
220,
751,
62,
17080,
62,
22046,
11,
198,
220,
220,
220,
751,
62,
24442,
62,
22046,
11,
198,
220,
220,
220,
651,
62,
2435,
62,
10709,
44549,
11,
198,
220,
220,
220,
651,
62,
9503,
11,
198,
220,
220,
220,
751,
62,
35428,
24455,
62,
22046,
11,
198,
220,
220,
220,
4174,
62,
35428,
24455,
11,
198,
220,
220,
220,
751,
62,
2833,
24455,
62,
22046,
11,
198,
220,
220,
220,
4174,
62,
2833,
24455,
11,
198,
220,
220,
220,
751,
62,
265,
6384,
1456,
62,
22046,
11,
198,
220,
220,
220,
751,
62,
3919,
786,
62,
22046,
11,
198,
220,
220,
220,
29308,
62,
3919,
786,
11,
198,
220,
220,
220,
751,
62,
70,
1299,
66,
859,
43400,
62,
22046,
11,
198,
220,
220,
220,
36755,
62,
70,
1299,
11,
198,
220,
220,
220,
751,
62,
4122,
278,
62,
22046,
11,
198,
220,
220,
220,
4292,
62,
4122,
278,
11,
198,
220,
220,
220,
751,
62,
9937,
321,
62,
22046,
11,
198,
220,
220,
220,
9058,
62,
9937,
321,
11,
198,
220,
220,
220,
4174,
62,
9937,
321,
11,
198,
220,
220,
220,
751,
62,
15688,
62,
8899,
62,
22046,
11,
198,
220,
220,
220,
751,
62,
79,
893,
76,
62,
22046,
11,
198,
220,
220,
220,
9367,
62,
15688,
62,
12683,
282,
11,
198,
220,
220,
220,
29308,
62,
15688,
62,
12683,
282,
11,
198,
220,
220,
220,
4866,
62,
12683,
282,
11,
198,
220,
220,
220,
751,
62,
83,
24496,
62,
22046,
11,
198,
220,
220,
220,
5072,
62,
83,
24496,
11,
198,
220,
220,
220,
751,
62,
82,
457,
18,
70,
62,
22046,
11,
198,
220,
220,
220,
5072,
62,
82,
457,
18,
70,
11,
198,
220,
220,
220,
751,
62,
83,
375,
2833,
62,
22046,
11,
198,
220,
220,
220,
651,
62,
30058,
11,
198,
220,
220,
220,
376,
4374,
14382,
11,
198,
220,
220,
220,
3440,
62,
15952,
5950,
11,
198,
220,
220,
220,
751,
62,
23209,
62,
22046,
11,
198,
220,
220,
220,
751,
62,
65,
5083,
62,
22046,
11,
198,
220,
220,
220,
2315,
62,
65,
5083,
11,
198,
220,
220,
220,
4174,
62,
65,
5083,
11,
198,
8,
628,
628,
198,
4299,
2251,
62,
672,
3168,
602,
7,
22046,
11,
725,
11,
7269,
2599,
198,
220,
220,
220,
37227,
3184,
5039,
6937,
22910,
23824,
13,
628,
220,
220,
220,
3184,
5039,
6937,
22910,
23824,
379,
366,
15654,
1,
12336,
12784,
287,
198,
220,
220,
220,
366,
439,
62,
728,
1911,
220,
5501,
13919,
1110,
318,
8686,
284,
257,
1180,
198,
220,
220,
220,
1429,
1448,
284,
1249,
1642,
1110,
8739,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
19781,
796,
5045,
263,
3419,
198,
220,
220,
220,
2604,
796,
5972,
1362,
13,
1136,
3419,
628,
220,
220,
220,
1366,
796,
6060,
7,
9503,
8,
628,
220,
220,
220,
24344,
796,
7269,
13,
37524,
3798,
3008,
198,
220,
220,
220,
2524,
796,
24344,
13,
15654,
198,
220,
220,
220,
25397,
14382,
796,
24344,
13,
69,
4374,
14382,
198,
220,
220,
220,
477,
62,
728,
796,
7269,
13,
728,
4868,
198,
220,
220,
220,
299,
728,
796,
18896,
7,
439,
62,
728,
8,
628,
220,
220,
220,
9457,
796,
651,
62,
30058,
7,
9503,
11,
477,
62,
728,
11,
26498,
8,
628,
220,
220,
220,
299,
9032,
796,
18896,
7,
30058,
8,
628,
220,
220,
220,
1448,
17080,
796,
14983,
62,
403,
6933,
7,
3179,
11,
725,
13,
782,
14459,
11,
9457,
28,
30058,
8,
198,
220,
220,
220,
1448,
62,
11085,
8158,
796,
1448,
17080,
58,
9503,
13,
8094,
7131,
15,
60,
198,
220,
220,
220,
1448,
62,
22510,
8158,
796,
1448,
17080,
58,
9503,
13,
8094,
7131,
16,
60,
628,
220,
220,
220,
611,
725,
13,
9503,
62,
8094,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
299,
15255,
43027,
796,
725,
13,
9503,
62,
8094,
13,
7857,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
299,
15255,
43027,
796,
352,
628,
220,
220,
220,
329,
220,
1063,
287,
2837,
7,
8094,
62,
11085,
8158,
11,
1448,
62,
11085,
8158,
1343,
1448,
62,
22510,
8158,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
269,
274,
796,
477,
62,
728,
58,
1063,
60,
198,
220,
220,
220,
220,
220,
220,
220,
284,
912,
12629,
796,
493,
19510,
728,
13,
11338,
62,
2435,
532,
269,
274,
13,
9688,
62,
2435,
8,
1635,
26498,
13,
39873,
62,
4873,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
262,
2060,
16926,
329,
428,
13432,
628,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
67,
796,
16926,
35539,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
725,
13,
9503,
62,
8094,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25397,
14382,
13,
15255,
421,
1381,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
912,
12629,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1062,
81,
2283,
28,
358,
21879,
962,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
717,
2435,
28,
728,
13,
9688,
62,
2435,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2494,
28,
22046,
13,
39873,
62,
4873,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2524,
62,
14995,
28,
15654,
13,
14995,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2524,
62,
15460,
28,
15654,
13,
15460,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2524,
62,
2501,
28,
15654,
13,
2501,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35560,
1084,
28,
728,
13,
1031,
1084,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35560,
9806,
28,
728,
13,
1031,
9806,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
28,
728,
13,
417,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9367,
4873,
28,
22046,
13,
35836,
62,
4873,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9367,
62,
330,
5276,
28,
22046,
13,
35836,
62,
330,
5276,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
577,
66,
415,
62,
4666,
1741,
28,
22046,
13,
35836,
62,
66,
577,
66,
415,
62,
4666,
5039,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42700,
62,
9688,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42700,
62,
11338,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4252,
62,
9248,
62,
1084,
28,
22046,
13,
19155,
62,
9248,
62,
1084,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6349,
28,
22046,
13,
37652,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
9430,
4340,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
989,
62,
16514,
278,
28,
22046,
13,
24442,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
43160,
12331,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
37,
6255,
284,
2251,
262,
42700,
9367,
25,
23884,
1911,
18982,
7,
68,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
13610,
262,
357,
29762,
8,
13432,
628,
220,
220,
220,
220,
220,
220,
220,
909,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
3672,
8973,
796,
366,
34,
1546,
12,
90,
92,
12,
90,
92,
12,
90,
92,
1911,
18982,
7,
728,
13,
3672,
11,
269,
274,
13,
35836,
11,
269,
274,
13,
7266,
35836,
8,
198,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
83,
375,
8973,
796,
284,
67,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
83,
375,
13,
7266,
1416,
504,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
3849,
12786,
8973,
796,
284,
67,
13,
7266,
1416,
504,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
90,
92,
468,
645,
4938,
20016,
1911,
18982,
7,
672,
14692,
3672,
8973,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
12093,
20655,
8973,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
3919,
786,
8973,
796,
25397,
14382,
13,
3919,
786,
198,
220,
220,
220,
220,
220,
220,
220,
909,
14692,
312,
8973,
796,
493,
7,
728,
13,
76,
73,
67,
9688,
1635,
33028,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1366,
13,
8158,
13,
33295,
7,
672,
8,
628,
220,
220,
220,
329,
909,
287,
1366,
13,
8158,
25,
198,
220,
220,
220,
220,
220,
220,
220,
284,
67,
796,
909,
14692,
83,
375,
8973,
198,
220,
220,
220,
220,
220,
220,
220,
284,
67,
13,
5787,
62,
41319,
62,
421,
1381,
3419,
628,
220,
220,
220,
611,
725,
13,
9503,
62,
6894,
318,
6045,
393,
725,
13,
9503,
62,
8094,
13,
43027,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
10951,
7203,
13247,
1303,
46110,
19,
92,
468,
23884,
13050,
526,
13,
18982,
7,
9503,
13,
8094,
11,
18896,
7,
7890,
13,
8158,
22305,
628,
220,
220,
220,
611,
18896,
7,
7890,
13,
8158,
8,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
23307,
867,
8861,
13,
3887,
4904,
40,
4876,
1276,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1350,
8686,
284,
379,
1551,
530,
13432,
526,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
611,
725,
13,
6894,
62,
43027,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19781,
13,
13116,
62,
20063,
7203,
8890,
5039,
23824,
4943,
628,
220,
220,
220,
1441,
1366,
628,
198,
4299,
9058,
62,
82,
328,
30073,
7,
22046,
11,
725,
11,
6737,
3672,
2599,
198,
220,
220,
220,
37227,
31122,
329,
23345,
262,
6737,
523,
356,
460,
1057,
8106,
10,
8800,
290,
4627,
321,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
26498,
13,
1904,
62,
9937,
321,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6737,
3672,
62,
9937,
321,
796,
366,
12683,
282,
62,
9937,
321,
1,
198,
220,
220,
220,
220,
220,
220,
220,
43237,
30073,
62,
9937,
321,
796,
8670,
30562,
29881,
7,
12683,
282,
3672,
11,
6737,
3672,
62,
9937,
321,
8,
198,
220,
220,
220,
220,
220,
220,
220,
43237,
20063,
796,
8670,
30562,
19856,
7,
12683,
282,
3672,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6737,
3672,
62,
9937,
321,
796,
6737,
3672,
198,
220,
220,
220,
220,
220,
220,
220,
43237,
30073,
62,
9937,
321,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
43237,
20063,
796,
6045,
628,
220,
220,
220,
1441,
6737,
3672,
62,
9937,
321,
11,
43237,
30073,
62,
9937,
321,
11,
43237,
20063,
628,
198,
198,
4299,
4866,
62,
12683,
282,
62,
9937,
321,
7,
22046,
11,
725,
11,
1366,
11,
43237,
30073,
62,
9937,
321,
2599,
198,
220,
220,
220,
37227,
6889,
257,
4866,
286,
262,
16926,
329,
4627,
321,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
43237,
30073,
62,
9937,
321,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
725,
13,
6894,
62,
43027,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
23874,
257,
4866,
286,
262,
16926,
329,
4627,
321,
1600,
24773,
28,
22046,
13,
25925,
8,
198,
220,
220,
220,
220,
220,
220,
220,
43237,
30073,
62,
9937,
321,
13,
18558,
7,
7890,
8,
628,
220,
220,
220,
1441,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
3419,
198,
220,
220,
220,
2845,
35528,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
775,
423,
281,
555,
38788,
6631,
319,
379,
1551,
530,
1429,
13,
220,
12578,
257,
8931,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
12854,
329,
428,
1429,
290,
788,
15614,
523,
326,
477,
7767,
23654,
13,
198,
220,
220,
220,
220,
220,
220,
220,
285,
14415,
6894,
11,
386,
6359,
11,
4279,
796,
651,
62,
6894,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
386,
6359,
6624,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
198,
220,
220,
220,
220,
220,
220,
220,
2859,
62,
4906,
11,
2859,
62,
8367,
11,
2859,
62,
40546,
1891,
796,
25064,
13,
41194,
62,
10951,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
12854,
1891,
13,
18982,
62,
1069,
4516,
7,
41194,
62,
4906,
11,
2859,
62,
8367,
11,
2859,
62,
40546,
1891,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
14631,
2964,
66,
23884,
25,
23884,
1911,
18982,
7,
43027,
11,
2124,
8,
329,
2124,
287,
3951,
60,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
1911,
22179,
7,
6615,
828,
24773,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
285,
14415,
6894,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
14415,
6894,
13,
4826,
419,
7,
21,
8,
198
] | 2.235628 | 2,644 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Type checking functions for datetime related types for use with arparse."""
from argparse import ArgumentTypeError
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
6030,
10627,
5499,
329,
4818,
8079,
3519,
3858,
329,
779,
351,
610,
29572,
526,
15931,
198,
198,
6738,
1822,
29572,
1330,
45751,
6030,
12331,
628
] | 3.34 | 50 |
#!/usr/bin/env python3
# coding=utf-8
# author: @netmanchris
# -*- coding: utf-8 -*-
"""
This module contains functions for working with the device capabilities
of the HPE IMC NMS platform using the RESTful API
"""
# This section imports required libraries
import json
import requests
from pyhpeimc.auth import HEADERS
# This section contains functions which operate at the system level
# This whole section has been moved to pyhpeimc.plat.system - functions left here for legacy.
# Intention is to remove by version 1.0.60 or greater. Please modify any scripts using functions
# in this section to use the new functions in the new module
# TODO Delete function when version => 1.60
def get_system_vendors(auth, url):
"""Takes string no input to issue RESTUL call to HP IMC\n
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list of dictionaries where each dictionary represents a single vendor
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> vendors = get_system_vendors(auth.creds, auth.url)
>>> assert type(vendors) is list
>>> assert 'name' in vendors[0]
"""
f_url = url + '/imcrs/plat/res/vendor?start=0&size=10000&orderBy=id&desc=false&total=false'
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
system_vendors = (json.loads(response.text))
return system_vendors['deviceVendor']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_details: An Error has occured"
# TODO remove function when version => 1.60
def get_system_category(auth, url):
"""Takes string no input to issue RESTUL call to HP IMC\n
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list of dictionaries where each dictionary represents a single device category
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> categories = get_system_category(auth.creds, auth.url)
>>> assert type(categories) is list
>>> assert 'name' in categories[0]
"""
f_url = url + '/imcrs/plat/res/category?start=0&size=10000&orderBy=id&desc=false&total=false'
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
system_category = (json.loads(response.text))
return system_category['deviceCategory']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_details: An Error has occured"
# TODO Delete function when version => 1.60
def get_system_device_models(auth, url):
"""Takes string no input to issue RESTUL call to HP IMC\n
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list of dictionaries where each dictionary represents a single device model
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> device_models = get_system_device_models(auth.creds, auth.url)
>>> assert type(device_models) is list
>>> assert 'virtualDeviceName' in device_models[0]
"""
f_url = url + '/imcrs/plat/res/model?start=0&size=10000&orderBy=id&desc=false&total=false'
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
system_device_model = (json.loads(response.text))
return system_device_model['deviceModel']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_details: An Error has occured"
# TODO Delete function when version => 1.60
def get_system_series(auth, url):
"""Takes string no input to issue RESTUL call to HP IMC\n
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list of dictionaries where each dictionary represents a single device series
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> series = get_system_series(auth.creds, auth.url)
>>> assert type(series) is list
>>> assert 'name' in series[0]
"""
f_url = url + '/imcrs/plat/res/series?managedOnly=false&start=0&size=10000&orderBy=id&desc' \
'=false&total=false'
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
system_series = (json.loads(response.text))
return system_series['deviceSeries']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_series: An Error has occured"
# This section contains functions which operate at the device level.
def get_all_devs(auth, url, network_address=None, category=None, label=None):
"""Takes string input of IP address to issue RESTUL call to HP IMC\n
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param network_address: str IPv4 Network Address
:param category: str or int corresponding to device category (0=router, 1=switches, see API docs for other examples)
:return: dictionary of device details
:rtype: dict
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> dev_list = get_all_devs( auth.creds, auth.url, network_address= '10.11.')
>>> assert type(dev_list) is list
>>> assert 'sysName' in dev_list[0]
"""
base_url = "/imcrs/plat/res/device?resPrivilegeFilter=false"
end_url = "&start=0&size=1000&orderBy=id&desc=false&total=false"
if network_address:
network_address = "&ip=" + str(network_address)
else:
network_address = ''
if label:
label = "&label=" + str(label)
else:
label = ''
if category:
category = "&category" + category
else:
category = ''
f_url = url + base_url + str(network_address) + str(label) + str(category) + end_url
print(f_url)
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
dev_details = (json.loads(response.text))
if len(dev_details) == 0:
print("Device not found")
return "Device not found"
elif type(dev_details['device']) is dict:
return [dev_details['device']]
else:
return dev_details['device']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_details: An Error has occured"
def get_dev_details(ip_address, auth, url):
"""Takes string input of IP address to issue RESTUL call to HP IMC
:param ip_address: string object of dotted decimal notation of IPv4 address
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: dictionary of device details
:rtype: dict
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> dev_1 = get_dev_details('10.101.0.221', auth.creds, auth.url)
>>> assert type(dev_1) is dict
>>> assert 'sysName' in dev_1
>>> dev_2 = get_dev_details('8.8.8.8', auth.creds, auth.url)
Device not found
>>> assert type(dev_2) is str
"""
get_dev_details_url = "/imcrs/plat/res/device?resPrivilegeFilter=false&ip=" + \
str(ip_address) + "&start=0&size=1000&orderBy=id&desc=false&total=false"
f_url = url + get_dev_details_url
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
dev_details = (json.loads(response.text))
if len(dev_details) == 0:
print("Device not found")
return "Device not found"
elif isinstance(dev_details['device'], list):
for i in dev_details['device']:
if i['ip'] == ip_address:
dev_details = i
return dev_details
elif isinstance(dev_details['device'], dict):
return dev_details['device']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_details: An Error has occured"
def get_dev_interface(auth, url, devid=None, devip=None):
"""
Function takes devid as input to RESTFUL call to HP IMC platform and returns list of device
interfaces
:param devid: optional devid as the input
:param devip: str of ipv4 address of the target device
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list object which contains a dictionary per interface
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> dev_interfaces = get_dev_interface(auth.creds, auth.url, devid='15')
>>> dev_interfaces = get_dev_interface(auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(dev_interfaces) is list
>>> assert 'ifAlias' in dev_interfaces[0]
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
get_dev_interface_url = "/imcrs/plat/res/device/" + str(devid) + \
"/interface?start=0&size=1000&desc=false&total=false"
f_url = url + get_dev_interface_url
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
int_list = json.loads(response.text)
if 'interface' in int_list:
return int_list['interface']
else:
return []
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_interface: An Error has occured"
def get_dev_run_config(auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and issues a RESTFUL call to get the most
current running config file as known by the HP IMC Base Platform ICC module for the target
device.
:param devid: int or str value of the target device
:param devip: str of ipv4 address of the target device
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: str which contains the entire content of the target device running configuration.
If the device is not currently supported in the HP IMC Base Platform ICC module, this call
returns a string of "This feature is not supported on this device"
:rtype: str
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> run_config = get_dev_run_config(auth.creds, auth.url, devid='10')
>>> run_config = get_dev_run_config(auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(run_config) is str
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
f_url = url + "/imcrs/icc/deviceCfg/" + str(devid) + "/currentRun"
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
run_conf = (json.loads(response.text))['content']
return run_conf
elif response.status_code == 404:
return "This features is no supported on this device"
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_run_config: An Error has occured"
def get_dev_latest_run_config(auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and issues a RESTFUL call to get the most
current existing backup of the running config file as known by the HP IMC Base Platform ICC module for the target
device.
:param devid: int or str value of the target device
:param devip: str of ipv4 address of the target device
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: str which contains the entire content of the target device running configuration.
If the device is not currently supported in the HP IMC Base Platform ICC module, this call
returns a string of "This feature is not supported on this device"
:rtype: str
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> run_config = get_dev_run_config(auth.creds, auth.url, devid='10')
>>> run_config = get_dev_run_config(auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(run_config) is str
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
f_url = url + "/imcrs/icc/deviceCfg/" + str(devid) + "/latestRun"
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
run_conf = (json.loads(response.text))['content']
return run_conf
elif response.status_code == 404:
return "This features is no supported on this device"
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_run_config: An Error has occured"
def get_dev_start_config(auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and issues a RESTFUL call to get the most
current startup config file as known by the HP IMC Base Platform ICC module for the target
device.
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param devid: optional int or str value of the target device
:param devip: optional ipv4 address of the target device
:return: str which contains the entire content of the target device startup configuration.
If the device is not currently supported in the HP IMC Base Platform ICC module, this call
returns a string of "This feature is not supported on this device"
:retype: str
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> start_config = get_dev_start_config(auth.creds, auth.url, devId='10')
>>> start_config = get_dev_start_config(auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(start_config) is str
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
f_url = url + "/imcrs/icc/deviceCfg/" + str(devid) + "/currentStart"
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
start_conf = (json.loads(response.text))['content']
return start_conf
elif response.status_code == 404:
return "This features is no supported on this device"
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_start_config: An Error has occured"
def get_dev_latest_start_config(auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and issues a RESTFUL call to get the most
current startup config file as known by the HP IMC Base Platform ICC module for the target
device.
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param devid: optional int or str value of the target device
:param devip: optional ipv4 address of the target device
:return: str which contains the entire content of the target device startup configuration.
If the device is not currently supported in the HP IMC Base Platform ICC module, this call
returns a string of "This feature is not supported on this device"
:retype: str
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> start_config = get_dev_start_config(auth.creds, auth.url, devId='10')
>>> start_config = get_dev_start_config(auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(start_config) is str
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
f_url = url + "/imcrs/icc/deviceCfg/" + str(devid) + "/latestStart"
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
start_conf = (json.loads(response.text))['content']
return start_conf
elif response.status_code == 404:
return "This features is no supported on this device"
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_start_config: An Error has occured"
def get_dev_mac_learn(auth, url, devid=None, devip=None):
"""
function takes devid of specific device and issues a RESTFUL call to gather the current
IP-MAC learning entries on the target device.
:param devid: int value of the target device
:param devip: ipv4 address of the target device
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: list of dict objects which contain the mac learn table of target device id
:rtype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> dev_mac_learn = get_dev_mac_learn( auth.creds, auth.url, devid='10')
>>> dev_mac_learn = get_dev_mac_learn( auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(dev_mac_learn) is list
>>> assert 'deviceId' in dev_mac_learn[0]
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
f_url = url + '/imcrs/res/access/ipMacLearn/' + str(devid)
try:
response = requests.get(f_url, auth=auth, headers=HEADERS)
if response.status_code == 200:
if len(json.loads(response.text)) < 1:
mac_learn_query = []
return mac_learn_query
else:
mac_learn_query = (json.loads(response.text))['ipMacLearnResult']
if isinstance(mac_learn_query, dict):
mac_learn_query = [mac_learn_query]
return mac_learn_query
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_dev_mac_learn: An Error has occured"
def run_dev_cmd(cmd_list, auth, url, devid=None, devip=None):
"""
Function takes devid of target device and a sequential list of strings which define the
specific commands to be run on the target device and returns a str object containing the
output of the commands.
:param devid: int devid of the target device
:param cmd_list: list of strings
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param devip: str of ipv4 address of the target device
:return: str containing the response of the commands
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> cmd_list = ['display version']
>>> cmd_output = run_dev_cmd( cmd_list, auth.creds, auth.url, devid ='10')
>>> cmd_output = run_dev_cmd( cmd_list, auth.creds, auth.url, devip='10.101.0.221')
>>> assert type(cmd_output) is dict
>>> assert 'cmdlist' in cmd_output
>>> assert 'success' in cmd_output
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
run_dev_cmd_url = '/imcrs/icc/confFile/executeCmd'
f_url = url + run_dev_cmd_url
cmd_list = _make_cmd_list(cmd_list)
payload = '''{ "deviceId" : "''' + str(devid) + '''",
"cmdlist" : { "cmd" :
[''' + cmd_list + ''']
}
}'''
try:
response = requests.post(f_url, data=payload, auth=auth, headers=HEADERS)
if response.status_code == 200:
if len(response.text) < 1:
return ''
else:
return json.loads(response.text)
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " run_dev_cmd: An Error has occured"
# This section contains functions which operate at the interface level
def get_all_interface_details(auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and the ifindex value assigned to a specific
interface and issues a RESTFUL call to get the interface details file as known by the HP IMC
Base Platform ICC module for the target device.
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param devid: int or str value of the devId of the target device
:param devip: ipv4 address of the target device
:return: list of dict objects which contains the details of all interfaces on the target device
:retype: list
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> all_interface_details = get_all_interface_details( auth.creds, auth.url, devId='10')
>>> all_interface_details = get_all_interface_details( auth.creds, auth.url,
devip='10.101.0.221')
>>> assert type(all_interface_details) is list
>>> assert 'ifAlias' in all_interface_details[0]
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
get_all_interface_details_url = "/imcrs/plat/res/device/" + str(
devid) + "/interface/?start=0&size=1000&desc=false&total=false"
f_url = url + get_all_interface_details_url
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
dev_details = (json.loads(response.text))
return dev_details['interface']
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_all_interface_details: An Error has occured"
def get_interface_details(ifindex, auth, url, devid=None, devip=None):
"""
function takes the devId of a specific device and the ifindex value assigned to a specific
interface and issues a RESTFUL call to get the interface details
file as known by the HP IMC Base Platform ICC module for the target device.
:param ifindex: int or str value of the ifIndex of the target interface
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:param devid: int or str value of the devId of the target device
:param devip: str of ipv4 address of the target device
:return: dict which contains the details of the target interface"
:retype: dict
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> interface_details = get_interface_details('1', auth.creds, auth.url, devId = '10')
>>> interface_details = get_interface_details('1', auth.creds, auth.url, devip = '10.101.0.221')
>>> assert type(interface_details) is dict
>>> assert 'ifAlias' in interface_details
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
get_interface_details_url = "/imcrs/plat/res/device/" + str(devid) + "/interface/" + \
str(ifindex)
f_url = url + get_interface_details_url
response = requests.get(f_url, auth=auth, headers=HEADERS)
try:
if response.status_code == 200:
dev_details = (json.loads(response.text))
return dev_details
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " get_interface_details: An Error has occured"
def set_interface_down(ifindex, auth, url, devid=None, devip=None):
"""
function takest devid and ifindex of specific device and interface and issues a RESTFUL call
to " shut" the specified interface on the target device.
:param devid: int or str value of the target device
:param devip: ipv4 address of the target devices
:param ifindex: int or str value of the target interface
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: HTTP status code 204 with no values.
:rtype:int
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> int_up_response = set_inteface_up('9', auth.creds, auth.url, devip = '10.101.0.221')
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devid = '10')
204
>>> int_up_response = set_inteface_up('9', auth.creds, auth.url, devip = '10.101.0.221')
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devip = '10.101.0.221')
204
>>> assert type(int_down_response) is int
>>> assert int_down_response is 204
>>> int_up_response = set_inteface_up('9', auth.creds, auth.url, devip = '10.101.0.221')
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
set_int_down_url = "/imcrs/plat/res/device/" + str(devid) + "/interface/" + str(ifindex) + \
"/down"
f_url = url + set_int_down_url
try:
response = requests.put(f_url, auth=auth, headers=HEADERS)
print(response.status_code)
if response.status_code == 204:
return response.status_code
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " set_inteface_down: An Error has occured"
def set_inteface_up(ifindex, auth, url, devid=None, devip=None):
"""
function takest devid and ifindex of specific device and interface and issues a RESTFUL call
to "undo shut" the specified interface on the target device.
:param devid: int or str value of the target device
:param devip: ipv4 address of the target devices
:param ifindex: int or str value of the target interface
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: HTTP status code 204 with no values.
