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import pandas as pd
from sklearn.pipeline import Pipeline
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.metrics import confusion_matrix, roc_auc_score
from category_encoders import MEstimateEncoder
import numpy as np
from collections import defaultdict
import os
from sklearn.metrics import roc_au... |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 15 11:43:21 2021
@author: Sander
"""
import random
# TODO: '/poll vote 88' has no output
# : invalid poll id gives no output
# Poll datastructure
#
# {
# "number or name of person":
# {
# "__id" : unique id for every poll
# "__name... |
import hashlib
import json
import math
import os
import dill
import base64
from sys import exit
import requests
from bson import ObjectId
from Crypto.Cipher import PKCS1_OAEP
from Crypto.Hash import SHA256
from Crypto.PublicKey import RSA
#from cryptography.hazmat.primitives.asymmetric import padding
#from cryptography... |
r"""
This module is a ITK Web server application.
The following command line illustrates how to use it::
$ python .../server/itk-tube.py --data /.../path-to-your-data-file
--data
Path to file to load.
Any WSLink executable script comes with a set of standard arguments that ca... |
# file eulxml/xmlmap/cerp.py
#
# Copyright 2010,2011 Emory University Libraries
#
# 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
#
... |
# Copyright 2018 <NAME>, <NAME>.
# (Strongly inspired by original Google BERT code and Hugging Face's code)
""" Fine-tuning on A Classification Task with pretrained Transformer """
import itertools
import csv
import fire
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
import toke... |
"""
basic.py : Some basic classes encapsulating filter chains
* Copyright 2017-2020 Valkka Security Ltd. and <NAME>
*
* Authors: <NAME> <<EMAIL>>
*
* This file is part of the Valkka library.
*
* Valkka is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Publi... |
import re
import time
import requests
from telethon import events
from userbot import CMD_HELP
from userbot.utils import register
import asyncio
import random
EMOJIS = [
"😂",
"😂",
"👌",
"💞",
"👍",
"👌",
"💯",
"🎶",
"👀",
"😂",
"👓",
"👏",
"👐",
"🍕",
"💥... |
# -*- coding: utf-8 -*-
""""
Bandidos estocásticos: introducción, algoritmos y experimentos
TFG Informática
Sección 8.4.4
Figuras 26, 27 y 28
Autor: <NAME>
"""
import math
import random
import scipy.stats as stats
import matplotlib.pyplot as plt
import numpy as np
def computemTeor(n,Delta):
if Del... |
import copy
import datetime
import os
import random
import traceback
import numpy as np
import torch
from torch.utils.data import DataLoader
from torchvision.utils import save_image
from inference.inference_utils import get_trange, get_tqdm
def init_random_seed(value=0):
random.seed(value)
np.random.seed(va... |
# Copyright 2019 <NAME>
#
# 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... |
"""This module contains the code related to the DAG and the scheduler."""
from pathlib import Path
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
from mpl_toolkits.axes_grid1 import make_axes_locatable
from networkx.drawing import nx_pydot... |
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import statsmodels.api as sm
import datetime as dt
from statsmodels.stats.multitest import fdrcorrection
from pylab import savefig
# FUNCTIONS YOU CAN USE:
# analyses(filepath) spits out a nifty heatmap to let you check ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
2D linear elasticity example
Solve the equilibrium equation -\nabla \cdot \sigma(x) = f(x) for x\in\Omega
with the strain-displacement equation:
\epsilon = 1/2(\nabla u + \nabla u^T)
and the constitutive law:
\sigma = 2*\mu*\epsilon + \lambda*(\nabla\cdot u)I,... |
import datetime
import os
import sys
from cmath import inf
from typing import Any
import hypothesis.extra.numpy as xps
import hypothesis.strategies as st
import numpy
import pytest
from hypothesis import assume, given
from eopf.product.utils import (
apply_xpath,
conv,
convert_to_unix_time,
is_date,
... |
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: MIT
from __future__ import absolute_import, print_function, unicode_literals
import os
import shutil
try:
from unittest.mock import MagicMock
except ImportError:
from mock import MagicMock
import uuid
from ddt import ddt as DataDrivenTestCase, data as ddt_da... |
# Stat_Canada.py (flowsa)
# !/usr/bin/env python3
# coding=utf-8
'''
Pulls Statistics Canada data on water intake and discharge for 3 digit NAICS from 2005 - 2015
'''
import pandas as pd
import io
import zipfile
import pycountry
from flowsa.common import *
def sc_call(url, sc_response, args):
"""
Convert res... |
"""
Test functions for regular module.
