blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 3 281 | content_id stringlengths 40 40 | detected_licenses listlengths 0 57 | license_type stringclasses 2
values | repo_name stringlengths 6 116 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringclasses 313
values | visit_date timestamp[us] | revision_date timestamp[us] | committer_date timestamp[us] | github_id int64 18.2k 668M ⌀ | star_events_count int64 0 102k | fork_events_count int64 0 38.2k | gha_license_id stringclasses 17
values | gha_event_created_at timestamp[us] | gha_created_at timestamp[us] | gha_language stringclasses 107
values | src_encoding stringclasses 20
values | language stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.02M | extension stringclasses 78
values | content stringlengths 2 6.02M | authors listlengths 1 1 | author stringlengths 0 175 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
25454d11e4902e3ee96778aa068c6150e7eb95d9 | ee10de6ce6a56c3ba8670144490c61ff7ecaface | /json_to_csv.py | c6eb6a65a8864162d2eab96fb9ce3dbe9dcc350a | [] | no_license | thegsi/appstore-api | 91bdc2f8cdf32703981dc8a34c6679e11e3a2adb | 4c1e3a92d67a741a9f481f31d4303e45a0dab483 | refs/heads/master | 2020-03-19T20:52:33.445477 | 2018-09-27T10:53:04 | 2018-09-27T10:53:04 | 136,920,345 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 530 | py | import pandas as pd
from pandas import DataFrame
import json
with open('appstore_books150.json') as f:
appContent = json.load(f)
keys = appContent['results'][0].keys()
print(keys)
df = pd.DataFrame(columns=keys)
for i in range(len(appContent['results'])):
for k in keys:
if k in appContent['results'][i]:
appContent['results'][i][k] = str(appContent['results'][i][k])
df = df.append(appContent['results'][i], ignore_index=True)
df.to_csv('appstore_books150.csv', sep=',', encoding='utf-8')
| [
"dr.gethin.rees@gmail.com"
] | dr.gethin.rees@gmail.com |
a75789c16f0297f9a5da3ef0759607a3352284a8 | 161f0edac3720b488b3ba6e7f21083409bb841bc | /problem093.py | ed25ce7a8f68c6600c319b335ab97256bebb9124 | [] | no_license | chadheyne/project-euler | cd28589c12a092faf2c3f6f52df16b30bba2bf2d | 20155d0987754685a89d11b45a58580f7d1528de | refs/heads/master | 2021-01-09T20:14:00.659905 | 2013-11-10T06:41:59 | 2013-11-10T06:41:59 | 61,950,422 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,514 | py | #!/usr/bin/env python
from itertools import (
combinations,
permutations,
chain,
product)
def partitions(iterable):
n, s = len(iterable), iterable
first, middle, last = [0], range(1, n), [n]
return ['{}'.join(map(lambda i, j: '(' + '{}'.join(s[i:j]) + ')', chain(first, div), chain(div, last)))
for i in range(n) for div in combinations(middle, i)]
OPERATIONS = [(op1, op2, op3) for op1, op2, op3 in product(('+', '-', '/', '*'), repeat=3)]
def compute(numbers):
for operation in OPERATIONS:
try:
yield eval(numbers.format(*operation))
except ZeroDivisionError:
yield 0
def compute_permuted(number_string):
for perm in permutations(number_string):
for partition in partitions(perm):
yield from compute(partition)
def compute_combined(digits='0123456789'):
numbers = {}
for combo in combinations(digits, 4):
number = ''.join(combo)
numbers[number] = set()
for result in compute_permuted(number):
if result < 0:
continue
if isinstance(result, int) or result.is_integer():
numbers[number].add(int(result))
for number, results in numbers.items():
first_missing = min([i for i in results if i+1 not in results])
numbers[number] = first_missing
return numbers
def main():
results = compute_combined()
print(max(results, key=results.get))
if __name__ == "__main__":
main()
| [
"chadheyne@gmail.com"
] | chadheyne@gmail.com |
a72ddaff756e17ca53489a0964db37665a6783d2 | ded7716aaf8b0d118759bbb0f8f68e21ad1b2bf0 | /tasks.py | 68c4ed354fc47a747264b87ed2187e8492c70259 | [] | no_license | wmeaney/national-oceanographic-data-centre | 1617f0f398b9dfb8c2cf3b255da18678aa6258e7 | 83d9bd1627aa4f67217186019f9b4f686e4b7e88 | refs/heads/master | 2020-07-30T17:11:35.737649 | 2019-09-09T15:58:15 | 2019-09-09T15:58:15 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,107 | py | from invoke import task
import os
import xml.etree.ElementTree
import flask
app = flask.Flask('flaskInInvoke')
def enum():
return {'baseUrl':
'https://irishmarineinstitute.github.io/national-oceanographic-data-centre/'}
def getXmlNamespaces():
return {'gmd': 'http://www.isotc211.org/2005/gmd',
'gco': 'http://www.isotc211.org/2005/gco'}
def getNewFileName(oldFileName,switch):
e = xml.etree.ElementTree.parse(oldFileName).getroot()
if switch == "dataset":
for p in e.findall('./gmd:fileIdentifier/gco:CharacterString',
getXmlNamespaces()):
return str.replace(str.replace(p.text,'.','_'),':','__')
@task
def rename(c, dataset=False, sensor=False):
if dataset:
for f in (os.listdir("./iso-xml")):
if(getNewFileName("./iso-xml/" + f,'dataset') == None):
raise Exception('No metadata identifier found... File {}'.
format(f))
else:
os.rename("./iso-xml/" + f,
"./iso-xml/" + getNewFileName("./iso-xml/" +
f,'dataset') + ".xml")
@task
def applytransforms(c, dataset = False, sensor=False):
if dataset:
for f in (os.listdir("./iso-xml")):
print("Applying transformation to HTML...")
print("Applying transformation to RDF...")
@task
def buildsitemap(c):
Enum = enum()
urls = []
for f in (os.listdir("./html")):
with open('./html/'+f, 'r') as content_file:
content = content_file.read()
content = content[content.find('div id="lastModified"'):]
content = content[content.find('div class="blockValue"'):]
content = content[content.find('>') + 1:]
content = content[:content.find('<')]
urls.append({'url': 'html/' + f, 'lastModified': content})
with app.app_context():
rendered = flask.render_template('sitemap.xml',Enum = Enum, urls=urls)
with open('sitemap.xml', 'w+') as sitemap:
sitemap.write(rendered)
| [
"aleadbetter9@gmail.com"
] | aleadbetter9@gmail.com |
2d81eefaf47a0eaeb84f24fa28661b2e22ca929b | d67b4d6907b31ac2d9c07b73305e25a20d3a827b | /repro_packs/ellis/repro_exec_files/scripts/cext_wave_iso_pillar_AR3.py | 5e45796944c98b73f432fb3c66af6f6b4e675634 | [
"BSD-3-Clause",
"CC-BY-4.0",
"CC-BY-3.0"
] | permissive | stjordanis/pygbe_validation_paper | 13de7b06ebdb792146abdd8fb775d6e7361f4709 | ef826a8e956a817f919c4357a08aa8f675a910a4 | refs/heads/master | 2023-03-19T05:13:51.961685 | 2021-03-03T15:38:39 | 2021-03-03T15:38:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,200 | py | import numpy
import time
import sys
import os
from argparse import ArgumentParser
import pygbe
from pygbe.util.read_data import read_fields
from pygbe.main import main
from cext_wavelength_scanning import create_diel_list, Cext_wave_scan, Cext_analytical
def read_inputs(args):
"""
Parse command-line arguments to read arguments in main.
"""
parser = ArgumentParser(description='Read path where input files are located')
parser.add_argument('-if',
'--infiles',
type=str,
help="Absolute path where input files are located (downloaded from zenodo)")
return parser.parse_args(args)
def main(argv=sys.argv):
argv=sys.argv
args = read_inputs(argv[1:])
in_files_path = args.infiles
#Import surface data
wave_s, diel_rs, diel_is = numpy.loadtxt('../dielectric_data/4H-SIC_Angs_permittivity_800-1000cm-1.csv', skiprows=1, unpack=True)
air_diel = [1. + 1j*0.] * len(wave_s)
#Creating dielectric list first dielectric outside, then inside
diel_list = [list(eps) for eps in zip(air_diel, diel_rs + 1j*diel_is)]
#Set enviornment variable for PyGBe
folder_path = in_files_path + 'AR_3'
full_path = os.path.abspath(folder_path)+'/'
os.environ['PYGBE_PROBLEM_FOLDER'] = full_path
#Creating dictionary field. We will modify the 'E' key in the for loop.
field_dict_pillars = read_fields(full_path + 'iso_pillar.config')
#Calculate Cext(lambda) for pillars' surface
tic_ss = time.time()
e_field = -1.
wave, Cext_pillars = Cext_wave_scan(e_field, wave_s, diel_list, field_dict_pillars, full_path)
toc_ss = time.time()
numpy.savetxt('../results_data/iso_pillar_AR/'+'iso_pillar_AR_3'+'_800-1000cm-1_in_ang.txt',
list(zip(wave, Cext_pillars)),
fmt = '%.5f %.5f',
header = 'lambda [Ang], Cext [nm^2]')
time_simulation = (toc_ss - tic_ss)
with open('../results_data/iso_pillar_AR/Time_'+'iso_pillar_AR_3'+'_800-1000cm-1.txt', 'w') as f:
print('time_total: {} s'.format(time_simulation), file=f)
if __name__ == "__main__":
main(sys.argv)
| [
"natyclementi@gmail.com"
] | natyclementi@gmail.com |
bc125099241b8ffd9f1ccc9d93c01b6f7eaf5f23 | a05550df7d8385ac8cfe2f1ac30aa438e706dd59 | /src/eval/create_ranking_3models.py | 18e28432ac756acbb80fa5497ee808f946b56465 | [] | no_license | raosudha89/clarification_question_generation | 9a537e4410d649519e662c8ddd1d776d5a891deb | f8ed75cc25622fc82c753e8f73e9c25d5e2df344 | refs/heads/master | 2020-03-08T10:34:33.771492 | 2018-06-27T18:27:54 | 2018-06-27T18:27:54 | 128,076,744 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,741 | py | import argparse
import gzip
import nltk
import pdb
import sys, os
from collections import defaultdict
import csv
import random
def parse(path):
g = gzip.open(path, 'r')
for l in g:
yield eval(l)
def read_ids(fname):
return [line.strip('\n') for line in open(fname, 'r').readlines()]
def read_model_outputs(model_fname, model_test_ids_fname):
model_test_ids = read_ids(model_test_ids_fname)
with open(model_fname, 'r') as model_file:
model_outputs = [line.strip('\n') for line in model_file.readlines()]
model_output_dict = defaultdict(list)
for i, test_id in enumerate(model_test_ids):
asin = test_id.split('_')[0]
model_output_dict[asin].append(model_outputs[i])
return model_output_dict
def get_subset(candidates):
print len(candidates)
new_candidates = []
for cand in candidates:
if len(cand.split()) <= 50:
new_candidates.append(cand)
print len(new_candidates)
if len(new_candidates) == 0:
pdb.set_trace()
return new_candidates
def main(args):
titles = {}
descriptions = {}
test_ids = read_ids(args.test_ids)
lucene_model_outs = read_model_outputs(args.lucene_model, args.lucene_model_test_ids)
context_model_outs = read_model_outputs(args.context_model, args.context_model_test_ids)
candqs_model_outs = read_model_outputs(args.candqs_model, args.candqs_model_test_ids)
candqs_template_model_outs = read_model_outputs(args.candqs_template_model, \
args.candqs_template_model_test_ids)
for v in parse(args.metadata_fname):
asin = v['asin']
if asin not in test_ids:
continue
if asin not in lucene_model_outs or \
asin not in context_model_outs or \
asin not in candqs_model_outs or \
asin not in candqs_template_model_outs:
continue
description = v['description']
length = len(description.split())
title = v['title']
if length >= 100 or length < 10 or len(title.split()) == length:
continue
titles[asin] = title
descriptions[asin] = description
if len(descriptions) >= 100:
break
print len(descriptions)
questions = defaultdict(list)
for v in parse(args.qa_data_fname):
asin = v['asin']
if asin not in descriptions:
continue
questions[asin].append(v['question'])
csv_file = open(args.csv_file, 'w')
writer = csv.writer(csv_file, delimiter=',')
writer.writerow(['asin', 'title', 'description', \
'q1_model', 'q1', 'q2_model', 'q2', \
'q3_model', 'q3', 'q4_model', 'q4', \
'q5_model', 'q5'])
all_rows = []
for asin in descriptions:
title = titles[asin]
description = descriptions[asin]
#ques_candidates = []
#for ques in questions[asin]:
# if len(ques.split()) > 30:
# continue
# ques_candidates.append(ques)
gold_question = random.choice(questions[asin])
lucene_question = random.choice(lucene_model_outs[asin])
context_question = random.choice(context_model_outs[asin])
candqs_question = random.choice(candqs_model_outs[asin])
candqs_template_question = random.choice(candqs_template_model_outs[asin])
pairs = [('gold', gold_question), ('lucene', lucene_question), \
('context', context_question), ('candqs', candqs_question), \
('candqs_template', candqs_template_question)]
random.shuffle(pairs)
writer.writerow([asin, title, description, \
pairs[0][0], pairs[0][1], pairs[1][0], pairs[1][1], \
pairs[2][0], pairs[2][1], pairs[3][0], pairs[3][1], \
pairs[4][0], pairs[4][1]])
csv_file.close()
if __name__ == "__main__":
argparser = argparse.ArgumentParser(sys.argv[0])
argparser.add_argument("--qa_data_fname", type = str)
argparser.add_argument("--metadata_fname", type = str)
argparser.add_argument("--test_ids", type=str)
argparser.add_argument("--csv_file", type=str)
argparser.add_argument("--lucene_model", type=str)
argparser.add_argument("--lucene_model_test_ids", type=str)
argparser.add_argument("--context_model", type=str)
argparser.add_argument("--context_model_test_ids", type=str)
argparser.add_argument("--candqs_model", type=str)
argparser.add_argument("--candqs_model_test_ids", type=str)
argparser.add_argument("--candqs_template_model", type=str)
argparser.add_argument("--candqs_template_model_test_ids", type=str)
args = argparser.parse_args()
print args
print ""
main(args)
| [
"raosudha@umiacs.umd.edu"
] | raosudha@umiacs.umd.edu |
34a3c2e383db34435bf9f7f6871b4759c697745c | 30f15a184450d6e914ac16375e674cc2f993b9ce | /game/engine/scummvm/actions.py | 753eacd9cdf63940e2303b46b603fc71086fe5a4 | [] | no_license | Erick-Pardus/2013 | 9d0dd48e19400965476480a8e6826beb865bdb2e | 80943b26dbb4474f6e99f81752a0d963af565234 | refs/heads/master | 2021-01-18T16:57:58.233209 | 2012-10-30T20:35:42 | 2012-10-30T20:35:42 | 6,467,098 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,046 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Licensed under the GNU General Public License, version 2.
# See the file http://www.gnu.org/licenses/old-licenses/gpl-2.0.txt
from pisi.actionsapi import autotools
from pisi.actionsapi import pisitools
from pisi.actionsapi import shelltools
from pisi.actionsapi import get
shelltools.export("HOME", get.workDIR())
def setup():
autotools.rawConfigure("--prefix=/usr \
--enable-verbose-build \
--backend=sdl \
--enable-alsa \
--enable-flac \
--enable-mad \
--with-nasm-prefix=/usr/bin/nasm \
--enable-vorbis \
--enable-zlib")
def build():
autotools.make()
def install():
autotools.rawInstall("DESTDIR=%s" % get.installDIR())
pisitools.dohtml("doc/he/*.html")
pisitools.dodoc("AUTHORS", "COPYING", "COPYRIGHT", "NEWS", "README", "TODO", "doc/he/*.txt")
| [
"yusuf.aydemir@istanbul.com"
] | yusuf.aydemir@istanbul.com |
3ae3022f4d02fd4850ca632a44e0205b7d1fa653 | c93080264201fe6d0c84a79ae435022981d8ccf6 | /panoptic/panoptic/doctype/frt_link/frt_link.py | 67e8a4394dda3a574c7eb1b126c1d9f854e6c6c7 | [
"MIT"
] | permissive | wisharya/panoptic | 100e733e9aad33d087851fc4ea9bd064e81954f2 | 7c9a0eeb6bd5d9032087ccb7c805a3e65a357ba8 | refs/heads/master | 2023-07-09T14:20:45.377441 | 2021-08-25T06:58:45 | 2021-08-25T06:58:45 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 273 | py | # -*- coding: utf-8 -*-
# Copyright (c) 2020, Internet Freedom Foundation and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
# import frappe
from frappe.model.document import Document
class FRTLink(Document):
pass
| [
"scm.mymail@gmail.com"
] | scm.mymail@gmail.com |
938be44e36a1a72ed095f30a41dfeae540855d1a | c9ecaf4c376f7a4617588f382ee70fb3b4142bf0 | /weight/main_window.py | f3558dfdb195e521e543436566d94c614d53f91a | [] | no_license | Snowfly11531/api_get | d69a0629bc16d3dc3218163999e680ce18d9b9bb | 9668c563fb19cf5fe8a27b9a0ea082a763fb6797 | refs/heads/master | 2020-09-22T18:42:35.260445 | 2019-12-10T14:31:21 | 2019-12-10T14:31:21 | 225,300,450 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 901 | py | import sys
from PyQt5 import *
from weight.main_window_ui import *
from weight.parameter_frame import *
class Main_Window(QtWidgets.QWidget,Ui_Form):
def __init__(self):
super(QtWidgets.QWidget,self).__init__()
self.frameHeight=0
self.frameCount=0
self.setupUi(self)
def addframe(self):
test_frame = Parameter_Frame(self.scrollAreaWidgetContents)
self.frameHeight = test_frame.geometry().height()
top=self.frameHeight*self.frameCount
test_frame.setGeometry(QtCore.QRect(0, top, test_frame.geometry().width(), test_frame.geometry().height()))
self.scrollAreaWidgetContents.setMinimumHeight(top+self.frameHeight+10)
test_frame.show()
self.frameCount += 1
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
main_window = Main_Window()
main_window.show()
sys.exit(app.exec_()) | [
"245134041@qq.com"
] | 245134041@qq.com |
f4ef2defc06bdd2a35f26acedd9b7bac282e0460 | 4e54d2199f7c601f6efc58d88447eeeb3594a637 | /riselive/python_courses/datatype.3.py | f917572804f2b27081ab90ec6371e9caf2148654 | [
"MIT"
] | permissive | Z3Prover/doc | 4e23e40cef32cf8102bd0dda7fb76d01051f9210 | f79ba59ce06e855d783508d9b6f47a8947480d12 | refs/heads/master | 2023-09-05T19:45:26.160516 | 2023-08-01T17:01:16 | 2023-08-01T17:01:16 | 151,014,945 | 34 | 20 | MIT | 2023-06-30T03:29:19 | 2018-09-30T23:09:21 | HTML | UTF-8 | Python | false | false | 393 | py | Color = Datatype('Color')
Color.declare('red')
Color.declare('green')
Color.declare('blue')
Color = Color.create()
print is_expr(Color.green)
print Color.green == Color.blue
print simplify(Color.green == Color.blue)
# Let c be a constant of sort Color
c = Const('c', Color)
# Then, c must be red, green or blue
prove(Or(c == Color.green,
c == Color.blue,
c == Color.red))
| [
"nbjorner@microsoft.com"
] | nbjorner@microsoft.com |
63d075ebba8d418a5abd61db3765aec5ea7064c8 | 57ae9f6e97851930616739893493c335d04f6520 | /wings_sanic/utils.py | 515a95b58ee2d700a6b29faf48909962acc1669c | [] | no_license | songtao-git/wings-sanic | 25c9c5b4d75949b4872f1e32cb6d0368d877e2b2 | f273759360021aafdcf83ae30786e98af1b5df3d | refs/heads/master | 2021-06-11T23:27:45.604572 | 2021-03-29T08:11:58 | 2021-03-29T10:43:34 | 161,740,871 | 10 | 4 | null | 2021-03-29T10:43:35 | 2018-12-14T06:21:53 | Python | UTF-8 | Python | false | false | 5,059 | py | # -*- coding: utf-8 -*-
import datetime
import decimal
import inspect
import json
import os
from typing import Sequence, Mapping
from wings_sanic import datetime_helper
def instance_to_dict(instance):
"""
Convert instance to dict
"""
if not hasattr(instance, '__dict__'):
return None
data = {}
for k, v in instance.__dict__.items():
if k.startswith('__'):
continue
if k.startswith('_'):
continue
if callable(v):
continue
data[k] = v
return data
def instance_from_json(data, cls=None):
"""
如果cls有值, 则将data_string转化成对应的instance(s)
否则，转化成python内置类型
转化失败时：
如果cls是None, 则返回原字符串
否则，返回None
:param data: json结构的字符串
:param cls: type of class
:return:
"""
if isinstance(data, str):
try:
data = json.loads(data)
except:
pass
data = to_native(data)
if not cls:
return data
if isinstance(data, Mapping):
try:
return cls(**data)
except:
return None
if isinstance(data, Sequence) and not isinstance(data, str):
result = []
for i in data:
item_result = instance_from_json(i)
if item_result:
result.append(item_result)
return result or None
return None
def to_native(obj):
"""Convert obj to a richer Python construct. The obj can be anything
"""
if obj is None:
return None
if isinstance(obj, (int, float, bool, datetime.datetime, datetime.date, decimal.Decimal)):
return obj
elif isinstance(obj, str):
value = datetime_helper.parse_datetime(obj)
if not value:
value = datetime_helper.parse_date(obj)
return value or obj
if hasattr(obj, 'to_native') and callable(obj.to_native) \
and len(inspect.signature(obj.to_native).parameters) == 1:
return obj.to_native()
if hasattr(obj, '__dict__'):
obj = instance_to_dict(obj)
if isinstance(obj, Sequence):
return [to_native(item) for item in obj]
if isinstance(obj, Mapping):
return dict(
(k, to_native(v)) for k, v in obj.items()
)
return obj
def to_primitive(obj):
"""Convert obj to a value safe to serialize.
"""
if obj is None:
return None
if hasattr(obj, 'to_primitive') and callable(obj.to_primitive) \
and len(inspect.signature(obj.to_primitive).parameters) == 1:
return obj.to_primitive()
data = to_native(obj)
if isinstance(data, (int, float, bool, str)):
return data
if isinstance(data, datetime.datetime):
return datetime_helper.get_time_str(obj)
if isinstance(data, datetime.date):
return datetime_helper.get_date_str(obj)
if isinstance(data, Sequence):
return [to_primitive(e) for e in data]
elif isinstance(data, Mapping):
return dict(
(k, to_primitive(v)) for k, v in data.items()
)
return str(data)
def get_value(instance_or_dict, name, default=None):
if isinstance(instance_or_dict, Mapping):
return instance_or_dict.get(name, default)
return getattr(instance_or_dict, name, default)
def cls_str_of_meth(meth, separator='.'):
if meth is None:
return None
mod = inspect.getmodule(meth)
cls = meth.__qualname__.split('.<locals>', 1)[0].rsplit('.', 1)[0]
return f'{mod.__name__}.{cls}'.replace('.', separator)
def cls_str_of_obj(obj, separator='.'):
if obj is None:
return None
return f'{obj.__class__.__module__}.{obj.__class__.__name__}'.replace('.', separator)
def cls_str_of_cls(cls, separator='.'):
if cls is None:
return None
return f'{cls.__module__}.{cls.__name__}'.replace('.', separator)
def meth_str(meth, separator='.'):
if meth is None:
return None
return f'{meth.__module__}.{meth.__qualname__}'.replace('.', separator)
def import_from_str(obj_path):
module_name, obj_name = obj_path.rsplit('.', 1)
module_meta = __import__(module_name, globals(), locals(), [obj_name])
obj_meta = getattr(module_meta, obj_name)
return obj_meta
# Removes all null values from a dictionary
def remove_nulls(dictionary, deep=True):
return {
k: remove_nulls(v, deep) if deep and type(v) is dict else v
for k, v in dictionary.items()
if v not in [None, dict(), list(), tuple(), set(), '']
}
def __load(path):
for item in os.listdir(path):
item_path = '%s/%s' % (path, item)
if item.endswith('.py'):
__import__('{pkg}.{mdl}'.format(pkg=path.replace('/', '.'), mdl=item[:-3]))
elif os.path.isdir(item_path):
load_path(item_path)
def load_path(*path):
"""加载某目录下所有的.py文件，可用于加载某目录下所有的event handlers时"""
for p in path:
__load(p)
| [
"songtao@kicen.com"
] | songtao@kicen.com |
5b5698735c4bd1e1ec8573b99abd07c76cd9c04b | b5c6599d206ff282e9aa7539024d320bbafc99d2 | /dmtools/dmt_content/urls.py | 1877a2d967859034ad9c567ec20c2cdb5b58f142 | [] | no_license | BlitzKraft/DigitalMediaTools | e58c3a53fce5fb145d0e8f11e0780ec7e0b775bb | 86b7fd90dcf80c6cde7263864feee5691f6736d6 | refs/heads/master | 2021-01-22T11:29:18.500685 | 2017-05-29T05:59:17 | 2017-05-29T05:59:17 | 92,703,898 | 1 | 0 | null | 2017-05-29T03:38:07 | 2017-05-29T03:38:07 | null | UTF-8 | Python | false | false | 851 | py | """dmtools URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.10/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.conf.urls import url, include
2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls'))
"""
from django.conf.urls import url, include
from django.contrib import admin
from django.conf import settings
from django.conf.urls.static import static
urlpatterns = [
#url(r'^admin/', admin.site.urls),
]
| [
"andie.yancey@icloud.com"
] | andie.yancey@icloud.com |
3d1563c262a258c965c363b560ee8504998737bb | f214053ac4ea47da1c1ed1757625834c4251d79d | /utils/Yaml_Factory.py | 27d2e1473a4ffdfd5fa182f6d7266c9097c2222b | [] | no_license | gaozhao1989/mobile_uiautomation | fb031ccb6161c73b4aca92852891d4f0dc947ceb | 554edcaeb0164d3ac3e7fb1c99933b58e46d4a2d | refs/heads/master | 2020-12-03T00:09:25.556194 | 2017-07-02T00:59:42 | 2017-07-02T00:59:42 | 95,994,842 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,508 | py | import os, yaml
current_path = os.getcwd()
workspace_name = 'mobile_uiautomation'
workspace_path = current_path[:current_path.index(workspace_name) + len(workspace_name)]
def get_yaml_data(file_path):
stream = open(file_path, 'r', encoding='utf-8')
yaml_data = yaml.load(stream)
stream.close()
return yaml_data
def get_android_caps():
android_caps = get_yaml_data(workspace_path + '\\config\\android.yaml')['capabilities']
app_rel_path = android_caps['app']
android_caps['app'] = get_app_rel_path(app_rel_path)
return android_caps
def get_ios_caps():
ios_caps = get_yaml_data(workspace_path + '\\config\\ios.yaml')['capabilities']
app_rel_path = ios_caps['app']
ios_caps['app'] = get_app_rel_path(app_rel_path)
return ios_caps
def get_appium_config():
return get_yaml_data(workspace_path + '\\config\\server.yaml')['appium']
def get_test_platform():
return get_yaml_data(workspace_path + '\\config\\server.yaml')['platform']
def get_page_locators(locator_file):
return get_yaml_data(workspace_path + '\\pages\\locator\\' + locator_file + '.yaml')
def get_locator_properties(locator_file, locator_name, test_platform):
yaml_data = get_page_locators(locator_file)
return yaml_data[locator_file]['elements'][locator_name][test_platform]['find_by'], \
yaml_data[locator_file]['elements'][locator_name][test_platform]['value']
def get_app_rel_path(app_name):
return os.path.join(workspace_path, 'apps', app_name)
| [
"zhaogao@ZhaodeMacBook-Pro.local"
] | zhaogao@ZhaodeMacBook-Pro.local |
2cd19af823e90d2a4f99f3ee7ad155f837d1bb6c | f708a01bdfd1133883ec43dc9f7fc1dd8efd655c | /backend/home/migrations/0002_load_initial_data.py | cd9ce165d6eece5be8715f7fd500ce6e879c1ef5 | [] | no_license | crowdbotics-apps/cws-v2-24857 | d289f5011c0c122079399365b040ccde1731282c | 2bd623d18e207ddf7f048ca117eaf3f864edae7e | refs/heads/master | 2023-03-12T10:33:38.218689 | 2021-03-05T02:19:14 | 2021-03-05T02:19:14 | 344,669,015 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,278 | py | from django.db import migrations
def create_customtext(apps, schema_editor):
CustomText = apps.get_model("home", "CustomText")
customtext_title = "CWS v2"
CustomText.objects.create(title=customtext_title)
def create_homepage(apps, schema_editor):
HomePage = apps.get_model("home", "HomePage")
homepage_body = """
<h1 class="display-4 text-center">CWS v2</h1>
<p class="lead">
This is the sample application created and deployed from the Crowdbotics app.
You can view list of packages selected for this application below.
</p>"""
HomePage.objects.create(body=homepage_body)
def create_site(apps, schema_editor):
Site = apps.get_model("sites", "Site")
custom_domain = "cws-v2-24857.botics.co"
site_params = {
"name": "CWS v2",
}
if custom_domain:
site_params["domain"] = custom_domain
Site.objects.update_or_create(defaults=site_params, id=1)
class Migration(migrations.Migration):
dependencies = [
("home", "0001_initial"),
("sites", "0002_alter_domain_unique"),
]
operations = [
migrations.RunPython(create_customtext),
migrations.RunPython(create_homepage),
migrations.RunPython(create_site),
]
| [
"team@crowdbotics.com"
] | team@crowdbotics.com |
3298c87b6791939424088c9efb422d0f53e6f361 | cb3d5a3cebfb1cc06f563bc36001d5f100cac97a | /fb/parser.py | 18cb6d4cbc44d9b1eb4a10778b4ecf0c74e35fbc | [] | no_license | ax-sh/facebook-saved-saver | 8f6f3a3795a7f631710c93ea17e49cea920ff0aa | 34f453a9e9d7ecb26684b32093ed1d8652aa1817 | refs/heads/master | 2022-11-28T15:55:57.815165 | 2020-08-07T17:42:04 | 2020-08-07T17:42:04 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,822 | py | import re
from urllib import parse
import json
class ParseError(Exception):
pass
class TokensParseException(ParseError):
pass
def url(url):
parsed = parse.urlparse(url)
result = {'query_json': dict(parse.parse_qsl(parsed.query))}
result.update(parsed._asdict())
return result
def rx_json_var(key):
return re.compile(fr'{key}[\'"]\s*:\s*[\'"]([^"\']+)')
find_csrf_token = rx_json_var('(async_get_token|token)').findall
photos_count = re.compile(r'(\d+) Photos?').findall
def post_item_if_photos(text):
count = photos_count(text)
if count:
return int(count[0])
return 0
def extract_csrf(text):
raw = find_csrf_token(text)
return dict(raw)
def extract_csrf_from_html(html):
for i in html.find('script'):
text = i.text.strip()
if 'DTSGInitData' in text:
return extract_csrf(text)
def parse_error(data):
error = data.get('error', 'ERROR')
errorSummary = data.get('errorSummary', '')
errorDescription = data.get('errorDescription', '')
text = f'[{errorSummary}-{error}]=>{errorDescription}'.upper()
return text
def parse_saved_json_response_html(data):
domops = data.get('domops', {})
if not domops:
error = parse_error(data)
raise ParseError(error)
try:
html = domops[0][3]['__html']
except Exception:
raise ParseError(domops)
return html
def remove_params(url, params=('fbclid', 'eid', 'ref')):
url = parse_link(url)
u = parse.urlparse(url)
q = dict(parse.parse_qsl(u.query))
for i in params:
q.pop(i, '')
q = parse.urlencode(q)
return u._replace(query=q).geturl()
def parse_link(link):
_url = url(link)
if _url['netloc'] == 'l.facebook.com':
link = _url['query_json']['u']
return link
| [
"ahwn@pm.me"
] | ahwn@pm.me |
a05fd4236ca57745dbcdd8597f5735fa61ad3ca4 | 863a6e23a71bbddccd73b0891cd5e4f85a51c29f | /cesar_env/bin/python-config | 1d6b23686401646f119adabbe21ba6e285a47602 | [] | no_license | neonua/ceaser | e3b2d6e2f484b5b05a3aaa62e97151e9ed663194 | 0ad25bdb1ad16abeee7a54591b9d22162cb5a4e5 | refs/heads/master | 2021-01-11T23:16:17.670349 | 2017-01-11T08:50:11 | 2017-01-11T08:50:11 | 78,562,060 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,347 | #!/Users/igor/new_prj/cesar_env/bin/python
import sys
import getopt
import sysconfig
valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags',
'ldflags', 'help']
if sys.version_info >= (3, 2):
valid_opts.insert(-1, 'extension-suffix')
valid_opts.append('abiflags')
if sys.version_info >= (3, 3):
valid_opts.append('configdir')
def exit_with_usage(code=1):
sys.stderr.write("Usage: {0} [{1}]\n".format(
sys.argv[0], '|'.join('--'+opt for opt in valid_opts)))
sys.exit(code)
try:
opts, args = getopt.getopt(sys.argv[1:], '', valid_opts)
except getopt.error:
exit_with_usage()
if not opts:
exit_with_usage()
pyver = sysconfig.get_config_var('VERSION')
getvar = sysconfig.get_config_var
opt_flags = [flag for (flag, val) in opts]
if '--help' in opt_flags:
exit_with_usage(code=0)
for opt in opt_flags:
if opt == '--prefix':
print(sysconfig.get_config_var('prefix'))
elif opt == '--exec-prefix':
print(sysconfig.get_config_var('exec_prefix'))
elif opt in ('--includes', '--cflags'):
flags = ['-I' + sysconfig.get_path('include'),
'-I' + sysconfig.get_path('platinclude')]
if opt == '--cflags':
flags.extend(getvar('CFLAGS').split())
print(' '.join(flags))
elif opt in ('--libs', '--ldflags'):
abiflags = getattr(sys, 'abiflags', '')
libs = ['-lpython' + pyver + abiflags]
libs += getvar('LIBS').split()
libs += getvar('SYSLIBS').split()
# add the prefix/lib/pythonX.Y/config dir, but only if there is no
# shared library in prefix/lib/.
if opt == '--ldflags':
if not getvar('Py_ENABLE_SHARED'):
libs.insert(0, '-L' + getvar('LIBPL'))
if not getvar('PYTHONFRAMEWORK'):
libs.extend(getvar('LINKFORSHARED').split())
print(' '.join(libs))
elif opt == '--extension-suffix':
ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
if ext_suffix is None:
ext_suffix = sysconfig.get_config_var('SO')
print(ext_suffix)
elif opt == '--abiflags':
if not getattr(sys, 'abiflags', None):
exit_with_usage()
print(sys.abiflags)
elif opt == '--configdir':
print(sysconfig.get_config_var('LIBPL'))
| [
"neonua666@gmail.com"
] | neonua666@gmail.com | |
31f19286a7a027e1aa34217ed97ef9790a1d3f06 | 2d9762e34f80c169daa9b2f724cab3a83f90d5fb | /dao/Topic_QuestionDao.py | bdcebed9dc8ce957e79e35ad2cb25288412c17ba | [] | no_license | skomefen/ZhihuSpider | 11ae293a294e4d2f18c4d58e602ffa087f96c3c5 | 735a32bcdee784a3c303befae35e23e7ed5aab25 | refs/heads/master | 2021-08-24T09:38:32.422571 | 2017-12-09T02:48:11 | 2017-12-09T02:48:11 | 108,355,021 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,659 | py | import logging
from dao.ConnManager import ConnManager
class Topic_QuestionDao:
def __init__(self):
logger = logging.getLogger(__name__)
conn = ConnManager().get_conn()
# 表不存在就创建表
tableIsOK = False
try:
if not tableIsOK:
sql = 'create table topic_question (topic_id text not null,question_id text not null,primary key (topic_id,question_id))'
c = conn.cursor()
c.execute(sql)
tableIsOK = True
except Exception as e:
logger.debug("topic_question表已存在")
#print('表已存在')
finally:
ConnManager().conn_commit()
def save_topic_question(self, topic_question):
logger = logging.getLogger(__name__)
conn = ConnManager().get_conn()
c = conn.cursor()
try:
sql = 'select * from topic_question where topic_id = ? and question_id = ?'
u = (topic_question['topic_id'], topic_question['question_id'])
c.execute(sql, u)
date = None
for row in c:
date = row
if not date:
sql = 'insert into topic_question (topic_id, question_id) values (?,?)'
