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"""Profiles"""
import os
import random
import sqlite3
from datetime import datetime
import scrapy
from scrapy.http import Request
from scrapy.selector import Selector
from scrapy_jsonschema.item import JsonSchemaItem
from ..items import ParliamentPipeline
parties_dictionary = {
"ПП ГЕРБ": "GERP",
"БСП за БЪ... |
# stdlib imports
import warnings
import os.path
import sys
from collections import OrderedDict
# third party imports
import netCDF4 as netcdf
import rasterio
import numpy as np
from rasterio.profiles import DefaultGTiffProfile
# local imports
from mapio.geodict import affine_from_geodict
def get_nodata(grid):
i... |
from dataclasses import dataclass
from typing import List, Tuple, Callable
import torch
from cached_property import cached_property
from graph_pit.graph import Graph
from graph_pit.loss.base import GraphPITBase, LossModule
__all__ = [
'GraphPITLoss',
'GraphPITLossModule',
'graph_pit_loss',
]
def solve_... |
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import KFold
from sklearn.svm import LinearSVC
import numpy as n... |
#!/usr/bin/env python
"""
Convert all recipes into feedstocks.
This script is to be run in a TravisCI context, with all secret environment variables defined (BINSTAR_TOKEN, GH_TOKEN)
Such as:
export GH_TOKEN=$(cat ~/.conda-smithy/github.token)
"""
from __future__ import print_function
from conda_smithy.github i... |
#!/usr/bin/python
#
# Copyright (c) 2019 <NAME>, (@zikalino)
#
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
... |
#coding=utf-8
from .dt import *
from .Match import *
import sys
version = sys.version < '3'
tdt = Datatype()
tcs = Constructor()
tdt.List('a') == tcs.Nil() \
| tcs.Cons('hd','tl')
List = tdt.List
Nil = tcs.Nil
nil = Nil()
Cons = tcs.Cons
@matcher(Nil,False)
def null(self):
return True
@ma... |
import hashlib
import hmac
import random
from datetime import datetime
from functools import wraps
from flask import request
from googleapiclient.errors import HttpError
from server import config
from server.log import log
from server.services import calendar_service, slack_service
_POTENTIAL_REASONS_ = [
"Would... |
#Import Tkinter
from tkinter import *
import tkinter as tk
from tkinter import filedialog
from PIL import ImageTk,Image
import subprocess,io
#------------------------
from imageai.Detection import ObjectDetection #Import ImageAi
import os #Import Os
root = tk.Tk()
root.title('ImageAi ile Nesne Algılama') #Pencere Başl... |
"""Module for Pokemon Helpers calculations."""
from math import floor
from random import uniform
from random import random
from config import POKEMON_DATA
from config import WEAKNESS_CHART
from config import (BRN_STATUS, PSN_STATUS, TOX_STATUS)
def calculate_stat(base_val, ev_val, level):
"""
Calculate the ... |
"""
Copyright 2014 Rackspace
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
dist... |
##############################################################################
#
# Copyright (c) 2002 Zope Foundation and Contributors.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS I... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 27 15:31:29 2017
@author: robert
"""
import unittest
import warnings
import sys
#ways to execute this test_file
#python -m mono.tests.test_file.py ( __name__ ='__main__' and package ='mono.tests')
#python tests/test_file.py ( __name__ ='__main__' ... |
#! /usr/bin/python
from __future__ import print_function
import os
import sys
import random
import string
import subprocess
from collections import defaultdict
from _lib.bootstrapping import from_project_root, from_env_bin
from _lib.params import APP_NAME
from _lib.frontend import frontend, ember
from _lib.db import ... |
import numpy as np
from random import randint, random
def objective_function(vector):
s = sum([i**2 for i in vector])
return abs(s)
def random_vector(minmax):
rand_vector = [minmax[i][0] + ((minmax[i][1]-minmax[i][0]) * random()) for i in range(len(minmax))]
return rand_vector
def create_particle(search_... |
import os
import pytest
import re
import sys
import tempfile
# We're not using python packages, so we have to solve the path problem the old way.
sys.path.append(os.path.normpath(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..')))
import rfcs
@pytest.fixture
def scratch_space():
x = tempfile.Temporar... |
import pexpect
from threading import Thread
mpg_outs = [
{
"mpg_code": "@P 0",
"action": "user_stop",
"description": "Music has been stopped by the user."
},
{
"mpg_code": "@P 1",
"action": "user_pause",
"description": "Music has been paused by the user."
