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from dash import dcc from dash import html import dash_bootstrap_components as dbc import altair as alt from dash.dependencies import Input, Output from data.data import energy_df_full from ..app import app from .style import plot1a_style,plot1b_style,whole_tab_style,label_style_active,label_style_init alt.data_tran...
#Import required libraries import pandas as pd import numpy as np import spacy from tqdm import tqdm import re import time import pickle pd.set_option('display.max_colwidth', 100) # read train and test dataset train = pd.read_csv("train.csv") test = pd.read_csv("test.csv") print(train.shape, test.shape) # Check di...
class DiGraph: def __init__(self, edges=[]): self.vertexList = VertexList(edges) for e in edges: self.addEdge(e) ## Modification # for directed graph, we only need to store one direction - (in, out) # self.addEdge((e[1],e[0])) def addEdge(self, ed...
import os from shutil import copy import PyPDF2 import pytest from pdf_manager import get_file_list, get_pdfs, concat_pdfs, create_budget from pdf_manager.core import PdfTypes, PDF from pdf_manager.main import parse_args class Memory: dummy_a4 = '' dummy_a4_inverted = '' dummy_slide = '' tmp_path = ...
from pycricbuzz import Cricbuzz c=Cricbuzz() def first(): #fetching match data match_data = c.matches() #print(match_data) matches = [] mt_id = [] status = [] mtype = [] mnums = [] m_srs = ...
import json import numpy as np from copy import deepcopy from io import BytesIO from .. import MAGIC_SEAMLESS, _integer_types, _float_types, _string_types from .util import get_buffersize, get_buffersize_debug, \ sanitize_dtype from ...json_util import json_encode def _convert_np_void(data): if not isinstance(d...
#!/usr/bin/env python3 import argparse import gzip import sys import os if not __package__: sys.path.insert(1, os.path.dirname(os.path.dirname(os.path.realpath(__file__)))) from mementomap import __VERSION__ from mementomap.cli import compact, generate, lookup def run_generate(**kw): if kw["infile"].endswi...
# For division from __future__ import division import pandas as pd from pandas import Series,DataFrame import numpy as np # For Visualization import matplotlib.pyplot as plt import seaborn as sns import seaborn.linearmodels as snslin sns.set_style('whitegrid') #%matplotlib inline # For reading stock data from yahoo f...
# Mostly based on the code written by <NAME>: # https://github.com/mrharicot/monodepth/blob/master/utils/evaluate_kitti.py from __future__ import division import sys import cv2 import os import numpy as np import argparse from depth_evaluation_utils import * parser = argparse.ArgumentParser() parser.add_argument("--k...
import numpy as np from deep_np import utils def _pool_forward(X, pool_fun, size=2, stride=2): n, d, h, w = X.shape h_out = (h - size) // stride + 1 w_out = (w - size) // stride + 1 X_reshaped = X.reshape(n * d, 1, h, w) X_col = utils.im2col_indices( X_reshaped, size, size, padding=0, stride=stride)...
import os import requests import sys import threading import tqdm import pump.utils as utils import uuid from math import ceil from time import sleep from typing import IO, Dict from urllib.parse import urlparse GLOBAL_THREAD_LOCK = threading.Lock() class Downloader(threading.Thread): """Downloader for single c...
from LambdaQuery.reroute import * def sub_sql(self): return sql(self, reduce=False, subquery=True) def tableGen(self, reduce=True, debug=False, correlated=False, subquery=False): alltables = self.getTables() if correlated: correlated_tables = self.groupbys.getTables() alltables...
''' Created on May 27, 2016 @author: cesar ''' from scipy.stats import norm, pareto, lognorm, gamma, weibull_min, weibull_max, gengamma, expon import numpy as np from scipy.stats import kstest import sys from matplotlib import pyplot as plt from scipy import interpolate from scipy.integrate import quadrature from sci...
import os import numpy as np import pandas as pd import collections import pickle import sys import psutil as ps import random import csv import json from utils.timeseries import TimeSeries class Shapelet(object): def __init__(self): self.id = id(self) self.name = 0.0 self.Class = '' ...