c.execute(sql, u)
except Exception as e:
logger.debug('保存失败,或者该数据已存在，错误:%s',e)
#print('保存失败,或者该数据已存在，错误:' + e)
finally:
# conn.commit()
ConnManager().conn_commit()
| [
"1072760797@qq.com"
] | 1072760797@qq.com |
6bfd98d0acb97cfadfc17f5ebe4ecf36c7af746b | 4ea92cda40dce3acec7016aaf65488a5c5286b36 | /src/crumblebundle/input/windows_keycodes.py | 10e46ca9876170d11ccb4cd7fc2231a94097efaa | [
"MIT"
] | permissive | Peilonrayz/crumblebundle | 694137315617201a9797a7bc1f249121981c2bd9 | cffb3b0b16e9bc6497e9ba43f9c7cc3fd008c3ee | refs/heads/master | 2021-01-09T13:34:25.026340 | 2020-02-21T20:09:50 | 2020-02-21T20:09:50 | 242,320,620 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,565 | py | # Table headers
# [name, ext, ext-shift, ext-ctrl, ext-alt]
# [name, dec, char, dec, char, dec char, dec char]
_keycodes = [
["ESC", 1, 27, None, 27, None, 27, None, 1, 0],
["1!", 2, 49, "1", 33, "!", None, None, 120, 0],
["2@", 3, 50, "2", 64, "@", 3, 0, 121, 0],
["3#", 4, 51, "3", 35, "#", None, None, 122, 0],
["4$", 5, 52, "4", 36, "$", None, None, 123, 0],
["5%", 6, 53, "5", 37, "%", None, None, 124, 0],
["6^", 7, 54, "6", 94, "^", 30, "\x1e", 125, 0],
["7&", 8, 55, "7", 38, "&", None, None, 126, 0],
["8*", 9, 56, "8", 42, "*", None, None, 127, 0],
["9(", 10, 57, "9", 40, "(", None, None, 128, 0],
["0)", 11, 48, "0", 41, ")", None, None, 129, 0],
["-_", 12, 45, "-", 95, "_", 31, "\x1f", 130, 0],
["=+", 13, 61, "=", 43, "+", None, None, 131, 0],
["BKSP", 14, 8, None, 8, None, 127, None, 14, 0],
["TAB", 15, 9, None, 15, 0, 148, 0, 15, 0],
["Q", 16, 113, "q", 81, "Q", 17, "\x11", 16, 0],
["W", 17, 119, "w", 87, "W", 23, "\x17", 17, 0],
["E", 18, 101, "e", 69, "E", 5, "\x05", 18, 0],
["R", 19, 114, "r", 82, "R", 18, "\x12", 19, 0],
["T", 20, 116, "t", 84, "T", 20, "SO", 20, 0],
["Y", 21, 121, "y", 89, "Y", 25, "\x19", 21, 0],
["U", 22, 117, "u", 85, "U", 21, "\x15", 22, 0],
["I", 23, 105, "i", 73, "I", 9, "\t", 23, 0],
["O", 24, 111, "o", 79, "O", 15, "\x0f", 24, 0],
["P", 25, 112, "p", 80, "P", 16, "\x10", 25, 0],
["[{", 26, 91, "[", 123, "{", 27, "\x1b", 26, 0],
["]}", 27, 93, "]", 125, "}", 29, "\x1d", 27, 0],
["ENTER", 28, 13, "\r", 13, "\r", 10, "\x0a", 28, 0],
["ENTER£", 28, 13, "\r", 13, "\r", 10, "\x0a", 166, 0],
["LCTRL", 29, None, None, None, None, None, None, None, None],
["RCTRL£", 29, None, None, None, None, None, None, None, None],
["A", 30, 97, "a", 65, "A", 1, "\x01", 30, 0],
["S", 31, 115, "s", 83, "S", 19, "\x13", 31, 0],
["D", 32, 100, "d", 68, "D", 4, "\x04", 32, 0],
["F", 33, 102, "f", 70, "F", 6, "\x06", 33, 0],
["G", 34, 103, "g", 71, "G", 7, "\a", 34, 0],
["H", 35, 104, "h", 72, "H", 8, "\b", 35, 0],
["J", 36, 106, "j", 74, "J", 10, "\x0a", 36, 0],
["K", 37, 107, "k", 75, "K", 11, "\v", 37, 0],
["L", 38, 108, "l", 76, "L", 12, "\f", 38, 0],
[";:", 39, 59, ";", 58, ":", None, None, 39, 0],
["'\"", 40, 39, "'", 34, '"', None, None, 40, 0],
["`~", 41, 96, "`", 126, "~", None, None, 41, 0],
["L SHIFT", 42, None, None, None, None, None, None, None, None],
["\\|", 43, 92, "\\", 124, "|", 28, "\x1c", None, None],
["Z", 44, 122, "z", 90, "Z", 26, "\x1a", 44, 0],
["X", 45, 120, "x", 88, "X", 24, "\x18", 45, 0],
["C", 46, 99, "c", 67, "C", 3, "\x03", 46, 0],
["V", 47, 118, "v", 86, "V", 22, "\x16", 47, 0],
["B", 48, 98, "b", 66, "B", 2, "\x02", 48, 0],
["N", 49, 110, "n", 78, "N", 14, "\x0e", 49, 0],
["M", 50, 109, "m", 77, "M", 13, "\x0d", 50, 0],
[",<", 51, 44, ",", 60, "<", None, None, 51, 0],
[".>", 52, 46, ".", 62, ">", None, None, 52, 0],
["/?", 53, 47, "/", 63, "?", None, None, 53, 0],
["GRAY/£", 53, 47, "/", 63, "?", 149, 0, 164, 0],
["R SHIFT", 54, None, None, None, None, None, None, None, None],
["PRISC", 55, 42, "*", "PRISC", "✝✝", 16, None, None, None],
["L ALT", 56, None, None, None, None, None, None, None, None],
["R ALT£", 57, None, None, None, None, None, None, None, None],
["SPACE", 57, 32, " ", 32, " ", 32, " ", 32, " "],
["CAPS", 58, None, None, None, None, None, None, None, None],
["F1", 59, 59, 0, 84, 0, 94, 0, 104, 0],
["F2", 60, 60, 0, 85, 0, 95, 0, 105, 0],
["F3", 61, 61, 0, 86, 0, 96, 0, 106, 0],
["F4", 62, 62, 0, 87, 0, 97, 0, 107, 0],
["F5", 63, 63, 0, 88, 0, 98, 0, 108, 0],
["F6", 64, 64, 0, 89, 0, 99, 0, 109, 0],
["F7", 65, 65, 0, 90, 0, 100, 0, 110, 0],
["F8", 66, 66, 0, 91, 0, 101, 0, 111, 0],
["F9", 67, 67, 0, 92, 0, 102, 0, 112, 0],
["F10", 68, 68, 0, 93, 0, 103, 0, 113, 0],
["F11£", 87, 133, 0xE0, 135, 0xE0, 137, 0xE0, 139, 0xE0],
["F12£", 88, 134, 0xE0, 136, 0xE0, 138, 0xE0, 140, 0xE0],
["NUM", 69, None, None, None, None, None, None, None, None],
["HOME", 71, 71, 0, 55, "7", 119, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["HOME£", 71, 71, 0xE0, 71, 0xE0, 119, 0xE0, 151, 0],
["UP", 72, 72, 0, 56, "8", 141, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["UP£", 72, 72, 0xE0, 72, 0xE0, 141, 0xE0, 152, 0],
["PGUP", 73, 73, 0, 57, "9", 132, 0, 153, 0],
[None, None, None, None, None, None, None, None, None, None],
["PGUP£", 73, 73, 0xE0, 73, 0xE0, 132, 0xE0, 153, 0],
["GRAY-", 74, None, None, 45, "-", None, None, None, None],
["LEFT", 75, 75, 0, 52, "4", 115, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["LEFT£", 75, 75, 0xE0, 75, 0xE0, 115, 0xE0, 155, 0],
["CENTER", 76, None, None, 53, "5", None, None, None, None],
[None, None, None, None, None, None, None, None, None, None],
["RIGHT", 77, 77, 0, 54, "6", 116, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["RIGHT£", 77, 77, 0xE0, 77, 0xE0, 116, 0xE0, 157, 0],
["GRAY+", 78, None, None, 43, "+", None, None, None, None],
["END", 79, 79, 0, 49, "1", 117, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["END£", 79, 79, 0xE0, 79, 0xE0, 117, 0xE0, 159, 0],
["DOWN", 80, 80, 0, 50, "2", 145, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["DOWN£", 80, 80, 0xE0, 80, 0xE0, 145, 0xE0, 160, 0],
["PGDN", 81, 81, 0, 51, "3", 118, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["PGDN£", 81, 81, 0xE0, 81, 0xE0, 118, 0xE0, 161, 0],
["INS", 82, 82, 0, 48, "0", 146, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["INS£", 82, 82, 0xE0, 82, 0xE0, 146, 0xE0, 162, 0],
["DEL", 83, 83, 0, 46, ".", 147, 0, None, None],
[None, None, None, None, None, None, None, None, None, None],
["DEL£", 83, 83, 0xE0, 83, 0xE0, 147, 0xE0, 163, 0],
]
keycodes = [
["ESC", 1, 27, None, 27, None, None, None, None, None],
["1!", 2, 49, "1", 33, "!", None, None, 49, None],
["2@", 3, 50, "2", 64, "@", 3, 0, 50, None],
["3#", 4, 51, "3", 35, "#", None, None, 51, None],
["4$", 5, 52, "4", 36, "$", None, None, 52, None],
["5%", 6, 53, "5", 37, "%", None, None, 53, None],
["6^", 7, 54, "6", 94, "^", None, None, 54, None],
["7&", 8, 55, "7", 38, "&", None, None, 55, None],
["8*", 9, 56, "8", 42, "*", None, None, 56, None],
["9(", 10, 57, "9", 40, "(", None, None, 57, None],
["0)", 11, 48, "0", 41, ")", None, None, 48, None],
["-_", 12, 45, "-", 95, "_", None, None, 45, None],
["=+", 13, 61, "=", 43, "+", None, None, 61, None],
["BKSP", 14, 8, None, 8, None, 127, None, 8, None],
["TAB", 15, 9, None, 9, None, 148, 0, None, None],
["Q", 16, 113, "q", 81, "Q", 17, "\x11", 113, None],
["W", 17, 119, "w", 87, "W", 23, "\x17", 119, None],
["E", 18, 101, "e", 69, "E", 5, "\x05", 101, None],
["R", 19, 114, "r", 82, "R", 18, "\x12", 114, None],
["T", 20, 116, "t", 84, "T", 20, "SO", 116, None],
["Y", 21, 121, "y", 89, "Y", 25, "\x19", 121, None],
["U", 22, 117, "u", 85, "U", 21, "\x15", 117, None],
["I", 23, 105, "i", 73, "I", 9, "\t", 105, None],
["O", 24, 111, "o", 79, "O", 15, "\x0f", 111, None],
["P", 25, 112, "p", 80, "P", 16, "\x10", 112, None],
["[{", 26, 91, "[", 123, "{", 27, "\x1b", 91, None],
["]}", 27, 93, "]", 125, "}", 29, "\x1d", 93, None],
["ENTER", 28, 13, "\r", 13, "\r", 10, "\x0a", None, None],
["ENTER£", 28, 13, "\r", 13, "\r", 10, "\x0a", None, None],
["LCTRL", 29, None, None, None, None, None, None, None, None],
["RCTRL£", 29, None, None, None, None, None, None, None, None],
["A", 30, 97, "a", 65, "A", 1, "\x01", 97, None],
["S", 31, 115, "s", 83, "S", 19, "\x13", 115, None],
["D", 32, 100, "d", 68, "D", 4, "\x04", 100, None],
["F", 33, 102, "f", 70, "F", 6, "\x06", 102, None],
["G", 34, 103, "g", 71, "G", 7, "\a", 103, None],
["H", 35, 104, "h", 72, "H", 8, "\b", 104, None],
["J", 36, 106, "j", 74, "J", 10, "\x0a", 106, None],
["K", 37, 107, "k", 75, "K", 11, "\v", 107, None],
["L", 38, 108, "l", 76, "L", 12, "\f", 108, None],
[";:", 39, 59, ";", 58, ":", None, None, 59, None],
["'\"", 40, 39, "'", 34, '"', None, None, 39, None],
["`~", 41, 96, "`", 126, "~", None, None, 96, None],
["L SHIFT", 42, None, None, None, None, None, None, None, None],
["\\|", 43, 92, "\\", 124, "|", 28, "\x1c", 92, None],
["Z", 44, 122, "z", 90, "Z", 26, "\x1a", 122, None],
["X", 45, 120, "x", 88, "X", 24, "\x18", 120, None],
["C", 46, 99, "c", 67, "C", 3, "\x03", 99, None],
["V", 47, 118, "v", 86, "V", 22, "\x16", 118, None],
["B", 48, 98, "b", 66, "B", 2, "\x02", 98, None],
["N", 49, 110, "n", 78, "N", 14, "\x0e", 110, None],
["M", 50, 109, "m", 77, "M", 13, "\x0d", 109, None], # Ctrl-m -> \r
[",<", 51, 44, ",", 60, "<", None, None, 44, None],
[".>", 52, 46, ".", 62, ">", None, None, 46, None],
["/?", 53, 47, "/", 63, "?", None, None, 47, None],
["GRAY/£", 53, 47, "/", 63, "?", 149, 0, 164, 0],
["R SHIFT", 54, None, None, None, None, None, None, None, None],
["PRISC", 55, 42, "*", "PRISC", "✝✝", 16, None, None, None],
["L ALT", 56, None, None, None, None, None, None, None, None],
["R ALT£", 57, None, None, None, None, None, None, None, None],
["SPACE", 57, 32, " ", 32, " ", 32, " ", None, None],
["CAPS", 58, None, None, None, None, None, None, None, None],
["F1", 59, 59, 0, 84, 0, 94, 0, 104, 0],
["F2", 60, 60, 0, 85, 0, 95, 0, 105, 0],
["F3", 61, 61, 0, 86, 0, 96, 0, 106, 0],
["F4", 62, 62, 0, 87, 0, 97, 0, 107, 0],
["F5", 63, 63, 0, 88, 0, 98, 0, 108, 0],
["F6", 64, 64, 0, 89, 0, 99, 0, 109, 0],
["F7", 65, 65, 0, 90, 0, 100, 0, 110, 0],
["F8", 66, 66, 0, 91, 0, 101, 0, 111, 0],
["F9", 67, 67, 0, 92, 0, 102, 0, 112, 0],
["F10", 68, 68, 0, 93, 0, 103, 0, 113, 0],
["F11£", 87, 133, 0xE0, 135, 0xE0, 137, 0xE0, 139, 0xE0],
["F12£", 88, 134, 0xE0, 136, 0xE0, 138, 0xE0, 140, 0xE0],
["NUM", 69, None, None, None, None, None, None, None, None],
["HOME", 71, 71, 0, None, None, 119, 0, None, None],
[None, None, 55, "7", 71, 0, 119, 0, None, None],
["HOME£", 71, 71, 0xE0, 71, 0xE0, 119, 0xE0, 151, 0],
["UP", 72, 72, 0, None, None, 141, 0, None, None],
[None, None, 56, "8", 72, 0, 141, 0, None, None],
["UP£", 72, 72, 0xE0, 72, 0xE0, 141, 0xE0, 152, 0],
["PGUP", 73, 73, 0, None, None, 132, 0, None, None],
[None, None, 57, "9", 73, 0, 132, 0, None, None],
["PGUP£", 73, 73, 0xE0, 73, 0xE0, 134, 0xE0, 153, 0],
["GRAY-", 74, None, None, 45, "-", None, None, None, None],
["LEFT", 75, 75, 0, None, None, 115, 0, None, None],
[None, None, 52, "4", 75, 0, 115, 0, None, None],
["LEFT£", 75, 75, 0xE0, 75, 0xE0, 115, 0xE0, 155, 0],
["CENTER", 76, None, None, None, None, None, None, None, None],
[None, None, 53, "5", None, None, None, None, None, None],
["RIGHT", 77, 77, 0, None, None, 116, 0, None, None],
[None, None, 54, "6", 77, 0, 116, 0, None, None],
["RIGHT£", 77, 77, 0xE0, 77, 0xE0, 116, 0xE0, 157, 0],
["GRAY+", 78, None, None, 43, "+", None, None, None, None],
["END", 79, 79, 0, None, None, 117, 0, None, None],
[None, None, 49, "1", 79, 0, 117, 0, None, None],
["END£", 79, 79, 0xE0, 79, 0xE0, 117, 0xE0, 159, 0],
["DOWN", 80, 80, 0, None, None, 145, 0, None, None],
[None, None, 50, "2", 80, 0, 145, 0, None, None],
["DOWN£", 80, 80, 0xE0, 80, 0xE0, 145, 0xE0, 160, 0],
["PGDN", 81, 81, 0, None, None, 118, 0, None, None],
[None, None, 51, "3", 81, 0, 118, 0, None, None],
["PGDN£", 81, 81, 0xE0, 81, 0xE0, 118, 0xE0, 161, 0],
["INS", 82, 82, 0, None, None, 146, 0, None, None],
[None, None, 48, "0", 82, 0, 146, 0, None, None],
["INS£", 82, 82, 0xE0, 82, 0xE0, 146, 0xE0, 162, 0],
["DEL", 83, 83, 0, None, None, 147, 0, None, None],
[None, None, 46, ".", 83, 0, 147, 0, None, None],
["DEL£", 83, 83, 0xE0, 83, 0xE0, 147, 0xE0, 163, 0],
]
noms = "base shift ctrl alt".split()
if __name__ == "__main__":
import textwrap
text = r"\text{{{}}}".format
error = r"\color{{red}}{{{}}}".format
gray = r"\color{{gray}}{{{}}}".format
green = r"\color{{green}}{{{}}}".format
to = r"{} \to {}".format
def repr_text(value):
return text(
repr(value)[1:-1]
.replace("{", r"\{")
.replace("}", r"\}")
.replace("$", r"\$")
.replace(r"\'", "'")
)
def error_text(value):
return error(repr_text(value))
class Wrapper:
def __init__(self, new, old):
self.new = new
self.old = old
def __str__(self):
if isinstance(self.new, int) or isinstance(self.old, int):
if self.new == self.old:
return gray(text(self.old))
else:
return to(error_text(self.old), green(text(self.new)))
elif self.new == self.old:
if self.new is None:
return ""
else:
return repr_text(self.old)
elif self.new is None:
return error_text(self.old)
elif self.old is None:
return green(repr_text(self.new))
else:
return to(error_text(self.old), green(repr_text(self.new)))
def read_table(table):
for name, scan, *groups in table:
codes = []
for code, other in zip(*[iter(groups)] * 2):
if code is None:
if other is None:
codes.append(None)
else:
print("code: None other: ??? - {}".format(other))
codes.append(str(other))
elif isinstance(code, str):
print("code: str - {} {}".format(code, other))
codes.append(
"".join([str(i) for i in (other, code) if i is not None])
)
elif other is None or isinstance(other, str):
codes.append(chr(code))
else:
codes.append("".join(chr(i) for i in (other, code)))
yield (name, scan, *codes)
def read_tables(n, o):
for n_values, o_values in zip(read_table(n), read_table(o)):
yield [
Wrapper(n_value, o_value)
for n_value, o_value in zip(n_values, o_values)
]
fmt = r"""
$$
\begin{{array}}{{l|r|l|l|l|l}}
\textrm{{Name}} &
\textrm{{Scan Code}} &
\textrm{{Base}} &
\textrm{{Shift}} &
\textrm{{Ctrl}} &
\textrm{{Alt}} \\
\hline
{}\\
\end{{array}}
$$
"""
def format_(rows):
values = "\\\\\n".join("&".join(map(str, row)) for row in rows)
return textwrap.indent(fmt.format(textwrap.indent(values, " ")), " " * 4)
def chunks(l, n):
l = list(l)
for i in range(0, len(l), n):
yield l[i : i + n]
for chunk in chunks(read_tables(keycodes, _keycodes), 40):
print(format_(chunk))
| [
"peilonrayz@gmail.com"
] | peilonrayz@gmail.com |
df37a819293392094e379a0bab9ba5496f5eac55 | a96f8bac6128c04a8df342c93767387a497baac4 | /__init__.py | 270588e7f5d006e36163f42b0b07b2d5540b9db7 | [
"MIT"
] | permissive | unhideschool/uhql | 0587ba601885087f0f81b4988fe67c4f3da72ff9 | b2194388ee73d7bb4d08ef73ced44c73ab598e6a | refs/heads/master | 2020-09-26T01:35:39.923209 | 2019-12-09T15:09:22 | 2019-12-09T15:09:22 | 226,133,093 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 23 | py | from .main import UHQL
| [
"cadu.coelho@gmail.com"
] | cadu.coelho@gmail.com |
bcae55b9da79fb75de68d0bdce8f367853beb588 | 5439206885b4161a50491affa08b1983e5adb7ed | /scope_test.py | 473c94095fe00ce95eabb4fbf38b135bc9bd9f89 | [] | no_license | adamwatts112358/horn_fieldmap | 50ec364c99e7f2eafff69ca4f6ca34df00a59209 | e33cc001535966014a2000b189aee4d04c04d4f7 | refs/heads/master | 2022-12-16T09:03:31.966938 | 2020-08-25T23:52:31 | 2020-08-25T23:52:31 | 259,395,331 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,246 | py | from scope_communication import *
import numpy as np
from os import system
import Adafruit_BBIO.GPIO as GPIO
# Define and setup the horn trigger pin
trigger = 'P8_7'
GPIO.setup(trigger, GPIO.IN)
stripline_scope_IP = '192.168.1.2'
stripline_scope_type = 'Agilent'
# Setup BBB ethernet connection
print 'Setting up BeagleBone ethernet connection.'
system('sudo ifconfig eth0 192.168.1.1 netmask 255.255.248.0')
# Setup stripline scope
print 'Initializing stripline scope.'
stripline_scope = initialize(stripline_scope_type, stripline_scope_IP)
# Define the number of data points to take
npoints = 5
point = 1
time_data = []
voltage_data = []
while point != (npoints+1):
# Wait for a horn trigger
GPIO.wait_for_edge(trigger, GPIO.RISING)
# Download the scope data (does this need a delay?)
time, voltage = acquire(stripline_scope_type, stripline_scope, 1)
print 'Data point %i acquired.'%(point)
time_data.append(time)
voltage_data.append(voltage)
# Increment the point count
point = point + 1
print 'Data acquisition complete'
# Print out data to check it
for n in range(len(time_data)):
for i in range(len(time)):
print '%i \t %f \t %f'%(n+1, time_data[n][i], voltage_data[n][i])
| [
"39932368+adamwatts112358@users.noreply.github.com"
] | 39932368+adamwatts112358@users.noreply.github.com |
d7d0149d97c5d90e7a108933c72213f71f493c05 | 3e84ee44588ee906cf782a1719b96355987e2f45 | /IMBD/Actors.py | f519b15a03d404ba842f447d147f40cf126aacfc | [
"MIT"
] | permissive | himansh-nagar/web_scraping | b66e1854d4c3d0046fb9c759cb56e1d8f6d3d33b | f63b7c879c70b88429d33b949784e1dcb2908f5b | refs/heads/master | 2022-09-03T00:03:33.219753 | 2020-05-29T10:44:59 | 2020-05-29T10:44:59 | 255,666,008 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 788 | py | import json,pprint
file=open('all_movie_cast.json','r')
File=json.load(file)
file.close()
all_movie_cast=[]
all_movie_cast2=[]
for dic_list in File:
one_cast_list=[]
for dic in dic_list:
cast_list=dic_list[dic]
for j in range(2):
one_cast_list.append(cast_list[j])
all_movie_cast.append(one_cast_list)
for dic_list_2 in File:
for dic2 in dic_list_2:
all_movie_cast2.append(dic_list_2[dic2])
num_list=[]
for i in all_movie_cast:
num_dic={}
num=0
inde=0
inde2=1
first_ele=i[inde]
sec_ele=i[inde2]
for dic_list in File:
for dic in dic_list:
if first_ele in dic_list[dic] and sec_ele in dic_list[dic]:
num+=1
first_ele2=str(first_ele)
sec_ele2=str(str(sec_ele)+" "+str(num))
num_dic[first_ele2]=sec_ele2
num_list.append(num_dic)
pprint.pprint(num_list)
| [
"noreply@github.com"
] | noreply@github.com |
4762de0549dd0e5a2c55d037f49bed37dd3c8877 | 5e2fd1d42423cb1de218ce2b07696c98c14adb09 | /extest/migrations/0002_auto_20200711_2145.py | 89a65cda1206afbf0a35558e54fd058cfa3b9bae | [] | no_license | Yaanibaano/Todo-Web-App | ea72ac08703d9ce227e1c1de73a704ddbda48bcf | 5fe929f9b3bcf57140bf8d5514f4525870d40a0d | refs/heads/master | 2022-12-22T09:28:37.120036 | 2020-09-23T09:48:04 | 2020-09-23T09:48:04 | 297,924,635 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 315 | py | # Generated by Django 3.0 on 2020-07-11 16:15
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('extest', '0001_initial'),
]
operations = [
migrations.RenameModel(
old_name='Element',
new_name='Task',
),
]
| [
"chandru.vijayan101999@gmail.com"
] | chandru.vijayan101999@gmail.com |
5c45e9998b505e3bdd5403e41fd8ec79d4127387 | f43418339d85ab07ec369fd8f14df6f0b1d4bcd8 | /ch3/barrier/python/barrier.py | 86ed375668e3f0bb72ae10219c42461b09699ee9 | [] | no_license | frankieliu/little-book-semaphores | 732fbb1787d826666e750c4e8c8897877631921c | 9017ddceeab30090af983100729649f0f29c7c99 | refs/heads/master | 2021-07-14T03:40:05.503689 | 2020-08-15T13:55:19 | 2020-08-15T13:55:19 | 195,286,896 | 1 | 4 | null | null | null | null | UTF-8 | Python | false | false | 967 | py | from threading import Thread, Semaphore
import time
from random import randint
class Person(Thread):
def __init__(self,i,m,s,count,numthreads):
self.s = s
self.m = m
self.count = count
self.count.i = 0
self.numthreads = numthreads
super().__init__(name=i)
def run(self):
time.sleep(1e-3*randint(1,10))
print(f"{self.name} rendez")
# barrier
self.m.acquire()
self.count.i += 1
if self.count.i == self.numthreads:
self.s.release()
self.m.release()
self.s.acquire()
self.s.release()
print(f"{self.name} critical section")
class Count():
pass
def main():
nthreads = 10
m = Semaphore(1)
s = Semaphore(0)
count = Count()
thr = []
for i in range(nthreads):
thr.append(Person(i+1, m, s, count, nthreads))
for t in thr:
t.start()
for t in thr:
t.join()
main()
| [
"frankie.y.liu@gmail.com"
] | frankie.y.liu@gmail.com |
a9874ad67c55edcf3fa4110df2021f892397f8be | cc1118a5033fb13b68473fb6e7dc1fcbcbd955e1 | /models/encoder.py | 1ec642809f0b3d87deab3dbdeed022f0bbca7caf | [] | no_license | Tony-Xiang-Cao/3D-Reconstruction-Pix2Vox-LSTM | d961729510ea554a5e9b67343ea0c935144c268b | 05cf1a76224217cb5b2a5a1b2c9b776aa143360a | refs/heads/main | 2023-04-01T16:15:07.396181 | 2021-04-18T04:02:58 | 2021-04-18T04:02:58 | 358,793,458 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,348 | py | # -*- coding: utf-8 -*-
#
#
# References:
# - https://github.com/shawnxu1318/MVCNN-Multi-View-Convolutional-Neural-Networks/blob/master/mvcnn.py
import torch
import torchvision.models
class Encoder(torch.nn.Module):
def __init__(self, cfg):
super(Encoder, self).__init__()
self.cfg = cfg
# Layer Definition
vgg16_bn = torchvision.models.vgg16_bn(pretrained=True)
self.vgg = torch.nn.Sequential(*list(vgg16_bn.features.children()))[:27]
self.layer1 = torch.nn.Sequential(
torch.nn.Conv2d(512, 512, kernel_size=3),
torch.nn.BatchNorm2d(512),
torch.nn.ELU(),
)
self.layer2 = torch.nn.Sequential(
torch.nn.Conv2d(512, 512, kernel_size=3),
torch.nn.BatchNorm2d(512),
torch.nn.ELU(),
torch.nn.MaxPool2d(kernel_size=3)
)
self.layer3 = torch.nn.Sequential(
torch.nn.Conv2d(512, 256, kernel_size=1),
torch.nn.BatchNorm2d(256),
torch.nn.ELU()
)
# Don't update params in VGG16
for param in vgg16_bn.parameters():
param.requires_grad = False
def forward(self, rendering_images):
# print(rendering_images.size()) # torch.Size([batch_size, n_views, img_c, img_h, img_w])
rendering_images = rendering_images.permute(1, 0, 2, 3, 4).contiguous()
rendering_images = torch.split(rendering_images, 1, dim=0)
image_features = []
for img in rendering_images:
features = self.vgg(img.squeeze(dim=0))
# print(features.size()) # torch.Size([batch_size, 512, 28, 28])
features = self.layer1(features)
# print(features.size()) # torch.Size([batch_size, 512, 26, 26])
features = self.layer2(features)
# print(features.size()) # torch.Size([batch_size, 512, 24, 24])
features = self.layer3(features)
# print(features.size()) # torch.Size([batch_size, 256, 8, 8])
image_features.append(features)
image_features = torch.stack(image_features).permute(1, 0, 2, 3, 4).contiguous()
# print(image_features.size()) # torch.Size([batch_size, n_views, 256, 8, 8])
return image_features
| [
"noreply@github.com"
] | noreply@github.com |
532c1fbc727c31ff6486882eee4a7280a77783c2 | bb0efa84c5e3fdbb406a5cbbdcacabcdaf041a68 | /venv/bin/easy_install-2.7 | f6822712f8fb3243675c82786863af5ac8515e4d | [] | no_license | luzhaohong/Pyramide_myproject | ce85a22ec4c5fea34f6a5c8360f3e29a10ba0b3f | 30b51981dfdeb9c3c53734579bf2274a4b010c18 | refs/heads/master | 2020-04-01T00:34:32.515469 | 2018-10-12T06:42:09 | 2018-10-12T06:42:09 | 152,702,914 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 279 | 7 | #!/home/luzhaohong/PycharmProjects/myproject/venv/bin/python2.7
# -*- coding: utf-8 -*-
import re
import sys
from setuptools.command.easy_install import main
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(main())
| [
"luzhaohong@yeah.net"
] | luzhaohong@yeah.net |
30e2605d76c1c5ced65e21beb0f039317794a686 | 15fbe75198cc2646f843de9a795c1b3cb1b9bf21 | /tools/optimization/candidate.py | e5b0c706f8353a729b047536ad353fa83b10c319 | [
"BSD-3-Clause"
] | permissive | jlcox119/HOPP | 8750b4a82bf97e8fc1d1794418f7c40650b22baf | e8faa5012cab8335c75f8d1e84270e3127ff64bb | refs/heads/master | 2023-06-18T15:09:55.119235 | 2021-05-17T17:06:37 | 2021-05-17T17:06:37 | 368,262,087 | 0 | 0 | BSD-3-Clause | 2021-07-19T16:16:41 | 2021-05-17T17:03:13 | PowerBuilder | UTF-8 | Python | false | false | 470 | py | import pprint
class Candidate:
"""
Simulation inputs to be optimized
"""
def __init__(
self
) -> None:
pass
def __repr__(self) -> str:
return pprint.pformat(vars(self))
def __str__(self) -> str:
return self.__repr__()
def __setitem__(self,
key: str,
value: object
) -> None:
self.__setattr__(key, value)
| [
"noreply@github.com"
] | noreply@github.com |
79b42026725b7e117b7171373a8e3a7e7a7b72d5 | 227f6d603ed405ec6f82928102de3d00cd24837c | /python/start_algs.py | 26d46349ec3a437fcaf9c827977e36e2a0109f01 | [] | no_license | Egorich42/algs | 946022389e13384a796918272fe088cb01e80862 | 65b02b7d818fc53ca3f90406e7a13ea444ad4b59 | refs/heads/master | 2020-07-30T02:14:02.106929 | 2019-09-21T20:53:23 | 2019-09-21T20:53:23 | 210,051,982 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,161 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
#бинарная
#быстрая
#Сортировка вставками / Insertion sort
#Сортировка выбором / Selection sort
#Сортировка слиянием / Merge sort
test_arr = [8,0, 16, -3, 889, 19, 19, 0, 11, 6,4,56]
def bubble_sort(arr):
for i in range(len(arr)-1):
# идет простая проходка по циклу.
for x in range(len(arr)-1-i):
"""
а вот здесь уже идет процесс смены.
каждый внутренний цикл проходится по всему списку.
и каждую проходку
ТОЛЬКО ПРОПИХИВАЕТ В КОНЕЦ БОЛЬШИЙ ЭЛЕМЕНТ.
И все!
ТОЛЬКО один элемент становится в конец.
И каждый раз тебе нужно в конце поставть элемент ПЕРЕд самым последним.
Бо в первую проходку в конце выдвинется самый толстый, за счет сравнения.
В следующую - чуть меньший и т.д.
"""
#print("Arr on big iteration",arr)
if arr[x] > arr[x+1]:
arr[x], arr[x+1] = arr[x+1], arr[x]
#print("####arr on inside iters", arr)
return arr
pass
#bubble_sort(test_arr)
def find_min(arr):
mini = None
for element in arr:
if not mini:
mini = element
if element < mini:
mini = element
return mini
pass
def insert_sort(arr):
#Важно помнить о большом и малм шаге. Внутренний цикл ВЕСЬ проходит на ОДНОМ большом шаге.
#Соответственно на одном БОЛШОМ шаге мы концентрируемся на сортировке вокруг ОДНОГО большого элемента
#И вот тут на каждом большом шаге мы берем один БОЛШОЙ элемент, и двигаем его в отсортированную зону.
#А потом сменяем БОЬШОЙ на следующий, который так же пропихиваем.
for position in range(1, len(arr)):
current_value = arr[position]
while position > 0 and current_value < arr[position - 1]:
arr[position] = arr[position-1]
position = position-1
arr[position] = current_value
return arr
pass
def insert_sort_2(arr):
sorted_arr = []
for i in range(len(arr)):
min_el = find_min(arr)
sorted_arr.append(arr.pop(arr.index(min_el)))
return sorted_arr
pass
def insert_sort_3(arr):
sorted_arr = []
for i in range(len(arr)):
min_el = find_min(arr)
sorted_arr.append(min_el)
arr.remove(min_el)
return sorted_arr
pass
def insert_sort_4(arr):
for position in range(1, len(arr)):
current_value = arr[position]
for x in range(0, position):
if current_value < arr[x]:
current_value, arr[x] = arr[x], current_value
arr[position] = current_value
return arr
pass
def selection_sort(arr):
for element in range(len(arr)):
current_value = element
print(current_value)
for inner_element in range(element+1, len(arr)):
if arr[inner_element] < arr[current_value]:
#print(arr[inner_element], arr[current_value])
current_value = inner_element
#print(arr)
arr[current_value], arr[element] = arr[element], arr[current_value]
print("Смена:", arr)
return arr
pass
def qsort1(list):
if list == []:
return []
else:
pivot = list[0]
lesser = qsort1([x for x in list[1:] if x < pivot])
greater = qsort1([x for x in list[1:] if x >= pivot])
return lesser + [pivot] + greater
def quick_sort(arr):
if arr == []:
return []
else:
start_el = arr[0]
middle = []
maxi = []
mini = []
for x in arr:
if x > start_el:
maxi += [x]
if x < start_el:
mini += [x]
if x == start_el:
middle.append(x)
return quick_sort(mini) + middle + quick_sort(maxi)
#print(qsort1(test_arr))
#print(quick_sort(test_arr))
#print(insert_sort(test_arr))
#print(insert_sort_4(test_arr))
#print(selection_sort(test_arr))
| [
"e.g.hutter@gmail.com"
] | e.g.hutter@gmail.com |
74a36c63655f9b9bee75b5c2fbfe2b5322ae3db4 | 9b1e600c3e1c521a82a782be6b26ec3634168843 | /CLRS/1 排序/堆排序.py | 25fcf4e01ca2821158a4b7cf9d3f99a7ecb4e52b | [] | no_license | lijingwei1995/Algorithm | b782732c4364c4eaa256ebec827b4241cb39ad45 | 5d8a228d75369e4d72e3d76608584e43e329d531 | refs/heads/master | 2021-01-03T18:47:42.165193 | 2020-02-28T09:57:16 | 2020-02-28T09:57:16 | 240,197,233 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,326 | py | # 最大堆的heapify
# 这是一个递归函数，他可以调整 任意左右子树以满足性质，但父节点未知的树
def MAX_HEAPIFY(A, heap_size, i):
# 下标i如果是父节点
left = 2 * i + 1
right = 2 * i + 2
# 找到最大节点
max = i
if left < heap_size and A[left] > A[i] : max = left # 将数字比较写在左边可以避免超限问题
if right < heap_size and A[right] > A[max]: max = right
# 如果最大不是i，则与最大的交换，并继续递归该分支
if max != i:
temp = A[i]
A[i] = A[max]
A[max] = temp
MAX_HEAPIFY(A, heap_size, max)
# 建堆
def BUILD_MAX_HEAP(A):
# 从最底下的一个父节点至顶，以此执行MAX_HEAPIFY
first_parent = int(len(A)/2) - 1
for i in range(first_parent, -1, -1):
MAX_HEAPIFY(A, len(A), i)
# 堆排序
# 我们可以将最大的数拿出，将最后一个数字重新放回堆，然后执行HEAPIFY
def HEAP_SORT(A):
# 先建堆
BUILD_MAX_HEAP(A)
# 依次执行交换、HEAPIFY
heap_size = len(A)
while heap_size > 0:
temp = A[0]
A[0] = A[heap_size-1]
A[heap_size-1] = temp
MAX_HEAPIFY(A, heap_size, 0)
heap_size -= 1
A = [16, 3, 10, 8, 1, 9, 14, 2, 4, 7]
HEAP_SORT(A)
A | [
"lijingwei@outlook.com"
] | lijingwei@outlook.com |
13564f1fa07291d92bd2edd1ade46fb1f410c888 | e84020108a7037d8d4867d95fada1b72cbcbcd25 | /django/nrega.libtech.info/src/nrega/migrations/0118_auto_20170621_1328.py | 219d29cf057534d7b88f61db611446f66075c53b | [] | no_license | rajesh241/libtech | 8384316051a2e8c2d4a925cd43216b855b82e4d9 | 0105e717357a3626106028adae9bf162a7f93fbf | refs/heads/master | 2022-12-10T03:09:00.048841 | 2020-06-14T09:39:04 | 2020-06-14T09:39:04 | 24,629,538 | 1 | 1 | null | 2022-12-08T02:26:11 | 2014-09-30T07:57:45 | Python | UTF-8 | Python | false | false | 3,064 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-06-21 07:58
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('nrega', '0117_auto_20170621_1123'),
]
operations = [
migrations.AlterField(
model_name='applicant',
name='panchayat',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Panchayat'),
),
migrations.AlterField(
model_name='block',
name='district',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.District'),
),
migrations.AlterField(
model_name='district',
name='state',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.State'),
),
migrations.AlterField(
model_name='fpsshop',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
migrations.AlterField(
model_name='fto',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
migrations.AlterField(
model_name='muster',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
migrations.AlterField(
model_name='muster',
name='panchayat',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='nrega.Panchayat'),
),
migrations.AlterField(
model_name='nicblockreport',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
migrations.AlterField(
model_name='panchayat',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
migrations.AlterField(
model_name='panchayatreport',
name='panchayat',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Panchayat'),
),
migrations.AlterField(
model_name='panchayatstat',
name='panchayat',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Panchayat'),
),
migrations.AlterField(
model_name='village',
name='panchayat',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='nrega.Panchayat'),
),
migrations.AlterField(
model_name='wagelist',
name='block',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='nrega.Block'),
),
]
| [
"togoli@gmail.com"
] | togoli@gmail.com |
75498a2f5f3b001a45ca4069131312af6328a494 | 7ad19e854135977ee5b789d7c9bdd39d67ec9ea4 | /members/amit/f0_experiments/model.py | 05a5e529b028aa62ab646eb7176aec7490be90a4 | [
"MIT"
] | permissive | Leofltt/rg_sound_generation | 1b4d522507bf06247247f3ef929c8d0b93015e61 | 8e79b4d9dce028def43284f80521a2ec61d0066c | refs/heads/main | 2023-05-02T19:53:23.645982 | 2021-05-22T16:09:54 | 2021-05-22T16:09:54 | 369,842,561 | 0 | 0 | MIT | 2021-05-22T15:27:28 | 2021-05-22T15:27:27 | null | UTF-8 | Python | false | false | 1,197 | py | import tensorflow as tf
from tensorflow.keras.layers import Input, concatenate, RepeatVector
from tensorflow.keras.layers import Dense, GRU, Dropout
def create_model():
_velocity = Input(shape=(5,), name='velocity')
_instrument_source = Input(shape=(3,), name='instrument_source')
_qualities = Input(shape=(10,), name='qualities')
_z = Input(shape=(1000, 16), name='z')
categorical_inputs = concatenate(
[_velocity, _instrument_source, _qualities],
name='categorical_inputs'
)
_input = concatenate(
[_z, RepeatVector(1000, name='repeat')(categorical_inputs)],
name='total_inputs'
)
x = GRU(256, return_sequences=True, name='gru_1')(_input)
x = Dropout(0.5, name='dropout_1')(x)
x = GRU(256, return_sequences=True, name='gru_2')(x)
x = Dropout(0.5, name='dropout_2')(x)
_f0_categorical = Dense(49, activation='softmax', name='f0_categorical')(x)
model = tf.keras.models.Model(
[_velocity, _instrument_source, _qualities, _z],
_f0_categorical
)
model.compile(
optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy']
)
return model
| [
"amit.yadav.iitr@gmail.com"
] | amit.yadav.iitr@gmail.com |
d88f28ea450ca654dba6310cde31716208642a8a | e5c04d26f143fff684684139c59e4f5f9519cc1a | /simple_python_game.py | a6aa8e200f749cc8d2d98ea6669bfe97ac98432a | [] | no_license | nabilnegm/simple-python-game | c243c5724572293479ca4227c2b789bba5c9c076 | 03f02c0344a5b99dbb9b1bbb2c4b8638c467b886 | refs/heads/master | 2020-09-29T01:09:29.079760 | 2019-12-09T16:01:57 | 2019-12-09T16:01:57 | 149,772,056 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,150 | py | import random
random_number = []
for x in range(3) :
random_number.append(random.randint(0,10))
if x > 0 :
for y in range(x) :
if random_number[x] == random_number[y] :
random_number[x] = random.randint(0,10)
y=0
while 1 :
input_from_user = []
for x in range(3) :
input_from_user.append(input("enter a 1 digit number ",))
if len(input_from_user[x]) > 1 :
print("input too big only first digit will be taken")
input_from_user[x] = input_from_user[x][0]
for x in range(3) :
input_from_user[x] = int(input_from_user[x])
match = 0
statement = 'nope'
for x in range(3) :
for y in range(3) :
if input_from_user[y] == random_number[x] :
if x == y :
statement = 'match'
match += 1
break
elif statement == 'match' :
break
else :
statement = 'close'
if match == 3 :
print("horraaayyyyy ^^")
break
else :
print(statement)
| [
"n.negm321@gmail.com"
] | n.negm321@gmail.com |
72f3f148ec829bafe29c6dfa81210b74988a3f3d | fd291e4d0291a96d1854f9b05e5b3628f953cfdc | /source/main/encryptor.py | 659595a42945106f6f826adea93f1ad1efcf2402 | [] | no_license | joegumke/csgy-6903_proj1 | a7ec7aaf510865aa3633325f938cbf4a7e1296f3 | de0a2f3c4ba9c093009b33dce004cd05266f62a9 | refs/heads/main | 2023-04-02T07:28:00.418883 | 2021-04-08T21:39:13 | 2021-04-08T21:39:13 | 356,054,027 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,861 | py | #! /usr/bin/python
# NYU Cryptography Project 1
from random import *
import decryptor as decryptor
import time, os
alphaLower = "abcdefghijklmnopqrstuvwxyz"
fileToWriteTo = "../test.resources/testDecryptorResult.txt"
selectedPlainTextFile = "../main.resources/selectedPlainText.txt"
plaintextDict1File = "../main.resources/test1dict.txt"
plaintextDict2File = "../main.resources/test2dict.txt"
def test1_plaintext_gen(dictfile):
# let's assume dictfile1 has 5 plaintext lines & dictfile2 has 40 english words
# this function returns either a single plaintext line or a word selected randomly
count = 0
for line in open(dictfile).readlines():
count += 1
# Take random word as input
f = open(dictfile)
lines = f.readlines()
randomLineNum = randint(0, count-1)
if randomLineNum % 2 == 0:
randomLineNum += 1
randomLine = lines[randomLineNum].rstrip()
stripped = lambda s: "".join(i for i in s if (96 < ord(i) < 123) or ord(i) == 32)
randomLine = stripped(randomLine)
# Output Results
print("Test 1 : Plain text Length:", len(randomLine))
print("Test 1 : Randomly selected plain text '%s'"%randomLine)
return randomLine
def test2_plaintext_gen(dictfile, maxLen):
# let's assume dictfile1 has 5 plaintext lines & dictfile2 has 40 english words
# this function returns either a single plaintext line or a word selected randomly
plaintext = ""
count = 0
for line in open(dictfile).readlines():
count += 1
# Take random word as input
f = open(dictfile)
lines = f.readlines()
while len(plaintext) < maxLen:
randomLineNum = randint(0, count-1)
randomWord = lines[randomLineNum]
randomWord = randomWord.strip()
plaintext += randomWord + " "
plaintext = plaintext[:500]
# Output Results
# print("Test 2 : Concatenated plaintext (length):", len(plaintext))
# print("Test 2 : Concatenated plaintext '%s'"%plaintext)
return plaintext
def enc_key_gen(maxKeyLength):
# Generate encryption key of random length from 1 to maxKeyLength made of numbers from 0 to 26
# !!!!Create a T length random number dictionary for 0-26 length of T numbers.
alphaDict = {0: ' ', 1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e', 6: 'f', 7: 'g', 8: 'h', 9: 'i', 10: 'j', 11: 'k',
12: 'l', 13: 'm', 14: 'n', 15: 'o', 16: 'p', 17: 'q', 18: 'r', 19: 's', 20: 't', 21: 'u', 22: 'v',
23: 'w', 24: 'x', 25: 'y', 26: 'z'}
# Initialize the encryptionKey array
encryptKey = []
alphaKey = []
alphaStrKey = ""
# select a random int from 0 to maxKeyLength as keyLength t for this instance
keyLen = randint(7, maxKeyLength)
# populate the encryptKey array of length keyLen with a random int from 0 to 26
for i in range(keyLen):
encryptKey.append(randint(0, 26))
# Output Results
for i in range(keyLen):
alphaKey += [v for k, v in alphaDict.items() if k == encryptKey[i]]
# print("Alpha Encryption Key: chars", alphaKey)
print("Encryption Key: '%s'"%alphaStrKey.join(alphaKey))
print("Encryption Key: ", encryptKey)
print("Encryption Key Length:", len(encryptKey))
return encryptKey
def encryptor(maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength):
alphaDict = {0: ' ', 1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e', 6: 'f', 7: 'g', 8: 'h', 9: 'i', 10: 'j', 11: 'k',
12: 'l', 13: 'm', 14: 'n', 15: 'o', 16: 'p', 17: 'q', 18: 'r', 19: 's', 20: 't', 21: 'u', 22: 'v',
23: 'w', 24: 'x', 25: 'y', 26: 'z'}
ciphertext = []
ciphertext_flat = []
ciphertext_str = ""
encryptKey = []
random_chars = 0
# generate random key
encryptKey = enc_key_gen(maxKeyLength)
t = len(encryptKey)
if testNum == 1:
plaintext_from_file = \
test1_plaintext_gen("../main.resources/test1dict.txt")
else:
plaintext_from_file = \
test2_plaintext_gen("../main.resources/test2dict_400.txt", maxMsgLength)
plaintext = plaintext_from_file
plaintext_len = len(plaintext)
s_i = m_i = 0
while m_i < plaintext_len:
if randomizer_action == "add":
k_i = s_i % t + randomizer # randomizer is static for the entire encryption run - it's passed in
# k_i = (2*s_i + 3) % t + randomizer # randomizer is static for the entire encryption run - it's passed in
else:
k_i = s_i % t - randomizer # randomizer is static for the entire encryption run - it's passed in
if k_i >= t or k_i < 0:
s_i += 1
randchar_k = randint(0, 26)
ciphertext.insert(len(ciphertext), [v for k, v in alphaDict.items() if k == randchar_k])
#print("Inserted random char: ", ciphertext[len(ciphertext)-1], "At index: ", len(ciphertext)-1)
random_chars += 1
continue
else:
plaintext_k = [k for k, v in alphaDict.items() if v == plaintext[m_i]]
ciphertext_k = plaintext_k[0] - encryptKey[k_i]
if ciphertext_k < 0:
ciphertext_k += len(alphaDict)
ciphertext.insert(len(ciphertext), [v for k, v in alphaDict.items() if k == ciphertext_k])
m_i += 1
s_i += 1
# print("Modified Plaintext (# indicates random char", plaintext)
print("Plaintext Length:", len(plaintext_from_file), " Ciphertext length:", len(ciphertext), "Rand Chars: ", random_chars)
rand_percent = round((random_chars/len(plaintext)) * 100, 2)
print("random chars in cipher text: ", rand_percent, "%")
for elem in ciphertext:
ciphertext_flat.extend(elem)
ciphertext_str = ''.join(ciphertext_flat)
# print("Cipher text list: ", ciphertext_flat)
if testNum == 2:
print("Randomly Generated Plaintext (from dict2): '%s'" % plaintext)
print("Cipher text str: '%s'"%ciphertext_str)
start=time.time()
decryptor.arrayPopulator(testNum, ciphertext_str)
end=time.time()
print(f"**************Runtime of the program is {end - start}")
#return ciphertext_str
def cipherText(fileName, maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength):
alphaDict = {0: ' ', 1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e', 6: 'f', 7: 'g', 8: 'h', 9: 'i', 10: 'j', 11: 'k',
12: 'l', 13: 'm', 14: 'n', 15: 'o', 16: 'p', 17: 'q', 18: 'r', 19: 's', 20: 't', 21: 'u', 22: 'v',
23: 'w', 24: 'x', 25: 'y', 26: 'z'}
ciphertext = []
ciphertext_flat = []
ciphertext_str = ""
encryptKey = []
random_chars = 0
# generate random key
encryptKey = enc_key_gen(maxKeyLength)
t = len(encryptKey)
dictNum = randint(1, 100) % 2
# dictNum = 1
if dictNum == 1:
plaintext_from_file = \
test1_plaintext_gen(plaintextDict1File) #test1_plaintext_gen("../main.resources/test1dict.txt")
else:
plaintext_from_file = \
test2_plaintext_gen(plaintextDict2File, maxMsgLength) #test2_plaintext_gen("../main.resources/test2dict.txt", maxMsgLength)
plaintext = plaintext_from_file
plaintext_len = len(plaintext)
s_i = m_i = 0
scheduler = randint(1, 5)
if scheduler == 1:
scheduler_str = "(i % t) + " + str(randomizer)
elif scheduler == 2:
scheduler_str = "(i % t) - " + str(randomizer)
elif scheduler == 3:
scheduler_str = "((2 * i + 3) % t) + " + str(randomizer)
elif scheduler == 4:
scheduler_str = "((3 * i - 4) % t) - " + str(randomizer)
elif scheduler == 5:
scheduler_str = "(2 * i + " + str(randomizer) + ") % t"
while m_i < plaintext_len:
if scheduler == 1:
k_i = s_i % t + randomizer # randomizer is static for the entire encryption run - it's passed in
elif scheduler == 2:
k_i = s_i % t - randomizer # randomizer is static for the entire encryption run - it's passed in
elif scheduler == 3:
k_i = (2 * s_i + 3) % t + randomizer # randomizer is static for the entire encryption run - it's passed in
elif scheduler == 4:
k_i = (3 * s_i - 4) % t - randomizer # randomizer is static for the entire encryption run - it's passed in
elif scheduler == 5:
k_i = (2 * s_i + randomizer) % t # randomizer is static for the entire encryption run - it's passed in
if k_i >= t or k_i < 0:
s_i += 1
randchar_k = randint(0, 26)
ciphertext.insert(len(ciphertext), [v for k, v in alphaDict.items() if k == randchar_k])
if len(ciphertext)-1 < 3*t:
print("Inserted random char: ", ciphertext[len(ciphertext)-1], "At index: ", len(ciphertext)-1)
random_chars += 1
continue
else:
plaintext_k = [k for k, v in alphaDict.items() if v == plaintext[m_i]]
ciphertext_k = plaintext_k[0] - encryptKey[k_i]
if ciphertext_k < 0:
ciphertext_k += len(alphaDict)
ciphertext.insert(len(ciphertext), [v for k, v in alphaDict.items() if k == ciphertext_k])
m_i += 1
s_i += 1
# print("Modified Plaintext (# indicates random char", plaintext)
print(f'Randomly selected Scheduler: {scheduler_str}')
print("Plaintext Length:", len(plaintext_from_file), " Ciphertext length:", len(ciphertext), "Rand Chars: ", random_chars)
rand_percent = round((random_chars/len(plaintext)) * 100, 2)
print("random chars in cipher text: ", rand_percent, "%")
for elem in ciphertext:
ciphertext_flat.extend(elem)
ciphertext_str = ''.join(ciphertext_flat)
# print("Cipher text list: ", ciphertext_flat)
if dictNum == 1:
print("Randomly Selected Plaintext (from dict1 strings): '%s'" % plaintext)
else:
print("Randomly Generated Plaintext (concatenated dict2 words): '%s'" % plaintext)
print("Cipher text str: '%s'"%ciphertext_str)
ptFile = open(selectedPlainTextFile, "w")
ptFile.write(plaintext)
ptFile.close()
mode = 'a+' if os.path.exists(fileToWriteTo) else 'w+'
with open(fileToWriteTo,mode) as f:
f.write('Encryptor :: Randomly generated plain text\n')
f.write(plaintext)
f.write('\n')
f.write('Encryptor :: Key Scheduler Function (i: plaintext index, t: key length = ' + str(t) + ')\n')
f.write(scheduler_str)
f.write('\n')
f.write('Encryptor :: Cipher text\n')
f.write(ciphertext_str)
f.write('\n')
f.write('\n**************************')
f.close()
return (ciphertext_str)
def encryptor(fileName, maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength):
ciphertext_str = cipherText(fileName, maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength)
tot_runtime = decryptor.arrayPopulator(fileName, testNum, ciphertext_str)
# print(f"**************Runtime of the Decryptor is {tot_runtime}")
return (tot_runtime)
def get_dict2_freq_distribution(num_strings, maxMsgLength):
frequencies = {" ": 0.0000, "a": 0.08497,"b": 0.01492,"c": 0.02202,"d": 0.04253,"e": 0.11162,"f": 0.02228,"g": 0.02015,
"h": 0.06094,"i": 0.07546,"j": 0.00153,"k": 0.01292,"l": 0.04025,"m": 0.02406,"n": 0.06749,
"o": 0.07507,"p": 0.01929,"q": 0.00095,"r": 0.07587,"s": 0.06327,"t": 0.09356,"u": 0.02758,
"v": 0.00978,"w": 0.02560,"x": 0.00150,"y": 0.01994,"z": 0.00077,}
# Build Alphabet Map
alphabet = [' '] + [chr(i + ord('a')) for i in range(26)]
alphabet_distribution = {}
alphabet_freq = {}
for i in range(0, len(alphabet)):
alphabet_distribution[alphabet[i]] = 0
alphabet_freq[alphabet[i]] = 0
test2_sample_str = ""
total_chars = 0
# num_strings = 50000
for i in range(0, num_strings):
test2_sample_str += test2_plaintext_gen("../main.resources/test2dict_400.txt", maxMsgLength)
for c in test2_sample_str:
alphabet_distribution[c] += 1
total_chars += 1
for i in range(len(alphabet)):
alphabet_freq[alphabet[i]] = round(alphabet_distribution[alphabet[i]]/total_chars, 4)
# print("Test 2 sample str: ",test2_sample_str)
print("Total chars: ", len(test2_sample_str))
print("Test 2 alpha distribution: ",alphabet_distribution)
print("Test 2 alpha frequency: ", alphabet_freq)
print("==============================")
print("English Lang Std Freq:", frequencies)
print("==============================")
return alphabet_freq
def get_dict2_freq_distribution(filename, num_strings, maxMsgLength):
frequencies = {" ": 0.0000, "a": 0.08497,"b": 0.01492,"c": 0.02202,"d": 0.04253,"e": 0.11162,"f": 0.02228,"g": 0.02015,
"h": 0.06094,"i": 0.07546,"j": 0.00153,"k": 0.01292,"l": 0.04025,"m": 0.02406,"n": 0.06749,
"o": 0.07507,"p": 0.01929,"q": 0.00095,"r": 0.07587,"s": 0.06327,"t": 0.09356,"u": 0.02758,
"v": 0.00978,"w": 0.02560,"x": 0.00150,"y": 0.01994,"z": 0.00077,}
# Build Alphabet Map
alphabet = [' '] + [chr(i + ord('a')) for i in range(26)]
alphabet_distribution = {}
alphabet_freq = {}
for i in range(0, len(alphabet)):
alphabet_distribution[alphabet[i]] = 0
alphabet_freq[alphabet[i]] = 0
test2_sample_str = ""
total_chars = 0
# num_strings = 50000
for i in range(0, num_strings):
test2_sample_str += test2_plaintext_gen(filename, maxMsgLength)
for c in test2_sample_str:
alphabet_distribution[c] += 1
total_chars += 1
for i in range(len(alphabet)):
alphabet_freq[alphabet[i]] = round(alphabet_distribution[alphabet[i]]/total_chars, 4)
# print("Test 2 sample str: ",test2_sample_str)
print("Total chars: ", len(test2_sample_str))
print("Test 2 alpha distribution: ",alphabet_distribution)
print("Test 2 alpha frequency: ", alphabet_freq)
print("==============================")
print("English Lang Std Freq:", frequencies)
print("==============================")
return alphabet_freq
def main():
# *********************************************************************************************************
# Project 1 configuration to test encryption / decryption of 2 attack types
# *********************************************************************************************************
# test random message generator
# maxKeyLength = 24
maxKeyLength = 24
# randomizer value of 1 is a simple randomizer : (i % t) + 1 : i is the plaintext index, t is the key length
randomizer = 1
# randomizer = 0
# randomizer action tells the encryptor whether to add or subtract the randomizer from i % t
randomizer_action = "add"
# randomizer_action = "subtract"
# testNum = 1: Randomly select 1 of 5, 500 char strings and try to decrypt it
# testNum = 2: Randomly select words from a dict to generate a ~500 char string and try to decrypt it
testNum = 2
maxMsgLength = 500
fileName = "../main.resources/wordsMerged.txt"
#encryptor(maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength)
encryptor(fileName, maxKeyLength, randomizer, randomizer_action, testNum, maxMsgLength)
#get_dict2_freq_distribution(fileName, 50000, 500)
if __name__ == "__main__":
main()
| [
"noreply@github.com"
] | noreply@github.com |
e4d4fea068c46ee67164d1c119beff0d536a0ce2 | b02234111d79ea1fe352e57884cbaef7822c92b6 | /day6/Hurdle 3_3.py | be5ec4b303a9686852f4d5432d3963c476cd52d1 | [] | no_license | medbasso/python_bootcamp_solution | 1567d257d6cf4c339195f59f341fdf289790d09c | 07e234d4199cfdaa87e0f4e3b039bfaa0ac522be | refs/heads/main | 2023-02-05T00:47:29.722318 | 2020-12-24T20:03:23 | 2020-12-24T20:03:23 | 322,890,807 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 538 | py | def right():
turn_left()
turn_left()
turn_left()
def jump():
turn_left()
move()
right()
move()
right()
move()
turn_left()
while at_goal() !=True:
if wall_in_front() != True:
move()
else:
jump()