... |
#DustSim IRL :)
#Allows us to play around and model real dust particles using le Gauss
#Also enables some smart mode switching between peak-detect and bgdetect.
#@Alto et al.
#Imports - verify if they are on Your machine :)
import serial
import turtle
import math
import random
import time
import statistics
#Globals
s... |
import heterocl as hcl
import hlib
import numpy as np
hcl.init()
def softmax(out, x):
assert len(x.shape) == 2, "only support 2-dim softmax"
m, n = x.shape
k = hcl.reduce_axis(0, n)
max_elem = hcl.compute((m,), lambda i: hcl.max(x[i, k], axis=k))
k = hcl.reduce_axis(0, n)
expsum = hcl.compute(... |
import copy
import tarfile
import os
import os.path
import itertools
import math
import numpy as np
import scipy.signal as signal
from pysit.util.image_processing import blur_image
from pysit.gallery.gallery_base import GeneratedGalleryModel
from pysit import * #PML, Domain
__all__ = ['LinearIncreasedMediumModel',... |
import logging
import subprocess
import os
import sys
import pysam
from distutils.version import LooseVersion
# Check java version to make sure it is Java 8
MY_DIR = os.path.dirname(os.path.realpath(__file__))
VARSIMJAR = os.path.realpath(os.path.join(MY_DIR, "VarSim.jar"))
RTGJAR = os.path.realpath(os.path.join(MY_DIR... |
# -*- coding: utf-8 -*-
import bs4, pyexcel_xls, random, re, requests, time
from tqdm import tqdm
from collections import OrderedDict
data_save = OrderedDict()
actor_name = []
actor_id = []
actor_movie_count = []
headers = { # 请求头
'Host': 'movie.douban.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64... |
# Copyright 2011 the original author or authors.
#
# 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 a... |
#!/usr/bin/env python3
# coding: utf-8
# Copyright 2016 <NAME>, https://github.com/tywtyw2002, and https://github.com/treedust
#
# 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:/... |
#!/usr/bin/env python
from typing import List
from pypozyx import (Coordinates, DeviceCoordinates, SingleRegister, DeviceList, PozyxConstants,
get_first_pozyx_serial_port, PozyxSerial)
from flux_sensors.models import models
NUMBER_OF_CALIBRATION_CYCLES = 10
class LocalizerError(Exception):
"... |
# Copyright (c) 2015 OpenStack Foundation
# 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 ... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# By <NAME> (Naereen)
# https://github.com/Naereen/gym-nes-mario-bros
# MIT License https://lbesson.mit-license.org/
#
from __future__ import division, print_function # Python 2 compatibility
from collections import deque
import numpy as np
import matplotlib.pyplot as plt... |
import os
import sys
import json
import collections
from nltk.translate.bleu_score import corpus_bleu, SmoothingFunction
import numpy as np
from transformers import BertTokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
def load_txt(path):
with open(path, encoding='UTF-8', errors='ignore')... |
#!/usr/bin/env python3
__description__ = \
"""
Take a fasta file with an alignment, grab the secondary structure and solvent
accessibility for each site, then create a stockholm file encoding secondary
structure call and accessiblity for input to phyml-ss.
"""
__author__ = "<NAME>"
__date__ = "121101"
__usage__ = "prep... |
import os
import datetime
import tempfile
import logging
import json
import argparse
from functools import partial
import numpy as np
import ray
from ray.rllib.agents.registry import get_agent_class
from ray.tune.registry import register_env
from ray.rllib.agents import dqn as ray_dqn
from ray.tune.logger import pret... |
from torch import nn
from efficientnet_pytorch import EfficientNet
from torchvision import models
import pretrainedmodels
import torch
import torch.nn.functional as F
# sorted(
# name for name in models.__dict__
# if name.islower() and not name.startswith("__") and callable(models.__dict__[name])
# )
# ['alexn... |
'''
Coded by Z1 :)
More features are underway! Email questions/concerns/feature requests
at <EMAIL> or via twitter: @z1rk4
'''