:rype: int
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devid = '10')
204
>>> int_up_response = set_inteface_up( '9', auth.creds, auth.url, devid = '10')
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devid = '10')
204
>>> int_up_response = set_inteface_up('9', auth.creds, auth.url, devip = '10.101.0.221')
>>> assert type(int_up_response) is int
>>> assert int_up_response is 204
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
set_int_up_url = "/imcrs/plat/res/device/" + str(devid) + "/interface/" + str(ifindex) + "/up"
f_url = url + set_int_up_url
try:
response = requests.put(f_url, auth=auth, headers=HEADERS)
if response.status_code == 204:
return response.status_code
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " set_inteface_up: An Error has occured"
def set_interface_up(ifindex, auth, url, devid=None, devip=None):
"""
function takest devid and ifindex of specific device and interface and issues a RESTFUL call
to "undo shut" the specified interface on the target device.
:param devid: int or str value of the target device
:param devip: ipv4 address of the target devices
:param ifindex: int or str value of the target interface
:param auth: requests auth object #usually auth.creds from auth pyhpeimc.auth.class
:param url: base url of IMC RS interface #usually auth.url from pyhpeimc.auth.authclass
:return: HTTP status code 204 with no values.
:rype: int
>>> from pyhpeimc.auth import *
>>> from pyhpeimc.plat.device import *
>>> auth = IMCAuth("http://", "10.101.0.203", "8080", "admin", "admin")
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devid = '10')
204
>>> int_up_response = set_interface_up( '9', auth.creds, auth.url, devid = '10')
>>> int_down_response = set_interface_down( '9', auth.creds, auth.url, devid = '10')
204
>>> int_up_response = set_interface_up('9', auth.creds, auth.url, devip = '10.101.0.221')
>>> assert type(int_up_response) is int
>>> assert int_up_response is 204
"""
if devip is not None:
devid = get_dev_details(devip, auth, url)['id']
set_int_up_url = "/imcrs/plat/res/device/" + str(devid) + "/interface/" + str(ifindex) + "/up"
f_url = url + set_int_up_url
try:
response = requests.put(f_url, auth=auth, headers=HEADERS)
if response.status_code == 204:
return response.status_code
except requests.exceptions.RequestException as error:
return "Error:\n" + str(error) + " set_interface_up: An Error has occured"
def _make_cmd_list(cmd_list):
"""
Helper function to easily create the proper json formated string from a list of strs
:param cmd_list: list of strings
:return: str json formatted
"""
cmd = ''
for i in cmd_list:
cmd = cmd + '"' + i + '",'
cmd = cmd[:-1]
return cmd
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
19617,
28,
40477,
12,
23,
198,
2,
1772,
25,
2488,
3262,
805,
354,
2442,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
1212,
8265,
4909,
5499,
329,
1762,
351,
262,
3335,
9889,
198,
1659,
262,
6574,
36,
8959,
34,
399,
5653,
3859,
1262,
262,
30617,
913,
7824,
198,
198,
37811,
198,
198,
2,
770,
2665,
17944,
2672,
12782,
198,
11748,
33918,
198,
198,
11748,
7007,
198,
198,
6738,
12972,
71,
431,
320,
66,
13,
18439,
1330,
39837,
4877,
628,
198,
2,
770,
2665,
4909,
5499,
543,
8076,
379,
262,
1080,
1241,
198,
2,
770,
2187,
2665,
468,
587,
3888,
284,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
10057,
532,
5499,
1364,
994,
329,
10655,
13,
198,
2,
2558,
1463,
318,
284,
4781,
416,
2196,
352,
13,
15,
13,
1899,
393,
3744,
13,
4222,
13096,
597,
14750,
1262,
5499,
198,
2,
287,
428,
2665,
284,
779,
262,
649,
5499,
287,
262,
649,
8265,
628,
198,
198,
2,
16926,
46,
23520,
2163,
618,
2196,
5218,
352,
13,
1899,
198,
4299,
651,
62,
10057,
62,
85,
437,
669,
7,
18439,
11,
19016,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
645,
5128,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
59,
77,
628,
220,
220,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
220,
220,
1058,
7783,
25,
1351,
286,
48589,
3166,
810,
1123,
22155,
6870,
257,
2060,
18371,
628,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
220,
220,
13163,
17192,
796,
651,
62,
10057,
62,
85,
437,
669,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
628,
220,
220,
220,
220,
220,
13163,
6818,
2099,
7,
85,
437,
669,
8,
318,
1351,
628,
220,
220,
220,
220,
220,
13163,
6818,
705,
3672,
6,
287,
17192,
58,
15,
60,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
31051,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
85,
18738,
30,
9688,
28,
15,
5,
7857,
28,
49388,
5,
2875,
3886,
28,
312,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
6,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1080,
62,
85,
437,
669,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1080,
62,
85,
437,
669,
17816,
25202,
53,
18738,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
2,
16926,
46,
4781,
2163,
618,
2196,
5218,
352,
13,
1899,
198,
4299,
651,
62,
10057,
62,
22872,
7,
18439,
11,
19016,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
645,
5128,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
59,
77,
628,
220,
220,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
220,
220,
1058,
7783,
25,
1351,
286,
48589,
3166,
810,
1123,
22155,
6870,
257,
2060,
3335,
6536,
628,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
220,
220,
13163,
9376,
796,
651,
62,
10057,
62,
22872,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
628,
220,
220,
220,
220,
220,
13163,
6818,
2099,
7,
66,
26129,
8,
318,
1351,
628,
220,
220,
220,
220,
220,
13163,
6818,
705,
3672,
6,
287,
9376,
58,
15,
60,
628,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
31051,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
22872,
30,
9688,
28,
15,
5,
7857,
28,
49388,
5,
2875,
3886,
28,
312,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
6,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1080,
62,
22872,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1080,
62,
22872,
17816,
25202,
27313,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
2,
16926,
46,
23520,
2163,
618,
2196,
5218,
352,
13,
1899,
198,
4299,
651,
62,
10057,
62,
25202,
62,
27530,
7,
18439,
11,
19016,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
645,
5128,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
59,
77,
628,
220,
220,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
220,
220,
1058,
7783,
25,
1351,
286,
48589,
3166,
810,
1123,
22155,
6870,
257,
2060,
3335,
2746,
628,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
220,
220,
13163,
3335,
62,
27530,
796,
651,
62,
10057,
62,
25202,
62,
27530,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
628,
220,
220,
220,
220,
220,
13163,
6818,
2099,
7,
25202,
62,
27530,
8,
318,
1351,
628,
220,
220,
220,
220,
220,
13163,
6818,
705,
32844,
24728,
5376,
6,
287,
3335,
62,
27530,
58,
15,
60,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
31051,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
19849,
30,
9688,
28,
15,
5,
7857,
28,
49388,
5,
2875,
3886,
28,
312,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
6,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1080,
62,
25202,
62,
19849,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1080,
62,
25202,
62,
19849,
17816,
25202,
17633,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
2,
16926,
46,
23520,
2163,
618,
2196,
5218,
352,
13,
1899,
198,
4299,
651,
62,
10057,
62,
25076,
7,
18439,
11,
19016,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
645,
5128,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
59,
77,
628,
220,
220,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
220,
220,
1058,
7783,
25,
1351,
286,
48589,
3166,
810,
1123,
22155,
6870,
257,
2060,
3335,
2168,
628,
220,
220,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
220,
220,
13163,
2168,
796,
651,
62,
10057,
62,
25076,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
628,
220,
220,
220,
220,
220,
13163,
6818,
2099,
7,
25076,
8,
318,
1351,
628,
220,
220,
220,
220,
220,
13163,
6818,
705,
3672,
6,
287,
2168,
58,
15,
60,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
31051,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25076,
30,
39935,
10049,
28,
9562,
5,
9688,
28,
15,
5,
7857,
28,
49388,
5,
2875,
3886,
28,
312,
5,
20147,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28,
9562,
5,
23350,
28,
9562,
6,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1080,
62,
25076,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1080,
62,
25076,
17816,
25202,
27996,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
25076,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
2,
770,
2665,
4909,
5499,
543,
8076,
379,
262,
3335,
1241,
13,
628,
198,
4299,
651,
62,
439,
62,
7959,
82,
7,
18439,
11,
19016,
11,
3127,
62,
21975,
28,
14202,
11,
6536,
28,
14202,
11,
6167,
28,
14202,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
5128,
286,
6101,
2209,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
59,
77,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
198,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
198,
220,
220,
220,
1058,
17143,
3127,
62,
21975,
25,
965,
25961,
19,
7311,
17917,
198,
220,
220,
220,
1058,
17143,
6536,
25,
965,
393,
493,
11188,
284,
3335,
6536,
357,
15,
28,
472,
353,
11,
352,
28,
2032,
9249,
11,
766,
7824,
34165,
329,
584,
6096,
8,
198,
220,
220,
220,
1058,
7783,
25,
22155,
286,
3335,
3307,
198,
220,
220,
220,
1058,
81,
4906,
25,
8633,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1614,
62,
4868,
796,
651,
62,
439,
62,
7959,
82,
7,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
3127,
62,
21975,
28,
705,
940,
13,
1157,
2637,
8,
628,
220,
220,
220,
13163,
6818,
2099,
7,
7959,
62,
4868,
8,
318,
1351,
628,
220,
220,
220,
13163,
6818,
705,
17597,
5376,
6,
287,
1614,
62,
4868,
58,
15,
60,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
2779,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30,
411,
20184,
41866,
22417,
28,
9562,
1,
198,
220,
220,
220,
886,
62,
6371,
796,
366,
5,
9688,
28,
15,
5,
7857,
28,
12825,
5,
2875,
3886,
28,
312,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
1,
198,
220,
220,
220,
611,
3127,
62,
21975,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3127,
62,
21975,
796,
366,
5,
541,
2625,
1343,
965,
7,
27349,
62,
21975,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3127,
62,
21975,
796,
10148,
198,
220,
220,
220,
611,
6167,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
796,
366,
5,
18242,
2625,
1343,
965,
7,
18242,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
796,
10148,
198,
220,
220,
220,
611,
6536,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6536,
796,
366,
5,
22872,
1,
1343,
6536,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6536,
796,
10148,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
2779,
62,
6371,
1343,
965,
7,
27349,
62,
21975,
8,
1343,
965,
7,
18242,
8,
1343,
965,
7,
22872,
8,
1343,
886,
62,
6371,
198,
220,
220,
220,
3601,
7,
69,
62,
6371,
8,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
62,
36604,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
7959,
62,
36604,
8,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
24728,
407,
1043,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
24728,
407,
1043,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2099,
7,
7959,
62,
36604,
17816,
25202,
6,
12962,
318,
8633,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
7959,
62,
36604,
17816,
25202,
6,
11907,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1614,
62,
36604,
17816,
25202,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
36604,
7,
541,
62,
21975,
11,
6284,
11,
19016,
2599,
198,
220,
220,
220,
37227,
51,
1124,
4731,
5128,
286,
6101,
2209,
284,
2071,
30617,
6239,
869,
284,
6574,
8959,
34,
628,
220,
220,
220,
1058,
17143,
20966,
62,
21975,
25,
4731,
2134,
286,
38745,
32465,
33274,
286,
25961,
19,
2209,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
22155,
286,
3335,
3307,
628,
220,
220,
220,
1058,
81,
4906,
25,
8633,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1614,
62,
16,
796,
220,
651,
62,
7959,
62,
36604,
10786,
940,
13,
8784,
13,
15,
13,
26115,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
628,
220,
220,
220,
13163,
6818,
2099,
7,
7959,
62,
16,
8,
318,
8633,
628,
220,
220,
220,
13163,
6818,
705,
17597,
5376,
6,
287,
1614,
62,
16,
628,
220,
220,
220,
13163,
1614,
62,
17,
796,
651,
62,
7959,
62,
36604,
10786,
23,
13,
23,
13,
23,
13,
23,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
8,
198,
220,
220,
220,
16232,
407,
1043,
628,
220,
220,
220,
13163,
6818,
2099,
7,
7959,
62,
17,
8,
318,
965,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
651,
62,
7959,
62,
36604,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30,
411,
20184,
41866,
22417,
28,
9562,
5,
541,
2625,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
7,
541,
62,
21975,
8,
1343,
366,
5,
9688,
28,
15,
5,
7857,
28,
12825,
5,
2875,
3886,
28,
312,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
651,
62,
7959,
62,
36604,
62,
6371,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
62,
36604,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
7959,
62,
36604,
8,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
24728,
407,
1043,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
24728,
407,
1043,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
318,
39098,
7,
7959,
62,
36604,
17816,
25202,
6,
4357,
1351,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
1614,
62,
36604,
17816,
25202,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
17816,
541,
20520,
6624,
20966,
62,
21975,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
62,
36604,
796,
1312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1614,
62,
36604,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
318,
39098,
7,
7959,
62,
36604,
17816,
25202,
6,
4357,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1614,
62,
36604,
17816,
25202,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
39994,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
2753,
1614,
312,
355,
5128,
284,
30617,
46476,
869,
284,
6574,
8959,
34,
3859,
290,
5860,
1351,
286,
3335,
198,
220,
220,
220,
20314,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
11902,
1614,
312,
355,
262,
5128,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
965,
286,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
198,
220,
220,
220,
1058,
7783,
25,
1351,
2134,
543,
4909,
257,
22155,
583,
7071,
628,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1614,
62,
3849,
32186,
796,
651,
62,
7959,
62,
39994,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
11639,
1314,
11537,
628,
220,
220,
220,
13163,
1614,
62,
3849,
32186,
796,
651,
62,
7959,
62,
39994,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
7959,
62,
3849,
32186,
8,
318,
1351,
628,
220,
220,
220,
13163,
6818,
705,
361,
40489,
6,
287,
1614,
62,
3849,
32186,
58,
15,
60,
628,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
651,
62,
7959,
62,
39994,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12813,
39994,
30,
9688,
28,
15,
5,
7857,
28,
12825,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
651,
62,
7959,
62,
39994,
62,
6371,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
62,
4868,
796,
33918,
13,
46030,
7,
26209,
13,
5239,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
39994,
6,
287,
493,
62,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
493,
62,
4868,
17816,
39994,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
17635,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
39994,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
5143,
62,
11250,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
749,
198,
220,
220,
220,
1459,
220,
2491,
4566,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
329,
262,
2496,
198,
220,
220,
220,
3335,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
965,
286,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
965,
543,
4909,
262,
2104,
2695,
286,
262,
2496,
3335,
2491,
8398,
13,
198,
220,
220,
220,
1002,
262,
3335,
318,
407,
3058,
4855,
287,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
11,
428,
869,
198,
220,
220,
220,
5860,
257,
4731,
286,
366,
1212,
3895,
318,
407,
4855,
319,
428,
3335,
1,
628,
220,
220,
220,
1058,
81,
4906,
25,
965,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1057,
62,
11250,
796,
651,
62,
7959,
62,
5143,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
11639,
940,
11537,
628,
220,
220,
220,
13163,
1057,
62,
11250,
796,
651,
62,
7959,
62,
5143,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
5143,
62,
11250,
8,
318,
965,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
12813,
320,
66,
3808,
14,
44240,
14,
25202,
34,
40616,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
14421,
10987,
1,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1057,
62,
10414,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
17816,
11299,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1057,
62,
10414,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2882,
13,
13376,
62,
8189,
6624,
32320,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
1212,
3033,
318,
645,
4855,
319,
428,
3335,
1,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
5143,
62,
11250,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
42861,
62,
5143,
62,
11250,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
749,
198,
220,
220,
220,
1459,
4683,
11559,
286,
262,
2491,
4566,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
329,
262,
2496,
198,
220,
220,
220,
3335,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
965,
286,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
965,
543,
4909,
262,
2104,
2695,
286,
262,
2496,
3335,
2491,
8398,
13,
198,
220,
220,
220,
1002,
262,
3335,
318,
407,
3058,
4855,
287,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
11,
428,
869,
198,
220,
220,
220,
5860,
257,
4731,
286,
366,
1212,
3895,
318,
407,
4855,
319,
428,
3335,
1,
628,
220,
220,
220,
1058,
81,
4906,
25,
965,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1057,
62,
11250,
796,
651,
62,
7959,
62,
5143,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
11639,
940,
11537,
628,
220,
220,
220,
13163,
1057,
62,
11250,
796,
651,
62,
7959,
62,
5143,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
5143,
62,
11250,
8,
318,
965,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
12813,
320,
66,
3808,
14,
44240,
14,
25202,
34,
40616,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
42861,
10987,
1,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1057,
62,
10414,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
17816,
11299,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1057,
62,
10414,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2882,
13,
13376,
62,
8189,
6624,
32320,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
1212,
3033,
318,
645,
4855,
319,
428,
3335,
1,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
5143,
62,
11250,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
9688,
62,
11250,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
749,
198,
220,
220,
220,
1459,
13693,
4566,
220,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
329,
262,
2496,
198,
220,
220,
220,
3335,
13,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
11902,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
220,
11902,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
7783,
25,
965,
543,
4909,
262,
2104,
2695,
286,
262,
2496,
3335,
13693,
8398,
13,
198,
220,
220,
220,
1002,
262,
3335,
318,
407,
3058,
4855,
287,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
11,
428,
869,
198,
220,
220,
220,
5860,
257,
4731,
286,
366,
1212,
3895,
318,
407,
4855,
319,
428,
3335,
1,
628,
220,
220,
220,
1058,
260,
4906,
25,
965,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
923,
62,
11250,
796,
651,
62,
7959,
62,
9688,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
7390,
11639,
940,
11537,
628,
220,
220,
220,
13163,
923,
62,
11250,
796,
651,
62,
7959,
62,
9688,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
9688,
62,
11250,
8,
318,
965,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
12813,
320,
66,
3808,
14,
44240,
14,
25202,
34,
40616,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
14421,
10434,
1,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
923,
62,
10414,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
17816,
11299,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
923,
62,
10414,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2882,
13,
13376,
62,
8189,
6624,
32320,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
1212,
3033,
318,
645,
4855,
319,
428,
3335,
1,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
9688,
62,
11250,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
42861,
62,
9688,
62,
11250,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
749,
198,
220,
220,
220,
1459,
13693,
4566,
220,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
329,
262,
2496,
198,
220,
220,
220,
3335,
13,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
11902,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
220,
11902,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
7783,
25,
965,
543,
4909,
262,
2104,
2695,
286,
262,
2496,
3335,
13693,
8398,
13,
198,
220,
220,
220,
1002,
262,
3335,
318,
407,
3058,
4855,
287,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
11,
428,
869,
198,
220,
220,
220,
5860,
257,
4731,
286,
366,
1212,
3895,
318,
407,
4855,
319,
428,
3335,
1,
628,
220,
220,
220,
1058,
260,
4906,
25,
965,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
923,
62,
11250,
796,
651,
62,
7959,
62,
9688,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
7390,
11639,
940,
11537,
628,
220,
220,
220,
13163,
923,
62,
11250,
796,
651,
62,
7959,
62,
9688,
62,
11250,
7,
18439,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
9688,
62,
11250,
8,
318,
965,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
12813,
320,
66,
3808,
14,
44240,
14,
25202,
34,
40616,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
42861,
10434,
1,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
923,
62,
10414,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
17816,
11299,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
923,
62,
10414,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2882,
13,
13376,
62,
8189,
6624,
32320,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
1212,
3033,
318,
645,
4855,
319,
428,
3335,
1,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
9688,
62,
11250,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
7959,
62,
20285,
62,
35720,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
1614,
312,
286,
2176,
3335,
290,
2428,
257,
30617,
46476,
869,
284,
6431,
262,
1459,
198,
220,
220,
220,
6101,
12,
44721,
220,
4673,
12784,
319,
262,
2496,
3335,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
493,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
1351,
286,
8633,
5563,
543,
3994,
262,
8352,
2193,
3084,
286,
2496,
3335,
4686,
628,
220,
220,
220,
1058,
81,
4906,
25,
1351,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
1614,
62,
20285,
62,
35720,
796,
651,
62,
7959,
62,
20285,
62,
35720,
7,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
11639,
940,
11537,
628,
220,
220,
220,
13163,
1614,
62,
20285,
62,
35720,
796,
651,
62,
7959,
62,
20285,
62,
35720,
7,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
7959,
62,
20285,
62,
35720,
8,
318,
1351,
628,
220,
220,
220,
13163,
6818,
705,
25202,
7390,
6,
287,
1614,
62,
20285,
62,
35720,
58,
15,
60,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
31051,
320,
66,
3808,
14,
411,
14,
15526,
14,
541,
14155,
20238,
14,
6,
1343,
965,
7,
7959,
312,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8352,
62,
35720,
62,
22766,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
8352,
62,
35720,
62,
22766,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8352,
62,
35720,
62,
22766,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
17816,
541,
14155,
20238,
23004,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
20285,
62,
35720,
62,
22766,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8352,
62,
35720,
62,
22766,
796,
685,
20285,
62,
35720,
62,
22766,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
8352,
62,
35720,
62,
22766,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
7959,
62,
20285,
62,
35720,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
1057,
62,
7959,
62,
28758,
7,
28758,
62,
4868,
11,
6284,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
2753,
1614,
312,
286,
2496,
3335,
290,
257,
35582,
1351,
286,
13042,
543,
8160,
262,
198,
220,
220,
220,
2176,
9729,
284,
307,
1057,
319,
262,
2496,
3335,
290,
5860,
257,
965,
2134,
7268,
262,
198,
220,
220,
220,
5072,
286,
262,
9729,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
493,
1614,
312,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
23991,
62,
4868,
25,
1351,
286,
13042,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
965,
286,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
7783,
25,
965,
7268,
262,
2882,
286,
262,
9729,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
23991,
62,
4868,
796,
37250,
13812,
2196,
20520,
628,
220,
220,
220,
13163,
23991,
62,
22915,
796,
1057,
62,
7959,
62,
28758,
7,
23991,
62,
4868,
11,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
6,
940,
11537,
628,
220,
220,
220,
13163,
23991,
62,
22915,
796,
1057,
62,
7959,
62,
28758,
7,
23991,
62,
4868,
11,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
28758,
62,
22915,
8,
318,
8633,
628,
220,
220,
220,
13163,
6818,
705,
28758,
4868,
6,
287,
23991,
62,
22915,
628,
220,
220,
220,
13163,
6818,
705,
13138,
6,
287,
23991,
62,
22915,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
1057,
62,
7959,
62,
28758,
62,
6371,
796,
31051,
320,
66,
3808,
14,
44240,
14,
10414,
8979,
14,
41049,
40109,
6,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
1057,
62,
7959,
62,
28758,
62,
6371,
198,
220,
220,
220,
23991,
62,
4868,
796,
4808,
15883,
62,
28758,
62,
4868,
7,
28758,
62,
4868,
8,
198,
220,
220,
220,
21437,
796,
705,
7061,
90,
366,
25202,
7390,
1,
1058,
366,
7061,
6,
1343,
965,
7,
7959,
312,
8,
1343,
705,
7061,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
28758,
4868,
1,
1058,
1391,
366,
28758,
1,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
7061,
6,
1343,
23991,
62,
4868,
1343,
705,
7061,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
7061,
6,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
7007,
13,
7353,
7,
69,
62,
6371,
11,
1366,
28,
15577,
2220,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
26209,
13,
5239,
8,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
10148,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
33918,
13,
46030,
7,
26209,
13,
5239,
8,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
1057,
62,
7959,
62,
28758,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
2,
770,
2665,
4909,
5499,
543,
8076,
379,
262,
7071,
1241,
628,
198,
4299,
651,
62,
439,
62,
39994,
62,
36604,
7,
18439,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
262,
611,
9630,
1988,
8686,
284,
257,
2176,
198,
220,
220,
220,
7071,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
7071,
3307,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
198,
220,
220,
220,
7308,
19193,
32300,
8265,
329,
262,
2496,
3335,
13,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
493,
393,
965,
1988,
286,
262,
1614,
7390,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
7783,
25,
1351,
286,
8633,
5563,
543,
4909,
262,
3307,
286,
477,
20314,
319,
262,
2496,
3335,
628,
220,
220,
220,
1058,
260,
4906,
25,
1351,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
477,
62,
39994,
62,
36604,
796,
651,
62,
439,
62,
39994,
62,
36604,
7,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
7390,
11639,
940,
11537,
628,
220,
220,
220,
13163,
477,
62,
39994,
62,
36604,
796,
651,
62,
439,
62,
39994,
62,
36604,
7,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
541,
11639,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
439,
62,
39994,
62,
36604,
8,
318,
1351,
628,
220,
220,
220,
13163,
6818,
705,
361,
40489,
6,
287,
477,
62,
39994,
62,
36604,
58,
15,
60,
628,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
651,
62,
439,
62,
39994,
62,
36604,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
8,
1343,
12813,
39994,
20924,
9688,
28,
15,
5,
7857,
28,
12825,
5,
20147,
28,
9562,
5,
23350,
28,
9562,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
651,
62,
439,
62,
39994,
62,
36604,
62,
6371,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
62,
36604,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1614,
62,
36604,
17816,
39994,
20520,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
439,
62,
39994,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
651,
62,
39994,
62,
36604,
7,
361,
9630,
11,
6284,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
2753,
262,
1614,
7390,
286,
257,
2176,
3335,
290,
262,
611,
9630,
1988,
8686,
284,
257,
2176,
198,
220,
220,
220,
7071,
220,
290,
2428,
257,
30617,
46476,
869,
284,
651,
262,
7071,
3307,
198,
220,
220,
220,
2393,
355,
1900,
416,
262,
6574,
8959,
34,
7308,
19193,
32300,
8265,
329,
262,
2496,
3335,
13,
628,
220,
220,
220,
1058,
17143,
611,
9630,
25,
493,
393,
965,
1988,
286,
262,
611,
15732,
286,
262,
2496,
7071,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
220,
493,
393,
965,
1988,
286,
262,
1614,
7390,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
965,
286,
20966,
85,
19,
2209,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
7783,
25,
8633,
543,
4909,
262,
3307,
286,
262,
2496,
7071,
1,
628,
220,
220,
220,
1058,
260,
4906,
25,
8633,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
7071,
62,
36604,
796,
651,
62,
39994,
62,
36604,
10786,
16,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
7390,
796,
705,
940,
11537,
628,
220,
220,
220,
13163,
7071,
62,
36604,
796,
651,
62,
39994,
62,
36604,
10786,
16,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
39994,
62,
36604,
8,
318,
8633,
628,
220,
220,
220,
13163,
6818,
705,
361,
40489,
6,
287,
7071,
62,
36604,
628,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
651,
62,
39994,
62,
36604,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
39994,
30487,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
7,
361,
9630,
8,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
651,
62,
39994,
62,
36604,
62,
6371,
198,
220,
220,
220,
2882,
796,
7007,
13,
1136,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
939,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1614,
62,
36604,
796,
357,
