xszheng2020/the_stack_dedup_python_hits_1 · Datasets at Hugging Face

be62c8d9e725078536f0891cffbcc08c85ff6f54

979

py

Python

my_general_helpers.py

arminbahl/drosophila_phototaxis_paper

e01dc95675f835926c9104b34bf6cfd7244dee2b

[ "MIT" ]

null

my_general_helpers.py

arminbahl/drosophila_phototaxis_paper

e01dc95675f835926c9104b34bf6cfd7244dee2b

[ "MIT" ]

null

my_general_helpers.py

arminbahl/drosophila_phototaxis_paper

e01dc95675f835926c9104b34bf6cfd7244dee2b

[ "MIT" ]

null

from scipy.signal import butter,filtfilt from numba import jit import bisect def is_number_in_sorted_vector(sorted_vector, num): index = bisect.bisect_left(sorted_vector, num) return index != len(sorted_vector) and sorted_vector[index] == num # def butter_lowpass(cutoff, fs, order=5): # nyq = 0.5 * fs # normal_cutoff = cutoff / nyq # b, a = butter(order, normal_cutoff, btype='low', analog=False) # return b, a def butter_lowpass_filter(data, cutoff, fs, order): nyq = 0.5 * fs # Nyquist Frequency normal_cutoff = cutoff / nyq # Get the filter coefficients b, a = butter(order, normal_cutoff, btype='low', analog=False) y = filtfilt(b, a, data) return y @jit def first_order_lowpass_filter(signal_in, signal_out, tau, dt): alpha_lowpass = dt / (tau + dt) signal_out[0] = signal_in[0] for i in range(1, len(signal_in)): signal_out[i] = alpha_lowpass*signal_in[i] + (1-alpha_lowpass)*signal_out[i-1]

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0

null

0

null

0

1

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1

be665281e674fbcee73480a5a06334a427283318

1,254

py

Python

download.py

kaija/taiwan_stockloader

637244c3b0bc96093cc5a7b3df093a829f9e3c2d

[ "MIT" ]

2

2015-06-13T09:17:46.000Z

2015-10-25T15:31:33.000Z

download.py

kaija/taiwan_stockloader

637244c3b0bc96093cc5a7b3df093a829f9e3c2d

[ "MIT" ]

null

download.py

kaija/taiwan_stockloader

637244c3b0bc96093cc5a7b3df093a829f9e3c2d

[ "MIT" ]

3

2016-02-01T07:36:55.000Z

2018-08-03T12:22:20.000Z

import datetime import httplib import urllib from datetime import timedelta #now = datetime.datetime.now(); #today = now.strftime('%Y-%m-%d') #print today def isfloat(value): try: float(value) return True except ValueError: return False def convfloat(value): try: return float(value) except ValueError: return -1 today = datetime.date.today() one_day = timedelta(days=1); #start_day = datetime.date(2004, 2, 11); start_day = datetime.date(2010, 8, 21); print "Download from " + start_day.strftime("%Y-%m-%d") + " to " + today.strftime("%Y-%m-%d") dl_date = start_day while dl_date < today: httpreq = httplib.HTTPConnection('www.twse.com.tw') headers = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"} date_str = str(dl_date.year - 1911 ) + dl_date.strftime("/%m/%d") form = urllib.urlencode({'download': 'csv', 'qdate': date_str, 'selectType': 'ALLBUT0999'}) httpreq.request("POST", "/ch/trading/exchange/MI_INDEX/MI_INDEX.php", form, headers); httpres = httpreq.getresponse() stock_csv = httpres.read() file_name = "data/" + dl_date.strftime("%Y%m%d") + ".csv" print "downloading " + file_name f = open(file_name, "w") f.write(stock_csv) dl_date += one_day print "Download Finish!"

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be687c8fd20a0765459343471aaeb0dc60aa0c2b

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py

Python

evennia/scripts/migrations/0013_auto_20191025_0831.py

Jaykingamez/evennia

cf7cab1fea99ede3efecb70a65c3eb0fba1d3745

[ "BSD-3-Clause" ]

1,544

2015-01-01T22:16:31.000Z

2022-03-31T19:17:45.000Z

evennia/scripts/migrations/0013_auto_20191025_0831.py

Jaykingamez/evennia

cf7cab1fea99ede3efecb70a65c3eb0fba1d3745

[ "BSD-3-Clause" ]

1,686

2015-01-02T18:26:31.000Z

2022-03-31T20:12:03.000Z

evennia/scripts/migrations/0013_auto_20191025_0831.py

Jaykingamez/evennia

cf7cab1fea99ede3efecb70a65c3eb0fba1d3745

[ "BSD-3-Clause" ]

867

2015-01-02T21:01:54.000Z

2022-03-29T00:28:27.000Z

# Generated by Django 2.2.6 on 2019-10-25 12:31 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [("scripts", "0012_auto_20190128_1820")] operations = [ migrations.AlterField( model_name="scriptdb", name="db_typeclass_path", field=models.CharField( db_index=True, help_text="this defines what 'type' of entity this is. This variable holds a Python path to a module with a valid Evennia Typeclass.", max_length=255, null=True, verbose_name="typeclass", ), ) ]

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null

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1

be6d27c87017d3ff2b758a9a1954cf3e265b550c

554

py

Python

iocms/iocms/urls.py

Gaurav-Zaiswal/iw-acad-iocms-be

a133f120eed93433925608f08c5145d2d0d1db39

[ "MIT" ]

null

iocms/iocms/urls.py

Gaurav-Zaiswal/iw-acad-iocms-be

a133f120eed93433925608f08c5145d2d0d1db39

[ "MIT" ]

null

iocms/iocms/urls.py

Gaurav-Zaiswal/iw-acad-iocms-be

a133f120eed93433925608f08c5145d2d0d1db39

[ "MIT" ]

2

2021-09-16T04:44:59.000Z

2021-09-16T05:45:31.000Z

from django.contrib import admin from django.urls import include, path from django.conf import settings from django.conf.urls.static import static urlpatterns = [ path('admin/', admin.site.urls), path('class/', include('classroom.urls')), path('assignment-api/', include('assignment.urls', namespace='assignment')), path('feed/', include('feed.urls', namespace='feed')), path('users/', include('users.urls'), name="user-register") ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

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0

null

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0

1

be6f16523ef2463524119c42f75567ed0f66d560

1,905

py

Python

src/security/__init__.py

slippers/blogging_security_flatpage

53644978b798c66369416b1e5625cc04d89c0a87

[ "MIT" ]

1

2018-12-31T05:30:13.000Z

src/security/__init__.py

slippers/blogging_security_flatpage

53644978b798c66369416b1e5625cc04d89c0a87

[ "MIT" ]

null

src/security/__init__.py

slippers/blogging_security_flatpage

53644978b798c66369416b1e5625cc04d89c0a87

[ "MIT" ]

null

from src import app, db from .models import User, Role, RoleUsers from .security_admin import UserAdmin, RoleAdmin from flask_security import Security, SQLAlchemyUserDatastore, \ login_required, roles_accepted from flask_security.utils import encrypt_password def config_security_admin(admin): admin.add_view(UserAdmin(db.session)) admin.add_view(RoleAdmin(db.session)) def configure_security(): # Create the Roles "admin" and "end-user" -- unless they already exist user_datastore.find_or_create_role(name='admin', description='Administrator') user_datastore.find_or_create_role(name='end-user', description='End user') user_datastore.find_or_create_role(name='blogger', description='Blogger') # Create two Users for testing purposes -- unless they already exists. # In each case, use Flask-Security utility function to encrypt the password. pw = encrypt_password('password') # pw = 'password' if not user_datastore.get_user('someone@example.com'): user_datastore.create_user(email='someone@example.com', password=pw) if not user_datastore.get_user('admin@example.com'): user_datastore.create_user(email='admin@example.com', password=pw) # Give one User has the "end-user" role, while the other has the "admin" role. #(This will have no effect if the # Users already have these Roles.) Again, commit any database changes. user_datastore.add_role_to_user('someone@example.com', 'end-user') user_datastore.add_role_to_user('someone@example.com', 'blogger') user_datastore.add_role_to_user('admin@example.com', 'admin') user_datastore.add_role_to_user('admin@example.com', 'blogger') db.session.commit() # Setup Flask-Security user_datastore = SQLAlchemyUserDatastore(db, User, Role) security = Security(app, user_datastore) # Create any database tables that don't exist yet. db.create_all()

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null

0

null

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1

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1

be76f999496b5e5961109377d7a8e9bebf2c7e1e

2,576

py

Python

regexem.py

lvijay/ilc

1c3b1381e7e5a5064bda829e3d34bfaf24745d1a

[ "BSD-3-Clause-No-Nuclear-Warranty" ]

1

2019-01-03T17:44:11.000Z

regexem.py

lvijay/ilc

1c3b1381e7e5a5064bda829e3d34bfaf24745d1a

[ "BSD-3-Clause-No-Nuclear-Warranty" ]

null

regexem.py

lvijay/ilc

1c3b1381e7e5a5064bda829e3d34bfaf24745d1a

[ "BSD-3-Clause-No-Nuclear-Warranty" ]

null

#!/usr/bin/python # -*- mode: python; -*- ## This file is part of Indian Language Converter ## Copyright (C) 2006 Vijay Lakshminarayanan <liyer.vijay@gmail.com> ## Indian Language Converter is free software; you can redistribute it ## and/or modify it under the terms of the GNU General Public License ## as published by the Free Software Foundation; either version 2 of ## the License, or (at your option) any later version. ## This program is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## You should have received a copy of the GNU General Public License ## along with this program; if not, write to the Free Software ## Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA ## 02110-1301, USA. ## $Id: regexem.py,v 1.4 2006-03-26 03:15:24 vijay Exp $ ## Author: Vijay Lakshminarayanan ## $Date: 2006-03-26 03:15:24 $ import sys from re import escape def regexem (strlst): """Returns a single string which is the regular expression to identify any single word in the given argument. See the Examples given at the end of this file.""" return regexem_internal([escape(s) for s in strlst]) def regexem_internal (strlst): strlst.sort() s, rest = strlst[0], strlst[1:] groups = {} groups[s] = [s] for string in rest: if string.startswith(s) and len(s) < len(string): # avoid duplicates groups[s].append(string[len(s):]) # add the suffix to the group else: s = string # a fresh prefix groups[s] = [s] regex = '' for prefix, words in groups.items(): inreg = '' if len(words) == 2: # i.e. words[0] is a subset of words[1] inreg += words[0] + '(' + words[1] + ')' + '?' elif len(words) > 2: inreg += words[0] + '(' + regexem_internal(words[1:]) + ')' + '?' else: inreg += prefix # since prefix == words[0] in this case. regex += '(' + inreg + ')' + '|' return regex[:-1] # we don't need the last '|' if __name__ == '__main__': print ''.join(regexem(sys.argv[1:])) ## Examples # # $ ./regexem.py emacs vi ed # (ed)|(emacs)|(vi) # # $ ./regexem.py batsman bats well # (well)|(bats(man)?) # # $ ./regexem.py houses housefly # (houses)|(housefly) ## Note that they aren't grouped together # ## a slightly complicated example # $ ./regexem.py an anteater and an ant # (an((d)|(t(eater)?))?)

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1

be876cf3ef298b948a6559bdc7b9b04da2062463

589

py

Python

0201-0300/0251-Flatten 2D Vector/0251-Flatten 2D Vector.py

jiadaizhao/LeetCode

4ddea0a532fe7c5d053ffbd6870174ec99fc2d60

[ "MIT" ]

49

2018-05-05T02:53:10.000Z

2022-03-30T12:08:09.000Z

0201-0300/0251-Flatten 2D Vector/0251-Flatten 2D Vector.py

jolly-fellow/LeetCode

ab20b3ec137ed05fad1edda1c30db04ab355486f

[ "MIT" ]

11

2017-12-15T22:31:44.000Z

2020-10-02T12:42:49.000Z

0201-0300/0251-Flatten 2D Vector/0251-Flatten 2D Vector.py

jolly-fellow/LeetCode

ab20b3ec137ed05fad1edda1c30db04ab355486f

[ "MIT" ]

28

2017-12-05T10:56:51.000Z

2022-01-26T18:18:27.000Z

class Vector2D: def __init__(self, v: List[List[int]]): def getIt(): for row in v: for val in row: yield val self.it = iter(getIt()) self.val = next(self.it, None) def next(self) -> int: result = self.val self.val = next(self.it, None) return result def hasNext(self) -> bool: return self.val is not None # Your Vector2D object will be instantiated and called as such: # obj = Vector2D(v) # param_1 = obj.next() # param_2 = obj.hasNext()

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null

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null

0

1

0

1

be8cef6fbad82834998e279653a3e939a968c9d8

2,244

py

Python

instructions/instructions.py

fernandozanutto/PyNES

cb8d589ceb55cd7df0e114e726c6b6bbbc556172

[ "Apache-2.0" ]

null

instructions/instructions.py

fernandozanutto/PyNES

cb8d589ceb55cd7df0e114e726c6b6bbbc556172

[ "Apache-2.0" ]

null

instructions/instructions.py

fernandozanutto/PyNES

cb8d589ceb55cd7df0e114e726c6b6bbbc556172

[ "Apache-2.0" ]

null

from addressing import * from instructions.base_instructions import SetBit, ClearBit from instructions.generic_instructions import Instruction from status import Status # set status instructions class Sec(SetBit): identifier_byte = bytes([0x38]) bit = Status.StatusTypes.carry class Sei(SetBit): identifier_byte = bytes([0x78]) bit = Status.StatusTypes.interrupt class Sed(SetBit): identifier_byte = bytes([0xF8]) bit = Status.StatusTypes.decimal # clear status instructions class Cld(ClearBit): identifier_byte = bytes([0xD8]) bit = Status.StatusTypes.decimal class Clc(ClearBit): identifier_byte = bytes([0x18]) bit = Status.StatusTypes.carry class Clv(ClearBit): identifier_byte = bytes([0xB8]) bit = Status.StatusTypes.overflow class Cli(ClearBit): identifier_byte = bytes([0x58]) bit = Status.StatusTypes.interrupt class Bit(Instruction): @classmethod def get_data(cls, cpu, memory_address, data_bytes) -> Optional[int]: return cpu.bus.read_memory(memory_address) @classmethod def apply_side_effects(cls, cpu, memory_address, value): and_result = cpu.a_reg & value cpu.status_reg.bits[Status.StatusTypes.zero] = not and_result cpu.status_reg.bits[Status.StatusTypes.overflow] = ( value & (1 << 6)) > 0 cpu.status_reg.bits[Status.StatusTypes.negative] = ( value & (1 << 7)) > 0 class BitZeroPage(ZeroPageAddressing, Bit): identifier_byte = bytes([0x24]) class BitAbsolute(AbsoluteAddressing, Bit): identifier_byte = bytes([0x2C]) class Brk(ImplicitAddressing, Instruction): identifier_byte = bytes([0x00]) @classmethod def get_data(cls, cpu, memory_address, data_bytes) -> Optional[int]: return super().get_data(cpu, memory_address, data_bytes) @classmethod def write(cls, cpu, memory_address, value): cpu.push_to_stack(cpu.pc_reg + 1, 2) cpu.push_to_stack(cpu.status_reg.to_int() | (1 << 4), 1) @classmethod def apply_side_effects(cls, cpu, memory_address, value): cpu.status_reg.bits[Status.StatusTypes.interrupt] = 1 cpu.running = False @classmethod def get_cycles(cls): return 7

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null

0

null

0

1

0

1

be917ccdfeb7754dd0eabc0327954755752723d8

425

py

Python

Estrutura_Decisao/who.py

M3nin0/supreme-broccoli

186c1ea3b839ba3139f9301660dec8fbd27a162e

[ "Apache-2.0" ]

null

Estrutura_Decisao/who.py

M3nin0/supreme-broccoli

186c1ea3b839ba3139f9301660dec8fbd27a162e

[ "Apache-2.0" ]

null

Estrutura_Decisao/who.py

M3nin0/supreme-broccoli

186c1ea3b839ba3139f9301660dec8fbd27a162e

[ "Apache-2.0" ]

null

prod1 = float(input("Insira o valor do produto A: ")) prod2 = float(input("Insira o valor do produto B: ")) prod3 = float(input("Insira o valor do produto C: ")) if prod1 < prod2 and prod1 < prod3: print ("Escolha o produto A é o mais barato") elif prod2 < prod1 and prod2 < prod3: print ("Escolha o produto B é o mais barato") elif prod3 < prod1 and prod3 < prod2: print ("Escolha o produto C é o mais barato")

38.636364

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null

0

1

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null

0

1

be99d62141111a8ad89510bea1e2a527e33cf08b

478

py

Python

autodiff/debug_vjp.py

Jakob-Unfried/msc-legacy

2c41f3f714936c25dd534bd66da802c26176fcfa

[ "MIT" ]

1

2021-03-22T14:16:43.000Z

autodiff/debug_vjp.py

Jakob-Unfried/msc-legacy

2c41f3f714936c25dd534bd66da802c26176fcfa

[ "MIT" ]

null

autodiff/debug_vjp.py

Jakob-Unfried/msc-legacy

2c41f3f714936c25dd534bd66da802c26176fcfa

[ "MIT" ]

null

import pdb import warnings from jax import custom_vjp @custom_vjp def debug_identity(x): """ acts as identity, but inserts a pdb trace on the backwards pass """ warnings.warn('Using a module intended for debugging') return x def _debug_fwd(x): warnings.warn('Using a module intended for debugging') return x, x # noinspection PyUnusedLocal def _debug_bwd(x, g): pdb.set_trace() return g debug_identity.defvjp(_debug_fwd, _debug_bwd)

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0

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null

0

1

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1

bea3fce840a92d3dac26a2f605494f57192e6efe

1,217

py

Python

pyscf/nao/test/test_0037_aos.py

fdmalone/pyscf

021b17ac721e292b277d2b740e2ff8ab38bb6a4a

[ "Apache-2.0" ]

1

2019-07-01T12:39:45.000Z

pyscf/nao/test/test_0037_aos.py

fdmalone/pyscf

021b17ac721e292b277d2b740e2ff8ab38bb6a4a

[ "Apache-2.0" ]

null

pyscf/nao/test/test_0037_aos.py

fdmalone/pyscf

021b17ac721e292b277d2b740e2ff8ab38bb6a4a

[ "Apache-2.0" ]

null

# Copyright 2014-2018 The PySCF Developers. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function, division import os,unittest,numpy as np class KnowValues(unittest.TestCase): def test_aos_libnao(self): """ Computing of the atomic orbitals """ from pyscf.nao import system_vars_c from pyscf.tools.cubegen import Cube sv = system_vars_c().init_siesta_xml(label='water', cd=os.path.dirname(os.path.abspath(__file__))) cc = Cube(sv, nx=20, ny=20, nz=20) aos = sv.comp_aos_den(cc.get_coords()) self.assertEqual(aos.shape[0], cc.nx*cc.ny*cc.nz) self.assertEqual(aos.shape[1], sv.norbs) if __name__ == "__main__": unittest.main()

38.03125

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1,217

4.565445

0.633508

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0.083333

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null

0

null

0

1

0

1

bea8aa6132f2274610cc25a57ec0c74c8765342d

371

py

Python

students/K33402/Komarov_Georgy/LAB2/elevennote/src/api/urls.py

aglaya-pill/ITMO_ICT_WebDevelopment_2021-2022

a63691317a72fb9b29ae537bc3d7766661458c22

[ "MIT" ]

null

students/K33402/Komarov_Georgy/LAB2/elevennote/src/api/urls.py

aglaya-pill/ITMO_ICT_WebDevelopment_2021-2022

a63691317a72fb9b29ae537bc3d7766661458c22

[ "MIT" ]

null

students/K33402/Komarov_Georgy/LAB2/elevennote/src/api/urls.py

aglaya-pill/ITMO_ICT_WebDevelopment_2021-2022

a63691317a72fb9b29ae537bc3d7766661458c22

[ "MIT" ]

null

from django.urls import path, include from rest_framework_jwt.views import obtain_jwt_token from rest_framework.routers import DefaultRouter from .views import NoteViewSet app_name = 'api' router = DefaultRouter(trailing_slash=False) router.register('notes', NoteViewSet) urlpatterns = [ path('jwt-auth/', obtain_jwt_token), path('', include(router.urls)), ]

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0.77628

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5.8125

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0.078853

0.121864

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0.121294

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54

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0.363636

0

null

0

null

0

1

0

1

beb313eb5f64fc657c1686ad77dc2225b87a4889

570

py

Python

viewer_examples/plugins/median_filter.py

atemysemicolon/scikit-image

a48cf5822f9539c6602b9327c18253aed14fa692

[ "BSD-3-Clause" ]

null

viewer_examples/plugins/median_filter.py

atemysemicolon/scikit-image

a48cf5822f9539c6602b9327c18253aed14fa692

[ "BSD-3-Clause" ]

null

viewer_examples/plugins/median_filter.py

atemysemicolon/scikit-image

a48cf5822f9539c6602b9327c18253aed14fa692

[ "BSD-3-Clause" ]

null

from skimage import data from skimage.filter.rank import median from skimage.morphology import disk from skimage.viewer import ImageViewer from skimage.viewer.widgets import Slider, OKCancelButtons, SaveButtons from skimage.viewer.plugins.base import Plugin def median_filter(image, radius): return median(image, selem=disk(radius)) image = data.coins() viewer = ImageViewer(image) plugin = Plugin(image_filter=median_filter) plugin += Slider('radius', 2, 10, value_type='int') plugin += SaveButtons() plugin += OKCancelButtons() viewer += plugin viewer.show()

25.909091

71

0.784211

74

570

5.986486

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0.148984

0.115124

0

0.005952

0.115789

570

21

72

27.142857

0.873016

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0.0625

false

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0.375

0.0625

0.5

0

null

0

null

0

1

0

1

beb680071d94ed8dd93dc11b2e313714df1f9b83

1,727

py

Python

dingtalk/message/conversation.py

kangour/dingtalk-python

b37b9dac3ca3ff9d727308fb120a8fd05e11eaa5

[ "Apache-2.0" ]

88

2017-12-28T05:23:15.000Z

2021-12-20T13:44:18.000Z

dingtalk/message/conversation.py

niulinlnc/dingtalk-python

c4209658f88344e8f0890137ed7c887c8b740a6c

[ "Apache-2.0" ]

8

2018-04-28T05:41:49.000Z

2021-06-01T21:51:11.000Z

dingtalk/message/conversation.py

niulinlnc/dingtalk-python

c4209658f88344e8f0890137ed7c887c8b740a6c

[ "Apache-2.0" ]

43

2017-12-07T09:43:48.000Z

2021-12-03T01:19:52.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2017/11/30 下午3:02 # @Author : Matrix # @Github : https://github.com/blackmatrix7/ # @Blog : http://www.cnblogs.com/blackmatrix/ # @File : messages.py # @Software: PyCharm import json from ..foundation import * from json import JSONDecodeError __author__ = 'blackmatrix' __all__ = ['async_send_msg', 'get_msg_send_result', 'get_msg_send_progress'] @dingtalk_resp def async_send_msg(access_token, msgtype, agent_id, msgcontent, userid_list=None, dept_id_list=None, to_all_user=False): try: msgcontent = json.dumps(msgcontent) except JSONDecodeError: # 如果传入的msgcontent不能转换为json格式，依旧传给钉钉，由钉钉处理 pass if not isinstance(userid_list, str): userid_list = ','.join(userid_list) args = locals().copy() payload = {} # 请求参数整理 for k, v in args.items(): if k in ('msgtype', 'agent_id', 'msgcontent', 'userid_list', 'dept_id_list'): if v is not None: payload.update({k: v}) resp = call_dingtalk_webapi(access_token, 'dingtalk.corp.message.corpconversation.asyncsend', **payload) return resp @dingtalk_resp def get_msg_send_result(access_token, agent_id, task_id): url = get_request_url(access_token, 'dingtalk.corp.message.corpconversation.getsendresult') payload = {'task_id': task_id, 'agent_id': agent_id} return requests.get(url, params=payload) @dingtalk_resp def get_msg_send_progress(access_token, agent_id, task_id): url = get_request_url(access_token, 'dingtalk.corp.message.corpconversation.getsendprogress') payload = {'task_id': task_id, 'agent_id': agent_id} return requests.get(url, params=payload) if __name__ == '__main__': pass

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120

0.70469

227

1,727

5.044053

0.427313

0.048908

0.034935

0.060262

0.408734

0.265502

0

0.009059

0.169079

1,727

53

121

32.584906

0.78885

0.149392

0

0.272727

0

0.209733

0.119945

0

1

0.090909

false

0.060606

0.090909

0

0.272727

0

null

0

null

0

1

0

1

bebc4c58538a85c2ad00b34ebacde9538e3d0d9b

1,613

py

Python

board/models.py

Fahreeve/TaskManager

7f0a16312b43867270eaade1fe153c07abc2c10e

[ "MIT" ]

null

board/models.py

Fahreeve/TaskManager

7f0a16312b43867270eaade1fe153c07abc2c10e

[ "MIT" ]

null

board/models.py

Fahreeve/TaskManager

7f0a16312b43867270eaade1fe153c07abc2c10e

[ "MIT" ]

1

2020-09-15T09:15:13.000Z

from django.contrib.auth.models import User from django.core.validators import MaxValueValidator, MinValueValidator from django.db import models from django.utils.translation import ugettext_lazy as _ class Task(models.Model): CLOSE = 'cl' CANCEL = 'ca' LATER = 'la' UNDEFINED = 'un' CHOICES = ( (UNDEFINED, _("Неизвестно")), (CLOSE, _("Завершить")), (CANCEL, _("Отменить")), (LATER, _("Отложить")), ) title = models.CharField(_("Заголовок"), max_length=50) description = models.TextField(_("Описание")) executor = models.ForeignKey(User, verbose_name=_("Исполнитель"), on_delete=models.CASCADE) status = models.CharField(_("Статус"), choices=CHOICES, default=UNDEFINED, max_length=2) deadline = models.DateTimeField(_("Дедлайн")) priority = models.IntegerField(_("Приоритет"), default=1, validators=[MinValueValidator(1), MaxValueValidator(3)]) changed = models.DateTimeField(_("Дата последнего изменения"), auto_now=True) created = models.DateTimeField(_("Дата создания"), auto_now_add=True) @property def text_status(self): choices = dict(self.CHOICES) return choices[self.status] @property def text_deadline(self): return self.deadline.strftime("%d.%m.%Y %H:%M") class Comment(models.Model): task = models.ForeignKey(Task, related_name="comments", on_delete=models.CASCADE) creator = models.ForeignKey(User, on_delete=models.SET_NULL, null=True) text = models.TextField(_('Комментарий')) created = models.DateTimeField(_("Дата создания"), auto_now_add=True)

37.511628

118

0.695598

180

1,613

6.061111

0.5

0.036664

0.038497

0.095325

0

0.004461

0.16615

1,613

42

119

38.404762

0.806691

0

0.114286

0

0.109733

0

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0.057143

false

0

0.114286

0.028571

0.771429

0

null

0

null

0

1

0

1

bebe436d87bb3f3a76cbb71e91dc6e70bb5b2e46

475

py

Python

test/test_hex_line.py

bicobus/Hexy

e75d58e66546c278fb648af85e3f9dae53127826

[ "MIT" ]

72

2017-08-30T03:02:51.000Z

2022-03-11T23:15:15.000Z

test/test_hex_line.py

bicobus/Hexy

e75d58e66546c278fb648af85e3f9dae53127826

[ "MIT" ]

10

2019-03-14T08:04:33.000Z

2021-08-10T09:36:45.000Z

test/test_hex_line.py

bicobus/Hexy

e75d58e66546c278fb648af85e3f9dae53127826

[ "MIT" ]

15

2017-11-08T05:37:06.000Z

2021-08-05T19:16:48.000Z

import numpy as np import hexy as hx def test_get_hex_line(): expected = [ [-3, 3, 0], [-2, 2, 0], [-1, 2, -1], [0, 2, -2], [1, 1, -2], ] start = np.array([-3, 3, 0]) end = np.array([1, 1, -2]) print(hx.get_hex_line(start, end)) print(expected); assert(np.array_equal( hx.get_hex_line(start, end), expected)); if __name__ == "__main__": test_get_hex_line()

21.590909

38

0.471579

68

475

3.014706

0.367647

0.117073

0.195122

0.136585

0.195122

0

0.068627

0.355789

475

21

39

22.619048

0.601307

0

0.016842

0

0.052632

1

0.052632

false

0

0.105263

0

0.157895

0.105263

0

null

0

1

0

null

0

1

bebe5670df71295bc98ec96c4bde4a3c31d4fb66

6,747

py

Python

wofry/propagator/propagators2D/integral.py

PaNOSC-ViNYL/wofry

779b5a738ee7738e959a58aafe01e7e49b03894a

[ "MIT" ]

null

wofry/propagator/propagators2D/integral.py

PaNOSC-ViNYL/wofry

779b5a738ee7738e959a58aafe01e7e49b03894a

[ "MIT" ]

1

2021-02-16T12:12:10.000Z

wofryimpl/propagator/propagators2D/integral.py

oasys-kit/wofryimpl

f300b714b038110987783c40d2c3af8dca7e54eb

[ "MIT" ]

null

# propagate_2D_integral: Simplification of the Kirchhoff-Fresnel integral. TODO: Very slow and give some problems import numpy from wofry.propagator.wavefront2D.generic_wavefront import GenericWavefront2D from wofry.propagator.propagator import Propagator2D # TODO: check resulting amplitude normalization (fft and srw likely agree, convolution gives too high amplitudes, so needs normalization) class Integral2D(Propagator2D): HANDLER_NAME = "INTEGRAL_2D" def get_handler_name(self): return self.HANDLER_NAME def do_specific_progation_after(self, wavefront, propagation_distance, parameters, element_index=None): return self.do_specific_progation(wavefront, propagation_distance, parameters, element_index=element_index) def do_specific_progation_before(self, wavefront, propagation_distance, parameters, element_index=None): return self.do_specific_progation( wavefront, propagation_distance, parameters, element_index=element_index) """ 2D Fresnel-Kirchhoff propagator via simplified integral NOTE: this propagator is experimental and much less performant than the ones using Fourier Optics Therefore, it is not recommended to use. :param wavefront: :param propagation_distance: propagation distance :param shuffle_interval: it is known that this method replicates the central diffraction spot The distace of the replica is proportional to 1/pixelsize To avoid that, it is possible to change a bit (randomly) the coordinates of the wavefront. shuffle_interval controls this shift: 0=No shift. A typical value can be 1e5. The result shows a diffraction pattern without replica but with much noise. :param calculate_grid_only: if set, it calculates only the horizontal and vertical profiles, but returns the full image with the other pixels to zero. This is useful when calculating large arrays, so it is set as the default. :return: a new 2D wavefront object with propagated wavefront """ def do_specific_progation(self, wavefront, propagation_distance, parameters, element_index=None): shuffle_interval = self.get_additional_parameter("shuffle_interval",False,parameters,element_index=element_index) calculate_grid_only = self.get_additional_parameter("calculate_grid_only",True,parameters,element_index=element_index) return self.propagate_wavefront(wavefront,propagation_distance,shuffle_interval=shuffle_interval, calculate_grid_only=calculate_grid_only) @classmethod def propagate_wavefront(cls,wavefront,propagation_distance,shuffle_interval=False,calculate_grid_only=True): # # Fresnel-Kirchhoff integral (neglecting inclination factor) # if not calculate_grid_only: # # calculation over the whole detector area # p_x = wavefront.get_coordinate_x() p_y = wavefront.get_coordinate_y() wavelength = wavefront.get_wavelength() amplitude = wavefront.get_complex_amplitude() det_x = p_x.copy() det_y = p_y.copy() p_X = wavefront.get_mesh_x() p_Y = wavefront.get_mesh_y() det_X = p_X det_Y = p_Y amplitude_propagated = numpy.zeros_like(amplitude,dtype='complex') wavenumber = 2 * numpy.pi / wavelength for i in range(det_x.size): for j in range(det_y.size): if not shuffle_interval: rd_x = 0.0 rd_y = 0.0 else: rd_x = (numpy.random.rand(p_x.size,p_y.size)-0.5)*shuffle_interval rd_y = (numpy.random.rand(p_x.size,p_y.size)-0.5)*shuffle_interval r = numpy.sqrt( numpy.power(p_X + rd_x - det_X[i,j],2) + numpy.power(p_Y + rd_y - det_Y[i,j],2) + numpy.power(propagation_distance,2) ) amplitude_propagated[i,j] = (amplitude / r * numpy.exp(1.j * wavenumber * r)).sum() output_wavefront = GenericWavefront2D.initialize_wavefront_from_arrays(det_x,det_y,amplitude_propagated) else: x = wavefront.get_coordinate_x() y = wavefront.get_coordinate_y() X = wavefront.get_mesh_x() Y = wavefront.get_mesh_y() wavenumber = 2 * numpy.pi / wavefront.get_wavelength() amplitude = wavefront.get_complex_amplitude() used_indices = wavefront.get_mask_grid(width_in_pixels=(1,1),number_of_lines=(1,1)) indices_x = wavefront.get_mesh_indices_x() indices_y = wavefront.get_mesh_indices_y() indices_x_flatten = indices_x[numpy.where(used_indices == 1)].flatten() indices_y_flatten = indices_y[numpy.where(used_indices == 1)].flatten() X_flatten = X[numpy.where(used_indices == 1)].flatten() Y_flatten = Y[numpy.where(used_indices == 1)].flatten() complex_amplitude_propagated = amplitude*0 print("propagate_2D_integral: Calculating %d points from a total of %d x %d = %d"%( X_flatten.size,amplitude.shape[0],amplitude.shape[1],amplitude.shape[0]*amplitude.shape[1])) for i in range(X_flatten.size): r = numpy.sqrt( numpy.power(wavefront.get_mesh_x() - X_flatten[i],2) + numpy.power(wavefront.get_mesh_y() - Y_flatten[i],2) + numpy.power(propagation_distance,2) ) complex_amplitude_propagated[int(indices_x_flatten[i]),int(indices_y_flatten[i])] = (amplitude / r * numpy.exp(1.j * wavenumber * r)).sum() output_wavefront = GenericWavefront2D.initialize_wavefront_from_arrays(x_array=x, y_array=y, z_array=complex_amplitude_propagated, wavelength=wavefront.get_wavelength()) # added srio@esrf.eu 2018-03-23 to conserve energy - TODO: review method! output_wavefront.rescale_amplitude( numpy.sqrt(wavefront.get_intensity().sum() / output_wavefront.get_intensity().sum())) return output_wavefront

49.977778

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5.100765

0.276786

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0.032008

0.047512

0.35859

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0.218555

0.188547

0.144536

0

0.011702

0.303394

6,747

134

157

50.350746

0.839149

0.062102

0

0.109589

0

0.024619

0.004299

0

0.014925

0

1

0.068493

false

0

0.041096

0.205479

0.013699

0

null

0

null

0

1

0

1

bebf8ceeebe9e29c2c913232279dc6462e901f90

334

py

Python

Desafio051.py

GabrielSanchesRosa/Python

3a129e27e076b2a91af03d68ede50b9c45c50217

[ "MIT" ]

null

Desafio051.py

GabrielSanchesRosa/Python

3a129e27e076b2a91af03d68ede50b9c45c50217

[ "MIT" ]

null

Desafio051.py

GabrielSanchesRosa/Python

3a129e27e076b2a91af03d68ede50b9c45c50217

[ "MIT" ]

null

# Desenvolva um programa que leia o primeiro termo e a razão de uma PA. No final mostre, os 10 primeiros termos dessa prograssão. primeiro = int(input("Primeiro Termo: ")) razao = int(input("Razão: ")) decimo = primeiro + (10 - 1) * razao for c in range(primeiro, decimo + razao, razao): print(f"{c}", end=" -> ") print("Acabou")

33.4

129

0.679641

51

334

4.45098

0.705882

0.114537

0

0.018182

0.176647

334

9

130

37.111111

0.807273

0.38024

0

0.17561

0

1

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false

0

0.333333

0

null

0

1

0

null

0

1

bec28b12230a8be61261eca269a7854ba31ae9da

820

py

Python

src/15 listener_and_backdoor/listener_2.py

raminjafary/ethical-hacking

e76f74f4f23e1d8cb7f433d19871dcf966507dfc

[ "MIT" ]

null

src/15 listener_and_backdoor/listener_2.py

raminjafary/ethical-hacking

e76f74f4f23e1d8cb7f433d19871dcf966507dfc

[ "MIT" ]

null

src/15 listener_and_backdoor/listener_2.py

raminjafary/ethical-hacking

e76f74f4f23e1d8cb7f433d19871dcf966507dfc

[ "MIT" ]

null

#!/usr/bin/python import socket class Listener: def __init__(self,ip,port): listener = socket.socket(socket.AF_INET,socket.SOCK_STREAM) listener.setsockopt(socket.SOL_SOCKET,socket.SO_REUSEADDR,1) #options to reuse sockets #listener.bind(("localhost",1234)) listener.bind((ip,port)) listener.listen(0) print "[+] Waiting for Incoming Connection" #listen for connecion backlog is set to 0 don't need to wory about 0 self.connection,address = listener.accept() print "[+] Got a Connection from " + str(address) def execute_remotely(self,command): self.connection.send(command) return self.connection.recv(1024) def run(self): while True: command = raw_input(">> ") result = self.execute_remotely(command) print result my_listener = Listener("localhost",1234) my_listener.run()

25.625

70

0.734146

114

820

5.166667

0.561404

0.061121

0.047538

0

0.02276

0.142683

820

32

71

25.625

0.815078

0.170732

0

0.107829

0

null

0

0.05

null

0.15

0

null

0

null

0

1

0

1

bec6becd26fa525cff31dffaad9d3ab5e8f46f15

11,873

py

Python

lib/fbuild/builders/__init__.py

felix-lang/fbuild

9595fbfd6d3ceece31fda2f96c35d4a241f0129b

[ "PSF-2.0", "BSD-2-Clause" ]

40

2015-02-07T00:44:12.000Z

2021-04-02T13:41:08.000Z

lib/fbuild/builders/__init__.py

felix-lang/fbuild

9595fbfd6d3ceece31fda2f96c35d4a241f0129b

[ "PSF-2.0", "BSD-2-Clause" ]

30

2015-02-06T17:45:15.000Z

2019-01-10T16:34:29.000Z

lib/fbuild/builders/__init__.py

felix-lang/fbuild

9595fbfd6d3ceece31fda2f96c35d4a241f0129b

[ "PSF-2.0", "BSD-2-Clause" ]

3

2015-09-03T06:38:02.000Z

2019-10-24T14:26:57.000Z

import abc import contextlib import os import sys from functools import partial from itertools import chain import fbuild import fbuild.db import fbuild.path import fbuild.temp from . import platform # ------------------------------------------------------------------------------ class MissingProgram(fbuild.ConfigFailed): def __init__(self, programs=None): self.programs = programs def __str__(self): if self.programs is None: return 'cannot find program' else: return 'cannot find any of the programs %s' % \ ' '.join(repr(str(p)) for p in self.programs) # ------------------------------------------------------------------------------ @fbuild.db.caches def find_program(ctx, names, paths=None, *, quieter=0): """L{find_program} is a test that searches the paths for one of the programs in I{name}. If one is found, it is returned. If not, the next name in the list is searched for.""" if paths is None: paths = os.environ['PATH'].split(os.pathsep) # If we're running on windows, we need to append '.exe' to the filenames # that we're searching for. if sys.platform == 'win32': new_names = [] for name in names: if \ not name.endswith('.exe') or \ not name.endswith('.cmd') or \ not name.endswith('.bat'): new_names.append(name + '.exe') new_names.append(name + '.cmd') new_names.append(name + '.bat') new_names.append(name) names = new_names for name in names: filename = fbuild.path.Path(name) ctx.logger.check('looking for ' + filename.name, verbose=quieter) if filename.exists() and filename.isfile(): ctx.logger.passed('ok %s' % filename, verbose=quieter) return fbuild.path.Path(name) else: for path in paths: filename = fbuild.path.Path(path, name) if filename.exists() and filename.isfile(): ctx.logger.passed('ok %s' % filename, verbose=quieter) return fbuild.path.Path(filename) ctx.logger.failed(verbose=quieter) raise MissingProgram(names) # ------------------------------------------------------------------------------ def check_version(ctx, builder, version_function, *, requires_version=None, requires_at_least_version=None, requires_at_most_version=None): """Helper function to simplify checking the version of a builder.""" if any(v is not None for v in ( requires_version, requires_at_least_version, requires_at_most_version)): ctx.logger.check('checking %s version' % builder) version_str = version_function() # Convert the version into a tuple version = [] for i in version_str.split('.'): try: version.append(int(i)) except ValueError: # The subversion isn't a number, so just convert it to a # string. version.append(i) version = tuple(version) if requires_version is not None and requires_version != version: msg = 'version %s required; found %s' % ( '.'.join(str(i) for i in requires_version), version_str) ctx.logger.failed(msg) raise fbuild.ConfigFailed(msg) if requires_at_least_version is not None and \ requires_at_least_version > version: msg = 'at least version %s required; found %s' % ( '.'.join(str(i) for i in requires_at_least_version), version_str) ctx.logger.failed(msg) raise fbuild.ConfigFailed(msg) if requires_at_most_version is not None and \ requires_at_most_version < version: msg = 'at most version %s required; found %s' % ( '.'.join(str(i) for i in requires_at_most_version), version_str) ctx.logger.failed(msg) raise fbuild.ConfigFailed(msg) ctx.logger.passed(version_str) # ------------------------------------------------------------------------------ class AbstractCompiler(fbuild.db.PersistentObject): def __init__(self, *args, src_suffix, **kwargs): super().__init__(*args, **kwargs) self.src_suffix = src_suffix @fbuild.db.cachemethod def compile(self, src:fbuild.db.SRC, *args, **kwargs) -> fbuild.db.DST: return self.uncached_compile(src, *args, **kwargs) @abc.abstractmethod def uncached_compile(self, src, *args, **kwargs): pass @fbuild.db.cachemethod @platform.auto_platform_options() def build_objects(self, srcs:fbuild.db.SRCS, *args, **kwargs) -> \ fbuild.db.DSTS: """Compile all of the passed in L{srcs} in parallel.""" # When a object has extra external dependencies, such as .c files # depending on .h changes, depending on library changes, we need to add # the dependencies in build_objects. Unfortunately, the db doesn't # know about these new files and so it can't tell when a function # really needs to be rerun. So, we'll just not cache this function. # We need to add extra dependencies to our call. objs = [] src_deps = [] dst_deps = [] for o, s, d in self.ctx.scheduler.map( partial(self.compile.call, *args, **kwargs), srcs): objs.append(o) src_deps.extend(s) dst_deps.extend(d) self.ctx.db.add_external_dependencies_to_call( srcs=src_deps, dsts=dst_deps) return objs # -------------------------------------------------------------------------- def tempfile(self, code): return fbuild.temp.tempfile(code, self.src_suffix) @contextlib.contextmanager def tempfile_compile(self, code='', *, quieter=1, **kwargs): with self.tempfile(code) as src: yield self.uncached_compile(src, quieter=quieter, **kwargs) @platform.auto_platform_options() def try_compile(self, *args, **kwargs): try: with self.tempfile_compile(*args, **kwargs): return True except fbuild.ExecutionError: return False @platform.auto_platform_options() def check_compile(self, code, msg, *args, **kwargs): self.ctx.logger.check(msg) if self.try_compile(code, *args, **kwargs): self.ctx.logger.passed() return True else: self.ctx.logger.failed() return False # ------------------------------------------------------------------------------ class AbstractLibLinker(AbstractCompiler): @fbuild.db.cachemethod @platform.auto_platform_options() def link_lib(self, dst, srcs:fbuild.db.SRCS, *args, libs:fbuild.db.SRCS=(), **kwargs) -> fbuild.db.DST: """Link compiled files into a library and caches the results.""" return self.uncached_link_lib(dst, srcs, *args, libs=libs, **kwargs) @abc.abstractmethod def uncached_link_lib(self, *args, **kwargs): pass @platform.auto_platform_options() def build_lib(self, dst, srcs, *, objs=(), libs=(), ckwargs={}, lkwargs={}): """Compile all of the passed in L{srcs} in parallel, then link them into a library.""" objs = tuple(chain(objs, self.build_objects(srcs, **ckwargs))) return self.link_lib(dst, objs, libs=libs, **lkwargs) # -------------------------------------------------------------------------- @contextlib.contextmanager @platform.auto_platform_options() def tempfile_link_lib(self, code='', *, quieter=1, ckwargs={}, **kwargs): with self.tempfile(code) as src: dst = src.parent / 'temp' obj = self.uncached_compile(src, quieter=quieter, **ckwargs) yield self.uncached_link_lib(dst, [obj], quieter=quieter, **kwargs) def try_link_lib(self, *args, **kwargs): try: with self.tempfile_link_lib(*args, **kwargs): return True except fbuild.ExecutionError: return False def check_link_lib(self, code, msg, *args, **kwargs): self.ctx.logger.check(msg) if self.try_link_lib(code, *args, **kwargs): self.ctx.logger.passed() return True else: self.ctx.logger.failed() return False # ------------------------------------------------------------------------------ class AbstractRunner(fbuild.db.PersistentObject): @abc.abstractmethod def tempfile_run(self, *args, **kwargs): pass def try_run(self, code='', quieter=1, **kwargs): try: self.tempfile_run(code, quieter=quieter, **kwargs) except fbuild.ExecutionError: return False else: return True def check_run(self, code, msg, *args, **kwargs): self.ctx.logger.check(msg) if self.try_run(code, *args, **kwargs): self.ctx.logger.passed() return True else: self.ctx.logger.failed() return False # ------------------------------------------------------------------------------ class AbstractExeLinker(AbstractCompiler, AbstractRunner): @fbuild.db.cachemethod @platform.auto_platform_options() def link_exe(self, dst, srcs:fbuild.db.SRCS, *args, libs:fbuild.db.SRCS=(), **kwargs) -> fbuild.db.DST: """Link compiled files into an executable.""" return self.uncached_link_exe(dst, srcs, *args, libs=libs, **kwargs) @abc.abstractmethod def uncached_link_exe(self, *args, **kwargs): pass @platform.auto_platform_options() def build_exe(self, dst, srcs, *, objs=(), libs=(), ckwargs={}, lkwargs={}): """Compile all of the passed in L{srcs} in parallel, then link them into an executable.""" objs = tuple(chain(objs, self.build_objects(srcs, **ckwargs))) return self.link_exe(dst, objs, libs=libs, **lkwargs) # -------------------------------------------------------------------------- @contextlib.contextmanager @platform.auto_platform_options() def tempfile_link_exe(self, code='', *, quieter=1, ckwargs={}, **kwargs): with self.tempfile(code) as src: dst = src.parent / 'temp' obj = self.uncached_compile(src, quieter=quieter, **ckwargs) yield self.uncached_link_exe(dst, [obj], quieter=quieter, **kwargs) @platform.auto_platform_options() def try_link_exe(self, *args, **kwargs): try: with self.tempfile_link_exe(*args, **kwargs): return True except fbuild.ExecutionError: return False @platform.auto_platform_options() def check_link_exe(self, code, msg, *args, **kwargs): self.ctx.logger.check(msg) if self.try_link_exe(code, *args, **kwargs): self.ctx.logger.passed() return True else: self.ctx.logger.failed() return False @platform.auto_platform_options() def tempfile_run(self, *args, quieter=1, ckwargs={}, lkwargs={}, **kwargs): with self.tempfile_link_exe(*args, quieter=quieter, ckwargs=ckwargs, **lkwargs) as exe: return self.ctx.execute([exe], quieter=quieter, cwd=exe.parent, **kwargs) # ------------------------------------------------------------------------------ class AbstractCompilerBuilder(AbstractLibLinker, AbstractExeLinker): pass

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0.536288

0.482285

0.461058

0.437334

0.418136

0.376151

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0.305439

0

null

0

null

0

1

0

1

bec81857d7e4af0801337540f4b978497c5536f9

1,897

py

Python

tuprolog/solve/exception/error/existence/__init__.py

DavideEva/2ppy

55609415102f8116165a42c8e33e029c4906e160

[ "Apache-2.0" ]

1

2021-08-07T06:29:28.000Z

tuprolog/solve/exception/error/existence/__init__.py

DavideEva/2ppy

55609415102f8116165a42c8e33e029c4906e160

[ "Apache-2.0" ]

14

2021-09-16T13:25:12.000Z

2022-01-03T10:12:22.000Z

tuprolog/solve/exception/error/existence/__init__.py

DavideEva/2ppy

55609415102f8116165a42c8e33e029c4906e160

[ "Apache-2.0" ]

