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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""This module declares the different meanings that the Orbit 6 components can take
and their conversions
"""
from numpy import cos, arccos, sin, arcsin, arctan2, sqrt, arctanh, sinh, cosh
import numpy as np
from ..errors import UnknownFormError
from ..utils.node import... |
from django.test import TestCase
from django.contrib.auth.models import User
from django.urls import reverse
from csvexport import apps, settings
from csvexport.actions import ModelNode
from csvexport.forms import CSVFieldsForm
from csvexport.forms import CSVFormatForm
from csvexport.forms import UniqueForm
from ..m... |
import random
import numpy as np
import cv2
import matplotlib.pyplot as plt
# from matplotlib import pyplot as plt
import scipy
from scipy import signal
from PIL import Image
from scipy.ndimage import median_filter
# 由于卷积核的大小一般是奇数，因此这里假设卷积核是奇数的
'''
####################
图像处理的基本函数
####################
'''... |
import itertools
import os
import time
from datetime import datetime
import numpy as np
import torch
import torchvision.utils as vutils
import utils
from cyclegan import Generator as cycG
from cyclegan import Discriminator as cycD
def _weights_init(m):
classname = m.__class__.__name__
if classname.find('C... |
"""
Contains all errors specific to this package.
"""
import re
import sys
__all__ = [
'AccountLimitExceeded', 'AWSError', 'CartInfoMismatch', 'DEFAULT_ERROR_REGS',
'InvalidClientTokenId', 'InvalidSignature', 'InvalidAccount', 'MissingClientTokenId', 'MissingParameters',
'ParameterOutOfRange',... |
import re
from collections import defaultdict
import numpy as np
import pandas as pd
from terminaltables import DoubleTable
from pathlib import Path
def weather_table(weather_dict, path):
table_data = []
for weather, seeds in weather_dict.items():
successes = []
totals = []
collisions = []
collided_and_s... |
import numpy as np
import cv2
from sklearn.utils import shuffle
from sklearn.model_selection import cross_val_score
from sklearn.neighbors import KNeighborsClassifier
import matplotlib.pyplot as plt
import pandas as pd
def single_ch_hist(image, channels, bins, chrange, color):
hist = cv2.calcHist(image, channels,... |
import discord
import asyncio
import os
import math
import feedparser
import requests
import shlex
import database
import bom
import utils
from settings import *
from datetime import datetime, time, timezone
from random import choice
from discord.ext import commands
from discord.utils import get
import atexit
CURR... |
# SPDX-License-Identifier: MIT
#
# Copyright (c) 2020 <NAME> <<EMAIL>>
import re
import git
import glob
import tempfile
import shutil
import subprocess
import jenkinsapi
import requests
import time
import hashlib
import os
from enum import Enum
from click import style, echo, confirm, progressbar
from datetime import d... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for `ml` package."""
import pytest
from click.testing import CliRunner
from ml import np
from ml import cli
from ml.rbms import BernoulliRBM
from ml.rbms.core import RBM
from ml.rbms.rbm import SimpleBernoulliRBM
from ml.rbms.gaussian import GaussianRBM
from ml... |
#!/usr/bin/env python
"""
A library and command-line utility for turning an XPJSON PlanSchema document
into an HTML-format command dictionary.
This tool focuses on the @commandSpecs part of the PlanSchema (and indirectly
on the @paramSpecs used by the commands). It doesn't output anything about
plan params, station p... |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Categorical, Distribution
import torch_ac
import math
from torch.distributions.utils import _standard_normal, lazy_property
# Function from https://github.com/ikostrikov/pytorch-a2c-ppo-acktr/blob/master/model.py
def in... |
import os
import pickle
import numpy
import music21
import itertools
from src import DATA_DIR
from src.helpers import save_pickle, load_pickle, get_pitch_space
def tokenize(chars):
if type(chars) == bytes:
chars = chars.decode("utf-8")
return chars.replace('(', ' ( ').replace(')', ' ) ').split()
