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import pybullet as p from gym import spaces from diy_gym.addons.addon import Addon class ExternalForce(Addon): """ExternalForce defines a addon that can be used to apply an external force to the base a model. """ def __init__(self, parent, config): super(ExternalForce, self).__init__(parent, confi...
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import pytest from yahooquery import Screener def test_screener(): s = Screener() assert s.get_screeners("most_actives") is not None def test_available_screeners(): s = Screener() assert s.available_screeners is not None def test_bad_screener(): with pytest.raises(ValueError): s = Scr...
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from collections import OrderedDict from fcgiproto.constants import FCGI_KEEP_CONN class RequestEvent(object): """ Base class for events that target a specific request. :ivar int request_id: identifier of the associated request """ __slots__ = ('request_id',) def __init__(self, request_id)...
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import spacy nlp = spacy.load('en') doc = nlp(u'President Trump has a dispute with Mexico over immigration. IBM and Apple are cooperating on marketing in 2014. Pepsi and Coke sell well to Asian and South American customers. He bought a Ford Escort for $20,000 and drove to the lake for the weekend. The parade was last S...
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import numpy as np import unittest from chainer import testing from chainercv.experimental.links.model.pspnet import convolution_crop class TestConvolutionCrop(unittest.TestCase): def test_convolution_crop(self): size = (8, 6) stride = (8, 6) n_channel = 3 img = np.random.uniform...
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from ._version import __version__, __js__ def _jupyter_labextension_paths(): return [{"src": "labextension", "dest": __js__["name"]}] def _jupyter_server_extension_points(): return [{"module": "jupyterlab_pullrequests"}] def _load_jupyter_server_extension(server_app): """Registers the API handler to re...
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import itertools import numpy as np import networkx as nx import vocab def coref_score(instance, property_id): return [ instance.subject_entity["coref_score"], instance.object_entity["coref_score"] ] def el_score(instance, property_id): return [ instance.subject_entity["el_score"], instance.object_entity["el_scor...
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import numpy as np from ..Delboeuf.delboeuf_parameters import _delboeuf_parameters_sizeinner, _delboeuf_parameters_sizeouter def _ebbinghaus_parameters(illusion_strength=0, difference=0, size_min=0.25, distance=1, distance_auto=False): # Size inner circles parameters = _delboeuf_parameters_sizeinner(differe...
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import json import os from typing import List, Tuple import pytest @pytest.fixture(scope='module') def here(): return os.path.abspath(os.path.dirname(__file__)) @pytest.fixture(scope='module') def accounts(here) -> List[Tuple] or None: """Return account list""" accounts_path = os.path.join(here, 'confi...
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import datetime from typing import TYPE_CHECKING, Generator import Evtx.Evtx as evtx from lxml import etree from beagle.common.logging import logger from beagle.datasources.base_datasource import DataSource from beagle.transformers.evtx_transformer import WinEVTXTransformer if TYPE_CHECKING: from beagle.transfor...
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import tempfile import strax import straxen from straxen.test_utils import nt_test_run_id, DummyRawRecords, testing_config_1T, test_run_id_1T def _run_plugins(st, make_all=False, run_id=nt_test_run_id, from_scratch=False, **process_kwargs): """ ...
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import caffe2onnx.src.c2oObject as Node from typing import List import copy def get_concat_attributes(layer): axis = layer.concat_param.axis attributes = {"axis": axis} return attributes def get_concat_outshape(layer, input_shape: List) -> List: bottom = input_shape[0] axis = layer.concat_param....
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from __future__ import absolute_import from __future__ import division from __future__ import print_function __license__ = 'MIT' __maintainer__ = ['<NAME>'] __email__ = ['<EMAIL>']
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from abc import ABC, abstractmethod import gym class BaseGymEnvironment(gym.Env): """Base class for all Gym environments.""" @property def parameters(self): """Return environment parameters.""" return { 'id': self.spec.id, } class EnvBinarySuccessMixin(ABC): """...