1

2021-12-22T00:25:32.000Z

from typing import Union from tuprolog import logger # noinspection PyUnresolvedReferences import jpype.imports # noinspection PyUnresolvedReferences import it.unibo.tuprolog.solve.exception.error as errors from tuprolog.core import Term, Atom from tuprolog.solve import ExecutionContext, Signature ExistenceError = errors.ExistenceError ObjectType = ExistenceError.ObjectType OBJECT_PROCEDURE = ObjectType.PROCEDURE OBJECT_SOURCE_SINK = ObjectType.SOURCE_SINK OBJECT_RESOURCE = ObjectType.RESOURCE OBJECT_STREAM = ObjectType.STREAM OBJECT_OOP_ALIAS = ObjectType.OOP_ALIAS OBJECT_OOP_METHOD = ObjectType.OOP_METHOD OBJECT_OOP_CONSTRUCTOR = ObjectType.OOP_CONSTRUCTOR OBJECT_OOP_PROPERTY = ObjectType.OOP_PROPERTY def existence_error( context: ExecutionContext, type: ObjectType, culprit: Term, message: str ) -> ExistenceError: return ExistenceError.of(context, type, culprit, message) def existence_error_for_source_sink( context: ExecutionContext, alias: Union[Atom, str] ) -> ExistenceError: return ExistenceError.forSourceSink(context, alias) def existence_error_for_procedure( context: ExecutionContext, procedure: Signature ) -> ExistenceError: return ExistenceError.forProcedure(context, procedure) def existence_error_for_stream( context: ExecutionContext, stream: Term ) -> ExistenceError: return ExistenceError.forStream(context, stream) def existence_error_for_resource( context: ExecutionContext, name: str ) -> ExistenceError: return ExistenceError.forResource(context, name) def object_type(name: Union[str, Term]) -> ObjectType: if isinstance(name, str): return ObjectType.of(name) else: return ObjectType.fromTerm(name) logger.debug("Loaded JVM classes from it.unibo.tuprolog.solve.exception.error.ExistenceError.*")

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0.387755

0

null

0

null

0

1

0

1

fe2070ac8557cbd4275cc5e584c79388af700674

2,510

py

Python

detection/contor.py

chika626/chainer_rep

a1d4fd32a8cfcab753269455d08c1918f273388d

[ "MIT" ]

null

detection/contor.py

chika626/chainer_rep

a1d4fd32a8cfcab753269455d08c1918f273388d

[ "MIT" ]

7

2020-03-13T08:29:46.000Z

2020-05-27T17:34:14.000Z

detection/contor.py

chika626/chainer_rep

a1d4fd32a8cfcab753269455d08c1918f273388d

[ "MIT" ]

null

import json import math from PIL import Image,ImageDraw import pandas as pd import glob import argparse import copy import numpy as np import matplotlib.pyplot as plt import pickle import cv2 from PIL import ImageEnhance import chainer from chainer.datasets import ConcatenatedDataset from chainer.datasets import TransformDataset from chainer.optimizer_hooks import WeightDecay from chainer import serializers from chainer import training from chainer.training import extensions from chainer.training import triggers from chainercv.datasets import voc_bbox_label_names from chainercv.datasets import VOCBboxDataset from chainercv.extensions import DetectionVOCEvaluator from chainercv.links.model.ssd import GradientScaling from chainercv.links.model.ssd import multibox_loss from chainercv.links import SSD300 from chainercv.links import SSD512 from chainercv import transforms from chainercv.utils import read_image from chainercv.links.model.ssd import random_crop_with_bbox_constraints from chainercv.links.model.ssd import random_distort from chainercv.links.model.ssd import resize_with_random_interpolation import queue def run(img): # c , H , W = img.shape H,W = img.size img = np.asarray(img) # 変換後データ配列 transed = Image.new('RGB',(H,W)) for x in range(H): for y in range(W): transed.putpixel((x,y),(255,255,255)) for x in range(H): for y in range(W): if x + 1 == H or y + 1 == W: break if img[y][x][0] != img[y][x+1][0]: transed.putpixel((x,y),(0,0,0)) for y in range(W): for x in range(H): if x + 1 == H or y + 1 == W: break if img[y][x][0] != img[y+1][x][0]: transed.putpixel((x,y),(0,0,0)) return transed def main(): # # 単一の場合のコード # img = Image.open('cont/transed/X.jpg') # img=img.convert('L') # img=np.asarray(img) # ret2, img = cv2.threshold(img, 0, 255, cv2.THRESH_OTSU) # img=Image.fromarray(img) # img=img.convert('RGB') # transed = run(img) # transed.save('transec_0.png') # return # 大量変換機 img_path=glob.glob("cont/crop/*") counter=0 for path in img_path: img = Image.open(path) transed = run(img) transed.save('transec_{}.png'.format(counter)) counter+=1 if __name__ == '__main__': main()

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0.298851

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0.079747

0.072785

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0.248101

0.139241

0.091139

0.064557

0

0.022605

0.259761

2,510

93

73

26.989247

0.827772

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0.031746

false

0

0.52381

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0.571429

0

null

0

null

0

1

0

1

fe21f2c89737b3c4d120cba724974597cb079bc4

1,675

py

Python

src/boot.py

johngtrs/krux

7b6c6d410e29c16ab5d3c05a5aafab618f13a86f

[ "MIT" ]

null

src/boot.py

johngtrs/krux

7b6c6d410e29c16ab5d3c05a5aafab618f13a86f

[ "MIT" ]

null

src/boot.py

johngtrs/krux

7b6c6d410e29c16ab5d3c05a5aafab618f13a86f

[ "MIT" ]

null

# The MIT License (MIT) # Copyright (c) 2021 Tom J. Sun # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. import machine from pmu import axp192 from context import Context from login import Login from home import Home import settings pmu = axp192() # Enable power management so that if power button is held down 6 secs, # it shuts off as expected pmu.enablePMICSleepMode(True) ctx = Context() ctx.display.flash_text(settings.load('splash', ( 'Krux' ), strip=False)) while True: if not Login(ctx).run(): break if not Home(ctx).run(): break ctx.display.flash_text(( 'Shutting down..' )) ctx.clear() pmu.setEnterSleepMode() machine.reset()

32.211538

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4.972441

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0.030087

0

0.007971

0.176119

1,675

51

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0.907246

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0

0.051125

0

1

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false

0

0.315789

0

0.315789

0

null

0

null

0

1

0

1

fe2900b93b3b942d3363b1695eb5a7b3920a90d6

1,913

py

Python

app.py

Nishanth-Gobi/Da-Vinci-Code

b44a2d0c553e4f9cf9e2bb3283ebb5f6eaecea4a

[ "MIT" ]

null

app.py

Nishanth-Gobi/Da-Vinci-Code

b44a2d0c553e4f9cf9e2bb3283ebb5f6eaecea4a

[ "MIT" ]

null

app.py

Nishanth-Gobi/Da-Vinci-Code

b44a2d0c553e4f9cf9e2bb3283ebb5f6eaecea4a

[ "MIT" ]

null

from flask import Flask, render_template, request, redirect, url_for from os.path import join from stego import Steganography app = Flask(__name__) UPLOAD_FOLDER = 'static/files/' app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg'} @app.route("/") def home(): return render_template('home.html') @app.route("/encrypt", methods=['GET', 'POST']) def get_image(): if request.method == 'GET': return render_template('encrypt.html') # Check if the user has entered the secret message if 'file' in request.files and 'Secret' in request.values: uploaded_image = request.files['file'] message = request.values.get('Secret') password = request.values.get("key") filepath = join(app.config['UPLOAD_FOLDER'], "cover_image.png") uploaded_image.save(filepath) im = Steganography(filepath=app.config['UPLOAD_FOLDER'], key=password) im.encode(message=message) return render_template('encrypt.html', value=filepath, image_flag=True, secret_flag=True) return redirect(url_for('encrypt')) @app.route("/decrypt", methods=['GET', 'POST']) def get_image_to_decrypt(): if request.method == 'GET': return render_template('decrypt.html') if 'key' in request.values: password = request.values.get('key') filepath = join(app.config['UPLOAD_FOLDER'], "stego_image.png") im = Steganography(filepath=app.config['UPLOAD_FOLDER'], key=password) message = im.decode() return render_template('decrypt.html', value=filepath, message=message) if 'file' in request.files: uploaded_image = request.files['file'] filepath = join(app.config['UPLOAD_FOLDER'], "stego_image.png") uploaded_image.save(filepath) return render_template('decrypt.html', value=filepath) if __name__ == '__main__': app.run(debug=True)

31.360656

97

0.67747

239

1,913

5.242678

0.276151

0.076616

0.071828

0.100559

0.579409

0.490822

0.361532

0.230646

0.09577

0

0.182436

1,913

60

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0.801151

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0

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0

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0

1

0.073171

false

0.097561

0.073171

0.02439

0.317073

0

null

0

null

0

1

0

1

fe2b48a6665b98787ac1bd205fe634201bd2120e

1,480

py

Python

job-queue-portal/postgres_django_queue/djangoenv/lib/python3.8/site-packages/django_celery_results/migrations/0006_taskresult_date_created.py

Sruthi-Ganesh/postgres-django-queue

4ea8412c073ff8ceb0efbac48afc29456ae11346

[ "Apache-2.0" ]

null

job-queue-portal/postgres_django_queue/djangoenv/lib/python3.8/site-packages/django_celery_results/migrations/0006_taskresult_date_created.py

Sruthi-Ganesh/postgres-django-queue

4ea8412c073ff8ceb0efbac48afc29456ae11346

[ "Apache-2.0" ]

null

job-queue-portal/postgres_django_queue/djangoenv/lib/python3.8/site-packages/django_celery_results/migrations/0006_taskresult_date_created.py

Sruthi-Ganesh/postgres-django-queue

4ea8412c073ff8ceb0efbac48afc29456ae11346

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by Django 2.2.4 on 2019-08-21 19:53 # this file is auto-generated so don't do flake8 on it # flake8: noqa from __future__ import absolute_import, unicode_literals from django.db import migrations, models import django.utils.timezone def copy_date_done_to_date_created(apps, schema_editor): TaskResult = apps.get_model('django_celery_results', 'taskresult') db_alias = schema_editor.connection.alias TaskResult.objects.using(db_alias).all().update( date_created=models.F('date_done') ) def reverse_copy_date_done_to_date_created(app, schema_editor): # the reverse of 'copy_date_done_to_date_created' is do nothing # because the 'date_created' will be removed. pass class Migration(migrations.Migration): dependencies = [ ('django_celery_results', '0005_taskresult_worker'), ] operations = [ migrations.AddField( model_name='taskresult', name='date_created', field=models.DateTimeField( auto_now_add=True, db_index=True, default=django.utils.timezone.now, help_text='Datetime field when the task result was created in UTC', verbose_name='Created DateTime' ), preserve_default=False, ), migrations.RunPython(copy_date_done_to_date_created, reverse_copy_date_done_to_date_created), ]

30.204082

83

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1,480

5.065574

0.519126

0.09493

0.064725

0.075512

0.149946

0.06904

0

0.019838

0.250676

1,480

48

84

30.833333

0.816051

0.161486

0

0.064516

1

0

0.141815

0.051864

0

1

0.064516

false

0.032258

0.096774

0

0.258065

0

null

0

1

0

null

0

1

fe3002f8ab77d8668df51f08f7789bc9628e8c1f

2,370

py

Python

EC2 Auto Clean Room Forensics/Lambda-Functions/snapshotForRemediation.py

spartantri/aws-security-automation

a3904931220111022d12e71a3d79e4a85fc82173

[ "Apache-2.0" ]

null

EC2 Auto Clean Room Forensics/Lambda-Functions/snapshotForRemediation.py

spartantri/aws-security-automation

a3904931220111022d12e71a3d79e4a85fc82173

[ "Apache-2.0" ]

null

EC2 Auto Clean Room Forensics/Lambda-Functions/snapshotForRemediation.py

spartantri/aws-security-automation

a3904931220111022d12e71a3d79e4a85fc82173

[ "Apache-2.0" ]

null

# MIT No Attribution # 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. # 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 NON-INFRINGEMENT. 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 boto3 import os def lambda_handler(event, context): # TODO implement print(event) client = boto3.client('ec2') instanceID = event.get('instanceID') response = client.describe_instances( InstanceIds=[ instanceID ] ) volumeID = response['Reservations'][0]['Instances'][0]['BlockDeviceMappings'][0]['Ebs']['VolumeId'] print(volumeID) SnapShotDetails = client.create_snapshot( Description='Isolated Instance', VolumeId=volumeID ) client.create_tags(Resources=[SnapShotDetails['SnapshotId']], Tags=[{'Key': 'Name', 'Value': instanceID}]) # TODO Dump Response into S3 - response # TODO Dump Response details into Snapshot - SnapShotDetails['SnapshotId'] print(response) print(SnapShotDetails['SnapshotId']) response = client.modify_instance_attribute( Groups=[ os.environ['ISOLATED_SECUTRITYGROUP'], ], InstanceId=instanceID ) tagresponse = client.create_tags( Resources=[ instanceID, ], Tags=[ { 'Key': 'IsIsolated', 'Value': 'InstanceIsolated' }, ] ) waiter = client.get_waiter('snapshot_completed') waiter.wait( SnapshotIds=[ SnapShotDetails['SnapshotId'], ] ) # event['SnapshotId'] = SnapShotDetails['SnapshotId'] return SnapShotDetails['SnapshotId']

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0.670042

261

2,370

6.045977

0.521073

0.048796

0.016477

0.031686

0

0.00387

0.236709

2,370

69

111

34.347826

0.868436

0.444726

0

0.045455

0

0.160123

0.017706

0

0.014493

0

1

0.022727

false

0

0.045455

0

0.090909

0

null

0

null

0

1

0

1

fe317187c1c12b8c77ea5e51802f388e760744e4

1,324

py

Python

tests/test_intbounds.py

alex/optimizer-model

0e40a0763082f5fe0bd596e8e77ebccbcd7f4a98

[ "BSD-3-Clause" ]

4

2015-04-29T22:49:25.000Z

2018-02-16T09:06:08.000Z

tests/test_intbounds.py

alex/optimizer-model

0e40a0763082f5fe0bd596e8e77ebccbcd7f4a98

[ "BSD-3-Clause" ]

null

tests/test_intbounds.py

alex/optimizer-model

0e40a0763082f5fe0bd596e8e77ebccbcd7f4a98

[ "BSD-3-Clause" ]

null

from optimizer.utils.intbounds import IntBounds class TestIntBounds(object): def test_make_gt(self): i0 = IntBounds() i1 = i0.make_gt(IntBounds(10, 10)) assert i1.lower == 11 def test_make_gt_already_bounded(self): i0 = IntBounds() i1 = i0.make_gt(IntBounds(10, 10)).make_gt(IntBounds(0, 0)) assert i1.lower == 11 def test_make_lt(self): i0 = IntBounds() i1 = i0.make_lt(IntBounds(10, 10)) assert i1.upper == 9 def test_make_lt_already_bounded(self): i0 = IntBounds() i1 = i0.make_lt(IntBounds(0, 0)).make_lt(IntBounds(10, 10)) assert i1.upper == -1 def test_both_bounds(self): i0 = IntBounds() i1 = i0.make_lt(IntBounds(10, 10)).make_gt(IntBounds(0, 0)) assert i1.upper == 9 assert i1.lower == 1 i2 = i0.make_gt(IntBounds(0, 0)).make_lt(IntBounds(10, 10)) assert i2.lower == 1 assert i2.upper == 9 def test_make_le_already_bounded(self): i0 = IntBounds() i1 = i0.make_le(IntBounds(0, 0)).make_le(IntBounds(2, 2)) assert i1.upper == 0 def test_make_ge_already_bounded(self): i0 = IntBounds() i1 = i0.make_ge(IntBounds(10, 10)).make_ge(IntBounds(0, 0)) assert i1.lower == 10

23.22807

67

0.5929

192

1,324

3.901042

0.166667

0.064085

0.140187

0.158879

0.699599

0.65287

0.620828

0.562083

0.365821

0.269693

0

0.092147

0.278701

1,324

56

68

23.642857

0.692147

0

0.323529

0

0.294118

1

0.205882

false

0

0.029412

0

0.264706

0

null

0

null

0

1

0

1

fe32cc9e555895354fe2279db255494d9b4433fb

1,652

py

Python

address_book/address_book.py

wowsuchnamaste/address_book

4877d16d795c54b750e151fa93e69c080717ae72

[ "MIT" ]

null

address_book/address_book.py

wowsuchnamaste/address_book

4877d16d795c54b750e151fa93e69c080717ae72

[ "MIT" ]

null

address_book/address_book.py

wowsuchnamaste/address_book

4877d16d795c54b750e151fa93e69c080717ae72

[ "MIT" ]

null

"""A simple address book.""" from ._tools import generate_uuid class AddressBook: """ A simple address book. """ def __init__(self): self._entries = [] def add_entry(self, entry): """Add an entry to the address book.""" self._entries.append(entry) def get_entries(self): """Returns a list of all entries in the address book. :return: ``list`` of ``Person`` objects. """ return self._entries def get_entry(self, name): entry = [entry for entry in self._entries if entry.name == name] return entry[0] class Entry: def __init__( self, name, first_name=None, last_name=None, address=None, phone_number=None, email=None, organization=None, ): self._uuid = generate_uuid() self.name = name self.first_name = first_name self.last_name = last_name self._parse_name(name) self.address = address self.phone_number = phone_number self.email = email self.organization = organization def __repr__(self): return self.name def _parse_name(self, name): """ Parse whatever is passed as ``name`` and update ``self.name`` from that. :param name: A person's name as string or dictionary. :return: The method doesn't return anything. """ if type(name) == dict: self.first_name = name["first_name"] self.last_name = name["last_name"] self.name = self.first_name + " " + self.last_name

25.415385

80

0.565981

197

1,652

4.532995

0.309645

0.080627

0.043673

0.057111

0.079507

0.055991

0

0.000906

0.331719

1,652

64

81

25.8125

0.807971

0.208838

0

1

0

0.016393

0

1

0.184211

false

0

0.026316

0.342105

0

null

0

1

0

null

0

1

fe358e9590f17c8d7c10eb92232dc2f7d4b20167

235

py

Python

config.py

volgachen/Chinese-Tokenization

467e08da6fe271b6e33258d5aa6682c0405a3f32

[ "Apache-2.0" ]

null

config.py

volgachen/Chinese-Tokenization

467e08da6fe271b6e33258d5aa6682c0405a3f32

[ "Apache-2.0" ]

null

config.py

volgachen/Chinese-Tokenization

467e08da6fe271b6e33258d5aa6682c0405a3f32

[ "Apache-2.0" ]

1

2020-07-12T10:38:34.000Z

class Config: ngram = 2 train_set = "data/rmrb.txt" modified_train_set = "data/rmrb_modified.txt" test_set = "" model_file = "" param_file = "" word_max_len = 10 proposals_keep_ratio = 1.0 use_re = 1 subseq_num = 15

21.363636

47

0.67234

37

235

3.918919

0.756757

0.110345

0.165517

0.22069

0

0.043478

0.217021

235

11

48

21.363636

0.744565

0

0.154867

0.097345

0

1

0

false

0

1

0

null

0

1

0

null

0

1

fe3845f60103709c0d0030d388891565874650ad

1,076

py

Python

blogtech/src/blog/views.py

IVAN-URBACZKA/django-blog

7ef6050c0de2938791843c3ec93e6e6a1e683baa

[ "MIT" ]

null

blogtech/src/blog/views.py

IVAN-URBACZKA/django-blog

7ef6050c0de2938791843c3ec93e6e6a1e683baa

[ "MIT" ]

null

blogtech/src/blog/views.py

IVAN-URBACZKA/django-blog

7ef6050c0de2938791843c3ec93e6e6a1e683baa

[ "MIT" ]

null

from django.urls import reverse_lazy, reverse from django.utils.decorators import method_decorator from django.views.generic import ListView, DetailView, CreateView, DeleteView, UpdateView from .models import BlogPost from django.contrib.auth.decorators import login_required class BlogPostHomeView(ListView): model = BlogPost context_object_name = "posts" class BlogPostDetailsView(DetailView): model = BlogPost context_object_name = "post" @method_decorator(login_required, name='dispatch') class BlogPostCreateView(CreateView): model = BlogPost fields = ['title', 'image','author', 'category', 'content'] def get_success_url(self): return reverse('posts:home') @method_decorator(login_required, name='dispatch') class BlogPostUpdateView(UpdateView): model = BlogPost fields = ['title', 'author', 'category', 'content'] template_name = 'blog/blogpost_update.html' @method_decorator(login_required, name='dispatch') class BlogPostDeleteView(DeleteView): model = BlogPost success_url = reverse_lazy('posts:home')

31.647059

89

0.760223

119

1,076

6.714286

0.445378

0.081352

0.075094

0.105131

0.244055

0.168961

0

0.136617

1,076

34

90

31.647059

0.860065

0

0.307692

0

0.125348

0.023213

0

1

0.038462

false

0

0.192308

0.038462

0.884615

0

null

0

null

0

1

0

1

fe393898f4084fe1c0d82dbb19e8e9bf170a60ea

4,514

py

Python

apc_deep_vision/python/generate_data.py

Juxi/apb-baseline

fd47a5fd78cdfd75c68601a40ca4726d7d20c9ce

[ "BSD-3-Clause" ]

9

2017-02-06T10:24:56.000Z

2022-02-27T20:59:52.000Z

apc_deep_vision/python/generate_data.py

Juxi/apb-baseline

fd47a5fd78cdfd75c68601a40ca4726d7d20c9ce

[ "BSD-3-Clause" ]

null

apc_deep_vision/python/generate_data.py

Juxi/apb-baseline

fd47a5fd78cdfd75c68601a40ca4726d7d20c9ce

[ "BSD-3-Clause" ]

2

2017-10-15T08:33:37.000Z

2019-03-05T07:29:38.000Z

#! /usr/bin/env python # ******************************************************************** # Software License Agreement (BSD License) # # Copyright (c) 2015, University of Colorado, Boulder # 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 University of Colorado Boulder # 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. # ********************************************************************/ import cv2 import os import numpy as np if __name__ == '__main__': import argparse parser = argparse.ArgumentParser() parser.add_argument("proposal_path", type=str, help="relative path from python script to proposals, no slash") parser.add_argument("--view", default=None, help="true/1 shows each masked image") args = parser.parse_args() # args.proposal_path = "../test_proposals" # args.proposal_path = args.proposal_path included_extenstions = ['txt'] image_names = [fn[0:len(fn)-4] for fn in os.listdir(args.proposal_path) if any(fn.endswith(ext) for ext in included_extenstions)] for image_name in image_names: load_path = args.proposal_path + '/' + image_name image = cv2.imread(load_path + ".jpeg") data = np.loadtxt(load_path + ".txt", str) # If there is only one line, force data to be a list of lists anyway # Note, only works for our data as first list item is a string if isinstance(data[0], basestring): data = [data] # If any line does not conform to classification tl_x tl_y br_x br_y # then forget about it skip = False for line in data: if len(line) < 5: skip = True if skip: continue for i, proposal in zip(range(0,len(data)),data): mask = cv2.imread(load_path + '_mask{0:04d}.jpeg'.format(i)) mask = np.invert(mask) maskGray = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY) ret, maskGray = cv2.threshold(maskGray,128,255,cv2.THRESH_BINARY) print load_path + '_mask{0:04d}.jpeg'.format(i) cropped = image[float(proposal[2]):float(proposal[4]), float(proposal[1]):float(proposal[3])] masked = cv2.bitwise_and(cropped, cropped, mask = maskGray) if args.view: cv2.imshow("original", masked) cv2.waitKey(0) mask_directory = args.proposal_path + '/masked/' + proposal[0]; crop_directory = args.proposal_path + '/cropped/' + proposal[0]; if not os.path.exists(mask_directory): os.makedirs(mask_directory) if not os.path.exists(crop_directory): os.makedirs(crop_directory) cv2.imwrite(mask_directory + '/{}_{}.jpeg'.format(image_name,i), masked) cv2.imwrite(crop_directory + '/{}_{}.jpeg'.format(image_name,i), cropped) # item = data[] # cropped = image[70:170, 440:540] # startY:endY, startX:endX # startX:startY, endX:endY #

37.932773

105

0.634914

577

4,514

4.87695

0.42461

0.034115

0.039801

0.01919

0.117271

0.088131

0.06752

0.04833

0

0.015616

0.248117

4,514

118

106

38.254237

0.813494

0.476961

0

0.088985

0

null

0

0.088889

null

0.022222

0

null

0

null

0

1

0

1

fe39cd977754d7baa5900e133ad7f76b583b9786

3,509

py

Python

stats.py

shirshanka/fact-ory

9e6bae63ca7f8f534b811058efb8942004d6a37b

[ "Apache-2.0" ]

null

stats.py

shirshanka/fact-ory

9e6bae63ca7f8f534b811058efb8942004d6a37b

[ "Apache-2.0" ]

null

stats.py

shirshanka/fact-ory

9e6bae63ca7f8f534b811058efb8942004d6a37b

[ "Apache-2.0" ]

null

import numpy as np; import sys import matplotlib.pyplot as plt; from matplotlib import cm; from termcolor import colored; class Stats(): def __init__(self, param1_range, param2_range): self._total_times = 0; self._total_time = 0.0; self._wrong_answers = []; self._time_dict = {}; self._param1_range = param1_range self._param2_range = param2_range self._param1_length = param1_range[1] - param1_range[0] + 1 self._param2_length = param2_range[1] - param2_range[0] + 1 self._red_color = 1.0 self._green_color = 0.3 self._cream_color = 0.6 self._default_color = np.nan self._wrong_color = 1000.0 self._time_penalty = 2.0 # time penalty for wrong answer is 5 seconds self._result_matrix = np.full((self._param1_length, self._param2_length), self._default_color) def add_statistic(self, operator, param1,param2,ans,time_diff): self.add_time_statistic(param1, param2, time_diff) x_axis = param1 - self._param1_range[0] y_axis = param2 - self._param2_range[0] curr_value = self._result_matrix[x_axis][y_axis] incr_value = time_diff if (operator.evaluate(param1, param2) != ans): # wrong answer self.add_wrong_answer(param1,param2,ans) incr_value = incr_value + self._time_penalty else: # right answer: do nothing pass if np.isnan(curr_value): self._result_matrix[x_axis][y_axis] = incr_value else: self._result_matrix[x_axis][y_axis] = curr_value + incr_value def add_time_statistic(self, param1, param2, time_diff): self._total_times = self._total_times +1; self._total_time = self._total_time + time_diff; if not self._time_dict.has_key(param1): self._time_dict[param1] = [] if not self._time_dict.has_key(param2): self._time_dict[param2] = [] self._time_dict[param1].append(time_diff) self._time_dict[param2].append(time_diff) def add_wrong_answer(self, param1, param2, answer_given): self._wrong_answers.append((param1,param2, answer_given)) def get_avg_time(self): return (self._total_time / self._total_times); def print_stats(self, operator): sys.stdout.write("You took an average of %0.2f seconds to answer each question!\n" % self.get_avg_time()); if self._wrong_answers != []: print("Here were the answers you got wrong...") for (f1,f2,ans) in self._wrong_answers: print ("%d %s %d = " % (f1,operator.symbol,f2)), colored("%d" % ans, "red"), "Correct answer is ", colored("%d" % operator.evaluate(f1,f2), "green") row_labels = range(self._param1_range[0],self._param1_range[1]+1) col_labels = range(self._param2_range[0],self._param2_range[1]+1) #plt.matshow(self._result_matrix, cmap=cm.Spectral_r, vmin=0, vmax=1) fig = plt.figure() ax = fig.add_subplot(111) cax = ax.matshow(self._result_matrix, interpolation='nearest', vmin=0) fig.colorbar(cax) plt.gca().set_aspect('auto') row_ticks = range(len(row_labels)) col_ticks = range(len(col_labels)) if (len(row_labels) > 10): skip_every = int(len(row_labels) / 10); row_labels = row_labels[0::skip_every] row_ticks = row_ticks[0::skip_every] if (len(col_labels) > 10): skip_every = int(len(col_labels)/10) col_labels = col_labels[0::skip_every] col_ticks = col_ticks[0::skip_every] plt.xticks(col_ticks, col_labels) plt.yticks(row_ticks, row_labels) plt.show() if __name__=="__main__": print "hello world"

34.742574

154

0.68937

529

3,509

4.228733

0.253308

0.040232

0.03755

0.022798

0.111757

0.092088

0.071524

0.039338

0

0.03499

0.185523

3,509

100

155

35.09

0.747726

0.042177

0

0.025641

0

0.051251

0

null

0.012821

0.064103

null

0.051282

0

null

0

null

0

1

0

1

fe3c354a94b9bc97c332f504c7fb8dc959b31224

7,019

py

Python

manila/tests/share/test_snapshot_access.py

gouthampacha/manila

4b7ba9b99d272663f519b495668715fbf979ffbc

[ "Apache-2.0" ]

3

2016-06-06T13:05:00.000Z

2021-05-05T04:29:24.000Z

manila/tests/share/test_snapshot_access.py

gouthampacha/manila

4b7ba9b99d272663f519b495668715fbf979ffbc

[ "Apache-2.0" ]

5

2019-08-14T06:46:03.000Z

2021-12-13T20:01:25.000Z

manila/tests/share/test_snapshot_access.py

gouthampacha/manila

4b7ba9b99d272663f519b495668715fbf979ffbc

[ "Apache-2.0" ]

2

2020-03-15T01:24:15.000Z

2020-07-22T20:34:26.000Z

# Copyright (c) 2016 Hitachi Data Systems, Inc. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import copy import ddt import mock from manila.common import constants from manila import context from manila import db from manila import exception from manila.share import snapshot_access from manila import test from manila.tests import db_utils from manila import utils @ddt.ddt class SnapshotAccessTestCase(test.TestCase): def setUp(self): super(SnapshotAccessTestCase, self).setUp() self.driver = self.mock_class("manila.share.driver.ShareDriver", mock.Mock()) self.snapshot_access = snapshot_access.ShareSnapshotInstanceAccess( db, self.driver) self.context = context.get_admin_context() share = db_utils.create_share() self.snapshot = db_utils.create_snapshot(share_id=share['id']) self.snapshot_instance = db_utils.create_snapshot_instance( snapshot_id=self.snapshot['id'], share_instance_id=self.snapshot['share']['instance']['id']) @ddt.data(constants.ACCESS_STATE_QUEUED_TO_APPLY, constants.ACCESS_STATE_QUEUED_TO_DENY) def test_update_access_rules(self, state): rules = [] for i in range(2): rules.append({ 'id': 'id-%s' % i, 'state': state, 'access_id': 'rule_id%s' % i }) all_rules = copy.deepcopy(rules) all_rules.append({ 'id': 'id-3', 'state': constants.ACCESS_STATE_ERROR, 'access_id': 'rule_id3' }) snapshot_instance_get = self.mock_object( db, 'share_snapshot_instance_get', mock.Mock(return_value=self.snapshot_instance)) snap_get_all_for_snap_instance = self.mock_object( db, 'share_snapshot_access_get_all_for_snapshot_instance', mock.Mock(return_value=all_rules)) self.mock_object(db, 'share_snapshot_instance_access_update') self.mock_object(self.driver, 'snapshot_update_access') self.mock_object(self.snapshot_access, '_check_needs_refresh', mock.Mock(return_value=False)) self.mock_object(db, 'share_snapshot_instance_access_delete') self.snapshot_access.update_access_rules(self.context, self.snapshot_instance['id']) snapshot_instance_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id'], with_share_data=True) snap_get_all_for_snap_instance.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id']) if state == constants.ACCESS_STATE_QUEUED_TO_APPLY: self.driver.snapshot_update_access.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance, rules, add_rules=rules, delete_rules=[], share_server=None) else: self.driver.snapshot_update_access.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance, [], add_rules=[], delete_rules=rules, share_server=None) def test_update_access_rules_delete_all_rules(self): rules = [] for i in range(2): rules.append({ 'id': 'id-%s' % i, 'state': constants.ACCESS_STATE_QUEUED_TO_DENY, 'access_id': 'rule_id%s' % i }) snapshot_instance_get = self.mock_object( db, 'share_snapshot_instance_get', mock.Mock(return_value=self.snapshot_instance)) snap_get_all_for_snap_instance = self.mock_object( db, 'share_snapshot_access_get_all_for_snapshot_instance', mock.Mock(side_effect=[rules, []])) self.mock_object(db, 'share_snapshot_instance_access_update') self.mock_object(self.driver, 'snapshot_update_access') self.mock_object(db, 'share_snapshot_instance_access_delete') self.snapshot_access.update_access_rules(self.context, self.snapshot_instance['id'], delete_all_rules=True) snapshot_instance_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id'], with_share_data=True) snap_get_all_for_snap_instance.assert_called_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id']) self.driver.snapshot_update_access.assert_called_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance, [], add_rules=[], delete_rules=rules, share_server=None) def test_update_access_rules_exception(self): rules = [] for i in range(2): rules.append({ 'id': 'id-%s' % i, 'state': constants.ACCESS_STATE_APPLYING, 'access_id': 'rule_id%s' % i }) snapshot_instance_get = self.mock_object( db, 'share_snapshot_instance_get', mock.Mock(return_value=self.snapshot_instance)) snap_get_all_for_snap_instance = self.mock_object( db, 'share_snapshot_access_get_all_for_snapshot_instance', mock.Mock(return_value=rules)) self.mock_object(db, 'share_snapshot_instance_access_update') self.mock_object(self.driver, 'snapshot_update_access', mock.Mock(side_effect=exception.NotFound)) self.assertRaises(exception.NotFound, self.snapshot_access.update_access_rules, self.context, self.snapshot_instance['id']) snapshot_instance_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id'], with_share_data=True) snap_get_all_for_snap_instance.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance['id']) self.driver.snapshot_update_access.assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.snapshot_instance, rules, add_rules=rules, delete_rules=[], share_server=None)

41.532544

78

0.648383

812

7,019

5.273399

0.172414

0.13078

0.079402

0.041102

0.662774

0.65717

0.626576

0

0.002511

0.262431

7,019

168

79

41.779762

0.824609

0.087762

0

0.53125

0

0.108172

0.080776

0

0.085938

1

0.03125

false

0

0.085938

0

0.125

0

null

0

1

0

null

0

1

fe3d447e3c8eb707e5a1d8550493f94e70efafc2

269

py

Python

packages/pyright-internal/src/tests/samples/unnecessaryCast1.py

sasano8/pyright

e804f324ee5dbd25fd37a258791b3fd944addecd

[ "MIT" ]

4,391

2019-05-07T01:18:57.000Z

2022-03-31T20:45:44.000Z

packages/pyright-internal/src/tests/samples/unnecessaryCast1.py

sasano8/pyright

e804f324ee5dbd25fd37a258791b3fd944addecd

[ "MIT" ]

2,740

2019-05-07T03:29:30.000Z

2022-03-31T12:57:46.000Z

packages/pyright-internal/src/tests/samples/unnecessaryCast1.py

sasano8/pyright

e804f324ee5dbd25fd37a258791b3fd944addecd

[ "MIT" ]

455

2019-05-07T12:55:14.000Z

2022-03-31T17:09:15.000Z

# This sample tests the type checker's reportUnnecessaryCast feature. from typing import cast, Union def foo(a: int): # This should generate an error if # reportUnnecessaryCast is enabled. b = cast(int, a) c: Union[int, str] = "hello" d = cast(int, c)

19.214286

69

0.687732

40

269

4.625

0.75

0.075676

0

0.215613

269

13

70

20.692308

0.876777

0.498141

0

1

0

0.038168

0

1

0.2

false

0

0.2

0

0.4

0

null

0

1

0

null

0

1

fe3e90a0352653677e5f89aa3d6275c22d3a1048

470

py

Python

tests/test1.py

SaijC/manhwaDownloader

f6e97cfe25355598e42633a3796d84b666d5302f

[ "MIT" ]

null

tests/test1.py

SaijC/manhwaDownloader

f6e97cfe25355598e42633a3796d84b666d5302f

[ "MIT" ]

null

tests/test1.py

SaijC/manhwaDownloader

f6e97cfe25355598e42633a3796d84b666d5302f

[ "MIT" ]

null

import requests import logging import cfscrape import os from manhwaDownloader.constants import CONSTANTS as CONST logging.basicConfig(level=logging.DEBUG) folderPath = os.path.join(CONST.OUTPUTPATH, 'serious-taste-of-forbbiden-fruit') logging.info(len([file for file in os.walk(folderPath)])) walkList = [file for file in os.walk(folderPath)] chapterDicts = dict() for folder, _, files in walkList[1:]: chapterDicts.update({folder: files}) print(chapterDicts)

24.736842

79

0.778723

63

470

5.793651

0.571429

0.038356

0.060274

0.071233

0.158904

0

0.002392

0.110638

470

19

80

24.736842

0.870813

0

0.067941

0

1

0

false

0

0.384615

0

0.384615

0.076923

0

null

0

null

0

1

0

1

fe48c3bafe5a6523868023e377aa4dab0192c3a1

407

py

Python

solutions/python3/894.py

sm2774us/amazon_interview_prep_2021

f580080e4a6b712b0b295bb429bf676eb15668de

[ "MIT" ]

42

2020-08-02T07:03:49.000Z

2022-03-26T07:50:15.000Z

solutions/python3/894.py

ajayv13/leetcode

de02576a9503be6054816b7444ccadcc0c31c59d

[ "MIT" ]

null

solutions/python3/894.py

ajayv13/leetcode

de02576a9503be6054816b7444ccadcc0c31c59d

[ "MIT" ]

40

2020-02-08T02:50:24.000Z

2022-03-26T15:38:10.000Z

class Solution: def allPossibleFBT(self, N): def constr(N): if N == 1: yield TreeNode(0) for i in range(1, N, 2): for l in constr(i): for r in constr(N - i - 1): m = TreeNode(0) m.left = l m.right = r yield m return list(constr(N))

33.916667

47

0.371007

49

407

3.081633

0.489796

0.139073

0

0.031915

0.538084

407

12

48

33.916667

0.771277

0

1

0.166667

false

0

0.333333

0

null

0

1

0

null

0

1

fe4e2e11b7395e1b93b6ba3044a09072e2e8f08b

1,230

py

Python

Modules/Phylogenetic.py

DaneshMoradigaravand/PlasmidPerm

7a84c1d4dbf7320dd5ba821ff0e715a89fe4b3e4

[ "MIT" ]

null

Modules/Phylogenetic.py

DaneshMoradigaravand/PlasmidPerm

7a84c1d4dbf7320dd5ba821ff0e715a89fe4b3e4

[ "MIT" ]

null

Modules/Phylogenetic.py

DaneshMoradigaravand/PlasmidPerm

7a84c1d4dbf7320dd5ba821ff0e715a89fe4b3e4

[ "MIT" ]

null

import os from Bio import AlignIO, Phylo from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor class Phylogenetic: def __init__(self, PATH): self.PATH=PATH def binary_sequence_generator(self, input_kmer_pattern, label): string_inp="".join([ 'A' if x==0 else 'C' for x in input_kmer_pattern]) return([">"+label,string_inp]) def multifasta_fille_generator(self, converted_sequences_phyolgenetic): file_output = open(os.path.join(self.PATH,"binary_presence_absence_kmers.fasta"), "w") file_output.writelines('\n'.join(converted_sequences_phyolgenetic) + '\n' ) file_output.close() def distance_matrix_generator(self): align = AlignIO.read(os.path.join(self.PATH,"binary_presence_absence_kmers.fasta"), "fasta") calculator = DistanceCalculator('identity') distMatrix = calculator.get_distance(align) return(distMatrix) def distance_tree_file_generator(self,distance_matrix): constructor = DistanceTreeConstructor() UPGMATree = constructor.upgma(distance_matrix) Phylo.write(UPGMATree, os.path.join(self.PATH,"binary_presence_absence_kmers.tre") , "newick")

45.555556

102

0.71626

143

1,230

5.895105

0.454545

0.04745

0.035587

0.049822

0.168446

0.116251

0

0.000988

0.177236

1,230

27

102

45.555556

0.832016

0

0.105605

0.083672

0

1

0.227273

false

0

0.136364

0

0.409091

0

null

0

null

0

1

0

1

fe50481354faa15f773f5ba3bf0a4fb0f0ded16b

8,854

py

Python

retrieve_regmod_values.py

cbcommunity/cbapi-examples

f8a81006b27c724582b4b04c124eb97a8c8e75d3

[ "MIT" ]

17

2016-07-21T14:58:49.000Z

2020-10-26T15:51:38.000Z

retrieve_regmod_values.py

cbcommunity/cbapi-examples

f8a81006b27c724582b4b04c124eb97a8c8e75d3

[ "MIT" ]

5

2017-06-07T02:42:09.000Z

2019-10-23T12:26:29.000Z

retrieve_regmod_values.py

cbcommunity/cbapi-examples

f8a81006b27c724582b4b04c124eb97a8c8e75d3

[ "MIT" ]

9

2016-10-03T02:18:23.000Z

2021-03-08T22:44:33.000Z

#!/usr/bin/env python # #The MIT License (MIT) # # Copyright (c) 2015 Bit9 + Carbon Black # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # # ----------------------------------------------------------------------------- # Extension regmod watcher and grabber # # This script listens to the CB messaging bus for registry modification events, # and when a modification is seen that matches a regular expression from a file # of registry path regular expressions, it goes and grabs the registry value # using CB Live Response. # # You need to make sure rabbitmq is enabled in cb.conf, and you might need to # open a firewall rule for port 5004. You also will need to enable regmod # in the DatastoreBroadcastEventTypes=<values> entry. If anything is changed # here, you'll have to do service cb-enterprise restart. # # TODO: More error handling, more performance improvements # # last updated 2016-01-23 by Ben Johnson bjohnson@bit9.com (dev-support@bit9.com) # import re import Queue import sys from threading import Thread import time import traceback try: from cbapi.legacy.util.cli_helpers import main_helper from cbapi.legacy.util.composite_helpers import MessageSubscriberAndLiveResponseActor import cbapi.legacy.util.sensor_events_pb2 as cpb except ImportError: from cbapi.util.cli_helpers import main_helper from cbapi.util.composite_helpers import MessageSubscriberAndLiveResponseActor import cbapi.util.sensor_events_pb2 as cpb class RegistryModWatcherAndValueGrabber(MessageSubscriberAndLiveResponseActor): """ This class subscribes to messages from the CB messaging bus, looking for regmod events. For each regmod event, it checks to see if the the registry path matches one of our regexes. If it does, it goes and grabs it. """ def __init__(self, cb_server_url, cb_ext_api, username, password, regmod_regexes, verbose): self.regmod_regexes = regmod_regexes self.verbose = verbose MessageSubscriberAndLiveResponseActor.__init__(self, cb_server_url, cb_ext_api, username, password, "ingress.event.regmod") # Threading so that message queue arrives do not block waiting for live response self.queue = Queue.Queue() self.go = True self.worker_thread = Thread(target=self._worker_thread_loop) self.worker_thread.start() def on_stop(self): self.go = False self.worker_thread.join(timeout=2) MessageSubscriberAndLiveResponseActor.on_stop(self) def consume_message(self, channel, method_frame, header_frame, body): if "application/protobuf" != header_frame.content_type: return try: # NOTE -- this is not very efficient in PYTHON, and should # use a C parser to make this much, much faster. # http://yz.mit.edu/wp/fast-native-c-protocol-buffers-from-python/ x = cpb.CbEventMsg() x.ParseFromString(body) if not x.regmod or x.regmod.action != 2: # Check for MODIFICATION event because we will usually get # a creation event and a modification event, and might as # well go with the one that says data has actually been written. return regmod_path = None if x.regmod.utf8_regpath: if self.verbose: print "Event arrived: |%s|" % x.regmod.utf8_regpath for regmod_regex in self.regmod_regexes: if regmod_regex.match(x.regmod.utf8_regpath): regmod_path = x.regmod.utf8_regpath break if regmod_path: regmod_path = regmod_path.replace("\\registry\\machine\\", "HKLM\\") regmod_path = regmod_path.replace("\\registry\\user\\", "HKEY_USERS\\") regmod_path = regmod_path.strip() # TODO -- more cleanup here potentially? self.queue.put((x, regmod_path)) except: traceback.print_exc() def _worker_thread_loop(self): while self.go: try: try: (x, regmod_path) = self.queue.get(timeout=0.5) except Queue.Empty: continue # TODO -- could comment this out if you want CSV data to feed into something print "--> Attempting for %s" % regmod_path # Go Grab it if we think we have something! sensor_id = x.env.endpoint.SensorId hostname = x.env.endpoint.SensorHostName # TODO -- this could use some concurrency and work queues because we could wait a while for # each of these to get established and retrieve the value # Establish our CBLR session if necessary! lrh = self._create_lr_session_if_necessary(sensor_id) data = lrh.get_registry_value(regmod_path) print "%s,%s,%d,%s,%s,%s" % ( time.asctime(), hostname, sensor_id, x.header.process_path, regmod_path, data.get('value_data', "") if data else "<UNKNOWN>") # TODO -- could *do something* here, like if it is for autoruns keys then go check the signature status # of the binary at the path pointed to, and see who wrote it out, etc except: traceback.print_exc() def main(cb, args): username = args.get("username") password = args.get("password") regpaths_file = args.get("regpaths_file") verbose = args.get("verbose", False) if verbose: # maybe you want to print out all the regpaths we're using? print "Regpaths file:", regpaths_file f = file(regpaths_file, 'rb') regpaths_data = f.read() f.close() regmod_regexes = [] for line in regpaths_data.split('\n'): line = line.strip() if len(line) == 0: continue regmod_regexes.append(re.compile(line)) listener = RegistryModWatcherAndValueGrabber(args.get('server_url'), cb, username, password, regmod_regexes, verbose) try: if verbose: print "Registry Mod Watcher and Grabber -- started. Watching for:", regpaths_data else: print "Registry Mod Watcher and Grabber -- started. Watching for %d regexes" % len(regmod_regexes) listener.process() except KeyboardInterrupt: print >> sys.stderr, "Caught Ctrl-C" listener.stop() print "Registry Mod Watcher and Grabber -- stopped." if __name__ == "__main__": ## YOU CAN USE data/autoruns_regexes.txt to test ## required_args =[("-i", "--username", "store", None, "username", "CB messaging username"), ("-p", "--password", "store", None, "password", "CB messaging password"), ("-r", "--regpaths_file", "store", None, "regpaths_file", "File of newline delimited regexes for regpaths")] optional_args = [("-v", "--verbose", "store_true", False, "verbose", "Enable verbose output")] main_helper("Subscribe to message bus events and for each registry modification that matches one of our supplied regexes, go retrieve value.", main, custom_required=required_args, custom_optional=optional_args)

42.980583

146

0.61588

1,065

8,854

5.015023

0.367136

0.026212

0.013106

0.013481

0.126006

0.105785

0.077514

0.049803

0.035199

0.016102

0

0.004838

0.299639

8,854

205

147

43.190244

0.856475

0.332279

0

0.135135

0

0.009009

0.138755

0.003745

0

0.009756

0

null

0.045045

0.117117

null

0.09009

0

null

0

null

0

1

0

1

fe52c241e006580225be521c666de64401063758

410

py

Python

lib/models/bn_helper.py

hongrui16/naic2020_B

9321bdd19e7d2d47ac9c711eb8437cd364e25f44

[ "MIT" ]

null

lib/models/bn_helper.py

hongrui16/naic2020_B

9321bdd19e7d2d47ac9c711eb8437cd364e25f44

[ "MIT" ]

null

lib/models/bn_helper.py

hongrui16/naic2020_B

9321bdd19e7d2d47ac9c711eb8437cd364e25f44

[ "MIT" ]

null

import torch import functools if torch.__version__.startswith('0'): from .sync_bn.inplace_abn.bn import InPlaceABNSync BatchNorm2d = functools.partial(InPlaceABNSync, activation='none') BatchNorm2d_class = InPlaceABNSync relu_inplace = False else: # BatchNorm2d_class = BatchNorm2d = torch.nn.SyncBatchNorm BatchNorm2d_class = BatchNorm2d = torch.nn.BatchNorm2d relu_inplace = True