"""
import pytest
import numpy as np
from sklearn.linear_model import LinearRegression, LogisticRegression
from sklearn.base import clone
import tensorflow as tf
from tensorflow.keras import Sequential, Model
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimiz... |
#!/usr/bin/env python
#
# soaplib - Copyright (C) Soaplib contributors.
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any late... |
##############################################################################
# Copyright (c) 2016 <NAME> and others.
#
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Apache License, Version 2.0
# which accompanies this distribution, and is available at
#... |
from flask import Flask, request, jsonify, abort, render_template, redirect, session, url_for
import MySQLdb.cursors
import hashlib
import html
import json
import math
import os
import pathlib
import random
import re
import string
import urllib
import sys
from werkzeug.contrib.profiler import ProfilerMiddleware, MergeS... |
import os.path
import scipy.io as sio
import numpy as np # for algebraic operations, matrices
import keras.models
from keras.models import Sequential
from keras.layers.core import Dense, Activation, Flatten, Dropout # , Layer, Flatten
# from keras.layers import containers
from keras.models import model_from_json,Mode... |
# -*- coding: utf-8 -*-
from flask import flash, make_response, request
import json
from flask_babel import lazy_gettext, gettext
from datetime import datetime
from flask_login import current_user
from flask_appbuilder.actions import action
from flask_appbuilder import expose
from flask import redirect
from plugins.com... |
#!/usr/bin/env python3
import sys,re,os,re, datetime
import requests
import json
import hashlib
import getopt
from pprint import pprint
from pathlib import Path
################################################################################
## Hashing large files
####################################################... |
bl_info = {
"name": "Import Planar Code",
"author": "<NAME>",
"version": (1, 0),
"blender": (2, 80, 0),
"location": "File > Import > Planar Code",
"description": "Import planar code and construct mesh by assigning vertex positions.",
"warning": "",
"support": "TESTING",
"wik... |
import argparse
import collections
import os
import cv2
import numpy as np
import pandas as pd
import pretrainedmodels
import torch
import torch.optim as optim
import torchsummary
from torch.optim import lr_scheduler
from torch.utils.data import DataLoader
from torchvision import datasets, models, transforms
from tqdm... |
import functools
import numpy as np
def dft2(f, alpha, npix=None, shift=(0, 0), offset=(0, 0), unitary=True, out=None):
"""Compute the 2-dimensional discrete Fourier Transform.
This function allows independent control over input shape, output shape,
and output sampling by implementing the matrix triple p... |
from multiprocessing.dummy import Value
from agents.Base_Agent import Base_Agent
import copy
import numpy as np
import torch
import torch.nn.functional as F
from torch.optim import Adam
class RunningMeanStd(object):
# https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
def _... |
from __future__ import absolute_import
from __future__ import print_function
import unittest
from aiida.manage.fixtures import PluginTestCase
import subprocess, os
def backend_obj_users():
"""Test if aiida accesses users through backend object."""
backend_obj_flag = False
try:
from aiida.backends... |
import pandas as pd
import yaml
import gzip
import re
import urllib
import shutil # for removing and creating folders
from pathlib import Path
from tqdm.autonotebook import tqdm
import warnings
from Bio import SeqIO
from Bio.Seq import Seq
from .cloud_caching import CLOUD_CACHE, download_from_cloud_cache
CACHE_PATH... |
#!/usr/bin/env python
from __future__ import print_function
import sys
sys.path.insert(0, "/home/liangjiang/code/keras-jl-mean/")
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.models import model_from_json
from keras.models import Sequential
from keras.layers imp... |
from builtins import str
import collections
import contextlib
import functools
import itertools
import io
import os
import re
import six
import subprocess
import threading
import tempfile
import time
import traceback
import termcolor
from . import command
from . import parser
COLORS = ['yellow', 'blue', 'red', 'gre... |
"""
Model construction utilities based on keras
"""
import warnings
from distutils.version import LooseVersion
import tensorflow.keras
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Activation, Flatten
# from cleverhans.model import Model, NoSuchLayerError
import tensorflow a... |
"""
paw_structure.ion
-----------------
Ion complex detection using geometric :ref:`algorithm<Control_ION_algorithm>`.
Main routine is :func:`.ion_find_parallel`.
