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import numpy as np
import tensorflow as tf
import time
from common import *
from _datetime import timedelta
def new_weights(shape,name):
return tf.Variable(tf.truncated_normal(shape, stddev=0.05), name=name)
def new_biases(length,name):
return tf.Variable(tf.constant(0.05, shape=[length]), name=name)
def new... |
#!/usr/bin/env python3
import itertools
import re
__all__ = [
'Puzzle3',
'Puzzle8',
'Puzzle15',
'puzzle_class',
'make_puzzle',
'read_puzzle',
'write_puzzle',
]
from .config import config_getkey
from .driver import make_driver, Node
from .utils import (
flatten,
)
class PuzzleMeta(t... |
"""
Process a pickled DataFrame of annotations so that the labels assigned by the annotators (`label` column) are parsed into separate columns (e.g. `ENR`, `ENR_lvl`, 'background', etc.). Save the resulting parsed DataFrame in pkl format.
The input pickled DataFrame is created from a batch of annotated tsv files with ... |
import torch
from torch import nn
from utils import compute_gradient_penalty, optimizer_to
from block import Block, ResBlock
class Generator(nn.Module):
def __init__(self, domain_dim: int, begin_conv_dim: int):
super().__init__()
self.begin_layers = Block(domain_dim + 3, begin_conv_dim,
... |
from django.db import models
from phone_field import PhoneField
from localflavor.in_.models import INStateField
from django.core.mail import send_mail
GENDER_CHOICES = (
("Male", "Male"),
("Female", "Female"),
("Other", "Other"),
)
# Create your models here.
class Student(models.Model):
id = models.A... |
# coding=utf-8
#! /usr/bin/env python3.4
"""
MIT License
Copyright (c) 2018 NLX-Group
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... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 18 12:40:54 2018
reference: https://github.com/prateekroy/Computer-Vision/blob/master/HW3/
detection_tracking.py
@author: lrianu
"""
# import sys
import cv2
import numpy as np
# Read the video file
video = cv2.VideoCapture('FishVideo.mp4')
file_na... |
import sys, os, pkg_resources, zipfile
from PIL import Image
from PyQt5 import QtCore
from PyQt5.QtGui import QPixmap, QIcon
from PyQt5.QtWidgets import QMainWindow, QApplication, QLabel, QFileDialog ,QPushButton,QListWidget, QCheckBox, QListWidgetItem, QComboBox
"""This section is needed so relative paths still work... |
"""
These are utility functions for doing dense prediction of an image.
We want to take multiple crops from the image and process them.
We want to take the union of all proposals, and then do some non-max-suppression.
"""
from matplotlib import pyplot as plt
import numpy as np
def extract_patches(image, patch_dims... |
# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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... |
''' a package of functions to convert data architecture formats '''
__author__ = 'rcj1492'
__created__ = '2017.06'
__licence__ = 'MIT'
def _to_camelcase(input_string):
''' a helper method to convert python to camelcase'''
camel_string = ''
for i in range(len(input_string)):
if input_string[i] == '_... |
#%%
from kdg import kdf
from kdg.utils import get_ece
import openml
import multiprocessing
from joblib import Parallel, delayed
import numpy as np
import pandas as pd
from sklearn.model_selection import StratifiedKFold
from sklearn.ensemble import RandomForestClassifier as rf
from sklearn.metrics import cohen_kappa_sco... |
import math
from scipy.stats import norm
import pandas as pd, numpy as np
from datetime import date
from matplotlib import ticker
import matplotlib.dates as mdates
def set_plot(ax):
ax.set_axisbelow(True)
# Turn on the minor TICKS, which are required for the minor GRID
ax.minorticks_on()
# Customize th... |
import math
import numpy as np
from PIL import Image
from skimage import color, io
def load(image_path):
"""Loads an image from a file path.
HINT: Look up `skimage.io.imread()` function.
Args:
image_path: file path to the image.
Returns:
out: numpy array of shape(image_height, imag... |
import datetime
import re
from os import walk, listdir
from os.path import exists, relpath, splitext
import markdown
from yaml import safe_load as load
from babel.messages.catalog import Catalog
from babel.messages.pofile import write_po, read_po
from flask import safe_join
from bolttools.common import UNITS
def spli... |
"""
Only testing custom functionality not (re-)testing django model framework.
