xszheng2020/the_stack_dedup_python_hits_1 · Datasets at Hugging Face

24b7c41cba674d3c5a96735fae3e61b4d3db7195

1,376

py

Python

i3configger/bindings.py

obestwalter/i3-configger

c981a01f5b89fd37ab5a98af1229819cea305f6a

[ "MIT" ]

30

2017-05-20T12:27:37.000Z

2021-09-27T17:01:20.000Z

i3configger/bindings.py

obestwalter/i3configger

c981a01f5b89fd37ab5a98af1229819cea305f6a

[ "MIT" ]

9

2017-05-21T23:17:04.000Z

2019-05-09T13:24:32.000Z

i3configger/bindings.py

obestwalter/i3-configger

c981a01f5b89fd37ab5a98af1229819cea305f6a

[ "MIT" ]

3

2017-06-04T20:29:29.000Z

2021-09-27T17:01:23.000Z

"""WARNING Just an experiment - please ignore this.""" from i3configger import config BINDCODE = "bindcode" BINDSYM = "bindsym" class Bindings: """ bindsym | bindcode [--release] [<Group>+][<Modifiers>+]<keysym> command [--release] [--border] [--whole-window] [<Modifiers>+]button<n> command """ def __init__(self, content): self.content = content def get_all_bindings(self): lines = [l.strip() for l in self.content.splitlines()] lines = [l for l in lines if any(m in l for m in [BINDCODE, BINDSYM])] lines = [l for l in lines if not l.startswith(config.MARK.COMMENT)] return sorted(set(lines)) def translate_bindings(self): """translate bindcode to bindsym assignments this need to be done the moment the information is asked because it depends on the currently active layout. """ raise NotImplementedError() def write_bindings_info(self): """Write info in some format that can be nicely displayed""" raise NotImplementedError() if __name__ == "__main__": # use partials and account for modes # a naming convention would make this quite easy # mode-<modename>.conf -> bindings active in <modename> p = config.I3configgerConfig().targetPath b = Bindings(p.read_text()) print("\n".join(b.get_all_bindings()))

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null

0

1

0

1

24ba97b99cd37843fd8b359e53696bd9e75b0abb

1,867

py

Python

musketeer/fitSignals.py

TChis/Musketeer

bd67b2e7f4e1827c96d10bbf278c781ce22681f3

[ "MIT" ]

null

musketeer/fitSignals.py

TChis/Musketeer

bd67b2e7f4e1827c96d10bbf278c781ce22681f3

[ "MIT" ]

null

musketeer/fitSignals.py

TChis/Musketeer

bd67b2e7f4e1827c96d10bbf278c781ce22681f3

[ "MIT" ]

2

2021-05-07T12:29:02.000Z

2022-01-10T11:57:22.000Z

import numpy as np from numpy.linalg import lstsq from scipy.optimize import lsq_linear from . import moduleFrame class FitSignals(moduleFrame.Strategy): def __call__(self, signalVars, knownSpectra): # rows are additions, columns are contributors knownMask = ~np.isnan(knownSpectra[:, 0]) knownSignals = signalVars[:, knownMask] unknownSignals = signalVars[:, ~knownMask] knownSpectrum = knownSignals @ knownSpectra[knownMask, :] unknownSpectrum = self.titration.processedData - knownSpectrum fittedSignals, residuals, _, _ = lstsq( unknownSignals, unknownSpectrum, rcond=None ) fittedCurves = unknownSignals @ fittedSignals + knownSpectrum allSignals = knownSpectra.copy() allSignals[~knownMask, :] = fittedSignals return allSignals, residuals, fittedCurves class FitSignalsNonnegative(moduleFrame.Strategy): # TODO: account for known spectra def __call__(self, signalVars, knownSpectra): fittedSignals = np.empty((0, signalVars.shape[1])) residuals = np.empty((1, 0)) for signal in self.titration.processedData.T: result = lsq_linear(signalVars, signal, (0, np.inf), method="bvls") fittedSignals = np.vstack((fittedSignals, result.x)) residuals = np.append(residuals, result.cost) fittedSignals = fittedSignals.T fittedCurves = signalVars @ fittedSignals return fittedSignals, residuals, fittedCurves class ModuleFrame(moduleFrame.ModuleFrame): frameLabel = "Fit signals" dropdownLabelText = "Fit signals to curve using:" # TODO: add least squares with linear constraints dropdownOptions = { "Ordinary least squares": FitSignals, "Nonnegative least squares": FitSignalsNonnegative, } attributeName = "fitSignals"

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1

24bce25b915ba22957eca242f8aa3b075851e90b

588

py

Python

translations/migrations/0025_move_category_m2m.py

TranslateForSG/translateforsg-backend

319d90229fa0b22e4a6e77b321276e0e93cb6413

[ "MIT" ]

2

2020-05-08T07:18:05.000Z

2020-05-13T13:22:19.000Z

translations/migrations/0025_move_category_m2m.py

aniruddha-adhikary/translateforsg-backend

319d90229fa0b22e4a6e77b321276e0e93cb6413

[ "MIT" ]

7

2021-03-19T02:03:21.000Z

2021-09-22T18:54:02.000Z

translations/migrations/0025_move_category_m2m.py

aniruddha-adhikary/translateforsg-backend

319d90229fa0b22e4a6e77b321276e0e93cb6413

[ "MIT" ]

null

# Generated by Django 3.0.5 on 2020-04-21 11:08 from django.db import migrations def move_category_m2m(apps, schema_editor): Category = apps.get_model('translations', 'Category') Phrase = apps.get_model('translations', 'Phrase') for category in Category.objects.all(): for phrase in Phrase.objects.filter(category=category): phrase.categories.add(category) class Migration(migrations.Migration): dependencies = [ ('translations', '0024_auto_20200421_1908'), ] operations = [ migrations.RunPython(move_category_m2m) ]

25.565217

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588

5.671429

0.614286

0.060453

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null

0

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null

0

1

24c51f4ab48e95013feb31263b800f59b0194d64

4,028

py

Python

mipkit/dl/metrics.py

congvmit/mipkit

d65a5083852dcfc5db766175aa402a5e3a506f21

[ "MIT" ]

8

2021-06-17T08:13:51.000Z

2022-02-21T13:31:18.000Z

mipkit/dl/metrics.py

congvmit/mipkit

d65a5083852dcfc5db766175aa402a5e3a506f21

[ "MIT" ]

null

mipkit/dl/metrics.py

congvmit/mipkit

d65a5083852dcfc5db766175aa402a5e3a506f21

[ "MIT" ]

null

""" The MIT License (MIT) Copyright (c) 2021 Cong Vo Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. Provided license texts might have their own copyrights and restrictions THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import scipy.stats as scs def pearsonr( x, y, dim ): r"""Computes Pearson Correlation Coefficient across rows. Pearson Correlation Coefficient (also known as Linear Correlation Coefficient or Pearson's :math:`\rho`) is computed as: .. math:: \rho = \frac {E[(X-\mu_X)(Y-\mu_Y)]} {\sigma_X\sigma_Y} If inputs are matrices, then then we assume that we are given a mini-batch of sequences, and the correlation coefficient is computed for each sequence independently and returned as a vector. If `batch_fist` is `True`, then we assume that every row represents a sequence in the mini-batch, otherwise we assume that batch information is in the columns. Warning: We do not account for the multi-dimensional case. This function has been tested only for the 2D case, either in `batch_first==True` or in `batch_first==False` mode. In the multi-dimensional case, it is possible that the values returned will be meaningless. Args: x (torch.Tensor): input tensor y (torch.Tensor): target tensor batch_first (bool, optional): controls if batch dimension is first. Default: `True` Returns: torch.Tensor: correlation coefficient between `x` and `y` Note: :math:`\sigma_X` is computed using **PyTorch** builtin **Tensor.std()**, which by default uses Bessel correction: .. math:: \sigma_X=\displaystyle\frac{1}{N-1}\sum_{i=1}^N({x_i}-\bar{x})^2 We therefore account for this correction in the computation of the covariance by multiplying it with :math:`\frac{1}{N-1}`. Shape: - Input: :math:`(N, M)` for correlation between matrices, or :math:`(M)` for correlation between vectors - Target: :math:`(N, M)` or :math:`(M)`. Must be identical to input - Output: :math:`(N, 1)` for correlation between matrices, or :math:`(1)` for correlation between vectors Examples: >>> import torch >>> _ = torch.manual_seed(0) >>> input = torch.rand(3, 5) >>> target = torch.rand(3, 5) >>> output = pearsonr(input, target) >>> print('Pearson Correlation between input and target is {0}'.format(output[:, 0])) Pearson Correlation between input and target is tensor([ 0.2991, -0.8471, 0.9138]) """ # noqa: E501 assert x.shape == y.shape centered_x = x - x.mean(dim=dim, keepdim=True) centered_y = y - y.mean(dim=dim, keepdim=True) covariance = (centered_x * centered_y).sum(dim=dim, keepdim=True) bessel_corrected_covariance = covariance / (x.shape[dim] - 1) x_std = x.std(dim=dim, keepdim=True) y_std = y.std(dim=dim, keepdim=True) corr = bessel_corrected_covariance / (x_std * y_std + 10e-7) return corr

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null

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1

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null

0

1

24cccb183a4ac3f9434412a945c1d0bccd279086

4,709

py

Python

app/scripts/config_check.py

PromoFaux/plex-utills

570e2e4525b992978780b6a195df94c674c94ac3

[ "MIT" ]

179

2020-02-27T01:09:32.000Z

2022-03-28T21:56:20.000Z

app/scripts/config_check.py

PromoFaux/plex-utills

570e2e4525b992978780b6a195df94c674c94ac3

[ "MIT" ]

94

2020-03-03T03:22:42.000Z

2022-03-28T20:13:22.000Z

app/scripts/config_check.py

PromoFaux/plex-utills

570e2e4525b992978780b6a195df94c674c94ac3

[ "MIT" ]

36

2020-02-28T13:58:54.000Z

2022-03-26T10:04:25.000Z

#!/usr/local/bin/python3 import os import subprocess from subprocess import Popen, PIPE, STDOUT from configparser import ConfigParser import subprocess import plexapi import schedule import time from datetime import datetime import re from colorama import Fore, Back, Style import socket from urllib import parse from plexapi.server import PlexServer config_object = ConfigParser() config_object.read("/config/config.ini") server = config_object["PLEXSERVER"] schedules = config_object["SCHEDULES"] options = config_object["OPTIONS"] hdr_4k_posters = str.lower((options["4k_hdr_posters"])) poster_3d = str.lower((options["3D_posters"])) Disney = str.lower((options["Disney"])) Pixar = (str.lower(options["Pixar"])) hide_4k = str.lower((options["hide_4k"])) pbak = str.lower((options["POSTER_BU"])) HDR_BANNER = str.lower((options["HDR_BANNER"])) optimise = str.lower((options["transcode"])) mini_4k = str.lower((options["mini_4k"])) mini_3d = str.lower((options["mini_3D"])) t1 = (schedules["4k_poster_schedule"]) t2 = (schedules["disney_schedule"]) t3 = (schedules["pixar_schedule"]) t4 = (schedules["hide_poster_schedule"]) t5 = (schedules["3d_poster_schedule"]) url = parse.urlparse(server["PLEX_URL"]).hostname try: url = parse.urlparse(server["PLEX_URL"]).hostname socket.inet_aton(url) except socket.error: raise Exception("Uh-Oh, it looks like your PLEX_URL is not correct in the config file \n Make sure you enter it as 'http://ip-address:plex-port'") if server["TOKEN"] == '<token>': raise Exception("You must add your Plex Token to the config file.") try: print("Your Server's Friendly name is ", PlexServer((server["PLEX_URL"]), (server["TOKEN"])).friendlyName) except : print('Cannot access your Plex account, please make sure that your Plex URL and Token are correct') exit() if pbak == 'true': pass elif pbak == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if HDR_BANNER == 'true': pass elif HDR_BANNER == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if mini_4k == 'true': pass elif mini_4k == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if hdr_4k_posters == 'true': pass elif hdr_4k_posters == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if poster_3d == 'true': pass elif poster_3d == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if Disney == 'true': pass elif Disney == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if Pixar == 'true': pass elif Pixar == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if hide_4k == 'true': pass elif hide_4k == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') if optimise == 'true': pass elif optimise == 'false': pass else: raise ValueError('SYNTAX ERROR: Please enter either "true" or "false" to set the script behaviour.') a = re.compile("^[0-9]{2}:[0-9]{2}$") if a.match(t1) and hdr_4k_posters == 'true': pass elif hdr_4k_posters != 'true': pass else: raise ValueError('Please make sure that your scheduled times are written in the format HH:MM') if a.match(t5) and poster_3d == 'true': pass elif poster_3d != 'true': pass else: raise ValueError('Please make sure that your scheduled times are written in the format HH:MM') if a.match(t2) and Disney == 'true': pass elif Disney != 'true': pass else: raise ValueError('Please make sure that your scheduled times are written in the format HH:MM') if a.match(t3) and Pixar == 'true': pass elif Pixar != 'true': pass else: raise ValueError('Please make sure that your scheduled times are written in the format HH:MM') if a.match(t4) and hide_4k == 'true': pass elif hide_4k != 'true': pass else: raise ValueError('Please make sure that your scheduled times are written in the format HH:MM') print('Config check passed') p = Popen('python -u ./run_all.py', shell=True) output = p.communicate() print(output[0])

30.185897

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null

0

null

0

1

0

1

24cf41a00623d50e881d78fdc44ceca7f693a7f5

1,371

py

Python

feed/models.py

mehDkhan/zngol

3a6449cb1b83e4a9707d103e8b9c9748a8ba5810

[ "MIT" ]

null

feed/models.py

mehDkhan/zngol

3a6449cb1b83e4a9707d103e8b9c9748a8ba5810

[ "MIT" ]

8

2020-02-12T01:08:53.000Z

2022-02-10T08:31:06.000Z

feed/models.py

mehDkhan/zngol

3a6449cb1b83e4a9707d103e8b9c9748a8ba5810

[ "MIT" ]

null

from django.db import models from account.models import User from django.utils import timezone from django.utils.text import slugify class Post(models.Model): author = models.ForeignKey(to=User, on_delete=models.SET_NULL, related_name='feed_posts', null=True ) title = models.CharField(max_length=140,blank=False,null=False) body = models.TextField(max_length=250,blank=False,null=False) slug = models.SlugField(max_length=250,unique_for_date='created') created = models.DateTimeField(auto_now_add=True) updated = models.DateTimeField(auto_now=True) class Meta: ordering = ('-created','-updated') def __str__(self): return self.title def save(self, *args, **kwargs): if not self.slug: self.slug = slugify(self.title) super().save(*args, **kwargs) class Comment(models.Model): post = models.ForeignKey(Post, related_name='comments', on_delete=models.CASCADE) author = models.ForeignKey(User, on_delete=models.CASCADE) body = models.TextField() created = models.DateTimeField(auto_now_add=timezone.now()) class Meta: ordering = ('-created',) def __str__(self): return 'Comment by {} on {}'.format(self.author,self.post)

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1,371

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false

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0

null

0

null

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1

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1

24d041644a0972c3d43a61ae3680b9999e219c63

898

py

Python

setup.py

ebruagbay/dsmlbc6_ebruagbay

b58ade5c808ded057595b9c607b745971580b3dd

[ "MIT" ]

null

setup.py

ebruagbay/dsmlbc6_ebruagbay

b58ade5c808ded057595b9c607b745971580b3dd

[ "MIT" ]

null

setup.py

ebruagbay/dsmlbc6_ebruagbay

b58ade5c808ded057595b9c607b745971580b3dd

[ "MIT" ]

null

import setuptools setuptools.setup(name="dsmlbc6_ebruagbay", version="0.0.2", license="MIT", author="Ebru Topsakal Agbay", author_mail="ebrugeo@gmail.com", description="Data Science Tools", url="https://github.com/ebruagbay/dsmlbc6_ebruagbay.git", keywords=["datascience","machine learning","bootcamp"], classifiers=[ "Development Status :: 4 - Beta", "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.5", "Topic :: Scientific/Engineering", ], package=setuptools.find_packages() )

44.9

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0

0.018727

0.405345

898

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null

0

null

0

1

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1

24d17cdc96014255022efc31f4e73c1c00af18cc

996

py

Python

outputs/admin.py

jayvdb/django-outputs

fcd1386b5dd95d71655e44fa49b766941bbcad43

[ "Apache-2.0" ]

null

outputs/admin.py

jayvdb/django-outputs

fcd1386b5dd95d71655e44fa49b766941bbcad43

[ "Apache-2.0" ]

null

outputs/admin.py

jayvdb/django-outputs

fcd1386b5dd95d71655e44fa49b766941bbcad43

[ "Apache-2.0" ]

null

from django.contrib import admin from outputs.models import Export, Scheduler @admin.register(Export) class ExportAdmin(admin.ModelAdmin): date_hierarchy = 'created' search_fields = ['creator__first_name', 'creator__last_name'] list_select_related = ['creator', 'content_type'] list_filter = ['format', 'context', 'content_type'] list_display = ('id', 'content_type', 'format', 'creator', 'total', 'created') actions = ['send_mail'] def send_mail(self, request, queryset): for obj in queryset.all(): obj.send_mail(language=request.LANGUAGE_CODE) @admin.register(Scheduler) class SchedulerAdmin(admin.ModelAdmin): date_hierarchy = 'created' search_fields = ['creator__first_name', 'creator__last_name'] list_select_related = ['creator', 'content_type'] list_filter = ['routine', 'is_active', 'format', 'context', 'content_type'] list_display = ('id', 'routine', 'is_active', 'content_type', 'format', 'creator', 'created')

36.888889

97

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996

5.747826

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996

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null

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null

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1

0

1

24d19ac974b3536f36cf25e1c8b1eefc826bb152

1,124

py

Python

scrapeProject/spiders/pragativadi.py

OdiaNLP/DataScraper

a065d350602fc370cacde3f8ab62c3cc5b9e1ba9

[ "MIT" ]

null

scrapeProject/spiders/pragativadi.py

OdiaNLP/DataScraper

a065d350602fc370cacde3f8ab62c3cc5b9e1ba9

[ "MIT" ]

null

scrapeProject/spiders/pragativadi.py

OdiaNLP/DataScraper

a065d350602fc370cacde3f8ab62c3cc5b9e1ba9

[ "MIT" ]

null

from scrapy.linkextractors import LinkExtractor from scrapy.loader import ItemLoader from scrapy.loader.processors import MapCompose, Join from scrapy.spiders import CrawlSpider, Rule from scrapeProject.items import ScrapeprojectItem class PragativadiSpider(CrawlSpider): name = 'pragativadi' start_urls = ["https://pragativadinews.com/blog/"] # Rules for horizontal and vertical scrolling rules = ( Rule(LinkExtractor(restrict_xpaths="//div[@class='older']/a"), follow=True), Rule(LinkExtractor(restrict_xpaths="//h2/a[@class='post-url post-title']"), follow=True, callback='parse_item'), ) def parse_item(self, response): l = ItemLoader(item=ScrapeprojectItem(), response=response) # Load fields using XPath expressions l.add_xpath('header', "//h1[@class='single-post-title']//text()", MapCompose(lambda text: text.strip()), Join()) l.add_xpath('content', "//div[@class='entry-content clearfix single-post-content']/p//text()", MapCompose(lambda text: text.strip()), Join()) return l.load_item()

40.142857

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0

null

0

1

0

1

24dba7886b98a74cae8aad667f6a9c05f67ebc42

1,745

py

Python

deeplearning/ml4pl/filesystem_paths.py

island255/ProGraML

6c4ea50639773009e7c287feb62c6994fa4f3445

[ "Apache-2.0" ]

1

2020-07-14T12:17:45.000Z

deeplearning/ml4pl/filesystem_paths.py

island255/ProGraML

6c4ea50639773009e7c287feb62c6994fa4f3445

[ "Apache-2.0" ]

null

deeplearning/ml4pl/filesystem_paths.py

island255/ProGraML

6c4ea50639773009e7c287feb62c6994fa4f3445

[ "Apache-2.0" ]

null

# Copyright 2019-2020 the ProGraML authors. # # Contact Chris Cummins <chrisc.101@gmail.com>. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Module for generating filesystem paths. We occasionally want to create or read files. When doing so, use this module to generate the path. This module contains a default hardcoded location for files which can be overridden by setting the ${ML4PL_TMP_ROOT} environment variable. """ import os import pathlib from typing import Union from labm8.py import app FLAGS = app.FLAGS # The root directory for storing temporary files. # We use /tmp/ as the default root because other plausible locations like # ~/.cache are sandboxed by bazel during testing. TMP_ROOT = pathlib.Path( os.environ.get( "ML4PL_TMP_ROOT", f"/tmp/ml4pl/{os.environ.get('USER', 'anon')}" ) ).absolute() os.environ["ML4PL_TMP_ROOT"] = str(TMP_ROOT) def TemporaryFilePath(relpath: Union[str, pathlib.Path]): """Generate an absolute path for a temporary file. Args: relpath: A relative path. Returns: A concatenation of the ${ML4PL_TMP_ROOT} directory and the relative path. No assumption is made on the type of path, or whether it (or any parent directories) exist. """ return TMP_ROOT / relpath

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null

0

null

0

1

0

1

24e20217d793c96b06ef2e09e523e4525409a89a

4,565

py

Python

var/www/cgi-bin/ewmethodConf.py

DanielAndreasen/FASMA-web

4b87b2ac0be98817825fc94e5f287e5eb968d392

[ "MIT" ]

1

2017-01-24T14:15:22.000Z

var/www/cgi-bin/ewmethodConf.py

DanielAndreasen/FASMA-web

4b87b2ac0be98817825fc94e5f287e5eb968d392

[ "MIT" ]

2

2016-11-02T15:07:13.000Z

2018-03-10T12:20:09.000Z

var/www/cgi-bin/ewmethodConf.py

DanielAndreasen/FASMA-web

4b87b2ac0be98817825fc94e5f287e5eb968d392

[ "MIT" ]

null

#!/home/daniel/Software/anaconda3/bin/python # Import modules for CGI handling import os import cgi, cgitb from ewDriver import ewdriver from emailSender import sendEmail def cgi2dict(form): """Convert the form from cgi.FieldStorage to a python dictionary""" params = {'initial': False, 'fixteff': False, 'fixlogg': False, 'fixfeh': False, 'fixvt': False, 'refine': False, 'outlier': False, 'teffrange': False, 'autofixvt': False} outlier = {'None': None, 'All once': 'allOnce', 'All iteratively': 'allIter', 'One iteratively': '1Iter'} for key in form.keys(): params[key] = form[key].value params['outlier'] = outlier[params['outlier']] # Translate to FASMA # Adjust the model atmosphere for FASMA if params['atmosphere'] == 'Kurucz': params['atmosphere'] = 'kurucz95' params['atmosphere'] = params['atmosphere'].lower() return params def ew(form, name=None): """Create the configuration file for running the ARES driver""" fout = 'linelist.moog ' fout += '%s ' % form['Teff'] fout += '%s ' % form['logg'] fout += '%s ' % form['feh'] fout += '%s ' % form['vt'] fout += 'model:%s' % form['atmosphere'] fout += ',iterations:%s' % form['iterations'] fout += ',EPcrit:%s' % form['EPslope'] fout += ',RWcrit:%s' % form['RWslope'] fout += ',Abdiffcrit:%s' % form['feDiff'] if form['teffrange']: fout += ',teffrange' if form['autofixvt']: fout += ',autofixvt' if form['refine']: fout += ',refine' if form['initial']: fout += ',tmcalc' if form['outlier']: fout += ',outlier:%s' % form['outlier'] fout += ',sigma:%s' % form['sigma'] if form['fixteff']: fout += ',teff' if form['fixlogg']: fout += ',logg' if form['fixfeh']: fout += ',feh' if form['fixvt']: fout += ',vt' with open('/tmp/StarMe_ew.cfg', 'w') as f: f.writelines(fout + '\n') parameters = ewdriver(starLines='/tmp/StarMe_ew.cfg', overwrite=True, name=name) return parameters def parameters2HTML(parameters): """Convert the parameters to HTML in a table""" data = {'teff': parameters[0], 'tefferr': parameters[1], 'logg': parameters[2], 'loggerr': parameters[3], 'feh': parameters[4], 'feherr': parameters[5], 'vt': parameters[6], 'vterr': parameters[7]} table = '''<table class="table table-hover table-bordered table-striped"> <thead> <tr> <th>Parameters</th> <th>Value</th> </tr> </thead> <tbody> <tr> <td>T<sub>eff</sub></td> <td>{teff}±{tefferr}</td> </tr> <tr> <td>logg</td> <td>{logg}±{loggerr}</td> </tr> <tr> <td>[Fe/H]</td> <td>{feh}±{feherr}</td> </tr> <tr> <td>ξ<sub>tur</sub></td> <td>{vt}±{vterr}</td> </tr> </tbody> </table>'''.format(**data) print table if __name__ == '__main__': # Enable debugging cgitb.enable() form = cgi.FieldStorage() # Run the minimization for a line list formDict = cgi2dict(form) parameters = ew(formDict, name=formDict['linelist']) sendEmail(to=formDict['email'], driver='EWmethod', data='/tmp/EWresults.dat') os.remove('/tmp/EWresults.dat') os.remove('/tmp/linelist.moog') os.remove('/tmp/StarMe_ew.cfg') os.remove('/tmp/batch.par') os.remove('/tmp/out.atm') os.remove('/tmp/result.out') os.remove('/tmp/summary.out') os.remove('/tmp/error_summary.out') # Show the finished html page print 'Content-type: text/html\n\n' with open('../html/finish.html', 'r') as lines: for line in lines: if 'Congratulations' in line: print line, print '<h2 class="text-secondary text-center">Results for %s</h2>' % formDict['linelist'].rpartition('.')[0] print '<br>' parameters2HTML(parameters) continue print line,

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null

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null

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1

0

1

24e30f0e72c5758202069450d33b77fffecaba08

5,964

py

Python

common/utils.py

quentin-xia/Maticv

76d599b68ef5bdab10e8dbc0c120657610933ad8

[ "MIT" ]

null

common/utils.py

quentin-xia/Maticv

76d599b68ef5bdab10e8dbc0c120657610933ad8

[ "MIT" ]

null

common/utils.py

quentin-xia/Maticv

76d599b68ef5bdab10e8dbc0c120657610933ad8

[ "MIT" ]

null

#/usr/bin/env python #-*- coding:utf-8 -*- import math,os import numpy as np from adb import Adb from screencap import MinicapStream import tempfile import hashlib import gl import platform if platform.system() is "Windows": try: import maticv.common.opencv.x32.cv2 as cv2 except: import maticv.common.opencv.x64.cv2 as cv2 else: import maticv.common.opencv.linux.cv2 as cv2 class Utils(Adb): def __init__(self): pass #super(Utils,self).__init__() #旋转图片函数 def rotate_about_center(self,src,angle=90,scale=1.0): w,h = src.shape[1::-1] rangle = np.deg2rad(angle) nw = (abs(np.sin(rangle)*h) + abs(np.cos(rangle)*w))*scale nh = (abs(np.cos(rangle)*h) + abs(np.sin(rangle)*w))*scale rot_mat = cv2.getRotationMatrix2D((nw*0.5, nh*0.5), angle, scale) rot_move = np.dot(rot_mat, np.array([(nw-w)*0.5, (nh-h)*0.5,0])) rot_mat[0,2] += rot_move[0] rot_mat[1,2] += rot_move[1] return cv2.warpAffine(src, rot_mat, (int(math.ceil(nw)), int(math.ceil(nh))), flags=cv2.INTER_LANCZOS4) #获取矩形坐标 def get_rectangle_point(self,strX,strY,endX,endY,rate): if strX > endX: x1,x2 = endX,strX else: x1,x2 = strX,endX if strY > endY: y1,y2 = endY,strY else: y1,y2 = strY,endY if rate: x1 = self.reduction_point(x1,rate) x2 = self.reduction_point(x2,rate) y1 = self.reduction_point(y1,rate) y2 = self.reduction_point(y2,rate) return x1,y1,x2,y2 #获取目标位置坐标 def get_circle_point(self,strX,strY,endX,endY,width=0,window=0): centerX = int((endX - strX) / 2) + strX centerY = int((endY - strY) / 2) + strY if window: centerX = centerY centerY = int((endX - strX) / 2) + (width - endX) return centerX,centerY #根据比例还原坐标 def reduction_point(self,point,rate): return int(round(point * (1 / float(rate)))) #根据比例缩小图片 def zoom(self,image,rate): return cv2.resize(image,None,fx=rate,fy=rate,interpolation=cv2.INTER_AREA) #生成文件名 def get_img_name(self,project): path = tempfile.mktemp(".png","%s_" % project,"projects/%s" % project) path = path.replace("\\","/") return path #截屏 def screenshot(self): #self.shell("screencap -p /sdcard/screenshot.png") #self.pull("/sdcard/screenshot.png",gl.TEMP_IMAGE_PATH) screencap = MinicapStream() screencap.ReadImageStream(gl.TEMP_IMAGE_PATH) #安装app def install_app_for_test(self,apk=None,pkg=None,clr=True): if apk: installed = self.is_app_installed(pkg) remoteApk = self._remote_apk_is_exists(apk) if installed and remoteApk: self._reset_app(pkg,clr) else: self._mk_remote_dir() remoteApk,md5 = self._get_remote_path(apk) #print remoteApk,md5 self._remove_temp_apks(md5) self._install_remote_with_retry(remoteApk,pkg,apk) else: self._reset_app(pkg,clr) #private #安装app def _install_remote_with_retry(self,remoteApk,pkg,localApk): installed = self.is_app_installed(pkg) if installed: self.uninstall_app(pkg) print "Install APK should to wait for a few minutes." self.push(localApk,remoteApk) self.install_remote(remoteApk) #删除app安装包 def _remove_temp_apks(self,md5): remoteTempPath = self._remote_temp_path() cmd = "ls %s*.apk" % remoteTempPath try: stdout = self.shell(cmd) if "No such file" in stdout: apks = [] else: apks = stdout.split("\n") except: if len(apks) < 1: #print "No apks to examine" return False noMd5Matched = True for path in apks: path = path.strip() if path != "": noMd5Matched = True if not md5 in path: noMd5Matched = False if noMd5Matched: filePath = remoteTempPath + path self.rimraf(filePath) #手机上创建临时目录 def _mk_remote_dir(self): path = self._remote_temp_path() self.mkdir(path) #重置app def _reset_app(self,pkg,clr): if clr: self.stop_and_clear(pkg) else: self.force_stop(pkg) #手机上是否存在安装包 def _remote_apk_is_exists(self,apk): remoteApk,appMd5Hash = self._get_remote_path(apk) cmd = "ls %s" % remoteApk stdout = self.shell(cmd) if not "No such file" in stdout: return stdout.strip() else: return False #获取apk路径和md5 def _get_remote_path(self,apk): appMd5 = self._get_md5(apk) remoteTempPath = self._remote_temp_path() remoteApk = "%s%s.apk" % (remoteTempPath,appMd5) return remoteApk,appMd5 #手机临时目录 def _remote_temp_path(self): return "/data/local/tmp/" #获取md5 def _get_md5(self,apk): appMd5Hash = self._get_app_md5(apk) appMd5 = "%s%s%s" % (appMd5Hash[0],appMd5Hash,appMd5Hash[-1]) return appMd5 #获取app md5 def _get_app_md5(self,apk): app = None ret = False strMd5 = "" try: app = open(apk,"rb") md5 = hashlib.md5() strRead = "" while True: strRead = app.read(8096) if not strRead: break md5.update(strRead) ret = True strMd5 = md5.hexdigest() except Exception,ex: #print ex ret = False finally: if app: app.close() return strMd5

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0

null

0

null

0

1

0

1

24ec8172b6e1c2fe9947b2843a4b87484a6b677e

6,510

py

Python

code/ner/model/net.py

gilbert98xD/mtextos2122

4811575134344c0bf255fa592c3b82efdb59d867

[ "CC-BY-4.0" ]

2

2022-03-07T13:47:36.000Z

2022-03-07T16:10:34.000Z

code/ner/model/net.py

gilbert98xD/mtextos2122

4811575134344c0bf255fa592c3b82efdb59d867

[ "CC-BY-4.0" ]

null

code/ner/model/net.py

gilbert98xD/mtextos2122

4811575134344c0bf255fa592c3b82efdb59d867

[ "CC-BY-4.0" ]

null

""" ## Minería de textos Universidad de Alicante, curso 2021-2022 Esta documentación forma parte de la práctica "[Lectura y documentación de un sistema de extracción de entidades](https://jaspock.github.io/mtextos2122/bloque2_practica.html)" y se basa en el código del curso [CS230](https://github.com/cs230-stanford/cs230-code-examples) de la Universidad de Stanford. **Autores de los comentarios:** Gilbert Lurduy & Enrique Moreno Este módulo define la red neuronal, la función de pérdida y la métrica de aciertos para la evaluación del modelo. Se hace uso de la libería torch. """ import numpy as np import torch import torch.nn as nn import torch.nn.functional as F class Net(nn.Module): """ ### Clase 'Net' Definición de la clase red neuronal """ def __init__(self, params): """ ### Constructor Se define una red neuronal recurrente para la obtención de entidades nombradas de un texto. Se compone de tres capas: capa lineal de embedding, capa LSTM y capa 'fully-connceted'. #### Parámetros: * 'params': parámetros con 'vocab_size', 'embedding_dim' y 'lstm_hidden_dim' #### Devuelve: * Tres capas para la red nuronal """ """ Llama al constructor de la clase 'Params', se construye su clase y a continuación la clase hija 'Net' """ super(Net, self).__init__() """ Se le da el tamaño del vocabulario y las dimensiones del embedding a la capa de embedding """ self.embedding = nn.Embedding(params.vocab_size, params.embedding_dim) """ Capa LSTM que recibe como parámetros las dimensiones del embedding y las dimensiones del estado 'hidden' que no tienen porqué coincidir batch_first = True -> hace que los tensores de entrada y salida se den de forma batch,seq,feature """ self.lstm = nn.LSTM(params.embedding_dim, params.lstm_hidden_dim, batch_first=True) """ Capa 'fully-connected', es la capa que da el output final, me dice la probabilidad de que la palabra sea una ner (named entitty recognition) tag de cierto tipo (nombre, tiempo, lugar...) """ self.fc = nn.Linear(params.lstm_hidden_dim, params.number_of_tags) """ En resumen la primera capa, dada una palabra, me da su embedding, en la segunda ese embedding se lleva a otros espacio de embeddings que no tiene porque tener la misma dimension, y la tercera capa se lleva este nuevo embedding a otro espacio, el número de etiqueta """ def forward(self, s): """ ### Función 'forward' A partir de un batch input obtiene las probablidades logits de los tokens #### Parámetros: * 's': argumento con un 'lote' de oraciones organizados en filas y de dimensión tamaño del batch x longitud frase más larga. A las frases más cortas se le aplica padding. #### Devuelve: * probabilidades logits de los tokens """ """ aplicamos una capa de embedding las dimensiones resultantes son(x,dimension de los embeddings) """ s = self.embedding(s) """ Aplicación de la LSTM """ s, _ = self.lstm(s) """ Se hace una copia del tensor en memoria """ s = s.contiguous() """ Cambiamos la forma de la variable s (es una matriz) de tal manera que cada fila tiene un token. Con el -1 le indicamos que calcule la dimensión automáticamente para obtener dos dimensiones. Y el s.shape[2] es lstm_hidden_dim. Se le pone el [2] porque el [0] es el tamaño de batch y el [1] es el máximo de la secuencia """ s = s.view(-1, s.shape[2]) """ Última capa 'fully-connected'proyecta el nuevo embedding hacia un espacio con el número de etqiuetas """ s = self.fc(s) """ No obstante, aun no tenemos probabilidades hay que aplicar una softmax. Por una mayor eficiencia se aplica un log(softmax) por lo que las probabilidades de 0 a 1 pasan a ser negativas. Cuanto más cerca estemos del cero más alta es la probabilidad. """ return F.log_softmax(s, dim=1) def loss_fn(outputs, labels): """ ### Función 'loss_fn' Método función de pérdida #### Parámetros: * 'outputs': resultados del modelo * 'labels': las etiqeutas para evaluar la pérdida #### Devuelve: * La entro`pía cruzada de todos los tokens, menos los de padding """ """ aplana la variable """ labels = labels.view(-1) """ Los inputs de una red neuronal deben tener la misma forma y tamaño, para que esto sea así al pasar oraciones se hace 'padding', que añade ceros a las secuencias o corta oraciones largas. Estos token tienen -1 como etiqueta, por lo que podemos usar una máscara que los excluya del cálculo de la función de pérdida. """ mask = (labels >= 0).float() """ Conversión de las etiquetas en positivas (por los padding tokens) """ labels = labels % outputs.shape[1] num_tokens = int(torch.sum(mask)) return -torch.sum(outputs[range(outputs.shape[0]), labels]*mask)/num_tokens """ Se devuelve la entropía cruzada de todos los tokens, menos los de padding, mediante el uso de la variable 'mask' que hace de máscara, la cual hemos definido antes """ def accuracy(outputs, labels): """ ### Función 'accuracy' Cálculo de la precisión a partir de las etiquetas y las salidas teniendo en cuenta los términos de padding #### Parámetros: * 'outputs': resultados del modelo * 'labels': las etiqeutas para evaluar la pérdida #### Devuelve: * Tasa de acierto """ """ Aplanamiento de la variable """ labels = labels.ravel() """ Máscara similar al anterior método 'loss_fn' """ mask = (labels >= 0) """ Índices con los mayores valores, es decir, obtención de las clases más probables de cada token """ outputs = np.argmax(outputs, axis=1) return np.sum(outputs == labels)/float(np.sum(mask)) metrics = { 'accuracy': accuracy, }

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null

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null

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24f4d7e1005a990eff108660ee3c6c03d85c23a0

439

py

Python

neosis_telephone_directory/telephone_directory/migrations/0003_contacts_profile_pic.py

borkarfaiz/neosis_telephone_directory

d4a0f7197ac15f4993488e21459a744c370fde0f

[ "MIT" ]

null

neosis_telephone_directory/telephone_directory/migrations/0003_contacts_profile_pic.py

borkarfaiz/neosis_telephone_directory

d4a0f7197ac15f4993488e21459a744c370fde0f

[ "MIT" ]

null

neosis_telephone_directory/telephone_directory/migrations/0003_contacts_profile_pic.py

borkarfaiz/neosis_telephone_directory

d4a0f7197ac15f4993488e21459a744c370fde0f

[ "MIT" ]

null

# Generated by Django 3.0.11 on 2020-12-09 06:05 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('telephone_directory', '0002_auto_20201208_1801'), ] operations = [ migrations.AddField( model_name='contacts', name='profile_pic', field=models.ImageField(blank=True, null=True, upload_to='profile_pic/'), ), ]

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1

24fce3d07a8f2fe74c6a87ee177cf440ad8e2e09

1,704

py

Python

backend/pah_fm/urls.py

w1stler/pah-fm

e69600ba602715ae0b61dfa0bead934a0ed7f36f

[ "MIT" ]

8

2019-08-09T11:06:16.000Z

2021-10-05T14:56:31.000Z

backend/pah_fm/urls.py

w1stler/pah-fm

e69600ba602715ae0b61dfa0bead934a0ed7f36f

[ "MIT" ]

382

2018-10-17T19:05:30.000Z

2022-02-10T07:09:45.000Z

backend/pah_fm/urls.py

w1stler/pah-fm

e69600ba602715ae0b61dfa0bead934a0ed7f36f

[ "MIT" ]

45

2018-10-17T17:04:04.000Z

2021-10-05T14:30:35.000Z

"""pah_fm URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.1/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 django.conf import settings from django.conf.urls.static import static from rest_framework.documentation import include_docs_urls from pah_fm.views import CustomObtainJSONWebToken from fleet_management.api import ( CarListView, CurrentUserRetrieveView, DriveView, PassengerListView, ProjectView, RefuelView, ) urlpatterns = [ path("admin/", admin.site.urls), path("api/docs/", include_docs_urls(title="PAH-FM", public=False)), path("api/api-token-auth/", CustomObtainJSONWebToken.as_view(), name="jwt"), path("api/users/me", CurrentUserRetrieveView.as_view(), name="me"), path("api/passengers", PassengerListView.as_view(), name="passengers"), path("api/cars", CarListView.as_view(), name="cars"), path("api/drives", DriveView.as_view(), name="drives"), path("api/projects", ProjectView.as_view(), name="projects"), path("api/refuels", RefuelView.as_view(), name="refuels"), ] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT)

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0

0.28

0

null

0

null

0

1

0

1

24fd6c41fe4fbfb1df5a007cfef9baca40a53801

172

py

Python

deciphon_cli/console/env.py

EBI-Metagenomics/deciphon-cli

aa090c886db1f4dacc6bc88b46b6ebcecb79eaab

[ "MIT" ]

null

deciphon_cli/console/env.py

EBI-Metagenomics/deciphon-cli

aa090c886db1f4dacc6bc88b46b6ebcecb79eaab

[ "MIT" ]

null

deciphon_cli/console/env.py

EBI-Metagenomics/deciphon-cli

aa090c886db1f4dacc6bc88b46b6ebcecb79eaab

[ "MIT" ]

null

import typer import deciphon_cli.data as data __all__ = ["app"] app = typer.Typer() @app.command() def default(): typer.echo(data.env_example_content(), nl=False)

13.230769

52

0.703488

25

172

4.56

0.68

0

0.151163

172

12

53

14.333333

0.780822

0

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0

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0

0.428571

0

1

0

null

0

null

0

1

24fd822b165bd2a82075658d81849e6e2daa014f

4,158

py

Python

wftests/ci/pylint_checker.py

YutakaMizugaki/warriorframework

685761cf044182ec88ce86a942d4be1e150a1256

[ "Apache-2.0" ]

24

2017-06-06T15:48:08.000Z

2021-03-17T07:52:52.000Z

wftests/ci/pylint_checker.py

YutakaMizugaki/warriorframework

685761cf044182ec88ce86a942d4be1e150a1256

[ "Apache-2.0" ]

272

2017-05-19T20:39:12.000Z

2021-12-13T19:34:51.000Z

wftests/ci/pylint_checker.py

pavithra-gowda/warrior

19b153310552b986b86b5470fcfea9547a74c3a9

[ "Apache-2.0" ]

37

2017-05-17T21:24:37.000Z

2021-07-24T18:09:22.000Z

""" Get a list of file and run pylint on each of the files on pull request source branch and target branch """ import sys import subprocess # from pylint import epylint as lint def process_file_list(input_file, rc_file): """ Generate a list of files that need to be pylint """ filelist = open(input_file).readlines() filelist = [x.strip() for x in filelist] pylintrc = open(rc_file).readlines() ignore = [x for x in pylintrc if x.startswith("ignore=")] if ignore: ignore = ignore[0][7:].replace('\n', '').split(',') result = [x for x in filelist if all([y not in x for y in ignore])] if result: print "The following files will be tested with Pylint:\n", "\n".join(result), "\n" else: print "No file requires pylint check, exiting" exit(0) return result def pylint(file_list): """ Pylint files from file list """ file_score = {} for fi in file_list: print "linting", fi try: output = subprocess.check_output('pylint --rcfile=.pylintrc {}'.format(fi), shell=True) except subprocess.CalledProcessError as e: output = e.output score = output.split('\n') score = [x.replace("Your code has been rated at ", "") for x in score if x.startswith("Your code has been")] if score: # code has been rated file_score[fi] = [score[0], output] else: print fi, "doesn't get a Pylint score on this branch" return file_score def report(branch_file_score): """ print out pylint result for each file """ print "\n\n\n!---------- Detail score for branch {} ----------!\n".format(sys.argv[4]) for k, v in branch_file_score.items(): print k, "\n", v[1] print "\n\n\n!---------- Summary score for branch {} ----------!\n".format(sys.argv[4]) for k, v in branch_file_score.items(): print k, v[0] def judge(branch_file_score): """ Check the score and difference for each file """ status = True for k, v in branch_file_score.items(): # print k, v[0] score = v[0].split("/")[0] if float(score) < 5: status = False print k, "failed with a score lower than 5" if "previous" in v[0]: improvement = float(v[0].split(",")[1][:-1]) if improvement < -0.1: status = False print k, "failed with a decreasing score" if float(score) >= 5 and "previous" in v[0] and improvement >= -0.1: print k, "pass" return status def custom_rules(file_list): """ Invoke custom rules checker on each file """ status = True for fi in file_list: try: output = subprocess.check_output('python wftests/ci/custom_rules.py {}'.format(fi), shell=True) except subprocess.CalledProcessError as e: output = e.output status = False print output return status def main(): """ main function to process logic """ if len(sys.argv) > 4: file_list = process_file_list(sys.argv[1], sys.argv[2]) print "target branch:", sys.argv[3], "\nsource branch:", sys.argv[4] subprocess.check_output("git checkout {}".format(sys.argv[3]), shell=True) print "Running pylint on", sys.argv[3] pylint(file_list) print "\n" subprocess.check_output("git checkout {}".format(sys.argv[4]), shell=True) print "\nRunning pylint on", sys.argv[4] branch_file_score = pylint(file_list) report(branch_file_score) print "\n\n\n!---------- Judging score for branch {} ----------!\n".format(sys.argv[4]) status = judge(branch_file_score) print "\n\n\n!---------- Custom Rules Checker for branch {} ----------!\n".format(sys.argv[4]) status &= custom_rules(file_list) if status: exit(0) else: exit(1) else: print "Missing arguments, require filenames, pylintrc_file, target_branch, source_branch" if __name__ == "__main__": main()