34.166667

70

0.770732

45

410

6.777778

0.533333

0.157377

0.177049

0.209836

0.222951

0

0.023055

0.153659

410

12

71

34.166667

0.855908

0.136585

0

0.014164

0

1

0

false

0

0.3

0

0.3

0

null

0

1

0

null

0

1

fe551b06355686622edde6ba5da6a8305143cb35

2,193

py

Python

ordered_model/tests/models.py

HiddenClever/django-ordered-model

c94709403cfbb35fa4da3d6470ead816096fdec8

[ "BSD-3-Clause" ]

null

ordered_model/tests/models.py

HiddenClever/django-ordered-model

c94709403cfbb35fa4da3d6470ead816096fdec8

[ "BSD-3-Clause" ]

null

ordered_model/tests/models.py

HiddenClever/django-ordered-model

c94709403cfbb35fa4da3d6470ead816096fdec8

[ "BSD-3-Clause" ]

null

from django.db import models from ordered_model.models import OrderedModel, OrderedModelBase class Item(OrderedModel): name = models.CharField(max_length=100) class Question(models.Model): pass class TestUser(models.Model): pass class Answer(OrderedModel): question = models.ForeignKey(Question, on_delete=models.CASCADE, related_name='answers') user = models.ForeignKey(TestUser, on_delete=models.CASCADE, related_name='answers') order_with_respect_to = ('question', 'user') class Meta: ordering = ('question', 'user', 'order') def __unicode__(self): return u"Answer #{0:d} of question #{1:d} for user #{2:d}".format(self.order, self.question_id, self.user_id) class CustomItem(OrderedModel): id = models.CharField(max_length=100, primary_key=True) name = models.CharField(max_length=100) modified = models.DateTimeField(null=True, blank=True) class CustomOrderFieldModel(OrderedModelBase): sort_order = models.PositiveIntegerField(editable=False, db_index=True) name = models.CharField(max_length=100) order_field_name = 'sort_order' class Meta: ordering = ('sort_order',) class Topping(models.Model): name = models.CharField(max_length=100) class Pizza(models.Model): name = models.CharField(max_length=100) toppings = models.ManyToManyField(Topping, through='PizzaToppingsThroughModel') class PizzaToppingsThroughModel(OrderedModel): pizza = models.ForeignKey(Pizza, on_delete=models.CASCADE) topping = models.ForeignKey(Topping, on_delete=models.CASCADE) order_with_respect_to = 'pizza' class Meta: ordering = ('pizza', 'order') class BaseQuestion(OrderedModel): order_class_path = __module__ + '.BaseQuestion' question = models.TextField(max_length=100) class Meta: ordering = ('order',) class MultipleChoiceQuestion(BaseQuestion): good_answer = models.TextField(max_length=100) wrong_answer1 = models.TextField(max_length=100) wrong_answer2 = models.TextField(max_length=100) wrong_answer3 = models.TextField(max_length=100) class OpenQuestion(BaseQuestion): answer = models.TextField(max_length=100)

29.24

117

0.735522

259

2,193

6.042471

0.301158

0.06901

0.092013

0.31885

0.301597

0.174441

0.053674

0

0.022642

0.154127

2,193

74

118

29.635135

0.821024

0

0.22449

0

0.077063

0.0114

0

1

0.020408

false

0.040816

0.020408

0.877551

0

null

0

null

0

1

0

1

fe56b7b7af27f780f7fa9407871404e8b6436b3d

1,587

py

Python

app/services/base.py

grace1307/lan_mapper

5d244078732b86a2e38a5b21436ffca83c689eeb

[ "MIT" ]

null

app/services/base.py

grace1307/lan_mapper

5d244078732b86a2e38a5b21436ffca83c689eeb

[ "MIT" ]

null

app/services/base.py

grace1307/lan_mapper

5d244078732b86a2e38a5b21436ffca83c689eeb

[ "MIT" ]

null

from app.db import db # Ignore it if db can't find the row when updating/deleting # Todo: not ignore it, raise some error, remove checkers in view class BaseService: __abstract__ = True model = None # Create def add_one(self, **kwargs): new_row = self.model(**kwargs) db.session.add(new_row) db.session.commit() # sqlalchemy auto flushes so maybe this just need commit ? return new_row # Read def select_one(self, id): return self.model.query.filter(self.model.id == id).one_or_none() def select_all(self, conditions: list = None, sort_by=None, is_asc=None): query = db.session.query(self.model) if conditions is not None: for condition in conditions: query = query.filter(condition) if sort_by is not None and is_asc is not None: sort_column = self.model.__table__._columns[sort_by] is_asc = is_asc == 'true' if sort_column is not None: query = query.order_by(sort_column.asc() if is_asc else sort_column.desc()) return query.all() # Update def update_one(self, id, updated): row = self.model.query.filter(self.model.id == id) row_result = row.one_or_none() if row_result is not None: row.update(updated) db.session.commit() return row.one_or_none() # Delete def delete_one(self, id): row = self.select_one(id) if row is not None: db.session.delete(row) db.session.commit()

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null

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null

0

1

0

1

fe5b28c8c0a814b5544650e3dacd259358d5495e

4,972

py

Python

sbpy/photometry/bandpass.py

jianyangli/sbpy

6b79cbea9bada89207fba17d02dc0c321fa46bf4

[ "BSD-3-Clause" ]

1

2017-11-28T02:58:51.000Z

sbpy/photometry/bandpass.py

jianyangli/sbpy

6b79cbea9bada89207fba17d02dc0c321fa46bf4

[ "BSD-3-Clause" ]

null

sbpy/photometry/bandpass.py

jianyangli/sbpy

6b79cbea9bada89207fba17d02dc0c321fa46bf4

[ "BSD-3-Clause" ]

null

# Licensed under a 3-clause BSD style license - see LICENSE.rst """ sbpy bandpass Module """ __all__ = [ 'bandpass' ] import os from astropy.utils.data import get_pkg_data_filename def bandpass(name): """Retrieve bandpass transmission spectrum from sbpy. Parameters ---------- name : string Name of the bandpass, case insensitive. See notes for available filters. Returns ------- bp : `~synphot.SpectralElement` Notes ----- Available filters: +-------------+---------------------------+ | Name | Source | +=============+===========================+ | 2MASS J | Cohen et al. 2003 | +-------------+---------------------------+ | 2MASS H | Cohen et al. 2003 | +-------------+---------------------------+ | 2MASS Ks | Cohen et al. 2003 | +-------------+---------------------------+ | Cousins R | STScI CDBS, v4 | +-------------+---------------------------+ | Cousins I | STScI CDBS, v4 | +-------------+---------------------------+ | Johnson U | STScI CDBS, v4 | +-------------+---------------------------+ | Johnson B | STScI CDBS, v4 | +-------------+---------------------------+ | Johnson V | STScI CDBS, v4 | +-------------+---------------------------+ | PS1 g | Tonry et al. 2012 | +-------------+---------------------------+ | PS1 r | Tonry et al. 2012 | +-------------+---------------------------+ | PS1 i | Tonry et al. 2012 | +-------------+---------------------------+ | PS1 w | Tonry et al. 2012 | +-------------+---------------------------+ | PS1 y | Tonry et al. 2012 | +-------------+---------------------------+ | PS1 z | Tonry et al. 2012 | +-------------+---------------------------+ | SDSS u | SDSS, dated 2001 | +-------------+---------------------------+ | SDSS g | SDSS, dated 2001 | +-------------+---------------------------+ | SDSS r | SDSS, dated 2001 | +-------------+---------------------------+ | SDSS i | SDSS, dated 2001 | +-------------+---------------------------+ | SDSS z | SDSS, dated 2001 | +-------------+---------------------------+ | WFC3 F438W | HST/WFC3 UVIS, v4 | +-------------+---------------------------+ | WFC3 F606W | HST/WFC3 UVIS, v4 | +-------------+---------------------------+ | WISE W1 | Jarrett et al. 2011 | +-------------+---------------------------+ | WISE W2 | Jarrett et al. 2011 | +-------------+---------------------------+ | WISE W3 | Jarrett et al. 2011 | +-------------+---------------------------+ | WISE W4 | Jarrett et al. 2011 | +-------------+---------------------------+ References ---------- .. [CDBS] Space Telescope Science Institute. HST Calibration Reference Data System. https://hst-crds.stsci.edu/ . .. [COH03] Cohen, M. et al. 2003. Spectral Irradiance Calibration in the Infrared. XIV. The Absolute Calibration of 2MASS. AJ 126, 1090. .. [JAR11] Jarrett, T. H. et al. 2011. The Spitzer-WISE Survey of the Ecliptic Poles. ApJ 735, 112. .. [SDSS] Sloan Digital Sky Survey. Camera. www.sdss.org/instruments/camera . .. [TON12] Tonry, J. L. et al. 2012. The Pan-STARRS1 Photometric System. ApJ 750, 99. """ try: import synphot except ImportError: raise ImportError('synphot is required.') name2file = { '2mass j': '2mass-j-rsr.txt', '2mass h': '2mass-h-rsr.txt', '2mass ks': '2mass-ks-rsr.txt', 'cousins r': 'cousins_r_004_syn.fits', 'cousins i': 'cousins_i_004_syn.fits', 'johnson u': 'johnson_u_004_syn.fits', 'johnson b': 'johnson_b_004_syn.fits', 'johnson v': 'johnson_v_004_syn.fits', 'ps1 g': 'ps1-gp1.txt', 'ps1 r': 'ps1-rp1.txt', 'ps1 i': 'ps1-ip1.txt', 'ps1 w': 'ps1-wp1.txt', 'ps1 y': 'ps1-yp1.txt', 'ps1 z': 'ps1-zp1.txt', 'sdss u': 'sdss-u.fits', 'sdss g': 'sdss-g.fits', 'sdss r': 'sdss-r.fits', 'sdss i': 'sdss-i.fits', 'sdss z': 'sdss-z.fits', 'wfc3 f438w': 'wfc3_uvis_f438w_004_syn.fits', 'wfc3 f606w': 'wfc3_uvis_f606w_004_syn.fits', 'wise w1': 'WISE-RSR-W1.EE.txt', 'wise w2': 'WISE-RSR-W2.EE.txt', 'wise w3': 'WISE-RSR-W3.EE.txt', 'wise w4': 'WISE-RSR-W4.EE.txt', } fn = get_pkg_data_filename(os.path.join( '..', 'photometry', 'data', name2file[name.lower()])) bp = synphot.SpectralElement.from_file(fn) return bp

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4,972

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null

0

1

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null

0

1

fe5c54cf485f5924948c2f9e92bdf0e6152fda9f

1,566

py

Python

teams/migrations/0001_initial.py

Sudani-Coder/teammanager

857082bc14d7a783d2327b4e982edba7c061f303

[ "MIT" ]

null

teams/migrations/0001_initial.py

Sudani-Coder/teammanager

857082bc14d7a783d2327b4e982edba7c061f303

[ "MIT" ]

null

teams/migrations/0001_initial.py

Sudani-Coder/teammanager

857082bc14d7a783d2327b4e982edba7c061f303

[ "MIT" ]

null

# Generated by Django 3.1.2 on 2020-10-18 17:19 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='GameScore', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_team', models.CharField(max_length=200)), ('second_team', models.CharField(max_length=200)), ('first_team_score', models.IntegerField(default=0)), ('second_team_score', models.IntegerField(default=0)), ], ), migrations.CreateModel( name='Player', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('number', models.IntegerField()), ('age', models.IntegerField()), ('position_in_field', models.CharField(choices=[('1', 'حارس'), ('2', 'دفاع'), ('3', 'وسط'), ('4', 'هجوم')], max_length=200)), ], ), migrations.CreateModel( name='Team', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200, unique=True)), ('details', models.TextField()), ], ), ]

36.418605

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1,566

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1,566

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null

0

1

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null

0

1

fe5f635d76dff706767d5a4351544f241f8b385b

3,192

py

Python

examples/gather_demo.py

mununum/MAgent

7272cd726182280444597310d52369fac5e13e37

[ "MIT" ]

1

2021-06-22T10:22:26.000Z

examples/gather_demo.py

mununum/MAgent

7272cd726182280444597310d52369fac5e13e37

[ "MIT" ]

null

examples/gather_demo.py

mununum/MAgent

7272cd726182280444597310d52369fac5e13e37

[ "MIT" ]

null

import random import magent from magent.builtin.rule_model import RandomActor import numpy as np def init_food(env, food_handle): tree = np.asarray([[-1,0], [0,0], [0,-1], [0,1], [1,0]]) third = map_size//4 # mapsize includes walls for i in range(1, 4): for j in range(1, 4): base = np.asarray([third*i, third*j]) env.add_agents(food_handle, method="custom", pos=tree+base) def neigbor_regen_food(env, food_handle, p=0.003): coords = env.get_pos(food_handle) rands = np.random.random(len(coords)) for i, pos in enumerate(coords): if rands[i] > p: continue neighbor = np.asarray([[-1,0],[0,-1], [0,1], [1,0]]) regen_pos = [pos+neighbor[np.random.randint(0,4)]] env.add_agents(food_handle, method="custom", pos=regen_pos) if __name__ == "__main__": gw = magent.gridworld cfg = gw.Config() map_size = 25 cfg.set({"map_width": map_size, "map_height": map_size}) agent_group = cfg.add_group( cfg.register_agent_type( name="agent", attr={ 'width': 1, 'length': 1, 'view_range': gw.CircleRange(4), 'can_gather': True})) food_group = cfg.add_group( cfg.register_agent_type( "food", attr={'width': 1, 'length': 1, 'can_be_gathered': True})) # add reward rule a = gw.AgentSymbol(agent_group, index='any') b = gw.AgentSymbol(food_group, index='any') e = gw.Event(a, 'collide', b) cfg.add_reward_rule(e, receiver=a, value=1) # cfg.add_reward_rule(e2, receiver=b, value=1, die=True) # cfg.add_reward_rule(e3, receiver=[a,b], value=[-1,-1]) env = magent.GridWorld(cfg) agent_handle, food_handle = env.get_handles() model1 = RandomActor(env, agent_handle, "up") env.set_render_dir("build/render") env.reset() upstart = [(map_size//2 - 2, map_size//2 - 2), (map_size//2 + 2, map_size//2 - 2), (map_size//2, map_size//2), (map_size//2 - 2, map_size//2 + 2), (map_size//2 + 2, map_size//2 + 2)] # spawnrate = 0.1 env.add_agents(agent_handle, method="custom", pos=upstart) # env.add_agents(rightgroup, method="custom", pos=rightstart) init_food(env, food_handle) k = env.get_observation(agent_handle) print env.get_pos(agent_handle) print len(env.get_pos(food_handle)) done = False step_ct = 0 r_sum = 0 while not done: obs_1 = env.get_observation(agent_handle) ids_1 = env.get_agent_id(agent_handle) acts_1 = model1.infer_action(obs_1, ids_1) env.set_action(agent_handle, acts_1) # simulate one step done = env.step() # render env.render() # get reward reward = sum(env.get_reward(agent_handle)) r_sum += reward # clear dead agents env.clear_dead() neigbor_regen_food(env, food_handle) # print info # if step_ct % 10 == 0: # print("step %d" % step_ct) step_ct += 1 if step_ct > 250: break print r_sum

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3,192

3.818777

0.275109

0.056032

0.04574

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0

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0.280075

3,192

114

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0.053333

null

0.04

0

null

0

null

0

1

0

1

fe6407132244604eabc2321eb05eb24333b3bd82

669

py

Python

pyTorch/utils.py

rajasekar-venkatesan/Deep_Learning

c375dab303f44043a4dc30ea53b298d7eca1d5a7

[ "MIT" ]

null

pyTorch/utils.py

rajasekar-venkatesan/Deep_Learning

c375dab303f44043a4dc30ea53b298d7eca1d5a7

[ "MIT" ]

null

pyTorch/utils.py

rajasekar-venkatesan/Deep_Learning

c375dab303f44043a4dc30ea53b298d7eca1d5a7

[ "MIT" ]

null

import pandas as pd, numpy as np from sklearn.preprocessing import OneHotEncoder author_int_dict = {'EAP':0,'HPL':1,'MWS':2} def load_train_test_data (num_samples=None): train_data = pd.read_csv('../data/train.csv') train_data['author'] = [author_int_dict[a] for a in train_data['author'].tolist()] test_data = pd.read_csv('../data/test.csv') return train_data[:num_samples],test_data[:num_samples] def categorical_labeler (labels): labels = labels.reshape(-1, 1) #labels = OneHotEncoder().fit_transform(labels).todense() labels = np.array(labels, dtype=np.int64) return labels if __name__ == '__main__': pass

33.45

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0.083141

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false

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0.428571

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null

0

null

0

1

0

1

fe64404bf937356d7de814318a6e0bdf49ea36b3

6,987

py

Python

example/dec/dec.py

TheBurningCrusade/A_mxnet

fa2a8e3c438bea16b993e9537f75e2082d83346f

[ "Apache-2.0" ]

159

2016-08-23T22:13:26.000Z

2021-10-24T01:31:35.000Z

example/dec/dec.py

mrgloom/FaceDetection-ConvNet-3D

f9251c48eb40c5aec8fba7455115c355466555be

[ "Apache-2.0" ]

10

2016-08-23T05:59:07.000Z

2018-05-24T02:31:41.000Z

example/dec/dec.py

mrgloom/FaceDetection-ConvNet-3D

f9251c48eb40c5aec8fba7455115c355466555be

[ "Apache-2.0" ]

77

2016-08-21T00:35:00.000Z

2021-06-01T05:03:34.000Z

# pylint: skip-file import sys import os # code to automatically download dataset curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) sys.path = [os.path.join(curr_path, "../autoencoder")] + sys.path import mxnet as mx import numpy as np import data from scipy.spatial.distance import cdist from sklearn.cluster import KMeans import model from autoencoder import AutoEncoderModel from solver import Solver, Monitor import logging def cluster_acc(Y_pred, Y): from sklearn.utils.linear_assignment_ import linear_assignment assert Y_pred.size == Y.size D = max(Y_pred.max(), Y.max())+1 w = np.zeros((D,D), dtype=np.int64) for i in range(Y_pred.size): w[Y_pred[i], Y[i]] += 1 ind = linear_assignment(w.max() - w) return sum([w[i,j] for i,j in ind])*1.0/Y_pred.size, w class DECModel(model.MXModel): class DECLoss(mx.operator.NumpyOp): def __init__(self, num_centers, alpha): super(DECModel.DECLoss, self).__init__(need_top_grad=False) self.num_centers = num_centers self.alpha = alpha def forward(self, in_data, out_data): z = in_data[0] mu = in_data[1] q = out_data[0] self.mask = 1.0/(1.0+cdist(z, mu)**2/self.alpha) q[:] = self.mask**((self.alpha+1.0)/2.0) q[:] = (q.T/q.sum(axis=1)).T def backward(self, out_grad, in_data, out_data, in_grad): q = out_data[0] z = in_data[0] mu = in_data[1] p = in_data[2] dz = in_grad[0] dmu = in_grad[1] self.mask *= (self.alpha+1.0)/self.alpha*(p-q) dz[:] = (z.T*self.mask.sum(axis=1)).T - self.mask.dot(mu) dmu[:] = (mu.T*self.mask.sum(axis=0)).T - self.mask.T.dot(z) def infer_shape(self, in_shape): assert len(in_shape) == 3 assert len(in_shape[0]) == 2 input_shape = in_shape[0] label_shape = (input_shape[0], self.num_centers) mu_shape = (self.num_centers, input_shape[1]) out_shape = (input_shape[0], self.num_centers) return [input_shape, mu_shape, label_shape], [out_shape] def list_arguments(self): return ['data', 'mu', 'label'] def setup(self, X, num_centers, alpha, save_to='dec_model'): sep = X.shape[0]*9/10 X_train = X[:sep] X_val = X[sep:] ae_model = AutoEncoderModel(self.xpu, [X.shape[1],500,500,2000,10], pt_dropout=0.2) if not os.path.exists(save_to+'_pt.arg'): ae_model.layerwise_pretrain(X_train, 256, 50000, 'sgd', l_rate=0.1, decay=0.0, lr_scheduler=mx.misc.FactorScheduler(20000,0.1)) ae_model.finetune(X_train, 256, 100000, 'sgd', l_rate=0.1, decay=0.0, lr_scheduler=mx.misc.FactorScheduler(20000,0.1)) ae_model.save(save_to+'_pt.arg') logging.log(logging.INFO, "Autoencoder Training error: %f"%ae_model.eval(X_train)) logging.log(logging.INFO, "Autoencoder Validation error: %f"%ae_model.eval(X_val)) else: ae_model.load(save_to+'_pt.arg') self.ae_model = ae_model self.dec_op = DECModel.DECLoss(num_centers, alpha) label = mx.sym.Variable('label') self.feature = self.ae_model.encoder self.loss = self.dec_op(data=self.ae_model.encoder, label=label, name='dec') self.args.update({k:v for k,v in self.ae_model.args.items() if k in self.ae_model.encoder.list_arguments()}) self.args['dec_mu'] = mx.nd.empty((num_centers, self.ae_model.dims[-1]), ctx=self.xpu) self.args_grad.update({k: mx.nd.empty(v.shape, ctx=self.xpu) for k,v in self.args.items()}) self.args_mult.update({k: k.endswith('bias') and 2.0 or 1.0 for k in self.args}) self.num_centers = num_centers def cluster(self, X, y=None, update_interval=None): N = X.shape[0] if not update_interval: update_interval = N batch_size = 256 test_iter = mx.io.NDArrayIter({'data': X}, batch_size=batch_size, shuffle=False, last_batch_handle='pad') args = {k: mx.nd.array(v.asnumpy(), ctx=self.xpu) for k, v in self.args.items()} z = model.extract_feature(self.feature, args, test_iter, N, self.xpu).values()[0] kmeans = KMeans(self.num_centers, n_init=20) kmeans.fit(z) args['dec_mu'][:] = kmeans.cluster_centers_ solver = Solver('sgd', momentum=0.9, wd=0.0, learning_rate=0.01) def ce(label, pred): return np.sum(label*np.log(label/(pred+0.000001)))/label.shape[0] solver.set_metric(mx.metric.CustomMetric(ce)) label_buff = np.zeros((X.shape[0], self.num_centers)) train_iter = mx.io.NDArrayIter({'data': X}, {'label': label_buff}, batch_size=batch_size, shuffle=False, last_batch_handle='roll_over') self.y_pred = np.zeros((X.shape[0])) def refresh(i): if i%update_interval == 0: z = model.extract_feature(self.feature, args, test_iter, N, self.xpu).values()[0] p = np.zeros((z.shape[0], self.num_centers)) self.dec_op.forward([z, args['dec_mu'].asnumpy()], [p]) y_pred = p.argmax(axis=1) print np.std(np.bincount(y_pred)), np.bincount(y_pred) print np.std(np.bincount(y.astype(np.int))), np.bincount(y.astype(np.int)) if y is not None: print(cluster_acc(y_pred, y)[0]) weight = 1.0/p.sum(axis=0) weight *= self.num_centers/weight.sum() p = (p**2)*weight train_iter.data_list[1][:] = (p.T/p.sum(axis=1)).T print np.sum(y_pred != self.y_pred), 0.001*y_pred.shape[0] if np.sum(y_pred != self.y_pred) < 0.001*y_pred.shape[0]: self.y_pred = y_pred return True self.y_pred = y_pred solver.set_iter_start_callback(refresh) solver.set_monitor(Monitor(50)) solver.solve(self.xpu, self.loss, args, self.args_grad, train_iter, 0, 1000000000, {}, False) self.end_args = args if y is not None: return cluster_acc(self.y_pred, y)[0] else: return -1 def mnist_exp(xpu): X, Y = data.get_mnist() dec_model = DECModel(xpu, X, 10, 1.0, 'data/mnist') acc = [] for i in [10*(2**j) for j in range(9)]: acc.append(dec_model.cluster(X, Y, i)) logging.log(logging.INFO, 'Clustering Acc: %f at update interval: %d'%(acc[-1], i)) logging.info(str(acc)) logging.info('Best Clustering ACC: %f at update_interval: %d'%(np.max(acc), 10*(2**np.argmax(acc)))) if __name__ == '__main__': logging.basicConfig(level=logging.INFO) mnist_exp(mx.gpu(0))

44.788462

116

0.586232

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6,987

3.665417

0.208997

0.028126

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0.013296

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null

0.028571

0

null

0

null

0

1

0

1

fe6806edfc8769087714d9060a7456450c7a5f90

1,608

py

Python

tests/env_config/test_base.py

DAtek/datek-app-utils

4783345d548bd85b1f6f99679be30b978e368e0e

[ "MIT" ]

null

tests/env_config/test_base.py

DAtek/datek-app-utils

4783345d548bd85b1f6f99679be30b978e368e0e

[ "MIT" ]

2

2022-02-05T12:15:03.000Z

2022-03-27T09:55:51.000Z

tests/env_config/test_base.py

DAtek/datek-app-utils

4783345d548bd85b1f6f99679be30b978e368e0e

[ "MIT" ]

null

from pytest import raises from datek_app_utils.env_config.base import BaseConfig from datek_app_utils.env_config.errors import InstantiationForbiddenError class SomeOtherMixinWhichDoesntRelateToEnvConfig: color = "red" class TestConfig: def test_iter(self, monkeypatch, key_volume, base_config_class): volume = 5 monkeypatch.setenv(key_volume, str(volume)) class Config(SomeOtherMixinWhichDoesntRelateToEnvConfig, base_config_class): TYPE: str items = [item for item in Config] assert len(items) == 5 assert Config.color == "red" assert items[0].name == "TYPE" assert items[0].value is None assert items[0].type == str assert items[1].name == "FIELD_WITH_DEFAULT_VALUE" assert items[1].value == "C" assert items[1].type == str assert items[2].name == "NON_MANDATORY_FIELD" assert items[2].value is None assert items[2].type == str assert items[3].name == "TYPED_NON_MANDATORY_FIELD" assert items[3].value is None assert items[3].type == str assert items[4].name == "VOLUME" assert items[4].value == volume assert items[4].type == int def test_get(self, monkeypatch, key_volume, base_config_class): volume = 10 monkeypatch.setenv(key_volume, str(volume)) assert getattr(base_config_class, "VOLUME") == volume def test_constructor_is_forbidden(self): class Config(BaseConfig): pass with raises(InstantiationForbiddenError): Config()

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0.300518

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0.328417

0.208456

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0.254353

1,608

55

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0.83236

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0.026316

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0

null

0

null

0

1

0

1

fe68c2686760a20f5158d8a2bc5c4a835377dc27

6,801

py

Python

mapclientplugins/argonsceneexporterstep/ui_configuredialog.py

Kayvv/mapclientplugins.argonsceneexporterstep

59b0b9cb15660c5747c1a7cba9da0e1eaf0bdf48

[ "Apache-2.0" ]

null

mapclientplugins/argonsceneexporterstep/ui_configuredialog.py

Kayvv/mapclientplugins.argonsceneexporterstep

59b0b9cb15660c5747c1a7cba9da0e1eaf0bdf48

[ "Apache-2.0" ]

null

mapclientplugins/argonsceneexporterstep/ui_configuredialog.py

Kayvv/mapclientplugins.argonsceneexporterstep

59b0b9cb15660c5747c1a7cba9da0e1eaf0bdf48

[ "Apache-2.0" ]

3

2021-07-26T00:53:24.000Z

2021-11-17T23:23:11.000Z

# -*- coding: utf-8 -*- ################################################################################ ## Form generated from reading UI file 'configuredialog.ui' ## ## Created by: Qt User Interface Compiler version 5.15.2 ## ## WARNING! All changes made in this file will be lost when recompiling UI file! ################################################################################ from PySide2.QtCore import * from PySide2.QtGui import * from PySide2.QtWidgets import * class Ui_ConfigureDialog(object): def setupUi(self, ConfigureDialog): if not ConfigureDialog.objectName(): ConfigureDialog.setObjectName(u"ConfigureDialog") ConfigureDialog.resize(510, 342) self.gridLayout = QGridLayout(ConfigureDialog) self.gridLayout.setObjectName(u"gridLayout") self.configGroupBox = QGroupBox(ConfigureDialog) self.configGroupBox.setObjectName(u"configGroupBox") self.formLayout = QFormLayout(self.configGroupBox) self.formLayout.setObjectName(u"formLayout") self.label0 = QLabel(self.configGroupBox) self.label0.setObjectName(u"label0") self.formLayout.setWidget(0, QFormLayout.LabelRole, self.label0) self.lineEditIdentifier = QLineEdit(self.configGroupBox) self.lineEditIdentifier.setObjectName(u"lineEditIdentifier") self.formLayout.setWidget(0, QFormLayout.FieldRole, self.lineEditIdentifier) self.label_3 = QLabel(self.configGroupBox) self.label_3.setObjectName(u"label_3") self.formLayout.setWidget(1, QFormLayout.LabelRole, self.label_3) self.prefix_lineEdit = QLineEdit(self.configGroupBox) self.prefix_lineEdit.setObjectName(u"prefix_lineEdit") self.formLayout.setWidget(1, QFormLayout.FieldRole, self.prefix_lineEdit) self.label_4 = QLabel(self.configGroupBox) self.label_4.setObjectName(u"label_4") self.formLayout.setWidget(3, QFormLayout.LabelRole, self.label_4) self.timeSteps_lineEdit = QLineEdit(self.configGroupBox) self.timeSteps_lineEdit.setObjectName(u"timeSteps_lineEdit") self.formLayout.setWidget(3, QFormLayout.FieldRole, self.timeSteps_lineEdit) self.label = QLabel(self.configGroupBox) self.label.setObjectName(u"label") self.formLayout.setWidget(4, QFormLayout.LabelRole, self.label) self.initialTime_lineEdit = QLineEdit(self.configGroupBox) self.initialTime_lineEdit.setObjectName(u"initialTime_lineEdit") self.formLayout.setWidget(4, QFormLayout.FieldRole, self.initialTime_lineEdit) self.label_2 = QLabel(self.configGroupBox) self.label_2.setObjectName(u"label_2") self.formLayout.setWidget(5, QFormLayout.LabelRole, self.label_2) self.finishTime_lineEdit = QLineEdit(self.configGroupBox) self.finishTime_lineEdit.setObjectName(u"finishTime_lineEdit") self.formLayout.setWidget(5, QFormLayout.FieldRole, self.finishTime_lineEdit) self.label1 = QLabel(self.configGroupBox) self.label1.setObjectName(u"label1") self.formLayout.setWidget(6, QFormLayout.LabelRole, self.label1) self.horizontalLayout = QHBoxLayout() self.horizontalLayout.setObjectName(u"horizontalLayout") self.lineEditOutputDirectory = QLineEdit(self.configGroupBox) self.lineEditOutputDirectory.setObjectName(u"lineEditOutputDirectory") self.horizontalLayout.addWidget(self.lineEditOutputDirectory) self.pushButtonOutputDirectory = QPushButton(self.configGroupBox) self.pushButtonOutputDirectory.setObjectName(u"pushButtonOutputDirectory") self.horizontalLayout.addWidget(self.pushButtonOutputDirectory) self.formLayout.setLayout(6, QFormLayout.FieldRole, self.horizontalLayout) self.label_5 = QLabel(self.configGroupBox) self.label_5.setObjectName(u"label_5") self.formLayout.setWidget(2, QFormLayout.LabelRole, self.label_5) self.comboBoxExportType = QComboBox(self.configGroupBox) self.comboBoxExportType.addItem("") self.comboBoxExportType.addItem("") self.comboBoxExportType.setObjectName(u"comboBoxExportType") self.formLayout.setWidget(2, QFormLayout.FieldRole, self.comboBoxExportType) self.gridLayout.addWidget(self.configGroupBox, 0, 0, 1, 1) self.buttonBox = QDialogButtonBox(ConfigureDialog) self.buttonBox.setObjectName(u"buttonBox") self.buttonBox.setOrientation(Qt.Horizontal) self.buttonBox.setStandardButtons(QDialogButtonBox.Cancel|QDialogButtonBox.Ok) self.gridLayout.addWidget(self.buttonBox, 1, 0, 1, 1) QWidget.setTabOrder(self.lineEditIdentifier, self.prefix_lineEdit) QWidget.setTabOrder(self.prefix_lineEdit, self.comboBoxExportType) QWidget.setTabOrder(self.comboBoxExportType, self.timeSteps_lineEdit) QWidget.setTabOrder(self.timeSteps_lineEdit, self.initialTime_lineEdit) QWidget.setTabOrder(self.initialTime_lineEdit, self.finishTime_lineEdit) QWidget.setTabOrder(self.finishTime_lineEdit, self.lineEditOutputDirectory) QWidget.setTabOrder(self.lineEditOutputDirectory, self.pushButtonOutputDirectory) self.retranslateUi(ConfigureDialog) self.buttonBox.accepted.connect(ConfigureDialog.accept) self.buttonBox.rejected.connect(ConfigureDialog.reject) self.comboBoxExportType.setCurrentIndex(0) QMetaObject.connectSlotsByName(ConfigureDialog) # setupUi def retranslateUi(self, ConfigureDialog): ConfigureDialog.setWindowTitle(QCoreApplication.translate("ConfigureDialog", u"Configure Step", None)) self.configGroupBox.setTitle("") self.label0.setText(QCoreApplication.translate("ConfigureDialog", u"identifier: ", None)) self.label_3.setText(QCoreApplication.translate("ConfigureDialog", u"Prefix : ", None)) self.label_4.setText(QCoreApplication.translate("ConfigureDialog", u"Time Steps : ", None)) self.label.setText(QCoreApplication.translate("ConfigureDialog", u"Initial Time : ", None)) self.label_2.setText(QCoreApplication.translate("ConfigureDialog", u"Finish Time : ", None)) self.label1.setText(QCoreApplication.translate("ConfigureDialog", u"Output directory:", None)) self.pushButtonOutputDirectory.setText(QCoreApplication.translate("ConfigureDialog", u"...", None)) self.label_5.setText(QCoreApplication.translate("ConfigureDialog", u"Export type:", None)) self.comboBoxExportType.setItemText(0, QCoreApplication.translate("ConfigureDialog", u"webgl", None)) self.comboBoxExportType.setItemText(1, QCoreApplication.translate("ConfigureDialog", u"thumbnail", None)) # retranslateUi

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null

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null

0

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fe6de4a21365edf7ffd30ec000387c588b119366

9,086

py

Python

equipments/migrations/0001_initial.py

fagrimacs/fagrimacs_production

ea1a8f92c41c416309cc1fdd8deb02f41a9c95a0

[ "MIT" ]

null

equipments/migrations/0001_initial.py

fagrimacs/fagrimacs_production

ea1a8f92c41c416309cc1fdd8deb02f41a9c95a0

[ "MIT" ]

8

2020-09-16T05:28:33.000Z

2020-09-28T06:29:03.000Z

equipments/migrations/0001_initial.py

fagrimacs/fagrimacs_production

ea1a8f92c41c416309cc1fdd8deb02f41a9c95a0

[ "MIT" ]

null

# Generated by Django 3.0.7 on 2020-09-18 05:52 from django.conf import settings from django.db import migrations, models import django.db.models.deletion import multiselectfield.db.fields class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Equipment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('type', models.CharField(choices=[(None, 'Please select'), ('tractor', 'Tractor'), ('implement', 'Implement'), ('other_equipment', 'Other Equipment')], max_length=100, verbose_name='What Equipment you want to Add?')), ], ), migrations.CreateModel( name='ImplementCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('image', models.ImageField(upload_to='implements_category')), ], options={ 'verbose_name_plural': 'Implement Categories', }, ), migrations.CreateModel( name='Phone', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('phone', models.CharField(max_length=18)), ], ), migrations.CreateModel( name='TractorCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('image', models.ImageField(upload_to='tractor_category')), ], options={ 'verbose_name_plural': 'Tractor Categories', }, ), migrations.CreateModel( name='Tractor', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created', models.DateTimeField(auto_now_add=True)), ('modified', models.DateTimeField(auto_now=True)), ('drive_type', models.CharField(choices=[(None, 'Please Select'), ('two wheel drive', 'Two wheel Drive'), ('four wheel drive', 'Four wheel Drive')], max_length=100, verbose_name='What Drive Type')), ('name', models.CharField(help_text='eg. John Deere 6190R', max_length=200, verbose_name='Name/Models of Tractor')), ('mode_of_transmission', models.CharField(choices=[(None, 'Please Select'), ('gear', 'Gear'), ('manual', 'Manual'), ('hydrostatic', 'Hydrostatic'), ('turbochanged', 'Turbocharged')], max_length=100, verbose_name='Mode of Transmission')), ('engine_hp', models.PositiveIntegerField(verbose_name='Engine Horse Power (eg. 75hp)')), ('drawbar_hp', models.PositiveIntegerField(verbose_name='Drawbar Horse Power (eg. 65hp)')), ('pto_hp', models.PositiveIntegerField(verbose_name='PTO Horse Power (eg. 85hp)')), ('hydraulic_capacity', models.CharField(help_text='Use a SI units of gpm or psi', max_length=100, verbose_name='Hydaulic capacity (gallon per minutes(gpm) or psi-pound per square inchies)')), ('type_of_hitching', models.CharField(choices=[(None, 'Please Select'), ('two point hitches', 'Two-point hitches'), ('three point hitches', 'Three-point hitches')], max_length=100, verbose_name='What is Hitching type?')), ('cab', models.BooleanField(default=False, verbose_name='Does have a cab?')), ('rollover_protection', models.BooleanField(default=False, verbose_name='Does have the rollover protection?')), ('fuel_consumption', models.PositiveIntegerField(verbose_name='Fuel consumption (gallon per hour on operation)')), ('attachment_mode', models.CharField(choices=[(None, 'Please select'), ('frontend loader', 'frontend loader'), ('backhoe', 'Backhoe'), ('both', 'Both')], max_length=100, verbose_name='What mode of attachment?')), ('operator', models.BooleanField(default=False, verbose_name='Do you have an operator(s)?')), ('file', models.FileField(help_text='Upload quality picture of real tractor you have, only 5 picture.', upload_to='tractors_photos/', verbose_name='Upload the Tractor pictures')), ('other_informations', models.TextField(blank=True, verbose_name='Describe your Tractor')), ('price_hour', models.PositiveIntegerField(verbose_name='Specify the price per Hour in TShs.')), ('price_hectare', models.PositiveIntegerField(verbose_name='Specify the price per Hectare')), ('farm_services', multiselectfield.db.fields.MultiSelectField(choices=[('soil cultivations', 'Soil cultivations'), ('planting', 'Planting'), ('haversting/post-haversting', 'Haversting/Post-Haversting'), ('fertilizing & pest-control', 'Fertilizing & Pest-control'), ('drainage & irrigation', 'Drainage & Irrigation'), ('loading', 'Loading'), ('hay making', 'Hay making'), ('miscellaneous', 'Miscellaneous')], max_length=135, verbose_name='What are farming service(s) do you offer?')), ('agree_terms', models.BooleanField(default=False, verbose_name='Do your Accept our Terms and Conditions?')), ('status', models.CharField(choices=[('pending', 'Pending'), ('approved', 'Approved')], default='pending', max_length=100)), ('tractor_type', models.ForeignKey(on_delete=models.SET('others'), to='equipments.TractorCategory', verbose_name='What type of Tractor?')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='ImplementSubCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='equipments.ImplementCategory')), ], options={ 'verbose_name_plural': 'Implement Subcategories', }, ), migrations.CreateModel( name='Implement', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created', models.DateTimeField(auto_now_add=True)), ('modified', models.DateTimeField(auto_now=True)), ('name', models.CharField(max_length=100, verbose_name='Name/Models of Implement')), ('width', models.PositiveIntegerField(help_text='SI UNITS in metre', verbose_name='Width of the Implement')), ('weight', models.PositiveIntegerField(help_text='SI UNITS in KG', verbose_name='Weight of the Implement')), ('operation_mode', models.CharField(choices=[(None, 'Please Select'), ('tractor drive', 'Tractor drive'), ('self-propelled', 'Self-propelled')], max_length=100, verbose_name='What is mode of operation?')), ('pto', models.PositiveIntegerField(verbose_name='What is Horse Power required for Operation?')), ('hydraulic_capacity', models.CharField(max_length=100, verbose_name='What is Hydaulic capacity required to lift?')), ('operator', models.BooleanField(verbose_name='Do you have an operator(s)?')), ('file', models.FileField(help_text='Upload quality picture of real implement you have, only 5 pictures.', upload_to='implements_photos/', verbose_name='Upload the Implement pictures')), ('other_informations', models.TextField(blank=True, verbose_name='Describe your Implement')), ('price_hour', models.PositiveIntegerField(verbose_name='Specify the price per Hour')), ('price_hectare', models.PositiveIntegerField(verbose_name='Specify the price per Hectare')), ('agree_terms', models.BooleanField(default=False, verbose_name='Do your Accept our Terms and Conditions?')), ('status', models.CharField(choices=[('pending', 'Pending'), ('approved', 'Approved')], default='pending', max_length=100)), ('category', models.ForeignKey(on_delete=models.SET('others'), to='equipments.ImplementCategory', verbose_name='What category of your Implement')), ('subcategory', models.ForeignKey(on_delete=models.SET('others'), to='equipments.ImplementSubCategory', verbose_name='What is subcategory of your Implement')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

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0

0.010819

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9,086

119

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0

null

0

1

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null

0

1

fe70b613f1b25d8770820b6d2050c23b8fcae093

47,242

py

Python

gralog-fx/src/main/java/gralog/gralogfx/piping/scripts/Gralog.py

gralog/gralog

0ab2e3137b83950cdc4e9234d4df451a22034285

[ "Apache-2.0", "BSD-3-Clause" ]

12

2016-11-11T13:24:48.000Z

2022-01-27T19:49:36.000Z

gralog-fx/src/main/java/gralog/gralogfx/piping/scripts/Gralog.py

gralog/gralog

0ab2e3137b83950cdc4e9234d4df451a22034285

[ "Apache-2.0", "BSD-3-Clause" ]

6

2017-01-05T14:23:59.000Z

2018-09-20T19:14:57.000Z

gralog-fx/src/main/java/gralog/gralogfx/piping/scripts/Gralog.py

gralog/gralog

0ab2e3137b83950cdc4e9234d4df451a22034285

[ "Apache-2.0", "BSD-3-Clause" ]