Uses tests.utils.ModelTesterMixin to patch out model save() methods to make
unit tests that avoid slow calls to database when testing custom save methods
on models.
"""
from django.test import TestCase, override_settings
from mixer.backend... |
#!/usr/bin/env python3
"""
Train ranfom forest classifier on Boston dataset
"""
import argparse
import pickle
import numpy as np
import sklearn.datasets
import sklearn.ensemble
import sklearn.model_selection
import termcolor
def parse_args():
"""
Parse command line arguments.
Returns:
args (ar... |
#!/usr/bin/python
#
# Copyright (C) 2016 Google, Inc
# Written by <NAME> <<EMAIL>>
#
# SPDX-License-Identifier: GPL-2.0+
#
import struct
import sys
import fdt
from fdt import Fdt, NodeBase, PropBase
import fdt_util
import libfdt
# This deals with a device tree, presenting it as a list of Node and Prop
# objects... |
from .languages import Language
import os
import time
class Compile:
"""
This class works as a wrapper class for receiving the run events
for different languages. The main job of this class is to factor out
the common patterns in various language compilation flow and called
the relevant class
... |
from django.contrib.auth import login, views
from django.contrib.auth.mixins import LoginRequiredMixin
from django.contrib.auth.tokens import PasswordResetTokenGenerator
from django.contrib.sites.shortcuts import get_current_site
from django.core.mail import EmailMessage
from django.http import HttpResponse
from django... |
import cv2
import time
import secrets
import numpy as np
import face_recognition
from models import cnn_model_2
img_file_ext = '.jpg'
vid_file_ext = '.mp4'
class_labels = {0: 'Anger', 1: 'disgust', 2: 'fear', 3: 'Happy', 4: 'Sad', 5: 'Surprise', 6: 'Neutral'}
# load model and model.predict_class
def l... |
# -*- coding: utf-8 -*-
"""The App Engine Transport Adapter for requests.
.. versionadded:: 0.6.0
This requires a version of requests >= 2.10.0 and Python 2.
There are two ways to use this library:
#. If you're using requests directly, you can use code like:
.. code-block:: python
>>> import requests
... |
# The MIT License (MIT)
#
# Copyright (c) 2019 <NAME> for Algebra Global, Inc.
#
# 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
#... |
# Copyright (c) 2017 Orange.
# 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 a... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Readers for the pke module."""
import os
import sys
import json
import logging
import xml.etree.ElementTree as etree
import spacy
from pke.data_structures import Document
class Reader(object):
def read(self, path):
raise NotImplementedError
class Minim... |
import gym
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from torch.utils.tensorboard import SummaryWriter
# The network of the actor
class Actor(nn.Module):
def __init__(self, state_dim, action_dim, hidden_width):
super(Actor, self).__init__()
s... |
"""
Contains utility functions for saving / retrieving menus from / to SQL
"""
from datetime import datetime, timedelta
import json
import pymysql
from menu2 import WebCrawler
from menu2.models import Dish
from sql import SQLConnectionHandler as sqlhandler
#import serverlessHandlers.HandleMessage as messageHandler
fr... |
from scipy.ndimage import rotate
from cil.framework import ImageGeometry
from cil.framework import AcquisitionGeometry
import matplotlib.pyplot as plt
from scipy.fft import fft, ifft, fftshift, fftfreq, ifftshift
import numpy as np
from cil.utilities.display import show2D
from cil.utilities import dataexample
from PIL ... |
from lxml import etree
angular_shells = ["s", "p", "d", "f", "g", "h", "i"]
class Shell:
def __init__(self, lval = 0, nexp = 0, nbfs = 0):
self.lval = lval
self.powers = []
self.nexp = nexp
self.exps = []
self.contr = []
class Atom:
def __init__(self, name="X", nshells... |
# This file is part of QuTiP: Quantum Toolbox in Python.
#
# Copyright (c) 2011 and later, <NAME> and <NAME>.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# 1. Redistrib... |
# from tapis_cli.main import PKG_NAME, About, VersionInfo
import requests
import curlify
from json import JSONDecodeError
from requests.auth import HTTPBasicAuth
from agavepy.agave import Agave
from tapis_cli.utils import print_stderr
from tapis_cli.settings import TAPIS_CLI_SHOW_CURL, TAPIS_CLI_VERBOSE_ERRORS
from tap... |
from cv2 import reduce
import pandas as pd
import numpy as np
import re as re
from sklearn.preprocessing import StandardScaler
from base import Feature, get_arguments, generate_features
Feature.dir = 'features'
# class Pclass(Feature):
# def create_features(self):
# self.train['Pclass'] = train['Pclass']... |
"""housing.py framework entity module
"""
#print("module {0}".format(__name__))
import pdb
import copy
from collections import deque
from ..aid.sixing import *
#from .globaling import *
from ..aid.odicting import odict
from . import excepting
from . import registering
from . import storing #needed by house and f... |
# 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 appl... |
#!/usr/bin/env python -W ignore::DeprecationWarning
import argparse
import asyncio
from _weakref import ref
import torchvision.transforms
from absl import app
from stable_baselines3.common.vec_env import CloudpickleWrapper
from rgb_stacking.run import init_env
import tensorflow as tf
import socket
from numpy import u... |
import sys
sys.path.append("/home/ray__/ssd/BERT/") # gpt model utils location
from gpt_feat_utils import GPT_Inference
import json
from copy import deepcopy
import pickle, json
import numpy as np
from scipy.spatial.distance import cosine
from collections import Counter
sys.path.append("../") # grouping functions mai... |
import json
from copy import deepcopy
import sys
def calinout(intermediateStates):
global dfa
mp=[]
for x in range(len(intermediateStates)):
ie=0
oe=0
for j in range(len(dfa["transition_function"])):
if dfa["transition_function"][j][2] == intermediateStates[x]:
... |
# Copyright 2018 Amazon.com, Inc. or its affiliates. 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. A copy of the License
# is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file acc... |
#!/usr/bin/env python
u"""
read_ee_phase.py
Written by <NAME>' (02/2022)
Compute the complex difference between two coregistered interferograms.
usage: read_ee_phase.py [-h] [--directory DIRECTORY]
[--outdir OUTDIR] reference secondary
TEST: Compute the complex difference between two coregistered interferogra... |
"""Optionally test filters."""
import logging
from itertools import repeat
from typing import Any, Callable, List
import pytest
from sunsynk.definitions import ALL_SENSORS
from tests.conftest import import_module
_LOGGER = logging.getLogger(__name__)
MOD_FOLDER = "hass-addon-sunsynk-dev"
@pytest.fixture
def filter... |
import os
import tensorflow as tf
from tensorflow import keras
import cv2
import numpy as np
from scipy.io import loadmat
from sklearn.preprocessing import LabelBinarizer
def prepare_not_mnist():
home_dir = os.path.expanduser('~')
data_dir = home_dir+"/Datasets"
os.system(f"gsutil cp -r gs://custom_datase... |
#%%
import numpy as np
import pandas as pd
import cremerlab.hplc
import matplotlib.pyplot as plt
import scipy.signal
import scipy.special
import scipy.stats
import imp
imp.reload(cremerlab.hplc)
start = 0
end = 45 * 60
step = 0.5
time = np.arange(start, end, step)
# Define peaks and width
intensities = np.array... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
class Digit:
def __init__(self, segments):
self.segments = segments
def length(self):
return len(self.segments)
def __sub__(self, d):
segments = [n for n in self.segments]
for segment in d.segments:
if segment in segments:
segments.remove(segment)
ret... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Source catalog and object base classes.