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import numpy as np def moving_average(a, n=3) : """ perform moving average, return a vector of same length as input """ a=a.ravel() a = np.concatenate(([a[0]]*(n-1),a)) # repeating first values ret = np.cumsum(a, dtype=float) ret[n:] = ret[n:] - ret[:-n] ret=ret[n - 1:] / n return ...
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import click from train_anomaly_detection import main_func import numpy as np import os # Define base parameters. dataset_name = 'selfsupervised' net_name = 'StackConvNet' xp_path_base = 'log' data_path = 'data/full' train_folder = 'train' val_pos_folder = 'val/wangen_sun_3_pos' val_neg_folder = 'val/wangen_sun_3_neg'...
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import logging import oscar ''' This family is deprecated, so it is remaining unimplemented ''' x0c_name="Translation - deprecated" log = logging.getLogger('oscar.snac.x0c') subcodes = {} def x0c_init(o, sock, cb): log.info('initializing') cb() log.info('finished initializing') def x0c...
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from src.environments.slippery_grid import SlipperyGrid import numpy as np # A modified version of OpenAI Gym FrozenLake # only the labelling function needs to be specified sinks = [] for i in range(12, 16): for j in range(15, 19): sinks.append([i, j]) # create a SlipperyGrid object FrozenLake = SlipperyG...
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import argparse import imagesize import os import subprocess parser = argparse.ArgumentParser(description='MegaDepth Undistortion') parser.add_argument( '--colmap_path', type=str, required=True, help='path to colmap executable' ) parser.add_argument( '--base_path', type=str, required=True, help='pa...
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import numpy as np import util from linear_model import LinearModel def main(train_path, eval_path, pred_path): """Problem 1(b): Logistic regression with Newton's Method. Args: train_path: Path to CSV file containing dataset for training. eval_path: Path to CSV file containing dataset for ev...
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from lightning import Lightning from lightning.types.base import Base from functools import wraps import inspect def viztype(VizType): # wrapper that passes inputs to cleaning function and creates viz @wraps(VizType.clean) def plotter(self, *args, **kwargs): if kwargs['height'] is None and kwarg...
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import os import pytest import shutil import flask from flask import Flask import graphene import pprint from graphene.test import Client from mock import patch import responses from gtmcore.auth.identity import get_identity_manager_class from gtmcore.configuration import Configuration from gtmcore.gitlib import RepoL...
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import os import simplejson as json from getpass import getpass from pytezos.crypto import Key class Keychain: def __init__(self, path='~/.tezos-client/secret_keys'): self._path = os.path.expanduser(path) self._secret_keys = list() self._last_modified = 0 def reload(self): l...
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from topaz.module import ClassDef from topaz.objects.objectobject import W_Object from topaz.modules.ffi.function import W_FFIFunctionObject from rpython.rlib import jit class W_VariadicInvokerObject(W_Object): classdef = ClassDef('VariadicInvoker', W_Object.classdef) def __init__(self, space): W_Ob...
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from recolor import Core def main(): # Simulating Protanopia with diagnosed degree of 0.9 and saving the image to file. Core.simulate(input_path='Examples_Check/ex_original.jpg', return_type='save', save_path='Examples_Check/ex_simulate_protanopia.png', si...
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from aydin.it.normalisers.base import NormaliserBase class IdentityNormaliser(NormaliserBase): """Identity Normaliser""" def __init__(self, **kwargs): """Constructs a normalisers""" super().__init__(**kwargs) def calibrate(self, array): """Calibrate method Parameters ...
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from django.test import TestCase from django_hats.bootstrap import Bootstrapper class RolesTestCase(TestCase): def setUp(self, *args, **kwargs): '''Clears `Roles` cache for testing. ''' for role in Bootstrapper.get_roles(): setattr(role, 'group', None) return super(Rol...