2

2019-11-25T18:17:00.000Z

2020-06-04T21:38:50.000Z

#!/usr/bin/env python3 import sys from random import randint import os try: import networkx as nx except: print("gPrint#-1#" + "netwrokx not installed for " + sys.executable) sys.stdout.flush() try: import igraph as ig except: print("gPrint#-1#" + "igraph not installed for " + sys.executable) import xml.etree.cElementTree as ET import math # debugging = False class Vertex: def __init__(self, graph, vid): self.sourced = False self.id = int(vid) self.graph = graph self.properties = dict() self.properties["id"] = None self.properties["label"] = None self.properties["color"] = None self.properties["strokeColor"] = None self.properties["shape"] = None self.properties["coordinates"] = None self.incomingEdges = [] self.outgoingEdges = [] self.incidentEdges = [] self.wasSourced = False def sourceProperties(self, stringFromGralog): self.sourced = True strings = stringFromGralog.split("#") for string in strings: propVal = string.split("=") valueType = "" try: prop = propVal[0] valueType = propVal[1] except: pass try: valueType = valueType.split("|") val = valueType[0] typ = valueType[1] castedValue = self.graph.castValueToType(val, typ) self.properties[prop] = castedValue except: pass def getId(self): return self.id def getLabel(self): if not self.wasSourced: self.source() return self.properties["label"] def setLabel(self, label): label = str(label) self.properties["label"] = label self.graph.setVertexLabel(self.id, label) def setCoordinates(self, coordinates): co = self.properties["coordinates"] x = coordinates[0] y = coordinates[1] if co == None: co = (None, None) if x == None: x = co[0] if y == None: y = co[1] newCoordinates = (x, y) self.properties["coordinates"] = newCoordinates self.graph.setVertexCoordinates(self.id, newCoordinates) def setFillColor(self, colorHex=-1, colorRGB=-1): self.setColor(colorHex, colorRGB) def getFillColor(self): return self.getColor() def getColor(self): if not self.wasSourced: self.source() return self.properties["color"] def setColor(self, colorHex=-1, colorRGB=-1): if colorHex != -1: self.properties["fillColor"] = colorHex elif colorRGB != -1: self.properties["fillColor"] = colorRGB else: return self.graph.setVertexFillColor(self.id, colorHex, colorRGB) def setStrokeColor(self, colorHex=-1, colorRGB=-1): if colorHex != -1: self.properties["strokeColor"] = colorHex elif colorRGB != -1: self.properties["strokeColor"] = colorRGB else: return self.graph.setVertexStrokeColor(self.id, colorHex, colorRGB) def getStrokeColor(self): if not self.sourced: self.source() return self.properties["strokeColor"] def setRadius(self, radius): self.properties["radius"] = radius self.properties["width"] = radius self.properties["height"] = radius self.graph.setVertexRadius(self.id, radius) def setWidth(self, width): self.properties["width"] = width self.graph.setVertexWidth(self.getId(), width) def setHeight(self, height): self.properties["height"] = height self.graph.setVertexHeight(self.getId(), height) def setShape(self, shape): self.properties["shape"] = shape self.graph.setVertexShape(self.id, shape) def setProperty(self, otherProperty, value): self.properties[otherProperty] = value self.graph.setVertexProperty(self.id, otherProperty, value) def getProperty(self, otherProperty): if not self.sourced: self.source() return self.properties[otherProperty] def get(self, prop): if not self.sourced: self.source() return self.properties[prop] def getNeighbours(self): return self.graph.getNeighbours(self.id) def getOutgoingNeighbours(self): return self.graph.getOutgoingNeighbours(self.id) def getIncomingNeighbours(self): return self.graph.getIncomingNeighbours(self.id) def getOutgoingEdges(self): return self.graph.getOutgoingEdges(self.id) def getIncomingEdges(self): return self.graph.getIncomingEdges(self.id) def getIncidentEdges(self): return self.graph.getIncidentEdges(self.id) def delete(self): return self.graph.deleteVertex(self) def connect(self, v1, edgeId=-1): return self.graph.addEdge(self, v1, edgeId) def getAllEdgesBetween(self, vertex2): return self.graph.getAllEdgesBetween((self.id, vertex2)) def source(self): return self.graph.getVertex(self) def __str__(self): return str(self.getId()) # what if i want to get a vertex? should i also get all its neighbours? how about incident edges? This is all v aufw\"andig and leads to the paradigm by which we just store the grpah in python??? class Edge: # private methods def __init__(self, graph, eid): self.sourced = False self.id = int(eid) #if -2, then imported without id like in TGF self.graph = graph self.properties = dict() self.properties["id"] = None self.properties["label"] = None self.properties["color"] = None self.properties["weight"] = None self.properties["contour"] = None self.properties["source"] = None self.properties["target"] = None self.wasSourced = False def sourceProperties(self, stringFromGralog): self.sourced = True strings = stringFromGralog.split("#") for string in strings: propVal = string.split("=") try: prop = propVal[0] valueType = propVal[1] valueType = valueType.split("|") val = valueType[0] typ = valueType[1] self.properties[prop] = self.graph.castValueToType(val, typ) except: pass def setTarget(self, target): # don't use!! self.properties["target"] = target def setSource(self, source): self.properties["source"] = source # public methods def getId(self): return self.id def setLabel(self, label): label = str(label) self.properties["label"] = label self.graph.setEdgeLabel(self.id, label) def getLabel(self): if not self.sourced: self.source() return self.properties["label"] def setColor(self, colorHex=-1, colorRGB=-1): if colorHex != -1: self.properties["color"] = colorHex elif colorRGB != -1: self.properties["color"] = colorRGB else: return self.graph.setEdgeColor(self.id, colorHex, colorRGB) def getColor(self): if not self.sourced: self.source() return self.properties["color"] def setWeight(self, weight): self.properties["weight"] = float(weight) self.graph.setEdgeWeight(self.id, weight) def getWeight(self): if not self.sourced: self.source() return self.properties["weight"] def setThickness(self, thickness): self.properties["thickness"] = float(thickness) self.graph.setEdgeThickness(self.id, thickness) def getThickness(self): if not self.sourced: self.source() return self.properties["thickness"] def setContour(self, contour): self.properties["contour"] = contour self.graph.setEdgeContour(self.id, contour) def getContour(self): if not self.sourced: self.source() return self.properties["contour"] def getSource(self): if not self.sourced: self.source() return self.properties["source"] def getTarget(self): if not self.sourced: self.source() return self.properties["target"] def setProperty(self, otherProperty, value): self.properties[otherProperty] = value self.graph.setEdgeProperty(self, otherProperty, value) def getProperty(self, otherProperty): if not self.sourced: self.source() return self.properties[otherProperty] def get(self, prop): self.source() return self.properties[prop] def delete(self): return self.graph.deleteEdge(self.id) def source(self): return self.graph.getEdge(self) def getAdjacentEdges(self): return self.graph.getAdjacentEdges(self.id) def __str__(self): v = self.getId() v_str = str(v) source = self.getSource().getId() target = self.getTarget().getId() return "({:},{:})".format(source, target) def rgbFormatter(colorRGB): r = colorRGB[0] g = colorRGB[1] b = colorRGB[2] s = "rgb" s += "(" + str(r).rstrip() + "," + \ str(g).rstrip() + "," + str(b).rstrip() + ")" return s.rstrip() def hexFormatter(colorHex): s = "hex" if colorHex[0] == "#": colorHex = colorHex[1:] s += "("+str(colorHex).rstrip() + ")" return s.rstrip() def vertexId(vertex): if isinstance(vertex, Vertex): return vertex.getId() return vertex def edgeId(edge): if isinstance(edge, Edge): return edge.getId() return edge def extractIdFromProperties(stringFromGralog): strings = stringFromGralog.split(",") for string in strings: propVal = string.split("=") if propVal[0] == "id": return propVal[1] return None def edgeSplitter(edge): if type(edge) == tuple and len(edge) == 2: # edge as defined by start, end nodes return str(vertexId(edge[0])).rstrip()+","+str(vertexId(edge[1])).rstrip() if type(edge) == int: # edge is given by id return str(edge).rstrip() return str(edge.getId()).rstrip()#edge has type Edge class Graph: def __init__(self, format="Undirected Graph"): # perform analysis of graph self.id_to_vertex = dict() self.id_to_edge = dict() self.lastIndex = -1 self.id = -1 self.variablesToTrack = dict() if format == None or format.lower() == "none": # we want a new graph print("useCurrentGraph") sys.stdout.flush() self.lastIndex = -1 self.id = sys.stdin.readline() self.getGraph("gtgf") else: print(format) sys.stdout.flush() self.id = sys.stdin.readline() # helper functions def castValueToType(self, val, typ): if typ == "float": return float(val) if typ == "int": return int(val) if typ == "bool": return bool(val) if typ == "string": return str(val) if typ == "vertex": return self.getVertexOrNew(val) return val def getVertexOrNew(self, currId): v = currId if (isinstance(currId, str)): currId = int(currId) if (isinstance(currId, int)): if currId in self.id_to_vertex: v=self.id_to_vertex[currId] else: v=Vertex(self, currId) self.id_to_vertex[currId] = v return v def getEdgeOrNew(self, currId): if type(currId) == tuple: e = self.getEdgeIdByEndpoints(currId) return e e = currId if not (isinstance(currId, Edge)): try: e = self.id_to_edge[int(currId)] except: e = Edge(self, currId) else: gPrint("Error (getEdgeOrNew()): the argument \ is neither an edge id nor a pair of vertices.") return e def termToEdge(self, term): endpoints = term.split(",") eid = int(endpoints[0]) e = self.id_to_edge[eid] e.sourceProperties(endpoints[0]) sourceId = int(endpoints[1]) source = self.getVertexOrNew(sourceId) targetId = int(endpoints[2]) target = self.getVertexOrNew(targetId) e.setSource(source) e.setTarget(target) return e def representsInt(s): try: int(s) return True except ValueError: return False def edgifyTGFCommand(self, line): line = line.strip() endpoints = line.split(" ") v1String = endpoints[0] v1 = self.getVertexOrNew(int(v1String)) v2String = endpoints[1] v2 = self.getVertexOrNew(int(v2String)) e = self.getEdgeOrNew(-2) e.setSource(v1) e.setTarget(v2) def vertexifyTGFCommand(self, line): line = line.strip() vString = line[0] v = self.getVertexOrNew(int(vString)) self.vertices[v.getId()] = v def edgifyGTGFCommand(self, line): line = line.strip() endpoints = line.split(" ") v1String = endpoints[0] v1 = self.getVertexOrNew(int(v1String)) v2String = endpoints[1] v2 = self.getVertexOrNew(int(v2String)) eid = int(endpoints[2]) e = self.getEdgeOrNew(eid) e.setSource(v1) e.setTarget(v2) self.id_to_edge[eid] = e def vertexifyGTGFCommand(self, line): self.vertexifyTGFCommand(line) def getEdgeIdByEndpoints(self, endpoints): line = "getEdgeIdByEndpoints#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(endpoints) print(line.rstrip()) sys.stdout.flush() edgeId = sys.stdin.readline().rstrip() return edgeId def getVertex(self, vertex): line = "getVertex#"+str(self.id).rstrip() + "#" line = line + str(vertex).rstrip() print (line.rstrip()) sys.stdout.flush() vertexTuple = sys.stdin.readline().rstrip() vertex.sourceProperties(vertexTuple) return vertex def getEdge(self, edge): line = "getEdge#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) print (line.rstrip()) sys.stdout.flush() edgeTuple = sys.stdin.readline().rstrip() edge.sourceProperties(edgeTuple) return edge # end helper functions # Graph Manipulating Functions def addVertex(self, vertexId=-1, pos=(None, None)): # return: Vertex object with id line = "addVertex#" + str(self.id).rstrip() x = -1 y = -1 vertexIdSwap = False if type(vertexId) == tuple and pos == (None, None): x = vertexId[0] y = vertexId[1] vertexId = -1 else: x = pos[0] y = pos[1] if vertexId != -1: line += "#"+str(vertexId).rstrip() if x != None and y != None: line += "#" + str(x).rstrip() + "#" + str(y).rstrip() print(line) sys.stdout.flush() vid = sys.stdin.readline() v = Vertex(self, vid) self.id_to_vertex[v.getId()] = v return v def deleteVertex(self, v): edges = self.getIncidentEdges(v) for e in edges: del self.id_to_edge[e.getId()] v = vertexId(v) del self.id_to_vertex[v] print("deleteVertex#" + str(self.id).rstrip() + "#" + str(v)) sys.stdout.flush() def addEdge(self, sourceVertex, targetVertex, edgeId = -1): # return: Edge object with id only sourceVertex = vertexId(sourceVertex) targetVertex = vertexId(targetVertex) idSubString = "" if not edgeId == -1: idSubString = "#"+str(edgeId) line = "addEdge#"+str(self.id).rstrip() + "#" + str(sourceVertex).rstrip() + \ "#" + str(targetVertex).rstrip() + idSubString.rstrip() print(line.rstrip()) sys.stdout.flush() eid = sys.stdin.readline() if eid != "\n": # it's possible that the edge cannot be added (e.g., a new selfloop) e = Edge(self, eid) self.id_to_edge[e.getId()] = e return e return None def existsEdge(self, edge): line = "existsEdge#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) print(line.rstrip()) sys.stdout.flush() thereExistsAnEdge = sys.stdin.readline().rstrip() return thereExistsAnEdge.lower() == "true" def existsVertex(self, vertex): line = "existsVertex#"+str(self.id).rstrip() + "#" line = line + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() thereExistsAVertex = sys.stdin.readline().rstrip() return thereExistsAVertex.lower() == "true" def deleteEdge(self, edge): del self.id_to_edge[edge.getId()] line = "deleteEdge#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) print(line.rstrip()) sys.stdout.flush() def getAllEdgesBetween(self, vertexPair): line = "getAllEdgesBetween#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(vertexPair) print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges # creates a random Erdos-Reny graph with n id_to_vertex and edge probability p def generateRandomGraph(self, vertexCount, p): if not isinstance(vertexCount, int): gPrint("Cannot generate a random graph, wrong parameter: \ vertex number must be an int.") if vertexCount < 0: gPrint("Cannot generate a random graph, wrong parameter: \ vertex number cannot be less than 0.") if not isinstance(p, float) or p < 0 or p > 1.0: gPrint("Cannot generate a random graph, wrong parameter: \ probability of an edge must be a float in [0,1].") if vertexCount == 0: return vertices = [] coordinates = dict() for id in range(vertexCount): coordinates[id] = (10*math.cos(2*id*math.pi/vertexCount), 10*math.sin(2*id*math.pi/vertexCount)) nxgraph = nx.fast_gnp_random_graph(vertexCount, p) d = dict() id = 0 for nxV in nxgraph.nodes(): d[id] = nxV id += 1 nxEdges = nxgraph.edges() id = 0 for x in range(vertexCount): vertices.append(self.addVertex(id, coordinates[id])) id += 1 for x in vertices: for y in vertices: if x.getId() < y.getId(): if (d[x.getId()], d[y.getId()]) in nxEdges: x.connect(y) # end manilupative functions # setter functions # begin: best for private use! def setVertexFillColor(self, vertex, colorHex=-1, colorRGB=-1): vertex = vertexId(vertex) line = "setVertexFillColor#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() + "#" if not (colorHex == -1): line = line + hexFormatter(str(colorHex)) elif not (colorRGB == -1): try: line = line + rgbFormatter(colorRGB) except: self.sendErrorToGralog("the rgb color: " + str(colorRGB).rstrip() + " is not properly formatted!") else: self.sendErrorToGralog("neither Hex nor RGB color specified!") print(line.rstrip()) sys.stdout.flush() def setVertexStrokeColor(self, vertex, colorHex=-1, colorRGB=-1): vertex = vertexId(vertex) # print("colorhex: " + str(colorHex)) line = "setVertexStrokeColor#"+str(self.id).rstrip() + "#" + str(vertex).rstrip() + "#" if not (colorHex == -1): line = line + hexFormatter(str(colorHex)) elif not (colorRGB == -1) and len(colorRGB) == 3: line = line + rgbFormatter(colorRGB) print(line.rstrip()) sys.stdout.flush() def setVertexCoordinates(self, vertex, coordinates): line = "setVertexCoordinates#" + str(self.id).rstrip()+"#" + str(vertexId(vertex)).rstrip() x = -1 y = -1 x = coordinates[0] y = coordinates[1] if x == None: x = "empty" if y == None: y = "empty" line += "#" + str(x).rstrip() + "#" + str(y).rstrip() print(line) sys.stdout.flush() def setEdgeContour(self, edge, contour): line = line = "setEdgeContour#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) line = line + "#" + str(contour).rstrip() print(line) sys.stdout.flush() def setEdgeColor(self, edge, colorHex=-1, colorRGB=-1): line = "setEdgeColor#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) line = line + "#" if not (colorHex == -1): line = line + hexFormatter(colorHex) elif not (colorRGB == -1) and len(colorRGB) == 3: line = line + rgbFormatter(colorRGB) print(line.rstrip()) sys.stdout.flush() def setVertexRadius(self, vertex, newRadius): self.setVertexDimension(vertex, newRadius, "radius") def setVertexHeight(self, vertex, newHeight): self.setVertexDimension(vertex, newHeight, "height") def setVertexWidth(self, vertex, newWidth): self.setVertexDimension(vertex, newWidth, "width") def setVertexDimension(self, vertex, newDimension, dimension): vertex = vertexId(vertex) line = "setVertexDimension#"+str(self.id).rstrip() + "#" + str(vertex).rstrip() + "#" + str(newDimension).rstrip()+"#" + dimension.rstrip() print(line.rstrip()) sys.stdout.flush() def setVertexShape(self, vertex, shape): vertex = vertexId(vertex) line = "setVertexShape#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() + "#" + str(shape).rstrip() print(line.rstrip()) sys.stdout.flush() def setEdgeWeight(self, edge, weight): self.setEdgeProperty(edge, "weight", weight) def setEdgeThickness(self, edge, thickness): self.setEdgeProperty(edge, "thickness", thickness) def setEdgeProperty(self, edge, propertyName, value): line = "setEdgeProperty#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) line = line + "#" + propertyName.rstrip().lower() + "#" + str(value).rstrip().lower() print(line.rstrip()) sys.stdout.flush() def setVertexProperty(self, vertex, propertyName, value): line = "setVertexProperty#"+str(self.id).rstrip() + "#" line = line + str(vertexId(vertex)).rstrip() line = line + "#" + propertyName.rstrip().lower() + "#" + str(value).rstrip().lower() print(line.rstrip()) sys.stdout.flush() def setEdgeLabel(self, edge, label): line = "setEdgeLabel#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) line = line + "#" + label print(line.rstrip()) sys.stdout.flush() def setVertexLabel(self, vertex, label): vertex = vertexId(vertex) line = "setVertexLabel#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() + "#" + label print(line.rstrip()) sys.stdout.flush() # end: best for private use! def setGraph(self, graphFormat, graphString = "hello_world"): graphFormat = graphFormat.lower() line = "setGraph#"+str(self.id).rstrip() + "#" + graphFormat.rstrip()+"#" if graphFormat == "gtgf" or graphFormat == "tgf": line += "$$\n" line += graphString if graphFormat == "gtgf" or graphFormat == "tgf": line += "$\n" print(line) sys.stdout.flush() # TODO: implement this # end setter functions # getter functions def toIgraph(self): grlgML_file = open("tmp.graphml", "w") grlgML_file.write(self.toXml()) grlgML_file.close() g_ig = ig.Graph.Read_GraphML("tmp.graphml") os.remove("tmp.graphml") return g_ig def toNx(self): grlgML_file = open("tmp.graphml", "w") grlgML_file.write(self.toXml()) grlgML_file.close() g_nx = nx.read_graphml("tmp.graphml") os.remove("tmp.graphml") return g_nx def toElementTree(self): grlgML_file = open("tmp.graphml", "w") grlgML_file.write(self.toXml()) grlgML_file.close() g_ET = ET.parse("tmp.graphml") os.remove("tmp.graphml") return g_ET def toXml(self): return self.getGraph("xml") def getGraph(self, graphFormat): # warning!! importing as pure TGF will mean edge id's will # be lost. This will result in errors on the Gralog side. line = "getGraph#"+str(self.id).rstrip() + "#" + graphFormat.rstrip() print(line.rstrip()) i = 0 sys.stdout.flush() line = sys.stdin.readline() graphString = "" if graphFormat.lower() == "tgf" or graphFormat.lower() == "gtgf": tgf = graphFormat.lower() == "tgf" multiline = False first = False if line[0] == line[1] == '$': multiline = True if tgf: first = True line = sys.stdin.readline() hashtagSeen = False if not multiline: return graphString while line[0] != '$': # gPrint("line: " + line +" and line[0]: " + line[0] + " and line[0]!='$': " + str(line[0] != '$')) graphString += line if line[0] == '#': hashtagSeen = True else: if not first: if hashtagSeen: if tgf: self.edgifyTGFCommand(line) else: self.edgifyGTGFCommand(line) else: if tgf: self.vertexifyTGFCommand(line) else: self.vertexifyGTGFCommand(line) line = sys.stdin.readline() i += 1 first = False return graphString if graphFormat.lower() == "xml": return line def getAllVertices(self): # return: list of Vertex objects with id line = "getAllVertices#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() vertexIdStringList = (sys.stdin.readline()).split("#") vertexList = [] for vertexIdString in vertexIdStringList: if representsInt(vertexIdString): v = self.getVertexOrNew(vertexIdString) vertexList.append(v) return vertexList def getVertices(self): return(self.getAllVertices()) def getAllEdges(self): # return: list of fully sourced Edge objects with fully sourced endpoint Vertices line = "getAllEdges#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] if len(endpointList) == 1 and endpointList[-1] == "\n": endpointList = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges def getEdges(self): return(self.getAllEdges()) # start: best for private use! def getNeighbours(self, vertex): # return: list of Vertex objects with id vertex = vertexId(vertex) line = "getNeighbours#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() neighbourIdStringList = (sys.stdin.readline()).split("#") neighboursList = [] for neighbourIdString in neighbourIdStringList: if representsInt(neighbourIdString): v = self.getVertexOrNew(neighbourIdString) neighboursList.append(v) return neighboursList def getOutgoingNeighbours(self, vertex): # return: list of Vertex objects with id vertex = vertexId(vertex) line = "getOutgoingNeighbours#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() outgoingNeighbourIdStringList = (sys.stdin.readline()).split("#") outgoingNeighboursList = [] for outgoingNeighbourIdString in outgoingNeighbourIdStringList: if representsInt(outgoingNeighbourIdString): v = self.getVertexOrNew(outgoingNeighbourIdString) outgoingNeighboursList.append(v) return outgoingNeighboursList def getIncomingNeighbours(self, vertex): # return: list of Vertex objects with id vertex = vertexId(vertex) line = "getIncomingNeighbours#"+str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() incomingNeighbourIdStringList = (sys.stdin.readline()).split("#") incomingNeighboursList = [] for incomingNeighbourIdString in incomingNeighbourIdStringList: if representsInt(incomingNeighbourIdString): v = self.getVertexOrNew(incomingNeighbourIdString) incomingNeighboursList.append(v) return incomingNeighboursList def getIncidentEdges(self, vertex): # return: list of Edge objects with id's only vertex = vertexId(vertex) line = "getIncidentEdges#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges def getAdjacentEdges(self, edge): # return: list of Edge objects with id's only line = "getAdjacentEdges#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges def getOutgoingEdges(self, vertex): # return: list of Edge objects with id's only vertex = vertexId(vertex) line = "getOutgoingEdges#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges def getIncomingEdges(self, vertex): # return: list of Edge objects with id's only vertex = vertexId(vertex) line = "getIncomingEdges#" + str(self.id).rstrip() + "#" + str(vertex).rstrip() print(line.rstrip()) sys.stdout.flush() endpointList = sys.stdin.readline() endpointList = endpointList.split("#") edges = [] for i in range(len(endpointList)): term = endpointList[i].rstrip() term = term[1:-1] e = self.termToEdge(term) if e != None: edges.append(e) return edges def getEdgeWeight(self, edge): return self.getEdgeProperty(edge, "weight") def getEdgeLabel(self, edge): return self.getEdgeProperty(edge, "label") def getEdgeProperty(self, edge, prop): # internally: fill edge property dictionary # return: String representing queried property line = "getEdgeProperty#"+str(self.id).rstrip() + "#" line = line + edgeSplitter(edge) line = line + "#" + prop.rstrip().lower() print(line.rstrip()) sys.stdout.flush() edgeTuple = sys.stdin.readline().rstrip() edge.sourceProperties(edgeTuple) return edge.getProperty(prop) def getVertexProperty(self, vertex, prop): # internally: fill edge property dictionary # return: String representing queried property vid = vertexId(vertex) line = "getVertexProperty#"+str(self.id).rstrip() + "#" line = line + vid line = line + "#" + prop.rstrip().lower() print(line.rstrip()) sys.stdout.flush() vertexTuple = sys.stdin.readline().rstrip() vertex.sourceProperties(vertexTuple) return vertex.getProperty(prop) # end: best use privately! def requestVertex(self): line = "requestVertex#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() vid = sys.stdin.readline().rstrip() vertex = self.getVertexOrNew(vid) return vertex def requestRandomVertex(self): line = "requestRandomVertex#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() vid = sys.stdin.readline().rstrip() vertex = self.getVertexOrNew(vid) return vertex def requestEdge(self): line = "requestEdge#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() vid = sys.stdin.readline().rstrip() edge = self.getEdgeOrNew(vid) return edge def requestRandomEdge(self): line = "requestRandomEdge#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() eid = sys.stdin.readline().rstrip() edge = self.getEdgeOrNew(eid) return edge def requestInteger(self): line = "requestInteger#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() i = sys.stdin.readline().rstrip() return int(i) def requestFloat(self): line = "requestFloat#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() d = sys.stdin.readline().rstrip() return float(d) def requestString(self): line = "requestString#"+str(self.id).rstrip() print(line.rstrip()) sys.stdout.flush() st = sys.stdin.readline().rstrip() return str(st) # runtime changer functions def pauseUntilSpacePressed(self, *args): line = "pauseUntilSpacePressed" rank = None try: rank = int(args[0]) except: pass if len(args) > 0 and rank != None: rank = int(args[0]) args = args[1:] argString = "" if rank != None: argString += "#"+str(rank).rstrip() for key in sorted(self.variablesToTrack.keys()): term = "#("+str(key).rstrip()+"=" + \ str(self.variablesToTrack[key]).rstrip()+")" argString = argString + term.rstrip() for x in args: if len(x) != 2: argString = "#(syntax=pauseUntilSpacePressed((key, val)))" break if (type(x) == list): for each in x: term = "#("+"arrayyyy"+str(each[0])+"="+str(each[1])+")" argString = argString + term else: term = "#("+str(x[0])+"="+str(x[1])+")" argString = argString + term.rstrip() line = line + argString print(line) sys.stdout.flush() toSkip = sys.stdin.readline() def track(self, name, var): # ideally, something like this: self.variablesToTrack[name] = var # if this is a pointer, it will work # if it is an int or str, or some other non-reference type, it will not def unTrack(self, name): del self.variablesToTrack[name] def sendMessage(self, toSend): print(toSend) sys.stdout.flush() def message(self, message): print("message#"+str(self.id).rstrip() + "#"+str(message).rstrip()) sys.stdout.flush() def sendErrorToGralog(self, toSend): print("error#"+str(self.id).rstrip() + "#"+str(toSend).rstrip()) sys.stdout.flush() exit() def mistakeLine(self): print("wubbadubdub 3 men in a tub") sys.stdout.flush() sys.stdin.readline() def pause(self, *args): self.pauseUntilSpacePressed(*args) # end runtime changer functions def __str__(self): vertices = [str(v) for v in self.id_to_vertex] vertices.sort() edges = [str(e) for e in self.getEdges()] edges.sort() return "VERTICES: " + " ".join(vertices) + "\nEDGES: " + " ".join(edges) def gPrint(message): if not message: # empty: print nothing except the new line (hacked with \t; <space> doesn't work) print("gPrint#-1#" + "\t") sys.stdout.flush() else: message = str(message) lines = message.split('\n') for line in lines: print("gPrint#-1#" + line) sys.stdout.flush() def representsInt(s): try: int(s) return True except ValueError: return False

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fe759c78dfaceadf537006e1685f7155df52a71a

10,073

py

Python

vm_setup/pmevo/measurement-server/PITE/register_file.py

qcjiang/pmevo-artifact

bf5da1788f9ede42086c31b3996d9e41363cc7ee

[ "MIT" ]

6

2020-04-21T12:16:19.000Z

2022-02-10T09:18:08.000Z

vm_setup/pmevo/measurement-server/PITE/register_file.py

qcjiang/pmevo-artifact

bf5da1788f9ede42086c31b3996d9e41363cc7ee

[ "MIT" ]

1

2021-12-07T13:09:53.000Z

vm_setup/pmevo/measurement-server/PITE/register_file.py

qcjiang/pmevo-artifact

bf5da1788f9ede42086c31b3996d9e41363cc7ee

[ "MIT" ]

2

2021-03-30T12:40:01.000Z

2021-11-23T15:49:50.000Z

#! /usr/bin/env python3 # vim: et:ts=4:sw=4:fenc=utf-8 from abc import ABC, abstractmethod from collections import defaultdict import re class RegisterFile(ABC): registers = NotImplemented def __init__(self): # for each register kind an index pointing to the next register to use self.reset_indices() def reset_indices(self): self.next_indices = defaultdict(lambda:0) def get_memory_base(self): return self.registers["MEM"][0]["64"] def get_div_register(self): return self.registers["DIV"][0]["64"] def get_clobber_list(self): res = [] for k, v in self.registers.items(): for regset in v: reg = regset["repr"] if reg is not None: res.append(reg) return res class X86_64_RegisterFile(RegisterFile): registers = { "G": # general purpose registers [ # {"64": "rax", "32": "eax", "repr": "rax"}, # {"64": "rcx", "32": "ecx", "repr": "rcx"}, # {"64": "rdx", "32": "edx", "repr": "rdx"}, {"64": "rbx", "32": "ebx", "repr": "rbx"}, # used by gcc # {"64": "rsp", "32": "esp", "repr": "rsp"}, # used by gcc # {"64": "rbp", "32": "ebp", "repr": "rbp"}, # used by gcc {"64": "rsi", "32": "esi", "repr": "rsi"}, # used for string instructions {"64": "rdi", "32": "edi", "repr": "rdi"}, # used for string instructions {"64": "r8", "32": "r8d", "repr": "r8"}, {"64": "r9", "32": "r9d", "repr": "r9"}, {"64": "r10", "32": "r10d", "repr": "r10"}, {"64": "r11", "32": "r11d", "repr": "r11"}, {"64": "r12", "32": "r12d", "repr": "r12"}, # {"64": "r13", "32": "r13d", "repr": "r13"}, # used as divisor register # {"64": "r14", "32": "r14d", "repr": "r14"}, # used as memory register # {"64": "r15", "32": "r15d", "repr": "r15"}, # used by program frame ], "V": # vector registers [ {"256": "ymm0", "128": "xmm0", "repr": "ymm0"}, {"256": "ymm1", "128": "xmm1", "repr": "ymm1"}, {"256": "ymm2", "128": "xmm2", "repr": "ymm2"}, {"256": "ymm3", "128": "xmm3", "repr": "ymm3"}, {"256": "ymm4", "128": "xmm4", "repr": "ymm4"}, {"256": "ymm5", "128": "xmm5", "repr": "ymm5"}, {"256": "ymm6", "128": "xmm6", "repr": "ymm6"}, {"256": "ymm7", "128": "xmm7", "repr": "ymm7"}, {"256": "ymm8", "128": "xmm8", "repr": "ymm8"}, {"256": "ymm9", "128": "xmm9", "repr": "ymm9"}, {"256": "ymm10", "128": "xmm10", "repr": "ymm10"}, {"256": "ymm11", "128": "xmm11", "repr": "ymm11"}, {"256": "ymm12", "128": "xmm12", "repr": "ymm12"}, {"256": "ymm13", "128": "xmm13", "repr": "ymm13"}, {"256": "ymm14", "128": "xmm14", "repr": "ymm14"}, {"256": "ymm15", "128": "xmm15", "repr": "ymm15"}, ], "DIV": # register for non-zero divisor [ {"64": "r13", "32": "r13d", "repr": None}, # no need to represent this in the clobber list as it is # hardwired to a this register anyway ], "MEM": # base register for memory operands [ {"64": "r14", "32": "r14d", "repr": None} # no need to represent this in the clobber list as it is # hardwired to a this register anyway ], } def __init__(self): super().__init__() class AArch64_RegisterFile(RegisterFile): registers = { "G": # general puprose registers [ # {"64": "x0", "32": "w0", "repr": "x0"}, # used for frame # {"64": "x1", "32": "w1", "repr": "x1"}, # used for frame {"64": "x2", "32": "w2", "repr": "x2"}, {"64": "x3", "32": "w3", "repr": "x3"}, {"64": "x4", "32": "w4", "repr": "x4"}, {"64": "x5", "32": "w5", "repr": "x5"}, {"64": "x6", "32": "w6", "repr": "x6"}, {"64": "x7", "32": "w7", "repr": "x7"}, {"64": "x8", "32": "w8", "repr": "x8"}, {"64": "x9", "32": "w9", "repr": "x9"}, {"64": "x10", "32": "w10", "repr": "x10"}, {"64": "x11", "32": "w11", "repr": "x11"}, {"64": "x12", "32": "w12", "repr": "x12"}, {"64": "x13", "32": "w13", "repr": "x13"}, {"64": "x14", "32": "w14", "repr": "x14"}, {"64": "x15", "32": "w15", "repr": "x15"}, {"64": "x16", "32": "w16", "repr": "x16"}, {"64": "x17", "32": "w17", "repr": "x17"}, {"64": "x18", "32": "w18", "repr": "x18"}, {"64": "x19", "32": "w19", "repr": "x19"}, {"64": "x20", "32": "w20", "repr": "x20"}, {"64": "x21", "32": "w21", "repr": "x21"}, {"64": "x22", "32": "w22", "repr": "x22"}, {"64": "x23", "32": "w23", "repr": "x23"}, {"64": "x24", "32": "w24", "repr": "x24"}, {"64": "x25", "32": "w25", "repr": "x25"}, {"64": "x26", "32": "w26", "repr": "x26"}, {"64": "x27", "32": "w27", "repr": "x27"}, # {"64": "x28", "32": "w28", "repr": "x28"}, # used for memory # {"64": "x29", "32": "w29", "repr": "x29"}, # used for divisor # {"64": "x30", "32": "w30", "repr": "x30"}, # link register # {"64": "x31", "32": "w31", "repr": "x31"}, # zero/sp register ], "F": # vector/floating point registers [ {"VEC": "v0", "128": "q0", "64": "d0", "32": "s0", "16": "h0", "8": "b0", "repr": "v0"}, {"VEC": "v1", "128": "q1", "64": "d1", "32": "s1", "16": "h1", "8": "b1", "repr": "v1"}, {"VEC": "v2", "128": "q2", "64": "d2", "32": "s2", "16": "h2", "8": "b2", "repr": "v2"}, {"VEC": "v3", "128": "q3", "64": "d3", "32": "s3", "16": "h3", "8": "b3", "repr": "v3"}, {"VEC": "v4", "128": "q4", "64": "d4", "32": "s4", "16": "h4", "8": "b4", "repr": "v4"}, {"VEC": "v5", "128": "q5", "64": "d5", "32": "s5", "16": "h5", "8": "b5", "repr": "v5"}, {"VEC": "v6", "128": "q6", "64": "d6", "32": "s6", "16": "h6", "8": "b6", "repr": "v6"}, {"VEC": "v7", "128": "q7", "64": "d7", "32": "s7", "16": "h7", "8": "b7", "repr": "v7"}, {"VEC": "v8", "128": "q8", "64": "d8", "32": "s8", "16": "h8", "8": "b8", "repr": "v8"}, {"VEC": "v9", "128": "q9", "64": "d9", "32": "s9", "16": "h9", "8": "b9", "repr": "v9"}, {"VEC": "v10", "128": "q10", "64": "d10", "32": "s10", "16": "h10", "8": "b10", "repr": "v10"}, {"VEC": "v11", "128": "q11", "64": "d11", "32": "s11", "16": "h11", "8": "b11", "repr": "v11"}, {"VEC": "v12", "128": "q12", "64": "d12", "32": "s12", "16": "h12", "8": "b12", "repr": "v12"}, {"VEC": "v13", "128": "q13", "64": "d13", "32": "s13", "16": "h13", "8": "b13", "repr": "v13"}, {"VEC": "v14", "128": "q14", "64": "d14", "32": "s14", "16": "h14", "8": "b14", "repr": "v14"}, {"VEC": "v15", "128": "q15", "64": "d15", "32": "s15", "16": "h15", "8": "b15", "repr": "v15"}, {"VEC": "v16", "128": "q16", "64": "d16", "32": "s16", "16": "h16", "8": "b16", "repr": "v16"}, {"VEC": "v17", "128": "q17", "64": "d17", "32": "s17", "16": "h17", "8": "b17", "repr": "v17"}, {"VEC": "v18", "128": "q18", "64": "d18", "32": "s18", "16": "h18", "8": "b18", "repr": "v18"}, {"VEC": "v19", "128": "q19", "64": "d19", "32": "s19", "16": "h19", "8": "b19", "repr": "v19"}, {"VEC": "v20", "128": "q20", "64": "d20", "32": "s20", "16": "h20", "8": "b20", "repr": "v20"}, {"VEC": "v21", "128": "q21", "64": "d21", "32": "s21", "16": "h21", "8": "b21", "repr": "v21"}, {"VEC": "v22", "128": "q22", "64": "d22", "32": "s22", "16": "h22", "8": "b22", "repr": "v22"}, {"VEC": "v23", "128": "q23", "64": "d23", "32": "s23", "16": "h23", "8": "b23", "repr": "v23"}, {"VEC": "v24", "128": "q24", "64": "d24", "32": "s24", "16": "h24", "8": "b24", "repr": "v24"}, {"VEC": "v25", "128": "q25", "64": "d25", "32": "s25", "16": "h25", "8": "b25", "repr": "v25"}, {"VEC": "v26", "128": "q26", "64": "d26", "32": "s26", "16": "h26", "8": "b26", "repr": "v26"}, {"VEC": "v27", "128": "q27", "64": "d27", "32": "s27", "16": "h27", "8": "b27", "repr": "v27"}, {"VEC": "v28", "128": "q28", "64": "d28", "32": "s28", "16": "h28", "8": "b28", "repr": "v28"}, {"VEC": "v29", "128": "q29", "64": "d29", "32": "s29", "16": "h29", "8": "b29", "repr": "v29"}, {"VEC": "v30", "128": "q30", "64": "d30", "32": "s30", "16": "h30", "8": "b30", "repr": "v30"}, {"VEC": "v31", "128": "q31", "64": "d31", "32": "s31", "16": "h31", "8": "b31", "repr": "v31"}, ], "DIV": # register for non-zero divisor [ {"64": "x29", "32": "w29", "repr": None}, # no need to represent this in the clobber list as it is # hardwired to a this register anyway ], "MEM": # base register for memory operands [ {"64": "x28", "32": "w28", "repr": None}, # no need to represent this in the clobber list as it is # hardwired to a this register anyway ], } def __init__(self): super().__init__()

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fe79e20af0abaadf27ef0edd6010a9d9587df465

2,019

py

Python

test/test_basic_functions.py

azagajewski/ColiCoords

fa26e46971e24ff582c4d33331c5b8181f605c9f

[ "MIT" ]

18

2018-09-11T01:14:31.000Z

2021-12-27T10:21:59.000Z

test/test_basic_functions.py

azagajewski/ColiCoords

fa26e46971e24ff582c4d33331c5b8181f605c9f

[ "MIT" ]

77

2018-09-19T09:28:33.000Z

2021-11-12T13:31:50.000Z

test/test_basic_functions.py

azagajewski/ColiCoords

fa26e46971e24ff582c4d33331c5b8181f605c9f

[ "MIT" ]

8

2019-06-17T16:02:32.000Z

2021-06-30T23:31:17.000Z

import hashlib import unittest from colicoords.cell import Cell, CellList from colicoords.preprocess import data_to_cells from test import testcase from test.test_functions import load_testdata class DataTest(testcase.ArrayTestCase): def setUp(self): self.data = load_testdata('ds1') def test_data_slicing(self): sl1 = self.data[2:5, :, :] self.assertEqual(sl1.shape, (3, 512, 512)) sl2 = self.data[:, 20:40, 100:200] self.assertEqual(sl2.shape, (10, 20, 100)) def test_data_copy(self): m0 = self.data.binary_img.mean() data_copy = self.data.copy() self.assertEqual(m0, self.data.binary_img.mean()) data_copy.data_dict['binary'] += 20 self.assertEqual(m0, self.data.binary_img.mean()) self.assertEqual(data_copy.binary_img.mean(), m0 + 20) def _test_cell_list(self): #todo check order print(hashlib.md5(self.data).hexdigest()) cell_list = data_to_cells(self.data, initial_crop=2, cell_frac=0.5, rotate='binary') print(hashlib.md5(self.data).hexdigest()) cell_list = data_to_cells(self.data, initial_crop=2, cell_frac=0.5, rotate='binary') print(hashlib.md5(self.data).hexdigest()) d = self.data.copy() print(d == self.data) cl = CellList(cell_list) self.assertEqual(len(cl), 48) c5 = cl[5] self.assertIsInstance(c5, Cell) del cl[5] self.assertEqual(len(cl), 47) self.assertTrue(cl[3] in cl) cl.append(c5) self.assertTrue(c5 in cl) vol = cl.volume self.assertEqual(len(vol), 48) class CellListTest(testcase.ArrayTestCase): def setUp(self): data = load_testdata('ds1') self.cell_list = data_to_cells(data) def test_slicing(self): sliced = self.cell_list[:5] self.assertIsInstance(sliced, CellList) if __name__ == '__main__': unittest.main()

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0.081633

0

null

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null

0

1

0

1

fe7d3ca44a30c1b45cb010d74a7365ccccfb69bc

691

py

Python

app.py

aosjehdgus/transliteration

1934999385863009cdf9f8806e949157d653a9f4

[ "Apache-2.0" ]

null

app.py

aosjehdgus/transliteration

1934999385863009cdf9f8806e949157d653a9f4

[ "Apache-2.0" ]

null

app.py

aosjehdgus/transliteration

1934999385863009cdf9f8806e949157d653a9f4

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import os import sys import tensorflow as tf import numpy as np import data_utils from translate import Transliteration from flask import Flask, request, jsonify transliteration = Transliteration() app = Flask(__name__) # Flask 객체 선언, 파라미터로 어플리케이션 패키지의 이름을 넣어 준다. app.config['JSON_AS_ASCII'] = False # 한글 데이터 전송을 위해서 설정해 준다. @app.route("/transliterate", methods=['GET']) def transliterate(): input = request.args.get('input') output = transliteration.run(input) learned = transliteration.is_learned(input) print(input, learned) return jsonify(output) if __name__ == "__main__": app.run(debug = True, host='0.0.0.0', port=80, use_reloader=False)

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0.052632

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null

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null

0

1

0

1

fe7f812fda345139b99dd24f883eb46ae8bf8541

609

py

Python

cime/scripts/lib/CIME/XML/env_build.py

cbeall123/E3SM

ec32b40d549b292f14acd11e6774686564539d3c

[ "FTL", "zlib-acknowledgement", "RSA-MD" ]

1

2020-08-28T14:57:15.000Z

cime/scripts/lib/CIME/XML/env_build.py

cbeall123/E3SM

ec32b40d549b292f14acd11e6774686564539d3c

[ "FTL", "zlib-acknowledgement", "RSA-MD" ]

null

cime/scripts/lib/CIME/XML/env_build.py

cbeall123/E3SM

ec32b40d549b292f14acd11e6774686564539d3c

[ "FTL", "zlib-acknowledgement", "RSA-MD" ]

1

2021-03-11T23:20:58.000Z

""" Interface to the env_build.xml file. This class inherits from EnvBase """ from CIME.XML.standard_module_setup import * from CIME.XML.env_base import EnvBase logger = logging.getLogger(__name__) class EnvBuild(EnvBase): # pylint: disable=unused-argument def __init__(self, case_root=None, infile="env_build.xml",components=None): """ initialize an object interface to file env_build.xml in the case directory """ schema = os.path.join(get_cime_root(), "config", "xml_schemas", "env_entry_id.xsd") EnvBase.__init__(self, case_root, infile, schema=schema)

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null

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null

0

1

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1

fe87ead9a791db821c1f883b4076bac8b4dc4efb

99,064

py

Python

lib/XChemPANDDA.py

graeme-winter/XChemExplorer

7b0779387705ab37074d80f77baf22891eb56907

[ "MIT" ]

2

2018-03-11T08:38:43.000Z

2021-09-25T07:46:44.000Z

lib/XChemPANDDA.py

graeme-winter/XChemExplorer

7b0779387705ab37074d80f77baf22891eb56907

[ "MIT" ]

208

2017-06-30T10:32:12.000Z

2022-03-29T10:38:32.000Z

lib/XChemPANDDA.py

graeme-winter/XChemExplorer

7b0779387705ab37074d80f77baf22891eb56907

[ "MIT" ]