def t... |
# ___________________________________________________________________________
#
# Prescient
# Copyright 2020 National Technology & Engineering Solutions of Sandia, LLC
# (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S.
# Government retains certain rights in this software.
# This software is ... |
from torch.utils.data import Dataset
from torch.utils.data import Dataset, DataLoader
from torch.utils.data.sampler import RandomSampler, SequentialSampler, WeightedRandomSampler
from torch.utils.data.distributed import DistributedSampler
import torch
import cv2
import numpy as np
import pandas as pd
import numpy as n... |
"""
In this pretrain-finetune example, we do the following:
epoch 1 - 10: pretrain a ResNet9 model on Cifar100
epoch 11-12: freeze the backbone, use a new classification head and finetune on cifar10 data
"""
import tempfile
import fastestimator as fe
import torch
import torch.nn as nn
import torch.nn.functional as fn... |
#!/usr/bin/env python
""" Translate reg_tracker.txt to a python script using the host_api
Usage:
regTrackerToPython.py <input_file_name> <output_file_name> [--no_firmware_load]
Options:
--help Shows this help message.
"""
from __future__ import print_function
from __future__ import absolute_import
from __fu... |
import cv2
import math
import numpy as np
import h5py
import sys
import uuid
from joblib import Parallel, delayed
from bisect import bisect_left
from datetime import datetime, timedelta
from sklearn.model_selection import train_test_split
from cloudseg.utils.files import get_contained_dirs, get_contained_files
from... |
from ctypes import pointer, c_float
from .bindings import so, FPDF_RECT, FPDF_MATRIX, FPDF_ITEM_INFO
from .font import Font
import contextlib
class PageObject:
OBJ_TYPE_TEXT = 1 #: see :class:`TextObject`
OBJ_TYPE_PATH = 2 #: see :class:`PathObject`
OBJ_TYPE_IMAGE = 3 #: see :class:`ImageObject... |
from __future__ import print_function
import numpy as np
import scipy.sparse as sp
import hashlib
import warnings
import time
# from gcn.utils import normalize_adj
cupy_is_available = False
try:
import cupy as cp
cupy_is_available = True
except ImportError:
warnings.warn("cupy is not imported, some operat... |
import os
import keras
import h5py
import math
import numpy as np
import datetime as dt
from glob import glob
from PIL import Image
import cv2
import matplotlib.pyplot as plt
import io
class Hdf5Sequence(keras.utils.Sequence):
def __init__(self, myHd5File, idlist, batch_size):
self.srcF... |
#!/usr/bin/env python3
# Back Side (HDMI/microUSB)
# ------------- [] 17 - Shutdown / Reboot
# | PiTFT | [] 22 - IP Address / VNC Server
# | Display | [] 23 - Pixel Desktop ("startx") / RetroPie ("emulationstation")
# ------------- [] 27 - Toggle Backlight
import RPi.GPIO as GPIO
import os, ... |
import numpy as np
import random
import tensorflow as tf
from lwau import LWAU
from tensorflow.python.platform import flags
import os
from task_generator import TaskGenerator
FLAGS = flags.FLAGS
flags.DEFINE_integer('metatrain_iterations', 60000, 'number of metatraining iterations.')
# Training options
flags.DEFINE_... |
import datetime
import os
import random
from vod_metadata import default_template_path
from vod_metadata.vodpackage import VodPackage
__all__ = ["generate_metadata"]
IMAGE_EXTENSIONS = [".bmp", ".jpg"]
def _check_for_ae(ae_type, movie_name, extensions):
ae_safe = ae_type.replace(' ', '_')
ae_paths = ['{}_{... |
#!/usr/bin/env python3
import argparse
from pathlib import Path
import numpy as np
import statsmodels.api as sm
from scipy import stats
from matplotlib import pyplot as plt
parser = argparse.ArgumentParser(
description="Train generalized linear model to get coefficient for each variable."