from tweepy.streaming import StreamListener
from tweepy import OAuthHandler
from tweepy import Stream
from tweepy import API
from tweepy import Cursor
import tweepy
import time
import datet... |
# Copyright (c) 2015 Rackspace, 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 wr... |
#!/usr/bin/env python3
#
# Copyright (c) 2018-2022 The Bitcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
#
# Check for duplicate includes.
# Guard against accidental introduction of new Boost dependencies.
# C... |
import time
import torch
import numpy as np
from hpbandster.core.worker import Worker
from hpbandster.optimizers import BOHB as BOHB
import hpbandster.core.nameserver as hpns
import hpbandster.core.result as hpres
from hpo.model import MyMetaLearner, MyLearner, MyPredictor
from hpo.helpers import *
from hpo.utils im... |
import faiss
import numpy as np
from sklearn import preprocessing
from utils import load_image, get_image_paths
class Analyst:
def __init__(self, V_dict):
self.classes = list(V_dict)
self.V_dict = V_dict
self._V_dict = V_dict # save a copy that won't be
@property
def V_norm_dic... |
# Copyright 2017 Google 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 writing,... |
from django.views.generic import DetailView, ListView, UpdateView, CreateView
from .models import Category, ProductType, Product, ProductVariant, Attribute, AttributeValue, ProductImage, VariantImage,Stock,StockTransaction
from .forms import CategoryForm, ProductTypeForm, ProductForm, ProductVariantForm, AttributeForm,... |
'''
Take your oracle function from #12. Now generate a random count of random bytes and prepend this string to every plaintext. You are now doing:
AES-128-ECB(random-prefix || attacker-controlled || target-bytes, random-key)
Same goal: decrypt the target-bytes.
'''
import random
from AES_ECB import EncryptAESECB,Decr... |
from pytorch3d.transforms import rotation_6d_to_matrix, quaternion_to_matrix
import torch.nn.functional as F
from src.geometry.vector import cross_product, normalize_vector
import torch
import numpy as np
# m: batch*3*3
# out: batch*4*4
def get_4x4_rotation_matrix_from_3x3_rotation_matrix(m):
batch_size = m.shape[... |
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distri... |
import torch
import random
import torchvision
import os
import my_custom_transforms as mtr
from dataloader_rgbdsod import RgbdSodDataset
from torch.utils.data import DataLoader
########################################[ Optimizer ]########################################
def get_optimizer(mode, train_params, lr, kwarg... |
# -*- coding: utf-8 -*-
"""
Created on Fri Feb 22 09:13:58 2019
@author: rocco
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
files = [i for i in os.listdir("../data/mipas_pd")]
files = files[19:24]
classifier_type = "labels_svm_pc_rf_2"
def plot_bar(files, classifier... |
"""
Adapter for ODIN control FileInterface.
This class implements a simple adapter used for retrieving config file(s)
<NAME>, STFC Detector Systems Software Group
<NAME>, STFC Detector Systems Software Group
"""
import logging
import tornado
import time
from concurrent import futures
import os
from tornado.escape i... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import json
import logging
import psutil
import subprocess
import os
import yaml
from threading import Thread
import srvdb
import requests as orig_requests
import time
from flask import Flask
from flask import request
from two1.commands.config import Config
from two1.wa... |
# -*- coding: utf-8 -*-
#
# Copyright (C) 2019-2020 CERN.
# Copyright (C) 2019-2020 Northwestern University.
#
# Invenio App RDM is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
"""Blueprint used for loading templates.
The sole purpose... |
import os
import sys
import glob
import psycopg2
import pandas as pd
from sql_queries import *
def process_song_file(cur, filepath):
"""Extracts songs and artists from the JSON data source
and inserts them into the database.
Args:
cur: The PostgreSQL cursor object.
filepath (str): Th... |
from rest_framework import serializers
from rest_auth.models import TokenModel
from django.contrib.auth.models import User
from rest_framework_gis.serializers import GeoFeatureModelSerializer
from api.fields import Base64ImageField
from .models import MetadataObservation, Help, Phenomenon, Parameter, Dictionary, Pheno... |
# coding:utf-8
import re
import six
import codecs
import pickle
import functools
import heapq as hq
from pathlib import Path
from collections import defaultdict
# should be directory contains the files ending with '.txt'
data_dir = '10_July/'
# save path for compressed file, need to determine further
save_path = '10_... |
#!/usr/bin/env python
"""
Based on storcli.py example from node_exporter, with substantial changes.
https://github.com/prometheus/node_exporter/blob/master/text_collector_examples/storcli.py
megaraid_controllers{controller,model}=1
megaraid_controller_memory_errors{controller,correctable=y|n}=counter
megaraid_contro... |
#!/usr/bin/env python3
import argparse
from operator import add, sub, mul
import sys
import time
import cv2
import numpy as np
BLACK = (0, 0, 0)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
YELLOW = (255, 255, 0)
BLUE = (0, 0, 255)
MAGENTA = (255, 0, 255)
CYAN = (0, 255, 255)
WHITE = (255, 255, 255)
def brighten(rgb, valu... |
# HACK: if the profile plugin is imported before the coverage plugin then all
# the top-level code in pytest_profiling will be omitted from
# coverage, so force it to be reloaded within this test unit under coverage
from six.moves import reload_module # @UnresolvedImport
import pytest_profiling
reload_module(pytest_... |
"""
Schlagzeilengenerator
~~~~~~~~~~~~~~~~~~~~~
A small web application to generate tabloid press headlines.