################################################################
# WARNING: Do not change this comment.
# Library Code is below.
################################################################
| [
"tounsi1295@gmail.com"
] | tounsi1295@gmail.com |
42caf49b668d0512a63087fa1f772a41f02fcc14 | f811ff7901a565842b71ceb347ff613c07036ffb | /python/1-6-2.py | 33d9c37acd775d62b517bbd642bf54a1021a6b67 | [] | no_license | anfernee84/Learning | 600f8006f1c0033245b9e1bf7e4191540d7bd04f | 6fd9e24e6ca51155b313957c77119bab816c0a07 | refs/heads/master | 2021-08-03T15:47:53.226387 | 2021-07-25T12:00:26 | 2021-07-25T12:00:26 | 234,156,414 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 339 | py | def total_salary(path):
fh = open(path, 'r')
sums = 0
while True:
line = fh.readline()
if not line:
break
l = line
l = l.rstrip("\n")
l = l.split(",")
sums += float(l[1])
fh.close()
return (sums)
print(total_salary('test.txt')) | [
"noreply@github.com"
] | noreply@github.com |
93e57d2c77d07d9aed1f2c455f9e6ead7e2746ae | 621070139978d383f95203aaf994ba8ee8814fcc | /brewwolf/rate_beer/migrations/0003_auto_20191225_1931.py | 67436c421a8f252f6975620f23a93ab626a29d48 | [] | no_license | AMPER54ND/tin-django | 2c0022653d8c7a455ce2bd9a5425f14a45990393 | 90aa56abbf412f809d978cff8d1bb121744a4379 | refs/heads/master | 2020-11-29T15:56:20.785884 | 2020-01-07T15:18:52 | 2020-01-07T15:18:52 | 230,158,346 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 361 | py | # Generated by Django 3.0 on 2019-12-25 19:31
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('rate_beer', '0002_auto_20191212_0116'),
]
operations = [
migrations.RenameField(
model_name='beer',
old_name='creator',
new_name='owner',
),
]
| [
"btmacd@gmail.com"
] | btmacd@gmail.com |
e0b5ca9db7e40e9b5e0260f2d584aa234eb16f94 | cb2a40b70bc21d0057c96ddb2c86edceffe19707 | /payments/migrations/0011_auto_20180104_1301.py | 259d5612830139f25d17956bd53eef9cb226afa7 | [] | no_license | rebkwok/pipsevents | ceed9f420b08cd1a3fa418800c0870f5a95a4067 | c997349a1b4f3995ca4bb3a897be6a73001c9810 | refs/heads/main | 2023-08-09T14:11:52.227086 | 2023-07-27T20:21:01 | 2023-07-27T20:21:01 | 29,796,344 | 1 | 1 | null | 2023-09-13T14:32:16 | 2015-01-24T23:53:34 | Python | UTF-8 | Python | false | false | 697 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2018-01-04 13:01
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('payments', '0010_auto_20180102_1130'),
]
operations = [
migrations.AlterField(
model_name='paypalblocktransaction',
name='invoice_id',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AlterField(
model_name='paypalblocktransaction',
name='transaction_id',
field=models.CharField(blank=True, max_length=255, null=True),
),
]
| [
"rebkwok@gmail.com"
] | rebkwok@gmail.com |
ea3767f48063c198e4644402f4f8bd10e8f8c404 | 5683e0be45bbd4c0eff0bc143e1fabb39e3dd2d1 | /data_bootstrap/management/commands/bootstrap.py | 63aa966cbb00559c06f1852f44fddc334c1e4161 | [
"BSD-3-Clause",
"BSD-2-Clause",
"MIT"
] | permissive | SteveWaweru/mfl_api | be1e6b24a039553447dc6fdc23b588c4a6756a8f | 695001fb48cb1b15661cd480831ae33fe6374532 | refs/heads/master | 2023-05-29T04:27:35.421574 | 2021-10-27T06:07:10 | 2021-10-27T06:07:10 | 205,343,934 | 0 | 5 | MIT | 2023-05-15T00:38:30 | 2019-08-30T08:54:14 | Python | UTF-8 | Python | false | false | 734 | py | import os
import glob
from django.core.management import BaseCommand
from ...bootstrap import process_json_file
class Command(BaseCommand):
def add_arguments(self, parser):
# Positional arguments
parser.add_argument('data_file', nargs='+', type=str)
def handle(self, *args, **options):
for suggestion in options['data_file']:
# if it's just a simple json file
if os.path.exists(suggestion) and os.path.isfile(suggestion):
process_json_file(suggestion)
else:
# check if it's a glob
for filename in glob.glob(suggestion):
process_json_file(filename)
self.stdout.write("Done loading")
| [
"marika@savannahinformatics.com"
] | marika@savannahinformatics.com |
41719d1f84a14e2c8c31ca71d64fb6fe025054a3 | 40c6fa589a0dfe88e82f8bd969cd5ef0ed04f303 | /SWEA/D2/1954.py | 6f69fcd9fca262d0e6c5087f16a45514a8d6b3b2 | [] | no_license | EHwooKim/Algorithms | 7d8653e55a491f3bca77a197965f15792f7ebe47 | 5db0a22b9dc0ba9a30bb9812c54d2d5ecec1676b | refs/heads/master | 2021-08-20T04:05:09.967910 | 2021-06-15T07:54:17 | 2021-06-15T07:54:17 | 197,136,680 | 0 | 2 | null | 2021-01-08T05:51:37 | 2019-07-16T06:46:57 | Python | UTF-8 | Python | false | false | 751 | py | T = int(input())
for t in range(1, T + 1):
print(f'#{t}')
N = int(input())
i = j = 0
min_num = 0
max_num = N - 1
count = 1
result = [[0]*N for i in range(N)]
while count <= N**2 - 1:
while j < max_num:
result[i][j] = count
j += 1
count += 1
while i < max_num:
result[i][j] = count
i += 1
count += 1
max_num -= 1
while j > min_num:
result[i][j] = count
j -= 1
count += 1
min_num += 1
while i > min_num:
result[i][j] = count
i -= 1
count +=1
result[i][j] = count
for n in range(N):
print(*result[n], sep = ' ')
| [
"ehwoo0707@naver.com"
] | ehwoo0707@naver.com |
a2efb56dab315b04b0175314bda7483e3137b35a | b08f5367ffd3bdd1463de2ddc05d34cbfba6796e | /search/search_missing_among_billions.py | 89e090a9dfd46719bbba7f53ba780a4de22f17eb | [] | no_license | uohzxela/fundamentals | cb611fa6c820dc8643a43fd045efe96bc43ba4ed | 6bbbd489c3854fa4bf2fe73e1a2dfb2efe4aeb94 | refs/heads/master | 2020-04-04T03:56:44.145222 | 2018-04-05T01:08:14 | 2018-04-05T01:08:14 | 54,199,110 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,038 | py | '''
create an array of 2^16 32-bit integers
for every integer in the file, take its 16 most significant bits to index into this array and increment count
since the file contains less than 2^32 numbers, there must be one entry in the array that is less than 2^16
this tells us that there is at least one integer which has those upper bits and is not in the file
in the second pass, we focus only on the integers whose leading 16 bits match the one we have found
and use a bit array of size 2^16 to identify a missing address
'''
def search(file):
count = [0 for i in xrange(2^16)]
for e in file:
count[e >> 16] += 1
for i in xrange(len(count)):
c = count[i]
bitset = [False for i in xrange(2^16)]
if c < 2^16:
for e in file:
if e >> 16 == i:
'''
2^16-1 is used to mask off the upper 16 bits so that
only the lower 16 bits can be obtained
why minus 1? e.g. 2^4 = 10000, 2^4-1 = 01111
'''
bitset[2^16-1 & e] = True
for j in xrange(2^16):
if not bitset[j]: return i << 16 | j | [
"uohzxela@gmail.com"
] | uohzxela@gmail.com |
e8da1751379981edada6b01f73513a0670fac6bd | f15620243d86981982ac3f79839fc5224a5a2adf | /__main__.py | a14001cb1571124598d6c1a7f8ae6aab9654a3b0 | [
"Unlicense"
] | permissive | w73pa/kivy-calc | 6f47866993e78101fad56fd230567728a2f493f7 | 1284d5e6ecca7a537c2b5391da43596c7bf2ffce | refs/heads/master | 2016-09-06T07:57:52.182411 | 2013-11-05T19:53:46 | 2013-11-05T19:53:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,100 | py | from kivy.app import App
from kivy.uix.boxlayout import BoxLayout
from kivy.properties import *
class Calculator(BoxLayout):
wip = BooleanProperty(False)
display = ObjectProperty(None)
info = ObjectProperty(None)
def append(self, c):
if self.wip:
self.display.text += c
else:
self.display.text = c
self.wip = True
def clr(self):
self.wip = False
self.display.text = '0'
def ce(self):
if self.wip:
self.display.text = self.display.text[:-1]
def compute(self):
self.wip = False
try:
# multiply the expression with 1.0 to force a float operation
expression = '1.0 * {0}'.format(self.display.text)
result = eval(expression)
self.info.text = self.display.text + '='
self.display.text = '{0}'.format(result)
except Exception as e:
self.display.text = 'Error: {0}'.format(e)
class Calc(App):
def build(self):
return Calculator()
if __name__ == "__main__":
Calc().run()
| [
"bernd@gauweiler.net"
] | bernd@gauweiler.net |
be823ef9a397bb6adc46c4212db7e1c05d19effa | afe50e43fcdcda9bc8ab3d48d8e46dfd8e3b40a8 | /django_env/bin/pip | f7fda958f777a5249a24a98774f9b5e6e659f79c | [] | no_license | astazja/Opti | 79ef7cc9f89191a2b1b079765c62c3744827d163 | c4792dc5e9b9da4fa86e9396d05e5222cdd134e4 | refs/heads/master | 2022-12-10T10:36:30.629227 | 2020-09-07T07:52:46 | 2020-09-07T07:52:46 | 293,458,585 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 403 | #!/home/kasia/coderslab/OptiKurier/django_env/bin/python
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==19.0.3','console_scripts','pip'
__requires__ = 'pip==19.0.3'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==19.0.3', 'console_scripts', 'pip')()
)
| [
"katarzyna@pacewi.cz"
] | katarzyna@pacewi.cz | |
9124041deaeabe8651514004072aaac126543069 | a36f2bea040d5b2da1da3af6162008cdb0b9dcea | /ADXL345.py | 0fd034e277a4a36fd67735a6ee245bb439accd33 | [] | no_license | omar-abdelwahab2/cpsc359-4 | 5ef11823d910d638269441c25e58a900795b1ae9 | cec4643cf8dee755a3799c0714edf7e742744c9d | refs/heads/master | 2021-08-23T17:50:34.354969 | 2017-12-05T23:59:22 | 2017-12-05T23:59:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,254 | py | '''
class:
ADXL345
Purpose:
This class is used to communicate through the SMbus and collect
information from the accelerometer.
Methods:
Constants:
These constants are used throughout the code of the ADXL345 class
and have been provided by the manufacturer.
__init__:
constructor for the ADXL345
begin:
Used to check that the accelerometer is connected properly to pi
and the explorer hat and that eveything is communicating properly
to each other.
write_register:
takes a value and gives it to the accelerometer through smbus methods
while making sure to open and close lines of communication properly
read_register:
similar to previous method except it returns a value from the ADXL345
but it needs a register to be given to know which one to read from
values for used registers are defined in the constants at the top
of the class.
read_16:
used to read a word instead of just a byte by reading a byte,
shifting it to the higher bits then reading another byte.
get_x, get_y, get_z:
returns properly formatted data from the accelerometer with the
length of a word for each of the x, y, and z axes respectively.
'''
import mySmbus
class ADXL345:
ADXL345_ADDRESS = 0x53 # Assumes ALT address pin low
ADXL345_REG_DEVID = 0x00 # Device ID
ADXL345_REG_POWER_CTL = 0x2D # Power-saving features control
ADXL345_REG_DATAX0 = 0x32 # X-axis data 0
ADXL345_REG_DATAY0 = 0x34 # Y-axis data 0
ADXL345_REG_DATAZ0 = 0x36 # Z-axis data 0
def __init__(self):
self.mySmbus = mySmbus
# self.bus = smbus.SMBus()
self.BUS_ID = 1
self.range = 0
def begin(self):
# check connection
self.mySmbus.my_my_init()
device_id = self.read_register(self.ADXL345_REG_DEVID)
if device_id != 0xe5:
# No ADXL345 detected ... return false
#print(format(device_id, '02x'))
# print(device_id)
return False
# enable measurements
self.write_register(self.ADXL345_REG_POWER_CTL, 0x08)
self.mySmbus.my_my_uninit()
return True
def write_register(self, reg, value):
# self.bus.open(self.BUS_ID)
self.mySmbus.my_my_init()
self.mySmbus.my_i2c_write_byte_data(self.ADXL345_ADDRESS, reg, value)
self.mySmbus.my_my_uninit()
# self.bus.close()
def read_register(self, reg):
# self.bus.open(self.BUS_ID)
temp = self.mySmbus.my_my_init()
reply = self.mySmbus.my_i2c_read_byte_data(self.ADXL345_ADDRESS, reg)
self.mySmbus.my_my_uninit()
# self.bus.close()
return reply
def read_16(self, reg):
# self.bus.open(self.BUS_ID)
self.mySmbus.my_my_init()
reply = self.mySmbus.my_i2c_read_word_data(self.ADXL345_ADDRESS, reg)
self.mySmbus.my_my_uninit()
# self.bus.close()
return reply
def get_x(self):
return self.read_16(self.ADXL345_REG_DATAX0)
def get_y(self):
return self.read_16(self.ADXL345_REG_DATAY0)
def get_z(self):
return self.read_16(self.ADXL345_REG_DATAZ0)
| [
"baraka.am@gmail.com"
] | baraka.am@gmail.com |
fdb02bf66446c83561f10691d239c3aad88bb1b7 | 09efdf48ca3444c4020dfac88000e4cf182db2e7 | /Basic Programs/menu.py | 2033960b26c6d31422418cbdc8eee029268c8ea3 | [] | no_license | himanij11/Python---Basic-Programs | 1aac3a1d0caccd2bde0d6cf067a70fb9427476e6 | 2f9a92bbd1fe1530f26027d24685bc927109b14e | refs/heads/master | 2020-11-24T15:04:37.270439 | 2019-12-15T15:28:40 | 2019-12-15T15:28:40 | 228,207,045 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,078 | py | #menu driven for even,palindrome,armstrong
def even(n):
if(n%2==0):
print("{} is an even number.".format(n))
else:
print("{} is not an even no.".format(n))
def palindrome(n):
temp=n
rev=0
while n!=0:
a=n%10
rev=rev*10+a
n=int(n/10)
if temp==rev:
print("{} is a palindrome number.".format(temp))
else:
print("{} is not a palindrome number.".format(temp))
def armstrong(n):
temp=n
sum=0
while n!=0:
a=n%10
sum=sum+a*a*a
n=int(n/10)
if temp==sum:
print("{} is a armstrong number.".format(temp))
else:
print("{} is not an armstrong number.".format(temp))
n=int(input("enter n:"))
ch=int(input("1.Even no \n2.Palindrome \n3.Armstrong \n4.Exit \nEnter choice="))
while ch!=4:
if ch==1:
even(n)
elif ch==2:
palindrome(n)
else:
armstrong(n)
n=int(input("enter n:"))
ch=int(input("1.Even no \n2.Palindrome \n3.Armstrong \n4.Exit \nEnter choice="))
| [
"himanij2451@gmail.com"
] | himanij2451@gmail.com |
4c17a2fd6c5aae776b17d9474dacb25c0396c160 | 738aedb8035e49951f83ce3f4291eee149cad5fb | /OB Damage - Li-Hopfield Model/All the code/Damage Trials/MC-1col_20_2D.py | 83d3c9d36ca88bf3d357b7ab8bca600c998a336b | [] | no_license | jkberry07/OB_PD_Model | fb453303bfa64c1a3a43c7d81d2b5373950e1f4d | 1ce30205354dc30cab4673e406988bfa76390238 | refs/heads/master | 2022-11-21T09:39:09.692654 | 2020-07-25T23:25:11 | 2020-07-25T23:25:11 | 282,358,721 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 24,848 | py | # -*- coding: utf-8 -*-
"""
Created on Tue Dec 18 13:38:32 2018
@author: wmmjk
"""
#This one does the damage to each of the granule cells (columns of H0)
#Olfactory Bulb Model a la Li/Hopfield and Li/Hertz
#Translated from Avinash's Matlab code
#This one I have the initial condition in odeint as the equilibrium at rest plus noise
#Change Log
import numpy as np
import scipy.linalg as lin
import scipy.stats as stats
import scipy.signal as signal
from scipy.optimize import fsolve
from scipy.integrate import solve_ivp
import time
import os
import sys
sys.path.append(os.getcwd())
tm1 = time.time()
Nmitral0 = 20 #define network size in parent process
#####Chapter 1 - The Output functions########################
def cellout(x,s1,s2,th):
g = np.zeros(np.shape(x))
for i in np.r_[0:np.size(x)]:
if x[i] < th:
g[i] = s2 + s2*np.tanh((x[i]-th)/s2)
else:
g[i] = s2 + s1*np.tanh((x[i]-th)/s1)
return g
def celldiff(x,s1,s2,th):
#Returns the differentiated outputs in a diagonal matrix for calculating
#the matrix A
Gdiff = np.zeros((np.size(x),np.size(x)))
for i in np.r_[0:np.size(x)]:
if x[i] < th:
Gdiff[i,i] = (1 - (np.tanh((x[i]-th)/s2))**2)
else:
Gdiff[i,i] = (1 - (np.tanh((x[i]-th)/s1))**2)
return Gdiff
######Chapter 2 - The Equations###########################
def equi(x,Ndim,Nmitral,Sx,Sx2,Sy,Sy2,th,alpha,t_inh,H0,W0,P_odor,Ib,Ic,dam):
F = np.zeros(Ndim)
gx = cellout(x[0:Nmitral],Sx,Sx2,th) #calculate output from internal state
gy = cellout(x[Nmitral:],Sy,Sy2,th) #for mitral and granule cells respectively
F[0:Nmitral] = dam*(np.ravel(-np.dot(H0,gy)) - np.ravel(alpha*x[0:Nmitral]) + np.ravel(Ib) + \
np.ravel(P_odor*(180-t_inh))) - np.ravel(alpha*x[0:Nmitral]) #180 is 25 ms before the end of inhale
F[Nmitral:] = np.ravel(np.dot(W0,gx)) - np.ravel(alpha*x[Nmitral:]) + np.ravel(Ic)
return F
def diffeq(t,x,Nmitral,Ngranule,Ndim,lastnoise,noise,noisewidth,noiselevel,\
t_inh,t_exh,exh_rate,alpha,Sy,Sy2,Sx,Sx2,th,H0,W0,P_odor,Ic,Ib,dam):
y = x
dydt = np.zeros(np.shape(y))
for i in np.r_[0:Nmitral]:
if t < t_inh:
dydt[i] = dam[i]*((t-lastnoise[i])*noise[i] - np.dot(np.reshape(H0[i,:],\
(1,Ngranule)), cellout(y[Nmitral:],Sy,Sy2,th)) + \
Ib[i]) - alpha*y[i]
elif t < t_exh:
dydt[i] = dam[i]*((t-lastnoise[i])*noise[i] - np.dot(np.reshape(H0[i,:],\
(1,Ngranule)), cellout(y[Nmitral:],Sy,Sy2,th)) + \
Ib[i] + P_odor[i]*(t-t_inh)) - alpha*y[i]
else:
dydt[i] = dam[i]*((t-lastnoise[i])*noise[i] - np.dot(np.reshape(H0[i,:],\
(1,Ngranule)), cellout(y[Nmitral:],Sy,Sy2,th)) + \
Ib[i] + P_odor[i]*(t-t_inh)*np.exp(-exh_rate*(t-t_exh))) - alpha*y[i]
for i in np.r_[Nmitral:Ndim]:
dydt[i] = (t-lastnoise[i])*noise[i] + np.dot(np.reshape(\
W0[i-Nmitral,:],(1,Nmitral)),cellout(y[:Nmitral],Sx,Sx2,th)) - \
alpha*y[i] + Ic[i-Nmitral]
for i in np.r_[0:Ndim]:
if (t-lastnoise[i])/noisewidth > .8 + np.random.rand():
lastnoise[i] = t
noise[i] = noiselevel*(2*np.random.rand() -1) #to get noise btwn
#-noiselevel and +nslvl
return dydt
#########Chapter3 - The solver##############################
def olf_bulb_10(Nmitral,H_in,W_in,P_odor_in,dam):
# Nmitral = 10 #number of mitral cells
Ngranule = np.copy(Nmitral) #number of granule cells pg. 383 of Li/Hop
Ndim = Nmitral+Ngranule #total number of cells
t_inh = 25 ; # time when inhalation starts
t_exh = 205; #time when exhalation starts
finalt = 395; # end time of the cycle
#y = zeros(ndim,1);
Sx = 1.43 #Sx,Sx2,Sy,Sy2 are parameters for the activation functions
Sx2 = 0.143
Sy = 2.86 #These are given in Li/Hopfield pg 382, slightly diff in her thesis
Sy2 = 0.286
th = 1 #threshold for the activation function
tau_exh = 33.3333; #Exhale time constant, pg. 382 of Li/Hop
exh_rate = 1/tau_exh
alpha = .15 #decay rate for the neurons
#Li/Hop have it as 1/7 or .142 on pg 383
P_odor0=np.zeros((Nmitral,1)) #odor pattern, no odor
H0 = H_in #weight matrix: to mitral from granule
W0 = W_in #weights: to granule from mitral
Ib = np.ones((Nmitral,1))*.243 #initial external input to mitral cells
Ic = np.ones((Ngranule,1))*.1 #initial input to granule cells, these values are
#given on pg 382 of Li/Hop
signalflag = 1 # 0 for linear output, 1 for activation function
noise = np.zeros((Ndim,1)) #noise in inputs
noiselevel = .00143
noisewidth = 7 #noise correlation time, given pg 383 Li/Hop as 9, but 7 in thesis
lastnoise = np.zeros((Ndim,1)) #initial time of last noise pule
#******************************************************************************
#CALCULATE FIXED POINTS
#Calculating equilibrium value with no input
rest0 = np.zeros((Ndim,1))
restequi = fsolve(lambda x: equi(x,Ndim,Nmitral,Sx,Sx2,Sy,Sy2,th,alpha,\
t_inh,H0,W0,P_odor0,Ib,Ic,dam),rest0) #about 20 ms to run this
np.random.seed(seed=23)
#init0 = restequi+np.random.rand(Ndim)*.00143 #initial conditions plus some noise
#for no odor input
init0 = restequi+np.random.rand(Ndim)*.00143 #initial conditions plus some noise
#for no odor input
np.random.seed()
#Now calculate equilibrium value with odor input
lastnoise = lastnoise + t_inh - noisewidth #initialize lastnoise value
#But what is it for? to have some
#kind of correlation in the noise
#find eigenvalues of A to see if input produces oscillating signal
xequi = fsolve(lambda x: equi(x,Ndim,Nmitral,Sx,Sx2,Sy,Sy2,th,alpha,\
t_inh,H0,W0,P_odor_in,Ib,Ic,dam),rest0)
#equilibrium values with some input, about 20 ms to run
#******************************************************************************
#CALCULATE A AND DETERMINE EXISTENCE OF OSCILLATIONS
diffgy = celldiff(xequi[Nmitral:],Sy,Sy2,th)
diffgx = celldiff(xequi[0:Nmitral],Sx,Sx2,th)
H1 = np.dot(H0,diffgy)
W1 = np.dot(W0,diffgx) #intermediate step in constructing A
A = np.dot(H1,W1) #Construct A
dA,vA = lin.eig(A) #about 20 ms to run this
#Find eigenvalues of A
diff = (1j)*(dA)**.5 - alpha #criteria for a growing oscillation
negsum = -(1j)*(dA)**.5 - alpha #Same
diff_re = np.real(diff)
#Take the real part
negsum_re = np.real(negsum)
#do an argmax to return the eigenvalue that will cause the fastest growing oscillations
#Then do a spectrograph to track the growth of the associated freq through time
indices = np.where(diff_re>0) #Find the indices where the criteria is met
indices2 = np.where(negsum_re>0)
#eigenvalues that could lead to growing oscillations
# candidates = np.append(np.real((dA[indices])**.5),np.real((dA[indices2])**.5))
largest = np.argmax(diff_re)
check = np.size(indices)
check2 = np.size(indices2)
if check==0 and check2==0:
# print("No Odor Recognized")
dominant_freq = 0
else:
dominant_freq = np.real((dA[largest])**.5)/(2*np.pi) #find frequency of the dominant mode
#Divide by 2pi to get to cycles/ms
# print("Odor detected. Eigenvalues:",dA[indices],dA[indices2],\
# "\nEigenvectors:",vA[indices],vA[indices2],\
# "\nDominant Frequency:",dominant_freq)
#*************************************************************************
#SOLVE DIFFERENTIAL EQUATIONS TO GET INPUT AND OUTPUTS AS FN'S OF t
#differential equation to solve
teval = np.r_[0:finalt]
#solve the differential equation
sol = solve_ivp(lambda t,y: diffeq(t,y,Nmitral,Ngranule,Ndim,lastnoise,\
noise,noisewidth,noiselevel, t_inh,t_exh,exh_rate,alpha,Sy,\
Sy2,Sx,Sx2,th,H0,W0,P_odor_in,Ic,Ib,dam),\
[0,395],init0,t_eval = teval,method = 'RK45')
t = sol.t
y = sol.y
y = np.transpose(y)
yout = np.copy(y)
#convert signal into output signal given by the activation fn
if signalflag ==1:
for i in np.arange(np.size(t)):
yout[i,:Nmitral] = cellout(y[i,:Nmitral],Sx,Sx2,th)
yout[i,Nmitral:] = cellout(y[i,Nmitral:],Sy,Sy2,th)
#solve diffeq for P_odor = 0
#first, reinitialize lastnoise & noise
noise = np.zeros((Ndim,1))
lastnoise = np.zeros((Ndim,1))
lastnoise = lastnoise + t_inh - noisewidth
sol0 = sol = solve_ivp(lambda t,y: diffeq(t,y,Nmitral,Ngranule,Ndim,lastnoise,\
noise,noisewidth,noiselevel, t_inh,t_exh,exh_rate,alpha,Sy,\
Sy2,Sx,Sx2,th,H0,W0,P_odor0,Ic,Ib,dam),\
[0,395],init0,t_eval = teval,method = 'RK45')
y0 = sol0.y
y0 = np.transpose(y0)
y0out = np.copy(y0)
#convert signal into output signal given by the activation fn
if signalflag ==1:
for i in np.arange(np.size(t)):
y0out[i,:Nmitral] = cellout(y0[i,:Nmitral],Sx,Sx2,th)
y0out[i,Nmitral:] = cellout(y0[i,Nmitral:],Sy,Sy2,th)
#*****************************************************************************
#SIGNAL PROCESSING
#Filtering the signal - O_mean: Lowpass fitered signal, under 20 Hz
#S_h: Highpass filtered signal, over 20 Hz
fs = 1/(.001*(t[1]-t[0])) #sampling freq, converting from ms to sec
f_c = 15/fs # Cutoff freq at 20 Hz, written as a ratio of fc to sample freq
flter = np.sinc(2*f_c*(t - (finalt-1)/2))*np.blackman(finalt) #creating the
#windowed sinc filter
#centered at the middle
#of the time data
flter = flter/np.sum(flter) #normalize
hpflter = -np.copy(flter)
hpflter[int((finalt-1)/2)] += 1 #convert the LP filter into a HP filter
Sh = np.zeros(np.shape(yout))
Sl = np.copy(Sh)
Sl0 = np.copy(Sh)
Sbp = np.copy(Sh)
for i in np.arange(Ndim):
Sh[:,i] = np.convolve(yout[:,i],hpflter,mode='same')
Sl[:,i] = np.convolve(yout[:,i],flter,mode='same')
Sl0[:,i] = np.convolve(y0out[:,i],flter,mode='same')
#find the oscillation period Tosc (Tosc must be greater than 5 ms to exclude noise)
Tosc0 = np.zeros(np.size(np.arange(5,50)))
for i in np.arange(5,50):
Sh_shifted=np.roll(Sh,i,axis=0)
Tosc0[i-5] = np.sum(np.diagonal(np.dot(np.transpose(Sh[:,:Nmitral]),Sh_shifted[:,:Nmitral])))
#That is, do the correlation matrix (time correlation), take the diagonal to
#get the autocorrelations, and find the max
Tosc = np.argmax(Tosc0)
Tosc = Tosc + 5
f_c2 = 1000*(1.3/Tosc)/fs #Filter out components with frequencies higher than this
#to get rid of noise effects in cross-correlation
#times 1000 to get units right
flter2 = np.sinc(2*f_c2*(t - (finalt-1)/2))*np.blackman(finalt)
flter2 = flter2/np.sum(flter2)
for i in np.arange(Ndim):
Sbp[:,i] = np.convolve(Sh[:,i],flter2,mode='same')
#CALCULATE THE DISTANCE MEASURES
#calculate phase via cross-correlation with each cell
phase = np.zeros(Nmitral)
for i in np.arange(1,Nmitral):
crosscor = signal.correlate(Sbp[:,0],Sbp[:,i])
tdiff = np.argmax(crosscor)-(finalt-1)
phase[i] = tdiff/Tosc * 2*np.pi
#Problem with the method below is that it will only give values from 0 to pi
#for i in np.arange(1,Nmitral):
# phase[i]=np.arccos(np.dot(Sbp[:,0],Sbp[:,i])/(lin.norm(Sbp[:,0])*lin.norm(Sbp[:,i])))
OsciAmp = np.zeros(Nmitral)
Oosci = np.copy(OsciAmp)*0j
Omean = np.zeros(Nmitral)
for i in np.arange(Nmitral):
OsciAmp[i] = np.sqrt(np.sum(Sh[125:250,i]**2)/np.size(Sh[125:250,i]))
Oosci[i] = OsciAmp[i]*np.exp(1j*phase[i])
Omean[i] = np.average(Sl[:,i] - Sl0[:,i])
Omean = np.maximum(Omean,0)
Ooscibar = np.sqrt(np.dot(Oosci,np.conjugate(Oosci)))/Nmitral #can't just square b/c it's complex
Omeanbar = np.sqrt(np.dot(Omean,Omean))/Nmitral
maxlam = np.max(np.abs(np.imag(np.sqrt(dA))))
return yout,y0out,Sh,t,OsciAmp,Omean,Oosci,Omeanbar,Ooscibar,dominant_freq,maxlam
def dmg_seed_20_2D(colnum):
#INITIALIZING STUFF
Nmitral = 20
Ngranule = np.copy(Nmitral) #number of granule cells pg. 383 of Li/Hop
Ndim = Nmitral+Ngranule #total number of cells
# t_inh = 25 ; # time when inhalation starts
# t_exh = 205; #time when exhalation starts
# Ndamagetotal = Nmitral*2 + 1 #number of damage steps
Ndamage = 6
Ncols = int(Nmitral/2) #define number of columns to damage
finalt = 395; # end time of the cycle
#y = zeros(ndim,1);
P_odor0=np.zeros((Nmitral,1)) #odor pattern, no odor
P_odor1 = P_odor0 + .00429 #Odor pattern 1
# P_odor2 = 1/70*np.array([.6,.5,.5,.5,.3,.6,.4,.5,.5,.5])
# P_odor3 = 4/700*np.array([.7,.8,.5,1.2,.7,1.2,.8,.7,.8,.8])
#control_odor = control_order + .00429
#control_odor = np.zeros((Nmitral,1)) #odor input for adaptation
#controllevel = 1 #1 is full adaptation
H0 = np.zeros((Nmitral,Ngranule)) #weight matrix: to mitral from granule
W0 = np.zeros((Ngranule,Nmitral)) #weights: to granule from mitral
H0 = np.load('H0_20_2D_50Hz.npy') #load weight matrix
W0 = np.load('W0_20_2D_50Hz.npy') #load weight matrix
#H0 = H0 + H0*np.random.rand(np.shape(H0))
#W0 = W0+W0*np.random.rand(np.shape(W0))
M = 5 #average over 5 trials for each level of damage
#initialize iterative variables
d1it,d2it,d3it,d4it = np.zeros(M),np.zeros(M),np.zeros(M),np.zeros(M)
IPRit,IPR2it,pnit = np.zeros(M),np.zeros(M),np.zeros(M)
frequencyit = np.zeros(M)
pwrit = np.zeros(M)
yout2,Sh2 = np.zeros((finalt,Ndim)),np.zeros((finalt,Ndim))
psi = np.copy(Sh2[:,:Nmitral])
#initialize quantities to be returned at end of the process
dmgpct1 = np.zeros(Ncols*(Ndamage-1)+1)
eigfreq1 = np.zeros(Ncols*(Ndamage-1)+1)
d11 = np.zeros(Ncols*(Ndamage-1)+1)
d21 = np.zeros(Ncols*(Ndamage-1)+1)
d31 = np.zeros(Ncols*(Ndamage-1)+1)
d41 = np.zeros(Ncols*(Ndamage-1)+1)
pwr1 = np.zeros(Ncols*(Ndamage-1)+1)
IPR1 = np.zeros(Ncols*(Ndamage-1)+1)
IPR2 = np.zeros(Ncols*(Ndamage-1)+1)
pn1 = np.zeros(Ncols*(Ndamage-1)+1)
freq1 = np.zeros(Ncols*(Ndamage-1)+1)
cell_act = np.zeros((finalt,Ndim,Ncols*(Ndamage-1)+1))
# spread = -1 #start at -1 so that the first damage level has a spread of 0 radius
damage = 0
dam = np.ones(Nmitral)
#Get the base response first
Omean1,Oosci1,Omeanbar1,Ooscibar1 = np.zeros((Nmitral,M))+0j,\
np.zeros((Nmitral,M))+0j,np.zeros(M)+0j,np.zeros(M)+0j
for m in np.arange(M):
yout,y0out,Sh,t,OsciAmp1,Omean1[:,m],Oosci1[:,m],Omeanbar1[m],\
Ooscibar1[m],freq0,maxlam = olf_bulb_10(Nmitral,H0,W0,P_odor1,dam)
counter = 0 #to get the right index for each of the measures
damage = 0
dam[colnum]+=.2 # so that first level is zero damage
for col in range(Ncols):
cols = int(np.mod(colnum+col,Nmitral))
for lv in np.arange(Ndamage):
#reinitialize all iterative variables to zero (really only need to do for distance measures, but good habit)
d1it,d2it,d3it,d4it = np.zeros(M),np.zeros(M),np.zeros(M),np.zeros(M)
IPRit,IPR2it,pnit = np.zeros(M),np.zeros(M),np.zeros(M)
frequencyit = np.zeros(M)
pwrit = np.zeros(M)
if not(lv==0 and cols!=colnum): #if it's the 0th level for any but the original col, skip
dam[cols] = dam[cols] - 0.2
dam[dam<1e-10] = 0
damage = np.sum(1-dam)
for m in np.arange(M):
#Then get respons of damaged network
yout2[:,:],y0out2,Sh2[:,:],t2,OsciAmp2,Omean2,Oosci2,Omeanbar2,\
Ooscibar2,freq2,grow_eigs2 = olf_bulb_10(Nmitral,H0,W0,P_odor1,dam)
#calculate distance measures
print(time.time()-tm1)
for i in np.arange(M):
d1it[m] += 1-Omean1[:,m].dot(Omean2)/(lin.norm(Omean1[:,m])*lin.norm(Omean2))
d2it[m] += 1-lin.norm(Oosci1[:,m].dot(np.conjugate(Oosci2)))/(lin.norm(Oosci1[:,m])*lin.norm(Oosci2))
d3it[m] += (Omeanbar1[m] - Omeanbar2)/(Omeanbar1[m] + Omeanbar2)
d4it[m] += np.real((Ooscibar1[m] - Ooscibar2)/(Ooscibar1[m] + Ooscibar2))
d1it[m] = d1it[m]/M
d2it[m] = d2it[m]/M
d3it[m] = d3it[m]/M
d4it[m] = d4it[m]/M
#calculate spectral density and "wave function" to get average power and IPR
P_den = np.zeros((501,Nmitral)) #only calculate the spectral density from
for i in np.arange(Nmitral): #t=125 to t=250, during the main oscillations
f, P_den[:,i] = signal.periodogram(Sh2[125:250,i],nfft=1000,fs=1000)
psi = np.zeros(Nmitral)
for p in np.arange(Nmitral):
psi[p] = np.sum(P_den[:,p])
psi = psi/np.sqrt(np.sum(psi**2))
psi2 = np.copy(OsciAmp2)
psi2 = psi2/np.sqrt(np.sum(psi2**2))
maxAmp = np.max(OsciAmp2)
pnit[m] = len(OsciAmp2[OsciAmp2>maxAmp/2])
IPRit[m] = 1/np.sum(psi**4)
IPR2it[m] = 1/np.sum(psi2**4)
pwrit[m] = np.sum(P_den)/Nmitral
#get the frequency according to the adiabatic analysis
maxargs = np.argmax(P_den,axis=0)
argf = stats.mode(maxargs[maxargs!=0])
frequencyit[m] = f[argf[0][0]]
# print(cols)
# print(time.time()-tm1)
#
# print('level',lv)
#Get the returned variables for each level of damage
dmgpct1[counter]=damage/Nmitral
IPR1[counter] = np.average(IPRit) #Had to do 1D list, so
pwr1[counter] = np.average(pwrit) #it goes column 0 damage counterl
freq1[counter]=np.average(frequencyit) #0,1,2,3,4...Ndamage-1, then
#col 1 damage level 0,1,2...
