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import numpy as np
# Plotting
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
#####
# Plot a time series data set
#####
def plot_series(series, n_steps, y=None, y_pred=None, x_label="$t$", y_label="$x(t)$"):
plt.plot(series, ".-")
if y is not None:
plt.plot(n_steps, y,... |
import os
import numpy as np
import pandas as pd
import datetime
import matplotlib.pyplot as plt
from fpdf import FPDF
########## Defining functions and classes ##########
def aggregate_data(data_list, filepath, column):
'''Takes a list containing csvs, a filepath to the folder containing the csvs and a column... |
from evaluation.EvaluatorBase import EvaluatorBase, get_transform
from torch.autograd import Variable
import numpy as np
import torch
from torch.nn import functional as F
from evaluation.face_recognition.model import create_model
import os
import glob
from PIL import Image
class ResultsLabeledDataset(torch.utils.data.... |
# Metronome - <NAME> (Kwistech)
from tkinter import *
from winsound import Beep
class Metronome:
"""Create Metronome app with class instance."""
def __init__(self, root):
"""Initiate default values for class and call interface().
Args:
root (tkinter.Tk): Main class instance for t... |
"""
OpenVZ services -- asynchronous objects that exchange data to/from the device
"""
import collections
from enum import Enum
class IncompletePacket(IOError):
""" Exception used if we attempt to parse a packet that's insufficiently long to parse. """
pass
class InappropriatePacket(IOError):
""" Except... |
# coding: utf-8
import numpy as np
import json
import datetime
import sys
import boto3
from Reversi import choice_random, Reversi
from Reversi import DualNet, ChoiceReplaySteps, choice_primitive_monte_carlo, ChoiceMonteCarloTreeSearch, ChoiceSupervisedLearningPolicyNetwork, ChoiceAsynchronousPolicyAndValueMonteCarloT... |
# Copyright 2019 Xanadu Quantum Technologies 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 agre... |
# A script to copy positions using Interactive Brokers because SierrChart does
# not support adaptive market orders
import asyncio
import json
import logging
import typing as t
import datetime as dt
from asyncio.tasks import ensure_future
from contextlib import suppress
import click
from ib_insync import ContFuture, ... |
from nltk import word_tokenize
import string
from nltk.stem import SnowballStemmer
from tqdm import tqdm
"""
This file used to generate baseline paraphrases from ppdb.
"""
PPDB_DB = "./rep_ppdb/ppdb-2.0-tldr"
############ THIS IS THE NLTK-BASED PARAPHRASE GENERATOR !!!! ##########
def add_to_dict_of_set(key, value, ... |
"""
idea: spawn in waves. everyone saves up food from the plant until a certain time at which everyone spawns soldiers as fast as possible.
Triggered by an attack. Everyone set their spawn requirement according to the distance to the attack so that the spawn will all reach the spot at the same time.
idea: use avg pos... |
from xml.dom import minidom
from xml.etree.ElementTree import Element, SubElement, Comment, tostring
from xml.etree import ElementTree
import os
from parser import Parser
from formatter import *
import sys
class XMLMaker:
"""Class to construct the XML file.