17752,
13,
46030,
7,
26209,
13,
5239,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1614,
62,
36604,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
651,
62,
39994,
62,
36604,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
900,
62,
39994,
62,
2902,
7,
361,
9630,
11,
6284,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
256,
461,
395,
1614,
312,
290,
611,
9630,
286,
2176,
3335,
290,
7071,
290,
2428,
257,
30617,
46476,
869,
198,
220,
220,
220,
284,
366,
4423,
1,
262,
7368,
7071,
319,
262,
2496,
3335,
13,
198,
220,
220,
220,
1058,
17143,
1614,
312,
25,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
20966,
85,
19,
2209,
286,
262,
2496,
4410,
628,
220,
220,
220,
1058,
17143,
611,
9630,
25,
493,
393,
965,
1988,
286,
262,
2496,
7071,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
14626,
3722,
2438,
26956,
351,
645,
3815,
13,
628,
220,
220,
220,
1058,
81,
4906,
25,
600,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
600,
891,
558,
62,
929,
10786,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
600,
891,
558,
62,
929,
10786,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
6818,
2099,
7,
600,
62,
2902,
62,
26209,
8,
318,
493,
628,
220,
220,
220,
13163,
6818,
493,
62,
2902,
62,
26209,
318,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
600,
891,
558,
62,
929,
10786,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
900,
62,
600,
62,
2902,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
39994,
30487,
1343,
965,
7,
361,
9630,
8,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12813,
2902,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
900,
62,
600,
62,
2902,
62,
6371,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
7007,
13,
1996,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
26209,
13,
13376,
62,
8189,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
26956,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2882,
13,
13376,
62,
8189,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
900,
62,
600,
891,
558,
62,
2902,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
900,
62,
600,
891,
558,
62,
929,
7,
361,
9630,
11,
6284,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
256,
461,
395,
1614,
312,
290,
611,
9630,
286,
2176,
3335,
290,
7071,
290,
2428,
257,
30617,
46476,
869,
198,
220,
220,
220,
284,
366,
41204,
4423,
1,
262,
7368,
7071,
319,
262,
2496,
3335,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
20966,
85,
19,
2209,
286,
262,
2496,
4410,
628,
220,
220,
220,
1058,
17143,
611,
9630,
25,
493,
393,
965,
1988,
286,
262,
2496,
7071,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
14626,
3722,
2438,
26956,
351,
645,
3815,
13,
628,
220,
220,
220,
1058,
563,
431,
25,
493,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
600,
891,
558,
62,
929,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
600,
891,
558,
62,
929,
10786,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
600,
62,
929,
62,
26209,
8,
318,
493,
628,
220,
220,
220,
13163,
6818,
493,
62,
929,
62,
26209,
318,
26956,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
900,
62,
600,
62,
929,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
39994,
30487,
1343,
965,
7,
361,
9630,
8,
1343,
12813,
929,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
900,
62,
600,
62,
929,
62,
6371,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
7007,
13,
1996,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
26956,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2882,
13,
13376,
62,
8189,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
900,
62,
600,
891,
558,
62,
929,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
900,
62,
39994,
62,
929,
7,
361,
9630,
11,
6284,
11,
19016,
11,
1614,
312,
28,
14202,
11,
1614,
541,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2163,
256,
461,
395,
1614,
312,
290,
611,
9630,
286,
2176,
3335,
290,
7071,
290,
2428,
257,
30617,
46476,
869,
198,
220,
220,
220,
284,
366,
41204,
4423,
1,
262,
7368,
7071,
319,
262,
2496,
3335,
13,
628,
220,
220,
220,
1058,
17143,
1614,
312,
25,
493,
393,
965,
1988,
286,
262,
2496,
3335,
628,
220,
220,
220,
1058,
17143,
1614,
541,
25,
20966,
85,
19,
2209,
286,
262,
2496,
4410,
628,
220,
220,
220,
1058,
17143,
611,
9630,
25,
493,
393,
965,
1988,
286,
262,
2496,
7071,
628,
220,
220,
220,
1058,
17143,
6284,
25,
7007,
6284,
2134,
1303,
23073,
6284,
13,
66,
445,
82,
422,
6284,
12972,
71,
431,
320,
66,
13,
18439,
13,
4871,
628,
220,
220,
220,
1058,
17143,
19016,
25,
2779,
19016,
286,
8959,
34,
19340,
7071,
1303,
23073,
6284,
13,
6371,
422,
12972,
71,
431,
320,
66,
13,
18439,
13,
18439,
4871,
628,
220,
220,
220,
1058,
7783,
25,
14626,
3722,
2438,
26956,
351,
645,
3815,
13,
628,
220,
220,
220,
1058,
563,
431,
25,
493,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
18439,
1330,
1635,
628,
220,
220,
220,
13163,
422,
12972,
71,
431,
320,
66,
13,
489,
265,
13,
25202,
1330,
1635,
628,
220,
220,
220,
13163,
6284,
796,
8959,
8141,
1071,
7203,
4023,
1378,
1600,
366,
940,
13,
8784,
13,
15,
13,
22416,
1600,
366,
1795,
1795,
1600,
366,
28482,
1600,
366,
28482,
4943,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
39994,
62,
929,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
628,
220,
220,
220,
13163,
493,
62,
2902,
62,
26209,
796,
900,
62,
39994,
62,
2902,
7,
705,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
312,
796,
705,
940,
11537,
198,
220,
220,
220,
26956,
628,
220,
220,
220,
13163,
493,
62,
929,
62,
26209,
796,
900,
62,
39994,
62,
929,
10786,
24,
3256,
6284,
13,
66,
445,
82,
11,
6284,
13,
6371,
11,
1614,
541,
796,
705,
940,
13,
8784,
13,
15,
13,
26115,
11537,
628,
220,
220,
220,
13163,
6818,
2099,
7,
600,
62,
929,
62,
26209,
8,
318,
493,
628,
220,
220,
220,
13163,
6818,
493,
62,
929,
62,
26209,
318,
26956,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
1614,
541,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
312,
796,
651,
62,
7959,
62,
36604,
7,
7959,
541,
11,
6284,
11,
19016,
8,
17816,
312,
20520,
198,
220,
220,
220,
900,
62,
600,
62,
929,
62,
6371,
796,
12813,
320,
66,
3808,
14,
489,
265,
14,
411,
14,
25202,
30487,
1343,
965,
7,
7959,
312,
8,
1343,
12813,
39994,
30487,
1343,
965,
7,
361,
9630,
8,
1343,
12813,
929,
1,
198,
220,
220,
220,
277,
62,
6371,
796,
19016,
1343,
900,
62,
600,
62,
929,
62,
6371,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
7007,
13,
1996,
7,
69,
62,
6371,
11,
6284,
28,
18439,
11,
24697,
28,
37682,
4877,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
13,
13376,
62,
8189,
6624,
26956,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2882,
13,
13376,
62,
8189,
198,
220,
220,
220,
2845,
7007,
13,
1069,
11755,
13,
18453,
16922,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
366,
12331,
7479,
77,
1,
1343,
965,
7,
18224,
8,
1343,
366,
900,
62,
39994,
62,
929,
25,
1052,
13047,
468,
1609,
1522,
1,
628,
198,
4299,
4808,
15883,
62,
28758,
62,
4868,
7,
28758,
62,
4868,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
5053,
525,
2163,
284,
3538,
2251,
262,
1774,
33918,
1296,
515,
4731,
422,
257,
1351,
286,
965,
82,
198,
220,
220,
220,
1058,
17143,
23991,
62,
4868,
25,
1351,
286,
13042,
198,
220,
220,
220,
1058,
7783,
25,
965,
33918,
39559,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
23991,
796,
10148,
198,
220,
220,
220,
329,
1312,
287,
23991,
62,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
23991,
796,
23991,
1343,
705,
30543,
1343,
1312,
1343,
705,
1600,
6,
198,
220,
220,
220,
23991,
796,
23991,
58,
21912,
16,
60,
198,
220,
220,
220,
1441,
23991,
198
] | 2.624469 | 12,236 |
from .base import (
CPObject, TextField, ObjectField, BooleanField, LinkField, CollectionField
)
from .qualifier import Qualifier
| [
6738,
764,
8692,
1330,
357,
198,
220,
220,
220,
16932,
10267,
11,
8255,
15878,
11,
9515,
15878,
11,
41146,
15878,
11,
7502,
15878,
11,
12251,
15878,
198,
8,
198,
6738,
764,
13255,
7483,
1330,
9537,
7483,
628
] | 3.648649 | 37 |
from pydp.algorithms import laplacian as dp
import numpy as np
import pandas as pd
import time
import os
import psutil
from utils import *
epsilon = pd.read_pickle('epsilon.pkl')
library_name = 'pydp'
| [
6738,
279,
5173,
79,
13,
282,
7727,
907,
1330,
8591,
489,
330,
666,
355,
288,
79,
198,
11748,
299,
32152,
355,
45941,
220,
198,
11748,
19798,
292,
355,
279,
67,
220,
198,
11748,
640,
198,
11748,
28686,
198,
11748,
26692,
22602,
198,
6738,
3384,
4487,
1330,
1635,
198,
538,
18217,
261,
796,
279,
67,
13,
961,
62,
27729,
293,
10786,
538,
18217,
261,
13,
79,
41582,
11537,
198,
198,
32016,
62,
3672,
796,
705,
79,
5173,
79,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198
] | 2.329787 | 94 |
from django.apps import AppConfig
| [
6738,
42625,
14208,
13,
18211,
1330,
2034,
16934,
628
] | 3.888889 | 9 |
import io
from pathlib import Path
import re
import responses
from shutil import copy
from testpath import MockCommand, modified_env, assert_isfile, assert_isdir
from testpath.tempdir import TemporaryWorkingDirectory
from zipfile import ZipFile
from nsist import main
from nsist.util import CACHE_ENV_VAR
from .utils import test_dir
example_dir = Path(test_dir, 'console_example')
@responses.activate
| [
11748,
33245,
198,
6738,
3108,
8019,
1330,
10644,
198,
11748,
302,
198,
11748,
9109,
198,
6738,
4423,
346,
1330,
4866,
198,
6738,
1332,
6978,
1330,
44123,
21575,
11,
9518,
62,
24330,
11,
6818,
62,
4468,
576,
11,
6818,
62,
9409,
343,
198,
6738,
1332,
6978,
13,
29510,
15908,
1330,
46042,
28516,
43055,
198,
6738,
19974,
7753,
1330,
38636,
8979,
198,
198,
6738,
36545,
396,
1330,
1388,
198,
6738,
36545,
396,
13,
22602,
1330,
327,
2246,
13909,
62,
1677,
53,
62,
53,
1503,
198,
6738,
764,
26791,
1330,
1332,
62,
15908,
198,
198,
20688,
62,
15908,
796,
10644,
7,
9288,
62,
15908,
11,
705,
41947,
62,
20688,
11537,
198,
198,
31,
16733,
274,
13,
39022,
198
] | 3.513043 | 115 |
"""
..
Copyright (c) 2014-2017, Magni developers.
All rights reserved.
See LICENSE.rst for further information.
Module providing a robust configger class.
Routine listings
----------------
Configger(object)
Provide functionality to access a set of configuration options.
Notes
-----
This module does not itself contain any configuration options and thus has no
access to any configuration options unlike the other config modules of `magni`.
"""
from __future__ import division
from itertools import chain
from magni.utils.validation import decorate_validation as _decorate_validation
from magni.utils.validation import validate_generic as _generic
from magni.utils.validation import validate_levels as _levels
from magni.utils.validation import validate_numeric as _numeric
class Configger(object):
"""
Provide functionality to access a set of configuration options.
The set of configuration options, their default values, and their
validation schemes are specified upon initialisation.
Parameters
----------
params : dict
The configuration options and their default values.
valids : dict
The validation schemes of the configuration options.
See Also
--------
magni.utils.validation : Validation.
Notes
-----
`valids` must contain the same keys as `params`. For each key in 'valids',
the first value is the validation function ('generic', 'levels', or
'numeric'), whereas the remaining values are passed to that validation
function.
Examples
--------
Instantiate Configger with the parameter 'key' with default value 'default'
which can only assume string values.
>>> import magni
>>> from magni.utils.config import Configger
>>> valid = magni.utils.validation.validate_generic(None, 'string')
>>> config = Configger({'key': 'default'}, {'key': valid})
The number of parameters can be retrieved as the length:
>>> len(config)
1
That parameter can be retrieved in a number of ways:
>>> config['key']
'default'
>>> for key, value in config.items():
... print('key: {!r}, value: {!r}'.format(key, value))
key: 'key', value: 'default'
>>> for key in config.keys():
... print('key: {!r}'.format(key))
key: 'key'
>>> for value in config.values():
... print('value: {!r}'.format(value))
value: 'default'
Likewise, the parameter can be changed in a number of ways:
>>> config['key'] = 'value'
>>> config['key']
'value'
>>> config.update({'key': 'value changed by dict'})
>>> config['key']
'value changed by dict'
>>> config.update(key='value changed by keyword')
>>> config['key']
'value changed by keyword'
Finally, the parameter can be reset to the default value at any point:
>>> config.reset()
>>> config['key']
'default'
"""
_funcs = {'generic': _generic, 'levels': _levels, 'numeric': _numeric}
def __getitem__(self, name):
"""
Get the value of a configuration parameter.
Parameters
----------
name : str
The name of the parameter.
Returns
-------
value : None
The value of the parameter.
"""
@_decorate_validation
validate_input()
return self._params[name]
def __len__(self):
"""
Get the number of configuration parameters.
Returns
-------
length : int
The number of parameters.
"""
return len(self._params)
def __setitem__(self, name, value):
"""
Set the value of a configuration parameter.
The value is validated according to the validation scheme of that
parameter.
Parameters
----------
name : str
The name of the parameter.
value : None
The new value of the parameter.
"""
@_decorate_validation
validate_input()
self._params[name] = value
def get(self, key=None):
"""
Deprecated method.
See Also
--------
Configger.__getitem__ : Replacing method.
Configger.items : Replacing method.
Configger.keys : Replacing method.
Configger.values : Replacing method.
"""
raise DeprecationWarning("'get' will be removed in version 1.3.0 - "
"use 'var[name]', 'items', 'keys', or "
"'values' instead.")
if key is None:
return dict(self.items())
else:
return self[key]
def items(self):
"""
Get the configuration parameters as key, value pairs.
Returns
-------
items : set-like
The list of parameters.
"""
for key in self.keys():
yield (key, self[key])
def keys(self):
"""
Get the configuration parameter keys.
Returns
-------
keys : set-like
The keys.
"""
return self._params.keys()
def reset(self):
"""
Reset the parameter values to the default values.
"""
self._params = self._default.copy()
def set(self, dictionary={}, **kwargs):
"""
Deprecated method.
See Also
--------
Configger.__setitem__ : Replacing function.
"""
raise DeprecationWarning("'set' will be removed in version 1.3.0 - "
"use 'var[name] = value' or 'update' "
"instead.")
self.update(dictionary, **kwargs)
def update(self, params={}, **kwargs):
"""
Update the value of one or more configuration parameters.
Each value is validated according to the validation scheme of that
parameter.
Parameters
----------
params : dict, optional
A dictionary containing the key and values to update. (the default
value is an empty dictionary)
kwargs : dict
Keyword arguments being the key and values to update.
"""
@_decorate_validation
validate_input()
if params is not None:
for key, value in params.items():
self[key] = value
if len(kwargs) > 0:
for key, value in kwargs.items():
self[key] = value
def values(self):
"""
Get the configuration parameter values.
Returns
-------
values : set-like
The values.
"""
for key in self.keys():
yield self[key]
| [
37811,
198,
492,
198,
220,
220,
220,
15069,
357,
66,
8,
1946,
12,
5539,
11,
2944,
8461,
6505,
13,
198,
220,
220,
220,
1439,
2489,
10395,
13,
198,
220,
220,
220,
4091,
38559,
24290,
13,
81,
301,
329,
2252,
1321,
13,
198,
198,
26796,
4955,
257,
12373,
4566,
1362,
1398,
13,
198,
198,
49,
28399,
26890,
198,
1783,
198,
16934,
1362,
7,
15252,
8,
198,
220,
220,
220,
44290,
11244,
284,
1895,
257,
900,
286,
8398,
3689,
13,
198,
198,
16130,
198,
30934,
198,
1212,
8265,
857,
407,
2346,
3994,
597,
8398,
3689,
290,
4145,
468,
645,
198,
15526,
284,
597,
8398,
3689,
5023,
262,
584,
4566,
13103,
286,
4600,
76,
4660,
72,
44646,
198,
198,
37811,
198,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
6738,
340,
861,
10141,
1330,
6333,
198,
198,
6738,
7842,
72,
13,
26791,
13,
12102,
341,
1330,
11705,
378,
62,
12102,
341,
355,
4808,
12501,
16262,
62,
12102,
341,
198,
6738,
7842,
72,
13,
26791,
13,
12102,
341,
1330,
26571,
62,
41357,
355,
4808,
41357,
198,
6738,
7842,
72,
13,
26791,
13,
12102,
341,
1330,
26571,
62,
46170,
355,
4808,
46170,
198,
6738,
7842,
72,
13,
26791,
13,
12102,
341,
1330,
26571,
62,
77,
39223,
355,
4808,
77,
39223,
628,
198,
4871,
17056,
1362,
7,
15252,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
44290,
11244,
284,
1895,
257,
900,
286,
8398,
3689,
13,
628,
220,
220,
220,
383,
900,
286,
8398,
3689,
11,
511,
4277,
3815,
11,
290,
511,
198,
220,
220,
220,
21201,
16546,
389,
7368,
2402,
4238,
5612,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
42287,
1058,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
383,
8398,
3689,
290,
511,
4277,
3815,
13,
198,
220,
220,
220,
1188,
2340,
1058,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
383,
21201,
16546,
286,
262,
8398,
3689,
13,
628,
220,
220,
220,
4091,
4418,
198,
220,
220,
220,
24200,
198,
220,
220,
220,
7842,
72,
13,
26791,
13,
12102,
341,
1058,
3254,
24765,
13,
628,
220,
220,
220,
11822,
198,
220,
220,
220,
37404,
198,
220,
220,
220,
4600,
2100,
2340,
63,
1276,
3994,
262,
976,
8251,
355,
4600,
37266,
44646,
1114,
1123,
1994,
287,
705,
2100,
2340,
3256,
198,
220,
220,
220,
262,
717,
1988,
318,
262,
21201,
2163,
19203,
41357,
3256,
705,
46170,
3256,
393,
198,
220,
220,
220,
705,
77,
39223,
33809,
9472,
262,
5637,
3815,
389,
3804,
284,
326,
21201,
198,
220,
220,
220,
2163,
13,
628,
220,
220,
220,
21066,
198,
220,
220,
220,
24200,
198,
220,
220,
220,
24470,
9386,
17056,
1362,
351,
262,
11507,
705,
2539,
6,
351,
4277,
1988,
705,
12286,
6,
198,
220,
220,
220,
543,
460,
691,
7048,
4731,
3815,
13,
628,
220,
220,
220,
13163,
1330,
7842,
72,
198,
220,
220,
220,
13163,
422,
7842,
72,
13,
26791,
13,
11250,
1330,
17056,
1362,
198,
220,
220,
220,
13163,
4938,
796,
7842,
72,
13,
26791,
13,
12102,
341,
13,
12102,
378,
62,
41357,
7,
14202,
11,
705,
8841,
11537,
198,
220,
220,
220,
13163,
4566,
796,
17056,
1362,
15090,
6,
2539,
10354,
705,
12286,
6,
5512,
1391,
6,
2539,
10354,
4938,
30072,
628,
220,
220,
220,
383,
1271,
286,
10007,
460,
307,
29517,
355,
262,
4129,
25,
628,
220,
220,
220,
13163,
18896,
7,
11250,
8,
198,
220,
220,
220,
352,
628,
220,
220,
220,
1320,
11507,
460,
307,
29517,
287,
257,
1271,
286,
2842,
25,
628,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
198,
220,
220,
220,
705,
12286,
6,
628,
220,
220,
220,
13163,
329,
1994,
11,
1988,
287,
4566,
13,
23814,
33529,
198,
220,
220,
220,
2644,
220,
220,
220,
220,
3601,
10786,
2539,
25,
1391,
0,
81,
5512,
1988,
25,
1391,
0,
81,
92,
4458,
18982,
7,
2539,
11,
1988,
4008,
198,
220,
220,
220,
1994,
25,
705,
2539,
3256,
1988,
25,
705,
12286,
6,
628,
220,
220,
220,
13163,
329,
1994,
287,
4566,
13,
13083,
33529,
198,
220,
220,
220,
2644,
220,
220,
220,
220,
3601,
10786,
2539,
25,
1391,
0,
81,
92,
4458,
18982,
7,
2539,
4008,
198,
220,
220,
220,
1994,
25,
705,
2539,
6,
628,
220,
220,
220,
13163,
329,
1988,
287,
4566,
13,
27160,
33529,
198,
220,
220,
220,
2644,
220,
220,
220,
220,
3601,
10786,
8367,
25,
1391,
0,
81,
92,
4458,
18982,
7,
8367,
4008,
198,
220,
220,
220,
1988,
25,
705,
12286,
6,
628,
220,
220,
220,
22660,
11,
262,
11507,
460,
307,
3421,
287,
257,
1271,
286,
2842,
25,
628,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
796,
705,
8367,
6,
198,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
198,
220,
220,
220,
705,
8367,
6,
628,
220,
220,
220,
13163,
4566,
13,
19119,
15090,
6,
2539,
10354,
705,
8367,
3421,
416,
8633,
6,
30072,
198,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
198,
220,
220,
220,
705,
8367,
3421,
416,
8633,
6,
628,
220,
220,
220,
13163,
4566,
13,
19119,
7,
2539,
11639,
8367,
3421,
416,
21179,
11537,
198,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
198,
220,
220,
220,
705,
8367,
3421,
416,
21179,
6,
628,
220,
220,
220,
9461,
11,
262,
11507,
460,
307,
13259,
284,
262,
4277,
1988,
379,
597,
966,
25,
628,
220,
220,
220,
13163,
4566,
13,
42503,
3419,
198,
220,
220,
220,
13163,
4566,
17816,
2539,
20520,
198,
220,
220,
220,
705,
12286,
6,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
4808,
12543,
6359,
796,
1391,
6,
41357,
10354,
4808,
41357,
11,
705,
46170,
10354,
4808,
46170,
11,
705,
77,
39223,
10354,
4808,
77,
39223,
92,
628,
220,
220,
220,
825,
11593,
1136,
9186,
834,
7,
944,
11,
1438,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3497,
262,
1988,
286,
257,
8398,
11507,
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,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1438,
286,
262,
11507,
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,
1988,
1058,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1988,
286,
262,
11507,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2488,
62,
12501,
16262,
62,
12102,
341,
628,
220,
220,
220,
220,
220,
220,
220,
26571,
62,
15414,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
37266,
58,
3672,
60,
628,
220,
220,
220,
825,
11593,
11925,
834,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3497,
262,
1271,
286,
8398,
10007,
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,
4129,
1058,
493,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1271,
286,
10007,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
18896,
7,
944,
13557,
37266,
8,
628,
220,
220,
220,
825,
11593,
2617,
9186,
834,
7,
944,
11,
1438,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
5345,
262,
1988,
286,
257,
8398,
11507,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
1988,
318,
31031,
1864,
284,
262,
21201,
7791,
286,
326,
198,
220,
220,
220,
220,
220,
220,
220,
11507,
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,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1438,
286,
262,
11507,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
1058,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
649,
1988,
286,
262,
11507,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2488,
62,
12501,
16262,
62,
12102,
341,
628,
220,
220,
220,
220,
220,
220,
220,
26571,
62,
15414,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
37266,
58,
3672,
60,
796,
1988,
628,
220,
220,
220,
825,
651,
7,
944,
11,
1994,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2129,
31023,
2446,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
4418,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
198,
220,
220,
220,
220,
220,
220,
220,
17056,
1362,
13,
834,
1136,
9186,
834,
1058,
18407,
4092,
2446,
13,
198,
220,
220,
220,
220,
220,
220,
220,
17056,
1362,
13,
23814,
1058,
18407,
4092,
2446,
13,
198,
220,
220,
220,
220,
220,
220,
220,
17056,
1362,
13,
13083,
1058,
18407,
4092,
2446,
13,
198,
220,
220,
220,
220,
220,
220,
220,
17056,
1362,
13,
27160,
1058,
18407,
4092,
2446,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
5298,
2129,
8344,
341,
20361,
7203,
6,
1136,
6,
481,
307,
4615,
287,
2196,
352,
13,
18,
13,
15,
532,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1904,
705,
7785,
58,
3672,
60,
3256,
705,
23814,
3256,
705,
13083,
3256,
393,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24018,
27160,
6,
2427,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1994,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
8633,
7,
944,
13,
23814,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
58,
2539,
60,
628,
220,
220,
220,
825,
3709,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3497,
262,
8398,
10007,
355,
1994,
11,
1988,
14729,
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,
3709,
1058,
900,
12,
2339,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1351,
286,
10007,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
287,
2116,
13,
13083,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
357,
2539,
11,
2116,
58,
2539,
12962,
628,
220,
220,
220,
825,
8251,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3497,
262,
8398,
11507,
8251,
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,
8251,
1058,
900,
12,
2339,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
8251,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
37266,
13,
13083,
3419,
628,
220,
220,
220,
825,
13259,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
30027,
262,
11507,
3815,
284,
262,
4277,
3815,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
37266,
796,
2116,
13557,
12286,
13,
30073,
3419,
628,
220,
220,
220,
825,
900,
7,
944,
11,
22155,
34758,
5512,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2129,
31023,
2446,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
4418,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
198,
220,
220,
220,
220,
220,
220,
220,
17056,
1362,
13,
834,
2617,
9186,
834,
1058,
18407,
4092,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
5298,
2129,
8344,
341,
20361,
7203,
6,
2617,
6,
481,
307,
4615,
287,
2196,
352,
13,
18,
13,
15,
532,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1904,
705,
7785,
58,
3672,
60,
796,
1988,
6,
393,
705,
19119,
6,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
38070,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
19119,
7,
67,
14188,
11,
12429,
46265,
22046,
8,
628,
220,
220,
220,
825,
4296,
7,
944,
11,
42287,
34758,
5512,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
10133,
262,
1988,
286,
530,
393,
517,
8398,
10007,
13,
628,
220,
220,
220,
220,
220,
220,
220,
5501,
1988,
318,
31031,
1864,
284,
262,
21201,
7791,
286,
326,
198,
220,
220,
220,
220,
220,
220,
220,
11507,
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,
42287,
1058,
8633,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
317,
22155,
7268,
262,
1994,
290,
3815,
284,
4296,
13,
357,
1169,
4277,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
318,
281,
6565,
22155,
8,
198,
220,
220,
220,
220,
220,
220,
220,
479,
86,
22046,
1058,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7383,
4775,
7159,
852,
262,
1994,
290,
3815,
284,
4296,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2488,
62,
12501,
16262,
62,
12102,
341,
628,
220,
220,
220,
220,
220,
220,
220,
26571,
62,
15414,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
611,
42287,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
11,
1988,
287,
42287,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
58,
2539,
60,
796,
1988,
628,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
46265,
22046,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
11,
1988,
287,
479,
86,
22046,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
58,
2539,
60,
796,
1988,
628,
220,
220,
220,
825,
3815,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3497,
262,
8398,
11507,
3815,
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,
3815,
1058,
900,
12,
2339,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
3815,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
287,
2116,
13,
13083,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
2116,
58,
2539,
60,
198
] | 2.507784 | 2,698 |
"""
Grouped boxplots
================
"""
import seaborn as sns
sns.set(style="ticks")
tips = sns.load_dataset("tips")
sns.boxplot("day", "total_bill", "sex", tips, palette="PRGn")
sns.despine(offset=10, trim=True)
| [
37811,
198,
13247,
276,
3091,
489,
1747,
198,
4770,
198,
198,
37811,
198,
11748,
384,
397,
1211,
355,
3013,
82,
198,
82,
5907,
13,
2617,
7,
7635,
2625,
83,
3378,
4943,
198,
198,
41315,
796,
3013,
82,
13,
2220,
62,
19608,
292,
316,
7203,
41315,
4943,
198,
82,
5907,
13,
3524,
29487,
7203,
820,
1600,
366,
23350,
62,
35546,
1600,
366,
8044,
1600,
9040,
11,
27043,
2625,
4805,
38,
77,
4943,
198,
82,
5907,
13,
8906,
23908,
7,
28968,
28,
940,
11,
15797,
28,
17821,
8,
198
] | 2.494253 | 87 |
import gspread.utils
from django.contrib import admin
from django.utils.safestring import mark_safe
from .models import (
Campaign,
Preparedness,
Surge,
Round,
Config,
CountryUsersGroup,
URLCache,
SpreadSheetImport,
LQASIMCache,
IMStatsCache,
)
admin.site.register(Campaign, CampaignAdmin)
admin.site.register(Preparedness, PreparednessAdmin)
admin.site.register(Config)
admin.site.register(Surge)
admin.site.register(Round)
admin.site.register(CountryUsersGroup)
admin.site.register(URLCache)
admin.site.register(SpreadSheetImport, SpreadSheetImportAdmin)
admin.site.register(LQASIMCache)
admin.site.register(IMStatsCache)
| [
11748,
308,
43639,
13,
26791,
198,
6738,
42625,
14208,
13,
3642,
822,
1330,
13169,
198,
6738,
42625,
14208,
13,
26791,
13,
49585,
395,
1806,
1330,
1317,
62,
21230,
198,
198,
6738,
764,
27530,
1330,
357,
198,
220,
220,
220,
13718,
11,
198,
220,
220,
220,
19141,
1144,
1108,
11,
198,
220,
220,
220,
46774,
11,
198,
220,
220,
220,
10485,
11,
198,
220,
220,
220,
17056,
11,
198,
220,
220,
220,
12946,
14490,
13247,
11,
198,
220,
220,
220,
37902,
5639,
4891,
11,
198,
220,
220,
220,
31843,
3347,
316,
20939,
11,
198,
220,
220,
220,
406,
48,
1921,
3955,
30562,
11,
198,
220,
220,
220,
8959,
29668,
30562,
11,
198,
8,
628,
628,
198,
198,
28482,
13,
15654,
13,
30238,
7,
46102,
11,
13718,
46787,
8,
198,
28482,
13,
15654,
13,
30238,
7,
6719,
29190,
1108,
11,
19141,
1144,
1108,
46787,
8,
198,
28482,
13,
15654,
13,
30238,
7,
16934,
8,
198,
28482,
13,
15654,
13,
30238,
7,
14214,
469,
8,
198,
28482,
13,
15654,
13,
30238,
7,
22685,
8,
198,
28482,
13,
15654,
13,
30238,
7,
33921,
14490,
13247,
8,
198,
28482,
13,
15654,
13,
30238,
7,
4261,
5639,
4891,
8,
198,
28482,
13,
15654,
13,
30238,
7,
44458,
3347,
316,
20939,
11,
31843,
3347,
316,
20939,
46787,
8,
198,
28482,
13,
15654,
13,
30238,
7,
43,
48,
1921,
3955,
30562,
8,
198,
28482,
13,
15654,
13,
30238,
7,
3955,
29668,
30562,
8,
198
] | 2.838983 | 236 |
import numpy as np | [
11748,
299,
32152,
355,
45941
] | 3.6 | 5 |
import cv2
def read(path, video):
"""
@get path, video as string
@return void
"""
realpath = path + video
i = 0
myvideo = cv2.VideoCapture(realpath)
while(myvideo.isOpened()):
ret, frame = myvideo.read()
i += 1
cv2.imshow('frame', frame)
if (cv2.waitKey(0) == ord('c')):
cv2.imwrite('data/'+str(i)+'.png', frame)
if (cv2.waitKey(0) == ord('q')):
break
myvideo.release()
cv2.destroyAllWindows()
path = './mua/khmer/'
video = 'Khmer-Chol-Chnam-Thmay.webm'
read(path, video)
| [
11748,
269,
85,
17,
628,
198,
4299,
1100,
7,
6978,
11,
2008,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2488,
1136,
220,
3108,
11,
2008,
355,
4731,
628,
220,
220,
220,
220,
220,
220,
220,
2488,
7783,
7951,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1103,
6978,
796,
3108,
1343,
2008,
198,
220,
220,
220,
1312,
796,
657,
198,
220,
220,
220,
616,
15588,
796,
269,
85,
17,
13,
10798,
49630,
7,
5305,
6978,
8,
198,
220,
220,
220,
981,
7,
1820,
15588,
13,
271,
18257,
2945,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1005,
11,
5739,
796,
616,
15588,
13,
961,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1312,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