6

2017-06-01T20:33:31.000Z

2021-10-04T09:44:09.000Z

# last edited: 10/08/2017, 10:25 import os, sys, glob, subprocess from datetime import datetime from PyQt4 import QtGui, QtCore import math #from XChemUtils import mtztools import XChemDB import XChemRefine import XChemUtils import XChemLog import XChemToolTips import csv try: import gemmi import pandas except ImportError: pass #def get_names_of_current_clusters(xce_logfile,panddas_directory): # Logfile=XChemLog.updateLog(xce_logfile) # Logfile.insert('parsing {0!s}/cluster_analysis'.format(panddas_directory)) # os.chdir('{0!s}/cluster_analysis'.format(panddas_directory)) # cluster_dict={} # for out_dir in sorted(glob.glob('*')): # if os.path.isdir(out_dir): # cluster_dict[out_dir]=[] # found_first_pdb=False # for folder in glob.glob(os.path.join(out_dir,'pdbs','*')): # xtal=folder[folder.rfind('/')+1:] # if not found_first_pdb: # if os.path.isfile(os.path.join(panddas_directory,'cluster_analysis',out_dir,'pdbs',xtal,xtal+'.pdb') ): # cluster_dict[out_dir].append(os.path.join(panddas_directory,'cluster_analysis',out_dir,'pdbs',xtal,xtal+'.pdb')) # found_first_pdb=True # cluster_dict[out_dir].append(xtal) # return cluster_dict class export_and_refine_ligand_bound_models(QtCore.QThread): def __init__(self,PanDDA_directory,datasource,project_directory,xce_logfile,which_models): QtCore.QThread.__init__(self) self.PanDDA_directory = PanDDA_directory self.datasource = datasource self.db = XChemDB.data_source(self.datasource) self.Logfile = XChemLog.updateLog(xce_logfile) self.xce_logfile = xce_logfile self.project_directory = project_directory self.which_models=which_models self.external_software=XChemUtils.external_software(xce_logfile).check() # self.initial_model_directory=initial_model_directory # self.db.create_missing_columns() # self.db_list=self.db.get_empty_db_dict() # self.external_software=XChemUtils.external_software(xce_logfile).check() # self.xce_logfile=xce_logfile # self.already_exported_models=[] def run(self): self.Logfile.warning(XChemToolTips.pandda_export_ligand_bound_models_only_disclaimer()) # find all folders with *-pandda-model.pdb modelsDict = self.find_modeled_structures_and_timestamps() # if only NEW models shall be exported, check timestamps if not self.which_models.startswith('all'): modelsDict = self.find_new_models(modelsDict) # find pandda_inspect_events.csv and read in as pandas dataframe inspect_csv = None if os.path.isfile(os.path.join(self.PanDDA_directory,'analyses','pandda_inspect_events.csv')): inspect_csv = pandas.read_csv(os.path.join(self.PanDDA_directory,'analyses','pandda_inspect_events.csv')) progress = 0 try: progress_step = float(1/len(modelsDict)) except TypeError: self.Logfile.error('DID NOT FIND ANY MODELS TO EXPORT') return None for xtal in sorted(modelsDict): os.chdir(os.path.join(self.PanDDA_directory,'processed_datasets',xtal)) pandda_model = os.path.join('modelled_structures',xtal + '-pandda-model.pdb') pdb = gemmi.read_structure(pandda_model) # find out ligand event map relationship ligandDict = XChemUtils.pdbtools_gemmi(pandda_model).center_of_mass_ligand_dict('LIG') if ligandDict == {}: self.Logfile.error(xtal + ': cannot find ligand of type LIG; skipping...') continue self.show_ligands_in_model(xtal,ligandDict) emapLigandDict = self.find_ligands_matching_event_map(inspect_csv,xtal,ligandDict) self.Logfile.warning('emapLigandDict' + str(emapLigandDict)) # convert event map to SF self.event_map_to_sf(pdb.resolution,emapLigandDict) # move existing event maps in project directory to old folder self.move_old_event_to_backup_folder(xtal) # copy event MTZ to project directory self.copy_event_mtz_to_project_directory(xtal) # copy pandda-model to project directory self.copy_pandda_model_to_project_directory(xtal) # make map from MTZ and cut around ligand self.make_and_cut_map(xtal,emapLigandDict) # update database self.update_database(xtal,modelsDict) # refine models self.refine_exported_model(xtal) progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) def update_database(self,xtal,modelsDict): db_dict = {} timestamp_file = modelsDict[xtal] db_dict['DatePanDDAModelCreated'] = timestamp_file db_dict['RefinementOutcome'] = '3 - In Refinement' self.Logfile.insert('updating database for '+xtal+' setting time model was created to '+db_dict['DatePanDDAModelCreated']) self.db.update_data_source(xtal,db_dict) def make_and_cut_map(self,xtal,emapLigandDict): self.Logfile.insert('changing directory to ' + os.path.join(self.project_directory,xtal)) os.chdir(os.path.join(self.project_directory,xtal)) XChemUtils.pdbtools_gemmi(xtal + '-pandda-model.pdb').save_ligands_to_pdb('LIG') for ligID in emapLigandDict: m = emapLigandDict[ligID] emtz = m.replace('.ccp4','_' + ligID + '.mtz') emap = m.replace('.ccp4','_' + ligID + '.ccp4') XChemUtils.maptools().calculate_map(emtz,'FWT','PHWT') XChemUtils.maptools().cut_map_around_ligand(emap,ligID+'.pdb','7') if os.path.isfile(emap.replace('.ccp4','_mapmask.ccp4')): os.system('/bin/mv %s %s_%s_event.ccp4' %(emap.replace('.ccp4','_mapmask.ccp4'),xtal,ligID)) os.system('ln -s %s_%s_event.ccp4 %s_%s_event_cut.ccp4' %(xtal,ligID,xtal,ligID)) def copy_pandda_model_to_project_directory(self,xtal): os.chdir(os.path.join(self.project_directory,xtal)) model = os.path.join(self.PanDDA_directory,'processed_datasets',xtal,'modelled_structures',xtal+'-pandda-model.pdb') self.Logfile.insert('copying %s to project directory' %model) os.system('/bin/cp %s .' %model) def copy_event_mtz_to_project_directory(self,xtal): self.Logfile.insert('changing directory to ' + os.path.join(self.PanDDA_directory,'processed_datasets',xtal)) os.chdir(os.path.join(self.PanDDA_directory,'processed_datasets',xtal)) for emap in glob.glob('*-BDC_*.mtz'): self.Logfile.insert('copying %s to %s...' %(emap,os.path.join(self.project_directory,xtal))) os.system('/bin/cp %s %s' %(emap,os.path.join(self.project_directory,xtal))) def move_old_event_to_backup_folder(self,xtal): self.Logfile.insert('changing directory to ' + os.path.join(self.project_directory,xtal)) os.chdir(os.path.join(self.project_directory,xtal)) if not os.path.isdir('event_map_backup'): os.mkdir('event_map_backup') self.Logfile.insert('moving existing event maps to event_map_backup') for emap in glob.glob('*-BDC_*.ccp4'): os.system('/bin/mv %s event_map_backup/%s' %(emap,emap+'.'+str(datetime.now()).replace(' ','_').replace(':','-'))) def show_ligands_in_model(self,xtal,ligandDict): self.Logfile.insert(xtal + ': found the following ligands...') for lig in ligandDict: self.Logfile.insert(lig + ' -> coordinates ' + str(ligandDict[lig])) def find_modeled_structures_and_timestamps(self): self.Logfile.insert('finding out modelled structures in ' + self.PanDDA_directory) modelsDict={} for model in sorted(glob.glob(os.path.join(self.PanDDA_directory,'processed_datasets','*','modelled_structures','*-pandda-model.pdb'))): sample=model[model.rfind('/')+1:].replace('-pandda-model.pdb','') timestamp=datetime.fromtimestamp(os.path.getmtime(model)).strftime('%Y-%m-%d %H:%M:%S') self.Logfile.insert(sample+'-pandda-model.pdb was created on '+str(timestamp)) modelsDict[sample]=timestamp return modelsDict def find_new_models(self,modelsDict): samples_to_export = {} self.Logfile.hint('XCE will never export/ refine models that are "5-deposition ready" or "6-deposited"') self.Logfile.hint('Please change the RefinementOutcome flag in the Refinement table if you wish to re-export them') self.Logfile.insert('checking timestamps of models in database...') for xtal in modelsDict: timestamp_file = modelsDict[xtal] db_query=self.db.execute_statement("select DatePanDDAModelCreated from mainTable where CrystalName is '"+xtal+"' and (RefinementOutcome like '3%' or RefinementOutcome like '4%')") try: timestamp_db=str(db_query[0][0]) except IndexError: self.Logfile.warning('%s: database query gave no results for DatePanDDAModelCreated; skipping...' %xtal) self.Logfile.warning('%s: this might be a brand new model; will continue with export!' %xtal) samples_to_export[xtal]=timestamp_file timestamp_db = "2100-01-01 00:00:00" # some time in the future... try: difference=(datetime.strptime(timestamp_file,'%Y-%m-%d %H:%M:%S') - datetime.strptime(timestamp_db,'%Y-%m-%d %H:%M:%S') ) if difference.seconds != 0: self.Logfile.insert('exporting '+xtal+' -> was already refined, but newer PanDDA model available') samples_to_export[xtal]=timestamp_file else: self.Logfile.insert('%s: model has not changed since it was created on %s' %(xtal,timestamp_db)) except (ValueError, IndexError), e: self.Logfile.error(str(e)) return samples_to_export def event_map_to_sf(self,resolution,emapLigandDict): for lig in emapLigandDict: emap = emapLigandDict[lig] emtz = emap.replace('.ccp4','.mtz') emtz_ligand = emap.replace('.ccp4','_' + lig + '.mtz') self.Logfile.insert('trying to convert %s to SF -> %s' %(emap,emtz_ligand)) self.Logfile.insert('>>> ' + emtz) XChemUtils.maptools_gemmi(emap).map_to_sf(resolution) if os.path.isfile(emtz): os.system('/bin/mv %s %s' %(emtz,emtz_ligand)) self.Logfile.insert('success; %s exists' %emtz_ligand) else: self.Logfile.warning('something went wrong; %s could not be created...' %emtz_ligand) def find_ligands_matching_event_map(self,inspect_csv,xtal,ligandDict): emapLigandDict = {} for index, row in inspect_csv.iterrows(): if row['dtag'] == xtal: for emap in glob.glob('*-BDC_*.ccp4'): self.Logfile.insert('checking if event and ligand are within 7A of each other') x = float(row['x']) y = float(row['y']) z = float(row['z']) matching_ligand = self.calculate_distance_to_ligands(ligandDict,x,y,z) if matching_ligand is not None: emapLigandDict[matching_ligand] = emap self.Logfile.insert('found matching ligand (%s) for %s' %(matching_ligand,emap)) break else: self.Logfile.warning('current ligand not close to event...') if emapLigandDict == {}: self.Logfile.error('could not find ligands within 7A of PanDDA events') return emapLigandDict def calculate_distance_to_ligands(self,ligandDict,x,y,z): matching_ligand = None p_event = gemmi.Position(x, y, z) for ligand in ligandDict: c = ligandDict[ligand] p_ligand = gemmi.Position(c[0], c[1], c[2]) self.Logfile.insert('coordinates ligand: ' + str(c[0])+' '+ str(c[1])+' '+str(c[2])) self.Logfile.insert('coordinates event: ' + str(x)+' '+ str(y)+' '+str(z)) distance = p_event.dist(p_ligand) self.Logfile.insert('distance between ligand and event: %s A' %str(distance)) if distance < 7: matching_ligand = ligand break return matching_ligand def refine_exported_model(self,xtal): RefmacParams={ 'HKLIN': '', 'HKLOUT': '', 'XYZIN': '', 'XYZOUT': '', 'LIBIN': '', 'LIBOUT': '', 'TLSIN': '', 'TLSOUT': '', 'TLSADD': '', 'NCYCLES': '10', 'MATRIX_WEIGHT': 'AUTO', 'BREF': ' bref ISOT\n', 'TLS': '', 'NCS': '', 'TWIN': '', 'WATER': '', 'LIGOCC': '', 'SANITY': '' } if 'nocheck' in self.which_models: RefmacParams['SANITY'] = 'off' self.Logfile.insert('trying to refine ' + xtal + '...') self.Logfile.insert('%s: getting compound code from database' %xtal) query=self.db.execute_statement("select CompoundCode from mainTable where CrystalName='%s';" %xtal) compoundID=str(query[0][0]) self.Logfile.insert('%s: compounds code = %s' %(xtal,compoundID)) if os.path.isfile(os.path.join(self.project_directory,xtal,xtal+'.free.mtz')): if os.path.isfile(os.path.join(self.project_directory,xtal,xtal+'-pandda-model.pdb')): self.Logfile.insert('running inital refinement on PANDDA model of '+xtal) Serial=XChemRefine.GetSerial(self.project_directory,xtal) if not os.path.isdir(os.path.join(self.project_directory,xtal,'cootOut')): os.mkdir(os.path.join(self.project_directory,xtal,'cootOut')) # create folder for new refinement cycle if os.path.isdir(os.path.join(self.project_directory,xtal,'cootOut','Refine_'+str(Serial))): os.chdir(os.path.join(self.project_directory,xtal,'cootOut','Refine_'+str(Serial))) else: os.mkdir(os.path.join(self.project_directory,xtal,'cootOut','Refine_'+str(Serial))) os.chdir(os.path.join(self.project_directory,xtal,'cootOut','Refine_'+str(Serial))) os.system('/bin/cp %s in.pdb' %os.path.join(self.project_directory,xtal,xtal+'-pandda-model.pdb')) Refine=XChemRefine.Refine(self.project_directory,xtal,compoundID,self.datasource) Refine.RunBuster(str(Serial),RefmacParams,self.external_software,self.xce_logfile,None) else: self.Logfile.error('%s: cannot find %s-pandda-model.pdb; cannot start refinement...' %(xtal,xtal)) else: self.Logfile.error('%s: cannot start refinement because %s.free.mtz is missing in %s' % ( xtal, xtal, os.path.join(self.project_directory, xtal))) class refine_bound_state_with_buster(QtCore.QThread): def __init__(self,panddas_directory,datasource,initial_model_directory,xce_logfile,which_models): QtCore.QThread.__init__(self) self.panddas_directory=panddas_directory self.datasource=datasource self.initial_model_directory=initial_model_directory self.db=XChemDB.data_source(self.datasource) self.db.create_missing_columns() self.db_list=self.db.get_empty_db_dict() self.external_software=XChemUtils.external_software(xce_logfile).check() self.xce_logfile=xce_logfile self.Logfile=XChemLog.updateLog(xce_logfile) self.which_models=which_models self.already_exported_models=[] def run(self): samples_to_export=self.export_models() self.refine_exported_models(samples_to_export) def refine_exported_models(self,samples_to_export): self.Logfile.insert('will try to refine the following crystals:') for xtal in sorted(samples_to_export): self.Logfile.insert(xtal) for xtal in sorted(samples_to_export): self.Logfile.insert('%s: getting compound code from database' %xtal) query=self.db.execute_statement("select CompoundCode from mainTable where CrystalName='%s';" %xtal) compoundID=str(query[0][0]) self.Logfile.insert('%s: compounds code = %s' %(xtal,compoundID)) # compoundID=str(item[1]) if os.path.isfile(os.path.join(self.initial_model_directory,xtal,xtal+'.free.mtz')): if os.path.isfile(os.path.join(self.initial_model_directory,xtal,xtal+'-pandda-model.pdb')): self.Logfile.insert('running inital refinement on PANDDA model of '+xtal) Serial=XChemRefine.GetSerial(self.initial_model_directory,xtal) ####################################################### if not os.path.isdir(os.path.join(self.initial_model_directory,xtal,'cootOut')): os.mkdir(os.path.join(self.initial_model_directory,xtal,'cootOut')) # create folder for new refinement cycle if os.path.isdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))): os.chdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) else: os.mkdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) os.chdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) os.system('/bin/cp %s in.pdb' %os.path.join(self.initial_model_directory,xtal,xtal+'-pandda-model.pdb')) Refine=XChemRefine.Refine(self.initial_model_directory,xtal,compoundID,self.datasource) Refine.RunBuster(str(Serial),self.external_software,self.xce_logfile,None) else: self.Logfile.error('%s: cannot find %s-pandda-model.pdb; cannot start refinement...' %(xtal,xtal)) elif xtal in samples_to_export and not os.path.isfile( os.path.join(self.initial_model_directory, xtal, xtal + '.free.mtz')): self.Logfile.error('%s: cannot start refinement because %s.free.mtz is missing in %s' % ( xtal, xtal, os.path.join(self.initial_model_directory, xtal))) else: self.Logfile.insert('%s: nothing to refine' % (xtal)) def export_models(self): self.Logfile.insert('finding out which PanDDA models need to be exported') # first find which samples are in interesting datasets and have a model # and determine the timestamp fileModelsDict={} queryModels='' for model in glob.glob(os.path.join(self.panddas_directory,'processed_datasets','*','modelled_structures','*-pandda-model.pdb')): sample=model[model.rfind('/')+1:].replace('-pandda-model.pdb','') timestamp=datetime.fromtimestamp(os.path.getmtime(model)).strftime('%Y-%m-%d %H:%M:%S') self.Logfile.insert(sample+'-pandda-model.pdb was created on '+str(timestamp)) queryModels+="'"+sample+"'," fileModelsDict[sample]=timestamp # now get these models from the database and compare the datestamps # Note: only get the models that underwent some form of refinement, # because only if the model was updated in pandda.inspect will it be exported and refined dbModelsDict={} if queryModels != '': dbEntries=self.db.execute_statement("select CrystalName,DatePanDDAModelCreated from mainTable where CrystalName in ("+queryModels[:-1]+") and (RefinementOutcome like '3%' or RefinementOutcome like '4%' or RefinementOutcome like '5%')") for item in dbEntries: xtal=str(item[0]) timestamp=str(item[1]) dbModelsDict[xtal]=timestamp self.Logfile.insert('PanDDA model for '+xtal+' is in database and was created on '+str(timestamp)) # compare timestamps and only export the ones where the timestamp of the file is newer than the one in the DB samples_to_export={} self.Logfile.insert('checking which PanDDA models were newly created or updated') if self.which_models=='all': self.Logfile.insert('Note: you chose to export ALL available PanDDA!') for sample in fileModelsDict: if self.which_models=='all': self.Logfile.insert('exporting '+sample) samples_to_export[sample]=fileModelsDict[sample] else: if sample in dbModelsDict: try: difference=(datetime.strptime(fileModelsDict[sample],'%Y-%m-%d %H:%M:%S') - datetime.strptime(dbModelsDict[sample],'%Y-%m-%d %H:%M:%S') ) if difference.seconds != 0: self.Logfile.insert('exporting '+sample+' -> was already refined, but newer PanDDA model available') samples_to_export[sample]=fileModelsDict[sample] except ValueError: # this will be raised if timestamp is not properly formatted; # which will usually be the case when respective field in database is blank # these are hopefully legacy cases which are from before this extensive check was introduced (13/01/2017) advice = ( 'The pandda model of '+xtal+' was changed, but it was already refined! ' 'This is most likely because this was done with an older version of XCE. ' 'If you really want to export and refine this model, you need to open the database ' 'with DBbroweser (sqlitebrowser.org); then change the RefinementOutcome field ' 'of the respective sample to "2 - PANDDA model", save the database and repeat the export prodedure.' ) self.Logfile.insert(advice) else: self.Logfile.insert('exporting '+sample+' -> first time to be exported and refined') samples_to_export[sample]=fileModelsDict[sample] # update the DB: # set timestamp to current timestamp of file and set RefinementOutcome to '2-pandda...' if samples_to_export != {}: select_dir_string='' select_dir_string_new_pannda=' ' for sample in samples_to_export: self.Logfile.insert('changing directory to ' + os.path.join(self.initial_model_directory,sample)) os.chdir(os.path.join(self.initial_model_directory,sample)) self.Logfile.insert(sample + ': copying ' + os.path.join(self.panddas_directory,'processed_datasets',sample,'modelled_structures',sample+'-pandda-model.pdb')) os.system('/bin/cp %s .' %os.path.join(self.panddas_directory,'processed_datasets',sample,'modelled_structures',sample+'-pandda-model.pdb')) db_dict= {'RefinementOutcome': '2 - PANDDA model', 'DatePanDDAModelCreated': samples_to_export[sample]} for old_event_map in glob.glob('*-BDC_*.ccp4'): if not os.path.isdir('old_event_maps'): os.mkdir('old_event_maps') self.Logfile.warning(sample + ': moving ' + old_event_map + ' to old_event_maps folder') os.system('/bin/mv %s old_event_maps' %old_event_map) for event_map in glob.glob(os.path.join(self.panddas_directory,'processed_datasets',sample,'*-BDC_*.ccp4')): self.Logfile.insert(sample + ': copying ' + event_map) os.system('/bin/cp %s .' %event_map) select_dir_string+="select_dir={0!s} ".format(sample) select_dir_string_new_pannda+='{0!s} '.format(sample) self.Logfile.insert('updating database for '+sample+' setting time model was created to '+db_dict['DatePanDDAModelCreated']+' and RefinementOutcome to '+db_dict['RefinementOutcome']) self.db.update_data_source(sample,db_dict) return samples_to_export class run_pandda_export(QtCore.QThread): def __init__(self,panddas_directory,datasource,initial_model_directory,xce_logfile,update_datasource_only,which_models,pandda_params): QtCore.QThread.__init__(self) self.panddas_directory=panddas_directory self.datasource=datasource self.initial_model_directory=initial_model_directory self.db=XChemDB.data_source(self.datasource) self.db.create_missing_columns() self.db_list=self.db.get_empty_db_dict() self.external_software=XChemUtils.external_software(xce_logfile).check() self.xce_logfile=xce_logfile self.Logfile=XChemLog.updateLog(xce_logfile) self.update_datasource_only=update_datasource_only self.which_models=which_models self.already_exported_models=[] self.pandda_analyse_data_table = pandda_params['pandda_table'] self.RefmacParams={ 'HKLIN': '', 'HKLOUT': '', 'XYZIN': '', 'XYZOUT': '', 'LIBIN': '', 'LIBOUT': '', 'TLSIN': '', 'TLSOUT': '', 'TLSADD': '', 'NCYCLES': '10', 'MATRIX_WEIGHT': 'AUTO', 'BREF': ' bref ISOT\n', 'TLS': '', 'NCS': '', 'TWIN': '' } def run(self): # v1.3.8.2 - removed option to update database only # if not self.update_datasource_only: samples_to_export=self.export_models() self.import_samples_into_datasouce(samples_to_export) # if not self.update_datasource_only: self.refine_exported_models(samples_to_export) def refine_exported_models(self,samples_to_export): self.Logfile.insert('will try to refine the following crystals:') for xtal in samples_to_export: self.Logfile.insert(xtal) # sample_list=self.db.execute_statement("select CrystalName,CompoundCode from mainTable where RefinementOutcome='2 - PANDDA model';") # for item in sample_list: # xtal=str(item[0]) for xtal in sorted(samples_to_export): self.Logfile.insert('%s: getting compound code from database' %xtal) query=self.db.execute_statement("select CompoundCode from mainTable where CrystalName='%s';" %xtal) compoundID=str(query[0][0]) self.Logfile.insert('%s: compounds code = %s' %(xtal,compoundID)) # compoundID=str(item[1]) if os.path.isfile(os.path.join(self.initial_model_directory,xtal,xtal+'.free.mtz')): if os.path.isfile(os.path.join(self.initial_model_directory,xtal,xtal+'-ensemble-model.pdb')): self.Logfile.insert('running inital refinement on PANDDA model of '+xtal) Serial=XChemRefine.GetSerial(self.initial_model_directory,xtal) ####################################################### if not os.path.isdir(os.path.join(self.initial_model_directory,xtal,'cootOut')): os.mkdir(os.path.join(self.initial_model_directory,xtal,'cootOut')) # create folder for new refinement cycle if os.path.isdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))): os.chdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) try: os.system('/bin/rm *-ensemble-model.pdb *restraints*') except: self.Logfile.error("Restraint files didn't exist to remove. Will try to continue") else: os.mkdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) os.chdir(os.path.join(self.initial_model_directory,xtal,'cootOut','Refine_'+str(Serial))) Refine=XChemRefine.panddaRefine(self.initial_model_directory,xtal,compoundID,self.datasource) os.symlink(os.path.join(self.initial_model_directory,xtal,xtal+'-ensemble-model.pdb'),xtal+'-ensemble-model.pdb') Refine.RunQuickRefine(Serial,self.RefmacParams,self.external_software,self.xce_logfile,'pandda_refmac',None) # elif xtal in os.path.join(self.panddas_directory,'processed_datasets',xtal,'modelled_structures', # '{}-pandda-model.pdb'.format(xtal)): # self.Logfile.insert('{}: cannot start refinement because {}'.format(xtal,xtal) + # ' does not have a modelled structure. Check whether you expect this dataset to ' + # ' have a modelled structure, compare pandda.inspect and datasource,' # ' then tell XCHEMBB ') else: self.Logfile.error('%s: cannot find %s-ensemble-model.pdb; cannot start refinement...' %(xtal,xtal)) self.Logfile.error('Please check terminal window for any PanDDA related tracebacks') elif xtal in samples_to_export and not os.path.isfile( os.path.join(self.initial_model_directory, xtal, xtal + '.free.mtz')): self.Logfile.error('%s: cannot start refinement because %s.free.mtz is missing in %s' % ( xtal, xtal, os.path.join(self.initial_model_directory, xtal))) else: self.Logfile.insert('%s: nothing to refine' % (xtal)) def import_samples_into_datasouce(self,samples_to_export): # first make a note of all the datasets which were used in pandda directory os.chdir(os.path.join(self.panddas_directory,'processed_datasets')) for xtal in glob.glob('*'): self.db.execute_statement("update mainTable set DimplePANDDAwasRun = 'True',DimplePANDDAreject = 'False',DimplePANDDApath='{0!s}' where CrystalName is '{1!s}'".format(self.panddas_directory, xtal)) # do the same as before, but look for rejected datasets try: os.chdir(os.path.join(self.panddas_directory,'rejected_datasets')) for xtal in glob.glob('*'): self.db.execute_statement("update mainTable set DimplePANDDAwasRun = 'True',DimplePANDDAreject = 'True',DimplePANDDApath='{0!s}',DimplePANDDAhit = 'False' where CrystalName is '{1!s}'".format(self.panddas_directory, xtal)) except OSError: pass site_list = [] pandda_hit_list=[] with open(os.path.join(self.panddas_directory,'analyses','pandda_inspect_sites.csv'),'rb') as csv_import: csv_dict = csv.DictReader(csv_import) self.Logfile.insert('reding pandda_inspect_sites.csv') for i,line in enumerate(csv_dict): self.Logfile.insert(str(line).replace('\n','').replace('\r','')) site_index=line['site_idx'] name=line['Name'].replace("'","") comment=line['Comment'] site_list.append([site_index,name,comment]) self.Logfile.insert('add to site_list_:' + str([site_index,name,comment])) progress_step=1 for i,line in enumerate(open(os.path.join(self.panddas_directory,'analyses','pandda_inspect_events.csv'))): n_lines=i if n_lines != 0: progress_step=100/float(n_lines) else: progress_step=0 progress=0 self.emit(QtCore.SIGNAL('update_progress_bar'), progress) self.Logfile.insert('reading '+os.path.join(self.panddas_directory,'analyses','pandda_inspect_events.csv')) with open(os.path.join(self.panddas_directory,'analyses','pandda_inspect_events.csv'),'rb') as csv_import: csv_dict = csv.DictReader(csv_import) for i,line in enumerate(csv_dict): db_dict={} sampleID=line['dtag'] if sampleID not in samples_to_export: self.Logfile.warning('%s: not to be exported; will not add to panddaTable...' %sampleID) continue if sampleID not in pandda_hit_list: pandda_hit_list.append(sampleID) site_index=str(line['site_idx']).replace('.0','') event_index=str(line['event_idx']).replace('.0','') self.Logfile.insert(str(line)) self.Logfile.insert('reading {0!s} -> site {1!s} -> event {2!s}'.format(sampleID, site_index, event_index)) for entry in site_list: if entry[0]==site_index: site_name=entry[1] site_comment=entry[2] break # check if EVENT map exists in project directory event_map='' for file in glob.glob(os.path.join(self.initial_model_directory,sampleID,'*ccp4')): filename=file[file.rfind('/')+1:] if filename.startswith(sampleID+'-event_'+event_index) and filename.endswith('map.native.ccp4'): event_map=file self.Logfile.insert('found respective event maps in {0!s}: {1!s}'.format(self.initial_model_directory, event_map)) break # initial pandda model and mtz file pandda_model='' for file in glob.glob(os.path.join(self.initial_model_directory,sampleID,'*pdb')): filename=file[file.rfind('/')+1:] if filename.endswith('-ensemble-model.pdb'): pandda_model=file if sampleID not in self.already_exported_models: self.already_exported_models.append(sampleID) break inital_mtz='' for file in glob.glob(os.path.join(self.initial_model_directory,sampleID,'*mtz')): filename=file[file.rfind('/')+1:] if filename.endswith('pandda-input.mtz'): inital_mtz=file break db_dict['CrystalName'] = sampleID db_dict['PANDDApath'] = self.panddas_directory db_dict['PANDDA_site_index'] = site_index db_dict['PANDDA_site_name'] = site_name db_dict['PANDDA_site_comment'] = site_comment db_dict['PANDDA_site_event_index'] = event_index db_dict['PANDDA_site_event_comment'] = line['Comment'].replace("'","") db_dict['PANDDA_site_confidence'] = line['Ligand Confidence'] db_dict['PANDDA_site_InspectConfidence'] = line['Ligand Confidence'] db_dict['PANDDA_site_ligand_placed'] = line['Ligand Placed'] db_dict['PANDDA_site_viewed'] = line['Viewed'] db_dict['PANDDA_site_interesting'] = line['Interesting'] db_dict['PANDDA_site_z_peak'] = line['z_peak'] db_dict['PANDDA_site_x'] = line['x'] db_dict['PANDDA_site_y'] = line['y'] db_dict['PANDDA_site_z'] = line['z'] db_dict['PANDDA_site_ligand_id'] = '' db_dict['PANDDA_site_event_map'] = event_map db_dict['PANDDA_site_initial_model'] = pandda_model db_dict['PANDDA_site_initial_mtz'] = inital_mtz db_dict['PANDDA_site_spider_plot'] = '' # find apo structures which were used # XXX missing XXX self.db.update_insert_site_event_panddaTable(sampleID,db_dict) # this is necessary, otherwise RefinementOutcome will be reset for samples that are actually already in refinement self.db.execute_statement("update panddaTable set RefinementOutcome = '2 - PANDDA model' where CrystalName is '{0!s}' and RefinementOutcome is null".format(sampleID)) self.db.execute_statement("update mainTable set RefinementOutcome = '2 - PANDDA model' where CrystalName is '{0!s}' and (RefinementOutcome is null or RefinementOutcome is '1 - Analysis Pending')".format(sampleID)) self.db.execute_statement("update mainTable set DimplePANDDAhit = 'True' where CrystalName is '{0!s}'".format(sampleID)) progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) self.Logfile.insert('done reading pandda_inspect_sites.csv') # finally find all samples which do not have a pandda hit os.chdir(os.path.join(self.panddas_directory,'processed_datasets')) self.Logfile.insert('check which datasets are not interesting') # DimplePANDDAhit # for xtal in glob.glob('*'): # if xtal not in pandda_hit_list: # self.Logfile.insert(xtal+': not in interesting_datasets; updating database...') # self.db.execute_statement("update mainTable set DimplePANDDAhit = 'False' where CrystalName is '{0!s}'".format(xtal)) def export_models(self): self.Logfile.insert('finding out which PanDDA models need to be exported') # first find which samples are in interesting datasets and have a model # and determine the timestamp fileModelsDict={} queryModels='' for model in glob.glob(os.path.join(self.panddas_directory,'processed_datasets','*','modelled_structures','*-pandda-model.pdb')): sample=model[model.rfind('/')+1:].replace('-pandda-model.pdb','') timestamp=datetime.fromtimestamp(os.path.getmtime(model)).strftime('%Y-%m-%d %H:%M:%S') self.Logfile.insert(sample+'-pandda-model.pdb was created on '+str(timestamp)) queryModels+="'"+sample+"'," fileModelsDict[sample]=timestamp # now get these models from the database and compare the datestamps # Note: only get the models that underwent some form of refinement, # because only if the model was updated in pandda.inspect will it be exported and refined dbModelsDict={} if queryModels != '': dbEntries=self.db.execute_statement("select CrystalName,DatePanDDAModelCreated from mainTable where CrystalName in ("+queryModels[:-1]+") and (RefinementOutcome like '3%' or RefinementOutcome like '4%' or RefinementOutcome like '5%')") for item in dbEntries: xtal=str(item[0]) timestamp=str(item[1]) dbModelsDict[xtal]=timestamp self.Logfile.insert('PanDDA model for '+xtal+' is in database and was created on '+str(timestamp)) # compare timestamps and only export the ones where the timestamp of the file is newer than the one in the DB samples_to_export={} self.Logfile.insert('checking which PanDDA models were newly created or updated') if self.which_models=='all': self.Logfile.insert('Note: you chose to export ALL available PanDDA!') for sample in fileModelsDict: if self.which_models=='all': self.Logfile.insert('exporting '+sample) samples_to_export[sample]=fileModelsDict[sample] elif self.which_models == 'selected': for i in range(0, self.pandda_analyse_data_table.rowCount()): if str(self.pandda_analyse_data_table.item(i, 0).text()) == sample: if self.pandda_analyse_data_table.cellWidget(i, 1).isChecked(): self.Logfile.insert('Dataset selected by user -> exporting '+sample) samples_to_export[sample]=fileModelsDict[sample] break else: if sample in dbModelsDict: try: difference=(datetime.strptime(fileModelsDict[sample],'%Y-%m-%d %H:%M:%S') - datetime.strptime(dbModelsDict[sample],'%Y-%m-%d %H:%M:%S') ) if difference.seconds != 0: self.Logfile.insert('exporting '+sample+' -> was already refined, but newer PanDDA model available') samples_to_export[sample]=fileModelsDict[sample] except ValueError: # this will be raised if timestamp is not properly formatted; # which will usually be the case when respective field in database is blank # these are hopefully legacy cases which are from before this extensive check was introduced (13/01/2017) advice = ( 'The pandda model of '+xtal+' was changed, but it was already refined! ' 'This is most likely because this was done with an older version of XCE. ' 'If you really want to export and refine this model, you need to open the database ' 'with DBbroweser (sqlitebrowser.org); then change the RefinementOutcome field ' 'of the respective sample to "2 - PANDDA model", save the database and repeat the export prodedure.' ) self.Logfile.insert(advice) else: self.Logfile.insert('exporting '+sample+' -> first time to be exported and refined') samples_to_export[sample]=fileModelsDict[sample] # update the DB: # set timestamp to current timestamp of file and set RefinementOutcome to '2-pandda...' if samples_to_export != {}: select_dir_string='' select_dir_string_new_pannda=' ' for sample in samples_to_export: db_dict= {'RefinementOutcome': '2 - PANDDA model', 'DatePanDDAModelCreated': samples_to_export[sample]} select_dir_string+="select_dir={0!s} ".format(sample) select_dir_string_new_pannda+='{0!s} '.format(sample) self.Logfile.insert('updating database for '+sample+' setting time model was created to '+db_dict['DatePanDDAModelCreated']+' and RefinementOutcome to '+db_dict['RefinementOutcome']) self.db.update_data_source(sample,db_dict) if os.path.isdir(os.path.join(self.panddas_directory,'rejected_datasets')): Cmds = ( 'pandda.export' ' pandda_dir=%s' %self.panddas_directory+ ' export_dir={0!s}'.format(self.initial_model_directory)+ ' {0!s}'.format(select_dir_string)+ ' export_ligands=False' ' generate_occupancy_groupings=True\n' ) else: Cmds = ( 'source /dls/science/groups/i04-1/software/pandda-update/ccp4/ccp4-7.0/bin/ccp4.setup-sh\n' # 'source '+os.path.join(os.getenv('XChemExplorer_DIR'),'setup-scripts','pandda.setup-sh')+'\n' 'pandda.export' ' pandda_dir=%s' %self.panddas_directory+ ' export_dir={0!s}'.format(self.initial_model_directory)+ ' {0!s}'.format(select_dir_string_new_pannda)+ ' generate_restraints=True\n' ) self.Logfile.insert('running pandda.export with the following settings:\n'+Cmds) os.system(Cmds) return samples_to_export class run_pandda_analyse(QtCore.QThread): def __init__(self,pandda_params,xce_logfile,datasource): QtCore.QThread.__init__(self) self.data_directory=pandda_params['data_dir'] self.panddas_directory=pandda_params['out_dir'] self.submit_mode=pandda_params['submit_mode'] self.pandda_analyse_data_table = pandda_params['pandda_table'] self.nproc=pandda_params['nproc'] self.min_build_datasets=pandda_params['min_build_datasets'] self.pdb_style=pandda_params['pdb_style'] self.mtz_style=pandda_params['mtz_style'] self.sort_event=pandda_params['sort_event'] self.number_of_datasets=pandda_params['N_datasets'] self.max_new_datasets=pandda_params['max_new_datasets'] self.grid_spacing=pandda_params['grid_spacing'] self.reference_dir=pandda_params['reference_dir'] self.filter_pdb=os.path.join(self.reference_dir,pandda_params['filter_pdb']) self.wilson_scaling = pandda_params['perform_diffraction_data_scaling'] self.Logfile=XChemLog.updateLog(xce_logfile) self.datasource=datasource self.db=XChemDB.data_source(datasource) self.appendix=pandda_params['appendix'] self.write_mean_maps=pandda_params['write_mean_map'] self.calc_map_by = pandda_params['average_map'] self.select_ground_state_model='' projectDir = self.data_directory.replace('/*', '') self.make_ligand_links='$CCP4/bin/ccp4-python %s %s %s\n' %(os.path.join(os.getenv('XChemExplorer_DIR'), 'helpers', 'make_ligand_links_after_pandda.py') ,projectDir,self.panddas_directory) self.use_remote = pandda_params['use_remote'] self.remote_string = pandda_params['remote_string'] if self.appendix != '': self.panddas_directory=os.path.join(self.reference_dir,'pandda_'+self.appendix) if os.path.isdir(self.panddas_directory): os.system('/bin/rm -fr %s' %self.panddas_directory) os.mkdir(self.panddas_directory) if self.data_directory.startswith('/dls'): self.select_ground_state_model = 'module load ccp4\n' self.select_ground_state_model +='$CCP4/bin/ccp4-python %s %s\n' %(os.path.join(os.getenv('XChemExplorer_DIR'),'helpers','select_ground_state_dataset.py'),self.panddas_directory) self.make_ligand_links='' def run(self): # print self.reference_dir # print self.filter_pdb # how to run pandda.analyse on large datasets # # 1) Run the normal pandda command, with the new setting, e.g. # pandda.analyse data_dirs=... max_new_datasets=500 # This will do the analysis on the first 500 datasets and build the statistical maps - just as normal. # # 2) Run pandda with the same command: # pandda.analyse data_dirs=... max_new_datasets=500 # This will add 500 new datasets, and process them using the existing statistical maps # (this will be quicker than the original analysis). It will then merge the results of the two analyses. # # 3) Repeat 2) until you don't add any "new" datasets. Then you can build the models as normal. number_of_cyles=int(self.number_of_datasets)/int(self.max_new_datasets) if int(self.number_of_datasets) % int(self.max_new_datasets) != 0: # modulo gives remainder after integer division number_of_cyles+=1 self.Logfile.insert('will run %s rounds of pandda.analyse' %str(number_of_cyles)) if os.path.isfile(os.path.join(self.panddas_directory,'pandda.running')): self.Logfile.insert('it looks as if a pandda.analyse job is currently running in: '+self.panddas_directory) msg = ( 'there are three possibilities:\n' '1.) choose another PANDDA directory\n' '2.) - check if the job is really running either on the cluster (qstat) or on your local machine\n' ' - if so, be patient and wait until the job has finished\n' '3.) same as 2., but instead of waiting, kill the job and remove at least the pandda.running file\n' ' (or all the contents in the directory if you want to start from scratch)\n' ) self.Logfile.insert(msg) return None else: # if os.getenv('SHELL') == '/bin/tcsh' or os.getenv('SHELL') == '/bin/csh': # source_file=os.path.join(os.getenv('XChemExplorer_DIR'),'setup-scripts','pandda.setup-csh\n') # elif os.getenv('SHELL') == '/bin/bash' or self.use_remote: # source_file='export XChemExplorer_DIR="'+os.getenv('XChemExplorer_DIR')+'"\n' # source_file+='source %s\n' %os.path.join(os.getenv('XChemExplorer_DIR'),'setup-scripts','pandda.setup-sh\n') # else: # source_file='' # v1.2.1 - pandda.setup files should be obsolete now that pandda is part of ccp4 # 08/10/2020 - pandda v0.2.12 installation at DLS is obsolete # source_file='source /dls/science/groups/i04-1/software/pandda_0.2.12/ccp4/ccp4-7.0/bin/ccp4.setup-sh\n' source_file = '' source_file += 'export XChemExplorer_DIR="' + os.getenv('XChemExplorer_DIR') + '"\n' if os.path.isfile(self.filter_pdb + '.pdb'): print('filter pdb located') filter_pdb=' filter.pdb='+self.filter_pdb+'.pdb' print('will use ' + filter_pdb + 'as a filter for pandda.analyse') else: if self.use_remote: stat_command = self.remote_string.replace("qsub'", str('stat ' + self.filter_pdb + "'")) output = subprocess.Popen(stat_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) out, err = output.communicate() print out if 'cannot stat' in out: filter_pdb = '' else: filter_pdb = ' filter.pdb=' + self.filter_pdb + '.pdb' else: filter_pdb='' os.chdir(self.panddas_directory) # note: copied latest pandda.setup-sh from XCE2 installation (08/08/2017) dls = '' if self.data_directory.startswith('/dls'): dls = ( source_file + '\n' 'module load pymol/1.8.2.0\n' '\n' 'module load ccp4/7.0.072\n' '\n' ) Cmds = ( '#!'+os.getenv('SHELL')+'\n' + '\n' + dls + 'cd ' + self.panddas_directory + '\n' + '\n' ) ignore = [] char = [] zmap = [] for i in range(0, self.pandda_analyse_data_table.rowCount()): ignore_all_checkbox = self.pandda_analyse_data_table.cellWidget(i, 7) ignore_characterisation_checkbox = self.pandda_analyse_data_table.cellWidget(i, 8) ignore_zmap_checkbox = self.pandda_analyse_data_table.cellWidget(i, 9) if ignore_all_checkbox.isChecked(): ignore.append(str(self.pandda_analyse_data_table.item(i, 0).text())) if ignore_characterisation_checkbox.isChecked(): char.append(str(self.pandda_analyse_data_table.item(i, 0).text())) if ignore_zmap_checkbox.isChecked(): zmap.append(str(self.pandda_analyse_data_table.item(i, 0).text())) print ignore def append_to_ignore_string(datasets_list, append_string): if len(datasets_list)==0: append_string = '' for i in range(0, len(datasets_list)): if i < len(datasets_list)-1: append_string += str(datasets_list[i] + ',') else: append_string += str(datasets_list[i] +'"') print(append_string) return append_string ignore_string = 'ignore_datasets="' ignore_string = append_to_ignore_string(ignore, ignore_string) char_string = 'exclude_from_characterisation="' char_string = append_to_ignore_string(char, char_string) zmap_string = 'exclude_from_z_map_analysis="' zmap_string = append_to_ignore_string(zmap, zmap_string) for i in range(number_of_cyles): Cmds += ( 'pandda.analyse '+ ' data_dirs="'+self.data_directory.replace('/*','')+'/*"'+ ' out_dir="'+self.panddas_directory+'"' ' min_build_datasets='+self.min_build_datasets+ ' max_new_datasets='+self.max_new_datasets+ ' grid_spacing='+self.grid_spacing+ ' cpus='+self.nproc+ ' events.order_by='+self.sort_event+ filter_pdb+ ' pdb_style='+self.pdb_style+ ' mtz_style='+self.mtz_style+ ' lig_style=/compound/*.cif'+ ' apply_b_factor_scaling='+self.wilson_scaling+ ' write_average_map='+self.write_mean_maps + ' average_map=' + self.calc_map_by + ' ' + ignore_string +' '+ char_string +' '+ zmap_string +' '+ '\n' ) Cmds += self.select_ground_state_model Cmds += self.make_ligand_links Cmds += '\n' data_dir_string = self.data_directory.replace('/*', '') Cmds += str( 'find ' + data_dir_string + '/*/compound -name "*.cif" | while read line; do echo ${line//"' + data_dir_string + '"/"' + self.panddas_directory + '/processed_datasets/"}| while read line2; do cp $line ${line2//compound/ligand_files} > /dev/null 2>&1; ' 'done; done;') Cmds += '\n' Cmds += str( 'find ' + data_dir_string + '/*/compound -name "*.pdb" | while read line; do echo ${line//"' + data_dir_string + '"/"' + self.panddas_directory + '/processed_datasets/"}| while read line2; do cp $line ${line2//compound/ligand_files} > /dev/null 2>&1; ' 'done; done;') self.Logfile.insert('running pandda.analyse with the following command:\n'+Cmds) f = open('pandda.sh','w') f.write(Cmds) f.close() # #>>> for testing # self.submit_mode='local machine' self.Logfile.insert('trying to run pandda.analyse on ' + str(self.submit_mode)) if self.submit_mode=='local machine': self.Logfile.insert('running PANDDA on local machine') os.system('chmod +x pandda.sh') os.system('./pandda.sh &') elif self.use_remote: # handles remote submission of pandda.analyse jobs submission_string = self.remote_string.replace("qsub'", str('cd ' + self.panddas_directory + '; ' + "qsub -P labxchem -q medium.q -N pandda 5 -l exclusive,m_mem_free=100G pandda.sh'")) os.system(submission_string) self.Logfile.insert(str('running PANDDA remotely, using: ' + submission_string)) else: self.Logfile.insert('running PANDDA on cluster, using qsub...') os.system('qsub -P labxchem -q medium.q -N pandda -l exclusive,m_mem_free=100G pandda.sh') self.emit(QtCore.SIGNAL('datasource_menu_reload_samples')) class giant_cluster_datasets(QtCore.QThread): def __init__(self,initial_model_directory,pandda_params,xce_logfile,datasource,): QtCore.QThread.__init__(self) self.panddas_directory=pandda_params['out_dir'] self.pdb_style=pandda_params['pdb_style'] self.mtz_style=pandda_params['mtz_style'] self.Logfile=XChemLog.updateLog(xce_logfile) self.initial_model_directory=initial_model_directory self.db=XChemDB.data_source(datasource) def run(self): self.emit(QtCore.SIGNAL('update_progress_bar'), 0) if self.pdb_style.replace(' ','') == '': self.Logfile.insert('PDB style is not set in pandda.analyse!') self.Logfile.insert('cannot start pandda.analyse') self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'PDB style is not set in pandda.analyse!') return None if self.mtz_style.replace(' ','') == '': self.Logfile.insert('MTZ style is not set in pandda.analyse!') self.Logfile.insert('cannot start pandda.analyse') self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'MTZ style is not set in pandda.analyse!') return None # 1.) prepare output directory os.chdir(self.panddas_directory) if os.path.isdir('cluster_analysis'): self.Logfile.insert('removing old cluster_analysis directory in {0!s}'.format(self.panddas_directory)) self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'removing old cluster_analysis directory in {0!s}'.format(self.panddas_directory)) os.system('/bin/rm -fr cluster_analysis 2> /dev/null') self.Logfile.insert('creating cluster_analysis directory in {0!s}'.format(self.panddas_directory)) self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'creating cluster_analysis directory in {0!s}'.format(self.panddas_directory)) os.mkdir('cluster_analysis') self.emit(QtCore.SIGNAL('update_progress_bar'), 10) # 2.) go through project directory and make sure that all pdb files really exist # broken links derail the giant.cluster_mtzs_and_pdbs script self.Logfile.insert('cleaning up broken links of {0!s} and {1!s} in {2!s}'.format(self.pdb_style, self.mtz_style, self.initial_model_directory)) self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'cleaning up broken links of {0!s} and {1!s} in {2!s}'.format(self.pdb_style, self.mtz_style, self.initial_model_directory)) os.chdir(self.initial_model_directory) for xtal in glob.glob('*'): if not os.path.isfile(os.path.join(xtal,self.pdb_style)): self.Logfile.insert('missing {0!s} and {1!s} for {2!s}'.format(self.pdb_style, self.mtz_style, xtal)) os.system('/bin/rm {0!s}/{1!s} 2> /dev/null'.format(xtal, self.pdb_style)) os.system('/bin/rm {0!s}/{1!s} 2> /dev/null'.format(xtal, self.mtz_style)) self.emit(QtCore.SIGNAL('update_progress_bar'), 20) # 3.) giant.cluster_mtzs_and_pdbs self.Logfile.insert("running giant.cluster_mtzs_and_pdbs {0!s}/*/{1!s} pdb_regex='{2!s}/(.*)/{3!s}' out_dir='{4!s}/cluster_analysis'".format(self.initial_model_directory, self.pdb_style, self.initial_model_directory, self.pdb_style, self.panddas_directory)) self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'running giant.cluster_mtzs_and_pdbs') if os.getenv('SHELL') == '/bin/tcsh' or os.getenv('SHELL') == '/bin/csh': source_file=os.path.join(os.getenv('XChemExplorer_DIR'),'setup-scripts','pandda.setup-csh') elif os.getenv('SHELL') == '/bin/bash': source_file=os.path.join(os.getenv('XChemExplorer_DIR'),'setup-scripts','pandda.setup-sh') else: source_file='' Cmds = ( '#!'+os.getenv('SHELL')+'\n' 'unset PYTHONPATH\n' 'source '+source_file+'\n' "giant.datasets.cluster %s/*/%s pdb_regex='%s/(.*)/%s' out_dir='%s/cluster_analysis'" %(self.initial_model_directory,self.pdb_style,self.initial_model_directory,self.pdb_style,self.panddas_directory) ) # os.system("giant.cluster_mtzs_and_pdbs %s/*/%s pdb_regex='%s/(.*)/%s' out_dir='%s/cluster_analysis'" %(self.initial_model_directory,self.pdb_style,self.initial_model_directory,self.pdb_style,self.panddas_directory)) os.system(Cmds) self.emit(QtCore.SIGNAL('update_progress_bar'), 80) # 4.) analyse output self.Logfile.insert('parsing {0!s}/cluster_analysis'.format(self.panddas_directory)) self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'parsing {0!s}/cluster_analysis'.format(self.panddas_directory)) os.chdir('{0!s}/cluster_analysis'.format(self.panddas_directory)) cluster_dict={} for out_dir in sorted(glob.glob('*')): if os.path.isdir(out_dir): cluster_dict[out_dir]=[] for folder in glob.glob(os.path.join(out_dir,'pdbs','*')): xtal=folder[folder.rfind('/')+1:] cluster_dict[out_dir].append(xtal) self.emit(QtCore.SIGNAL('update_progress_bar'), 90) # 5.) update datasource self.Logfile.insert('updating datasource with results from giant.cluster_mtzs_and_pdbs') if cluster_dict != {}: for key in cluster_dict: for xtal in cluster_dict[key]: db_dict= {'CrystalFormName': key} self.db.update_data_source(xtal,db_dict) # 6.) finish self.emit(QtCore.SIGNAL('update_progress_bar'), 100) self.Logfile.insert('finished giant.cluster_mtzs_and_pdbs') self.emit(QtCore.SIGNAL('datasource_menu_reload_samples')) class check_if_pandda_can_run: # reasons why pandda cannot be run # - there is currently a job running in the pandda directory # - min datasets available is too low # - required input paramters are not complete # - map amplitude and phase labels don't exist def __init__(self,pandda_params,xce_logfile,datasource): self.data_directory=pandda_params['data_dir'] self.panddas_directory=pandda_params['out_dir'] self.min_build_datasets=pandda_params['min_build_datasets'] self.pdb_style=pandda_params['pdb_style'] self.mtz_style=pandda_params['mtz_style'] self.input_dir_structure=pandda_params['pandda_dir_structure'] self.problem_found=False self.error_code=-1 self.Logfile=XChemLog.updateLog(xce_logfile) self.db=XChemDB.data_source(datasource) def number_of_available_datasets(self): counter=0 for file in glob.glob(os.path.join(self.input_dir_structure,self.pdb_style)): if os.path.isfile(file): counter+=1 self.Logfile.insert('pandda.analyse: found {0!s} useable datasets'.format(counter)) return counter def get_first_dataset_in_project_directory(self): first_dataset='' for file in glob.glob(os.path.join(self.input_dir_structure,self.pdb_style)): if os.path.isfile(file): first_dataset=file break return first_dataset def compare_number_of_atoms_in_reference_vs_all_datasets(self,refData,dataset_list): mismatched_datasets=[] pdbtools=XChemUtils.pdbtools(refData) refPDB=refData[refData.rfind('/')+1:] refPDBlist=pdbtools.get_init_pdb_as_list() n_atom_ref=len(refPDBlist) for n_datasets,dataset in enumerate(dataset_list): if os.path.isfile(os.path.join(self.data_directory.replace('*',''),dataset,self.pdb_style)): n_atom=len(pdbtools.get_pdb_as_list(os.path.join(self.data_directory.replace('*',''),dataset,self.pdb_style))) if n_atom_ref == n_atom: self.Logfile.insert('{0!s}: atoms in PDB file ({1!s}): {2!s}; atoms in Reference file: {3!s} ===> OK'.format(dataset, self.pdb_style, str(n_atom), str(n_atom_ref))) if n_atom_ref != n_atom: self.Logfile.insert('{0!s}: atoms in PDB file ({1!s}): {2!s}; atoms in Reference file: {3!s} ===> ERROR'.format(dataset, self.pdb_style, str(n_atom), str(n_atom_ref))) mismatched_datasets.append(dataset) return n_datasets,mismatched_datasets def get_datasets_which_fit_to_reference_file(self,ref,reference_directory,cluster_dict,allowed_unitcell_difference_percent): refStructure=XChemUtils.pdbtools(os.path.join(reference_directory,ref+'.pdb')) symmRef=refStructure.get_spg_number_from_pdb() ucVolRef=refStructure.calc_unitcell_volume_from_pdb() cluster_dict[ref]=[] cluster_dict[ref].append(os.path.join(reference_directory,ref+'.pdb')) for dataset in glob.glob(os.path.join(self.data_directory,self.pdb_style)): datasetStructure=XChemUtils.pdbtools(dataset) symmDataset=datasetStructure.get_spg_number_from_pdb() ucVolDataset=datasetStructure.calc_unitcell_volume_from_pdb() if symmDataset == symmRef: try: difference=math.fabs(1-(float(ucVolRef)/float(ucVolDataset)))*100 if difference < allowed_unitcell_difference_percent: sampleID=dataset.replace('/'+self.pdb_style,'')[dataset.replace('/'+self.pdb_style,'').rfind('/')+1:] cluster_dict[ref].append(sampleID) except ZeroDivisionError: continue return cluster_dict def remove_dimple_files(self,dataset_list): for n_datasets,dataset in enumerate(dataset_list): db_dict={} if os.path.isfile(os.path.join(self.data_directory.replace('*',''),dataset,self.pdb_style)): os.system('/bin/rm '+os.path.join(self.data_directory.replace('*',''),dataset,self.pdb_style)) self.Logfile.insert('{0!s}: removing {1!s}'.format(dataset, self.pdb_style)) db_dict['DimplePathToPDB']='' db_dict['DimpleRcryst']='' db_dict['DimpleRfree']='' db_dict['DimpleResolutionHigh']='' db_dict['DimpleStatus']='pending' if os.path.isfile(os.path.join(self.data_directory.replace('*',''),dataset,self.mtz_style)): os.system('/bin/rm '+os.path.join(self.data_directory.replace('*',''),dataset,self.mtz_style)) self.Logfile.insert('{0!s}: removing {1!s}'.format(dataset, self.mtz_style)) db_dict['DimplePathToMTZ']='' if db_dict != {}: self.db.update_data_source(dataset,db_dict) def analyse_pdb_style(self): pdb_found=False for file in glob.glob(os.path.join(self.data_directory,self.pdb_style)): if os.path.isfile(file): pdb_found=True break if not pdb_found: self.error_code=1 message=self.warning_messages() return message def analyse_mtz_style(self): mtz_found=False for file in glob.glob(os.path.join(self.data_directory,self.mtz_style)): if os.path.isfile(file): mtz_found=True break if not mtz_found: self.error_code=2 message=self.warning_messages() return message def analyse_min_build_dataset(self): counter=0 for file in glob.glob(os.path.join(self.data_directory,self.mtz_style)): if os.path.isfile(file): counter+=1 if counter <= self.min_build_datasets: self.error_code=3 message=self.warning_messages() return message def warning_messages(self): message='' if self.error_code==1: message='PDB file does not exist' if self.error_code==2: message='MTZ file does not exist' if self.error_code==3: message='Not enough datasets available' return message class convert_all_event_maps_in_database(QtCore.QThread): def __init__(self,initial_model_directory,xce_logfile,datasource): QtCore.QThread.__init__(self) self.xce_logfile=xce_logfile self.Logfile=XChemLog.updateLog(xce_logfile) self.initial_model_directory=initial_model_directory self.datasource=datasource self.db=XChemDB.data_source(datasource) def run(self): sqlite = ( 'select' ' CrystalName,' ' PANDDA_site_event_map,' ' PANDDA_site_ligand_resname,' ' PANDDA_site_ligand_chain,' ' PANDDA_site_ligand_sequence_number,' ' PANDDA_site_ligand_altLoc ' 'from panddaTable ' 'where PANDDA_site_event_map not like "event%"' ) print sqlite query=self.db.execute_statement(sqlite) print query progress_step=1 if len(query) != 0: progress_step=100/float(len(query)) else: progress_step=1 progress=0 self.emit(QtCore.SIGNAL('update_progress_bar'), progress) for item in query: print item xtalID=str(item[0]) event_map=str(item[1]) resname=str(item[2]) chainID=str(item[3]) resseq=str(item[4]) altLoc=str(item[5]) if os.path.isfile(os.path.join(self.initial_model_directory,xtalID,'refine.pdb')): os.chdir(os.path.join(self.initial_model_directory,xtalID)) self.Logfile.insert('extracting ligand ({0!s},{1!s},{2!s},{3!s}) from refine.pdb'.format(str(resname), str(chainID), str(resseq), str(altLoc))) XChemUtils.pdbtools(os.path.join(self.initial_model_directory,xtalID,'refine.pdb')).save_specific_ligands_to_pdb(resname,chainID,resseq,altLoc) if os.path.isfile('ligand_{0!s}_{1!s}_{2!s}_{3!s}.pdb'.format(str(resname), str(chainID), str(resseq), str(altLoc))): ligand_pdb='ligand_{0!s}_{1!s}_{2!s}_{3!s}.pdb'.format(str(resname), str(chainID), str(resseq), str(altLoc)) print os.path.join(self.initial_model_directory,xtalID,ligand_pdb) else: self.Logfile.insert('could not extract ligand; trying next...') continue else: self.Logfile.insert('directory: '+os.path.join(self.initial_model_directory,xtalID)+' -> cannot find refine.pdb; trying next') continue if os.path.isfile(os.path.join(self.initial_model_directory,xtalID,'refine.mtz')): resolution=XChemUtils.mtztools(os.path.join(self.initial_model_directory,xtalID,'refine.mtz')).get_high_resolution_from_mtz() else: self.Logfile.insert('directory: '+os.path.join(self.initial_model_directory,xtalID)+' -> cannot find refine.mtz; trying next') continue self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'eventMap -> SF for '+event_map) convert_event_map_to_SF(self.initial_model_directory,xtalID,event_map,ligand_pdb,self.xce_logfile,self.datasource,resolution).run() progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) class convert_event_map_to_SF: def __init__(self,project_directory,xtalID,event_map,ligand_pdb,xce_logfile,db_file,resolution): self.Logfile=XChemLog.updateLog(xce_logfile) self.event_map=event_map if not os.path.isfile(self.event_map): self.Logfile.insert('cannot find Event map: '+self.event_map) self.Logfile.insert('cannot convert event_map to structure factors!') return None self.project_directory=project_directory self.xtalID=xtalID self.event_map=event_map self.ligand_pdb=ligand_pdb self.event=event_map[event_map.rfind('/')+1:].replace('.map','').replace('.ccp4','') self.db=XChemDB.data_source(db_file) self.resolution=resolution def run(self): os.chdir(os.path.join(self.project_directory,self.xtalID)) # remove exisiting mtz file if os.path.isfile(self.event+'.mtz'): self.Logfile.insert('removing existing '+self.event+'.mtz') os.system('/bin/rm '+self.event+'.mtz') # event maps generated with pandda v0.2 or higher have the same symmetry as the crystal # but phenix.map_to_structure_facors only accepts maps in spg P1 # therefore map is first expanded to full unit cell and spg of map then set tp p1 # other conversion option like cinvfft give for whatever reason uninterpretable maps self.convert_map_to_p1() # run phenix.map_to_structure_factors self.run_phenix_map_to_structure_factors() self.remove_and_rename_column_labels() # check if output files exist if not os.path.isfile('{0!s}.mtz'.format(self.event)): self.Logfile.insert('cannot find {0!s}.mtz'.format(self.event)) else: self.Logfile.insert('conversion successful, {0!s}.mtz exists'.format(self.event)) # update datasource with event_map_mtz information self.update_database() def calculate_electron_density_map(self,mtzin): missing_columns=False column_dict=XChemUtils.mtztools(mtzin).get_all_columns_as_dict() if 'FWT' in column_dict['F'] and 'PHWT' in column_dict['PHS']: labin=' labin F1=FWT PHI=PHWT\n' elif '2FOFCWT' in column_dict['F'] and 'PH2FOFCWT' in column_dict['PHS']: labin=' labin F1=2FOFCWT PHI=PH2FOFCWT\n' else: missing_columns=True if not missing_columns: os.chdir(os.path.join(self.project_directory,self.xtalID)) cmd = ( 'fft hklin '+mtzin+' mapout 2fofc.map << EOF\n' +labin+ 'EOF\n' ) self.Logfile.insert('calculating 2fofc map from '+mtzin) os.system(cmd) else: self.Logfile.insert('cannot calculate 2fofc.map; missing map coefficients') def prepare_conversion_script(self): os.chdir(os.path.join(self.project_directory, self.xtalID)) # see also: # http://www.phaser.cimr.cam.ac.uk/index.php/Using_Electron_Density_as_a_Model if os.getcwd().startswith('/dls'): phenix_module='module_load_phenix\n' else: phenix_module='' cmd = ( '#!'+os.getenv('SHELL')+'\n' '\n' +phenix_module+ '\n' 'pdbset XYZIN %s XYZOUT mask_ligand.pdb << eof\n' %self.ligand_pdb+ ' SPACEGROUP {0!s}\n'.format(self.space_group)+ ' CELL {0!s}\n'.format((' '.join(self.unit_cell)))+ ' END\n' 'eof\n' '\n' 'ncsmask XYZIN mask_ligand.pdb MSKOUT mask_ligand.msk << eof\n' ' GRID %s\n' %(' '.join(self.gridElectronDensityMap))+ ' RADIUS 10\n' ' PEAK 1\n' 'eof\n' '\n' 'mapmask MAPIN %s MAPOUT onecell_event_map.map << eof\n' %self.event_map+ ' XYZLIM CELL\n' 'eof\n' '\n' 'maprot MAPIN onecell_event_map.map MSKIN mask_ligand.msk WRKOUT masked_event_map.map << eof\n' ' MODE FROM\n' ' SYMMETRY WORK %s\n' %self.space_group_numberElectronDensityMap+ ' AVERAGE\n' ' ROTATE EULER 0 0 0\n' ' TRANSLATE 0 0 0\n' 'eof\n' '\n' 'mapmask MAPIN masked_event_map.map MAPOUT masked_event_map_fullcell.map << eof\n' ' XYZLIM CELL\n' ' PAD 0.0\n' 'eof\n' '\n' 'sfall HKLOUT %s.mtz MAPIN masked_event_map_fullcell.map << eof\n' %self.event+ ' LABOUT FC=FC_event PHIC=PHIC_event\n' ' MODE SFCALC MAPIN\n' ' RESOLUTION %s\n' %self.resolution+ ' END\n' ) self.Logfile.insert('preparing script for conversion of Event map to SF') f = open('eventMap2sf.sh','w') f.write(cmd) f.close() os.system('chmod +x eventMap2sf.sh') def run_conversion_script(self): self.Logfile.insert('running conversion script...') os.system('./eventMap2sf.sh') def convert_map_to_p1(self): self.Logfile.insert('running mapmask -> converting map to p1...') cmd = ( '#!'+os.getenv('SHELL')+'\n' '\n' 'mapmask mapin %s mapout %s_p1.map << eof\n' %(self.event_map,self.event) + 'xyzlin cell\n' 'symmetry p1\n' ) self.Logfile.insert('mapmask command:\n%s' %cmd) os.system(cmd) def run_phenix_map_to_structure_factors(self): if float(self.resolution) < 1.21: # program complains if resolution is 1.2 or higher self.resolution='1.21' self.Logfile.insert('running phenix.map_to_structure_factors {0!s}_p1.map d_min={1!s} output_file_name={2!s}_tmp.mtz'.format(self.event, self.resolution, self.event)) os.system('phenix.map_to_structure_factors {0!s}_p1.map d_min={1!s} output_file_name={2!s}_tmp.mtz'.format(self.event, self.resolution, self.event)) def run_cinvfft(self,mtzin): # mtzin is usually refine.mtz self.Logfile.insert('running cinvfft -mapin {0!s} -mtzin {1!s} -mtzout {2!s}_tmp.mtz -colout event'.format(self.event_map, mtzin, self.event)) os.system('cinvfft -mapin {0!s} -mtzin {1!s} -mtzout {2!s}_tmp.mtz -colout event'.format(self.event_map, mtzin, self.event)) def remove_and_rename_column_labels(self): cmd = ( '#!'+os.getenv('SHELL')+'\n' '\n' 'cad hklin1 %s_tmp.mtz hklout %s.mtz << eof\n' %(self.event,self.event)+ ' labin file_number 1 E1=F-obs E2=PHIF\n' ' labout file_number 1 E1=F_ampl E2=PHIF\n' 'eof\n' '\n' ) self.Logfile.insert('running CAD: new column labels F_ampl,PHIF') os.system(cmd) def remove_and_rename_column_labels_after_cinvfft(self): cmd = ( '#!'+os.getenv('SHELL')+'\n' '\n' 'cad hklin1 %s_tmp.mtz hklout %s.mtz << eof\n' %(self.event,self.event)+ ' labin file_number 1 E1=event.F_phi.F E2=event.F_phi.phi\n' ' labout file_number 1 E1=F_ampl E2=PHIF\n' 'eof\n' '\n' ) self.Logfile.insert('running CAD: renaming event.F_phi.F -> F_ampl and event.F_phi.phi -> PHIF') os.system(cmd) def update_database(self): sqlite = ( "update panddaTable set " " PANDDA_site_event_map_mtz = '%s' " %os.path.join(self.project_directory,self.xtalID,self.event+'.mtz')+ " where PANDDA_site_event_map is '{0!s}' ".format(self.event_map) ) self.db.execute_statement(sqlite) self.Logfile.insert('updating data source: '+sqlite) def clean_output_directory(self): os.system('/bin/rm mask_targetcell.pdb') os.system('/bin/rm mask_targetcell.msk') os.system('/bin/rm onecell.map') os.system('/bin/rm masked_targetcell.map') os.system('/bin/rm masked_fullcell.map') os.system('/bin/rm eventMap2sf.sh') os.system('/bin/rm '+self.ligand_pdb) class run_pandda_inspect_at_home(QtCore.QThread): def __init__(self,panddaDir,xce_logfile): QtCore.QThread.__init__(self) self.panddaDir=panddaDir self.Logfile=XChemLog.updateLog(xce_logfile) def run(self): os.chdir(os.path.join(self.panddaDir,'processed_datasets')) progress_step=1 if len(glob.glob('*')) != 0: progress_step=100/float(len(glob.glob('*'))) else: progress_step=1 progress=0 self.emit(QtCore.SIGNAL('update_progress_bar'), progress) self.Logfile.insert('parsing '+self.panddaDir) for xtal in sorted(glob.glob('*')): for files in glob.glob(xtal+'/ligand_files/*'): if os.path.islink(files): self.emit(QtCore.SIGNAL('update_status_bar(QString)'), 'replacing symlink for {0!s} with real file'.format(files)) self.Logfile.insert('replacing symlink for {0!s} with real file'.format(files)) os.system('cp --remove-destination {0!s} {1!s}/ligand_files'.format(os.path.realpath(files), xtal)) progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) XChemToolTips.run_pandda_inspect_at_home(self.panddaDir) class convert_apo_structures_to_mmcif(QtCore.QThread): def __init__(self,panddaDir,xce_logfile): QtCore.QThread.__init__(self) self.panddaDir=panddaDir self.Logfile=XChemLog.updateLog(xce_logfile) def sf_convert_environment(self): pdb_extract_init = '' if os.path.isdir('/dls'): pdb_extract_init = 'source /dls/science/groups/i04-1/software/pdb-extract-prod/setup.sh\n' pdb_extract_init += '/dls/science/groups/i04-1/software/pdb-extract-prod/bin/sf_convert' else: pdb_extract_init = 'source ' + os.path.join(os.getenv('XChemExplorer_DIR'), 'pdb_extract/pdb-extract-prod/setup.sh') + '\n' pdb_extract_init += +os.path.join(os.getenv('XChemExplorer_DIR'), 'pdb_extract/pdb-extract-prod/bin/sf_convert') return pdb_extract_init def run(self): self.Logfile.insert('converting apo structures in pandda directory to mmcif files') self.Logfile.insert('chanfing to '+self.panddaDir) progress_step=1 if len(glob.glob('*')) != 0: progress_step=100/float(len(glob.glob(os.path.join(self.panddaDir,'processed_datasets','*')))) else: progress_step=1 progress=0 self.emit(QtCore.SIGNAL('update_progress_bar'), progress) pdb_extract_init = self.sf_convert_environment() self.Logfile.insert('parsing '+self.panddaDir) for dirs in glob.glob(os.path.join(self.panddaDir,'processed_datasets','*')): xtal = dirs[dirs.rfind('/')+1:] self.Logfile.insert('%s: converting %s to mmcif' %(xtal,xtal+'-pandda-input.mtz')) if os.path.isfile(os.path.join(dirs,xtal+'-pandda-input.mtz')): if os.path.isfile(os.path.join(dirs,xtal+'_sf.mmcif')): self.Logfile.insert('%s: %s_sf.mmcif exists; skipping...' %(xtal,xtal)) else: os.chdir(dirs) Cmd = (pdb_extract_init + ' -o mmcif' ' -sf %s' % xtal+'-pandda-input.mtz' + ' -out {0!s}_sf.mmcif > {1!s}.sf_mmcif.log'.format(xtal, xtal)) self.Logfile.insert('running command: '+Cmd) os.system(Cmd) progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) class check_number_of_modelled_ligands(QtCore.QThread): def __init__(self,project_directory,xce_logfile,db_file): QtCore.QThread.__init__(self) self.Logfile=XChemLog.updateLog(xce_logfile) self.project_directory=project_directory self.db=XChemDB.data_source(db_file) self.errorDict={} def update_errorDict(self,xtal,message): if xtal not in self.errorDict: self.errorDict[xtal]=[] self.errorDict[xtal].append(message) def insert_new_row_in_panddaTable(self,xtal,ligand,site,dbDict): resname= site[0] chain= site[1] seqnum= site[2] altLoc= site[3] x_site= site[5][0] y_site= site[5][1] z_site= site[5][2] resnameSimilarSite= ligand[0] chainSimilarSite= ligand[1] seqnumSimilarSite= ligand[2] siteList=[] for entry in dbDict[xtal]: siteList.append(str(entry[0])) if entry[4] == resnameSimilarSite and entry[5] == chainSimilarSite and entry[6] == seqnumSimilarSite: eventMap= str(entry[7]) eventMap_mtz= str(entry[8]) initialPDB= str(entry[9]) initialMTZ= str(entry[10]) event_id= str(entry[12]) PanDDApath= str(entry[13]) db_dict={ 'PANDDA_site_index': str(int(max(siteList))+1), 'PANDDApath': PanDDApath, 'PANDDA_site_ligand_id': resname+'-'+chain+'-'+seqnum, 'PANDDA_site_ligand_resname': resname, 'PANDDA_site_ligand_chain': chain, 'PANDDA_site_ligand_sequence_number': seqnum, 'PANDDA_site_ligand_altLoc': 'D', 'PANDDA_site_event_index': event_id, 'PANDDA_site_event_map': eventMap, 'PANDDA_site_event_map_mtz': eventMap_mtz, 'PANDDA_site_initial_model': initialPDB, 'PANDDA_site_initial_mtz': initialMTZ, 'PANDDA_site_ligand_placed': 'True', 'PANDDA_site_x': x_site, 'PANDDA_site_y': y_site, 'PANDDA_site_z': z_site } print xtal,db_dict def run(self): self.Logfile.insert('reading modelled ligands from panddaTable') dbDict={} sqlite = ( "select " " CrystalName," " PANDDA_site_index," " PANDDA_site_x," " PANDDA_site_y," " PANDDA_site_z," " PANDDA_site_ligand_resname," " PANDDA_site_ligand_chain," " PANDDA_site_ligand_sequence_number," " PANDDA_site_event_map," " PANDDA_site_event_map_mtz," " PANDDA_site_initial_model," " PANDDA_site_initial_mtz," " RefinementOutcome," " PANDDA_site_event_index," " PANDDApath " "from panddaTable " ) dbEntries=self.db.execute_statement(sqlite) for item in dbEntries: xtal= str(item[0]) site= str(item[1]) x= str(item[2]) y= str(item[3]) z= str(item[4]) resname= str(item[5]) chain= str(item[6]) seqnum= str(item[7]) eventMap= str(item[8]) eventMap_mtz= str(item[9]) initialPDB= str(item[10]) initialMTZ= str(item[11]) outcome= str(item[12]) event= str(item[13]) PanDDApath= str(item[14]) if xtal not in dbDict: dbDict[xtal]=[] dbDict[xtal].append([site,x,y,z,resname,chain,seqnum,eventMap,eventMap_mtz,initialPDB,initialMTZ,outcome,event,PanDDApath]) os.chdir(self.project_directory) progress_step=1 if len(glob.glob('*')) != 0: progress_step=100/float(len(glob.glob('*'))) else: progress_step=1 progress=0 self.emit(QtCore.SIGNAL('update_progress_bar'), progress) for xtal in sorted(glob.glob('*')): if os.path.isfile(os.path.join(xtal,'refine.pdb')): ligands=XChemUtils.pdbtools(os.path.join(xtal,'refine.pdb')).ligand_details_as_list() self.Logfile.insert('{0!s}: found file refine.pdb'.format(xtal)) if ligands: if os.path.isdir(os.path.join(xtal,'xceTmp')): os.system('/bin/rm -fr {0!s}'.format(os.path.join(xtal,'xceTmp'))) os.mkdir(os.path.join(xtal,'xceTmp')) else: self.Logfile.warning('{0!s}: cannot find ligand molecule in refine.pdb; skipping...'.format(xtal)) continue made_sym_copies=False ligands_not_in_panddaTable=[] for n,item in enumerate(ligands): resnameLIG= item[0] chainLIG= item[1] seqnumLIG= item[2] altLocLIG= item[3] occupancyLig= item[4] if altLocLIG.replace(' ','') == '': self.Logfile.insert(xtal+': found a ligand not modelled with pandda.inspect -> {0!s} {1!s} {2!s}'.format(resnameLIG, chainLIG, seqnumLIG)) residue_xyz = XChemUtils.pdbtools(os.path.join(xtal,'refine.pdb')).get_center_of_gravity_of_residue_ish(item[1],item[2]) ligands[n].append(residue_xyz) foundLigand=False if xtal in dbDict: for entry in dbDict[xtal]: resnameTable=entry[4] chainTable=entry[5] seqnumTable=entry[6] self.Logfile.insert('panddaTable: {0!s} {1!s} {2!s} {3!s}'.format(xtal, resnameTable, chainTable, seqnumTable)) if resnameLIG == resnameTable and chainLIG == chainTable and seqnumLIG == seqnumTable: self.Logfile.insert('{0!s}: found ligand in database -> {1!s} {2!s} {3!s}'.format(xtal, resnameTable, chainTable, seqnumTable)) foundLigand=True if not foundLigand: self.Logfile.error('{0!s}: did NOT find ligand in database -> {1!s} {2!s} {3!s}'.format(xtal, resnameLIG, chainLIG, seqnumLIG)) ligands_not_in_panddaTable.append([resnameLIG,chainLIG,seqnumLIG,altLocLIG,occupancyLig,residue_xyz]) else: self.Logfile.warning('ligand in PDB file, but dataset not listed in panddaTable: {0!s} -> {1!s} {2!s} {3!s}'.format(xtal, item[0], item[1], item[2])) for entry in ligands_not_in_panddaTable: self.Logfile.error('{0!s}: refine.pdb contains a ligand that is not assigned in the panddaTable: {1!s} {2!s} {3!s} {4!s}'.format(xtal, entry[0], entry[1], entry[2], entry[3])) for site in ligands_not_in_panddaTable: for files in glob.glob(os.path.join(self.project_directory,xtal,'xceTmp','ligand_*_*.pdb')): mol_xyz = XChemUtils.pdbtools(files).get_center_of_gravity_of_molecule_ish() # now need to check if there is a unassigned entry in panddaTable that is close for entry in dbDict[xtal]: distance = XChemUtils.misc().calculate_distance_between_coordinates(mol_xyz[0], mol_xyz[1],mol_xyz[2],entry[1],entry[2], entry[3]) self.Logfile.insert('{0!s}: {1!s} {2!s} {3!s} <---> {4!s} {5!s} {6!s}'.format(xtal, mol_xyz[0], mol_xyz[1], mol_xyz[2], entry[1], entry[2], entry[3])) self.Logfile.insert('{0!s}: symm equivalent molecule: {1!s}'.format(xtal, files)) self.Logfile.insert('{0!s}: distance: {1!s}'.format(xtal, str(distance))) progress += progress_step self.emit(QtCore.SIGNAL('update_progress_bar'), progress) if self.errorDict != {}: self.update_errorDict('General','The aforementioned PDB files were automatically changed by XCE!\nPlease check and refine them!!!') self.emit(QtCore.SIGNAL('show_error_dict'), self.errorDict) class find_event_map_for_ligand(QtCore.QThread): def __init__(self,project_directory,xce_logfile,external_software): QtCore.QThread.__init__(self) self.Logfile=XChemLog.updateLog(xce_logfile) self.project_directory=project_directory self.external_software=external_software try: import gemmi self.Logfile.insert('found gemmi library in ccp4-python') except ImportError: self.external_software['gemmi'] = False self.Logfile.warning('cannot import gemmi; will use phenix.map_to_structure_factors instead') def run(self): self.Logfile.insert('======== checking ligand CC in event maps ========') for dirs in sorted(glob.glob(os.path.join(self.project_directory,'*'))): xtal = dirs[dirs.rfind('/')+1:] if os.path.isfile(os.path.join(dirs,'refine.pdb')) and \ os.path.isfile(os.path.join(dirs,'refine.mtz')): self.Logfile.insert('%s: found refine.pdb' %xtal) os.chdir(dirs) try: p = gemmi.read_structure('refine.pdb') except: self.Logfile.error('gemmi library not available') self.external_software['gemmi'] = False reso = XChemUtils.mtztools('refine.mtz').get_dmin() ligList = XChemUtils.pdbtools('refine.pdb').save_residues_with_resname(dirs,'LIG') self.Logfile.insert('%s: found %s ligands of type LIG in refine.pdb' %(xtal,str(len(ligList)))) for maps in glob.glob(os.path.join(dirs,'*event*.native.ccp4')): if self.external_software['gemmi']: self.convert_map_to_sf_with_gemmi(maps,p) else: self.expand_map_to_p1(maps) self.convert_map_to_sf(maps.replace('.ccp4','.P1.ccp4'),reso) summary = '' for lig in sorted(ligList): if self.external_software['gemmi']: for mtz in sorted(glob.glob(os.path.join(dirs,'*event*.native.mtz'))): self.get_lig_cc(mtz,lig) cc = self.check_lig_cc(mtz.replace('.mtz', '_CC.log')) summary += '%s: %s LIG CC = %s (%s)\n' %(xtal,lig,cc,mtz[mtz.rfind('/')+1:]) else: for mtz in sorted(glob.glob(os.path.join(dirs,'*event*.native*P1.mtz'))): self.get_lig_cc(mtz,lig) cc = self.check_lig_cc(mtz.replace('.mtz', '_CC.log')) summary += '%s: %s LIG CC = %s (%s)\n' %(xtal,lig,cc,mtz[mtz.rfind('/')+1:]) self.Logfile.insert('\nsummary of CC analysis:\n======================:\n'+summary) def expand_map_to_p1(self,emap): self.Logfile.insert('expanding map to P1: %s' %emap) if os.path.isfile(emap.replace('.ccp4','.P1.ccp4')): self.Logfile.warning('P1 map exists; skipping...') return cmd = ( 'mapmask MAPIN %s MAPOUT %s << eof\n' %(emap,emap.replace('.ccp4','.P1.ccp4'))+ ' XYZLIM CELL\n' ' PAD 0.0\n' ' SYMMETRY 1\n' 'eof\n' ) os.system(cmd) def convert_map_to_sf(self,emap,reso): self.Logfile.insert('converting ccp4 map to mtz with phenix.map_to_structure_factors: %s' %emap) if os.path.isfile(emap.replace('.ccp4','.mtz')): self.Logfile.warning('mtz file of event map exists; skipping...') return cmd = ( 'module load phenix\n' 'phenix.map_to_structure_factors %s d_min=%s\n' %(emap,reso)+ '/bin/mv map_to_structure_factors.mtz %s' %emap.replace('.ccp4', '.mtz') ) os.system(cmd) def get_lig_cc(self,mtz,lig): self.Logfile.insert('calculating CC for %s in %s' %(lig,mtz)) if os.path.isfile(mtz.replace('.mtz', '_CC.log')): self.Logfile.warning('logfile of CC analysis exists; skipping...') return cmd = ( 'module load phenix\n' 'phenix.get_cc_mtz_pdb %s %s > %s' % (mtz, lig, mtz.replace('.mtz', '_CC.log')) ) os.system(cmd) def check_lig_cc(self,log): cc = 'n/a' if os.path.isfile(log): for line in open(log): if line.startswith('local'): cc = line.split()[len(line.split()) - 1] else: self.Logfile.error('logfile does not exist: %s' %log) return cc def convert_map_to_sf_with_gemmi(self,emap,p): self.Logfile.insert('converting ccp4 map to mtz with gemmi map2sf: %s' %emap) if os.path.isfile(emap.replace('.ccp4','.mtz')): self.Logfile.warning('mtz file of event map exists; skipping...') return cmd = 'gemmi map2sf %s %s FWT PHWT --dmin=%s' %(emap,emap.replace('.ccp4','.mtz'),p.resolution) self.Logfile.insert('converting map with command:\n' + cmd) os.system(cmd)