:copyright: (c) 2012-2016 by <NAME>, <NAME>.
:license: BSD 3-clause, see LICENSE for more details.
"""
import os
import sys
import random
import json
from urllib.parse import quote_plus
fr... |
"""
pgsql_holidays
Script for building the holidays schema in a configured PostgreSQL database
from source SQL files
"""
# Standard Imports
import json
import os
import re
# PyPi Imports
import psycopg2
import psycopg2.extras
# Local Imports
## None
##################################################################... |
###############################################################################
#
# Copyright (C) 2021 - Skinok
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License,... |
# encoding=utf8
import numpy as np
import networkx as nx
import scipy.sparse
import scipy.sparse as sp
from scipy import linalg
from scipy.special import iv
from sklearn import preprocessing
from sklearn.utils.extmath import randomized_svd
import argparse
import time
class ProNE():
def __init__(self, graph_file, ... |
"""Yandex Authentication Views
You may see developer docs at http://api.yandex.com/oauth/
"""
import uuid
from pyramid.httpexceptions import HTTPFound
from pyramid.security import NO_PERMISSION_REQUIRED
import requests
from ..api import (
AuthenticationComplete,
AuthenticationDenied,
register_provider,
... |
from sklearn.metrics import r2_score as r2
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error as mse
import pandas as pd
import numpy as np
import constant
import joblib
import model_pipeline
import plotly.express as px
original = pd.read_csv(constant.PATH + 'life_expec... |
import time
import sys
from collections import defaultdict
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
from pycocotools import mask as COCOmask
import json
import numpy as np
# Percentage movement on (x,y,w,h).
# Each movement will generate a json file, consisting of 'dious', 'act', '... |
import hashlib
import json
import os
import threading
import time
from dbx import IsDirError
class Config(object):
def __init__(self, config_file):
self._raw = json.load(open(config_file))
def __getitem__(self, key):
return self._raw[key]
class ETagCache(object):
def __init__(self, dbx_f... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
##
## @file train_classification.py
## @brief Trainer Class for Classification CNN Training
## @author Keitetsu
## @date 2020/05/22
## @copyright Copyright (c) 2020 Keitetsu
## @par License
## This software is released under ... |
import bpy
class ShaderNodeBuilding:
"""Base utilities to construct node trees"""
node_tree = None
inputs = {}
outputs = {}
def init_tree(self, name):
self.node_tree = bpy.data.node_groups.new(name, 'ShaderNodeTree')
self.node_tree.nodes.new('NodeGroupInput')
self.node_tr... |
import unittest
from .molecule import Molecule
from .inchi import *
class InChITest(unittest.TestCase):
def test_constructor(self):
inchi1 = InChI('InChI=1S/foo')
self.assertTrue( inchi1 is not None)
with self.assertRaises(InchiException):
inchi1 = InChI('foo')
def test... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import collections
import sys
import numpy as np
import errno
import logging
import json
import _jsonnet
import torch
from pytorch_memlab import MemReporter
from cluster import Span
def initialize_f... |
import operator
from functools import reduce
from django.contrib.auth.models import User
from django.db.models import Q
from django.utils import timezone
from rest_framework import generics, permissions, filters, mixins, status
from rest_framework.generics import get_object_or_404
from rest_framework.permissions impor... |
import pdb
import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
class MLPBlock(nn.Module):
def __init__(self, out_channel, dimension, with_bn=True):
super(MLPBlock, self).__init__()
self.layer_list = []
if dimension == 1:
for idx, channels in en... |
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the ... |
# MIT License
#
# Copyright (C) IBM Corporation 2019
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
# documentation files (the "Software"), to deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge... |
# -*- coding: utf-8 -*-
__author__ = '<NAME> and <NAME>'
__copyright__ = 'Copyright 2020, The arXivDigest project'
from datetime import datetime
from flask import Flask
from flask import g
from flask import jsonify
from flask import make_response
from flask import request
import arxivdigest.api.database as db
impor... |
from collections import OrderedDict
import pandas as pd
def perf_attrib(returns, positions, factor_returns, factor_loadings):
"""
Attributes the performance of a returns stream to a set of risk factors.