14535,
3256,
5739,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
357,
33967,
17,
13,
17077,
9218,
7,
15,
8,
6624,
2760,
10786,
66,
11537,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
13564,
10786,
7890,
14,
6,
10,
2536,
7,
72,
47762,
4458,
11134,
3256,
5739,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
357,
33967,
17,
13,
17077,
9218,
7,
15,
8,
6624,
2760,
10786,
80,
11537,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
616,
15588,
13,
20979,
3419,
198,
220,
220,
220,
269,
85,
17,
13,
41659,
3237,
11209,
3419,
198,
198,
6978,
796,
705,
19571,
76,
6413,
14,
14636,
647,
14,
6,
198,
15588,
796,
705,
33155,
647,
12,
1925,
349,
12,
1925,
7402,
12,
817,
11261,
13,
12384,
76,
6,
198,
198,
961,
7,
6978,
11,
2008,
8,
198
] | 1.976667 | 300 |
import os
from pathlib import Path
from typing import List
import pytest
| [
11748,
28686,
198,
6738,
3108,
8019,
1330,
10644,
198,
6738,
19720,
1330,
7343,
198,
198,
11748,
12972,
9288,
628,
198
] | 3.8 | 20 |
# coding=utf-8
# Copyright 2021 The Balloon Learning Environment 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.
"""A wrapper for training the Dopamine QR-DQN agent."""
import functools
from typing import Callable, Optional, Sequence, Union
from absl import logging
from balloon_learning_environment.agents import agent
from balloon_learning_environment.agents import dopamine_utils
from balloon_learning_environment.agents import exploration
from balloon_learning_environment.agents import marco_polo_exploration # pylint: disable=unused-import
from balloon_learning_environment.agents import perciatelli44
from dopamine.jax.agents.quantile import quantile_agent
import flax
from flax import linen as nn
import gin
import jax
import jax.numpy as jnp
import numpy as np
@gin.configurable(allowlist=['network',
'exploration_wrapper_constructor',
'checkpoint_duration',
'reload_perciatelli'])
class QuantileAgent(agent.Agent, quantile_agent.JaxQuantileAgent):
"""A wrapper for training the Dopamine QR-DQN agent."""
def __init__(
self,
num_actions: int,
observation_shape: Sequence[int],
*, # Everything after this is a keyword-only argument.
seed: Optional[int] = None,
network: nn.Module = gin.REQUIRED,
exploration_wrapper_constructor: Callable[
[int, Sequence[int]], exploration.Exploration] = gin.REQUIRED,
checkpoint_duration: Optional[int] = gin.REQUIRED,
reload_perciatelli: bool = gin.REQUIRED):
"""Create the Agent.
This agent enables one to wrap action selection with another agent, such
as for exploratory policies. The exploratory agent is in charge of deciding
whether it will pick the action, or the calling QuantileAgent will.
Args:
num_actions: Number of actions.
observation_shape: Shape of input observations.
seed: Optional seed for the PRNG.
network: Network to use for training and inference.
exploration_wrapper_constructor: Exploration wrapper for action selection.
checkpoint_duration: Optional duration of checkpoints for garbage
collection.
reload_perciatelli: Whether to reload the weights from the Perciatelli44
agent.
"""
self._checkpoint_duration = checkpoint_duration
# Although Python MRO goes from left to right, we call each __init__
# function explicitly as opposed to using `super()` (which would just call
# agent.Agent's init) to avoid confusion.
agent.Agent.__init__(self, num_actions, observation_shape)
quantile_agent.JaxQuantileAgent.__init__(
self,
num_actions,
observation_shape=observation_shape,
observation_dtype=jnp.float32,
stack_size=1,
network=network,
seed=seed)
self._exploration_wrapper = exploration_wrapper_constructor(
num_actions, observation_shape)
if reload_perciatelli:
self.online_params = self.load_perciatelli_weights()
self.target_network_params = self.online_params
logging.info('Successfully loaded Perciatelli44 parameters.')
def save_checkpoint(self, checkpoint_dir: str, iteration_number: int) -> None:
"""Checkpoint agent parameters as a pickled dict."""
dopamine_utils.save_checkpoint(
checkpoint_dir, iteration_number,
functools.partial(quantile_agent.JaxQuantileAgent.bundle_and_checkpoint,
self))
# Get rid of old checkpoints if necessary.
if self._checkpoint_duration is not None:
dopamine_utils.clean_up_old_checkpoints(
checkpoint_dir, iteration_number,
checkpoint_duration=self._checkpoint_duration)
def load_checkpoint(self, checkpoint_dir: str, iteration_number: int) -> None:
"""Checkpoint agent parameters as a pickled dict."""
dopamine_utils.load_checkpoint(
checkpoint_dir, iteration_number,
functools.partial(quantile_agent.JaxQuantileAgent.unbundle, self))
@staticmethod
def load_perciatelli_weights() -> flax.core.FrozenDict:
"""Load the Perciatelli weights and convert to a JAX array."""
sess = perciatelli44.load_perciatelli_session()
layer_names = [n.name
for n in sess.graph.as_graph_def().node
if 'Online' in n.name]
param_dict = {}
for name in layer_names:
if not ('weights' in name or 'biases' in name) or 'read' in name:
continue
params = sess.run(sess.graph.get_tensor_by_name(f'{name}:0'))
param_dict[name] = params
jax_params = {
'params': {
'Dense_0': {
'kernel': param_dict['Online/fully_connected/weights'],
'bias': param_dict['Online/fully_connected/biases'],
},
'Dense_1': {
'kernel': param_dict['Online/fully_connected_1/weights'],
'bias': param_dict['Online/fully_connected_1/biases'],
},
'Dense_2': {
'kernel': param_dict['Online/fully_connected_2/weights'],
'bias': param_dict['Online/fully_connected_2/biases'],
},
'Dense_3': {
'kernel': param_dict['Online/fully_connected_3/weights'],
'bias': param_dict['Online/fully_connected_3/biases'],
},
'Dense_4': {
'kernel': param_dict['Online/fully_connected_4/weights'],
'bias': param_dict['Online/fully_connected_4/biases'],
},
'Dense_5': {
'kernel': param_dict['Online/fully_connected_5/weights'],
'bias': param_dict['Online/fully_connected_5/biases'],
},
'Dense_6': {
'kernel': param_dict['Online/fully_connected_6/weights'],
'bias': param_dict['Online/fully_connected_6/biases'],
},
'Dense_7': {
'kernel': param_dict['Online/fully_connected_7/weights'],
'bias': param_dict['Online/fully_connected_7/biases'],
},
}
}
jax_params = jax.tree_map(jnp.asarray, jax_params)
return flax.core.FrozenDict(jax_params)
| [
2,
19617,
28,
40477,
12,
23,
198,
2,
15069,
33448,
383,
47821,
18252,
9344,
46665,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
37811,
32,
29908,
329,
3047,
262,
360,
404,
9862,
42137,
12,
35,
48,
45,
5797,
526,
15931,
198,
198,
11748,
1257,
310,
10141,
198,
6738,
19720,
1330,
4889,
540,
11,
32233,
11,
45835,
11,
4479,
198,
198,
6738,
2352,
75,
1330,
18931,
198,
6738,
21190,
62,
40684,
62,
38986,
13,
49638,
1330,
5797,
198,
6738,
21190,
62,
40684,
62,
38986,
13,
49638,
1330,
26252,
62,
26791,
198,
6738,
21190,
62,
40684,
62,
38986,
13,
49638,
1330,
13936,
198,
6738,
21190,
62,
40684,
62,
38986,
13,
49638,
1330,
1667,
1073,
62,
79,
14057,
62,
20676,
6944,
220,
1303,
279,
2645,
600,
25,
15560,
28,
403,
1484,
12,
11748,
198,
6738,
21190,
62,
40684,
62,
38986,
13,
49638,
1330,
583,
979,
7528,
72,
2598,
198,
6738,
26252,
13,
73,
897,
13,
49638,
13,
40972,
576,
1330,
5554,
576,
62,
25781,
198,
11748,
781,
897,
198,
6738,
781,
897,
1330,
41822,
355,
299,
77,
198,
11748,
39733,
198,
11748,
474,
897,
198,
11748,
474,
897,
13,
77,
32152,
355,
474,
37659,
198,
11748,
299,
32152,
355,
45941,
628,
198,
31,
1655,
13,
11250,
11970,
7,
12154,
4868,
28,
17816,
27349,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
20676,
6944,
62,
48553,
62,
41571,
273,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9122,
4122,
62,
32257,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
2220,
62,
525,
979,
7528,
72,
6,
12962,
198,
4871,
16972,
576,
36772,
7,
25781,
13,
36772,
11,
5554,
576,
62,
25781,
13,
41,
897,
24915,
576,
36772,
2599,
198,
220,
37227,
32,
29908,
329,
3047,
262,
360,
404,
9862,
42137,
12,
35,
48,
45,
5797,
526,
15931,
628,
220,
825,
11593,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
997,
62,
4658,
25,
493,
11,
198,
220,
220,
220,
220,
220,
13432,
62,
43358,
25,
45835,
58,
600,
4357,
198,
220,
220,
220,
220,
220,
1635,
11,
220,
1303,
11391,
706,
428,
318,
257,
21179,
12,
8807,
4578,
13,
198,
220,
220,
220,
220,
220,
9403,
25,
32233,
58,
600,
60,
796,
6045,
11,
198,
220,
220,
220,
220,
220,
3127,
25,
299,
77,
13,
26796,
796,
39733,
13,
2200,
10917,
37819,
11,
198,
220,
220,
220,
220,
220,
13936,
62,
48553,
62,
41571,
273,
25,
4889,
540,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
600,
11,
45835,
58,
600,
60,
4357,
13936,
13,
18438,
6944,
60,
796,
39733,
13,
2200,
10917,
37819,
11,
198,
220,
220,
220,
220,
220,
26954,
62,
32257,
25,
32233,
58,
600,
60,
796,
39733,
13,
2200,
10917,
37819,
11,
198,
220,
220,
220,
220,
220,
18126,
62,
525,
979,
7528,
72,
25,
20512,
796,
39733,
13,
2200,
10917,
37819,
2599,
198,
220,
220,
220,
37227,
16447,
262,
15906,
13,
628,
220,
220,
220,
770,
5797,
13536,
530,
284,
14441,
2223,
6356,
351,
1194,
5797,
11,
884,
198,
220,
220,
220,
355,
329,
39180,
2870,
4788,
13,
383,
39180,
2870,
5797,
318,
287,
3877,
286,
14615,
198,
220,
220,
220,
1771,
340,
481,
2298,
262,
2223,
11,
393,
262,
4585,
16972,
576,
36772,
481,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
997,
62,
4658,
25,
7913,
286,
4028,
13,
198,
220,
220,
220,
220,
220,
13432,
62,
43358,
25,
25959,
286,
5128,
13050,
13,
198,
220,
220,
220,
220,
220,
9403,
25,
32233,
9403,
329,
262,
4810,
10503,
13,
198,
220,
220,
220,
220,
220,
3127,
25,
7311,
284,
779,
329,
3047,
290,
32278,
13,
198,
220,
220,
220,
220,
220,
13936,
62,
48553,
62,
41571,
273,
25,
36806,
29908,
329,
2223,
6356,
13,
198,
220,
220,
220,
220,
220,
26954,
62,
32257,
25,
32233,
9478,
286,
36628,
329,
15413,
198,
220,
220,
220,
220,
220,
220,
220,
4947,
13,
198,
220,
220,
220,
220,
220,
18126,
62,
525,
979,
7528,
72,
25,
10127,
284,
18126,
262,
19590,
422,
262,
2448,
979,
7528,
72,
2598,
198,
220,
220,
220,
220,
220,
220,
220,
5797,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2116,
13557,
9122,
4122,
62,
32257,
796,
26954,
62,
32257,
198,
220,
220,
220,
1303,
4900,
11361,
337,
13252,
2925,
422,
1364,
284,
826,
11,
356,
869,
1123,
11593,
15003,
834,
198,
220,
220,
220,
1303,
2163,
11777,
355,
6886,
284,
1262,
4600,
16668,
3419,
63,
357,
4758,
561,
655,
869,
198,
220,
220,
220,
1303,
5797,
13,
36772,
338,
2315,
8,
284,
3368,
10802,
13,
198,
220,
220,
220,
5797,
13,
36772,
13,
834,
15003,
834,
7,
944,
11,
997,
62,
4658,
11,
13432,
62,
43358,
8,
198,
220,
220,
220,
5554,
576,
62,
25781,
13,
41,
897,
24915,
576,
36772,
13,
834,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
4658,
11,
198,
220,
220,
220,
220,
220,
220,
220,
13432,
62,
43358,
28,
672,
3168,
341,
62,
43358,
11,
198,
220,
220,
220,
220,
220,
220,
220,
13432,
62,
67,
4906,
28,
73,
37659,
13,
22468,
2624,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8931,
62,
7857,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3127,
28,
27349,
11,
198,
220,
220,
220,
220,
220,
220,
220,
9403,
28,
28826,
8,
198,
220,
220,
220,
2116,
13557,
20676,
6944,
62,
48553,
796,
13936,
62,
48553,
62,
41571,
273,
7,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
4658,
11,
13432,
62,
43358,
8,
198,
220,
220,
220,
611,
18126,
62,
525,
979,
7528,
72,
25,
198,
220,
220,
220,
220,
220,
2116,
13,
25119,
62,
37266,
796,
2116,
13,
2220,
62,
525,
979,
7528,
72,
62,
43775,
3419,
198,
220,
220,
220,
220,
220,
2116,
13,
16793,
62,
27349,
62,
37266,
796,
2116,
13,
25119,
62,
37266,
198,
220,
220,
220,
220,
220,
18931,
13,
10951,
10786,
33244,
2759,
9639,
2448,
979,
7528,
72,
2598,
10007,
2637,
8,
628,
220,
825,
3613,
62,
9122,
4122,
7,
944,
11,
26954,
62,
15908,
25,
965,
11,
24415,
62,
17618,
25,
493,
8,
4613,
6045,
25,
198,
220,
220,
220,
37227,
9787,
4122,
5797,
10007,
355,
257,
2298,
992,
8633,
526,
15931,
198,
220,
220,
220,
26252,
62,
26791,
13,
21928,
62,
9122,
4122,
7,
198,
220,
220,
220,
220,
220,
220,
220,
26954,
62,
15908,
11,
24415,
62,
17618,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
40972,
576,
62,
25781,
13,
41,
897,
24915,
576,
36772,
13,
65,
31249,
62,
392,
62,
9122,
4122,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
4008,
198,
220,
220,
220,
1303,
3497,
5755,
286,
1468,
36628,
611,
3306,
13,
198,
220,
220,
220,
611,
2116,
13557,
9122,
4122,
62,
32257,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
26252,
62,
26791,
13,
27773,
62,
929,
62,
727,
62,
9122,
13033,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26954,
62,
15908,
11,
24415,
62,
17618,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26954,
62,
32257,
28,
944,
13557,
9122,
4122,
62,
32257,
8,
628,
220,
825,
3440,
62,
9122,
4122,
7,
944,
11,
26954,
62,
15908,
25,
965,
11,
24415,
62,
17618,
25,
493,
8,
4613,
6045,
25,
198,
220,
220,
220,
37227,
9787,
4122,
5797,
10007,
355,
257,
2298,
992,
8633,
526,
15931,
198,
220,
220,
220,
26252,
62,
26791,
13,
2220,
62,
9122,
4122,
7,
198,
220,
220,
220,
220,
220,
220,
220,
26954,
62,
15908,
11,
24415,
62,
17618,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1257,
310,
10141,
13,
47172,
7,
40972,
576,
62,
25781,
13,
41,
897,
24915,
576,
36772,
13,
403,
65,
31249,
11,
2116,
4008,
628,
220,
2488,
12708,
24396,
198,
220,
825,
3440,
62,
525,
979,
7528,
72,
62,
43775,
3419,
4613,
781,
897,
13,
7295,
13,
37,
42005,
35,
713,
25,
198,
220,
220,
220,
37227,
8912,
262,
2448,
979,
7528,
72,
19590,
290,
10385,
284,
257,
449,
25922,
7177,
526,
15931,
198,
220,
220,
220,
264,
408,
796,
583,
979,
7528,
72,
2598,
13,
2220,
62,
525,
979,
7528,
72,
62,
29891,
3419,
198,
220,
220,
220,
7679,
62,
14933,
796,
685,
77,
13,
3672,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
299,
287,
264,
408,
13,
34960,
13,
292,
62,
34960,
62,
4299,
22446,
17440,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
14439,
6,
287,
299,
13,
3672,
60,
628,
220,
220,
220,
5772,
62,
11600,
796,
23884,
198,
220,
220,
220,
329,
1438,
287,
7679,
62,
14933,
25,
198,
220,
220,
220,
220,
220,
611,
407,
19203,
43775,
6,
287,
1438,
393,
705,
8482,
1386,
6,
287,
1438,
8,
393,
705,
961,
6,
287,
1438,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
42287,
796,
264,
408,
13,
5143,
7,
82,
408,
13,
34960,
13,
1136,
62,
83,
22854,
62,
1525,
62,
3672,
7,
69,
6,
90,
3672,
38362,
15,
6,
4008,
198,
220,
220,
220,
220,
220,
5772,
62,
11600,
58,
3672,
60,
796,
42287,
198,
220,
220,
220,
474,
897,
62,
37266,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
705,
37266,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
15,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
16,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
16,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
16,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
17,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
17,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
17,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
18,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
18,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
18,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
19,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
19,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
19,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
20,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
20,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
20,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
21,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
21,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
21,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
35,
1072,
62,
22,
10354,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
33885,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
22,
14,
43775,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
65,
4448,
10354,
5772,
62,
11600,
17816,
14439,
14,
2759,
62,
15236,
62,
22,
14,
8482,
1386,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
1782,
198,
220,
220,
220,
474,
897,
62,
37266,
796,
474,
897,
13,
21048,
62,
8899,
7,
73,
37659,
13,
292,
18747,
11,
474,
897,
62,
37266,
8,
198,
220,
220,
220,
1441,
781,
897,
13,
7295,
13,
37,
42005,
35,
713,
7,
73,
897,
62,
37266,
8,
198
] | 2.505035 | 2,681 |
"""
Process settlement layer
Written by Ed Oughton.
December 2020
"""
import os
import configparser
import json
import math
import glob
import numpy as np
import pandas as pd
import geopandas as gpd
import pyproj
from shapely.geometry import Point, LineString, Polygon, MultiPolygon, shape, mapping, box
from shapely.ops import unary_union, nearest_points, transform
import rasterio
from rasterio.warp import calculate_default_transform, reproject, Resampling
from rasterio.mask import mask
from rasterstats import zonal_stats, gen_zonal_stats
from tqdm import tqdm
CONFIG = configparser.ConfigParser()
CONFIG.read(os.path.join(os.path.dirname(__file__), 'script_config.ini'))
BASE_PATH = CONFIG['file_locations']['base_path']
DATA_RAW = os.path.join(BASE_PATH, 'raw')
DATA_INTERMEDIATE = os.path.join(BASE_PATH, 'intermediate')
DATA_PROCESSED = os.path.join(BASE_PATH, 'processed')
def find_country_list(continent_list):
"""
This function produces country information by continent.
Parameters
----------
continent_list : list
Contains the name of the desired continent, e.g. ['Africa']
Returns
-------
countries : list of dicts
Contains all desired country information for countries in
the stated continent.
"""
path = os.path.join(DATA_RAW, 'gadm36_levels_shp', 'gadm36_0.shp')
countries = gpd.read_file(path)
glob_info_path = os.path.join(DATA_RAW, '..', 'global_information.csv')
load_glob_info = pd.read_csv(glob_info_path, encoding = "ISO-8859-1")
countries = countries.merge(load_glob_info, left_on='GID_0',
right_on='ISO_3digit')
if len(continent_list) > 0:
selected_countries = countries.loc[countries['continent'].isin(continent_list)]
else:
selected_countries = countries.loc[countries['global'] == 1]
countries = []
for index, country in selected_countries.iterrows():
countries.append({
'country_name': country['country'],
'iso3': country['GID_0'],
'iso2': country['ISO_2digit'],
'regional_level': country['gid_region'],
})
return countries
def process_country_shapes(country):
"""
Creates a single national boundary for the desired country.
Parameters
----------
country : string
Three digit ISO country code.
"""
iso3 = country['iso3']
path = os.path.join(DATA_INTERMEDIATE, iso3)
if os.path.exists(os.path.join(path, 'national_outline.shp')):
return 'Completed national outline processing'
if not os.path.exists(path):
# print('Creating directory {}'.format(path))
os.makedirs(path)
shape_path = os.path.join(path, 'national_outline.shp')
# print('Loading all country shapes')
path = os.path.join(DATA_RAW, 'gadm36_levels_shp', 'gadm36_0.shp')
countries = gpd.read_file(path)
# print('Getting specific country shape for {}'.format(iso3))
single_country = countries[countries.GID_0 == iso3]
# print('Excluding small shapes')
single_country['geometry'] = single_country.apply(
exclude_small_shapes, axis=1)
# print('Adding ISO country code and other global information')
glob_info_path = os.path.join(DATA_RAW, 'global_information.csv')
load_glob_info = pd.read_csv(glob_info_path, encoding = "ISO-8859-1")
single_country = single_country.merge(
load_glob_info,left_on='GID_0', right_on='ISO_3digit')
single_country.to_file(shape_path, driver='ESRI Shapefile')
return
def process_regions(country):
"""
Function for processing the lowest desired subnational regions for the
chosen country.
Parameters
----------
country : string
Three digit ISO country code.
"""
regions = []
iso3 = country['iso3']
level = country['regional_level']
for regional_level in range(1, level + 1):
filename = 'regions_{}_{}.shp'.format(regional_level, iso3)
folder = os.path.join(DATA_INTERMEDIATE, iso3, 'regions')
path_processed = os.path.join(folder, filename)
if os.path.exists(path_processed):
continue
if not os.path.exists(folder):
os.mkdir(folder)
filename = 'gadm36_{}.shp'.format(regional_level)
path_regions = os.path.join(DATA_RAW, 'gadm36_levels_shp', filename)
regions = gpd.read_file(path_regions)
regions = regions[regions.GID_0 == iso3]
regions['geometry'] = regions.apply(exclude_small_shapes, axis=1)
try:
regions.to_file(path_processed, driver='ESRI Shapefile')
except:
pass
return
def process_settlement_layer(country):
"""
Clip the settlement layer to the chosen country boundary and place in
desired country folder.
Parameters
----------
country : string
Three digit ISO country code.
"""
iso3 = country['iso3']
path_settlements = os.path.join(DATA_RAW,'settlement_layer',
'ppp_2020_1km_Aggregated.tif')
settlements = rasterio.open(path_settlements, 'r+')
settlements.nodata = 255
settlements.crs = {"init": "epsg:4326"}
iso3 = country['iso3']
path_country = os.path.join(DATA_INTERMEDIATE, iso3,
'national_outline.shp')
if os.path.exists(path_country):
country = gpd.read_file(path_country)
else:
print('Must generate national_outline.shp first for {}'.format(iso3) )
path_country = os.path.join(DATA_INTERMEDIATE, iso3)
shape_path = os.path.join(path_country, 'settlements.tif')
if os.path.exists(shape_path):
return
bbox = country.envelope
geo = gpd.GeoDataFrame()
geo = gpd.GeoDataFrame({'geometry': bbox})
coords = [json.loads(geo.to_json())['features'][0]['geometry']]
#chop on coords
out_img, out_transform = mask(settlements, coords, crop=True)
# Copy the metadata
out_meta = settlements.meta.copy()
out_meta.update({"driver": "GTiff",
"height": out_img.shape[1],
"width": out_img.shape[2],
"transform": out_transform,
"crs": 'epsg:4326'})
with rasterio.open(shape_path, "w", **out_meta) as dest:
dest.write(out_img)
return
def exclude_small_shapes(x):
"""
Remove small multipolygon shapes.