""" <NAME> CSE 163 Quiz Section AA Final Project Part Two This file contains the functions used to analyze the cleaned and merged NBA from the data_processing file. """ import data_processing # noqa: F401 import matplotlib.pyplot as plt import seaborn as seabornInstance import seaborn as sns # hw2_manual.max_level(m...
#!/usr/bin/env python3 from sys import stdin, stdout, stderr from random import choice from string import ascii_uppercase from collections import deque from parent import Track from time import sleep from os import system resources = [] maze = [] player = () path = deque() enemy = {} other_player = "" # track_maze =...
"""test tts module.""" import random import string import unittest try: # py3 from unittest import mock except ImportError: # py2 import mock import pytest try: from melissa.tts import tts except IOError: # NOTE: don't test with existing profile. # taken from http://stackoverflow.com/a/8658332 ...
# -*- coding: utf-8 -*- # Global imports import argparse as ap import numpy as np from sklearn import cluster # Local variable Backbone_atoms = ["_CA_","_C__","_N__","_O__","_OXT","_HA_","_HA2","_HA3","_H__","_H1_","_H2_","_H3_"] # Script information __author__ = "<NAME>" __license__ = "MIT" __version__ = "1.0.1" __...
# -*- coding: utf-8 -*- # @Time : 2021/9/19 下午5:43 # @Author : DaiPuWei # @Email : <EMAIL> # @File : yolov4_tiny.py # @Software: PyCharm """ 这是YOLOv4-tiny模型定义脚本 """ import os from tensorflow.keras.models import Model from tensorflow.keras.layers import Input from tensorflow.keras.layers import Lambda fr...
import torch from architecture import Net, L1_Charbonnier_loss from lap_dataset import DatasetFromFolder import torch.nn as nn import torch.optim as optim from torch.autograd import Variable from torch.utils.data import DataLoader from data import get_training_set, get_test_set import argparse from os.path imp...
from discord.ext import commands from cogs.aux_functions import * import discord class Help(commands.Cog): """ Sends this help message """ def __init__(self, bot, prefix): self.bot = bot self.prefix = prefix @commands.command() # @commands.bot_has_permissions(add_reactions=Tru...
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved """ Utilities for bounding box manipulation and GIoU. """ import torch from torchvision.ops.boxes import box_area def box_cxcywh_to_xyxy(x): x_c, y_c, w, h = x.unbind(-1) b = [(x_c - 0.5 * w), (y_c - 0.5 * h), (x_c + 0.5 * w), (y_...
""" Module for web houses urls parsing """ import os import csv import time from collections import defaultdict from typing import Any, List, Tuple import pandas as pd from bs4 import BeautifulSoup from loguru import logger from selenium.common.exceptions import StaleElementReferenceException from selenium.webdriver.c...
import numpy as np import scipy import scipy.optimize def cov_se(x, xp, lengthscales, signal): return signal**2 * np.exp(-0.5 * np.linalg.norm((x - xp)/lengthscales)**2) def cov_main(str_cov, X, Xs, hyps, jitter=1e-5): num_X = X.shape[0] num_d_X = X.shape[1] num_Xs = Xs.shape[0] num_d_Xs = Xs.sha...
import unittest from conans.test.utils.tools import TestClient, TestServer from conans.paths import CONANFILE from conans.util.files import load import os from nose_parameterized import parameterized class VersionRangesMultiRemoteTest(unittest.TestCase): def setUp(self): self.servers = {"default": TestSe...
#!/usr/bin/env python3 import json import random import string import re import networkx as nx import matplotlib.pyplot as plt from networkx.readwrite import json_graph from enum import IntEnum # from logging import logging import logging # TODO: make this multiline nicer DESCRIPTION = "The Decentralized Index of Kn...
import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib as matplotlib from torch import nn, Tensor, sqrt, pi, stack, optim class Normalization(nn.Module): def __init__(self, S_low, S_up, a_low, a_up, **kwargs): super(Normalization, self).__init__(**kwargs) self.l...