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def create_500M_file(name): native.genrule( name = name + "_target", outs = [name], output_to_bindir = 1, cmd = "truncate -s 500M $@", )
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from fastapi import FastAPI from models import User, db app = FastAPI() db.init_app(app) @app.get("/") async def root(): # count number of users in DB return {"hello": "Hello!"} @app.get("/users") async def users(): # count number of users in DB return {"count_users": await db.func.count(User.id)....
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import numpy as np import cPickle import os import pdb import cv2 def unpickle(file): fo = open(file, 'rb') dict = cPickle.load(fo) fo.close() return dict def load_data(train_path,order,nb_groups, nb_cl, nb_val,SubMean = False): xs = [] ys = [] for j in range(1): d = unpickle(train_p...
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from wayback_machine_archiver.archiver import format_archive_url def test_archive_org(): BASE = "https://web.archive.org/save/" URLS = ( "https://alexgude.com", "http://charles.uno", ) for url in URLS: assert BASE + url == format_archive_url(url)
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from kiwoom import config from kiwoom.config import valid_event from functools import wraps from textwrap import dedent from types import LambdaType from inspect import ( getattr_static, ismethod, isfunction, isclass, ismodule ) class Connector: """ Decorator class for mapping empty event...
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from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, BigInteger, String import config Base = declarative_base() formFields = config.form_fields class Register(Base): __tablename__ = config.table_name col1 = Column(formFields[0]['fname'], formFields[0]['ftype'], primary_key=T...
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import logging import sys def get_logger(filename, logger_name='centroFlye', level=logging.INFO, filemode='a', stdout=True): logger = logging.getLogger(logger_name) logger.setLevel(level) # create the logging file handler fh = logging.FileHa...
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import os, sys sys.path.insert(0, os.path.join(os.pardir, 'src')) def sympy_solution(): from sympy import symbols, Rational, solve C1, C3, C4 = symbols('C1 C3 C4') s = solve([C1 - 1 - C3, C1 - Rational(1,2) - C3 - C4, 2 + 2*C3 + C4], [C1,C3,C4]) return s import numpy as np import matplo...
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import pytest from requests.exceptions import HTTPError from commercetools.platform import models def test_channel_get_by_id(old_client): channel = old_client.channels.create( models.ChannelDraft( key="test-channel", roles=[models.ChannelRoleEnum.INVENTORY_SUPPLY] ) ) assert ...
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import numpy as np import torch from scipy.stats import entropy as sc_entropy class MultipredictionEntropy: def __int__(self): """ Computes the entropy on multiple predictions of the same batch. """ super(MultipredictionEntropy, self).__init__() def __call__(self, y, device='...
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from django.contrib import admin # Register your models here. from training.models import Training admin.site.register(Training)
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import unittest from os.path import join, dirname from io import BytesIO from urllib.parse import quote from falcon_heavy.http.multipart_parser import MultiPartParser, MultiPartParserError from falcon_heavy.http.exceptions import RequestDataTooBig, TooManyFieldsSent from falcon_heavy.http.utils import parse_options_he...
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from __future__ import division import datetime import time from PyQt5.QtCore import Qt from PyQt5 import QtWidgets from chainer.training import extension try: from chainer.training.triggers import interval except ImportError: from chainer.training.triggers import interval_trigger as interval class CWProgr...
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from django.conf.urls import url from .views import ( post_model_create_view, post_model_detail_view, post_model_delete_view, post_model_list_view, post_model_update_view ) urlpatterns = [ url(r'^$', post_model_list_view, name='list'), url(r'^create/$', post_model_create_view, name='c...
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from django.core.cache import cache from django.shortcuts import render, get_object_or_404 from django_redis import get_redis_connection from .models import Image # Create your views here. con = get_redis_connection("default") def index(request): query = Image.objects.all() images_seq = [ {'id': da...