Dependencies:
:py:mod:`functools`
:py:mod:`miniutils`
:py:mod:`numpy`
:py:mod:`pandas`
:mod:`.neighbor`
:mod:`.utility`
:class:... |
import re
import _pickle as cPickle
import logging
import argparse
#This script is not dependant on table of contents. It detects books and chapters based their titles
# Dictionary containing key and regex pattern to match the keys
pattern_dict = {
'blank_line': re.compile(r'^\s*$'),
'book_number': re.compile... |
from numpy.random import seed
seed(5393)
from tensorflow import set_random_seed
set_random_seed(12011)
import os
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.preprocessing import LabelEncoder, LabelBinarizer
from sklearn.pipeline import FeatureUnion
from sklearn.feature_extraction.te... |
import math
from itertools import product
from typing import Tuple, List, Optional, Union
import numpy as np
import torch
import torch.nn as nn
import torch.nn.init as init
class EMA:
"""
Class that keeps track of exponential moving average of model parameters of a particular model.
Also see https://gith... |
# -*- coding: utf-8 -*-
import matplotlib.colors as colorplt
import matplotlib.pyplot as plt
import numpy as np
from sktime.distances._distance import distance_alignment_path, pairwise_distance
gray_cmap = colorplt.LinearSegmentedColormap.from_list("", ["#c9cacb", "white"])
def _path_mask(cost_matrix, path, ax, the... |
"""Finds out all the people you need to follow to follow all the same people as another user. Then, optionally, follows them for you."""
import configparser
import csv
import errno
import os
import tweepy
from tqdm import tqdm
#Useful Constants
PATH_TO_TARGET_CSV = "./output/targetfriends.csv"
PATH_TO_USER... |
import inspect
from IPython.core.interactiveshell import InteractiveShell
from IPython.core.magic import cell_magic, magics_class, Magics
from IPython.core.magic_arguments import (argument, magic_arguments,
parse_argstring)
import warnings
from htools.meta import timebox
@ma... |
# p2wsh input (2-of-2 multisig)
# p2wpkh output
import argparse
import hashlib
import ecdsa
def dSHA256(data):
hash_1 = hashlib.sha256(data).digest()
hash_2 = hashlib.sha256(hash_1).digest()
return hash_2
def hash160(s):
'''sha256 followed by ripemd160'''
return hashlib.new('ripemd160', hashlib.s... |
#!/usr/bin/env python
"""Module for global fitting titrations (pH and cl) on 2 datasets
"""
import os
import sys
import argparse
import numpy as np
from lmfit import Parameters, Minimizer, minimize, conf_interval, report_fit
import pandas as pd
import matplotlib.pyplot as plt
# from scipy import optimize
def ci_repo... |
# Recipe creation tool - create command build system handlers
#
# Copyright (C) 2014 Intel Corporation
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation.
#
# This program is distributed... |
import pytest
import numpy as np
import pandas as pd
from SPARTACUS10 import spatial_silhouette as spasi
import sklearn.metrics as metrics
import os
def find_path(name, path = None):
if path is None:
path = os.getcwd()
for root, dirs, files in os.walk(path):
if name in files:
... |
# iPhone Manager bot by Oldmole
# No support will be provided, this code is provided "as is" without warranty of any kind, either express or implied. Use at your own risk.
# The use of the software and scripts is done at your own discretion and risk and with agreement that you will be solely responsible for any damage
... |
from __future__ import absolute_import
from __future__ import print_function
from __future__ import unicode_literals
import os
import textwrap
import time
import bs4
from django.core.urlresolvers import get_resolver
from django.http import HttpResponse
from django.http import HttpResponseBadRequest
from django.http i... |
# Copyright 2017-2020 TensorHub, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writ... |
r"""Provides functions used by strategies that use a tree to select the
permutation.