31.5

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0.575998

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4,158

4.145133

0.238938

0.038856

0.051238

0.029889

0.30316

0.235696

0.192143

0.125961

0

0.012097

0.284271

4,158

131

117

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null

0.218391

0

null

0

null

0

1

0

1

24ff72339ada2faf39d38cc9fe1209fcafd6136d

3,269

py

Python

draw_macros/drawEnvelope.py

nkarast/WWTheoryUncertainties

d2d3e5cab4cd72256cdc572fee05acfbe3372f5a

[ "MIT" ]

null

draw_macros/drawEnvelope.py

nkarast/WWTheoryUncertainties

d2d3e5cab4cd72256cdc572fee05acfbe3372f5a

[ "MIT" ]

null

draw_macros/drawEnvelope.py

nkarast/WWTheoryUncertainties

d2d3e5cab4cd72256cdc572fee05acfbe3372f5a

[ "MIT" ]

null

import ROOT as rt import glob debug = 1 def setstyle(): rt.gStyle.SetOptStat(0); rt.gStyle.SetFillColor(10); rt.gStyle.SetFrameFillColor(10); rt.gStyle.SetCanvasColor(10); rt.gStyle.SetPadColor(10); rt.gStyle.SetTitleFillColor(0); rt.gStyle.SetStatColor(10); rt.gStyle.SetCanvasBorderMode(0); rt.gStyle.SetFrameBorderMode(0); rt.gStyle.SetPadBorderMode(0); rt.gStyle.SetDrawBorder(0); rt.gStyle.SetTitleBorderSize(0); rt.gStyle.SetFuncWidth(2); rt.gStyle.SetHistLineWidth(2); rt.gStyle.SetFuncColor(2); rt.gStyle.SetPadTopMargin(0.05) rt.gStyle.SetPadBottomMargin(0.16); rt.gStyle.SetPadLeftMargin(0.16); rt.gStyle.SetPadRightMargin(0.05); rt.gStyle.SetPadTickX(1); rt.gStyle.SetPadTickY(1); rt.gStyle.SetFrameLineWidth(1); rt.gStyle.SetLineWidth(1); def HSG3HistStyle(histo): histo.SetTitle(""); histo.SetLineWidth(3); histo.SetTitleSize(0.07,"x"); histo.SetTitleSize(0.07,"y"); histo.SetNdivisions(505,"x"); histo.SetNdivisions(505,"y"); histo.SetLabelSize(0.07,"x"); histo.SetLabelSize(0.07,"y"); histo.SetTitleOffset(1.,"x"); histo.SetTitleOffset(1.,"y"); for filename in glob.glob("/Users/nkarast/Documents/Higgs/Work/CPMixing/TheoryNtuples/finalVersionOfCode/UEPS/*.dat"): setstyle() file = open(filename, 'read') print 'Working with ', filename # bin_contents = bincontents[] # nbins = len(bincontents) bincontents = [] nominalContent = [] for line in file.readlines(): if "#" in line : continue bincontents.append(float(line.split()[0])) nominalContent.append(1.) file.close() hist_nom = rt.TH1F("Nominal","Nominal", len(bincontents), 0, len(bincontents)) hist_one = rt.TH1F("Ones","Ones", len(bincontents), 0, len(bincontents)) for bin in range(len(bincontents)): hist_nom.SetBinContent(bin+1, 1.) hist_one.SetBinContent(bin+1, 1.) if bincontents[bin]==1 : bincontents[bin]=0. hist_nom.SetBinError(bin+1, bincontents[bin]) canvas = rt.TCanvas("WW","WW", 800, 600) canvas.cd() HSG3HistStyle(hist_nom) HSG3HistStyle(hist_nom) hist_nom.SetTitle("") rt.gStyle.SetOptStat(0) hist_nom.SetMinimum(0) hist_nom.GetXaxis().SetTitle("BDT Output") hist_nom.GetYaxis().SetTitle("Variation") hist_nom.SetMaximum(2.5) hist_nom.SetFillColor(46) hist_nom.SetFillStyle(3001) hist_nom.SetLineColor(46) hist_nom.Draw("E2") hist_one.SetLineColor(rt.kBlack) hist_one.SetLineWidth(2) hist_one.Draw("same") leg = rt.TLegend(0.60, 0.70, 0.90, 0.90) leg.SetBorderSize(0) leg.SetTextFont(42) leg.SetTextSize(0.045) leg.SetFillColor(0) leg.SetNColumns(1) leg.AddEntry(hist_one, "Nominal", "l") leg.AddEntry(hist_nom, "WW UE/PS", "f") leg.Draw("same") lumi = rt.TLatex(); lumi.SetNDC(); lumi.SetTextFont(42); lumi.SetTextSize(0.045); lumi.SetTextColor(1); lumi.DrawLatex(0.22, 0.8, "Simulation #sqrt{s} = 8 TeV") lumi.DrawLatex(0.2, 0.70, "#sqrt{s} = 8 TeV, #int L dt = 20.3 fb^{-1}") savename = filename[:-4]+"_wwUEPS.pdf" canvas.SaveAs(savename) print bincontents

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3,269

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0.186296

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0.083696

0.02738

0

null

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0.021505

null

0.021505

0

null

0

null

0

1

0

1

7002ef7c1c1b47d0e90a43b630eeacf894b6e9ba

3,071

py

Python

code/nearest_neighbor_classify.py

lionelmessi6410/Scene-recognition-with-bag-of-words

1bbc11cd060f792b54b86baa8a5f7483133b9f2c

[ "MIT" ]

22

2019-11-27T04:14:07.000Z

2022-01-10T08:16:58.000Z

code/nearest_neighbor_classify.py

lionelmessi6410/Scene-recognition-with-bag-of-words

1bbc11cd060f792b54b86baa8a5f7483133b9f2c

[ "MIT" ]

null

code/nearest_neighbor_classify.py

lionelmessi6410/Scene-recognition-with-bag-of-words

1bbc11cd060f792b54b86baa8a5f7483133b9f2c

[ "MIT" ]

10

2019-12-13T07:31:09.000Z

2021-12-18T18:21:20.000Z

from __future__ import print_function import numpy as np import scipy.spatial.distance as distance def nearest_neighbor_classify(train_image_feats, train_labels, test_image_feats): ########################################################################### # TODO: # # This function will predict the category for every test image by finding # # the training image with most similar features. Instead of 1 nearest # # neighbor, you can vote based on k nearest neighbors which will increase # # performance (although you need to pick a reasonable value for k). # ########################################################################### ########################################################################### # NOTE: Some useful functions # # distance.cdist : # # This function will calculate the distance between two list of features# # e.g. distance.cdist(? ?) # ########################################################################### ''' Input : train_image_feats : image_feats is an (N, d) matrix, where d is the dimensionality of the feature representation. train_labels : image_feats is a list of string, each string indicate the ground truth category for each training image. test_image_feats : image_feats is an (M, d) matrix, where d is the dimensionality of the feature representation. Output : test_predicts : a list(M) of string, each string indicate the predict category for each testing image. ''' CATEGORIES = ['Kitchen', 'Store', 'Bedroom', 'LivingRoom', 'Office', 'Industrial', 'Suburb', 'InsideCity', 'TallBuilding', 'Street', 'Highway', 'OpenCountry', 'Coast', 'Mountain', 'Forest'] K = 1 N = train_image_feats.shape[0] M = test_image_feats.shape[0] d = train_image_feats.shape[1] # d are same in both train and test dist = distance.cdist(test_image_feats, train_image_feats, metric='euclidean') #dist = distance.cdist(train_image_feats, test_image_feats, metric='euclidean') test_predicts = [] for each in dist: label = [] idx = np.argsort(each) for i in range(K): label.append(train_labels[idx[i]]) #print(label) amount = 0 for item in CATEGORIES: if label.count(item) > amount: label_final = item test_predicts.append(label_final) ############################################################################# # END OF YOUR CODE # ############################################################################# return test_predicts

43.871429

83

0.471508

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3,071

4.885417

0.4375

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0.063966

0.028429

0.157783

0.082445

0

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0.320091

3,071

70

84

43.871429

0.670977

0.451319

0

0.112108

0

0.014286

0

1

0.041667

false

0

0.125

0

0.208333

0.041667

0

null

0

null

0

1

0

1

700d715f42f1fc60d05299634ce5489d3b1d246c

1,178

py

Python

programs/pygame/dwarf_fight/utils.py

xzpeter/pylibs

d4aa451e5ecb1cfb160a7e39846f9ae148e5c3d6

[ "BSD-3-Clause" ]

null

programs/pygame/dwarf_fight/utils.py

xzpeter/pylibs

d4aa451e5ecb1cfb160a7e39846f9ae148e5c3d6

[ "BSD-3-Clause" ]

null

programs/pygame/dwarf_fight/utils.py

xzpeter/pylibs

d4aa451e5ecb1cfb160a7e39846f9ae148e5c3d6

[ "BSD-3-Clause" ]

null

import time import math import random # Define some colors black = ( 0, 0, 0) white = ( 255, 255, 255) green = ( 0, 255, 0) blue = ( 0, 0, 255) red = ( 255, 0, 0) yellow = ( 255, 255, 0) def debug (msg): print "%s: %s" % (time.strftime("%D %H:%m:%S"), msg) def warn (msg): debug("WARN: " + msg) def err (msg): debug("ERROR: " + msg) raise Exception(msg) def point_in_rect (point, rect): x = point[0] y = point[1] if x >= rect.left and x <= rect.right and \ y >= rect.top and y <= rect.bottom: return True return False def rect_collide (rect1, rect2): points = [rect1.topleft, rect1.topright, rect1.bottomleft, rect1.bottomright] for point in points: if point_in_rect(point, rect2): return True return False def vector_norm (vector): x = vector[0] y = vector[1] len = math.sqrt(x**2 + y**2) return [x/len, y/len] def vector_mul (vector, n): return [vector[0]*n, vector[1]*n] def random_vector (norm): x = random.random() * 2 - 1 y = random.random() * 2 - 1 return vector_mul(vector_norm([x,y]), norm)

22.653846

56

0.556876

177

1,178

3.649718

0.338983

0.012384

0.034056

0.049536

0.074303

0

0.063702

0.293718

1,178

51

57

23.098039

0.71274

0.01528

0

0.097561

0

0.025907

0

null

0

0.073171

null

0.02439

0

null

0

null

0

1

0

1

70155480f5510345df2cb67b5bd92fa6a2bec8a6

4,564

py

Python

yearn/vaults_v2.py

nymmrx/yearn-exporter

64b87128b76cd637965abb56e421bfd67238e2a7

[ "MIT" ]

null

yearn/vaults_v2.py

nymmrx/yearn-exporter

64b87128b76cd637965abb56e421bfd67238e2a7

[ "MIT" ]

null

yearn/vaults_v2.py

nymmrx/yearn-exporter

64b87128b76cd637965abb56e421bfd67238e2a7

[ "MIT" ]

1

2021-06-04T19:07:16.000Z

from dataclasses import dataclass from typing import List from brownie import interface, web3 from brownie.network.contract import InterfaceContainer from packaging import version from yearn import strategies from yearn import uniswap from yearn.mutlicall import fetch_multicall VAULTS_EVENT_TOPIC = '0xce089905ba4a4d622553bcb5646fd23e895c256f0376eee04e99e61cec1dc7e8' EXPERIMENTAL_VAULTS_EVENT_TOPIC = '0x57a9cdc2a05e05f66e76769bdbe88e21ec45d9ee0f97d4cb60395d4c75dcbcda' ZERO_ADDRESS = "0x0000000000000000000000000000000000000000" MIN_VERSION = version.parse("0.2.0") VAULT_VIEWS = [ "decimals", "totalAssets", "maxAvailableShares", "pricePerShare", "debtOutstanding", "creditAvailable", "expectedReturn", "totalSupply", "emergencyShutdown", "depositLimit", "debtRatio", "totalDebt", "lastReport", "managementFee", "performanceFee", ] VAULT_VIEWS_SCALED = [ "totalAssets", "maxAvailableShares", "pricePerShare", "debtOutstanding", "creditAvailable", "expectedReturn", "totalSupply", "depositLimit", "totalDebt", ] @dataclass class VaultV2: name: str vault: InterfaceContainer strategies: List[strategies.Strategy] def __post_init__(self): api_version = version.parse(self.vault.apiVersion()) assert api_version >= MIN_VERSION, f"{self.name} unsupported vault api version {api_version}" def describe(self): scale = 10 ** self.vault.decimals() strats = [str(strat.strategy) for strat in self.strategies] strats.extend([ZERO_ADDRESS] * (40 - len(strats))) try: results = fetch_multicall(*[[self.vault, view] for view in VAULT_VIEWS]) info = dict(zip(VAULT_VIEWS, results)) for name in VAULT_VIEWS_SCALED: info[name] /= scale info['strategies'] = {} except ValueError as e: info = {"strategies": {}} for strat in self.strategies: info["strategies"][strat.name] = strat.describe() try: info["token price"] = uniswap.token_price(self.vault.token()) except ValueError: info["token price"] = 0 if "totalAssets" in info: info["tvl"] = info["token price"] * info["totalAssets"] return info vaults = { "DAI 0.3.0": "0x19D3364A399d251E894aC732651be8B0E4e85001", "USDC 0.3.0": "0x5f18C75AbDAe578b483E5F43f12a39cF75b973a9", "HEGIC 0.3.0": "0xe11ba472F74869176652C35D30dB89854b5ae84D", "curve.fi/steth 0.3.0": "0xdCD90C7f6324cfa40d7169ef80b12031770B4325", "WBTC 0.3.1": "0xcB550A6D4C8e3517A939BC79d0c7093eb7cF56B5", "WETH 0.3.2": "0xa9fE4601811213c340e850ea305481afF02f5b28", "curve.fi/seth 0.3.2": "0x986b4AFF588a109c09B50A03f42E4110E29D353F", } experimental_vaults = { "sUSD Idle 0.3.1": "0x3466c90017F82DDA939B01E8DBd9b0f97AEF8DfC", # https://etherscan.io/address/0xA04fE40eD8a8a8d657E41276ec9e9Ee877675e34#code "WETH Gen Lender 0.3.1": "0x5f18C75AbDAe578b483E5F43f12a39cF75b973a9", # https://etherscan.io/address/0xac5DA2Ca938A7328dE563D7d7209370e24BFd21e#code # "Egyptian God sETH/ETH 0.3.0": "0x0e880118C29F095143dDA28e64d95333A9e75A47", # https://etherscan.io/address/0x3B1a1AE6052ccD643a250fa843c1fB20F9246E1a#code "WETH Iron Lender 0.3.0": "0xED0244B688cF059f32f45E38A6ac6E479D6755f6", # https://etherscan.io/address/0xa35A4972D74d4B3e4486163066E5fFed6d62b213#code "yvSushi YFI-ETH 0.2.2": "0x27Eb83254D900AB4F9b15d5652d913963FeC35e3", # https://etherscan.io/address/0x3213a6389f3f4c287925a47A6D44fe1148FA0C0d#code "DEV Hugger 0.2.2": "0xFeD651936Af7e98F7F2A93c03B1E28a2DA7dfaD4", # https://etherscan.io/address/0x2E949057Ce561BAA9d494895235ACCe310a73FDB#code # https://etherscan.io/address/0x38a97cB34FCE4FAc87D1F7f8639e3341978613b6#code "USDc Idle 0.2.2": "0x33bd0f9618cf38fea8f7f01e1514ab63b9bde64b", # https://etherscan.io/address/0xc29CBe79F1a35a6AA00Df70851E36B14316Ab990#code "Mushroom Worker 0.3.0": "0x0e8A7717A4FD7694682E7005957dD5d7598bF14A" # https://etherscan.io/address/0xE5dc99Cbf841A6721781E592214674A87a1A70BC#code # Left out Lido St. Ether Vault, and ApeTrump Vault } def get_vaults(): # TODO: read from registry return [VaultV2(name=name, vault=interface.Vault(vault), strategies=[]) for name, vault in vaults.items()] def get_experimental_vaults(): return [ VaultV2(name=name, vault=interface.Vault(vault), strategies=[]) for name, vault in experimental_vaults.items() ]

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0.171122

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0.204301

0

null

0

1

0

null

0

1

702de2efe4664687f5a4403142b920e4ac69ee5e

22,245

py

Python

exactdiag_4site2particles/fh.py

PedroMDuarte/thesis-hubbard

c63df1283086267bd3014e084b36408cbdcde5eb

[ "MIT" ]

2

2019-06-08T14:55:24.000Z

2021-01-18T13:52:17.000Z

exactdiag_4site2particles/fh.py

PedroMDuarte/thesis-hubbard

c63df1283086267bd3014e084b36408cbdcde5eb

[ "MIT" ]

null

exactdiag_4site2particles/fh.py

PedroMDuarte/thesis-hubbard

c63df1283086267bd3014e084b36408cbdcde5eb

[ "MIT" ]

2

2020-07-08T05:50:34.000Z

2022-01-17T09:57:31.000Z

import numpy as np class lattice(): """Contains functions to help out calculate matrices in the Fermi-Hubbard model""" def __init__(self, xs,ys,zs): '''The dimensions of the grid are given to initialize the lattice. Recommended max of 4 sites, otherwise it can take too long to complete.''' # x, y, and z have the shape of the grid, and contain the # respective (x,y,z) coordinates of the latttic sites: self.x, self.y, self.z = np.mgrid[ 0:xs, 0:ys, 0:zs] self.xs = xs self.ys = ys self.zs = zs def show(self,spins): ''' This prints a particular state to the terminal''' for i in np.ravel(spins): print "%d "%i, print def state(self,m): ''' # Each site can have 4 possible configurations, we have # labeled them as follows: # # 0 = vacuum # 1 = spin up # 2 = spin down # 3 = doubly occupied # # All possible states are numbered with an index m. This function # constructs the m_th state in the lattice. The spin configuration of # the m_th state is stored in the 'spins' matrix and returned. # # Since there are 4 possible states per site (see above) the # convention is that m be represented in base-4 (quaternary) and # each digit can be assigned using the 0,1,2,3 convention above. # ''' spins = np.zeros_like( self.x) i = 0 end = False while m > 0: if i>=spins.size: end =True break spins.flat[i] = (m%4) m = m /4 i = i +1 if end: return None else: return spins def sector(self): # Finds the spin sector for the current state s = 0 for i in self.spins.flat: if i == 0 : s = s+0 elif i == 1 : s = s+1 elif i == 2 : s = s-1 elif i == 3 : s = s+0 return s def filling(self): # Finds the filling for the current state f = 0 for i in self.spins.flat: if i == 0 : f = f+0 elif i == 1 : f = f+1 elif i == 2 : f = f+1 elif i == 3 : f = f+2 return f def defstates(self): '''This function defines the half filling states of the Fermi-Hubbard model in a 3D lattice. It creates a dictionary where the keys correspond to the different spin sectors available, and the values are a list of the states in the spin sector. For a balanced spin mixture one only needs to consider the spin=0 sector. ''' end = False n = 0 self.states = {} while n < 300: self.spins = self.state(n) # ATTENTION: in this code we have changed to HALF-FILLING to # QUARTER-FILLING, in order to explore the 2x2 lattice with only # 2 particles. We use /2 in the filling check: if self.spins is not None and self.filling() == self.spins.size/2: sec = self.sector() if sec in self.states.keys(): self.states[ sec].append(self.spins) else: self.states[ sec]=[self.spins] n = n+1 for k in self.states.keys(): print "Sector %d, %d states:"%(k,len(self.states[k])) for spins in self.states[k]: self.show(spins) def nearest(self): '''This function makes a list of the nearest neighbor pairs in the lattice''' print "\nNearest neighbors:" # First we create a flat list of all the lattice sites. # each element in the list is (x[i], y[i], z[i], i) sites = [] for i in range(self.x.size): sites.append( (self.x.flat[i], self.y.flat[i], self.z.flat[i], i)) # We do a nested iteration over the lists and create a list # of pairs which are nearest neighbors. neighbors = [] for i,s1 in enumerate(sites): for j,s2 in enumerate(sites): if j > i: d2 = (s1[0]-s2[0])**2 + (s1[1]-s2[1])**2 + (s1[2]-s2[2])**2 print s1,"--",s2," = ",d2 if d2 == 1: neighbors.append( (s1[3],s2[3])) print print "Final neighbor list: " print neighbors self.neighbors = neighbors def kinetic0(self): r'''This function calculates the kinetic energy matrix in the spin=0 sector. The matrix is constructed by iterating over the nearest neighbors. As a reminder, the kinertic enrgy is given by K = -t \sum_{\langle i j \rangle} a_{i\sigma}^{\dagger} a_{j\sigma} So in order to find it's matrix elements we need to apply first an annihilation operator and then a creation operator. The tricky part is keeping track of the signs. ''' print msize = len(self.states[0]) kinetic = np.zeros((msize,msize)) for i,s1 in enumerate(self.states[0]): for j,s2 in enumerate(self.states[0]): # We will calculate the matrix element # < s1 | K | s2 > # This matrix element involves a sum over nearest neighbors # and sum over spins, so we go ahead and iterate: t = 0. for n in self.neighbors: PRINT = False for spin in ['up','down']: if PRINT: print print "<", np.ravel(s1)," | K | ", np.ravel(s2),">" # Annihilates 'spin' at site n[0] signA, stateA = annihilate( n[0], spin, s2) # Create 'spin' at site n[1] signC, stateC = create(n[1], spin, stateA) if PRINT: print "annihilate %d,%5s"%(n[0],spin)," -->",stateA print " create %d,%5s"%(n[1],spin)," -->",stateC # If K|s2> has a projecton on <s1| then we add it to # t if np.array_equal(stateC,np.ravel(s1)): if PRINT: print " tmatrix --> % d" % (signA*signC ) t+= signA*signC r''' Notice that sometimes people write the kinetic energy as K = -t \sum_{\langle i j \rangle} a_{i\sigma}^{\dagger} a_{j\sigma} + c.c. where the letters c.c. refer to the complex conjugate. If they do that, then it means that the sum over nearest neighbors must only occur for one ordering of the neighbor pair, for instance just 1-2 whereas the sum over both orderings includes 1-2 and 2-1. Here we just run the sum over both orderings. ''' # We repeat the process with the different neighbor # ordering: signA, stateA = annihilate( n[1], spin, s2) signC, stateC = create(n[0], spin, stateA) if PRINT: print "annihilate %d,%5s"%(n[1],spin)," -->",stateA print " create %d,%5s"%(n[0],spin)," -->",stateC if np.array_equal(stateC,np.ravel(s1)): if PRINT: print " tmatrix --> % d" % (signA*signC ) t+= signA*signC kinetic[i,j] = t print "\nKinetic energy matrix: ",kinetic.shape print kinetic self.kinetic = kinetic def interaction0(self): '''This fuction calculates the interaction energy matrix in the spin=0 sector''' print msize = len(self.states[0]) inter = np.zeros((msize,msize)) # The basis we have chose is of number states, # so the interaction energy is diagonal for i,s1 in enumerate(self.states[0]): for site in s1.flat: if site == 3: # 3=double occupancy inter[i,i] = inter[i,i] + 1 print "\nInteraction energy matrix:i ",inter.shape print inter self.inter = inter def diagonal0(self): '''This fuction calculates a diagonal matrix in the spin=0 sector''' print msize = len(self.states[0]) diag = np.zeros((msize,msize)) # The basis we have chose is of number states, # so the interaction energy is diagonal for i,s1 in enumerate(self.states[0]): for site in s1.flat: diag[i,i] = 1.0 self.diag = diag def annihilate( i, spin, state): # The order for the creation operators is lower site number # to the left, and then spin-up to the left s = np.ravel(state) out = np.copy(s) samespin = {'up':1, 'down':2} flipspin = {'up':2, 'down':1} ncommute = 0. for j in range(i): if s[j] == 3: ncommute +=2 if s[j] == 1 or s[j] == 2: ncommute+=1 sign = (-1)**ncommute if s[i] == 0: out = np.zeros_like(s) if s[i] == flipspin[spin]: out = np.zeros_like(s) if s[i] == 3: out[i] = flipspin[spin] if spin == 'up': sign*= 1 if spin == 'down': sign*=-1 if s[i] == samespin[spin]: out[i] = 0 #print s, ", annihilate %d,%5s"%(i,spin)," --> %+d"%sign, out return sign, out def create( i, spin, state): # The order for the creation operators is lower site number # to the left, and then spin-up to the left s = np.ravel(state) out = np.copy(s) samespin = {'up':1, 'down':2} flipspin = {'up':2, 'down':1} ncommute = 0. for j in range(i): if s[j] == 3: ncommute +=2 if s[j] == 1 or s[j] == 2: ncommute+=1 sign = (-1)**ncommute if s[i] == 0: out[i] = samespin[spin] if s[i] == flipspin[spin]: out[i] = 3 if spin == 'up': sign*=1 if spin == 'down': sign*=-1 if s[i] == 3: out = np.zeros_like(s) if s[i] == samespin[spin]: out = np.zeros_like(s) #print s, ", create %d,%5s"%(i,spin)," --> %+d"%sign, out return sign, out def puretext(state): out = r'|' for j,i in enumerate(np.ravel(state)): if i == 0 : out+='0' elif i == 1 : out+=r'1' elif i == 2 : out+=r'2' elif i == 3 : out+=r'D' if j+1< state.size: out+=',' else: out+= r'>' return out def latex(state): MATRIX = True if MATRIX: # one of the dimensions needs to be 1 to do matrix output dims = [] idx = [] one = None for ss,s in enumerate(state.shape): if s > 1 : dims.append( s ) idx.append( ss ) if s == 1 : one = ss assert( len(dims) == 2 ) assert( one is not None ) just='' for i in range( dims[0] ) : just = just+ 'c' if i < dims[0]-1: just = just +'|' #print state out = r"$ \begin{array}{"+just+"} " for mm in range(dims[0]): for nn in range(dims[1]): tup = np.empty_like( state.shape ) tup[one] = 0 tup[idx[0]] = mm tup[idx[1]] = nn i = state[ tuple( tup.tolist() ) ] if i == 0 : out+='0' elif i == 1 : out+=r'\uparrow' elif i == 2 : out+=r'\downarrow' elif i == 3 : out+=r'\uparrow\! \downarrow' if nn < dims[1] - 1 : out += ' & ' else: out += r' \\ ' if mm < dims[0] - 1 : out += r'\hline' out += r"\end{array}$" return out else: out = r"$|" for j,i in enumerate(np.ravel(state)): if i == 0 : out+='0' elif i == 1 : out+=r'\uparrow' elif i == 2 : out+=r'\downarrow' elif i == 3 : out+=r'\uparrow\! \downarrow' if j+1< state.size: out+=',' else: out+= r'\rangle' out+=r'$' return out import matplotlib.pyplot as plt import matplotlib from matplotlib import rc rc('font',**{'family':'serif'}) if __name__=="__main__": #a = lattice(2,2,1) #a.defstates() #a.nearest() #a.kinetic0() #a.interaction0() #np.savetxt('221_t.dat', a.kinetic) #np.savetxt('221_U.dat', a.inter) SITES = 4 if SITES == 4 : b = lattice(1,2,2) b.defstates() b.nearest() b.kinetic0() b.interaction0() b.diagonal0() np.savetxt('221_t.dat', b.kinetic, fmt='% 01d') np.savetxt('221_U.dat', b.inter, fmt='% 01d') outfile = 'Ut_eigenvalues_4site.png' elif SITES == 2: b = lattice(2,1,1) b.defstates() b.nearest() b.kinetic0() b.interaction0() b.diagonal0() np.savetxt('211_t.dat', b.kinetic, fmt='%01d') np.savetxt('211_U.dat', b.inter, fmt='%01d') outfile = 'Ut_eigenvalues_2site.png' # SOLUTION IS CALCULATED FOR A SET OF U VALUES t = 1. U = np.linspace(0.1,18.,32) eva = [] eve = [] for u in U: H = t*b.kinetic + u*b.inter ##print H evals,evecs = np.linalg.eigh(H) ##print "U = ",u ##print evals ##print evecs SORT = True if SORT: # Sort the eigenvals and eigenvecs index = np.argsort(evals) eva.append(evals[index]) # Ensure the eigenvecs have correct phase vecs=[] for i in index: vec = evecs[:,index[i]] #Find first entry that is non-zero i = list(np.abs(vec) > 1e-5).index(True) vec = vec / np.sign(vec[i]) vecs.append(vec) vecs = np.transpose( np.array(vecs) ) eve.append(vecs) else: eva.append(evals) eve.append(evecs) if False: print print evals[index] print evecs[index] print "#################" print index print for i in index: print "Eigenvalue %d = "%i, evals[index[i]] print "Eigenvector %d = "%i, evecs[:,index[i]] print "H*ev %d = "%i, np.dot(H, evecs[:,index[i]]) #print np.dot(H, evecs[index[i]]) / evecs[index[i]] print eva = np.array(eva) eve = np.array(eve) print "Eigenvalues", eva.shape print "Eigenvectors", eve.shape # SOLUTIONS ARE PLOTTED # Start matplotlib from matplotlib import rc rc('text', usetex=True) plt.rcParams['text.latex.preamble'] = [ r'\usepackage{bm}', # for bold math ] plt.rcParams['axes.linewidth'] = 0.6 plt.rcParams['patch.linewidth'] = 0.4 nstates = len(b.states[0]) print "Number of States in Sector 0 = ", nstates #This number should be a square: if np.abs( np.sqrt(nstates) % 1. ) > 1e-4: "Error, number of states in Sector 0 is not a square." SQUARE = False if SQUARE: plotrows = int(np.sqrt(nstates)) plotcols = plotrows else: plotrows = 2 plotcols = 8 figure = plt.figure(figsize=(4.5*plotrows,2.8*plotrows)) print "Making %d x %d figure" % (plotrows, plotcols) gs0 = matplotlib.gridspec.GridSpec( 1,1, left=0.3, right=0.7,\ bottom=0.52, top=0.98) gs = matplotlib.gridspec.GridSpec( plotrows, plotcols, \ left=0.03, right=0.98, bottom=0.05, top=0.42, \ wspace=0.14, hspace=0.05) figure.suptitle('') ax = plt.subplot( gs0[0] ) #ax = plt.subplot( gs[0:plotrows,0:plotcols0] ) axvs = [] for i in range(plotrows): for j in range(plotcols): axvs.append( plt.subplot( gs[i,j])) # Find indices for the ground state, and other relevant states ground = 0 high = nstates-1 if SITES == 4: important = [ground, high] if SITES == 2: important = [ground, high] # Find if there is a state with energy U Uindex = -1 for nn in range(nstates): if np.abs( eva[Uindex,nn] - U[Uindex] ) < 1e-4: #important.append(nn) break print "Importaant states = ", important cc = 0 c=['blue','red', 'green','red','black','purple','limegreen','orange','brown'] for col in range(eva.shape[1]): labeltxt = '%d'%col if col in important: color = c[cc % len(c)] ax.plot( U, eva[:,col], '-', c=color,lw=1.5,\ label=labeltxt) for i,axv in enumerate(axvs): if i >= len(eve[0,:,0]): continue if col == 6: subset = U > 4 axv.plot( U[subset], eve[:,i,col][subset],\ '-',c=color,lw=1.1,alpha=1.0) else: axv.plot( U, eve[:,i,col],\ '-',c=color,lw=1.1,alpha=1.0 ) cc = cc + 1 else: ax.plot( U, eva[:,col], '-', c='0.5',lw=0.8, alpha=0.4) # Print out the ground state for various Us Uindex=U.size-1 #Uindex=0 Eindex =0 print print "Energies = ", eva[Uindex,:] print "Ground state U=",U[Uindex]," E=",eva[Uindex,Eindex], ":" # Organize the basis states by the magnitude of their projection # onto the ground state order = np.argsort(np.abs(eve[Uindex,:,Eindex]))[::-1] for i in order: print "%02d --> % 02.6f %s" %(i,eve[Uindex,i,Eindex], \ puretext(b.states[0][i])) print "Ground state norm = ", np.linalg.norm( eve[Uindex,:,Eindex] ) frame_coding = { \ 12: 'blue',\ 07: 'blue',\ 05: 'blue',\ 9: 'blue',\ 0: 'red',\ 15: 'red',\ 8: 'red',\ 3: 'red',\ } for i,axv in enumerate(axvs): if i in frame_coding.keys(): if False: for spine in axv.spines.values(): spine.set_edgecolor( frame_coding[i] ) axv.text( 0.28,0.16,latex( b.states[0][i]), rotation=0 ,\ ha='center',va='center', fontsize=9,\ color = frame_coding[i],\ bbox=dict(facecolor='white', lw=0., pad=-1.),\ transform=axv.transAxes) else: axv.text( 0.28,0.16,latex( b.states[0][i]), rotation=0 ,\ ha='center',va='center', fontsize=9,\ bbox=dict(facecolor='white', lw=0., pad=-1.),\ transform=axv.transAxes) axv.yaxis.grid(which='both', alpha=0.3) axv.xaxis.grid(which='major', alpha=0.3) axv.set_ylim(-1.1,1.1) axv.set_xlim(0., 18.4) axv.xaxis.set_major_locator( matplotlib.ticker.MultipleLocator(6.) ) axv.xaxis.set_minor_locator( matplotlib.ticker.MultipleLocator(3.) ) axv.yaxis.set_major_locator( matplotlib.ticker.MultipleLocator(1.) ) axv.yaxis.set_minor_locator( matplotlib.ticker.MultipleLocator(0.5) ) axv.tick_params(axis='both', which='major', labelsize=9., length=1.5) axv.tick_params(axis='both', which='minor', labelsize=9., length=1.0) if i // plotcols < plotrows-1: axv.xaxis.set_ticklabels([]) if i % plotcols > 0 : axv.yaxis.set_ticklabels([]) ax.set_xlabel('$U/t$') #ax.plot( U, -4./U , '--', color='black') #ax.grid() ax.set_ylim(-6., 20.) ax.set_xlabel('$U/t$') ax.set_ylabel('$E/t$') #ax.legend(loc='best',numpoints=1,ncol=int(nstates)//8,\ # prop={'size':10}, \ # handlelength=1.2,handletextpad=0.5) #gs.tight_layout( figure, rect=[0.0, 0.0, 1.00, 0.7]) figure.savefig(outfile, dpi=250) # Print out the analytical ground state calculated by R.Schuman # (arXiv:cond-mat/0101476v1) t = 1. + 0j u = 18. + 0j s3 = np.sqrt(3.) X = np.sqrt( -1.*( t**2 * ( 512.*t**4 + 26.*t**2*u**2 + u**4 ))) Y = -36.*t**2*u + u**3. + 6.*np.sqrt(6.) * X C1n = 6j *np.sqrt(2.) * t * Y**(1./3.) C1d = -48. * ( -1j + s3)*t**2 - ( -1j + s3)*u**2 + 4j*u * Y**(1./3.) \ + (1j+s3) * Y**(2./3.) C1 = C1n / C1d C2n = 6j *np.sqrt(2.) * t * Y**(1./3.) C2d = -48. * ( -1j + s3)*t**2 + ( -u + Y**(1./3.) ) * \ ( (-1j+s3)*u + (1j+s3)* Y**(1./3.)) C2 = C2n / C2d C3 = -1 / (2.*np.sqrt(2.) ) print "Schumman eigenvector result:" print "C1 = ",C1 print "C2 = ",C2 print "C3 = ",C3 norm = 4.*np.abs(C1)**2 + 4.*np.abs(C2)**2 \ + 8.*np.abs(C3)**2 print "Schumman norm = ", norm\ print "Schumman eigenvector (normalized):" print "C1 = ",C1 / np.sqrt(norm) print "C2 = ",C2 / np.sqrt(norm) print "C3 = ",C3 / np.sqrt(norm) # It seems that my eigenvectors are correct, by comparing to the # analytical result by schuman

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null

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7030d6e9feb4e14bd7bd841d594abc3eb0f18ef0

5,422

py

Python

tests/test_connection.py

miiklay/pymapd

4665ea704eb7ffabf72048f1cb3519b4497b8830

[ "Apache-2.0" ]

null

tests/test_connection.py

miiklay/pymapd

4665ea704eb7ffabf72048f1cb3519b4497b8830

[ "Apache-2.0" ]

null

tests/test_connection.py

miiklay/pymapd

4665ea704eb7ffabf72048f1cb3519b4497b8830

[ "Apache-2.0" ]

null

import pytest from mapd.ttypes import TColumnType, TTypeInfo from pymapd import OperationalError, connect from pymapd.cursor import Cursor from pymapd.connection import _parse_uri, ConnectionInfo from pymapd._parsers import ColumnDetails, _extract_column_details class TestConnect(object): def test_host_specified(self): with pytest.raises(TypeError): connect(user='foo') def test_raises_right_exception(self): with pytest.raises(OperationalError): connect(host='localhost', protocol='binary', port=1234) def test_close(self, mock_transport, mock_client): con = connect(user='user', password='password', host='localhost', dbname='dbname') assert con.closed == 0 con.close() assert con.closed == 1 def test_connect(self, mock_transport, mock_client): con = connect(user='user', password='password', host='localhost', dbname='dbname') assert mock_client.call_count == 1 assert con._client.connect.call_args == [ ('user', 'password', 'dbname') ] def test_context_manager(self, mock_transport, mock_client): con = connect(user='user', password='password', host='localhost', dbname='dbname') with con as cur: pass assert isinstance(cur, Cursor) assert con.closed == 0 def test_commit_noop(self, mock_transport, mock_client): con = connect(user='user', password='password', host='localhost', dbname='dbname') result = con.commit() # it worked assert result is None def test_bad_protocol(self, mock_transport, mock_client): with pytest.raises(ValueError) as m: connect(user='user', host='localhost', dbname='dbname', protocol='fake-proto') assert m.match('fake-proto') class TestURI(object): def test_parse_uri(self): uri = ('mapd://mapd:HyperInteractive@localhost:9091/mapd?' 'protocol=binary') result = _parse_uri(uri) expected = ConnectionInfo("mapd", "HyperInteractive", "localhost", 9091, "mapd", "binary") assert result == expected def test_both_raises(self): uri = ('mapd://mapd:HyperInteractive@localhost:9091/mapd?' 'protocol=binary') with pytest.raises(TypeError): connect(uri=uri, user='my user') class TestExtras(object): def test_extract_row_details(self): data = [ TColumnType(col_name='date_', col_type=TTypeInfo(type=6, encoding=4, nullable=True, is_array=False, precision=0, scale=0, comp_param=32), is_reserved_keyword=False, src_name=''), TColumnType(col_name='trans', col_type=TTypeInfo(type=6, encoding=4, nullable=True, is_array=False, precision=0, scale=0, comp_param=32), is_reserved_keyword=False, src_name=''), TColumnType(col_name='symbol', col_type=TTypeInfo(type=6, encoding=4, nullable=True, is_array=False, precision=0, scale=0, comp_param=32), is_reserved_keyword=False, src_name=''), TColumnType(col_name='qty', col_type=TTypeInfo(type=1, encoding=0, nullable=True, is_array=False, precision=0, scale=0, comp_param=0), is_reserved_keyword=False, src_name=''), TColumnType(col_name='price', col_type=TTypeInfo(type=3, encoding=0, nullable=True, is_array=False, precision=0, scale=0, comp_param=0), is_reserved_keyword=False, src_name=''), TColumnType(col_name='vol', col_type=TTypeInfo(type=3, encoding=0, nullable=True, is_array=False, precision=0, scale=0, comp_param=0), is_reserved_keyword=False, src_name='')] result = _extract_column_details(data) expected = [ ColumnDetails(name='date_', type='STR', nullable=True, precision=0, scale=0, comp_param=32), ColumnDetails(name='trans', type='STR', nullable=True, precision=0, scale=0, comp_param=32), ColumnDetails(name='symbol', type='STR', nullable=True, precision=0, scale=0, comp_param=32), ColumnDetails(name='qty', type='INT', nullable=True, precision=0, scale=0, comp_param=0), ColumnDetails(name='price', type='FLOAT', nullable=True, precision=0, scale=0, comp_param=0), ColumnDetails(name='vol', type='FLOAT', nullable=True, precision=0, scale=0, comp_param=0) ] assert result == expected

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0

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0.356326

5,422

123

80

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0.00166

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0

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1

0.095238

false

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0.180952

0

null

0

null

0

1

0

1

703107f699c7f26c45918048eaa30145a2e5dcb7

1,149

py

Python

setup.py

tmeiczin/pyautomount

1e1b01538e8cb15931e63a97633f37f3e55a96b3

[ "MIT" ]

null

setup.py

tmeiczin/pyautomount

1e1b01538e8cb15931e63a97633f37f3e55a96b3

[ "MIT" ]

null

setup.py

tmeiczin/pyautomount

1e1b01538e8cb15931e63a97633f37f3e55a96b3

[ "MIT" ]

null

#!/usr/bin/env python from setuptools import setup, find_packages from subprocess import Popen, PIPE setup( name='pyautomount', version='1.0.0', author=['Terrence Meiczinger'], author_email='terrence72@gmail.com', license='LICENSE', url='https://github.com/tmeiczin/pyautomount', download_url='https://github.com/tmeiczin/pydhcp', description='Python Auto Mounter', long_description=open('README.md').read(), packages=find_packages('src'), package_dir={'': 'src'}, include_package_data=False, zip_safe=False, classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Operating System :: Unix', 'Operating System :: POSIX', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: Implementation :: CPython', 'Programming Language :: Python :: Implementation :: PyPy', 'Topic :: Utilities', ], install_requires=[ 'pyudev', ], entry_points={ 'console_scripts': [ 'pyautomounter = pyautomount.__main__:main' ], }, )

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70

0.624021

112

1,149

6.258929

0.705357

0.081312

0.10699

0.048502

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0.230635

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38

71

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null

0

null

0

1

0

1

70365219313e16a31641d194a9ebac7e3c52aa71

7,190

py

Python

app/auth/views.py

fushouhai/flask_11_28

49a030d8a61a1a3cdd1f32746978781a5266c599

[ "MIT" ]

null

app/auth/views.py

fushouhai/flask_11_28

49a030d8a61a1a3cdd1f32746978781a5266c599

[ "MIT" ]

null

app/auth/views.py

fushouhai/flask_11_28

49a030d8a61a1a3cdd1f32746978781a5266c599

[ "MIT" ]

null

from flask import render_template, redirect, request, url_for, flash, session, current_app from flask_login import login_user, logout_user, login_required, \ current_user from . import auth from .. import db from ..models import User from ..email import send_email from .forms import LoginForm, RegistrationForm, ChangePasswordForm, ForgetPasswordForm, FPNewPasswordForm, \ ChangeEmailPasswordConfirmForm, ChangeEmailSetForm from itsdangerous import TimedJSONWebSignatureSerializer as Serializer @auth.before_app_request def before_request(): if current_user.is_authenticated: current_user.ping() if not current_user.confirmed \ and request.endpoint[:5] != 'auth.': return redirect(url_for('auth.unconfirmed')) @auth.route('/unconfirmed') def unconfirmed(): if current_user.is_anonymous or current_user.confirmed: return redirect(url_for('main.index')) return render_template('auth/unconfirmed.html') @auth.route('/login', methods=['GET', 'POST']) def login(): form = LoginForm() if form.validate_on_submit(): user = User.query.filter_by(email=form.email.data).first() if user is not None and user.verify_password(form.password.data): login_user(user, form.remember_me.data) return redirect(request.args.get('next') or url_for('main.index')) flash('Invalid username or password.') return render_template('auth/login.html', form=form) @auth.route('/change_password', methods=['GET', 'POST']) @login_required def change_password(): form = ChangePasswordForm() if form.validate_on_submit(): if current_user.verify_password(form.old_passwd.data): current_user.password = form.new_passwd.data flash('Password changed!') return redirect(url_for('main.index')) flash('Invalid password.') return render_template('auth/change_password.html', form=form) @auth.route('/change_email', methods=['GET', 'POST']) @login_required def change_email(): form = ChangeEmailPasswordConfirmForm() if form.validate_on_submit(): if current_user.verify_password(form.password.data): return redirect(url_for('auth.change_email_set')) else: flash('password error') return redirect(url_for('main.index')) return render_template('auth/change_email_password_confirm.html', form=form) @auth.route('/change_email_set', methods=['GET', 'POST']) @login_required def change_email_set(): form = ChangeEmailSetForm() if form.validate_on_submit(): token = current_user.generate_confirmation_token(email=form.email.data) send_email(form.email.data, 'Confirm', 'auth/email/change_email_set', user=current_user, token=token) flash('A confirm email has been sent to you by new email') return redirect(url_for('main.index')) return render_template('auth/change_email_set.html', form=form) @auth.route('/change_email_set_done/<token>') @login_required def change_email_set_done(token): s = Serializer(current_app.config['SECRET_KEY']) try: data = s.loads(token) except: flash('confirm error!') return redirect(url_for('main.index')) if current_user.id == data.get('confirm'): current_user.email = data.get('email') current_user.avatar_hash = hashlib.md5( current_user.email.encode('utf-8')).hexdigest() flash('email changed') return redirect(url_for('main.index')) flash('user changed or logout') return redirect(url_for('main.index')) @auth.route('/forget_password', methods=['GET', 'POST']) def forget_password(): form = ForgetPasswordForm() if form.validate_on_submit(): user = User.query.filter_by(email=form.email.data).first() if user is not None: token = user.generate_confirmation_token() send_email(user.email, 'Confirm Your Account', 'auth/email/forget_password', user=user, token=token) flash('A confirmation email has been sent to you by email, which is about forgetting password') return redirect(url_for('main.index')) return render_template('auth/forget_password.html', form=form) @auth.route('/confirm_forget_password/<token>') def confirm_forget_password(token): session['token'] = token return redirect(url_for('auth.forget_password_set_password')) @auth.route('/forget_password_set_password', methods=['GET', 'POST']) def forget_password_set_password(): form = FPNewPasswordForm() if form.validate_on_submit(): s = Serializer(current_app.config['SECRET_KEY']) try: token = session.get('token') data = s.loads(token) except: flash('confirm error!') return redirect(url_for('main.index')) val_id = data.get('confirm') if val_id is not None: user = User.query.filter_by(id=val_id).first() if user is not None: user.password = form.password.data db.session.add(user) db.session.commit() flash('password has changed!') return redirect(url_for('auth.login')) else: flash('can not find user!') return redirect(url_for('main.index')) else: flash('user is error!') return redirect(url_for('main.index')) return render_template('auth/forget_password_set_password.html', form=form) @auth.route('/logout') @login_required def logout(): logout_user() flash('You have been logged out.') return redirect(url_for('main.index')) @auth.route('/register', methods=['GET', 'POST']) def register(): form = RegistrationForm() flash('Warning:Email@163.com does not work!') if form.validate_on_submit(): user = User(email=form.email.data, username=form.username.data, password=form.password.data) db.session.add(user) db.session.commit() token = user.generate_confirmation_token() send_email(user.email, 'Confirm Your Account', 'auth/email/confirm', user=user, token=token) flash('A confirmation email has been sent to you by email.') return redirect(url_for('auth.login')) return render_template('auth/register.html', form=form) @auth.route('/confirm/<token>') @login_required def confirm(token): if current_user.confirmed: return redirect(url_for('main.index')) if current_user.confirm(token): flash('You have confirmed your account. Thanks!') else: flash('The confirmation link is invalid or has expired.') return redirect(url_for('main.index')) @auth.route('/confirm') @login_required def resend_confirmation(): token = current_user.generate_confirmation_token() send_email(current_user.email, 'Confirm Your Account', 'auth/email/confirm', user=current_user, token=token) flash('A new confirmation email has been sent to you by email.') return redirect(url_for('main.index'))