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from gazette.spiders.base.fecam import FecamGazetteSpider class ScCuritibanosSpider(FecamGazetteSpider): name = "sc_curitibanos" FECAM_QUERY = "cod_entidade:82" TERRITORY_ID = "4204806"
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class Test: """ Lorem ipsum dolor sit amet, consectetur adipiscing elit, deserunt mollit anim id est laborum. .. sourcecode:: pycon >>> # extract 100 LDA topics, using default parameters >>> lda = LdaModel(corpus=mm, id2word=id2word, num_topics=100, distributed=True) using distrib...
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import matplotlib matplotlib.use('TkAgg') import matplotlib.pyplot as plt import torch import torch.nn as nn import torchvision import torchvision.transforms as transforms import torch.utils.data as Data import numpy as np import time import sys import utils print('生成测试数据') n_train, n_test, num_inputs = 20, 100, 200 t...
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import numpy as np import unittest from convolution import conv2d, add_padding class TestConvolution(unittest.TestCase): def test_paddings_shape(self, N: int = 1000): for _ in range(N): m_h = np.random.randint(3, 100) m_w = np.random.randint(3, 100) random_matrix = np....
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import os from arcsv.helper import get_ucsc_name def get_inverted_pair(pair, bam): chrom = bam.getrname(pair[0].rname) # already checked reads on same chrom if pair[0].pos < pair[1].pos: left = pair[0] right = pair[1] else: left = pair[1] right = pair[0] left_coord = ...
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from __future__ import annotations import typing import toolcli from ctc import evm from ctc import spec from ctc.cli import cli_utils def get_command_spec() -> toolcli.CommandSpec: return { 'f': async_events_command, 'help': 'get contract events', 'args': [ { ...
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import sys from pathlib import Path sys.path.append(str(Path(__file__).resolve().parent)) import unittest import nanopq import numpy as np class TestSuite(unittest.TestCase): def setUp(self): np.random.seed(123) def test_property(self): opq = nanopq.OPQ(M=4, Ks=256) self.assertEqual...
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from typing import List from unittest.case import TestCase from uuid import uuid4 from eventsourcing.application import Application from eventsourcing.persistence import Notification from eventsourcing.system import ( AlwaysPull, Follower, Leader, NeverPull, ProcessApplication, Promptable, ...
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import os import os.path as osp import random as rd import subprocess from typing import Optional, Tuple, Union import click from mim.click import CustomCommand, param2lowercase from mim.utils import ( echo_success, exit_with_error, get_installed_path, highlighted_error, is_installed, module_f...
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import asyncio import logging from timeit import default_timer as timer from podping_hivewriter.async_context import AsyncContext from podping_hivewriter.models.podping_settings import PodpingSettings from podping_hivewriter.podping_settings import get_podping_settings from pydantic import ValidationError class Podp...
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from operator import itemgetter from collections import defaultdict import scipy.stats as st import numpy as np import pandas as pd def k_factor(margin_of_victory, elo_diff): init_k = 20 if margin_of_victory>0: multiplier = (margin_of_victory+3) ** (0.8) / (7.5 + 0.006 * (elo_diff)) else: ...
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from collections.abc import ( AsyncIterator, ) from typing import ( Any, ) from ...database import ( DatabaseClient, ) from .operations import ( MockedDatabaseOperation, ) class MockedDatabaseClient(DatabaseClient): """For testing purposes""" def __init__(self, *args, **kwargs): supe...
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import torch import numpy as np import shutil import os from data import ljspeech import hparams as hp def preprocess_ljspeech(filename): in_dir = filename out_dir = hp.mel_ground_truth if not os.path.exists(out_dir): os.makedirs(out_dir, exist_ok=True) metadata = ljspeech.build_from_path(in_...
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from django.core.management.base import BaseCommand, CommandError from canvas.thumbnailer import update_all_content from canvas.models import Content from canvas.upload import get_fs from configuration import Config from django.conf import settings class Command(BaseCommand): args = '' help = 'Recreates all th...