Parameters
---------
x : polygon
Feature to simplify.
Returns
-------
MultiPolygon : MultiPolygon
Shapely MultiPolygon geometry without tiny shapes.
"""
# if its a single polygon, just return the polygon geometry
if x.geometry.geom_type == 'Polygon':
return x.geometry
# if its a multipolygon, we start trying to simplify
# and remove shapes if its too big.
elif x.geometry.geom_type == 'MultiPolygon':
area1 = 0.01
area2 = 50
# dont remove shapes if total area is already very small
if x.geometry.area < area1:
return x.geometry
# remove bigger shapes if country is really big
if x['GID_0'] in ['CHL','IDN']:
threshold = 0.01
elif x['GID_0'] in ['RUS','GRL','CAN','USA']:
threshold = 0.01
elif x.geometry.area > area2:
threshold = 0.1
else:
threshold = 0.001
# save remaining polygons as new multipolygon for
# the specific country
new_geom = []
for y in x.geometry:
if y.area > threshold:
new_geom.append(y)
return MultiPolygon(new_geom)
def create_pop_regional_lookup(country):
"""
Extract regional luminosity and population data.
Parameters
----------
country : string
Three digit ISO country code.
"""
level = country['regional_level']
iso3 = country['iso3']
GID_level = 'GID_{}'.format(level)
filename = 'population_lookup_level_{}.csv'.format(level)
path_output = os.path.join(DATA_INTERMEDIATE, iso3, filename)
if os.path.exists(path_output):
output = pd.read_csv(path_output).to_dict('records')
return output
filename = 'settlements.tif'
path_settlements = os.path.join(DATA_INTERMEDIATE, iso3, filename)
filename = 'regions_{}_{}.shp'.format(level, iso3)
folder = os.path.join(DATA_INTERMEDIATE, iso3, 'regions')
regions = gpd.read_file(os.path.join(folder, filename), crs='epsg:4326')
output = []
for index, region in regions.iterrows():
area_km = get_area(region['geometry'])
population = find_population(region, path_settlements)
if not isinstance(population, float):
continue
if population > 0:
pop_density_km2 = population / area_km
else:
pop_density_km2 = 0
output.append({
'iso3': iso3,
'regions': region[GID_level],
'population': population,
'area_m': area_km,
'pop_density_km2': pop_density_km2,
})
output_pandas = pd.DataFrame(output)
output_pandas.to_csv(path_output, index=False)
return output
def find_population(region, path_settlements):
"""
"""
with rasterio.open(path_settlements) as src:
affine = src.transform
array = src.read(1)
array[array <= 0] = 0
population = [d['sum'] for d in zonal_stats(
region['geometry'], array, stats=['sum'], affine=affine)][0]
return population
def get_area(modeling_region_geom):
"""
Return the area in square km.
"""
project = pyproj.Transformer.from_crs('epsg:4326', 'epsg:3857', always_xy=True).transform
new_geom = transform(project, modeling_region_geom)
area_km = new_geom.area / 1e6
return area_km
if __name__ == '__main__':
countries = find_country_list([])#[:2] #['Africa']
output = []
for country in tqdm(countries):
print('-Working on {}: {}'.format(country['country_name'], country['iso3']))
process_country_shapes(country)
process_regions(country)
process_settlement_layer(country)
results = create_pop_regional_lookup(country)
output = output + results
path_output = os.path.join(DATA_INTERMEDIATE, 'global_regional_population_lookup.csv')
output = pd.DataFrame(output)
output.to_csv(path_output, index=False)
print('Preprocessing complete')
| [
37811,
198,
18709,
9443,
7679,
198,
198,
25354,
416,
1717,
440,
6724,
1122,
13,
198,
198,
20588,
12131,
198,
198,
37811,
198,
11748,
28686,
198,
11748,
4566,
48610,
198,
11748,
33918,
198,
11748,
10688,
198,
11748,
15095,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
30324,
392,
292,
355,
27809,
67,
198,
11748,
12972,
1676,
73,
198,
6738,
5485,
306,
13,
469,
15748,
1330,
6252,
11,
6910,
10100,
11,
12280,
14520,
11,
15237,
34220,
14520,
11,
5485,
11,
16855,
11,
3091,
198,
6738,
5485,
306,
13,
2840,
1330,
555,
560,
62,
24592,
11,
16936,
62,
13033,
11,
6121,
198,
11748,
374,
1603,
952,
198,
6738,
374,
1603,
952,
13,
86,
5117,
1330,
15284,
62,
12286,
62,
35636,
11,
43969,
752,
11,
1874,
321,
11347,
198,
6738,
374,
1603,
952,
13,
27932,
1330,
9335,
198,
6738,
374,
1603,
34242,
1330,
1976,
20996,
62,
34242,
11,
2429,
62,
89,
20996,
62,
34242,
198,
6738,
256,
80,
36020,
1330,
256,
80,
36020,
198,
198,
10943,
16254,
796,
4566,
48610,
13,
16934,
46677,
3419,
198,
10943,
16254,
13,
961,
7,
418,
13,
6978,
13,
22179,
7,
418,
13,
6978,
13,
15908,
3672,
7,
834,
7753,
834,
828,
705,
12048,
62,
11250,
13,
5362,
6,
4008,
198,
33,
11159,
62,
34219,
796,
25626,
17816,
7753,
62,
17946,
602,
6,
7131,
6,
8692,
62,
6978,
20520,
198,
198,
26947,
62,
20530,
796,
28686,
13,
6978,
13,
22179,
7,
33,
11159,
62,
34219,
11,
705,
1831,
11537,
198,
26947,
62,
41358,
30733,
40,
6158,
796,
28686,
13,
6978,
13,
22179,
7,
33,
11159,
62,
34219,
11,
705,
3849,
13857,
11537,
198,
26947,
62,
4805,
4503,
7597,
1961,
796,
28686,
13,
6978,
13,
22179,
7,
33,
11159,
62,
34219,
11,
705,
14681,
276,
11537,
628,
198,
4299,
1064,
62,
19315,
62,
4868,
7,
3642,
7233,
62,
4868,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
770,
2163,
11073,
1499,
1321,
416,
15549,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
15549,
62,
4868,
1058,
1351,
198,
220,
220,
220,
220,
220,
220,
220,
49850,
262,
1438,
286,
262,
10348,
15549,
11,
304,
13,
70,
13,
37250,
17584,
30997,
20520,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
2678,
1058,
1351,
286,
8633,
82,
198,
220,
220,
220,
220,
220,
220,
220,
49850,
477,
10348,
1499,
1321,
329,
2678,
287,
198,
220,
220,
220,
220,
220,
220,
220,
262,
5081,
15549,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
11,
705,
70,
324,
76,
2623,
62,
46170,
62,
1477,
79,
3256,
705,
70,
324,
76,
2623,
62,
15,
13,
1477,
79,
11537,
198,
220,
220,
220,
2678,
796,
27809,
67,
13,
961,
62,
7753,
7,
6978,
8,
628,
220,
220,
220,
15095,
62,
10951,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
11,
705,
492,
3256,
705,
20541,
62,
17018,
13,
40664,
11537,
198,
220,
220,
220,
3440,
62,
4743,
672,
62,
10951,
796,
279,
67,
13,
961,
62,
40664,
7,
4743,
672,
62,
10951,
62,
6978,
11,
21004,
796,
366,
40734,
12,
3459,
3270,
12,
16,
4943,
198,
220,
220,
220,
2678,
796,
2678,
13,
647,
469,
7,
2220,
62,
4743,
672,
62,
10951,
11,
1364,
62,
261,
11639,
38,
2389,
62,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
826,
62,
261,
11639,
40734,
62,
18,
27003,
11537,
628,
220,
220,
220,
611,
18896,
7,
3642,
7233,
62,
4868,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6163,
62,
9127,
1678,
796,
2678,
13,
17946,
58,
9127,
1678,
17816,
3642,
7233,
6,
4083,
45763,
7,
3642,
7233,
62,
4868,
15437,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6163,
62,
9127,
1678,
796,
2678,
13,
17946,
58,
9127,
1678,
17816,
20541,
20520,
6624,
352,
60,
628,
220,
220,
220,
2678,
796,
17635,
628,
220,
220,
220,
329,
6376,
11,
1499,
287,
6163,
62,
9127,
1678,
13,
2676,
8516,
33529,
628,
220,
220,
220,
220,
220,
220,
220,
2678,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
19315,
62,
3672,
10354,
1499,
17816,
19315,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
26786,
18,
10354,
1499,
17816,
38,
2389,
62,
15,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
26786,
17,
10354,
1499,
17816,
40734,
62,
17,
27003,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2301,
1538,
62,
5715,
10354,
1499,
17816,
70,
312,
62,
36996,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
220,
220,
220,
1441,
2678,
628,
198,
4299,
1429,
62,
19315,
62,
1477,
7916,
7,
19315,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7921,
274,
257,
2060,
2260,
18645,
329,
262,
10348,
1499,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1499,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
7683,
16839,
19694,
1499,
2438,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
47279,
18,
796,
1499,
17816,
26786,
18,
20520,
628,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
8,
628,
220,
220,
220,
611,
28686,
13,
6978,
13,
1069,
1023,
7,
418,
13,
6978,
13,
22179,
7,
6978,
11,
705,
14648,
62,
448,
1370,
13,
1477,
79,
11537,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
705,
43768,
2260,
19001,
7587,
6,
628,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
6978,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3601,
10786,
32071,
8619,
23884,
4458,
18982,
7,
6978,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
6978,
8,
628,
220,
220,
220,
5485,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
6978,
11,
705,
14648,
62,
448,
1370,
13,
1477,
79,
11537,
628,
220,
220,
220,
1303,
3601,
10786,
19031,
477,
1499,
15268,
11537,
198,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
11,
705,
70,
324,
76,
2623,
62,
46170,
62,
1477,
79,
3256,
705,
70,
324,
76,
2623,
62,
15,
13,
1477,
79,
11537,
198,
220,
220,
220,
2678,
796,
27809,
67,
13,
961,
62,
7753,
7,
6978,
8,
628,
220,
220,
220,
1303,
3601,
10786,
20570,
2176,
1499,
5485,
329,
23884,
4458,
18982,
7,
26786,
18,
4008,
198,
220,
220,
220,
2060,
62,
19315,
796,
2678,
58,
9127,
1678,
13,
38,
2389,
62,
15,
6624,
47279,
18,
60,
628,
220,
220,
220,
1303,
3601,
10786,
3109,
6360,
1402,
15268,
11537,
198,
220,
220,
220,
2060,
62,
19315,
17816,
469,
15748,
20520,
796,
2060,
62,
19315,
13,
39014,
7,
198,
220,
220,
220,
220,
220,
220,
220,
19607,
62,
17470,
62,
1477,
7916,
11,
16488,
28,
16,
8,
628,
220,
220,
220,
1303,
3601,
10786,
32901,
19694,
1499,
2438,
290,
584,
3298,
1321,
11537,
198,
220,
220,
220,
15095,
62,
10951,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
11,
705,
20541,
62,
17018,
13,
40664,
11537,
198,
220,
220,
220,
3440,
62,
4743,
672,
62,
10951,
796,
279,
67,
13,
961,
62,
40664,
7,
4743,
672,
62,
10951,
62,
6978,
11,
21004,
796,
366,
40734,
12,
3459,
3270,
12,
16,
4943,
198,
220,
220,
220,
2060,
62,
19315,
796,
2060,
62,
19315,
13,
647,
469,
7,
198,
220,
220,
220,
220,
220,
220,
220,
3440,
62,
4743,
672,
62,
10951,
11,
9464,
62,
261,
11639,
38,
2389,
62,
15,
3256,
826,
62,
261,
11639,
40734,
62,
18,
27003,
11537,
628,
220,
220,
220,
2060,
62,
19315,
13,
1462,
62,
7753,
7,
43358,
62,
6978,
11,
4639,
11639,
1546,
7112,
25959,
7753,
11537,
628,
220,
220,
220,
1441,
628,
198,
4299,
1429,
62,
2301,
507,
7,
19315,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
329,
7587,
262,
9016,
10348,
850,
14648,
7652,
329,
262,
198,
220,
220,
220,
7147,
1499,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1499,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
7683,
16839,
19694,
1499,
2438,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
7652,
796,
17635,
628,
220,
220,
220,
47279,
18,
796,
1499,
17816,
26786,
18,
20520,
198,
220,
220,
220,
1241,
796,
1499,
17816,
2301,
1538,
62,
5715,
20520,
628,
220,
220,
220,
329,
7915,
62,
5715,
287,
2837,
7,
16,
11,
1241,
1343,
352,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
29472,
796,
705,
2301,
507,
23330,
92,
23330,
27422,
1477,
79,
4458,
18982,
7,
2301,
1538,
62,
5715,
11,
47279,
18,
8,
198,
220,
220,
220,
220,
220,
220,
220,
9483,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
11,
705,
2301,
507,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
3108,
62,
14681,
276,
796,
28686,
13,
6978,
13,
22179,
7,
43551,
11,
29472,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
28686,
13,
6978,
13,
1069,
1023,
7,
6978,
62,
14681,
276,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
43551,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
28015,
15908,
7,
43551,
8,
628,
220,
220,
220,
220,
220,
220,
220,
29472,
796,
705,
70,
324,
76,
2623,
23330,
27422,
1477,
79,
4458,
18982,
7,
2301,
1538,
62,
5715,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3108,
62,
2301,
507,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
11,
705,
70,
324,
76,
2623,
62,
46170,
62,
1477,
79,
3256,
29472,
8,
198,
220,
220,
220,
220,
220,
220,
220,
7652,
796,
27809,
67,
13,
961,
62,
7753,
7,
6978,
62,
2301,
507,
8,
628,
220,
220,
220,
220,
220,
220,
220,
7652,
796,
7652,
58,
2301,
507,
13,
38,
2389,
62,
15,
6624,
47279,
18,
60,
628,
220,
220,
220,
220,
220,
220,
220,
7652,
17816,
469,
15748,
20520,
796,
7652,
13,
39014,
7,
1069,
9152,
62,
17470,
62,
1477,
7916,
11,
16488,
28,
16,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7652,
13,
1462,
62,
7753,
7,
6978,
62,
14681,
276,
11,
4639,
11639,
1546,
7112,
25959,
7753,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1208,
628,
220,
220,
220,
1441,
628,
198,
4299,
1429,
62,
17744,
1732,
62,
29289,
7,
19315,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
42512,
262,
9443,
7679,
284,
262,
7147,
1499,
18645,
290,
1295,
287,
198,
220,
220,
220,
10348,
1499,
9483,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1499,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
7683,
16839,
19694,
1499,
2438,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
47279,
18,
796,
1499,
17816,
26786,
18,
20520,
628,
220,
220,
220,
3108,
62,
17744,
3639,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
20530,
4032,
17744,
1732,
62,
29289,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
381,
79,
62,
42334,
62,
16,
13276,
62,
46384,
2301,
515,
13,
49929,
11537,
628,
220,
220,
220,
18573,
796,
374,
1603,
952,
13,
9654,
7,
6978,
62,
17744,
3639,
11,
705,
81,
10,
11537,
198,
220,
220,
220,
18573,
13,
77,
375,
1045,
796,
14280,
198,
220,
220,
220,
18573,
13,
66,
3808,
796,
19779,
15003,
1298,
366,
25386,
70,
25,
3559,
2075,
20662,
628,
220,
220,
220,
47279,
18,
796,
1499,
17816,
26786,
18,
20520,
198,
220,
220,
220,
3108,
62,
19315,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
11,
198,
220,
220,
220,
220,
220,
220,
220,
705,
14648,
62,
448,
1370,
13,
1477,
79,
11537,
628,
220,
220,
220,
611,
28686,
13,
6978,
13,
1069,
1023,
7,
6978,
62,
19315,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1499,
796,
27809,
67,
13,
961,
62,
7753,
7,
6978,
62,
19315,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
34320,
7716,
2260,
62,
448,
1370,
13,
1477,
79,
717,
329,
23884,
4458,
18982,
7,
26786,
18,
8,
1267,
628,
220,
220,
220,
3108,
62,
19315,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
8,
198,
220,
220,
220,
5485,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
6978,
62,
19315,
11,
705,
17744,
3639,
13,
49929,
11537,
628,
220,
220,
220,
611,
28686,
13,
6978,
13,
1069,
1023,
7,
43358,
62,
6978,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
628,
220,
220,
220,
275,
3524,
796,
1499,
13,
268,
1091,
68,
198,
220,
220,
220,
40087,
796,
27809,
67,
13,
10082,
78,
6601,
19778,
3419,
628,
220,
220,
220,
40087,
796,
27809,
67,
13,
10082,
78,
6601,
19778,
15090,
6,
469,
15748,
10354,
275,
3524,
30072,
628,
220,
220,
220,
763,
3669,
796,
685,
17752,
13,
46030,
7,
469,
78,
13,
1462,
62,
17752,
28955,
17816,
40890,
6,
7131,
15,
7131,
6,
469,
15748,
6,
11907,
628,
220,
220,
220,
1303,
354,
404,
319,
763,
3669,
198,
220,
220,
220,
503,
62,
9600,
11,
503,
62,
35636,
796,
9335,
7,
17744,
3639,
11,
763,
3669,
11,
13833,
28,
17821,
8,
628,
220,
220,
220,
1303,
17393,
262,
20150,
198,
220,
220,
220,
503,
62,
28961,
796,
18573,
13,
28961,
13,
30073,
3419,
628,
220,
220,
220,
503,
62,
28961,
13,
19119,
7,
4895,
26230,
1298,
366,
19555,
733,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17015,
1298,
503,
62,
9600,
13,
43358,
58,
16,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
10394,
1298,
503,
62,
9600,
13,
43358,
58,
17,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
35636,
1298,
503,
62,
35636,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
66,
3808,
1298,
705,
25386,
70,
25,
3559,
2075,
6,
30072,
628,
220,
220,
220,
351,
374,
1603,
952,
13,
9654,
7,
43358,
62,
6978,
11,
366,
86,
1600,
12429,
448,
62,
28961,
8,
355,
2244,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2244,
13,
13564,
7,
448,
62,
9600,
8,
628,
220,
220,
220,
1441,
628,
198,
4299,
19607,
62,
17470,
62,
1477,
7916,
7,
87,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
17220,
1402,
18540,
3366,
14520,
15268,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
45337,
198,
220,
220,
220,
2124,
1058,
7514,
14520,
198,
220,
220,
220,
220,
220,
220,
220,
27018,
284,
30276,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
15237,
34220,
14520,
1058,
15237,
34220,
14520,
198,
220,
220,
220,
220,
220,
220,
220,
25959,
306,
15237,
34220,
14520,
22939,
1231,
7009,
15268,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
611,
663,
257,
2060,
7514,
14520,
11,
655,
1441,
262,
7514,
14520,
22939,
198,
220,
220,
220,
611,
2124,
13,
469,
15748,
13,
469,
296,
62,
4906,
6624,
705,
34220,
14520,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2124,
13,
469,
15748,
628,
220,
220,
220,
1303,
611,
663,
257,
18540,
3366,
14520,
11,
356,
923,
2111,
284,
30276,
198,
220,
220,
220,
1303,
290,
4781,
15268,
611,
663,
1165,
1263,
13,
198,
220,
220,
220,
1288,
361,
2124,
13,
469,
15748,
13,
469,
296,
62,
4906,
6624,
705,
29800,
34220,
14520,
10354,
628,
220,
220,
220,
220,
220,
220,
220,
1989,
16,
796,
657,
13,
486,
198,
220,
220,
220,
220,
220,
220,
220,
1989,
17,
796,
2026,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17666,
4781,
15268,
611,
2472,
1989,
318,
1541,
845,
1402,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2124,
13,
469,
15748,
13,
20337,
1279,
1989,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2124,
13,
469,
15748,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4781,
5749,
15268,
611,
1499,
318,
1107,
1263,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2124,
17816,
38,
2389,
62,
15,
20520,
287,
37250,
3398,
43,
41707,
2389,
45,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11387,
796,
657,
13,
486,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2124,
17816,
38,
2389,
62,
15,
20520,
287,
37250,
49,
2937,
41707,
38,
7836,
41707,
44565,
41707,
14053,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11387,
796,
657,
13,
486,
628,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2124,
13,
469,
15748,
13,
20337,
1875,
1989,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11387,
796,
657,
13,
16,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11387,
796,
657,
13,
8298,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3613,
5637,
25052,
684,
355,
649,
18540,
3366,
14520,
329,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
262,
2176,
1499,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
469,
296,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
331,
287,
2124,
13,
469,
15748,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
331,
13,
20337,
1875,
11387,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
469,
296,
13,
33295,
7,
88,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
15237,
34220,
14520,
7,
3605,
62,
469,
296,
8,
628,
198,
4299,
2251,
62,
12924,
62,
2301,
1538,
62,
5460,
929,
7,
19315,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
29677,
7915,
29763,
16579,
290,
3265,
1366,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
628,
220,
220,
220,
1499,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
7683,
16839,
19694,
1499,
2438,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1241,
796,
1499,
17816,
2301,
1538,
62,
5715,
20520,
198,
220,
220,
220,
47279,
18,
796,
1499,
17816,
26786,
18,
20520,
198,
220,
220,
220,
402,
2389,
62,
5715,
796,
705,
38,
2389,
23330,
92,
4458,
18982,
7,
5715,
8,
628,
220,
220,
220,
29472,
796,
705,
39748,
62,
5460,
929,
62,
5715,
23330,
27422,
40664,
4458,
18982,
7,
5715,
8,
198,
220,
220,
220,
3108,
62,
22915,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
11,
29472,
8,
628,
220,
220,
220,
611,
28686,
13,
6978,
13,
1069,
1023,
7,
6978,
62,
22915,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
279,
67,
13,
961,
62,
40664,
7,
6978,
62,
22915,
737,
1462,
62,
11600,
10786,
8344,
3669,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5072,
628,
220,
220,
220,
29472,
796,
705,
17744,
3639,
13,
49929,
6,
198,
220,
220,
220,
3108,
62,
17744,
3639,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
11,
29472,
8,
628,
220,
220,
220,
29472,
796,
705,
2301,
507,
23330,
92,
23330,
27422,
1477,
79,
4458,
18982,
7,
5715,
11,
47279,
18,
8,
198,
220,
220,
220,
9483,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
47279,
18,
11,
705,
2301,
507,
11537,
198,
220,
220,
220,
7652,
796,
27809,
67,
13,
961,
62,
7753,
7,
418,
13,
6978,
13,
22179,
7,
43551,
11,
29472,
828,
1067,
82,
11639,
25386,
70,
25,
3559,
2075,
11537,
628,
220,
220,
220,
5072,
796,
17635,
628,
220,
220,
220,
329,
6376,
11,
3814,
287,
7652,
13,
2676,
8516,
33529,
628,
220,
220,
220,
220,
220,
220,
220,
1989,
62,
13276,
796,
651,
62,
20337,
7,
36996,
17816,
469,
15748,
6,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
3265,
796,
1064,
62,
39748,
7,
36996,
11,
3108,
62,
17744,
3639,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
407,
318,
39098,
7,
39748,
11,
12178,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
611,
3265,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1461,
62,
43337,
62,
13276,
17,
796,
3265,
1220,
1989,
62,
13276,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1461,
62,
43337,
62,
13276,
17,
796,
657,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
26786,
18,
10354,
47279,
18,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2301,
507,
10354,
3814,
58,
38,
2389,
62,
5715,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
39748,
10354,
3265,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
20337,
62,
76,
10354,
1989,
62,
13276,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12924,
62,
43337,
62,
13276,
17,
10354,
1461,
62,
43337,
62,
13276,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
220,
220,
220,
5072,
62,
79,
392,
292,
796,
279,
67,
13,
6601,
19778,
7,
22915,
8,
628,
220,
220,
220,
5072,
62,
79,
392,
292,
13,
1462,
62,
40664,
7,
6978,
62,
22915,
11,
6376,
28,
25101,
8,
628,
220,
220,
220,
1441,
5072,
628,
198,
4299,
1064,
62,
39748,
7,
36996,
11,
3108,
62,
17744,
3639,
2599,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
351,
374,
1603,
952,
13,
9654,
7,
6978,
62,
17744,
3639,
8,
355,
12351,
25,
628,
220,
220,
220,
220,
220,
220,
220,
1527,
500,
796,
12351,
13,
35636,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
796,
12351,
13,
961,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
58,
18747,
19841,
657,
60,
796,
657,
628,
220,
220,
220,
220,
220,
220,
220,
3265,
796,
685,
67,
17816,
16345,
20520,
329,
288,
287,
1976,
20996,
62,
34242,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3814,
17816,
469,
15748,
6,
4357,
7177,
11,
9756,
28,
17816,
16345,
6,
4357,
1527,
500,
28,
2001,
500,
8,
7131,
15,
60,
628,
220,
220,
220,
1441,
3265,
628,
198,
4299,
651,
62,
20337,
7,
4666,
10809,
62,
36996,
62,
469,
296,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