# IPRsd[counter]=np.std(IPRit)
# pwrsd[counter]=np.std(pwrit)
# freqsd[counter]=np.std(frequencyit)
IPR2[counter] = np.average(IPR2it)
pn1[counter] = np.average(pnit)
d11[counter]= np.average(d1it)
d21[counter] = np.average(d2it)
d31[counter] = np.average(d3it)
d41[counter] = np.average(d4it)
# d1sd[counter] = np.std(d1it)
# d2sd[counter] = np.std(d2it)
# d3sd[counter]=np.std(d3it)
# d4sd[counter]=np.std(d4it)
eigfreq1[counter] = np.copy(freq2)
if (colnum == 0 or colnum==int(Nmitral/2)):
cell_act[:,:,lv]=np.copy(yout2)
counter+=1
return dmgpct1,eigfreq1,d11,d21,d31,d41,pwr1,IPR1,IPR2,pn1,freq1,cell_act
#save all the data
#******************************************************************************
Ndamage0 = 21 #Recording 0 level damage, too, so it will be 21 levels of damage
counterl = 0 #used to be an iterative variable, but now just a place holder
if __name__ == '__main__':
# dmgpct,eigfreq = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# d1, d1sd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# d2,d2sd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# d3,d3sd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# d4,d4sd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# pwr,pwrsd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# IPR,IPRsd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# freq,freqsd = np.zeros((Ndamage,Nmitral)),np.zeros((Ndamage,Nmitral))
# poolsize = np.copy(Nmitral)
# Ncolumns = np.copy(Nmitral)
Ncolumns = np.copy(Nmitral0)
arrayid = int(os.environ["SLURM_ARRAY_TASK_ID"])
dmgpct,eigfreq,d1,d2,d3,d4,pwr,IPR,IPR2,pn,freq,cell_act = dmg_seed_20_2D(arrayid)
print(time.time()-tm1)
##************For testing the function*********************
#d1,d2,d3,d4 = [0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)]
#pwr,IPR,freq= [0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)]
#d1sd,d2sd,d3sd=[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)]
#d4sd,pwrsd,IPRsd = [0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)],[0 for i in range(Ndamage*Ncols)]
#freqsd,lock = [0 for i in range(Ndamage*Ncols)],0
#lvl,coln,dmgpct = 1,1,[0 for i in range(Ndamage*Ncols)]
#dmg_col_10_1D(lvl,coln,lock,dmgpct,d1,d2,d3,d4,pwr,IPR,freq,d1sd,d2sd,d3sd,d4sd,\
# pwrsd,IPRsd,freqsd)
#******************************************************************************
dmgpctfl,d1fl,d2fl,d3fl,d4fl,IPRfl,pwrfl,frequencyfl,eigfreqfl = "dmgpct","d1",\
"d2","d3","d4","IPR","pwr","frequency","eigfreq"
# d1sdfl,d2sdfl,d3sdfl,d4sdfl,IPRsdfl,pwrsdfl,frequencysdfl = "d1sd",\
# "d2sd","d3sd","d4sd","IPRsd","pwrsd","frequencysd"
IPR2fl,pnfl = "IPR2","pn"
pd_type = "_20_" + str(arrayid)
np.save(d1fl+pd_type,d1),np.save(d2fl+pd_type,d2),np.save(d3fl+pd_type,d3),np.save(d4fl+pd_type,d4)
np.save(IPRfl+pd_type,IPR),np.save(pwrfl+pd_type,pwr)
# np.save(d1sdfl+pd_type,d1sd),np.save(d2sdfl+pd_type,d2sd),np.save(d3sdfl+pd_type,d3sd),np.save(d4sdfl+pd_type,d4sd)
# np.save(IPRsdfl+pd_type,IPRsd),np.save(pwrsdfl+pd_type,pwrsd)
np.save(eigfreqfl+pd_type,eigfreq),np.save(dmgpctfl+pd_type,dmgpct)
np.save(frequencyfl+pd_type,freq)
np.save(IPR2fl+pd_type,IPR2), np.save(pnfl+pd_type,pn)
# np.save(frequencysdfl+pd_type,freqsd)
if arrayid == 0 or arrayid==int(Nmitral0/2):
np.save("cell_act"+pd_type,cell_act) | [
"noreply@github.com"
] | noreply@github.com |
3545e70ca1d77d61f305eff8dd5a893eeea97f75 | d2eb6c904536abf3c66ecd3a67d160285ea32bc4 | /process_image.py | b2439d8bb9ed8695f23a5906c3e53e4671c56fe5 | [] | no_license | peiciwu/CarND-Advanced-Lane-Lines | 7f9fe92c13bbec26b6c1bfc2b6bd933f59d99f06 | 7b2c6933dad2ab19e61cbded0b0e9391c65e45b7 | refs/heads/master | 2021-01-05T08:58:55.470407 | 2017-08-23T07:09:36 | 2017-08-23T07:09:36 | 99,514,760 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 16,740 | py | import numpy as np
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import glob
import os
import collections
from image_processor import ImageProcessor, plotTwo
# Global parameters
ym_per_pixel = 30/720 # meters per pixel in y dimension
xm_per_pixel = 3.7/700 # meters per pixel in x dimension
ploty = np.linspace(0, 719, 720) # y range of image
num_failed_allowed = 10 # max number of consecutive failed frames
num_recent_fits = 10 # max number of the past fits to average
# Use window slding to detect lines
def run_one_image(fname, plot = False, debug = False):
img = mpimg.imread(fname)
name = ' (' + os.path.splitext(os.path.basename(fname))[0] + ')'
# Pre-process all the images: distort, thresholding, and perspective transform
undist = processor.undistort(img)
plotTwo((img, undist), ('Original'+name, 'Undistorted'+name))
thresh = processor.thresholding(undist, debug)
plotTwo((undist, thresh), ('Undistorted'+name, 'Thresholding'+name))
# For debugging, warp on the undistort image.
if debug:
processor.perspective_transform(undist, debug)
warped = processor.perspective_transform(thresh)
plotTwo((thresh, warped), ('Thresholding'+name, 'Warped'+name))
# Use window sliding to find the lines
left_fit, right_fit = find_lane_lines_sliding_window(warped, plot)
if debug:
print(name, ": ", left_fit, ", ", right_fit)
result = draw_lane(img, warped, left_fit, right_fit)
if plot:
plt.title('Detected lane'+name)
plt.imshow(result)
plt.show(block=True)
# Calculate radius_of_curvature
curv = (cal_radius_of_curvature(left_fit) + cal_radius_of_curvature(right_fit))/2
draw_radius_of_curvature(result, curv)
draw_vehicle_position(result, left_fit, right_fit)
if debug:
left_fitx = left_fit[0]*ploty**2 + left_fit[1]*ploty + left_fit[2]
right_fitx = right_fit[0]*ploty**2 + right_fit[1]*ploty + right_fit[2]
diff = right_fitx - left_fitx
min_width = np.min(diff)
max_width = np.max(diff)
cv2.putText(result, 'min_width = ' + str(round(min_width, 3))+' (pixel)',(50,150), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255),2)
cv2.putText(result, 'max_width = ' + str(round(max_width, 3))+' (pixel)',(50,200), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255),2)
print("min_width: ", min_width)
print("max_width: ", max_width)
plt.title('Detected lane with info'+name)
plt.imshow(result)
plt.show(block=True)
def run_all_test_images(imageDir, plot = False, debug = False):
testFiles = glob.glob(imageDir+'/*.jpg')
for fname in testFiles:
run_one_image(fname, plot, debug)
def find_lane_lines_sliding_window(img, plot=False):
# Parameters setting
num_windows = 9
window_height = np.int(img.shape[0]/num_windows)
margin = 80 # widnow width = 2 * margin
min_pixels = 50 # minimum number of pixels found in one window
# Create an output image to draw on and visualize the result
if plot == True:
out_img = np.dstack((img, img, img))*255
# Starting points: The peaks of the histogram at the left half and the right half.
histogram = np.sum(img[img.shape[0]//2:,:], axis=0)
midpoint = np.int(histogram.shape[0]/2)
leftx_current = np.argmax(histogram[:midpoint])
rightx_current = np.argmax(histogram[midpoint:]) + midpoint
# X and y positions where the pixels are nonzero
nonzero = img.nonzero()
nonzeroy = np.array(nonzero[0])
nonzerox = np.array(nonzero[1])
# For pixel found within windows, record the indices to nonzero array
left_lane_indices = []
right_lane_indices = []
for window in range(num_windows):
# Window boundaries
win_y = (img.shape[0] - (window+1)*window_height, img.shape[0] - window*window_height)
win_left_x = (leftx_current - margin, leftx_current + margin)
win_right_x = (rightx_current - margin, rightx_current + margin)
if plot == True:
# Draw the windows
cv2.rectangle(out_img, (win_left_x[0], win_y[0]), (win_left_x[1], win_y[1]), (0, 255, 0), 2)
cv2.rectangle(out_img, (win_right_x[0], win_y[0]), (win_right_x[1], win_y[1]), (0, 255, 0), 2)
# Find nonzero pixels within the window
nonzero_left_indices = ((nonzeroy >= win_y[0]) & (nonzeroy < win_y[1]) & (nonzerox >= win_left_x[0]) & (nonzerox < win_left_x[1])).nonzero()[0]
nonzero_right_indices = ((nonzeroy >= win_y[0]) & (nonzeroy < win_y[1]) & (nonzerox >= win_right_x[0]) & (nonzerox < win_right_x[1])).nonzero()[0]
# Record the indices of nonzero pixels
left_lane_indices.append(nonzero_left_indices)
right_lane_indices.append(nonzero_right_indices)
# Move to the next widnow if > minimum pixels found
if len(nonzero_left_indices) > min_pixels:
leftx_current = np.int(np.mean(nonzerox[nonzero_left_indices]))
if len(nonzero_right_indices) > min_pixels:
rightx_current = np.int(np.mean(nonzerox[nonzero_right_indices]))
# Concatenate the indices array
left_lane_indices = np.concatenate(left_lane_indices)
right_lane_indices = np.concatenate(right_lane_indices)
# Fit a second order polynomial
leftx = nonzerox[left_lane_indices]
lefty = nonzeroy[left_lane_indices]
rightx = nonzerox[right_lane_indices]
righty = nonzeroy[right_lane_indices]
left_fit = np.polyfit(lefty, leftx, 2)
right_fit = np.polyfit(righty, rightx, 2)
# Plot the current fitted polynomial
if plot == True:
# Mark the pixels in the window: left with red, right with blue
out_img[nonzeroy[left_lane_indices], nonzerox[left_lane_indices]] = [255, 0, 0]
out_img[nonzeroy[right_lane_indices], nonzerox[right_lane_indices]] = [0, 0, 255]
plt.imshow(out_img)
# Plot the fitted polynomial
left_fitx = left_fit[0]*ploty**2 + left_fit[1]*ploty + left_fit[2]
right_fitx = right_fit[0]*ploty**2 + right_fit[1]*ploty + right_fit[2]
plt.plot(left_fitx, ploty, color='yellow')
plt.plot(right_fitx, ploty, color='yellow')
plt.xlim(0, img.shape[1])
plt.ylim(img.shape[0], 0)
plt.show(block=True)
return left_fit, right_fit
def find_lane_lines_using_previous_fit(img, left_fit, right_fit, plot=False):
# X and y positions where the pixels are nonzero
nonzero = img.nonzero()
nonzeroy = np.array(nonzero[0])
nonzerox = np.array(nonzero[1])
margin = 100 # widnow width = 2 * margin
# Indices within the margin of the polynomial
left_lane_indices = ((nonzerox > (left_fit[0]*(nonzeroy**2) + left_fit[1]*nonzeroy + left_fit[2]) - margin) &
(nonzerox < (left_fit[0]*(nonzeroy**2) + left_fit[1]*nonzeroy + left_fit[2]) + margin))
right_lane_indices = ((nonzerox > (right_fit[0]*(nonzeroy**2) + right_fit[1]*nonzeroy + right_fit[2]) - margin) &
(nonzerox < (right_fit[0]*(nonzeroy**2) + right_fit[1]*nonzeroy + right_fit[2]) + margin))
# Extract left and right line pixel positions
leftx = nonzerox[left_lane_indices]
lefty = nonzeroy[left_lane_indices]
rightx = nonzerox[right_lane_indices]
righty = nonzeroy[right_lane_indices]
# Fit a second order polynomial
left_fit = np.polyfit(lefty, leftx, 2)
right_fit = np.polyfit(righty, rightx, 2)
if plot == True:
# Create an output image to draw on and visualize the result
out_img = np.dstack((img, img, img))*255
# Mark the pixels in the window: left with red, right with blue
out_img[nonzeroy[left_lane_indices], nonzerox[left_lane_indices]] = [255, 0, 0]
out_img[nonzeroy[right_lane_indices], nonzerox[right_lane_indices]] = [0, 0, 255]
plt.imshow(out_img)
# Generate a polygon to illustrate the search window area
left_fitx = left_fit[0]*ploty**2 + left_fit[1]*ploty + left_fit[2]
right_fitx = right_fit[0]*ploty**2 + right_fit[1]*ploty + right_fit[2]
# And recast the x and y points into usable format for cv2.fillPoly()
left_line_window1 = np.array([np.transpose(np.vstack([left_fitx-margin, ploty]))])
left_line_window2 = np.array([np.flipud(np.transpose(np.vstack([left_fitx+margin, ploty])))])
left_line_pts = np.hstack((left_line_window1, left_line_window2))
right_line_window1 = np.array([np.transpose(np.vstack([right_fitx-margin, ploty]))])
right_line_window2 = np.array([np.flipud(np.transpose(np.vstack([right_fitx+margin, ploty])))])
right_line_pts = np.hstack((right_line_window1, right_line_window2))
# window img
window_img = np.zeros_like(out_img)
# Draw the lane onto the window image
cv2.fillPoly(window_img, np.int_([left_line_pts]), (0,255, 0))
cv2.fillPoly(window_img, np.int_([right_line_pts]), (0,255, 0))
result = cv2.addWeighted(out_img, 1, window_img, 0.3, 0)
plt.imshow(result)
plt.plot(left_fitx, ploty, color='yellow')
plt.plot(right_fitx, ploty, color='yellow')
plt.xlim(0, img.shape[1])
plt.ylim(img.shape[0], 0)
plt.show(block=True)
return left_fit, right_fit
def draw_lane(img, warped, left_fit, right_fit):
warp_zero = np.zeros_like(warped).astype(np.uint8)
if img.shape[2] == 3:
color_warp = np.dstack((warp_zero, warp_zero, warp_zero))
else:
# Images dumped from video have 4 channels.
color_warp = np.dstack((warp_zero, warp_zero, warp_zero, warp_zero))
left_fitx = left_fit[0]*ploty**2 + left_fit[1]*ploty + left_fit[2]
right_fitx = right_fit[0]*ploty**2 + right_fit[1]*ploty + right_fit[2]
# Recast the x and y points into usable format for cv2.fillPoly()
pts_left = np.array([np.transpose(np.vstack([left_fitx, ploty]))])
pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fitx, ploty])))])
pts = np.hstack((pts_left, pts_right))
# Draw the lane onto the warped blank image
cv2.fillPoly(color_warp, np.int_([pts]), (0,255, 0))
cv2.polylines(color_warp, np.int32([pts_left]), isClosed=False, color=(255, 0, 0), thickness=20)
cv2.polylines(color_warp, np.int32([pts_right]), isClosed=False, color=(0, 0, 255), thickness=20)
# Warp the blank back to original image space using inverse perspective matrix (Minv)
new_warp = cv2.warpPerspective(color_warp, processor.invM, (warped.shape[1], warped.shape[0]))
# Combine the result with the original image
result = cv2.addWeighted(img, 1, new_warp, 0.3, 0)
return result
# Define a class to receive the characteristics of each line detection
class Line:
def __init__(self):
# polynomial coefficients for the most recent fit
self.current_fit = None
# x values of the last n fits of the line
self.recent_xfitted = collections.deque(maxlen=num_recent_fits)
# polynomial coefficients averaged over the last n iterations
self.best_fit = None
# radius of curvature of the best fit
self.radius_of_curvature = None
# frame number in the video
self.frame_counter = -1
# number of consecutive failed frames
self.num_failed = 0
def add_fit(self, fit, valid_line):
self.frame_counter += 1
if not valid_line:
self.num_failed += 1
else:
self.current_fit = fit
fitx = fit[0]*ploty**2 + fit[1]*ploty + fit[2]
self.recent_xfitted.append(fitx)
avg_fitx = np.average(self.recent_xfitted, axis=0)
self.best_fit = np.polyfit(ploty, avg_fitx, 2)
self.radius_of_curvature = cal_radius_of_curvature(self.best_fit)
def do_slide_window(self):
if self.best_fit == None:
return True # Start from scratch
if self.num_failed >= num_failed_allowed:
self.reset()
return True
return False
def reset(self):
self.current_fit = None
self.best_fit = None
self.radius_of_curvature = None
self.num_of_faileds = 0
def check_line(self, fit):
# Check radius_ofcurvature change
curverad = cal_radius_of_curvature(fit)
change = abs(curverad - self.radius_of_curvature)/self.radius_of_curvature
if change > 0.3:
return False
# Check diff of polynomial cofficients between \fit and the best fit
diff = abs(fit - self.best_fit)
if diff[0] > 0.001 or diff[1] > 1 or diff[2] > 100:
return False
return True
def cal_radius_of_curvature(fit):
fitx = fit[0]*ploty**2 + fit[1]*ploty + fit[2]
# Fit new polynomials to x, y in world space
fit_cr = np.polyfit(ploty * ym_per_pixel, fitx * xm_per_pixel, 2)
y_eval = np.max(ploty)
curverad = ((1 + (2*fit_cr[0]*y_eval*ym_per_pixel + fit_cr[1])**2)**1.5) / np.absolute(2*fit_cr[0])
return curverad
# Draw radius of curvature on the result image
def draw_radius_of_curvature(img, curv):
cv2.putText(img, 'Radius of curvature = ' + str(round(curv, 3))+' m',(50,50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255),2)
# Draw vehicle position from the center of the lane
def draw_vehicle_position(img, left_fit, right_fit):
left_bottom = left_fit[0]*ploty[-1]**2 + left_fit[1]*ploty[-1] + left_fit[2]
right_bottom = right_fit[0]*ploty[-1]**2 + right_fit[1]*ploty[-1] + right_fit[2]
lane_center = (left_bottom + right_bottom) / 2
vehicle_pos = img.shape[1]/2
diff = (vehicle_pos - lane_center) * xm_per_pixel
l_or_r = ' left' if diff < 0 else ' right'
cv2.putText(img, 'Vehicle position : ' + str(abs(round(diff, 3)))+' m'+l_or_r+' of center',(50,100), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255),2)
def process_image(img, plot = False, dump = False):
undist = processor.undistort(img)
thresh = processor.thresholding(undist)
warped = processor.perspective_transform(thresh)
if left_line.do_slide_window() or right_line.do_slide_window():
left_fit, right_fit = find_lane_lines_sliding_window(warped, plot)
else:
left_fit, right_fit = find_lane_lines_using_previous_fit(warped, left_line.current_fit, right_line.current_fit, plot)
valid_lane = check_lane(left_fit, right_fit)
left_line.add_fit(left_fit, valid_lane)
right_line.add_fit(right_fit, valid_lane)
# Draw the best fit
result = draw_lane(img, warped, left_line.best_fit, right_line.best_fit)
draw_radius_of_curvature(result,
(left_line.radius_of_curvature+right_line.radius_of_curvature)/2)
draw_vehicle_position(result, left_line.best_fit, right_line.best_fit)
if dump:
filename = "./video_frames_images/" + str(left_line.frame_counter) + ".jpg"
mpimg.imsave(filename, img)
filename = "./video_frames_processed_images/" + str(left_line.frame_counter) + ".jpg"
mpimg.imsave(filename, result)
if plot == True:
plt.imshow(result)
plt.show(block=True)
return result
def check_width(left_fit, right_fit):
# Check lane width
left_fitx = left_fit[0]*ploty**2 + left_fit[1]*ploty + left_fit[2]
right_fitx = right_fit[0]*ploty**2 + right_fit[1]*ploty + right_fit[2]
diff = right_fitx - left_fitx
min_width = np.min(diff)
max_width = np.max(diff)
if min_width < 550 or max_width > 850: # 550 <= valid lane width <= 850
return False
return True
def check_lane(left_fit, right_fit):
if left_line.best_fit == None or right_line.best_fit == None:
return True # Take whatever we have right now
if not check_width(left_fit, right_fit):
return False
if not left_line.check_line(left_fit):
return False
if not right_line.check_line(right_fit):
return False
return True
def process_video(in_name, out_name, plot = False, dump = False):
from moviepy.editor import VideoFileClip
output1 = './project_video_processed.mp4'
clip1 = VideoFileClip("./project_video.mp4")
processed_clip1 = clip1.fl_image(process_image) #NOTE: this function expects color images!!
processed_clip1.write_videofile(output1, audio=False)
MODE = 1 # 1 - Images, 2 - Videos
processor = ImageProcessor()
if MODE == 1:
run_all_test_images('./test_images', plot=True, debug=False)
#run_all_test_images('./my_test_images/other_types_test_images/', plot=True, debug=True)
#run_all_test_images('./my_test_images', plot=True, debug=True)
elif MODE == 2:
left_line = Line()
right_line = Line()
process_video('./project_video.mp4', 'project_video_processed.mp4')
| [
"peiciwu@gmail.com"
] | peiciwu@gmail.com |
d509eed695ce2b3e20d2b819a42172b2c95fccab | 4e04db11d891f869a51adf0e0895999d425f29f6 | /portalbackend/lendapi/v1/accounts/permissions.py | d03cc4c6a2749a8264b3b36768a2678d71de1192 | [] | no_license | mthangaraj/ix-ec-backend | 21e2d4b642c1174b53a86cd1a15564f99985d23f | 11b80dbd665e3592ed862403dd8c8d65b6791b30 | refs/heads/master | 2022-12-12T12:21:29.237675 | 2018-06-20T13:10:21 | 2018-06-20T13:10:21 | 138,033,811 | 0 | 0 | null | 2022-06-27T16:54:14 | 2018-06-20T13:04:22 | JavaScript | UTF-8 | Python | false | false | 4,807 | py | import json
import re
from rest_framework import permissions, status
from rest_framework.exceptions import APIException
from portalbackend.validator.errormapping import ErrorMessage
from portalbackend.validator.errorcodemapping import ErrorCode
from django.utils.deprecation import MiddlewareMixin
from datetime import datetime, timedelta
from portalbackend.lendapi.accounts.models import UserSession,CompanyMeta
from re import sub
from oauth2_provider.models import AccessToken
from portalbackend.lendapi.v1.accounting.utils import Utils
from django.http import JsonResponse
from django.utils.timezone import utc
from portalbackend.lendapi.constants import SESSION_EXPIRE_MINUTES, SESSION_SAVE_URLS
class IsAuthenticatedOrCreate(permissions.IsAuthenticated):
def has_permission(self, request, view):
if request.method == 'POST':
return True
return super(IsAuthenticatedOrCreate, self).has_permission(request, view)
class ResourceNotFound(APIException):
status_code = status.HTTP_404_NOT_FOUND
default_detail = {"message": ErrorMessage.RESOURCE_NOT_FOUND, "status": "failed"}
class UnauthorizedAccess(APIException):
status_code = status.HTTP_401_UNAUTHORIZED
default_detail = {"message": ErrorMessage.UNAUTHORIZED_ACCESS, "status": "failed"}
class IsCompanyUser(permissions.IsAuthenticated):
message = {"message": ErrorMessage.UNAUTHORIZED_ACCESS, "status": "failed"}
def has_permission(self, request, view):
try:
split_url = request.META.get('PATH_INFO').split("/")
if split_url[3] == "docs":
return request.user.is_authenticated()
if len(view.kwargs) == 0 or split_url[3] != "company":
if request.user.is_superuser:
return request.user and request.user.is_authenticated()
else:
raise UnauthorizedAccess
is_valid_company, message = Utils.check_company_exists(view.kwargs["pk"])
if not is_valid_company:
raise ResourceNotFound
if request.user.is_superuser:
return request.user and request.user.is_authenticated()
else:
return ((request.user.is_superuser or request.user.company.id == int(
view.kwargs["pk"])) and request.user.is_authenticated())
except APIException as err:
raise err
class SessionValidator(MiddlewareMixin):
def process_request(self, request):
try:
session_save_urls = SESSION_SAVE_URLS
request_api_url = request.META.get('PATH_INFO')
for url in session_save_urls:
if re.search(url, request_api_url):
return
header_token = request.META.get('HTTP_AUTHORIZATION', None)
if header_token is not None:
token = sub('Token ', '', request.META.get('HTTP_AUTHORIZATION', None))
token = token.split(' ')
token_obj = AccessToken.objects.get(token=token[1])
user = token_obj.user
meta = CompanyMeta.objects.get(company = user.company)
if meta is not None and meta.monthly_reporting_sync_method == 'QBD':
return
try:
user_session = UserSession.objects.get(user=user)
if user_session:
if user_session.is_first_time:
user_session.is_first_time = False
user_session.auth_key = token_obj
if user_session.auth_key == token_obj:
now = datetime.utcnow().replace(tzinfo=utc)
if user_session.end_time > now:
user_session.end_time = now + timedelta(minutes=SESSION_EXPIRE_MINUTES)
user_session.save()
else:
user_session.delete()
return JsonResponse(
{'error': ErrorMessage.SESSION_EXPRIED, 'code': ErrorCode.SESSION_EXPRIED},
status=401)
else:
return JsonResponse(
{'error': ErrorMessage.SESSION_ALREADY_ACTIVE,
'code': ErrorCode.SESSION_ALREADY_ACTIVE},
status=401)
except UserSession.DoesNotExist:
return JsonResponse({'error': ErrorMessage.SESSION_EXPRIED, 'code': ErrorCode.SESSION_EXPRIED},
status=401)
except Exception as e:
print(e)
return | [
"thangaraj.matheson@ionixxtech.com"
] | thangaraj.matheson@ionixxtech.com |
76d246ae50464e8ce26b99f4892ebf619b0fd6bd | 0d98a09a81bdcead13e6020877380a4e7e6b5d74 | /fizyka/pyfiz.py | 2bdca7ea555847122d2cad6111eb675dc7d39be6 | [] | no_license | pawelsag/Studies | e7f56b823fdf5d7aa438c6dfb41f0d617718576e | 34c2e8a786df59ce18c8dbf9f4476d891a456fe1 | refs/heads/master | 2020-04-04T14:29:38.184527 | 2020-01-11T08:16:45 | 2020-01-11T08:16:45 | 156,000,522 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 710 | py | import math
# data amount
n = 12
tau = 0.0
fiY = 0.0
delA =0.0
delB =0.0
with open("fiz.txt", "r") as f:
# get A, B coefficients
A,B = f.readline().split(',')
A = float(A)
B = float(B)
# get measured values x,y
data = []
for line in f:
x,y = line.split(' ')
data.append( ( float(x),float(y) ) )
# calculate tau
v1 = 0.0
v2 = 0.0
for x,y in data:
v1 += x**2
v2 += x
tau = (n*(v1)) - (v2**2)
for x,y in data:
fiY += (y - A*x -B)**2
print("SUMA(epislon^2)=",fiY)
fiY = math.sqrt(fiY/(n-2))
delA = fiY*math.sqrt(n/tau)
delB = fiY*math.sqrt(v1/tau)
print("n =",n )
print("tau=",tau )
print("fiY=",fiY)
print("v1=",v1)
print("delA =", delA)
print("delB =", delB)
| [
"sagan.pawel1000@gmail.com"
] | sagan.pawel1000@gmail.com |
c2e0941d1ce77fcbec7429f96196816cf290fd15 | 99d8cdf79898b5dabd2b80340d9b90e78831a3b7 | /handlers/helper.py | dcec79c00fe8067c52bf0d4dd66f856d3e0767c5 | [] | no_license | crazcarl/gridironguessinggame | 99fa021f1ce8e946d68e8524317b5e969510a7e7 | 517596dbec03c6f2126fbbbe08e4ce9d0ea90467 | refs/heads/master | 2021-01-01T17:16:05.986335 | 2015-10-20T01:29:47 | 2015-10-20T01:29:47 | 16,240,124 | 0 | 0 | null | 2014-01-29T04:19:25 | 2014-01-25T21:16:50 | Python | UTF-8 | Python | false | false | 2,547 | py | def teamToLong(input):
if input=="NYG":
return "NY Giants"
if input=="WAS":
return "Washington"
if input=="BAL":
return "Baltimore"
if input=="CAR":
return "Carolina"
if input=="CHI":
return "Chicago"
if input=="GB":
return "Green Bay"
if input=="HOU":
return "Houston"
if input=="BUF":
return "Buffalo"
if input=="IND":
return "Indianapolis"
if input=="TEN":
return "Tennessee"
if input=="NYJ":
return "NY Jets"
if input=="DET":
return "Detroit"
if input=="OAK":
return "Oakland"
if input=="MIA":
return "Miami"
if input=="PIT":
return "Pittsburgh"
if input=="TB":
return "Tampa Bay"
if input=="SD":
return "San Diego"
if input=="JAC":
return "Jacksonville"
if input=="MIN":
return "Minnesota"
if input=="ATL":
return "Atlanta"
if input=="SF":
return "San Francisco"
if input=="PHI":
return "Philadelphia"
if input=="DAL":
return "Dallas"
if input=="NO":
return "New Orleans"
if input=="KC":
return "Kansas City"
if input=="NE":
return "New England"
if input=="STL":
return "St. Louis"
if input=="CLE":
return "Cleveland"
if input=="DEN":
return "Denver"
if input=="ARI":
return "Arizona"
if input=="CIN":
return "Cincinnati"
if input=="SEA":
return "Seattle"
return "OTHER"
def teamToShort(input):
if input=="NY Giants":
return "NYG"
if input=="Washington":
return "WAS"
if input=="Baltimore":
return "BAL"
if input=="Carolina":
return "CAR"
if input=="Chicago":
return "CHI"
if input=="Green Bay":
return "GB"
if input=="Houston":
return "HOU"
if input=="Buffalo":
return "BUF"
if input=="Indianapolis":
return "IND"
if input=="Tennessee":
return "TEN"
if input=="NY Jets":
return "NYJ"
if input=="Detroit":
return "DET"
if input=="Oakland":
return "OAK"
if input=="Miami":
return "MIA"
if input=="Pittsburgh":
return "PIT"
if input=="Tampa Bay":
return "TB"
if input=="San Diego":
return "SD"
if input=="Jacksonville":
return "JAC"
if input=="Minnesota":
return "MIN"
if input=="Atlanta":
return "ATL"
if input=="San Francisco":
return "SF"
if input=="Philadelphia":
return "PHI"
if input=="Dallas":
return "DAL"
if input=="New Orleans":
return "NO"
if input=="Kansas City":
return "KC"
if input=="New England":
return "NE"
if input=="St. Louis":
return "STL"
if input=="Cleveland":
return "CLE"
if input=="Denver":
return "DEN"
if input=="Arizona":
return "ARI"
if input=="Cincinnati":
return "CIN"
if input=="Seattle":
return "SEA"
return "OTHER" | [
"crazcarl@gmail.com"
] | crazcarl@gmail.com |
4e0e5d6bdbe92c957594f844fe1240c99f90303c | 25cb3605e3239f41ca73e860c65fddf63c887924 | /src/Calculator.py | 7e16169da3ceeeb37f5174a0e53d7dd28ecf1c4c | [
"MIT"
] | permissive | Ayush6459/Simple_Calculator_package | 8dacc5ee345e8efcd01456288f77c3adb1ac95ea | 8c7260ed8e91def3bf0964798b716e1305433872 | refs/heads/master | 2023-04-25T10:56:36.308773 | 2021-05-14T10:41:35 | 2021-05-14T10:41:35 | 367,270,133 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 192 | py | def add_num(num1, num2):
return num1+num2
def sub_num(num1,num2):
return num1-num2
def multi_num(num1, num2):
return num1*num2
def div_num(num1,num2):
return num1/num2
| [
"ayushranjan6459@gmail.com"
] | ayushranjan6459@gmail.com |
702dc360e83014136e7a9d53ebe06f992815b006 | ebf6463d4e520429a24d1fd34375d3302b245346 | /net/modifire/PStats.py | 3ca2c2ffd73208b91bc45b11b48128de21450347 | [] | no_license | czorn/Modifire | 6f8c8f2d679c7be7618607e1b46a3a019f09b918 | 77f2cdff0214468482a98ca92c7a2d548d77f3d9 | refs/heads/master | 2020-12-24T14:26:53.286484 | 2013-10-22T18:54:26 | 2013-10-22T18:54:26 | 3,159,644 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 915 | py |
#import direct.directbase.DirectStart
def pstat(func):
from pandac.PandaModules import PStatCollector
collectorName = "Debug:%s" % func.__name__
if hasattr(base, 'custom_collectors'):
if collectorName in base.custom_collectors.keys():
pstat = base.custom_collectors[collectorName]
else:
base.custom_collectors[collectorName] = PStatCollector(collectorName)
pstat = base.custom_collectors[collectorName]
else:
base.custom_collectors = {}
base.custom_collectors[collectorName] = PStatCollector(collectorName)
pstat = base.custom_collectors[collectorName]
def doPstat(*args, **kargs):
pstat.start()
returned = func(*args, **kargs)
pstat.stop()
return returned
doPstat.__name__ = func.__name__
doPstat.__dict__ = func.__dict__
doPstat.__doc__ = func.__doc__
return doPstat | [
"chrismzorn@gmail.com"
] | chrismzorn@gmail.com |
3452b41fdad457f398c9c0dc90e7f1a6f36d42ff | 8fbafbd67689c487615ed4b08db835457b67ea52 | /demo_python_backend_files/sparse_feature_selection_methods.py | 061fa59e3d9473a7298ccecc67f959cd9834112a | [] | no_license | RezaBorhani/RezaBorhani.github.io | c8939e2f3484a7e5f3f0b4b9199c9d90ca51bf78 | ca23e5288f7ac8aab80559192fbf4fa6f3aeb20f | refs/heads/master | 2021-01-21T06:39:02.122817 | 2017-07-21T01:31:43 | 2017-07-21T01:31:43 | 82,868,389 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,878 | py | import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import matplotlib.patches as mpatches
def plot_genes(X, gene_id_1, gene_id_2):
N = X.shape[1]/2
plt.xlabel('gene #'+str(gene_id_1))
plt.ylabel('gene #'+str(gene_id_2))
red_patch = mpatches.Patch(color='red', label='healthy')
blue_patch = mpatches.Patch(color='blue', label='afflicted')
plt.legend(handles=[red_patch, blue_patch])
plt.legend(handles=[red_patch, blue_patch], loc = 2)
ax = plt.scatter(X[gene_id_1+1,0:N], X[gene_id_2+1,0:N], color='r', s=30) #plotting the data
plt.scatter(X[gene_id_1+1,N+1:2*N], X[gene_id_2+1,N+1:2*N], color='b', s=30)
plt.show()
return
def plot_weights(w, gene_id_1, gene_id_2):
plt.figure(figsize=(20,5))
plt.xlabel('genes')
plt.ylabel('learned weights')
plt.bar(np.arange(0,len(w)), w, color='grey', alpha=.5)
plt.bar([gene_id_1, gene_id_2],[w[gene_id_1], w[gene_id_2]], color='k', alpha=.7)
plt.show()
return
def compute_grad(X, y, w):
#produce gradient for each class weights
grad = 0
for p in range(0,len(y)):
x_p = X[:,p]
y_p = y[p]
grad+= -1/(1 + np.exp(y_p*np.dot(x_p.T,w)))*y_p*x_p
grad.shape = (len(grad),1)
return grad
def L1_logistic_regression(X, y, lam):
# initialize weights - we choose w = random for illustrative purposes
w = np.zeros((X.shape[0],1))
# set maximum number of iterations and step length
alpha = 1
max_its = 2000
# make list to record weights at each step of algorithm
w_history = np.zeros((len(w),max_its+1))
w_history[:,0] = w.flatten()
# gradient descent loop
for k in range(1,max_its+1):
# form gradient
grad = compute_grad(X,y,w)
# take gradient descent step
w = w - alpha*grad
# take a proximal step
w[1:] = proximal_step(w[1:], lam)
# save new weights
w_history[:,k] = w.flatten()
# return weights from each step
return w_history[1:,-1]
def proximal_step(w, lam):
return np.maximum(np.abs(w) - 2*lam,0)*np.sign(w)
def logistic_regression(X, y):
# initialize weights - we choose w = random for illustrative purposes
w = np.zeros((X.shape[0],1))
# set maximum number of iterations and step length
alpha = 1
max_its = 2000
# make list to record weights at each step of algorithm
w_history = np.zeros((len(w),max_its+1))
w_history[:,0] = w.flatten()
# gradient descent loop
for k in range(1,max_its+1):
# form gradient
grad = compute_grad(X,y,w)
# take gradient descent step
w = w - alpha*grad
# save new weights
w_history[:,k] = w.flatten()
# return weights from each step
return w_history[1:,-1]
| [
"rezaborhani@Rezas-MacBook-Pro.local"
] | rezaborhani@Rezas-MacBook-Pro.local |
29c4cee2c425d08ec436f41058b807836271e49a | 89e53cff0ab14d22511157e1b6ed877790a862e1 | /posegan/code/param.py | d0417371a71487157f112356d4d9cf1aff3feb44 | [] | no_license | dahburj/deepcoaching | 96d6cabe120043f4ebf6bfb0e425b38d94213b54 | 535e0a374666f7815f6cf5c20eb05f455871ff38 | refs/heads/master | 2020-06-13T23:59:01.781604 | 2019-06-11T00:51:58 | 2019-06-11T00:51:58 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,510 | py | """
Various important parameters of our model and training procedure.
"""
def get_general_params():
param = {}
dn = 1
param['IMG_HEIGHT'] = int(256/dn)
param['IMG_WIDTH'] = int(256/dn)
param['obj_scale_factor'] = 1.14/dn
param['scale_max'] = 1.05 # Augmentation scaling
param['scale_min'] = 0.95
param['max_rotate_degree'] = 5
param['max_sat_factor'] = 0.05
param['max_px_shift'] = 5
param['posemap_downsample'] = 2
param['sigma_joint'] = 7/4.0
param['n_joints'] = 14
param['n_limbs'] = 10
# Using MPII-style joints: head (0), neck (1), r-shoulder (2), r-elbow (3), r-wrist (4), l-shoulder (5),
# l-elbow (6), l-wrist (7), r-hip (8), r-knee (9), r-ankle (10), l-hip (11), l-knee (12), l-ankle (13)
param['limbs'] = [[0, 1], [2, 3], [3, 4], [5, 6], [6, 7], [8, 9], [9, 10], [11, 12], [12, 13], [2, 5, 8, 11]]
# Using OpenPose joints: Nose (0), Neck (1), RShoulder (2), RElbow (3), RWrist (4), LShoulder (5),
# LElbow (6), LWrist (7), r-hip (8), r-knee (9), r-ankle (10), l-hip (11), l-knee (12), l-ankle (13)
param['limbs'] = [[0, 1], [2, 3], [3, 4], [5, 6], [6, 7], [8, 9], [9, 10], [11, 12], [12, 13], [2, 5, 8, 11]]
param['n_training_iter'] = 200000
param['test_interval'] = 5
param['model_save_interval'] = 200
param['project_dir'] = '..'
param['model_save_dir'] = param['project_dir'] + '/models/'
param['data_dir'] = param['project_dir'] + '/data/'
param['batch_size'] = 8
return param
| [
"chuanqi.chen@gmail.com"
] | chuanqi.chen@gmail.com |
65c21d782d2fdb0fa84bfc14127e2a04d4bf7534 | 0a66dcbf1f96676ccca588191f940c798d15eebb | /DRL_data/data_labeling.py | 8c24d935ce6b438655dfe8441f251cae7f85c637 | [] | no_license | Fence/Documents | 5e498203f2b2363b98441ecba0e2eadc74aaec4d | d5874fae9cb6618d275fcc9ea303a2c68e331f52 | refs/heads/master | 2020-03-11T07:02:33.351230 | 2018-05-14T14:55:40 | 2018-05-14T14:55:40 | 129,847,147 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 49,850 | py | import re
import os
import sys
import ipdb
import time
import json
import pickle
from tqdm import tqdm
class QuitProgram(Exception):
def __init__(self, message='Quit the program.\n'):
Exception.__init__(self)
self.message = message
class TextParsing(object):
"""docstring for TextParsing"""
def __init__(self):
from nltk.stem import WordNetLemmatizer
from nltk.parse.stanford import StanfordDependencyParser
core = '/home/fengwf/stanford/stanford-corenlp-3.7.0.jar'
model = '/home/fengwf/stanford/english-models.jar'
self.dep_parser = StanfordDependencyParser(path_to_jar=core, path_to_models_jar=model,
encoding='utf8', java_options='-mx2000m')
self.lemma = WordNetLemmatizer()
def build_vocab(self, save_name):
# e.g. save_name = 'wikihow/wikihow_act_seq.pkl'
with open(save_name, 'rb') as f:
data = pickle.load(f)
word_dict = {}
verb_dict = {}
objs_dict = {}
for text in data:
for act, objs in text['act_seq']:
act = act.lower()
if act not in word_dict:
word_dict[act] = 1
else:
word_dict[act] += 1
if act not in verb_dict:
verb_dict[act] = 1
else:
verb_dict[act] += 1
for obj in objs.split('_'):
if obj not in word_dict:
word_dict[obj] = 1
else:
word_dict[obj] += 1
if obj not in objs_dict:
objs_dict[obj] = 1
else:
objs_dict[obj] += 1
ipdb.set_trace()
words = sorted(word_dict.items(), key=lambda x:x[1], reverse=True)
verbs = sorted(verb_dict.items(), key=lambda x:x[1], reverse=True)
objs = sorted(objs_dict.items(), key=lambda x:x[1], reverse=True)
print(len(word_dict), len(verb_dict), len(objs_dict))
def stanford_find_vp_details(self, indata_name, outdata_name):
data = []
with open(indata_name, 'rb') as f0:
indata = pickle.load(f0)[-1]
if os.path.exists('%s.pkl' % outdata_name):
print('Loading data...')
data = pickle.load(open('%s.pkl' % outdata_name, 'rb'))
print('len(data) = %d' % len(data))
try:
count = 0
for cate in indata:
print(cate)
for page in indata[cate]:
if 'detail' not in page:
continue
for detail in page['detail']:
count += 1
if count <= len(data):
continue
tmp_data = {'title': page['title']}
tmp_data['sent'] = []
tmp_data['act_seq'] = []
tmp_data['dep_conll'] = []
sents = []
for step in detail:
text = re.sub(r'\[.*\]|/', '', step)
text = re.sub(r'[\n\r]', ' ', text)
tmp_sents = re.split(r'\. |\? |\! ', text)
for s in tmp_sents:
if len(s.strip().split()) > 1:
sents.append(s.strip())
try:
dep = self.dep_parser.raw_parse_sents(sents)
except AssertionError:
print('Raise AssertionError')
sents = [' '.join(re.findall(r'[\w\'\.]+', s)) for s in sents]
try:
dep = self.dep_parser.raw_parse_sents(sents)
except Exception as e:
print(e)
continue
except Exception as e:
print(e)
continue
for j in range(len(sents)):
try:
dep_root = next(dep)
dep_sent = next(dep_root)
except StopIteration:
print('j = %d len(sents) = %d Raise StopIteration.\n' % (j, len(sents)))
break
conll = [_.split() for _ in str(dep_sent.to_conll(10)).split('\n') if _]
words = []
idx2word = {}
for w in conll:
idx2word[w[0]] = w[1]
words.append(w[1])
tmp_data['sent'].append(' '.join(words))
#tmp_data['dep_conll'].append(conll)
for line in conll:
if 'dobj' in line or 'nsubjpass' in line:
obj = [line[1]]
obj_idxs = [line[0]]
verb_idx = line[6]
for one_line in conll:
if one_line[6] == obj_idxs[0] and one_line[7] == 'conj':
obj.append(one_line[1])
obj_idxs.append(one_line[0])
act = idx2word[verb_idx].lower()
act_obj_pair = (act, '_'.join(obj))
tmp_data['act_seq'].append(act_obj_pair)
data.append(tmp_data)
print(len(data), page['title'])
if len(data) % 2000 == 0:
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data)
print('Successfully save %s\n' % outdata_name)
elif len(data) % 1000 == 0:
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data, False)
print('Successfully save %s\n' % outdata_name)
except KeyboardInterrupt:
print('Manually keyboard interrupt!\n')
except Exception as e:
print(e)
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data)
print('Successfully save %s\n' % outdata_name)
def stanford_find_vp(self, indata_name, outdata_name):
num_texts = 124 # 96 #
source = 'wikihow/new_details/' #'ehow/out_data/' # 'cooking/out_data/' #
#save_name = 'wikihow/wikihow_act_seq_100k' # 'ehow/ehow_act_seq' # 'cooking/cooking_act_seq' #
data = []
#ipdb.set_trace()
with open(indata_name, 'rb') as f0:
indata = pickle.load(f0)[-1]
if os.path.exists('%s.pkl' % outdata_name):
print('Loading data...')
data = pickle.load(open('%s.pkl' % outdata_name, 'rb'))
print('len(data) = %d' % len(data))
#for i in range(num_texts):
#for name in os.listdir(source):
try:
count = 0
for cate in indata:
print(cate)
for page in indata[cate]:
if 'sub_task' not in page:
continue
for sub_task in page['sub_task']:
count += 1
if count <= len(data):
continue
text = '\n'.join(sub_task)
tmp_data = {'title': page['title']}
tmp_data['sent'] = []
tmp_data['act_seq'] = []
tmp_data['dep_conll'] = []
#fname = '%s%d.txt' % (source, i + 1)
#fname = source + name
#print(fname)
#try:
#text = open(fname).read()
text = re.sub(r'/', ' ', text)
sents = text.split('\n') #.readlines()
try:
dep = self.dep_parser.raw_parse_sents(sents)
except AssertionError:
#print('\n', sents)
print('Raise AssertionError')
sents = [' '.join(re.findall(r'[\w\'\.]+', s)) for s in sents]
#print(sents, '\n')
try:
dep = self.dep_parser.raw_parse_sents(sents)
except Exception as e:
print(e)
continue
except Exception as e:
print(e)
continue
for j in range(len(sents)):
try:
dep_root = next(dep)
dep_sent = next(dep_root)
except StopIteration:
print('j = %d len(sents) = %d Raise StopIteration.\n' % (j, len(sents)))
break
conll = [_.split() for _ in str(dep_sent.to_conll(10)).split('\n') if _]
words = []
idx2word = {}
for w in conll:
idx2word[w[0]] = w[1]
#word_lemma = self.lemma.lemmatize(w[1])
#if word_lemma == 'pythonly':
# word_lemma = w[1]
words.append(w[1]) #word_lemma
tmp_data['sent'].append(' '.join(words))
tmp_data['dep_conll'].append(conll)
for line in conll:
if 'dobj' in line or 'nsubjpass' in line:
obj = [line[1]]
obj_idxs = [line[0]]
verb_idx = line[6]
for one_line in conll:
if one_line[6] == obj_idxs[0] and one_line[7] == 'conj':
obj.append(one_line[1])
obj_idxs.append(one_line[0])
# lemmatize, find the original word of action
act = idx2word[verb_idx].lower()
act_obj_pair = (act, '_'.join(obj))
tmp_data['act_seq'].append(act_obj_pair)
data.append(tmp_data)
print(len(data), page['title'])
if len(data) % 2000 == 0:
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data)
print('Successfully save %s\n' % outdata_name)
elif len(data) % 1000 == 0:
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data, False)
print('Successfully save %s\n' % outdata_name)
except KeyboardInterrupt:
print('Manually keyboard interrupt!\n')
except Exception as e:
print(e)
print('len(data): %d, try to save file.' % len(data))
self.save_txt_and_pkl(outdata_name, data)
print('Successfully save %s' % outdata_name)
def get_labeled_win2k(self):
text = open('win2k/window2k_annotations.txt').read()
articles = text.split('-------------------------------------------------')[1:]
data = []
#ipdb.set_trace()
for article in articles:
tmp_data = {}
tmp_data['sent'] = []
tmp_data['act_seq'] = []
lines = article.split('\n')
for line in lines:
if line.startswith('article', 4):
print(line.strip())
elif line.startswith('c:', 9):
pass
elif line.startswith('- ', 9) or line.startswith('~ ', 9):
a = re.split(r'\([\w\-\/\:]*\)', line)
assert len(a) >= 2
act = re.findall(r'\w+', a[0])
obj = re.findall(r'\w+', a[1])
if len(act) == 0 or len(obj) == 0:
ipdb.set_trace()
act = self.lemma.lemmatize('_'.join(act).lower(), pos='v')
obj = '_'.join(obj).lower()
act_obj_pair = (act, obj)
tmp_data['act_seq'].append(act_obj_pair)
elif len(line.strip()):
tmp_data['sent'].append(line.strip())
if len(tmp_data['act_seq']) == 0:
ipdb.set_trace()
data.append(tmp_data)
self.save_txt_and_pkl('win2k/win2k_act_seq', data, True, protocol=2)
def save_txt_and_pkl(self, fname, data, save_txt=False, protocol=3):
with open('%s.pkl'%fname, 'wb') as f1:
pickle.dump(data, f1, protocol=protocol)
if save_txt:
with open('%s.txt'%fname, 'w') as f0:
count = 0
for d in data:
count += 1
if 'title' in d:
try:
f0.write('<Article %d>: %s\n' % (count, d['title']))
except Exception as e:
print('An error occurs in saving file', e)
else:
try:
f0.write('<Article %d>: \n' % count)
except Exception as e:
print('An error occurs in saving file', e)
for i, s in enumerate(d['sent']):
try:
f0.write('<Sentence %d>: %s\n' % (i, s))
except Exception as e:
print('An error occurs in saving file', e)
f0.write('\n')
for j, (act, obj) in enumerate(d['act_seq']):
try:
f0.write('<Action %d>: %s %s\n' % (j, act, obj))
except Exception as e:
print('An error occurs in saving file', e)
f0.write('\n')
#if 'dep_conll' in d.keys():
# f0.write('\n<Dependency>\n')
# for dc in d['dep_conll']:
# for c in dc:
# f0.write(' '.join(c)+'\n')
# f0.write('\n')
f0.write('\n')
class DataLabeler(object):
"""for wikihow dataset:
1. find top 500 'or texts' of home and garden
2. text labeling, add annotations: action types, action indexes, object indexes
3. add object type, split object indexes by 'or, Or'
"""
def __init__(self):
self.num_texts = 154
self.one_line_data = 1
self.home = 'wikihow' #'ehow' #'cooking' #'win2k' #wikihow
self.source = '%s/raw_data/' % self.home
self.out_path = '%s/out_data/' % self.home
self.save_file = '%s/%s_data.pkl' % (self.home, self.home)
self.save_labeled_data = '%s/labeled_%s_data.pkl' % (self.home, self.home)
self.refined_data = '%s/refined_%s_data.pkl' % (self.home, self.home)
def find_top_or_text_by_category(self):
print('Loading data...')