)
parser.add_argument(
... |
import datetime
from django import forms
from django.contrib import admin
from django.contrib.admin import SimpleListFilter
from django.urls import reverse
from ordered_model.admin import OrderedTabularInline
from solo.admin import SingletonModelAdmin
from taggit.models import Tag
from taggit_helpers.admin import Taggi... |
# -*- coding=utf-8 -*-
from abc import ABC, abstractmethod
from itertools import count
from textwrap import dedent, indent
from typing import AbstractSet, Any, Callable, Container, Generic, Iterable, \
Optional, \
Set, \
TypeVar
T = TypeVar("T")
INDENTION = " " * 2
class Parser(Generic[T], ABC):
@a... |
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 21 13:03:42 2018
@author: <NAME>
"""
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import SVG, display
#Import Keras objects
from keras.models import Model
from keras.layers import Input, Flatten, Reshape, Softmax
from keras.layers import Dens... |
import csv
import json
import os
import random
import subprocess
from django.conf import settings
from django.contrib.auth.models import User
from django.db import transaction
from django.utils import timezone
from django.utils.timezone import localtime
from .models import CurriculumDocument, HumanRelevanceJudgment, ... |
import argparse
import json
import logging
import random
import numpy as np
import torch
from decouple import config
from tqdm import tqdm
from GPT2.config import GPT2Config
from GPT2.encoder import get_encoder
from GPT2.model import GPT2LMHeadModel
from GPT2.utils import load_weight
# import os
# import torch.nn.... |
#!/usr/bin/env python
# Standard library
import logging as log
import random
import sys
import unittest
from pprint import pprint as pp
from unittest import TestCase
# Third-party
from numpy import array as arr
from numpy.testing import assert_almost_equal
from shapely.geometry import Point
from shapely.geometry impo... |
import numpy as np
from keras.layers.core import Lambda, Merge
from keras.layers.convolutional import Convolution2D
from keras import backend as K
from keras.regularizers import l1l2, Regularizer
from keras.engine import Layer
def crosschannelnormalization(alpha = 1e-4, k=2, beta=0.75, n=5,**kwargs):
"""
... |
from threading import Lock
from mesh.standard import OperationError, ValidationError
from scheme import Boolean, Text
from scheme.supplemental import ObjectReference
from sqlalchemy import MetaData, Table, create_engine, event
from sqlalchemy.engine.reflection import Inspector
from sqlalchemy.exc import NoSuchTableEr... |
#! python3
# -*- encoding: utf-8 -*-
'''
Current module: rman.app.httpcase.views.testsuite
Rough version history:
v1.0 Original version to use
********************************************************************
@AUTHOR: Administrator-<NAME>(罗科峰)
MAIL: <EMAIL>
RCS: rman.app.httpcase.views.tes... |
'''
Number: 4
This file models sequences of words using the statistical properties of n-grams.
I follow the Markov assumption (or independence assumption).
As for probabilities, I use and implement the Kneser-Ney Smoothing method.
'''
import pandas as pd
# --> Unigrams Probabilities (something wrong with this)
def kn... |
from __future__ import unicode_literals
import os
from django.shortcuts import get_object_or_404, redirect, render
from django.urls import reverse
from django.utils.translation import ugettext as _
from django.views.decorators.vary import vary_on_headers
from django.core.files import File
from wagtail import VERSION ... |
# -*- coding: utf-8 -*-
from telegram.ext import Updater, MessageHandler, CommandHandler, Filters
import os
import subprocess
import logging
import random
import numpy
import datetime
import time
import atexit
logging.basicConfig(
filename='spam.log',
level=logging.INFO,
format='[%(asctime)s] [%(levelname)... |
import codecs
import csv
import io
import os
from collections import defaultdict
import falcon
from addok.config import config
from addok.core import reverse, search
from addok.helpers.text import EntityTooLarge
from addok.http import View, log_notfound, log_query
def register_http_endpoint(api):
api.add_route(... |
# -*- test-case-name: pymeta.test.test_pymeta -*-
"""
Public interface to OMeta, as well as the grammars used to compile grammar
definitions.
"""
import string
from .builder import TreeBuilder, moduleFromGrammar
from .boot import BootOMetaGrammar
from .runtime import OMetaBase, ParseError, EOFError
class OMeta(OMetaBa... |
"""
Unit tests for ``cidrize``.