#!/usr/bin/env python ''' Preprocessing for training and inference on DeepMind's Inception-v1 Inflated 3D CNN for action recognition. The model is introduced in: Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset <NAME>, <NAME> https://arxiv.org/pdf/1705.07750v1.pdf. ''' __author__ = "<NAME>" __...
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, <NAME>. 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 # # ...
import unittest2 as unittest from asp.codegen.cpp_ast import * import xml.etree.ElementTree as ElementTree class GenerationTests(unittest.TestCase): # these are simply regression tests for some of the more complicated ast # nodes to make sure we don't muck them up when fixing our handling of # semicolons. ...
import tensorflow as tf import numpy as np # tensorflow >= 2.0 def discriminator_loss(Ra, real_logit, fake_logit): # Ra = Relativistic if Ra: fake_logit = tf.exp(tf.nn.log_softmax(fake_logit, axis=-1)) real_logit = tf.exp(tf.nn.log_softmax(real_logit, axis=-1)) num_outcomes = real_log...
from django.shortcuts import render from django.views import generic from django.contrib.auth import logout from django.shortcuts import redirect from django.utils import timezone from django.contrib.auth.forms import UserChangeForm from django.urls import reverse from .forms import ImageForm, ItemForm from .forms impo...
import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as tick from scipy.stats.kde import gaussian_kde from scipy.interpolate import UnivariateSpline def mean(s): calc = sum(s)/len(s) return calc def stdev(s): calc1 = mean(s) calc2 = [(s[i]-calc1)**2 for i in...
# coding=utf-8 # =================== Imports =================== from pydub import AudioSegment from argparse import ArgumentParser import os, sys, inspect current_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) parent_dir = os.path.dirname(current_dir) sys.path.insert(0, parent_dir) fr...
#!/usr/bin/env python3 import os import lgsvl import time import sys import logging sys.path.append(os.path.join(os.path.dirname(__file__), '..')) from lib.utils import * logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s', datefmt='%m-%d %H:%M:%S') logging.debug('Initializing Simulation Varia...
import data import copy, logging import numpy as np def minimize_states_and_actions_to_iterate(): logging.info("Minimizing states and actions to iterate for each engine type...") for engine_subtype in data.engine_subtypes: num_working_engines = data.engines_info[engine_subtype]['NUM_WORKING_ENGINES'] current_sta...
import os import sys import cv2 import numpy as np import tensorflow as tf import hdr_utils import tensorkit as tk from config import config from model.unetpps import UnetppGeneratorS from tensorkit import logger, logging_to_file UnetGeneratorS, UnetppGenerator = None, None class TestData(object): def __init_...
# # Copyright 2020 Haiku, Inc. All rights reserved. # Distributed under the terms of the MIT License. # # Authors: # <NAME>, <EMAIL> # """ Transparent HTTP proxy. """ import http.client import http.server import optparse import socket import sys import urllib.parse class RequestHandler(http.server.BaseHTTPRequestH...
import discord import json from discord.ext import commands import random TEAM = [ 899722893603274793, 883004373519716372, 685180177419993102 ] crime_success = [ "You stole <en> ZeroBux from a small Café", "You commited Tax Fraud and earned <en> ZeroBux", "You robbed a bank and got <en> ZeroBux!" ] crime_...
""" Functions used for LCI formatting. """ import collections import pandas as pd import scipy as sp from scipy import linalg from lib.parameters import * def compartment_coords(lci, compartments, new_names=None): """ Gets the coordinates of given compartments in a Simapro LCI export. If new_names is ...
"""General matrix math functions.""" # Author: <NAME> import numpy as np from numpy import linalg as la from scipy.linalg import solve_discrete_lyapunov, solve_discrete_are from functools import reduce from extramath import quadratic_formula def vec(A): """Return the vectorized matrix A by stacking its columns....
from src.env_wrappers import wrap_dqn from src.models import Nature import tensorflow as tf import numpy as np nonlin_dict = { 'elu': tf.nn.elu, 'relu': tf.nn.relu, 'sigmoid': tf.nn.sigmoid, 'tanh': tf.nn.tanh } # If you add a new network you should add "string --> class" mapping here. network_dict ...