Note: this class makes it much easier to debug/test ... |
# Read position from gulp outfile
import numpy as np
import pandas as pd
def read_index(OUTfile,k_number,Atomic_number=240):
with open(OUTfile,'r') as out:
# print(out.read())
for index, line in enumerate(out,1):
if 'Final fractional' in line:
print(line,index)
i = index
if 'Final Cartesian lattice... |
from datetime import (
datetime,
timedelta
)
from http import HTTPStatus
from flask import request
from flask_restful import Resource
from pymongo import MongoClient
from backend.clients.sbb_client import SBBClient
from backend.clients.swisscom_client import SwisscomClient
class PingView(Resource):
def... |
import os
import re
import threading
import urllib.parse as urlparse
import xbmc
import xbmcvfs
from contextlib import closing
from libs import mediainfo as info, mediatypes, pykodi, quickjson
from libs.addonsettings import settings
from libs.pykodi import localize as L, log
from libs.webhelper import Getter, GetterEr... |
from psdaq.configdb.typed_json import cdict
import psdaq.configdb.configdb as cdb
import pyrogue
import pyrogue.interfaces.simulation
import epix100a_gen2
import ePixFpga as fpga
import numpy as np
import sys
import IPython
import argparse
import re
mem = pyrogue.interfaces.simulation.MemEmulate()
class EpixBoard(pyr... |
import tensorflow as tf
import src.settings as settings
'''
refer to: https://github.com/wenxinxu/resnet-in-tensorflow/blob/master/resnet.py
'''
def activation_summary(x):
tensor_name = x.op.name
tf.summary.histogram(tensor_name + '/activations', x)
tf.summary.scalar(tensor_name + '/sparsity', tf.nn.zero_... |
# BSD 2-CLAUSE LICENSE
# Redistribution and use in source and binary forms, with or without modification,
# are permitted provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# Redistributions i... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import uuid
import shutil
import zipfile
import logging
import subprocess
from hashlib import md5
from pathlib import Path
import rarfile
from ezsub import const
from ezsub.utils import to_screen
from ezsub.errors import (
EmptyArchiveError,
BadCompressedFileErr... |
from rdkit import Chem
import pandas as pd
#==========================================================
# validate SMILES
def molStructVerify(compounds,
getFailedStruct=False,
getFailedStructIdx=False,
printlogs=True):
#-----------------------... |
'''
Data aggregation facilities.
'''
import threading as th
import queue
import multiprocessing as mp
from .module_exceptions import ConfigurationError
from .util import FactoryBase
from .guns.base import Sample
from .util import q_to_dict
import asyncio
import time
from dateutil import tz
import numpy as np
import pa... |
from utils.database import dbutils
import json
import requests
import polyline
import cPickle as pickle
import os
def get_routes(location_pairs, routes_path, get_time=False):
"""
Gets the driving route from Open Street Routing Machine for an array
of pairs of coordinates. Decodes the returned polyline rou... |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
from vision.ssd.data_preprocessing import PredictionTransform
from vision.ssd.vgg_ssd import create_vgg_ssd, create_vgg_ssd_predictor
from vision.ssd.mobilenetv1_ssd import create_mobilenetv1_ssd, create_mobilenetv1_ssd_predictor
from vision.ssd.mobilenetv1_ssd_lite import create_mobilenetv1_ssd_lite, create_mobilenetv... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright: (c) 2021, Ansible Project
# 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
from ansible.module_utils.basic import AnsibleModule, env_fallback
from ansib... |
# ------------------------------------------------------------------------------
# BSD 2-Clause License
#
# Copyright (c) 2019-2020, <NAME>
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following condi... |
from django.core.validators import MinValueValidator, MaxValueValidator
from django.db import models
from django.utils import timezone
from django.utils.translation import pgettext_lazy
from modelcluster.fields import ParentalKey
from modelcluster.models import ClusterableModel
from wagtail.admin.edit_handlers import F... |
import torch
import torch.nn as nn
import onmt.utils
import programmingalpha
import logging
import numpy as np
import math
from copy import deepcopy
from .BertGen import OnmtBertEncoder, buildBert
from .RoBertaGen import OnmtRobertaEncoder, buildRoberta