"""
import unittest
from netaddr import IPRange, IPNetwork
import pytest
import cidrize
class TestParseBrackets(unittest.TestCase):
def test_parse_brackets(self):
expected = IPRange("1.2.3.118", "1.2.3.121")
_input = "1.2.3.1[18-21]"
assert expected == ci... |
"""
"""
import os
import tempfile
import unittest
from .context import fabulist
class BasicTestSuite(unittest.TestCase):
"""Basic test cases."""
def setUp(self):
self.fab = fabulist.Fabulist()
self.temp_path = None
def tearDown(self):
self.fab = None
if self.temp_path:
... |
import sys
import numpy as np
import torch
import os
from tqdm import tqdm, trange
sys.path.append("..")
import moviepy.editor as mpy
import env
import gym
import pickle
from gym import spaces
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from config import argparser
from config.motion_plan... |
import re
import sys
import PySimpleGUI as sg
from tkinter import filedialog
from tkinter import *
data_file = []
files = []
if len(sys.argv) == 1:
layout = [[sg.Text('Document to open')],
[sg.In(), sg.FileBrowse()],[sg.CloseButton('Open'), sg.CloseButton('Cancel')]]
window = sg.... |
import argparse
from torch.nn import functional
from mdptetris_experiments.agents.action_networks import NN1DAction
import os
import random
import time
from collections import deque
import numpy as np
import torch
from gym_mdptetris.envs import board, piece, tetris
from gym_mdptetris.envs.tetris import TetrisFlat
fro... |
import cv2
import numpy as np
import trackpy as tp
import pandas as pd
from ..general.parameters import get_param_val, get_method_key
from ..track import intensity_methods as im
from ..customexceptions.track_error import *
from ..user_methods import *
'''
-------------------------------------------------------------... |
#!/usr/bin/env python
# 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
# "Li... |
# Third Party
import pytest
# Local
import bel.lang.parse
from bel.lang.ast import BELAst
from bel.schemas.bel import Pair
# TODO test reading in a string from a file doesn't remove the escape backslash
def test_ordered_pairs():
"""Matching left, right pairs of characters"""
left = [10, 20, 40, 50, 70]
... |
import pytest
import numpy as np
from funkyAD.base import AD, grad, Node
from funkyAD.functions import addition, multiplication, division, floordiv, power, sign, r_der, pos, neg, _abs, invert, _round, floor, ceil, trunc, exp, sin, cos, tan
# to do:
# deal with int, float, long
# test new methods
# test AD class
def... |
"""
Created on Thu Sep 28 15:17:50 2017
@author: zqwu
"""
import numpy as np
import tensorflow as tf
import copy
import sys
from deepchem.metrics import to_one_hot, from_one_hot
from deepchem.models import KerasModel, layers
from deepchem.models.losses import L2Loss, SoftmaxCrossEntropy
from deepchem.trans import und... |
# Copyright © 2012-2021 <NAME> <<EMAIL>>
#
# 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, publish,... |
import bge
from resources import increase_resource
from mathutils import Vector, noise
import random
class Unit(bge.types.KX_GameObject):
def __init__(self, own):
pass
def select(self):
pass
class Ant(bge.types.BL_ArmatureObject):
antlist = []
def __ini... |
import os
import sys
import math
import random
import numpy as np
from datetime import datetime
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import data_utils
def _stoke_decoding(stoke):
lift_pen_padding = 2.0
lines = []
points = []
x_prev = 0
y_prev = 0
was_dr... |
# Copyright 2016 <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 in writing, softwa... |
import random
import random
import sys
import time
from lib import game_object
from lib.ascii import print_warrior, print_mage, print_rogue
from lib.fight import fight_setup
from lib.guards import BridgeGuard
from lib.map import zonemap, solved_places
from lib.npc import Spell
from lib.player import myPlayer
from lib.... |
"""Provide functions to write the Order Parameters into files."""
import numpy as np
# For debugging.
# TODO: Remove it after implement logging feature
DEBUG=False
def pandasdf2pdb(df):
"""Return a string in PDB format from a pandas dataframe.