38.864865

108

0.665229

889

7,190

5.20135

0.150731

0.028547

0.073529

0.086505

0.588235

0.532007

0.443123

0.384516

0.292388

0.260164

0

0.001059

0.212239

7,190

184

109

39.076087

0.815325

0

0.345455

0

0.211266

0.054659

0

1

0.084848

false

0.193939

0.048485

0

0.309091

0

null

0

null

0

1

0

1

703c18b3d77e9deeb40500573ea0b2b61e8d29d8

12,733

py

Python

src/evaluation_system/model/user.py

FREVA-CLINT/Freva

53c6d0951a8dcfe985c8f33cbb3fbac7e8a3db04

[ "BSD-2-Clause-FreeBSD" ]

2

2020-06-12T18:18:48.000Z

2021-12-18T03:35:08.000Z

src/evaluation_system/model/user.py

FREVA-CLINT/Freva

53c6d0951a8dcfe985c8f33cbb3fbac7e8a3db04

[ "BSD-2-Clause-FreeBSD" ]

null

src/evaluation_system/model/user.py

FREVA-CLINT/Freva

53c6d0951a8dcfe985c8f33cbb3fbac7e8a3db04

[ "BSD-2-Clause-FreeBSD" ]

null

''' .. moduleauthor:: Sebastian Illing / estani This module manages the abstraction of a user providing thus all information about him/her that might be required anywhere else. ''' import pwd import os import sys from ConfigParser import SafeConfigParser as Config from evaluation_system.misc import config, utils from evaluation_system.model.db import UserDB class User(object): ''' This Class encapsulates a user (configurations, etc). ''' CONFIG_DIR = 'config' "The directory name where all plug-in/system configurations will be stored." CACHE_DIR = 'cache' "The temporary directory where plug-ins can store files while performing some computation." OUTPUT_DIR = 'output' "The directory where output files are stored. Intended for files containing data and thus taking much space." PLOTS_DIR = 'plots' """The directory where just plots are stored. Plots are assumed to be much smaller in size than data and might therefore live longer""" PROCESSES_DIR = 'processes' "The directory might handle information required for each running process." EVAL_SYS_CONFIG = os.path.join(CONFIG_DIR,'evaluation_system.config') """The file containing a central configuration for the whole system (user-wise)""" EVAL_SYS_DEFAULT_CONFIG = os.path.normpath(os.path.dirname(sys.modules[__name__].__file__)+'/../../etc/system_default.config') """The central default configuration file for all users. It should not be confused with the system configuration file that is handled by :class:`evaluation_system.api.config`.""" def __init__(self, uid = None, email = None): '''Creates a user object for the provided id. If no id is given, a user object for the current user, i.e. the one that started the application, is created instead. :type uid: int :param uid: user id in the local system, if not provided the current user is used. :type email: str :param email: user's email address ''' self._dir_type = config.get(config.DIRECTORY_STRUCTURE_TYPE) if uid is None: uid = os.getuid() self._userdata = None if isinstance(uid, basestring): self._userdata = pwd.getpwnam(uid) else: self._userdata = pwd.getpwuid(uid) if self._userdata is None: raise Exception("Cannot find user %s" % uid) if email is None: self._email = '' else: self._email = email self._userconfig = Config() #try to load teh configuration from the very first time. self._userconfig.read([User.EVAL_SYS_DEFAULT_CONFIG, os.path.join(self._userdata.pw_dir, User.EVAL_SYS_CONFIG)]) self._db = UserDB(self) row_id = self._db.getUserId(self.getName()) if row_id: try: self._db.updateUserLogin(row_id, email) except: raise pass else: self._db.createUser(self.getName(), email=self._email) #-------------------------- self._meta = metadict(compact_creation=True, #--------------------------------- USER_BASE_DIR=) # """Expand the user specific values in the given string. Those values might be one of: # $USER_BASE_DIR := central directory for this user in the evaluation system. # $USER_OUTPUT_DIR := directory where the output data for this user is stored. #------ $USER_PLOT_DIR := directory where the plots for this user is stored. # $USER_CACHE_DIR := directory where the cached data for this user is stored.""" def __str__(self): return "<User (username:%s, info:%s)>" % (self._userdata[0], str(self._userdata[2:])) def getUserConfig(self): """:returns: the user configuration object :py:class:`ConfigParser.SafeConfigParser`""" return self._userconfig def getUserDB(self): """:returns: the db abstraction for this user. :rtype: :class:`evaluation_system.model.db.UserDB`""" return self._db def reloadConfig(self): """Reloads user central configuration from disk (not the plug-in related one).""" self._userconfig = Config() self._userconfig.read([User.EVAL_SYS_DEFAULT_CONFIG, os.path.join(self.getUserBaseDir(), User.EVAL_SYS_CONFIG)]) return self._userconfig def writeConfig(self): """Writes the user central configuration to disk according to :class:`EVAL_SYS_CONFIG`""" fp = open(os.path.join(self.getUserBaseDir(), User.EVAL_SYS_CONFIG), 'w') self._userconfig.write(fp) fp.close() def getName(self): """:returns: the user name :rtype: str""" return self._userdata.pw_name def getEmail(self): """ :returns: user's email address. Maybe None. :rtype: str """ return self._email def getUserID(self): """:returns: the user id. :rtype: int""" return self._userdata.pw_uid def getUserHome(self): """:returns: the path to the user home directory. :rtype: str""" return self._userdata.pw_dir def getUserScratch(self): """:returns: the path to the user's scratch directory. :rtype: str""" path = config.get(config.SCRATCH_DIR) path = path.replace('$USER', self.getName()) return path def _getUserBaseDir(self): if self._dir_type == config.DIRECTORY_STRUCTURE.LOCAL: return os.path.join(self.getUserHome(), config.get(config.BASE_DIR)) elif self._dir_type == config.DIRECTORY_STRUCTURE.CENTRAL: return os.path.join(config.get(config.BASE_DIR_LOCATION), config.get(config.BASE_DIR), str(self.getName())) elif self._dir_type == config.DIRECTORY_STRUCTURE.SCRATCH: return os.path.join(config.get(config.BASE_DIR_LOCATION), str(self.getName()), config.get(config.BASE_DIR)) def _getUserDir(self, dir_type, tool = None, create=False): base_dir = dict(base='', config=User.CONFIG_DIR, cache=User.CACHE_DIR, output=User.OUTPUT_DIR, \ plots=User.PLOTS_DIR, processes=User.PROCESSES_DIR, \ scheduler_in=config.get(config.SCHEDULER_INPUT_DIR), \ scheduler_out=config.get(config.SCHEDULER_OUTPUT_DIR)) if tool is None: bd = base_dir[dir_type] # concatenate relative paths only if bd and bd[0]=='/': dir_name = bd else: #return the directory where the tool configuration files are stored dir_name = os.path.join(self._getUserBaseDir(), bd) else: #It's too confusing if we create case sensitive directories... tool = tool.lower() #return the specific directory for the given tool dir_name = os.path.join(self._getUserBaseDir(), base_dir[dir_type], tool) #make sure we have a canonical path dir_name = os.path.abspath(dir_name) if create and not os.path.isdir(dir_name): #we are letting this fail in case of problems. utils.supermakedirs(dir_name, 0755) return dir_name def getUserBaseDir(self, **kwargs): """Returns path to where this system is managing this user data. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :returns: (str) path""" return self._getUserDir('base', **kwargs) def getUserSchedulerInputDir(self, **kwargs): """Returns path to where this system is managing this user data. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :returns: (str) path""" return self._getUserDir('scheduler_in', **kwargs) def getUserSchedulerOutputDir(self, **kwargs): """Returns path to where this system is managing this user data. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :returns: (str) path""" return self._getUserDir('scheduler_out', **kwargs) def getUserToolConfig(self, tool, **kwargs): """Returns the path to the configuration file. :param kwargs: ``create`` := If ``True`` assure the underlaying directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. :type tool: str :returns: path to the configuration file.""" config_dir = self._getUserDir('config', tool, **kwargs) return os.path.join(config_dir,'%s.conf' % tool) def getUserConfigDir(self, tool = None, **kwargs): """Return the path to the directory where all configurations for this user are stored. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. If None, then the directory where all information for all tools reside is returned insted (normally, that would be the parent directrory). :type tool: str :returns: path to the directory.""" return self._getUserDir('config', tool, **kwargs) def getUserCacheDir(self, tool = None, **kwargs): """Return directory where cache files for this user (might not be "only" for this user though). :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. If None, then the directory where all information for all tools reside is returned insted (normally, that would be the parent directrory). :type tool: str :returns: path to the directory.""" return self._getUserDir('cache', tool, **kwargs) def getUserProcessDir(self, tool = None, **kwargs): """Return directory where files required for processes can be held. Is not clear what this will be used for, but it should at least serve as a possibility for the future. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. If None, then the directory where all information for all tools reside is returned insted (normally, that would be the parent directrory). :type tool: str :returns: path to the directory.""" return self._getUserDir('processes', tool, **kwargs) def getUserOutputDir(self, tool = None, **kwargs): """Return directory where output data for this user is stored. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. If None, then the directory where all information for all tools reside is returned insted (normally, that would be the parent directrory). :type tool: str :returns: path to the directory.""" return self._getUserDir('output', tool, **kwargs) def getUserPlotsDir(self, tool = None, **kwargs): """Return directory where all plots for this user are stored. :param kwargs: ``create`` := If ``True`` assure the directory exists after the call is done. :param tool: tool/plug-in for which the information is returned. If None, then the directory where all information for all tools reside is returned insted (normally, that would be the parent directrory). :type tool: str :returns: path to the directory.""" return self._getUserDir('plots', tool, **kwargs) def prepareDir(self): """Prepares the configuration directory for this user if it's not already been done.""" if os.path.isdir(self.getUserBaseDir()): #we assume preparation was successful... but we might to be sure though... #return pass if not os.path.isdir(self.getUserHome()): raise Exception("Can't create configuration, user HOME doesn't exist (%s)" % self.getUserHome()) #create directory for the framework #create all required subdirectories dir_creators = [self.getUserBaseDir, self.getUserConfigDir, self.getUserCacheDir, self.getUserOutputDir, self.getUserPlotsDir, self.getUserSchedulerInputDir, self.getUserSchedulerOutputDir,] for f in dir_creators: f(create=True)

42.872054

130

0.641404

1,612

12,733

4.968983

0.183002

0.035955

0.015106

0.021348

0.402497

0.369164

0.348315

0.290262

0.280774

0

0.000741

0.258305

12,733

296

131

43.016892

0.847416

0.079636

0

0.085271

0

0.090721

0.008274

0

null

0.015504

0.046512

null

0

null

0

null

0

1

0

1

703c2951dba5449a5db47926cbcfb472f6a8c13d

622

py

Python

python/sortalgorithm/quickSort.py

Turingu/leetcode

ac75c14604b29df394b768b23a94bb7bf310777b

[ "MIT" ]

1

2020-01-01T17:46:11.000Z

python/sortalgorithm/quickSort.py

Turingu/leetcode

ac75c14604b29df394b768b23a94bb7bf310777b

[ "MIT" ]

null

python/sortalgorithm/quickSort.py

Turingu/leetcode

ac75c14604b29df394b768b23a94bb7bf310777b

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- class QuickSort: """ 快速排序 """ def __init__(self): pass def quicksort(self, nums): if len(nums) == 1 or len(nums) == 0: return nums less = [] greater = [] middle_num = nums.pop() for num in nums: if num > middle_num: greater.append(num) if num < middle_num: less.append(num) return self.quicksort(less) + [middle_num] + self.quicksort(greater) if __name__ == '__main__': print(QuickSort().quicksort([5, 6, 1, 3, 4, 2]))

19.4375

76

0.5

73

622

4.041096

0.506849

0.122034

0.074576

0.094915

0

0.022613

0.360129

622

31

77

20.064516

0.718593

0.075563

0

0.014337

0

1

0.117647

false

0.058824

0

0.294118

0.058824

0

null

0

null

0

1

0

1

7041ada191d0f5730f5d5dde284d632d5177384a

24,098

py

Python

src/SegnetModel.py

JasonChu1313/Satellite-Segmentation

c41727af305d09ce93f745b841d228b7a4f24a9c

[ "MIT" ]

1

2019-01-29T04:35:39.000Z

src/SegnetModel.py

JasonChu1313/Satellite-Segmentation

c41727af305d09ce93f745b841d228b7a4f24a9c

[ "MIT" ]

null

src/SegnetModel.py

JasonChu1313/Satellite-Segmentation

c41727af305d09ce93f745b841d228b7a4f24a9c

[ "MIT" ]

null

from Model import Model from Config import Config from math import ceil import readfile import customer_init import numpy as np import time import datetime import util import os import random from tempfile import TemporaryFile from customer_init import orthogonal_initializer import tensorflow as tf from tensorflow.core.protobuf import saver_pb2 # import the inspect_checkpoint library from tensorflow.python.tools import inspect_checkpoint as chkp import math class SegnetModel(Model): def __init__(self): self.config = Config() def add_placeholders(self): self.train_data_node = tf.placeholder(tf.float32, shape=[self.config.BATCH_SIZE, self.config.IMAGE_HEIGHT, self.config.IMAGE_WIDTH, self.config.IMAGE_DEPTH]) self.train_label_node = tf.placeholder(tf.int32, shape=[self.config.BATCH_SIZE, self.config.IMAGE_HEIGHT, self.config.IMAGE_WIDTH,1]) self.phase_train = tf.placeholder(tf.bool, name="phase_train") self.average_pl = tf.placeholder(tf.float32) self.acc_pl = tf.placeholder(tf.float32) self.iu_pl = tf.placeholder(tf.float32) self.test_data_node = tf.placeholder( tf.float32, shape=[self.config.TEST_BATCH_SIZE, self.config.IMAGE_HEIGHT, self.config.IMAGE_WIDTH, self.config.IMAGE_DEPTH]) self.test_labels_node = tf.placeholder(tf.int64, shape=[self.config.TEST_BATCH_SIZE, self.config.IMAGE_HEIGHT, self.config.IMAGE_WIDTH,1]) def add_loss_op(self, pred): pass def add_training_op(self, total_loss): """ fix lr """ lr = self.config.INITIAL_LEARNING_RATE loss_averages_op = util._add_loss_summaries(total_loss) # Compute gradients. with tf.control_dependencies([loss_averages_op]): opt = tf.train.AdamOptimizer(lr) grads = opt.compute_gradients(total_loss) apply_gradient_op = opt.apply_gradients(grads, global_step=self.global_step) # Add histograms for trainable variables. for var in tf.trainable_variables(): tf.summary.histogram(var.op.name, var) # Add histograms for gradients. for grad, var in grads: if grad is not None: tf.summary.histogram(var.op.name + '/gradients', grad) # Track the moving averages of all trainable variables. variable_averages = tf.train.ExponentialMovingAverage( self.config.MOVING_AVERAGE_DECAY, self.global_step) variables_averages_op = variable_averages.apply(tf.trainable_variables()) with tf.control_dependencies([apply_gradient_op, variables_averages_op]): train_op = tf.no_op(name='train') return train_op def train_on_batch(self, sess, inputs_batch, labels_batch): pass def add_prediction_op(self): # norm1 norm1 = tf.nn.lrn(self.train_data_node, depth_radius=5, bias=1.0, alpha=0.0001, beta=0.75, name='norm1') # conv1 conv1 = self.conv_layer_with_bn(norm1, [7, 7, self.train_data_node.get_shape().as_list()[3], 64], self.phase_train, name="conv1") # pool1 pool1, pool1_indices = tf.nn.max_pool_with_argmax(conv1, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool1') # conv2 conv2 = self.conv_layer_with_bn(pool1, [7, 7, 64, 64], self.phase_train, name="conv2") # pool2 pool2, pool2_indices = tf.nn.max_pool_with_argmax(conv2, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool2') # conv3 conv3 = self.conv_layer_with_bn(pool2, [7, 7, 64, 64], self.phase_train, name="conv3") # pool3 pool3, pool3_indices = tf.nn.max_pool_with_argmax(conv3, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool3') # conv4 conv4 = self.conv_layer_with_bn(pool3, [7, 7, 64, 64], self.phase_train, name="conv4") """ End of encoder """ """ start upsample """ # pool4 pool4, pool4_indices = tf.nn.max_pool_with_argmax(conv4, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool4') # upsample4 # Need to change when using different dataset out_w, out_h # upsample4 = upsample_with_pool_indices(pool4, pool4_indices, pool4.get_shape(), out_w=45, out_h=60, scale=2, name='upsample4') upsample4 = self.deconv_layer(pool4, [2, 2, 64, 64], [self.config.BATCH_SIZE, 64, 64, 64], 2, "up4") # decode 4 conv_decode4 = self.conv_layer_with_bn(upsample4, [7, 7, 64, 64], self.phase_train, False, name="conv_decode4") # upsample 3 # upsample3 = upsample_with_pool_indices(conv_decode4, pool3_indices, conv_decode4.get_shape(), scale=2, name='upsample3') upsample3 = self.deconv_layer(conv_decode4, [2, 2, 64, 64], [self.config.BATCH_SIZE, 128, 128, 64], 2, "up3") # decode 3 conv_decode3 = self.conv_layer_with_bn(upsample3, [7, 7, 64, 64], self.phase_train, False, name="conv_decode3") # upsample2 # upsample2 = upsample_with_pool_indices(conv_decode3, pool2_indices, conv_decode3.get_shape(), scale=2, name='upsample2') upsample2 = self.deconv_layer(conv_decode3, [2, 2, 64, 64], [self.config.BATCH_SIZE, 256, 256, 64], 2, "up2") # decode 2 conv_decode2 = self.conv_layer_with_bn(upsample2, [7, 7, 64, 64], self.phase_train, False, name="conv_decode2") # upsample1 # upsample1 = upsample_with_pool_indices(conv_decode2, pool1_indices, conv_decode2.get_shape(), scale=2, name='upsample1') upsample1 = self.deconv_layer(conv_decode2, [2, 2, 64, 64], [self.config.BATCH_SIZE, 512, 512, 64], 2, "up1") # decode4 conv_decode1 = self.conv_layer_with_bn(upsample1, [7, 7, 64, 64], self.phase_train, False, name="conv_decode1") """ Start Classify """ # output predicted class number (6) with tf.variable_scope('conv_classifier', reuse=tf.AUTO_REUSE) as scope: kernel = util._variable_with_weight_decay('weights', shape=[1, 1, 64, 2], initializer=customer_init.msra_initializer(1, 64), wd=0.0005) conv = tf.nn.conv2d(conv_decode1, kernel, [1, 1, 1, 1], padding='SAME') biases = util._variable('biases', [2], tf.constant_initializer(0.0)) conv_classifier = tf.nn.bias_add(conv, biases, name=scope.name) logit = conv_classifier loss = self.cal_loss(conv_classifier, self.train_label_node) return loss, logit def cal_loss(self, conv_classifier, labels): with tf.name_scope("loss"): logits = tf.reshape(conv_classifier, (-1, self.config.NUM_CLASSES)) epsilon = tf.constant(value=1e-10) logits = logits + epsilon softmax = tf.nn.softmax(logits) # consturct one-hot label array label_flat = tf.reshape(labels, (-1, 1)) # should be [batch ,num_classes] labels = tf.reshape(tf.one_hot(label_flat, depth=self.config.NUM_CLASSES), (-1, self.config.NUM_CLASSES)) w1_n = tf.ones([softmax.shape[0],1],tf.float32) w2_n = tf.slice(softmax,[0,0],[-1,1]) _T = 0.3 T = tf.ones(softmax.shape[0],1) * _T condition = tf.greater(w2_n, 0.5) w2_n = tf.where(condition, tf.math.maximum(_T, w2_n), tf.ones(w2_n.shape)) #w2_n = tf.cond(tf.greater(w2_n, 0.5), lambda : 1-w2_n, lambda : [1]) #tf.cond(tf.greater(w2_n,0.5) , lambda : 1, lambda : 0) weight = tf.concat([w2_n,w1_n],1) cross_entropy = -tf.reduce_sum(weight * labels * tf.log(softmax + epsilon), axis=[1]) cross_entropy_mean = tf.reduce_mean(cross_entropy, name='cross_entropy') tf.add_to_collection('losses', cross_entropy_mean) loss = tf.add_n(tf.get_collection('losses'), name='total_loss') return loss def conv_layer_with_bn(self, inputT, shape, train_phase, activation = True, name = None): in_channel = shape[2] out_channel = shape[3] k_size = shape[0] with tf.variable_scope(name, reuse=tf.AUTO_REUSE) as scope: kernel = util._variable_with_weight_decay('ort_weights', shape=shape, initializer=orthogonal_initializer(), wd=None) conv = tf.nn.conv2d(inputT, kernel, [1, 1, 1, 1], padding='SAME') biases = util._variable('biases', [out_channel], tf.constant_initializer(0.0)) bias = tf.nn.bias_add(conv, biases) if activation is True: conv_out = tf.nn.relu(self.batch_norm_layer(bias, train_phase, scope.name)) else: conv_out = self.batch_norm_layer(bias, train_phase, scope.name) return conv_out def batch_norm_layer(self, inputT, is_training, scope): return tf.cond(is_training, lambda: tf.contrib.layers.batch_norm(inputT, is_training=True, center=False, updates_collections=None, scope=scope + "_bn"), lambda: tf.contrib.layers.batch_norm(inputT, is_training=False, updates_collections=None, center=False, scope=scope + "_bn", reuse=True)) def deconv_layer(self, inputT, f_shape, output_shape, stride=2, name=None): # output_shape = [b, w, h, c] # sess_temp = tf.InteractiveSession() sess_temp = tf.global_variables_initializer() strides = [1, stride, stride, 1] with tf.variable_scope(name): weights = self.get_deconv_filter(f_shape) deconv = tf.nn.conv2d_transpose(inputT, weights, output_shape, strides=strides, padding='SAME') return deconv def get_deconv_filter(self, f_shape): """ reference: https://github.com/MarvinTeichmann/tensorflow-fcn """ width = f_shape[0] heigh = f_shape[0] f = ceil(width / 2.0) c = (2 * f - 1 - f % 2) / (2.0 * f) bilinear = np.zeros([f_shape[0], f_shape[1]]) for x in range(width): for y in range(heigh): value = (1 - abs(x / f - c)) * (1 - abs(y / f - c)) bilinear[x, y] = value weights = np.zeros(f_shape) for i in range(f_shape[2]): weights[:, :, i, i] = bilinear init = tf.constant_initializer(value=weights, dtype=tf.float32) return tf.get_variable(name="up_filter", initializer=init, shape=weights.shape) def get_train_val(self, image_filenames, label_filenames): val_size = int(len(image_filenames) * 0.06) val_image_filenames = [] val_label_filenames = [] for i in range(val_size): pop_index = random.randint(0, len(image_filenames)-1) val_image_filenames.append(image_filenames.pop(pop_index)) val_label_filenames.append(label_filenames.pop(pop_index)) val_image_filenames.pop(0) val_label_filenames.pop(0) return image_filenames, label_filenames, val_image_filenames, val_label_filenames def training(self, is_finetune=False): batch_size = self.config.BATCH_SIZE train_dir = self.config.log_dir # ../data/Logs image_dir = self.config.image_dir # ../data/train val_dir = self.config.val_dir # ../data/val finetune_ckpt = self.config.finetune image_w = self.config.IMAGE_WIDTH image_h = self.config.IMAGE_HEIGHT image_c = self.config.IMAGE_DEPTH image_filenames, label_filenames = readfile.get_filename_list(image_dir, prefix = "../data/train") print "total file size {}".format(len(image_filenames)) #val_image_filenames, val_label_filenames = readfile.get_filename_list(val_dir, prefix = "../data/val", is_train=False) # image_filenames, label_filenames, val_image_filenames, val_label_filenames = self.get_train_val(image_filenames, label_filenames) # print "train size {}".format(len(image_filenames)) # print "test size {}".format(len(val_image_filenames)) # should be changed if your model stored by different convention startstep = 0 if not is_finetune else int(self.config.finetune.split('-')[-1]) #with tf.device('/device:GPU:0'): with tf.Graph().as_default(): self.add_placeholders() self.global_step = tf.Variable(0, trainable=False) train_dataset = readfile.get_dataset(image_filenames, label_filenames, self.config.BATCH_SIZE, True) # val_dataset = readfile.get_dataset(val_image_filenames, val_label_filenames, self.config.EVAL_BATCH_SIZE) train_iterator = train_dataset.make_one_shot_iterator() next_train_element = train_iterator.get_next() # val_iterator = val_dataset.make_one_shot_iterator() # next_val_element = val_iterator.get_next() # Build a Graph that computes the logits predictions from the inference model. loss, eval_prediction = self.add_prediction_op() # Build a Graph that trains the model with one batch of examples and updates the model parameters. train_op = self.add_training_op(loss) saver = tf.train.Saver(tf.global_variables(),write_version= saver_pb2.SaverDef.V1) summary_op = tf.summary.merge_all() with tf.Session() as sess: # Build an initialization operation to run below. if (is_finetune == True): saver.restore(sess, finetune_ckpt) else: init = tf.global_variables_initializer() sess.run(init) # Summery placeholders summary_writer = tf.summary.FileWriter(train_dir, sess.graph) average_pl = tf.placeholder(tf.float32) acc_pl = tf.placeholder(tf.float32) iu_pl = tf.placeholder(tf.float32) average_summary = tf.summary.scalar("test_average_loss", average_pl) acc_summary = tf.summary.scalar("test_accuracy", acc_pl) iu_summary = tf.summary.scalar("Mean_IU", iu_pl) for step in range(startstep, startstep + self.config.maxsteps): image_batch, label_batch = sess.run(next_train_element) # since we still use mini-batches in validation, still set bn-layer phase_train = True feed_dict = { self.train_data_node: image_batch, self.train_label_node: label_batch, self.phase_train: True } start_time = time.time() _, loss_value = sess.run([train_op, loss], feed_dict=feed_dict) duration = time.time() - start_time assert not np.isnan(loss_value), 'Model diverged with loss = NaN' if step % 50 == 0: num_examples_per_step = batch_size examples_per_sec = num_examples_per_step / duration sec_per_batch = float(duration) format_str = ('%s: step %d, loss = %.4f (%.1f examples/sec; %.3f ' 'sec/batch)') print (format_str % (datetime.datetime.now(), step, loss_value, examples_per_sec, sec_per_batch)) # eval current training batch pre-class accuracy pred = sess.run(eval_prediction, feed_dict=feed_dict) util.per_class_acc(pred, label_batch) # if step % 100 == 0: # print("start validating.....") # total_val_loss = 0.0 # hist = np.zeros((self.config.NUM_CLASSES, self.config.NUM_CLASSES)) # for test_step in range(int(self.config.TEST_ITER)): # val_images_batch, val_labels_batch = sess.run(next_val_element) # # _val_loss, _val_pred = sess.run([loss, eval_prediction], feed_dict={ # self.train_data_node: val_images_batch, # self.train_label_node: val_labels_batch, # self.phase_train: True # }) # total_val_loss += _val_loss # hist += util.get_hist(_val_pred, val_labels_batch) # print("val loss: ", total_val_loss / self.config.TEST_ITER) # acc_total = np.diag(hist).sum() / hist.sum() # iu = np.diag(hist) / (hist.sum(1) + hist.sum(0) - np.diag(hist)) # test_summary_str = sess.run(average_summary, feed_dict={average_pl: total_val_loss / self.config.TEST_ITER}) # acc_summary_str = sess.run(acc_summary, feed_dict={acc_pl: acc_total}) # iu_summary_str = sess.run(iu_summary, feed_dict={iu_pl: np.nanmean(iu)}) # util.print_hist_summery(hist) # print(" end validating.... ") # # summary_str = sess.run(summary_op, feed_dict=feed_dict) # summary_writer.add_summary(summary_str, step) # summary_writer.add_summary(test_summary_str, step) # summary_writer.add_summary(acc_summary_str, step) # summary_writer.add_summary(iu_summary_str, step) # Save the model checkpoint periodically. if step % 1000 == 0 or (step + 1) == self.config.maxsteps: checkpoint_path = os.path.join(train_dir, 'model.ckpt') saver.save(sess, checkpoint_path, global_step=step) def visualize_prediction(self, meta_name = None, data_name = None): with tf.Session() as sess: self.add_placeholders() prediction = np.random.randint(2, size=self.train_label_node.shape) prediction.astype(np.float32) loss, eval_prediction = self.add_prediction_op() saver = tf.train.Saver() data_file_path = os.path.join(self.config.test_ckpt, data_name) if os.path.isfile(data_file_path): saver.restore(sess, data_file_path) else: raise Exception('restore variable data fail') # chkp.print_tensors_in_checkpoint_file(data_file_path, tensor_name = '', all_tensors = True) image_filenames, label_filenames = readfile.get_filename_list("../data/test_prediction", prefix="../data/test_prediction", is_train=False) print "image length {}".format(len(image_filenames)) image_paths = tf.convert_to_tensor(image_filenames, dtype=tf.string) dataset = tf.data.Dataset.from_tensor_slices(image_paths) dataset = dataset.map(readfile.map_fn_test, num_parallel_calls=8) dataset = dataset.batch(self.config.BATCH_SIZE) test_iterator = dataset.make_one_shot_iterator() test_next_element = test_iterator.get_next() image_batch = sess.run(test_next_element) feed_dict = { self.train_data_node: image_batch, self.phase_train: True } result = sess.run([eval_prediction], feed_dict)[0] print "begin to write the result as image back to folder..." for i in range(self.config.BATCH_SIZE): util.writemask(result[i],'mask_'+str(i)+".png") def get_submission_result(self, meta_name = None, data_name = None): is_first = True with tf.Session() as sess: self.add_placeholders() prediction = np.random.randint(2, size=self.train_label_node.shape) prediction.astype(np.float32) loss, eval_prediction = self.add_prediction_op() # meta_file_path = os.path.join(self.config.test_ckpt, meta_name) # if os.path.isfile(meta_file_path): # saver = tf.train.import_meta_graph(meta_file_path,clear_devices=True) # else: # raise Exception('restore graph meta data fail') saver = tf.train.Saver() data_file_path = os.path.join(self.config.test_ckpt, data_name) if os.path.isfile(data_file_path): saver.restore(sess, data_file_path) else: raise Exception('restore variable data fail') #chkp.print_tensors_in_checkpoint_file(data_file_path, tensor_name = '', all_tensors = True) image_filenames, label_filenames = readfile.get_filename_list("../data/val", prefix="../data/val", is_train=False) # the length of validation set; 2169 print "image length {}".format(len(image_filenames)) # construct the image dataset image_paths = tf.convert_to_tensor(image_filenames, dtype=tf.string) dataset = tf.data.Dataset.from_tensor_slices(image_paths) dataset = dataset.map(readfile.map_fn_test, num_parallel_calls=8) dataset = dataset.batch(self.config.BATCH_SIZE) test_iterator = dataset.make_one_shot_iterator() test_next_element = test_iterator.get_next() for i in range(len(image_filenames)/self.config.BATCH_SIZE): #for i in range(2): # for i in range(len(image_filenames)) image_batch = sess.run(test_next_element) #print image_batch.shape feed_dict = { self.train_data_node: image_batch, self.phase_train: True } if is_first: result = sess.run([eval_prediction],feed_dict)[0] # prediction = tf.stack([prediction, result]) print "prediction shape : {}".format(result.shape) is_first = False continue # 5,512,512,2 new_result = sess.run([eval_prediction],feed_dict)[0] #print "old result shape {}".format(np.asarray(result).shape) #print "new result shape {}".format(new_result.shape) result = np.concatenate([result, new_result],axis=0) #prediction = tf.stack([prediction, result]) print "prediction shape : {}".format(result.shape) # preprocess the prediction and product submission, prediction is [numexample, 512, 512, 2] util.create_submission('../data/subid2_1.csv', result, image_filenames) if __name__ == '__main__': segmodel = SegnetModel() # print all tensors in checkpoint file segmodel.visualize_prediction(meta_name="model.ckpt-38000.meta", data_name="model.ckpt-38000") #segmodel.get_submission_result()

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70474720aff7dcf7a5a4c61d68b746a8c74298dc

51,753

py

Python

pythonjs/runtime/builtins.py

bpmbank/PythonJS

591a80afd8233fb715493591db2b68f1748558d9

[ "BSD-3-Clause" ]

319

2015-01-02T11:34:16.000Z

2022-03-25T00:43:33.000Z

pythonjs/runtime/builtins.py

bpmbank/PythonJS

591a80afd8233fb715493591db2b68f1748558d9

[ "BSD-3-Clause" ]

10

2015-02-03T02:33:09.000Z

2021-11-09T21:41:00.000Z

pythonjs/runtime/builtins.py

bpmbank/PythonJS

591a80afd8233fb715493591db2b68f1748558d9

[ "BSD-3-Clause" ]