"""
from __future__ import absolute_import, division, print_function, unicode_literals
from collections import OrderedDict
from copy import deepcopy
import numpy as np
from ..extern import six
from astropy.utils i... |
# all the imports
import os
import re
import sys
import glob
import time
import uuid
import atexit
import requests
import subprocess
import pandas as pd
import seaborn as sns
import pybtex.database
from datetime import datetime
from contextlib import closing
from numpy import array, random
from os.path import abspath, ... |
import time
import machine
from machine import I2C, Pin
from leddriver import Max7219Chain
from textmatrix import TextFinder
from lightsensor import BH1750
from touch import TouchSensor
from localtime import LocalTime
from common import get_main_cfg, get_custompos_cfg
CURRENT_MODE = 0 # 0: Time, 1: Temperature, 2: ... |
"""
Utilities for pushing models to the Hugging Face Hub ([hf.co](https://hf.co/)).
"""
import logging
import shutil
import tarfile
import tempfile
import zipfile
from os import PathLike
from pathlib import Path
from typing import Optional, Union
from huggingface_hub import HfApi, HfFolder, Repository
from allennlp.... |
# -*- coding: utf-8 -*-
""" Example of g-function calculation using non-uniform segment lengths along
the boreholes.
The g-functions of a field of 6x4 boreholes are calculated for two
boundary conditions : (1) a uniform borehole wall temperature along the
boreholes equal for all boreholes, and (2) an e... |
"""
Wrapper script around compliance-checker to automatically find and run the
relevant YAML checks for AMF datasets.
"""
from __future__ import print_function
import os
import subprocess
import sys
import re
import argparse
from netCDF4 import Dataset
import cchecker
from amf_check_writer.spreadsheet_handler import ... |
"""Graph encoders."""
import manifolds
import layers.hyp_layers as hyp_layers
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import utils.math_utils as pmath
from layers.layers import GraphConvolution, Linear, get_dim_act
class Encoder(nn.Module):
"""
Encoder abstract cl... |
# -*- coding: utf-8 -*-
"""
vitals.api.base
~~~~~~~~~~~~~~~
:author: <NAME>
:copyright: © 2014-2015, Fog Mine LLC
:license: Proprietary, see LICENSE for more details.
templated from https://github.com/ryanolson/cookiecutter-webapp
"""
import logging
from flask import request
from flask.ext.cl... |
from keras.applications import InceptionV3
from keras.models import Model
from keras.layers import Input, Dropout, Dense, BatchNormalization
from keras.layers import GlobalAveragePooling2D, Concatenate
import tensorflow as tf
import pandas as pd
import os
import numpy as np
from sklearn.model_selection import train_tes... |
import scipy.ndimage as ndimage
import numpy as np
from PIL import Image
import pycocotools.mask as cocomask
from .pycococreater import binary_mask_to_rle
def __bbox_from_bboxes(bboxes: list):
"""
Compute the overall bbox of multiple bboxes
:param bboxes: list of bounding boxes. (should be list of list)
... |
import os, stat, sys
import shutil
import dsz, dsz.env, dsz.version
import ops, ops.db, ops.survey, ops.data
import util
from ops.pprint import pprint
BAD_PROCS = os.path.normpath(('%s/Ops/Data/bad_processes.txt' % ops.RESDIR))
def main(args):
bad = []
with open(BAD_PROCS) as input:
for i in input:
... |
from django.db import models
from django.conf import settings
from django.dispatch import receiver
import uuid
import os
import urllib
from custom_storages import PublicMediaStorage
from .services.create_update_delete import create_row_w_validated_params
from .services.create_update_delete import update_row_w_validat... |
# %%
import os
import traceback
from ctrace.utils import calculateD, calculateExpected, calculateMILP
import numpy as np
from ctrace import PROJECT_ROOT
from ctrace.simulation import InfectionState
from ctrace.exec.param import GraphParam, SIRParam, FileParam, ParamBase, LambdaParam
from ctrace.exec.parallel import Csv... |
#Imports & Dependencies
from splinter import Browser
from bs4 import BeautifulSoup
#pip install ipython
#pip install nbconver
import requests
import pandas as pd
#Site Navigation
def init_browser():
executable_path = {"executable_path": '/usr/local/bin/chromedriver'}
return Browser("chrome", **executable_path... |