from .XLNetGen import OnmtXLNetEncoder, buildXLNet
... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# @date Dec 13 2015
# @brief
#
import sys
import threading
import logging
from logging.handlers import (
TimedRotatingFileHandler,
SocketHandler,
DatagramHandler,
SysLogHandler,
SMTPHandler,
HTTPHandler,
)
from logging import LoggerAdapter
t... |
import mistune
import re
import os
import time
ROOT_MD_DIR = '../docs/'
ROOT_IMG_DIR = ROOT_MD_DIR + 'figures/'
ROOT_TEX_DIR = './chaps/'
# LaTeXRenderer
class LaTeXRenderer(mistune.HTMLRenderer):
NAME = 'latex'
IS_TREE = False
def __init__(self, is_book_or_report=True):
self._is_book_or_repor... |
import tensorflow as tf
import numpy as np
import random
import csv
import cv2
import json
import h5py
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split
from keras.layers import Activation, Dense, Dropout, ELU, Flatten, Input, Lambda
from keras.layers.convolutional import Convolut... |
#!/usr/bin/env python3
# <xbar.title>Jackpot</xbar.title>
# <xbar.version>v1.1</xbar.version>
# <xbar.author>Marcos</xbar.author>
# <xbar.author.github>astrowonk</xbar.author.github>
# <xbar.desc>Displays current Mega Millions and Powerball jackpots.</xbar.desc>
# <xbar.dependencies>python</xbar.dependencies>
# <xbar.... |
import aiohttp
import asyncio
import sys
from aiohttp import web
from collections import defaultdict, Counter
import datetime as dt
from src.db_analysis_functions import count_date_status_function, count_date_status_format, \
count_approval_history_function, get_form_date, get_form, get_old_status
from src.db_inter... |
from collections import namedtuple, deque
import rx
from rxx.types import NamedObservable, Update, Updated
from rxx.internal.trampoline import Trampoline
from rx.disposable import CompositeDisposable, SingleAssignmentDisposable
class Source(object):
def __init__(self, on_back):
self.buffer = deque()
... |
import logging
import sys
import numpy as np
import matplotlib.pyplot as plt
def load_file(filename):
"""
Carrega o dataset para a memória
:param filename: nome do arquivo
:return: matriz x e y
"""
x_input = []
y_input = []
f = open("data/" + filename + ".txt")
lines = f.r... |
import datetime
import argparse
import torch
import random
import numpy as np
from configs.config import MyConfiguration
from BaseTrainer import BaseTrainer
from BaseTester import BaseTester
from data.dataset import MyDataset
from torch.utils.data import DataLoader
from models.MyNetworks import ESFNet
from v... |
"""
This is a Tank Game based on PocketTanks, made in Python 3 using Pygame and Pymunk for physics
"""
from random import randint
import sys
import pygame
import pymunk
import pymunk.pygame_util
# CLASS AND FUNCTION IMPORTS
from ground import Ground
from tank import Tank
from text import text
class PyTanksIO:
"... |
from queue import Queue
import pysc2.agents.myAgent.myAgent_2.macro_operation as macro_operation
from absl import app
from pysc2.agents import base_agent
from pysc2.lib import actions, features
from pysc2.env import sc2_env, run_loop
import pysc2.agents.myAgent.myAgent_2.smart_actions as sa
import pysc2.agents.myAgen... |
import json
from threading import Thread
import os
import logging
import sys
import shutil
import copy
from PyQt5.QtWidgets import QWidget, QPushButton, QApplication, QLabel, QMainWindow, QSizePolicy, QGraphicsDropShadowEffect, QProgressBar
from PyQt5.QtCore import QCoreApplication, QTimer, pyqtSlot
from PyQt5.QtGui i... |
from PIL import Image, ImageCms
def rgb2lab(image):
RGB_p = ImageCms.createProfile('sRGB')
LAB_p = ImageCms.createProfile('LAB')
return ImageCms.profileToProfile(image, RGB_p, LAB_p, outputMode='LAB')
def lab2rgb(image):
RGB_p = ImageCms.createProfile('sRGB')
LAB_p = ImageCms.createProfile('LAB'... |
import collections
import os
import numpy as np
from torch import Tensor
import librosa
from torch.utils.data import Dataset
___author__ = "<NAME>"
__email__ = "<EMAIL>"
def genSpoof_list(dir_meta, is_train=False, is_eval=False):
d_meta = {}
file_list = []
with open(dir_meta, 'r') as f:
... |
import sys
from six.moves.collections_abc import Iterable
from functools import partial
from promise import Promise, is_thenable
from ...error import GraphQLError, GraphQLLocatedError
from ...type import (GraphQLEnumType, GraphQLInterfaceType, GraphQLList,
GraphQLNonNull, GraphQLObjectType, Graph... |
import os
from random import shuffle