Performance attribution determines how much each risk factor, e.g.,
momentum, the technology secto... |
"""This module is not considered part of the public interface. As of 2.3, anything here
may change or be removed without warning."""
import platform
import os
import requests
import six
import trafaret as t
from requests_toolbelt.multipart.encoder import MultipartEncoder
from six.moves.urllib_parse import urlparse
f... |
# [LICENSE]
# Copyright (c) 2020, Alliance for Sustainable Energy.
# 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 must retain the above
# copyright no... |
#!/usr/bin/env python
import argparse
import os
import subprocess
import sys
import textwrap
from pathlib import Path
# compat mappings
ENV_TO_ENV: dict[str, str] = {
"INPUT_CONFIG": "SEMGREP_RULES",
"BASELINE_REF": "SEMGREP_BASELINE_COMMIT",
"SEMGREP_BASELINE_REF": "SEMGREP_BASELINE_COMMIT",
"INPUT_PU... |
"""
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Real time animation of hyperbolic tilings with pyglet and glsl
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Code adapted from <NAME>'s excellent shadertoy program at
"https://www.shadertoy.com/view/3tsSzM"
Again Matt's program h... |
# coding: utf-8
from argparse import ArgumentTypeError
import mock
import pytest
from cmdtree import types
class TestParamTypeFactory:
def setup_method(self, method):
self.instance = types.ParamTypeFactory()
def test_should_call_return_argparse_kwargs(self):
assert self.instance() == {"typ... |
# SPDX-FileCopyrightText: 2020 <NAME> <<EMAIL>>
#
# SPDX-License-Identifier: Apache-2.0
from enum import Enum
from typing import List, Tuple, Optional
from codeprep.preprocess.core import ReprConfig
from codeprep.preprocess.metadata import PreprocessingMetadata, with_empty_metadata, unwrap_single_string
from codeprep... |
# grid_generation_utils
import numpy as np
def height_filter(pc_input, height_max):
# To filter out possible noise in the raw LiDAR pc input
mask = np.ones(pc_input.shape[0], dtype = bool)
mask = np.logical_and(mask, pc_input[:, 2] < height_max)
pc_filtered = pc_input[mask, :]
return pc_filtered
def get_stati... |
import random
import time
import mesh as meshtools
from random import randint
from typing import List, Tuple
from PIL import Image, ImageDraw, ImageChops, ImageStat
# Type definitions
tyPosition = Tuple[float, float]
tyColor = Tuple[int, int, int, int]
tyColors = List[tyColor]
tyVertex = dict
tyVertices = List[List[... |
try:
from configparser import ConfigParser
except ImportError:
from ConfigParser import ConfigParser # ver. < 3.0
import ipdb
from datetime import datetime
import asyncio
import datetime
from .model import main, TableRegistry
# https://stackoverflow.com/questions/8884188/how-to-read-and-write-ini-file-wit... |
from flask import render_template, url_for, flash, redirect, request, session
from surprise.forms import RegistrationForm, AddRecepientForm
from surprise.models import Creator, Recepient
from surprise import app, db
from datetime import datetime
import hashlib
import time
# change the format of the recepient list
# ge... |
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
from .resnext101_32x4d_features import resnext101_32x4d_features,resnext101_32x4d_features_blob
__all__ = ['ResNeXt101_32x4d', 'resnext101_32x4d']
pretrained_settings = {
'resnext101_32x4d': {
'imagenet': {
'url': 'http://data.lip... |
#!/usr/bin/env python
"""
Generate a simple scatter plot of power...
"""
import cgi
import sys
import datetime
import numpy as np
import matplotlib.colors as mpcolors
import matplotlib.colorbar as mpcolorbar
import matplotlib.patheffects as PathEffects
from pyiem.meteorology import uv
from pyiem.plot.use_agg import ... |
# Copyright 2017-present Open Networking Foundation
#
# 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 agr... |
from typing import *
import numpy as np
from itertools import combinations, product, permutations
from scipy.special import loggamma
def rss_objective( y_test: np.ndarray, y_predicted: np.ndarray) -> float:
"""Return the residual sum of squares"""
return np.sum((y_predicted - y_test)**2)
def rmse_objective(... |
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""
Purpose
Shows how to assume a role using AWS Security Token Service (AWS STS) credentials.