# Copyright (c) 2018 <NAME>. # Cura is released under the terms of the LGPLv3 or higher. import configparser # An input for some functions we're testing. import os.path # To find the integration test .ini files. import pytest # To register tests with. import unittest.mock # To mock the application, plug-in and contain...
# TODO: implement BatchNorm2d and Swish # aka batch_norm, pad, swish, dropout # https://github.com/lukemelas/EfficientNet-PyTorch/releases/download/1.0/efficientnet-b0-355c32eb.pth # a rough copy of # https://github.com/lukemelas/EfficientNet-PyTorch/blob/master/efficientnet_pytorch/model.py import io import numpy as n...
import argparse import copy import ctypes import glob import json import os import re import sys import elftools import elftools.construct.macros as macros import elftools.elf.elffile as elffile import elftools.elf.structs as structs from jsonmerge import merge symbols = {} rules = {} fut = None _mapping_table = { ...
from pudzu.charts import * from pudzu.sandbox.bamboo import * import seaborn as sns # generate map FONT = verdana df = pd.read_csv("datasets/eufemaleleaders.csv") df = df.assign_rows(assign_if='hosdate:exists or hogdate:exists', date=lambda d: min(get_non(d,'hosdate',2018), get_non(d,'hogdate',2018))) df = df.set_ind...
# ------------------------------------------------------------------------------ # Copy from https://github.com/HRNet/HRNet-Image-Classification # Modified by us # ------------------------------------------------------------------------------ from __future__ import absolute_import from __future__ import division from ...
import numpy as np import re from kmer import * def motif_emnumeration(gen, k, d): p = set() for kmer in generate_kmer(k): if all(any(hamming(kmer, gen_kmer) <= d for gen_kmer in enumerat_kmer(gen_string, k)) for gen_string in gen): p.add(kmer) return list(p) def median_string(gen, k)...
# Copyright (c) 2013, <NAME> and contributors # For license information, please see license.txt from __future__ import unicode_literals import frappe from frappe.utils import cstr __all__ = ["execute"] def execute(filters={}): return get_columns(filters), \ get_data(filters) def get_conditions(filters): """ R...
# Licensed under a 3-clause BSD style license - see LICENSE.rst """ This module contains functions to determine where configuration and data/cache files used by Astropy should be placed. """ from __future__ import (absolute_import, division, print_function, unicode_literals) import os import sy...
""" Loqed API integration """ import logging import aiohttp #from .apiclient import APIClient from typing import List import os import json from abc import abstractmethod from asyncio import CancelledError, TimeoutError, get_event_loop from aiohttp import ClientError, ClientSession, ClientResponse from typing import L...
import tensorflow as tf import numpy as np import os from PIL import Image import math def variable(name, shape, initializer, trainable = True, dtype = tf.float32): out = tf.get_variable(name, shape, dtype, initializer, trainable = True) return out def reshape(input, out_shape, n_in, scope = 'reshape'): with tf....
from django.contrib.auth.decorators import login_required from django.contrib import messages from django.conf import settings from django.utils.decorators import method_decorator from django.shortcuts import render, redirect, get_object_or_404 from django.views import View from django.db import transaction from django...
""" Module for robustly opening an output file. Rationale --------- Suppose the following scenario. A program needs to perform some analysis and save its results to an output file (usually chosen by the user). The most natural and intuitive structure for this program would be: - Perform the analysis and store the re...
# Functions fid_features_to_statistics and fid_statistics_to_metric are adapted from # https://github.com/bioinf-jku/TTUR/blob/master/fid.py commit id d4baae8 # Distributed under Apache License 2.0: https://github.com/bioinf-jku/TTUR/blob/master/LICENSE import numpy as np import scipy.linalg import torch from tor...