import datetime
import json
import tensorflow as tf
import pandas as pd
import click
from tensorflow.python.keras.metrics import AUC
from src.models.models import get_model
from src.models.loss import loss_with_fl, dice_coe_metric, dice_coe_loss
from src.data.drive import (get_dat... |
# ******************************************************************************
# Copyright 2017-2018 Intel 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.apa... |
# --------------
# import libraries
import numpy as np
import pandas as pd
import re
# Load data
data = pd.read_csv(path, parse_dates = [0], infer_datetime_format = True)
# Sort headlines by date of publish
data.sort_values(by=['publish_date'], axis=0, ascending=True, inplace = True)
# Retain only alphabets
data['h... |
import tkinter
from tkinter import *
questions = [
"1.Depressed mood most of the day, nearly every day",
"2.Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day.",
"3.Significant weight loss when not dieting or weight gain, or decrease or increa... |
import pandas as pd
import sys
from common import *
import configparser,json,os
import glob as glob
import ntpath
import pandas as pd
def read_protodata(folder_name,mdd=0):
fields=['amp_fac','server_id']
folder_dir=folder_name+'query/*/*'
folders=glob.glob(folder_dir)
eachfile=folders[0]
if mdd==1... |
import discord
import os
import requests
import json
from keep_alive import keep_alive
client = discord.Client()
dog_words = ["puppy", "pup", "dog", "woofer", "woof", "bork", "borker", "good boy", "good girl", ":dog:"]
dog_breeds = [
'affenpinscher',
'african',
'airedale',
'akita',
'appenzeller',
'austr... |
import math, sys
from lux.game import Game
from lux.game_map import Cell, RESOURCE_TYPES
from lux.constants import Constants
from lux.game_constants import GAME_CONSTANTS
from lux import annotate
DIRECTIONS = Constants.DIRECTIONS
game_state = None
def getSurroundingTiles(pos,range):
directions = ["NORTH", "SOUTH",... |
# -*- coding: utf-8 -*-
""""""
import colorsys
import pathlib
import numpy as np
from ruamel.yaml import YAML
def unpack(compressed: np.ndarray):
assert compressed.ndim == 1
uncompressed = np.zeros(compressed.shape[0] * 8, dtype=np.bool)
for b in range(8):
uncompressed[b::8] = compressed >> (7 - b... |
import skew
from collections import namedtuple
import argparse
skew_tuple = namedtuple("skew_tuple",
"skew_resource instances_filters cluster_count instance_type "
"reserved_filters reserved_count reserved_type dimensions")
skew_dict = {
'rds' : skew_tuple(
'db',{'DBInstanceStatus':'avail... |
"""
author: Prabhu
"""
'''
*******A convolutional neuralnet**********
convolution:
Convolution is the first filter applied as part of the feature engineering step.
An application of a filter to a image. We pass over a mini image, usually called a kernel and outputting
the filtered subset of our image.
... |
"""
This file contains api resources for interacting with the tutor as users take the course.
"""
import time
from flask_restful import abort, reqparse
from edx_adapt.api.resources.base_resource import BaseResource
from edx_adapt.data.interface import DataException
from edx_adapt import logger
from edx_adapt.select.i... |
from handsome.MicropolygonMesh import MicropolygonMesh, Position
from handsome.Pixel import FloatPixel, array_view, pixel_view
from handsome.Tile import Tile
from handsome.TileCache import TileCache
from handsome.capi import fill_micropolygon_mesh, generate_numpy_begin
from handsome.util import save_array_as_image, poi... |
from datetime import datetime
import threading
from flask import Flask, request, jsonify
import os
import sys
import numpy as np
import json
import cv2
from maskrcnn_benchmark.config import cfg
from maskrcnn_benchmark.data import make_data_loader
from maskrcnn_benchmark.structures.bounding_box import BoxList
from pre... |
# -*- coding: utf-8 -*-
import itertools
import time
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as sc_stats
def get_bps(modulation):
if modulation.upper() in ['BPSK']:
return 1
else:
raise Exception(f"Unknown modulation {modulation}")
def get_fec_matrix(name):
... |
from typing import List, Iterator, Dict
from typing_extensions import Literal
from itertools import groupby
from pathlib import Path
import datetime
import bson
import numpy as np
from pymatgen import Structure
from pymatgen.analysis.structure_matcher import StructureMatcher, ElementComparator