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from django.apps import AppConfig class ProfileConfig(AppConfig): label = "profile" name = "edd.profile" verbose_name = "User Profiles"
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import h5py import numpy as np from keras.datasets import mnist from keras.utils import to_categorical # input image dimensions img_rows, img_cols = 28, 28 # the data, shuffled and split between train and test sets (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train = x_train.reshape(x_train.shape[0], img...
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class Model(object): def __init__(self,configModel,utils,strTrial): self.tag = configModel[0] self.mode = configModel[1] self.featureSet = configModel[2] self.misc = configModel[3] self.masterTest = utils.TEST_IDS_PATH self.bootTrain = utils.MODEL...
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from moncash import constants class Environment(object): def __init__(self, name, host): self.__name__ = name self.host = host self.protocol = "https://" if name == 'Sandbox': self.redirect_url = constants.SANDBOX_REDIRECT_URL elif name == 'Production': ...
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import torch import mmocr.utils as utils from mmocr.models.builder import CONVERTORS from .base import BaseConvertor import numpy as np @CONVERTORS.register_module() class MasterConvertor(BaseConvertor): """Convert between text, index and tensor for encoder-decoder based pipeline. Args: dict_typ...
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from rply.token import BaseBox from vython.errors import error, Errors as errors import sys class BinaryOp(BaseBox): def __init__(self, left, right): self.left = left self.right = right if self.right.kind == "string" or self.left.kind == "string": self.kind = "string" el...
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import sys from time import time class Progress: """ """ def __init__(self, iterable, size = None, interval = 0.1): """ Args: iterable size (int): max size of iterable interval (float): update bar interval second, default is `0.1` Attrs: ...
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from ariadne import QueryType from neo4j_graphql_py import neo4j_graphql query = QueryType() @query.field('Movie') @query.field('MoviesByYear') def resolve(obj, info, **kwargs): return neo4j_graphql(obj, info.context, info, **kwargs)
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def set_fill_color(red, green, blue): pass def draw_rectangle(corner, other_corner): pass set_fill_color(red=161, green=219, blue=114) draw_rectangle(corner=(105,20), other_corner=(60,60))
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import pytest import unittest from pydu.dict import AttrDict, LookupDict, CaseInsensitiveDict, OrderedDefaultDict, attrify class TestAttrDict: def test_attr_access_with_init(self): d = AttrDict(key=1) assert d['key'] == 1 assert d.key == 1 def test_attr_access_without_init(self): ...
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import operator from django.db.models import Q as DjangoQ from django.db.models.lookups import Lookup from ..ql import Q as SearchQ def resolve_filter_value(v): """Resolve a filter value to one that the search API can handle We can't pass model instances for example. """ return getattr(v, 'pk', v) ...
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import unittest import pytest import paramak class TestExtrudeHollowRectangle(unittest.TestCase): def setUp(self): self.test_shape = paramak.ExtrudeHollowRectangle( height=10, width=15, casing_thickness=1, distance=2 ) def test_default_parameters(self): """Checks that th...
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from __future__ import print_function from __future__ import absolute_import from __future__ import division from numpy import asarray from scipy.spatial import Voronoi from scipy.spatial import Delaunay __all__ = [ 'delaunay_from_points_numpy', 'voronoi_from_points_numpy', ] def delaunay_from_points_numpy...
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import sys from ..api import plot import fuc import pysam description = f""" Plot allele fraction profile from VcfFrame[Imported]. """ def create_parser(subparsers): parser = fuc.api.common._add_parser( subparsers, fuc.api.common._script_name(), description=description, help='Plo...
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f = plt.figure(figsize=(6,6)) plt.scatter(pres.swing_full, lp.weights.lag_spatial(w, pres.swing_full)) plt.plot((-.3,.1),(-.3,.1), color='k') plt.title('$I = {:.3f} \ \ (p < {:.3f})$'.format(moran.I,moran.p_sim))
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import sys import pprint pp = pprint.PrettyPrinter(); import pymongo from pymongo import MongoClient #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Oct 12 20:30:54 2016 @author: ryanlim, jpitts Requirements: - pymongo needs to be installed - mongodb needs to be running - brigade-match...