To compute optimal permutations, we use the belief states
.. math::
b(y^{k-1}) := \mathbb{P}(s_0, s_k|y^{k-1}),
where the :math:`s_k` are the states of the HMM at step :math:`k`, and the
superscript :math:`y^{k-1}` is the sequen... |
# Get arxiv data
import json
import logging
import os
import pickle
from collections import Counter
from datetime import datetime
from io import BytesIO
from zipfile import ZipFile
import numpy as np
import pandas as pd
import requests
from kaggle.api.kaggle_api_extended import KaggleApi
from eurito_indicators impor... |
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional
from talon import Context, Module, actions, app, cron, ui
# XXX(nriley) actions are being returned out of order; that's a problem if we want to pop up a menu
mod = Module()
mod.list("notification_actions", desc="Notific... |
import discord
import random
from asd import *
from mtgsdk import Card
from mtgsdk import Set
from mtgsdk import Type
from mtgsdk import Supertype
from mtgsdk import Subtype
from mtgsdk import Changelog
client=discord.Client()
@client.event
async def on_ready():
print('logged in as')
print... |
# -*- coding: utf-8 -*-
#
# <NAME> 2021 gpSTS
###########################################
###Configuration File######################
###for gpSTS steering of experiments######
###########################################
import os
import numpy as np
from gpsts.NanonisInterface.nanonis_interface import Nanonis
from gps... |
from mach_utils import *
import logging
from argparse import ArgumentParser
from fc_network import FCNetwork
import tqdm
from dataset import XCDataset,XCDataset_massive
import json
from typing import Dict, List
from trim_labels import get_discard_set
from xclib.evaluation import xc_metrics
from xclib.data import data_u... |
import crypt
import io
import json
import logging
import re
import requests
import uuid
import yaml
from flask import current_app as app
from base64 import b64encode
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.backends imp... |
#!/usr/bin/env python
# hsslms.py
#
# This provides a command line interface for the pyhsslms.py
# implementation of HSS/LMS Hash-based Signatures as defined
# in RFC 8554.
#
#
# Copyright (c) 2020-2021, Vigil Security, LLC
# All rights reserved.
#
# Redistribution and use, with or without modification, are permitted
... |
#!/usr/bin/python
import os, glob, hashlib, pickle, argparse, shutil, ntpath
import os, glob, hashlib, pickle, argparse, shutil, multiprocessing, signal, sys
from multiprocessing import Pool
from functools import partial
######################### Classes ##############################
class AndroidDensity:
def __i... |
from typing import *
from dataclasses import asdict
from transformers import BertModel
from torch.nn.utils.rnn import pad_sequence
from stud.models.ner_classifier import NERClassifier
from stud.models.polarity_classifier import PolarityClassifier
from stud.constants import LOGGER_TRAIN_LOSS, LOGGER_VALID_LOSS, LOGGER_T... |
##################################################
#
# Tests for model.py
#
#
#
#
#
#
#
#
#
#
#
##################################################
from boole.core.model import *
from boole.core.language import clear_default_language
from nose.tools import *
def is_prime(x):
if x == 0 or x == 1:
return Fa... |
"""
Low level miscilanious calls
"""
import UserDict
import types
import random
import datetime
import pprint
import re
import unicodedata
import logging
log = logging.getLogger(__name__)
now_override = None
def now():
"""
A passthough to get now()
We can override this so that automated tests can fake ... |
import os
import zipfile
from typing import List, Tuple, Dict
import numpy as np
import pandas as pd
import requests
import structlog
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForestClassifier
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import train... |
import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import numpy as np
import torch.nn.functional as F
from attention import AdditiveAttention
class Encoder(nn.Module):
"""Encoder bi-GRU"""
def __init__(self, input_dim, char_embed_dim,
e... |
import datetime
import os
import time
from enum import Enum
import sys
from MediaPlayer.Player import vlc
from MediaPlayer.Player.vlc import libvlc_get_version, Media, MediaList
from Shared.Events import EventManager, EventType
from Shared.Logger import Logger, LogVerbosity
from Shared.Observable import Observable
fr... |
import os
import aiohttp
import asyncio
import json
import time
import datetime
import logging
import gidgethub
import requests
from gidgethub import aiohttp as gh_aiohttp
import sys
import pandas as pd
sys.path.append("..")
from utils.auth import get_jwt, get_installation, get_installation_access_token
from utils.test... |
import numpy as np
import tensorflow as tf
def deconv_layer(output_shape, filter_shape, activation, strides, name):
scale = 1.0 / np.prod(filter_shape[:3])
seed = int(np.random.randint(0, 1000)) # 123
with tf.name_scope('conv_mnist/conv'):
W = tf.Variable(tf.random_uniform(filter_shape,
... |
"""
Copyright (C) 2022 <NAME>
Released under MIT License. See the file LICENSE for details.
This module describes 2D/3D tracks. GUTS's output is a list of instances
of these classes.