from monty.serializatio... |
#!/usr/bin/python3
# Standard libraries.
import os
import sys
import collections
chromiumPath = ""
if os.path.exists("/usr/bin/chromium"):
chromiumPath = "/usr/bin/chromium"
elif os.path.exists("/usr/bin/chromium-browser"):
chromiumPath = "/usr/bin/chromium-browser"
# Reads the given file, returns the entire... |
import math
import numpy as np
from numba import jit, cuda
import srfnef as nef
def change_id(id1,id2):
index = np.where(id1<id2)[0]
maxs = id2[index]
id2[index] = id1[index]
id1[index] = maxs
return id1.reshape(-1,1),id2.reshape(-1,1)
@jit(nopython = True)
def cal_sinogram(list_mode_data, tot... |
from __future__ import absolute_import
from __future__ import division
from builtins import zip
from builtins import object
import pandas as pd
import numpy as np
import json
import matplotlib.pyplot as plt
from .. import plot
def json_eci_to_pandas(jsoneci):
"""Go through an eci.json file and extract all
the... |
import _ailib
class CostFunction():
SQUARED_ERROR = 0
CROSSENTROPY = 1
class neuralnetwork():
def __init__(self, filepath=""):
if filepath == "": self.net = _ailib.neuralnetwork_init()
else: self.net = _ailib.neuralnetwork_init_fromfile(filepath)
def __del__(self):
_a... |
#!/usr/bin/env python
import json
import sys
import gzip
import pdb
def write_dataset(dataset, output_file):
with gzip.open(output_file, 'wt') as fout:
json.dump(dataset.to_dict(), fout, indent=2)
def read_dataset(input_file):
with gzip.open(input_file, 'rt') as fin:
dataset = Dataset()
... |
import matplotlib
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.patches import FancyArrowPatch
from mpl_toolkits.mplot3d import proj3d
from mpl_toolkits.axes_grid1 import make_axes_locatable
matplotlib.rcParams['mathtext.fontset'] = 'cm'
matplotlib.rcP... |
#!/usr/bin/env python
# coding: utf-8
#
# Copyright 2016 The Fontbakery Authors
# Copyright 2017 The Google Font Tools 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://ww... |
#!/usr/bin/env python3
# Copyright (c) 2014-2018 <NAME>
# Distributed under the MIT/X11 software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
# RPC test for basic name registration and access (name_show, name_history).
from test_framework.names import NameTestFra... |
#!/usr/bin/env python3
import sys
import tempfile
def chunks(x, n):
return [x[i:i+n] for i in range(0, len(x), n)]
COLORS = [
# "alice blue",
# "aquamarine",
# "azure",
# "beige",
# "bisque",
# "black",
# "blanched almond",
"blue",
"blue violet",
"brown",
"burlywood",... |
import numpy as np
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
os.environ[
'XLA_FLAGS'] = '--xla_gpu_cuda_data_dir=/usr/local/cuda'
from absl import app
from absl import flags
import matplotlib.pyplot as plt
import tensorflow as tf
import pickle
import jax
import jax.numpy as jnp
import jax_cosmo as jc
impo... |
import torch
from torch.autograd import Variable as var
import torch.nn.functional as F
import numpy as np
def Gaussian2D(x, mu, sigma, rho):
factor = 1.0 / (2 * np.pi * sigma[0] * sigma[1] * torch.sqrt(1 - rho**2))
norm_x = (x - mu)/sigma
Z = torch.sum(norm_x**2) - 2 * rho * norm_x[0] * norm_x[1]
val = factor * t... |
# -*- coding: utf-8 -*-
"""
Javelin Web2Py Default Controller
"""
from applications.javelin.ctr_data import ctr_enabled, get_ctr_data
from gluon.tools import Service
service = Service(globals())
@auth.requires_login()
@auth.requires_membership('standard')
def index():
"""
example action using the internationaliza... |
#!/usr/bin/env python
# coding: utf-8
# Script for running example BSEP inhibition classification models against user-provided data.
import sys
import os
import pandas as pd
import numpy as np
from sklearn import metrics
import argparse
from atomsci.ddm.pipeline import model_pipeline as mp
from atomsci.ddm.pipeline ... |
import unittest
from lxml import etree
from lxml.etree import XPathSyntaxError
from pyxmlmapper import base
from pyxmlmapper.components.exceptions import NotFoundException
from pyxmlmapper.components.fields import XmlField
xml = """
<PurchaseOrder PurchaseOrderNumber="99503" OrderDate="1999-10-20" EmptyDate="">
<... |
# -*- coding: utf-8 -*-
"""Views to run a survey by the instructor.