data = pickle.load(open('wikihow/wikihow_data_100k.pkl', 'rb'))[-1]
garden = data['Category:Home-and-Garden']
print(len(garden))
texts = []
for page in garden:
if 'detail' not in page or len(page['detail']) != len(page['task']):
continue
for i, detail in enumerate(page['detail']):
sents = []
for step in detail:
text = re.sub(r'\[.*\]|/', '', step)
text = re.sub(r'[\n\r]', ' ', text)
tmp_sents = re.split(r'\. |\? |\! ', text)
for s in tmp_sents:
s = re.sub(r'<.*>|<*', '', s)
if len(s.strip().split()) > 1:
sents.append(s.strip())
texts.append({'title': page['task'][i], 'sent': sents})
with open('wikihow/wikihow_home_and_garden_data.pkl', 'wb') as f:
pickle.dump(texts, f)
self.find_top_or_text('', 'wikihow/home_and_garden_500_words', texts)
def find_top_or_text(self, infile, outfile, texts='', topn=-1):
# infile = 'wikihow/wikihow_act_seq_152k_details.pkl'
# outfile = 'top1000_or_texts_152k.txt'
if texts:
data = texts
else:
data = pickle.load(open(infile, 'rb'))
or_dicts = {}
for i, text in enumerate(data):
#if len(text['sent']) > 40:
# continue
if sum([len(s.split()) for s in text['sent']]) > 500:
continue
for sent in text['sent']:
words = sent.split()
if 'or' in words or 'Or' in words:
if i not in or_dicts:
or_dicts[i] = 1
else:
or_dicts[i] += 1
or_list = sorted(or_dicts.items(), key=lambda x:x[1], reverse=True)
f = open(outfile + '.txt', 'w')
if topn <= 0:
topn = len(or_list)
print('topn:', topn)
texts = []
for idx in or_list[: topn]:
text = data[idx[0]]['sent']
sents = [re.sub(r',|;|:|\.|', '', s) for s in text]
texts.append(sents)
f.write('text: %d\n' % idx[0])
if 'title' in data[idx[0]]:
f.write('title: %s\n' % data[idx[0]]['title'])
for j, sent in enumerate(text):
f.write('No%d: %s\n' % (j, sent))
f.write('\n\n')
f.close()
with open(outfile + '.pkl', 'wb') as f:
pickle.dump(texts, f, protocol=2)
def get_sail_data(self):
lines = open('sail/paragraph.instructions').readlines()
i = 0
data = {}
assert len(lines) % 4 == 0
for i in range(int(len(lines) / 4)):
tags = lines[i * 4].split('_')
key = '_'.join(tags[1: 4])
#key = lines[i*4]
sents = lines[i * 4 + 2].replace('\n', ' ')
sents = sents.split('. ')
assert len(sents[-1]) == 0
words = [s.split() for s in sents[: -1]]
if key not in data:
data[key] = [words]
else:
data[key].append(words)
print(len(data))
total = 0
for key, sents in data.items():
words_num = 0
for sent in sents:
words_num += sum([len(s) for s in sent])
total += words_num
print('{:<20}\t{:<5}\t{:<5}\t{:<5}'.format(key, len(sents), words_num, total))
ipdb.set_trace()
for i in sorted(data.items(),key=lambda x:x[1], reverse=True): print(i)
def add_action_type(self):
self.save_labeled_data = 'cooking/new_refined_cooking_data2.pkl'
self.refined_data = 'cooking/new_cooking_labeled_data2.pkl'
with open(self.save_labeled_data, 'rb') as f:
data = pickle.load(f)
last_sent = last_text = 0
out_data = []
if os.path.exists(self.refined_data):
print('Load data from %s...\n' % self.refined_data)
last_text, last_sent, out_data = pickle.load(open(self.refined_data, 'rb'))
print('last_text: %d\t last_sent: %d\n' % (last_text, last_sent))
while True:
init = input('Input last text num and sent num\n')
if not init:
print('No input, program exit!\n')
if len(init.split()) == 2:
start_text = int(init.split()[0])
start_sent = int(init.split()[1])
break
ipdb.set_trace()
else:
start_text = start_sent = 0
out_data = [[] for _ in range(len(data))]
try:
for i in range(start_text, len(data)):
if i == start_text and len(out_data[i]) > 0:
out_sents = out_data[i]
else:
out_sents = [{} for _ in range(len(data[i]))]
if i != start_text:
start_sent = 0
for j in range(start_sent, len(data[i])):
print('\nT%d of %d, S%d of %d:' % (i, len(data), j, len(data[i])))
sent = data[i][j]
words = sent['last_sent'] + sent['this_sent']
acts = []
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
print('\n')
tips = False
for w in ['or', 'Or', 'if', 'If', "don't", 'not', 'avoid']:
if w in sent['this_sent']:
tips = True
print("\n%s in words[%d]\n" % (w, words.index(w)))
tmp_acts = sorted(sent['acts'].items(), key=lambda x:x[0])
for act_idx, obj_idxs in tmp_acts:
objs = []
for o in obj_idxs:
if o >= 0:
objs.append(words[o])
else:
objs.append('NULL')
print('%s(%s)'%(words[act_idx], ','.join(objs)))
for act_idx, obj_idxs in tmp_acts:
print(act_idx, obj_idxs)
if not tips:
act_type = 1
related_acts = []
acts.append({'act_idx': act_idx, 'obj_idxs': obj_idxs,
'act_type': act_type, 'related_acts': related_acts})
continue
while True:
inputs = input('\nInput action type and related action indecies:\n')
if not inputs:
continue
if inputs == 'q':
last_sent = j
last_text = i
out_data[i] = out_sents
raise QuitProgram()
elif inputs == 'r': # revise a sent
print(' '.join(sent['this_sent']))
text = input('Input right this sentence\n')
sent['this_sent'] = text.strip().split()
words = sent['last_sent'] + sent['this_sent']
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
continue
elif inputs == 'w':
print(' '.join(sent['last_sent']))
text = input('Input right last sentence\n')
sent['last_sent'] = text.strip().split()
words = sent['last_sent'] + sent['this_sent']
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
continue
elif inputs == 't':
#ipdb.set_trace()
sent['this_sent'][0] = sent['this_sent'][0][0] + sent['this_sent'][0][1:].lower()
for ii in range(1, len(sent['this_sent'])):
sent['this_sent'][ii] = sent['this_sent'][ii].lower()
words = sent['last_sent'] + sent['this_sent']
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
continue
elif inputs == 'e':
sent['last_sent'][0] = sent['last_sent'][0][0] + sent['last_sent'][0][1:].lower()
for ii in range(1, len(sent['last_sent'])):
sent['last_sent'][ii] = sent['last_sent'][ii].lower()
words = sent['last_sent'] + sent['this_sent']
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
continue
inputs = inputs.split()
if len(inputs) >= 1:
act_type = int(inputs[0])
related_acts = [int(ra) for ra in inputs[1: ]]
if act_type > 3 or act_type < 1:
print('Wrong action type! act_type should be 1, 2 or 3!')
continue
if act_type == 3 and len(related_acts) == 0:
print('Wrong inputs! Missed related actions!')
continue
if len(related_acts) > 0:
related_act_words = []
for ra in related_acts:
related_act_words.append(words[ra])
print(act_type, ' '.join(related_act_words))
acts.append({'act_idx': act_idx, 'obj_idxs': obj_idxs,
'act_type': act_type, 'related_acts': related_acts})
break
print(acts)
sent['acts'] = acts
out_sents[j] = sent
out_data[i] = out_sents
except Exception as e:
print(e)
with open(self.refined_data, 'wb') as f:
pickle.dump([i, j, out_data], f, protocol=2)
print('last_text: %d\t last_sent: %d\n' % (i, j))
def add_object_type(self):
with open(self.save_labeled_data, 'rb') as f:
data = pickle.load(f)[-1]
last_sent = last_text = 0
out_data = []
if os.path.exists(self.refined_data):
print('Load data from %s...\n' % self.refined_data)
last_text, last_sent, out_data = pickle.load(open(self.refined_data, 'rb'))
print('last_text: %d\t last_sent: %d\n' % (last_text, last_sent))
while True:
init = input('Input last text num and sent num\n')
if not init:
print('No input, program exit!\n')
if len(init.split()) == 2:
start_text = int(init.split()[0])
start_sent = int(init.split()[1])
break
ipdb.set_trace()
else:
start_text = start_sent = 0
out_data = [[] for _ in range(len(data))]
try:
for i in range(start_text, len(data)):
if i == start_text and len(out_data[i]) > 0:
if len(out_data[i]) == len(data[i]):
out_sents = out_data[i]
else:
out_sents = [{} for _ in range(len(data[i]))]
else:
out_sents = [{} for _ in range(len(data[i]))] #[]#
if i != start_text:
start_sent = 0
for j in range(start_sent, len(data[i])):
sent = data[i][j]
if len(sent) == 0:
#print('\nEmpty sentence: (i=%d, j=%d)\n' % (i, j))
continue
words = sent['last_sent'] + sent['this_sent']
acts = []
or_ind = []
print_change = False
for k, w in enumerate(sent['this_sent']):
if w == 'or':
or_ind.append(k + len(sent['last_sent']))
if len(or_ind) == 0:
for act in sent['acts']:
act['obj_idxs'] = [act['obj_idxs'], []]
acts.append(act)
else:
for act in sent['acts']:
split = None
for k in range(len(act['obj_idxs']) - 1):
for oi in or_ind:
if act['obj_idxs'][k] < oi < act['obj_idxs'][k+1]:
split = k + 1
break
if split != None:
break
if split != None:
print('\nT%d of %d, S%d of %d:' % (i, len(data), j, len(data[i])))
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
print('\n')
print('or_ind: {}\n'.format(or_ind))
print('{}({})'.format(act['act_idx'], act['obj_idxs']))
confirm = input('Split or not? (y/n)\n')
if confirm.lower() == 'y':
act['obj_idxs'] = [act['obj_idxs'][: split], act['obj_idxs'][split: ]]
print('{}({}; {})'.format(act['act_idx'], act['obj_idxs'][0], act['obj_idxs'][1]))
print_change = True
else:
act['obj_idxs'] = [act['obj_idxs'], []]
else:
act['obj_idxs'] = [act['obj_idxs'], []]
acts.append(act)
if print_change:
print('before: {}\n\nafter : {}\n'.format(sent['acts'], acts))
sent['acts'] = acts
if len(out_sents) < j + 1:
out_sents.append({})
out_sents[j] = sent
#out_sents.append(sent)
out_data[i] = out_sents
# if(len(out_sents) != len(data[i])):
# #ipdb.set_trace()
# time.sleep(1)
# print('\nlen(out_sents) != len(data[i]): (i=%d, j=%d)\n' % (i, j))
except Exception as e:
ipdb.set_trace()
print(e)
with open(self.refined_data, 'wb') as f:
pickle.dump([i, j, out_data], f, protocol=2)
print('last_text: %d\t last_sent: %d\n' % (i, j))
def transfer(self, name):
_, __, indata = pickle.load(open('%s/refined_%s_data.pkl'%(name, name),'rb'))
data = []
tmp_data = {}
max_sent_len = 0
max_char_len = 0
log = {'wrong_last_sent': 0, 'act_reference_1': 0, 'related_act_reference_1': 0,
'obj_reference_1': 0, 'non-obj_reference_1': 0}
#ipdb.set_trace()
for i in range(len(indata)):
words = []
sents = []
word2sent = {}
text_acts = []
sent_acts = []
#if i == 44:
# ipdb.set_trace()
reference_related_acts = False
for j in range(len(indata[i])):
if len(indata[i][j]) == 0:
print('%s, len(indata[%d][%d]) == 0'%(name, i, j))
continue
last_sent = indata[i][j]['last_sent']
this_sent = indata[i][j]['this_sent']
acts = indata[i][j]['acts']
if j > 0 and len(last_sent) != len(indata[i][j-1]['this_sent']):
#ipdb.set_trace()
b1 = len(last_sent)
b2 = len(indata[i][j-1]['this_sent'])
for k in range(len(acts)):
ai = acts[k]['act_idx']
new_act_type = acts[k]['act_type']
new_act_idx = ai - b1 + b2
new_obj_idxs = [[],[]]
for l in range(2):
for oi in acts[k]['obj_idxs'][l]:
if oi == -1:
new_obj_idxs[l].append(oi)
else:
new_obj_idxs[l].append(oi - b1 + b2)
assert len(new_obj_idxs[l]) == len(acts[k]['obj_idxs'][l])
#if len(acts[k]['related_acts']) > 0:
# ipdb.set_trace()
new_related_acts = []
acts[k] = {'act_idx': new_act_idx, 'obj_idxs': new_obj_idxs,
'act_type': new_act_type, 'related_acts': new_related_acts}
last_sent = indata[i][j-1]['this_sent']
log['wrong_last_sent'] += 1
sent = last_sent + this_sent
bias = len(last_sent)
reference_obj_flag = False
tmp_acts = []
for k in range(len(acts)):
act_idx = acts[k]['act_idx']
obj_idxs = acts[k]['obj_idxs']
tmp_act_idx = act_idx - bias
if tmp_act_idx < 0:
log['act_reference_1'] += 1
#continue
tmp_obj_idxs = [[],[]]
for l in range(2):
for oi in obj_idxs[l]:
if oi == -1:
tmp_obj_idxs[l].append(oi)
else:
tmp_obj_idxs[l].append(oi - bias)
if oi - bias < 0:
reference_obj_flag = True
assert len(tmp_obj_idxs[l]) == len(obj_idxs[l])
tmp_act_type = acts[k]['act_type']
tmp_related_acts = []
if len(acts[k]['related_acts']) > 0:
for idx in acts[k]['related_acts']:
tmp_related_acts.append(idx - bias)
if idx - bias < 0:
reference_related_acts = True
log['related_act_reference_1'] += 1
assert len(tmp_related_acts) == len(acts[k]['related_acts'])
tmp_acts.append({'act_idx': tmp_act_idx, 'obj_idxs': tmp_obj_idxs,
'act_type': tmp_act_type, 'related_acts': tmp_related_acts})
assert len(tmp_acts) == len(acts)
if j == 0:
if reference_obj_flag:
log['obj_reference_1'] += 1
for ii in range(len(words), len(words)+len(last_sent)):
word2sent[ii] = len(sents)
words.extend(last_sent)
sents.append(last_sent)
sent_acts.append({})
#elif reference_related_acts:
# log['related_act_reference_1'] += 1
else:
if len(last_sent) > 0:
log['non-obj_reference_1'] += 1
last_sent = []
bias = len(last_sent)
sent = last_sent + this_sent
acts = tmp_acts
add_bias = len(words)
for ii in range(len(words), len(words)+len(this_sent)):
word2sent[ii] = len(sents)
words.extend(this_sent)
sents.append(this_sent)
sent_acts.append(acts)
for k in range(len(tmp_acts)):
act_idx = tmp_acts[k]['act_idx']
obj_idxs = tmp_acts[k]['obj_idxs']
text_act_idx = act_idx + add_bias
if sent[act_idx + bias] != words[act_idx + add_bias]:
ipdb.set_trace()
print(sent[act_idx + bias], words[act_idx + add_bias])
text_obj_idxs = [[],[]]
for l in range(2):
for oi in obj_idxs[l]:
if oi == -1:
text_obj_idxs[l].append(-1)
else:
text_obj_idxs[l].append(oi + add_bias)
if sent[oi + bias] != words[oi + add_bias]:
ipdb.set_trace()
print(sent[oi + bias], words[oi + add_bias])
assert len(text_obj_idxs[l]) == len(obj_idxs[l])
text_act_type = tmp_acts[k]['act_type']
text_related_acts = []
if len(tmp_acts[k]['related_acts']) > 0:
for idx in tmp_acts[k]['related_acts']:
text_related_acts.append(idx + add_bias)
assert len(text_related_acts) == len(tmp_acts[k]['related_acts'])
text_acts.append({'act_idx': text_act_idx, 'obj_idxs': text_obj_idxs,
'act_type': text_act_type, 'related_acts': text_related_acts})
assert len(word2sent) == len(words)
assert len(sents) == len(sent_acts)
if reference_related_acts:
for m, a in enumerate(text_acts):
print('{}\t{}\n'.format(m, a))
#ipdb.set_trace()
data.append({'words': words, 'acts': text_acts, 'sent_acts': sent_acts,
'sents': sents, 'word2sent': word2sent})
upper_bound = 0
lower_bound = 0
for d in data:
for n in range(len(d['acts'])):
act = d['acts'][n]['act_idx']
objs = d['acts'][n]['obj_idxs']
for l in range(2):
for obj in objs[l]:
if obj == -1:
continue
if obj - act < lower_bound:
lower_bound = obj - act
print(act, obj)
if obj - act > upper_bound:
upper_bound = obj - act
print(act, obj)
print('\nupper_bound: {}\tlower_bound: {}\nlog history: {}\n'.format(
upper_bound, lower_bound, log))
with open('%s/%s_labeled_text_data.pkl'%(name, name), 'wb') as f:
pickle.dump(data, f, protocol=2)
def split_sents(self):
num = 1
ipdb.set_trace()
texts = []
#for fname in os.listdir(self.source):
for i in range(self.num_texts):
fname = '%d.txt' % (i + 1)
if not fname.endswith('.txt'):
continue
with open(self.source + fname) as f:
if self.one_line_data:
atext = f.read() #f.readlines()
#atext = re.sub(r'\.\n|\?\n|\!\n', '\n', atext)
#for j in range(len(btext)):
btext = atext.split('\n')#[:-1]
assert len(btext[-1]) != 0
#btext[0] = btext[0][0] + btext[0][1:].lower()
texts.append(btext)
else:
text = f.read()
#atext = re.sub(r'\n|\r|,|;|\(|\)', ' ', text)
atext = re.sub(r'\n|\r|\(|\)', ' ', text)
btext = re.split(r'\. |\? |\! ', atext)
texts.append(btext[:-1])
with open(self.out_path + '%d.txt' % num, 'w') as f1:
print(num)
f1.write('\n'.join(btext))
num += 1
with open(self.save_file, 'wb') as outfile:
pickle.dump(texts, outfile, protocol=2)
def text_labeling(self):
if self.home == 'wikihow':
self.num_texts = 256
self.save_file = 'wikihow/home_and_garden_500_words.pkl'
if self.home != 'cooking':
with open(self.save_file, 'rb') as f:
texts = pickle.load(f)
if self.home == 'wikihow':
_ = texts.pop(87) # skip out of place texts
_ = texts.pop(108)
_ = texts.pop(118)
_ = texts.pop(118)
_ = texts.pop(122)
_ = texts.pop(123)
_ = texts.pop(126)
_ = texts.pop(126)
if os.path.exists(self.save_labeled_data):
with open(self.save_labeled_data, 'rb') as f:
print('Load data from %s...\n' % self.save_labeled_data)
last_text, last_sent, data = pickle.load(f)
print('last_text: %d\t last_sent: %d\n' % (last_text, last_sent))
while True:
init = input('Input last text num and sent num\n')
if not init:
print('No input, program exit!\n')
if len(init.split()) == 2:
start_text = int(init.split()[0])
start_sent = int(init.split()[1])
break
# for i in range(len(data)):
# for j in range(len(data[i])):
# if len(data[i][j]) == 0:
# print(i, j)
ipdb.set_trace()
else:
start_text = start_sent = 0
data = [[] for _ in range(self.num_texts)]
for i in range(start_text, self.num_texts):
if self.home == 'cooking' and i >= 96:
text = open('cooking/new_texts/%d.txt'%(i+1)).read()
text = re.sub(r',|;', ' ', text)
text = [t for t in text.split('\n') if len(t.split()) > 1]
else:
text = [t for t in texts[i] if len(t.split()) > 1]
sents_num = len(text)
print('\ntext %d: total %d words\n' % (i, sum([len(t.split()) for t in text])))
if len(data[i]) > 0: #self.home != 'cooking' and i == start_text and
sents = data[i]
else:
sents = [{} for _ in range(sents_num)]
try:
if i != start_text:
start_sent = 0
for j in range(start_sent, sents_num):
#if len(data[i]) <= j or len(data[i][j]) > 0:
# continue
sent = {}
this_sent = text[j].split()
if j > 0: # print two sentences, used for coreference resolution
last_sent = text[j - 1].split()
else:
last_sent = []
if self.home == 'win2k':
this_sent[0] = this_sent[0].title()
if len(last_sent) > 0:
last_sent[0] = last_sent[0].title()
sent['last_sent'] = last_sent
sent['this_sent'] = this_sent
sent['acts'] = []
words = last_sent + this_sent
words_num = len(words)
print('T%d of %d, S%d of %d:' % (i, self.num_texts, j, sents_num))
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
while True:
act = input('\nInput an action and object indices:\n')
if not act:
break
if self.home == 'win2k2':
lest_input = 1
act_i = 0
obj_i = 1
else:
lest_input = 2
act_i = 1
obj_i = 2
if len(act.split()) <= lest_input:
if act == 'q':
raise QuitProgram()
elif act == 'r': # revise a sent
print(' '.join(sent['this_sent']))
text[j] = input('Input right sentence\n')
sent['this_sent'] = text[j].strip().split()
words = last_sent + sent['this_sent']
words_num = len(words)
for l, w in enumerate(words):
print('%s(%d)'%(w, l), end=' ')
continue
else:
continue
nums = [int(a) for a in act.split()]
if self.home == 'win2k2':
act_type = 1
related_acts = []
else:
act_type = nums[0]
if act_type not in [1, 2, 3]: # essential, optional, exclusive
print('Wrong act_type!')
continue
if act_type == 3:
related_acts = input('Enter its related actions (indices):\n')
related_acts = [int(r) for r in related_acts.split()]
if len(related_acts) == 0:
print('You should input related_acts!\n')
continue
print('\tRelated actions: {}'.format([words[idx] for idx in related_acts]))
else:
related_acts = []
act_idx = nums[act_i]
if act_idx >= words_num:
print('action index %d out of range' % act_idx)
continue
obj_idxs = []
continue_flag = False
for idx in nums[obj_i: ]:
if idx >= words_num:
print('object index %d out of range' % idx)
continue_flag = True
break
obj_idxs.append(idx)
if continue_flag:
continue
obj_names = []
for k in obj_idxs:
if k >= 0:
obj_names.append(words[k])
else:
obj_names.append('NULL')
print('\t%s(%s) act_type: %d' % (words[act_idx], ','.join(obj_names), act_type))
sent['acts'].append({'act_idx': act_idx, 'obj_idxs': obj_idxs,
'act_type': act_type, 'related_acts': related_acts})
if len(sents) < sents_num:
sents.append({})
sents[j] = sent
except Exception as e:
print('Error:',e)
if len(data) < self.num_texts:
data.append([])
data[i] = sents
with open(self.save_labeled_data, 'wb') as f:
pickle.dump([i, j, data], f)
break_flag = True
print('last_text: %d\t last_sent: %d\n' % (i, j))
break
if len(data) < self.num_texts:
data.append([])
data[i] = sents
with open(self.save_labeled_data, 'wb') as f:
pickle.dump([i, j, data], f, protocol=2)
break_flag = True
print('last_text: %d\t last_sent: %d\n' % (i, j))
if __name__ == '__main__':
start = time.time()
model = DataLabeler()
#model.find_top_or_text_by_category()
#model.add_object_type()
#model.transfer('wikihow')
model.text_labeling()
#for name in ['win2k', 'wikihow', 'cooking']:
# model.transfer(name)
end = time.time()
print('Total time cost: %.2fs\n' % (end - start))
| [
"787499313@qq.com"
] | 787499313@qq.com |
a3858baa61f208bad13adece86e95fda7e011367 | d8f858b496a7133868d0e89cc8f4aad8f3001dff | /pytex.py | d5a8f7d16131824c54853c3167b2274141118044 | [] | no_license | shawsa/m565 | 812b451acfb7239486a3fe689cafed0a174edaf0 | 47511eef4a921a1f02b5ed7311fac6067825f350 | refs/heads/master | 2021-01-20T08:38:17.971734 | 2017-12-08T05:10:09 | 2017-12-08T05:10:09 | 101,568,001 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 708 | py |
def latex_table(t, headers=None):
cols = len(t)
rows = len(t[0])
print('\t\\begin{center}')
print('\t\t\\begin{tabular}{' + '|c'*cols + '|}')
print('\t\t\t\\hline')
if headers != None:
assert len(headers) == cols
header_str = ''
for h in headers:
header_str += str(h) + '&'
header_str = header_str[:-1] #remove trailing &
print('\t\t\t' + header_str + '\\\\ \\hline')
for i in range(rows):
col = ''
for j in range(cols):
col += str(t[j][i]) + '&'
col = col[:-1] #remove trailing &
print('\t\t\t' + col + '\\\\ \\hline')
print('\t\t\\end{tabular}')
print('\t\\end{center}')
| [
"sage.b.shaw@gmail.com"
] | sage.b.shaw@gmail.com |
ce1cd13eb01ac664a6e72d6cac7965fbd900cff5 | fcae2c35e3430702b643b8d914992c1d044f785d | /test_gp3.py | 28a822b2c3fa4546c449b674823580521761759a | [] | no_license | 016mm/gpTest | 1754faf4c66c3735d5d39e0294374139917af201 | 5a83f51cd738bbfd5ea5ba0604487a567a694118 | refs/heads/master | 2023-03-06T18:13:36.785870 | 2021-02-23T03:33:33 | 2021-02-23T03:33:33 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,356 | py | import urllib3
import requests
import json
from bs4 import BeautifulSoup
def get_html(stock):
headers = {"User-Agent":"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36"}
url = "https://xuangubao.cn/stock/"
reponse=requests.get(url+stock,headers=headers)
reponse.raise_for_status()
soup=BeautifulSoup(reponse.text,'html.parser')
stock_name=soup.title.string[0:4]
item=soup.find_all('div',class_='zhibiao-item')
dict={}
dict.update({stock_name:stock})
#print (new_item)
for inform in item:
item_0=inform.find('span',class_='zhibiao-item-label')
item_1=inform.find('span',class_='zhibiao-item-text')
#print (item_0.get_text(),item_1.get_text())
dict.update({item_0.get_text():item_1.get_text()})
#print (inform.get_text())
# print (dict.items())
return dict
# 忽略警告：InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised.
requests.packages.urllib3.disable_warnings()
# 一个PoolManager实例来生成请求, 由该实例对象处理与线程池的连接以及线程安全的所有细节
http = urllib3.PoolManager()
# 通过request()方法创建一个请求：
headers = {
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36"}
#7x24快讯api接口
url='https://api.xuangubao.cn/api/pc/msgs?subjids=9,10,162,723,35,469,821&limit=30'
#r = http.request('GET', url, headers=headers)
r = requests.get(url , headers=headers)
#print(r.status) # 200
data=r.text
#reponse = json.dumps(r.data.decode(),ensure_ascii=False)
#print (reponse)
resjson=json.loads(data)
#print (resjson['NewMsgs'][0])
#print(type(resjson))
msg=resjson['NewMsgs']
print (len(msg))
for items in msg[0:]:
title=items['Title']
BkjInfoArr=items['BkjInfoArr']
stock=items['Stocks']
print (title,"\t=group=",BkjInfoArr,"\t=stocks=",stock)
if stock is not None:
for stock_item in stock:
#print(get_html(stock_item['Symbol']))
dict_stock=get_html(stock_item['Symbol'])
print ("\t相关股票:",stock_item['Name'],stock_item['Symbol'],"最新：",dict_stock["最新"],dict_stock["涨幅"])
| [
"menghongtao@sinotrans.com"
] | menghongtao@sinotrans.com |
251796be631c7ff6cc48f6a893e651c17c6cd7a2 | e2b7ba8a2df5089f0af1c52cd5ef33efbb389f4c | /tests/test_extension.py | 77bf946e745db38ab065a80f7525d14a65dacd91 | [
"Apache-2.0",
"MIT",
"BSD-2-Clause"
] | permissive | Neki/datadog-lambda-python | 22406422a8984e4c4e9d348c0ea6e6f8da611c60 | 57cc2404b7d2d8ee5ff7791f41f0036aabd13d0c | refs/heads/main | 2023-07-14T06:08:39.913580 | 2021-09-08T07:38:55 | 2021-09-08T07:38:55 | 384,703,202 | 0 | 0 | NOASSERTION | 2021-07-10T13:22:32 | 2021-07-10T13:22:31 | null | UTF-8 | Python | false | false | 2,646 | py | import os
import sys
import unittest
import httpretty
try:
from unittest.mock import patch
except ImportError:
from mock import patch
from datadog_lambda.extension import (
is_extension_running,
flush_extension,
should_use_extension,
)
def exceptionCallback(request, uri, headers):
raise Exception("oopsy!")
class TestLambdaExtension(unittest.TestCase):
# do not execute tests for Python v2.x
__test__ = sys.version_info >= (3, 0)
@patch("datadog_lambda.extension.EXTENSION_PATH", os.path.abspath(__file__))
def test_is_extension_running_true(self):
httpretty.enable()
last_request = httpretty.last_request()
httpretty.register_uri(httpretty.GET, "http://127.0.0.1:8124/lambda/hello")
assert is_extension_running() == True
assert httpretty.last_request() != last_request
httpretty.disable()
def test_is_extension_running_file_not_found(self):
httpretty.enable()
last_request = httpretty.last_request()
httpretty.register_uri(httpretty.GET, "http://127.0.0.1:8124/lambda/hello")
assert is_extension_running() == False
assert httpretty.last_request() == last_request
httpretty.disable()
@patch("datadog_lambda.extension.EXTENSION_PATH", os.path.abspath(__file__))
def test_is_extension_running_http_failure(self):
httpretty.enable()
last_request = httpretty.last_request()
httpretty.register_uri(
httpretty.GET,
"http://127.0.0.1:8124/lambda/hello",
status=503,
body=exceptionCallback,
)
assert is_extension_running() == False
assert httpretty.last_request() != last_request
httpretty.disable()
@patch("datadog_lambda.extension.EXTENSION_PATH", os.path.abspath(__file__))
def test_flush_ok(self):
httpretty.enable()
last_request = httpretty.last_request()
httpretty.register_uri(httpretty.POST, "http://127.0.0.1:8124/lambda/flush")
assert flush_extension() == True
assert httpretty.last_request() != last_request
httpretty.disable()
@patch("datadog_lambda.extension.EXTENSION_PATH", os.path.abspath(__file__))
def test_flush_not_ok(self):
httpretty.enable()
last_request = httpretty.last_request()
httpretty.register_uri(
httpretty.POST,
"http://127.0.0.1:8124/lambda/flush",
status=503,
body=exceptionCallback,
)
assert flush_extension() == False
assert httpretty.last_request() != last_request
httpretty.disable()
| [
"noreply@github.com"
] | noreply@github.com |
6fda0d0407e79c6d9a3df29ca3f097cbd2dcf0f5 | b5cec2e9527e130d652ba87bcee9648c29a05e84 | /src/zojax/cms/generations/__init__.py | 641f878dc1da3c0ecf8825234b5d5b1b71677adf | [] | no_license | suvanna/zojax.cms | 162766ccfb6df74421f8653fa1d3eb1a94447536 | f5d88f6a2769e81369c3bdd302aefcee94d8cf28 | refs/heads/master | 2021-01-18T01:11:17.313119 | 2014-02-12T22:06:37 | 2014-02-12T22:06:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 885 | py | ##############################################################################
#
# Copyright (c) 2009 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
"""
$Id$
"""
from zope.app.generations.generations import SchemaManager
pkg = 'zojax.cms.generations'
schemaManager = SchemaManager(minimum_generation=0,
generation=0,
package_name=pkg)
| [
"suvdim@gmail.com"
] | suvdim@gmail.com |
7f0af037e66773cb760072ebad5fd4da7c335db8 | 9748610adb3d3ffcb3efd2d2661b691c2afbd2d4 | /MERCURY2/m6_input.py | 9fa18d19e363b09f203c128fb4d62bbb9e820f73 | [] | no_license | Jooehn/Stars-Eating-Planets | bb421a9b283fe414e863b94b4a8a2760fff9bff7 | 5f66c23c82d79c89fbaa88c98ef8654ead68343e | refs/heads/master | 2021-06-07T21:31:33.956125 | 2021-05-19T09:13:18 | 2021-05-19T09:13:18 | 172,890,639 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 14,609 | py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 30 13:51:34 2019
@author: John Wimarsson
"""
import numpy as np
from tempfile import mkstemp
from shutil import move
from os import fdopen, remove
##### Format of input #####
# Bigdata must be an array with Nx10 elements containing for each big body the name,
# mass, radius and density, as well its six orbital elements.
# Smalldata must be an array with Nx8 elements, as the small particles are considered
# point objects with not mass, radius or density
def big_input(names,bigdata,asteroidal=False,epoch=0):
"""Function that generates the big.in input file for MERCURY6 given an Nx10
array of data in the following format:
Columns:
0: mass of the object given in solar masses
1: radius of the object in Hill radii
2: density of the object
3: semi-major axis in AU
4: eccentricity
5: inclination in degrees
6: argument of pericentre in degrees
7: longitude of the ascending node
8: mean anomaly in degrees
We can also pass the argument asteroidal as True if we want that coordinate
system. Also the epoch can be specified, it should be given in years."""
N = len(bigdata)
if asteroidal:
style = 'Asteroidal'
else:
style = 'Cartesian'
initlist = [')O+_06 Big-body initial data (WARNING: Do not delete this line!!)\n',\
") Lines beginning with `)' are ignored.\n",\
')---------------------------------------------------------------------\n',\
' style (Cartesian, Asteroidal, Cometary) = {}\n'.format(style),\
' epoch (in days) = {}\n'.format(epoch*365.25),\
')---------------------------------------------------------------------\n']
with open('big.in','w+') as bigfile:
for i in initlist:
bigfile.write(i)
for j in range(N):
bigfile.write(' {0:11}m={1:.17E} r={2:.0f}.d0 d={3:.2f}\n'.format(names[j],*bigdata[j,0:3]))
bigfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*bigdata[j,3:6]))
bigfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*bigdata[j,6:]))
bigfile.write(' 0. 0. 0.\n')
def small_input(names=[],smalldata=[],epochs=[]):
"""Function that generates the small.in input file for MERCURY6 given an Nx10
array of data in the following format:
Columns:
0: Name of the object in upper case letters
1: the object's epoch, set to zero if not relevant
2: semi-major axis in AU
3: eccentricity
4: inclination in degrees
5: argument of pericentre in degrees
6: longitude of the ascending node
7: mean anomaly in degrees
If no data is given, the function will simply write only the necessary lines"""
N = len(smalldata)
if len(epochs) == 0:
epochs = np.zeros(N)
initlist = [')O+_06 Small-body initial data (WARNING: Do not delete this line!!)\n',\
')---------------------------------------------------------------------\n',\
' style (Cartesian, Asteroidal, Cometary) = Asteroidal\n',\
')---------------------------------------------------------------------\n']
with open('small.in','w+') as smallfile:
for i in initlist:
smallfile.write(i)
if N == 0:
return
for j in range(N):
smallfile.write(' {0:9}epoch={1}\n'.format(*smalldata[j,0:2]))
smallfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*smalldata[j,2:5]))
smallfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*smalldata[j,5:]))
smallfile.write(' 0. 0. 0.\n')
def rand_big_input(names,bigdata):
"""Function that generates the big.in input file for MERCURY6 given that
we wish to make a run for an unspecified system. bigdata should be an array
containing Nx4 array that contains data in the following form:
Columns:
1: mass of the object
2: Distance in Hill radii that yields a close encounter
3: semi-major axis in AU
The code generates random properties of the objects from a uniform distribution.
It yields a new mean anomaly for each body in the system."""
N = len(bigdata)
initlist = [')O+_06 Big-body initial data (WARNING: Do not delete this line!!)\n',\
") Lines beginning with `)' are ignored.\n",\
')---------------------------------------------------------------------\n',\
' style (Cartesian, Asteroidal, Cometary) = Asteroidal\n',\
' epoch (in days) = 0\n',\
')---------------------------------------------------------------------\n']
# rho = calc_density(bigdata[:,0])
ecc = np.random.uniform(0,0.01,size=N)
i = np.random.uniform(0,5,size=N)
n = np.random.uniform(0,360,size=N)
M = np.random.uniform(0,360,size=N)
p = np.random.uniform(0,360,size=N)
# bigdata = np.insert(bigdata,2,rho,axis=1)
bigdata = np.insert(bigdata,4,ecc,axis=1)
bigdata = np.insert(bigdata,5,i,axis=1)
bigdata = np.insert(bigdata,6,p,axis=1)
bigdata = np.insert(bigdata,7,n,axis=1)
bigdata = np.insert(bigdata,8,M,axis=1)
with open('big.in','w+') as bigfile:
for i in initlist:
bigfile.write(i)
for j in range(N):
bigfile.write(' {0:11}m={1:.17E} r={2:.0f}.d0 d={3:.2f}\n'.format(names[j],*bigdata[j,0:3]))
bigfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*bigdata[j,3:6]))
bigfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*bigdata[j,6:]))
bigfile.write(' 0. 0. 0.\n')
def rand_small_input(smalldata,epochs=[]):
"""Function that generates the big.in input file for MERCURY6 given that
we wish to make a run for an unspecified system. smalldata should be an array
containing Nx2 elements with data in the following form:
Columns:
0: name of the objects in upper case letters
1: argument of pericentre in degrees
The code generates random properties of the objects from a uniform distribution.
It yields eccentricities between 0 and 0.01, inclinations between 0 and 5 degrees,
longitude of the ascending node between 0 and 360 degrees and mean anomalies
between 0 and 360 degrees. Epochs for the small bodies can be specified
"""
N = len(smalldata)
if len(epochs) == 0:
epochs = np.zeros(N)
a = np.random.uniform(0.65,2,size=N)
ecc = np.random.uniform(0,0.01,size=N)
i = np.random.uniform(0,5,size=N)
n = np.random.uniform(0,360,size=N)
M = np.random.uniform(0,360,size=N)
smalldata = np.insert(smalldata,1,epochs,axis=1)
smalldata = np.insert(smalldata,2,a,axis=1)
smalldata = np.insert(smalldata,3,ecc,axis=1)
smalldata = np.insert(smalldata,4,i,axis=1)
smalldata = np.insert(smalldata,6,n,axis=1)
smalldata = np.insert(smalldata,7,M,axis=1)
initlist = [')O+_06 Small-body initial data (WARNING: Do not delete this line!!)\n',\
')---------------------------------------------------------------------\n',\
' style (Cartesian, Asteroidal, Cometary) = Asteroidal\n',\
' epoch (in days) = 0\n',\
')---------------------------------------------------------------------\n']
with open('small.in','w+') as smallfile:
for i in initlist:
smallfile.write(i)
if N == 0:
return
for j in range(N):
smallfile.write(' {0} epoch={1}\n'.format(*smalldata[j,0:2]))
smallfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*smalldata[j,2:5]))
smallfile.write(' {0: .17E} {1: .17E} {2: .17E}\n'.format(*smalldata[j,5:]))
smallfile.write(' 0. 0. 0.\n')
def calc_density(mass):
"""Calculates the average density of a planet with a given mass using the
mass-radius relations from Tremaine & Dong (2012) for planets above 10 Earth
masses and Zeng, Sasselov & Jacobsen (2016) for the planets below 10 Earth
masses. We assume that the planet is a perfect sphere."""
rjtoau = 1/2150
retoau = rjtoau/11
metoms = 1/332946
mjtoms = 300/332946
mstogr = 1.99e33
autocm = 1.496e13
rhovals = []
for m in mass:
#We use the TD12 mass-relation for our planets if they are above 2.62
#Earth masses
if m>=2.62*metoms:
R = 10**(0.087+0.141*np.log10(m/mjtoms)-0.171*np.log10(m/mjtoms)**2)*rjtoau
else:
CMF = 0.33 #Core mass fraction of the Earth
R = (1.07-0.21*CMF)*(m/metoms)**(1/3.7)*retoau
V = 4*np.pi*(R*autocm)**3/3
rho = m*mstogr/V
rhovals.append(rho)
return rhovals
def mass_boost(alpha):
"""Boosts the mass of the big objects in the system by a factor alpha, which
is provided as input."""
#Makes temporary file
fh, abs_path = mkstemp()
with fdopen(fh,'w') as new_file:
with open('big.in') as old_file:
for line in old_file:
if 'm=' in line:
#We obtain the old arguments
largs = line.split()
#We extract the mass argument from the file and scale it
#by a factor alpha
mass_str = largs[1]
old_mass = float(mass_str.split('m=')[1])
new_mass = alpha*old_mass
#We then save this as our new mass argument
largs[1] = new_mass
#Finally we write this new line of object properties into
#the big.in file.
new_line = (' {0:11}m={1:.17E} {2} {3}\n'.format(*largs))
new_file.write(line.replace(line, new_line))
else:
new_file.write(line)
#Remove original file and move new file
remove('big.in')
move(abs_path, 'big.in')
def setup_end_time(T,T_start=0):
"""Small function that sets up the duration of our integration.
T: the total time of the integration given in yr
T_start: we can also specify the start time. If no start time
is given, it is set to zero by default. Should aso be given in yr"""
#The string we want to change
start_str = ' start time (days) = '
end_str = ' stop time (days) = '
#Makes temporary file
fh, abs_path = mkstemp()
with fdopen(fh,'w') as new_file:
with open('param.in') as old_file:
for line in old_file:
if start_str in line:
old_sstr = line
# old_stime = float(old_sstr.strip(start_str))
new_stime = T_start
new_sstr = start_str+str(new_stime)+'\n'
new_file.write(line.replace(old_sstr, new_sstr))
elif end_str in line:
old_estr = line
etime = T*365.25
new_estr = end_str+str(etime)+'\n'
new_file.write(line.replace(old_estr, new_estr))
else:
new_file.write(line)
#Remove original file and move new file
remove('param.in')
move(abs_path, 'param.in')
def setup_rerun_time(T):
"""Small function that updates the stop time in param.dmp to allow for an
extended integration in case we have no collisions. Updates the old time
value by adding the value T."""
#The string we want to change
start_str = ' start time (days) = '
end_str = ' stop time (days) = '
#Makes temporary file
fh, abs_path = mkstemp()
with fdopen(fh,'w') as new_file:
with open('param.in') as old_file:
lines = old_file.readlines()
for line in lines:
if start_str in line:
old_sstr_idx = lines.index(line)
elif end_str in line:
old_estr_idx = lines.index(line)
old_sstr = lines[old_sstr_idx]
old_estr = lines[old_estr_idx]
old_stime = float(old_sstr.strip(start_str))
old_etime = float(old_estr.strip(end_str))
new_stime = old_etime
new_etime = old_etime+T*365.25
new_sstr = start_str+str(new_stime)+'\n'
new_estr = end_str+str(new_etime)+'\n'
lines[old_sstr_idx] = new_sstr
lines[old_estr_idx] = new_estr
new_file.writelines(lines)
#Remove original file and move new file
remove('param.in')
move(abs_path, 'param.in')
def extend_stop_time(T):
"""Small function that updates the stop time in param.dmp to allow for an
extended integration in case we have no collisions. Updates the old time
value by adding the value T."""
#The string we want to change
stime_str = ' stop time (days) = '
#Makes temporary file
fh, abs_path = mkstemp()
with fdopen(fh,'w') as new_file:
with open('param.dmp') as old_file:
for line in old_file:
if stime_str in line:
old_str = line
old_time = float(old_str.strip(stime_str))
new_time = old_time+T*365.25
rep_str = stime_str+str(old_time)
new_str = stime_str+str(new_time)
new_file.write(line.replace(rep_str, new_str))
else:
new_file.write(line)
#Remove original file and move new file
remove('param.dmp')
move(abs_path, 'param.dmp')
| [
"jooehn@gmail.com"
] | jooehn@gmail.com |
dd503f30535313cc118f2aff0289365f7759c68e | db3a0578ef5d79cee7f9e96fa3fd291bbaaf9eb4 | /Web/flask/morse/morseclient.py | 51987ad7f8af39d04cbbd30327428eafbe498b75 | [
"MIT"
] | permissive | otisgbangba/python-lessons | 0477a766cda6bc0e2671e4cce2f95bc62c8d3c43 | a29f5383b56b21e6b0bc21aa9acaec40ed4df3cc | refs/heads/master | 2022-11-03T22:10:52.845204 | 2020-06-13T15:42:40 | 2020-06-13T15:42:40 | 261,255,751 | 1 | 0 | MIT | 2020-05-04T17:48:12 | 2020-05-04T17:48:11 | null | UTF-8 | Python | false | false | 626 | py | import requests
from time import sleep
from codes import PASSWORD, morse_codes, words_by_symbol
URL_BASE = 'http://localhost:5000'
INTER_LETTER_DELAY = 0.2
def request_secret():
response = requests.get(URL_BASE + '/secret')
print(response.text)
def send_unlock_request(message):
for letter in message:
symbols_for_letter = morse_codes[letter]
for symbol in symbols_for_letter:
response = requests.get(URL_BASE + '/code/' + words_by_symbol[symbol])
print(response.text)
sleep(INTER_LETTER_DELAY)
request_secret()
send_unlock_request(PASSWORD)
request_secret()
| [
"daveb@davebsoft.com"
] | daveb@davebsoft.com |
863a9e7fabd741444ae2d183a4dac774c8e404b4 | 204d62b325fe5dff332a517a6bea9a3cad76371d | /django/first_project/first_project/settings.py | 770e2788b153469112fe4d647d2f72998cd71d5f | [] | no_license | tedyeung/Python- | ca5b87b66df95cf3e2d68e516becc04a890bb361 | f379aa48d1e2118729c422e6d48a067b70639c5f | refs/heads/master | 2021-09-21T11:52:20.389770 | 2018-08-25T14:47:46 | 2018-08-25T14:47:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,274 | py | """
Django settings for first_project project.
Generated by 'django-admin startproject' using Django 1.11.8.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.11/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
TEMPLATE_DIR = os.path.join(BASE_DIR,'templates')
STATIC_DIR = os.path.join(BASE_DIR,'static')
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'bf=qzo1f4aew!i*@^^a^_mo6l0pmh@8#^l)%2(%7(n&o&p2@%i'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'first_app'
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'first_project.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [TEMPLATE_DIR,],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'first_project.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
STATICFILES_DIRS = [STATIC_DIR,]
| [
"slavo@mimicom24.com"
] | slavo@mimicom24.com |
3dca66b0b5cacb2e54ac3f447510aa0439007103 | 03fee24072271df3afde70f7c6abaa6bceaf4d18 | /utils/image_downloader.py | eccd908636408c09dbd06c33bf313e71abf85b2c | [] | no_license | pottlock1/Automatic-celebrity-face-detection | 1939a536c53c5a278d840157ba5e88b695b61c0a | 3dff70e2edccfe5ae59d034127b0ba5297690787 | refs/heads/main | 2023-06-01T20:57:10.322600 | 2021-06-18T04:45:53 | 2021-06-18T04:45:53 | 373,872,966 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,869 | py | import os
from selenium import webdriver
import requests
import time
import pickle
class CollectCelebImages:
def __init__(self, celeb1, no_of_images = 20):
self.celebs = [celeb1]
self.no_of_images = no_of_images
def download(self):
for celeb in self.celebs:
self.link_extractor(search_string=celeb, no_of_images=self.no_of_images)
self.imagedownloader(celeb)
def link_extractor(self, search_string: str, no_of_images, sleep_time=2, wd=webdriver):
# opeing google chrome using selenium webdriver and searching our query...
wd = webdriver.Chrome(executable_path='chromedriver.exe')
search_url = "https://www.google.com/search?safe=off&site=&tbm=isch&source=hp&q={q}&oq={q}&gs_l=img"
wd.get(search_url.format(q=search_string))
time.sleep(5)
# getting thumbnail_images...
thumbnail_result = wd.find_elements_by_css_selector('img.Q4LuWd')
print(f'{len(thumbnail_result)} images are found!!')
links = []
counter = 0
while len(links) < no_of_images:
img = thumbnail_result[counter]
img.click()
time.sleep(sleep_time)
actual_images = wd.find_elements_by_css_selector('img.n3VNCb')
print(f'{len(actual_images)} candidate actual images are found for image {counter} !!')
for actual_image in actual_images:
if actual_image.get_attribute('src') and 'http' in actual_image.get_attribute('src'):
links.append(actual_image.get_attribute('src'))
else:
pass
print(f'no of links extracted = {len(links)}')
counter += 1
f = open('train_dumps\image_links_{}.pickle'.format(search_string.replace(' ', '')), 'ab')
pickle.dump(links, f)
f.close()
print('{} image links have been saved in pickle format!!'.format(len(links)))
wd.quit()
def imagedownloader(self, query):
if not os.path.exists(os.path.join('celeb_images', query)):
os.mkdir(os.path.join('celeb_images', query))
links = pickle.loads(open('train_dumps\image_links_{}.pickle'.format(query.replace(' ', '')), 'rb').read())
counter = 0
for i, link in enumerate(links):
# try:
response = requests.get(link)
f = open(os.path.join('celeb_images', query, 'img_{}.jpg'.format(str(i+1))), 'wb')
f.write(response.content)
f.close()
counter += 1
print('Total downloaded imges = {}'.format(counter))
# except:
# print('Cannot download image {}'.format(i))
print('{} images of {} have been downloaded!!'.format(len(links), query))
| [
"noreply@github.com"
] | noreply@github.com |
0ab796f72f784b236f26c7a00d313df9f1ed0f6e | 7bf5c0107bc2aa5eb2cccacc7096d95d0d54f176 | /config/settings.py | e7c097b616f92377165a76b7ed3144228d9e9dd5 | [] | no_license | aycaateser/djangoBlog | 072704cf12334906953ff9b9f3e753ba290ba510 | 921f1e48d1efd32b1f9b6b3ad33474f6bf1e5856 | refs/heads/master | 2023-08-04T04:29:05.918480 | 2021-09-18T14:53:02 | 2021-09-18T14:53:02 | 401,058,729 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,090 | py | """
Django settings for config project.
Generated by 'django-admin startproject' using Django 3.1.5.