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0.043836

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0.627952

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0.439305

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99,064

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null

0.006739

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null

0

null

0

1

0

1

fe8a256140b6390c55cadca6d58880f260544702

5,253

py

Python

OmegaErp/Apps/base/forms/__init__.py

OMAR-EHAB777/FerpMenu

6aee4616bc9bc7801023fe51acfa28e1e1267b66

[ "BSD-3-Clause" ]

null

OmegaErp/Apps/base/forms/__init__.py

OMAR-EHAB777/FerpMenu

6aee4616bc9bc7801023fe51acfa28e1e1267b66

[ "BSD-3-Clause" ]

null

OmegaErp/Apps/base/forms/__init__.py

OMAR-EHAB777/FerpMenu

6aee4616bc9bc7801023fe51acfa28e1e1267b66

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Global app forms """ # Standard Library import re # Django Library from django import forms from django.contrib.auth.forms import UserChangeForm, UserCreationForm from django.utils.translation import ugettext_lazy as _ # Thirdparty Library from dal import autocomplete # Localfolder Library from ..models import PyCompany, PyCountry, PyUser from .partner import PartnerForm class PerfilForm(forms.ModelForm): """Class to update the user profile on the system """ class Meta: model = PyUser fields = ( 'first_name', 'last_name', 'celular', ) labels = { 'first_name': _('Name'), 'last_name': _('Last Name'), 'celular': _('Mobile Phone'), } widgets = { 'first_name': forms.TextInput(attrs={'class': 'form-control'}), 'last_name': forms.TextInput(attrs={'class': 'form-control'}), 'celular': forms.TextInput(attrs={'class': 'form-control'}), } class PersonaChangeForm(UserChangeForm): """for something will be """ class Meta(UserChangeForm.Meta): model = PyUser fields = ( 'email', 'is_superuser', 'is_staff', 'is_active', 'last_login', 'date_joined', 'first_name', 'last_name', ) # ========================================================================== # class PasswordRecoveryForm(forms.ModelForm): """To send the account recovery correction """ class Meta(): model = PyUser fields = ( 'email', ) widgets = { 'email': forms.EmailInput( attrs={'class': 'form-control', 'placeholder': _('Email')} ), } # ========================================================================== # class PasswordSetForm(forms.Form): """To send the account recovery correction """ password1 = forms.CharField( widget=forms.PasswordInput( attrs={'class': 'form-control', 'placeholder': _('Password')} ) ) password2 = forms.CharField( widget=forms.PasswordInput( attrs={'class': 'form-control', 'placeholder': _('Retype password')} ) ) def clean(self): super().clean() password1 = self.cleaned_data.get('password1') password2 = self.cleaned_data.get('password2') print('entre8888') if password1 != password2: raise forms.ValidationError( _('The two password fields didn\'t match.') ) if password1 != password2: raise forms.ValidationError( _('The two password fields didn\'t match.') ) class PersonaCreationForm(UserCreationForm): """This form class renders the record sheet of users """ class Meta(UserCreationForm.Meta): model = PyUser fields = ( 'email', ) widgets = { 'email': forms.EmailInput( attrs={'class': 'form-control', 'placeholder': _('Email')} ), } class AvatarForm(forms.ModelForm): """Class to update the user profile on the system """ class Meta: model = PyUser fields = ( 'avatar', ) class InitForm(forms.ModelForm): """From of OMegaERP initializacion """ email = forms.EmailField( widget=forms.EmailInput( attrs={ 'placeholder': _('Admin email') } ) ) password = forms.CharField( max_length=100, widget=forms.PasswordInput( attrs={ 'placeholder': _('Admin Password') } ) ) class Meta: model = PyCompany fields = [ 'name', 'country', 'email', 'password' ] labels = { 'name': _('Company Name'), 'country': _('Country'), 'email': _('Admin user email'), 'password': _('Password'), } widgets = { 'name': forms.TextInput( attrs={ 'class': 'form-control', 'data-placeholder': _('Company Name'), 'style': 'width: 100%', }, ), 'country': autocomplete.ModelSelect2( url='PyCountry:autocomplete', attrs={ 'class': 'form-control', 'data-placeholder': _('Select a country...'), 'style': 'width: 100%', }, ), 'email': forms.EmailInput( attrs={ 'class': 'form-control', 'data-placeholder': _('Admin user email'), 'style': 'width: 100%', }, ), } class ActivateForm(forms.Form): """To activate or deactivate an object in OmegaERP """ object_name = forms.CharField(max_length=100, widget=forms.HiddenInput) object_pk = forms.IntegerField(widget=forms.HiddenInput)

26.938462

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0.491148

421

5,253

6.035629

0.320665

0.039355

0.055096

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0.006803

0

null

0

null

0

1

0

1

fe8c212fdb626e028311eb927a139fd3cc7bba51

1,455

py

Python

tests/unit/dataactvalidator/test_fabs38_detached_award_financial_assistance_2.py

COEJKnight/one

6a5f8cd9468ab368019eb2597821b7837f74d9e2

[ "CC0-1.0" ]

1

2018-10-29T12:54:44.000Z

tests/unit/dataactvalidator/test_fabs38_detached_award_financial_assistance_2.py

COEJKnight/one

6a5f8cd9468ab368019eb2597821b7837f74d9e2

[ "CC0-1.0" ]

null

tests/unit/dataactvalidator/test_fabs38_detached_award_financial_assistance_2.py

COEJKnight/one

6a5f8cd9468ab368019eb2597821b7837f74d9e2

[ "CC0-1.0" ]

null

from tests.unit.dataactcore.factories.staging import DetachedAwardFinancialAssistanceFactory from tests.unit.dataactvalidator.utils import number_of_errors, query_columns _FILE = 'fabs38_detached_award_financial_assistance_2' def test_column_headers(database): expected_subset = {"row_number", "awarding_office_code"} actual = set(query_columns(_FILE, database)) assert expected_subset == actual def test_success(database): """ AwardingOfficeCode must be six characters long. """ det_award_1 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='AAAAAA') det_award_2 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='111111') det_award_3 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='AAA111') det_award_4 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='') det_award_5 = DetachedAwardFinancialAssistanceFactory(awarding_office_code=None) errors = number_of_errors(_FILE, database, models=[det_award_1, det_award_2, det_award_3, det_award_4, det_award_5]) assert errors == 0 def test_failure(database): """ AwardingOfficeCode must be six characters long. """ det_award_1 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='AAAA1') det_award_2 = DetachedAwardFinancialAssistanceFactory(awarding_office_code='AAAAAAA') errors = number_of_errors(_FILE, database, models=[det_award_1, det_award_2]) assert errors == 2

45.46875

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0.808935

164

1,455

6.762195

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0

0.022446

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1,455

31

121

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0.15

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0.25

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null

0

1

0

null

0

1

fe8e1c215219c1805761ef6232ba7b858bfbd7b4

3,641

py

Python

src/conv/convertManifest2Curation.py

nakamura196/i3

16d7695e5412b45dc8e0192d9ca285723ac9f788

[ "Apache-2.0" ]

3

2020-04-21T11:36:10.000Z

2022-02-01T00:46:59.000Z

src/conv/convertManifest2Curation.py

nakamura196/i3

16d7695e5412b45dc8e0192d9ca285723ac9f788

[ "Apache-2.0" ]

17

2021-01-08T17:20:38.000Z

2021-06-29T05:55:47.000Z

src/conv/convertManifest2Curation.py

nakamura196/i3

16d7695e5412b45dc8e0192d9ca285723ac9f788

[ "Apache-2.0" ]

null

import urllib.request from bs4 import BeautifulSoup import csv import requests import os import json import time import glob files = glob.glob("/Users/nakamura/git/d_iiif/iiif/src/collections/nijl/data/json/*.json") for i in range(len(files)): file = files[i] file_id = file.split("/")[-1].replace(".json", "") opath = "/Users/nakamura/git/d_iiif/iiif/src/collections/nijl/data/curation/"+file_id+".json" if not os.path.exists(opath): fw = open(opath, 'w') curation_data = {} curation_uri = "curation:"+file_id+".json" with open(file) as f: try: df = json.load(f) except: continue anno_count = 1 if "sequences" in df: print(file) members = [] canvases = df["sequences"][0]["canvases"] for j in range(len(canvases)): canvas = canvases[j] if "otherContent" in canvas: id = canvas["otherContent"][0]["@id"] headers = {"content-type": "application/json"} # time.sleep(0.5) r = requests.get(id, headers=headers) data = r.json() print(id) resources = data["resources"] for resource in resources: member_id = resource["on"] res = resource["resource"] chars = res["chars"] member = { "@id": member_id, "@type": "sc:Canvas", "label": "[Annotation " + str(anno_count) + "]", "description": chars, "metadata": [ { "label": res["@type"], "value": chars } ] } anno_count += 1 members.append(member) if len(members) > 0: label = "" if "label" in df: label = df["label"] curation_data = { "@context": [ "http://iiif.io/api/presentation/2/context.json", "http://codh.rois.ac.jp/iiif/curation/1/context.json" ], "@type": "cr:Curation", "@id": curation_uri, "label": "Automatic curation by IIIF Converter", "selections": [ { "@id": curation_uri + "/range1", "@type": "sc:Range", "label": "Automatic curation by IIIF Converter", "members": members, "within": { "@id": df["@id"], "@type": "sc:Manifest", "label": label } } ] } json.dump(curation_data, fw, ensure_ascii=False, indent=4, sort_keys=True, separators=(',', ': '))

31.938596

106

0.355397

275

3,641

4.64

0.4

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0.025078

0.026646

0.131661

0.073668

0

0.007688

0.535567

3,641

113

107

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0.00412

0

0.024691

0

0.024691

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0.037528

0

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0.024691

0

null

0

1

0

null

0

1

fe93e83fe7e8770b4f2c1e2cf97bec6cd0abb158

1,628

py

Python

examples/multiprocess_example.py

ct-clmsn/distributed-tensorflow-orchestration

c841659881e98209149bd6e3e09774a50e3c748e

[ "Apache-2.0" ]

5

2016-07-27T08:25:17.000Z

2022-02-07T19:41:45.000Z

examples/multiprocess_example.py

ct-clmsn/distributed-tensorflow-orchestration

c841659881e98209149bd6e3e09774a50e3c748e

[ "Apache-2.0" ]

null

examples/multiprocess_example.py

ct-clmsn/distributed-tensorflow-orchestration

c841659881e98209149bd6e3e09774a50e3c748e

[ "Apache-2.0" ]

1

2022-02-07T19:41:46.000Z

''' marathon_example.py performs a simple matrix multiply using 3 compute nodes ''' def parseargs(): parser = argparse.ArgumentParser(description='Marathon for TensorFlow.') parser.add_argument('--n_tasks', default=1, help='an integer for the accumulator') parser.add_argument('--cpu', default=100.0, help='an integer for the accumulator') parser.add_argument('--mem', default=100.0, help='an integer for the accumulator') parser.add_argument('--taskname', default=uuid.uuid1(), help='name for the task') parser.add_argument('--url', help='DNS addr to marathon') parser.add_argument('--usr', help='marathon username') parser.add_argument('--usrpwd', help='marathon password') parser.add_argument('--uri', help='curl-friendly URI to the tensorflow client executable (url?, hdfs?, docker?)') args = parser.parse_args() return args if __name__ == '__main__': from sys import argv import tensorflow as tf from dtforchestrator import * args = parseargs() with MultiprocessTensorFlowSession(args.taskname, args.n_tasks) as tfdevices: with tf.device(tfdevices.getDeviceSpec(1)): matrix1 = tf.constant([[3.],[3.]]) with tf.device(tfdevices.getDeviceSpec(2)): matrix2 = tf.constant([[3.,3.]]) with tf.device(tfdevices.getDeviceSpec(0)): matrix0 = tf.constant([[3.,3.]]) product1 = tf.matmul(matrix0, matrix1) product2 = tf.matmul(matrix2, matrix1) with tf.Session(tfdevices.localGRPC()) as sess: res = sess.run(product1) print res res = sess.run(product2) print res

34.638298

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0.066915

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0.04461

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0.107807

0

0.023432

0.187346

1,628

46

117

35.391304

0.789872

0

0.064516

0

0.209121

0

null

0.032258

0.096774

null

0.064516

0

null

0

null

0

1

0

1

fe97e4775b3fbd1abdf826717d17fd4e96f2144c

353

py

Python

user_messages/context_processors.py

everaccountable/django-user-messages

101d539b785bdb440bf166fb16ad25eb66e4174a

[ "MIT" ]

21

2018-04-18T17:58:12.000Z

2022-01-19T12:41:01.000Z

user_messages/context_processors.py

everaccountable/django-user-messages

101d539b785bdb440bf166fb16ad25eb66e4174a

[ "MIT" ]

4

2018-04-24T11:04:15.000Z

2022-02-03T18:35:21.000Z

user_messages/context_processors.py

everaccountable/django-user-messages

101d539b785bdb440bf166fb16ad25eb66e4174a

[ "MIT" ]

7

2018-03-04T16:03:44.000Z

2022-02-03T15:50:39.000Z

from django.contrib.messages.constants import DEFAULT_LEVELS from user_messages.api import get_messages def messages(request): """ Return a lazy 'messages' context variable as well as 'DEFAULT_MESSAGE_LEVELS'. """ return { "messages": get_messages(request=request), "DEFAULT_MESSAGE_LEVELS": DEFAULT_LEVELS, }

23.533333

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0.708215

41

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5.878049

0.512195

0.107884

0.165975

0

0.203966

353

14

61

25.214286

0.857651

0.220963

0

0.117647

0.086275

0

1

0.142857

false

0

0.285714

0

0.571429

0

null

0

null

0

1

0

1

fe98a505a6e3e05977900098d14a4c4efb60654a

502

py

Python

Day_5/highest_score.py

ecanro/100DaysOfCode_Python

a86ebe5a793fd4743e0de87454ba76925efdd23d

[ "MIT" ]

null

Day_5/highest_score.py

ecanro/100DaysOfCode_Python

a86ebe5a793fd4743e0de87454ba76925efdd23d

[ "MIT" ]

null

Day_5/highest_score.py

ecanro/100DaysOfCode_Python

a86ebe5a793fd4743e0de87454ba76925efdd23d

[ "MIT" ]

null

## Highest Score # 🚨 Don't change the code below 👇 student_scores = input("Input a list of student scores: ").split() for n in range(0, len(student_scores)): student_scores[n] = int(student_scores[n]) print(student_scores) # 🚨 Don't change the code above 👆 # Write your code below this row 👇 highest_score = 0 for scores in student_scores: if scores > highest_score: highest_score = scores print(f'The highest score is: {highest_score}') # functional code print(max(student_scores))

26.421053

66

0.721116

82

502

4.341463

0.439024

0.292135

0.02809

0.061798

0.101124

0

0.004819

0.173307

502

19

67

26.421053

0.840964

0.250996

0

0.186486

0

1

0

false

0

0.3

0

null

1

0

null

0

1

fea585d93413c287bd31eaa0525d97e26cbdcd0b

742

py

Python

codeforces.com/1669F/solution.py

zubtsov/competitive-programming

919d63130144347d7f6eddcf8f5bc2afb85fddf3

[ "MIT" ]

null

codeforces.com/1669F/solution.py

zubtsov/competitive-programming

919d63130144347d7f6eddcf8f5bc2afb85fddf3

[ "MIT" ]

null

codeforces.com/1669F/solution.py

zubtsov/competitive-programming

919d63130144347d7f6eddcf8f5bc2afb85fddf3

[ "MIT" ]

null

for i in range(int(input())): number_of_candies = int(input()) candies_weights = list(map(int, input().split())) bob_pos = number_of_candies - 1 alice_pos = 0 bob_current_weight = 0 alice_current_weight = 0 last_equal_candies_total_number = 0 while alice_pos <= bob_pos: if alice_current_weight <= bob_current_weight: alice_current_weight += candies_weights[alice_pos] alice_pos += 1 else: bob_current_weight += candies_weights[bob_pos] bob_pos -= 1 if alice_current_weight == bob_current_weight: last_equal_candies_total_number = alice_pos + (number_of_candies - bob_pos - 1) print(last_equal_candies_total_number)

29.68

91

0.665768

100

742

4.47

0.27

0.232662

0.143177

0.14094

0.342282

0.161074

0

0.014467

0.254717

742

24

92

30.916667

0.793852

0

1

0

false

0

0.055556

0

null

1

0

null

0

1

feb04d32f16beda0e1b583eb23a6f47a91df44ef

695

py

Python

src/applications/blog/migrations/0003_post_author.py

alexander-sidorov/tms-z43

61ecd204f5de4e97ff0300f6ef91c36c2bcda31c

[ "MIT" ]

2

2020-12-17T20:19:21.000Z

2020-12-22T12:46:43.000Z

src/applications/blog/migrations/0003_post_author.py

alexander-sidorov/tms-z43

61ecd204f5de4e97ff0300f6ef91c36c2bcda31c

[ "MIT" ]

4

2021-04-20T08:40:30.000Z

2022-02-10T07:50:30.000Z

src/applications/blog/migrations/0003_post_author.py

alexander-sidorov/tms-z43

61ecd204f5de4e97ff0300f6ef91c36c2bcda31c

[ "MIT" ]

1

2021-02-10T06:42:19.000Z

# Generated by Django 3.1.7 on 2021-03-24 17:41 import django.db.models.deletion from django.conf import settings from django.db import migrations from django.db import models class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("blog", "0002_auto_20210323_1834"), ] operations = [ migrations.AddField( model_name="post", name="author", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, ), ), ]

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228122dba71ea421f33f3e5c51b862184d5fc4c8

205

py

Python

hubcare/metrics/community_metrics/issue_template/urls.py

aleronupe/2019.1-hubcare-api

3f031eac9559a10fdcf70a88ee4c548cf93e4ac2

[ "MIT" ]

7

2019-03-31T17:58:45.000Z

2020-02-29T22:44:27.000Z

hubcare/metrics/community_metrics/issue_template/urls.py

aleronupe/2019.1-hubcare-api

3f031eac9559a10fdcf70a88ee4c548cf93e4ac2

[ "MIT" ]

90

2019-03-26T01:14:54.000Z

2021-06-10T21:30:25.000Z

hubcare/metrics/community_metrics/issue_template/urls.py

aleronupe/2019.1-hubcare-api

3f031eac9559a10fdcf70a88ee4c548cf93e4ac2

[ "MIT" ]

null

from django.urls import path from issue_template.views import IssueTemplateView urlpatterns = [ path( '<str:owner>/<str:repo>/<str:token_auth>/', IssueTemplateView.as_view() ), ]

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22849e131dffff72236a4d1d46cddf477f92bab9

2,823

py

Python

src/collectors/rabbitmq/rabbitmq.py

lreed/Diamond

2772cdbc27a7ba3fedeb6d4241aeee9d2fcbdb80

[ "MIT" ]

null

src/collectors/rabbitmq/rabbitmq.py

lreed/Diamond

2772cdbc27a7ba3fedeb6d4241aeee9d2fcbdb80

[ "MIT" ]

null

src/collectors/rabbitmq/rabbitmq.py

lreed/Diamond

2772cdbc27a7ba3fedeb6d4241aeee9d2fcbdb80

[ "MIT" ]

null

# coding=utf-8 """ Collects data from RabbitMQ through the admin interface #### Notes * if two vhosts have the queues with the same name, the metrics will collide #### Dependencies * pyrabbit """ import diamond.collector try: from numbers import Number Number # workaround for pyflakes issue #13 import pyrabbit.api except ImportError: Number = None class RabbitMQCollector(diamond.collector.Collector): def get_default_config_help(self): config_help = super(RabbitMQCollector, self).get_default_config_help() config_help.update({ 'host': 'Hostname and port to collect from', 'user': 'Username', 'password': 'Password', 'queues': 'Queues to publish. Leave empty to publish all.', }) return config_help def get_default_config(self): """ Returns the default collector settings """ config = super(RabbitMQCollector, self).get_default_config() config.update({ 'path': 'rabbitmq', 'host': 'localhost:55672', 'user': 'guest', 'password': 'guest', }) return config def collect(self): if Number is None: self.log.error('Unable to import either Number or pyrabbit.api') return {} queues = [] if 'queues' in self.config: queues = self.config['queues'].split() try: client = pyrabbit.api.Client(self.config['host'], self.config['user'], self.config['password']) for queue in client.get_queues(): # skip queues we don't want to publish if queues and queue['name'] not in queues: continue for key in queue: name = '{0}.{1}'.format('queues', queue['name']) self._publish_metrics(name, [], key, queue) overview = client.get_overview() for key in overview: self._publish_metrics('', [], key, overview) except Exception, e: self.log.error('Couldnt connect to rabbitmq %s', e) return {} def _publish_metrics(self, name, prev_keys, key, data): """Recursively publish keys""" value = data[key] keys = prev_keys + [key] if isinstance(value, dict): for new_key in value: self._publish_metrics(name, keys, new_key, value) elif isinstance(value, Number): joined_keys = '.'.join(keys) if name: publish_key = '{0}.{1}'.format(name, joined_keys) else: publish_key = joined_keys self.publish(publish_key, value)

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null

0

null

0

null

0

1

0

1

2285470cfe61c3208efb829c668012f4eb4c042d

196

py

Python

classifier/cross_validation.py

ahmdrz/spam-classifier

a9cc3916a7c22545c82f0bfae7e4b95f3b36248f

[ "MIT" ]

1

2019-08-05T12:02:53.000Z

classifier/cross_validation.py

ahmdrz/spam-classifier

a9cc3916a7c22545c82f0bfae7e4b95f3b36248f

[ "MIT" ]

null

classifier/cross_validation.py

ahmdrz/spam-classifier

a9cc3916a7c22545c82f0bfae7e4b95f3b36248f

[ "MIT" ]

null

from sklearn.model_selection import KFold def kfold_cross_validation(data, k=10): kfold = KFold(n_splits=k) for train, test in kfold.split(data): yield data[train], data[test]

32.666667

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0.4

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null

0

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null

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1

228b1c94896beb15138918d15679461767abdb01

3,238

py

Python

examples/nlp/language_modeling/megatron_gpt_ckpt_to_nemo.py

rilango/NeMo

6f23ff725c596f25fab6043d95e7c0b4a5f56331

[ "Apache-2.0" ]

null

examples/nlp/language_modeling/megatron_gpt_ckpt_to_nemo.py

rilango/NeMo

6f23ff725c596f25fab6043d95e7c0b4a5f56331

[ "Apache-2.0" ]

null

examples/nlp/language_modeling/megatron_gpt_ckpt_to_nemo.py

rilango/NeMo

6f23ff725c596f25fab6043d95e7c0b4a5f56331

[ "Apache-2.0" ]

1

2021-12-07T08:15:36.000Z

# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from argparse import ArgumentParser import torch.multiprocessing as mp from pytorch_lightning.trainer.trainer import Trainer from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector from nemo.utils import AppState, logging def get_args(): parser = ArgumentParser() parser.add_argument( "--checkpoint_folder", type=str, default=None, required=True, help="Path to PTL checkpoints saved during training. Ex: /raid/nemo_experiments/megatron_gpt/checkpoints", ) parser.add_argument( "--checkpoint_name", type=str, default=None, required=True, help="Name of checkpoint to be used. Ex: megatron_gpt--val_loss=6.34-step=649-last.ckpt", ) parser.add_argument( "--hparams_file", type=str, default=None, required=False, help="Path config for restoring. It's created during training and may need to be modified during restore if restore environment is different than training. Ex: /raid/nemo_experiments/megatron_gpt/hparams.yaml", ) parser.add_argument("--nemo_file_path", type=str, default=None, required=True, help="Path to output .nemo file.") parser.add_argument("--tensor_model_parallel_size", type=int, required=True, default=None) args = parser.parse_args() return args def convert(rank, world_size, args): app_state = AppState() app_state.data_parallel_rank = 0 trainer = Trainer(gpus=args.tensor_model_parallel_size) # TODO: reach out to PTL For an API-safe local rank override trainer.accelerator.training_type_plugin._local_rank = rank if args.tensor_model_parallel_size is not None and args.tensor_model_parallel_size > 1: # inject model parallel rank checkpoint_path = os.path.join(args.checkpoint_folder, f'mp_rank_{rank:02d}', args.checkpoint_name) else: checkpoint_path = os.path.join(args.checkpoint_folder, args.checkpoint_name) model = MegatronGPTModel.load_from_checkpoint(checkpoint_path, hparams_file=args.hparams_file, trainer=trainer) model._save_restore_connector = NLPSaveRestoreConnector() model.save_to(args.nemo_file_path) logging.info(f'NeMo model saved to: {args.nemo_file_path}') def main() -> None: args = get_args() world_size = args.tensor_model_parallel_size mp.spawn(convert, args=(world_size, args), nprocs=world_size, join=True) if __name__ == '__main__': main() # noqa pylint: disable=no-value-for-parameter