61

2015-01-02T12:01:56.000Z

2021-12-08T07:16:16.000Z

# PythonJS builtins # by Amirouche Boubekki and Brett Hartshorn - copyright 2013 # License: "New BSD" pythonjs.configure( runtime_exceptions=False ) pythonjs.configure( direct_operator='+' ) pythonjs.configure( direct_operator='*' ) pythonjs.configure( direct_keys=True ) _PythonJS_UID = 0 inline('IndexError = function(msg) {this.message = msg || "";}; IndexError.prototype = Object.create(Error.prototype); IndexError.prototype.name = "IndexError";') inline('KeyError = function(msg) {this.message = msg || "";}; KeyError.prototype = Object.create(Error.prototype); KeyError.prototype.name = "KeyError";') inline('ValueError = function(msg) {this.message = msg || "";}; ValueError.prototype = Object.create(Error.prototype); ValueError.prototype.name = "ValueError";') inline('AttributeError = function(msg) {this.message = msg || "";}; AttributeError.prototype = Object.create(Error.prototype);AttributeError.prototype.name = "AttributeError";') inline('RuntimeError = function(msg) {this.message = msg || "";}; RuntimeError.prototype = Object.create(Error.prototype);RuntimeError.prototype.name = "RuntimeError";') with lowlevel: def __getfast__(ob, attr): v = ob[ attr ] if v is undefined: raise AttributeError(attr) else: return v with javascript: def __wrap_function__(f): f.is_wrapper = True return f def __gpu_object(cls, struct_name, data_name): cls.prototype.__struct_name__ = struct_name cls.prototype.__struct_data__ = data_name with lowlevel: gpu = { 'object' : __gpu_object } def glsljit_runtime(header): return new( GLSLJITRuntime(header) ) class GLSLJITRuntime: def __init__(self, header): self.header = header self.shader = [] self.object_packagers = [] self.struct_types = {} self.glsltypes = ['vec2', 'vec3', 'vec4', 'mat4'] self.matrices = [] def compile_header(self): a = [] ## insert structs at top of header for sname in self.struct_types: if sname in self.glsltypes: pass else: a.push( self.struct_types[sname]['code'] ) ## calls get_global_id, see WebCLGL API docs. ## a.push('int matrix_index() { return int(get_global_id().y*%s.0); }' %self.matrices.length) a.push('int matrix_row() { return int(get_global_id().x*4.0); }') ## returns: 0, 1, 2, 3 ## first class array error, can not return an array, even when the size is known ## #a.push('float[3] floatN( float a, float b, float c) { float f[3]; f[0]=a; f[1]=b; f[2]=b; return f; }') ## these could be generated for each array size to reduce the mess in main, ## TODO it would be better to upload them as uniforms. #a.push('void floatN( float f[3], float a, float b, float c) { f[0]=a; f[1]=b; f[2]=b; }') ## the array can be declared in the header, but not filled with data here. #a.push('float XXX[3];') #a.push('floatN( XXX, 1.1, 2.2, 3.3 );') #a.push('XXX[0]=1.1;') a = '\n'.join(a) ## code in header could be methods that reference the struct types above. b = "\n".join(self.header) return '\n'.join([a,b]) def compile_main(self): return '\n'.join(self.shader) def push(self, s): self.shader.push(s) def define_structure(self, ob): struct_name = None #if Object.hasOwnProperty.call(ob,'__struct_name__'): if ob.__struct_name__: struct_name = ob.__struct_name__ if struct_name in self.struct_types: return struct_name arrays = [] floats = [] integers = [] structs = [] struct_type = [] ## fallback for javascript objects if struct_name and struct_name in self.glsltypes: return struct_name #for key in ob.keys(): for key in dir( ob ): if key.length==1 and key in '0123456789': raise RuntimeError(key) t = typeof( ob[key] ) if t=='object' and instanceof(ob[key], Array) and ob[key].length and typeof(ob[key][0])=='number': struct_type.push( 'ARY_'+key ) arrays.push(key) elif t=='number': struct_type.push( 'NUM_'+key) floats.push(key) elif instanceof(ob[key], Int16Array): struct_type.push( 'INT_'+key) if ob[key].length == 1: integers.push(key) else: pass ## TODO int16array elif t=='object' and ob[key].__struct_name__: struct_type.push( 'S_'+key) structs.push( key ) if ob[key].__struct_name__ not in self.struct_types: if ob[key].__struct_name__ in self.glsltypes: pass else: self.define_structure( ob[key] ) if struct_name is None: #print('DEGUG: new struct name', ob.__struct_name__) #print(ob) struct_name = ''.join( struct_type ) ob.__struct_name__ = struct_name if struct_name not in self.struct_types: member_list = [] for key in integers: member_list.append('int '+key+';') for key in floats: member_list.append('float '+key+';') for key in arrays: arr = ob[key] member_list.append('float '+key+'['+arr.length+'];') for key in structs: subtype = ob[key].__struct_name__ member_list.append( subtype+' '+key+';') if len(member_list)==0: raise RuntimeError(struct_name) members = ''.join(member_list) code = 'struct ' +struct_name+ ' {' +members+ '};' #print('-------struct glsl code-------') #print(code) #print('------------------------------') self.struct_types[ struct_name ] = { 'arrays' : arrays, 'floats' : floats, 'integers': integers, 'structs' : structs, 'code' : code } return struct_name def structure(self, ob, name): wrapper = None if instanceof(ob, Object): pass elif ob.__class__ is dict: wrapper = ob ob = ob[...] sname = self.define_structure(ob) if wrapper: wrapper.__struct_name__ = sname args = [] stype = self.struct_types[ sname ] # if stype is None: ## TODO fix me if sname not in self.struct_types: if sname in self.glsltypes: if sname == 'mat4': if ob.__struct_data__: o = ob[ ob.__struct_data__ ] else: o = ob for i in range(o.length): value = o[i] +'' if '.' not in value: value += '.0' args.push( value ) else: raise RuntimeError('no method to pack structure: ' +sname) has_arrays = False if stype: if stype['arrays'].length > 0: has_arrays = True for key in stype['integers']: args.push( ob[key][0]+'' ) for key in stype['floats']: value = ob[key] + '' if '.' not in value: value += '.0' args.push( value ) for key in stype['arrays']: #args.push( '{'+ob[key].toString()+ '}') ## this will not work ## arrays need to be assigned to a local variable before passing ## it to the struct constructor. aname = '_'+key+name self.array(ob[key], aname) args.push( aname ) for key in stype['structs']: aname = '_'+key+name self.structure(ob[key], aname) args.push( aname ) args = ','.join(args) if has_arrays: self.shader.push( sname + ' ' +name+ '=' +sname+ '(' +args+ ');' ) else: self.header.push( 'const ' + sname + ' ' +name+ '=' +sname+ '(' +args+ ');' ) return stype def int16array(self, ob, name): a = ['int ' + name + '[' + ob.length + ']'] i = 0 while i < ob.length: a.push(';'+name+'['+i+']='+ob[i]) i += 1 self.shader.push( ''.join(a) ) def array(self, ob, name): if instanceof(ob[0], Array): a = [] #'float ' + name + '[' + ob.length + ']'] i = 0 while i < ob.length: subarr = ob[i] subname = '%s_%s'%(name,i) if a.length==0: a.append('float ' + subname + '[' + subarr.length + ']') else: a.append(';float ' + subname + '[' + subarr.length + ']') j = 0 while j < subarr.length: v = subarr[j] + '' if '.' not in v: v += '.0' a.push(';'+subname+'['+j+']='+v) j += 1 i += 1 self.shader.push( ''.join(a) ) elif instanceof(ob[0], Object) or ob[0].__class__ is dict: i = 0 while i < ob.length: self.structure( ob[i], name+'_'+i) i += 1 else: a = ['float ' + name + '[' + ob.length + '];'] i = 0 while i < ob.length: a.push(name+'['+i+']='+ob[i] + ';') i += 1 self.shader.push( ''.join(a) ) def object(self, ob, name): for p in self.object_packagers: cls, func = p if instanceof(ob, cls): return func(ob) def unpack_array2d(self, arr, dims): if typeof(dims)=='number': return arr w,h = dims row = [] rows = [row] for value in arr: row.append(value) if row.length >= w: row = [] rows.append(row) rows.pop() if rows.length != h: print('ERROR: __unpack_array2d, invalid height.') return rows def unpack_vec4(self, arr, dims): if typeof(dims)=='number': w = dims h = 1 else: w,h = dims rows = [] i=0 for y in range(h): row = [] rows.append( row ) for x in range(w): vec = [] for j in range(4): vec.append( arr[i]) i += 1 row.append( vec ) if rows.length != h: print('ERROR: __unpack_vec4, invalid height.') return rows def unpack_mat4(self, arr): i = 0 for mat in self.matrices: for j in range(16): mat[j] = arr[i] i += 1 return self.matrices with lowlevel: def __getattr__(ob, a ): if ob.__getattr__: return JS("ob.__getattr__(a)") #else: # raise AttributeError(a) def __test_if_true__( ob ): if ob is True: return True elif ob is False: return False elif typeof(ob) == 'string': return ob.length != 0 elif not ob: return False elif instanceof(ob, Array): return ob.length != 0 elif typeof(ob) == 'function': return True elif ob.__class__ and ob.__class__ is dict: #isinstance(ob, dict): return Object.keys( ob[...] ).length != 0 elif instanceof(ob, Object): return Object.keys(ob).length != 0 else: return True def __replace_method(ob, a, b): ## this is required because string.replace in javascript only replaces the first occurrence if typeof(ob) == 'string': return ob.split(a).join(b) else: return ob.replace(a,b) def __split_method( ob, delim ): ## special case because calling string.split() without args its not the same as python, ## and we do not want to touch the default string.split implementation. if typeof(ob) == 'string': if delim is undefined: return ob.split(' ') else: return ob.split( delim ) else: if delim is undefined: return ob.split() else: return ob.split( delim ) with javascript: __dom_array_types__ = [] if typeof(NodeList) == 'function': ## NodeList is only available in browsers ## minimal dom array types common to allow browsers ## __dom_array_types__ = [ NodeList, FileList, DOMStringList, HTMLCollection, SVGNumberList, SVGTransformList] ## extra dom array types ## if typeof(DataTransferItemList) == 'function': ## missing in NodeWebkit __dom_array_types__.push( DataTransferItemList ) if typeof(HTMLAllCollection) == 'function': ## missing in Firefox __dom_array_types__.push( HTMLAllCollection ) if typeof(SVGElementInstanceList) == 'function':## missing in Firefox __dom_array_types__.push( SVGElementInstanceList ) if typeof(ClientRectList) == 'function': ## missing in Firefox-trunk __dom_array_types__.push( ClientRectList ) def __is_some_array( ob ): if __dom_array_types__.length > 0: for t in __dom_array_types__: if instanceof(ob, t): return True return False def __is_typed_array( ob ): if instanceof( ob, Int8Array ) or instanceof( ob, Uint8Array ): return True elif instanceof( ob, Int16Array ) or instanceof( ob, Uint16Array ): return True elif instanceof( ob, Int32Array ) or instanceof( ob, Uint32Array ): return True elif instanceof( ob, Float32Array ) or instanceof( ob, Float64Array ): return True else: return False def __js_typed_array( t, a ): if t == 'i': arr = new( Int32Array(a.length) ) arr.set( a ) return arr def __contains__( ob, a ): t = typeof(ob) if t == 'string': if ob.indexOf(a) == -1: return False else: return True elif t == 'number': raise TypeError elif __is_typed_array(ob): for x in ob: if x == a: return True return False elif ob.__contains__: return ob.__contains__(a) elif instanceof(ob, Object) and Object.hasOwnProperty.call(ob, a): return True else: return False def __add_op(a, b): ## 'number' is already checked before this gets called (ternary op) ## but it can still appear here when called from an inlined lambda t = typeof(a) if t == 'string' or t == 'number': return JS("a+b") elif instanceof(a, Array): c = [] c.extend(a) c.extend(b) return c elif a.__add__: return a.__add__(b) else: raise TypeError('invalid objects for addition') def __mul_op(a, b): t = typeof(a) if t == 'number': return JS("a * b") elif t == 'string': arr = [] for i in range(b): arr.append(a) return ''.join(arr) elif instanceof(a, Array): c = [] for i in range(b): c.extend(a) return c elif a.__mul__: return a.__mul__(b) else: raise TypeError('invalid objects for multiplication') def __jsdict( items ): d = JS("{}") for item in items: key = item[0] if instanceof(key, Array): key = JSON.stringify(key) elif key.__uid__: key = key.__uid__ d[ key ] = item[1] return d def __jsdict_get(ob, key, default_value): if instanceof(ob, Object): if instanceof(key, Array): key = JSON.stringify(key) if JS("key in ob"): return ob[key] return default_value else: ## PythonJS object instance ## ## this works because instances from PythonJS are created using Object.create(null) ## if default_value is not undefined: return JS("ob.get(key, default_value)") else: return JS("ob.get(key)") def __jsdict_set(ob, key, value): if instanceof(ob, Object): if instanceof(key, Array): key = JSON.stringify(key) ob[ key ] = value else: ## PythonJS object instance ## ## this works because instances from PythonJS are created using Object.create(null) ## JS("ob.set(key,value)") def __jsdict_keys(ob): if instanceof(ob, Object): ## in the case of tuple keys this would return stringified JSON instead of the original arrays, ## TODO, should this loop over the keys and convert the json strings back to objects? ## but then how would we know if a given string was json... special prefix character? return JS("Object.keys( ob )") else: ## PythonJS object instance ## ## this works because instances from PythonJS are created using Object.create(null) ## return JS("ob.keys()") def __jsdict_values(ob): if instanceof(ob, Object): arr = [] for key in ob: if ob.hasOwnProperty(key): value = ob[key] arr.push( value ) return arr else: ## PythonJS object instance ## ## this works because instances from PythonJS are created using Object.create(null) ## return JS("ob.values()") def __jsdict_items(ob): ## `ob.items is None` is for: "self.__dict__.items()" because self.__dict__ is not actually a dict if instanceof(ob, Object) or ob.items is undefined: ## in javascript-mode missing attributes do not raise AttributeError arr = [] for key in ob: if Object.hasOwnProperty.call(ob, key): value = ob[key] arr.push( [key,value] ) return arr else: ## PythonJS object instance ## return JS("ob.items()") def __jsdict_pop(ob, key, _default=None): if instanceof(ob, Array): if ob.length: ## note: javascript array.pop only pops the end of an array if key is undefined: return inline("ob.pop()") else: return ob.splice( key, 1 )[0] else: raise IndexError(key) elif instanceof(ob, Object): if JS("key in ob"): v = ob[key] JS("delete ob[key]") return v elif _default is undefined: raise KeyError(key) else: return _default else: ## PythonJS object instance ## ## this works because instances from PythonJS are created using Object.create(null) ## return JS("ob.pop(key, _default)") def dir(ob): if instanceof(ob, Object): return JS("Object.keys( ob )") else: return __object_keys__(ob) def __object_keys__(ob): ''' notes: . Object.keys(ob) will not work because we create PythonJS objects using `Object.create(null)` . this is different from Object.keys because it traverses the prototype chain. ''' arr = [] JS('for (var key in ob) { arr.push(key) }') return arr def __bind_property_descriptors__(o, klass): for name in klass.__properties__: desc = {"enumerable":True} prop = klass.__properties__[ name ] if prop['get']: desc['get'] = __generate_getter__(klass, o, name) if prop['set']: desc['set'] = __generate_setter__(klass, o, name) Object.defineProperty( o, name, desc ) for base in klass.__bases__: __bind_property_descriptors__(o, base) def __generate_getter__(klass, o, n): return lambda : klass.__properties__[ n ]['get']([o],{}) def __generate_setter__(klass, o, n): return lambda v: klass.__properties__[ n ]['set']([o,v],{}) def __sprintf(fmt, args): ## note: '%sXXX%s'.split().length != args.length ## because `%s` at the start or end will split to empty chunks ## if instanceof(args, Array): chunks = fmt.split('%s') arr = [] for i,txt in enumerate(chunks): arr.append( txt ) if i >= args.length: break item = args[i] if typeof(item) == 'string': arr.append( item ) elif typeof(item) == 'number': arr.append( ''+item ) else: arr.append( Object.prototype.toString.call(item) ) return ''.join(arr) else: return fmt.replace('%s', args) def __create_class__(class_name, parents, attrs, props): """Create a PythonScript class""" #if attrs.__metaclass__: # metaclass = attrs.__metaclass__ # attrs.__metaclass__ = None # return metaclass([class_name, parents, attrs]) klass = Object.create(null) klass.__bases__ = parents klass.__name__ = class_name #klass.__dict__ = attrs klass.__unbound_methods__ = Object.create(null) klass.__all_method_names__ = [] klass.__properties__ = props klass.__attributes__ = attrs for key in attrs: if typeof( attrs[key] ) == 'function': klass.__all_method_names__.push( key ) f = attrs[key] if hasattr(f, 'is_classmethod') and f.is_classmethod: pass elif hasattr(f, 'is_staticmethod') and f.is_staticmethod: pass else: klass.__unbound_methods__[key] = attrs[key] if key == '__getattribute__': continue klass[key] = attrs[key] ## this is needed for fast lookup of property names in __set__ ## klass.__setters__ = [] klass.__getters__ = [] for name in klass.__properties__: prop = klass.__properties__[name] klass.__getters__.push( name ) if prop['set']: klass.__setters__.push( name ) for base in klass.__bases__: Array.prototype.push.apply( klass.__getters__, base.__getters__ ) Array.prototype.push.apply( klass.__setters__, base.__setters__ ) Array.prototype.push.apply( klass.__all_method_names__, base.__all_method_names__ ) def __call__(): """Create a PythonJS object""" object = Object.create(null) ## this makes pythonjs object not compatible with things like: Object.hasOwnProperty object.__class__ = klass object.__dict__ = object ## we need __dict__ so that __setattr__ can still set attributes using `old-style`: self.__dict__[n]=x #Object.defineProperty( # object, # '__dict__', # {enumerable:False, value:object, writeable:False, configurable:False} #) has_getattribute = False has_getattr = False for name in klass.__all_method_names__: if name == '__getattribute__': has_getattribute = True elif name == '__getattr__': has_getattr = True else: wrapper = __get__(object, name) if not wrapper.is_wrapper: print 'RUNTIME ERROR: failed to get wrapper for:',name ## to be safe the getters come after other methods are cached ## if has_getattr: __get__(object, '__getattr__') if has_getattribute: __get__(object, '__getattribute__') __bind_property_descriptors__(object, klass) if object.__init__: object.__init__.apply(this, arguments) #object.__init__.call(this,args, kwargs) return object __call__.is_wrapper = True klass.__call__ = __call__ return klass def type(ob_or_class_name, bases=None, class_dict=None): ''' type(object) -> the object's type type(name, bases, dict) -> a new type ## broken? - TODO test ''' with javascript: if bases is None and class_dict is None: return ob_or_class_name.__class__ else: return create_class(ob_or_class_name, bases, class_dict) ## TODO rename create_class to _pyjs_create_class def hasattr(ob, attr): ## TODO check parent classes for attr with javascript: return Object.hasOwnProperty.call(ob, attr) def getattr(ob, attr, property=False): with javascript: if property: prop = _get_upstream_property( ob.__class__, attr ) if prop and prop['get']: return prop['get']( [ob], {} ) else: print "ERROR: getattr property error", prop else: return __get__(ob, attr) def setattr(ob, attr, value, property=False): with javascript: if property: prop = _get_upstream_property( ob.__class__, attr ) if prop and prop['set']: prop['set']( [ob, value], {} ) else: print "ERROR: setattr property error", prop else: __set__(ob, attr, value) def issubclass(C, B): if C is B: return True with javascript: bases = C.__bases__ ## js-array i = 0 while i < bases.length: if issubclass( bases[i], B ): return True i += 1 return False def isinstance( ob, klass): with javascript: if ob is undefined or ob is null: return False elif instanceof(ob, Array) and klass is list: return True #elif klass is dict and instanceof(ob, Object): ## this is safe because instances created with Object.create(null) are not instances-of Object # if instanceof(ob, Array): # return False # elif ob.__class__: # return False # else: # return True elif not Object.hasOwnProperty.call(ob, '__class__'): return False ob_class = ob.__class__ if ob_class is undefined: return False else: return issubclass( ob_class, klass ) def int(a): with javascript: a = Math.round(a) if isNaN(a): raise ValueError('not a number') return a with javascript: def int16(a): ## used by glsljit when packing structs. arr = new(Int16Array(1)) arr[0]=a return arr def float(a): with javascript: if typeof(a)=='string': if a.lower()=='nan': return NaN elif a.lower()=='inf': return Infinity b = Number(a) if isNaN(b): ## invalid strings also convert to NaN, throw error ## raise ValueError('can not convert to float: '+a) return b def round(a, places=0): with javascript: b = '' + a if b.indexOf('.') == -1: return a else: ## this could return NaN with large numbers and large places, ## TODO check for NaN and instead fallback to `a.toFixed(places)` p = Math.pow(10, places) return Math.round(a * p) / p def str(s): return ''+s def _setup_str_prototype(): ''' Extend JavaScript String.prototype with methods that implement the Python str API. The decorator @String.prototype.[name] assigns the function to the prototype, and ensures that the special 'this' variable will work. ''' with javascript: @String.prototype.__contains__ def func(a): if this.indexOf(a) == -1: return False else: return True @String.prototype.get def func(index): if index < 0: return this[ this.length + index ] else: return this[ index ] @String.prototype.__iter__ def func(self): with python: return Iterator(this, 0) @String.prototype.__getitem__ def func(idx): if idx < 0: return this[ this.length + idx ] else: return this[ idx ] @String.prototype.__len__ def func(): return this.length @String.prototype.__getslice__ def func(start, stop, step): if start is undefined and stop is undefined and step == -1: return this.split('').reverse().join('') else: if stop < 0: stop = this.length + stop return this.substring(start, stop) @String.prototype.splitlines def func(): return this.split('\n') @String.prototype.strip def func(): return this.trim() ## missing in IE8 @String.prototype.startswith def func(a): if this.substring(0, a.length) == a: return True else: return False @String.prototype.endswith def func(a): if this.substring(this.length-a.length, this.length) == a: return True else: return False @String.prototype.join def func(a): out = '' if instanceof(a, Array): arr = a else: arr = a[...] i = 0 for value in arr: out += value i += 1 if i < arr.length: out += this return out @String.prototype.upper def func(): return this.toUpperCase() @String.prototype.lower def func(): return this.toLowerCase() @String.prototype.index def func(a): i = this.indexOf(a) if i == -1: raise ValueError(a + ' - not in string') return i @String.prototype.find def func(a): return this.indexOf(a) @String.prototype.isdigit def func(): digits = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] for char in this: if char in digits: pass else: return False return True @String.prototype.isnumber def func(): digits = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '.'] for char in this: if char in digits: pass else: return False return True ## TODO - for now these are just dummy functions. @String.prototype.decode def func(encoding): return this @String.prototype.encode def func(encoding): return this @String.prototype.format def func(fmt): r = this keys = Object.keys(fmt) for key in keys: r = r.split(key).join(fmt[key]) r = r.split('{').join('').split('}').join('') return r _setup_str_prototype() ## note Arrays in javascript by default sort by string order, even if the elements are numbers. with javascript: def __sort_method(ob): if instanceof(ob, Array): def f(a,b): if a < b: return -1 elif a > b: return 1 else: return 0 return JS("ob.sort( f )") else: return JS("ob.sort()") def _setup_array_prototype(): with javascript: @Array.prototype.jsify def func(): i = 0 while i < this.length: item = this[ i ] if typeof(item) == 'object': if item.jsify: this[ i ] = item.jsify() i += 1 return this @Array.prototype.__contains__ def func(a): if this.indexOf(a) == -1: return False else: return True @Array.prototype.__len__ def func(): return this.length @Array.prototype.get def func(index): return this[ index ] @Array.prototype.__getitem__ def __getitem__(index): if index < 0: index = this.length + index return this[index] @Array.prototype.__setitem__ def __setitem__(index, value): if index < 0: index = this.length + index this[ index ] = value @Array.prototype.__iter__ def func(): with python: return Iterator(this, 0) @Array.prototype.__getslice__ def func(start, stop, step): arr = [] start = start | 0 if stop is undefined: stop = this.length if start < 0: start = this.length + start if stop < 0: stop = this.length + stop #reverse = step < 0 ## in javascript `null<0` and `undefined<0` are false #reverse = False if typeof(step)=='number': #reverse = step < 0 #if reverse: if step < 0: #step = Math.abs(step) i = start while i >= 0: arr.push( this[i] ) i += step return arr else: i = start n = stop while i < n: arr.push( this[i] ) i += step return arr else: i = start n = stop while i < n: #arr[ i ] = this[i] ## slower in chrome arr.push( this[i] ) i += 1 ## this gets optimized to i++ return arr #if reverse: # arr.reverse() #if step == 1: # arr = new(Array(this.length)) # i = 0 # while i < this.length: # arr[ i ] = this[i] # i += 1 ## this gets optimized to i++ #else: # arr = [] # i = 0 # while i < this.length: # arr.push( this[i] ) # i += step #if start is undefined and stop is undefined: # if reverse: arr.reverse() #elif reverse: # arr = arr.slice(stop, start+1) # arr.reverse() #else: # #if stop < 0: ## mozilla spec says negative indices are supported # # stop = arr.length + stop # arr = arr.slice(start, stop) #return arr @Array.prototype.__setslice__ def func(start, stop, step, items): if start is undefined: start = 0 if stop is undefined: stop = this.length arr = [start, stop-start] for item in items: arr.push( item ) this.splice.apply(this, arr ) @Array.prototype.append def func(item): this.push( item ) return this @Array.prototype.extend def extend(other): for obj in other: this.push(obj) return this @Array.prototype.remove def func(item): index = this.indexOf( item ) this.splice(index, 1) @Array.prototype.insert def insert(index, obj): if index < 0: index = this.length + index this.splice(index, 0, obj) @Array.prototype.index def index(obj): return this.indexOf(obj) @Array.prototype.count def count(obj): a = 0 for item in this: if item is obj: ## note that `==` will not work here, `===` is required for objects a += 1 return a ## set-like features ## @Array.prototype.bisect def func(x, low, high): if low is undefined: low = 0 if high is undefined: high = this.length while low < high: a = low+high mid = Math.floor(a/2) if x < this[mid]: high = mid else: low = mid + 1 return low ## `-` operator @Array.prototype.difference def func(other): f = lambda i: other.indexOf(i)==-1 return this.filter( f ) ## `&` operator @Array.prototype.intersection def func(other): f = lambda i: other.indexOf(i)!=-1 return this.filter( f ) ## `<=` operator @Array.prototype.issubset def func(other): for item in this: if other.indexOf(item) == -1: return False return True ## non-standard utils ## @Array.prototype.copy def func(): arr = [] i = 0 while i < this.length: arr.push( this[i] ) i += 1 return arr _setup_array_prototype() def _setup_nodelist_prototype(): with javascript: @NodeList.prototype.__contains__ def func(a): if this.indexOf(a) == -1: return False else: return True @NodeList.prototype.__len__ def func(): return this.length @NodeList.prototype.get def func(index): return this[ index ] @NodeList.prototype.__getitem__ def __getitem__(index): if index < 0: index = this.length + index return this[index] @NodeList.prototype.__setitem__ def __setitem__(index, value): if index < 0: index = this.length + index this[ index ] = value @NodeList.prototype.__iter__ def func(): with python: return Iterator(this, 0) @NodeList.prototype.index def index(obj): return this.indexOf(obj) if __NODEJS__ == False and __WEBWORKER__ == False: _setup_nodelist_prototype() def bisect(a, x, low=None, high=None): ## bisect function from bisect module of the stdlib with javascript: return a.bisect(x, low, high) def range(num, stop, step): """Emulates Python's range function""" if stop is not undefined: i = num num = stop else: i = 0 if step is undefined: step = 1 with javascript: arr = [] while i < num: arr.push(i) i += step return arr def xrange(num, stop, step): return range(num, stop, step) def sum( arr ): a = 0 for b in arr: a += b return a class StopIteration: ## DEPRECATED pass def len(ob): with javascript: if instanceof(ob, Array): return ob.length elif __is_typed_array(ob): return ob.length elif instanceof(ob, ArrayBuffer): return ob.byteLength elif ob.__len__: return ob.__len__() else: #elif instanceof(ob, Object): return Object.keys(ob).length def next(obj): return obj.next() def map(func, objs): with javascript: arr = [] for ob in objs: v = func(ob) with javascript: arr.push( v ) return arr def filter(func, objs): with javascript: arr = [] for ob in objs: if func( ob ): with javascript: arr.push( ob ) return arr def min( lst ): a = None for value in lst: if a is None: a = value elif value < a: a = value return a def max( lst ): a = None for value in lst: if a is None: a = value elif value > a: a = value return a def abs( num ): return JS('Math.abs(num)') def ord( char ): return JS('char.charCodeAt(0)') def chr( num ): return JS('String.fromCharCode(num)') with javascript: class __ArrayIterator: def __init__(self, arr, index): self.arr = arr self.index = index self.length = arr.length def next(self): index = self.index self.index += 1 arr = self.arr return JS('arr[index]') class Iterator: ## rather than throwing an exception, it could be more optimized to have the iterator set a done flag, ## and another downside is having the try/catch around this makes errors in in the loop go slient. def __init__(self, obj, index): self.obj = obj self.index = index self.length = len(obj) self.obj_get = obj.get ## cache this for speed def next(self): with javascript: index = self.index self.index += 1 return self.obj_get( [index], {} ) def tuple(a): ## TODO tuple needs a solution for dict keys with javascript: if Object.keys(arguments).length == 0: #arguments.length == 0: return [] elif instanceof(a, Array): return a.slice() elif typeof(a) == 'string': return a.split('') else: print a print arguments raise TypeError def list(a): with javascript: if Object.keys(arguments).length == 0: #arguments.length == 0: return [] elif instanceof(a, Array): return a.slice() elif typeof(a) == 'string': return a.split('') else: print a print arguments raise TypeError with javascript: def __tuple_key__(arr): r = [] i = 0 while i < arr.length: item = arr[i] t = typeof(item) if t=='string': r.append( "'"+item+"'") elif instanceof(item, Array): r.append( __tuple_key__(item) ) elif t=='object': if item.__uid__ is undefined: raise KeyError(item) r.append( item.__uid__ ) else: r.append( item ) i += 1 return r.join(',') class dict: # http://stackoverflow.com/questions/10892322/javascript-hashtable-use-object-key # using a function as a key is allowed, but would waste memory because it gets converted to a string # http://stackoverflow.com/questions/10858632/are-functions-valid-keys-for-javascript-object-properties def __init__(self, js_object=None, pointer=None): with javascript: self[...] = {} if pointer is not None: self[...] = pointer elif js_object: ob = js_object if instanceof(ob, Array): for o in ob: with lowlevel: if instanceof(o, Array): k= o[0]; v= o[1] else: k= o['key']; v= o['value'] try: self.__setitem__( k,v ) except KeyError: raise KeyError('error in dict init, bad key') elif isinstance(ob, dict): for key in ob.keys(): value = ob[ key ] self.__setitem__( key, value ) else: print 'ERROR init dict from:', js_object raise TypeError def jsify(self): #keys = Object.keys( self[...] ) ## TODO check how this got broken, this should always be a low-level object? keys = __object_keys__( self[...] ) for key in keys: value = self[...][key] if typeof(value) == 'object': if hasattr(value, 'jsify'): self[...][key] = value.jsify() elif typeof(value) == 'function': raise RuntimeError("can not jsify function") return self[...] def copy(self): return dict( self ) def clear(self): with javascript: self[...] = {} def has_key(self, key): __dict = self[...] if JS("typeof(key) === 'object' || typeof(key) === 'function'"): # Test undefined because it can be in the dict key = key.__uid__ if JS("key in __dict"): return True else: return False def update(self, other): for key in other: self.__setitem__( key, other[key] ) def items(self): arr = [] for key in self.keys(): arr.append( [key, self[key]] ) return arr def get(self, key, _default=None): try: return self[key] except: return _default def set(self, key, value): self.__setitem__(key, value) def __len__(self): __dict = self[...] return JS('Object.keys(__dict).length') def __getitem__(self, key): ''' note: `"4"` and `4` are the same key in javascript, is there a sane way to workaround this, that can remain compatible with external javascript? ''' with javascript: __dict = self[...] err = False if instanceof(key, Array): #key = JSON.stringify( key ) ## fails on objects with circular references ## key = __tuple_key__(key) elif JS("typeof(key) === 'object' || typeof(key) === 'function'"): # Test undefined because it can be in the dict if JS("key.__uid__ && key.__uid__ in __dict"): return JS('__dict[key.__uid__]') else: err = True if __dict and JS("key in __dict"): return JS('__dict[key]') else: err = True if err: msg = "missing key: %s -\n" %key raise KeyError(__dict.keys()) def __setitem__(self, key, value): with javascript: if key is undefined: raise KeyError('undefined is invalid key type') if key is null: raise KeyError('null is invalid key type') __dict = self[...] if instanceof(key, Array): #key = JSON.stringify( key ) ## fails on objects with circular references ## key = __tuple_key__(key) if key is undefined: raise KeyError('undefined is invalid key type (tuple)') inline( '__dict[key] = value') elif JS("typeof(key) === 'object' || typeof(key) === 'function'"): if JS("key.__uid__ === undefined"): # "" is needed so that integers can also be used as keys # JS(u"key.__uid__ = '' + _PythonJS_UID++") JS('__dict[key.__uid__] = value') else: JS('__dict[key] = value') def keys(self): with lowlevel: return Object.keys( self[...] ) def pop(self, key, d=None): v = self.get(key, None) if v is None: return d else: js_object = self[...] JS("delete js_object[key]") return v def values(self): with javascript: keys = Object.keys( self[...] ) out = [] for key in keys: out.push( self[...][key] ) return out def __contains__(self, value): try: self[value] return True except: return False def __iter__(self): return Iterator(self.keys(), 0) def set(a): ''' This returns an array that is a minimal implementation of set. Often sets are used simply to remove duplicate entries from a list, and then it get converted back to a list, it is safe to use fastset for this. The array prototype is overloaded with basic set functions: difference intersection issubset Note: sets in Python are not subscriptable, but can be iterated over. Python docs say that set are unordered, some programs may rely on this disorder for randomness, for sets of integers we emulate the unorder only uppon initalization of the set, by masking the value by bits-1. Python implements sets starting with an array of length 8, and mask of 7, if set length grows to 6 (3/4th), then it allocates a new array of length 32 and mask of 31. This is only emulated for arrays of integers up to an array length of 1536. ''' with javascript: hashtable = null if a.length <= 1536: hashtable = {} keys = [] if a.length < 6: ## hash array length 8 mask = 7 elif a.length < 22: ## 32 mask = 31 elif a.length < 86: ## 128 mask = 127 elif a.length < 342: ## 512 mask = 511 else: ## 2048 mask = 2047 fallback = False if hashtable: for b in a: if typeof(b)=='number' and b is (b|0): ## set if integer key = b & mask hashtable[ key ] = b keys.push( key ) else: fallback = True break else: fallback = True s = [] if fallback: for item in a: if s.indexOf(item) == -1: s.push( item ) else: keys.sort() for key in keys: s.push( hashtable[key] ) return s def frozenset(a): return set(a) class array: ## note that class-level dicts can only be used after the dict class has been defined above, ## however, we can still not rely on using a dict here because dict creation relies on get_attribute, ## and get_attribute relies on __NODEJS__ global variable to be set to False when inside NodeJS, ## to be safe this is changed to use JSObjects with javascript: typecodes = { 'c': 1, # char 'b': 1, # signed char 'B': 1, # unsigned char 'u': 2, # unicode 'h': 2, # signed short 'H': 2, # unsigned short 'i': 4, # signed int 'I': 4, # unsigned int 'l': 4, # signed long 'L': 4, # unsigned long 'f': 4, # float 'd': 8, # double 'float32':4, 'float16':2, 'float8' :1, 'int32' :4, 'uint32' :4, 'int16' :2, 'uint16' :2, 'int8' :1, 'uint8' :1, } typecode_names = { 'c': 'Int8', 'b': 'Int8', 'B': 'Uint8', 'u': 'Uint16', 'h': 'Int16', 'H': 'Uint16', 'i': 'Int32', 'I': 'Uint32', #'l': 'TODO', #'L': 'TODO', 'f': 'Float32', 'd': 'Float64', 'float32': 'Float32', 'float16': 'Int16', 'float8' : 'Int8', 'int32' : 'Int32', 'uint32' : 'Uint32', 'int16' : 'Int16', 'uint16' : 'Uint16', 'int8' : 'Int8', 'uint8' : 'Uint8', } def __init__(self, typecode, initializer=None, little_endian=False): self.typecode = typecode self.itemsize = self.typecodes[ typecode ] self.little_endian = little_endian if initializer: self.length = len(initializer) self.bytes = self.length * self.itemsize if self.typecode == 'float8': self._scale = max( [abs(min(initializer)), max(initializer)] ) self._norm_get = self._scale / 127 ## half 8bits-1 self._norm_set = 1.0 / self._norm_get elif self.typecode == 'float16': self._scale = max( [abs(min(initializer)), max(initializer)] ) self._norm_get = self._scale / 32767 ## half 16bits-1 self._norm_set = 1.0 / self._norm_get else: self.length = 0 self.bytes = 0 size = self.bytes buff = JS('new ArrayBuffer(size)') self.dataview = JS('new DataView(buff)') self.buffer = buff self.fromlist( initializer ) def __len__(self): return self.length def __contains__(self, value): #lst = self.to_list() #return value in lst ## this old style is deprecated arr = self.to_array() with javascript: if arr.indexOf(value) == -1: return False else: return True def __getitem__(self, index): step = self.itemsize offset = step * index dataview = self.dataview func_name = 'get'+self.typecode_names[ self.typecode ] func = JS('dataview[func_name].bind(dataview)') if offset < self.bytes: value = JS('func(offset)') if self.typecode == 'float8': value = value * self._norm_get elif self.typecode == 'float16': value = value * self._norm_get return value else: raise IndexError(index) def __setitem__(self, index, value): step = self.itemsize if index < 0: index = self.length + index -1 ## TODO fixme offset = step * index dataview = self.dataview func_name = 'set'+self.typecode_names[ self.typecode ] func = JS('dataview[func_name].bind(dataview)') if offset < self.bytes: if self.typecode == 'float8': value = value * self._norm_set elif self.typecode == 'float16': value = value * self._norm_set JS('func(offset, value)') else: raise IndexError(index) def __iter__(self): return Iterator(self, 0) def get(self, index): return self[ index ] def fromlist(self, lst): length = len(lst) step = self.itemsize typecode = self.typecode size = length * step dataview = self.dataview func_name = 'set'+self.typecode_names[ typecode ] func = JS('dataview[func_name].bind(dataview)') if size <= self.bytes: i = 0; offset = 0 while i < length: item = lst[i] if typecode == 'float8': item *= self._norm_set elif typecode == 'float16': item *= self._norm_set JS('func(offset,item)') offset += step i += 1 else: raise TypeError def resize(self, length): buff = self.buffer source = JS('new Uint8Array(buff)') new_size = length * self.itemsize new_buff = JS('new ArrayBuffer(new_size)') target = JS('new Uint8Array(new_buff)') JS('target.set(source)') self.length = length self.bytes = new_size self.buffer = new_buff self.dataview = JS('new DataView(new_buff)') def append(self, value): length = self.length self.resize( self.length + 1 ) self[ length ] = value def extend(self, lst): ## TODO optimize for value in lst: self.append( value ) def to_array(self): arr = JSArray() i = 0 while i < self.length: item = self[i] JS('arr.push( item )') i += 1 return arr def to_list(self): return self.to_array() def to_ascii(self): string = '' arr = self.to_array() i = 0; length = arr.length while i < length: JS('var num = arr[i]') JS('var char = String.fromCharCode(num)') string += char i += 1 return string ## file IO ## class file: ''' TODO, support multiple read/writes. Currently this just reads all data, and writes all data. ''' def __init__(self, path, flags): self.path = path if flags == 'rb': self.flags = 'r' self.binary = True elif flags == 'wb': self.flags = 'w' self.binary = True else: self.flags = flags self.binary = False self.flags = flags def read(self, binary=False): _fs = require('fs') path = self.path with javascript: if binary or self.binary: return _fs.readFileSync( path, encoding=None ) else: return _fs.readFileSync( path, {'encoding':'utf8'} ) def write(self, data, binary=False): _fs = require('fs') path = self.path with javascript: if binary or self.binary: binary = binary or self.binary if binary == 'base64': ## TODO: fixme, something bad in this if test #print('write base64 data') buff = new Buffer(data, 'base64') _fs.writeFileSync( path, buff, {'encoding':None}) else: #print('write binary data') #print(binary) _fs.writeFileSync( path, data, {'encoding':None}) else: #print('write utf8 data') _fs.writeFileSync( path, data, {'encoding':'utf8'} ) def close(self): pass def __open__( path, mode=None): ## this can not be named `open` because it replaces `window.open` return file( path, mode ) with javascript: ## mini json library ## json = { 'loads': lambda s: JSON.parse(s), 'dumps': lambda o: JSON.stringify(o) } def __get_other_workers_with_shared_arg( worker, ob ): a = [] for b in threading.workers: other = b['worker'] args = b['args'] if other is not worker: for arg in args: if arg is ob: if other not in a: a.append( other ) return a threading = {'workers': [], '_blocking_callback':None } def __start_new_thread(f, args): worker = new(Worker(f)) worker.__uid__ = len( threading.workers ) threading.workers.append( {'worker':worker,'args':args} ) def func(event): #print('got signal from thread') #print(event.data) if event.data.type == 'terminate': worker.terminate() elif event.data.type == 'call': res = __module__[ event.data.function ].apply(null, event.data.args) if res is not None and res is not undefined: worker.postMessage({'type':'return_to_blocking_callback', 'result':res}) elif event.data.type == 'append': #print('got append event') a = args[ event.data.argindex ] a.push( event.data.value ) for other in __get_other_workers_with_shared_arg(worker, a): other.postMessage( {'type':'append', 'argindex':event.data.argindex, 'value':event.data.value} ) elif event.data.type == '__setitem__': #print('got __setitem__ event') a = args[ event.data.argindex ] value = event.data.value if a.__setitem__: a.__setitem__(event.data.index, value) else: a[event.data.index] = value for other in __get_other_workers_with_shared_arg(worker, a): #print('relay __setitem__') other.postMessage( {'type':'__setitem__', 'argindex':event.data.argindex, 'key':event.data.index, 'value':event.data.value} ) else: raise RuntimeError('unknown event') worker.onmessage = func jsargs = [] for i,arg in enumerate(args): if arg.jsify: jsargs.append( arg.jsify() ) else: jsargs.append( arg ) if instanceof(arg, Array): __gen_worker_append(worker, arg, i) worker.postMessage( {'type':'execute', 'args':jsargs} ) return worker def __gen_worker_append(worker, ob, index): def append(item): #print('posting to thread - append') worker.postMessage( {'type':'append', 'argindex':index, 'value':item} ) ob.push( item ) Object.defineProperty(ob, "append", {'enumerable':False, 'value':append, 'writeable':True, 'configurable':True}) ######## webworker client ######### def __webworker_wrap(ob, argindex): if instanceof(ob, Array): #ob.__argindex__ = argindex def func(index, item): #print('posting to parent setitem') postMessage({'type':'__setitem__', 'index':index, 'value':item, 'argindex':argindex}) Array.prototype.__setitem__.call(ob, index, item) ## this can raise RangeError recursive overflow if the worker entry point is a recursive function Object.defineProperty(ob, "__setitem__", {"enumerable":False, "value":func, "writeable":True, "configurable":True}) #ob.__setitem__ =func def func(item): #print('posting to parent append') postMessage({'type':'append', 'value':item, 'argindex':argindex}) Array.prototype.push.call(ob, item) Object.defineProperty(ob, "append", {"enumerable":False, "value":func, "writeable":True, "configurable":True}) #ob.append = func elif typeof(ob) == 'object': def func(key, item): #print('posting to parent setitem object') postMessage({'type':'__setitem__', 'index':key, 'value':item, 'argindex':argindex}) ob[ key ] = item #ob.__setitem__ = func Object.defineProperty(ob, "__setitem__", {"enumerable":False, "value":func, "writeable":True, "configurable":True}) return ob ######### simple RPC API ######### def __rpc__( url, func, args): req = new( XMLHttpRequest() ) req.open('POST', url, False) ## false is sync req.setRequestHeader("Content-Type", "application/json;charset=UTF-8") req.send( JSON.stringify({'call':func, 'args':args}) ) return JSON.parse( req.responseText ) def __rpc_iter__( url, attr): req = new( XMLHttpRequest() ) req.open('POST', url, False) ## false is sync req.setRequestHeader("Content-Type", "application/json;charset=UTF-8") req.send( JSON.stringify({'iter':attr}) ) return JSON.parse( req.responseText ) def __rpc_set__( url, attr, value): req = new( XMLHttpRequest() ) req.open('POST', url, False) ## false is sync req.setRequestHeader("Content-Type", "application/json;charset=UTF-8") req.send( JSON.stringify({'set':attr, 'value':value}) ) def __rpc_get__( url, attr): req = new( XMLHttpRequest() ) req.open('POST', url, False) ## false is sync req.setRequestHeader("Content-Type", "application/json;charset=UTF-8") req.send( JSON.stringify({'get':attr}) ) return JSON.parse( req.responseText )

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704898ebecbbd9155f7d6b166429c2459741b79f

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Python

feedmapper/migrations/0001_initial.py

benwhalley/django-feedmapper

23eeabeda4d7ab6c3404f96348905c2ca12e964e

[ "BSD-3-Clause" ]

null

feedmapper/migrations/0001_initial.py

benwhalley/django-feedmapper

23eeabeda4d7ab6c3404f96348905c2ca12e964e

[ "BSD-3-Clause" ]

null

feedmapper/migrations/0001_initial.py

benwhalley/django-feedmapper

23eeabeda4d7ab6c3404f96348905c2ca12e964e

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.15 on 2018-11-26 10:42 from __future__ import unicode_literals from django.db import migrations, models import jsonfield.fields class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Mapping', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('label', models.CharField(help_text='Label for your reference', max_length=255, verbose_name='label')), ('source', models.CharField(help_text='The source feed for your data', max_length=255, verbose_name='source')), ('parser', models.CharField(choices=[(b'feedmapper.parsers.AtomParser', b'Atom'), (b'feedmapper.parsers.XMLParser', b'XML')], help_text='Which parser to use when synchronizing', max_length=255, verbose_name='parser')), ('purge', models.BooleanField(default=False, help_text='Purge existing items on sync?', verbose_name='purge')), ('data_map', jsonfield.fields.JSONField(default=dict, verbose_name='data map')), ('notification_recipients', models.TextField(blank=True, help_text='Specify one email address per line to be notified of parsing errors.', verbose_name='notification recipients')), ('parse_attempted', models.DateTimeField(blank=True, null=True, verbose_name='parse attempted')), ('parse_succeeded', models.BooleanField(verbose_name='parse succeeded')), ('parse_log', models.TextField(blank=True, verbose_name='parse log')), ], ), ]

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7048c4e22df4e28d615e6cb3c66edb19918a9647

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py

Python

static/_source.py

Manazius/blacksmith-bot

c31ebdc8f8df1ab79ea1cc833e2c5c2266a231ea

[ "Apache-2.0" ]

3

2015-10-15T15:40:17.000Z

2021-06-08T05:39:21.000Z

static/_source.py

Manazius/blacksmith-bot

c31ebdc8f8df1ab79ea1cc833e2c5c2266a231ea

[ "Apache-2.0" ]

1

2019-04-06T11:54:56.000Z

2019-04-07T00:57:49.000Z

static/_source.py

Manazius/blacksmith-bot

c31ebdc8f8df1ab79ea1cc833e2c5c2266a231ea

[ "Apache-2.0" ]

3

2015-10-26T14:49:57.000Z

2018-03-04T15:34:11.000Z

# coding: utf-8 # BlackSmith general configuration file # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- # Jabber server to connect SERVER = 'example.com' # Connecting Port PORT = 5222 # Jabber server`s connecting Host HOST = 'example.com' # Using TLS (True - to enable, False - to disable) SECURE = True # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- # User`s account USERNAME = 'username' # Jabber ID`s Password PASSWORD = 'password' # Resourse (please don`t touch it) RESOURCE = u'simpleApps' # You can write unicode symbols here # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- # Default chatroom nick DEFAULT_NICK = u'BlackSmith-m.1' # You can write unicode symbols here # Groupchat message size limit CHAT_MSG_LIMIT = 1024 # Private/Roster message size limit PRIV_MSG_LIMIT = 2024 # Incoming message size limit INC_MSG_LIMIT = 8960 # Working without rights of moder (True - to enable, False - to disable) MSERVE = False # Jabber account of bot`s owner BOSS = 'boss@example.com' # Memory usage limit (size in kilobytes, 0 - not limited) MEMORY_LIMIT = 49152 # Admin password, used as a key to command "login" BOSS_PASS = '' # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-

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null

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null

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1

0

1

704c2153fa8d91e12d420a68efc08384b40b0410

2,025

py

Python

src/ndn/app_support/light_versec/grammar.py

tianyuan129/python-ndn

f390b3122d2a233a9a22a1ee9468b1241c46ef86

[ "Apache-2.0" ]

null

src/ndn/app_support/light_versec/grammar.py

tianyuan129/python-ndn

f390b3122d2a233a9a22a1ee9468b1241c46ef86

[ "Apache-2.0" ]

null

src/ndn/app_support/light_versec/grammar.py

tianyuan129/python-ndn

f390b3122d2a233a9a22a1ee9468b1241c46ef86

[ "Apache-2.0" ]

1

2020-09-25T18:38:23.000Z

# ----------------------------------------------------------------------------- # This piece of work is inspired by Pollere' VerSec: # https://github.com/pollere/DCT # But this code is implemented independently without using any line of the # original one, and released under Apache License. # # Copyright (C) 2019-2022 The python-ndn authors # # This file is part of python-ndn. # # 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. # ----------------------------------------------------------------------------- lvs_grammar = r''' ?start: file_input TAG_IDENT: CNAME RULE_IDENT: "#" CNAME FN_IDENT: "$" CNAME name: "/"? component ("/" component)* component: STR -> component_from_str | TAG_IDENT -> tag_id | RULE_IDENT -> rule_id definition: RULE_IDENT ":" def_expr def_expr: name ("&" comp_constraints)? ("<=" sign_constraints)? sign_constraints: RULE_IDENT ("|" RULE_IDENT)* comp_constraints: cons_set ("|" cons_set)* cons_set: "{" cons_term ("," cons_term)* "}" cons_term: TAG_IDENT ":" cons_expr cons_expr: cons_option ("|" cons_option)* cons_option: STR -> component_from_str | TAG_IDENT -> tag_id | FN_IDENT "(" fn_args ")" -> fn_call fn_args: (STR | TAG_IDENT)? ("," (STR | TAG_IDENT))* file_input: definition* %import common (DIGIT, LETTER, WS, CNAME, CPP_COMMENT) %import common.ESCAPED_STRING -> STR %ignore WS %ignore CPP_COMMENT '''

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null

0

1

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null

0

1

7052230dd2fbe62419de26e704bc3a6fc7f8c7d8

335

py

Python

service/models.py

robscarvalho8/currency_converter

21ac36583da15271bfbae9ee511093948af37534

[ "MIT" ]

null

service/models.py

robscarvalho8/currency_converter

21ac36583da15271bfbae9ee511093948af37534

[ "MIT" ]

null

service/models.py

robscarvalho8/currency_converter

21ac36583da15271bfbae9ee511093948af37534

[ "MIT" ]

null

from sqlalchemy import Column, Date, Integer, String, Float from database import Base class Currency(Base): __tablename__ = "currency" id = Column(Integer, primary_key=True, autoincrement=True) name = Column(String) abbreviated = Column(String) dolar_quotation = Column(Float) date_quotation = Column(Date)

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1

0

null

0

null

0

1

0

1

7055e9bdeeea00b88731d10f9f645b5f2d10ded1

3,640

py

Python

stanCode_Projects/boggle_game_solver/boggle.py

yjchang-tw/sc-projects

474f10ec740b8ce9dedcdd01f8c285f58d642ec8

[ "MIT" ]

null

stanCode_Projects/boggle_game_solver/boggle.py

yjchang-tw/sc-projects

474f10ec740b8ce9dedcdd01f8c285f58d642ec8

[ "MIT" ]

null

stanCode_Projects/boggle_game_solver/boggle.py

yjchang-tw/sc-projects

474f10ec740b8ce9dedcdd01f8c285f58d642ec8

[ "MIT" ]

null

""" File: boggle.py Name: ---------------------------------------- TODO: """ # This is the file name of the dictionary txt file # we will be checking if a word exists by searching through it FILE = 'dictionary.txt' dict_list = [] final = [] def main(): """ TODO: """ read_dictionary() temp = '' word_lst = [] for i in range(4): while True: row = input(str(i + 1) + ' row of letters: ') ch = row.split() if len(ch)!= 4 or len(ch[0])!=1 or len(ch[1])!=1 or len(ch[2])!=1 or len(ch[3])!=1: print('illegal input') else: break for j in range(4): word_lst.append(ch[j]) for start in range(16): temp = word_lst[start] word_lst[start] = '' find_word(word_lst,[temp],start) word_lst[start] = temp print(f'There are {len(final)} words in total.') def find_word(word_lst,current,now): if now == 0 or now ==4 or now == 8 or now == 12: nums = [-4,-3,1,4,5,1000] elif now ==1 or now ==5 or now ==9 or now ==13 or now ==2 or now ==6 or now ==10 or now ==14 : nums = [-5, -4, -3, -1, 1, 3, 4, 5,1000] elif now == 3 or now == 7 or now == 11 or now ==15: nums =[-5,-4,-1,3,4,1000] # print(current) temp = '' temp2 = '' a = '' for word in current: a+=word for dict in dict_list: if len(dict)>=4: if dict == a: if a not in final: final.append(a) print('Found "'+a+'"') for num in nums: # credential = 0 # if 16 > (now+num) > 0: # if word_lst[now+num] != '': # credential = 1 # if credential == 0: # pass # print(num) if num > 100: break else: # for num in nums: # print('now:',now) # print(num) # print(word_lst,current) if 0 <= now + num < 16: if word_lst[now+num] != '': temp='' for ch in current: temp += ch # print(word_lst) # print(temp+word_lst[now+num]) if has_prefix(temp+word_lst[now+num]): current.append(word_lst[now+num]) temp2 = word_lst[now+num] word_lst[now+num] = '' find_word(word_lst,current,now+num) word_lst[now+num] = temp2 current.pop() # print('--') # print(word_lst) # print(current) # print('--') 'roof coif hoof ' # nums = [-5,-1,-1,-1,1,3,4,5] # a = 0 # temp='' # sub='' # a='' # for ch in word_lst: # if ch != '': # a =1 # if a == 0: # print(current) # else: # for i in range(16): # if word_lst[i] != '': # current.append(word_lst[i]) # a = word_lst[i] # word_lst[i] = '' # for num in nums: # if 0 < i+num < 16: # if word_lst[i+num] != '': # for ch in current: # temp += ch # if has_prefix(temp+word_lst[i+num]): # print('-----------') # print(temp+word_lst[i+num]) # print('-----------') # current.append(word_lst[i+num]) # sub = word_lst[i+num] # word_lst[i+num] = '' # find_word(word_lst,current) # else: # word_lst[i+num] = '' # if len(current)!=0: # current.pop() # word_lst[i+num] = sub # word_lst[i] = a # if len(current) != 0: # current.pop() # print(i) def read_dictionary(): """ This function reads file "dictionary.txt" stored in FILE and appends words in each line into a Python list """ with open(FILE, 'r') as f: for line in f: word = line.strip() dict_list.append(word) def has_prefix(sub_s): """ :param sub_s: (str) A substring that is constructed by neighboring letters on a 4x4 square grid :return: (bool) If there is any words with prefix stored in sub_s """ for word in dict_list: if word.startswith(sub_s): return True return False if __name__ == '__main__': main()

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0

null

0

null

0

1

0

1

7056d18658c61757b2d33f0ad939e77a9975faf5

207

py

Python

tags/urls.py

jrdbnntt/FaceTags

0d2e9a78521d90f19f3feb6440421a42f0327472

[ "Apache-2.0" ]

null

tags/urls.py

jrdbnntt/FaceTags

0d2e9a78521d90f19f3feb6440421a42f0327472

[ "Apache-2.0" ]

null

tags/urls.py

jrdbnntt/FaceTags

0d2e9a78521d90f19f3feb6440421a42f0327472

[ "Apache-2.0" ]

null

from django.conf.urls import url import views urlpatterns = [ url(r'^user/', views.get_user, name='user'), url(r'^all/', views.get_all, name='all'), url(r'^fix/$', views.get_fix, name='fix'), ]

23

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0.154589

207

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0

null

0

1

0

null

0

1

705c42c02eee24ad63d65a1412a711fc1a3dbabb

377

py

Python

code/utils.py

Riccorl/ml-malware-classifier

f07d40f395bf11169d6eb57b9975760e625eb092

[ "MIT" ]

5

2018-11-26T13:34:20.000Z

2019-10-22T03:25:24.000Z

code/utils.py

Riccorl/ml-malware-classificator

f07d40f395bf11169d6eb57b9975760e625eb092

[ "MIT" ]

2

2019-06-01T05:28:14.000Z

2019-06-02T10:55:42.000Z

code/utils.py

Riccorl/ml-malware-classificator

f07d40f395bf11169d6eb57b9975760e625eb092

[ "MIT" ]

2

2020-09-20T21:22:59.000Z

2021-05-26T02:57:41.000Z

def timer(start: float, end: float) -> str: """ Timer function. Compute execution time from strart to end (end - start). :param start: start time :param end: end time :return: end - start """ hours, rem = divmod(end - start, 3600) minutes, seconds = divmod(rem, 60) return "{:0>2}:{:0>2}:{:05.2f}".format(int(hours), int(minutes), seconds)

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0

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null

0

null

0

1

0

1

7060539b2e45ee14195f9314ca889a6ddf2387b8

695

py

Python

malib/envs/gr_football/__init__.py

ReinholdM/play_football_with_human

9ac2f0a8783aede56f4ac1f6074db7daa41b6b6c

[ "MIT" ]

5

2021-11-17T03:11:13.000Z

2021-12-23T09:04:21.000Z

malib/envs/gr_football/__init__.py

ReinholdM/play_football_with_human

9ac2f0a8783aede56f4ac1f6074db7daa41b6b6c

[ "MIT" ]

null

malib/envs/gr_football/__init__.py

ReinholdM/play_football_with_human

9ac2f0a8783aede56f4ac1f6074db7daa41b6b6c

[ "MIT" ]

null

from .grf_env import BaseGFootBall as base_env, ParameterSharingWrapper from .encoders import encoder_basic, encoder_highpass, rewarder_basic default_config = { # env building config "use_built_in_GK": True, "scenario_config": { "env_name": "5_vs_5", "number_of_left_players_agent_controls": 4, "number_of_right_players_agent_controls": 4, "representation": "raw", "logdir": "", "write_goal_dumps": False, "write_full_episode_dumps": False, "render": False, "stacked": False, }, } def env(**kwargs): return ParameterSharingWrapper(base_env(**kwargs), lambda x: x[:6]) # return base_env(**kwargs)

28.958333

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0.222222

0

null

0

null

0

1

0

1

706338e7331b1562584249f362b42d600f79a095

1,215

py

Python

tools/perf/contrib/cluster_telemetry/rasterize_and_record_micro_ct.py

zealoussnow/chromium

fd8a8914ca0183f0add65ae55f04e287543c7d4a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

14,668

2015-01-01T01:57:10.000Z

2022-03-31T23:33:32.000Z

tools/perf/contrib/cluster_telemetry/rasterize_and_record_micro_ct.py

zealoussnow/chromium

fd8a8914ca0183f0add65ae55f04e287543c7d4a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