#
# Copyright 2020 IBM Corporation
#
# 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... |
from abc import abstractmethod
import json
import os
import shutil
from typing import List, Union, cast
import tarfile
from numpy import source
from .dockerimage import DockerImage, RemoteDockerImage
from ._bindmount import BindMount
def run_scriptdir_in_container(*,
scriptdir: str,
image_name: str,
bind_... |
import os
import ltron.ldraw.paths as ldraw_paths
from ltron.ldraw.commands import (
LDrawCommand,
LDrawFileComment,
LDCadSnapInclCommand,
LDrawImportCommand,
LDrawTriangleCommand,
LDrawQuadCommand,
)
from ltron.ldraw.exceptions import LDrawException
class LDrawMissingFileComment(LDrawExceptio... |
import unittest
import numpy as np
import tensorflow as tf
import tensorflow_probability
import mvg_distributions.gamma as custom_dist
from mvg_distributions.test.test_losses_base import LossesTestBase
tf_dist = tensorflow_probability.distributions
tf_bij = tensorflow_probability.bijectors
class TestGamma(LossesTe... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# @created: 21.05.2014
# @author: <NAME>
# @contact: <EMAIL>
from trseeker.tools.ngrams_tools import print_next_cutoff
from trseeker.tools.ngrams_tools import print_prev_cutoff
# def extend_with_consensus(kmer, kmer2tf, tf_cutoff=0, fraq_cutoff=0.0, verbose=False, lyre... |
from __future__ import absolute_import
from __future__ import print_function
from uncertainties import ufloat, umath
from pychron.processing.arar_constants import ArArConstants
from six.moves import zip
def mcalc_fractional_error(*args):
'''
args= a,b,...,k,T
where fa**2+fb**2+...+fk**2=fT**2
... |
# -*- coding: utf-8 -*-
"""
Project: China-idiom
Creator: DoubleThunder
Create time: 2019-10-12 11:45
Introduction:
"""
import re
import pandas as pd
from china_idiom.constants import (
idiom_df, clean_complie
)
__all__ = [
'is_idiom', 'is_idiom_solitaire',
'next_idioms_solitaire', 'auto_idioms_solitaire',... |
#!/usr/bin/env python3
# License: CC0
import csv
import re
import requests
import datetime
PROG_MAP = {"UK": "United Kingdom", "US": "United States"}
def mysql_quote(x):
'''
Quote the string x using MySQL quoting rules. If x is the empty string,
return "NULL". Probably not safe against maliciously formed... |
''' Tasks which don't include any visuals or bmi, such as laser-only or camera-only tasks'''
from riglib.experiment import LogExperiment, Sequence
from features.laser_features import DigitalWave
from riglib.experiment import traits
import itertools
import numpy as np
MAX_EDGES = 1000
class Conditions(Sequence):
... |
# TODO: Remove this file
raise ValueError('Deprecated file')
import matplotlib
import numpy as np
import sys
from os.path import expanduser
home = expanduser("~")
sys.path.append(home)
sys.path.append(home + '/neurogym')
sys.path.append(home + '/gym')
import gym
from neurogym.wrappers import trial_hist
from neurogym.... |
"""
================================
K-means clustering - PyTorch API
================================
The :meth:`pykeops.torch.LazyTensor.argmin` reduction supported by KeOps :class:`pykeops.torch.LazyTensor` allows us
to perform **bruteforce nearest neighbor search** with four lines of code.
It can thus be used to i... |
import requests
from bs4 import BeautifulSoup
import lxml
import pandas
from datetime import datetime
from datetime import timedelta
import time
import re
reqheaders = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36',
'accept'... |
import numpy as np
from matplotlib import gridspec
from matplotlib import pyplot as plt
from abc import ABCMeta, abstractmethod
from sklearn.utils.extmath import softmax
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils.validation import check_is_fitted
from sklearn.utils import check_array, check_X_... |
###############################################################################
#
# Copyright 2014 by Shoobx, Inc.
#
###############################################################################
from typing import TypeVar, Dict, List, Tuple, Generic
import logging
import multiprocessing
import functools
from migrant... |
# 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 warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from . import ... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Advent of Code 2019 day 15 module."""