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null

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null

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1

228b861994dfd3c8d5b7524f5b44ae49bacc2148

6,007

py

Python

sdk/python/pulumi_aws/apigateway/api_key.py

dixler/pulumi-aws

88838ed6d412c092717a916b0b5b154f68226c3a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/apigateway/api_key.py

dixler/pulumi-aws

88838ed6d412c092717a916b0b5b154f68226c3a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/apigateway/api_key.py

dixler/pulumi-aws

88838ed6d412c092717a916b0b5b154f68226c3a

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import json import warnings import pulumi import pulumi.runtime from typing import Union from .. import utilities, tables class ApiKey(pulumi.CustomResource): arn: pulumi.Output[str] """ Amazon Resource Name (ARN) """ created_date: pulumi.Output[str] """ The creation date of the API key """ description: pulumi.Output[str] """ The API key description. Defaults to "Managed by Pulumi". """ enabled: pulumi.Output[bool] """ Specifies whether the API key can be used by callers. Defaults to `true`. """ last_updated_date: pulumi.Output[str] """ The last update date of the API key """ name: pulumi.Output[str] """ The name of the API key """ tags: pulumi.Output[dict] """ Key-value mapping of resource tags """ value: pulumi.Output[str] """ The value of the API key. If not specified, it will be automatically generated by AWS on creation. """ def __init__(__self__, resource_name, opts=None, description=None, enabled=None, name=None, tags=None, value=None, __props__=None, __name__=None, __opts__=None): """ Provides an API Gateway API Key. > **NOTE:** Since the API Gateway usage plans feature was launched on August 11, 2016, usage plans are now **required** to associate an API key with an API stage. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] description: The API key description. Defaults to "Managed by Pulumi". :param pulumi.Input[bool] enabled: Specifies whether the API key can be used by callers. Defaults to `true`. :param pulumi.Input[str] name: The name of the API key :param pulumi.Input[dict] tags: Key-value mapping of resource tags :param pulumi.Input[str] value: The value of the API key. If not specified, it will be automatically generated by AWS on creation. > This content is derived from https://github.com/terraform-providers/terraform-provider-aws/blob/master/website/docs/r/api_gateway_api_key.html.markdown. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() if description is None: description = 'Managed by Pulumi' __props__['description'] = description __props__['enabled'] = enabled __props__['name'] = name __props__['tags'] = tags __props__['value'] = value __props__['arn'] = None __props__['created_date'] = None __props__['last_updated_date'] = None super(ApiKey, __self__).__init__( 'aws:apigateway/apiKey:ApiKey', resource_name, __props__, opts) @staticmethod def get(resource_name, id, opts=None, arn=None, created_date=None, description=None, enabled=None, last_updated_date=None, name=None, tags=None, value=None): """ Get an existing ApiKey resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param str id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] arn: Amazon Resource Name (ARN) :param pulumi.Input[str] created_date: The creation date of the API key :param pulumi.Input[str] description: The API key description. Defaults to "Managed by Pulumi". :param pulumi.Input[bool] enabled: Specifies whether the API key can be used by callers. Defaults to `true`. :param pulumi.Input[str] last_updated_date: The last update date of the API key :param pulumi.Input[str] name: The name of the API key :param pulumi.Input[dict] tags: Key-value mapping of resource tags :param pulumi.Input[str] value: The value of the API key. If not specified, it will be automatically generated by AWS on creation. > This content is derived from https://github.com/terraform-providers/terraform-provider-aws/blob/master/website/docs/r/api_gateway_api_key.html.markdown. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["arn"] = arn __props__["created_date"] = created_date __props__["description"] = description __props__["enabled"] = enabled __props__["last_updated_date"] = last_updated_date __props__["name"] = name __props__["tags"] = tags __props__["value"] = value return ApiKey(resource_name, opts=opts, __props__=__props__) def translate_output_property(self, prop): return tables._CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return tables._SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

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0

null

0

1

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null

0

1

228d76877f0d9f67ffc6dc7483c7c0a95962b0f9

864

py

Python

var/spack/repos/builtin/packages/perl-ipc-run/package.py

adrianjhpc/spack

0a9e4fcee57911f2db586aa50c8873d9cca8de92

[ "ECL-2.0", "Apache-2.0", "MIT" ]

2

2020-10-15T01:08:42.000Z

2021-10-18T01:28:18.000Z

var/spack/repos/builtin/packages/perl-ipc-run/package.py

adrianjhpc/spack

0a9e4fcee57911f2db586aa50c8873d9cca8de92

[ "ECL-2.0", "Apache-2.0", "MIT" ]

2

2019-07-30T10:12:28.000Z

2019-12-17T09:02:27.000Z

var/spack/repos/builtin/packages/perl-ipc-run/package.py

adrianjhpc/spack

0a9e4fcee57911f2db586aa50c8873d9cca8de92

[ "ECL-2.0", "Apache-2.0", "MIT" ]

5

2019-07-30T09:42:14.000Z

2021-01-25T05:39:20.000Z

# Copyright 2013-2019 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack import * class PerlIpcRun(PerlPackage): """IPC::Run allows you to run and interact with child processes using files, pipes, and pseudo-ttys. Both system()-style and scripted usages are supported and may be mixed. Likewise, functional and OO API styles are both supported and may be mixed.""" homepage = "https://metacpan.org/pod/IPC::Run" url = "https://cpan.metacpan.org/authors/id/T/TO/TODDR/IPC-Run-20180523.0.tar.gz" version('20180523.0', sha256='3850d7edf8a4671391c6e99bb770698e1c45da55b323b31c76310913349b6c2f') depends_on('perl-io-tty', type=('build', 'run')) depends_on('perl-readonly', type='build')

39.272727

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864

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864

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101

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0.571429

0

null

0

null

0

1

0

1

228e9262ba137f922fefb676a2a9e3eabc4bf87c

804

py

Python

src/tevatron/tevax/loss.py

vjeronymo2/tevatron

7235b0823b5c3cdf1c8ce8f67cb5f1209218086a

[ "Apache-2.0" ]

95

2021-09-16T00:35:17.000Z

2022-03-31T04:59:05.000Z

src/tevatron/tevax/loss.py

vjeronymo2/tevatron

7235b0823b5c3cdf1c8ce8f67cb5f1209218086a

[ "Apache-2.0" ]

16

2021-10-05T12:29:33.000Z

2022-03-31T17:59:20.000Z

src/tevatron/tevax/loss.py

vjeronymo2/tevatron

7235b0823b5c3cdf1c8ce8f67cb5f1209218086a

[ "Apache-2.0" ]

15

2021-09-19T02:20:03.000Z

2022-03-10T03:00:23.000Z

import jax.numpy as jnp from jax import lax import optax import chex def _onehot(labels: chex.Array, num_classes: int) -> chex.Array: x = labels[..., None] == jnp.arange(num_classes).reshape((1,) * labels.ndim + (-1,)) x = lax.select(x, jnp.ones(x.shape), jnp.zeros(x.shape)) return x.astype(jnp.float32) def p_contrastive_loss(ss: chex.Array, tt: chex.Array, axis: str = 'device') -> chex.Array: per_shard_targets = tt.shape[0] per_sample_targets = int(tt.shape[0] / ss.shape[0]) labels = jnp.arange(0, per_shard_targets, per_sample_targets) + per_shard_targets * lax.axis_index(axis) tt = lax.all_gather(tt, axis).reshape((-1, ss.shape[-1])) scores = jnp.dot(ss, jnp.transpose(tt)) return optax.softmax_cross_entropy(scores, _onehot(labels, scores.shape[-1]))

36.545455

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null

0

null

0

1

0

1

22915424775bb0c1cd95df8d2deeb30cca4451ba

1,845

py

Python

python_test.py

jackKiZhu/mypython

43eac97bec07338ed3b8b9473d4e4fae26f7140c

[ "MIT" ]

null

python_test.py

jackKiZhu/mypython

43eac97bec07338ed3b8b9473d4e4fae26f7140c

[ "MIT" ]

null

python_test.py

jackKiZhu/mypython

43eac97bec07338ed3b8b9473d4e4fae26f7140c

[ "MIT" ]

null

from flask import Flask, render_template, request from flask_sqlalchemy import SQLAlchemy app = Flask(__name__) app.config["SQLALCHEMY_DATABASE_URI"] = "mysql://root:mysql@127.0.0.1:3306/python_github" app.config["SQLALCHEMY_TRACK_MODIFICATIONS"] = True db = SQLAlchemy(app) class User(db.Model): id = db.Column(db.Integer, primary_key=True) user_name = db.Column(db.String(64), unique=True) user_password = db.Column(db.String(32)) def __repr__(self): return "用户id:%s 用户名:%s" % (self.id, self.user_name) @app.route("/", methods=["post", "get"]) def index(): index_meg = "" if request.method == "POST": user_name = request.form.get("user_name", "") user_pwd = request.form.get("user_pwd", "") if not all([user_name, user_pwd]): index_meg = "请正确输入信息" else: print(request.get_data()) user_name_is_exits = User.query.filter(User.user_name == user_name).first() if user_name_is_exits: index_meg = "用户名已存在" else: user_obj = User(user_name=user_name, user_password=user_pwd) db.session.add(user_obj) db.session.commit() index_meg = "注册成功" print("注册成功") # user_name = request.args.get("user_name", "") # user_pwd = request.args.get("user_pwd", "") # user_is_login = User.query.filter_by(user_name=user_name, user_password=user_pwd).first() # if user_is_login: # index_meg = "登陆成功" # print("登陆成功") # return render_template("login_ok.html", index_meg=index_meg) # else: # # index_meg = "登陆失败" # print("登陆失败") return render_template("index.html", index_meg=index_meg) if __name__ == "__main__": db.drop_all() db.create_all() app.run(debug=True)

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0

null

0

1

0

1

2293c25414f578bb3829ecd6692177ce5d098784

1,218

py

Python

python/tree/0103_binary_tree_zigzag_level_order_traversal.py

linshaoyong/leetcode

ea052fad68a2fe0cbfa5469398508ec2b776654f

[ "MIT" ]

6

2019-07-15T13:23:57.000Z

2020-01-22T03:12:01.000Z

python/tree/0103_binary_tree_zigzag_level_order_traversal.py

linshaoyong/leetcode

ea052fad68a2fe0cbfa5469398508ec2b776654f

[ "MIT" ]

null

python/tree/0103_binary_tree_zigzag_level_order_traversal.py

linshaoyong/leetcode

ea052fad68a2fe0cbfa5469398508ec2b776654f

[ "MIT" ]

1

2019-07-24T02:15:31.000Z

class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None class Solution(object): def zigzagLevelOrder(self, root): """ :type root: TreeNode :rtype: List[List[int]] """ if not root: return [] a = [root] b = [] c = [] r = [[root.val]] i = 1 while True: for n in a: if n.left: b.append(n.left) c.append(n.left.val) if n.right: b.append(n.right) c.append(n.right.val) if not b: break else: a = b if i & 1 == 1: c.reverse() r.append(c) b = [] c = [] i += 1 return r def test_zigzag_level_order(): a = TreeNode(3) b = TreeNode(9) c = TreeNode(20) d = TreeNode(15) e = TreeNode(7) a.left = b a.right = c c.left = d c.right = e assert Solution().zigzagLevelOrder(a) == [ [3], [20, 9], [15, 7] ]

21

46

0.374384

136

1,218

3.301471

0.352941

0.062361

0.035635

0

0.03005

0.50821

1,218

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21.368421

0.719533

0.036125

0

0.083333

0

0.020833

1

0.0625

false

0

0.145833

0

null

0

1

0

null

0

1

229f21bdd7be594d33b1093f3cb181d2690aa326

3,714

py

Python

pyroute/poi_osm.py

ftrimble/route-grower

d4343ecc9b13a3e1701c8460c8a1792d08b74567

[ "Apache-2.0" ]

null

pyroute/poi_osm.py

ftrimble/route-grower

d4343ecc9b13a3e1701c8460c8a1792d08b74567

[ "Apache-2.0" ]

null

pyroute/poi_osm.py

ftrimble/route-grower

d4343ecc9b13a3e1701c8460c8a1792d08b74567

[ "Apache-2.0" ]

null

#!/usr/bin/python #---------------------------------------------------------------- # OSM POI handler for pyroute # #------------------------------------------------------ # Copyright 2007, Oliver White # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. #------------------------------------------------------ from xml.sax import make_parser, handler from poi_base import * import os from xml.sax._exceptions import SAXParseException import urllib class osmPoiModule(poiModule, handler.ContentHandler): def __init__(self, modules): poiModule.__init__(self, modules) self.draw = False self.loadPOIs("all", "amenity|shop=*") def loadPOIs(self, name, search): filename = os.path.join(os.path.dirname(__file__), "data", "poi_%s.osm" % name) url = "http://www.informationfreeway.org/api/0.5/node[%s][%s]" %(search, self.bbox()) if(not os.path.exists(filename)): print "Downloading POIs from OSM" urllib.urlretrieve(url, filename) self.load(filename, os.path.join(os.path.dirname(__file__), "Setup", "poi.txt")) def bbox(self): # TODO: based on location! return "bbox=-6,48,2.5,61" def load(self, filename, listfile): self.filters = [] print "Loading POIs from %s" % listfile f = open(listfile,"r") try: for line in f: if(len(line) > 1): text = line.rstrip() name, filter = text.split('|') group = poiGroup(name) self.groups.append(group) self.filters.append({'name':name,'filter':filter,'group':group}) finally: f.close() if(not os.path.exists(filename)): print "Can't load %s"%filename return elif not os.path.getsize(filename): print "%s is empty"%filename self.inNode = False parser = make_parser() parser.setContentHandler(self) try: parser.parse(filename) except SAXParseException: print "Error while parsing file" #TODO: what should now happens? def startElement(self, name, attrs): if name == "node": self.currentNode = { \ 'lat': float(attrs.get('lat')), 'lon': float(attrs.get('lon'))} self.inNode = True if name == "tag" and self.inNode: self.currentNode[attrs.get('k')] = attrs.get('v') def endElement(self, name): if(name == "node"): self.storeNode(self.currentNode) self.inNode = False def passesFilter(self,n,f): parts = f.split(';') matched = True for part in parts: k,v = part.split('=',1) if(n.get(k,'') != v): matched = False return(matched) def storeNode(self, n): for f in self.filters: if(self.passesFilter(n,f['filter'])): x = poi(n['lat'], n['lon']) x.title = n.get('amenity','') + ': ' + n.get('name', '?') #print "%s matches %s" % (x.title, f['name']) f['group'].items.append(x) def save(self): # Default filename if none was loaded if(self.filename == None): self.filename = os.path.join(os.path.dirname(__file__), "data", "poi.osm") self.saveAs(self.filename) def saveAs(self,filename): if(filename == None): return pass if __name__ == "__main__": nodes = osmPoiModule(None) nodes.sort({'valid':True,'lat':51.3,'lon':-0.2}) #nodes.report()

29.244094

74

0.630856

510

3,714

4.529412

0.398039

0.023377

0.016883

0.024675

0.112987

0.101732

0.077489

0.051515

0.036364

0

0.006881

0.178244

3,714

126

75

29.47619

0.75

0.270328

0

0.093023

0

0.116201

0

0.007937

0

null

0.034884

0.05814

null

0.05814

0

null

0

null

0

1

0

1

22a26cac9546e3d04238eea2e14e595751d5270c

11,429

py

Python

geo_regions.py

saeed-moghimi-noaa/Maxelev_plot

5bb701d8cb7d64db4c89ea9d7993a8269e57e504

[ "CC0-1.0" ]

null

geo_regions.py

saeed-moghimi-noaa/Maxelev_plot

5bb701d8cb7d64db4c89ea9d7993a8269e57e504

[ "CC0-1.0" ]

null

geo_regions.py

saeed-moghimi-noaa/Maxelev_plot

5bb701d8cb7d64db4c89ea9d7993a8269e57e504

[ "CC0-1.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Geo regions for map plot """ __author__ = "Saeed Moghimi" __copyright__ = "Copyright 2017, UCAR/NOAA" __license__ = "GPL" __version__ = "1.0" __email__ = "moghimis@gmail.com" import matplotlib.pyplot as plt from collections import defaultdict defs = defaultdict(dict) defs['elev']['var'] = 'elev' defs['elev']['vmin'] = -1 defs['elev']['vmax'] = 1 defs['elev']['label'] = 'Elev. [m]' defs['elev']['format']= '%3.1g' defs['elev']['cmap'] = plt.cm.jet_r def get_region_extent(region = 'hsofs_region'): if region == 'hsofs_region': defs['lim']['xmin'] = -99.0 defs['lim']['xmax'] = -52.8 defs['lim']['ymin'] = 5.0 defs['lim']['ymax'] = 46.3 ##IKE elif region == 'caribbean': defs['lim']['xmin'] = -78. defs['lim']['xmax'] = -74. defs['lim']['ymin'] = 20. defs['lim']['ymax'] = 24. defs['lim']['xmin'] = -82. defs['lim']['xmax'] = -71. defs['lim']['ymin'] = 18. defs['lim']['ymax'] = 26. elif region == 'ike_region': defs['lim']['xmin'] = -98.5 defs['lim']['xmax'] = -84.5 defs['lim']['ymin'] = 24. defs['lim']['ymax'] = 31.5 elif region == 'caribbean_bigger': defs['lim']['xmin'] = -78.0 defs['lim']['xmax'] = -58 defs['lim']['ymin'] = 10.0 defs['lim']['ymax'] = 28. elif region == 'ike_local': defs['lim']['xmin'] = -96 defs['lim']['xmax'] = -92 defs['lim']['ymin'] = 28.5 defs['lim']['ymax'] = 30.6 elif region == 'ike_wave': defs['lim']['xmin'] = -95.63 defs['lim']['xmax'] = -88.0 defs['lim']['ymin'] = 28.37 defs['lim']['ymax'] = 30.50 elif region == 'ike_hwm': defs['lim']['xmin'] = -96.15 defs['lim']['xmax'] = -88.5 defs['lim']['ymin'] = 28.45 defs['lim']['ymax'] = 30.7 elif region == 'ike_galv_bay': defs['lim']['xmin'] = -95.92 defs['lim']['xmax'] = -94.81 defs['lim']['ymin'] = 29.37 defs['lim']['ymax'] = 29.96 elif region == 'ike_galv_nwm': defs['lim']['xmin'] = -95.4 defs['lim']['xmax'] = -94.2 defs['lim']['ymin'] = 28.66 defs['lim']['ymax'] = 30.4 elif region == 'ike_wav_break': defs['lim']['xmin'] = -95 defs['lim']['xmax'] = -94.5 defs['lim']['ymin'] = 28.7 + 0.6 defs['lim']['ymax'] = 30.4 - 0.6 elif region == 'ike_f63_timeseries': defs['lim']['xmin'] = -94.2579 - 0.1 defs['lim']['xmax'] = -94.2579 + 0.1 defs['lim']['ymin'] = 29.88642 - 0.1 defs['lim']['ymax'] = 29.88642 + 0.1 elif region == 'ike_f63_timeseries_det': defs['lim']['xmin'] = -94.2300 defs['lim']['xmax'] = -94.1866 defs['lim']['ymin'] = 29.82030 defs['lim']['ymax'] = 29.84397+0.05 elif region == 'ike_cpl_paper': defs['lim']['xmin'] = -95.127481 defs['lim']['xmax'] = -93.233053 defs['lim']['ymin'] = 29.198490 defs['lim']['ymax'] = 30.132224 ##IRMA elif region == 'carib_irma': defs['lim']['xmin'] = -84.0 defs['lim']['xmax'] = -60. defs['lim']['ymin'] = 15.0 defs['lim']['ymax'] = 29. elif region == 'burbuda': defs['lim']['xmin'] = -65.0 defs['lim']['xmax'] = -60. defs['lim']['ymin'] = 15.0 defs['lim']['ymax'] = 19. elif region == 'burbuda_zoom': defs['lim']['xmin'] = -63.8 defs['lim']['xmax'] = -60.8 defs['lim']['ymin'] = 16.8 defs['lim']['ymax'] = 18.65 elif region == 'puertorico': defs['lim']['xmin'] = -67.35 defs['lim']['xmax'] = -66.531 defs['lim']['ymin'] = 18.321 defs['lim']['ymax'] = 18.674 elif region == 'puertorico_shore': defs['lim']['xmin'] = -67.284 defs['lim']['xmax'] = -66.350 defs['lim']['ymin'] = 18.360 defs['lim']['ymax'] = 18.890 elif region == 'key_west': defs['lim']['xmin'] = -82.7 defs['lim']['xmax'] = -74.5 defs['lim']['ymin'] = 21.3 defs['lim']['ymax'] = 27.2 elif region == 'key_west_zoom': defs['lim']['xmin'] = -82.2 defs['lim']['xmax'] = -79.4 defs['lim']['ymin'] = 24.1 defs['lim']['ymax'] = 26.1 elif region == 'cuba_zoom': defs['lim']['xmin'] = -82. defs['lim']['xmax'] = -77. defs['lim']['ymin'] = 21.5 defs['lim']['ymax'] = 23.5 elif region == 'key_west_timeseries': defs['lim']['xmin'] = -84.62 defs['lim']['xmax'] = -79.2 defs['lim']['ymin'] = 23.6 defs['lim']['ymax'] = 30.0 elif region == 'pr_timeseries': defs['lim']['xmin'] = -68 defs['lim']['xmax'] = -64 defs['lim']['ymin'] = 17.3 defs['lim']['ymax'] = 19.2 elif region == 'key_west_anim': defs['lim']['xmin'] = -85.5 defs['lim']['xmax'] = -74.5 defs['lim']['ymin'] = 21.0 defs['lim']['ymax'] = 31.5 ## ISABEL elif region == 'isa_region': defs['lim']['xmin'] = -80.2 defs['lim']['xmax'] = -71.6 defs['lim']['ymin'] = 31.9 defs['lim']['ymax'] = 41.9 elif region == 'isa_local': defs['lim']['xmin'] = -77.5 defs['lim']['xmax'] = -74 defs['lim']['ymin'] = 34.5 defs['lim']['ymax'] = 40.0 defs['lim']['xmin'] = -78.5 defs['lim']['xmax'] = -74 defs['lim']['ymin'] = 33.5 defs['lim']['ymax'] = 39.5 elif region == 'isa_hwm': defs['lim']['xmin'] = -76.01 defs['lim']['xmax'] = -75.93 defs['lim']['ymin'] = 36.74 defs['lim']['ymax'] = 36.93 elif region == 'isa_landfall': defs['lim']['xmin'] = -77.8 defs['lim']['xmax'] = -75.2 defs['lim']['ymin'] = 34.2 defs['lim']['ymax'] = 37.5 elif region == 'isa_landfall_zoom': defs['lim']['xmin'] = -77.8 defs['lim']['xmax'] = -75.2 defs['lim']['ymin'] = 34.2 defs['lim']['ymax'] = 36.0 ## SANDY elif region == 'san_track': defs['lim']['xmin'] = -82.0 defs['lim']['xmax'] = -67.0 defs['lim']['ymin'] = 23.0 defs['lim']['ymax'] = 43.6 elif region == 'san_area': defs['lim']['xmin'] = -77.0 defs['lim']['xmax'] = -70.0 defs['lim']['ymin'] = 37.0 defs['lim']['ymax'] = 42.0 elif region == 'san_track': defs['lim']['xmin'] = -82.0 defs['lim']['xmax'] = -67.0 defs['lim']['ymin'] = 23.0 defs['lim']['ymax'] = 43.6 elif region == 'san_area': defs['lim']['xmin'] = -77.0 defs['lim']['xmax'] = -70.0 defs['lim']['ymin'] = 37.0 defs['lim']['ymax'] = 42.0 elif region == 'san_area2': defs['lim']['xmin'] = -75.9 defs['lim']['xmax'] = -73.3 defs['lim']['ymin'] = 38.5 defs['lim']['ymax'] = 41.3 elif region == 'san_newyork': defs['lim']['xmin'] = -74.5 defs['lim']['xmax'] = -73.55 defs['lim']['ymin'] = 40.35 defs['lim']['ymax'] = 41.2 elif region == 'san_delaware': defs['lim']['xmin'] = -75.87 defs['lim']['xmax'] = -74.31 defs['lim']['ymin'] = 38.26 defs['lim']['ymax'] = 40.51 elif region == 'san_jamaica_bay': defs['lim']['xmin'] = -73.963520 defs['lim']['xmax'] = -73.731455 defs['lim']['ymin'] = 40.518074 defs['lim']['ymax'] = 40.699618 elif region == 'irn_region': defs['lim']['xmin'] = -78.41 defs['lim']['xmax'] = -73.48 defs['lim']['ymin'] = 33.55 defs['lim']['ymax'] = 41.31 elif region == 'irn_hwm': defs['lim']['xmin'] = -78.64 defs['lim']['xmax'] = -69.54 defs['lim']['ymin'] = 33.80 defs['lim']['ymax'] = 41.82 ## ANDREW elif region == 'and_region': defs['lim']['xmin'] = -98.5 defs['lim']['xmax'] = -77.5 defs['lim']['ymin'] = 23. defs['lim']['ymax'] = 32. elif region == 'and_fl_lu': defs['lim']['xmin'] = -98.5 defs['lim']['xmax'] = -76.5 defs['lim']['ymin'] = 21. defs['lim']['ymax'] = 32. elif region == 'and_local_lu': defs['lim']['xmin'] = -95 defs['lim']['xmax'] = -86 defs['lim']['ymin'] = 28. defs['lim']['ymax'] = 32 elif region == 'and_local_fl': defs['lim']['xmin'] = -86 defs['lim']['xmax'] = -79.5 defs['lim']['ymin'] = 24. defs['lim']['ymax'] = 34 elif region == 'and_local_lu_landfall': defs['lim']['xmin'] = -92.4 defs['lim']['xmax'] = -87.5 defs['lim']['ymin'] = 28. defs['lim']['ymax'] = 31. elif region == 'and_local_fl_landfall': defs['lim']['xmin'] = -80.0 defs['lim']['xmax'] = -80.5 defs['lim']['ymin'] = 25.34 defs['lim']['ymax'] = 25.8 ## operational upgrade # NYC area: -74.027725,40.596099 elif region == 'NYC_area': defs['lim']['xmin'] = -74.027725 - 0.25 defs['lim']['xmax'] = -74.027725 + 0.25 defs['lim']['ymin'] = 40.596099 - 0.2 defs['lim']['ymax'] = 40.596099 + 0.2 # Tampa area: -82.455511,27.921438 elif region == 'Tampa_area': defs['lim']['xmin'] = -82.455511 - 0.25 defs['lim']['xmax'] = -82.455511 + 0.25 defs['lim']['ymin'] = 27.921438 - 0.2 defs['lim']['ymax'] = 27.921438 + 0.2 # Marshall Islands: 169.107299,7.906637 elif region == 'Marshall': defs['lim']['xmin'] = 169.107299 - 0.25 defs['lim']['xmax'] = 169.107299 + 0.25 defs['lim']['ymin'] = 7.906637 - 0.2 defs['lim']['ymax'] = 7.906637 + 0.2 # Palau: 134.461436,7.436438 elif region == 'Palau': defs['lim']['xmin'] = 134.461436 - 0.25 defs['lim']['xmax'] = 134.461436 + 0.25 defs['lim']['ymin'] = 7.436438 - 0.2 defs['lim']['ymax'] = 7.436438 + 0.2 elif region == 'NYC_Area_m': defs['lim']['xmin'] = -73.55 defs['lim']['xmax'] = -74.26 defs['lim']['ymin'] = 40.55 defs['lim']['ymax'] = 40.91 elif region == 'Tampa_Area_m': defs['lim']['xmin'] = -82.37 defs['lim']['xmax'] = -82.75 defs['lim']['ymin'] = 27.63 defs['lim']['ymax'] = 28.05 elif region == 'Marshall_Islands_m': defs['lim']['xmin'] = 164.92 defs['lim']['xmax'] = 173.45 defs['lim']['ymin'] = 5.10 defs['lim']['ymax'] = 11.90 elif region == 'Palau_m': defs['lim']['xmin'] = 134.01 defs['lim']['xmax'] = 134.78 defs['lim']['ymin'] = 6.78 defs['lim']['ymax'] = 8.52 elif region == 'Port_Arthur_m': defs['lim']['xmin'] = -93.60 defs['lim']['xmax'] = -94.24 defs['lim']['ymin'] = 29.62 defs['lim']['ymax'] = 30.14 return defs['lim']

34.116418

52

0.441683

1,473

11,429

3.361847

0.157502

0.318053

0.124394

0.024233

0.30937

0.240913

0.197294

0.160339

0.122577

0.099152

0

0.125334

0.313063

11,429

334

53

34.218563

0.505413

0.021262

0

0.166667

0

0.209031

0.005734

0

1

0.003401

false

0

0.006803

0

0.013605

0

null

1

0

null

0

1

22a96894a0336c7d7df8e78f4c4c6ea30cbd0530

1,507

py

Python

microservices/validate/tools/validates.py

clodonil/pipeline_aws_custom

8ca517d0bad48fe528461260093f0035f606f9be

[ "Apache-2.0" ]

null

microservices/validate/tools/validates.py

clodonil/pipeline_aws_custom

8ca517d0bad48fe528461260093f0035f606f9be

[ "Apache-2.0" ]

null

microservices/validate/tools/validates.py

clodonil/pipeline_aws_custom

8ca517d0bad48fe528461260093f0035f606f9be

[ "Apache-2.0" ]

null

""" Tools para validar o arquivo template recebido do SQS """ class Validate: def __init__(self): pass def check_validate_yml(self, template): """ valida se o arquivo yml é valido """ if template: return True else: return False def check_yml_struct(self, template): """ Valida se a estrutura do yml é valido """ if template: return True else: return False def check_template_exist(self, template): """ Valida se o template informado no arquivo yml existe """ if template: return True else: return False def check_callback_protocol_endpoint(self, template): """ validar se o protocolo e endpoint são validos """ return True def check_template(self, template): if self.check_validate_yml(template) \ and self.check_yml_struct(template) \ and self.check_template_exist(template) \ and self.check_callback_protocol_endpoint(template): msg = {"status": True} return msg else: msg = {'status': False, 'message': 'problema no arquivo yml'} return msg def change_yml_to_json(content): try: template_json = yaml.safe_load(content) return template_json except yaml.YAMLError as error: return {"message": str(error)}

25.542373

73

0.568016

166

1,507

4.981928

0.349398

0.048368

0.065296

0.072551

0.230955

0.180169

0.128174

0

0.357664

1,507

58

74

25.982759

0.854339

0.147976

0

0.444444

0

0.041385

0

1

0.194444

false

0.027778

0

0.527778

0

null

0

null

0

1

0

1

22ac34a9639b610355752302f9ba8f423e657538

436

py

Python

Specialization/Personal/SortHours.py

lastralab/Statistics

358679f2e749db2e23c655795b34382c84270704

[ "MIT" ]

3

2017-09-26T20:19:57.000Z

2020-02-03T16:59:59.000Z

Specialization/Personal/SortHours.py

lastralab/Statistics

358679f2e749db2e23c655795b34382c84270704

[ "MIT" ]

1

2017-09-22T13:57:04.000Z

2017-09-26T20:03:24.000Z

Specialization/Personal/SortHours.py

lastralab/Statistics

358679f2e749db2e23c655795b34382c84270704

[ "MIT" ]

3

2018-05-09T01:41:16.000Z

2019-01-16T15:32:59.000Z

name = "mail.txt" counts = dict() handle = open(name) for line in handle: line = line.rstrip() if line == '': continue words = line.split() if words[0] == 'From': counts[words[5][:2]] = counts.get(words[5][:2], 0) + 1 tlist = list() for key, value in counts.items(): newtup = (key, value) tlist.append(newtup) tlist.sort() for key, value in tlist: print key, value

18.956522

64

0.548165

60

436

3.983333

0.5

0.133891

0.058577

0.108787

0

0.022654

0.291284

436

22

65

19.818182

0.750809

0

0.027523

0

null

0

null

0.058824

0

null

0

null

0

1

0

1

22ae53d11248d624a0ee5f564b8dd2e374ddaa54

606

py

Python

Day 2/Day_2_Python.py

giTan7/30-Days-Of-Code

f023a2bf1b5e58e1eb5180162443b9cd4b6b2ff8

[ "MIT" ]

1

2020-10-15T14:44:08.000Z

Day 2/Day_2_Python.py

giTan7/30-Days-Of-Code

f023a2bf1b5e58e1eb5180162443b9cd4b6b2ff8

[ "MIT" ]

null

Day 2/Day_2_Python.py

giTan7/30-Days-Of-Code

f023a2bf1b5e58e1eb5180162443b9cd4b6b2ff8

[ "MIT" ]

null

#!/bin/python3 import math import os import random import re import sys # Complete the solve function below. def solve(meal_cost, tip_percent, tax_percent): tip = (meal_cost * tip_percent)/100 tax = (meal_cost * tax_percent)/100 print(int(meal_cost + tip + tax + 0.5)) # We add 0.5 because the float should be rounded to the nearest integer if __name__ == '__main__': meal_cost = float(input()) tip_percent = int(input()) tax_percent = int(input()) solve(meal_cost, tip_percent, tax_percent) # Time complexity: O(1) # Space complexity: O(1)

22.444444

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606

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0.115789

0.142105

0.173684

0

0.027957

0.232673

606

26

77

23.307692

0.789247

0.268977

0

0.019417

0

1

0.071429

false

0

0.357143

0

0.428571

0.071429

0

null

0

null

0

1

0

1

22aec8fbe47f7975a1e7f4a0caa5c88c56e4a03e

1,133

py

Python

data/train/python/22aec8fbe47f7975a1e7f4a0caa5c88c56e4a03e__init__.py

harshp8l/deep-learning-lang-detection

2a54293181c1c2b1a2b840ddee4d4d80177efb33

[ "MIT" ]

84

2017-10-25T15:49:21.000Z

2021-11-28T21:25:54.000Z

data/train/python/22aec8fbe47f7975a1e7f4a0caa5c88c56e4a03e__init__.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

5

2018-03-29T11:50:46.000Z

2021-04-26T13:33:18.000Z

data/train/python/22aec8fbe47f7975a1e7f4a0caa5c88c56e4a03e__init__.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

24

2017-11-22T08:31:00.000Z

2022-03-27T01:22:31.000Z

def save_form(form, actor=None): """Allows storing a form with a passed actor. Normally, Form.save() does not accept an actor, but if you require this to be passed (is not handled by middleware), you can use this to replace form.save(). Requires you to use the audit.Model model as the actor is passed to the object's save method. """ obj = form.save(commit=False) obj.save(actor=actor) form.save_m2m() return obj #def intermediate_save(instance, actor=None): # """Allows saving of an instance, without storing the changes, but keeping the history. This allows you to perform # intermediate saves: # # obj.value1 = 1 # intermediate_save(obj) # obj.value2 = 2 # obj.save() # <value 1 and value 2 are both stored in the database> # """ # if hasattr(instance, '_audit_changes'): # tmp = instance._audit_changes # if actor: # instance.save(actor=actor) # else: # instance.save() # instance._audit_changes = tmp # else: # if actor: # instance.save(actor=actor) # else: # instance.save()

32.371429

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1,133

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0.059238

0.06488

0.126939

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0.263019

1,133

34

119

33.323529

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1

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0.4

0

null

0

1

0

null

0

1

22b2735d6e9bb2b53a0a0541af9ec0a4bc2db7e4

738

py

Python

pair.py

hhgarnes/python-validity

82b42e4fd152f10f75584de56502fd9ada299bb5

[ "MIT" ]

null

pair.py

hhgarnes/python-validity

82b42e4fd152f10f75584de56502fd9ada299bb5

[ "MIT" ]

null

pair.py

hhgarnes/python-validity

82b42e4fd152f10f75584de56502fd9ada299bb5

[ "MIT" ]

null

from time import sleep from proto9x.usb import usb from proto9x.tls import tls from proto9x.flash import read_flash from proto9x.init_flash import init_flash from proto9x.upload_fwext import upload_fwext from proto9x.calibrate import calibrate from proto9x.init_db import init_db #usb.trace_enabled=True #tls.trace_enabled=True def restart(): print('Sleeping...') sleep(3) tls.reset() usb.open() usb.send_init() tls.parseTlsFlash(read_flash(1, 0, 0x1000)) tls.open() usb.open() print('Initializing flash...') init_flash() restart() print('Uploading firmware...') upload_fwext() restart() print('Calibrating...') calibrate() print('Init database...') init_db() print('That\'s it, pairing\'s finished')

18.45

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0.023511

0.135501

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0.214286

0

null

0

null

0

1

0

1

22b61a63d3fab6ac5a4af3febf6a8b869aa2fb13

926

py

Python

tests/tools/test-tcp4-client.py

jimmy-huang/zephyr.js

cef5c0dffaacf7d5aa3f8265626f68a1e2b32eb5

[ "Apache-2.0" ]

null

tests/tools/test-tcp4-client.py

jimmy-huang/zephyr.js

cef5c0dffaacf7d5aa3f8265626f68a1e2b32eb5

[ "Apache-2.0" ]

null

tests/tools/test-tcp4-client.py

jimmy-huang/zephyr.js

cef5c0dffaacf7d5aa3f8265626f68a1e2b32eb5

[ "Apache-2.0" ]

null

# !usr/bin/python # coding:utf-8 import time import socket def main(): print "Socket client creat successful" host = "192.0.2.1" port = 9876 bufSize = 1024 addr = (host, port) Timeout = 300 mySocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) mySocket.settimeout(Timeout) mySocket.connect(addr) while 1: try : Data = mySocket.recv(bufSize) Data = Data.strip() print "Got data: ", Data time.sleep(2) if Data == "close": mySocket.close() print "close socket" break else: mySocket.sendall(Data) print "Send data: ", Data except KeyboardInterrupt : print "exit client" break except : print "time out" continue if __name__ == "__main__" : main()

20.577778

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0.512959

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4.894737

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0.051613

0

0.035651

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0.181818

0

null

0

null

0

1

0

1

22b976d4af390f9c20bc3dedbfcb6376fdbf0308

5,277

py

Python

hw2/deeplearning/style_transfer.py

axelbr/berkeley-cs182-deep-neural-networks

2bde27d9d5361d48dce7539d00b136209c1cfaa1

[ "MIT" ]

null

hw2/deeplearning/style_transfer.py

axelbr/berkeley-cs182-deep-neural-networks

2bde27d9d5361d48dce7539d00b136209c1cfaa1

[ "MIT" ]

null

hw2/deeplearning/style_transfer.py

axelbr/berkeley-cs182-deep-neural-networks

2bde27d9d5361d48dce7539d00b136209c1cfaa1

[ "MIT" ]

null

import numpy as np import torch import torch.nn.functional as F def content_loss(content_weight, content_current, content_target): """ Compute the content loss for style transfer. Inputs: - content_weight: Scalar giving the weighting for the content loss. - content_current: features of the current image; this is a PyTorch Tensor of shape (1, C_l, H_l, W_l). - content_target: features of the content image, Tensor with shape (1, C_l, H_l, W_l). Returns: - scalar content loss """ ############################################################################## # YOUR CODE HERE # ############################################################################## _, C, H, W = content_current.shape current_features = content_current.view(C, H*W) target_features = content_target.view(C, H*W) loss = content_weight * torch.sum(torch.square(current_features - target_features)) return loss ############################################################################## # END OF YOUR CODE # ############################################################################## def gram_matrix(features, normalize=True): """ Compute the Gram matrix from features. Inputs: - features: PyTorch Variable of shape (N, C, H, W) giving features for a batch of N images. - normalize: optional, whether to normalize the Gram matrix If True, divide the Gram matrix by the number of neurons (H * W * C) Returns: - gram: PyTorch Variable of shape (N, C, C) giving the (optionally normalized) Gram matrices for the N input images. """ ############################################################################## # YOUR CODE HERE # ############################################################################## C, H, W = features.shape[-3], features.shape[-2], features.shape[-1] reshaped = features.view(-1, C, H*W) G = reshaped @ reshaped.transpose(dim0=1, dim1=2) if normalize: G = G / (H*W*C) return G ############################################################################## # END OF YOUR CODE # ############################################################################## def style_loss(feats, style_layers, style_targets, style_weights): """ Computes the style loss at a set of layers. Inputs: - feats: list of the features at every layer of the current image, as produced by the extract_features function. - style_layers: List of layer indices into feats giving the layers to include in the style loss. - style_targets: List of the same length as style_layers, where style_targets[i] is a PyTorch Variable giving the Gram matrix the source style image computed at layer style_layers[i]. - style_weights: List of the same length as style_layers, where style_weights[i] is a scalar giving the weight for the style loss at layer style_layers[i]. Returns: - style_loss: A PyTorch Variable holding a scalar giving the style loss. """ # Hint: you can do this with one for loop over the style layers, and should # not be very much code (~5 lines). You will need to use your gram_matrix function. ############################################################################## # YOUR CODE HERE # ############################################################################## loss = 0 for i, l in enumerate(style_layers): A, G = style_targets[i], gram_matrix(feats[l]) loss += style_weights[i] * torch.sum(torch.square(G - A)) return loss ############################################################################## # END OF YOUR CODE # ############################################################################## def tv_loss(img, tv_weight): """ Compute total variation loss. Inputs: - img: PyTorch Variable of shape (1, 3, H, W) holding an input image. - tv_weight: Scalar giving the weight w_t to use for the TV loss. Returns: - loss: PyTorch Variable holding a scalar giving the total variation loss for img weighted by tv_weight. """ # Your implementation should be vectorized and not require any loops! ############################################################################## # YOUR CODE HERE # ############################################################################## tv = torch.square(img[..., 1:, :-1] - img[..., :-1, :-1]) + torch.square(img[..., :-1, 1:] - img[..., :-1, :-1]) return tv_weight * torch.sum(tv) ############################################################################## # END OF YOUR CODE # ##############################################################################

45.886957

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0.437938

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4.25188

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0.157383

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0

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5,277

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46.289474

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false

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0.44

0

null

0

null

0

1

0

1

22c0a198d3ffbdb90c8a504d310e057f35103de5

2,740

py

Python

site_settings/models.py

shervinbdndev/Django-Shop

baa4e7b91fbdd01ee591049c12cd9fbfaa434379

[ "MIT" ]

13

2022-02-25T05:04:58.000Z

2022-03-15T10:55:24.000Z

site_settings/models.py

iTsSobhan/Django-Shop

9eb6a08c6e93e5401d6bc2eeb30f2ef35adec730

[ "MIT" ]

null

site_settings/models.py

iTsSobhan/Django-Shop

9eb6a08c6e93e5401d6bc2eeb30f2ef35adec730

[ "MIT" ]

1

2022-03-03T09:21:49.000Z

from django.db import models class SiteSettings(models.Model): site_name = models.CharField(max_length=200 , verbose_name='Site Name') site_url = models.CharField(max_length=200 , verbose_name='Site URL') site_address = models.CharField(max_length=300 , verbose_name='Site Address') site_phone = models.CharField(max_length=100 , null=True , blank=True , verbose_name='Site Phone') site_fax = models.CharField(max_length=200 , null=True , blank=True , verbose_name='Site Fax') site_email = models.EmailField(max_length=200 , null=True , blank=True , verbose_name='Site Email') about_us_text = models.TextField(verbose_name='About Us Text') site_copy_right = models.TextField(verbose_name='Copyright Text') site_logo = models.ImageField(upload_to='images/site-setting/' , verbose_name='Site Logo') is_main_setting = models.BooleanField(verbose_name='Site Main Settings') def __str__(self) -> str: super(SiteSettings , self).__str__() return self.site_name class Meta: verbose_name = 'Site Setting' verbose_name_plural = 'Site Settings' class FooterLinkBox(models.Model): title = models.CharField(max_length=200 , verbose_name='Title') def __str__(self) -> str: super(FooterLinkBox , self).__str__() return self.title class Meta: verbose_name = 'Footer Link Setting' verbose_name_plural = 'Footer Link Settings' class FooterLink(models.Model): title = models.CharField(max_length=200 , verbose_name='Title') url = models.URLField(max_length=500 , verbose_name='Links') footer_link_box = models.ForeignKey(to=FooterLinkBox , verbose_name='Category' , on_delete=models.CASCADE) def __str__(self) -> str: super(FooterLink , self).__str__() return self.title class Meta: verbose_name = 'Footer Link' verbose_name_plural = 'Footer Links' class Slider(models.Model): title = models.CharField(max_length=200 , verbose_name='Title') description = models.TextField(verbose_name='Slider Description') url_title = models.CharField(max_length=200 , verbose_name='URL Title') url = models.URLField(max_length=200 , verbose_name='URL Address') image = models.ImageField(upload_to='images/sliders' , verbose_name='Slider Image') is_active = models.BooleanField(default=False , verbose_name='Active / Inactive') def __str__(self) -> str: super(Slider , self).__str__() return self.title class Meta: verbose_name = 'Slider' verbose_name_plural = 'Sliders'

36.052632

110

0.670073

329

2,740

5.285714

0.218845

0.177113

0.093157

0.124209

0.456584

0.372053

0.327775

0.309373

0.236343

0.212191

0

0.016941

0.224453

2,740

76

111

36.052632

0.801412

0

0.285714

0

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0

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false

0

0.020408

0

0.755102

0

null

0

null

0

1

0

1

22c745e9fe90945bd78c2b0b4951b89a65ce5057

3,482

py

Python

py_hanabi/card.py

krinj/hanabi-simulator

b77b04aa09bab8bd8d7b784e04bf8b9d5d76d1a6

[ "MIT" ]

1

2018-09-28T00:47:52.000Z

py_hanabi/card.py

krinj/hanabi-simulator

b77b04aa09bab8bd8d7b784e04bf8b9d5d76d1a6

[ "MIT" ]

null

py_hanabi/card.py

krinj/hanabi-simulator

b77b04aa09bab8bd8d7b784e04bf8b9d5d76d1a6

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ A card (duh). """ import random import uuid from enum import Enum from typing import List from py_hanabi.settings import CARD_DECK_DISTRIBUTION __author__ = "Jakrin Juangbhanich" __email__ = "juangbhanich.k@gmail.com" class Color(Enum): RED = 1 BLUE = 2 GREEN = 3 YELLOW = 4 WHITE = 5 class Card: def __init__(self, number: int, color: Color): self._number: int = number self._color: Color = color self._id: str = uuid.uuid4().hex self._hint_number_counter: int = 0 self._hint_color_counter: int = 0 # self._index_hinted: List[int] = [] # self._lone_hinted: List[bool] = [] # According to hints, these are the ones we know it is NOT. self.not_color: List[Color] = [] self.not_number: List[int] = [] def __repr__(self): hint_str = "" if self.hint_received_color: hint_str += "C" if self.hint_received_number: hint_str += "N" return f"[{self.color} {self.number} {hint_str}]" def __eq__(self, other: 'Card'): return self.color == other.color and self.number == other.number def receive_hint_number(self, number: int): if number == self.number: self._hint_number_counter += 1 else: self.not_number.append(number) def receive_hint_color(self, color: Color): if color == self.color: self._hint_color_counter += 1 else: self.not_color.append(color) def remove_hint_number(self, number: int): if number == self.number: self._hint_number_counter -= 1 else: self.not_number.pop() def remove_hint_color(self, color: Color): if color == self.color: self._hint_color_counter -= 1 else: self.not_color.pop() @property def label(self): return f"{self.number} of {self.get_color_label(self.color)}" @property def id(self) -> str: return self._id @property def key(self) -> tuple: return self.get_key(self.color, self.number) @staticmethod def get_key(c: Color, n: int) -> tuple: return c, n @property def number(self) -> int: return self._number @property def color(self) -> Color: return self._color @property def observed_color(self) -> Color: return None if not self.hint_received_color else self._color @property def observed_number(self) -> int: return None if not self.hint_received_number else self._number @property def hint_received_number(self) -> bool: return self._hint_number_counter > 0 @property def hint_received_color(self) -> bool: return self._hint_color_counter > 0 @staticmethod def generate_deck() -> List['Card']: """ Generate the starting deck for the game. """ deck: List[Card] = [] for color in Color: for i in CARD_DECK_DISTRIBUTION: card = Card(i, color) deck.append(card) random.shuffle(deck) return deck @staticmethod def get_color_label(color: Color) -> str: color_labels = { Color.BLUE: "Blue", Color.RED: "Red", Color.YELLOW: "Yellow", Color.GREEN: "Green", Color.WHITE: "White", } return color_labels[color]

24.871429

72

0.587881

435

3,482

4.471264

0.222989

0.064781

0.043188

0.243702

0.192288

0.160411

0

0.006203

0.305572

3,482

139

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25.05036

0.79818

0.059161

0

0.2

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0.11

0.45

0

null

0

null

0

1

0

1

22c78686c8b8a763f3206d86fcbc87e20d6ea1aa

1,186

py

Python

setup.py

d2gex/distpickymodel

7acd4ffafbe592d6336d91d6e7411cd45357e41c

[ "MIT" ]

null

setup.py

d2gex/distpickymodel

7acd4ffafbe592d6336d91d6e7411cd45357e41c

[ "MIT" ]

null

setup.py

d2gex/distpickymodel

7acd4ffafbe592d6336d91d6e7411cd45357e41c

[ "MIT" ]

null

import setuptools import distpickymodel def get_long_desc(): with open("README.rst", "r") as fh: return fh.read() setuptools.setup( name="distpickymodel", version=distpickymodel.__version__, author="Dan G", author_email="daniel.garcia@d2garcia.com", description="A shared Mongoengine-based model library", long_description=get_long_desc(), url="https://github.com/d2gex/distpickymodel", # Exclude 'tests' and 'docs' packages=['distpickymodel'], python_requires='>=3.6', install_requires=['pymongo>=3.7.2', 'mongoengine>=0.17.0', 'six'], tests_require=['pytest>=4.4.0', 'PyYAML>=5.1'], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Environment :: Web Environment', 'Environment :: Console', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Operating System :: OS Independent', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: Implementation :: CPython', 'Topic :: Software Development :: Libraries :: Python Modules', ] )

32.944444

71

0.636594

126

1,186

5.888889

0.690476

0.076819

0.101078

0.070081

0

0.02246

0.211636

1,186

35

72

33.885714

0.771123

0.021922

0

0.522453

0.022453

0

1

0.033333

true

0

0.066667

0

0.133333

0

null

0

null

0

1

0

1

22cc300c5aa21f713c2ef3f3b60722cc7d238f97

1,163

py

Python

rdl/data_sources/DataSourceFactory.py

pageuppeople-opensource/relational-data-loader

0bac7036d65636d06eacca4e68e09d6e1c506ea4

[ "MIT" ]

2

2019-03-11T12:45:23.000Z

2019-04-05T05:22:43.000Z

rdl/data_sources/DataSourceFactory.py

pageuppeople-opensource/relational-data-loader

0bac7036d65636d06eacca4e68e09d6e1c506ea4

[ "MIT" ]

5

2019-02-08T03:23:25.000Z

2019-04-11T01:29:45.000Z

rdl/data_sources/DataSourceFactory.py

PageUpPeopleOrg/relational-data-loader

0bac7036d65636d06eacca4e68e09d6e1c506ea4

[ "MIT" ]

1

2019-03-04T04:08:49.000Z

import logging from rdl.data_sources.MsSqlDataSource import MsSqlDataSource from rdl.data_sources.AWSLambdaDataSource import AWSLambdaDataSource class DataSourceFactory(object): def __init__(self, logger=None): self.logger = logger or logging.getLogger(__name__) self.sources = [MsSqlDataSource, AWSLambdaDataSource] def create_source(self, connection_string): for source in self.sources: if source.can_handle_connection_string(connection_string): self.logger.info( f"Found handler '{source}' for given connection string." ) return source(connection_string) raise RuntimeError( "There are no data sources that can handle this connection string" ) def is_prefix_supported(self, connection_string): for source in self.sources: if source.can_handle_connection_string(connection_string): return True return False def get_supported_source_prefixes(self): return list( map(lambda source: source.get_connection_string_prefix(), self.sources) )

35.242424

83

0.674979

124

1,163

6.08871

0.41129

0.211921

0.029139

0.047682

0.24106

0

0.263113

1,163

32

84

36.34375

0.88098

0

0.153846

0

0.100602

0

1

0.153846

false

0

0.115385

0.038462

0.461538

0

null

1

0

null

0

1

22cd87f92115b6affd305877641e7e519dbd0eb4

476

py

Python

server/WitClient.py

owo/jitalk

2db2782282a2302b4cf6049030822734a6856982

[ "MIT" ]

1

2020-06-22T14:28:41.000Z

server/WitClient.py

owo/jitalk

2db2782282a2302b4cf6049030822734a6856982

[ "MIT" ]

null

server/WitClient.py

owo/jitalk

2db2782282a2302b4cf6049030822734a6856982

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- import wit import json class WitClient(object): """docstring for WitClient""" _access_token = 'NBPOVLY7T6W3KOUEML2GXOWODH3LPWPD' def __init__(self): wit.init() def text_query(self, text): res = json.loads(wit.text_query(text, WitClient._access_token)) return res["outcomes"] def close_connection(self): wit.close() if __name__ == "__main__": print "You ran the Wit client, nothing will happen. Exiting..."