395

2020-04-18T08:22:18.000Z

2021-12-08T13:04:49.000Z

tools/perf/contrib/cluster_telemetry/rasterize_and_record_micro_ct.py

zealoussnow/chromium

fd8a8914ca0183f0add65ae55f04e287543c7d4a

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

5,941

2015-01-02T11:32:21.000Z

2022-03-31T16:35:46.000Z

# Copyright 2013 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from contrib.cluster_telemetry import ct_benchmarks_util from contrib.cluster_telemetry import page_set from contrib.cluster_telemetry import repaint_helpers from benchmarks import rasterize_and_record_micro # pylint: disable=protected-access class RasterizeAndRecordMicroCT( rasterize_and_record_micro._RasterizeAndRecordMicro): """Measures rasterize and record performance for Cluster Telemetry.""" @classmethod def Name(cls): return 'rasterize_and_record_micro_ct' @classmethod def AddBenchmarkCommandLineArgs(cls, parser): (rasterize_and_record_micro._RasterizeAndRecordMicro. AddBenchmarkCommandLineArgs(parser)) ct_benchmarks_util.AddBenchmarkCommandLineArgs(parser) @classmethod def ProcessCommandLineArgs(cls, parser, args): ct_benchmarks_util.ValidateCommandLineArgs(parser, args) def CreateStorySet(self, options): return page_set.CTPageSet( options.urls_list, options.user_agent, options.archive_data_file, run_page_interaction_callback=repaint_helpers.WaitThenRepaint)

34.714286

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0

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1,215

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0

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0.52381

0

null

0

null

0

1

0

1

706e04d6ec9e8da6c51a9f6c58f84eb9714001e8

691

py

Python

2016/python/day20.py

astonshane/AdventOfCode

25c7380e73eede3f79287de6a9dedc8314ab7965

[ "MIT" ]

null

2016/python/day20.py

astonshane/AdventOfCode

25c7380e73eede3f79287de6a9dedc8314ab7965

[ "MIT" ]

null

2016/python/day20.py

astonshane/AdventOfCode

25c7380e73eede3f79287de6a9dedc8314ab7965

[ "MIT" ]

null

MAX = 4294967295 blacklist = [] with open("inputs/day20.txt") as f: for line in f: line = line.strip().split('-') blacklist.append([int(x) for x in line]) blacklist.sort() def part1(): ip = 0 for i in range(0, len(blacklist)): bl = blacklist[i] if ip < bl[0]: break if bl[1] > ip: ip = bl[1]+1 print "(part1):", ip def part2(): ip = 0 good_ips = 0 for i in range(0, len(blacklist)): bl = blacklist[i] if ip < bl[0]: good_ips += bl[0]-ip ip = bl[1]+1 elif bl[1] > ip: ip = bl[1]+1 print "(part2):", good_ips part1() part2()

16.452381

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0.055728

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0

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691

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0

null

0

null

0

1

0

1

707f2e96048822ebc61af551711d5b289dab5523

4,550

py

Python

model.py

Riksi/nerf

4cbc0a19f2abd80465b4fba9ba2d6dbfd4ab08ea

[ "MIT" ]

null

model.py

Riksi/nerf

4cbc0a19f2abd80465b4fba9ba2d6dbfd4ab08ea

[ "MIT" ]

null

model.py

Riksi/nerf

4cbc0a19f2abd80465b4fba9ba2d6dbfd4ab08ea

[ "MIT" ]

null

import tensorflow as tf import math from helpers import get_rays, ndc_rays def get_sample_bounds(near, far, num_samples): diff = (far - near) idx = tf.range(num_samples) diff_term = diff / num_samples start = near + idx * diff_term end = start + diff_term return start, end def get_embedding(data, num_dims): # [L] rng = tf.range(num_dims) # [P, Z, L] embed_term = 2 ** rng * math.pi * data[..., None] # [P, Z, 2 * L] embed = tf.dynamic_stitch( [tf.sin(embed_term), tf.cos(embed_term)], [(rng * 2), (rng * 2 + 1)] ) return embed class NeRF(tf.keras.models.Model): def __init__(self, units1=256, num_layers1=8, units2=128, num_layers2=2): super(NeRF, self).__init__() self.part1 = tf.keras.models.Sequential( [ *(tf.keras.layers.Dense( units=units1, activation='relu' ) for _ in range(num_layers1 - 1) ), tf.keras.layers.Dense( units=units1 + 1, ) ] ) self.part2 = tf.keras.models.Sequential( [ *(tf.keras.layers.Dense( units=units2, activation='relu' ) for _ in range(num_layers2 - 1) ), tf.keras.layers.Dense( units=256 * 3, ) ] ) self.loss_fn = tf.losses.MeanSquaredError() def estimate_color(self, samples, t_far, origin, direction, mask=None): # [P, N] delta = tf.concat([samples[1:], t_far[None]], axis=-1) - samples # [P, N, 3] coords = samples[..., None] * direction + origin # [P, N, 1 + Z] y1 = self.part1(coords) # [P, Nc, 1], [P, Nc, Z] sigma, features = tf.split(y1, [1, -1], axis=-1) # [P, N, 3 + Z] x2 = tf.concat([features, direction], axis=-1) # [P, N, 3] clr = self.part2(x2) # [P, N, 1] neg_sig_times_delta = - sigma * delta[..., None] # [P, N, 1] transmittance = tf.exp(-tf.cumsum( neg_sig_times_delta, axis=1, exclusive=True )) # [P, N, 1] weights = transmittance * (1 - tf.exp(neg_sig_times_delta)) if mask is not None: weights = weights * mask # [P, 3] clr_est = tf.reduce_sum( clr * weights, axis=1 ) return clr_est, weights def call(self, inputs, num_samples=None, training=True): origin = get_embedding(inputs.origin, inputs.num_embed_dims) direction = get_embedding(inputs.direction, inputs.num_embed_dims) # [Nc], [Nc] starts, ends = get_sample_bounds(inputs.t_near, inputs.t_far, num_samples.coarse) t_coarse = tf.random.uniform( [tf.shape(inputs.direction)[0], num_samples.coarse], starts, ends ) # [P, 3], [P, Nc] clr_coarse, coarse_weights = self.estimate_color(t_coarse, t_far, origin, direction) coarse_weights = tf.stop_gradient(coarse_weights) # [P, Nc] regions = tf.random.categorical( tf.squeeze(tf.log(coarse_weights) - tf.log(tf.reduce_sum(coarse_weights)), axis=-1), num_samples=num_samples.fine ) # [P, Nf], [P, Nf] starts_for_regions = tf.gather(starts, regions) ends_for_regions = tf.gather(ends, regions) t_fine = tf.random.uniform( [tf.shape(direction)[0], num_samples.fine], starts_for_regions, ends_for_regions ) t_union_ragged = tf.RaggedTensor.from_sparse( tf.sets.union(t_fine, t_coarse) ) # [P, N'] t_union = t_union_ragged.to_tensor() # [P, N'] mask = tf.sequence_mask( t_union_ragged.row_lengths(), tf.shape(t_union)[-1] ) clr_fine = self.estimate_color(t_union_ragged, inputs.t_far, origin, direction, mask) return clr_coarse, clr_fine def train_step(self, data): clr_coarse, clr_fine = self.call(data.inputs, data.num_samples, training=True) 4 def inference_step(self, data): _, clr_fine = self.call(data.inputs, data.num_samples, False) pred = tf.reshape(clr_fine, [data.grid_shape, 3]) return pred

25.561798

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25.706215

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0.046154

0

0.074074

0

0.001862

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null

0

0.027778

null

0

null

0

null

0

1

0

1

70835d3043da389a933c6f4fb7d3c80b37959050

3,056

py

Python

diagnostics/diagnostic_analysis/scripts/export_csv.py

zhj-buffer/ROS2-driver-for-Realsense

936cf27be4e7dc3d699ff99499e72ea8638cc622

[ "Apache-2.0" ]

2

2021-07-14T12:33:55.000Z

2021-11-21T07:14:13.000Z

melodic/src/diagnostics/diagnostic_analysis/scripts/export_csv.py

disorn-inc/ROS-melodic-python3-Opencv-4.1.1-CUDA

3d265bb64712e3cd7dfa0ad56d78fcdebafdb4b0

[ "BSD-3-Clause" ]

1

2021-07-08T10:26:06.000Z

2021-07-08T10:31:11.000Z

melodic/src/diagnostics/diagnostic_analysis/scripts/export_csv.py

disorn-inc/ROS-melodic-python3-Opencv-4.1.1-CUDA

3d265bb64712e3cd7dfa0ad56d78fcdebafdb4b0

[ "BSD-3-Clause" ]

null

#!/usr/bin/python # # Software License Agreement (BSD License) # # Copyright (c) 2008, Willow Garage, Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following # disclaimer in the documentation and/or other materials provided # with the distribution. # * Neither the name of the Willow Garage nor the names of its # contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, # INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT # LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN # ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. ##\author Eric Berger, Kevin Watts ##\brief Converts diagnostics log files into CSV's for analysis PKG = 'diagnostic_analysis' import roslib; roslib.load_manifest(PKG) import diagnostic_msgs.msg import time, sys, os import operator, tempfile, subprocess from optparse import OptionParser from diagnostic_analysis.exporter import LogExporter if __name__ == '__main__': # Allow user to set output directory parser = OptionParser() parser.add_option("-d", "--directory", dest="directory", help="Write output to DIR/output. Default: %s" % PKG, metavar="DIR", default=roslib.packages.get_pkg_dir(PKG), action="store") options, args = parser.parse_args() exporters = [] print 'Output directory: %s/output' % options.directory try: for i, f in enumerate(args): filepath = 'output/%s_csv' % os.path.basename(f)[0:os.path.basename(f).find('.')] output_dir = os.path.join(options.directory, filepath) print "Processing file %s. File %d of %d." % (os.path.basename(f), i + 1, len(args)) exp = LogExporter(output_dir, f) exp.process_log() exp.finish_logfile() exporters.append(exp) print 'Finished processing files.' except: import traceback print "Caught exception processing log file" traceback.print_exc()

39.179487

96

0.708115

403

3,056

5.315136

0.526055

0.011204

0.019608

0.021008

0.085901

0.063492

0

0.002494

0.212696

3,056

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0.551047

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0.174663

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null

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null

0.172414

0

null

0

null

0

1

0

1

708a5b2019c15309a0d19d434e0322b1d3a4cda7

325

py

Python

unit_06/car7.py

janusnic/21v-pyqt

8ee3828e1c6e6259367d6cedbd63b9057cf52c24

[ "MIT" ]

null

unit_06/car7.py

janusnic/21v-pyqt

8ee3828e1c6e6259367d6cedbd63b9057cf52c24

[ "MIT" ]

null

unit_06/car7.py

janusnic/21v-pyqt

8ee3828e1c6e6259367d6cedbd63b9057cf52c24

[ "MIT" ]

2

2019-11-14T15:04:22.000Z

2021-10-31T07:34:46.000Z

#!/usr/bin/python # -*- coding: utf-8 -*- import sqlite3 as lite import sys uId = 1 uPrice = 62300 con = lite.connect('test.db') with con: cur = con.cursor() cur.execute("UPDATE Cars SET Price=? WHERE Id=?", (uPrice, uId)) con.commit() print "Number of rows updated: %d" % cur.rowcount

17.105263

76

0.593846

46

325

4.195652

0.804348

0

0.032922

0.252308

325

19

77

17.105263

0.761317

0.116923

0

0.234266

0

null

0

0.2

null

0.1

0

null

0

null

0

1

0

1

708ddb951ae7cdc4d261f043827396558a075007

1,470

py

Python

packages/pyright-internal/src/tests/samples/properties3.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

3,934

2019-03-22T09:26:41.000Z

2019-05-06T21:03:08.000Z

packages/pyright-internal/src/tests/samples/properties3.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

107

2019-03-24T04:09:37.000Z

2019-05-06T17:00:04.000Z

packages/pyright-internal/src/tests/samples/properties3.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

119

2019-03-23T10:48:04.000Z

2019-05-06T08:57:56.000Z

# This sample tests the type checker's ability to handle # custom subclasses of property. from typing import Any, Callable class custom_property1(property): pass class Custom1(object): @custom_property1 def x(self) -> int: return 3 @custom_property1 def y(self) -> float: return 3.5 @y.setter def y(self, val: float): pass @y.deleter def y(self): pass m1 = Custom1() a1: int = m1.x # This should generate an error because m.x is # an int and cannot be assigned to str. b1: str = m1.x c1: float = m1.y # This should generate an error because m.y is # a float and cannot be assigned to int. d1: int = m1.y # This should generate an error because there # is no setter for x. m1.x = 4 m1.y = 4 # This should generate an error because there is # no deleter for x. del m1.x del m1.y class custom_property2(property): _custom_func: Callable[..., Any] | None def custom_function(self, _custom_func: Callable[..., Any]): self._custom_func = _custom_func return self class Custom2(object): @custom_property2 def x(self) -> int: return 3 @custom_property2 def y(self) -> float: return 3.5 @y.setter def y(self, val: float): pass @y.deleter def y(self): pass @y.custom_function def y(self): pass m2 = Custom2() a2 = m2.y reveal_type(a2, expected_text="float") m2.y = 4 del m2.y

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0.061947

0.088496

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0.24115

0.150442

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0.27619

1,470

93

65

15.806452

0.81391

0.259184

0

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0

1

0.196078

false

0.117647

0.019608

0.078431

0.411765

0

null

0

null

0

1

0

1

70a1684fb88e63e0907be1bba1399d11eb060a74

150

py

Python

Project_Euler/01_mults_3_or_5/find_sum.py

perlygatekeeper/glowing-robot

7ef5eb089f552a1de309092606c95e805e6723a0

[ "Artistic-2.0" ]

2

2015-06-05T15:40:06.000Z

2020-03-19T17:08:37.000Z

Project_Euler/01_mults_3_or_5/find_sum.py

perlygatekeeper/glowing-robot

7ef5eb089f552a1de309092606c95e805e6723a0

[ "Artistic-2.0" ]

null

Project_Euler/01_mults_3_or_5/find_sum.py

perlygatekeeper/glowing-robot

7ef5eb089f552a1de309092606c95e805e6723a0

[ "Artistic-2.0" ]

null

#!/opt/local/bin/python sum_3_5 = 0 for i in range(1,1000): if i % 3 == 0 or i % 5 == 0: print(i) sum_3_5 += i print(sum_3_5)

12.5

32

0.513333

32

150

2.21875

0.53125

0.169014

0.211268

0

0.158416

0.326667

150

11

33

13.636364

0.544554

0.146667

0

1

0

false

0

0.333333

0

null

0

1

0

null

0

1

70a9bb288ab4678c73dcaaed29cf5fcda9867f4f

1,115

py

Python

playlist_creation/migrations/0002_create_privacy_policy_flatpage.py

theLionWar/time_capsule

64a5c8f430e6815dae8ee2f93f55d9b406911377

[ "MIT" ]

null

playlist_creation/migrations/0002_create_privacy_policy_flatpage.py

theLionWar/time_capsule

64a5c8f430e6815dae8ee2f93f55d9b406911377

[ "MIT" ]

null

playlist_creation/migrations/0002_create_privacy_policy_flatpage.py

theLionWar/time_capsule

64a5c8f430e6815dae8ee2f93f55d9b406911377

[ "MIT" ]

null

# Generated by Django 3.2.4 on 2021-08-03 15:02 from django.contrib.sites.management import create_default_site from django.db import migrations def create_privacy_policy_flatpage(apps, schema_editor): Site = apps.get_model("sites", "Site") site = Site.objects.first() if not site: create_default_site(None) site = Site.objects.first() FlatPage = apps.get_model("flatpages", "FlatPage") page, created = \ FlatPage.objects.get_or_create(url='/privacy-policy/', defaults={'title': 'Privacy Policy'}) if created: page.sites.add(site) def delete_privacy_policy_flatpage(apps, schema_editor): FlatPage = apps.get_model("flatpages", "FlatPage") FlatPage.objects.filter(url='/privacy-policy/').delete() class Migration(migrations.Migration): dependencies = [ ('playlist_creation', '0001_initial'), ("sites", "0002_alter_domain_unique") ] operations = [ migrations.RunPython(create_privacy_policy_flatpage, delete_privacy_policy_flatpage), ]

30.135135

76

0.658296

127

1,115

5.559055

0.464567

0.128895

0.11898

0.076487

0.209632

0

0.026682

0.226906

1,115

36

77

30.972222

0.792343

0.040359

0

0.153846

1

0

0.142322

0.022472

0

1

0.076923

false

0

0.076923

0

0.269231

0

null

0

1

0

null

0

1

70aa7222dc1e2e9cae7903ea030f5828a1ff715a

3,607

py

Python

profiles_api/views.py

singhmonika10/profiles-rest-api

69b403aaa24ca16a265db06cdbc99c970eb146c1

[ "MIT" ]

null

profiles_api/views.py

singhmonika10/profiles-rest-api

69b403aaa24ca16a265db06cdbc99c970eb146c1

[ "MIT" ]

6

2020-06-06T01:42:09.000Z

2021-06-10T20:01:52.000Z

profiles_api/views.py

singhmonika10/profiles-rest-api

69b403aaa24ca16a265db06cdbc99c970eb146c1

[ "MIT" ]

null

from rest_framework.views import APIView from rest_framework.response import Response from rest_framework import status from rest_framework import viewsets from rest_framework.authentication import TokenAuthentication from rest_framework import filters from profiles_api import serializers from profiles_api import models from profiles_api import permissions class HelloApiView(APIView): """Test API View""" serializer_class = serializers.HelloSerializer def get(self,request, format=None): """returns a list of APIView features""" an_apiview = [ 'uses HTTTP mothod as function(get, post, patch, put, delete) ', 'Is simmilar to Traditional Django View', 'Gives you the most control over your application logic', 'Is mapped manually to URLs', ] return Response({'message':'Hello!','an_apiview':an_apiview}) def post(self, request): """Create a hello message with our name""" serializer = self.serializer_class(data=request.data) if serializer.is_valid(): name = serializer.validated_data.get('name') message = f'Hello {name}' return Response({'message':message}) else: return Response( serializer.errors, status = status.HTTP_400_BAD_REQUEST ) def put(self, request, pk=None): """Handle updating an object""" return Response({'method': 'PUT'}) def patch(self, request, pk=None): """Handle partial update of object""" return Response({'method': 'PATCH'}) def delete(self, request, pk=None): """Delete an object""" return Response({'method': 'DELETE'}) class HelloViewSet(viewsets.ViewSet): """Test API ViewSet""" serializer_class = serializers.HelloSerializer def list(self, request): """Return a hello message.""" a_viewset = [ 'Uses actions (list, create, retrieve, update, partial_update)', 'Automatically maps to URLS using Routers', 'Provides more functionality with less code', ] return Response({'message': 'Hello!', 'a_viewset': a_viewset}) def create(self, request): """create a new hello mesage""" serializer= self.serializer_class(data=request.data) if serializer.is_valid(): name = serializer.validated_data.get('name') message = f'hello{name}!' return Response({'message':message}) else: return Response( serializer.errors, status = status.HTTP_400_BAD_REQUEST ) def retrieve(self, request,pk=None): """habdle getting an object by its id""" return Response({'http_method': 'GET'}) def update(self, request, pk=None): """handle updateing an object""" return Response({'http_method':'PUT'}) def partial_update(self, request, pk=None): """handle updating part of an object""" return Response({'http_method':'PATCH'}) def destroy(self, request, pk=None): """handle removing an object""" return Response({'http_method':'DELETE'}) class UserProfileViewSet(viewsets.ModelViewSet): """handle creating and updating profiles""" serializer_class = serializers.UserProfileSerializer queryset = models.UserProfile.objects.all() authentication_classes = (TokenAuthentication,) permission_class = (permissions.UpdateOwnProfile,) filter_backends = (filters.SearchFilter,) search_fields = ('name', 'email',)

30.567797

76

0.640144

392

3,607

5.788265

0.32398

0.080212

0.040106

0.052446

0.352138

0.2684

0.183341

0

0.002217

0.249792

3,607

117

77

30.82906

0.83629

0.107291

0

0.253521

0

0.163544

0

1

0.15493

false

0

0.126761

0

0.619718

0

null

0

null

0

1

0

1

5606244a09399ed959432761133bc9ec94e45b68

5,831

py

Python

mprocessing/client.py

ftranschel/evoMPS

b9e8d13066d12ee779376fdfd24ac2b34ac73ba2

[ "BSD-3-Clause" ]

1

2017-02-26T12:36:40.000Z

mprocessing/client.py

ftranschel/evoMPS

b9e8d13066d12ee779376fdfd24ac2b34ac73ba2

[ "BSD-3-Clause" ]

null

mprocessing/client.py

ftranschel/evoMPS

b9e8d13066d12ee779376fdfd24ac2b34ac73ba2

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ This module is part of an extension of evoMPS by adding dissipative dynmaics based on Monte-Carlo methods. This part is the client file for the distributed computing framework that utilizes parallel processing to speed up dissipative dynamics. @author: F.W.G. Transchel """ import Queue as qu import multiprocessing as mp import multiprocessing.managers as mpm import time import socket import sys import traceback import io import multiprocessing.sharedctypes from ast import literal_eval import string as STR import pickle as pic import numpy as np global np import scipy as sp global sp import scipy.linalg as la import nullspace as ns import matmul as m import tdvp_common_diss as tm import matmul as mm import tdvp_gen as TDVP import scipy.sparse as spp authkey = "SECRET" port = 5678 ip = '127.0.0.1' internal_call = True # This is used to tell tdvp_gen_diss.py #(and other dynamically loaded modules) # to not execute code on its own. def worker(job_q, result_q,codebase): """ A worker function to be launched in a separate process. Takes jobs from job_q - each job a list of numbers to factorize. When the job is done, the result (dict mapping number -> list of factors) is placed into result_q. Runs until job_q is empty. """ try: #print codebase exec(codebase,globals(),locals()) except: print "Unexpected error:", sys.exc_info()[0] traceback.print_exc() raise while True: try: job = job_q.get_nowait() # job = data for executing something... # idea: serialize the code and just have it executed distributively result = {} try: exec(job) except: print "Unexpected error:", sys.exc_info()[0] traceback.print_exc() raise #print result result_q.put(result) time.sleep(2) except qu.Empty: return except: print "Unexpected error:", sys.exc_info()[0] return #raise def scheduler(shared_job_q, shared_result_q, codebase, nprocs): """ Split the work with jobs in shared_job_q and results in shared_result_q into several processes. Launch each process with factorizer_worker as the worker function, and wait until all are finished. """ #print codebase #exec(codebase) procs = [] for i in range(nprocs): p = mp.Process( target=worker, args=(shared_job_q, shared_result_q, codebase)) procs.append(p) p.start() for p in procs: p.join() def runclient(): """ This is the __main__ function of client.py that connects to a server and distributes jobs to the scheduler(). """ max_tries = 0 max_tries_limit = 5 while True: try: manager = make_client_manager(ip,port,authkey) job_q = manager.get_job_q() result_q = manager.get_result_q() cdbs = manager.codebase().__str__() + "\n" code = cdbs[12:-3] #workaround to get rid of control chars decoded = code.replace("\\n","\n") decoded = decoded.replace("\\r","\r") #exec(decoded,globals(),locals()) #tdvp_obj = tdvp_diss() #print code scheduler(job_q, result_q, decoded, (2)) print "All available jobs finished." print "===" time.sleep(5) except socket.error: print "No answer from server. Trying again...." max_tries += 1 time.sleep(5) if max_tries >= max_tries_limit: break else: continue print "Process aborted from too many failed connection tries. Exiting." #from multiprocessing.managers import BaseManager class ServerQueueManager(mpm.SyncManager): pass def make_client_manager(ip, port, authkey): """ Create a manager for a client. This manager connects to a server on the given address and exposes the get_job_q and get_result_q methods for accessing the shared queues from the server. Return a manager object. """ ServerQueueManager.register('get_job_q') ServerQueueManager.register('get_result_q') ServerQueueManager.register('codebase') manager = ServerQueueManager(address=(ip, port), authkey=authkey) manager.connect() print 'Client connected to %s:%s' % (ip, port) return manager def dist_process(n): return n def importCode(code,name,add_to_sys_modules=0): """ Import dynamically generated code as a module. code is the object containing the code (a string, a file handle or an actual compiled code object, same types as accepted by an exec statement). The name is the name to give to the module, and the final argument says wheter to add it to sys.modules or not. If it is added, a subsequent import statement using name will return this module. If it is not added to sys.modules import will try to load it in the normal fashion. import foo is equivalent to foofile = open("/path/to/foo.py") foo = importCode(foofile,"foo",1) Returns a newly generated module. """ import sys,imp module = imp.new_module(name) exec code in module.__dict__ if add_to_sys_modules: sys.modules[name] = module return module if __name__ == '__main__': print "===" print "This is the mpsampling distributed computation CLIENT." print "===" print "Using " + str(mp.cpu_count()) + " cores." print "===" runclient()

28.724138

79

0.629395

776

5,831

4.612113

0.367268

0.013412

0.00922

0.077396

0.060631

0.043308

0.03297

0

0.006286

0.290688

5,831

202

80

28.866337

0.859043

0.079403

0

0.214286

0

0.099232

0

null

0.008929

0.205357

null

0.133929

0

null

0

null

0

1

0

1

560a9dc22e71652afba1f2f2605eeeb97cccd37c

2,268

py

Python

auctions/models.py

adamiantorno/CS50W-commerce

017d690b8b344158f0bdcff165f60702f173618b

[ "MIT" ]

null

auctions/models.py

adamiantorno/CS50W-commerce

017d690b8b344158f0bdcff165f60702f173618b

[ "MIT" ]

null

auctions/models.py

adamiantorno/CS50W-commerce

017d690b8b344158f0bdcff165f60702f173618b

[ "MIT" ]

null

from django.contrib.auth.models import AbstractUser from django.urls import reverse from django.db import models from datetime import date class User(AbstractUser): pass class Listing(models.Model): CATEGORIES = ( ('ART', 'Art'), ('CLT', 'Clothing & Accessories'), ('ELE', 'Electronics'), ('HME', 'Home'), ('KIT', 'Kitchen'), ('ENT', 'Entertainment'), ('TOY', 'Toys & Games'), ('SPT', 'Sports & Outdoors') ) creator = models.ForeignKey(User, on_delete=models.CASCADE, related_name='listings', editable=False) title = models.CharField(max_length=100) description = models.TextField() date_created = models.DateTimeField(auto_now_add=True) image = models.URLField(max_length=264, blank=True, null=True) start_bid = models.DecimalField(max_digits=10, decimal_places=2) category = models.CharField(max_length=50, choices=CATEGORIES) is_active = models.BooleanField(default=True) winner = models.ForeignKey(User, on_delete=models.CASCADE, null=True, blank=True) def __str__(self): return f"${self.start_bid} {self.title} - {self.creator}" def get_absolute_url(self): return reverse('listing', kwargs={'pk': self.pk}) class Bid(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='bids') listing = models.ForeignKey(Listing, on_delete=models.CASCADE, related_name='bids') bid = models.DecimalField(max_digits=10, decimal_places=2) def __str__(self): return f"${self.bid} for {self.listing} from {self.user}" class Comment(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='comments') listing = models.ForeignKey(Listing, on_delete=models.CASCADE, related_name='comments') comment = models.CharField(max_length=500) timestamp = models.DateTimeField(auto_now_add=True, blank=True, null=True) def __str__(self): return f"{self.comment} - {self.user}" class Watchlist(models.Model): user = models.OneToOneField(User, on_delete=models.CASCADE) listing = models.ManyToManyField(Listing, blank=True, related_name='watchlists') def __str__(self): return f"{self.user}'s Watchlist"

32.4

104

0.689594

279

2,268

5.437276

0.362007

0.036915

0.064601

0.096902

0.428477

0.411997

0.340804

0.264997

0.170073

0

0.009081

0.174603

2,268

69

105

32.869565

0.801282

0

0.083333

0

0.136544

0

1

0.104167

false

0.020833

0.083333

0.104167

0.791667

0

null

0

null

0

1

0

1

5611625ebacc0d47640b097555b0e9f837492d3b

3,109

py

Python

CameraToServer/python/client/SendDataWithSSL.py

yabuta/CameraSender

99b84ae941782924ecb677a1f38a18dd082459d5

[ "MIT" ]

null

CameraToServer/python/client/SendDataWithSSL.py

yabuta/CameraSender

99b84ae941782924ecb677a1f38a18dd082459d5

[ "MIT" ]

null

CameraToServer/python/client/SendDataWithSSL.py

yabuta/CameraSender

99b84ae941782924ecb677a1f38a18dd082459d5

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding:utf-8 -*- import socket import cv2 import time import threading import datetime import ssl import readSettings as RS """ send picture per 5 second. when called stop, thread finish. picture convert from mat to jpeg """ class SendThread(threading.Thread): def __init__(self,HOST,PORT,encrypt): super(SendThread,self).__init__() self.e = threading.Event() self.HOST,self.PORT,self.encrypt = HOST,PORT,encrypt self.frame = None self.lock = threading.RLock() self.ca_path = RS.getSettings([["settings","ca_cert_path"]])[0] #self.ca_path = RS.get_ca_path() error_flag = False error_message = [] if self.ca_path == None: error_flag = True error_message.append("fail to get ca_cert_path.") self.isError = [error_flag,error_message] def run(self): time.sleep(1) #ca_pathの取得失敗の場合はエラーとする if self.isError[0]: for e in self.isError[1]: print e return while not self.e.is_set(): start = time.time() self.sendImageToServer() elapse_time = time.time() - start print elapse_time * 1000 , "(ms)" time.sleep(5) def sendImageToServer(self): try: sock=socket.socket(socket.AF_INET,socket.SOCK_STREAM) #証明書はないのでNone #None以外にするとca_certsが必要になるような気がする #versionはv1,安全らしいので ssl_sock = ssl.wrap_socket(sock, ca_certs = self.ca_path, cert_reqs = ssl.CERT_REQUIRED, ssl_version = ssl.PROTOCOL_TLSv1) ssl_sock.connect((self.HOST,self.PORT)) #test print "test:",ssl_sock.cipher() #lock while processing picture data #because it is shared to Capture thread self.lock.acquire() if self.frame != None: #picture is sent after convert .jpeg from mat encode_param = [int(cv2.IMWRITE_JPEG_QUALITY),90] jpegstring = cv2.imencode('.jpeg',self.frame,encode_param)[1].tostring() jpegstring = self.encrypt.encrypt(jpegstring) #add date information tm = datetime.datetime.today() senddata = str(tm) + '\t' + jpegstring #test print "test:",len(senddata) #send ssl_sock.write(senddata) self.lock.release() ssl_sock.close() except Exception as e: print "In SendDataWithSSL.py" print e def stop(self): self.e.set() self.join() #get date def getDate(self): d = datetime.datetime.today() return '%4d-%2d-%2d %2d:%2d:%2d' % (d.year,d.month,d.day,d.hour,d.minute,d.second) #set picture data with lock def setFrame(self,frame): with self.lock: self.frame = frame

29.330189

90

0.5468

354

3,109

4.672316

0.412429

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3,109

105

91

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0

null

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null

0

1

0

1

561789e6a59c1c859ca74d0814d0ff171e8cafa1

6,112

py

Python

PyFunceble/checker/syntax/domain_base.py

Centaurioun/PyFunceble

59b809f3322118f7824195752c6015220738d4a0

[ "Apache-2.0" ]

213

2017-11-19T16:00:29.000Z

2022-03-30T20:51:35.000Z

PyFunceble/checker/syntax/domain_base.py

Centaurioun/PyFunceble

59b809f3322118f7824195752c6015220738d4a0

[ "Apache-2.0" ]

270

2018-01-10T12:42:41.000Z

2022-03-22T00:03:23.000Z

PyFunceble/checker/syntax/domain_base.py

Centaurioun/PyFunceble

59b809f3322118f7824195752c6015220738d4a0

[ "Apache-2.0" ]

48

2017-12-09T22:53:49.000Z

2022-01-29T15:50:52.000Z

""" The tool to check the availability or syntax of domain, IP or URL. :: ██████╗ ██╗ ██╗███████╗██╗ ██╗███╗ ██╗ ██████╗███████╗██████╗ ██╗ ███████╗ ██╔══██╗╚██╗ ██╔╝██╔════╝██║ ██║████╗ ██║██╔════╝██╔════╝██╔══██╗██║ ██╔════╝ ██████╔╝ ╚████╔╝ █████╗ ██║ ██║██╔██╗ ██║██║ █████╗ ██████╔╝██║ █████╗ ██╔═══╝ ╚██╔╝ ██╔══╝ ██║ ██║██║╚██╗██║██║ ██╔══╝ ██╔══██╗██║ ██╔══╝ ██║ ██║ ██║ ╚██████╔╝██║ ╚████║╚██████╗███████╗██████╔╝███████╗███████╗ ╚═╝ ╚═╝ ╚═╝ ╚═════╝ ╚═╝ ╚═══╝ ╚═════╝╚══════╝╚═════╝ ╚══════╝╚══════╝ Provides the base of all domain syntax checker. Author: Nissar Chababy, @funilrys, contactTATAfunilrysTODTODcom Special thanks: https://pyfunceble.github.io/#/special-thanks Contributors: https://pyfunceble.github.io/#/contributors Project link: https://github.com/funilrys/PyFunceble Project documentation: https://pyfunceble.readthedocs.io/en/dev/ Project homepage: https://pyfunceble.github.io/ License: :: Copyright 2017, 2018, 2019, 2020, 2021 Nissar Chababy Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import functools from typing import Optional, Tuple from PyFunceble.checker.base import CheckerBase from PyFunceble.dataset.iana import IanaDataset from PyFunceble.dataset.public_suffix import PublicSuffixDataset class DomainSyntaxCheckerBase(CheckerBase): """ Provides an interface to check the syntax of a second domain. :param str subject: Optional, The subject to work with. """ # pylint: disable=line-too-long SPECIAL_USE_DOMAIN_NAMES_EXTENSIONS = ["onion"] """ Specifies the extension which are specified as "Special-Use Domain Names" and supported by our project. :type: list .. seealso:: * `RFC6761`_ * `IANA Special-Use Domain Names`_ assignments. * `RFC7686`_ .. _RFC6761: https://tools.ietf.org/html/rfc6761 .. _RFC7686: https://tools.ietf.org/html/rfc6761 .. _IANA Special-Use Domain Names: https://www.iana.org/assignments/special-use-domain-names/special-use-domain-names.txt """ last_point_index: Optional[int] = None """ Saves the index of the last point. """ iana_dataset: Optional[IanaDataset] = None public_suffix_dataset: Optional[PublicSuffixDataset] = None def __init__(self, subject: Optional[str] = None) -> None: self.iana_dataset = IanaDataset() self.public_suffix_dataset = PublicSuffixDataset() super().__init__(subject) def reset_last_point_index(func): # pylint: disable=no-self-argument """ Resets the last point index before executing the decorated method. """ @functools.wraps(func) def wrapper(self, *args, **kwargs): self.last_point_index = None return func(self, *args, **kwargs) # pylint: disable=not-callable return wrapper def find_last_point_index(func): # pylint: disable=no-self-argument """ Try to find the index of the last point after the execution of the decorated method. """ @functools.wraps(func) def wrapper(self, *args, **kwargs): result = func(self, *args, **kwargs) # pylint: disable=not-callable self.last_point_index = self.get_last_point_index(self.idna_subject) return result return wrapper @CheckerBase.subject.setter @reset_last_point_index @find_last_point_index def subject(self, value: str): """ Sets the subject to work with. :param value: The subject to set. :raise TypeError: When the given :code:`value` is not a :py:class:`str`. :raise ValueError: When the given :code:`value` is empty. """ # pylint: disable=no-member super(DomainSyntaxCheckerBase, self.__class__).subject.fset(self, value) @staticmethod def get_last_point_index(subject: str) -> Optional[int]: """ Provides the index of the last point of the given subject. """ try: if subject.endswith("."): return subject[:-1].rfind(".") return subject.rindex(".") except ValueError: return None def get_subject_without_suffix( self, subject: str, extension: str ) -> Optional[Tuple[Optional[int], Optional[str]]]: """ Provides the given subject without the suffix. :param subject: The subject to work with. :param extension: The extension previously extracted. """ if extension in self.public_suffix_dataset: for suffix in self.public_suffix_dataset.get_available_suffix(extension): try: return subject[: subject.rindex(f".{suffix}")], suffix except ValueError: continue return None, None @CheckerBase.ensure_subject_is_given def get_extension(self) -> Optional[str]: """ Provides the extension to work with (if exists). """ if self.last_point_index is None: return None # Plus one is for the leading point. extension = self.idna_subject[self.last_point_index + 1 :] if extension.endswith("."): extension = extension[:-1] return extension def is_valid(self) -> bool: """ Validate the given subject. """ raise NotImplementedError()

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6,112

206

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0

null

0

null

0

1

0

1

562235d95b74c7a9bd19a09f477eb9ad2191d459

8,183

py

Python

Computer_science/B05_Python/01_Basics/S12_Debugging.py

Polirecyliente/SGConocimiento

560b08984236d7a10f50c6b5e6fb28844193d81b

[ "CC-BY-4.0" ]

null

Computer_science/B05_Python/01_Basics/S12_Debugging.py

Polirecyliente/SGConocimiento

560b08984236d7a10f50c6b5e6fb28844193d81b

[ "CC-BY-4.0" ]

null

Computer_science/B05_Python/01_Basics/S12_Debugging.py

Polirecyliente/SGConocimiento

560b08984236d7a10f50c6b5e6fb28844193d81b

[ "CC-BY-4.0" ]

null

# Debugging #T# Table of contents #C# Python debugger (pdb) #T# Beginning of content #C# Python debugger (pdb) # |------------------------------------------------------------- #T# pdb is the builtin Python debugger, it has breakpoints, stepping through the code, printing the values of variables, post-mortem debugging, debugging of modules, functions, scripts, among other features #T# pdb can be executed with an script argument to debug said script, the following syntax is done in the operating system shell # SYNTAX python3 -m pdb script1.py #T# python3 is the Python executable, -m pdb script1.py runs pdb to debug script1.py (see the file titled Interpreter), this automatically enters post-mortem if script1 crashes #T# the pdb module is imported to use the pdb debugger as part of a script import pdb #T# the run function of the pdb module allows debugging the execution of a Python string # SYNTAX pdb.run('string1') #T# the pdb debugger is started right before the execution of string1, and is used to debug whatever string1 executes pdb.run('import S01_Basic_syntax') # this debugs the S01_Basic_syntax.py file, because the import statement executes the imported module #T# the following code is used to show the syntax of the pdb debugger in its interactive mode output_var1 = "help variable to show the different output of the pdb debugger" var1 = [5, 2, 3] var2 = 7 def func1(num1, num2): num3 = num1 + num2 print("func1_string1") return num3 def func2(): func1(var1[0], var1[2]) loc1 = 72 for i1 in [1, 2, 3]: print("i1 is", i1) func2() #T# create a breakpoint with the breakpoint function, this starts the (Pdb) interpreter to do interactive debugging breakpoint() # |--------------------------------------------------\ #T# the following syntaxes are written in the pdb debugger language, so they can't be written outside of a comment because they are not valid Python syntax and this .py file would show errors in an IDE (IDE stands for Integrated Development Environment) #T# the 'output_var1' variable used in the following is used as a helper to signal and display the output of the pdb debugger commands #T# the pdb debugger prompt is (Pdb), so anything shown after a (Pdb) means that it was typed in said prompt, e.g. '(Pdb) prompt_typings1' prompt_typings1 was typed directly in the pdb debugger prompt #T# when source code is printed, the current line is shown with '->' after the line number # SYNTAX next #T# the next command executes code up to the next line of code (not entering functions) output_var1 # (Pdb) next # this shows output of the script or program under debugging # SYNTAX step #T# the step command steps into functions or the next line output_var1 # (Pdb) step # this shows output of the script or program under debugging, possibly inside a function # SYNTAX continue #T# the continue command continues execution until a breakpoint is found output_var1 # (Pdb) continue # this shows output of the script or program under debugging, up to the next breakpoint or the end of the file # SYNTAX until int1 #T# the until command continues execution until a line of number int1 or greater is reached, without int1 it continues until the next bigger line number output_var1 # (Pdb) until # this shows output of the script or program under debugging, up to the next bigger line number # SYNTAX return #T# the return command continues execution until arriving at the return keyword of the current function, so this is used inside functions output_var1 # (Pdb) return # inside a function, this shows output of the script or program under debugging, up to the return keyword of the current function # SYNTAX run # SYNTAX restart #T# the run command and its alias the restart command restart the script or program under debugging, preserving the options and created breakpoints output_var1 # (Pdb) restart # the script or program restarts # SYNTAX p var1 #T# the p command (for print) prints the value of var1, if the name var1 is defined, this syntax is an alias for print(var1) output_var1 # (Pdb) p var1 # [5, 2, 3] output_var1 # (Pdb) print(var1) # [5, 2, 3] # SYNTAX p func1 #T# same as before, but when used with a function, its address is printed output_var1 # (Pdb) p func1 # <function func1 at 0x7f35210401f0> # or similar # SYNTAX p func1(arg1, arg2) #T# same as before, but this prints any output from func1 and its return value using arg1, arg2 as arguments, and any other arguments present output_var1 # (Pdb) p func1(2, 3) #T# the former prints # func1_string1 # 5 # SYNTAX args #T# the args command displays the arguments passed to a function output_var1 # (Pdb) args # inside func1(5, 3) #T# the former prints # num1 = 5 # num2 = 3 # SYNTAX display var1 #T# the display command prints a variable each time it changes # SYNTAX undisplay var1 #T# stop displaying a variable var1 with the undisplay command # SYNTAX l int1 #T# the l command lists 11 source code lines, this is done around line int1, 5 lines above and 5 lines below it, this syntax is an alias for list int1 output_var1 # (Pdb) l 7 # (Pdb) list 7 #T# the former prints # 2 # Debugging # 3 # 4 #T# Table of contents # 5 # 6 #C# Python debugger (pdb) # 7 # 8 #T# Beginning of content # 9 # 10 #C# Python debugger (pdb) # 11 # 12 # |------------------------------------------------------------- # SYNTAX l . #T# same as before, but list source code lines around the current line output_var1 # (Pdb) l . # this prints similar as before # SYNTAX ll #T# the ll commands does a long list of the source code local to the current line output_var1 # (Pdb) ll # the output is too large to put here, more than 150 lines # SYNTAX break #T# the break command alone displays all breakpoints output_var1 # (Pdb) break # with two breakpoints already created #T# the former prints # Num Type Disp Enb Where # 1 breakpoint keep yes at /path/to/S13_Debugging.py:20 # 2 breakpoint keep yes at /path/to/S13_Debugging.py:35 # stop only if var2 < 10 # SYNTAX break file1:int1 #T# the break command is used to create breakpoints in file1 (the current python script name without the .py extension), in line int1 output_var1 # (Pdb) break S13_Debugging:20 # Breakpoint 1 at /path/to/S13_Debugging.py:20 # SYNTAX break file1.func1, condition1 #T# same as before, but the breakpoint is created in the first line of func1 (its def line), and the breakpoint only activates if condition1 evaluates to True using Python boolean syntax output_var1 # (Pdb) break S13_Debugging.func1, var2 < 10 # Breakpoint 2 at /path/to/S13_Debugging.py:35 # SYNTAX disable int1 #T# the disable command disables the breakpoint numbered with the number int1 output_var1 # (Pdb) disable 1 # Disabled breakpoint 1 at /path/to/S13_Debugging.py:20 # SYNTAX enable int1 #T# the enable command enables the breakpoint numbered with the number int1 output_var1 # (Pdb) enable 1 # Enabled breakpoint 1 at /path/to/S13_Debugging.py:20 # SYNTAX clear int1 #T# the clear command completely deletes a breakpoint output_var1 # (Pdb) clear 1 # Deleted breakpoint 1 at /path/to/S13_Debugging.py:20 # SYNTAX where #T# the where command prints the stack_frame trace output_var1 # (Pdb) where #T# the former prints # /path/to/S13_Debugging.py(46)<module>() #-> func2() # /path/to/S13_Debugging.py(42)func2() #-> func1(var1[0], var1[2]) #> /path/to/S13_Debugging.py(40)func1()->8 #-> return num3 # SYNTAX up int1 #T# the up command goes up to an older frame in the stack trace, the amount of frames that go up is int1 output_var1 # (Pdb) up 1 #T# the former prints #> /path/to/S13_Debugging.py(42)func2() #-> func1(var1[0], var1[2]) # SYNTAX down int1 #T# the down command goes down to a newer frame in the stack trace, the amount of frames that go down is int1 output_var1 # (Pdb) down 1 # *** Newest frame # this is the output at the lowest frame # SYNTAX help #T# print the debugger pdb help with the help command # SYNTAX quit #T# quit the debugger with the quit command # |--------------------------------------------------/ # |-------------------------------------------------------------

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null

0

1

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null

0

1

5624f94b924fed45d90c5a7120d1219ba2228c0e

543

py

Python

python3/numpy/numpy_absolute.py

Nahid-Hassan/code-snippets

24bd4b81564887822a0801a696001fcbeb6a7a75

[ "MIT" ]

2

2020-09-29T04:09:41.000Z

2020-10-18T13:33:36.000Z

python3/numpy/numpy_absolute.py

Nahid-Hassan/code-snippets

24bd4b81564887822a0801a696001fcbeb6a7a75

[ "MIT" ]

null

python3/numpy/numpy_absolute.py

Nahid-Hassan/code-snippets

24bd4b81564887822a0801a696001fcbeb6a7a75

[ "MIT" ]

1

2021-12-26T04:55:55.000Z

""" Created on Sat Mar 23 00:23:27 2019 @author: nahid """ #https://docs.scipy.org/doc/numpy/reference/generated/numpy.absolute.html import numpy as np import matplotlib.pyplot as plt x = np.array([-1.2, 1.2]) x = np.absolute(x) print(x) print(np.absolute(1 + 2j)) #Plot the function over [-10, 10]: x = np.linspace(-10, 10, 101); #start, end, totalElements you want to create plt.plot(np.absolute(x)) plt.show() plt.plot(x) plt.show() xx = x + 1j * x[:, np.newaxis] plt.imshow(np.abs(xx), extent=[-10, 10, -10, 10], cmap='gray') plt.show()