""" Module containing main DLPOLY class """ import subprocess import os.path import os import shutil from dlpoly.control import Control from dlpoly.config import Config from dlpoly.field import Field from dlpoly.statis import Statis from dlpoly.cli import get_command_args class DLPoly: """ Main class of a DLPOLY...
try: from rgbmatrix import graphics except ImportError: from RGBMatrixEmulator import graphics def render_team_banner(canvas, layout, team_colors, home_team, away_team, full_team_names, short_team_names_for_runs_hits): default_colors = team_colors.color("default") away_colors = __team_colors(team_colo...
import loading_data import numpy as np import scipy.stats import itertools import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt dataset_to_metric = {"sst": "acc", "mrpc": "acc_and_f1", "cola": "mcc", "rte": "acc"} dataset_to_failurenum = {"sst": 0, "mrpc": 0.75, "cola": 0.1, "rte": .5} def main...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ TOF Fault Injector For Camera FI Demo Tool """ import os from os import listdir from os.path import isfile, join import random from class_fi_offline_ui import OfflineImageFault as ofi #from class_list_creator import ListCreator as img_list def main(ndir_name, fdir_na...
import keras import os import numpy as np import import_data def fit(model, train_set, valid_set, batch_size, epochs, train_version, freq): """ freq: freq (in step) of recording train history """ # train train_steps = int(train_set[0].shape[0]/batch_size) last_step_batch_size = train_set[0].sh...
#!/usr/bin/python3 # Example of adding/removing models to gazebo simulator import argparse import rospy import numpy as np import copy from ur_gazebo.gazebo_spawner import GazeboModels from ur_gazebo.model import Model from ur_gazebo.basic_models import SPHERE, PEG_BOARD, BOX, SPHERE_COLLISION rospy.init_node('gazebo...
""" Non-Residential Efficiency preprocessing ---------------------------------------- preprocessing functions for Non-residential Efficiency component """ #~ import os.path #~ from pandas import read_csv # preprocessing in preprocessor import os from pandas import read_csv, concat, DataFrame import numpy as np impor...
# egion IMPORTS from selenium import webdriver from selenium.common.exceptions import NoSuchElementException from webdriver_manager.chrome import ChromeDriverManager from selenium.webdriver.common.keys import Keys import os import time import job_list # region END # Fill your personal details INFORMATION = { "fir...
#from MongoDB import MongoDB from constants import * import datetime import time get_date = lambda ts: datetime.datetime.fromtimestamp(ts/1000).strftime("%Y-%m-%d") get_days = lambda d1,d2: (datetime.datetime.strptime(d2, "%Y-%m-%d") - \ datetime.datetime.strptime(d1, "%Y-%m-%d")).days '最长高强度同传时间' def get_room_name...
from ctypes import * import ctypes.util from ctypes_configure import configure # Note: OpenSSL on OS X only provides md5 and sha1 libpath = ctypes.util.find_library('ssl') if not libpath: raise ImportError('could not find OpenSSL library') lib = CDLL(libpath) # Linux, OS X lib.EVP_get_digestbyname.restype = c_void...
#!/usr/bin/env python # Filename: pixel_evaluation """ introduction: authors: <NAME> email:<EMAIL> add time: 13 December, 2019 """ from optparse import OptionParser import os,sys import rasterio import basic_src.basic as basic import basic_src.io_function as io_function import parameters import gdal import numpy as ...
from django.shortcuts import render, get_object_or_404 from rest_framework import viewsets from rest_framework import permissions from .serializers import PlantSerializer # from rest_framework.views import APIView # from rest_framework.response import Response from rest_framework import permissions #, authentication...
# Optimization helper functions import numpy as np from sklearn.metrics import log_loss from numpy import sum, maximum, exp, log, log1p from scipy.optimize import fmin_l_bfgs_b as bfgs from scipy.optimize.lbfgsb import _minimize_lbfgsb from scipy.optimize.optimize import MemoizeJac, wrap_function from scipy.optimize...
import datetime import json import os import urllib import psycopg2 import psycopg2.extras import pandas as pd import redis import pmdarima as pm from mlxtend.preprocessing import TransactionEncoder from mlxtend.frequent_patterns import apriori A_PRIORI_LENGTH = 40 PERIOD_LENGTH = datetime.timedelta(hours=12) NUM_PER...