For more information on this file, see
https://docs.djangoproject.com/en/3.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.1/ref/settings/
"""
from pathlib import Path
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'on42z8izw!ip*@zj^2&ks5+(&o_(^+ot&f7jxo30eb0@med&=w'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'blog',
'ckeditor',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'config.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'config.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.1/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': BASE_DIR / 'db.sqlite3',
}
}
# Password validation
# https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.1/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.1/howto/static-files/
STATIC_URL = '/static/'
| [
"56490914+aycaateser@users.noreply.github.com"
] | 56490914+aycaateser@users.noreply.github.com |
58bcee664f37fd7932bda3ef2c04efa273f85d5a | 743d58b82ed4aaeb556e703e3f698072087f98da | /user/views.py | fccc2e3d2f6705bd62cb1efde1794831ea2d5616 | [] | no_license | johir9185/warrant_management | 45397ebab0be8ab2a8b8999718c5f370e734eb8f | 061d8b2f6a5e888dcd3b81bd89b3dd8bc2cd032b | refs/heads/main | 2023-08-22T11:11:41.537185 | 2021-10-07T11:20:28 | 2021-10-07T11:20:28 | 414,567,032 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,714 | py | from django.contrib.auth.decorators import login_required
from django.utils.decorators import method_decorator
from user.models import CustomUser
from user.forms import UserForm
from django.shortcuts import redirect, render
from django.views.generic.base import TemplateView
# Create your views here.
# user views start
@method_decorator(login_required, name='dispatch', )
def user_list(request):
data = {'user_list': CustomUser.objects.all()}
return render(request, "user/list.html", data)
@method_decorator(login_required, name='dispatch', )
def user_form(request, id=0):
if request.method == 'GET':
if id == 0:
form = UserForm()
else:
user = CustomUser.objects.get(pk=id)
form = UserForm(instance=user)
return render(request, "user/create.html", {'form': form, 'id': id})
else:
if id == 0:
form = UserForm(request.POST)
else:
user = CustomUser.objects.get(pk=id)
form = UserForm(request.POST, instance=user)
if form.is_valid():
form.save()
return redirect('/user/list')
@method_decorator(login_required, name='dispatch', )
def user_delete(request, id):
user = CustomUser.objects.get(pk=id)
user.delete()
return redirect('/user/list')
# user views end
@method_decorator(login_required, name='dispatch', )
class SampleTemplateView(TemplateView):
template_name = 'user_list.html'
@method_decorator(login_required, name='dispatch', )
class DashboardTemplate(TemplateView):
template_name = 'dashboard.html'
@method_decorator(login_required, name='dispatch', )
class UnionTemplate(TemplateView):
template_name = 'union.html'
| [
"johir9185@gmail.com"
] | johir9185@gmail.com |
fbe7dd8af83e6e959b7c891b3883ac4c3029f0e0 | 0ccd82d94bfa1f6f1c0728dd19d89b7a29389a6f | /DOCODEX3/UmbralesN.py | 33595d18746065f6e3bcc37f87dcf975668459c7 | [] | no_license | plreyes/Memoria-DOCODEx3 | e571bea5fe87ce731da2b4becd29ea1f61bcaf55 | f2d4398de13fef7a3832a6c8c066fffa92456ddd | refs/heads/master | 2020-12-24T09:22:24.184300 | 2016-11-22T16:11:26 | 2016-11-22T16:11:26 | 73,300,180 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 125,904 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
a = [0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.001,
0.001,
0.001,
0.001,
0.001,
0.001,
0.001,
0.002,
0.003,
0.003,
0.003,
0.003,
0.004,
0.004,
0.004,
0.004,
0.004,
0.004,
0.004,
0.005,
0.005,
0.005,
0.006,
0.006,
0.006,
0.006,
0.006,
0.006,
0.006,
0.007,
0.007,
0.007,
0.007,
0.007,
0.007,
0.007,
0.008,
0.008,
0.008,
0.008,
0.008,
0.009,
0.009,
0.009,
0.009,
0.009,
0.009,
0.01,
0.01,
0.01,
0.01,
0.01,
0.01,
0.01,
0.01,
0.011,
0.011,
0.011,
0.011,
0.011,
0.011,
0.011,
0.011,
0.011,
0.012,
0.012,
0.012,
0.012,
0.012,
0.012,
0.013,
0.013,
0.013,
0.013,
0.014,
0.014,
0.014,
0.015,
0.015,
0.015,
0.016,
0.016,
0.016,
0.016,
0.016,
0.016,
0.016,
0.016,
0.016,
0.016,
0.017,
0.017,
0.017,
0.017,
0.017,
0.017,
0.017,
0.018,
0.018,
0.018,
0.018,
0.018,
0.018,
0.018,
0.018,
0.018,
0.019,
0.019,
0.019,
0.019,
0.019,
0.019,
0.019,
0.019,
0.019,
0.02,
0.02,
0.02,
0.02,
0.02,
0.02,
0.02,
0.02,
0.021,
0.021,
0.021,
0.021,
0.021,
0.021,
0.021,
0.021,
0.021,
0.021,
0.022,
0.022,
0.022,
0.022,
0.022,
0.022,
0.022,
0.022,
0.022,
0.022,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.023,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.024,
0.025,
0.025,
0.025,
0.025,
0.025,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.026,
0.027,
0.027,
0.027,
0.027,
0.027,
0.027,
0.027,
0.027,
0.027,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.028,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.029,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.03,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.031,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.032,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.033,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.034,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.035,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.036,
0.037,
0.037,
0.037,
0.037,
0.037,
0.037,
0.037,
0.037,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.038,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.039,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.04,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.041,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.042,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.043,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.044,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.045,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.046,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.047,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.048,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.049,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.05,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.051,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.052,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.053,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.054,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.055,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.056,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.057,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.058,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.059,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.06,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.061,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.062,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.063,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.064,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.065,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.066,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.067,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.068,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.069,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.07,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.071,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.072,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.073,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.074,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.075,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.076,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.077,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.078,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.079,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.08,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.081,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.082,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.083,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.084,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.085,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.086,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.087,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.088,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.089,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.09,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.091,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.092,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.093,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.094,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.095,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.096,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.097,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.098,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.099,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.1,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.101,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.102,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.103,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.104,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.105,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.106,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.107,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.108,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.109,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.11,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.111,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.112,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.113,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.114,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.115,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.116,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.117,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.118,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.119,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.12,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.121,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.122,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.123,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.124,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.126,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.127,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.128,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.129,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.13,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.131,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.132,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.133,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.134,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.135,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.136,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.137,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.138,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.139,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.14,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.141,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.142,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.143,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.144,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.145,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.146,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.147,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.148,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.149,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.15,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.151,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.152,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.153,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.154,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.155,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.156,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.157,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.158,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.159,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.16,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.161,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.162,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.163,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.164,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.165,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.166,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.167,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.168,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.169,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.17,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.171,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.172,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.173,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.174,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.175,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.176,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.177,
0.178,
0.178,
0.178,
0.178,
0.178,
0.178,
0.178,
0.178,
0.178,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.179,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.18,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.181,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.182,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.183,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.184,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.185,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.186,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.187,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.188,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.189,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.19,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.191,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.192,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.193,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.194,
0.195,
0.195,
0.195,
0.195,
0.195,
0.195,
0.195,
0.195,
0.195,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.196,
0.197,
0.197,
0.197,
0.197,
0.197,
0.197,
0.197,
0.197,
0.197,
0.197,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.198,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.199,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.2,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.201,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.202,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.203,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.204,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.205,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.206,
0.207,
0.207,
0.207,
0.207,
0.207,
0.207,
0.207,
0.208,
0.208,
0.208,
0.208,
0.208,
0.208,
0.208,
0.208,
0.209,
0.209,
0.209,
0.209,
0.209,
0.209,
0.209,
0.209,
0.21,
0.21,
0.21,
0.21,
0.21,
0.21,
0.21,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.211,
0.212,
0.212,
0.212,
0.212,
0.212,
0.212,
0.212,
0.212,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.213,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.214,
0.215,
0.215,
0.215,
0.215,
0.215,
0.215,
0.215,
0.215,
0.215,
0.215,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.216,
0.217,
0.217,
0.217,
0.217,
0.217,
0.217,
0.218,
0.218,
0.218,
0.218,
0.218,
0.218,
0.218,
0.219,
0.219,
0.219,
0.219,
0.219,
0.219,
0.22,
0.22,
0.22,
0.22,
0.22,
0.22,
0.22,
0.22,
0.22,
0.221,
0.221,
0.221,
0.221,
0.221,
0.221,
0.221,
0.221,
0.222,
0.222,
0.222,
0.222,
0.222,
0.222,
0.222,
0.222,
0.222,
0.223,
0.223,
0.223,
0.223,
0.223,
0.223,
0.223,
0.223,
0.223,
0.224,
0.224,
0.224,
0.224,
0.224,
0.224,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.225,
0.226,
0.226,
0.226,
0.226,
0.226,
0.226,
0.226,
0.226,
0.227,
0.227,
0.227,
0.227,
0.227,
0.227,
0.227,
0.227,
0.227,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.228,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.229,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.23,
0.231,
0.231,
0.231,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.232,
0.233,
0.233,
0.233,
0.233,
0.233,
0.234,
0.234,
0.234,
0.234,
0.234,
0.235,
0.235,
0.235,
0.235,
0.235,
0.235,
0.235,
0.235,
0.235,
0.235,
0.236,
0.236,
0.236,
0.236,
0.236,
0.236,
0.237,
0.237,
0.237,
0.238,
0.239,
0.239,
0.239,
0.239,
0.239,
0.239,
0.239,
0.24,
0.24,
0.24,
0.24,
0.24,
0.24,
0.24,
0.241,
0.241,
0.241,
0.241,
0.241,
0.241,
0.242,
0.243,
0.243,
0.243,
0.243,
0.243,
0.243,
0.243,
0.243,
0.244,
0.244,
0.244,
0.244,
0.244,
0.244,
0.244,
0.245,
0.245,
0.245,
0.246,
0.247,
0.247,
0.247,
0.247,
0.247,
0.248,
0.248,
0.248,
0.248,
0.248,
0.248,
0.249,
0.249,
0.25,
0.25,
0.25,
0.25,
0.25,
0.251,
0.251,
0.251,
0.251,
0.251,
0.251,
0.252,
0.252,
0.253,
0.253,
0.253,
0.254,
0.254,
0.254,
0.254,
0.254,
0.255,
0.255,
0.255,
0.255,
0.256,
0.256,
0.256,
0.256,
0.256,
0.256,
0.256,
0.256,
0.256,
0.257,
0.258,
0.258,
0.258,
0.259,
0.259,
0.259,
0.259,
0.259,
0.259,
0.26,
0.26,
0.26,
0.261,
0.261,
0.261,
0.261,
0.261,
0.262,
0.262,
0.262,
0.262,
0.262,
0.262,
0.263,
0.263,
0.263,
0.264,
0.265,
0.265,
0.265,
0.265,
0.265,
0.266,
0.266,
0.266,
0.266,
0.266,
0.267,
0.267,
0.268,
0.268,
0.268,
0.268,
0.268,
0.269,
0.269,
0.269,
0.269,
0.271,
0.271,
0.271,
0.271,
0.271,
0.271,
0.272,
0.272,
0.272,
0.272,
0.273,
0.273,
0.273,
0.273,
0.273,
0.274,
0.274,
0.275,
0.275,
0.275,
0.276,
0.276,
0.276,
0.277,
0.277,
0.277,
0.277,
0.277,
0.277,
0.277,
0.278,
0.278,
0.278,
0.278,
0.278,
0.279,
0.279,
0.28,
0.28,
0.28,
0.28,
0.28,
0.28,
0.281,
0.281,
0.281,
0.281,
0.281,
0.282,
0.283,
0.283,
0.283,
0.283,
0.284,
0.284,
0.284,
0.284,
0.284,
0.284,
0.284,
0.285,
0.285,
0.285,
0.286,
0.286,
0.286,
0.287,
0.287,
0.287,
0.287,
0.287,
0.287,
0.287,
0.288,
0.288,
0.288,
0.288,
0.288,
0.288,
0.289,
0.289,
0.289,
0.289,
0.289,
0.289,
0.29,
0.29,
0.29,
0.29,
0.291,
0.291,
0.292,
0.292,
0.292,
0.292,
0.293,
0.293,
0.293,
0.293,
0.293,
0.294,
0.294,
0.294,
0.294,
0.295,
0.295,
0.296,
0.296,
0.296,
0.297,
0.297,
0.298,
0.298,
0.299,
0.299,
0.299,
0.299,
0.3,
0.301,
0.301,
0.301,
0.301,
0.302,
0.302,
0.303,
0.303,
0.303,
0.304,
0.304,
0.305,
0.305,
0.305,
0.306,
0.306,
0.306,
0.306,
0.306,
0.306,
0.307,
0.307,
0.308,
0.308,
0.309,
0.309,
0.31,
0.31,
0.31,
0.311,
0.311,
0.312,
0.313,
0.313,
0.313,
0.314,
0.315,
0.316,
0.316,
0.317,
0.317,
0.317,
0.317,
0.318,
0.319,
0.319,
0.32,
0.32,
0.321,
0.321,
0.322,
0.323,
0.323,
0.324,
0.324,
0.324,
0.325,
0.325,
0.325,
0.327,
0.327,
0.327,
0.328,
0.328,
0.329,
0.329,
0.329,
0.329,
0.329,
0.33,
0.33,
0.332,
0.333,
0.333,
0.334,
0.334,
0.337,
0.339,
0.34,
0.34,
0.341,
0.342,
0.343,
0.345,
0.348,
0.349,
0.349,
0.35,
0.35,
0.35,
0.351,
0.352,
0.353,
0.353,
0.354,
0.354,
0.354,
0.354,
0.356,
0.365,
0.37,
0.37,
0.371,
0.372,
0.375,
0.382,
0.386,
0.386,
0.389,
0.393,
0.393,
0.394,
0.396,
0.396,
0.4,
0.404,
0.409,
0.41,
0.413,
0.421,
0.427,
0.439,
0.452,
0.463,
0.476,
0.478,
0.491,
0.516]
print np.mean(a)*2.3
plt.hist(a, bins=150)
plt.xlabel(r'$\sigma*\lambda$')
plt.ylabel('Frecuencua')
plt.title(r'Histograma')
plt.show()
| [
"pablo.reyes@net-works.cl"
] | pablo.reyes@net-works.cl |
620acd2432ea3ff3bb15d4301c8bbf72de6e9a3a | cfaa3a0762ca9655845637f4983c381d8d139a84 | /examples/summary.py | 00ce28e190ef109b1babc1fef25c5b12b3bffcb3 | [
"Apache-2.0"
] | permissive | dteach-rv/mrtparse | 6d72775060ef826a925f36e72562c2cde12b58c6 | 3a34fde53b5c2a65c11c0a559e06d18edb21e441 | refs/heads/master | 2020-07-22T01:02:12.368866 | 2019-05-02T15:19:29 | 2019-05-02T15:19:29 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,088 | py | #!/usr/bin/env python
'''
summary.py - This script displays summary of MRT format data.
Copyright (C) 2019 Tetsumune KISO
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.
Authors:
Tetsumune KISO <t2mune@gmail.com>
Yoshiyuki YAMAUCHI <info@greenhippo.co.jp>
Nobuhiro ITOU <js333123@gmail.com>
'''
import sys
from mrtparse import *
from datetime import datetime
summary = {}
start_time = end_time = 0
def count(d, k):
try:
d[k] += 1
except KeyError:
d[k] = 1
def total(d):
if isinstance(d, int):
return d
n = 0
for k in d:
if isinstance(d[k], dict):
n += total(d[k])
else:
n += d[k]
return n
def print_line(lv, s, n):
fmt = '%s%%-%ds%%8d' % (' ' * 4 * lv, 32 - 4 * lv)
print(fmt % (s + ':', n))
def get_summary(f):
global start_time, end_time
d = Reader(f)
m = d.next()
start_time = end_time = m.mrt.ts
d = Reader(f)
for m in d:
m = m.mrt
if m.err:
continue
if m.ts < start_time:
start_time = m.ts
elif m.ts > end_time:
end_time = m.ts
if m.type == MRT_T['BGP4MP'] \
or m.type == MRT_T['BGP4MP_ET']:
if not m.type in summary:
summary[m.type] = {}
if m.subtype == BGP4MP_ST['BGP4MP_MESSAGE'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_AS4'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_LOCAL'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_AS4_LOCAL'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_ADDPATH'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_AS4_ADDPATH'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_LOCAL_ADDPATH'] \
or m.subtype == BGP4MP_ST['BGP4MP_MESSAGE_AS4_LOCAL_ADDPATH']:
if not m.subtype in summary[m.type]:
summary[m.type][m.subtype] = {}
count(summary[m.type][m.subtype], m.bgp.msg.type)
elif m.subtype == BGP4MP_ST['BGP4MP_STATE_CHANGE'] \
or m.subtype == BGP4MP_ST['BGP4MP_STATE_CHANGE_AS4']:
if not m.subtype in summary[m.type]:
summary[m.type][m.subtype] = {}
count(summary[m.type][m.subtype], m.bgp.new_state)
else:
count(summary[m.type], m.subtype)
else:
if hasattr(m, 'subtype'):
if not m.type in summary:
summary[m.type] = {}
count(summary[m.type], m.subtype)
else:
count(summary, m.type)
def print_summary():
print('[%s - %s]' % (
datetime.fromtimestamp(start_time).strftime('%Y-%m-%d %H:%M:%S'),
datetime.fromtimestamp(end_time).strftime('%Y-%m-%d %H:%M:%S')))
for k1 in sorted(summary.keys()):
print_line(0, MRT_T[k1], total(summary[k1]))
if k1 == MRT_T['TABLE_DUMP']:
for k2 in sorted(summary[k1].keys()):
print_line(1, TD_ST[k2], total(summary[k1][k2]))
elif k1 == MRT_T['TABLE_DUMP_V2']:
for k2 in sorted(summary[k1].keys()):
print_line(1, TD_V2_ST[k2], total(summary[k1][k2]))
elif k1 == MRT_T['BGP4MP'] \
or k1 == MRT_T['BGP4MP_ET']:
for k2 in sorted(summary[k1].keys()):
print_line(1, BGP4MP_ST[k2], total(summary[k1][k2]))
if k2 == BGP4MP_ST['BGP4MP_MESSAGE'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_AS4'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_LOCAL'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_AS4_LOCAL'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_ADDPATH'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_AS4_ADDPATH'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_LOCAL_ADDPATH'] \
or k2 == BGP4MP_ST['BGP4MP_MESSAGE_AS4_LOCAL_ADDPATH']:
for k3 in sorted(summary[k1][k2].keys()):
print_line(2, BGP_MSG_T[k3], total(summary[k1][k2][k3]))
elif k2 == BGP4MP_ST['BGP4MP_STATE_CHANGE'] \
or k2 == BGP4MP_ST['BGP4MP_STATE_CHANGE_AS4']:
for k3 in sorted(summary[k1][k2].keys()):
print_line(2, BGP_FSM[k3], total(summary[k1][k2][k3]))
def main():
if len(sys.argv) != 2:
print('Usage: %s FILENAME' % sys.argv[0])
exit(1)
get_summary(sys.argv[1])
print_summary()
if __name__ == '__main__':
main()
| [
"t2mune@gmail.com"
] | t2mune@gmail.com |
9e4ee13b50083c91fb8d6304fd6933a06bc69f7b | 278b060127761f2300037ed8983db5901e7f5ca5 | /17.py | 00f6bf7b9cadc6f7d14338e090339acf473e90f2 | [] | no_license | AakashJaiswal21998/Basic-Python-Examples | d6de41f19fd4cdf3d395f151c20d0fd7e236680f | 9911f6e4faede067363cc18fc224d957c8e9c908 | refs/heads/master | 2022-12-19T00:56:34.699926 | 2020-10-01T04:04:01 | 2020-10-01T04:04:01 | 300,136,153 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 393 | py | '''Program to print the sum of 1/1-1/2+1/3+1/4-1/5+1/6-1/7.............1/n
Developer:Aakash
Date:03.03.2020
--------------------------------'''
a=int(input("Enter the number for which you want sum up="))
i=1;j=2
su=0;sm=0;
while(i<=a):
su=su+(1/i)
i=i+2
print("The odd sum is=",su)
while(j<=a):
sm=sm+(1/j)
j=j+2
print("The even sum is=",sm)
print("The desired sum is=",su-sm)
| [
"aakash123564@gmail.com"
] | aakash123564@gmail.com |
0ef158ff4223440075caf395937a47ef60ba3264 | 0d8e03c2d3d506a878730b6bedf3af4b714ad431 | /dz5/home/models.py | 96a0425bc2cee5f83640da9e90eec77074bfbadf | [] | no_license | RyslanaBinko/Django | 7baa0e1352fd3ec75aa1ea8967a541be92155e0f | 6df5aff2c1b12202ae75e3827c49cd1a43b6f2b8 | refs/heads/main | 2023-04-01T09:15:42.910096 | 2021-03-16T10:49:15 | 2021-03-16T10:49:15 | 321,369,492 | 0 | 0 | null | 2021-03-16T10:49:16 | 2020-12-14T14:15:40 | Python | UTF-8 | Python | false | false | 1,587 | py | from django.db import models
class Student(models.Model):
id = models.AutoField(primary_key=True) # noqa
name = models.CharField(max_length=200)
normalized_name = models.CharField(max_length=200, null=True)
age = models.SmallIntegerField(null=True)
sex = models.CharField(max_length=200, null=True)
address = models.CharField(max_length=200, null=True)
description = models.TextField(max_length=200, null=True)
birthday = models.DateField(null=True)
email = models.CharField(max_length=200, null=True)
url = models.CharField(max_length=200, null=True)
subject = models.ForeignKey("home.Subject",
on_delete=models.SET_NULL, null=True)
book = models.OneToOneField("home.Book",
on_delete=models.CASCADE, null=True)
teacher = models.ManyToManyField("home.Teacher")
class Teacher(models.Model):
id = models.AutoField(primary_key=True) # noqa
name = models.CharField(max_length=200, null=True)
class Subject(models.Model):
id = models.AutoField(primary_key=True) # noqa
title = models.CharField(max_length=200)
class Book(models.Model):
id = models.AutoField(primary_key=True) # noqa
title = models.CharField(max_length=200, null=True)
class Currency(models.Model):
id = models.AutoField(primary_key=True) # noqa
ccy = models.CharField(max_length=5, null=True)
base_ccy = models.CharField(max_length=5, null=True)
buy = models.FloatField(max_length=200, null=True)
sale = models.FloatField(max_length=200, null=True)
| [
"binko.ryslana@gmail.com"
] | binko.ryslana@gmail.com |
0a85d3a207041fe40d86bcaf79b55bb1e71d6e30 | 3ac6cc22d2a1c727064f4721a8e4e026dcfbfc9b | /configs/top_down/resnet/mpii/res101_mpii_256x256.py | 17e9c7e66d65027869079d8b699e9a86f265eba9 | [
"Apache-2.0"
] | permissive | Alex-bd/mmpose | 8a3201a40208c4687342ad08ef83c1c79d0e775a | 5bf1d8ceafc6ac4c3e1f4fdf10f5a8a0e86ad0e9 | refs/heads/master | 2022-12-12T00:10:13.368567 | 2020-08-31T11:15:01 | 2020-08-31T11:15:01 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,340 | py | log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
evaluation = dict(interval=1, metric='PCKh')
optimizer = dict(
type='Adam',
lr=5e-4,
)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[170, 200])
total_epochs = 210
log_config = dict(
interval=50, hooks=[
dict(type='TextLoggerHook'),
])
channel_cfg = dict(
num_output_channels=16,
dataset_joints=16,
dataset_channel=list(range(16)),
inference_channel=list(range(16)))
# model settings
model = dict(
type='TopDown',
pretrained='models/pytorch/imagenet/resnet101-5d3b4d8f.pth',
backbone=dict(type='ResNet', depth=101),
keypoint_head=dict(
type='TopDownSimpleHead',
in_channels=2048,
out_channels=channel_cfg['num_output_channels'],
),
train_cfg=dict(),
test_cfg=dict(
flip_test=True,
post_process=True,
shift_heatmap=True,
unbiased_decoding=False,
modulate_kernel=11),
loss_pose=dict(type='JointsMSELoss', use_target_weight=True))
data_cfg = dict(
image_size=[256, 256],
heatmap_size=[64, 64],
num_output_channels=channel_cfg['num_output_channels'],
num_joints=channel_cfg['dataset_joints'],
dataset_channel=channel_cfg['dataset_channel'],
inference_channel=channel_cfg['inference_channel'],
use_gt_bbox=True,
bbox_file=None,
)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='TopDownRandomFlip', flip_prob=0.5),
dict(
type='TopDownGetRandomScaleRotation', rot_factor=40, scale_factor=0.5),
dict(type='TopDownAffine'),
dict(type='ToTensor'),
dict(
type='NormalizeTensor',
mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225]),
dict(type='TopDownGenerateTarget', sigma=2),
dict(
type='Collect',
keys=['img', 'target', 'target_weight'],
meta_keys=[
'image_file', 'joints_3d', 'joints_3d_visible', 'center', 'scale',
'rotation', 'flip_pairs'
]),
]
val_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='TopDownAffine'),
dict(type='ToTensor'),
dict(
type='NormalizeTensor',
mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225]),
dict(
type='Collect',
keys=[
'img',
],
meta_keys=['image_file', 'center', 'scale', 'rotation', 'flip_pairs']),
]
data_root = 'data/mpii'
data = dict(
samples_per_gpu=64,
workers_per_gpu=2,
train=dict(
type='TopDownMpiiDataset',
ann_file=f'{data_root}/annotations/mpii_train.json',
img_prefix=f'{data_root}/images/',
data_cfg=data_cfg,
pipeline=train_pipeline),
val=dict(
type='TopDownMpiiDataset',
ann_file=f'{data_root}/annotations/mpii_val.json',
img_prefix=f'{data_root}/images/',
data_cfg=data_cfg,
pipeline=val_pipeline),
test=dict(
type='TopDownMpiiDataset',
ann_file=f'{data_root}/annotations/mpii_val.json',
img_prefix=f'{data_root}/images/',
data_cfg=data_cfg,
pipeline=val_pipeline),
)
| [
"noreply@github.com"
] | noreply@github.com |
711d23ae5d368b269fb5d365992d30d65c87469d | 21bd158545402c0912f303444002c7c8b62720d1 | /src/url_storer_test.py | 587d54d72613811f37c3d83bf54f7cefe6fedac4 | [
"MIT"
] | permissive | Taekyoon/PyCrawler | 23ef5cd6971ca00971ffd93380d3f915b75da5ea | 93f0ef8bc07436ff70ba9a198b89d2ffa27bcc9e | refs/heads/master | 2021-01-20T14:48:31.499910 | 2017-02-22T08:18:19 | 2017-02-22T08:18:19 | 82,775,691 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,214 | py | from url_storer import UrlStorer
table_name = 'TEST'
def create_database():
UrlStorer('test.db')
UrlStorer.create_table(table_name)
def close_database():
UrlStorer.close()
def get_test():
return UrlStorer.get(table_name)
def insert_test(key):
UrlStorer.put(table_name,key,1)
def exist_test():
UrlStorer.exist(table_name, 'naver.com')
def delete_test():
UrlStorer.delete(table_name, 'naver.com')
def test():
create_database()
insert_test('abc')
delete_test()
close_database()
import os
import threading
from queue import Queue
NUMBER_OF_THREADS = 8
def create_workers():
for _ in range(NUMBER_OF_THREADS):
t = threading.Thread(target=work)
t.daemon = True
t.start()
def work():
while True:
key = queue.get()
for i in range(1000):
insert_test(key + str(i))
print("%s: %s of 1000 is done." % (threading.current_thread().name, i+1))
queue.task_done()
create_database()
queue = Queue()
input_list = ['a'*n for n in range(10)]
for l in input_list:
queue.put(l)
create_workers()
queue.join()
for i,j in get_test():
print(i,j)
close_database()
os.delete('test.db')
#test()
| [
"tgchoi03@gmail.com"
] | tgchoi03@gmail.com |
bc52f37436a7565189d51e912a3ff824c5577c49 | d21326e0e2604431549e80cf025074624f36c6bb | /boneless/test/test_alsru.py | a8fd22835150c7e12b619be0fccb994aac84ee72 | [
"0BSD",
"Apache-2.0"
] | permissive | zignig/Boneless-CPU | ad9232d82e19c1035f5e10443b81f147d96c4072 | 10bb571b4efab015e1bf147c78f0b8b3c93443e4 | refs/heads/master | 2020-04-25T20:29:47.987910 | 2019-07-05T05:35:18 | 2019-07-05T05:35:18 | 173,051,283 | 0 | 0 | NOASSERTION | 2019-02-28T06:06:16 | 2019-02-28T06:06:15 | null | UTF-8 | Python | false | false | 4,413 | py | import unittest
import contextlib
import random
from nmigen import *
from nmigen.back.pysim import *
from ..gateware.alsru import *
class ALSRUTestCase:
dut_cls = None
def setUp(self):
self.checks = 100
self.width = 16
self.dut = self.dut_cls(self.width)
@contextlib.contextmanager
def assertComputes(self, ctrl, ci=None, si=None):
asserts = []
yield(self.dut, asserts)
random.seed(0)
for _ in range(self.checks):
rand_a = random.randint(0, (1 << self.width) - 1)
rand_b = random.randint(0, (1 << self.width) - 1)
rand_r = random.randint(0, (1 << self.width) - 1)
rand_ci = random.randint(0, 1) if ci is None else ci
rand_si = random.randint(0, 1) if si is None else si
with Simulator(self.dut) as sim:
def process():
yield self.dut.ctrl.eq(ctrl)
yield self.dut.a.eq(rand_a)
yield self.dut.b.eq(rand_b)
yield self.dut.r.eq(rand_r)
yield self.dut.ci.eq(rand_ci)
yield self.dut.si.eq(rand_si)
yield Delay()
fail = False
msg = "for a={:0{}x} b={:0{}x} ci={} si={}:" \
.format(rand_a, self.width // 4,
rand_b, self.width // 4,
rand_ci,
rand_si)
for signal, expr in asserts:
actual = (yield signal)
expect = (yield expr)
if expect != actual:
fail = True
msg += " {}={:0{}x} (expected {:0{}x})"\
.format(signal.name,
actual, signal.nbits // 4,
expect, signal.nbits // 4)
if fail:
self.fail(msg)
sim.add_process(process)
sim.run()
def test_A(self):
with self.assertComputes(self.dut_cls.CTRL_A, ci=0) as (dut, asserts):
asserts += [(dut.o, dut.a)]
def test_B(self):
with self.assertComputes(self.dut_cls.CTRL_B, ci=0) as (dut, asserts):
asserts += [(dut.o, dut.b)]
def test_nB(self):
with self.assertComputes(self.dut_cls.CTRL_nB, ci=0) as (dut, asserts):
asserts += [(dut.o, ~dut.b)]
def test_AaB(self):
with self.assertComputes(self.dut_cls.CTRL_AaB, ci=0) as (dut, asserts):
asserts += [(dut.o, dut.a & dut.b)]
def test_AoB(self):
with self.assertComputes(self.dut_cls.CTRL_AoB, ci=0) as (dut, asserts):
asserts += [(dut.o, dut.a | dut.b)]
def test_AxB(self):
with self.assertComputes(self.dut_cls.CTRL_AxB, ci=0) as (dut, asserts):
asserts += [(dut.o, dut.a ^ dut.b)]
def test_ApB(self):
with self.assertComputes(self.dut_cls.CTRL_ApB) as (dut, asserts):
result = dut.a + dut.b + dut.ci
asserts += [(dut.o, result[:self.width]),
(dut.co, result[self.width]),
(dut.vo, (dut.a[-1] == dut.b[-1]) &
(dut.a[-1] != result[self.width - 1]))]
def test_AmB(self):
with self.assertComputes(self.dut_cls.CTRL_AmB) as (dut, asserts):
result = dut.a - dut.b - ~dut.ci
asserts += [(dut.o, result[:self.width]),
(dut.co, ~result[self.width]),
(dut.vo, (dut.a[-1] == ~dut.b[-1]) &
(dut.a[-1] != result[self.width - 1]))]
def test_SL(self):
with self.assertComputes(self.dut_cls.CTRL_SL) as (dut, asserts):
result = (dut.r << 1) | dut.si
asserts += [(dut.o, result[:self.width]),
(dut.so, dut.r[-1])]
def test_SR(self):
with self.assertComputes(self.dut_cls.CTRL_SR) as (dut, asserts):
result = (dut.r >> 1) | (dut.si << (self.width - 1))
asserts += [(dut.o, result[:self.width]),
(dut.so, dut.r[0])]
class ALSRU_4LUT_TestCase(ALSRUTestCase, unittest.TestCase):
dut_cls = ALSRU_4LUT
| [
"whitequark@whitequark.org"
] | whitequark@whitequark.org |
75fd5e661c51351127197212dce3457ddcf5037a | aea7f59f919992d5b49366552e40d777042a0a7b | /lib/event_handler.py | 3a37e9dd98e30b54ad10b8ce6683532b36a01c62 | [] | no_license | yogae/serverless-lambdaedge-resize | 2f8334aef87a525574abe69562085ed1eb3a2b56 | 860e01b673f83cc4c186ce8fb7fd8a6a987368aa | refs/heads/master | 2022-11-25T04:01:06.916311 | 2019-10-27T07:55:28 | 2019-10-27T07:55:28 | 216,831,630 | 0 | 0 | null | 2022-11-22T04:46:36 | 2019-10-22T14:16:28 | Python | UTF-8 | Python | false | false | 1,054 | py | import urllib
def parse_resolution(request):
query_string = request.get("querystring", None)
if query_string is None:
resolution = "origin"
else:
resolution = urllib.parse.parse_qs(query_string).get("resolution", None)
if resolution is None:
resolution = "origin"
else:
resolution = resolution[0]
return resolution
def parse_origin(request):
domain_name = request["origin"]["s3"]["domainName"]
bucket_name = domain_name.split(".")[0]
return bucket_name
class EventHandler:
def __init__(self, event):
self.event = event
def get_request(self):
request = self.event["Records"][0]["cf"]["request"]
key = request["uri"][1:] if request["uri"].startswith("/") else request["uri"]
resolution = parse_resolution(request)
bucket_name = parse_origin(request)
return dict(resolution = resolution, key = key, bucket_name = bucket_name)
def get_response(self):
return self.event["Records"][0]["cf"]["response"]
| [
""
] | |
0baaa732089fcef332a853334b008c15112aac4d | 42d51b7f53a88e2808066782cc9786634a9138e5 | /recipes/iris_nn.py | 7d0721dc3a4c7d17be6d6e61297c965d4b64043c | [] | no_license | kent0304/PyTorchTutorial | 64707a3bc8e187a3bddf62a7bafe5afc672d163f | ee0a4bb7904829f06880991bd1cdf4689ce8d912 | refs/heads/master | 2022-12-11T21:18:38.889200 | 2020-09-16T07:56:18 | 2020-09-16T07:56:18 | 264,959,345 | 0 | 0 | null | 2020-05-18T14:12:51 | 2020-05-18T14:09:56 | Ruby | UTF-8 | Python | false | false | 1,823 | py | from sklearn import datasets
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
iris = datasets.load_iris()
# 教師ラベルをダミー変数化する必要はない
# y = np.zeros((len(iris.target), 1+iris.target.max()), dtype=int)
# y[np.arange(len(iris.target)), iris.target] = 1
y = iris.target
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(iris.data, y, test_size=0.2, random_state=0)
X_train = torch.tensor(X_train, dtype=torch.float)
y_train = torch.tensor(y_train)
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.fc1 = nn.Linear(4, 10)
self.fc2 = nn.Linear(10, 8)
self.fc3 = nn.Linear(8, 3)
def forward(self, x):
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
### Training
# ネットワークのインスタンス化
net = Net()
# パラメタータ更新手法、学習率の指定
optimizer = optim.SGD(net.parameters(), lr=0.001)
# 目的関数の指定
criterion = nn.CrossEntropyLoss()
for i in range(3000):
# 古い勾配は削除
optimizer.zero_grad()
output = net(X_train)
loss = criterion(output, y_train)
# バックプロパゲーションを用いて目的関数の微分を計算
loss.backward()
optimizer.step()
### Prediction
outputs = net(torch.tensor(X_test, dtype=torch.float))
_, predicted = torch.max(outputs.data, 1)
# print(outputs.data)
# print(torch.max(outputs.data, 1))
# 2つめの引数に1をつけることで、最大値とそのインデックスを順に出力
print(y_test)
accuracy = 100 * np.sum(predicted.numpy() == y_test) / len(iris.target)
print('accuracy = {:.1f}%'.format(accuracy))
| [
"tanaken0304.0123@gmail.com"
] | tanaken0304.0123@gmail.com |
3cf839ea331331771691d73a49bad587c20960f2 | 9952f1a28e430313211b609a73e5fa6ef4b7f976 | /lab_1/lab1.3.py | 93298e94680584cde666c1e47a5e91f17d03b718 | [] | no_license | onlysingle007/labs | f5666dc991d0fb7a14b03623454021635d8a0fc3 | f43a3f0d86ab5d370c49690bda6c5053ecf6ad2b | refs/heads/master | 2020-12-20T02:45:39.845664 | 2020-01-30T14:17:51 | 2020-01-30T14:17:51 | 235,938,089 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 268 | py | x=str(input("enter sentence to be checked: "))
print (x)
y=len(x)
z=a=b=0
for i in x:
if i.isalpha():
z=z+1
elif i.isdigit():
a=a+1
else:
b=b+1
print("number of alphabets are",z)
print("and number of numbers are",a)
print("number of special characters are",b) | [
"noreply@github.com"
] | noreply@github.com |
acdd334ba1e6d6b647648d7ce04d95c971a8a97c | 6b9084d234c87d7597f97ec95808e13f599bf9a1 | /Dataset/Utility/youtube_downloader.py | 9dfc738aba4989d5f42cfc43fb334b8de60c5b2a | [] | no_license | LitingLin/ubiquitous-happiness | 4b46234ce0cb29c4d27b00ec5a60d3eeb52c26fc | aae2d764e136ca4a36c054212b361dd7e8b22cba | refs/heads/main | 2023-07-13T19:51:32.227633 | 2021-08-03T16:02:03 | 2021-08-03T16:02:03 | 316,664,903 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,870 | py | import os
import subprocess
import threading
from tqdm import tqdm
import shutil
def _read_outputs_from_precess(process):
def _print_stdout(process):
for line_ in iter(process.stdout.readline, ""):
if len(line_) > 0:
print(line_.strip())
def _print_stderr(process):
for line_ in iter(process.stderr.readline, ""):
if len(line_) > 0:
print(line_.strip())
t1 = threading.Thread(target=_print_stdout, args=(process,))
t2 = threading.Thread(target=_print_stderr, args=(process,))
t1.start()
t2.start()
t1.join()
t2.join()
def download_youtube_videos(youtube_id_list, target_path: str, cache_path: str):
for youtube_id in tqdm(youtube_id_list):
youtube_video_path = os.path.join(target_path, youtube_id)
if os.path.exists(youtube_video_path):
continue
url = f'https://www.youtube.com/watch?v={youtube_id}'
# downloading_cache_path = os.path.join(cache_path, youtube_id)
temp_path = os.path.join(target_path, f'{youtube_id}.tmp')
if os.path.exists(temp_path):
shutil.rmtree(temp_path)
os.mkdir(temp_path)
youtube_dl_output_path = os.path.join(temp_path, '%(title)s-%(id)s.%(ext)s')
process = subprocess.Popen(['youtube-dl', '--cache-dir', cache_path, '-o', youtube_dl_output_path, url], stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding='utf-8')
_read_outputs_from_precess(process)
process.wait()
if process.returncode != 0:
print(f'Failed to download video {youtube_id}')
continue
files = os.listdir(temp_path)
if len(files) == 0:
print(f'Youtube-dl returns 0, but nothing downloaded in video {youtube_id}')
continue
os.rename(temp_path, youtube_video_path)
| [
"linliting06@live.com"
] | linliting06@live.com |
4f2562228bcdf52337ff368b81103a2b007a2635 | 9d14540c5cc793e10e7aa761cffddbb301004adc | /wide_resnet.py | 9f37d8bc2e5753a481218e443c9c67a4fa97f2db | [] | no_license | Liang-yc/will_delete_later | 290a1a5f407ad5c801895e2b2e8590d2c6cb94b9 | b5208754c1f6e868c53ba529ff32c72d11907de5 | refs/heads/master | 2022-10-12T10:01:03.456910 | 2019-08-22T22:50:06 | 2019-08-22T22:50:06 | 203,884,669 | 0 | 0 | null | 2022-09-29T12:20:19 | 2019-08-22T22:49:16 | Python | UTF-8 | Python | false | false | 2,122 | py | import keras
from keras.models import Model
from keras.layers import Dense, Conv2D, BatchNormalization, Activation
from keras.layers import Input, Add, GlobalAveragePooling2D, Dropout,PReLU
from keras import regularizers
weight_decay = 5e-4
def conv3x3(input, out_planes, stride=1):
"""3x3 convolution with padding"""
return Conv2D(out_planes, kernel_size=3, strides=stride,
padding='same', use_bias=False, kernel_initializer='he_normal',
kernel_regularizer=regularizers.l2(weight_decay))(input)
def conv1x1(input, out_planes, stride=1):
"""1x1 convolution"""
return Conv2D(out_planes, kernel_size=1, strides=stride,
padding='same', use_bias=False, kernel_initializer='he_normal',
kernel_regularizer=regularizers.l2(weight_decay))(input)
def BasicBlock(input, planes, dropout, stride=1):
inplanes = input._keras_shape[3]
out = BatchNormalization()(input)
out = PReLU()(out)
out = conv3x3(out, planes, stride)
out = BatchNormalization()(out)
out = PReLU()(out)
out = Dropout(dropout)(out)
out = conv3x3(out, planes)
if stride != 1 or inplanes != planes:
shortcut = conv1x1(input, planes, stride)
else:
shortcut = out
out = Add()([out, shortcut])
return out
def WideResNet(depth, width, num_classes=10, dropout=0.3,include_top=True):
layer = (depth - 4) // 6
input = Input(shape=(28,28,1))
x = conv3x3(input, 16)
for _ in range(layer):
x = BasicBlock(x, 16*width, dropout)
x = BasicBlock(x, 32*width, dropout, 2)
for _ in range(layer-1):
x = BasicBlock(x, 32*width, dropout)
x = BasicBlock(x, 64*width, dropout, 2)
for _ in range(layer-1):
x = BasicBlock(x, 64*width, dropout)
x = BatchNormalization()(x)
x = PReLU()(x)
x = GlobalAveragePooling2D()(x)
if include_top:
output = Dense(num_classes, activation='softmax', kernel_regularizer=regularizers.l2(weight_decay))(x)
model = Model(input, output)
model.summary()
return model
return x | [
"noreply@github.com"
] | noreply@github.com |
68e5589fe85596c30ef2e358b26b9a438f01ad92 | 0f7e18a483a44352dfac27137b8d351416f1d1bb | /application.py | c5bacc7030432a73f7dc538367825d6dc44c5983 | [] | no_license | rinoshinme/slim_finetune | b5ec4ed53a2d6c15dfa5b4cfb73677ccb58a4aa6 | 1e465e3faff668e65cc873828057365114d4cfb1 | refs/heads/master | 2022-11-07T21:02:38.253001 | 2022-11-02T14:48:45 | 2022-11-02T14:48:45 | 199,089,723 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 45 | py | from app.nsfw_process import NSFWProcessor
| [
"rinoshinme@163.com"
] | rinoshinme@163.com |
c81a40039c0c97890bc37a375a712236114ae380 | 1122bcd042953f085835483ca7809c7dfeac21e2 | /Gluon/k_means/main.py | 81e2ccb65324768e76ebb32bdd7d4405119e1af7 | [] | no_license | nguyen-viet-hung/Mxnet_Tutorial | 7b293db2f415720e144e4e506d5fd3678fbedeb4 | 9892dbd91377476f8482baff473ae2c74105faff | refs/heads/master | 2020-12-29T13:56:58.804003 | 2018-03-07T18:39:39 | 2018-03-07T18:39:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 124 | py | import mxnet as mx
import kmeans
kmeans.K_means_Algorithm(epoch=5000,centroid_numbers=10,point_numbers=5000,ctx=mx.gpu(0))
| [
"medical18@naver.com"
] | medical18@naver.com |
5d6557971ba1b18c0b15b18bead81f318c365147 | 87a22d7b301bb0234f813c5f142446f9d409e024 | /vumi_http_retry/workers/sender/tests/test_worker.py | 4235e92ef4ec536e996b3b1bb22f5a0259e6b174 | [
"BSD-2-Clause"
] | permissive | praekelt/vumi-http-retry-api | 9dad08ceef614fc9a5dc358cd45ec1927231706c | 01c1e5635b2d281986de66489582be0a7bd8e040 | refs/heads/develop | 2021-01-02T22:45:36.606706 | 2017-06-09T14:28:33 | 2017-06-09T14:28:33 | 39,622,844 | 0 | 0 | null | 2017-06-09T14:21:40 | 2015-07-24T09:15:25 | Python | UTF-8 | Python | false | false | 21,699 | py | from twisted.internet import reactor
from twisted.internet.task import Clock
from twisted.trial.unittest import TestCase
from twisted.internet.defer import (
inlineCallbacks, returnValue, DeferredQueue, Deferred)
from vumi_http_retry.workers.sender.worker import RetrySenderWorker
from vumi_http_retry.retries import (
set_req_count, get_req_count, pending_key, ready_key, add_ready)
from vumi_http_retry.tests.redis import zitems, lvalues, delete
from vumi_http_retry.tests.utils import (
Counter, ToyServer, ManualReadable, ManualWritable, pop_all)
class TestRetrySenderWorker(TestCase):
@inlineCallbacks
def teardown_worker(self, worker):
yield delete(worker.redis, 'test.*')
yield worker.teardown()
@inlineCallbacks
def mk_worker(self, config=None):
if config is None:
config = {}
config['redis_prefix'] = 'test'
config.setdefault('overrides', {}).update({'persistent': False})
worker = RetrySenderWorker(config)
self.patch_reactor_stop()
yield worker.setup(Clock())
self.addCleanup(self.teardown_worker, worker)
returnValue(worker)
def patch_retry(self):
reqs = DeferredQueue()
def retry(req):
reqs.put(req)
self.patch(RetrySenderWorker, 'retry', staticmethod(retry))
return reqs
def patch_next_req(self):
pops = []
def pop():
d = Deferred()
pops.append(d)
return d
self.patch(RetrySenderWorker, 'next_req', staticmethod(pop))
return pops
def patch_poll(self, fn):
self.patch(RetrySenderWorker, 'poll', fn)
def patch_on_error(self):
errors = []
def on_error(f):
errors.append(f.value)
self.patch(RetrySenderWorker, 'on_error', staticmethod(on_error))
return errors
def patch_reactor_stop(self):
c = Counter()
self.patch(RetrySenderWorker, 'stop_reactor', c.inc)
return c
def patch_reactor_call_later(self, clock):
self.patch(reactor, 'callLater', clock.callLater)
def patch_log(self):
msgs = []
def logger(*msg):
msgs.append(msg)
self.patch(RetrySenderWorker, 'log', staticmethod(logger))
return msgs
@inlineCallbacks
def test_retry(self):
msgs = self.patch_log()
worker = yield self.mk_worker()
yield worker.stop()
srv = yield ToyServer.from_test(self)
reqs = []
@srv.app.route('/foo')
def route(req):
reqs.append(req)
req = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 0,
'intervals': [10],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
pop_all(msgs)
yield worker.retry(req)
self.assertEqual(pop_all(msgs), [
('Retrying request', req),
('Retry successful (200)', req),
])
[req] = reqs
self.assertEqual(req.method, 'POST')
self.assertEqual((yield zitems(worker.redis, pending_key('test'))), [])
@inlineCallbacks
def test_retry_reschedule(self):
msgs = self.patch_log()
worker = yield self.mk_worker()
srv = yield ToyServer.from_test(self)
yield worker.stop()
@srv.app.route('/foo')
def route(req):
req.setResponseCode(500)
req1 = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 0,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
req2 = {
'owner_id': '1234',
'timestamp': 10,
'attempts': 0,
'intervals': [10, 30],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
pop_all(msgs)
yield worker.retry(req1)
self.assertEqual(pop_all(msgs), [
('Retrying request', req1),
('Retry failed (500)', req1),
('Rescheduling retry', req1),
])
yield worker.retry(req2)
self.assertEqual(pop_all(msgs), [
('Retrying request', req2),
('Retry failed (500)', req2),
('Rescheduling retry', req2),
])
pending = yield zitems(worker.redis, pending_key('test'))
self.assertEqual(pending, [
(5 + 20, {
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}),
(10 + 30, {
'owner_id': '1234',
'timestamp': 10,
'attempts': 1,
'intervals': [10, 30],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
})
])
@inlineCallbacks
def test_retry_end(self):
msgs = self.patch_log()
worker = yield self.mk_worker()
srv = yield ToyServer.from_test(self)
yield worker.stop()
@srv.app.route('/foo')
def route(req):
req.setResponseCode(500)
req1 = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
req2 = {
'owner_id': '1234',
'timestamp': 10,
'attempts': 2,
'intervals': [10, 30, 40],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
pop_all(msgs)
yield worker.retry(req1)
self.assertEqual(pop_all(msgs), [
('Retrying request', req1),
('Retry failed (500)', req1),
('No remaining retry intervals, discarding request', req1),
])
yield worker.retry(req2)
self.assertEqual(pop_all(msgs), [
('Retrying request', req2),
('Retry failed (500)', req2),
('No remaining retry intervals, discarding request', req2),
])
self.assertEqual((yield zitems(worker.redis, pending_key('test'))), [])
@inlineCallbacks
def test_retry_timeout_reschedule(self):
k = pending_key('test')
msgs = self.patch_log()
worker = yield self.mk_worker({'timeout': 3})
srv = yield ToyServer.from_test(self)
self.patch_reactor_call_later(worker.clock)
yield worker.stop()
@srv.app.route('/foo')
def route(req):
return Deferred()
req = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 0,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
pop_all(msgs)
d = worker.retry(req)
worker.clock.advance(2)
self.assertEqual((yield zitems(worker.redis, k)), [])
worker.clock.advance(4)
yield d
self.assertEqual(pop_all(msgs), [
('Retrying request', req),
('Retry timed out', req),
('Rescheduling retry', req),
])
self.assertEqual((yield zitems(worker.redis, k)), [
(5 + 20, {
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}),
])
@inlineCallbacks
def test_retry_timeout_end(self):
k = pending_key('test')
msgs = self.patch_log()
worker = yield self.mk_worker({'timeout': 3})
srv = yield ToyServer.from_test(self)
self.patch_reactor_call_later(worker.clock)
yield worker.stop()
@srv.app.route('/foo')
def route(req):
return Deferred()
req = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': "%s/foo" % (srv.url,),
'method': 'POST'
}
}
pop_all(msgs)
d = worker.retry(req)
worker.clock.advance(2)
self.assertEqual((yield zitems(worker.redis, k)), [])
worker.clock.advance(4)
yield d
self.assertEqual(pop_all(msgs), [
('Retrying request', req),
('Retry timed out', req),
('No remaining retry intervals, discarding request', req),
])
self.assertEqual((yield zitems(worker.redis, k)), [])
@inlineCallbacks
def test_retry_dec_req_count_success(self):
worker = yield self.mk_worker()
srv = yield ToyServer.from_test(self)
@srv.app.route('/')
def route(req):
pass
yield set_req_count(worker.redis, 'test', '1234', 3)
yield worker.retry({
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': srv.url,
'method': 'GET'
}
})
self.assertEqual(
(yield get_req_count(worker.redis, 'test', '1234')), 2)
@inlineCallbacks
def test_retry_dec_req_count_no_reattempt(self):
worker = yield self.mk_worker()
srv = yield ToyServer.from_test(self)
@srv.app.route('/')
def route(req):
pass
yield set_req_count(worker.redis, 'test', '1234', 3)
yield worker.retry({
'owner_id': '1234',
'timestamp': 5,
'attempts': 1,
'intervals': [10, 20],
'request': {
'url': srv.url,
'method': 'GET'
}
})
self.assertEqual(
(yield get_req_count(worker.redis, 'test', '1234')), 2)
@inlineCallbacks
def test_retry_no_dec_req_count_on_reattempt(self):
worker = yield self.mk_worker()
srv = yield ToyServer.from_test(self)
@srv.app.route('/')
def route(req):
req.setResponseCode(500)
yield set_req_count(worker.redis, 'test', '1234', 3)
yield worker.retry({
'owner_id': '1234',
'timestamp': 5,
'attempts': 0,
'intervals': [10, 20],
'request': {
'url': srv.url,
'method': 'GET'
}
})
self.assertEqual(
(yield get_req_count(worker.redis, 'test', '1234')), 3)
@inlineCallbacks
def test_loop(self):
k = ready_key('test')
msgs = self.patch_log()
retries = self.patch_retry()
worker = yield self.mk_worker({'frequency': 5})
reqs = [{
'owner_id': '1234',
'timestamp': t,
'attempts': 0,
'intervals': [10],
'request': {'foo': t}
} for t in range(5, 30, 5)]
yield add_ready(worker.redis, 'test', reqs)
self.assertEqual(pop_all(msgs), [
('Polling for requests to retry',),
('Retrieving next request from ready set',),
('Ready set is empty, rechecking on next poll',),
])
worker.clock.advance(5)
req = yield retries.get()
self.assertEqual(req, reqs[0])
self.assertEqual((yield lvalues(worker.redis, k)), reqs[1:])
self.assertEqual(pop_all(msgs), [
('Polling for requests to retry',),
('Retrieving next request from ready set',),
('Scheduling request for retrying', reqs[0]),
('Retrieving next request from ready set',),
])
req = yield retries.get()
self.assertEqual(req, reqs[1])
self.assertEqual((yield lvalues(worker.redis, k)), reqs[2:])
self.assertEqual(pop_all(msgs), [
('Scheduling request for retrying', reqs[1]),
('Retrieving next request from ready set',),
])
req = yield retries.get()
self.assertEqual(req, reqs[2])
self.assertEqual((yield lvalues(worker.redis, k)), reqs[3:])
self.assertEqual(pop_all(msgs), [
('Scheduling request for retrying', reqs[2]),
('Retrieving next request from ready set',),
])
req = yield retries.get()
self.assertEqual(req, reqs[3])
self.assertEqual((yield lvalues(worker.redis, k)), reqs[4:])
self.assertEqual(pop_all(msgs), [
('Scheduling request for retrying', reqs[3]),
('Retrieving next request from ready set',),
])
req = yield retries.get()
self.assertEqual(req, reqs[4])
self.assertEqual((yield lvalues(worker.redis, k)), [])
self.assertEqual(pop_all(msgs), [
('Scheduling request for retrying', reqs[4]),
('Retrieving next request from ready set',),
])
worker.clock.advance(10)
reqs = [{
'owner_id': '1234',
'timestamp': t,
'attempts': 0,
'intervals': [10],
'request': {'foo': t}
} for t in range(5, 15, 5)]
yield add_ready(worker.redis, 'test', reqs)
self.assertEqual(pop_all(msgs), [
('Ready set is empty, rechecking on next poll',),
])
worker.clock.advance(5)
req = yield retries.get()
self.assertEqual(req, reqs[0])
self.assertEqual((yield lvalues(worker.redis, k)), reqs[1:])
self.assertEqual(pop_all(msgs), [
('Polling for requests to retry',),
('Retrieving next request from ready set',),
('Scheduling request for retrying', reqs[0]),
('Retrieving next request from ready set',),
])
worker.clock.advance(5)
req = yield retries.get()
self.assertEqual(req, reqs[1])
self.assertEqual((yield lvalues(worker.redis, k)), [])
self.assertEqual(pop_all(msgs), [
('Scheduling request for retrying', reqs[1]),
('Retrieving next request from ready set',),
])
@inlineCallbacks
def test_loop_error(self):
e = Exception(':/')
def bad_poll():
raise e
errors = self.patch_on_error()
self.patch_poll(staticmethod(bad_poll))
worker = yield self.mk_worker({'frequency': 5})
self.assertEqual(errors, [e])
worker.clock.advance(5)
self.assertEqual(errors, [e])
worker.clock.advance(5)
self.assertEqual(errors, [e])
@inlineCallbacks
def test_loop_concurrency_limit(self):
r = ManualReadable([1, 2, 3, 4, 5])
w = ManualWritable()
self.patch(RetrySenderWorker, 'next_req', staticmethod(r.read))
self.patch(RetrySenderWorker, 'retry', staticmethod(w.write))
yield self.mk_worker({
'frequency': 5,
'concurrency_limit': 2,
})
# We haven't yet started any retries
self.assertEqual(r.unread, [2, 3, 4, 5])
self.assertEqual(r.reading, [1])
self.assertEqual(w.writing, [])
self.assertEqual(w.written, [])
# We've started retrying request 1 and still have space
yield r.next()
self.assertEqual(r.unread, [3, 4, 5])
self.assertEqual(r.reading, [2])
self.assertEqual(w.writing, [1])
self.assertEqual(w.written, [])
# We've started retrying request 2 and are at capacity
yield r.next()
self.assertEqual(r.unread, [4, 5])
self.assertEqual(r.reading, [3])
self.assertEqual(w.writing, [1, 2])
self.assertEqual(w.written, [])
# We've read request 3 from redis but haven't retried it yet, since we
# are waiting for request 1 and 2 to complete
yield r.next()
self.assertEqual(r.unread, [4, 5])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [1, 2])
self.assertEqual(w.written, [])