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from simple_playgrounds.playground.playgrounds import * from simple_playgrounds.engine import Engine from simple_playgrounds.agent.controllers import Keyboard from simple_playgrounds.agent.agents import HeadAgent import time import cv2 my_agent = HeadAgent(controller=Keyboard(), lateral=True, interactive=True) ####...
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from .nlm3 import nlm3 from .nlm2 import nlm2 from .bilateral2 import bilateral2 from .bilateral3 import bilateral3
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import logging import re import shlex import threading import sshim logging.basicConfig(level='DEBUG') logger = logging.getLogger() class Device(threading.Thread): def __init__(self, script): threading.Thread.__init__(self) self.history = [] self.script = script self.start() d...
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import numpy as np import nanonet.tb as tb from test.test_hamiltonian_module import expected_bulk_silicon_band_structure def test_simple_atomic_chain(): """ """ site_energy = -1.0 coupling = -1.0 l_const = 1.0 a = tb.Orbitals('A') a.add_orbital(title='s', energy=-1, ) xyz_file = """1 ...
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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import collections import json import os import re import mock import requests_mock from six.moves.urllib import parse as urlparse import testtools # Setup dummy enviro...
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import functools import numpy as np import torch as t import torch.nn as nn import torch.distributed as dist from jukebox.transformer.ops import Conv1D, ACT_FNS, LayerNorm from jukebox.transformer.factored_attention import FactoredAttention from jukebox.utils.checkpoint import checkpoint def _convert_mlp_traced(l): ...
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from __future__ import absolute_import, division, print_function from .multi_pose import MultiPoseTrainer train_factory = { 'multi_pose': MultiPoseTrainer, }
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from dassl.utils import Registry, check_availability EVALUATOR_REGISTRY = Registry("EVALUATOR") def build_evaluator(cfg, **kwargs): avai_evaluators = EVALUATOR_REGISTRY.registered_names() check_availability(cfg.TEST.EVALUATOR, avai_evaluators) if cfg.VERBOSE: print("Loading evaluator: {}".format(...
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from hybrid_astar_planner.HybridAStar.hybrid_astar_wrapper \ import apply_hybrid_astar import numpy as np from pylot.planning.planner import Planner class HybridAStarPlanner(Planner): """Wrapper around the Hybrid A* planner. Note: Details can be found at `Hybrid A* Planner`_. Args: ...
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import os import numpy as np import matplotlib.pyplot as plt import pyvips as Vips NP_DTYPE_TO_VIPS_FORMAT = { np.dtype('int8'): Vips.BandFormat.CHAR, np.dtype('uint8'): Vips.BandFormat.UCHAR, np.dtype('int16'): Vips.BandFormat.SHORT, np.dtype('uint16'): Vips.BandFormat.USHORT, ...
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from torch import nn import torch.nn.functional as F from ssd.modeling import registry from ssd.modeling.anchors.prior_box import PriorBox from ssd.modeling.box_head.box_predictor import make_box_predictor from ssd.utils import box_utils from .inference import PostProcessor from .loss import MultiBoxLoss, FocalLoss ...
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from __future__ import absolute_import from __future__ import unicode_literals import json import logging from urllib.parse import quote import requests from pypuppetdb.errors import (APIError, EmptyResponseError) log = logging.getLogger(__name__) ENDPOINTS = { 'facts': 'pdb/query/v4/facts', 'fact-names': ...
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from rllab.misc import logger import matplotlib as mpl mpl.use('Agg') import matplotlib.pyplot as plt import os.path as osp import numpy as np import math import random def line_intersect(pt1, pt2, ptA, ptB): """ Taken from https://www.cs.hmc.edu/ACM/lectures/intersections.html this returns the intersect...
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import json import sys import csv import argparse import time import subprocess import pingparsing # defined in parameters.py from parameters import ( filters, number_rules, iterations, iface, bandwidth, seed, ipnets, ping_interval, ping_count, ) from k8s import benchmark_pod_tmp...