from collections import defaultdict
from queue import Queue
def get_params(mem, input_params, modes, base):
params = []
for i, param in enumerate(input_params):
if i >= len(modes):
mode = 0
else... |
# Author: <NAME>
# Project: Kaggle Competition - TalkingData AdTracking Fraud Detection Challenge
# File: model and predict using processed data
# In[7]:
import numpy as np
from pyspark.sql import SparkSession, SQLContext
from pyspark.sql.functions import when, sum
from pyspark.ml.classification import LogisticReg... |
import numpy as np
import cochlea
import scipy.signal
#import matplotlib.pyplot as plt
def peripheralSpikes(sound, par, fs = -1):
if fs == -1:
fs = par['periphFs']
anfTrains = cochlea.run_zilany2014(sound, fs,
anf_num = [60, 25, 15],
... |
from tinygrad.tensor import Tensor
import tinygrad.nn as nn
from extra.utils import fetch, fake_torch_load, get_child
import numpy as np
class BasicBlock:
expansion = 1
def __init__(self, in_planes, planes, stride=1):
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=Fals... |
from .db import *
from flask import render_template, request, send_from_directory, url_for, redirect
from flask_security import current_user, login_required
import json
from flask import Markup
import markdown2
from .app import app
import sys
import os
@app.route('/')
def home():
txt = open('README.md', 'r', encod... |
from collections import namedtuple
from games import (Game)
from queue import PriorityQueue
from copy import deepcopy
class GameState:
def __init__(self, to_move, board, label=None, depth=8, score=0):
self.to_move = to_move
self.board = board
self.label = label
self.maxDepth = dept... |
import inspect, os, re, time, hashlib
from urllib import parse
import logging
from aiohttp import web
from www.apis import APIError
from www.model import User
RE_EMAIL = re.compile(r'^[a-z0-9\.\-\_]+\@[a-z0-9\-\_]+(\.[a-z0-9\-\_]+){1,4}$')
RE_SHAL = re.compile(r'^[0-9a-f]{40}$')
COOKIE_NAME = 'awesome-cookie'
COOKIE... |
import cv2
import heapq
import numpy as np
def get_intersection(a, b):
y = (a[1] * np.cos(b[0]) - b[1] * np.cos(a[0])) / (np.sin(a[0]) * np.cos(b[0]) - np.sin(b[0]) * np.cos(a[0]))
x = (a[1] * np.sin(b[0]) - b[1] * np.sin(a[0])) / (np.cos(a[0]) * np.sin(b[0]) - np.cos(b[0]) * np.sin(a[0]))
return (x, y)
... |
import logging
from typing import Dict, Optional, Set
import asyncpg.exceptions
from aiohttp import web
from aiopg.sa.result import RowProxy
from models_library.users import GroupID, UserID
from simcore_postgres_database.errors import DatabaseError
from . import users_exceptions
from .db_models import GroupType
from ... |
import datetime
from dataclasses import dataclass, field
import pytz
from typing import Sequence, Dict, Optional, List, Tuple
from vardb.datamodel import assessment, sample, attachment
from api.schemas import AlleleAssessmentSchema, ReferenceAssessmentSchema
from api import ApiError
import logging
log = logging.get... |
import os
import pandas as pd
from jinja2 import Environment, PackageLoader
from tqdm import tqdm, tqdm_notebook
from datetime import datetime
import shutil
import uuid
import argparse
from .utils_automl import *
def automl_grid_search(csv_path, target_field,
target_metric=None,
... |
from itertools import chain
from lazylawyer.nlp.helpers import cosine_similarity
from lazylawyer.models.word2vec_training_dataset import Word2VecTrainingDataset
import numpy as np
import os
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch.opt... |
from gensim.corpora import Dictionary
from src.clean_text import TextCleaner
from gensim.models import TfidfModel, LsiModel, LdaModel
from gensim.similarities import MatrixSimilarity
from src.clean_tools import *
from abc import abstractmethod
class WikiModel:
def __init__(self, wiki_tokens_path='data/token_sents... |
from policy.picker import pick_clear, pick_strike
from plays.defense.defense import Defense
from rlutilities.linear_algebra import dot, norm
from rlutilities.simulation import Car
from util.game_info import GameInfo
from util.intercept import Intercept
from tools.vector_math import align, ground, ground_distanc... |
import pandas as pd
import numpy as np
class EMA_class:
def __init__(self,df, base, target, period, alpha=False):
self.df=df
self.base=base
self.target=target
self.period=period
self.alpha=alpha
def EMA(self):
con = pd.concat([self.df[:self.period][self.base].ro... |
# -*- coding: utf-8 -*-
##############################################################################
#
# OpenERP, Open Source Management Solution
# Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>).