# Request 1 has completed, so we have space to start retrying
# request 3 and ask redis for request 4.
yield w.next()
self.assertEqual(r.unread, [5])
self.assertEqual(r.reading, [4])
self.assertEqual(w.writing, [2, 3])
self.assertEqual(w.written, [1])
# We've read request 4 from redis but haven't retried it yet, since we
# are waiting for request 2 and 3 to complete
yield r.next()
self.assertEqual(r.unread, [5])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [2, 3])
self.assertEqual(w.written, [1])
# Request 2 has completed, so we have space to start retrying
# request 3 and ask redis for request 5.
yield w.next()
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [5])
self.assertEqual(w.writing, [3, 4])
self.assertEqual(w.written, [1, 2])
# Request 3 and 4 complete while we are waiting for request 5
# from redis
yield w.next()
yield w.next()
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [5])
self.assertEqual(w.writing, [])
self.assertEqual(w.written, [1, 2, 3, 4])
# We've read request 5 from redis and started retrying it
yield r.next()
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [5])
self.assertEqual(w.written, [1, 2, 3, 4])
# We've retried request 5. Redis says we have nothing more to read, so
# we are done.
yield w.next()
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [])
self.assertEqual(w.written, [1, 2, 3, 4, 5])
@inlineCallbacks
def test_loop_retry_err(self):
e1 = Exception()
e3 = Exception()
errors = self.patch_on_error()
r = ManualReadable([1, 2, 3])
w = ManualWritable()
self.patch(RetrySenderWorker, 'next_req', staticmethod(r.read))
self.patch(RetrySenderWorker, 'retry', staticmethod(w.write))
yield self.mk_worker({
'frequency': 5,
'concurrency_limit': 2,
})
# We've read all three requests from redis and are busy retrying the
# first two
yield r.next()
yield r.next()
yield r.next()
self.assertEqual(errors, [])
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [1, 2])
self.assertEqual(w.written, [])
# Retry 1 throws an error, we catch it. We now have space for
# request 3.
yield w.err(e1)
self.assertEqual(errors, [e1])
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [2, 3])
self.assertEqual(w.written, [])
# Retry 2 succeeds.
yield w.next()
self.assertEqual(errors, [e1])
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [3])
self.assertEqual(w.written, [2])
# Retry 3 throws an error, we catch it.
yield w.err(e3)
self.assertEqual(errors, [e1, e3])
self.assertEqual(r.unread, [])
self.assertEqual(r.reading, [])
self.assertEqual(w.writing, [])
self.assertEqual(w.written, [2])
@inlineCallbacks
def test_stop_after_pop_non_empty(self):
"""
If the loop was stopped, but we've already asked redis for the next
request, we should retry the request.
"""
retries = self.patch_retry()
pops = self.patch_next_req()
worker = yield self.mk_worker({'frequency': 5})
self.assertTrue(worker.started)
worker.stop()
self.assertTrue(worker.stopping)
popped_req = {
'owner_id': '1234',
'timestamp': 5,
'attempts': 0,
'intervals': [10],
'request': {'foo': 5}
}
pops.pop().callback(popped_req)
req = yield retries.get()
self.assertEqual(req, popped_req)
self.assertEqual(pops, [])
self.assertTrue(worker.stopped)
@inlineCallbacks
def test_config_redis_db(self):
worker = yield self.mk_worker({
'redis_prefix': 'test',
'redis_db': 1
})
yield worker.redis.set('test.foo', 'bar')
yield worker.redis.select(1)
self.assertEqual((yield worker.redis.get('test.foo')), 'bar')
@inlineCallbacks
def test_on_error(self):
worker = yield self.mk_worker()
stops = self.patch_reactor_stop()
yield worker.stop()
self.assertEqual(self.flushLoggedErrors(), [])
self.assertEqual(stops.value, 0)
err = Exception()
worker.on_error(err)
self.assertEqual([e.value for e in self.flushLoggedErrors()], [err])
self.assertEqual(stops.value, 1)
| [
"justinvdm.0.1.0@gmail.com"
] | justinvdm.0.1.0@gmail.com |
ad4c83cd892a3de7b7eb7a93417326f79ec89583 | 34e9126f2044f1a38841e22563d3742a56cc24d4 | /ez-bof-exploit.py | c946f80877bf8ccd229cbcf1371244238d953095 | [] | no_license | Ko-kn3t/my-oscp | d2a40c5990d41f93e99e43e262402a83aab0fa36 | 1fe6ec31fa24f61d20483ba2f47e430181365df7 | refs/heads/master | 2023-06-06T17:41:29.269723 | 2021-07-09T20:05:24 | 2021-07-09T20:05:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 436 | py | import socket
ip = "192.168.34.110"
port = 4455
prefix = "OVRFLW "
offset = 0
overflow = "A" * offset
retn = ""
padding = ""
payload = ""
postfix = ""
buffer = prefix + overflow + retn + padding + payload + postfix
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
s.connect((ip, port))
print("Sending evil buffer...")
s.send(bytes(buffer + "\r\n", "latin-1"))
print("Done!")
except:
print("Could not connect.")
| [
"noreply@github.com"
] | noreply@github.com |
1be2af53fa6f016ff4072f573289d49e119594b7 | ca4b0be8f4ead842938c2f82254d5ebb781140be | /models/bilstm.py | 1f86e8cd2c213d8029750f61fcb01a531bc88333 | [
"Apache-2.0"
] | permissive | wuba/qa_match | 27bd64df81800329dfc88cda42a1e8afbd7d8308 | f74ffeb4a66589eb383a6c251b0a7413e0be7f20 | refs/heads/master | 2022-07-23T06:07:58.383905 | 2022-07-19T02:49:05 | 2022-07-19T02:49:05 | 245,431,046 | 348 | 90 | NOASSERTION | 2021-06-04T07:24:02 | 2020-03-06T13:47:37 | Python | UTF-8 | Python | false | false | 7,273 | py | # coding=utf-8
"""
a bi-lstm implementation for short text classification using tensroflow library
"""
from __future__ import print_function
import tensorflow as tf
from tensorflow.contrib import rnn
class BiLSTM(object):
def __init__(self, FLAGS):
"""Constructor for BiLSTM
Args:
FLAGS: tf.app.flags, you can see the FLAGS of run_bi_lstm.py
"""
self.input_x = tf.placeholder(tf.int64, [None, FLAGS.seq_length], name="input_x")
self.input_y = tf.placeholder(tf.int64, [None, ], name="input_y")
self.x_len = tf.placeholder(tf.int64, [None, ], name="x_len")
self.dropout_keep_prob = tf.placeholder(tf.float32, name="dropout_keep_prob")
with tf.variable_scope("embedding", initializer=tf.orthogonal_initializer()):
with tf.device('/cpu:0'):
# word embedding table
self.vocab = tf.get_variable('w', [FLAGS.vocab_size, FLAGS.embedding_size])
embedded = tf.nn.embedding_lookup(self.vocab, self.input_x) # [batch_size, seq_length, embedding_size]
inputs = tf.split(embedded, FLAGS.seq_length,
1) # [[batch_size, 1, embedding_size], [batch_size, 1, embedding_size], number is seq_length]
inputs = [tf.squeeze(input_, [1]) for input_ in
inputs] # [[batch_size, embedding_size], [batch_size, embedding_size], number is seq_length]
with tf.variable_scope("encoder", initializer=tf.orthogonal_initializer()):
lstm_fw_cell = rnn.BasicLSTMCell(FLAGS.num_units)
lstm_bw_cell = rnn.BasicLSTMCell(FLAGS.num_units)
lstm_fw_cell_stack = rnn.MultiRNNCell([lstm_fw_cell] * FLAGS.lstm_layers, state_is_tuple=True)
lstm_bw_cell_stack = rnn.MultiRNNCell([lstm_bw_cell] * FLAGS.lstm_layers, state_is_tuple=True)
lstm_fw_cell_stack = rnn.DropoutWrapper(lstm_fw_cell_stack, input_keep_prob=self.dropout_keep_prob,
output_keep_prob=self.dropout_keep_prob)
lstm_bw_cell_stack = rnn.DropoutWrapper(lstm_bw_cell_stack, input_keep_prob=self.dropout_keep_prob,
output_keep_prob=self.dropout_keep_prob)
self.outputs, self.fw_st, self.bw_st = rnn.static_bidirectional_rnn(lstm_fw_cell_stack, lstm_bw_cell_stack,
inputs, sequence_length=self.x_len,
dtype=tf.float32) # multi-layer
# only use the last layer
last_layer_no = FLAGS.lstm_layers - 1
self.states = tf.concat([self.fw_st[last_layer_no].h, self.bw_st[last_layer_no].h],
1) # [batchsize, (num_units * 2)]
attention_size = 2 * FLAGS.num_units
with tf.variable_scope('attention'):
attention_w = tf.Variable(tf.truncated_normal([2 * FLAGS.num_units, attention_size], stddev=0.1),
name='attention_w') # [num_units * 2, num_units * 2]
attention_b = tf.get_variable("attention_b", initializer=tf.zeros([attention_size])) # [num_units * 2]
u_list = []
for index in range(FLAGS.seq_length):
u_t = tf.tanh(tf.matmul(self.outputs[index], attention_w) + attention_b) # [batchsize, num_units * 2]
u_list.append(u_t) # seq_length * [batchsize, num_units * 2]
u_w = tf.Variable(tf.truncated_normal([attention_size, 1], stddev=0.1),
name='attention_uw') # [num_units * 2, 1]
attn_z = []
for index in range(FLAGS.seq_length):
z_t = tf.matmul(u_list[index], u_w)
attn_z.append(z_t) # seq_length * [batchsize, 1]
# transform to batch_size * sequence_length
attn_zconcat = tf.concat(attn_z, axis=1) # [batchsize, seq_length]
alpha = tf.nn.softmax(attn_zconcat) # [batchsize, seq_length]
# transform to sequence_length * batch_size * 1 , same rank as outputs
alpha_trans = tf.reshape(tf.transpose(alpha, [1, 0]),
[FLAGS.seq_length, -1, 1]) # [seq_length, batchsize, 1]
self.final_output = tf.reduce_sum(self.outputs * alpha_trans, 0) # [batchsize, num_units * 2]
with tf.variable_scope("output_layer"):
weights = tf.get_variable("weights", [2 * FLAGS.num_units, FLAGS.label_size])
biases = tf.get_variable("biases", initializer=tf.zeros([FLAGS.label_size]))
with tf.variable_scope("acc"):
# use attention
self.logits = tf.matmul(self.final_output, weights) + biases # [batchsize, label_size]
# not use attention
# self.logits = tf.matmul(self.states, weights) + biases
self.prediction = tf.nn.softmax(self.logits, name="prediction_softmax") # [batchsize, label_size]
self.loss = tf.reduce_mean(
tf.nn.sparse_softmax_cross_entropy_with_logits(logits=self.logits, labels=self.input_y))
self.global_step = tf.train.get_or_create_global_step()
self.correct = tf.equal(tf.argmax(self.prediction, 1), self.input_y)
self.acc = tf.reduce_mean(tf.cast(self.correct, tf.float32))
_, self.arg_index = tf.nn.top_k(self.prediction, k=FLAGS.label_size) # [batch_size, label_size]
with tf.variable_scope('training'):
# optimizer
self.learning_rate = tf.train.exponential_decay(FLAGS.lr, self.global_step, 200, 0.96, staircase=True)
self.train_step = tf.train.AdamOptimizer(self.learning_rate).minimize(self.loss,
global_step=self.global_step)
self.saver = tf.train.Saver(tf.global_variables(), max_to_keep=2)
def export_model(self, export_path, sess):
builder = tf.saved_model.builder.SavedModelBuilder(export_path)
tensor_info_x = tf.saved_model.utils.build_tensor_info(self.input_x)
tensor_info_y = tf.saved_model.utils.build_tensor_info(self.prediction)
tensor_info_len = tf.saved_model.utils.build_tensor_info(self.x_len)
tensor_dropout_keep_prob = tf.saved_model.utils.build_tensor_info(self.dropout_keep_prob) # 1.0 for inference
prediction_signature = (
tf.saved_model.signature_def_utils.build_signature_def(
inputs={'input': tensor_info_x, 'sen_len': tensor_info_len,
'dropout_keep_prob': tensor_dropout_keep_prob},
outputs={'output': tensor_info_y},
method_name=tf.saved_model.signature_constants.PREDICT_METHOD_NAME))
legacy_init_op = None
builder.add_meta_graph_and_variables(sess, [tf.saved_model.tag_constants.SERVING],
signature_def_map={'prediction': prediction_signature, },
legacy_init_op=legacy_init_op, clear_devices=True, saver=self.saver)
builder.save()
| [
"herui02@58.com"
] | herui02@58.com |
c38baec5d263b52e5b8b07f604db735e512f235b | 5a52ccea88f90dd4f1acc2819997fce0dd5ffb7d | /alipay/aop/api/domain/KbIsvMaCode.py | fa25c52f96b6b0de55cd7ffaf33dc6023902ce7c | [
"Apache-2.0"
] | permissive | alipay/alipay-sdk-python-all | 8bd20882852ffeb70a6e929038bf88ff1d1eff1c | 1fad300587c9e7e099747305ba9077d4cd7afde9 | refs/heads/master | 2023-08-27T21:35:01.778771 | 2023-08-23T07:12:26 | 2023-08-23T07:12:26 | 133,338,689 | 247 | 70 | Apache-2.0 | 2023-04-25T04:54:02 | 2018-05-14T09:40:54 | Python | UTF-8 | Python | false | false | 1,183 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.constant.ParamConstants import *
class KbIsvMaCode(object):
def __init__(self):
self._code = None
self._num = None
@property
def code(self):
return self._code
@code.setter
def code(self, value):
self._code = value
@property
def num(self):
return self._num
@num.setter
def num(self, value):
self._num = value
def to_alipay_dict(self):
params = dict()
if self.code:
if hasattr(self.code, 'to_alipay_dict'):
params['code'] = self.code.to_alipay_dict()
else:
params['code'] = self.code
if self.num:
if hasattr(self.num, 'to_alipay_dict'):
params['num'] = self.num.to_alipay_dict()
else:
params['num'] = self.num
return params
@staticmethod
def from_alipay_dict(d):
if not d:
return None
o = KbIsvMaCode()
if 'code' in d:
o.code = d['code']
if 'num' in d:
o.num = d['num']
return o
| [
"liuqun.lq@alibaba-inc.com"
] | liuqun.lq@alibaba-inc.com |
609d3a6c31bdda855c9cdee73943267fea809e40 | 9645bdfbb15742e0d94e3327f94471663f32061a | /Python/719 - Find K-th Smallest Pair Distance/719_find-k-th-smallest-pair-distance.py | 8370a768504118d06936fb1274d64a87cac376a5 | [] | no_license | aptend/leetcode-rua | f81c080b2260adb2da677612e5c437eda256781d | 80e44f4e9d3a5b592fdebe0bf16d1df54e99991e | refs/heads/master | 2023-06-22T00:40:05.533424 | 2021-03-17T13:51:28 | 2021-03-17T13:51:28 | 186,434,133 | 2 | 0 | null | 2023-06-21T22:12:51 | 2019-05-13T14:17:27 | HTML | UTF-8 | Python | false | false | 609 | py | from leezy import Solution, solution
from heapq import heappush, heappop
class Q719(Solution):
@solution
def smallestDistancePair(self, nums, k):
# MLE
A = sorted(nums)
N = len(A)
heap = []
def push(i, j):
heappush(heap, (abs(A[i]-A[j]), i, j))
for i in range(N-1):
push(i, i+1)
for _ in range(k):
ans, i, j = heappop(heap)
if j < N-1:
push(i, j+1)
return ans
def main():
q = Q719()
q.add_args([1, 3, 1], 1)
q.run()
if __name__ == "__main__":
main()
| [
"crescentwhale@hotmail.com"
] | crescentwhale@hotmail.com |
ad46c5cf701393737c5af474da5fe9ea2f31a1c9 | 56554999cdd882b6a6701b2a09e148c1fa4465c8 | /scramble.py | c9cd6805db2f8759634629df0b007e63d9a93de0 | [] | no_license | theriley106/Cubuyo | a266bd97fb82a8443785b40151222f68901a4bb2 | 38fb8caf2cb395c3df2274fd0651b51c621a5723 | refs/heads/master | 2020-04-11T17:17:43.095793 | 2018-12-16T02:34:15 | 2018-12-16T02:34:15 | 161,955,403 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 645 | py | import random
import re
Notation = ["R", "R'", "L", "L'", "U", "U'", "F", "F'", "B", "B'"]
def genNew(length):
Scramble = []
while len(Scramble) < length:
Move = random.choice(Notation)
MoveStr = " ".join(re.findall("[a-zA-Z]+", str(Move)))
PreviousMove = Scramble[-1:]
PreviousMove = " ".join(re.findall("[a-zA-Z]+", str(PreviousMove)))
if MoveStr != PreviousMove:
Num = random.randint(1,3)
if Num == 1 or Num == 3:
Scramble.append(Move)
else:
if "'" in str(Move):
Move = str(Move).replace("'", "")
Scramble.append('{}2'.format(Move))
T = ""
for moves in Scramble:
T = T + " " + str(moves)
return T
| [
"christopherlambert106@gmail.com"
] | christopherlambert106@gmail.com |
f46874aae652fa3eb63244fb046e91dd42da42aa | 80e152f49b355b3e07faaab6b468ca8dda6aa097 | /python/streamlit-sample/align-epub/epub.py | 94f4c812edb5b0b8ffabe802589336488cf1e1ca | [] | no_license | Pitrified/snippet | 13ad9222f584570b10abb23a122b010b088eb366 | 1d7e5657014b00612cde87b78d5506a9e8b6adfc | refs/heads/master | 2023-05-25T16:14:42.133900 | 2023-04-19T18:20:32 | 2023-04-19T18:20:32 | 174,192,523 | 2 | 0 | null | 2023-05-01T23:48:48 | 2019-03-06T17:47:16 | Python | UTF-8 | Python | false | false | 10,849 | py | """Class to load an EPub in memory and analyze it.
Split in chapter, paragraph, sentences.
Sentences are translated.
"""
import re
import zipfile
from collections import Counter
from pathlib import Path
from typing import IO, Literal, Union
from bs4 import BeautifulSoup, Tag
from spacy.language import Language
from spacy.tokens import Doc, Span
from cached_pipe import TranslationPipelineCache
VALID_CHAP_EXT = [".xhtml", ".xml", ".html"]
class Paragraph:
"""Paragraph class.
Split the paragraph in sentences using spacy and translate them using huggingface.
"""
def __init__(
self,
p_tag: Tag,
chapter: "Chapter",
) -> None:
"""Initialize a paragraph.
TODO:
Filter sentences that are too short?
Do not split in sentences if the par is short.
Merge short sentences.
"""
self.chapter = chapter
self.nlp: dict[str, Language] = self.chapter.nlp
self.pipe: dict[str, TranslationPipelineCache] = self.chapter.pipe
self.lang_orig: str = self.chapter.lang_orig
self.lang_dest: str = self.chapter.lang_dest
self.lang_tr = f"{self.lang_orig}_{self.lang_dest}"
self.p_tag = p_tag
# MAYBE: move to method that does clean up well
self.par_str = str(self.p_tag.string) # we want a str, not a NavigableString
self.par_str = self.par_str.replace("\n\r", " ")
self.par_str = self.par_str.replace("\n", " ")
self.par_str = self.par_str.replace("\r", " ")
self.par_doc = self.nlp[self.lang_orig](self.par_str)
self.sents_orig = list(self.par_doc.sents)
self.sents_tran: list[Doc] = []
for sent in self.sents_orig:
str_tran = self.pipe[self.lang_tr](sent.text)
# sent_tran = self.nlp[self.lang_dest](str_tran[0]["translation_text"])
sent_tran = self.nlp[self.lang_dest](str_tran)
self.sents_tran.append(sent_tran)
class Chapter:
"""Chapter class.
Parse the chapter content to find the Paragraphs in <p> tags.
"""
def __init__(
self,
chap_content: bytes,
chap_file_name: str,
epub: "EPub",
) -> None:
"""Initialize a chapter.
TODO:
Pass lang tags?
"""
self.chap_file_name = chap_file_name
self.epub = epub
self.nlp: dict[str, Language] = self.epub.nlp
self.pipe: dict[str, TranslationPipelineCache] = self.epub.pipe
self.lang_orig: str = self.epub.lang_orig
self.lang_dest: str = self.epub.lang_dest
# parse the soup and get the body
self.soup = BeautifulSoup(chap_content, features="html.parser")
self.body = self.soup.body
if self.body is None:
print(f"No body found in chapter {self.chap_file_name} of book {'book'}.")
return
# find the paragraphs
self.all_p_tag = self.body.find_all("p")
if len(self.all_p_tag) == 0:
print(
f"No paragraphs found in chapter {self.chap_file_name} of book {'book'}."
)
return
# build the list of Paragraphs
# self.paragraphs = [Paragraph(p_tag, self.nlp) for p_tag in self.all_p_tag]
self.paragraphs = []
for p_tag in self.all_p_tag[:]:
self.paragraphs.append(Paragraph(p_tag, self))
self.build_index()
self.build_flat_sents()
def build_index(self):
"""Build maps to go from ``sent_in_chap_id`` to ``(par_id, sent_in_par_id)`` and vice-versa."""
self.parsent_to_sent = {}
self.sent_to_parsent = {}
sc_id = 0
for p_id, par in enumerate(self.paragraphs):
for sp_id, sent in enumerate(par.sents_orig):
self.parsent_to_sent[(p_id, sp_id)] = sc_id
self.sent_to_parsent[sc_id] = (p_id, sp_id)
sc_id += 1
def build_flat_sents(self):
"""Build lists of sentences in the chapter, as Doc and text."""
# original sentences
self.sents_text_orig = []
self.sents_doc_orig = []
for _, sent_orig in self.enumerate_sents(which_sent="orig"):
self.sents_text_orig.append(sent_orig.text)
self.sents_doc_orig.append(sent_orig)
# translated sentences
self.sents_text_tran = []
self.sents_doc_tran = []
for _, sent_tran in self.enumerate_sents(which_sent="tran"):
self.sents_text_tran.append(sent_tran.text)
self.sents_doc_tran.append(sent_tran)
# the number of sentences in this chapter
self.sents_num = len(self.sents_text_orig)
def enumerate_sents(self, start_par: int = 0, end_par: int = 0, which_sent="orig"):
"""Enumerate all the sentences in the chapter, indexed as (par_id, sent_id)."""
if end_par == 0:
end_par = len(self.paragraphs) + 1
for i_p, par in enumerate(self.paragraphs[start_par:end_par]):
for i_s, sent in enumerate(par.sents_orig):
if which_sent == "orig":
yield (i_p + start_par, i_s), sent
elif which_sent == "tran":
yield (i_p + start_par, i_s), par.sents_tran[i_s]
def get_sent_with_parsent_id(
self, par_id: int, sent_id: int, which_sent=Literal["orig", "tran"]
) -> Span:
"""Get the sentence in the chapter indexed as (par_id, sent_id)."""
if which_sent == "orig":
return self.paragraphs[par_id].sents_orig[sent_id]
else:
return self.paragraphs[par_id].sents_tran[sent_id]
def get_sent_with_chapsent_id(
self, chapsent_id: int, which_sent=Literal["orig", "tran"]
) -> Span:
"""Get the sentence in the chapter indexed as the sentence number in the chapter."""
par_id, sent_id = self.sent_to_parsent[chapsent_id]
if which_sent == "orig":
return self.paragraphs[par_id].sents_orig[sent_id]
else:
return self.paragraphs[par_id].sents_tran[sent_id]
class EPub:
"""EPub class."""
def __init__(
self,
zipped_file: Union[str, IO[bytes], Path],
nlp: dict[str, Language],
pipe: dict[str, TranslationPipelineCache],
lang_orig: str,
lang_dest: str,
) -> None:
"""Initialize an epub.
TODO:
Pass file name? Yes, better debug. No can do with streamlit...
But I'd rather pass a fake name inside streamlit,
and the real one usually.
"""
self.nlp = nlp
self.pipe = pipe
self.lang_orig = lang_orig
self.lang_dest = lang_dest
# load the file in memory
self.zipped_file = zipped_file
self.input_zip = zipfile.ZipFile(self.zipped_file)
# analyze the contents and find the chapter file names
self.zipped_file_paths = [Path(p) for p in self.input_zip.namelist()]
self.get_text_chapters()
self.chap_file_names = [str(p) for p in self.chap_file_paths]
# build a list of chapters
# self.chapters = [
# Chapter(self.input_zip.read(chap_file_name), chap_file_name, self.nlp)
# for chap_file_name in self.chap_file_names
# ]
self.chapters: list[Chapter] = []
for chap_file_name in self.chap_file_names[:6]:
self.chapters.append(
Chapter(
self.input_zip.read(chap_file_name),
chap_file_name,
self,
)
)
def get_text_chapters(self) -> None:
"""Find the chapters names that match a regex ``name{number}`` and sort on ``number``."""
# get the paths that are valid xhtml and similar
self.chap_file_paths = [
f for f in self.zipped_file_paths if f.suffix in VALID_CHAP_EXT
]
# stem gets the file name without extensions
stems = [f.stem for f in self.chap_file_paths]
# get the longest stem
max_stem_len = max(len(c) for c in stems)
# track the best regex' performances
best_match_num = 0
best_stem_re = re.compile("")
# iterate over the len, looking for the best match
for num_kept_chars in range(max_stem_len):
# keep only the beginning of the names
stem_chops = [s[:num_kept_chars] for s in stems]
# count how many names have common prefix
stem_freqs = Counter(stem_chops)
# if there are no chapters with common prefix skip
if stem_freqs.most_common()[0][1] == 1:
continue
# try to match the prefix with re
for stem_might, stem_freq in stem_freqs.items():
# compile a regex looking for name{number}
stem_re = re.compile(f"{stem_might}(\\d+)")
# how many matches this stem has
good_match_num = 0
# track if a regex fails: it can have some matches and then fail
failed = False
for stem in stems:
stem_ch = stem[:num_kept_chars]
match = stem_re.match(stem)
# if the regex does not match but the stem prefix does, fails
if match is None and stem_ch == stem_might:
failed = True
break
good_match_num += 1
# if this stem failed to match, don't consider it for the best
if failed:
continue
# update info on best matching regex
if good_match_num > best_match_num:
best_stem_re = stem_re
best_match_num = good_match_num
# if the best match sucks keep all chapters
if best_match_num <= 2:
return
# pair chapter name and chapter number
chap_file_paths_id: list[tuple[Path, int]] = []
for stem, chap_file_path in zip(stems, self.chap_file_paths):
# match the stem and get the chapter number
match = best_stem_re.match(stem)
if match is None:
continue
chap_id = int(match.group(1))
chap_file_paths_id.append((chap_file_path, chap_id))
# sort the list according to the extracted id
self.chap_file_paths = [
cid[0] for cid in sorted(chap_file_paths_id, key=lambda x: x[1])
]
def get_chapter_by_name(self, chap_file_name: str) -> Chapter:
"""Get the chapter with the requested name."""
chap_id = self.chap_file_names.index(chap_file_name)
print(chap_id)
return self.chapters[chap_id]
| [
"nobilipietro@gmail.com"
] | nobilipietro@gmail.com |
6d20efd0a2f73ce1149cbb51844ba642ed36743f | 2016147854b89b96154644e6c18d686e90f40450 | /methods/exact_method.py | 2b681356d244986578c297c07523cff0b6d86494 | [] | no_license | ilshat-fatkhullin/differential_equations_assignment | 2b3cc596504a1b5b71e9ebd0db56483757a71d6c | a9f680c4b2a10a8fa9e18c10d605397a2dfcddff | refs/heads/master | 2020-04-01T11:38:06.083063 | 2018-11-01T16:41:55 | 2018-11-01T16:41:55 | 153,170,689 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 403 | py | from calculator import *
class ExactMethod:
@staticmethod
def get_result(x0, b, n, y0):
x = x0
step = (b - x0) / n
x_rows = list()
y_rows = list()
while abs(b - x) >= abs(step):
y = Calculator.get_general_solution(x, x0, y0)
x_rows.append(x)
y_rows.append(y)
x += step
return [x_rows, y_rows]
| [
"ilshat.fatkhullin@gmail.com"
] | ilshat.fatkhullin@gmail.com |
d727f6d92b367e32c9823e70668b9e985c4951f2 | d18b6a5ba144d3c13450e07c12ccc8b80a3bc222 | /main.py | 6c46c009a6b7b3f9e2ed57aba87c46e3b1be2e32 | [] | no_license | zhihuinang/SJTU-EE228-project1 | b6270f14317136de2f1a1676714058019c4f430a | 958c197bf56e52f66eb5ebd751f96219de012b5a | refs/heads/master | 2023-05-26T03:08:20.931244 | 2021-06-16T06:15:46 | 2021-06-16T06:15:46 | 366,617,112 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,591 | py | import argparse
import os
import torch
from tqdm import trange
from torchvision.transforms import transforms
import torch.utils.data as data
import torch.nn as nn
import torch.optim as optim
import numpy as np
from info import INFO
from model import ResNet18,ResNet50
from utils import ACC,AUC
from dataset import PathMNIST, ChestMNIST, DermaMNIST, OCTMNIST, PneumoniaMNIST, RetinaMNIST, \
BreastMNIST, OrganMNISTAxial, OrganMNISTCoronal, OrganMNISTSagittal
def train(model,optimizer,loss,train_loader,device,task):
model.train()
for batch_idx, data in enumerate(train_loader):
(inputs,labels) = data
inputs = inputs.to(device)
optimizer.zero_grad()
outputs = model(inputs)
if task == 'multi-label, binary-class':
labels = labels.to(torch.float32).to(device)
err = loss(outputs, labels)
else:
labels = labels.squeeze().long().to(device)
err = loss(outputs, labels)
err.backward()
optimizer.step()
def val(model, val_loader, device, val_auc_list, task, dir_path, epoch):
model.eval()
y_true = torch.tensor([]).to(device)
y_score = torch.tensor([]).to(device)
with torch.no_grad():
for batch_idx, (inputs, labels) in enumerate(val_loader):
outputs = model(inputs.to(device))
if task == 'multi-label, binary-class':
labels = labels.to(torch.float32).to(device)
m = nn.Sigmoid()
outputs = m(outputs).to(device)
else:
labels = labels.squeeze().long().to(device)
m = nn.Softmax(dim=1)
outputs = m(outputs).to(device)
labels = labels.float().resize_(len(labels), 1)
y_true = torch.cat((y_true, labels), 0)
y_score = torch.cat((y_score, outputs), 0)
y_true = y_true.cpu().numpy()
y_pred = y_score.detach().cpu().numpy()
auc = AUC(y_true, y_pred, task)
val_auc_list.append(auc)
state = {
'net': model.state_dict(),
'auc': auc,
'epoch': epoch,
}
print('Finish train epoch {}, AUC:{}'.format(epoch,auc))
path = os.path.join(dir_path, 'ckpt_%d_auc_%.5f.pth' % (epoch, auc))
torch.save(state, path)
def test(model, split, data_loader, device, flag, task, output_root=None):
model.eval()
y_true = torch.tensor([]).to(device)
y_score = torch.tensor([]).to(device)
with torch.no_grad():
for batch_idx, (inputs, targets) in enumerate(data_loader):
outputs = model(inputs.to(device))
if task == 'multi-label, binary-class':
targets = targets.to(torch.float32).to(device)
m = nn.Sigmoid()
outputs = m(outputs).to(device)
else:
targets = targets.squeeze().long().to(device)
m = nn.Softmax(dim=1)
outputs = m(outputs).to(device)
targets = targets.float().resize_(len(targets), 1)
y_true = torch.cat((y_true, targets), 0)
y_score = torch.cat((y_score, outputs), 0)
y_true = y_true.cpu().numpy()
y_score = y_score.detach().cpu().numpy()
auc = AUC(y_true, y_score, task)
acc = ACC(y_true, y_score, task)
print('%s AUC: %.5f ACC: %.5f' % (split, auc, acc))
# if output_root is not None:
# output_dir = os.path.join(output_root, flag)
# if not os.path.exists(output_dir):
# os.mkdir(output_dir)
# output_path = os.path.join(output_dir, '%s.csv' % (split))
# save_results(y_true, y_score, output_path)
def main(args):
data_name = args.data_name.lower()
input_root = args.input_root
output_root = args.output_root
num_epoch = args.num_epoch
download = args.download
model_type = args.model
flag_to_class = {
"pathmnist": PathMNIST,
"chestmnist": ChestMNIST,
"dermamnist": DermaMNIST,
"octmnist": OCTMNIST,
"pneumoniamnist": PneumoniaMNIST,
"retinamnist": RetinaMNIST,
"breastmnist": BreastMNIST,
"organmnist_axial": OrganMNISTAxial,
"organmnist_coronal": OrganMNISTCoronal,
"organmnist_sagittal": OrganMNISTSagittal,
}
DataClass = flag_to_class[data_name]
info = INFO[data_name]
task = info['task']
n_channels = info['n_channels']
n_classes = len(info['label'])
lr = 0.001
batch_size = 128
val_auc_list = []
dir_path = os.path.join(output_root, '%s_checkpoints' % (data_name+"_"+model_type))
if not os.path.exists(dir_path):
os.makedirs(dir_path)
print('doing data preprocessing......')
transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize(mean=[.5], std=[.5])])
train_dataset = DataClass(root=input_root,
split='train',
transform=transform,
download=download)
train_loader = data.DataLoader(dataset=train_dataset,
batch_size=batch_size,
shuffle=True)
val_dataset = DataClass(root=input_root,
split='val',
transform=transform,
download=download)
val_loader = data.DataLoader(dataset=val_dataset,
batch_size=batch_size,
shuffle=True)
test_dataset = DataClass(root=input_root,
split='test',
transform=transform,
download=download)
test_loader = data.DataLoader(dataset=test_dataset,
batch_size=batch_size,
shuffle=True)
print('data preprocessing done.....')
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
if model_type == 'ResNet18':
model = ResNet18(in_ch=n_channels,class_num=n_classes)
else:
model = ResNet50(in_ch=n_channels,class_num=n_classes)
model = model.to(device)
if task == 'multi-label, binary-class':
loss = nn.BCEWithLogitsLoss()
else:
loss = nn.CrossEntropyLoss()
optimizer = optim.Adam(model.parameters(), lr=lr)
for epoch in trange(0, num_epoch):
train(model, optimizer, loss, train_loader, device, task)
val(model, val_loader, device, val_auc_list, task, dir_path, epoch)
auc_list = np.array(val_auc_list)
index = auc_list.argmax()
print('epoch %s is the best model' % (index))
print('==> Testing model...')
restore_model_path = os.path.join(
dir_path, 'ckpt_%d_auc_%.5f.pth' % (index, auc_list[index]))
model.load_state_dict(torch.load(restore_model_path)['net'])
test(model,
'train',
train_loader,
device,
data_name,
task,
output_root=output_root)
test(model, 'val', val_loader, device, data_name, task, output_root=output_root)
test(model,
'test',
test_loader,
device,
data_name,
task,
output_root=output_root)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='RUN Baseline model of MedMNIST')
parser.add_argument('--data_name',
default='pathmnist',
help='subset of MedMNIST',
type=str)
parser.add_argument('--input_root',
default='../../data',
help='input root, the source of dataset files',
type=str)
parser.add_argument('--output_root',
default='../output',
help='output root, where to save models and results',
type=str)
parser.add_argument('--num_epoch',
default=5,
help='num of epochs of training',
type=int)
parser.add_argument('--download',
default=True,
help='whether download the dataset or not',
type=bool)
parser.add_argument('--model',
default='ResNet18',
help='model type',
type=str)
args = parser.parse_args()
main(args)
| [
"zhihuinang@126.com"
] | zhihuinang@126.com |
f268e4ec3c301c496e6e87cfff9d394bdb45b105 | 85fa96e129cac68d1f7c52142207d80c43650cc8 | /img_viewer.py | ef7d654feb38af027bec66ea3e7aca30e2aa7aa7 | [] | no_license | hitarthsolanki/ADV-C164-165-IMAGE-VIEWER | bfebaa42f60708a91e9aa379a06e9438a5f93cbe | 0704f49159e19a955dfe6a1328ebebc7317dd40e | refs/heads/main | 2023-06-29T04:33:34.133567 | 2021-08-02T16:09:27 | 2021-08-02T16:09:27 | 392,012,098 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,187 | py | from tkinter import *
from tkinter import filedialog
from PIL import ImageTk,Image
root=Tk()
root.title("Planet Encyclopedia")
root.geometry("600x600")
root.configure(background="black")
img_path=""
def Open():
global img_path
img_path=filedialog.askopenfilename(title = "Select Image File", filetypes= [("Image Files", "*.jpg *.gif *.png *.jpeg")])
print(img_path)
img=ImageTk.PhotoImage(Image.open(img_path))
label_image.configure(image=img)
label_image.image=img
def rotate():
print("Rotate")
print(img_path)
im=Image.open(img_path)
rotated_img=im.rotate(180)
img=ImageTk.PhotoImage(rotated_img)
label_image.configure(image=img)
label_image.image=img
btn_open=Button(root,text="Open Image",command=Open,relief="flat",font=("Times New Roman0",15),bg="#808080",fg="white")
btn_open.place(relx=0.5,rely=0.08,anchor=CENTER)
btn_rotate=Button(root,text="Rotate Image",command=rotate,relief="flat",font=("Times New Roman0",15),bg="#808080",fg="white")
btn_rotate.place(relx=0.5,rely=0.8,anchor=CENTER)
label_image=Label(root,text="royce",bg="black",fg="black")
label_image.pack()
root.mainloop() | [
"noreply@github.com"
] | noreply@github.com |
2a742123549ed793dd03e532042a323592171d10 | a2d36e471988e0fae32e9a9d559204ebb065ab7f | /huaweicloud-sdk-meeting/huaweicloudsdkmeeting/v1/model/show_sp_res_response.py | f475eccd26c2ba4a71ea8a20576fbef3e88e9b9f | [
"Apache-2.0"
] | permissive | zhouxy666/huaweicloud-sdk-python-v3 | 4d878a90b8e003875fc803a61414788e5e4c2c34 | cc6f10a53205be4cb111d3ecfef8135ea804fa15 | refs/heads/master | 2023-09-02T07:41:12.605394 | 2021-11-12T03:20:11 | 2021-11-12T03:20:11 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,331 | py | # coding: utf-8
import re
import six
from huaweicloudsdkcore.sdk_response import SdkResponse
from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization
class ShowSpResResponse(SdkResponse):
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
sensitive_list = []
openapi_types = {
'used_accounts_count': 'int'
}
attribute_map = {
'used_accounts_count': 'usedAccountsCount'
}
def __init__(self, used_accounts_count=None):
"""ShowSpResResponse - a model defined in huaweicloud sdk"""
super(ShowSpResResponse, self).__init__()
self._used_accounts_count = None
self.discriminator = None
if used_accounts_count is not None:
self.used_accounts_count = used_accounts_count
@property
def used_accounts_count(self):
"""Gets the used_accounts_count of this ShowSpResResponse.