20.695652

65

0.707983

62

476

5.129032

0.66129

0.09434

0.125786

0

0.014851

0.151261

476

23

66

20.695652

0.772277

0.088235

0

0.254951

0.079208

0

null

0

0.153846

null

0.076923

0

null

0

null

0

1

0

1

22cf943746c3603f630cb274d2c1d26e36acc1fd

3,472

py

Python

python_scripts/BUSCO_phylogenetics/rename_all_fa_seq.py

peterthorpe5/Methods_M.cerasi_R.padi_genome_assembly

c6cb771afaf40f5def47e33ff11cd8867ec528e0

[ "MIT" ]

4

2019-04-01T02:08:21.000Z

2022-02-04T08:37:47.000Z

python_scripts/BUSCO_phylogenetics/rename_all_fa_seq.py

peterthorpe5/Methods_M.cerasi_R.padi_genome_assembly

c6cb771afaf40f5def47e33ff11cd8867ec528e0

[ "MIT" ]

1

2018-09-30T00:29:43.000Z

2018-10-01T07:51:16.000Z

python_scripts/BUSCO_phylogenetics/rename_all_fa_seq.py

peterthorpe5/Methods_M.cerasi_R.padi_genome_assembly

c6cb771afaf40f5def47e33ff11cd8867ec528e0

[ "MIT" ]

1

2019-12-05T09:04:38.000Z

#!/usr/bin/env python # author: Peter Thorpe September 2015. The James Hutton Insitute, Dundee, UK. # title rename single copy busco genes from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord from Bio import SeqIO import os from sys import stdin,argv import sys from optparse import OptionParser ######################################################################## # functions def parse_busco_file(busco): """this is a function to open busco full ouput and get a list of duplicated genes. This list is required so we can ignore these genes later. Takes file, return list""" duplicated_list = [] with open(busco) as handle: for line in handle: if not line.strip(): continue # if the last line is blank if line.startswith("#"): continue if not line: print ("your file is empty") return False line_info = line.rstrip().split("\t") # first element Busco_name = line_info[0] # second element status = line_info[1] if status == "Duplicated" or status == "Fragmented": duplicated_list.append(Busco_name) return duplicated_list def reformat_as_fasta(filename,prefix,outfile): "this function re-write a file as a fasta file" f= open(outfile, 'w') fas = open(filename, "r") for line in fas: if not line.strip(): continue # if the last line is blank if line.startswith("#"): continue if not line: return False if not line.startswith(">"): seq = line title = ">" + prefix + "_" + filename.replace("BUSCOa", "").split(".fas")[0] data = "%s\n%s\n" %(title, seq) f.write(data) f.close() if "-v" in sys.argv or "--version" in sys.argv: print "v0.0.1" sys.exit(0) usage = """Use as follows: converts $ python renaem....py -p Mce -b full_table_BUSCO_output script to walk through all files in a folder and rename the seq id to start with Prefix. Used for Busco output. give it the busco full ouput table. The script will only return complete single copy gene. Duplicate gene will be ignored. """ parser = OptionParser(usage=usage) parser.add_option("-p", "--prefix", dest="prefix", default=None, help="Output filename", metavar="FILE") parser.add_option("-b", "--busco", dest="busco", default=None, help="full_table_*_BUSCO output from BUSCO", metavar="FILE") (options, args) = parser.parse_args() prefix = options.prefix busco = options.busco # Run as script if __name__ == '__main__': #call function to get a list of dupicated gene. #these genes will be ignored duplicated_list = parse_busco_file(busco) #iterate through the dir for filename in os.listdir("."): count = 1 if not filename.endswith(".fas"): continue #filter out the ones we dont want if filename.split(".fa")[0] in duplicated_list: continue out_file = "../"+prefix+filename out_file = out_file.replace("BUSCOa", "") #out_file = "../"+filename try: #print filename reformat_as_fasta(filename, prefix, out_file) except: ValueError continue

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null

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1

22d2e5e3c594615ca7c099c59610e2d90de239db

403

py

Python

pages/migrations/0004_auto_20181102_0944.py

yogeshprasad/spa-development

1bee9ca64da5815e1c9a2f7af43b44b59ee2ca7b

[ "Apache-2.0" ]

null

pages/migrations/0004_auto_20181102_0944.py

yogeshprasad/spa-development

1bee9ca64da5815e1c9a2f7af43b44b59ee2ca7b

[ "Apache-2.0" ]

7

2020-06-05T19:11:22.000Z

2022-03-11T23:30:57.000Z

pages/migrations/0004_auto_20181102_0944.py

yogeshprasad/spa-development

1bee9ca64da5815e1c9a2f7af43b44b59ee2ca7b

[ "Apache-2.0" ]

null

# Generated by Django 2.0.6 on 2018-11-02 09:44 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('pages', '0003_coachingcourse'), ] operations = [ migrations.AlterField( model_name='coachingcourse', name='username', field=models.CharField(default='', max_length=100), ), ]

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22d31dc3511cd477901e03ecc8f042e8c0f688bf

1,119

py

Python

imageclassification/src/sample/splitters/_StratifiedSplitter.py

waikato-datamining/keras-imaging

f044f883242895c18cfdb31a827bc32bdb0405ed

[ "MIT" ]

null

imageclassification/src/sample/splitters/_StratifiedSplitter.py

waikato-datamining/keras-imaging

f044f883242895c18cfdb31a827bc32bdb0405ed

[ "MIT" ]

null

imageclassification/src/sample/splitters/_StratifiedSplitter.py

waikato-datamining/keras-imaging

f044f883242895c18cfdb31a827bc32bdb0405ed

[ "MIT" ]

1

2020-04-16T15:29:28.000Z

from collections import OrderedDict from random import Random from typing import Set from .._types import Dataset, Split, LabelIndices from .._util import per_label from ._RandomSplitter import RandomSplitter from ._Splitter import Splitter class StratifiedSplitter(Splitter): """ TODO """ def __init__(self, percentage: float, labels: LabelIndices, random: Random = Random()): self._percentage = percentage self._labels = labels self._random = random def __str__(self) -> str: return f"strat-{self._percentage}" def __call__(self, dataset: Dataset) -> Split: subsets_per_label = per_label(dataset) sub_splits = { label: RandomSplitter(int(len(subsets_per_label[label]) * self._percentage), self._random)(subsets_per_label[label]) for label in self._labels.keys() } result = OrderedDict(), OrderedDict() for filename, label in dataset.items(): result_index = 0 if filename in sub_splits[label][0] else 1 result[result_index][filename] = label return result

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null

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1

0

1

22d37205c7c002b3538af8a7bcaeddcf556d57d9

315

py

Python

revenuecat_python/enums.py

YuraHavrylko/revenuecat_python

a25b234933b6e80e1ff09b6a82d73a0e3df91caa

[ "MIT" ]

1

2020-12-11T09:31:02.000Z

revenuecat_python/enums.py

YuraHavrylko/revenuecat_python

a25b234933b6e80e1ff09b6a82d73a0e3df91caa

[ "MIT" ]

null

revenuecat_python/enums.py

YuraHavrylko/revenuecat_python

a25b234933b6e80e1ff09b6a82d73a0e3df91caa

[ "MIT" ]

null

from enum import Enum class SubscriptionPlatform(Enum): ios = 'ios' android = 'android' macos = 'macos' uikitformac = 'uikitformac' stripe = 'stripe' class AttributionNetworkCode(Enum): apple_search_ads = 0 adjust = 1 apps_flyer = 2 branch = 3 tenjin = 4 facebook = 5

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null

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null

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1

22d9ab4bf21ea11b6c751dd2350676d79a0f46d5

397

py

Python

classroom/migrations/0025_myfile_file.py

Abulhusain/E-learing

65cfe3125f1b6794572ef2daf89917976f0eac09

[ "MIT" ]

5

2019-06-19T03:47:17.000Z

2020-06-11T17:46:50.000Z

classroom/migrations/0025_myfile_file.py

Abulhusain/E-learing

65cfe3125f1b6794572ef2daf89917976f0eac09

[ "MIT" ]

3

2021-03-19T01:23:12.000Z

2021-09-08T01:05:25.000Z

classroom/migrations/0025_myfile_file.py

seeej/digiwiz

96ddfc22fe4c815feec3d75c30576fec5f344154

[ "MIT" ]

1

2021-06-04T05:58:15.000Z

# Generated by Django 2.2.2 on 2019-08-25 09:29 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('classroom', '0024_auto_20190825_1723'), ] operations = [ migrations.AddField( model_name='myfile', name='file', field=models.CharField(blank=True, max_length=100), ), ]

20.894737

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0.119298

0.282116

397

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0.333333

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null

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null

0

1

22da72ceaa2598d408165e577728716dec2eb71a

11,928

py

Python

tmp/real_time_log_analy/logWatcher.py

hankai17/test

8f38d999a7c6a92eac94b4d9dc8e444619d2144f

[ "MIT" ]

7

2017-07-16T15:09:26.000Z

2021-09-01T02:13:15.000Z

tmp/real_time_log_analy/logWatcher.py

hankai17/test

8f38d999a7c6a92eac94b4d9dc8e444619d2144f

[ "MIT" ]

null

tmp/real_time_log_analy/logWatcher.py

hankai17/test

8f38d999a7c6a92eac94b4d9dc8e444619d2144f

[ "MIT" ]

3

2017-09-13T09:54:49.000Z

2019-03-18T01:29:15.000Z

#!/usr/bin/env python import os import sys import time import errno import stat import datetime import socket import struct import atexit import logging #from lru import LRUCacheDict from logging import handlers from task_manager import Job, taskManage from ctypes import * from urlparse import * from multiprocessing import Process,Lock from log_obj import CLog from parse_conf import cConfParser log_file = "timelog.log" log_fmt = '%(asctime)s: %(message)s' config_file = 'test.config' domain_white_dict = {} pps_ip_list = [] pps_port = 0 domain_sfx_err_count = 0 domain_sfx_err_rate = 0 ats_ip = '' def daemonize(pid_file=None): pid = os.fork() if pid: sys.exit(0) os.chdir('/') os.umask(0) os.setsid() _pid = os.fork() if _pid: sys.exit(0) sys.stdout.flush() sys.stderr.flush() with open('/dev/null') as read_null, open('/dev/null', 'w') as write_null: os.dup2(read_null.fileno(), sys.stdin.fileno()) os.dup2(write_null.fileno(), sys.stdout.fileno()) os.dup2(write_null.fileno(), sys.stderr.fileno()) if pid_file: with open(pid_file, 'w+') as f: f.write(str(os.getpid())) atexit.register(os.remove, pid_file) def get_suffix(p): if len(p) == 1: #return "pure domain" return "nil" fields = p.split("/") if len(fields) == 0 or len(fields) == 1: return "null" fields1 = fields[len(fields) - 1].split(".") if len(fields1) == 0 or len(fields1) == 1: return "null" else: return fields1[len(fields1) - 1] class LogWatcher(object): def __init__(self, folder, callback, extensions=["log"], logfile_keyword="squid", tail_lines=0): self.files_map = {} self.callback = callback self.folder = os.path.realpath(folder) self.extensions = extensions self.logfile_kw = logfile_keyword assert os.path.exists(self.folder), "%s does not exists" % self.folder assert callable(callback) self.update_files() for id, file in self.files_map.iteritems(): file.seek(os.path.getsize(file.name)) # EOF if tail_lines: lines = self.tail(file.name, tail_lines) if lines: self.callback(file.name, lines) def __del__(self): self.close() def loop(self, interval=0.1, async=False): while 1: try: self.update_files() for fid, file in list(self.files_map.iteritems()): self.readfile(file) if async: return time.sleep(interval) except KeyboardInterrupt: break def log(self, line): print line def listdir(self): ls = os.listdir(self.folder) if self.extensions: return [x for x in ls if os.path.splitext(x)[1][1:] in self.extensions and self.logfile_kw in os.path.split(x)[1] ] else: return ls @staticmethod def tail(fname, window): try: f = open(fname, 'r') except IOError, err: if err.errno == errno.ENOENT: return [] else: raise else: BUFSIZ = 1024 f.seek(0, os.SEEK_END) fsize = f.tell() block = -1 data = "" exit = False while not exit: step = (block * BUFSIZ) if abs(step) >= fsize: f.seek(0) exit = True else: f.seek(step, os.SEEK_END) data = f.read().strip() if data.count('\n') >= window: break else: block -= 1 return data.splitlines()[-window:] def update_files(self): ls = [] if os.path.isdir(self.folder): for name in self.listdir(): absname = os.path.realpath(os.path.join(self.folder, name)) try: st = os.stat(absname) except EnvironmentError, err: if err.errno != errno.ENOENT: raise else: if not stat.S_ISREG(st.st_mode): continue fid = self.get_file_id(st) ls.append((fid, absname)) elif os.path.isfile(self.folder): absname = os.path.realpath(self.folder) try: st = os.stat(absname) except EnvironmentError, err: if err.errno != errno.ENOENT: raise else: fid = self.get_file_id(st) ls.append((fid, absname)) else: print 'You submitted an object that was neither a file or folder...exiting now.' sys.exit() for fid, file in list(self.files_map.iteritems()): try: st = os.stat(file.name) except EnvironmentError, err: if err.errno == errno.ENOENT: self.unwatch(file, fid) else: raise else: if fid != self.get_file_id(st): self.unwatch(file, fid) self.watch(file.name) for fid, fname in ls: if fid not in self.files_map: self.watch(fname) def readfile(self, file): lines = file.readlines() if lines: self.callback(file.name, lines) def watch(self, fname): try: file = open(fname, "r") fid = self.get_file_id(os.stat(fname)) except EnvironmentError, err: if err.errno != errno.ENOENT: raise else: self.log("watching logfile %s" % fname) self.files_map[fid] = file def unwatch(self, file, fid): lines = self.readfile(file) self.log("un-watching logfile %s" % file.name) del self.files_map[fid] if lines: self.callback(file.name, lines) @staticmethod def get_file_id(st): return "%xg%x" % (st.st_dev, st.st_ino) def close(self): for id, file in self.files_map.iteritems(): file.close() self.files_map.clear() def udp_send_message(ip_list, port, arr): for ip in ip_list: s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.sendto(arr, (ip, port)) s.close() def pull_data(job): if not (job.sfx == "nil" or job.sfx == "null"): fmt = "=HHHH%dsH%dsH" %(len(job.url),len(job.sfx)) data = struct.pack( fmt, 80, #id 1, #type 8 + len(job.url) + 2 + len(job.sfx) + 1, #length len(job.url), #domain_len job.url, #domain len(job.sfx), #sfx_len job.sfx, #sfx 0 ) else: fmt = "=HHHH%dsH" %(len(job.url)) data = struct.pack( fmt, 80, #id 1, #type 8 + len(job.url) + 1, #length len(job.url), #domain_len job.url, 0 ) global pps_ip_list global pps_port udp_send_message(pps_ip_list, pps_port, data) tmg.done_task_add(job) log_message = job.url + ' ' + job.sfx loger.write(20, log_message) def callback_routine(idx): print 'callback_routinue' def get_domain_white(f): if len(f) == 0: print 'No domain_white_list' return filename = f fd = open(filename, 'r') for line in fd.readlines(): line = line.strip() if not domain_white_dict.has_key(line): domain_white_dict[line] = 1 print 'parse domain_white_list done' def period_check_task(job): global txn_idx global once_flag if txn_idx == 0 and once_flag == 0: once_flag = 1 tmg.done_task_add(job) job.addtime = time.time() tmg.task_add(job) return loger.write(10, '------>') mutex.acquire() for k in d1.keys(): if domain_white_dict.has_key(k): continue for k1 in d1[k].keys(): err_rate = d1[k][k1]['not_ok'] * 100 / (d1[k][k1]['not_ok'] + d1[k][k1]['20x']) log_message = k + ' ' + str(err_rate) loger.write(10, log_message) global domain_sfx_err_count global domain_sfx_err_rate if err_rate >= domain_sfx_err_rate and (d1[k][k1]['not_ok'] + d1[k][k1]['20x']) >= domain_sfx_err_count : #print "will add to task", k, k1, "ok:", d1[k][k1]['20x'], "not_ok:", d1[k][k1]['not_ok'], "err rate:", err_rate txn_idx += 1 job = Job(txn_idx, pull_data, time.time(), 0, k, '', callback_routine, k1, '') tmg.task_add(job) loger.write(10, '<------') d1.clear() mutex.release() tmg.done_task_add(job) if job.period > 0: job.addtime = time.time() tmg.task_add(job) def config_parse(): global domain_sfx_err_count global domain_sfx_err_rate global pps_ip_list global pps_port global ats_ip cp = cConfParser(config_file) pps_ip = cp.get('common', 'pps_ip') fields = pps_ip.strip().split('|') if len(fields) > 0: for i in fields: pps_ip_list.append(i) else: pps_ip_list.append(pps_ip) pps_port = int(cp.get('common', 'pps_port')) domain_sfx_err_count = int(cp.get('common', 'domain_sfx_err_count' )) domain_sfx_err_rate = int(cp.get('common', 'domain_sfx_err_rate' )) ats_ip = cp.get('common', 'ats_ip') print 'ats_ip: ', ats_ip print 'pps_ip: ', pps_ip print 'pps_port: ', pps_port print 'domain_sfx_err_count: ', domain_sfx_err_count print 'domain_sfx_err_rate: ', domain_sfx_err_rate return cp once_flag = 0 txn_idx = 0 d1 = {} mutex = Lock() version_message = '1.0.1' #1.0.1: Add conf obj; Add log obj #1.0.2: More pps. add tool config if __name__ == '__main__': help_message = 'Usage: python %s' % sys.argv[0] if len(sys.argv) == 2 and (sys.argv[1] in '--version'): print version_message exit(1) if len(sys.argv) == 2 and (sys.argv[1] in '--help'): print help_message exit(1) if len(sys.argv) != 1: print help_message exit(1) cp = config_parse() get_domain_white(cp.get('common', 'domain_white_list')) loger = CLog(log_file, log_fmt, 12, 5, cp.get('common', 'debug')) print 'Start ok' daemonize() tmg = taskManage() tmg.run() pull_pps_job = Job(txn_idx, period_check_task, time.time(), int(cp.get('common', 'interval')), '', '', callback_routine, '', '') tmg.task_add(pull_pps_job) def callback(filename, lines): for line in lines: fields = line.strip().split("'") http_code = fields[23] domain = fields[13] log_message = 'new line ' + domain #loger.write(10, log_message) if len(domain.split(":")) > 0: domain = domain.split(":")[0] user_ip = fields[5] result = urlparse(fields[15]) sfx = get_suffix(result.path) if sfx == 'nil' or sfx == 'null': continue if len(domain) <= 3: continue #is watch req global ats_ip if user_ip == ats_ip: continue mutex.acquire() sfx_dict = None if not d1.has_key(domain): d1[domain] = {} sfx_dict = d1[domain] else: sfx_dict = d1[domain] if not sfx_dict.has_key(sfx): sfx_dict[sfx] = {'20x':0, 'not_ok':0} if not(http_code in "200" or http_code in "206" or http_code in "304" or http_code in "204"): sfx_dict[sfx]['not_ok'] += 1 else: sfx_dict[sfx]['20x'] += 1 mutex.release() l = LogWatcher("/opt/ats/var/log/trafficserver", callback) l.loop() #https://docs.python.org/2/library/ctypes.html #https://blog.csdn.net/u012611644/article/details/80529746

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null

0

null

0

1

0

1

22df608412513a1bf5e311a4eae60aa3f6a7a737

1,609

py

Python

python/test/test_dynamic_bitset.py

hagabb/katana

a52a688b90315a79aa95cf8d279fd7f949a3b94b

[ "BSD-3-Clause" ]

null

python/test/test_dynamic_bitset.py

hagabb/katana

a52a688b90315a79aa95cf8d279fd7f949a3b94b

[ "BSD-3-Clause" ]

null

python/test/test_dynamic_bitset.py

hagabb/katana

a52a688b90315a79aa95cf8d279fd7f949a3b94b

[ "BSD-3-Clause" ]

null

import pytest from katana.dynamic_bitset import DynamicBitset __all__ = [] SIZE = 50 @pytest.fixture def dbs(): return DynamicBitset(SIZE) def test_set(dbs): dbs[10] = 1 assert dbs[10] def test_set_invalid_type(dbs): try: dbs[2.3] = 0 assert False except TypeError: pass def test_set_invalid_index_low(dbs): try: dbs[-1] = 1 assert False except IndexError: pass def test_set_invalid_index_high(dbs): try: dbs[SIZE] = 1 assert False except IndexError: pass def test_reset(dbs): dbs[10] = 1 dbs.reset() assert not dbs[10] assert len(dbs) == SIZE def test_reset_index(dbs): dbs[10] = 1 dbs[10] = 0 assert not dbs[10] def test_reset_begin_end(dbs): dbs[10] = 1 dbs[15] = 1 dbs[12:17] = 0 assert dbs[10] assert not dbs[15] def test_reset_begin_end_invalid_step(dbs): try: dbs[12:17:22] = 0 assert False except ValueError: pass def test_reset_none_end(dbs): dbs[10] = 1 dbs[15] = 1 dbs[:12] = 0 assert not dbs[10] assert dbs[15] def test_resize(dbs): dbs.resize(20) assert len(dbs) == 20 dbs[8] = 1 dbs.resize(20) assert len(dbs) == 20 assert dbs[8] dbs.resize(70) assert len(dbs) == 70 assert dbs[8] assert dbs.count() == 1 def test_clear(dbs): dbs[10] = 1 dbs.clear() assert len(dbs) == 0 dbs.resize(20) assert len(dbs) == 20 assert not dbs[10] def test_count(dbs): dbs[10] = 1 assert dbs.count() == 1

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245

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3.673469

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107

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null

0

null

0

1

0

1

22e1bc52c4e28d18d68ad09f117367db41946c7e

5,679

py

Python

src/clients/ctm_api_client/models/user_additional_properties.py

IceT-M/ctm-python-client

0ef1d8a3c9a27a01c088be1cdf5d177d25912bac

[ "BSD-3-Clause" ]

5

2021-12-01T18:40:00.000Z

2022-03-04T10:51:44.000Z

src/clients/ctm_api_client/models/user_additional_properties.py

IceT-M/ctm-python-client

0ef1d8a3c9a27a01c088be1cdf5d177d25912bac

[ "BSD-3-Clause" ]

3

2022-02-21T20:08:32.000Z

2022-03-16T17:41:03.000Z

src/clients/ctm_api_client/models/user_additional_properties.py

IceT-M/ctm-python-client

0ef1d8a3c9a27a01c088be1cdf5d177d25912bac

[ "BSD-3-Clause" ]

7

2021-12-01T11:59:16.000Z

2022-03-01T18:16:40.000Z

# coding: utf-8 """ Control-M Services Provides access to BMC Control-M Services # noqa: E501 OpenAPI spec version: 9.20.215 Contact: customer_support@bmc.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six from clients.ctm_api_client.configuration import Configuration class UserAdditionalProperties(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { "member_of_groups": "list[str]", "authentication": "AuthenticationData", "is_external_user": "bool", } attribute_map = { "member_of_groups": "memberOfGroups", "authentication": "authentication", "is_external_user": "isExternalUser", } def __init__( self, member_of_groups=None, authentication=None, is_external_user=None, _configuration=None, ): # noqa: E501 """UserAdditionalProperties - a model defined in Swagger""" # noqa: E501 if _configuration is None: _configuration = Configuration() self._configuration = _configuration self._member_of_groups = None self._authentication = None self._is_external_user = None self.discriminator = None if member_of_groups is not None: self.member_of_groups = member_of_groups if authentication is not None: self.authentication = authentication if is_external_user is not None: self.is_external_user = is_external_user @property def member_of_groups(self): """Gets the member_of_groups of this UserAdditionalProperties. # noqa: E501 List of role names # noqa: E501 :return: The member_of_groups of this UserAdditionalProperties. # noqa: E501 :rtype: list[str] """ return self._member_of_groups @member_of_groups.setter def member_of_groups(self, member_of_groups): """Sets the member_of_groups of this UserAdditionalProperties. List of role names # noqa: E501 :param member_of_groups: The member_of_groups of this UserAdditionalProperties. # noqa: E501 :type: list[str] """ self._member_of_groups = member_of_groups @property def authentication(self): """Gets the authentication of this UserAdditionalProperties. # noqa: E501 user authentication # noqa: E501 :return: The authentication of this UserAdditionalProperties. # noqa: E501 :rtype: AuthenticationData """ return self._authentication @authentication.setter def authentication(self, authentication): """Sets the authentication of this UserAdditionalProperties. user authentication # noqa: E501 :param authentication: The authentication of this UserAdditionalProperties. # noqa: E501 :type: AuthenticationData """ self._authentication = authentication @property def is_external_user(self): """Gets the is_external_user of this UserAdditionalProperties. # noqa: E501 :return: The is_external_user of this UserAdditionalProperties. # noqa: E501 :rtype: bool """ return self._is_external_user @is_external_user.setter def is_external_user(self, is_external_user): """Sets the is_external_user of this UserAdditionalProperties. :param is_external_user: The is_external_user of this UserAdditionalProperties. # noqa: E501 :type: bool """ self._is_external_user = is_external_user def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list( map(lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value) ) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict( map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items(), ) ) else: result[attr] = value if issubclass(UserAdditionalProperties, dict): for key, value in self.items(): result[key] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, UserAdditionalProperties): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, UserAdditionalProperties): return True return self.to_dict() != other.to_dict()

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101

0.611727

617

5,679

5.421394

0.212318

0.045441

0.079522

0.09148

0.40867

0.34858

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0.1429

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0.305335

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30.368984

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0.022222

0

null

0

1

0

null

0

1

22e6c10685bc8e3a610b18ebd720a7487a124de6

9,576

py

Python

object_detection/exporter_test.py

travisyates81/object-detection

931bebfa54798c08d2c401e9c1bad39015d8c832

[ "MIT" ]

1

2019-09-19T18:24:55.000Z

object_detection/exporter_test.py

travisyates81/object-detection

931bebfa54798c08d2c401e9c1bad39015d8c832

[ "MIT" ]

null

object_detection/exporter_test.py

travisyates81/object-detection

931bebfa54798c08d2c401e9c1bad39015d8c832

[ "MIT" ]

null

# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Travis Yates """Tests for object_detection.export_inference_graph.""" import os import mock import numpy as np import tensorflow as tf from object_detection import exporter from object_detection.builders import model_builder from object_detection.core import model from object_detection.protos import pipeline_pb2 class FakeModel(model.DetectionModel): def preprocess(self, inputs): return (tf.identity(inputs) * tf.get_variable('dummy', shape=(), initializer=tf.constant_initializer(2), dtype=tf.float32)) def predict(self, preprocessed_inputs): return {'image': tf.identity(preprocessed_inputs)} def postprocess(self, prediction_dict): with tf.control_dependencies(prediction_dict.values()): return { 'detection_boxes': tf.constant([[0.0, 0.0, 0.5, 0.5], [0.5, 0.5, 0.8, 0.8]], tf.float32), 'detection_scores': tf.constant([[0.7, 0.6]], tf.float32), 'detection_classes': tf.constant([[0, 1]], tf.float32), 'num_detections': tf.constant([2], tf.float32) } def restore_fn(self, checkpoint_path, from_detection_checkpoint): pass def loss(self, prediction_dict): pass class ExportInferenceGraphTest(tf.test.TestCase): def _save_checkpoint_from_mock_model(self, checkpoint_path, use_moving_averages): g = tf.Graph() with g.as_default(): mock_model = FakeModel(num_classes=1) mock_model.preprocess(tf.constant([1, 3, 4, 3], tf.float32)) if use_moving_averages: tf.train.ExponentialMovingAverage(0.0).apply() saver = tf.train.Saver() init = tf.global_variables_initializer() with self.test_session() as sess: sess.run(init) saver.save(sess, checkpoint_path) def _load_inference_graph(self, inference_graph_path): od_graph = tf.Graph() with od_graph.as_default(): od_graph_def = tf.GraphDef() with tf.gfile.GFile(inference_graph_path) as fid: serialized_graph = fid.read() od_graph_def.ParseFromString(serialized_graph) tf.import_graph_def(od_graph_def, name='') return od_graph def _create_tf_example(self, image_array): with self.test_session(): encoded_image = tf.image.encode_jpeg(tf.constant(image_array)).eval() def _bytes_feature(value): return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value])) example = tf.train.Example(features=tf.train.Features(feature={ 'image/encoded': _bytes_feature(encoded_image), 'image/format': _bytes_feature('jpg'), 'image/source_id': _bytes_feature('image_id') })).SerializeToString() return example def test_export_graph_with_image_tensor_input(self): with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pbtxt') pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = False exporter.export_inference_graph( input_type='image_tensor', pipeline_config=pipeline_config, checkpoint_path=None, inference_graph_path=inference_graph_path) def test_export_graph_with_tf_example_input(self): with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pbtxt') pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = False exporter.export_inference_graph( input_type='tf_example', pipeline_config=pipeline_config, checkpoint_path=None, inference_graph_path=inference_graph_path) def test_export_frozen_graph(self): checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt') self._save_checkpoint_from_mock_model(checkpoint_path, use_moving_averages=False) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pb') with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = False exporter.export_inference_graph( input_type='image_tensor', pipeline_config=pipeline_config, checkpoint_path=checkpoint_path, inference_graph_path=inference_graph_path) def test_export_frozen_graph_with_moving_averages(self): checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt') self._save_checkpoint_from_mock_model(checkpoint_path, use_moving_averages=True) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pb') with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = True exporter.export_inference_graph( input_type='image_tensor', pipeline_config=pipeline_config, checkpoint_path=checkpoint_path, inference_graph_path=inference_graph_path) def test_export_and_run_inference_with_image_tensor(self): checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt') self._save_checkpoint_from_mock_model(checkpoint_path, use_moving_averages=False) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pb') with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = False exporter.export_inference_graph( input_type='image_tensor', pipeline_config=pipeline_config, checkpoint_path=checkpoint_path, inference_graph_path=inference_graph_path) inference_graph = self._load_inference_graph(inference_graph_path) with self.test_session(graph=inference_graph) as sess: image_tensor = inference_graph.get_tensor_by_name('image_tensor:0') boxes = inference_graph.get_tensor_by_name('detection_boxes:0') scores = inference_graph.get_tensor_by_name('detection_scores:0') classes = inference_graph.get_tensor_by_name('detection_classes:0') num_detections = inference_graph.get_tensor_by_name('num_detections:0') (boxes, scores, classes, num_detections) = sess.run( [boxes, scores, classes, num_detections], feed_dict={image_tensor: np.ones((1, 4, 4, 3)).astype(np.uint8)}) self.assertAllClose(boxes, [[0.0, 0.0, 0.5, 0.5], [0.5, 0.5, 0.8, 0.8]]) self.assertAllClose(scores, [[0.7, 0.6]]) self.assertAllClose(classes, [[1, 2]]) self.assertAllClose(num_detections, [2]) def test_export_and_run_inference_with_tf_example(self): checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt') self._save_checkpoint_from_mock_model(checkpoint_path, use_moving_averages=False) inference_graph_path = os.path.join(self.get_temp_dir(), 'exported_graph.pb') with mock.patch.object( model_builder, 'build', autospec=True) as mock_builder: mock_builder.return_value = FakeModel(num_classes=1) pipeline_config = pipeline_pb2.TrainEvalPipelineConfig() pipeline_config.eval_config.use_moving_averages = False exporter.export_inference_graph( input_type='tf_example', pipeline_config=pipeline_config, checkpoint_path=checkpoint_path, inference_graph_path=inference_graph_path) inference_graph = self._load_inference_graph(inference_graph_path) with self.test_session(graph=inference_graph) as sess: tf_example = inference_graph.get_tensor_by_name('tf_example:0') boxes = inference_graph.get_tensor_by_name('detection_boxes:0') scores = inference_graph.get_tensor_by_name('detection_scores:0') classes = inference_graph.get_tensor_by_name('detection_classes:0') num_detections = inference_graph.get_tensor_by_name('num_detections:0') (boxes, scores, classes, num_detections) = sess.run( [boxes, scores, classes, num_detections], feed_dict={tf_example: self._create_tf_example( np.ones((4, 4, 3)).astype(np.uint8))}) self.assertAllClose(boxes, [[0.0, 0.0, 0.5, 0.5], [0.5, 0.5, 0.8, 0.8]]) self.assertAllClose(scores, [[0.7, 0.6]]) self.assertAllClose(classes, [[1, 2]]) self.assertAllClose(num_detections, [2]) if __name__ == '__main__': tf.test.main()

44.539535

77

0.680138

1,181

9,576

5.159187

0.130398

0.105695

0.064993

0.022977

0.684064

0.669457

0.659938

0.651567

0

0.016752

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9,576

214

78

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0.799786

0.012949

0

0.591398

0

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0

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1

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false

0.010753

0.048387

0.016129

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0

null

0

1

0

null

0

1

22f3312bdb283b4ef7d6f8aa9f88ddb5c8c89e30

662

py

Python

ch_4/stopping_length.py

ProhardONE/python_primer

211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0

[ "MIT" ]

51

2016-04-05T16:56:11.000Z

2022-02-08T00:08:47.000Z

ch_4/stopping_length.py

zhangxiao921207/python_primer

211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0

[ "MIT" ]

null

ch_4/stopping_length.py

zhangxiao921207/python_primer

211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0

[ "MIT" ]

47

2016-05-02T07:51:37.000Z

2022-02-08T01:28:15.000Z

# Exercise 4.11 # Author: Noah Waterfield Price import sys g = 9.81 # acceleration due to gravity try: # initial velocity (convert to m/s) v0 = (1000. / 3600) * float(sys.argv[1]) mu = float(sys.argv[2]) # coefficient of friction except IndexError: print 'Both v0 (in km/s) and mu must be supplied on the command line' v0 = (1000. / 3600) * float(raw_input('v0 = ?\n')) mu = float(raw_input('mu = ?\n')) except ValueError: print 'v0 and mu must be pure numbers' sys.exit(1) d = 0.5 * v0 ** 2 / mu / g print d """ Sample run: python stopping_length.py 120 0.3 188.771850342 python stopping_length.py 50 0.3 32.7728906843 """

22.827586

73

0.649547

111

662

3.837838

0.630631

0.028169

0.046948

0.070423

0

0.129594

0.219033

662

28

74

23.642857

0.694391

0.194864

0

0.25908

0

null

0

0.071429

null

0.214286

0

null

0

null

0

1

0

1

22f3a0221d0e140933a57d7b71e0a66cb6793a2d

5,761

py

Python

examples/DeepWisdom/Auto_NLP/deepWisdom/transformers_/__init__.py

zichuan-scott-xu/automl-workflow

d108e55da943775953b9f1801311a86ac07e58a0

[ "Apache-2.0" ]

3

2020-12-15T02:40:43.000Z

2021-01-14T02:32:13.000Z

examples/DeepWisdom/Auto_NLP/deepWisdom/transformers_/__init__.py

zichuan-scott-xu/automl-workflow

d108e55da943775953b9f1801311a86ac07e58a0

[ "Apache-2.0" ]

null

examples/DeepWisdom/Auto_NLP/deepWisdom/transformers_/__init__.py

zichuan-scott-xu/automl-workflow

d108e55da943775953b9f1801311a86ac07e58a0

[ "Apache-2.0" ]

4

2021-01-07T05:41:38.000Z

2021-04-07T08:02:22.000Z

__version__ = "2.1.1" # Work around to update TensorFlow's absl.logging threshold which alters the # default Python logging output behavior when present. # see: https://github.com/abseil/abseil-py/issues/99 # and: https://github.com/tensorflow/tensorflow/issues/26691#issuecomment-500369493 try: import absl.logging absl.logging.set_verbosity('info') absl.logging.set_stderrthreshold('info') absl.logging._warn_preinit_stderr = False except: pass import logging logger = logging.getLogger(__name__) # pylint: disable=invalid-name # Files and general utilities from .file_utils import (TRANSFORMERS_CACHE, PYTORCH_TRANSFORMERS_CACHE, PYTORCH_PRETRAINED_BERT_CACHE, cached_path, add_start_docstrings, add_end_docstrings, WEIGHTS_NAME, TF2_WEIGHTS_NAME, TF_WEIGHTS_NAME, CONFIG_NAME, is_tf_available, is_torch_available) # Tokenizers from .tokenization_utils import (PreTrainedTokenizer) from .tokenization_auto import AutoTokenizer from .tokenization_bert import BertTokenizer, BasicTokenizer, WordpieceTokenizer from .tokenization_openai import OpenAIGPTTokenizer from .tokenization_transfo_xl import (TransfoXLTokenizer, TransfoXLCorpus) from .tokenization_gpt2 import GPT2Tokenizer from .tokenization_ctrl import CTRLTokenizer from .tokenization_xlnet import XLNetTokenizer, SPIECE_UNDERLINE from .tokenization_xlm import XLMTokenizer from .tokenization_roberta import RobertaTokenizer from .tokenization_distilbert import DistilBertTokenizer # Configurations from .configuration_utils import PretrainedConfig from .configuration_auto import AutoConfig from .configuration_bert import BertConfig, BERT_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_openai import OpenAIGPTConfig, OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_transfo_xl import TransfoXLConfig, TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_gpt2 import GPT2Config, GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_ctrl import CTRLConfig, CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_xlnet import XLNetConfig, XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_ctrl import CTRLConfig, CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_xlm import XLMConfig, XLM_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_roberta import RobertaConfig, ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP from .configuration_distilbert import DistilBertConfig, DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP # Modeling if is_torch_available(): from .modeling_utils import (PreTrainedModel, prune_layer, Conv1D) from .modeling_auto import (AutoModel, AutoModelForSequenceClassification, AutoModelForQuestionAnswering, AutoModelWithLMHead) from .modeling_bert import (BertPreTrainedModel, BertModel, BertForPreTraining, BertForMaskedLM, BertForNextSentencePrediction, BertForSequenceClassification, BertForMultipleChoice, BertForTokenClassification, BertForQuestionAnswering, load_tf_weights_in_bert, BERT_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_openai import (OpenAIGPTPreTrainedModel, OpenAIGPTModel, OpenAIGPTLMHeadModel, OpenAIGPTDoubleHeadsModel, load_tf_weights_in_openai_gpt, OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_transfo_xl import (TransfoXLPreTrainedModel, TransfoXLModel, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl, TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_gpt2 import (GPT2PreTrainedModel, GPT2Model, GPT2LMHeadModel, GPT2DoubleHeadsModel, load_tf_weights_in_gpt2, GPT2_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_ctrl import (CTRLPreTrainedModel, CTRLModel, CTRLLMHeadModel, CTRL_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_xlnet import (XLNetPreTrainedModel, XLNetModel, XLNetLMHeadModel, XLNetForSequenceClassification, XLNetForMultipleChoice, XLNetForQuestionAnsweringSimple, XLNetForQuestionAnswering, load_tf_weights_in_xlnet, XLNET_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_xlm import (XLMPreTrainedModel , XLMModel, XLMWithLMHeadModel, XLMForSequenceClassification, XLMForQuestionAnswering, XLMForQuestionAnsweringSimple, XLM_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_roberta import (RobertaForMaskedLM, RobertaModel, RobertaForSequenceClassification, RobertaForMultipleChoice, ROBERTA_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_distilbert import (DistilBertForMaskedLM, DistilBertModel, DistilBertForSequenceClassification, DistilBertForQuestionAnswering, DISTILBERT_PRETRAINED_MODEL_ARCHIVE_MAP) from .modeling_albert import AlbertForSequenceClassification # Optimization from .optimization import (AdamW, ConstantLRSchedule, WarmupConstantSchedule, WarmupCosineSchedule, WarmupCosineWithHardRestartsSchedule, WarmupLinearSchedule) if not is_tf_available() and not is_torch_available(): logger.warning("Neither PyTorch nor TensorFlow >= 2.0 have been found." "Models won't be available and only tokenizers, configuration" "and file/data utilities can be used.")

59.391753

109

0.740844

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5,761

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0.387283

0.046512

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0.188005

0.053856

0

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0.5

0

null

0

null

0

1

0

1

22f68910ff9dfaa421812c8e74e6090e44df810d

1,797

py

Python

project/users/models.py

rchdlps/django-docker

2c12732264c1f17cd62e20927b5956db498c30b7

[ "MIT" ]

null

project/users/models.py

rchdlps/django-docker

2c12732264c1f17cd62e20927b5956db498c30b7

[ "MIT" ]

null

project/users/models.py

rchdlps/django-docker

2c12732264c1f17cd62e20927b5956db498c30b7

[ "MIT" ]

null

from django.contrib.auth.models import AbstractUser from django.db.models import CharField from django.urls import reverse from django.utils.translation import ugettext_lazy as _ from django.db import models from PIL import Image class User(AbstractUser): # First Name and Last Name do not cover name patterns # around the globe. name = CharField(_('Nome de usuário:'), blank=True, max_length=255) # Profile Models image = models.ImageField(verbose_name='Foto de Perfil:', default='default.jpg', upload_to='profile_pics') birth_date = models.DateField(_('Data de Nascimento:'), null=True, blank=True) cpf = models.CharField(_('CPF:'), max_length=50, blank=True) cnpj = models.CharField(_('CNPJ:'), max_length=50, blank=True) bio = models.TextField(_('Descrição:'), blank=True, default='') cep = models.CharField(_('CEP:'), max_length=50, blank=True) street = models.CharField(_('Rua:'), max_length=100, blank=True) number_home = models.CharField(_('Número:'), max_length=10, blank=True) neighborhood = models.CharField(_('Bairro:'), max_length=100, blank=True) city = models.CharField(_('Cidade:'), max_length=50, blank=True) state = models.CharField(_('Estado:'), max_length=50, blank=True) phone = models.CharField(_('Telefone:'), max_length=50, blank=True) cel_phone = models.CharField(_('Celular:'), max_length=50, blank=True) def get_absolute_url(self): return reverse("users:detail", kwargs={"username": self.username}) """def save(self): super().save() img = Image.open(self.image.path) if img.height > 300 or img.width > 300: output_size = (300, 300) img.thumbnail(output_size) img.save(self.image.path)"""

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null

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1

22feb380588bd77256d844c8ff999d4f5568fa43

1,499

py

Python

setup.py

ovnicraft/runa

4834b7467314c51c3e8e010b47a10bdfae597a5b

[ "MIT" ]

5

2018-02-02T13:12:55.000Z

2019-12-21T04:21:10.000Z

setup.py

ovnicraft/runa

4834b7467314c51c3e8e010b47a10bdfae597a5b

[ "MIT" ]

1

2017-12-18T15:49:13.000Z

setup.py

ovnicraft/runa

4834b7467314c51c3e8e010b47a10bdfae597a5b

[ "MIT" ]

1

2020-03-17T03:50:19.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """The setup script.""" from setuptools import setup, find_packages with open("README.rst") as readme_file: readme = readme_file.read() with open("HISTORY.rst") as history_file: history = history_file.read() requirements = ["Click>=6.0", "suds2==0.7.1"] setup_requirements = [ # TODO(ovnicraft): put setup requirements (distutils extensions, etc.) here ] test_requirements = [ # TODO: put package test requirements here ] setup( name="runa", version="0.2.10", description="Librería para uso de WS del Bus Gubernamental de Ecuador", long_description=readme + "\n\n" + history, author="Cristian Salamea", author_email="cristian.salamea@gmail.com", url="https://github.com/ovnicraft/runa", packages=find_packages(include=["runa"]), entry_points={"console_scripts": ["runa=runa.cli:main"]}, include_package_data=True, install_requires=requirements, license="MIT license", zip_safe=False, keywords="runa webservices ecuador bgs", classifiers=[ "Development Status :: 3 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", ], test_suite="tests", tests_require=test_requirements, setup_requires=setup_requirements, )

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null

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1

fe02b43015e3d0762066c7be3eb1af3c04bff4d4

2,757

py

Python

section_07_(files)/read_csv.py

govex/python-lessons

e692f48b6db008a45df0b941dee1e580f5a6c800

[ "MIT" ]

5

2019-10-25T20:47:22.000Z

2021-12-07T06:37:22.000Z

section_07_(files)/read_csv.py

govex/python-lessons

e692f48b6db008a45df0b941dee1e580f5a6c800

[ "MIT" ]

null

section_07_(files)/read_csv.py

govex/python-lessons

e692f48b6db008a45df0b941dee1e580f5a6c800

[ "MIT" ]

1

2021-07-20T18:56:15.000Z

# If you're new to file handling, be sure to check out with_open.py first! # You'll also want to check out read_text.py before this example. This one is a bit more advanced. with open('read_csv.csv', 'r') as states_file: # Instead of leaving the file contents as a string, we're splitting the file into a list at every new line, and we save that list into the variable states states = states_file.read().split("\n") # Since this is a spreadsheet in comma separated values (CSV) format, we can think of states as a list of rows. # But we'll need to split the columns into a list as well! for index, state in enumerate(states): states[index] = state.split(",") # Now we have a nested list with all of the information! # Our file looks like this: # State, Population Estimate, Percent of Total population # California, 38332521, 11.91% # Texas, 26448193, 8.04% # ... # Our header row is at state[0], so we can use that to display the information in a prettier way. for state in states[1:]: # We use [1:] so we skip the header row. # state[0] is the first column in the row, which contains the name of the state. print("\n---{0}---".format(state[0])) for index, info in enumerate(state[1:]): # We use [1:] so we don't repeat the state name. print("{0}:\t{1}".format(states[0][index+1], info)) # states is the full list of all of the states. It's a nested list. The outer list contains the rows, each inner list contains the columns in that row. # states[0] refers to the header row of the list # So states[0][0] would refer to "State", states[0][1] would refer to "Population Estimate", and states[0][2] would refer to "Percent of total population" # state is one state within states. state is also a list, containing the name, population, and percentage of that particular state. # So the first time through the loop, state[0] would refer to "California", state[1] would refer to 38332521, and state[2] would refer to 11.91% # Since state is being create by the for loop in line 24, it gets a new value each time through. # We're using enumerate to get the index (slicing number) of the column we're on, along with the information. # That way we can pair the column name with the information, as shown in line 30. # NOTE: Since we're slicing from [1:] in line 29, we need to increase the index by + 1, otherwise our headers will be off by one. # Sample output: # ---"California"--- # "Population Estimate": 38332521 # "Percent of Total population": "11.91%" # ---"Texas"--- # "Population Estimate": 26448193 # "Percent of Total population": "8.04%" # ---"New York"--- # "Population Estimate": 19651127 # "Percent of Total population": "6.19%"

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