23.608696

76

0.672192

100

543

3.65

0.55

0.054795

0.060274

0

0.080338

0.128913

543

23

77

23.608696

0.691332

0.368324

0

0.214286

1

0

0.011976

0

1

0

false

0

0.142857

0

0.142857

0

null

0

1

0

null

0

1

562f521bc543c349ce98082080bb5aacbf7c8b15

1,467

py

Python

problems/324.Wiggle_Sort_II/try.py

subramp-prep/leetcode

d125201d9021ab9b1eea5e5393c2db4edd84e740

[ "Unlicense" ]

null

problems/324.Wiggle_Sort_II/try.py

subramp-prep/leetcode

d125201d9021ab9b1eea5e5393c2db4edd84e740

[ "Unlicense" ]

null

problems/324.Wiggle_Sort_II/try.py

subramp-prep/leetcode

d125201d9021ab9b1eea5e5393c2db4edd84e740

[ "Unlicense" ]

null

# coding=utf-8 # Author: Jianghan LI # Question: 324.Wiggle_Sort_II # Date: # Complexity: O(N) import random class Solution(object): def wiggleSort(self, nums): """ :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead. """ i = 1 for j in range(2, len(nums)): print i, j, if i & 1: if nums[i - 1] < nums[j]: if i < j: nums[i], nums[j] = nums[j], nums[i] i += 2 else: i += 1 elif nums[i - 1] > nums[j]: nums[i - 1], nums[j] = nums[j], nums[i - 1] i += 1 else: if nums[i - 1] > nums[j]: if i < j: nums[i], nums[j] = nums[j], nums[i] i += 2 else: i += 1 elif nums[i - 1] < nums[j]: nums[i - 1], nums[j] = nums[j], nums[i - 1] i += 1 print nums return i == len(nums) ############ test case ########### s = Solution() nums = [1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2] nums = [2, 1, 1, 2, 2, 3] nums = [1, 3, 2, 2, 3, 1] nums = [5, 5, 4, 6] nums = [1, 2, 9, 5, 5, 5, 5, 5, 8, 2] s.wiggleSort(nums) print nums ############ comments ############ # 只能满足没有dup的情况

24.864407

74

0.362645

195

1,467

2.717949

0.297436

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0.169811

0.113208

0.339623

0.316981

0

0.075641

0.468303

1,467

58

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25.293103

0.603846

0.080436

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0.472222

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null

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null

0.083333

0

null

0

null

0

1

0

1

563378f9927ab2c4212b302cc8dcfd23528fc8a2

1,667

py

Python

mount_point.py

janglapuk/smstools-bot

e1bc4ee486b1425326028b68ce6d075cdcd6726d

[ "MIT" ]

null

mount_point.py

janglapuk/smstools-bot

e1bc4ee486b1425326028b68ce6d075cdcd6726d

[ "MIT" ]

null

mount_point.py

janglapuk/smstools-bot

e1bc4ee486b1425326028b68ce6d075cdcd6726d

[ "MIT" ]

1

2019-02-06T08:56:11.000Z

import spf, os from email.parser import Parser __author__ = "TRA" __doc__ = '''Modified mount point module''' RECEIVED = 'RECEIVED' SENT = 'SENT' FAILED = 'FAILED' REPORT = 'REPORT' class Bot(object, metaclass=spf.MountPoint): _runnable = False _program = None _headers = None _body = None trim = False def __init__(self, program): self._program = program self._runnable = self._program.event == self.bot_event self.__init() def __str__(self): return self.__class__.__name__ def __init(self): self.__read_message() self.__run() def __read_message(self): if os.path.isfile(self._program.fn): fn = self._program.fn f = None try: f = open(fn, 'r') raw = f.read() self.__parse_message(raw) except Exception as e: print(self, 'Exception:\n', e) else: f.close() def __run(self): if self.is_runnable(): self.run() def __parse_message(self, raw): parser = Parser() msg = parser.parsestr(raw) self._headers = {} for key in msg.keys(): # Force all keys to lowercase k = key.lower() self._headers[k] = msg.get(key) self._body = msg.get_payload() # Check if trim enabled and not binary body if self.trim and 'binary' not in self._headers.keys(): self._body = self._body.strip() def valid_event(self): return self.bot_event == self._program.event def is_runnable(self): return self._runnable def get_event(self): return self._program.event def get_headers(self): return self._headers def get_body(self): return self._body

20.084337

58

0.627475

221

1,667

4.402715

0.357466

0.079137

0.086331

0.032888

0

0.257349

1,667

82

59

20.329268

0.785945

0.041392

0

0.045768

0

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0.017241

0

null

0

null

0

1

0

1

565396c20414a45a7b60faed824ce5d1bc750a09

621

py

Python

kubernetes_typed/client/models/v1_iscsi_volume_source.py

nikhiljha/kubernetes-typed

4f4b969aa400c88306f92560e56bda6d19b2a895

[ "Apache-2.0" ]

22

2020-12-10T13:06:02.000Z

2022-02-13T21:58:15.000Z

kubernetes_typed/client/models/v1_iscsi_volume_source.py

nikhiljha/kubernetes-typed

4f4b969aa400c88306f92560e56bda6d19b2a895

[ "Apache-2.0" ]

4

2021-03-08T07:06:12.000Z

2022-03-29T23:41:45.000Z

kubernetes_typed/client/models/v1_iscsi_volume_source.py

nikhiljha/kubernetes-typed

4f4b969aa400c88306f92560e56bda6d19b2a895

[ "Apache-2.0" ]

2

2021-09-05T19:18:28.000Z

2022-03-14T02:56:17.000Z

# Code generated by `typeddictgen`. DO NOT EDIT. """V1ISCSIVolumeSourceDict generated type.""" from typing import TypedDict, List from kubernetes_typed.client import V1LocalObjectReferenceDict V1ISCSIVolumeSourceDict = TypedDict( "V1ISCSIVolumeSourceDict", { "chapAuthDiscovery": bool, "chapAuthSession": bool, "fsType": str, "initiatorName": str, "iqn": str, "iscsiInterface": str, "lun": int, "portals": List[str], "readOnly": bool, "secretRef": V1LocalObjectReferenceDict, "targetPortal": str, }, total=False, )

25.875

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621

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621

23

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0

1

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false

0

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0

0.105263

0

null

0

1

0

null

0

1

56700e57818953003d07b25e398460473fe1926b

525

py

Python

src/web_homepage/jinja.py

Mattan-Qwer/test1

16bc7642a18d632181480644d1f188c9fb3785bc

[ "Apache-2.0" ]

1

2021-07-25T12:46:08.000Z

src/web_homepage/jinja.py

Mattan-Qwer/test1

16bc7642a18d632181480644d1f188c9fb3785bc

[ "Apache-2.0" ]

3

2021-03-04T21:15:32.000Z

2021-05-15T22:01:11.000Z

src/web_homepage/jinja.py

Mattan-Qwer/test1

16bc7642a18d632181480644d1f188c9fb3785bc

[ "Apache-2.0" ]

2

2021-03-17T18:02:58.000Z

2021-07-15T17:58:28.000Z

from django.templatetags.static import static from django.urls import reverse from jinja2 import Environment from fontawesome_5.templatetags import fontawesome_5 from wissenslandkarte.settings import DEBUG, ENABLE_LIVE_JS def environment(**options): env = Environment(**options) env.globals.update({ 'static': static, 'url': reverse, 'fontawesome_5_static': fontawesome_5.fontawesome_5_static, 'debug': DEBUG, 'setting_enable_livejs' : ENABLE_LIVE_JS }) return env

26.25

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525

6.04918

0.42623

0.162602

0.065041

0

0.014151

0.192381

525

19

68

27.631579

0.856132

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0

0.333333

0

0.466667

0

null

0

null

0

1

0

1

5671326c276d2e23216bc6e77ae1e2508c743236

273

py

Python

app.py

EGeorge2021r/nft-marketplace

cc6a31f67e4657da72e59d5106a85b4d7dd0eb7f

[ "MIT" ]

null

app.py

EGeorge2021r/nft-marketplace

cc6a31f67e4657da72e59d5106a85b4d7dd0eb7f

[ "MIT" ]

5

2022-02-20T00:49:34.000Z

2022-02-25T21:29:49.000Z

app.py

EGeorge2021r/nft-marketplace

cc6a31f67e4657da72e59d5106a85b4d7dd0eb7f

[ "MIT" ]

2

2022-02-21T03:29:34.000Z

2022-03-04T00:46:46.000Z

import streamlit as st from multiapp import MultiApp from apps import buyer, home,creator # import your app modules here app = MultiApp() app.add_app("Home", home.home) app.add_app("Creator", creator.creator) app.add_app("Buyer", buyer.buyer) # The main app app.run()

18.2

67

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273

4.568182

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0.134328

0

0.139194

273

14

68

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0

0.375

0

null

0

null

0

1

0

1

56751bf83e23ee1f59d7cb7602bc4e9a2548390d

587

py

Python

library/tests/test_setup.py

edalatpour/unicornhatmini-python

d1bbfe8d4fdabad5a14489505ba3751386e2f990

[ "MIT" ]

32

2020-05-01T16:07:22.000Z

2022-03-18T13:02:54.000Z

library/tests/test_setup.py

edalatpour/unicornhatmini-python

d1bbfe8d4fdabad5a14489505ba3751386e2f990

[ "MIT" ]

10

2020-04-26T13:40:50.000Z

2022-01-06T14:22:03.000Z

library/tests/test_setup.py

edalatpour/unicornhatmini-python

d1bbfe8d4fdabad5a14489505ba3751386e2f990

[ "MIT" ]

19

2020-05-05T15:12:18.000Z

2022-03-31T09:18:20.000Z

import mock def test_setup(GPIO, spidev): from unicornhatmini import UnicornHATMini unicornhatmini = UnicornHATMini() spidev.SpiDev.assert_has_calls(( mock.call(0, 0), mock.call(0, 1) ), any_order=True) GPIO.setwarnings.assert_called_once_with(False) GPIO.setmode.assert_called_once_with(GPIO.BCM) del unicornhatmini def test_shutdown(GPIO, spidev, atexit): from unicornhatmini import UnicornHATMini unicornhatmini = UnicornHATMini() atexit.register.assert_called_once_with(unicornhatmini._exit) unicornhatmini._exit()

23.48

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68

587

6.147059

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0.267943

0.114833

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587

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0

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0

0.3125

0

null

1

0

null

0

1

567bcfdb694290f895bf395e9cbebe9b725dbb36

4,192

py

Python

namebench/appengine/models.py

chicks-net/namebench

8dd5e67ba3077650d49aa47a75a257e3286c8044

[ "Apache-2.0" ]

2

2017-12-13T00:39:46.000Z

2018-05-02T14:35:48.000Z

namebench/appengine/models.py

chicks-net/namebench

8dd5e67ba3077650d49aa47a75a257e3286c8044

[ "Apache-2.0" ]

null

namebench/appengine/models.py

chicks-net/namebench

8dd5e67ba3077650d49aa47a75a257e3286c8044

[ "Apache-2.0" ]

null

#!/usr/bin/env python # # Copyright 2010 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from google.appengine.ext import db from google.appengine.ext import webapp from google.appengine.ext.webapp import util class IndexHost(db.Model): record_type = db.StringProperty() record_name = db.StringProperty() listed = db.BooleanProperty() class NameServer(db.Model): ip = db.StringProperty() hostname = db.StringProperty() name = db.StringProperty() listed = db.BooleanProperty() city = db.StringProperty() region = db.StringProperty() country = db.StringProperty() country_code = db.StringProperty() coordinates = db.GeoPtProperty() is_global = db.BooleanProperty() is_regional = db.BooleanProperty() is_custom = db.BooleanProperty() url = db.LinkProperty() timestamp = db.DateTimeProperty(auto_now_add=True) class Submission(db.Model): client_id = db.IntegerProperty() submit_id = db.IntegerProperty() class_c = db.StringProperty() timestamp = db.DateTimeProperty(auto_now_add=True) listed = db.BooleanProperty() hidden = db.BooleanProperty() city = db.StringProperty() region = db.StringProperty() country = db.StringProperty() country_code = db.StringProperty() coordinates = db.GeoPtProperty() # de-normalized data, also duplicated in RunResults (though much slower) best_nameserver = db.ReferenceProperty(NameServer, collection_name='best_submissions') best_improvement = db.FloatProperty() primary_nameserver = db.ReferenceProperty(NameServer, collection_name="primary_submissions") class SubmissionConfig(db.Model): submission = db.ReferenceProperty(Submission, collection_name='config') input_source = db.StringProperty() benchmark_thread_count = db.IntegerProperty() health_thread_count = db.IntegerProperty() health_timeout = db.FloatProperty() timeout = db.FloatProperty() query_count = db.IntegerProperty() run_count = db.IntegerProperty() platform = db.StringProperty() version = db.StringProperty() class SubmissionNameServer(db.Model): nameserver = db.ReferenceProperty(NameServer, collection_name='submissions') submission = db.ReferenceProperty(Submission, collection_name='nameservers') is_error_prone = db.BooleanProperty() is_disabled = db.BooleanProperty() is_reference = db.BooleanProperty() overall_average = db.FloatProperty() check_average = db.FloatProperty() averages = db.ListProperty(float) duration_min = db.FloatProperty() duration_max = db.FloatProperty() error_count = db.IntegerProperty() timeout_count = db.IntegerProperty() nx_count = db.IntegerProperty() position = db.IntegerProperty() sys_position = db.IntegerProperty() version = db.StringProperty() node_ids = db.ListProperty(str) # TODO(tstromberg): Remove obsoleted improvement variable improvement = db.FloatProperty() diff = db.FloatProperty() notes = db.ListProperty(str) port_behavior = db.StringProperty() # Store one row per run for run_results, since we do not need to do much with them. class RunResult(db.Model): submission_nameserver = db.ReferenceProperty(SubmissionNameServer, collection_name='results') run_number = db.IntegerProperty() durations = db.ListProperty(float) answer_counts = db.ListProperty(int) # We may want to compare index results, so we will store one row per record class IndexResult(db.Model): submission_nameserver = db.ReferenceProperty(SubmissionNameServer, collection_name='index_results') index_host = db.ReferenceProperty(IndexHost, collection_name='results') duration = db.FloatProperty() answer_count = db.IntegerProperty() ttl = db.IntegerProperty() response = db.StringProperty()

37.428571

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4,192

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0

1

0

null

0

null

0

1

0

1

567e66953f9087009e3135f6fcd09362a85c10a2

416

py

Python

PE/PE77.py

bristy/codemania

ceaacce07cb1b66202e17ad313a3467bd591bdc1

[ "MIT" ]

null

PE/PE77.py

bristy/codemania

ceaacce07cb1b66202e17ad313a3467bd591bdc1

[ "MIT" ]

null

PE/PE77.py

bristy/codemania

ceaacce07cb1b66202e17ad313a3467bd591bdc1

[ "MIT" ]

null

# https://projecteuler.net/problem=77 from prime_util import sieve MAX = 5000 INF = 1 << 31 def pe77(): primes, s = sieve(MAX) dp = [0] * MAX dp[0] = 1 for p in primes: w = p while w < MAX: dp[w] = dp[w] + dp[w - p] w += 1 for i, p in enumerate(dp): if p > 5000: print i, p break if __name__ == '__main__': pe77()

16

37

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62

416

2.967742

0.532258

0.081522

0.065217

0

0.08502

0.40625

416

25

38

16.64

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0.084135

0

0.021108

0

null

0

0.055556

null

0.055556

0

null

0

null

0

1

0

1

5691317d3c567d014aec439954667396b59f6a2b

735

py

Python

src/my_pytube/__init__.py

mjmartinson/intravideo_search

7c123f515d0e9fb0934cae5894088a0dabcb166f

[ "MIT" ]

null

src/my_pytube/__init__.py

mjmartinson/intravideo_search

7c123f515d0e9fb0934cae5894088a0dabcb166f

[ "MIT" ]

null

src/my_pytube/__init__.py

mjmartinson/intravideo_search

7c123f515d0e9fb0934cae5894088a0dabcb166f

[ "MIT" ]

null

# -*- coding: utf-8 -*- # flake8: noqa # noreorder """ Pytube: a very serious Python library for downloading YouTube Videos. """ __title__ = 'my_pytube' __version__ = '9.5.2' __author__ = 'Nick Ficano' __license__ = 'MIT License' __copyright__ = 'Copyright 2019 Nick Ficano' #import logging #import query #import streams #import captions #import contrib #import __main__ from my_pytube.logging import create_logger from my_pytube.query import CaptionQuery from my_pytube.query import StreamQuery from my_pytube.streams import Stream from my_pytube.captions import Caption from my_pytube.contrib.playlist import Playlist from my_pytube.__main__ import YouTube logger = create_logger() logger.info('%s v%s', __title__, __version__)

22.96875

69

0.786395

100

735

5.32

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0.120301

0.157895

0.06391

0.086466

0

0.014041

0.127891

735

31

70

23.709677

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0.270748

0

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0

1

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false

0

0.5

0

0.5

0

null

0

null

0

1

0

1

56960d66f7d4e91cd7177d74b8b5d014ec97d10d

634

py

Python

setup.py

AjayMT/emitter

8b8c1aaab39ca858a59ad45a36f22f2737a0d46a

[ "MIT" ]

1

2021-01-04T05:29:49.000Z

setup.py

AjayMT/emitter

8b8c1aaab39ca858a59ad45a36f22f2737a0d46a

[ "MIT" ]

null

setup.py

AjayMT/emitter

8b8c1aaab39ca858a59ad45a36f22f2737a0d46a

[ "MIT" ]

null

#!/usr/bin/env python from distutils.core import setup setup( name='emitter', version='0.0.7', description='simple event emitter', author='Ajay MT', author_email='ajaymt@icloud.com', url='http://github.com/ajaymt/emitter', download_url='https://github.com/AjayMT/emitter/tarball/v0.0.7', py_modules=['emitter'], keywords='emitter event eventemitter node', classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Operating System :: POSIX', 'Programming Language :: Python', ] )

27.565217

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634

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0.736111

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0.110553

0

0.014056

0.214511

634

22

69

28.818182

0.785141

0.031546

0

0.535073

0

1

0

true

0

0.052632

0

0.052632

0

null

0

null

0

1

0

1

5697543911acf8f5ff9fcad51bfbbe032aa5d07b

358

py

Python

preprocessing/extract_hashtags.py

acvander/kaggle_real_or_not

737d949b1f8446e734ed5113b84b5b199a7aee3c

[ "MIT" ]

null

preprocessing/extract_hashtags.py

acvander/kaggle_real_or_not

737d949b1f8446e734ed5113b84b5b199a7aee3c

[ "MIT" ]

10

2020-02-11T19:07:36.000Z

2022-02-09T23:35:13.000Z

preprocessing/extract_hashtags.py

acvander/kaggle_real_or_not

737d949b1f8446e734ed5113b84b5b199a7aee3c

[ "MIT" ]

null

import re import pandas as pd def extract_hashtags(df: pd.DataFrame) -> pd.DataFrame: pattern = re.compile(r'#(\w+)') def get_hashtags(row: pd.Series) -> pd.Series: text = row['text'] hashtags = re.findall(pattern, text) row['hashtags'] = hashtags return row df = df.apply(get_hashtags, axis=1) return df

21.058824

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358

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0

0.003731

0.251397

358

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0

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0

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0

0.545455

0

null

0

null

0

1

0

1

56978a1f08405d1e9c9e366fa78cdc804de04d55

1,472

py

Python

app/app.py

escofresco/makeschool_fsp2_realtweets

a1df7c54e5ef3d5a91282141389200248b40f695

[ "MIT" ]

null

app/app.py

escofresco/makeschool_fsp2_realtweets

a1df7c54e5ef3d5a91282141389200248b40f695

[ "MIT" ]

9

2019-11-17T22:33:15.000Z

2021-06-02T00:37:50.000Z

app/app.py

escofresco/makeschool_fsp2_realtweets

a1df7c54e5ef3d5a91282141389200248b40f695

[ "MIT" ]

null

import marshal from multiprocessing import Condition, Process, Queue, Pipe import os from threading import Timer from types import FunctionType import pickle from celery import Celery from flask import Flask, url_for from grams.grams import Histogram from grams.markov import MC import time def make_app(): def make_model(): def _make_model(corpus, n_sentences=10): # global cv def _generate(): markovchain = MC(corpus) return markovchain.generate generate = _generate() child_conn.send(generate(n_sentences)) while True: if parent_conn.poll(): ## previously sent message got consumed # send another child_conn.send(generate(n_sentences)) parent_conn, child_conn = Pipe(duplex=True) with open("res/the_adventures_of_sherlock_holmes.txt", "r") as f: f_out = f.read() make_process = Process(target=_make_model, args=(f_out,)) make_process.start() return parent_conn, make_process # init app flask_app = Flask(__name__) parent_conn, make_process = make_model() @flask_app.route("/") def home(): if parent_conn.poll(): return parent_conn.recv() return "loading..." return flask_app flask_app = make_app() if __name__ == "__main__": flask_app.run(debug=True, port=8080)

23.365079

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0.293478

1,472

62

74

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0.828846

0.046196

0

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0

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0.029328

0

1

0.128205

false

0

0.282051

0

0.538462

0

null

0

null

0

1

0

1

56a4c4a9da8e522b22406ce899d916afef096ab3

427

py

Python

apps/blog/template.py

Bean-jun/PersonBlogSystemFlask

7935dfa8e8f1a385a296267045f6f26e03fd6b18

[ "MIT" ]

null

apps/blog/template.py

Bean-jun/PersonBlogSystemFlask

7935dfa8e8f1a385a296267045f6f26e03fd6b18

[ "MIT" ]

null

apps/blog/template.py

Bean-jun/PersonBlogSystemFlask

7935dfa8e8f1a385a296267045f6f26e03fd6b18

[ "MIT" ]

null

from flask import request from apps.blog import home_blueprint from apps.models import Category @home_blueprint.app_template_global("category_navigate") def category_navigate(): """导航栏""" category_obj = Category.query.all() return category_obj # 前端template页面可以使用这部分获取，或者直接使用request.user亦可 @home_blueprint.app_template_global("userinfo_navigate") def userinfo_navigate(): """导航栏头像""" return request.user

23.722222

56

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51

427

6.27451

0.509804

0.121875

0.1

0.15

0.1875

0

0.124122

427

17

57

25.117647

0.855615

0.124122

0

0.093664

0

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0.2

false

0

0.3

0

0.7

0.3

0

null

0

null

0

1

0

1

3b0964e54ac0934e525bad71399782f8aff00bb9

377

py

Python

alshamelah_api/apps/authors/models.py

devna-dev/durar-backend

36ea29bafd4cb95098e4057eb71df211dc923008

[ "MIT" ]

null

alshamelah_api/apps/authors/models.py

devna-dev/durar-backend

36ea29bafd4cb95098e4057eb71df211dc923008

[ "MIT" ]

null

alshamelah_api/apps/authors/models.py

devna-dev/durar-backend

36ea29bafd4cb95098e4057eb71df211dc923008

[ "MIT" ]

null

from django.db import models from django.utils.translation import ugettext_lazy as _ from ..core.models import BaseModel class Author(BaseModel): name = models.CharField(max_length=100, verbose_name=_(u'name'), null=False, blank=False) class Meta: verbose_name_plural = "Authors" ordering = ['name'] def __str__(self): return self.name

23.5625

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49

377

5.183673

0.653061

0.07874

0

0.009934

0.198939

377

15

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0

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0

1

0.1

false

0

0.3

0.1

0.8

0

null

0

null

0

1

0

1

3b13ffb0d8a69d11829542e3e7415101aea54667

394

py

Python

2020/2/2-1.py

jonathonball/adventofcode

041f3bb2b1ebe3ddcb21341bf52f29512e17a326

[ "MIT" ]

1

2020-01-17T18:59:59.000Z

2020/2/2-1.py

jonathonball/adventofcode

041f3bb2b1ebe3ddcb21341bf52f29512e17a326

[ "MIT" ]

null

2020/2/2-1.py

jonathonball/adventofcode

041f3bb2b1ebe3ddcb21341bf52f29512e17a326

[ "MIT" ]

null

#!/usr/bin/python3 import sys total_valid = 0 for line in sys.stdin: raw = line.strip() rules, password = raw.split(":") ranges, character = rules.split(" ") min_range, max_range = [ int(x) for x in ranges.split("-") ] count = password.count(character) if count >= min_range and count <= max_range: total_valid += 1 print(total_valid)

23.176471

64

0.598985

53

394

4.320755

0.54717

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0.010417

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16

65

24.625

0.784722

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0

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false

0.181818

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0.090909

0

null

0

null

0

1

0

1

3b1fa76083519e9576fd893b3ec3da51308b56e5

2,644

py

Python

test_auth_app/backend/db_set_users.py

MalyshevValery/testweb

fec105a62b0ef4488e523e1bf3a9bde16e82bffe

[ "MIT" ]

null

test_auth_app/backend/db_set_users.py

MalyshevValery/testweb

fec105a62b0ef4488e523e1bf3a9bde16e82bffe

[ "MIT" ]

null

test_auth_app/backend/db_set_users.py

MalyshevValery/testweb

fec105a62b0ef4488e523e1bf3a9bde16e82bffe

[ "MIT" ]

null

import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import warnings warnings.simplefilter(action='ignore', category=FutureWarning) __author__ = "eduard.snezhko@gmail.com" from test_auth_app.backend import test_auth_app_db from test_auth_app.backend.db_models import User, Role, Application from test_auth_app.backend.db_models import get_default_roles from uuid import uuid1 def clear_database(): users = User.query.all() for u in users: test_auth_app_db.session.delete(u) roles = Role.query.all() for r in roles: test_auth_app_db.session.delete(r) apps = Application.query.all() for a in apps: test_auth_app_db.session.delete(a) test_auth_app_db.session.commit() def list_users(): users = User.query.all() for u in users: print('\n{}:\n\t{}\n\t{}\n{}\n{}\n{}\nvalid = {}'.format(u.id, u.email, u.user_uid, u.roles, u.applications, u.password_hash, u.validated)) def list_roles(): roles = Role.query.all() for r in roles: print('{}:\n\t{}\n\t{}\n'.format(r.id, r.role, r.description)) def list_applications(): apps = Application.query.all() for a in apps: print('{}:\n\t{}\n\t{}\n'.format(a.id, a.name, a.description)) def init_prod_database(): user_1 = User(email='empty@email.org', user_uid=str(uuid1())) role_read = Role(role='read', description='Can list, view and download cases related to a user') role_read_all = Role(role='read_all', description='Can list, view and download all cases related to all user (as admin)') role_edit = Role(role='edit', description='Can add new case, run case processing, clear processing results and case delete. Case is relevant to a particular user') role_edit_all = Role(role='edit_all', description='Can run case processing, clear processing results and case delete. Case may be relevant to any user (as admin)') app_lungs = Application(name='lungs', description='Lungs segmentation on CT images using CNNs') app_lesions = Application(name='lesions', description='Lesions segmentation in lungs on CT images using CNNs') # Default Anonymous user has access only to the example cases, to list them, preview and download. # All apps are available user_1.set_password('empty') user_1.roles.append(role_read) user_1.roles.append(role_edit) user_1.set_validated(True) user_1.applications.append(app_lungs) user_1.applications.append(app_lesions) test_auth_app_db.session.add(user_1) test_auth_app_db.session.commit() if __name__ == '__main__': # clear_database() # init_prod_database() # list_users() pass

34.789474

167

0.708396

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2,644

4.352798

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0.044718

0.061487

0.050866

0.428731

0.329793

0.220235

0.202348

0.062605

0

0.005005

0.168684

2,644

75

168

35.253333

0.808917

0.064297

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0.024311

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0.1

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0.06

0.12

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0.22

0.06

0

null

0

null

0

1

0

1

3b212170dc8dc576e182a858e68aeef56e1e1acd

1,232

py

Python

activecollab_digger/views.py

kingsdigitallab/django-activecollab-digger

508c31eb4a3fe9887aa9d3a86ea160f3bc1e60b0

[ "MIT" ]

null

activecollab_digger/views.py

kingsdigitallab/django-activecollab-digger

508c31eb4a3fe9887aa9d3a86ea160f3bc1e60b0

[ "MIT" ]

null

activecollab_digger/views.py

kingsdigitallab/django-activecollab-digger

508c31eb4a3fe9887aa9d3a86ea160f3bc1e60b0

[ "MIT" ]

null

from django.conf import settings from django.contrib.auth.mixins import LoginRequiredMixin from django.http import JsonResponse from django.views.generic.base import TemplateView from .activecollab import get_activecollab, post_activecollab class IndexPageView(LoginRequiredMixin, TemplateView): template_name = 'activecollab_digger/index.html' def tasks(request): if request.method == 'POST': return _post_task(request) return _get_tasks(request) def _get_tasks(request): r = get_activecollab('projects/{}/tasks'.format(settings.AC_PROJECT_ID)) if r.status_code != 200: return JsonResponse({'error': r.status_code, 'message': r.json()['message']}) return JsonResponse(r.json()) def _post_task(request): params = { 'name': request.POST.get('name'), 'body': request.POST.get('body'), 'created_by_id': settings.AC_USER } r = post_activecollab('projects/{}/tasks'.format(settings.AC_PROJECT_ID), params=params) if r.status_code != 200: return JsonResponse({'error': r.status_code, 'message': r.json()['message']}) return JsonResponse(r.json())

27.377778

77

0.659091

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1,232

5.58156

0.347518

0.050826

0.055909

0.07878

0.360864

0.233799

0

0.006244

0.219968

1,232

44

78

28

0.812695

0

0.275862

0

0.109578

0.024351

0

1

0.103448

false

0

0.172414

0

0.551724

0

null

0

null

0

1

0

1

3b29c188db2f818925355ab781e7bf18b7f0fea1

933

py

Python

pool.py

Reno-Greenleaf/tomb

6a76f640e523903f32c5fa178295435a24289559

[ "MIT" ]

null

pool.py

Reno-Greenleaf/tomb

6a76f640e523903f32c5fa178295435a24289559

[ "MIT" ]

null

pool.py

Reno-Greenleaf/tomb

6a76f640e523903f32c5fa178295435a24289559

[ "MIT" ]

null

from actor import Actor, Location, Passage, Switch, Ghost from json import load class Pool(dict): """ Contains ingame objects. """ def fill(self): with open('data/actors.json', 'r') as data: actors = load(data) for name, properties in actors.items(): self._build(properties, name) with open('data/space.json', 'r') as data: self.space = load(data) def get_rooms(self): return self.space def _build(self, properties, name): actor = Actor() actor.load(properties) if 'io' not in properties: self[name] = actor return if 'labyrinth' in properties: actor = Location(actor) if 'labyrinth' in properties and 'right' in properties['labyrinth']: actor = Passage(actor) if 'access' in properties and 'used' in properties['access']: actor = Switch(actor) elif 'access' in properties: actor = Ghost(actor) self[name] = actor

24.552632

72

0.639871

121

933

4.909091

0.355372

0.141414

0.040404

0.037037

0

0.239014

933

38

73

24.552632

0.83662

0.025723

0

0.074074

0

0.09867

0

1

0.111111

false

0.074074

0.037037

0.296296

0

null

0

null

0

1

0

1

3b2f210471d573b08554a8de2790e7a4843a9bc9

1,072

py

Python

tests/test_equity.py

the-Arki/portfolio-tracker

eed07936876d720d29383d315003a11e9f6a2ee9

[ "MIT" ]

null

tests/test_equity.py

the-Arki/portfolio-tracker

eed07936876d720d29383d315003a11e9f6a2ee9

[ "MIT" ]

null

tests/test_equity.py

the-Arki/portfolio-tracker

eed07936876d720d29383d315003a11e9f6a2ee9

[ "MIT" ]

null

from defer import return_value from src.stock import Equity from src.io_manager import read_json import pytest equity_info = read_json('./tests/equity_info.json') equity = Equity('MSFT') def test__get_info(mocker): mocker.patch('src.stock.Equity._get_info', return_value=equity_info) assert equity._get_info() == equity_info def test_instance_info(mocker): mocker.patch('src.stock.Equity._get_info', return_value=equity_info) equity = Equity('MSFT') assert equity.info == equity_info def test_instance_currency(mocker): mocker.patch('src.stock.Equity._get_info', return_value=equity_info) equity = Equity('MSFT') assert equity.currency == equity_info['currency'] def test_instance_tradeable(mocker): mocker.patch('src.stock.Equity._get_info', return_value=equity_info) equity = Equity('MSFT') assert equity.tradeable == equity_info['tradeable'] def test_tradeable(): assert equity.is_tradeable() == equity_info['tradeable'] def test_tradeable_returns_boolean(): assert isinstance(equity.is_tradeable(), bool)

31.529412

72

0.75653

147

1,072

5.217687

0.204082

0.156454

0.084746

0.104302

0.617992

0.542373

0.42764

0

0.125933

1,072

34

73

31.529412

0.81857

0

0.32

0

0.158434

0.119292

0

0.24

1

0.24

false

0

0.16

0

0.4

0

null

0

null

0

1

0

1

3b35bf097dce90dcfad194835db3744ff6739f05

326

py

Python

mindefuse/strategy/swaszek/agent/agent.py

sinistro14/mindefuse

c7371a81731d0b9a03d3ef18f91c336e4135c17d

[ "MIT" ]

null

mindefuse/strategy/swaszek/agent/agent.py

sinistro14/mindefuse

c7371a81731d0b9a03d3ef18f91c336e4135c17d

[ "MIT" ]

1

2019-08-22T19:51:12.000Z

mindefuse/strategy/swaszek/agent/agent.py

sinistro14/mindefuse

c7371a81731d0b9a03d3ef18f91c336e4135c17d

[ "MIT" ]

null

#!/usr/bin/env python3.7 from abc import ABC, abstractmethod class Agent(ABC): @abstractmethod def agent_choice(self, possibilities): """ Returns the choice of the specific agent :param possibilities: list of all possible solutions of which the agent will pick one """ pass

21.733333

93

0.656442

41

326

5.195122

0.707317

0.159624

0

0.008439

0.273006

326

14

94

23.285714

0.890295

0.460123

0

1

0.2

false

0.2

0

0.6

0

null

0

null

0

1

0

1

3b36c4ed7d21b51f5c92a0c2c42d4ae3822cf137

4,497

py

Python

Python/klampt/robotcspace.py

bbgw/Klampt

3c022da372c81646ec9f7492fad499740431d38b

[ "BSD-3-Clause" ]

null

Python/klampt/robotcspace.py

bbgw/Klampt

3c022da372c81646ec9f7492fad499740431d38b

[ "BSD-3-Clause" ]

null

Python/klampt/robotcspace.py

bbgw/Klampt

3c022da372c81646ec9f7492fad499740431d38b

[ "BSD-3-Clause" ]

null

import cspace import robotsim import robotcollide from cspaceutils import AdaptiveCSpace class RobotCSpace(AdaptiveCSpace): """A basic robot cspace that allows collision free motion. Warning: if your robot has non-standard joints, like a free- floating base or continuously rotating (spin) joints, you will need to overload the sample() method.""" def __init__(self,robot,collider=None): AdaptiveCSpace.__init__(self) self.robot = robot self.bound = zip(*robot.getJointLimits()) self.collider = collider #set this to false to turn off the adaptive tester, which may #have some overhead self.adaptive = True #adaptive tests self.addFeasibleTest(lambda(x): self.inJointLimits(x),"joint limits") #TODO explode these into individual self collision / env collision #tests self.addFeasibleTest(lambda(x): not self.selfCollision(),"self collision") self.addFeasibleTest(lambda(x): not self.envCollision(),"env collision") def sample(self): """Overload this to implement custom sampling strategies or to handle non-standard joints""" return AdaptiveCSpace.sample(self) def feasible(self,x): """Feasibility test. If self.adaptive=True, uses the adaptive feasibility tester which may speed up collision testing.""" if self.adaptive: #Use the adaptive tester self.robot.setConfig(x) return AdaptiveCSpace.feasible(self,x) #Use the regular tester if not self.inJointLimits(x): return False #check collisions if self.collider: self.robot.setConfig(x) if self.selfCollision(): return False if self.envCollision(): return False return True def inJointLimits(self,x): """Checks joint limits of the configuration x""" for (xi,bi) in zip(x,self.bound): if xi < bi[0] or xi > bi[1]: return False return True def selfCollision(self): """Checks whether the robot at its current configuration is in self collision""" #This should be faster than going through the collider... return self.robot.selfCollides() #if not self.collider: return False #return any(self.collider.robotSelfCollisions(self.robot.index)) def envCollision(self): """Checks whether the robot at its current configuration is in collision with the environment.""" if not self.collider: return False for o in xrange(self.collider.world.numRigidObjects()): if any(self.collider.robotObjectCollisions(self.robot.index,o)): return True; for o in xrange(self.collider.world.numTerrains()): if any(self.collider.robotTerrainCollisions(self.robot.index,o)): return True; return False class ClosedLoopRobotCSpace(RobotCSpace): """A closed loop cspace. Allows one or more IK constraints to be maintained during the robot's motion.""" def __init__(self,robot,iks,collider=None): RobotCSpace.__init__self(robot,collider) self.solver = robotsim.IKSolver(robot) if hasattr(iks,'__iter__'): for ik in iks: self.solver.add(ik) else: self.solver.add(ik) #IK solve iterations self.maxIters = 100 self.tol = 1e-3 #adaptive checker self.addFeasibleTest(lambda(x): self.closedLoop()) def sample(self): """Samples directly on the contact manifold""" self.solver.sampleInitial() (res,iters) = self.solver.solve(self.maxIters,self.tol) return self.robot.getConfig() def feasible(self,x): if self.adaptive: #Use the adaptive tester self.robot.setConfig(x) return AdaptiveCSpace.feasible(self,x) if not self.inJointLimits(x): return False self.robot.setConfig(x) if not self.closedLoop(): return False; if self.selfCollision(): return False if self.envCollision(): return False return True def closedLoop(self,tol=None): """Returns true if the closed loop constraint has been met at the robot's current configuration.""" e = self.solver.getError() if tol==None: tol = self.tol return max(abs(ei) for ei in e) <= tol

35.976

82

0.632866

537

4,497

5.26257

0.318436

0.041401

0.015924

0.036801

0.302902

0.255485

0.194621

0.150035

0

0.002155

0.277741

4,497

124

83

36.266129

0.867919

0.096731

0

0.375

0

0.01528

0

0.008065

0

null

0

0.055556

null

0

null

0

null

0

1

0

1

3b3d82864cc0776c4af3325f627956c088809c05

673

py

Python

footy/test/clubs/test_club_gateway.py

bryce-klinker/hello-python

c62ac61f40c1d9fcb77dbde49161da399787d96d

[ "MIT" ]

null

footy/test/clubs/test_club_gateway.py

bryce-klinker/hello-python

c62ac61f40c1d9fcb77dbde49161da399787d96d

[ "MIT" ]

null

footy/test/clubs/test_club_gateway.py

bryce-klinker/hello-python

c62ac61f40c1d9fcb77dbde49161da399787d96d

[ "MIT" ]

null

import unittest from nose.tools import * from footy.test_data.test_data_paths import premier_league_2015_2016_path from footy.src.clubs.club_gateway import ClubGateway class ClubGatewayTest(unittest.TestCase): def setUp(self): self.gateway = ClubGateway(premier_league_2015_2016_path) def test_get_all_clubs(self): clubs = self.gateway.get_all() self.assertEquals(20, len(clubs)) def test_get_all_clubs_includes_club_name(self): clubs = self.gateway.get_all() self.assertEquals("Arsenal", clubs[0].name) self.assertEquals("Aston Villa", clubs[1].name) self.assertEquals("Bournemouth", clubs[2].name)

32.047619

73

0.732541

91

673

5.164835

0.428571

0.051064

0.07234

0.089362

0.361702

0.178723

0

0.0375

0.167905

673

20

74

33.65

0.801786

0

0.133333

0

0.043091

0

0.266667

1

0.2

false

0

0.266667

0

0.533333

0

null

0

null

0

1

0

1

3b466b48be2d2a162d6c9c6df33ff4e475906464

735

py

Python

k-way_merge/k_smallest_number.py

mridulpant2010/algorithms

1234b8a0232d6fce647e868e1057b6ec87e0b3bb

[ "Unlicense" ]

null

k-way_merge/k_smallest_number.py

mridulpant2010/algorithms

1234b8a0232d6fce647e868e1057b6ec87e0b3bb

[ "Unlicense" ]

null

k-way_merge/k_smallest_number.py

mridulpant2010/algorithms

1234b8a0232d6fce647e868e1057b6ec87e0b3bb

[ "Unlicense" ]

null

import heapq def find_k_closest_numbers(lis,k,n): he=[] #merged=[] heapq.heapify(he) for i in range(len(lis)): heapq.heappush(he,(lis[i][0],(i,0))) #print(he,len(he)) numberCount=0 top=0 while he: top,pos=heapq.heappop(he) #print(top,pos) x,y=pos numberCount+=1 if numberCount==k: break if n>y+1 : heapq.heappush(he,(lis[x][y+1],(x,y+1))) return top if __name__ == '__main__': arr=[[2, 6, 8], [3, 6, 7], [1, 3, 4]] n=len(arr) ans=find_k_closest_numbers(arr, 5,n) arr2=[[2, 6, 8], [3, 7, 10], [5, 8, 11]] ans2=find_k_closest_numbers(arr2,5,n) print(ans,ans2)

24.5

53

0.50068

117

735

3

0.393162

0.042735

0.102564

0.162393

0

0.067864

0.318367

735

30

54

24.5

0.632735

0.054422

0

0.012066

0

1

0.041667

false

0

0.041667

0

0.125

0.041667

0

null

0

1

0

null

0

1

3b49afd725f055d1a828c47230e22c3488471dc9

6,617

py

Python

abintb/spin.py

abyellow/abin-tight-binding

538aef632937b1840d5ffd184f162858637b01f5

[ "MIT" ]

1

2018-02-22T19:13:24.000Z

abintb/spin.py

abyellow/abin-tight-binding

538aef632937b1840d5ffd184f162858637b01f5

[ "MIT" ]

null

abintb/spin.py

abyellow/abin-tight-binding

538aef632937b1840d5ffd184f162858637b01f5

[ "MIT" ]

1

2017-09-14T17:25:09.000Z

import numpy as np from time import time #from itertools import product import sys import matplotlib.pyplot as plt #from matplotlib.colors import LogNorm from sshPES import PES from sshIniData import SSHIniData from sshHf import SSHHf #from mpl_toolkits.mplot3d import Axes3D class pseudoSpin(PES): def integral_PES(self,PESx,PESy,lb,ub,rang,form,line = True): w_num = self.w_num PESy = np.array(PESy) PESx = np.array(PESx) pl = int((np.pi-lb)/(2*np.pi) * w_num) pu = int((np.pi-ub)/(2*np.pi) * w_num) pr = int((rang)/(2*np.pi) * w_num)+1 absPESy = abs(PESy) intPESy = [] intPESx = [] if form == 'box': for i in range(len(PESy[0,:])): intPESy.append(np.sum(PESy[pu:pl,i],axis=0)) intPESx.append(np.sum(PESx[pu:pl,i],axis=0)) if line: PESx[pu,i] = 100 PESy[pl,i] = 100 PESx[pl,i] = 100 PESy[pu,i] = 100 elif form == 'wave': for i in range(len(PESy[0,:])): ind = pu + np.argmax(absPESy[pu:pl,i]) intPESy.append(np.sum(PESy[ind-pr:ind+pr,i],axis=0)) intPESx.append(np.sum(PESx[ind-pr:ind+pr,i],axis=0)) if line: PESx[ind-pr,i] = 100 PESy[ind-pr,i] = 100 PESx[ind+pr,i] = 100 PESy[ind+pr,i] = 100 intPESx.append(intPESx[0]) intPESy.append(intPESy[0]) return np.array(intPESx), np.array(intPESy), PESx, PESy def phase(self,x,y): phi = np.sign(y)*np.arccos(x/np.sqrt(x**2+y**2)) phb = phi[-1]-phi[0] x,y = self.norm_spin(x,y,factor=False) ox = y[1:]-y[:-1] oy = -(x[1:]-x[:-1]) drx = (x[1:]+x[:-1])/2. dry = (y[1:]+y[:-1])/2. pha = np.sum(ox*drx + oy*dry) return pha, phb def norm_spin(self,x,y,factor=True): fac = 1 if factor: fac = np.linspace(1,2,len(x)) r = np.sqrt(x**2+y**2) x, y = fac*x/r, fac*y/r #x=np.insert(x,0,1) #y=np.insert(y,0,0) #x=np.insert(x,len(x),2) #y=np.insert(y,len(y),0) return x, y def plot_spin(self,x,y, norm = True): if norm: x, y = self.norm_spin(x,y) plt.figure() plt.quiver(x[:-1], y[:-1], x[1:]-x[:-1], y[1:]-y[:-1], scale_units='xy', angles='xy', scale=1) #plt.plot(x, y, 'o-',linewidth=1.5) plt.plot(0,0,'x',markersize = 20) plt.plot(np.linspace(-3,3,len(x)),np.zeros(len(x)),'g--') plt.xlabel('Px') plt.ylabel('Py') plt.xlim([-2.1,2.1]) plt.ylim([-2.1,2.1]) #plt.title('tp = %.1f, E0 = %.1f, Freq = %.2f, dt = %.1f' %(tp0,E0,freq,deltau)) #plt.savefig('figure/sshspin_spin.png') def phase_PES(self,PESx,PESy): PESint = np.sqrt(PESx**2 + PESy**2) PESphi = np.pi*(1-np.sign(PESy))/2 + np.arccos(PESx/PESint) - np.pi print np.amax(PESphi) return PESint*PESphi/(4*np.pi) if __name__ == "__main__": tp0 = 0. E0 = 1. freq = 3. tau = 1. deltau = .5 paui = 'x' pauj = 'y' k_num = 12*6 width = 50 h_choose = 0 band = 'mix' option = 0 int_form = 'box' int_lb = -1.6#0#-3.#2.0 int_ub = -.8#.8#0#-2.#3.0 int_rang = .25 int_line = False import argparse pa = argparse.ArgumentParser() pa.add_argument('--f', type = float) pa.add_argument('--E', type = float) pa.add_argument('--dt', type = float) pa.add_argument('--tp', type = int) pa.add_argument('--model', type = int) pa.add_argument('--k', type = int) pa.add_argument('--opt', type = int) pa.add_argument('--wid', type = int) pa.add_argument('--lb', type = float) pa.add_argument('--ub', type = float) args = pa.parse_args() if args.f: freq = args.f if args.E: E0 = args.E if args.dt: deltau = args.dt if args.tp: tp0 = args.tp if args.model: h_choose = args.model if args.k: k_num = args.k if args.opt: option = args.opt if args.wid: width = args.wid if args.lb: int_lb = args.lb if args.ub: int_ub = args.ub cond = 'Conditions: model = %d, deltau = %.2f, freq = %.2f, E0 = %.2f, tp0 = %d, knum = %d, p_width = %d'\ %(h_choose, deltau, freq, E0, tp0, k_num,width) print cond t_s = -200 dt = .1 std1 = 15 t_in = t_s-std1*3 #print 'width of pulse: ',width #/ np.sqrt(2) n_tot = int(-2*t_s/dt) + int(std1*6/dt) t_rel = (np.array(range(n_tot-1)))*dt + t_in ctrl = np.exp(-.5*(t_rel/width)**2) * E0 * np.sin(freq*t_rel) m_max = 10 hf = SSHHf(deltau = (-1)**(h_choose) * deltau, m_max = m_max, freq = freq, E0 = E0, phase = 2, knum=k_num) def plot_hf(): eps = hf.eps spec = hf.spec() nk = k_num for i in range(np.shape(spec)[1]): plt.plot(eps/2.,spec[:,i],'k--',linewidth=2.) plt.xlim([-3.15/2.,3.15/2.]) plt.ylim([-3.15,3.15]) timea = time() init = SSHIniData(tau, deltau, ctrl, knum=k_num, dt=dt, ham_choose = h_choose, iniband= band) cvec1 = init.clc_cvec() PES_spin = pseudoSpin(init, cvec1, tin = t_in, E0=E0, freq=freq, std = std1, width = 1) try: load_i = 'data/PES2ssh_ham_%d_dt_%.2f_ktimes_%d_tp_%.1f_E0_%.1f_freq_%.2f_deltau_%.1f_paui_%s_std_%.1f_band_%s.txt'\ %(h_choose, dt,k_num,tp0,E0,freq,deltau,paui,std1,band) PESloadi = np.loadtxt(load_i)[::-1] print "file1 exist, loading====>" except IOError: print load_i print "no such file, calculating====>" PESloadi = PES_spin.final_run(tp = tp0, pau = paui)[::-1] try: load_j = 'data/PES2ssh_ham_%d_dt_%.2f_ktimes_%d_tp_%.1f_E0_%.1f_freq_%.2f_deltau_%.1f_paui_%s_std_%.1f_band_%s.txt'\ %(h_choose, dt,k_num,tp0,E0,freq,deltau,pauj,std1,band) PESloadj = np.loadtxt(load_j)[::-1] print "file2 exist, loading====>" except IOError: print load_j print "no such file, calculating====>" PESloadj = PES_spin.final_run(tp = tp0, pau = pauj)[::-1] # timea = time() PES2Dx = PESloadi PES2Dy = PESloadj print 'total time:', time()-timea if option == 1: x, y, PES2Dx, PES2Dy = PES_spin.integral_PES(PES2Dx,PES2Dy,int_lb,int_ub,int_rang,form=int_form,line = True) PES_spin.plot_spin(x,y) plt.title(cond) plt.show() x1,y1 = PES_spin.norm_spin(x,y,factor=False) savename = 'data/spin_ham_%d_dt_%.2f_ktimes_%d_tp_%.1f_E0_%.1f_freq_%.2f_deltau_%.1f_std_%.1f_band_%s_lb_%.1f_ub_%.1f.txt'\ %(h_choose, dt,k_num,tp0,E0,freq,deltau,std1,band,int_lb,int_ub) np.savetxt(savename,zip(x1,y1)) pha, phb = PES_spin.phase(x,y) ra = np.round(pha/(2*np.pi),1) %2 rb = np.round(phb/(2*np.pi),1) %2 print 'phase number: ',pha, phb, ra, rb fig = plt.figure() ax1 = fig.add_subplot(121) PES_spin.plot(PES2Dx,ax1) plot_hf() ax2 = fig.add_subplot(122) PES_spin.plot(PES2Dy,ax2) plot_hf() fig.suptitle(cond) plt.tight_layout() plt.savefig('figure/sshspin_pxpy.png') plt.show() if option == 2: PESphase = PES_spin.phase_PES(PES2Dx,PES2Dy) fig = plt.figure() ax = fig.add_subplot(111) PES_spin.plot(PESphase,ax,color='hsv') plot_hf() plt.tight_layout() plt.savefig('figure/sshspin_phase.png') plt.show()