"""
import json
import time
import sys
import boto3
from botocore.exceptions import ClientError
def progress_bar(... |
# SPDX-FileCopyrightText: 2019-2021 REFITT Team
# SPDX-License-Identifier: Apache-2.0
"""Implements the common `Alert` interface for all broker clients."""
# type annotations
from __future__ import annotations
from typing import List, Dict, Union, Any, Optional
# standard libs
import json
from datetime import datet... |
# CD to DAPPER folder
from IPython import get_ipython
IP = get_ipython()
if IP.magic("pwd").endswith('tutorials'):
IP.magic("cd ..")
else:
assert IP.magic("pwd").endswith("DAPPER")
# Load DAPPER
from common import *
# Load answers
from tutorials.resources.answers import answers, show_answer
# Load widgets
fr... |
#!/usr/bin/python
import re
import sys
import os
from multiprocessing import Process
from utils import *
try:
from argparse import ArgumentParser
except:
prettyprint('''
Welcome to the Mod-Lang-Scala Release Script.
This release script requires that you use at least Python 2.7.0.
It ap... |
from back.models import *
from pony.orm import db_session
from random import choice
import back.legacy
type_dict = {
'profile':'toone',
'sender':'toone',
'receiver':'toone',
'topic':'toone',
'node':'toone',
'nodemean_node':'toone',
'classrooms':'tomany',
'sentEnvelopes':'tomany',
'... |
import os.path as op
from collections import OrderedDict
from six import text_type
from datalad.utils import Path
from datalad.distribution.dataset import (
rev_get_dataset_root,
resolve_path,
)
from . import aggregate_layout_version
import logging
lgr = logging.getLogger('datalad.dataset')
# TODO drop wh... |
import os
from pathlib import Path
PATH_LIKE_KWARGS = [
"bids-filter-file",
"fs-license-file",
"fs-subjects-dir",
"work-dir",
"w",
]
FLAGS = (
"skip_bids_validation",
"low-mem",
"boilerplate",
"longitudinal",
"skull-strip-fixed-seed",
"no-submm-recon",
"fs-no-reconall",
... |
from typing import Callable, Union
from matplotlib.axes import Axes
import torch
import torch.nn as nn
import numpy as np
from models.custom import DentReLUFunction
import matplotlib.pyplot as plt
import utils
import models
plt.style.use("classic")
def _ax_plot(ax_func: Callable[[Axes], None], name):
plt.figure(... |
import os
import argparse
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
from read_data import ChestXrayDataSet
from model import DenseNet121
from cataly... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Train the model"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pandas as pd
import torch
import numpy as np
import os
import scipy
import matplotlib.image as mpimg
import torch.nn ... |
"""Most rules are described in 'Secrets in Source Code: Reducing False Positives Using Machine Learning'."""
import os.path
from abc import ABC, abstractmethod
from typing import List, Any
import numpy as np
from scipy.sparse.csr import csr_matrix
from sklearn.preprocessing import LabelBinarizer
from credsweeper.com... |
from picamera import PiCamera
from time import sleep
from PIL import Image
import argparse
import io
import numpy as np
from fractions import Fraction
import datetime
import os
class Config:
def __init__(self, resolution = None, sensor_mode = None, exposure = None, iso = None, exposure_mode = None, rotatio... |
import os
import torch
import pickle
import pandas as pd
import numpy as np
from torch.utils.data import Dataset
import tqdm
def createDataCSV(dataset):
labels = []
texts = []
dataType = []
label_map = {}
name_map = {'wiki31k': 'Wiki10-31K',
'wiki500k': 'Wiki-500... |
import argparse
import contextlib
import sys
import time
import cupy
import numpy
from black_scholes import black_scholes_kernel
# This sample computes call prices for Europian options with
# Monte-Carlo simulation. It was based on a sample of the financial package
# in CUDA toolkit. For details, please see the corr... |
#!/bin/env python
"""Plot script for uaibus log files."""
from math import atan2, radians, cos, sin, asin, sqrt
import click
import csv
import random
import datetime
import folium
import folium.plugins
import logging
import numpy as np
import sys
def distance(lat1, lng1, lat2, lng2):
R = 6371000 # raio da terra... |
import logging
import uuid
try:
from urllib.parse import urljoin, urlencode, parse_qs # Python 3
except ImportError:
from urlparse import urljoin, parse_qs # Python 2
from urllib import urlencode
import requests
logger = logging.getLogger('moneybird')
class Authentication(object):
"""
Base cl... |
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