'''https://www.reddit.com/r/dailyprogrammer/comments/6qutez/20170801_challenge_325_easy_color_maze/ Program tries to be efficient by never visiting the same step multiple times (even from different input paths) Can also handle no valid solution i.e. all possible paths are dead ends or get stuck in endless loops ''' f...
from pathlib import Path import cv2 import dlib import numpy as np import argparse from contextlib import contextmanager from wide_resnet import WideResNet from keras.utils.data_utils import get_file from os import path as osp import glob import json pretrained_model = "https://github.com/yu4u/age-gender-estimation...
# Copyright (c) 2008, <NAME>. All rights reserved. # # 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, merg...
#!/usr/bin/env python3 import yaml import os import logging import logging.config import sys import time import datetime import argparse import threading import traceback import signal import timeit import functools import subprocess import faulthandler from prometheus_client.twisted import MetricsResource from prome...
import vim import json import subprocess import io import os import sys import tempfile import logging tempdir = tempfile.gettempdir() logging.basicConfig(filename='%s/vim-rtags-python.log' % tempdir,level=logging.DEBUG) def get_identifier_beginning(): line = vim.eval('s:line') column = int(vim.eval('s:start'...
from ctypes import * import math import random import os import cv2 import numpy as np import time from . import darknet netMain = None metaMain = None altNames = None def convertBack(x, y, w, h): xmin = int(round(x - (w / 2))) xmax = int(round(x + (w / 2))) ymin = int(round(y - (h / 2))) ymax = int...
"""hls_streaming.py. Module with objects to handle HLS streaming. """ import io import asyncio from contextlib import nullcontext from collections import OrderedDict # Third-party imports. from tornado import web # Local imports. from pysdrweb.util import misc from pysdrweb.util.auth import authenticated from pysdrweb...
import sys DEBUG = False def main(): row_c, col_c, vehicle_c, ride_c, bonus, step_c = sys.stdin.readline().strip().split(" ") row_c, col_c, vehicle_c, ride_c, bonus, step_c = int(row_c), int(col_c), int(vehicle_c), int(ride_c), int(bonus), int(step_c) if DEBUG: print("CONFIG") print(f"Row...
""" This module performs subspace system identification. It enforces that matrices are used instead of arrays to avoid dimension conflicts. """ import numpy as np from scipy import linalg __all__ = ['subspace_det_algo1', 'prbs', 'nrms'] def block_hankel(data, f): """ Create a block hankel matrix. f : nu...
from typing import List import numba as nb import numpy as np from astropy.io import fits __all__ = ["makeaperpixmaps", "distarr", "subdistarr", "apercentre", "aperpixmap"] def makeaperpixmaps(npix: int, folderpath=None) -> None: '''Writes the aperture binary masks out after calculation. Parameters ---...
""" Contains the code related for face recognition/verification. """ from typing import Union, Tuple, Optional import torch import torchvision.transforms as T import numpy as np from torch import nn from facenet_pytorch import MTCNN, InceptionResnetV1 from PIL import Image import matplotlib.pyplot as plt from scipy.sp...
#!/usr/bin/env python # coding: utf-8 # # Illustrates function iteration, Newton, and secant methods # # **<NAME>, PhD** # # This demo is based on the original Matlab demo accompanying the <a href="https://mitpress.mit.edu/books/applied-computational-economics-and-finance">Computational Economics and Finance</a> 20...
#Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved. #This program is free software; #you can redistribute it and/or modify #it under the terms of the MIT License. #This program is distributed in the hope that it will be useful, #but WITHOUT ANY WARRANTY; without even the implied warranty of #...
# -*- coding: utf-8 -*- """ Created on Fri Jul 13 13:55:08 2018 @author: herminarto.nugroho """ import torch import torch.nn as nn import torch.nn.functional as F from torch import optim from torchvision.utils import save_image from custom_datasets import CustomDatasetFromImages, CustomSplitLoader # Device configura...
import json import codecs from typing import NamedTuple, Dict, List, Optional import ir_datasets from ir_datasets.util import GzipExtract, Cache, Lazy from ir_datasets.datasets.base import Dataset, YamlDocumentation, FilteredQueries from ir_datasets.formats import BaseQueries, BaseDocs, BaseQrels, TrecQrel from ir_data...