"""
import numpy as np
from filter import filter2D, filter3D
from options import Options, Filter2DParams, Filter3DPa... |
import argparse
import os
import torch
import matplotlib.pyplot as plt
from torch.utils.data.distributed import DistributedSampler
from torch import distributed as dist
from torch import optim
from tqdm import tqdm
from torch_ema import ExponentialMovingAverage
from cifr.core.config import Config
from cifr.models.bui... |
import numpy as np
import matplotlib.pyplot as plt
from docx import Document
from docx.shared import Cm
import math
def split_file(file):
"""split the file by different queries into seperate list element and return one list as a whole. """
answer = [[]]
j = 0
for i in file:
if i == "\n":
... |
'''
Collect results in Quantum ESPRESSO
'''
import sys
import numpy as np
from pymatgen.core import Structure
from . import structure as qe_structure
from ... import utility
from ...IO import pkl_data
from ...IO import read_input as rin
def collect_qe(current_id, work_path):
# ---------- check optimization in ... |
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 10 13:52:52 2022
@author: sarangbhagwat
"""
from biorefineries.TAL.system_TAL_adsorption_glucose import *
from matplotlib import pyplot as plt
import numpy as np
column = AC401
#%% Across regeneration fluid velocity and cycle time
def MPSP_at_adsorption_design(v, t):
... |
from m5stack import *
from m5stack_ui import *
from uiflow import *
from ble import ble_uart
import face
screen = M5Screen()
screen.clean_screen()
screen.set_screen_bg_color(0x000000)
mb_click = None
rb_click = None
lb_click = None
snd_val = None
st_mode = None
stval = None
prval = None
faces_encode = face.get(face... |
import scipy.sparse as ssp
import scipy.sparse.csgraph as csgraph
import networkx as nx
import pylab as pl
import pygraphviz as pgv
from itertools import product, chain
class DiGraph(ssp.lil_matrix):
"""
An implementation of a directed graph with a Sparse Matrix representation using Scipy's sparse module.
... |
##
## Software PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation
## Copyright Inria and UPC
## Year 2021
## Contact : <EMAIL>
##
## The software PI-Net is provided under MIT License.
##
#used in train for skeleton input
import os
import os.path as osp
import numpy as np
import math
from ut... |
from __future__ import absolute_import
from sklearn.exceptions import NotFittedError
from sklearn.neighbors import KernelDensity
from sklearn.linear_model import LinearRegression, LogisticRegression
import pickle
import os
import matplotlib.pylab as plt
from sklearn.externals import joblib
import numpy as np
from sklea... |
#!/usr/bin/env python
"""Generates a poller file that will be used as input to runsinglehap.py, hapsequencer.py, runmultihap.py or
hapmultisequencer.py based on the files or rootnames listed user-specified list file.
USAGE
>>> python drizzlepac/haputils/make_poller_files.py <input filename> -[ost]
- input fil... |
import os, pickle
import os.path as osp
import numpy as np
import cv2
import scipy.ndimage as nd
import init_path
from lib.dataset.get_dataset import get_dataset
from lib.network.sgan import SGAN
import torch
from torch.utils.data import DataLoader
import argparse
from ipdb import set_trace
import matplotlib.pyplot as... |
# -*- coding: UTF-8 -*-
import time
import simplejson as json
from MySQLdb.connections import numeric_part
from django.contrib.auth.decorators import permission_required
from django.http import HttpResponse
from common.utils.extend_json_encoder import ExtendJSONEncoder
from common.utils.const import SQLTuning
from s... |
import logging
from bottle import Bottle, request, response, abort, static_file
import os
import time
import threading
from threading import Thread
from pathlib import Path
import json
import subprocess
import io
import sys
import signal
from internal.notifier import getNotifier, NotificationLevel
from internal.interpr... |
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt
from __future__ import unicode_literals
import frappe
from frappe.utils import flt, cstr, cint
from frappe import _
from frappe.model.meta import get_field_precision
from erpnext.accounts.util... |
"""
Complex Valued Neural Layers From Scratch
Programmed by <NAME>
* MIT Licence
* 2022-02-15 Last Update
"""
from torch import nn
import torch
##__________________________________Complex Linear Layer __________________________________________
class CLinear(nn.Module):