262,
1989,
287,
6616,
10571,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1628,
796,
12972,
1676,
73,
13,
8291,
16354,
13,
6738,
62,
66,
3808,
10786,
25386,
70,
25,
3559,
2075,
3256,
705,
25386,
70,
25,
2548,
3553,
3256,
1464,
62,
5431,
28,
17821,
737,
35636,
198,
220,
220,
220,
649,
62,
469,
296,
796,
6121,
7,
16302,
11,
21128,
62,
36996,
62,
469,
296,
8,
198,
220,
220,
220,
1989,
62,
13276,
796,
649,
62,
469,
296,
13,
20337,
1220,
352,
68,
21,
628,
220,
220,
220,
1441,
1989,
62,
13276,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
628,
220,
220,
220,
2678,
796,
1064,
62,
19315,
62,
4868,
26933,
12962,
2,
58,
25,
17,
60,
1303,
17816,
17584,
30997,
20520,
628,
220,
220,
220,
5072,
796,
17635,
628,
220,
220,
220,
329,
1499,
287,
256,
80,
36020,
7,
9127,
1678,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
12,
28516,
319,
23884,
25,
23884,
4458,
18982,
7,
19315,
17816,
19315,
62,
3672,
6,
4357,
1499,
17816,
26786,
18,
20520,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1429,
62,
19315,
62,
1477,
7916,
7,
19315,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1429,
62,
2301,
507,
7,
19315,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1429,
62,
17744,
1732,
62,
29289,
7,
19315,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2482,
796,
2251,
62,
12924,
62,
2301,
1538,
62,
5460,
929,
7,
19315,
8,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
5072,
1343,
2482,
628,
220,
220,
220,
3108,
62,
22915,
796,
28686,
13,
6978,
13,
22179,
7,
26947,
62,
41358,
30733,
40,
6158,
11,
705,
20541,
62,
2301,
1538,
62,
39748,
62,
5460,
929,
13,
40664,
11537,
198,
220,
220,
220,
5072,
796,
279,
67,
13,
6601,
19778,
7,
22915,
8,
198,
220,
220,
220,
5072,
13,
1462,
62,
40664,
7,
6978,
62,
22915,
11,
6376,
28,
25101,
8,
628,
220,
220,
220,
3601,
10786,
6719,
36948,
1844,
11537,
198
] | 2.430433 | 4,298 |
fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(9, 3))
cols = ['vp', 'vs', 'rho']
labels = ['$V_p$ (m/s)', '$V_s$ (m/s)', 'Density (kg/m$^3$)']
for i, ax in enumerate(axes):
ax.hist(df[cols[i]], density=True, edgecolor='k', linewidth=0.5)
ax.set_xlabel(labels[i])
ax.set_ylabel('Probability')
plt.tight_layout()
plt.savefig('material_dists.pdf')
plt.show()
| [
5647,
11,
34197,
796,
458,
83,
13,
7266,
489,
1747,
7,
77,
8516,
28,
16,
11,
299,
4033,
82,
28,
18,
11,
2336,
7857,
16193,
24,
11,
513,
4008,
198,
4033,
82,
796,
37250,
36133,
3256,
705,
14259,
3256,
705,
81,
8873,
20520,
198,
23912,
1424,
796,
37250,
3,
53,
62,
79,
3,
357,
76,
14,
82,
8,
3256,
705,
3,
53,
62,
82,
3,
357,
76,
14,
82,
8,
3256,
705,
35,
6377,
357,
10025,
14,
76,
3,
61,
18,
3,
8,
20520,
198,
1640,
1312,
11,
7877,
287,
27056,
378,
7,
897,
274,
2599,
198,
220,
220,
220,
7877,
13,
10034,
7,
7568,
58,
4033,
82,
58,
72,
60,
4357,
12109,
28,
17821,
11,
5743,
8043,
11639,
74,
3256,
9493,
413,
5649,
28,
15,
13,
20,
8,
198,
220,
220,
220,
7877,
13,
2617,
62,
87,
18242,
7,
23912,
1424,
58,
72,
12962,
198,
220,
220,
220,
7877,
13,
2617,
62,
2645,
9608,
10786,
2964,
65,
1799,
11537,
198,
489,
83,
13,
33464,
62,
39786,
3419,
198,
489,
83,
13,
21928,
5647,
10786,
33665,
62,
67,
1023,
13,
12315,
11537,
198,
489,
83,
13,
12860,
3419,
198
] | 1.973545 | 189 |
import re
import json
from functools import reduce
from operator import itemgetter
from ip2loc import ip2loc, ip2loc_bulk
from funcs import count_occurence, folding, get_events_before_timestamp, get_timestamp, get_first_timestamp, get_unique_values
LOG_FILE_PATH = 'honey.log'
COUNTRY_STAT_HEADER_FORMAT = '{:<25s}\t{:<10s}\t{:<12s}'
COUNTRY_STAT_FORMAT = '{:<25s}\t{:<10d}\t{:<12.2f}'
REGION_STAT_HEADER_FORMAT = '{:<25s}\t{:<10s}\t{:<12s}'
REGION_STAT_FORMAT = '{:<25s}\t{:<10d}\t{:<12.2f}'
TIME_STAT_HEADER_FORMAT = '{:<25s}\t{:<10s}\t{:<12s}'
TIME_STAT_FORMAT = '{:<25s}\t{:<10d}\t{:<12.2f}'
# configurations
NUM_OF_COUNTRY_TO_DISPLAY = 3
NUM_OF_REGION_TO_DISPLAY = 5
NUM_OF_HOUR_TO_DISPLAY = 8
with open(LOG_FILE_PATH, 'r') as f:
data = f.read()
data = data.splitlines()
data = list(map(lambda x: json.loads(x), data))
################################ Try ################################
connect_events = list(filter(lambda x: x.get('eventid') == 'cowrie.session.connect', data))
unique_ips = list(get_unique_values('src_ip', connect_events))
locations_by_ip = ip2loc_bulk(unique_ips)
total_num_of_attcks = len(connect_events)
print('TOTAL ATTACKS: ', total_num_of_attcks)
print('\n')
connect_events = list(
map(lambda x:
update(
x,
{
'region': locations_by_ip.get(x.get('src_ip')).get('region_name'),
'country': locations_by_ip.get(x.get('src_ip')).get('country_name')
}
),
connect_events
)
)
# aggregate attacks by country
connect_events_count_by_country = reduce(count_occurence('country'), connect_events, {})
connect_events_count_by_country = sorted(connect_events_count_by_country.items(), key=itemgetter(1), reverse=True)
connect_events_by_country = reduce(folding('country'), connect_events, {})
# overall info
num_of_countries = len(connect_events_count_by_country)
print(COUNTRY_STAT_HEADER_FORMAT.format('COUNTRY', 'ATTACKS', 'PERCENTAGE %'))
for country, num_of_attack in connect_events_count_by_country[:min(NUM_OF_COUNTRY_TO_DISPLAY, num_of_countries)]:
print(COUNTRY_STAT_FORMAT.format(country, num_of_attack, 100 * num_of_attack / total_num_of_attcks))
# detailed breakdown by country
for country, num_of_attack in connect_events_count_by_country[:min(NUM_OF_COUNTRY_TO_DISPLAY, num_of_countries)]:
same_country_connect_events = connect_events_by_country.get(country)
connect_events_count_by_region = reduce(count_occurence('region'), same_country_connect_events, {})
connect_events_count_by_region = sorted(connect_events_count_by_region.items(), key=itemgetter(1), reverse=True)
connect_events_by_region = reduce(folding('region'), same_country_connect_events, {})
print('\n')
print(str.upper(country))
print('-'*100)
print(REGION_STAT_HEADER_FORMAT.format('REGION', 'ATTACKS', 'PERCENTAGE %'))
num_of_region = len(connect_events_count_by_region)
[print(REGION_STAT_FORMAT.format(r, n, 100 * n / num_of_attack)) for r, n in connect_events_count_by_region[:min(NUM_OF_REGION_TO_DISPLAY, num_of_region)]]
target_country_connect_timestamps = [{'hour':get_timestamp(x).strftime('%H')} for x in same_country_connect_events]
target_country_connect_hour_count = reduce(count_occurence('hour'), target_country_connect_timestamps, {})
target_country_connect_hour_count = sorted(target_country_connect_hour_count.items(), key=itemgetter(1), reverse=True)
num_of_hours = len(target_country_connect_hour_count)
print('')
print(TIME_STAT_HEADER_FORMAT.format('HOUR', 'ATTACKS', 'PERCENTAGE %'))
[print(TIME_STAT_FORMAT.format(t, n, 100 * n / num_of_attack)) for t, n in target_country_connect_hour_count[:min(NUM_OF_HOUR_TO_DISPLAY, num_of_hours)]]
####################################################################
# source locations
# attack times
# number of attacks by location | [
11748,
302,
201,
198,
11748,
33918,
201,
198,
6738,
1257,
310,
10141,
1330,
4646,
201,
198,
6738,
10088,
1330,
2378,
1136,
353,
201,
198,
6738,
20966,
17,
17946,
1330,
20966,
17,
17946,
11,
20966,
17,
17946,
62,
65,
12171,
201,
198,
6738,
1257,
6359,
1330,
954,
62,
13966,
495,
1198,
11,
29909,
11,
651,
62,
31534,
62,
19052,
62,
16514,
27823,
11,
651,
62,
16514,
27823,
11,
651,
62,
11085,
62,
16514,
27823,
11,
651,
62,
34642,
62,
27160,
201,
198,
201,
198,
25294,
62,
25664,
62,
34219,
796,
705,
71,
1419,
13,
6404,
6,
201,
198,
34,
19385,
40405,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
82,
32239,
83,
90,
25,
27,
1065,
82,
92,
6,
201,
198,
34,
19385,
40405,
62,
35744,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
67,
32239,
83,
90,
25,
27,
1065,
13,
17,
69,
92,
6,
201,
198,
201,
198,
31553,
2849,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
82,
32239,
83,
90,
25,
27,
1065,
82,
92,
6,
201,
198,
31553,
2849,
62,
35744,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
67,
32239,
83,
90,
25,
27,
1065,
13,
17,
69,
92,
6,
201,
198,
201,
198,
34694,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
82,
32239,
83,
90,
25,
27,
1065,
82,
92,
6,
201,
198,
34694,
62,
35744,
62,
21389,
1404,
796,
705,
90,
25,
27,
1495,
82,
32239,
83,
90,
25,
27,
940,
67,
32239,
83,
90,
25,
27,
1065,
13,
17,
69,
92,
6,
201,
198,
201,
198,
2,
25412,
201,
198,
41359,
62,
19238,
62,
34,
19385,
40405,
62,
10468,
62,
26288,
31519,
796,
513,
201,
198,
41359,
62,
19238,
62,
31553,
2849,
62,
10468,
62,
26288,
31519,
796,
642,
201,
198,
41359,
62,
19238,
62,
39,
11698,
62,
10468,
62,
26288,
31519,
796,
807,
201,
198,
201,
198,
4480,
1280,
7,
25294,
62,
25664,
62,
34219,
11,
705,
81,
11537,
355,
277,
25,
201,
198,
220,
220,
220,
1366,
796,
277,
13,
961,
3419,
201,
198,
201,
198,
7890,
796,
1366,
13,
35312,
6615,
3419,
201,
198,
7890,
796,
1351,
7,
8899,
7,
50033,
2124,
25,
33918,
13,
46030,
7,
87,
828,
1366,
4008,
201,
198,
201,
198,
29113,
9993,
1303,
14468,
7804,
4242,
21017,
201,
198,
8443,
62,
31534,
796,
1351,
7,
24455,
7,
50033,
2124,
25,
2124,
13,
1136,
10786,
15596,
312,
11537,
6624,
705,
8232,
5034,
13,
29891,
13,
8443,
3256,
1366,
4008,
201,
198,
34642,
62,
2419,
796,
1351,
7,
1136,
62,
34642,
62,
27160,
10786,
10677,
62,
541,
3256,
2018,
62,
31534,
4008,
201,
198,
17946,
602,
62,
1525,
62,
541,
796,
20966,
17,
17946,
62,
65,
12171,
7,
34642,
62,
2419,
8,
201,
198,
23350,
62,
22510,
62,
1659,
62,
1078,
4657,
796,
18896,
7,
8443,
62,
31534,
8,
201,
198,
4798,
10786,
51,
27510,
26195,
8120,
50,
25,
46083,
2472,
62,
22510,
62,
1659,
62,
1078,
4657,
8,
201,
198,
4798,
10786,
59,
77,
11537,
201,
198,
201,
198,
8443,
62,
31534,
796,
1351,
7,
201,
198,
220,
220,
220,
3975,
7,
50033,
2124,
25,
220,
201,
198,
220,
220,
220,
220,
220,
220,
220,
4296,
7,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2124,
11,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
36996,
10354,
7064,
62,
1525,
62,
541,
13,
1136,
7,
87,
13,
1136,
10786,
10677,
62,
541,
11537,
737,
1136,
10786,
36996,
62,
3672,
33809,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
19315,
10354,
7064,
62,
1525,
62,
541,
13,
1136,
7,
87,
13,
1136,
10786,
10677,
62,
541,
11537,
737,
1136,
10786,
19315,
62,
3672,
11537,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
201,
198,
220,
220,
220,
220,
220,
220,
220,
10612,
220,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2018,
62,
31534,
201,
198,
220,
220,
220,
1267,
201,
198,
8,
201,
198,
201,
198,
2,
19406,
3434,
416,
1499,
201,
198,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
796,
4646,
7,
9127,
62,
13966,
495,
1198,
10786,
19315,
33809,
2018,
62,
31534,
11,
23884,
8,
201,
198,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
796,
23243,
7,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
13,
23814,
22784,
1994,
28,
9186,
1136,
353,
7,
16,
828,
9575,
28,
17821,
8,
201,
198,
8443,
62,
31534,
62,
1525,
62,
19315,
796,
4646,
7,
11379,
278,
10786,
19315,
33809,
2018,
62,
31534,
11,
23884,
8,
201,
198,
201,
198,
2,
4045,
7508,
201,
198,
22510,
62,
1659,
62,
9127,
1678,
796,
18896,
7,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
8,
201,
198,
4798,
7,
34,
19385,
40405,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
13,
18982,
10786,
34,
19385,
40405,
3256,
705,
17139,
8120,
50,
3256,
705,
18973,
43960,
11879,
4064,
6,
4008,
201,
198,
1640,
1499,
11,
997,
62,
1659,
62,
20358,
287,
2018,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
58,
25,
1084,
7,
41359,
62,
19238,
62,
34,
19385,
40405,
62,
10468,
62,
26288,
31519,
11,
997,
62,
1659,
62,
9127,
1678,
8,
5974,
201,
198,
220,
220,
220,
3601,
7,
34,
19385,
40405,
62,
35744,
62,
21389,
1404,
13,
18982,
7,
19315,
11,
997,
62,
1659,
62,
20358,
11,
1802,
1635,
997,
62,
1659,
62,
20358,
1220,
2472,
62,
22510,
62,
1659,
62,
1078,
4657,
4008,
201,
198,
201,
198,
2,
6496,
14608,
416,
1499,
201,
198,
1640,
1499,
11,
997,
62,
1659,
62,
20358,
287,
2018,
62,
31534,
62,
9127,
62,
1525,
62,
19315,
58,
25,
1084,
7,
41359,
62,
19238,
62,
34,
19385,
40405,
62,
10468,
62,
26288,
31519,
11,
997,
62,
1659,
62,
9127,
1678,
8,
5974,
201,
198,
220,
220,
220,
976,
62,
19315,
62,
8443,
62,
31534,
796,
2018,
62,
31534,
62,
1525,
62,
19315,
13,
1136,
7,
19315,
8,
201,
198,
220,
220,
220,
2018,
62,
31534,
62,
9127,
62,
1525,
62,
36996,
796,
4646,
7,
9127,
62,
13966,
495,
1198,
10786,
36996,
33809,
976,
62,
19315,
62,
8443,
62,
31534,
11,
23884,
8,
201,
198,
220,
220,
220,
2018,
62,
31534,
62,
9127,
62,
1525,
62,
36996,
796,
23243,
7,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
36996,
13,
23814,
22784,
1994,
28,
9186,
1136,
353,
7,
16,
828,
9575,
28,
17821,
8,
201,
198,
220,
220,
220,
2018,
62,
31534,
62,
1525,
62,
36996,
796,
4646,
7,
11379,
278,
10786,
36996,
33809,
976,
62,
19315,
62,
8443,
62,
31534,
11,
23884,
8,
201,
198,
220,
220,
220,
220,
201,
198,
220,
220,
220,
3601,
10786,
59,
77,
11537,
201,
198,
220,
220,
220,
3601,
7,
2536,
13,
45828,
7,
19315,
4008,
201,
198,
220,
220,
220,
3601,
10786,
19355,
9,
3064,
8,
201,
198,
220,
220,
220,
3601,
7,
31553,
2849,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
13,
18982,
10786,
31553,
2849,
3256,
705,
17139,
8120,
50,
3256,
705,
18973,
43960,
11879,
4064,
6,
4008,
201,
198,
220,
220,
220,
997,
62,
1659,
62,
36996,
796,
18896,
7,
8443,
62,
31534,
62,
9127,
62,
1525,
62,
36996,
8,
201,
198,
220,
220,
220,
685,
4798,
7,
31553,
2849,
62,
35744,
62,
21389,
1404,
13,
18982,
7,
81,
11,
299,
11,
1802,
1635,
299,
1220,
997,
62,
1659,
62,
20358,
4008,
329,
374,
11,
299,
287,
2018,
62,
31534,
62,
9127,
62,
1525,
62,
36996,
58,
25,
1084,
7,
41359,
62,
19238,
62,
31553,
2849,
62,
10468,
62,
26288,
31519,
11,
997,
62,
1659,
62,
36996,
8,
11907,
201,
198,
201,
198,
220,
220,
220,
2496,
62,
19315,
62,
8443,
62,
16514,
395,
9430,
796,
685,
90,
6,
9769,
10354,
1136,
62,
16514,
27823,
7,
87,
737,
2536,
31387,
10786,
4,
39,
11537,
92,
329,
2124,
287,
976,
62,
19315,
62,
8443,
62,
31534,
60,
201,
198,
220,
220,
220,
2496,
62,
19315,
62,
8443,
62,
9769,
62,
9127,
796,
4646,
7,
9127,
62,
13966,
495,
1198,
10786,
9769,
33809,
2496,
62,
19315,
62,
8443,
62,
16514,
395,
9430,
11,
23884,
8,
201,
198,
220,
220,
220,
2496,
62,
19315,
62,
8443,
62,
9769,
62,
9127,
796,
23243,
7,
16793,
62,
19315,
62,
8443,
62,
9769,
62,
9127,
13,
23814,
22784,
1994,
28,
9186,
1136,
353,
7,
16,
828,
9575,
28,
17821,
8,
201,
198,
201,
198,
220,
220,
220,
997,
62,
1659,
62,
24425,
796,
18896,
7,
16793,
62,
19315,
62,
8443,
62,
9769,
62,
9127,
8,
201,
198,
220,
220,
220,
3601,
7,
7061,
8,
201,
198,
220,
220,
220,
3601,
7,
34694,
62,
35744,
62,
37682,
1137,
62,
21389,
1404,
13,
18982,
10786,
39,
11698,
3256,
705,
17139,
8120,
50,
3256,
705,
18973,
43960,
11879,
4064,
6,
4008,
201,
198,
220,
220,
220,
685,
4798,
7,
34694,
62,
35744,
62,
21389,
1404,
13,
18982,
7,
83,
11,
299,
11,
1802,
1635,
299,
1220,
997,
62,
1659,
62,
20358,
4008,
329,
256,
11,
299,
287,
2496,
62,
19315,
62,
8443,
62,
9769,
62,
9127,
58,
25,
1084,
7,
41359,
62,
19238,
62,
39,
11698,
62,
10468,
62,
26288,
31519,
11,
997,
62,
1659,
62,
24425,
8,
11907,
201,
198,
201,
198,
220,
220,
220,
220,
201,
198,
201,
198,
29113,
29113,
4242,
201,
198,
2,
2723,
7064,
201,
198,
2,
1368,
1661,
201,
198,
201,
198,
2,
1271,
286,
3434,
416,
4067
] | 2.438532 | 1,635 |
from imutils import face_utils
from imutils.face_utils import FaceAligner
import numpy as np
import imutils
import dlib
import cv2
from skimage.metrics import structural_similarity as ssim
#import os
import glob
#import time
from tkinter import *
import tkinter as tk
from tkinter import filedialog
from pandas import DataFrame
#import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
# loading models for face detection and set defaults
net = cv2.dnn.readNetFromCaffe('deploy.prototxt.txt', 'res10_300x300_ssd_iter_140000.caffemodel')
camera = cv2.VideoCapture(0)
main_option=1
# initialize dlib's face detector (HOG-based) and then create the facial landmark predictor
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')
fa = FaceAligner(predictor, desiredFaceWidth=256)
#Beginning GUI
gui = Tk(className=' LLRR_Facial_Similarity')
# set window size and position it at center of screen
windowWidth=800
windowHeight=400
positionRight = int(gui.winfo_screenwidth()/2 - windowWidth/2)
positionDown = int(gui.winfo_screenheight()/2 - windowHeight/2)
gui.geometry("{}x{}+{}+{}".format(windowWidth,windowHeight,positionRight,positionDown))
xx=gui.winfo_screenwidth()/2
w = Label(gui, text="\nWelcome! \n\nThis tool helps to analyze similarity of dynamic composite faces\n",font=("Helvetica", 15))
w.pack()
v = IntVar()# identifies which one is selected
Label(gui, text="Select one of the following ways of capturing a video:",justify = LEFT,padx = 20).pack()
Radiobutton(gui, text="Real-time Analysis via webcam",padx = 20, variable=v, value=1).pack(anchor=W)
Radiobutton(gui, text="Analysis of a pre-recorded video",padx = 20, variable=v, value=2).pack(anchor=W)
button = Button(gui, text='Confirm', width=25, command=helloCallBack)
button.pack()
gui.mainloop()
# starting video streaming
cv2.namedWindow('TestVideo')
cv2.namedWindow('Aligned')
cv2.namedWindow('LL RR composites')
cv2.moveWindow('TestVideo', int(xx-400),75)# width wise centerscreen
tlt = 25 # number of pixels of tilt allowance (allow if <tlt)
t_pass = []
frms=0
sim_list = []
while camera.isOpened():
ret, frame = camera.read()# by default the webcam reads at around 30fps, can be changed by other codes
if ret==False:
break
#reading the frame
frame = imutils.resize(frame,width=800)
if main_option==1:
frame = cv2.flip(frame, 1)
frameClone = frame.copy()
frameClone = cv2.putText(frameClone, 'Press Q to stop',(500, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2, cv2.LINE_AA)
t_pass.append(frms)
sim_list.append(-0.1)
frms = frms+1
if cv2.waitKey(1) & 0xFF == ord('q'):# press q to stop
break
###-------------begin finding 68 facial landmarks using dlib
## this section checks for correct facial alignment
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# detect faces in the grayscale image (dlib object for dlib shape prediction)
rects = detector(gray_frame, 1)
if len(rects)!=0:
# determine the facial landmarks for the face region, then
# convert the facial landmark (x, y)-coordinates to a NumPy array
shape = predictor(gray_frame, rects[0])
shape = face_utils.shape_to_np(shape)
# loop over the (x, y)-coordinates for the facial landmarks
# and draw them on the image
for (x, y) in shape:
cv2.circle(frameClone, (x, y), 1, (0, 0, 255), -1)
### ADD CODE for checking alignment
ylj = shape[0][1] # y coordinate of left jaw
yrj = shape[16][1] # y coordinate of right jaw
xtn = shape[27][0] # x coordinate of top of nose
xbn = shape[30][0] # x coordinate of bottom of nose
faceAligned = fa.align(frame, gray_frame, rects[0])
cv2.imshow('Aligned',faceAligned)
if abs(ylj-yrj)>=tlt or abs(xtn-xbn)>=tlt:
cv2.imshow('TestVideo', frameClone)
continue
# convert dlib's rectangle to a OpenCV-style bounding box [i.e., (x, y, w, h)], then draw the face bounding box
(x, y, w, h) = face_utils.rect_to_bb(rects[0])
cv2.rectangle(frameClone, (x, y), (x + w, y + h), (0, 255, 0), 1)
###-------------end finding 68 facial landmarks using dlib
### using CNN : (if face is well aligned)
# grab the frame dimensions and convert it to a blob
(h, w) = faceAligned.shape[:2]
#blob = cv2.dnn.blobFromImage(cv2.resize(faceAligned, (300, 300)), 1.0,(300, 300), (104.0, 177.0, 123.0))
# pass the blob through the network and obtain the detections and predictions
#net.setInput(blob)
#detections = net.forward()
#if detections[0, 0, 0, 2] > 0.75: # 75% confidence of a face existing in the frame
# compute the (x, y)-coordinates of the bounding box for the object
#box = detections[0, 0, 0, 3:7] * np.array([w, h, w, h])
#(startX, startY, endX, endY) = box.astype("int")
#(fX, fY, fW, fH) = (startX, startY, endX-startX, endY-startY)
#cv2.rectangle(frameClone, (fX, fY), (fX + fW, fY + fH),(255, 0, 0), 1)
#crop_face = faceAligned.copy()#[startY:endY, startX:endX]
crop_face = faceAligned[h//10:h*9//10, w//10:w*9//10]
#----------------------LL RR--------------
(hh,ww,dd) = crop_face.shape
if ww%2==0:
ww1=ww//2-1
else:
ww1=ww//2
flipHorizontal = cv2.flip(crop_face, 1)
img1 = crop_face[:,0:ww1]
img2 = flipHorizontal[:,ww1+1:]
LL = np.concatenate((img1, img2), axis=1)
img1 = flipHorizontal[:,0:ww1]
img2 = crop_face[:,ww1+1:]
RR = np.concatenate((img1, img2), axis=1)
llrr = np.concatenate((LL,RR),axis=0)
cv2.imshow('LL RR composites',llrr)
# calculate similarity index (0-1) (least - identical)
sim_index = ssim(cv2.cvtColor(LL, cv2.COLOR_BGR2GRAY), cv2.cvtColor(RR, cv2.COLOR_BGR2GRAY))
sim_list[frms-1] = sim_index
cv2.imshow('TestVideo', frameClone)
else:
cv2.imshow('TestVideo', frameClone)
continue
camera.release()
cv2.destroyAllWindows()
t_passn =np.array(t_pass)
t_passn =100*t_passn/t_pass[-1]
sim_listn = 100*np.array(sim_list) # percentage
data = {'Time': t_passn,
'Similarity_index': sim_listn
}
df2 = DataFrame(data,columns=['Time','Similarity_index'])
res = Tk(className=' Final Results')
# set window size and position it at center of screen
#winWidth=900
#winHeight=550
#posRight = int(res.winfo_screenwidth()/2 - winWidth/2)
#posDown = int(res.winfo_screenheight()/2 - winHeight/2)
#res.geometry("{}x{}+{}+{}".format(winWidth,winHeight,posRight,posDown))
figure2 = plt.Figure(figsize=(8,6), dpi=100)
ax2 = figure2.add_subplot(111)
line2 = FigureCanvasTkAgg(figure2, res)# using toplevel for graph
line2.get_tk_widget().pack(side=tk.LEFT, fill=tk.BOTH)
df2 = df2[['Time','Similarity_index']].groupby('Time').sum()
df2.plot(kind='line', legend=True, ax=ax2,fontsize=10)
ax2.set_title('Variation of Similarity index over captured frames')
res.mainloop() | [
198,
6738,
545,
26791,
1330,
1986,
62,
26791,
198,
6738,
545,
26791,
13,
2550,
62,
26791,
1330,
15399,
2348,
570,
263,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
545,
26791,
198,
11748,
288,
8019,
198,
11748,
269,
85,
17,
198,
6738,
1341,
9060,
13,
4164,
10466,
1330,
13204,
62,
38610,
414,
355,
264,
14323,
198,
2,
11748,
28686,
198,
11748,
15095,
198,
2,
11748,
640,
198,
6738,
256,
74,
3849,
1330,
1635,
198,
11748,
256,
74,
3849,
355,
256,
74,
198,
6738,
256,
74,
3849,
1330,
5717,
498,
519,
198,
6738,
19798,
292,
1330,
6060,
19778,
198,
2,
11748,
19798,
292,
355,
279,
67,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
6738,
2603,
29487,
8019,
13,
1891,
2412,
13,
1891,
437,
62,
30488,
9460,
1330,
11291,
6090,
11017,
51,
74,
46384,
198,
198,
2,
11046,
4981,
329,
1986,
13326,
290,
900,
26235,
198,
3262,
796,
269,
85,
17,
13,
67,
20471,
13,
961,
7934,
4863,
34,
21223,
10786,
2934,
1420,
13,
11235,
313,
742,
13,
14116,
3256,
705,
411,
940,