This module implements three views:
- run_survey_ss: Display the rows available for the survey and allow for
links to run each row individually
- run_survey_row: Run the survey as instructor for a single row
"""
from typing import List, Optional... |
# https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/dynamic_programming_frozenlake/
# -*- coding: utf-8 -*-
import gym
import numpy as np
import matplotlib.pyplot as plt
import random
np.set_printoptions(precision=3)
np.set_printoptions(suppress=True)
# Environment
# Slippery envir... |
"""
Fixed-Point GAN adapted from Siddiquee et al. (2019)
"""
from dataclasses import dataclass
import torch
import torch.autograd
from torch import Tensor, nn
from util.dataclasses import DataclassExtensions, DataShape
from util.pytorch_utils import relativistic_loss
from models.abstract_model import Abstr... |
"""General utilities."""
import collections.abc
import re
import shutil
import subprocess
from copy import deepcopy
from functools import partial
from os import cpu_count
from pathlib import Path
from haddock import log
from haddock.core.exceptions import SetupError
check_subprocess = partial(
subprocess.run,
... |
import os
import sys
import fire
import time
import torch
import torchplus
base_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, base_path)
sys.path.append(os.path.join(base_path, 'third_party/second.pytorch'))
MAJOR_VERSION = 1
MINOR_VERSION = 0
from tqdm import tqdm
from tensorboardX import Sum... |
from random import randint
import math, time
from tkinter import messagebox
import tkinter as tk
class Application(tk.Frame):
def __init__(self, master=None):
super().__init__(master)
master.wm_title("Find Shortest Path")
self.circleSize = 4
master.resizable(width=False, height=Fals... |
"""Intermediate variable preprocessor for PyBryt submissions"""
import ast
import astunparse
import nbformat
from IPython.core.inputtransformer2 import TransformerManager
from .abstract_preprocessor import AbstractPreprocessor
from ..utils import make_secret
class UnassignedVarWrapper(ast.NodeTransformer):
""... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Unit tests for the icompression module
"""
__author__ = "<NAME> <<EMAIL>>"
__date__ = "6/4/2020"
import unittest
import tempfile
import subprocess
import glob
import os
import sys
import numpy as np
import shutil
import test_all
from enb.config import get_options
opt... |
# -*- encoding: utf-8 -*-
import os
import sys
import argparse
from tqdm import tqdm
if os.path.abspath('..') not in sys.path:
sys.path.insert(0, os.path.abspath('..'))
from Evaluate.evaluate_openKBP import *
from model import *
from NetworkTrainer.network_trainer import *
def read_data(patient_dir)... |
import os
import time
import json
import random
import threading
import re
import urllib.request
from datetime import datetime
import praw
import yaml
from prawcore import NotFound
class OgreBot(threading.Thread):
__config = dict()
__dictionary = dict()
__error_dictionary = dict()
__header_dictionary... |
import tkinter as tk
from tkinter import ttk
import ttkthemes as tkT
from lib import sharelib
from PIL import ImageTk
import time
import datetime
ac_name = sharelib.connnection_popup()
chain_proxy = sharelib.def_credentials(ac_name)
file_uploading_proxy = sharelib.def_credentials(ac_name, mode="fileuploading")
roo... |
import numpy as np
from models import Policy, ValueFunction
def one_step_actor_critic(mdp, value_function_alpha, policy_alpha, iterations, episodes, max_actions, final_performance_episodes):
#print("One Step actor critic with mdp: " + mdp.name)
actions_vs_episodes_all = np.zeros((iterations, episodes))
f... |
"""
@Author: Lzy
@Time: 2022/03/09
@Description: 排序问题
"""
import functools
from typing import List
from heapq import *
def min_number(nums: List[int]) -> str:
"""
Offer 45. 把数组排成最小的数
核心思想：自定义排序规则
x + y < y + x; 则 x 应该放在 y 的左边，即 x 比 y 小
:param nums:
:return:
"""
def quick_sort(left: in... |
''' unit tests for Ansible module: na_ontap_vscan_on_demand_task '''
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import json
import pytest
from ansible_collections.netapp.ontap.tests.unit.compat import unittest
from ansible_collections.netapp.ontap.tests.unit.compat.mock im... |
import config as conf
import os
import sys
import numpy as np
from copy import deepcopy
import fnmatch
import basic_plot_functions
import var_utils as vu
import h5py as h5
'''
Directory structure and file names for ctest (or cycling experiments):