已用的企业并发数
:return: The used_accounts_count of this ShowSpResResponse.
:rtype: int
"""
return self._used_accounts_count
@used_accounts_count.setter
def used_accounts_count(self, used_accounts_count):
"""Sets the used_accounts_count of this ShowSpResResponse.
已用的企业并发数
:param used_accounts_count: The used_accounts_count of this ShowSpResResponse.
:type: int
"""
self._used_accounts_count = used_accounts_count
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
if attr in self.sensitive_list:
result[attr] = "****"
else:
result[attr] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
import simplejson as json
if six.PY2:
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
return json.dumps(sanitize_for_serialization(self), ensure_ascii=False)
def __repr__(self):
"""For `print`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, ShowSpResResponse):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other
| [
"hwcloudsdk@huawei.com"
] | hwcloudsdk@huawei.com |
7cb6b8c630bf709694fc2422eae80020740c9721 | e4814f60eefbc6ede78a91bd1a5717b225fbf1dd | /resizeeeeee.py | 2c248b099548a7e8529320ab56e23c269830c1a6 | [] | no_license | sukumargaonkar/MazeRunner | 9c52ce606438c0d19f210de7a7908c02d8259107 | 584b0418ddb64582f04b78481890cf8614fb97d3 | refs/heads/master | 2020-03-29T18:01:05.522220 | 2018-10-08T01:55:43 | 2018-10-08T01:55:43 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 647 | py | import math
import os
from PIL import Image
dim = 50
k = 600/dim
print(k)
j = math.ceil(k)
size = j, j
filename1 = 'mario.gif'
filename2 = 'wall.gif'
file_parts1 = os.path.splitext(filename1)
file_parts2 = os.path.splitext(filename2)
outfile1 = file_parts1[0] + "_" + file_parts1[1]
outfile2 = file_parts2[0] + "_" + file_parts2[1]
try:
img = Image.open(filename1)
img = img.resize(size, Image.ANTIALIAS)
img.save(outfile1, "GIF")
img = Image.open(filename2)
img = img.resize(size, Image.ANTIALIAS)
img.save(outfile2, "GIF")
except IOError as e:
print(" An exception occured '%s'" % e)
| [
"noreply@github.com"
] | noreply@github.com |
c31d6a0e04a28b132c1ee51440b80382e70f188b | 9de26c31c5904387932c7467870e469abb7ec488 | /test_case48/test_case19.py | 4fbf6cbe3ae6c400bb02e5e3167c4bc4cb476a06 | [] | no_license | wanghao-820/data_create | 6b680e980fcbba1fcd55fe1189472718f4ef5a2b | ec774e3a5f9341f3bcdf5760e712cb9b0521684b | refs/heads/master | 2023-06-13T01:00:28.099793 | 2021-07-08T15:53:20 | 2021-07-08T15:53:20 | 384,153,560 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,164 | py | from data_creater.utils import db_utils, str_utils
from data_creater.apis import portal_apis
from time import sleep
from data_creater.controllers.renewal_controller import Renewal
if __name__ == "__main__":
# 测试用例， 学生未续报；调账号
"""
A：春 → 调入秋
B：秋
A班主任：分子+1 pass
B班主任：不变 pass
"""
to_uid = 473
# 春季班
clazz_ids = [1793]
test = Renewal()
print(test.get_clazz_master_info_field(clazz_id=1793, master_id=10706952, field='service_num,conversion_num'))
print(test.get_clazz_master_info_field(clazz_id=1793, master_id=10706958,field='service_num,conversion_num'))
for i in range(len(clazz_ids)):
portal_apis.apply_clazz_student_nice(to_uid, clazz_id=clazz_ids[i])
sleep(1)
# 先查询info表确定服务人数
service_num,conversion_num=test.get_clazz_master_info_field(clazz_id=1793, master_id=10706952, field='service_num,conversion_num')
print(service_num, conversion_num)
print(test.get_clazz_master_info_field(clazz_id=1793, master_id=10706958,field='service_num,conversion_num'))
print("报班成功!")
sleep(1)
uid = 475
clazz_id = 1987
portal_apis.apply_clazz_student_nice(uid, clazz_id=clazz_id)
sleep(1)
# # # 报秋季班、五年级数学
order_id = test.get_order_id(uid,clazz_id)
portal_apis.exchange_order_user(order_id=order_id, to_user_id=to_uid)
sleep(1)
# info表分母不变算惩罚，分子不变
new_service_num,new_conversion_num=test.get_clazz_master_info_field(clazz_id=1793, master_id=10706952, field='service_num,conversion_num')
print(new_service_num, new_conversion_num)
new_service_num,new_conversion_num=test.get_clazz_master_info_field(clazz_id=1793, master_id=10706958, field='service_num,conversion_num')
print(new_service_num, new_conversion_num)
# assert new_conversion_num-conversion_num == 0, "调小班后分子变化了"
# assert new_service_num-service_num == 0, "调小班后分母变化了"
# print("购课后调小班功能测试通过!")
| [
"1427211856@qq.com"
] | 1427211856@qq.com |
5b370d6b432e10fca26598659c827a659c0d4f0e | 3decd738a2f43e70c040644aca4e604b13fd7eb6 | /tools/setup-deb-pkg.py | 3c45692405a61768039fa30350e1a268033d25b5 | [
"MIT"
] | permissive | mmarchini/libstapsdt | 433ab727ca886ea51ffbff5612ca8574ba186afa | 5a44c3a5e4b1cdb16e1c02e1cc2474f9ca56d4ff | refs/heads/main | 2021-12-04T19:05:56.550352 | 2021-10-16T03:09:11 | 2021-10-16T03:09:11 | 417,709,808 | 1 | 0 | MIT | 2021-10-16T03:59:54 | 2021-10-16T03:59:53 | null | UTF-8 | Python | false | false | 3,927 | py | #!/usr/bin/env python3
import os
import re
from os import path
import argparse
import fileinput
def inline_file_edit(filepath):
return fileinput.FileInput(filepath, inplace=True)
LIB_SHORT_DESCRIPTION = "Runtime USDT probes for Linux"
LIB_LONG_DESCRIPTION = """
Library to give Linux runtime USDT probes capability
""".strip()
HEADERS_SHORT_DESCRIPTION = "Headers for libstapsdt"
HEADERS_LONG_DESCRIPTION = """
Headers for libstapsdt, a library to give Linux runtime USDT probes capability
""".strip()
SITE = "https://github.com/sthima/libstapsdt"
parser = argparse.ArgumentParser()
parser.add_argument("codename", type=str)
parser.add_argument("version", type=str)
args = parser.parse_args()
BASE = path.join("dist", "libstapsdt-{0}".format(args.version))
DEBIAN = path.join(BASE, "debian")
print(args.version)
print(args.codename)
# Rename
os.rename(path.join(DEBIAN, "libstapsdt1.install"), path.join(DEBIAN, "libstapsdt0.install"))
os.rename(path.join(DEBIAN, "libstapsdt1.dirs"), path.join(DEBIAN, "libstapsdt0.dirs"))
# Fix changelog
with inline_file_edit(path.join(DEBIAN, "changelog")) as file_:
for line in file_:
if 'unstable' in line:
line = line.replace('unstable', args.codename)
elif 'Initial release' in line:
line = " * Initial release\n"
print(line, end="")
# Fix control
header = True
with inline_file_edit(path.join(DEBIAN, "control")) as file_:
for line in file_:
if line.startswith("#"):
continue
if "3.9.6" in line:
line = line.replace("3.9.6", "3.9.7")
if "upstream URL" in line:
line = line.replace("<insert the upstream URL, if relevant>", SITE)
if "BROKEN" in line:
line = line.replace("BROKEN", "0")
if "debhelper (>=9)" in line:
line = line.replace("\n", ", libelf1, libelf-dev\n")
if "insert up" in line:
if header:
line = line.replace("<insert up to 60 chars description>", HEADERS_SHORT_DESCRIPTION)
else:
line = line.replace("<insert up to 60 chars description>", LIB_SHORT_DESCRIPTION)
if "insert long" in line:
if header:
line = line.replace("<insert long description, indented with spaces>", HEADERS_LONG_DESCRIPTION)
header = False
else:
line = line.replace("<insert long description, indented with spaces>", LIB_LONG_DESCRIPTION)
print(line, end="")
# Fix copyright
header = True
COPYRIGHT_LINE = ""
copyright_regex = re.compile("Copyright: [0-9]")
with open(path.join(DEBIAN, "copyright")) as file_:
for line in file_.readlines():
if copyright_regex.match(line):
COPYRIGHT_LINE = line
with inline_file_edit(path.join(DEBIAN, "copyright")) as file_:
for line in file_:
if line.startswith("#"):
continue
if "url://example" in line:
line = line.replace("<url://example.com>", SITE)
if "<years>" in line:
if "Copyright" in line:
line = COPYRIGHT_LINE
else:
continue
print(line, end="")
# Fix installs
with open(path.join(DEBIAN, "libstapsdt-dev.links"), "w+") as file_:
file_.writelines(["usr/lib/libstapsdt.so.0 usr/lib/libstapsdt.so"])
with inline_file_edit(path.join(DEBIAN, "libstapsdt0.install")) as file_:
for line in file_:
print("usr/lib/lib*.so.*")
break
with inline_file_edit(path.join(DEBIAN, "libstapsdt-dev.install")) as file_:
for line in file_:
print("usr/include/*")
break
# Fix rules
with inline_file_edit(path.join(DEBIAN, "rules")) as file_:
for line in file_:
if "DH_VERBOSE" in line:
print("export DH_VERBOSE=1")
print("export DEB_BUILD_OPTIONS=nocheck")
continue
else:
print(line, end="")
| [
"oss@mmarchini.me"
] | oss@mmarchini.me |
e19aaa55db0692b20e430e06a921b19c03074b63 | 277540803d133c40b24733857fc553983a59d863 | /src/SwarmBot/run.py | e3223401213853893a2341cf05feb803cdc3a14a | [
"MIT"
] | permissive | Dyex719/Battlecode | d3ddf518b66ba09fe5243e997b3b1d2cef4c912f | 5ed0932b0ba18ce914725e90839a476328cb9460 | refs/heads/master | 2021-05-12T17:43:06.118059 | 2018-01-16T05:14:37 | 2018-01-16T05:14:37 | 117,052,193 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,400 | py | import battlecode as bc
import random
import sys
import traceback
print("pystarting")
# A GameController is the main type that you talk to the game with.
# Its constructor will connect to a running game.
gc = bc.GameController()
directions = list(bc.Direction)
useful_dir = [bc.Direction.North,bc.Direction.Northeast,bc.Direction.East,bc.Direction.Southeast,bc.Direction.South,bc.Direction.Southwest,bc.Direction.West,bc.Direction.Northwest]
tryRotate = [0,-1,1,-2,2]
print("pystarted")
# It's a good idea to try to keep your bots deterministic, to make debugging easier.
# determinism isn't required, but it means that the same things will happen in every thing you run,
# aside from turns taking slightly different amounts of time due to noise.
random.seed(6137)
# let's start off with some research!
# we can queue as much as we want.
gc.queue_research(bc.UnitType.Rocket)
gc.queue_research(bc.UnitType.Worker)
gc.queue_research(bc.UnitType.Knight)
my_team = gc.team()
global one_loc,enemy_start
def invert(loc):
inv_x = earth_map.width-loc.x
inv_y = earth_map.height-loc.y
return bc.MapLocation(bc.Planet.Earth,inv_x,inv_y)
# Lets analyse the map
# pm = bc.PlanetMap()
pl = bc.Player()
for planet in pl.planet: # This is ob wrong, I only want to run the code if it is earth, but it has to run before the main loop starts. We can use a function I guess.
if gc.planet() == bc.Planet.Earth:
earth_map = gc.starting_map(bc.Planet.Earth)
one_loc = gc.my_units()[0].location.map_location()
enemy_start = invert(one_loc)
print("Enemy starts at" + str(enemy_start.x) +" " +str(enemy_start.y))
print("We start at" + str(one_loc.x) +" " +str(one_loc.y))
def mid_point(loc1,loc2):
mid_x = int((loc1.x + loc2.x) / 2)
mid_y = int((loc1.y + loc2.y) / 2)
return bc.MapLocation(bc.Planet.Earth,mid_x,mid_y)
#
# def goto(unit,dest):
# d = unit.location.map_location().direction_to(dest)
# if gc.can_move(unit.id,d):
# gc.move_robot(unit.id,d)
def fuzzygoto(unit,dest):
toward = unit.location.map_location().direction_to(dest)
for tilt in tryRotate:
d = rotate(toward,tilt)
if gc.can_move(unit.id,d):
gc.move_robot(unit.id,d)
break
def rotate(direc,amount):
ind = directions.index(direc)
return directions[(ind+amount)%8]
swarm_loc = mid_point(one_loc,enemy_start)
knight_count = 0
while True:
# We only support Python 3, which means brackets around print()
print('pyround:', gc.round())
# frequent try/catches are a good idea
try:
# walk through our units:
for unit in gc.my_units():
# first, factory logic
if unit.unit_type == bc.UnitType.Factory:
garrison = unit.structure_garrison()
if len(garrison) > 0:
d = random.choice(directions)
if gc.can_unload(unit.id, d):
print('unloaded a knight!')
gc.unload(unit.id, d)
continue
elif gc.can_produce_robot(unit.id, bc.UnitType.Knight):
gc.produce_robot(unit.id, bc.UnitType.Knight)
print('produced a knight!')
knight_count += 1
continue
# first, let's look for nearby blueprints to work on
location = unit.location
if location.is_on_map():
nearby = gc.sense_nearby_units(location.map_location(), 2)
for other in nearby:
if unit.unit_type == bc.UnitType.Worker and gc.can_build(unit.id, other.id):
gc.build(unit.id, other.id)
print('built a factory!')
# move onto the next unit
continue
if other.team != my_team and gc.is_attack_ready(unit.id) and gc.can_attack(unit.id, other.id):
print('attacked a thing!')
gc.attack(unit.id, other.id)
continue
elif unit.unit_type == bc.UnitType.Knight and gc.is_move_ready(unit.id) and gc.round()<50:
fuzzygoto(unit,swarm_loc)
elif unit.unit_type == bc.UnitType.Knight and gc.is_move_ready(unit.id) and gc.round()>50:
fuzzygoto(unit,enemy_start)
# okay, there weren't any dudes around
# pick a random direction:
d = random.choice(directions)
# or, try to build a factory:
if gc.karbonite() > bc.UnitType.Factory.blueprint_cost() and gc.can_blueprint(unit.id, bc.UnitType.Factory, d):
gc.blueprint(unit.id, bc.UnitType.Factory, d)
# and if that fails, try to move
elif gc.is_move_ready(unit.id) and gc.can_move(unit.id, d):
gc.move_robot(unit.id, useful_dir)
except Exception as e:
print('Error:', e)
# use this to show where the error was
traceback.print_exc()
# send the actions we've performed, and wait for our next turn.
gc.next_turn()
# these lines are not strictly necessary, but it helps make the logs make more sense.
# it forces everything we've written this turn to be written to the manager.
sys.stdout.flush()
sys.stderr.flush()
| [
"30334566+Dyex719@users.noreply.github.com"
] | 30334566+Dyex719@users.noreply.github.com |
749b6395b6d8726189553c6d5d199595a4229343 | f9d564f1aa83eca45872dab7fbaa26dd48210d08 | /huaweicloud-sdk-gaussdbfornosql/huaweicloudsdkgaussdbfornosql/v3/model/show_pause_resume_stutus_response.py | c5684b791851a26cc2626b0be1f8ff75fd7fc5a2 | [
"Apache-2.0"
] | permissive | huaweicloud/huaweicloud-sdk-python-v3 | cde6d849ce5b1de05ac5ebfd6153f27803837d84 | f69344c1dadb79067746ddf9bfde4bddc18d5ecf | refs/heads/master | 2023-09-01T19:29:43.013318 | 2023-08-31T08:28:59 | 2023-08-31T08:28:59 | 262,207,814 | 103 | 44 | NOASSERTION | 2023-06-22T14:50:48 | 2020-05-08T02:28:43 | Python | UTF-8 | Python | false | false | 8,747 | py | # coding: utf-8
import six
from huaweicloudsdkcore.sdk_response import SdkResponse
from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization
class ShowPauseResumeStutusResponse(SdkResponse):
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
sensitive_list = []
openapi_types = {
'master_instance_id': 'str',
'slave_instance_id': 'str',
'status': 'str',
'data_sync_indicators': 'NoSQLDrDateSyncIndicators',
'rto_and_rpo_indicators': 'list[NoSQLDrRpoAndRto]'
}
attribute_map = {
'master_instance_id': 'master_instance_id',
'slave_instance_id': 'slave_instance_id',
'status': 'status',
'data_sync_indicators': 'data_sync_indicators',
'rto_and_rpo_indicators': 'rto_and_rpo_indicators'
}
def __init__(self, master_instance_id=None, slave_instance_id=None, status=None, data_sync_indicators=None, rto_and_rpo_indicators=None):
"""ShowPauseResumeStutusResponse
The model defined in huaweicloud sdk
:param master_instance_id: 主实例id
:type master_instance_id: str
:param slave_instance_id: 备实例id
:type slave_instance_id: str
:param status: 容灾实例数据同步状态 - NA：实例尚未搭建容灾关系 - NEW：尚未启动的数据同步状态 - SYNCING：数据同步正常进行中 - SUSPENDING：正在暂停数据同步 - SUSPENDED：数据同步已暂停 - RECOVERYING：正在恢复数据同步
:type status: str
:param data_sync_indicators:
:type data_sync_indicators: :class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrDateSyncIndicators`
:param rto_and_rpo_indicators: 切换或倒换RPO和RTO值，仅当请求实例id为主实例时有值
:type rto_and_rpo_indicators: list[:class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrRpoAndRto`]
"""
super(ShowPauseResumeStutusResponse, self).__init__()
self._master_instance_id = None
self._slave_instance_id = None
self._status = None
self._data_sync_indicators = None
self._rto_and_rpo_indicators = None
self.discriminator = None
if master_instance_id is not None:
self.master_instance_id = master_instance_id
if slave_instance_id is not None:
self.slave_instance_id = slave_instance_id
if status is not None:
self.status = status
if data_sync_indicators is not None:
self.data_sync_indicators = data_sync_indicators
if rto_and_rpo_indicators is not None:
self.rto_and_rpo_indicators = rto_and_rpo_indicators
@property
def master_instance_id(self):
"""Gets the master_instance_id of this ShowPauseResumeStutusResponse.
主实例id
:return: The master_instance_id of this ShowPauseResumeStutusResponse.
:rtype: str
"""
return self._master_instance_id
@master_instance_id.setter
def master_instance_id(self, master_instance_id):
"""Sets the master_instance_id of this ShowPauseResumeStutusResponse.
主实例id
:param master_instance_id: The master_instance_id of this ShowPauseResumeStutusResponse.
:type master_instance_id: str
"""
self._master_instance_id = master_instance_id
@property
def slave_instance_id(self):
"""Gets the slave_instance_id of this ShowPauseResumeStutusResponse.
备实例id
:return: The slave_instance_id of this ShowPauseResumeStutusResponse.
:rtype: str
"""
return self._slave_instance_id
@slave_instance_id.setter
def slave_instance_id(self, slave_instance_id):
"""Sets the slave_instance_id of this ShowPauseResumeStutusResponse.
备实例id
:param slave_instance_id: The slave_instance_id of this ShowPauseResumeStutusResponse.
:type slave_instance_id: str
"""
self._slave_instance_id = slave_instance_id
@property
def status(self):
"""Gets the status of this ShowPauseResumeStutusResponse.
容灾实例数据同步状态 - NA：实例尚未搭建容灾关系 - NEW：尚未启动的数据同步状态 - SYNCING：数据同步正常进行中 - SUSPENDING：正在暂停数据同步 - SUSPENDED：数据同步已暂停 - RECOVERYING：正在恢复数据同步
:return: The status of this ShowPauseResumeStutusResponse.
:rtype: str
"""
return self._status
@status.setter
def status(self, status):
"""Sets the status of this ShowPauseResumeStutusResponse.
容灾实例数据同步状态 - NA：实例尚未搭建容灾关系 - NEW：尚未启动的数据同步状态 - SYNCING：数据同步正常进行中 - SUSPENDING：正在暂停数据同步 - SUSPENDED：数据同步已暂停 - RECOVERYING：正在恢复数据同步
:param status: The status of this ShowPauseResumeStutusResponse.
:type status: str
"""
self._status = status
@property
def data_sync_indicators(self):
"""Gets the data_sync_indicators of this ShowPauseResumeStutusResponse.
:return: The data_sync_indicators of this ShowPauseResumeStutusResponse.
:rtype: :class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrDateSyncIndicators`
"""
return self._data_sync_indicators
@data_sync_indicators.setter
def data_sync_indicators(self, data_sync_indicators):
"""Sets the data_sync_indicators of this ShowPauseResumeStutusResponse.
:param data_sync_indicators: The data_sync_indicators of this ShowPauseResumeStutusResponse.
:type data_sync_indicators: :class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrDateSyncIndicators`
"""
self._data_sync_indicators = data_sync_indicators
@property
def rto_and_rpo_indicators(self):
"""Gets the rto_and_rpo_indicators of this ShowPauseResumeStutusResponse.
切换或倒换RPO和RTO值，仅当请求实例id为主实例时有值
:return: The rto_and_rpo_indicators of this ShowPauseResumeStutusResponse.
:rtype: list[:class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrRpoAndRto`]
"""
return self._rto_and_rpo_indicators
@rto_and_rpo_indicators.setter
def rto_and_rpo_indicators(self, rto_and_rpo_indicators):
"""Sets the rto_and_rpo_indicators of this ShowPauseResumeStutusResponse.
切换或倒换RPO和RTO值，仅当请求实例id为主实例时有值
:param rto_and_rpo_indicators: The rto_and_rpo_indicators of this ShowPauseResumeStutusResponse.
:type rto_and_rpo_indicators: list[:class:`huaweicloudsdkgaussdbfornosql.v3.NoSQLDrRpoAndRto`]
"""
self._rto_and_rpo_indicators = rto_and_rpo_indicators
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
if attr in self.sensitive_list:
result[attr] = "****"
else:
result[attr] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
import simplejson as json
if six.PY2:
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
return json.dumps(sanitize_for_serialization(self), ensure_ascii=False)
def __repr__(self):
"""For `print`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, ShowPauseResumeStutusResponse):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other
| [
"hwcloudsdk@huawei.com"
] | hwcloudsdk@huawei.com |
ee5f649704cbc12a6f353db6ecfd4a96c972f041 | f8c183aa549f36808844f5e6304a6129a222f182 | /lesson_01_slyusar_roman/02. task 2.py | 26a49235298f3db5d06d1e6681b78a4d9a1e669a | [] | no_license | ITihiy/gb_algo_solutions | 70f59a6b22412e7d7df1111c5506cf944245cd2a | faa94f916becca8524f55ca2630f134f3f4741de | refs/heads/master | 2023-08-04T07:18:14.159191 | 2021-09-25T17:54:29 | 2021-09-25T17:54:29 | 403,243,335 | 1 | 5 | null | 2021-09-25T17:54:30 | 2021-09-05T07:27:03 | Python | UTF-8 | Python | false | false | 1,269 | py | """"
2. Выполнить логические побитовые операции «И», «ИЛИ» и др. над числами 5 и 6.
Выполнить над числом 5 побитовый сдвиг вправо и влево на два знака.
Объяснить полученный результат.
"""
a = 5
b = 6
a_byte = format(a, 'b')
b_byte = format(b, 'b')
rez = []
print("Логическое \"И\": ")
for i in range(len(a_byte)):
rez.insert(i, int(a_byte[i]) and int(b_byte[i]))
print("Результат: ", ''.join(str(e) for e in rez))
rez = []
print("Логическое \"ИЛИ\": ")
for i in range(len(a_byte)):
rez.insert(i, int(a_byte[i]) or int(b_byte[i]))
print("Результат: ", ''.join(str(e) for e in rez))
print("Побитовый сдвиг числа 5 на два знака вправо: ")
# Отрезаем у скиска два знака с конца и дописываем два нуля вначале
list_to_right = [0, 0] + list(a_byte)[0:-2]
print(''.join(str(e) for e in list_to_right))
print("Побитовый сдвиг числа 5 на два знака влево: ")
list_to_left = list(a_byte)[2:len(a_byte)] + [0, 0]
print(''.join(str(e) for e in list_to_left))
| [
"slyusarrv@yandex.ru"
] | slyusarrv@yandex.ru |
d66816d4187adc8ec829d96ab77ec309eb85a3dc | 65d8d97a05ef63e0a43bdcb2ff6f683442d85b25 | /venv/Scripts/django-admin.py | e45374fb41873a133de05ebf09b01be163c1745b | [] | no_license | philipko100/Ecommerce-Site | a1ba8e15b59ef3a5e66bada044a169198a292a2f | 976268eb740ee664ee71b956b520697937271db2 | refs/heads/main | 2023-08-15T00:41:02.015798 | 2021-09-22T00:14:52 | 2021-09-22T00:14:52 | 405,302,940 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 680 | py | #!C:\Coding\ecommerce\venv\Scripts\python.exe
# When the django-admin.py deprecation ends, remove this script.
import warnings
from django.core import management
try:
from django.utils.deprecation import RemovedInDjango40Warning
except ImportError:
raise ImportError(
'django-admin.py was deprecated in Django 3.1 and removed in Django '
'4.0. Please manually remove this script from your virtual environment '
'and use django-admin instead.'
)
if __name__ == "__main__":
warnings.warn(
'django-admin.py is deprecated in favor of django-admin.',
RemovedInDjango40Warning,
)
management.execute_from_command_line()
| [
"philip.ko.100@gmail.com"
] | philip.ko.100@gmail.com |
7f23226f64137649209c8979392ca73a776cc6ed | 6b2a8dd202fdce77c971c412717e305e1caaac51 | /solutions_5738606668808192_0/Python/xulusko/CoinJam.py | 2d99d9e5c0b0750367878956b22ae6d543d493aa | [] | no_license | alexandraback/datacollection | 0bc67a9ace00abbc843f4912562f3a064992e0e9 | 076a7bc7693f3abf07bfdbdac838cb4ef65ccfcf | refs/heads/master | 2021-01-24T18:27:24.417992 | 2017-05-23T09:23:38 | 2017-05-23T09:23:38 | 84,313,442 | 2 | 4 | null | null | null | null | UTF-8 | Python | false | false | 697 | py | from random import randint
from pyprimes import nprimes
N = 16
J = 50
jamcoins = set()
somePrimes = list(nprimes(47))[1:]
def findDiv(val):
for p in somePrimes:
if val % p == 0: return p
return None
def getDivisors(coin):
divs = []
for base in range(2, 11):
val = int(coin, base)
div = findDiv(val)
if not div: return None
divs.append(div)
return tuple(divs)
while len(jamcoins) < J:
coin = ''
for i in range(N-2): coin += str(randint(0, 1))
coin = '1' + coin + '1'
divs = getDivisors(coin)
if divs: jamcoins.add((coin, divs))
print('Case #1:')
for coin, divs in jamcoins: print(coin, ' '.join(map(str, divs)))
| [
"alexandra1.back@gmail.com"
] | alexandra1.back@gmail.com |
5973172ad98373f1365860f01f4fce3b89ba00f1 | be81dc6b30ddfcb512a58aae2a592f5707b65479 | /8월/swea_4839.py | 0fcbd1792f442828f20b105382deff17b3b87d46 | [] | no_license | mingddo/Algo | 799082d2a9d8e2fa43a910ebf5e769e372774a70 | 6dee72aa3c99b59ada714bfe549b323dbdff2f30 | refs/heads/master | 2023-01-06T00:32:29.457676 | 2020-11-07T07:45:07 | 2020-11-07T07:45:07 | 281,081,195 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 686 | py | import sys
T = int(input())
for tc in range(1, T + 1):
num = list(map(int, input().split()))
result = []
for i in range(2):
start = 1
end = num[0]
cnt = 0
page = num[i+1]
while start <= end:
c = (start + end) // 2
if c == page:
break
elif c < page:
start = c
cnt += 1
else:
end = c
cnt += 1
result.append(cnt)
if result[0] < result[1]:
print('#%d'%tc, 'A')
elif result[0] == result[1]:
print('#%d'%tc,'0')
else:
print('#%d'%tc,'B')
| [
"dk.myeong@gmail.com"
] | dk.myeong@gmail.com |
a27f8c7745fc850e88e726b1c9dea6b2f85427bf | 844d9398f308362a88e1282f1c3c1963a1a93acd | /wordcount/urls.py | de041350b898e473ea6934e5293d0a37d529a5ba | [] | no_license | lcres7/wordcount-project | ea13f7b2c2e23d665e667878d7697720d75f80fc | 9b8cd00862452a625f58e94c44b224049cbae9aa | refs/heads/master | 2022-04-10T07:18:36.082882 | 2020-03-26T14:59:14 | 2020-03-26T14:59:14 | 250,291,176 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 867 | py | """wordcount URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path
from . import views
urlpatterns = [
path('', views.home, name='home'),
path('count/', views.count, name='count'),
path('about/', views.about, name='about'),
]
| [
"lukec@localhost.localdomain"
] | lukec@localhost.localdomain |
57b50a91bccb5468120878e16db6c15f95c792be | e87e71e01a14d3469f3249a5dc546f9f7e5f6332 | /api/blockchain/views.py | d2e4d7469e7440c82d438b051d6b2ee3e320d126 | [] | no_license | jlmallas160190/challenge-ripio-be | 7f4b55da67c45b1c5bbcea011376691f144a4a49 | bf7354ed61372e80c31d6120f062db193a651db4 | refs/heads/master | 2023-05-30T18:58:10.139040 | 2021-06-14T15:14:40 | 2021-06-15T04:36:53 | 373,355,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,174 | py | from decimal import Decimal
from app.blockchain.tasks import calculate_balance_task
import logging
from rest_framework.authtoken.models import Token
from api.blockchain.serializers import (CoinSerializer,
TransactionSerializer,
WalletSerializer)
from app.blockchain.models import Account, Coin, Transaction, Wallet
from rest_framework import permissions, status, viewsets
from rest_framework.decorators import action
from rest_framework.response import Response
class CoinViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows coins to be viewed or edited.
"""
queryset = Coin.objects.all()
serializer_class = CoinSerializer
permission_classes = [permissions.IsAuthenticated]
class WalletViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows wallet to be viewed or edited.
"""
queryset = Wallet.objects.all()
serializer_class = WalletSerializer
permission_classes = [permissions.IsAuthenticated]
def __authorize(self, request):
auth_header = request.META['HTTP_AUTHORIZATION']
index = auth_header.find(' ')
token = Token.objects.get(key=auth_header[index:].strip())
return Account.objects.get(user_id=token.user_id)
def list(self, request, *args, **kwargs):
try:
account = self.__authorize(request=request)
queryset = Wallet.objects.filter(account_id=account.id).all()
serializer = WalletSerializer(queryset, many=True)
return Response(serializer.data)
except Exception as ex:
logging.error(ex)
return Response({
'message': str(ex),
'status': status.HTTP_500_INTERNAL_SERVER_ERROR,
}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
def create(self, request, *args, **kwargs):
try:
account = self.__authorize(request=request)
data = request.data
data['account_id'] = account.id
serializer = WalletSerializer(data=data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data, status=status.HTTP_201_CREATED)
except Exception as ex:
logging.error(ex)
return Response({
'message': str(ex),
'status': status.HTTP_500_INTERNAL_SERVER_ERROR,
}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
def update(self, request, pk=None, *args, **kwargs):
try:
self.__authorize(request=request)
wallet = Wallet.objects.get(id=pk)
wallet.calculate_balance()
data = request.data
serializer = WalletSerializer(wallet, data=data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
except Exception as ex:
logging.error(ex)
return Response({
'message': str(ex),
'status': status.HTTP_500_INTERNAL_SERVER_ERROR,
}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
@action(detail=True, methods=['GET', 'POST'])
def transactions(self, request, pk=None, *args, **kwargs):
try:
account = self.__authorize(request=request)
if request.method == 'GET':
queryset = Transaction.objects.filter(
sender_id=pk, sender__account_id=account.id).all()
serializer = TransactionSerializer(queryset, many=True)
return Response(serializer.data)
if request.method == 'POST':
data = request.data.copy()
data['sender_id'] = pk
wallet = Wallet.objects.get(pk=pk)
wallet.calculate_balance()
if request.user.is_superuser is False and wallet.balance < Decimal(data['amount']):
return Response({
'message': 'You have not money in your wallet for this transaction, your balance is {}'.format(wallet.balance),
'status': status.HTTP_400_BAD_REQUEST,
}, status=status.HTTP_400_BAD_REQUEST)
serializer = TransactionSerializer(data=data)
if serializer.is_valid():
serializer.save()
calculate_balance_task.delay(
data['recipient'], 'recipient')
if (request.user.is_superuser is False):
calculate_balance_task.delay(
data['sender_id'], 'sender_id')
return Response(serializer.data, status=status.HTTP_201_CREATED)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
except Exception as ex:
logging.error(ex)
return Response({'status': status.HTTP_500_INTERNAL_SERVER_ERROR,
'message': str(ex)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
| [
"jomasloja@gmail.com"
] | jomasloja@gmail.com |
447ffb47be7aa30b0ecec7aad540537018d8f179 | d6703af7ee5c1f711fa117145c614801c5199762 | /lambda/pain_lambda.py | c63dd949fb764245e287e1b8c0536557f503e110 | [
"MIT"
] | permissive | AdamMcCormick/share-the-pain | 641b71a9af1608a83e5e23a75edddcf317717f0f | c7a7055723925dd36b42982b5d17c9f8ccf5b397 | refs/heads/master | 2021-09-01T11:56:46.637013 | 2017-12-26T21:17:03 | 2017-12-26T21:17:03 | 114,928,433 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,691 | py | from datetime import datetime
import json
import re
import os
import pyrebase
firebase = pyrebase.initialize_app(os.environ)
auth = firebase.auth()
def resource(path, base = None) :
base = base if base else firebase.database();
segment, subPath = re.sub(r'/+', '/', re.sub(r'^/', '', path)).partition('/')[::2]
#print('"' + base.path + '"', '"' + segment + '"', '"' + subPath + '"')
return base if not segment else resource(subPath, base.child(segment))
def getUserData(user) :
return resource('users/' + user['localId'] + '/metadata');
def getCurrentReason(user) :
userData = getUserData(user)
if not userData :
return None;
metadata = userData.get().val()
return metadata['currentReason'] if metadata and 'currentReason' in metadata else None;
def failure(typeVal, event) :
return lambda user, reason, note, isLearning: {
'isBase64Encoded': False,
'statusCode': 404,
'headers': {
'Content-Type': 'text/plain'
},
'body': 'Call failed, resource ' + typeVal + ' not found'
}
def pushMessage(user, type, reason = False, note = None, isLearning = False, date = None) :
if type :
message = {
'reason': reason if reason else 'unknown',
'note': note,
'isLearning': isLearning,
'type': type,
'date': (date if date else datetime.now()).isoformat()
}
userMessages = resource('users/' + user['localId'] + '/pain')
userMessages.push(message)
allMessage = message.copy()
allMessage['user'] = user['localId']
allMessages = resource('pain')
allMessages.push(allMessage)
return {
"isBase64Encoded": False,
"statusCode": 200,
"headers": {},
"body": None
}
def setReason(user, reason, note, isLearning = False) :
current = getCurrentReason(user)
if current :
pushMessage(user, 'DUN', current, note, isLearning)
getUserData(user).child('currentReason').set(reason)
return pushMessage(user, 'MUX', reason, note, isLearning)
def wtf(user, reason, note, isLearning) :
return pushMessage(user, 'WTF', reason if reason else getCurrentReason(user), note)
def yay(user, reason, note, isLearning) :
return pushMessage(user, 'YAY', reason if reason else getCurrentReason(user), note)
def handleRequest(event, context) :
body = json.loads(event['body'])
user = auth.sign_in_with_email_and_password(body['email'], body['password'])
typeVal = body.get('type', event['path'])
return {
'yay': yay,
'/yay': yay,
'wtf': wtf,
'/wtf': wtf,
'mux': setReason,
'/mux': setReason
}.get(typeVal.lower(), failure(typeVal, event))(
user,
body.get('reason', None),
body.get('note', None),
body.get('isLearning', None)
)
| [
"awMcCormick@sbgtv.com"
] | awMcCormick@sbgtv.com |
3fea2dc185356ece549895fc3905f0ab08fbe826 | eaae0c717cbb3189f84f64ec1e06c2b90184d6b2 | /ai_moive_project/build_database.py | dd63d337863727591507cab629c0671a7ec2dea9 | [] | no_license | ZhikunWei/AI_project_moive_conversation_agent | 50c5701f36486d5beab25e01f5590f38fe8e076a | f7637223915a654d71909c532c117bb5cdaef8ef | refs/heads/master | 2022-06-18T04:52:54.497144 | 2020-05-10T15:04:20 | 2020-05-10T15:04:20 | 262,812,079 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,822 | py | import rdflib
from rdflib import Graph, Literal, BNode, Namespace, URIRef
from rdflib import RDF, RDFS
import pickle
def buildGraph():
g = Graph()
url_prefix = "http://example.org/"
my_namespace = Namespace("http://example.org/")
uriDict = {}
# concepts
moiveID = URIRef(url_prefix+'moiveID')
rating = URIRef(url_prefix+'rating')
year = URIRef(url_prefix+'year')
title = URIRef(url_prefix+'title')
director = URIRef(url_prefix+'director')
actor = URIRef(url_prefix+'actor')
writer = URIRef(url_prefix+'writer')
person = URIRef(url_prefix+'person')
genres = URIRef(url_prefix+'genres')
uriDict['moiveID'] = moiveID
uriDict['rating'] = rating
uriDict['year'] = year
uriDict['title'] = title
uriDict['director'] = director
uriDict['actor'] = actor
uriDict['writer'] = writer
uriDict['person'] = person
uriDict['genres'] = genres
# each concept is a RDFS.Class
g.add((moiveID, RDF.type, RDFS.Class))
g.add((rating, RDF.type, RDFS.Class))
g.add((year, RDF.type, RDFS.Class))
g.add((title, RDF.type, RDFS.Class))
g.add((director, RDF.type, RDFS.Class))
g.add((actor, RDF.type, RDFS.Class))
g.add((writer, RDF.type, RDFS.Class))
g.add((person, RDF.type, RDFS.Class))
g.add((genres, RDF.type, RDFS.Class))
# concept label
g.add((moiveID, RDFS.label, Literal('moiveID')))
g.add((rating, RDFS.label, Literal('rating')))
g.add((year, RDFS.label, Literal('year')))
g.add((title, RDFS.label, Literal('title')))
g.add((director, RDFS.label, Literal('director')))
g.add((actor, RDFS.label, Literal('actor')))
g.add((writer, RDFS.label, Literal('writer')))
g.add((person, RDFS.label, Literal('person')))
g.add((genres, RDFS.label, Literal('genres')))
# property
ratedBy = URIRef(url_prefix+'ratedBy')
hasTitle = URIRef(url_prefix+'hasTitle')
showInYear = URIRef(url_prefix+'showInYear')
belongsToGenre = URIRef(url_prefix+'belongsToGenre')
directedBy = URIRef(url_prefix+'directedBy')
writedBy = URIRef(url_prefix+'writedBy')
starredBy = URIRef(url_prefix+'starredBy')
getId = URIRef(url_prefix+'getId')
involve = URIRef(url_prefix+'involve')
uriDict['ratedBy'] = ratedBy
uriDict['hasTitle'] = hasTitle
uriDict['showInYear'] = showInYear
uriDict['belongsToGenre'] = belongsToGenre
uriDict['directedBy'] = directedBy
uriDict['writedBy'] = writedBy
uriDict['starredBy'] = starredBy
uriDict['getId'] = getId
uriDict['involve'] = involve
# each property is a RDFS.Property
g.add((ratedBy, RDF.type, RDF.Property))
g.add((hasTitle, RDF.type, RDF.Property))
g.add((showInYear, RDF.type, RDF.Property))
g.add((belongsToGenre, RDF.type, RDF.Property))
g.add((directedBy, RDF.type, RDF.Property))
g.add((writedBy, RDF.type, RDF.Property))
g.add((starredBy, RDF.type, RDF.Property))
g.add((getId, RDF.type, RDF.Property))
g.add((involve, RDF.type, RDF.Property))
# property lable
g.add((ratedBy, RDFS.label, Literal('ratedBy')))
g.add((hasTitle, RDFS.label, Literal('hasTitle')))
g.add((showInYear, RDFS.label, Literal('showInYear')))
g.add((belongsToGenre, RDFS.label, Literal('belongsToGenre')))
g.add((directedBy, RDFS.label, Literal('directedBy')))
g.add((writedBy, RDFS.label, Literal('writedBy')))
g.add((starredBy, RDFS.label, Literal('starredBy')))
g.add((getId, RDFS.label, Literal('getId')))
g.add((involve, RDFS.label, Literal('involve')))
# subclass
g.add((director, RDFS.subClassOf, person))
g.add((actor, RDFS.subClassOf, person))
g.add((writer, RDFS.subClassOf, person))
g.add((directedBy, RDFS.subClassOf, involve))
g.add((starredBy, RDFS.subClassOf, involve))
g.add((writedBy, RDFS.subClassOf, involve))
#domain & range
g.add((hasTitle, RDFS.domain, moiveID))
g.add((ratedBy, RDFS.domain, title))
g.add((showInYear, RDFS.domain, title))
g.add((belongsToGenre, RDFS.domain, title))
g.add((directedBy, RDFS.domain, title))
g.add((writedBy, RDFS.domain, title))
g.add((starredBy, RDFS.domain, title))
g.add((getId, RDFS.domain, title))
g.add((hasTitle, RDFS.range, title))
g.add((ratedBy, RDFS.range, rating))
g.add((showInYear, RDFS.range, year))
g.add((belongsToGenre, RDFS.range, genres))
g.add((directedBy, RDFS.range, director))
g.add((writedBy, RDFS.range, writer))
g.add((starredBy, RDFS.range, actor))
g.add((getId, RDFS.range, moiveID))
ins_genres = {}
ins_directors = {}
ins_writers = {}
ins_actors = {}
with open('./imdb_data/moive_dict.pkl', 'rb') as f:
moive_dict = pickle.load(f)
for k in moive_dict:
ins_moiveID = URIRef(url_prefix+'_'+k+'_moiveID')
g.add((ins_moiveID, RDFS.label, Literal(k)))
g.add((ins_moiveID, RDF.type, moiveID))
ins_rating = URIRef(url_prefix+'_'+k+'_rating')
g.add((ins_rating, RDFS.label, Literal(moive_dict[k]['rating'])))
g.add((ins_rating, RDF.type, rating))
g.add((ins_moiveID, ratedBy, ins_rating))
ins_title = URIRef(url_prefix+'_'+k+'_title')
g.add((ins_title, RDFS.label, Literal(moive_dict[k]['primaryTitle'])))
g.add((ins_title, RDF.type, title))
g.add((ins_moiveID, hasTitle, ins_title))
ins_year = URIRef(url_prefix+'_'+k+'_year')
if moive_dict[k]['startYear'] != '\\N':
g.add((ins_year, RDFS.label, Literal(int(moive_dict[k]['startYear']))))
g.add((ins_year, RDF.type, year))
g.add((ins_moiveID, showInYear,ins_year))
for gener_name in moive_dict[k]['genres'].split(','):
if gener_name == r'\N':
continue
if gener_name not in ins_genres:
ins_genres[gener_name] = URIRef(url_prefix+'_genres_'+gener_name.replace(' ', '_'))
g.add((ins_genres[gener_name], RDF.type, genres))
g.add((ins_genres[gener_name], RDFS.label, Literal(gener_name)))
g.add((ins_moiveID, belongsToGenre, ins_genres[gener_name]))
for d in moive_dict[k]['directors']:
if d not in ins_directors:
ins_directors[d] = URIRef(url_prefix+'_director_'+d.replace(' ', '_'))
g.add((ins_directors[d], RDF.type, director))
g.add((ins_directors[d], RDFS.label, Literal(d)))
g.add((ins_moiveID, directedBy, ins_directors[d]))
g.add((ins_moiveID, involve, ins_directors[d]))
for w in moive_dict[k]['writers']:
if w not in ins_writers:
ins_writers[w] = URIRef(url_prefix+'_writer_'+w.replace(' ', '_'))
g.add((ins_writers[w], RDF.type, writer))
g.add((ins_writers[w], RDFS.label, Literal(w)))
g.add((ins_moiveID, writedBy, ins_writers[w]))
g.add((ins_moiveID, involve, ins_writers[w]))
if 'actors' in moive_dict[k]:
for a in moive_dict[k]['actors']:
if a not in ins_actors:
ins_actors[a] = URIRef(url_prefix+'_actor_'+a.replace(' ', '_').replace('"', ''))
g.add((ins_actors[a], RDF.type, actor))
g.add((ins_actors[a], RDFS.label, Literal(a)))
g.add((ins_moiveID, starredBy, ins_actors[a]))
g.add((ins_moiveID, involve, ins_actors[a]))
g.bind("ns", my_namespace)
g.serialize("imdb_data/moiveDatabase.ttl", format= "xml")
if __name__ == '__main__':
buildGraph() | [
"noreply@github.com"
] | noreply@github.com |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.