62,
6200,
87,
6200,
62,
824,
67,
62,
2676,
62,
1415,
2388,
13,
66,
2001,
368,
375,
417,
11537,
198,
25695,
796,
269,
85,
17,
13,
10798,
49630,
7,
15,
8,
198,
12417,
62,
18076,
28,
16,
198,
2,
41216,
288,
8019,
338,
1986,
31029,
357,
39,
7730,
12,
3106,
8,
290,
788,
2251,
262,
16324,
20533,
41568,
198,
15255,
9250,
796,
288,
8019,
13,
1136,
62,
8534,
282,
62,
2550,
62,
15255,
9250,
3419,
198,
79,
17407,
273,
796,
288,
8019,
13,
43358,
62,
79,
17407,
273,
10786,
43358,
62,
79,
17407,
273,
62,
3104,
62,
2550,
62,
1044,
14306,
13,
19608,
11537,
198,
13331,
796,
15399,
2348,
570,
263,
7,
79,
17407,
273,
11,
10348,
32388,
30916,
28,
11645,
8,
198,
198,
2,
45198,
25757,
198,
48317,
796,
309,
74,
7,
4871,
5376,
11639,
27140,
21095,
62,
37,
18150,
62,
18925,
414,
11537,
198,
2,
900,
4324,
2546,
290,
2292,
340,
379,
3641,
286,
3159,
198,
17497,
30916,
28,
7410,
198,
17497,
23106,
28,
7029,
198,
9150,
11028,
796,
493,
7,
48317,
13,
5404,
6513,
62,
9612,
10394,
3419,
14,
17,
532,
4324,
30916,
14,
17,
8,
198,
9150,
8048,
796,
493,
7,
48317,
13,
5404,
6513,
62,
9612,
17015,
3419,
14,
17,
532,
4324,
23106,
14,
17,
8,
198,
48317,
13,
469,
15748,
7203,
90,
92,
87,
90,
92,
10,
90,
92,
10,
90,
92,
1911,
18982,
7,
17497,
30916,
11,
17497,
23106,
11,
9150,
11028,
11,
9150,
8048,
4008,
198,
5324,
28,
48317,
13,
5404,
6513,
62,
9612,
10394,
3419,
14,
17,
198,
198,
86,
796,
36052,
7,
48317,
11,
2420,
2625,
59,
77,
14618,
0,
3467,
77,
59,
77,
1212,
2891,
5419,
284,
16602,
26789,
286,
8925,
24185,
6698,
59,
77,
1600,
10331,
28,
7203,
39,
32667,
3970,
1600,
1315,
4008,
198,
86,
13,
8002,
3419,
198,
85,
796,
2558,
19852,
3419,
2,
21079,
543,
530,
318,
6163,
198,
198,
33986,
7,
48317,
11,
2420,
2625,
17563,
530,
286,
262,
1708,
2842,
286,
21430,
257,
2008,
25,
1600,
3137,
1958,
796,
12509,
9792,
11,
15636,
87,
796,
1160,
737,
8002,
3419,
198,
49,
9189,
672,
21115,
7,
48317,
11,
2420,
2625,
15633,
12,
2435,
14691,
2884,
49823,
1600,
15636,
87,
796,
1160,
11,
7885,
28,
85,
11,
1988,
28,
16,
737,
8002,
7,
3702,
273,
28,
54,
8,
198,
49,
9189,
672,
21115,
7,
48317,
11,
2420,
2625,
32750,
286,
257,
662,
12,
47398,
2008,
1600,
15636,
87,
796,
1160,
11,
7885,
28,
85,
11,
1988,
28,
17,
737,
8002,
7,
3702,
273,
28,
54,
8,
628,
198,
16539,
796,
20969,
7,
48317,
11,
2420,
11639,
18546,
2533,
3256,
9647,
28,
1495,
11,
3141,
28,
31373,
14134,
7282,
8,
198,
16539,
13,
8002,
3419,
198,
198,
48317,
13,
12417,
26268,
3419,
198,
198,
2,
3599,
2008,
11305,
198,
33967,
17,
13,
13190,
27703,
10786,
14402,
10798,
11537,
198,
33967,
17,
13,
13190,
27703,
10786,
2348,
3916,
11537,
198,
33967,
17,
13,
13190,
27703,
10786,
3069,
26067,
18882,
2737,
11537,
198,
33967,
17,
13,
21084,
27703,
10786,
14402,
10798,
3256,
493,
7,
5324,
12,
7029,
828,
2425,
8,
2,
9647,
10787,
10399,
32060,
198,
83,
2528,
796,
1679,
1303,
1271,
286,
17848,
286,
26500,
24930,
357,
12154,
611,
1279,
83,
2528,
8,
198,
83,
62,
6603,
796,
17635,
198,
8310,
907,
28,
15,
198,
14323,
62,
4868,
796,
17635,
198,
198,
4514,
4676,
13,
271,
18257,
2945,
33529,
198,
220,
220,
220,
1005,
11,
5739,
796,
4676,
13,
961,
3419,
2,
416,
4277,
262,
49823,
9743,
379,
1088,
1542,
29647,
11,
460,
307,
3421,
416,
584,
12416,
198,
220,
220,
220,
611,
1005,
855,
25101,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
1303,
25782,
262,
5739,
198,
220,
220,
220,
5739,
796,
545,
26791,
13,
411,
1096,
7,
14535,
11,
10394,
28,
7410,
8,
198,
220,
220,
220,
611,
1388,
62,
18076,
855,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
269,
85,
17,
13,
2704,
541,
7,
14535,
11,
352,
8,
198,
220,
220,
220,
5739,
2601,
505,
796,
5739,
13,
30073,
3419,
198,
220,
220,
220,
5739,
2601,
505,
796,
269,
85,
17,
13,
1996,
8206,
7,
14535,
2601,
505,
11,
705,
13800,
1195,
284,
2245,
3256,
7,
4059,
11,
1542,
828,
269,
85,
17,
13,
37,
35830,
62,
39,
4877,
13909,
56,
62,
48913,
16437,
55,
11,
657,
13,
22,
11,
357,
15,
11,
14280,
11,
657,
828,
362,
11,
269,
85,
17,
13,
24027,
62,
3838,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
256,
62,
6603,
13,
33295,
7,
8310,
907,
8,
198,
220,
220,
220,
985,
62,
4868,
13,
33295,
32590,
15,
13,
16,
8,
198,
220,
220,
220,
1216,
907,
796,
1216,
907,
10,
16,
198,
220,
220,
220,
220,
198,
220,
220,
220,
611,
269,
85,
17,
13,
17077,
9218,
7,
16,
8,
1222,
657,
87,
5777,
6624,
2760,
10786,
80,
6,
2599,
2,
1803,
10662,
284,
2245,
198,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
44386,
32501,
27471,
4917,
8257,
16324,
41532,
1262,
288,
8019,
628,
220,
220,
220,
22492,
428,
2665,
8794,
329,
3376,
16324,
19114,
198,
220,
220,
220,
12768,
62,
14535,
796,
269,
85,
17,
13,
33967,
83,
10258,
7,
14535,
11,
269,
85,
17,
13,
46786,
62,
33,
10761,
17,
38,
30631,
8,
198,
220,
220,
220,
1303,
4886,
6698,
287,
262,
1036,
592,
38765,
2939,
357,
67,
8019,
2134,
329,
288,
8019,
5485,
17724,
8,
198,
220,
220,
220,
13621,
82,
796,
31029,
7,
44605,
62,
14535,
11,
352,
8,
198,
220,
220,
220,
611,
18896,
7,
2554,
82,
31520,
28,
15,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
5004,
262,
16324,
41532,
329,
262,
1986,
3814,
11,
788,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
10385,
262,
16324,
20533,
357,
87,
11,
331,
13219,
37652,
17540,
284,
257,
31835,
20519,
7177,
198,
220,
220,
220,
220,
220,
220,
220,
5485,
796,
41568,
7,
44605,
62,
14535,
11,
13621,
82,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
5485,
796,
1986,
62,
26791,
13,
43358,
62,
1462,
62,
37659,
7,
43358,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
9052,
625,
262,
357,
87,
11,
331,
13219,
37652,
17540,
329,
262,
16324,
41532,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
290,
3197,
606,
319,
262,
2939,
198,
220,
220,
220,
220,
220,
220,
220,
329,
357,
87,
11,
331,
8,
287,
5485,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
45597,
7,
14535,
2601,
505,
11,
357,
87,
11,
331,
828,
352,
11,
357,
15,
11,
657,
11,
14280,
828,
532,
16,
8,
628,
220,
220,
220,
220,
220,
220,
220,
44386,
27841,
42714,
329,
10627,
19114,
198,
220,
220,
220,
220,
220,
220,
220,
331,
75,
73,
796,
5485,
58,
15,
7131,
16,
60,
1303,
331,
20435,
286,
1364,
19218,
198,
220,
220,
220,
220,
220,
220,
220,
42635,
73,
796,
5485,
58,
1433,
7131,
16,
60,
1303,
331,
20435,
286,
826,
19218,
198,
220,
220,
220,
220,
220,
220,
220,
220,
742,
77,
796,
5485,
58,
1983,
7131,
15,
60,
1303,
2124,
20435,
286,
1353,
286,
9686,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
9374,
796,
5485,
58,
1270,
7131,
15,
60,
1303,
2124,
20435,
286,
4220,
286,
9686,
628,
220,
220,
220,
220,
220,
220,
220,
1986,
2348,
3916,
796,
24685,
13,
31494,
7,
14535,
11,
12768,
62,
14535,
11,
13621,
82,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
2348,
3916,
3256,
2550,
2348,
3916,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2352,
7,
2645,
73,
12,
2417,
73,
8,
29,
28,
83,
2528,
393,
2352,
7,
742,
77,
12,
87,
9374,
8,
29,
28,
83,
2528,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
14402,
10798,
3256,
5739,
2601,
505,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
10385,
288,
8019,
338,
35991,
284,
257,
4946,
33538,
12,
7635,
5421,
278,
3091,
685,
72,
13,
68,
1539,
357,
87,
11,
331,
11,
266,
11,
289,
8,
4357,
788,
3197,
262,
1986,
5421,
278,
3091,
198,
220,
220,
220,
220,
220,
220,
220,
357,
87,
11,
331,
11,
266,
11,
289,
8,
796,
1986,
62,
26791,
13,
2554,
62,
1462,
62,
11848,
7,
2554,
82,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
2554,
9248,
7,
14535,
2601,
505,
11,
357,
87,
11,
331,
828,
357,
87,
1343,
266,
11,
331,
1343,
289,
828,
357,
15,
11,
14280,
11,
657,
828,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
44386,
32501,
437,
4917,
8257,
16324,
41532,
1262,
288,
8019,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
44386,
1262,
8100,
1058,
357,
361,
1986,
318,
880,
19874,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
5552,
262,
5739,
15225,
290,
10385,
340,
284,
257,
44812,
198,
220,
220,
220,
220,
220,
220,
220,
357,
71,
11,
266,
8,
796,
1986,
2348,
3916,
13,
43358,
58,
25,
17,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2436,
672,
796,
269,
85,
17,
13,
67,
20471,
13,
2436,
672,
4863,
5159,
7,
33967,
17,
13,
411,
1096,
7,
2550,
2348,
3916,
11,
357,
6200,
11,
5867,
36911,
352,
13,
15,
11,
7,
6200,
11,
5867,
828,
357,
13464,
13,
15,
11,
26607,
13,
15,
11,
17031,
13,
15,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1208,
262,
44812,
832,
262,
3127,
290,
7330,
262,
4886,
507,
290,
16277,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3262,
13,
2617,
20560,
7,
2436,
672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
15255,
478,
507,
796,
2010,
13,
11813,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
361,
4886,
507,
58,
15,
11,
657,
11,
657,
11,
362,
60,
1875,
657,
13,
2425,
25,
1303,
5441,
4,
6628,
286,
257,
1986,
4683,
287,
262,
5739,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
24061,
262,
357,
87,
11,
331,
13219,
37652,
17540,
286,
262,
5421,
278,
3091,
329,
262,
2134,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3524,
796,
4886,
507,
58,
15,
11,
657,
11,
657,
11,
513,
25,
22,
60,
1635,
45941,
13,
18747,
26933,
86,
11,
289,
11,
266,
11,
289,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
7,
9688,
55,
11,
923,
56,
11,
886,
55,
11,
886,
56,
8,
796,
3091,
13,
459,
2981,
7203,
600,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
7,
69,
55,
11,
277,
56,
11,
277,
54,
11,
277,
39,
8,
796,
357,
9688,
55,
11,
923,
56,
11,
886,
55,
12,
9688,
55,
11,
886,
56,
12,
9688,
56,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
33967,
17,
13,
2554,
9248,
7,
14535,
2601,
505,
11,
357,
69,
55,
11,
277,
56,
828,
357,
69,
55,
1343,
277,
54,
11,
277,
56,
1343,
277,
39,
828,
7,
13381,
11,
657,
11,
657,
828,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
31476,
62,
2550,
796,
1986,
2348,
3916,
13,
30073,
3419,
2,
58,
9688,
56,
25,
437,
56,
11,
923,
55,
25,
437,
55,
60,
198,
220,
220,
220,
220,
220,
220,
220,
13833,
62,
2550,
796,
1986,
2348,
3916,
58,
71,
1003,
940,
25,
71,
9,
24,
1003,
940,
11,
266,
1003,
940,
25,
86,
9,
24,
1003,
940,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
19351,
438,
3069,
26067,
26171,
198,
220,
220,
220,
220,
220,
220,
220,
357,
12337,
11,
1383,
11,
1860,
8,
796,
13833,
62,
2550,
13,
43358,
198,
220,
220,
220,
220,
220,
220,
220,
611,
266,
86,
4,
17,
855,
15,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
266,
86,
16,
28,
1383,
1003,
17,
12,
16,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
266,
86,
16,
28,
1383,
1003,
17,
198,
220,
220,
220,
220,
220,
220,
220,
14283,
27991,
38342,
796,
269,
85,
17,
13,
2704,
541,
7,
31476,
62,
2550,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
33705,
16,
796,
13833,
62,
2550,
58,
45299,
15,
25,
1383,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
33705,
17,
796,
14283,
27991,
38342,
58,
45299,
1383,
16,
10,
16,
47715,
198,
220,
220,
220,
220,
220,
220,
220,
27140,
796,
45941,
13,
1102,
9246,
268,
378,
19510,
9600,
16,
11,
33705,
17,
828,
16488,
28,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
33705,
16,
796,
14283,
27991,
38342,
58,
45299,
15,
25,
1383,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
33705,
17,
796,
13833,
62,
2550,
58,
45299,
1383,
16,
10,
16,
47715,
198,
220,
220,
220,
220,
220,
220,
220,
26067,
796,
45941,
13,
1102,
9246,
268,
378,
19510,
9600,
16,
11,
33705,
17,
828,
16488,
28,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
32660,
21062,
796,
45941,
13,
1102,
9246,
268,
378,
19510,
3069,
11,
21095,
828,
22704,
28,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
3069,
26067,
18882,
2737,
3256,
297,
21062,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
15284,
26789,
6376,
357,
15,
12,
16,
8,
357,
293,
459,
532,
10411,
8,
198,
220,
220,
220,
220,
220,
220,
220,
985,
62,
9630,
796,
264,
14323,
7,
33967,
17,
13,
33967,
83,
10258,
7,
3069,
11,
269,
85,
17,
13,
46786,
62,
33,
10761,
17,
38,
30631,
828,
269,
85,
17,
13,
33967,
83,
10258,
7,
21095,
11,
269,
85,
17,
13,
46786,
62,
33,
10761,
17,
38,
30631,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
985,
62,
4868,
58,
8310,
907,
12,
16,
60,
796,
985,
62,
9630,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
14402,
10798,
3256,
5739,
2601,
505,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
269,
85,
17,
13,
320,
12860,
10786,
14402,
10798,
3256,
5739,
2601,
505,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
25695,
13,
20979,
3419,
198,
33967,
17,
13,
41659,
3237,
11209,
3419,
198,
198,
83,
62,
6603,
77,
796,
37659,
13,
18747,
7,
83,
62,
6603,
8,
198,
83,
62,
6603,
77,
796,
3064,
9,
83,
62,
6603,
77,
14,
83,
62,
6603,
58,
12,
16,
60,
198,
14323,
62,
4868,
77,
796,
1802,
9,
37659,
13,
18747,
7,
14323,
62,
4868,
8,
1303,
5873,
198,
198,
7890,
796,
1391,
6,
7575,
10354,
256,
62,
6603,
77,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
18925,
414,
62,
9630,
10354,
985,
62,
4868,
77,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
7568,
17,
796,
6060,
19778,
7,
7890,
11,
28665,
82,
28,
17816,
7575,
41707,
18925,
414,
62,
9630,
6,
12962,
198,
198,
411,
796,
309,
74,
7,
4871,
5376,
11639,
8125,
15691,
11537,
198,
2,
900,
4324,
2546,
290,
2292,
340,
379,
3641,
286,
3159,
198,
2,
5404,
30916,
28,
12865,
198,
2,
5404,
23106,
28,
22730,
198,
2,
1930,
11028,
796,
493,
7,
411,
13,
5404,
6513,
62,
9612,
10394,
3419,
14,
17,
532,
1592,
30916,
14,
17,
8,
198,
2,
1930,
8048,
796,
493,
7,
411,
13,
5404,
6513,
62,
9612,
17015,
3419,
14,
17,
532,
1592,
23106,
14,
17,
8,
198,
2,
411,
13,
469,
15748,
7203,
90,
92,
87,
90,
92,
10,
90,
92,
10,
90,
92,
1911,
18982,
7,
5404,
30916,
11,
5404,
23106,
11,
1930,
11028,
11,
1930,
8048,
4008,
198,
198,
26875,
17,
796,
458,
83,
13,
11337,
7,
5647,
7857,
16193,
23,
11,
21,
828,
288,
14415,
28,
3064,
8,
198,
897,
17,
796,
3785,
17,
13,
2860,
62,
7266,
29487,
7,
16243,
8,
198,
1370,
17,
796,
11291,
6090,
11017,
51,
74,
46384,
7,
26875,
17,
11,
581,
8,
2,
1262,
284,
1154,
626,
329,
4823,
198,
1370,
17,
13,
1136,
62,
30488,
62,
42655,
22446,
8002,
7,
1589,
28,
30488,
13,
2538,
9792,
11,
6070,
28,
30488,
13,
33,
26946,
8,
198,
7568,
17,
796,
47764,
17,
58,
17816,
7575,
41707,
18925,
414,
62,
9630,
20520,
4083,
8094,
1525,
10786,
7575,
27691,
16345,
3419,
198,
7568,
17,
13,
29487,
7,
11031,
11639,
1370,
3256,
8177,
28,
17821,
11,
7877,
28,
897,
17,
11,
10331,
7857,
28,
940,
8,
198,
897,
17,
13,
2617,
62,
7839,
10786,
23907,
341,
286,
11014,
414,
6376,
625,
7907,
13431,
11537,
198,
198,
411,
13,
12417,
26268,
3419
] | 2.349838 | 3,090 |
# AUTOGENERATED! DO NOT EDIT! File to edit: 00_scraper.ipynb (unless otherwise specified).
__all__ = ['Scraper', 'print_something']
# Cell
# Cell
from fastcore.foundation import patch
from facebook_scraper import get_posts
@patch
# Cell | [
2,
47044,
7730,
1677,
1137,
11617,
0,
8410,
5626,
48483,
0,
9220,
284,
4370,
25,
3571,
62,
1416,
38545,
13,
541,
2047,
65,
357,
25252,
4306,
7368,
737,
198,
198,
834,
439,
834,
796,
37250,
3351,
38545,
3256,
705,
4798,
62,
18927,
20520,
198,
198,
2,
12440,
198,
198,
2,
12440,
198,
6738,
3049,
7295,
13,
42526,
1330,
8529,
198,
6738,
23960,
62,
1416,
38545,
1330,
651,
62,
24875,
198,
198,
31,
17147,
198,
198,
2,
12440
] | 3.12987 | 77 |
# Copyright 2010 New Relic, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import starlette
import pytest
from testing_support.fixtures import (
validate_transaction_metrics,
validate_transaction_errors,
capture_transaction_metrics,
override_ignore_status_codes,
)
FRAMEWORK_METRIC = ("Python/Framework/Starlette/%s" % starlette.__version__, 1)
DEFAULT_MIDDLEWARE_METRICS = [
("Function/starlette.middleware.errors:ServerErrorMiddleware.__call__", 1),
("Function/starlette.exceptions:ExceptionMiddleware.__call__", 1),
]
MIDDLEWARE_METRICS = [
("Function/_target_application:middleware_factory.<locals>.middleware", 2),
("Function/_target_application:middleware_decorator", 1),
] + DEFAULT_MIDDLEWARE_METRICS
@pytest.mark.parametrize("app_name", ("no_error_handler",))
@validate_transaction_metrics(
"_target_application:index",
scoped_metrics=MIDDLEWARE_METRICS + [("Function/_target_application:index", 1)],
rollup_metrics=[FRAMEWORK_METRIC],
)
@pytest.mark.parametrize("app_name", ("no_error_handler",))
@validate_transaction_metrics(
"_target_application:non_async",
scoped_metrics=MIDDLEWARE_METRICS + [("Function/_target_application:non_async", 1)],
rollup_metrics=[FRAMEWORK_METRIC],
)
@pytest.mark.parametrize("app_name, transaction_name", (
("no_error_handler", "starlette.exceptions:ExceptionMiddleware.__call__"),
("non_async_error_handler_no_middleware", "starlette.exceptions:ExceptionMiddleware.__call__"),
))
@pytest.mark.parametrize("app_name", ("no_error_handler",))
@validate_transaction_metrics(
"_target_application:middleware_factory.<locals>.middleware",
scoped_metrics=[("Function/_target_application:middleware_factory.<locals>.middleware", 1)],
rollup_metrics=[FRAMEWORK_METRIC],
)
@pytest.mark.parametrize("app_name,transaction_name,path,scoped_metrics", (
("non_async_error_handler_no_middleware", "_target_application:runtime_error", "/runtime_error", []),
("async_error_handler_no_middleware", "_target_application:runtime_error", "/runtime_error", [("Function/_target_application:async_error_handler", 1)]),
("no_middleware", "_target_application:runtime_error", "/runtime_error", [("Function/starlette.middleware.errors:ServerErrorMiddleware.error_response", 1)]),
("debug_no_middleware", "_target_application:runtime_error", "/runtime_error", [("Function/starlette.middleware.errors:ServerErrorMiddleware.debug_response", 1)]),
("no_middleware", "_target_application:CustomRoute", "/raw_runtime_error", []),
))
@validate_transaction_errors(errors=["builtins:RuntimeError"])
@pytest.mark.parametrize("app_name,transaction_name,path,error", (
("async_error_handler_no_middleware", "_target_application:handled_error", "/handled_error", "_target_application:HandledError"),
("non_async_error_handler_no_middleware", "_target_application:non_async_handled_error", "/non_async_handled_error", "_target_application:NonAsyncHandledError")
))
@pytest.mark.parametrize("app_name,transaction_name,path", (
("async_error_handler_no_middleware", "_target_application:handled_error", "/handled_error"),
("non_async_error_handler_no_middleware", "_target_application:non_async_handled_error", "/non_async_handled_error")
))
@override_ignore_status_codes(set((500,)))
@pytest.mark.parametrize("app_name,scoped_metrics", (
("no_middleware", [("Function/starlette.exceptions:ExceptionMiddleware.http_exception", 1)]),
("teapot_exception_handler_no_middleware", [("Function/_target_application:teapot_handler", 1)])
))
@pytest.mark.parametrize("app_name", ("no_middleware",))
@validate_transaction_errors(errors=["builtins:RuntimeError"])
@validate_transaction_metrics(
"_target_application:CustomRoute", rollup_metrics=[FRAMEWORK_METRIC]
)
@pytest.mark.parametrize("app_name", ("no_error_handler",))
| [
2,
15069,
3050,
968,
43437,
11,
3457,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
11748,
3491,
21348,
198,
11748,
12972,
9288,
198,
6738,
4856,
62,
11284,
13,
69,
25506,
1330,
357,
198,
220,
220,
220,
26571,
62,
7645,
2673,
62,
4164,
10466,
11,
198,
220,
220,
220,
26571,
62,
7645,
2673,
62,
48277,
11,
198,
220,
220,
220,
8006,
62,
7645,
2673,
62,
4164,
10466,
11,
198,
220,
220,
220,
20957,
62,
46430,
62,
13376,
62,
40148,
11,
198,
8,
198,
198,
10913,
2390,
6217,
14670,
62,
47123,
41132,
796,
5855,
37906,
14,
21055,
6433,
14,
8248,
21348,
14,
4,
82,
1,
4064,
3491,
21348,
13,
834,
9641,
834,
11,
352,
8,
198,
7206,
38865,
62,
44,
2389,
35,
2538,
33746,
62,
47123,
49,
19505,
796,
685,
198,
220,
220,
220,
5855,
22203,
14,
7364,
21348,
13,
27171,
1574,
13,
48277,
25,
10697,
12331,
34621,
1574,
13,
834,
13345,
834,
1600,
352,
828,
198,
220,
220,
220,
5855,
22203,
14,
7364,
21348,
13,
1069,
11755,
25,
16922,
34621,
1574,
13,
834,
13345,
834,
1600,
352,
828,
198,
60,
198,
44,
2389,
35,
2538,
33746,
62,
47123,
49,
19505,
796,
685,
198,
220,
220,
220,
5855,
22203,
47835,
16793,
62,
31438,
25,
27171,
1574,
62,
69,
9548,
29847,
17946,
874,
28401,
27171,
1574,
1600,
362,
828,
198,
220,
220,
220,
5855,
22203,
47835,
16793,
62,
31438,
25,
27171,
1574,
62,
12501,
273,
1352,
1600,
352,
828,
198,
60,
1343,
5550,
38865,
62,
44,
2389,
35,
2538,
33746,
62,
47123,
49,
19505,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
1600,
5855,
3919,
62,
18224,
62,
30281,
1600,
4008,
198,
31,
12102,
378,
62,
7645,
2673,
62,
4164,
10466,
7,
198,
220,
220,
220,
45434,
16793,
62,
31438,
25,
9630,
1600,
198,
220,
220,
220,
629,
19458,
62,
4164,
10466,
28,
44,
2389,
35,
2538,
33746,
62,
47123,
49,
19505,
1343,
685,
7203,
22203,
47835,
16793,
62,
31438,
25,
9630,
1600,
352,
8,
4357,
198,
220,
220,
220,
4836,
929,
62,
4164,
10466,
41888,
10913,
2390,
6217,
14670,
62,
47123,
41132,
4357,
198,
8,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
1600,
5855,
3919,
62,
18224,
62,
30281,
1600,
4008,
198,
31,
12102,
378,
62,
7645,
2673,
62,
4164,
10466,
7,
198,
220,
220,
220,
45434,
16793,
62,
31438,
25,
13159,
62,
292,
13361,
1600,
198,
220,
220,
220,
629,
19458,
62,
4164,
10466,
28,
44,
2389,
35,
2538,
33746,
62,
47123,
49,
19505,
1343,
685,
7203,
22203,
47835,
16793,
62,
31438,
25,
13159,
62,
292,
13361,
1600,
352,
8,
4357,
198,
220,
220,
220,
4836,
929,
62,
4164,
10466,
41888,
10913,
2390,
6217,
14670,
62,
47123,
41132,
4357,
198,
8,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
11,
8611,
62,
3672,
1600,
357,
198,
220,
220,
220,
220,
220,
220,
220,
5855,
3919,
62,
18224,
62,
30281,
1600,
366,
7364,
21348,
13,
1069,
11755,
25,
16922,
34621,
1574,
13,
834,
13345,
834,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
5855,
13159,
62,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
366,
7364,
21348,
13,
1069,
11755,
25,
16922,
34621,
1574,
13,
834,
13345,
834,
12340,
198,
220,
220,
220,
15306,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
1600,
5855,
3919,
62,
18224,
62,
30281,
1600,
4008,
220,
220,
220,
220,
198,
31,
12102,
378,
62,
7645,
2673,
62,
4164,
10466,
7,
198,
220,
220,
220,
45434,
16793,
62,
31438,
25,
27171,
1574,
62,
69,
9548,
29847,
17946,
874,
28401,
27171,
1574,
1600,
198,
220,
220,
220,
629,
19458,
62,
4164,
10466,
41888,
7203,
22203,
47835,
16793,
62,
31438,
25,
27171,
1574,
62,
69,
9548,
29847,
17946,
874,
28401,
27171,
1574,
1600,
352,
8,
4357,
198,
220,
220,
220,
4836,
929,
62,
4164,
10466,
41888,
10913,
2390,
6217,
14670,
62,
47123,
41132,
4357,
198,
8,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
11,
7645,
2673,
62,
3672,
11,
6978,
11,
1416,
19458,
62,
4164,
10466,
1600,
357,
198,
220,
220,
220,
5855,
13159,
62,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
43282,
62,
18224,
1600,
12813,