def __init__(self, in_channels, ... |
import pytest
import json
import os
import logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
from glacierbackup.command import _construct_argparse_parser
from glacierbackup.jobs import BackupJob
from glacierbackup.database import GBDatabase, GBDatabaseError... |
import numpy as np
import torch
import argparse
from pina.pinn import PINN
from pina.ppinn import ParametricPINN as pPINN
from pina.label_tensor import LabelTensor
from torch.nn import ReLU, Tanh, Softplus
from pina.adaptive_functions.adaptive_softplus import AdaptiveSoftplus
from problems.parametric_elliptic_optimal_c... |
import pandas as pd
import dash
from dash.dependencies import Input, Output, State
import plotly.express as px
import dash_html_components as html
import dash_core_components as dcc
import dash_bootstrap_components as dbc
# self packages
from .data_generator import load_transactions, comparisons_df
from .nav_bar impor... |
# Copyright (c) 2020, <NAME>, Honda Research Institute Europe GmbH, and
# Technical University of Darmstadt.
# 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. Redistributions of source code mus... |
#!/usr/bin/env python
###########################################################################
# Active Inference algorithm
#
# Execute the AI algorithm using the data from the
# /filter/y_coloured_noise topic and publish the results to the
# /filter/ai/output topic.
# Note that only the filtering part of the AI ... |
from utils import load, save, path_list, DEAD_PMTS
import nets
import torch
import numpy as np
import pandas as pd
from scipy import interpolate
import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter
from itertools import repeat
from multiprocessing import Pool
def neural_residual(root_dir):... |
# Copyright 2018 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
"""Partial response utilities for an Endpoints v1 over webapp2 service.
Grammar of a fields partial response string:
fields: selector [,select... |
##############################
## MFP_K1000.py ##
## <NAME> ##
## Version 2020.03.25 ##
##############################
import os
import os.path as osp
import time
import subprocess as spc
import numpy as np
import scipy as sp
import astropy.io.fits as fits
import h... |
import discord
import json
import math
from discord.ext import commands
from common_functions import default_embed_template, use_exp_mat
MYSTIC = 10000
FINE = 2000
NORMAL = 400
ASCENSION_MILESTONES = [90, 80, 70, 60, 50, 40, 20]
class WeaponExpCalculator(commands.Cog):
def __init__(self, client):
self._client = c... |
import collections
import datetime
import logging
import os
import sys
from pathlib import Path
import numpy as np
import pdfkit as pdfkit
from bs4 import BeautifulSoup
from sklearn.metrics import mean_absolute_error, mean_squared_error, confusion_matrix, classification_report, \
accuracy_score
from tldextract imp... |
#!/usr/bin/python
#The MIT License (MIT)
#
#Copyright (c) 2017 <NAME>
#
#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... |
# -*- coding: utf-8 -*-
"""
Functionality for binding wx control label shortcut keys to events
automatically. In wx, a button with a label "E&xit" would be displayed as
having the label "Exit" with "x" underlined, indicating a keyboard shortcut,
but wx does not bind these shortcuts automatically, requiring constru... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 12 10:58:27 2020
Experiments where one marginal is fixed
"""
import os
import numpy as np
from joblib import Parallel, delayed
import torch
import ot
from unbalancedgw.batch_stable_ugw_solver import log_batch_ugw_sinkhorn
from unbalancedgw._batch_... |
"""
PatientFinders are used to find OpenMRS patients that correspond to
CommCare cases if none of the patient identifiers listed in
OpenmrsCaseConfig.match_on_ids have successfully matched a patient.
See `README.md`__ for more context.
"""
import logging
from collections import namedtuple
from functools import partial... |
import os
import datetime
import math
import traceback
from typing import List
import requests
from loguru import logger
from lxml import etree
from siphon.catalog import TDSCatalog
from dask.utils import memory_repr
import numpy as np
from dateutil import parser
from ooi_harvester.settings import harvest_settings
... |
import asyncio
import math
import networkx as nx
import ccxt.async_support as ccxt
import datetime
import logging
from .logging_utils import FormatForLogAdapter
__all__ = [
'FeesNotAvailable',
'create_exchange_graph',
'load_exchange_graph',
]
adapter = FormatForLogAdapter(logging.getLogger('peregrinearb.u... |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... |
from __future__ import unicode_literals
import logging
import re
from django.contrib import messages
from django.db import ProgrammingError
from django.http import HttpResponse, HttpResponseForbidden, HttpResponseRedirect
from django.shortcuts import redirect
from django.utils.translation import ugettext_lazy as _
fr... |
import torch.nn as nn
import numpy as np
from collections import OrderedDict
from torchmeta.modules import (MetaModule, MetaConv2d, MetaBatchNorm2d,
MetaSequential, MetaLinear)
import torch
def conv_block(in_channels, out_channels, **kwargs):
return MetaSequential(OrderedDict([
... |
from __future__ import division
from collections import defaultdict
import itertools
import sys
import os
import sqlite3
import click
from kSpider2.click_context import cli
import glob
class kClusters:
source = []
target = []
source2 = []
target2 = []
seq_to_kmers = dict()
names_map = dict()
... |
# 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... |
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