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU... |
import asyncio, telnetlib3
import re
import sys
import traceback
import datetime
import time
import json
from sqlalchemy import create_engine
import os
import threading
class CustomRoutine:
device = None
db = None
table = None
# Load Config Elements
param_interest_power = ["LED[0-99]_P", "vRELAY... |
# coding=utf-8
"""
定义VGG16网络层
"""
import tensorflow as tf
import tools
def VGG16(x, n_classes, is_pretrain=True):
"""
:param x: 输入数据
:param n_classes: 输出类别数量
:param is_pretrain: 是否对网络层进行训练
:return: 输出向量
"""
x = tools.conv('conv1_1', x, 64, kernel_size=[3,3], stride=[1,1,1,1], is_pretrain... |
from pygp_retina.rgc import RGC
import cv2
import pickle as pickle
import numpy as np
if False:
from typing import Tuple, List, Any
import math
#https://isotope11.com/blog/storing-surf-sift-orb-keypoints-using-opencv-in-python
def pickle_keypoints(keypoints, descriptors):
i = 0
temp_array = []
for poin... |
from grafana_api.grafana_api import GrafanaClientError, GrafanaBadInputError
from grafana_api.grafana_face import GrafanaFace
from .config import *
from .helpers import *
import logging
grafana_api = ""
configuration = ""
logger = logging.getLogger()
logger_mut = logging.getLogger("mutate")
def setup_grafana(config_... |
import os
import sys
import urllib.request
import re
import socket
from concurrent.futures import ThreadPoolExecutor
from time import gmtime, strftime, time
from typing import List, Optional, Union
def get_size(start_path: str) -> int:
total_size = 0
for dirpath, _, filenames in os.walk(start_path):
... |
from __future__ import print_function
#import sys
import os
import os.path as op
import traceback
#from os import listdir
#from os.path import isfile, join
import re
import logging
from seqcluster.libs.classes import sequence_unique
from seqcluster.libs.classes import quality
from seqcluster.libs.fastq import is_fastq,... |
import numpy as np
from PyQt5 import QtCore, QtGui, QtWidgets
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import struct
import pyaudio
from scipy.fftpack import fft
import peakutils
import padasip as pa
#separate timer class to handle 'multi-threading'
class Thread(QtCore.QThread):
def __init__(s... |
# Copyright (c) 2013, erpcloud.systems and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe import _
def execute(filters=None):
columns, data = [], []
columns=get_columns()
data=get_data(filters,columns)
return columns, data
def get_... |
from smach_based_introspection_framework.offline_part.model_training import train_anomaly_classifier
from smach_based_introspection_framework._constant import (
anomaly_classification_feature_selection_folder,
)
from smach_based_introspection_framework.configurables import model_type, model_config, score_metric
fro... |
from datetime import datetime
import os
import reframe as rfm
import reframe.utility.sanity as sn
class HelloWorldBaseTest(rfm.RegressionTest):
lang = parameter(['c', 'cpp', 'f90'])
prgenv_flags = {}
sourcepath = 'hello_world'
build_system = 'SingleSource'
prebuild_cmds = ['_rfm_build_time="$(date... |
# impy - a post-processor for HYADES implosion simulations
# Copyright (c) Massachusetts Institute of Technology / <NAME>
# Distributed under the MIT License
__author__ = '<NAME>'
import tkinter as tk
import tkinter.font as tkFont
import tkinter.ttk as ttk
import platform
def __sortby__(tree, col, descending):
"... |
import numpy as np
from matplotlib import cm
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d, axis3d, proj3d
from sklearn import decomposition
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.patches import FancyArrowPatch
def colormap_2d(length_x=40, length_y=40):
x = np.lins... |
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