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use ...
#!/usr/bin/env python3 ''' stat_assembly -- stat genome assemblies and get the following statistic values: 1:length 2:number_contigs 3:GC_content 4:N50 5:L50 6:N25 7:L25 8:N75 9:L75 10:N90 11:L90 12:minimum_len 13:median 14:m...
import time import pytest from helpers.cluster import ClickHouseCluster from helpers.network import PartitionManager from helpers.test_tools import TSV cluster = ClickHouseCluster(__file__) instance_test_reconnect = cluster.add_instance( "instance_test_reconnect", main_configs=["configs/remote_servers.xml"] ) in...
#!/usr/bin/env python3 from graph_tool.all import Graph, graph_draw, radial_tree_layout from urllib.parse import urlparse import os import re import requests guid_pattern = re.compile('[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}', re.I) class CfApi(object): root_path = '/v3' def __init__(...
import numpy as np from collections import defaultdict class Tarjan: """ adopted from : https://github.com/jcyk/Dynet-Biaffine-dependency-parser/blob/master/lib/tarjan.py """ def __init__(self, prediction, tokens): """ :param prediction: A predicted dependency tree where predic...
import torch from torch import nn from torch.nn.functional import dropout def top_T(x, T): values, indices = torch.topk(x.abs(), T, dim=1) dropped = torch.zeros_like(x).scatter(1, indices, values) dropped = dropped * x.sign() # <-- this should be included return dropped def dropout(x, p, seed=None)...
from src.sat_utilities import * from src.optimizer import * import math def generate_sat_qasm(expr_string, cnot_mode, sat_mode, apply_optimization=True, connected_qubit=None): """ Generate the QASM needed to evaluate the SAT problem for a given boolean expression. Args: expr_string: A boolean exp...
#!/usr/bin/env python # -*- coding: utf-8 -*- """ This file contains the definition of the XFoil OpenMDAO Component and its helper functions. """ import numpy as np import time from multiprocessing.pool import ThreadPool from xfoil import XFoil from xfoil.model import Airfoil from .. import rank from .airfoil import ...
import adsk.core, adsk.fusion, adsk.cam, traceback from datetime import datetime from pathlib import Path from typing import NamedTuple, List, Set import re import hashlib import os handlers = [] class Ctx(NamedTuple): ''' Context manager. Passed between functions to provide paramaters ''' folder: str ...
""" PRIVATE MODULE: do not import (from) it directly. This module contains implementations of common functionality that can be used throughout `jsons`. """ import builtins import warnings from importlib import import_module from typing import Callable, Optional, Tuple, TypeVar, Any from jsons._cache import...
"""Airfow DAG and helpers used in one or more istio release pipeline.""" """Copyright 2017 Istio Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.o...
import argparse import os import os.path as osp import mmcv import numpy as np import torch from mmcv import Config, DictAction from mmcv.parallel import collate, scatter from mmaction.apis import init_recognizer from mmaction.datasets.pipelines import Compose from mmaction.utils import GradCAM def parse_args(): ...
# Copyright 2018 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, ...
''' Created on 29 Jun 2015 @author: @willu47 This module provides the basic infrastructure for plotting charts for the Method of Morris results The procedures should build upon and return an axes instance:: import matplotlib.plot as plt Si = morris.analyze(problem, param_values, Y, conf_level=0.95, ...
from abc import ABC import pprint import logging from lark import Lark, Tree, Token from .parse_tabs import tabs_to_codeblocks from .la_builtins import LaBuiltins, LaInteger, LaBoolean, LaString, LaFunction, LaArgument import la.errors as errors grammar = open("la/grammar.lark", "r").read() code = tabs_to_codebloc...
# Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0 # For details: https://github.com/nedbat/coveragepy/blob/master/NOTICE.txt """Code coverage measurement for Python""" # Distutils setup for coverage.py # This file is used unchanged under all versions of Python, 2.x and 3.x. import os im...