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import os from unittest import TestCase # most of the features of this script are already tested indirectly when # running vensim and xmile integration tests _root = os.path.dirname(__file__) class TestErrors(TestCase): def test_canonical_file_not_found(self): from pysd.tools.benchmarking import runner...
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from abc import abstractmethod, abstractproperty import os from pathlib import Path import collections.abc import logging import pkg_resources import uuid from urllib.parse import urlparse from typing import Set, List import threading import numpy as np from frozendict import frozendict import pyarrow as pa import v...
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import os import argparse import pyautogui import time parser = argparse.ArgumentParser() parser.add_argument("-p", "--path", help="absolute path to store screenshot.", default=r"./images") parser.add_argument("-t", "--type", help="h (in hour) or m (in minutes) or s (in seconds)", default='h') parser.add_argument("-f...
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import os, sys, inspect sys.path.insert(1, os.path.join(sys.path[0], '..')) from core.bounds import WSR_mu_plus from core.concentration import get_tlambda, get_lhat_from_table, get_lhat_from_table_binarysearch import numpy as np from scipy.optimize import brentq from tqdm import tqdm import pdb def get_coco_example_l...
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import FWCore.ParameterSet.Config as cms process = cms.Process("WRITE") process.source = cms.Source("EmptySource", numberEventsInLuminosityBlock = cms.untracked.uint32(4)) process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(20)) process.out = cms.OutputModule("PoolOutputModule", fileName = cms.untra...
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import copy from django.http import HttpResponseBadRequest from django.contrib.sitemaps import views as django_sitemaps_views def custom_sitemap_index(request, sitemaps, section=None, template_name='sitemap.xml', content_type='application/xml'): platform = request.GET.get('platform', None) platform_in = reque...
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from jmetal.algorithm.singleobjective.simulated_annealing import SimulatedAnnealing from jmetal.operator import BitFlipMutation from jmetal.problem import OneMax from jmetal.util.solution import print_function_values_to_file, print_variables_to_file from jmetal.util.termination_criterion import StoppingByEvaluations i...
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import ledshim class Leds(object): def __init__(self): self.count = 24 def set_one(self, led_number, color): ledshim.set_pixel(led_number, *color) def set_range(self, a_range, color): ledshim.set_multiple_pixels(a_range, color) def set_all(self, color): l...
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import pytest from yamlpath.merger.enums.anchorconflictresolutions import ( AnchorConflictResolutions) class Test_merger_enum_anchorconflictresolutions(): """Tests for the AnchorConflictResolutions enumeration.""" def test_get_names(self): assert AnchorConflictResolutions.get_names() == [ "STOP", "LEFT",...
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import numpy as np import pandas as pd from statsmodels.sandbox.stats.multicomp import multipletests import regreg.api as rr from ...api import (randomization, glm_group_lasso, multiple_queries) from ...tests.instance import (gaussian_instance, lo...
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from django import template register = template.Library() @register.simple_tag(name='render_field') def render_field(field, **kwargs): field.field.widget.attrs.update(kwargs) return field
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import json data = ''' [ { "name":"Sister", "count":95 }, { "name":"Sidharth", "count":94 }, { "name":"Ilona", "count":93 }, { "name":"Ruairidh", "count":93 }, { "name":"Virginie", "count":92 }, { "name":"Alan...
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from tethys_sdk.testing import TethysTestCase import tethys_services.models as service_model from unittest import mock class SpatialDatasetServiceTests(TethysTestCase): def set_up(self): pass def tear_down(self): pass def test__str__(self): sds = service_model.SpatialDatasetServi...
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from django.utils.functional import cached_property from redis.exceptions import ConnectionError, ResponseError from experiments.redis_client import get_redis_client COUNTER_CACHE_KEY = 'experiments:participants:%s' COUNTER_FREQ_CACHE_KEY = 'experiments:freq:%s' class Counters(object): @cached_property d...