25.35249

125

0.626417

1,230

6,617

3.226829

0.196748

0.007055

0.032754

0.015117

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null

0.049261

0

null

0

null

0

1

0

1

3b588b6ce0959e11ca51f7007731ed436c1a00ca

1,923

py

Python

tests/test_types.py

juniorcarvalho/python-btr

3c63fe939882d719a4ebbc07685c87429782c247

[ "MIT" ]

null

tests/test_types.py

juniorcarvalho/python-btr

3c63fe939882d719a4ebbc07685c87429782c247

[ "MIT" ]

null

tests/test_types.py

juniorcarvalho/python-btr

3c63fe939882d719a4ebbc07685c87429782c247

[ "MIT" ]

1

2018-12-03T00:32:55.000Z

from decimal import InvalidOperation import pytest from binance.types import Results, Trading, format_fee def test_results_attributes(): tr = Results( datetime_value='2018-11-13 01:58:03', pair='STORMBTC', type_operation='SELL', order_price='0.0', order_amount='2200.0', avg_trading_price='0.00000126', filled='2200.0', total='0.002772', status='Filled' ) assert tr.datetime_value with pytest.raises(ValueError): tr.datetime_value = 'a' assert tr.pair assert tr.type_operation assert tr.order_price assert tr.order_amount assert tr.avg_trading_price assert tr.filled assert tr.total assert tr.status with pytest.raises(InvalidOperation): tr.order_price = 'a' with pytest.raises(InvalidOperation): tr.order_amount = 'a' with pytest.raises(InvalidOperation): tr.avg_trading_price = 'a' with pytest.raises(InvalidOperation): tr.filled = 'a' with pytest.raises(InvalidOperation): tr.total = 'a' def test_trading_attributes(): tr = Trading( datetime_value='2018-11-13 01:58:03', filled='0.00000126', total='2200', fee='0.00277200', fee_coin='0.00141268BNB' ) assert tr.datetime_value assert tr.filled assert tr.total assert tr.fee assert tr.fee_coin with pytest.raises(ValueError): tr.datetime_value = 'a' with pytest.raises(InvalidOperation): tr.filled = 'a' with pytest.raises(InvalidOperation): tr.total = 'a' with pytest.raises(InvalidOperation): tr.fee = 'a' def test_format_fee(): a, b = format_fee('0.01BTC') assert a == '0.01' assert b == 'BTC' a, b = format_fee('BTC') assert a is None assert b == 'BTC' a, b = format_fee('0.01') assert a == '0.01' assert b is None

23.740741

54

0.620905

249

1,923

4.666667

0.208835

0.096386

0.137694

0.22031

0.525818

0.51463

0.394148

0.319277

0.141136

0

0.070014

0.264691

1,923

80

55

24.0375

0.751768

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1

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false

0

0.044776

0

0.089552

0

null

0

1

0

null

0

1

3b69aec95b3206db693240793ada22d1a026d313

1,417

py

Python

tests/port_tests/polygon_tests/test_equals.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

7

2020-05-07T08:13:44.000Z

2021-12-17T07:33:51.000Z

tests/port_tests/polygon_tests/test_equals.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

17

2019-11-29T23:17:26.000Z

2020-12-20T15:47:17.000Z

tests/port_tests/polygon_tests/test_equals.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

1

2020-12-17T22:44:21.000Z

from typing import Tuple from hypothesis import given from tests.port_tests.hints import PortedPolygon from tests.utils import (equivalence, implication) from . import strategies @given(strategies.polygons) def test_reflexivity(polygon: PortedPolygon) -> None: assert polygon == polygon @given(strategies.polygons_pairs) def test_symmetry(polygons_pair: Tuple[PortedPolygon, PortedPolygon]) -> None: first_polygon, second_polygon = polygons_pair assert equivalence(first_polygon == second_polygon, second_polygon == first_polygon) @given(strategies.polygons_triplets) def test_transitivity(polygons_triplet: Tuple[PortedPolygon, PortedPolygon, PortedPolygon]) -> None: first_polygon, second_polygon, third_polygon = polygons_triplet assert implication(first_polygon == second_polygon and second_polygon == third_polygon, first_polygon == third_polygon) @given(strategies.polygons_pairs) def test_connection_with_inequality(polygons_pair: Tuple[PortedPolygon, PortedPolygon] ) -> None: first_polygon, second_polygon = polygons_pair assert equivalence(not first_polygon == second_polygon, first_polygon != second_polygon)

33.738095

78

0.661962

134

1,417

6.723881

0.261194

0.119867

0.17758

0.194229

0.449501

0.378468

0.224195

0

0.275229

1,417

41

79

34.560976

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0.142857

false

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0.178571

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0.321429

0

null

0

1

0

null

0

1

3b7429619e17d7df3d00811edac6228a84a03e82

12,649

py

Python

rsvis/tools/canvas/imgcv.py

Tom-Hirschberger/DataVisualization

1aec6a85e2af7ba62ba47e6ee93dc9a7d99c6221

[ "MIT" ]

null

rsvis/tools/canvas/imgcv.py

Tom-Hirschberger/DataVisualization

1aec6a85e2af7ba62ba47e6ee93dc9a7d99c6221

[ "MIT" ]

4

2020-04-28T11:53:24.000Z

2022-03-12T00:15:30.000Z

rsvis/tools/canvas/imgcv.py

Tom-Hirschberger/DataVisualization

1aec6a85e2af7ba62ba47e6ee93dc9a7d99c6221

[ "MIT" ]

2

2020-07-01T15:35:29.000Z

2021-03-11T17:53:23.000Z

# =========================================================================== # imgcv.py ---------------------------------------------------------------- # =========================================================================== # import ------------------------------------------------------------------ # --------------------------------------------------------------------------- import rsvis.utils.imgtools as imgtools import rsvis.utils.logger import logging import numpy as np from PIL import Image, ImageTk from tkinter import Canvas, NW # class ------------------------------------------------------------------- # --------------------------------------------------------------------------- class ImgCanvas(Canvas): # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def __init__( self, parent, shift=[4,4], sensitivity = 4, logger=None, **kwargs ): super(ImgCanvas, self).__init__(parent) self.bind("<Configure>", self.resize_image) self._mask = [None] self._mask_alpha = [150] self._mask_color = [[0,0,0]] self._mask_invert = [False] self._shift = shift self._scale = [1.0, 1.0] self.set_size([self.winfo_reqwidth(), self.winfo_reqheight()]) self._parent = parent self._logger = rsvis.utils.logger.Logger(logger=logger) # key bindings ---------------------------------------------------- self._mouse_sensitivity = 4 self._mouse_box = [0, 0, 0, 0] self._mouse_point = [0, 0] self._mouse_event = [0, 0] self._mouse_img = [0, 0] self._keys = dict() self.bind("<Button-1>", self.mouse_button_1_pressed) self.bind("<ButtonRelease-1>", self.mouse_button_1_released) # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def clear(self, **kwargs): pass # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_keys(self, **kwargs): return self._keys # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_logger(self): return self._logger # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_image(self, event): # determine the ratio of old width/height to new width/height event_size = [event.width, event.height] ##################### self._scale = [float(e)/s for e, s in zip(event_size, self._size)] self.set_size(event_size) # resize the canvas self.config(width=self._size[0], height=self._size[1]) ################# # rescale all the objects tagged with the "all" tag self.scale("all", 0, 0, self._scale[0], self._scale[1]) ################ self.create_image() # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_boxes(self, boxes, inversion=False): scale = [float(s)/i for s, i in zip(self.get_size(), self._img_size)] if inversion: scale = [1/s for s in scale] boxes = boxes if isinstance(boxes[0], list) and len(boxes[0]) !=2 else [boxes] return [self.resize_bbox(box, scale) for box in boxes] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_bbox(self, box, scale): if len(box)==4: return [ int(box[0]*scale[1]), int(box[1]*scale[1]), int(box[2]*scale[0]), int(box[3]*scale[0]) ] else: return [[int(n[0] *scale[0]), int(n[1]*scale[1])] for n in box ] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_points(self, points, inversion=False): scale = [float(s)/i for s, i in zip(self.get_size(), self._img_size)] if inversion: scale = [1/s for s in scale] points = points if isinstance(points[0], list) else [points] return [self.resize_point(point, scale) for point in points] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_point(self, point, scale): return [int(point[0]*scale[1]), int(point[1]*scale[0])] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def resize_event(self, event): ev = [event.y, event.x] ev[0] = ev[0] if ev[0] >= 0 else 0 ev[0] = ev[0] if ev[0] < self._img_draw.size[1] else self._img_draw.size[1]-1 ev[1] = ev[1] if ev[1] >= 0 else 0 ev[1] = ev[1] if ev[1] < self._img_draw.size[0] else self._img_draw.size[0]-1 return ev # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_event_box(self, event): return [ min([self._mouse_point[0], self._mouse_event[0]]), max([self._mouse_point[0], self._mouse_event[0]]), min([self._mouse_point[1], self._mouse_event[1]]), max([self._mouse_point[1], self._mouse_event[1]]) ] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def set_img(self, img, clear_mask=True): if not isinstance(img, np.ndarray): return self._img_size = [img.shape[1], img.shape[0]] self._data_img = imgtools.expand_image_dim(img) if not isinstance(img.dtype, np.uint8): img = imgtools.project_and_stack(img, dtype=np.uint8, factor=255) self._img = Image.fromarray(img) if clear_mask: self.set_mask(show=False) self.create_image() # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def set_mask(self, mask=None, show=True, alpha=150, color=[0,0,0], invert=False): self._mask = mask if isinstance(mask, list) else [mask] self._mask_alpha = alpha if isinstance(alpha, list) else [alpha] self._mask_color = color if isinstance(color[0], list) else [color] self._mask_invert= invert if isinstance(invert, list) else [invert] if show: self.create_image() # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_mask(self, index=None, resize=False): if index is None: mask = self._mask[0] for idx in range(1, len(self._mask)): if isinstance(self._mask[idx], np.ndarray): mask = np.where(np.logical_and(mask, self._mask[idx]), 1, 0).astype(np.uint8) return mask else: if isinstance(self._mask[index], np.ndarray): return np.asarray(Image.fromarray(self._mask[index]).resize(self.get_size())) if resize else self._mask[index] else: return self._mask[index] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def is_mouse_event(self, bbox): if not (bbox[1]-bbox[0] > self._mouse_sensitivity and bbox[3]-bbox[2] > self._mouse_sensitivity): return False return True # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_img(self, show=False): if show: return np.asarray(self._img).copy() return self._data_img.copy() # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def set_size(self, size): self._size = [s - sh for s, sh in zip(size, self._shift)] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_size(self): return [s + sh for s, sh in zip(self._size, self._shift)] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_shape(self): size = self.get_size() return (size[1], size[0], 3) # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_intial_draw_image(self): return np.zeros(self.get_shape(), dtype=np.int16) - 1 # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def create_image(self, **kwargs): self._img_draw = self._img.resize(self.get_size()) if isinstance(self._mask[0], np.ndarray): for idx, (mask, color, alpha, invert) in enumerate(zip(self._mask, self._mask_color, self._mask_alpha, self._mask_invert)): mask = self.get_mask(index=idx, resize=True) mask = mask if not invert else imgtools.invert_bool_img(mask) mask = Image.fromarray( imgtools.get_transparent_image( imgtools.bool_to_img(mask, value=-1, dtype=np.int16, color=color, factor=255), value=alpha ) ) self._img_draw.paste(mask, (0, 0), mask) image = Image.fromarray( imgtools.get_transparent_image(self.draw_image(), value=200)) self._img_draw.paste(image, (0, 0), image) self._img_canvas = ImageTk.PhotoImage(image=self._img_draw) self._img_on_canvas = super(ImgCanvas, self).create_image(0, 0, image=self._img_canvas, anchor=NW) # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def draw_image(self, **kwargs): img_assembly = self.get_intial_draw_image() return img_assembly # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def mouse_button_1_pressed(self, event): self.focus_set() self._mouse_event = self.resize_event(event) self._mouse_point = [self._mouse_event[0], self._mouse_event[1]] # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def get_roi(self): if sum(self._mouse_box): roi_xy = self.resize_boxes(self._mouse_box, inversion=True)[0] roi = [roi_xy[2], roi_xy[0], roi_xy[3]-roi_xy[2], roi_xy[1]-roi_xy[0]] else: roi = [0, 0, self._data_img.shape[1]-1, self._data_img.shape[0]-1] return roi # method -------------------------------------------------------------- # ----------------------------------------------------------------------- def mouse_button_1_released(self, event): self.focus_set() self._mouse_event = self.resize_event(event) self._mouse_box = self.get_event_box(event) self._mouse_img = self.resize_points(self._mouse_event, inversion=True)[0] self._logger("[MOUSE] Pixel: {}, Value: {}".format(self._mouse_img, self._data_img[self._mouse_img[0], self._mouse_img[1], :] ) )

43.920139

135

0.386908

1,164

12,649

3.99055

0.131443

0.058127

0.03014

0.012917

0.227987

0.152637

0.117115

0.09085

0.065016

0

0.015315

0.215353

12,649

288

136

43.920139

0.452695

0.342161

0

0.122807

0

0.00853

0

1

0.146199

false

0.005848

0.035088

0.315789

0

null

0

1

0

null

0

1

3b7cf7fe88491f39d41118c5372b2efff2e8da58

12,343

py

Python

doclabel/core/models.py

sondh0127/doclabel

2cadea9fc925435aea49ac0b56c29474664ade4e

[ "MIT" ]

null

doclabel/core/models.py

sondh0127/doclabel

2cadea9fc925435aea49ac0b56c29474664ade4e

[ "MIT" ]

null

doclabel/core/models.py

sondh0127/doclabel

2cadea9fc925435aea49ac0b56c29474664ade4e

[ "MIT" ]

null

import string import os from django.conf import settings from django.dispatch import receiver from django.db.models.signals import post_save, pre_delete, post_delete from django.db import models from django.urls import reverse from django.contrib.auth import get_user_model from django.contrib.postgres.fields import JSONField from django.core.files.storage import FileSystemStorage from django.contrib.staticfiles.storage import staticfiles_storage from django.core.exceptions import ValidationError from polymorphic.models import PolymorphicModel from .managers import AnnotationManager, Seq2seqAnnotationManager User = get_user_model() DOCUMENT_CLASSIFICATION = "TextClassificationProject" SEQUENCE_LABELING = "SequenceLabelingProject" SEQ2SEQ = "Seq2seqProject" PDF_LABELING = "PdfLabelingProject" PROJECT_CHOICES = ( (DOCUMENT_CLASSIFICATION, "Document Classification"), (SEQUENCE_LABELING, "Sequence Labeling"), (SEQ2SEQ, "Sequence to Sequence"), (PDF_LABELING, "PDF Labeling Project"), ) # Project class Project(PolymorphicModel): name = models.CharField(max_length=100, unique=True) description = models.TextField(default="") guideline = models.TextField(default="") created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) users = models.ManyToManyField(User, related_name="projects") project_type = models.CharField(max_length=30, choices=PROJECT_CHOICES, null=False) annotator_per_example = models.IntegerField(default=3) randomize_document_order = models.BooleanField(default=False) # Allow see annotation from other user collaborative_annotation = models.BooleanField(default=False) public = models.BooleanField(default=False) def get_absolute_url(self): return reverse("upload", args=[self.id]) @property def image(self): raise NotImplementedError() def get_annotation_serializer(self): raise NotImplementedError() def get_annotation_class(self): raise NotImplementedError() def get_storage(self, data): raise NotImplementedError() def __str__(self): return self.name class TextClassificationProject(Project): @property def image(self): return staticfiles_storage.url("images/cats/text_classification.jpg") def get_annotation_serializer(self): from doclabel.core.serializers import DocumentAnnotationSerializer return DocumentAnnotationSerializer def get_annotation_class(self): return DocumentAnnotation def get_storage(self, data): from .utils import ClassificationStorage return ClassificationStorage(data, self) class SequenceLabelingProject(Project): @property def image(self): return staticfiles_storage.url("images/cats/sequence_labeling.jpg") def get_annotation_serializer(self): from .serializers import SequenceAnnotationSerializer return SequenceAnnotationSerializer def get_annotation_class(self): return SequenceAnnotation def get_storage(self, data): from .utils import SequenceLabelingStorage return SequenceLabelingStorage(data, self) class Seq2seqProject(Project): @property def image(self): return staticfiles_storage.url("images/cats/seq2seq.jpg") def get_annotation_serializer(self): from .serializers import Seq2seqAnnotationSerializer return Seq2seqAnnotationSerializer def get_annotation_class(self): return Seq2seqAnnotation def get_storage(self, data): from .utils import Seq2seqStorage return Seq2seqStorage(data, self) class PdfLabelingProject(Project): @property def image(self): return staticfiles_storage.url("images/cats/pdf_labeling.jpg") def get_annotation_serializer(self): from .serializers import PdfAnnotationSerializer return PdfAnnotationSerializer def get_annotation_class(self): return PdfAnnotation def get_storage(self, data): from .utils import PdfLabelingStorage return PdfLabelingStorage(data, self) # Label class Label(models.Model): PREFIX_KEYS = (("ctrl", "ctrl"), ("shift", "shift"), ("ctrl shift", "ctrl shift")) SUFFIX_KEYS = tuple((c, c) for c in string.ascii_lowercase) text = models.CharField(max_length=100) prefix_key = models.CharField( max_length=10, blank=True, null=True, choices=PREFIX_KEYS ) suffix_key = models.CharField( max_length=1, blank=True, null=True, choices=SUFFIX_KEYS ) project = models.ForeignKey( Project, related_name="labels", on_delete=models.CASCADE ) background_color = models.CharField(max_length=7, default="#209cee") text_color = models.CharField(max_length=7, default="#ffffff") created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def __str__(self): return self.text def clean(self): # Don't allow shortcut key not to have a suffix key. if self.prefix_key and not self.suffix_key: raise ValidationError("Shortcut key may not have a suffix key.") # each shortcut (prefix key + suffix key) can only be assigned to one label if self.suffix_key or self.prefix_key: other_labels = self.project.labels.exclude(id=self.id) if other_labels.filter( suffix_key=self.suffix_key, prefix_key=self.prefix_key ).exists(): raise ValidationError( "A label with this shortcut already exists in the project" ) super().clean() class Meta: unique_together = (("project", "text"),) # Dataset class Document(models.Model): # text content or pdf content text = models.TextField() project = models.ForeignKey( Project, related_name="documents", on_delete=models.CASCADE ) meta = models.TextField(default="{}") created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) annotations_approved_by = models.ForeignKey( User, on_delete=models.SET_NULL, null=True ) def __str__(self): return self.text[:50] # Annotation class Annotation(models.Model): objects = AnnotationManager() prob = models.FloatField(default=0.0) manual = models.BooleanField(default=False) user = models.ForeignKey(User, on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) # user confirm finish task set finished = models.BooleanField(default=False) class Meta: abstract = True class DocumentAnnotation(Annotation): document = models.ForeignKey( Document, related_name="doc_annotations", on_delete=models.CASCADE ) label = models.ForeignKey(Label, on_delete=models.CASCADE) class Meta: unique_together = (("document", "user", "label"),) class SequenceAnnotation(Annotation): document = models.ForeignKey( Document, related_name="seq_annotations", on_delete=models.CASCADE ) label = models.ForeignKey(Label, on_delete=models.CASCADE) start_offset = models.IntegerField() end_offset = models.IntegerField() tokens = JSONField() def clean(self): if self.start_offset >= self.end_offset: raise ValidationError("start_offset is after end_offset") class Meta: unique_together = (("document", "user", "label", "start_offset", "end_offset"),) class Seq2seqAnnotation(Annotation): # Override AnnotationManager for custom functionality objects = Seq2seqAnnotationManager() document = models.ForeignKey( Document, related_name="seq2seq_annotations", on_delete=models.CASCADE ) text = models.CharField(max_length=500) class Meta: unique_together = (("document", "user", "text"),) class PdfAnnotation(Annotation): document = models.ForeignKey( Document, related_name="pdf_annotations", on_delete=models.CASCADE ) label = models.ForeignKey(Label, on_delete=models.CASCADE) content = JSONField() position = JSONField() class Meta: unique_together = (("document", "user", "label", "content", "position"),) class Role(models.Model): name = models.CharField(max_length=100, unique=True) description = models.TextField(default="") created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def __str__(self): return self.name class RoleMapping(models.Model): user = models.ForeignKey( User, related_name="role_mappings", on_delete=models.CASCADE ) project = models.ForeignKey( Project, related_name="role_mappings", on_delete=models.CASCADE ) role = models.ForeignKey(Role, on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def clean(self): other_rolemappings = self.project.role_mappings.exclude(id=self.id) if other_rolemappings.filter(user=self.user, project=self.project).exists(): raise ValidationError( "This user is already assigned to a role in this project." ) class Meta: unique_together = ("user", "project", "role") @receiver(post_save, sender=RoleMapping) def add_linked_project(sender, instance, created, **kwargs): if not created: return userInstance = instance.user projectInstance = instance.project isAnnotator = instance.role.name == settings.ROLE_ANNOTATOR if userInstance and projectInstance and isAnnotator: user = User.objects.get(pk=userInstance.pk) project = Project.objects.get(pk=projectInstance.pk) user.projects.add(project) user.save() @receiver(post_save) def add_superusers_to_project(sender, instance, created, **kwargs): if not created: return if sender not in Project.__subclasses__(): return superusers = User.objects.filter(is_superuser=True) admin_role = Role.objects.filter(name=settings.ROLE_PROJECT_ADMIN).first() if superusers and admin_role: RoleMapping.objects.bulk_create( [ RoleMapping( role_id=admin_role.id, user_id=superuser.id, project_id=instance.id ) for superuser in superusers ] ) @receiver(post_save, sender=User) def add_new_superuser_to_projects(sender, instance, created, **kwargs): if created and instance.is_superuser: admin_role = Role.objects.filter(name=settings.ROLE_PROJECT_ADMIN).first() projects = Project.objects.all() if admin_role and projects: RoleMapping.objects.bulk_create( [ RoleMapping( role_id=admin_role.id, user_id=instance.id, project_id=project.id, ) for project in projects ] ) @receiver(pre_delete, sender=RoleMapping) def delete_linked_project(sender, instance, using, **kwargs): userInstance = instance.user projectInstance = instance.project isAnnotator = instance.role.name == settings.ROLE_ANNOTATOR if userInstance and projectInstance and isAnnotator: user = User.objects.get(pk=userInstance.pk) project = Project.objects.get(pk=projectInstance.pk) user.projects.remove(project) user.save() @receiver(post_delete, sender=Document) def delete_file_on_remove(sender, instance, **kwargs): file = instance.text fs = FileSystemStorage(location=settings.MEDIA_ROOT + "/pdf_documents/") if fs.exists(file): fs.delete(file) @receiver(post_delete, sender=PdfAnnotation) def delete_anno_on_remove(sender, instance, **kwargs): content = instance.content if "image" in content: doc = instance.document fs = FileSystemStorage( location=settings.MEDIA_ROOT + "/pdf_annotations/doc_" + str(doc.id) + "/" ) if fs.exists(content["image"]): fs.delete(content["image"])

31.894057

88

0.694969

1,369

12,343

6.09569

0.17385

0.011504

0.023487

0.032714

0.47166

0.424206

0.36429

0.297903

0.270102

0.251168

0

0.004217

0.212347

12,343

386

89

31.976684

0.854145

0.024548

0

0.341463

0

0.067919

0.015629

0

1

0.118467

false

0

0.076655

0.045296

0.550523

0

null

0

null

0

1

0

1

3b979d74f6e8f31c561e6e8ceb34cc6c5fafe859

3,197

py

Python

config/HttpdParser.py

automicus/OpenAlarm

68bcc4aa75338e8d5a2ff423029f7c4064d2b9c8

[ "Apache-2.0" ]

1

2016-03-30T05:41:19.000Z

config/HttpdParser.py

automicus/OpenAlarm

68bcc4aa75338e8d5a2ff423029f7c4064d2b9c8

[ "Apache-2.0" ]

null

config/HttpdParser.py

automicus/OpenAlarm

68bcc4aa75338e8d5a2ff423029f7c4064d2b9c8

[ "Apache-2.0" ]

null

from HTMLParser import HTMLParser class HttpdParser(HTMLParser): def __init_var__(self): # create status variables self._inHttpd = None self._inKey = None self.httpd = None def read(self, fname): self.__init_var__() cache = open(fname).read() self.feed(cache) out = self.httpd self.__init_var__() return out # Default Syntax Handlers def handle_starttag(self, tag, attrs): #print 'START: ' + str(tag) if tag == 'httpd': self.httpd_start() elif tag == 'ip': self.ip_start() elif tag == 'port': self.port_start() else: raise FormatError(self.getpos()) def handle_endtag(self, tag): #print 'END: ' + str(tag) if tag == 'httpd': self.httpd_end() elif tag == 'ip': self.ip_end() elif tag == 'port': self.port_end() else: raise FormatError(self.getpos()) def handle_data(self, data): data = data.strip() if len(data) > 0: #print 'DATA: ' + str(data) if self._inHttpd: self.httpd_data(data) else: raise FormatError(self.getpos()) # HTTPD tag handlers def httpd_start(self): if self._inHttpd is None: self._inHttpd = {'ip': None, 'port': None} else: raise FormatError(self.getpos()) def httpd_end(self): if self._inHttpd is not None and self._inKey is None: if self._inHttpd['ip'] is not None \ and self._inHttpd['port'] is not None: self.httpd = self._inHttpd self._inHttpd = None else: raise FormatError(self.getpos()) else: raise FormatError(self.getpos()) def httpd_data(self, data): if self._inKey is not None: self._inHttpd[self._inKey] = data else: raise FormatError(self.getpos()) # IP tag handlers def ip_start(self): if self._inHttpd is not None and self._inKey is None: self._inKey = 'ip' else: raise FormatError(self.getpos()) def ip_end(self): if self._inKey == 'ip' and self._inHttpd['ip'] is not None: self._inKey = None else: raise FormatError(self.getpos()) # PORT tag handlers def port_start(self): if self._inHttpd is not None and self._inKey is None: self._inKey = 'port' else: raise FormatError(self.getpos()) def port_end(self): if self._inKey == 'port' and self._inHttpd['port'] is not None: self._inKey = None else: raise FormatError(self.getpos()) class FormatError(Exception): def __init__(self, pos): super(FormatError, self).__init__() self.pos = pos def __str__(self): return "Formatting error at: " + str(self.pos) def readHttpd(fname): parser = HttpdParser() return parser.read(fname) if __name__ == "__main__": print readHttpd('../httpd.conf')

26.865546

71

0.541758

369

3,197

4.482385

0.165312

0.093108

0.133011

0.159613

0.515115

0.452237

0.312576

0.189238

0.159613

0

0.000481

0.34939

3,197

118

72

27.09322

0.794712

0.055052

0

0.426966

0

0.031209

0

null

0

0.011236

null

0.011236

0

null

0

null

0

1

0

1

3b9fb3dac066072f489c406ee52505f3cf651095

14,898

py

Python

Script_Kali_Machine/DownloadTools_Old.py

manesec/tools4me

d6f0e41aabc3dc4fdc1ff8ad8bebaf578fdbe69e

[ "MIT" ]

null

Script_Kali_Machine/DownloadTools_Old.py

manesec/tools4me

d6f0e41aabc3dc4fdc1ff8ad8bebaf578fdbe69e

[ "MIT" ]

null

Script_Kali_Machine/DownloadTools_Old.py

manesec/tools4me

d6f0e41aabc3dc4fdc1ff8ad8bebaf578fdbe69e

[ "MIT" ]

2

2022-02-09T07:30:12.000Z

2022-03-06T08:00:22.000Z

# List slow update .. Optional_Installation = { # Update ExploitDB "EXPLOITDB" : True, # Install ZAP # It have some bug in old kali linux, if you are running old kali linux please disable it. "ZAP" : False, # Install DBeaver "DBEAVER" : True, # Install Big Webshell Collection ~ 0.84 GByte # I think kali buildin webshell just enough. # URL: https://github.com/tennc/webshell.git "BIG_WEBSHELL" : False, # Install Dictionary-Of-Pentesting (like seclist) ~ 1.2 GByte "DOP" : False, } ####################################################################### ################################# END ################################# ####################################################################### print(""" ▄▀▀▄ ▄▀▄ ▄▀▀█▄ ▄▀▀▄ ▀▄ ▄▀▀█▄▄▄▄ ▄▀▀▀▀▄ ▄▀▀█▄▄▄▄ ▄▀▄▄▄▄ █ █ ▀ █ ▐ ▄▀ ▀▄ █ █ █ █ ▐ ▄▀ ▐ █ █ ▐ ▐ ▄▀ ▐ █ █ ▌ ▐ █ █ █▄▄▄█ ▐ █ ▀█ █▄▄▄▄▄ ▀▄ █▄▄▄▄▄ ▐ █ █ █ ▄▀ █ █ █ █ ▌ ▀▄ █ █ ▌ █ ▄▀ ▄▀ █ ▄▀ ▄▀ █ ▄▀▄▄▄▄ █▀▀▀ ▄▀▄▄▄▄ ▄▀▄▄▄▄▀ █ █ ▐ ▐ █ ▐ █ ▐ ▐ █ ▐ █ ▐ ▐ ▐ ▐ ▐ ▐ ▐ Download Tools on AMD64 - Tools4me by Mane. Version: 20220301 https://github.com/manesec/tools4me ---------------------------------------------------------------""") import os # Mkdir os.system("rm -rf Linux") os.system("rm -rf Windows") os.system("rm -rf Tools") os.system("rm -rf Additions") os.system("rm -rf Wordlists") os.system("rm -rf Tools4mane") os.mkdir("Linux") os.mkdir("Windows") os.mkdir("Tools") os.mkdir("Additions") os.mkdir("Wordlists") print(" :: Apt pre-install ::") os.system("sudo apt update && sudo apt -y install python3-pip neo4j gobuster zaproxy hashcat nikto feroxbuster") print("---------------------------------------------------------------") if Optional_Installation["EXPLOITDB"]: print(" :: Updating ExploitDB And MSF ::") os.system("sudo apt update && sudo apt -y install exploitdb metasploit-framework && sudo searchsploit -u") os.system("sudo msfdb reinit") print("---------------------------------------------------------------") if Optional_Installation["ZAP"] : print(" :: Setting up zaproxy ::") print("[!] Set up for zaproxy it need to take a long time.") import pexpect,time print("[>] Installing all additions ...") zap = pexpect.spawn('zaproxy -addoninstallall -daemon -port 12345',timeout=60*10) zap.expect("ZAP is now listening") print(" - Waiting for 5 second ...") time.sleep(5) zap.kill(9) print("[>] Updating all additions ...") zap = pexpect.spawn('zaproxy -addonupdate -daemon -port 12345',timeout=60*10) zap.expect("ZAP is now listening") print(" - Waiting for 5 second ...") time.sleep(5) zap.kill(9) print("[>] Uninstall Non-compatible additions ...") zap = pexpect.spawn('zaproxy -addonuninstall browserView -daemon -port 12345',timeout=60*10) zap.expect("ZAP is now listening") print(" - Waiting for 5 second ...") time.sleep(5) zap.kill(9) if Optional_Installation["DBEAVER"]: print(" :: Setting up DBeaver ::") os.mkdir("tmp") os.chdir("tmp") os.system("wget https://github.com/dbeaver/dbeaver/releases/download/21.3.5/dbeaver-ce_21.3.5_amd64.deb -O dbeaver.deb") os.system("sudo dpkg -i dbeaver.deb") os.chdir("..") os.system("rm -rf tmp") print("---------------------------------------------------------------") print(" :: pip pre install ::") print("[>] Getting pwncat-cs ...") os.system("sudo pip3 install pwncat-cs") print("---------------------------------------------------------------") print(" :: Installing Tools ::") print("[>] Getting tools4mane ...") os.system("git clone https://github.com/manesec/tools4mane.git Tools4mane") print("[>] Getting nmapAutomator ...") os.system("wget https://raw.githubusercontent.com/21y4d/nmapAutomator/master/nmapAutomator.sh --quiet -O Tools/nmapAutomator.sh") print("[>] Getting Godzilla ...") os.system("wget https://github.com/BeichenDream/Godzilla/releases/latest/download/godzilla.jar --quiet -O Tools/godzilla.jar") print("[>] Getting Chisel ...") os.chdir("Tools") os.mkdir("Chisel") os.chdir("Chisel") os.system("wget https://github.com/jpillora/chisel/releases/latest/download/chisel_1.7.7_linux_386.gz --quiet -O chisel_linux_386.gz") os.system("wget https://github.com/jpillora/chisel/releases/latest/download/chisel_1.7.7_linux_amd64.gz --quiet -O chisel_linux_amd64.gz") os.system("wget https://github.com/jpillora/chisel/releases/latest/download/chisel_1.7.7_windows_386.gz --quiet -O chisel_windows_386.gz") os.system("wget https://github.com/jpillora/chisel/releases/latest/download/chisel_1.7.7_windows_amd64.gz --quiet -O chisel_windows_amd64.gz") os.system("gzip -d *.gz") os.chdir("..") os.chdir("..") print("---------------------------------------------------------------") print(" :: Installing For Windows Tools ::") print("[>] Getting Beroot ...") os.chdir("Windows") os.system("wget https://github.com/AlessandroZ/BeRoot/releases/latest/download/beRoot.zip -O beRoot.zip --quiet") os.system("unzip beRoot.zip") os.system("rm -r beRoot.zip") os.chdir("..") print("[>] Getting BloodHound ...") os.chdir("Windows") os.system("wget https://github.com/BloodHoundAD/BloodHound/releases/latest/download/BloodHound-linux-x64.zip -O BloodHound-linux-x64.zip") os.system("unzip BloodHound-linux-x64.zip") os.system("rm -rf BloodHound-linux-x64.zip") os.chdir("..") print("[>] Getting PowerSploit ...") os.chdir("Windows") os.system("git clone https://github.com/PowerShellMafia/PowerSploit.git PowerSoloit_dev -b dev") os.system("git clone https://github.com/PowerShellMafia/PowerSploit.git PowerSoloit_master -b master") os.chdir("..") print("[>] Getting Evil-winrm ...") os.chdir("Windows") os.system("git clone https://github.com/Hackplayers/evil-winrm.git Evil-winrm") os.system("sudo gem install evil-winrm") os.chdir("..") print("[>] Getting Nishang ...") os.chdir("Windows") os.system("git clone https://github.com/samratashok/nishang.git Nishang") os.chdir("..") print("[>] Getting RedTeamPowershellScripts ...") os.chdir("Windows") os.system("git clone https://github.com/Mr-Un1k0d3r/RedTeamPowershellScripts.git RedTeamPowershellScripts") os.chdir("..") print("[>] Getting gosecretsdump ...") os.chdir("Windows") os.system("wget https://github.com/C-Sto/gosecretsdump/releases/download/v0.3.1/gosecretsdump_win_v0.3.1.exe --quiet") os.chdir("..") print("[>] Getting python Impacket ...") os.chdir("Windows") os.system("git clone https://github.com/SecureAuthCorp/impacket.git Impacket") os.chdir("Impacket") os.system("pip3 install .") os.chdir("..") os.chdir("..") print("[>] Getting WinPEAS ...") os.chdir("Windows") os.mkdir("WinPEAS") os.chdir("WinPEAS") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEAS.bat --quiet -O winPEAS.bat") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASany.exe --quiet -O winPEASany.exe") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASany_ofs.exe --quiet -O winPEASany_ofs.exe") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASx64.exe --quiet -O winPEASx64.exe") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASx64_ofs.exe --quiet -O winPEASx64_ofs.exe") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASx86.exe --quiet -O winPEASx86.exe") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/winPEASx86_ofs.exe --quiet -O winPEASx86_ofs.exe") os.chdir("..") os.chdir("..") print("[>] Getting Mimikatz ...") os.mkdir("tmp") os.chdir("tmp") os.system("wget https://github.com/gentilkiwi/mimikatz/releases/latest/download/mimikatz_trunk.zip --quiet -O mimikatz.zip") os.system("unzip mimikatz.zip") os.system("rm mimikatz.zip") os.chdir("..") os.system("mv tmp Windows/Mimikatz") print("[>] Getting AD Collector ...") os.chdir("Windows") os.system("wget https://github.com/dev-2null/ADCollector/releases/download/Release/ADCollector.exe --quiet") os.chdir("..") print("[>] Getting ADACLScanner ...") os.chdir("Windows") os.system("wget https://github.com/canix1/ADACLScanner/releases/latest/download/ADACLScan.ps1 --quiet") os.chdir("..") print("[>] Getting WinPwn ...") os.chdir("Windows") os.system("wget https://github.com/S3cur3Th1sSh1t/WinPwn/releases/latest/download/WinPwn.exe --quiet") os.system("wget https://github.com/S3cur3Th1sSh1t/WinPwn/releases/latest/download/WinPwn.ps1 --quiet") os.chdir("..") print("[>] Getting juicy-potato ...") os.chdir("Windows") os.system("wget https://github.com/ohpe/juicy-potato/releases/latest/download/JuicyPotato.exe --quiet") os.chdir("..") print("[>] Getting Lovely-Potato ...") os.chdir("Windows") os.system("git clone https://github.com/TsukiCTF/Lovely-Potato.git") os.chdir("..") print("[>] Getting PowerUpSQL ...") os.chdir("Windows") os.system("wget https://raw.githubusercontent.com/NetSPI/PowerUpSQL/master/PowerUpSQL.ps1 -O PowerUpSQL.ps1 --quiet") os.chdir("..") print("[>] Getting kerbrute ...") os.chdir("Windows") os.system("git clone https://github.com/TarlogicSecurity/kerbrute") os.chdir("kerbrute") os.system("pip3 install -r requirements.txt") os.chdir("..") os.chdir("..") print("[>] Getting Sharp Collection ...") os.chdir("Windows") os.system("git clone https://github.com/Flangvik/SharpCollection.git SharpCollection") os.chdir("..") print("[>] Getting Sharp ADModule ...") os.chdir("Windows") os.system("git clone https://github.com/samratashok/ADModule.git ADModule") os.chdir("..") print("[>] Getting ADCS.ps1 ...") os.chdir("Windows") os.system("wget https://raw.githubusercontent.com/cfalta/PoshADCS/master/ADCS.ps1 -O ADCS.ps1 --quiet") os.chdir("..") print("[>] Getting Privesc.ps1 ...") os.chdir("Windows") os.system("wget https://raw.githubusercontent.com/enjoiz/Privesc/master/privesc.ps1 -O Privesc.ps1 --quiet") os.chdir("..") print("[>] Getting SharpView ...") os.chdir("Windows") os.system("wget https://github.com/tevora-threat/SharpView/raw/master/Compiled/SharpView.exe -O SharpView.exe --quiet") os.chdir("..") print("[>] Getting NetSPI PowerShell Scripts ...") os.chdir("Windows") os.system("git clone https://github.com/NetSPI/PowerShell.git NetSPIPowerShell") os.chdir("..") print("---------------------------------------------------------------") print(" :: Installing For Linux Tools ::") print("[>] Getting pspy ...") os.chdir("Linux") os.mkdir("Pspy") os.chdir("Pspy") os.system("wget https://github.com/DominicBreuker/pspy/releases/latest/download/pspy32 --quiet -O pspy32") os.system("wget https://github.com/DominicBreuker/pspy/releases/latest/download/pspy64 --quiet -O pspy64") os.system("wget https://github.com/DominicBreuker/pspy/releases/latest/download/pspy32s --quiet -O pspy32s") os.system("wget https://github.com/DominicBreuker/pspy/releases/latest/download/pspy64s --quiet -O pspy64s") os.chdir("..") os.chdir("..") print("[>] Getting LinPEAS ...") os.system("wget https://github.com/carlospolop/PEASS-ng/releases/latest/download/linpeas.sh --quiet -O Linux/linpeas.sh") print("[>] Getting LinuxSmartEnumeration ...") os.system("wget https://raw.githubusercontent.com/diego-treitos/linux-smart-enumeration/master/lse.sh --quiet -O Linux/lse.sh") print("[>] Getting LinEnum ...") os.system("wget https://raw.githubusercontent.com/rebootuser/LinEnum/master/LinEnum.sh --quiet -O Linux/LinEnum.sh") print("[>] Getting unix-privesc-check ...") os.chdir("Linux") os.system("git clone https://github.com/pentestmonkey/unix-privesc-check.git Unix-privesc-check") os.system("tar -cf Unix-privesc-check.tar.gz Unix-privesc-check") os.system("rm -rf Unix-privesc-check") os.chdir("..") print("[>] Getting SUDO_KILLER ...") os.chdir("Linux") os.system("git clone https://github.com/TH3xACE/SUDO_KILLER.git Sudo_Killer") os.system("tar -cf Sudo_Killer.tar.gz Sudo_Killer") os.system("rm -rf Sudo_Killer") os.chdir("..") print("---------------------------------------------------------------") print(" :: Installing Additions Tools ::") if Optional_Installation["BIG_WEBSHELL"] : print("[>] Getting Big Webshell Collection ...") os.chdir("Additions") os.system("git clone https://github.com/tennc/webshell.git") os.chdir("webshell") os.system("git submodule update --init --recursive") os.chdir("..") os.chdir("..") print("[>] Getting Hack-browser ...") os.chdir("Additions") os.mkdir("Hack-browser") os.chdir("Hack-browser") os.system("wget https://github.com/moonD4rk/HackBrowserData/releases/latest/download/hack-browser-data--linux-amd64.zip --quiet ") os.system("wget https://github.com/moonD4rk/HackBrowserData/releases/latest/download/hack-browser-data--linux-386.zip --quiet ") os.system("wget https://github.com/moonD4rk/HackBrowserData/releases/latest/download/hack-browser-data--windows-32bit.zip --quiet ") os.system("wget https://github.com/moonD4rk/HackBrowserData/releases/latest/download/hack-browser-data--windows-64bit.zip --quiet ") os.system("unzip hack-browser-data--linux-amd64.zip") os.system("unzip hack-browser-data--linux-386.zip") os.system("unzip hack-browser-data--windows-32bit.zip") os.system("unzip hack-browser-data--windows-64bit.zip") os.remove("hack-browser-data--linux-amd64.zip") os.remove("hack-browser-data--linux-386.zip") os.remove("hack-browser-data--windows-32bit.zip") os.remove("hack-browser-data--windows-64bit.zip") os.chdir("..") os.chdir("..") print("---------------------------------------------------------------") print(" :: Installing Wordlists ::") print("[>] Getting secLists ...") os.chdir("Wordlists") os.system("git clone https://github.com/danielmiessler/SecLists.git") os.chdir("..") print("[>] Getting Auto_Wordlists ...") os.chdir("Wordlists") os.system("git clone https://github.com/carlospolop/Auto_Wordlists.git") os.chdir("..") print("[>] Getting rockyou.txt ...") os.system("wget https://github.com/brannondorsey/naive-hashcat/releases/download/data/rockyou.txt -O Wordlists/rockyou.txt") if Optional_Installation["DOP"]: print("[>] Getting Dictionary-Of-Pentesting ...") os.chdir("Wordlists") os.system("git clone https://github.com/insightglacier/Dictionary-Of-Pentesting.git") os.chdir("..") print("[>] Getting Update.sh") os.system("wget https://raw.githubusercontent.com/manesec/tools4me/main/Script_Kali_Machine/Update.sh --quiet") os.system("chmod u+x Update.sh") print("If you want to update \"DownloadTools.py\" just run ./Update.sh ") print("-------------------------- Total ------------------------------") os.system("du -h --max-depth=1 .") print("\nDone! -- by manesec.")