43282,
62,
18224,
1600,
17635,
828,
198,
220,
220,
220,
5855,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
43282,
62,
18224,
1600,
12813,
43282,
62,
18224,
1600,
685,
7203,
22203,
47835,
16793,
62,
31438,
25,
292,
13361,
62,
18224,
62,
30281,
1600,
352,
15437,
828,
198,
220,
220,
220,
5855,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
43282,
62,
18224,
1600,
12813,
43282,
62,
18224,
1600,
685,
7203,
22203,
14,
7364,
21348,
13,
27171,
1574,
13,
48277,
25,
10697,
12331,
34621,
1574,
13,
18224,
62,
26209,
1600,
352,
15437,
828,
198,
220,
220,
220,
5855,
24442,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
43282,
62,
18224,
1600,
12813,
43282,
62,
18224,
1600,
685,
7203,
22203,
14,
7364,
21348,
13,
27171,
1574,
13,
48277,
25,
10697,
12331,
34621,
1574,
13,
24442,
62,
26209,
1600,
352,
15437,
828,
198,
220,
220,
220,
5855,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
15022,
43401,
1600,
12813,
1831,
62,
43282,
62,
18224,
1600,
17635,
828,
198,
4008,
198,
31,
12102,
378,
62,
7645,
2673,
62,
48277,
7,
48277,
28,
14692,
18780,
1040,
25,
41006,
12331,
8973,
8,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
11,
7645,
2673,
62,
3672,
11,
6978,
11,
18224,
1600,
357,
198,
220,
220,
220,
5855,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
38788,
62,
18224,
1600,
12813,
38788,
62,
18224,
1600,
45434,
16793,
62,
31438,
25,
12885,
992,
12331,
12340,
198,
220,
220,
220,
5855,
13159,
62,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
13159,
62,
292,
13361,
62,
38788,
62,
18224,
1600,
12813,
13159,
62,
292,
13361,
62,
38788,
62,
18224,
1600,
45434,
16793,
62,
31438,
25,
15419,
42367,
12885,
992,
12331,
4943,
198,
4008,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
11,
7645,
2673,
62,
3672,
11,
6978,
1600,
357,
198,
220,
220,
220,
5855,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
38788,
62,
18224,
1600,
12813,
38788,
62,
18224,
12340,
198,
220,
220,
220,
5855,
13159,
62,
292,
13361,
62,
18224,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
45434,
16793,
62,
31438,
25,
13159,
62,
292,
13361,
62,
38788,
62,
18224,
1600,
12813,
13159,
62,
292,
13361,
62,
38788,
62,
18224,
4943,
198,
4008,
198,
31,
2502,
13154,
62,
46430,
62,
13376,
62,
40148,
7,
2617,
19510,
4059,
11,
22305,
628,
198,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
11,
1416,
19458,
62,
4164,
10466,
1600,
357,
198,
220,
220,
220,
5855,
3919,
62,
27171,
1574,
1600,
685,
7203,
22203,
14,
7364,
21348,
13,
1069,
11755,
25,
16922,
34621,
1574,
13,
4023,
62,
1069,
4516,
1600,
352,
15437,
828,
198,
220,
220,
220,
5855,
660,
499,
313,
62,
1069,
4516,
62,
30281,
62,
3919,
62,
27171,
1574,
1600,
685,
7203,
22203,
47835,
16793,
62,
31438,
25,
660,
499,
313,
62,
30281,
1600,
352,
8,
12962,
198,
4008,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
1600,
5855,
3919,
62,
27171,
1574,
1600,
4008,
198,
31,
12102,
378,
62,
7645,
2673,
62,
48277,
7,
48277,
28,
14692,
18780,
1040,
25,
41006,
12331,
8973,
8,
198,
31,
12102,
378,
62,
7645,
2673,
62,
4164,
10466,
7,
198,
220,
220,
220,
45434,
16793,
62,
31438,
25,
15022,
43401,
1600,
4836,
929,
62,
4164,
10466,
41888,
10913,
2390,
6217,
14670,
62,
47123,
41132,
60,
198,
8,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
1324,
62,
3672,
1600,
5855,
3919,
62,
18224,
62,
30281,
1600,
4008,
628,
198
] | 2.903974 | 1,510 |
import jira
__URL = "http://jira.example.com"
__USER = "my_user"
__PASS = "my_pass"
__ISSUE = "VOL-1234"
my_jira = jira.Jira(__URL, __USER, __PASS)
my_issue = my_jira.get_issue(__ISSUE)
print(my_issue.summary) | [
11748,
474,
8704,
198,
198,
834,
21886,
796,
366,
4023,
1378,
73,
8704,
13,
20688,
13,
785,
1,
198,
834,
29904,
796,
366,
1820,
62,
7220,
1,
198,
834,
47924,
796,
366,
1820,
62,
6603,
1,
198,
834,
16744,
8924,
796,
366,
44558,
12,
1065,
2682,
1,
198,
198,
1820,
62,
73,
8704,
796,
474,
8704,
13,
41,
8704,
7,
834,
21886,
11,
11593,
29904,
11,
11593,
47924,
8,
198,
1820,
62,
21949,
796,
616,
62,
73,
8704,
13,
1136,
62,
21949,
7,
834,
16744,
8924,
8,
198,
4798,
7,
1820,
62,
21949,
13,
49736,
8
] | 2.197917 | 96 |
import os
from typing import List
import cv2
from fastapi import APIRouter, Depends, HTTPException, status
from fastapi.requests import Request
from fastapi.responses import FileResponse
from natsort import os_sorted
from pydantic import BaseModel, validator
from .projects import ProjectType
from ..config import Settings, get_settings
from ..managers import get_label_manager, LabelManager, LabelsModel
from ..responses import VideoResponse
from ..utils import QueryModel, get_project_path
router = APIRouter()
@router.get("", response_model=List[VideoItemResponse])
@router.get("/{video}", response_model=VideoDetailResponse)
@router.get("/{video}/stream")
@router.get("/{video}/frames")
@router.get("/{video}/frames/{frame}")
@router.post("/{video}/frames", response_model=List[str])
@router.get("/{video}/labels", response_model=LabelsModel)
@router.put("/{video}/labels")
| [
11748,
28686,
198,
6738,
19720,
1330,
7343,
198,
198,
11748,
269,
85,
17,
198,
6738,
3049,
15042,
1330,
3486,
4663,
39605,
11,
2129,
2412,
11,
14626,
16922,
11,
3722,
198,
6738,
3049,
15042,
13,
8897,
3558,
1330,
19390,
198,
6738,
3049,
15042,
13,
16733,
274,
1330,
9220,
31077,
198,
6738,
299,
1381,
419,
1330,
28686,
62,
82,
9741,
198,
6738,
279,
5173,
5109,
1330,
7308,
17633,
11,
4938,
1352,
198,
198,
6738,
764,
42068,
1330,
4935,
6030,
198,
6738,
11485,
11250,
1330,
16163,
11,
651,
62,
33692,
198,
6738,
11485,
805,
10321,
1330,
651,
62,
18242,
62,
37153,
11,
36052,
13511,
11,
3498,
1424,
17633,
198,
6738,
11485,
16733,
274,
1330,
7623,
31077,
198,
6738,
11485,
26791,
1330,
43301,
17633,
11,
651,
62,
16302,
62,
6978,
198,
198,
472,
353,
796,
3486,
4663,
39605,
3419,
628,
198,
198,
31,
472,
353,
13,
1136,
7203,
1600,
2882,
62,
19849,
28,
8053,
58,
10798,
7449,
31077,
12962,
628,
628,
198,
31,
472,
353,
13,
1136,
7203,
14,
90,
15588,
92,
1600,
2882,
62,
19849,
28,
10798,
11242,
603,
31077,
8,
628,
198,
31,
472,
353,
13,
1136,
7203,
14,
90,
15588,
92,
14,
5532,
4943,
628,
198,
31,
472,
353,
13,
1136,
7203,
14,
90,
15588,
92,
14,
37805,
4943,
628,
198,
31,
472,
353,
13,
1136,
7203,
14,
90,
15588,
92,
14,
37805,
14,
90,
14535,
92,
4943,
628,
198,
198,
31,
472,
353,
13,
7353,
7203,
14,
90,
15588,
92,
14,
37805,
1600,
2882,
62,
19849,
28,
8053,
58,
2536,
12962,
628,
198,
31,
472,
353,
13,
1136,
7203,
14,
90,
15588,
92,
14,
23912,
1424,
1600,
2882,
62,
19849,
28,
17822,
1424,
17633,
8,
628,
198,
31,
472,
353,
13,
1996,
7203,
14,
90,
15588,
92,
14,
23912,
1424,
4943,
198
] | 3.085616 | 292 |
r = range(8)
for x in r:
for y in r:
for x1 in r:
if x < x1:
print '(nCell %d east %d %d %d %d)' % (x1-x, x, y, x1, y)
elif x > x1:
print '(nCell %d west %d %d %d %d)' % (x-x1, x, y, x1, y)
for y1 in r:
if y < y1:
print '(nCell %d south %d %d %d %d)' % (y1-y, x, y, x, y1)
elif y > y1:
print '(nCell %d north %d %d %d %d)' % (y-y1, x, y, x, y1)
| [
81,
796,
2837,
7,
23,
8,
198,
1640,
2124,
287,
374,
25,
198,
197,
1640,
331,
287,
374,
25,
198,
197,
197,
1640,
2124,
16,
287,
374,
25,
198,
197,
197,
197,
361,
2124,
1279,
2124,
16,
25,
198,
197,
197,
197,
197,
4798,
29513,
77,
28780,
4064,
67,
7627,
4064,
67,
4064,
67,
4064,
67,
4064,
67,
33047,
4064,
357,
87,
16,
12,
87,
11,
2124,
11,
331,
11,
2124,
16,
11,
331,
8,
198,
197,
197,
197,
417,
361,
2124,
1875,
2124,
16,
25,
198,
197,
197,
197,
197,
4798,
29513,
77,
28780,
4064,
67,
7421,
4064,
67,
4064,
67,
4064,
67,
4064,
67,
33047,
4064,
357,
87,
12,
87,
16,
11,
2124,
11,
331,
11,
2124,
16,
11,
331,
8,
198,
197,
197,
1640,
331,
16,
287,
374,
25,
198,
197,
197,
197,
361,
331,
1279,
331,
16,
25,
198,
197,
197,
197,
197,
4798,
29513,
77,
28780,
4064,
67,
5366,
4064,
67,
4064,
67,
4064,
67,
4064,
67,
33047,
4064,
357,
88,
16,
12,
88,
11,
2124,
11,
331,
11,
2124,
11,
331,
16,
8,
198,
197,
197,
197,
417,
361,
331,
1875,
331,
16,
25,
198,
197,
197,
197,
197,
4798,
29513,
77,
28780,
4064,
67,
5093,
4064,
67,
4064,
67,
4064,
67,
4064,
67,
33047,
4064,
357,
88,
12,
88,
16,
11,
2124,
11,
331,
11,
2124,
11,
331,
16,
8,
198
] | 1.657895 | 228 |
# -*- coding: utf-8 -*-
import json
from datetime import datetime, timedelta
import requests
import lxml
from pykml.factory import KML_ElementMaker as KML
URL = 'http://iss-positioner.nkoshelev.tech/lst'
NOW = datetime.utcnow()
PARAMS = dict(start_dt=NOW.isoformat(),
end_dt=(NOW + timedelta(days=21)).isoformat(),
dist='250',
units='km',
sun_angle=json.dumps({'$between': [1, 90]}))
FILES = dict(lst=open('uragan.lst', 'rb'))
if __name__ == '__main__':
main()
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
33918,
198,
6738,
4818,
8079,
1330,
4818,
8079,
11,
28805,
12514,
198,
198,
11748,
7007,
198,
11748,
300,
19875,
198,
6738,
12972,
74,
4029,
13,
69,
9548,
1330,
509,
5805,
62,
20180,
48890,
355,
509,
5805,
198,
198,
21886,
796,
705,
4023,
1378,
747,
12,
9150,
263,
13,
77,
46150,
258,
2768,
13,
13670,
14,
75,
301,
6,
198,
45669,
796,
4818,
8079,
13,
315,
66,
2197,
3419,
198,
198,
27082,
40834,
796,
8633,
7,
9688,
62,
28664,
28,
45669,
13,
26786,
18982,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
886,
62,
28664,
16193,
45669,
1343,
28805,
12514,
7,
12545,
28,
2481,
29720,
26786,
18982,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1233,
11639,
9031,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4991,
11639,
13276,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4252,
62,
9248,
28,
17752,
13,
67,
8142,
15090,
6,
3,
23395,
10354,
685,
16,
11,
4101,
48999,
4008,
198,
46700,
1546,
796,
8633,
7,
75,
301,
28,
9654,
10786,
333,
7329,
13,
75,
301,
3256,
705,
26145,
6,
4008,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.209205 | 239 |
"""
Module for implementation Naive Bayes Classifier.
"""
import string
from collections import Counter
from typing import Dict
from bayesian_classifier import *
import pandas as pd
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
def process_data(data_file):
"""
Function for data processing and split it into X and y sets.
:param data_file: str - train data
:return: pd.DataFrame|list, pd.DataFrame|list - X and y data frames or lists
"""
data = pd.read_csv(data_file)
data = data.loc[:, ~data.columns.str.contains('^Unnamed')]
data = data.drop('id', 1)
X = []
y = data['author']
banwords = stopwords.words('english')
for index, row in data.iterrows():
row['text'] = row['text'].translate(str.maketrans('', '', string.punctuation))
X.append(dict(Counter([word.lower() for word in word_tokenize(row['text']) if word not in banwords])))
return X, y
def merge_dicts(dict1, dict2):
"""
Merges all the dictionaries, so in result bag of words can be created.
"""
if len(dict1) < len(dict2):
dict1, dict2 = dict2, dict1
for key, value in dict2.items():
dict1[key] = dict1.get(key, 0) + value
return dict1
if __name__ == '__main__':
train_X, train_y = process_data("data/train.csv")
print("Train parse done")
test_X, test_y = process_data("data/test.csv")
print("Test parse done")
classifier = BayesianClassifier()
classifier.fit(train_X, train_y)
print(f"Model score: {classifier.score(test_X, test_y)}")
| [
37811,
198,
26796,
329,
7822,
11013,
425,
4696,
274,
5016,
7483,
13,
198,
37811,
198,
11748,
4731,
198,
6738,
17268,
1330,
15034,
198,
6738,
19720,
1330,
360,
713,
198,
6738,
15489,
35610,
62,
4871,
7483,
1330,
1635,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
299,
2528,
74,
13,
10215,
79,
385,
1330,
2245,
10879,
198,
6738,
299,
2528,
74,
13,
30001,
1096,
1330,
1573,
62,
30001,
1096,
628,
198,
4299,
1429,
62,
7890,
7,
7890,
62,
7753,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
329,
1366,
7587,
290,
6626,
340,
656,
1395,
290,
331,
5621,
13,
198,
220,
220,
220,
1058,
17143,
1366,
62,
7753,
25,
965,
532,
4512,
1366,
198,
220,
220,
220,
1058,
7783,
25,
279,
67,
13,
6601,
19778,
91,
4868,
11,
279,
67,
13,
6601,
19778,
91,
4868,
532,
1395,
290,
331,
1366,
13431,
393,
8341,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1366,
796,
279,
67,
13,
961,
62,
40664,
7,
7890,
62,
7753,
8,
198,
220,
220,
220,
1366,
796,
1366,
13,
17946,
58,
45299,
5299,
7890,
13,
28665,
82,
13,
2536,
13,
3642,
1299,
10786,
61,
3118,
13190,
11537,
60,
198,
220,
220,
220,
1366,
796,
1366,
13,
14781,
10786,
312,
3256,
352,
8,
628,
220,
220,
220,
1395,
796,
17635,
198,
220,
220,
220,
331,
796,
1366,
17816,
9800,
20520,
198,
220,
220,
220,
3958,
10879,
796,
2245,
10879,
13,
10879,
10786,
39126,
11537,
198,
220,
220,
220,
329,
6376,
11,
5752,
287,
1366,
13,
2676,
8516,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
5752,
17816,
5239,
20520,
796,
5752,
17816,
5239,
6,
4083,
7645,
17660,
7,
2536,
13,
76,
461,
21879,
504,
10786,
3256,
705,
3256,
4731,
13,
79,
16260,
2288,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1395,
13,
33295,
7,
11600,
7,
31694,
26933,
4775,
13,
21037,
3419,
329,
1573,
287,
1573,
62,
30001,
1096,
7,
808,
17816,
5239,
6,
12962,
611,
1573,
407,
287,
3958,
10879,
60,
22305,
198,
220,
220,
220,
1441,
1395,
11,
331,
628,
198,
4299,
20121,
62,
11600,
82,
7,
11600,
16,
11,
8633,
17,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
4638,
3212,
477,
262,
48589,
3166,
11,
523,
287,
1255,
6131,
286,
2456,
460,
307,
2727,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
18896,
7,
11600,
16,
8,
1279,
18896,
7,
11600,
17,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
8633,
16,
11,
8633,
17,
796,
8633,
17,
11,
8633,
16,
628,
220,
220,
220,
329,
1994,
11,
1988,
287,
8633,
17,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
8633,
16,
58,
2539,
60,
796,
8633,
16,
13,
1136,
7,
2539,
11,
657,
8,
1343,
1988,
198,
220,
220,
220,
1441,
8633,
16,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
4512,
62,
55,
11,
4512,
62,
88,
796,
1429,
62,
7890,
7203,
7890,
14,
27432,
13,
40664,
4943,
198,
220,
220,
220,
3601,
7203,
44077,
21136,
1760,
4943,
198,
220,
220,
220,
1332,
62,
55,
11,
1332,
62,
88,
796,
1429,
62,
7890,
7203,
7890,
14,
9288,
13,
40664,
4943,
198,
220,
220,
220,
3601,
7203,
14402,
21136,
1760,
4943,
628,
220,
220,
220,
1398,
7483,
796,
4696,
35610,
9487,
7483,
3419,
198,
220,
220,
220,
1398,
7483,
13,
11147,
7,
27432,
62,
55,
11,
4512,
62,
88,
8,
198,
220,
220,
220,
3601,
7,
69,
1,
17633,
4776,
25,
1391,
4871,
7483,
13,
26675,
7,
9288,
62,
55,
11,
1332,
62,
88,
38165,
4943,
198
] | 2.622705 | 599 |
#!/usr/bin/env python
# -*-python-*-
#
# Copyright (C) 1999-2013 The ViewCVS Group. All Rights Reserved.
#
# By using this file, you agree to the terms and conditions set forth in
# the LICENSE.html file which can be found at the top level of the ViewVC
# distribution or at http://viewvc.org/license-1.html.
#
# For more information, visit http://viewvc.org/
#
# -----------------------------------------------------------------------
#
# CGI script to process and display queries to CVSdb
#
# This script is part of the ViewVC package. More information can be
# found at http://viewvc.org
#
# -----------------------------------------------------------------------
import os
import sys
import string
import time
from common import _item, TemplateData
import cvsdb
import viewvc
import ezt
import debug
import urllib
import fnmatch
## returns a tuple-list (mod-str, string)
def prev_rev(rev):
'''Returns a string representing the previous revision of the argument.'''
r = rev.split('.')
# decrement final revision component
r[-1] = str(int(r[-1]) - 1)
# prune if we pass the beginning of the branch
if len(r) > 2 and r[-1] == '0':
r = r[:-2]
return '.'.join(r)
def is_forbidden(cfg, cvsroot_name, module):
'''Return 1 if MODULE in CVSROOT_NAME is forbidden; return 0 otherwise.'''
# CVSROOT_NAME might be None here if the data comes from an
# unconfigured root. This interfaces doesn't care that the root
# isn't configured, but if that's the case, it will consult only
# the base and per-vhost configuration for authorizer and
# authorizer parameters.
if cvsroot_name:
cfg = cfg.get_root_config(cvsroot_name)
authorizer = cfg.options.authorizer
params = cfg.get_authorizer_params()
# If CVSROOT_NAME isn't configured to use an authorizer, nothing
# is forbidden. If it's configured to use something other than
# the 'forbidden' authorizer, complain. Otherwise, check for
# forbiddenness per the PARAMS as expected.
if not authorizer:
return 0
if authorizer != 'forbidden':
raise Exception("The 'forbidden' authorizer is the only one supported "
"by this interface. The '%s' root is configured to "
"use a different one." % (cvsroot_name))
forbidden = params.get('forbidden', '')
forbidden = map(lambda x: x.strip(), filter(None, forbidden.split(',')))
default = 0
for pat in forbidden:
if pat[0] == '!':
default = 1
if fnmatch.fnmatchcase(module, pat[1:]):
return 0
elif fnmatch.fnmatchcase(module, pat):
return 1
return default
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
29412,
12,
9,
12,
198,
2,
198,
2,
15069,
357,
34,
8,
7358,
12,
6390,
383,
3582,
34,
20304,
4912,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
2750,
1262,
428,
2393,
11,
345,
4236,
284,
262,
2846,
290,
3403,
900,
6071,
287,
198,
2,
262,
38559,
24290,
13,
6494,
2393,
543,
460,
307,
1043,
379,
262,
1353,
1241,
286,
262,
3582,
15922,
198,
2,
6082,
393,
379,
2638,
1378,
1177,
28435,
13,
2398,
14,
43085,
12,
16,
13,
6494,
13,
198,
2,
198,
2,
1114,
517,
1321,
11,
3187,
2638,
1378,
1177,
28435,
13,
2398,
14,
198,
2,
198,
2,
16529,
26866,
198,
2,
198,
2,
36378,
4226,
284,
1429,
290,
3359,
20743,
284,
327,
20304,
9945,
198,
2,
198,
2,
770,
4226,
318,
636,
286,
262,
3582,
15922,
5301,
13,
3125,
1321,
460,
307,
198,
2,
1043,
379,
2638,
1378,
1177,
28435,
13,
2398,
198,
2,
198,
2,
16529,
26866,
198,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
4731,
198,
11748,
640,
198,
198,
6738,
2219,
1330,
4808,
9186,
11,
37350,
6601,
198,
11748,
269,
14259,
9945,
198,
11748,
1570,
28435,
198,
11748,
304,
89,
83,
198,
11748,
14257,
198,
11748,
2956,
297,
571,
198,
11748,
24714,
15699,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
2235,
5860,
257,
46545,
12,
4868,
357,
4666,
12,
2536,
11,
4731,
8,
198,
198,
4299,
8654,
62,
18218,
7,
18218,
2599,
198,
220,
220,
220,
705,
7061,
35561,
257,
4731,
10200,
262,
2180,
18440,
286,
262,
4578,
2637,
7061,
198,
220,
220,
220,
374,
796,
2710,
13,
35312,
10786,
2637,
8,
198,
220,
220,
220,
1303,
5255,
434,
2457,
18440,
7515,
198,
220,
220,
220,
374,
58,
12,
16,
60,
796,
965,
7,
600,
7,
81,
58,
12,
16,
12962,
532,
352,
8,
198,
220,
220,
220,
1303,
778,
1726,
611,
356,
1208,
262,
3726,
286,
262,
8478,
198,
220,
220,
220,
611,
18896,
7,
81,
8,
1875,
362,
290,
374,
58,
12,
16,
60,
6624,
705,
15,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
374,
796,
374,
58,
21912,
17,
60,
198,
220,
220,
220,
1441,
705,
2637,
13,
22179,
7,
81,
8,
198,
198,
4299,
318,
62,
1640,
37978,
7,
37581,
11,
269,
14259,
15763,
62,
3672,
11,
8265,
2599,
198,
220,
220,
220,
705,
7061,
13615,
352,
611,
33893,
287,
26196,
12562,
46,
2394,
62,
20608,
318,
19467,
26,
1441,
657,
4306,
2637,
7061,
628,
220,
220,
220,
1303,
26196,
12562,
46,
2394,
62,
20608,
1244,
307,
6045,
994,
611,
262,
1366,
2058,
422,
281,
198,
220,
220,
220,
1303,
555,
11250,
1522,
6808,
13,
220,
770,
20314,
1595,
470,
1337,
326,
262,
6808,
198,
220,
220,
220,
1303,
2125,
470,
17839,
11,
475,
611,
326,
338,
262,
1339,
11,
340,
481,
5725,
691,
198,
220,
220,
220,
1303,
262,
2779,
290,
583,
12,
85,
4774,
8398,
329,
1772,
7509,
290,
198,
220,
220,
220,
1303,
1772,
7509,
10007,
13,
198,
220,
220,
220,
611,
269,
14259,
15763,
62,
3672,
25,
198,
220,
220,
220,
220,
220,
220,
220,
30218,
70,
796,
30218,
70,
13,
1136,
62,
15763,
62,
11250,
7,
66,
14259,
15763,
62,
3672,
8,
198,
220,
220,
220,
1772,
7509,
796,
30218,
70,
13,
25811,
13,
9800,
7509,
198,
220,
220,
220,
42287,
796,
30218,
70,
13,
1136,
62,
9800,
7509,
62,
37266,
3419,
628,
220,
220,
220,
1303,
1002,
26196,
12562,
46,
2394,
62,
20608,
2125,
470,
17839,
284,
779,
281,
1772,
7509,
11,
2147,
198,
220,
220,
220,
1303,
318,
19467,
13,
220,
1002,
340,
338,
17839,
284,
779,
1223,
584,
621,
198,
220,
220,
220,
1303,
262,
705,
1640,
37978,
6,
1772,
7509,
11,
13121,
13,
220,
15323,
11,
2198,
329,
198,
220,
220,
220,
1303,
19467,
1108,
583,
262,
29463,
40834,
355,
2938,
13,
198,
220,
220,
220,
611,
407,
1772,
7509,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
657,
198,
220,
220,
220,
611,
1772,
7509,
14512,
705,
1640,
37978,
10354,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
464,
705,
1640,
37978,
6,
1772,
7509,
318,
262,
691,
530,
4855,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1525,
428,
7071,
13,
220,
383,
705,
4,
82,
6,
6808,
318,
17839,
284,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1904,
257,
1180,
530,
526,
4064,
357,
66,
14259,
15763,
62,
3672,
4008,
198,
220,
220,
220,
19467,
796,
42287,
13,
1136,
10786,
1640,
37978,
3256,
10148,
8,
198,
220,
220,
220,
19467,
796,
3975,
7,
50033,
2124,
25,
2124,
13,
36311,
22784,
8106,
7,
14202,
11,
19467,
13,
35312,
7,
41707,
22305,
198,
220,
220,
220,
4277,
796,
657,
198,
220,
220,
220,
329,
1458,
287,
19467,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1458,
58,
15,
60,
6624,
705,
0,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
796,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
24714,
15699,
13,
22184,
15699,
7442,
7,
21412,
11,
1458,
58,
16,
47715,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
24714,
15699,
13,
22184,
15699,
7442,
7,
21412,
11,
1458,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
352,
198,
220,
220,
220,
1441,
4277,
198
] | 2.840671 | 954 |
try:
import pkg_resources
pkg_resources.declare_namespace(__name__)
except ImportError:
# don't prevent use of paste if pkg_resources isn't installed
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
try:
import modulefinder
except ImportError:
pass
else:
for p in __path__:
modulefinder.AddPackagePath(__name__, p)
| [
28311,
25,
198,
220,
220,
220,
1330,
279,
10025,
62,
37540,
198,
220,
220,
220,
279,
10025,
62,
37540,
13,
32446,
533,
62,
14933,
10223,
7,
834,
3672,
834,
8,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1303,
836,
470,
2948,
779,
286,
17008,
611,
279,
10025,
62,
37540,
2125,
470,
6589,
198,
220,
220,
220,
422,
279,
10025,
22602,
1330,
9117,
62,
6978,
198,
220,
220,
220,
11593,
6978,
834,
796,
9117,
62,
6978,
7,
834,
6978,
834,
11,
11593,
3672,
834,
8,
220,
198,
198,
28311,
25,
198,
220,
220,
220,
1330,
8265,
22805,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1208,
198,
17772,
25,
198,
220,
220,
220,
329,
279,
287,
11593,
6978,
834,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8265,
22805,
13,
4550,
27813,
15235,
7,
834,
3672,
834,
11,
279,
8,
198
] | 2.659722 | 144 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.