test/
├── Data/
│ ├── sondes_obs_2018041500_m.nc4 (or sondes_obs_201... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
TODO
"""
from numpy import arctan2, cos, digitize, linspace, log10, sin, sum, sqrt, zeros
from pandas import DataFrame
from .angle import Angle
from .catalog import SourceCatalog, HaloCatalog
from .distance import Distance
from .lensing import bmo_f, bmo_g, delta_c
... |
import time
from gettext import gettext as _
from string import Template
from django.core.exceptions import ValidationError, ObjectDoesNotExist
from django.core.urlresolvers import reverse
from django.db.models import Q, F
from django.db import models
from cyder.base.mixins import ObjectUrlMixin, DisplayMixin
from cy... |
"""pytest unit tests for vibrationtesting"""
import numpy as np
import vibrationtesting as vt
import numpy.testing as nt
import scipy.io as sio
def test_sos_modal_forsparse():
mat_contents=sio.loadmat('vibrationtesting/data/WingBeamforMAC.mat') # WFEM generated .mat file
K = (mat_contents['K'])
M = (mat_contents['... |
#Chapter 3 - Building interactive apps with Bokeh
#----------------------------------------------------------------------------------------------------#
#Using the current document
# Perform necessary imports
from bokeh.io import curdoc
from bokeh.plotting import figure
# Create a new plot: plot
plot = figure()
#... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
import logging
import smtplib
from email.mime.text import MIMEText
import types
import re
import yaml
import markdown
logger = logging.getLogger('emaillib')
logger.addHandler(logging.StreamHandler())
logger.setLevel(logging.INFO)
PROVIDERS_... |
#!/usr/bin/env python
# coding: utf-8
# In[97]:
# Task 1
# In[98]:
class Goose:
def __init__(self, name, weight):
self.name = name
self.weight = weight
def feed(self, food):
self.weight += food
def collect_eggs(self, quantity):
self.weight -= quantit... |
import os # Working with operation system environment
import shutil # Directories processing
import sys # Pass launch arguments
import ctypes # Dialogue messages
import datetime
from getpass import getuser
import re # Regular expressions (folder name mask)
def main(argv):
... |
import json
from collections import defaultdict
from pathlib import Path
import albumentations as A
import numpy as np
import pandas as pd
import torch
from easydict import EasyDict
from rasterio.features import rasterize
from shapely.geometry import Polygon
from skimage import io
from sklearn.model_selection import t... |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
"""
* UMSE Antivirus Agent Example
* Author: <NAME> <<EMAIL>[at]gmail[dot]com>
* Module: UMSE Decryption Tools
* Description: This module allows to decrypt UMSE file entries.
*
* Copyright (c) 2019-2020. The UMSE Authors. All Rights Reserved.
* Redistributi... |
from typing import List, Tuple, NamedTuple
import io
import shutil
import pathlib
import pkg_resources
from rawtypes.generator.cpp_writer import to_c_function, to_c_method
from rawtypes.generator.py_writer import to_ctypes_iter, write_pyi_function, write_pyi_struct
from ..parser.header import Header
from ..parser impor... |
from os import path
import pynvim
from pynvim import Nvim
from astropy.io import fits
from typing import List, Union
Number = Union[int, float]
@pynvim.plugin
class FitsOpen:
def __init__(self, nvim: Nvim):
self.nvim = nvim
@pynvim.function("FITSInfo", sync=True)
def fits_info(self, args):
... |
"""
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import argparse
import numpy as np
import matplotlib.pyplot as plt
LINE_COLORS = plt.rcParams['axes.prop_cycle'].by_key()['color']
LINE_STYLES... |
"""Encoder
Description:
This module encodes Planning Problem into Constraint Satisfaction Problem
License:
Copyright 2021 <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... |
import random
import matplotlib.pyplot as plt
# TO-D0 Make a Plot with Bicubic and SRCNN PSNR Evaluation Values with each Epoch
def evaluation_plot():
epoch_eval1 = {
'psnr_srcnn': [],
'psnr_bicubic': [],
'ssim_srcnn': [],
'ssim_bicubic': []
}
# Extracting SSIM and PSNR S... |
r"""
Basis Pursuit (BP) solvers tackle the original :math:`P_0` problem
:eq:`p0_approx` by posing L1-relaxation on the norm of unknown :math:`\vec{x}`.
.. autosummary::
:toctree: toctree/relaxation/
basis_pursuit_linprog
basis_pursuit_admm
"""
import numpy as np
from scipy.linalg import solve_triangular
f... |
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