39.941019

142

0.647872

1,964

14,898

4.974033

0.161914

0.07534

0.075955

0.069608

0.530556

0.483673

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0.361142

0.352032

0.314566

0

0.015756

0.105383

14,898

372

143

40.048387

0.704607

0.024097

0

0.319728

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0.142857

0.716461

0.083595

0

1

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false

0

0.006803

0

0.006803

0.238095

0

null

0

1

0

null

0

1

3ba11498a776ef72e094f9860944bc017a359568

7,375

py

Python

metrics/recall/recall.py

leondz/datasets

4110fb6034f79c5fb470cf1043ff52180e9c63b7

[ "Apache-2.0" ]

3,395

2020-05-13T21:16:50.000Z

2020-09-10T14:36:50.000Z

metrics/recall/recall.py

leondz/datasets

4110fb6034f79c5fb470cf1043ff52180e9c63b7

[ "Apache-2.0" ]

370

2020-05-13T21:28:57.000Z

2020-09-10T11:03:38.000Z

metrics/recall/recall.py

leondz/datasets

4110fb6034f79c5fb470cf1043ff52180e9c63b7

[ "Apache-2.0" ]

258

2020-05-15T01:17:09.000Z

2020-09-10T12:41:43.000Z

# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. """Recall metric.""" from sklearn.metrics import recall_score import datasets _DESCRIPTION = """ Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation: Recall = TP / (TP + FN) Where TP is the true positives and FN is the false negatives. """ _KWARGS_DESCRIPTION = """ Args: - **predictions** (`list` of `int`): The predicted labels. - **references** (`list` of `int`): The ground truth labels. - **labels** (`list` of `int`): The set of labels to include when `average` is not set to `binary`, and their order when average is `None`. Labels present in the data can be excluded in this input, for example to calculate a multiclass average ignoring a majority negative class, while labels not present in the data will result in 0 components in a macro average. For multilabel targets, labels are column indices. By default, all labels in y_true and y_pred are used in sorted order. Defaults to None. - **pos_label** (`int`): The class label to use as the 'positive class' when calculating the recall. Defaults to `1`. - **average** (`string`): This parameter is required for multiclass/multilabel targets. If None, the scores for each class are returned. Otherwise, this determines the type of averaging performed on the data. Defaults to `'binary'`. - `'binary'`: Only report results for the class specified by `pos_label`. This is applicable only if the target labels and predictions are binary. - `'micro'`: Calculate metrics globally by counting the total true positives, false negatives, and false positives. - `'macro'`: Calculate metrics for each label, and find their unweighted mean. This does not take label imbalance into account. - `'weighted'`: Calculate metrics for each label, and find their average weighted by support (the number of true instances for each label). This alters `'macro'` to account for label imbalance. Note that it can result in an F-score that is not between precision and recall. - `'samples'`: Calculate metrics for each instance, and find their average (only meaningful for multilabel classification). - **sample_weight** (`list` of `float`): Sample weights Defaults to `None`. - **zero_division** (): Sets the value to return when there is a zero division. Defaults to . - `'warn'`: If there is a zero division, the return value is `0`, but warnings are also raised. - `0`: If there is a zero division, the return value is `0`. - `1`: If there is a zero division, the return value is `1`. Returns: - **recall** (`float`, or `array` of `float`): Either the general recall score, or the recall scores for individual classes, depending on the values input to `labels` and `average`. Minimum possible value is 0. Maximum possible value is 1. A higher recall means that more of the positive examples have been labeled correctly. Therefore, a higher recall is generally considered better. Examples: Example 1-A simple example with some errors >>> recall_metric = datasets.load_metric('recall') >>> results = recall_metric.compute(references=[0, 0, 1, 1, 1], predictions=[0, 1, 0, 1, 1]) >>> print(results) {'recall': 0.6666666666666666} Example 2-The same example as Example 1, but with `pos_label=0` instead of the default `pos_label=1`. >>> recall_metric = datasets.load_metric('recall') >>> results = recall_metric.compute(references=[0, 0, 1, 1, 1], predictions=[0, 1, 0, 1, 1], pos_label=0) >>> print(results) {'recall': 0.5} Example 3-The same example as Example 1, but with `sample_weight` included. >>> recall_metric = datasets.load_metric('recall') >>> sample_weight = [0.9, 0.2, 0.9, 0.3, 0.8] >>> results = recall_metric.compute(references=[0, 0, 1, 1, 1], predictions=[0, 1, 0, 1, 1], sample_weight=sample_weight) >>> print(results) {'recall': 0.55} Example 4-A multiclass example, using different averages. >>> recall_metric = datasets.load_metric('recall') >>> predictions = [0, 2, 1, 0, 0, 1] >>> references = [0, 1, 2, 0, 1, 2] >>> results = recall_metric.compute(predictions=predictions, references=references, average='macro') >>> print(results) {'recall': 0.3333333333333333} >>> results = recall_metric.compute(predictions=predictions, references=references, average='micro') >>> print(results) {'recall': 0.3333333333333333} >>> results = recall_metric.compute(predictions=predictions, references=references, average='weighted') >>> print(results) {'recall': 0.3333333333333333} >>> results = recall_metric.compute(predictions=predictions, references=references, average=None) >>> print(results) {'recall': array([1., 0., 0.])} """ _CITATION = """ @article{scikit-learn, title={Scikit-learn: Machine Learning in {P}ython}, author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.}, journal={Journal of Machine Learning Research}, volume={12}, pages={2825--2830}, year={2011} """ @datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION) class Recall(datasets.Metric): def _info(self): return datasets.MetricInfo( description=_DESCRIPTION, citation=_CITATION, inputs_description=_KWARGS_DESCRIPTION, features=datasets.Features( { "predictions": datasets.Sequence(datasets.Value("int32")), "references": datasets.Sequence(datasets.Value("int32")), } if self.config_name == "multilabel" else { "predictions": datasets.Value("int32"), "references": datasets.Value("int32"), } ), reference_urls=["https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html"], ) def _compute( self, predictions, references, labels=None, pos_label=1, average="binary", sample_weight=None, zero_division="warn", ): score = recall_score( references, predictions, labels=labels, pos_label=pos_label, average=average, sample_weight=sample_weight, zero_division=zero_division, ) return {"recall": float(score) if score.size == 1 else score}

54.62963

503

0.672949

975

7,375

5.029744

0.315897

0.037113

0.027121

0.037113

0.226754

0.199429

0.184747

0.155791

0.140498

0

0.030833

0.21722

7,375

134

504

55.037313

0.818638

0.085288

0

0.203884

0

0.174757

0.792509

0.084869

0

1

0.019417

false

0.009709

0.019417

0.009709

0.067961

0

null

0

1

0

null

0

1

8e605be6a5e8d416273e08bffcd14fcff9ddc548

848

py

Python

blog/home/migrations/0001_initial.py

iflyBird/blog

33dbf6345ae4ae64f726c7ce5353b7c7864351af

[ "MIT" ]

null

blog/home/migrations/0001_initial.py

iflyBird/blog

33dbf6345ae4ae64f726c7ce5353b7c7864351af

[ "MIT" ]

null

blog/home/migrations/0001_initial.py

iflyBird/blog

33dbf6345ae4ae64f726c7ce5353b7c7864351af

[ "MIT" ]

null

# Generated by Django 2.1.8 on 2020-05-27 15:24 import datetime from django.db import migrations, models from django.utils.timezone import utc class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='ArticleCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(blank=True, max_length=100)), ('created', models.DateField(default=datetime.datetime(2020, 5, 27, 15, 24, 34, 743876, tzinfo=utc))), ], options={ 'verbose_name': '类别管理', 'verbose_name_plural': '类别管理', 'db_table': 'tb_category', }, ), ]

28.266667

118

0.568396

88

848

5.375

0.659091

0.069767

0.02537

0

0.062925

0.306604

848

29

119

29.241379

0.741497

0.053066

0

1

0

0.111111

0

1

0

false

0

0.136364

0

0.318182

0

null

0

1

0

null

0

1

8e66f42aa9f3d76581d68b02d53d96cb65653cfe

1,066

py

Python

src/compas_ghpython/artists/polylineartist.py

Sam-Bouten/compas

011c7779ded9b69bb602568b470bb0443e336f62

[ "MIT" ]

null

src/compas_ghpython/artists/polylineartist.py

Sam-Bouten/compas

011c7779ded9b69bb602568b470bb0443e336f62

[ "MIT" ]

null

src/compas_ghpython/artists/polylineartist.py

Sam-Bouten/compas

011c7779ded9b69bb602568b470bb0443e336f62

[ "MIT" ]

null

from __future__ import print_function from __future__ import absolute_import from __future__ import division import compas_ghpython from compas.artists import PrimitiveArtist from .artist import GHArtist class PolylineArtist(GHArtist, PrimitiveArtist): """Artist for drawing polylines. Parameters ---------- polyline : :class:`compas.geometry.Polyline` A COMPAS polyline. **kwargs : dict, optional Additional keyword arguments. See :class:`compas_ghpython.artists.GHArtist` and :class:`compas.artists.PrimitiveArtist` for more info. """ def __init__(self, polyline, **kwargs): super(PolylineArtist, self).__init__(primitive=polyline, **kwargs) def draw(self): """Draw the polyline. Returns ------- :rhino:`Rhino.Geometry.Polyline`. """ polylines = [self._get_args(self.primitive)] return compas_ghpython.draw_polylines(polylines)[0] @staticmethod def _get_args(primitive): return {'points': map(list, primitive.points)}

26.65

112

0.680113

110

1,066

6.318182

0.445455

0.043165

0.069065

0

0.00119

0.212008

1,066

39

113

27.333333

0.82619

0.336773

0

0.009554

0

1

0.2

false

0

0.4

0.066667

0.8

0.066667

0

null

0

null

0

1

0

1

8e67cd9cfa819f5435d8aaa629ca0362047fd00b

2,356

py

Python

auctions/utils.py

zebadiahtaylor/cs50-Commerce

c8c56a0da861a32b1929053dd62e926e37f6b1b5

[ "MIT" ]

null

auctions/utils.py

zebadiahtaylor/cs50-Commerce

c8c56a0da861a32b1929053dd62e926e37f6b1b5

[ "MIT" ]

null

auctions/utils.py

zebadiahtaylor/cs50-Commerce

c8c56a0da861a32b1929053dd62e926e37f6b1b5

[ "MIT" ]

null

from .models import Auction, Bid, Comment, User from django.db.models import Max def has_bids(auction): """ Returns True if others have bid on the item. TODO: Throws TypeError if user not logged in """ # auction = Auction.objects.get(id=auction) has_bids = False try: current_bid = Bid.objects.filter(auction=auction).aggregate(Max('bid_amount')) if current_bid['bid_amount__max']: has_bids = True except Bid.DoesNotExist: pass return has_bids def has_high_bid(user, auction): """ Returns True if User has highest bid. """ try: max_bid = Bid.objects.filter(auction=auction).aggregate(max_bid = Max('bid_amount')) user_high_bid = Bid.objects.filter(auction=auction, user=user).aggregate(user_bid = Max('bid_amount')) if user_high_bid['user_bid'] is not None and max_bid['max_bid'] == user_high_bid['user_bid']: return True else: return False except Bid.DoesNotExist: return False def is_users_auction(user, auction): """ Returns True if the user is the owner of the auction. """ auction = Auction.objects.get(id=auction) is_users_auction = False if auction.user == user: is_users_auction = True return is_users_auction def is_watched(user, auction): user = User.objects.get(username=user) watchlist = user.watchlist.all() is_watched = False for item in watchlist: if auction == item.id: is_watched = True return is_watched def return_active_auctions(): auctions = Auction.objects.all() auctions = [auction for auction in auctions if auction.active] for auction in auctions: auction.current_bid = return_highest_bid(auction.id) return auctions def return_highest_bid(auction): auction_object = Auction.objects.get(id=auction) current_bid = auction_object.starting_bid try: max_bid = Bid.objects.filter(auction=auction).aggregate(max_bid = Max('bid_amount')) if max_bid['max_bid']: current_bid = max_bid['max_bid'] return current_bid except Bid.DoesNotExist: pass return current_bid def return_all_comments(auction): comments = Comment.objects.filter(auction=auction) return comments

24.8

110

0.660866

311

2,356

4.807074

0.189711

0.056187

0.04214

0.090301

0.318395

0.190635

0.124415

0.092308

0

0.247029

2,356

94

111

25.06383

0.842728

0.095076

0

0.254545

0

0.044231

0

0.010638

0

1

0.127273

false

0.036364

0

0.345455

0

null

0

null

0

1

0

1

8e6c720ed11080cd24768da2e5b31afb17339d1c

1,778

py

Python

tests/test_urls.py

kverdecia/dj-mypypi2

4ca5f67901a6a41029b4e1b0eccf8d74d4958b58

[ "MIT" ]

1

2021-08-12T08:59:09.000Z

tests/test_urls.py

kverdecia/dj-mypypi2

4ca5f67901a6a41029b4e1b0eccf8d74d4958b58

[ "MIT" ]

8

2021-04-24T06:08:07.000Z

2021-07-25T07:18:03.000Z

tests/test_urls.py

kverdecia/dj-mypypi2

4ca5f67901a6a41029b4e1b0eccf8d74d4958b58

[ "MIT" ]

null

import cuid from django.urls import reverse, resolve from django.test import TestCase from djmypypi2 import models from djmypypi2 import factories class TestUrls(TestCase): def test_package_list_reverse(self): url = reverse('djmypypi2:package-list') self.assertEqual(url, '/mypypi2/') def test_package_list_resolve(self): view_name = resolve('/mypypi2/').view_name self.assertEqual(view_name, 'djmypypi2:package-list') def test_package_detail_reverse(self): package: models.Package = factories.PackageFactory() url = reverse('djmypypi2:package-detail', kwargs={'package_name': package.name}) self.assertEqual(url, f'/mypypi2/{package.name}/') def test_package_detail_resolve(self): package: models.Package = factories.PackageFactory() view_name = resolve(f'/mypypi2/{package.name}/').view_name self.assertEqual(view_name, 'djmypypi2:package-detail') def test_download_reverse(self): version: models.Version = factories.VersionFactory() url = reverse('djmypypi2:download-package', kwargs={'archive_name': version.archive_name}) self.assertEqual(url, f'/mypypi2/@download/{version.archive_name}') def test_download_resolve(self): version: models.Version = factories.VersionFactory() view_name = resolve(f'/mypypi2/@download/{version.archive_name}').view_name self.assertEqual(view_name, 'djmypypi2:download-package') def test_upload_reverse(self): url = reverse('djmypypi2:upload-package') self.assertEqual(url, f'/mypypi2/@upload/') def test_upload_resolve(self): view_name = resolve(f'/mypypi2/@upload/').view_name self.assertEqual(view_name, 'djmypypi2:upload-package')

35.56

98

0.707537

207

1,778

5.898551

0.154589

0.078624

0.093366

0.075348

0.548731

0.398034

0.149058

0.116298

0

0.012212

0.170979

1,778

49

99

36.285714

0.816147

0

0.117647

0

0.223847

0.181102

0

0.235294

1

0.235294

false

0

0.147059

0

0.411765

0

null

0

null

0

1

0

1

8e6f1d30087ea8e2e9784ed81ab2535019f36f7a

2,263

py

Python

google-datacatalog-tableau-connector/src/google/datacatalog_connectors/tableau/scrape/rest_api_helper.py

Parkman328/datacatalog-connectors-bi

630de336617728713779d7224eeab140d5abaec2

[ "Apache-2.0" ]

27

2020-04-27T21:55:49.000Z

2022-02-18T22:09:13.000Z

google-datacatalog-tableau-connector/src/google/datacatalog_connectors/tableau/scrape/rest_api_helper.py

Parkman328/datacatalog-connectors-bi

630de336617728713779d7224eeab140d5abaec2

[ "Apache-2.0" ]

36

2020-05-01T15:26:14.000Z

2022-03-26T00:09:19.000Z

google-datacatalog-tableau-connector/src/google/datacatalog_connectors/tableau/scrape/rest_api_helper.py

Parkman328/datacatalog-connectors-bi

630de336617728713779d7224eeab140d5abaec2

[ "Apache-2.0" ]

18

2020-04-30T22:14:09.000Z

2022-01-13T10:28:03.000Z

#!/usr/bin/python # # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import requests from google.datacatalog_connectors.tableau.scrape import \ authenticator, constants class RestAPIHelper: def __init__(self, server_address, api_version, username, password, site_content_url=None): self.__server_address = server_address self.__api_version = api_version self.__username = username self.__password = password self.__site_content_url = site_content_url self.__base_api_endpoint = f'{server_address}/api/{api_version}' self.__common_headers = { 'Content-Type': constants.JSON_CONTENT_TYPE, 'Accept': constants.JSON_CONTENT_TYPE } self.__auth_credentials = None def get_all_sites_for_server(self): self.__set_up_auth_credentials() url = f'{self.__base_api_endpoint}/sites' headers = self.__common_headers.copy() headers[constants.X_TABLEAU_AUTH_HEADER_NAME] = \ self.__auth_credentials['token'] response = requests.get(url=url, headers=headers).json() return response['sites']['site'] \ if response and response.get('sites') \ and 'site' in response['sites'] \ else [] def __set_up_auth_credentials(self): if self.__auth_credentials: return self.__auth_credentials = \ authenticator.Authenticator.authenticate( self.__server_address, self.__api_version, self.__username, self.__password, self.__site_content_url)

31

74

0.646929

260

2,263

5.280769

0.434615

0.0437

0.040787

0.023307

0.077203

0

0.004875

0.274856

2,263

72

75

31.430556

0.83181

0.249669

0

0.066548

0.039216

0

1

0.071429

false

0.071429

0.047619

0

0.190476

0

null

0

null

0

1

0

1

8e90797c1a396d8d5df4b10107f151b6eb6a4b1d

445

py

Python

Symbol Patterns/symbolpattern143.py

vaidehisinha1/Python-PatternHouse

49f71bcc5319a838592e69b0e49ef1edba32bf7c

[ "MIT" ]

null

Symbol Patterns/symbolpattern143.py

vaidehisinha1/Python-PatternHouse

49f71bcc5319a838592e69b0e49ef1edba32bf7c

[ "MIT" ]

471

2022-01-15T07:07:18.000Z

2022-02-28T16:01:42.000Z

Symbol Patterns/symbolpattern143.py

vaidehisinha1/Python-PatternHouse

49f71bcc5319a838592e69b0e49ef1edba32bf7c

[ "MIT" ]

2

2022-01-17T09:43:16.000Z

2022-01-29T15:15:47.000Z

height = int(input()) for i in range(1,height+1): for j in range(1, height+1): if(i == height//2 or i == height or j == 1 or j == height and i >= height//2 or (j%2==1 and i<= height//2)): print("*",end=" ") else: print(end=" ") print() # Sample Input :- 7 # Output :- # * * * * # * * * * # * * * * * * * # * * # * * # * * # * * * * * * *

18.541667

116

0.346067

52

445

2.961538

0.365385

0.181818

0.155844

0.181818

0.194805

0

0.043478

0.431461

445

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117

19.347826

0.565217

0.285393

0

0.012987

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false

0

0.375

0

null

0

1

0

null

0

1

8e9a24be54fa83ecc2a85a73f853297e027edb0d

4,001

py

Python

ejercicios/alarma.py

proto-tools-docs/Soluciones

7a619e00572a3496cb08a90702f152f52c6d5e56

[ "MIT" ]

null

ejercicios/alarma.py

proto-tools-docs/Soluciones

7a619e00572a3496cb08a90702f152f52c6d5e56

[ "MIT" ]

null

ejercicios/alarma.py

proto-tools-docs/Soluciones

7a619e00572a3496cb08a90702f152f52c6d5e56

[ "MIT" ]

null

"""AyudaEnPython: https://www.facebook.com/groups/ayudapython Crear una aplicación de consola que permita al usuario programar alarmas de tiempo. Para realizar esta aplicación deberá presentarle al usuario las siguientes opciones: ver alarmas activas, agregar nueva alarma, agregar nueva alarma con tiempo aleatorio, editar alarma existente y quitar alarma. Para este ejercicio debe crear una clase llamada Reloj que contenga los atributos necesarios para almacenar el tiempo (horas, minutos y segundos), guiarse de las siguientes restricciones y utilizar el diagrama de clase: - Programe un método constructor vacío que cree objetos con un tiempo (horas, minutos y segundos) aleatorio. - Programe un método que reciba las horas, minutos y segundos para la nueva alarma. - Cree un método para modificar los segundos. - Cree un método para modificar los minutos. - Cree un método para modificar las horas. - Programe un método que devuelva una cadena de texto que incluya la hora actual de la variable en formato hh:mm:ss. * Considere el valor actual y el valor máximo que puede contener cada uno de los atributos al momento de añadir tiempo. +----------------------------------------+ | Reloj | +----------------------------------------+ | - horas: int | | - minutos: int | | - segundos: int | +----------------------------------------+ | + agregar_horas(int horas): void | | + agregar_minutos(int minutos): void | | + agregar_segundos(int segundos): void | | + visualizar(): string | +----------------------------------------+ """ from random import randint from prototools.menu import EzMenu from prototools.entradas import entrada_int class Reloj: def __init__(self) -> None: self._horas = randint(0, 24) self._minutos = randint(0, 59) self._segundos = randint(0, 59) def agregar_horas(self, horas): self._horas = horas def agregar_minutos(self, minutos): self._minutos = minutos def agregar_segundos(self, segundos): self._segundos = segundos def visualizar(self): return f"{self._horas:02}:{self._minutos:02}:{self._segundos:02}" alarma = Reloj() alarmas = [] def _entradas(): horas = entrada_int("Ingrese la hora: ", min=0, max=24) minutos = entrada_int("Ingrese los minutos: ", min=0, max=59) segundos = entrada_int("Ingrese los segundos: ", min=0, max=59) return horas, minutos, segundos def _agregar(alarma, horas, minutos, segundos): alarma.agregar_horas(horas) alarma.agregar_minutos(minutos) alarma.agregar_segundos(segundos) def ver_alarmas(): if alarmas == []: print("No hay alarmas por el momento") for n, alarma in enumerate(alarmas, 1): print(f"{n}. {alarma.visualizar()}") def nueva_alarma(): alarma = Reloj() _agregar(alarma, *_entradas()) alarmas.append(alarma) def alarma_aleatorio(): alarmas.append(Reloj()) print("Alarma aleatoria agregada") def editar_alarma(): ver_alarmas() print("Seleccionar la alarma a ser editada") n = int(input(">>> ")) alarma = alarmas[n-1] _agregar(alarma, *_entradas()) def quitar_alarma(): ver_alarmas() print("Seleccionar la alarma a ser removida") n = int(input(">>> ")) alarmas.pop(n-1) if __name__ == "__main__": menu = EzMenu(ancho=40) menu.titulo("Alarmas") menu.agregar_opciones( "ver alarmas activas", "agregar nueva alarma", "agregar alarma aleatoria", "editar alarmas existente", "quitar alarma", "salir", ) menu.agregar_funciones( ver_alarmas, nueva_alarma, alarma_aleatorio, editar_alarma, quitar_alarma, ) menu.run()

31.015504

75

0.610847

460

4,001

5.195652

0.31087

0.025105

0.022594

0.02636

0.135146

0.102092

0.078661

0.03682

0

0.009781

0.258935

4,001

129

76

31.015504

0.79629

0.453887

0

0.115942

0

0.180817

0.034878

0

0.046512

0

1

0.173913

false

0

0.043478

0.014493

0.26087

0.072464

0

null

0

null

0

1

0

1

8e9d82a4e05b9da4170cbe9911065b74ac889a13

2,976

py

Python

climops/calculate_statistics.py

YakelynRJ/climops

79384df69a499784e9b4be6ed4f81c1866e1b29d

[ "MIT" ]

null

climops/calculate_statistics.py

YakelynRJ/climops

79384df69a499784e9b4be6ed4f81c1866e1b29d

[ "MIT" ]

8

2018-12-06T22:30:26.000Z

2018-12-12T02:32:12.000Z

climops/calculate_statistics.py

HamidPahlavan/project

79384df69a499784e9b4be6ed4f81c1866e1b29d

[ "MIT" ]

null

""" This module is used to generate correlation (R) and regression (b) coefficients for relationships between the 2015 Census, 2018 Yale Climate Opinion Maps (YCOM) and land area datasets, as well as p values for these relationships. """ import numpy as np import pandas as pd from scipy.stats import linregress def calculate_stats_outputs(n_ycom, n_census, ycom_county, census): """ Function to estimate regression coefficients correlation between YCOM data variables and US Census variables. Inputs: n_ycom, a full list of names for ycom variables, n_census, a full list of names for census variables Outputs: a matrix of correlation values between each variable each dataset """ stats_outputs = np.zeros((len(n_ycom), len(n_census), 5)) for yind, yvar in enumerate(n_ycom): for cind, cvar in enumerate(n_census): ycom_notnull = ycom_county[yvar][census[cvar].notnull()] census_notnull = census[cvar][census[cvar].notnull()] stats_outputs[yind, cind, 0:5] = linregress(ycom_notnull, census_notnull) return stats_outputs def calculate_stats_outputs_standard(n_ycom, n_census, ycom_county, census): """ Function to estimate regression coefficients between YCOM data variables and US Census variables on standardized variables standardized_column = (column - mean(column)) / std(column) Inputs: n_ycom, a full list of names for ycom variables, n_census, a full list of names for census variables Outputs: a matrix of correlation values between each variable each dataset """ stats_outputs_standard = np.zeros((len(n_ycom), len(n_census), 5)) for yind, yvar in enumerate(n_ycom): for cind, cvar in enumerate(n_census): ycom_notnull = ycom_county[yvar][census[cvar].notnull()] census_notnull = census[cvar][census[cvar].notnull()] #also doing calculations on standardized variables census_standard = (census_notnull - np.mean(census_notnull)) / np.std(census_notnull) stats_outputs_standard[yind, cind, 0:5] = linregress(ycom_notnull, census_standard) return stats_outputs_standard def get_regs_df(stats_outputs_standard, n_census, n_ycom): """ making dataframe of regression coefficients these are kinda standardized -they show what % change in an opinion is given a 1 standard deviation change in a census variable """ regs = pd.DataFrame(stats_outputs_standard[:, :, 0], columns=n_census, index=n_ycom) return regs def get_cors_df(stats_outputs, n_census, n_ycom): """ making dataframe of correlation coefficients """ cors = pd.DataFrame(stats_outputs[:, :, 2], columns=n_census, index=n_ycom) return cors def get_pvalues_df(stats_outputs, n_census, n_ycom): """ making dataframes of pvalues """ pval = pd.DataFrame(stats_outputs[:, :, 3], columns=n_census, index=n_ycom) return pval

39.68

97

0.713374

412

2,976

4.975728

0.254854

0.081951

0.058537

0.021463

0.555122

0.491707

0.381463

0

0.007595

0.203629

2,976

74

98

40.216216

0.857384

0.403898

0

0.275862

1

0

1

0.172414

false

0

0.103448

0

0.448276

0

null

0

1

0

null

0

1

8e9dcbc8e5b65bb12dd6691d988f8f04cfc8ae26

275

py

Python

vFXT/version.py

ekpgh/AvereSDK-1

1e3584f08d2fb519ea3870e7e440cded9aacacd2

[ "MIT" ]

null

vFXT/version.py

ekpgh/AvereSDK-1

1e3584f08d2fb519ea3870e7e440cded9aacacd2

[ "MIT" ]

2

2019-03-07T23:59:08.000Z

2019-03-20T21:47:25.000Z

vFXT/version.py

ekpgh/AvereSDK-1

1e3584f08d2fb519ea3870e7e440cded9aacacd2

[ "MIT" ]

null

# Copyright (c) 2015-2020 Avere Systems, Inc. All Rights Reserved. # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See LICENSE in the project root for license information. __version__ = "0.5.4.3" __version_info__ = (0, 5, 4, 3)

45.833333

90

0.745455

42

275

4.666667

0.690476

0.102041

0.173469

0.040816

0

0.068966

0.156364

275

5

91

55

0.775862

0.770909

0

0.118644

0

1

0

false

0

null

0

1

0

null

0

1

8e9e302f177c972e4caf914f4f0b636eed885e2d

251

py

Python

exercises/solution_F4.py

dataXcode/IPP

c9b94ad2d7dc14b01e6657a4fa555507bbc7e93b

[ "MIT" ]

null

exercises/solution_F4.py

dataXcode/IPP

c9b94ad2d7dc14b01e6657a4fa555507bbc7e93b

[ "MIT" ]

null

exercises/solution_F4.py

dataXcode/IPP

c9b94ad2d7dc14b01e6657a4fa555507bbc7e93b

[ "MIT" ]

null

house = [ ['hallway', 14.35], ['kitchen', 15.0], ['living room', 19.0], ['bedroom', 12.5], ['bathroom', 8.75] ] # Code the for loop for x in house: print(str(x[0]) + ' area is ' + str(x[1]) + 'm')

25.1

50

0.426295

35

251

3.057143

0.8

0.074766

0

0.110429

0.350598

251

9

51

27.888889

0.546012

0.067729

0

0.215517

0

1

0

false

0

0.142857

0

null

0

1

0

null

0

1

8eaa9e9b44dd4cdbcc7d177b9fd352b66bc449f6

1,050

py

Python

vuln_server/vulnerabilities/subprocess_vuln.py

denny00786/CASoftwareDevelopment

d03c82b6bb033a39b4270115ec464eca773e0814

[ "Apache-2.0" ]

1

2020-04-02T00:29:16.000Z

vuln_server/vulnerabilities/subprocess_vuln.py

denny00786/CASoftwareDevelopment

d03c82b6bb033a39b4270115ec464eca773e0814

[ "Apache-2.0" ]

null

vuln_server/vulnerabilities/subprocess_vuln.py

denny00786/CASoftwareDevelopment

d03c82b6bb033a39b4270115ec464eca773e0814

[ "Apache-2.0" ]

4

2021-04-01T21:31:01.000Z

2022-03-23T08:22:44.000Z

import subprocess from vuln_server.outputgrabber import OutputGrabber from flask import request, redirect, render_template class SubprocessVuln(): def bypass(self): if request.method == 'POST': # Check if data is not empty, post forms has all params defined # which may be empty and cause unexpected behaviour. if request.form['input_data'] != '': try: # Instanciate a different stdout grabber for subprocess output = OutputGrabber() with output: # Execute system command with an unsafe input parameter subprocess.call("ping -c1 " + request.form['input_data'], shell=True) return output.capturedtext except Exception as e: return "Server Error: {}:".format(str(e)) else: return redirect(request.url) return render_template('subprocess.html')

38.888889

79

0.552381

102

1,050

5.637255

0.686275

0.048696

0.055652

0.069565

0

0.001534

0.379048

1,050

26

80

40.384615

0.880368

0.209524

0

0.078788

0

1

0.055556

false

0.055556

0.166667

0

0.5

0

null

0

null

0

1

0

1

8eab0af3b0aca18605cc36d406b8f68048ee7f83

2,050

py

Python

tests/test_resource.py

luhn/pyramid-resource

7de2f4d136ef39f8b223ef675def6a04d71311ae

[ "MIT" ]

1

2019-02-05T03:06:24.000Z

tests/test_resource.py

luhn/pyramid-resource

7de2f4d136ef39f8b223ef675def6a04d71311ae

[ "MIT" ]

null

tests/test_resource.py

luhn/pyramid-resource

7de2f4d136ef39f8b223ef675def6a04d71311ae

[ "MIT" ]

null

import pytest from pyramid_resource import Resource def test_default_lookup(): class SubResource(Resource): pass class MyResource(Resource): __children__ = { "sub": SubResource, } root = MyResource("request") sub = root["sub"] assert isinstance(sub, SubResource) assert sub.request == "request" assert sub.__name__ == "sub" assert sub.__parent__ is root with pytest.raises(KeyError): root["sub2"] def test_custom_lookup_subclass(): class SubResource(Resource): pass class MyResource(Resource): def get_child(self, key): assert key == "sub" return SubResource root = MyResource("request") sub = root["sub"] assert isinstance(sub, SubResource) assert sub.request == "request" assert sub.__name__ == "sub" assert sub.__parent__ is root def test_custom_lookup_tuple(): class SubResource(Resource): pass class MyResource(Resource): def get_child(self, key): assert key == "sub" return SubResource, {"foo": "bar"} root = MyResource("request") sub = root["sub"] assert isinstance(sub, SubResource) assert sub.request == "request" assert sub.__name__ == "sub" assert sub.__parent__ is root assert sub.foo == "bar" def test_getattr(): class SubResource(Resource): pass class MyResource(Resource): subfoo = "subbar" @property def prop(self): return "myprop" parent = MyResource("request") child = SubResource("request", "sub", parent, foo="bar") grandchild = SubResource("request", "sub", child) with pytest.raises(AttributeError): assert parent.foo assert parent.subfoo == "subbar" assert parent.prop == "myprop" assert child.foo == "bar" assert child.subfoo == "subbar" assert child.prop == "myprop" assert grandchild.foo == "bar" assert grandchild.subfoo == "subbar" assert grandchild.prop == "myprop"

24.117647

60

0.621463

218

2,050

5.66055

0.201835

0.072934

0.077796

0.090762

0.544571

0.461912

0

0.000664

0.264878

2,050

84

61

24.404762

0.818182

0

0.523077

0

0.080976

0

0.369231

1

0.107692

false

0.061538

0.030769

0.015385

0.338462

0

null

0

null

0

1

0

1

8eb957a2a53df1c654647771e4169777cc775e3d

1,222

py

Python

pile.py

yehudareisler/risky-game

ea919bd07a2acf75dfd184b5c59ad80d41f47428

[ "MIT" ]

3

2021-01-21T02:06:12.000Z

2022-03-14T10:26:43.000Z

pile.py

yehudareisler/risky-game

ea919bd07a2acf75dfd184b5c59ad80d41f47428

[ "MIT" ]

null

pile.py

yehudareisler/risky-game

ea919bd07a2acf75dfd184b5c59ad80d41f47428

[ "MIT" ]

1

2021-08-29T07:47:12.000Z

import random from card import Card, CardType class Pile: def __init__(self, cards): self.cards = cards def __getitem__(self, key): return self.cards[key] def __str__(self): representation = f'Pile with {len(self.cards)} cards:\n' for card in self.cards: representation += f'{card}\n' return representation @staticmethod def from_config_file(path_to_file): new_cards = [ Card(None, CardType.WILDCARD), Card(None, CardType.WILDCARD) ] with open(path_to_file) as f: card_count = int(f.readline().strip()) for _ in range(card_count): territory = f.readline().strip() card_type = f.readline().strip() new_cards.append(Card(territory, CardType[card_type])) return Pile(new_cards) def shuffle(self): random.shuffle(self.cards) def remove_card(self, card): self.cards.remove(card) def remove_card_with_index(self, index): self.cards.remove(self.cards[index]) def add_card(self, card): self.cards.append(card) def draw_card(self): return self.cards.pop(0)

24.44

70

0.594926

151

1,222

4.602649

0.311258

0.142446

0.060432

0.069065

0.060432

0

0.001163

0.296236

1,222

49

71

24.938776

0.806977

0

0.036007

0

1

0.257143

false

0

0.057143

0.457143

0

null

0

null

0

1

0

1

8ec74f7148172e1125c6011ff0477dea31725ff0

1,038

py

Python

CH02/2.5.py

MonoHaru/Deep-Learning-from-Scratch_2

e7dd6e7c82a34fadfa17331c2934f5f9ae2c3ec3

[ "MIT" ]

null

CH02/2.5.py

MonoHaru/Deep-Learning-from-Scratch_2

e7dd6e7c82a34fadfa17331c2934f5f9ae2c3ec3

[ "MIT" ]

null

CH02/2.5.py

MonoHaru/Deep-Learning-from-Scratch_2

e7dd6e7c82a34fadfa17331c2934f5f9ae2c3ec3

[ "MIT" ]

null

# 2.5 정리 # 이번 장에서는 자연어를 대상으로, # 특히 컴퓨터에게 '단어의 의미'를 이해하기 위한 주제로 진행함 # 시소러스 기법 ''' 단어들의 관련성을 사람이 수작업으로 하나씩 정의한다. 이 작업은 매우 힘들고 (느낌의 미세한 차이를 나타낼 수 없다 등) 표현력에도 한계가 있다. ''' # 통계 기반 기법 ''' 말뭉치로부터 단어의 의미를 자동으로 추출하고, 그 의미를 벡터로 표현한다. 구체적으로 1. 단어의 동시발생 행렬을 만든다. 2. PPMI 행렬로 변환한다. 3. 안정성을 높이기 위해 SVD를 이용해 차원을 감소시켜, 각 단어의 분산 표현을 만든다. 4. 분산 표현에 따르면 의미가 (그리고 문법적인 용법면에서) 비슷한 단어들이 벡터 공간에서도 서로 가까이 모여 있음을 확인한다. ''' # 전처리 함수 ''' cos_similarity(): 벡터 간 유사도를 측정하는 함수 most_similar(): 유사 단어의 랭킹을 표시하는 함수 ''' # 이번 장에서 배운 내용 ''' 1. WordNet 등의 시소러스를 이용하면 유의어를 얻거나 단어 사이의 유사도를 측정하는 등 유용한 작업을 할 수 있다. 2. 시소러스 기반 기법은 시소러스를 작성하는 데 엄청난 인적 자원이 든다거나 새로운 단어에 대응하기 어렵다는 문제가 있다. 3. 현재는 말뭉치를 이용해 단어를 백터화하는 방식이 주로 쓰인다. 4. 최근의 단어 벡터화 기법들은 대부분 '단어의 의미는 주변 단어에 의해 형성된다'는 분포 가설에 기초한다. 5. 통계 기반 기법은 말뭉치 안의 각 단어에 대해서 그 단어의 주변 단어의 빈도를 집계한다(동시발생 행렬). 6. 동시발생 행렬 PPMI 행렬로 변환하고 다시 차원을 감소시킴으로써, 거대한 '희소벡터'를 작은 '밀집벡터'로 변환할 수 있다. 7. 단어의 벡터 공간에서는 의미가 가까운 단어는 그 거리도 가까울 것으로 기대된다. '''

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8eca58ddc6a8a4fc980e7ffec65c56c6b1e8dc5f

343

py

Python

data/bug_dataset.py

happygirlzt/soft_alignment_model_bug_deduplication

9c529542749a52e377baeb99d1782920bc72df49

[ "Unlicense" ]

2

2020-11-11T00:26:25.000Z

2020-12-21T16:17:28.000Z

data/bug_dataset.py

happygirlzt/soft_alignment_model_bug_deduplication

9c529542749a52e377baeb99d1782920bc72df49

[ "Unlicense" ]

5

2020-12-22T10:59:38.000Z

2021-07-13T15:00:46.000Z

data/bug_dataset.py

irving-muller/soft_alignment_model_bug_deduplication

abf786a17f526d965f1b6c303b06f26662d22f32

[ "Unlicense" ]

6

2020-09-25T01:01:37.000Z

2022-02-20T19:29:31.000Z

""" Each dataset has bug report ids and the ids of duplicate bug reports. """ class BugDataset(object): def __init__(self, file): f = open(file, 'r') self.info = f.readline().strip() self.bugIds = [id for id in f.readline().strip().split()] self.duplicateIds = [id for id in f.readline().strip().split()]

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8eca5e2a175ef4b1ea3f4ed24d6fd9463dbced1b

517

py

Python

orm_sqlfan/libreria/migrations/0004_auto_20191125_0518.py

rulotr/djangorm_sqlfan

4bcadd1459e5a39584bb5ad8bafaaf3993324f6a

[ "MIT" ]

2

2021-09-29T01:08:56.000Z

2022-02-14T03:34:37.000Z

orm_sqlfan/libreria/migrations/0004_auto_20191125_0518.py

rulotr/djangorm_sqlfan

4bcadd1459e5a39584bb5ad8bafaaf3993324f6a

[ "MIT" ]

4

2020-02-12T02:52:19.000Z

2021-04-08T20:46:05.000Z

orm_sqlfan/libreria/migrations/0004_auto_20191125_0518.py

rulotr/djangorm_sqlfan

4bcadd1459e5a39584bb5ad8bafaaf3993324f6a

[ "MIT" ]

null

# Generated by Django 2.2.7 on 2019-11-25 05:18 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('libreria', '0003_auto_20191125_0515'), ] operations = [ migrations.RemoveField( model_name='libro', name='id', ), migrations.AlterField( model_name='libro', name='isbn', field=models.CharField(max_length=13, primary_key=True, serialize=False), ), ]

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8ece4878dfbf0ffee3c017f8812769aed1333588

4,582

py

Python

tests/h/services/flag_test.py

pombredanne/h

9c4c2dc0d53ed5bed5183936c24b4c27b23070b4

[ "BSD-2-Clause" ]

2,103

2015-01-07T12:47:49.000Z

2022-03-29T02:38:25.000Z

tests/h/services/flag_test.py

pombredanne/h

9c4c2dc0d53ed5bed5183936c24b4c27b23070b4

[ "BSD-2-Clause" ]

4,322

2015-01-04T17:18:01.000Z

2022-03-31T17:06:02.000Z

tests/h/services/flag_test.py

admariner/h

25ef1b8d94889df86ace5a084f1aa0effd9f4e25

[ "BSD-2-Clause" ]

389

2015-01-24T04:10:02.000Z

2022-03-28T08:00:16.000Z

import pytest from h import models from h.services import flag class TestFlagServiceFlagged: def test_it_returns_true_when_flag_exists(self, svc, flag): assert svc.flagged(flag.user, flag.annotation) is True def test_it_returns_false_when_flag_does_not_exist(self, svc, user, annotation): assert not svc.flagged(user, annotation) def test_it_handles_missing_values(self, svc, user, annotation): assert not svc.flagged(None, annotation) assert not svc.flagged(user, None) def test_it_uses_the_cache_if_possible(self, svc, user, annotation): assert not svc.flagged(user, annotation) svc._flagged_cache[ # pylint:disable=protected-access (user.id, annotation.id) ] = True assert svc.flagged(user, annotation) def test_it_lists_flagged_ids(self, svc, user, flag, noise): annotation_ids = [flag.annotation_id for flag in noise] annotation_ids.append(flag.annotation_id) all_flagged = svc.all_flagged(user, annotation_ids) assert all_flagged == {flag.annotation_id} assert svc._flagged_cache == { # pylint:disable=protected-access (user.id, noise[0].annotation_id): False, (user.id, noise[1].annotation_id): False, (user.id, flag.annotation_id): True, } def test_it_handles_all_flagged_with_no_ids(self, svc, user): assert svc.all_flagged(user, []) == set() def test_it_handles_all_flagged_with_no_user(self, svc, annotation): assert svc.all_flagged(None, [annotation.id]) == set() @pytest.fixture def flag(self, factories, user, annotation): return factories.Flag(user=user, annotation=annotation) @pytest.fixture def user(self, factories): return factories.User() @pytest.fixture def annotation(self, factories): return factories.Annotation() @pytest.fixture(autouse=True) def noise(self, factories): return factories.Flag.create_batch(2) class TestFlagServiceCreate: def test_it_creates_flag(self, svc, db_session, factories): user = factories.User() annotation = factories.Annotation(userid=user.userid) svc.create(user, annotation) flag = ( db_session.query(models.Flag) .filter_by(user_id=user.id, annotation_id=annotation.id) .first() ) assert flag is not None def test_it_skips_creating_flag_when_already_exists( self, svc, db_session, factories ): existing = factories.Flag() svc.create(existing.user, existing.annotation) assert ( db_session.query(models.Flag) .filter_by(user_id=existing.user.id, annotation_id=existing.annotation.id) .count() == 1 ) class TestFlagServiceCount: def test_flag_count_returns_zero_for_unflagged_annotation(self, svc, unflagged): assert not svc.flag_count(unflagged) def test_flag_count_returns_zero_for_None(self, svc): assert not svc.flag_count(None) def test_flag_count_returns_flag_count_for_flagged_annotation(self, svc, flagged): assert svc.flag_count(flagged) == 2 def test_flag_count_uses_the_cache(self, svc, flagged): svc._flag_count_cache[flagged.id] = 99999 # pylint:disable=protected-access assert svc.flag_count(flagged) == 99999 def test_flag_counts(self, svc, flagged, unflagged): ann_ids = [flagged.id, unflagged.id] flag_counts = svc.flag_counts(ann_ids) assert ( # pylint:disable=protected-access flag_counts == svc._flag_count_cache == {flagged.id: 2, unflagged.id: 0} ) def test_flag_counts_returns_empty_dict_for_no_ids(self, svc): assert svc.flag_counts([]) == {} def test_flag_counts_returns_zero_for_unflagged_annotation(self, svc, unflagged): flag_counts = svc.flag_counts([unflagged.id]) assert not flag_counts[unflagged.id] @pytest.fixture def unflagged(self, factories): return factories.Annotation() @pytest.fixture def flagged(self, factories): annotation = factories.Annotation() factories.Flag.create_batch(2, annotation=annotation) return annotation class TestFlagServiceFactory: def test_it_returns_flag_service(self, pyramid_request): svc = flag.flag_service_factory(None, pyramid_request) assert isinstance(svc, flag.FlagService) @pytest.fixture def svc(db_session): return flag.FlagService(db_session)

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