Parameters
----------
df : pandas dataframe with columns... |
import matplotlib
import matplotlib.pyplot as plt
import json
import jinja2
import os
def _get_node_names(df):
'''
:param df: pandas DataFrame, each column represents a state
:return:
dictionary of (column name, column unique value list)
which means (state name, unique values in t... |
import argparse
import torch
from rl import rl_model, omss_env, rl_utils
from utils import config as cfg
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
from sklearn.model_selection import train_test_split
import os
import wandb
from tqdm import tqdm
import time
device = torch.device('cuda' i... |
import base64
try:
from hashlib import md5
except ImportError:
from md5 import md5
import os.path
import re
import shutil
from definitions import Style
import res
from lib.log import debug, exception
from lib import zipdir
from paths import TMP_PATH
import world
class Map(object):
map_string = None
... |
import hashlib
import importlib
from collections import namedtuple
from datetime import datetime
import pytest
import pytz
import requests
from asn1crypto import tsp, algos, core, cms, ocsp
from freezegun import freeze_time
from oscrypto import asymmetric, symmetric
from pyhanko_certvalidator import ValidationContext,... |
# -*- coding: utf-8 -*-
import os
import socket
import json
import logging
import uuid as _uuid
# noinspection PyCompatibility
from . import exceptions
logger = logging.getLogger('samsungctl')
LOGGING_FORMAT = '''\
[%(levelname)s][%(thread)d] %(name)s.%(module)s.%(funcName)s
%(message)s
'''
class CEC(object):
... |
from sdk.db import database
import os
import json
from sdk.db.mongo.schema import ClassInfo
from sdk.db.mongo.schema import Section
from bson.objectid import ObjectId
from utils import logger
def get_class_info(sc, cn, it, im):
try:
res = ClassInfo.objects.get(
sc=sc, cn=cn, it=it, im=im)
... |
# Copyright (c) 2017 Sony Corporation. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... |
"""Tests for :py:class:`rasterio.warp.WarpedVRT`."""
from __future__ import division
import affine
import boto3
import pytest
import rasterio
from rasterio.crs import CRS
from rasterio.enums import Resampling
from rasterio import shutil as rio_shutil
from rasterio.vrt import WarpedVRT
from rasterio.warp import tran... |
# -*- coding: utf-8 -*-
# Copyright (c) 2017 SoftBank Robotics Europe. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""
Sequencer features
"""
import os
import time
import pytest
from itertools import product
from wooqi.src import global_va... |
""" Useful neuroimaging coordinate map makers and utilities """
import numpy as np
from .coordinate_system import CoordSysMaker
from .coordinate_map import CoordMapMaker
from ..transforms.affines import from_matrix_vector
scanner_names = ['scanner-' + label for label in 'xyz'] + ['t']
mni_names = ['mni-' + label for... |
"""A switch driver for the Nexus 5500
Currently the driver uses telnet to connect to the switch's console; in the
long term we want to be using SNMP.
"""
import re
from schema import Schema, Optional, And, Use
import logging
from hil.model import db, Switch
from hil.ext.switches import _console
from hil.errors impor... |
import torch
import torch.nn as nn
import numpy as np
from abc import ABC, abstractmethod
import pandas as pd
import json
import bdmodule.bd_utils as bd_utils
#from module.data_loading_fromlocal import read_turkprob
class UserSimulator(ABC):
@abstractmethod
def answer(self ):
pass
class NoisyUser(Us... |
#
# Copyright 2015-2020 <NAME> <<EMAIL>>
#
# 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 ... |
import collections
from typing import List
import numpy as np
import torch
from genrl.agents.deep.dqn.base import DQN
def ddqn_q_target(
agent: DQN, next_states: torch.Tensor, rewards: torch.Tensor, dones: torch.Tensor,
) -> torch.Tensor:
"""Double Q-learning target
Can be used to replace the `get_targ... |
# -*- coding: utf-8 -*-
import logging
from pathlib import Path
def add_map_style(sum):
'''
Write the map style element to the HTML header
'''
logging.debug('Write the map style element to the HTML header')
sum.write('<style>\n')
sum.write(' #map {\n')
sum.write(' height: 400px;\n')
... |
import os
import csv
import glob
import argparse
import subprocess
import pysam
import pybedtools
from math import floor
from statistics import mean, stdev
def get_reads(sample, readdir):
r1 = glob.glob(f'{readdir}/{sample}_*R1*.gz')[0]
r2 = glob.glob(f'{readdir}/{sample}_*R2*.gz')[0]
return r1, r2
de... |
import numpy as np
import numpy.ma as ma
from PIL import Image
from dataclasses import dataclass
from skimage.transform import resize
import time
from typing import Tuple
nsamples = 2
width, height = 600, 400
# virtual width/height for FSAA
vwidth, vheight = width * nsamples, height * nsamples
bg_color = (0.2, 0.7, 0.... |
import datetime, os
from typing import List, Dict
from flask import (
Flask,
jsonify,
request,
Response,
make_response,
render_template,
send_from_directory,
)
from ...libs import json_lib, converter_lib, io_lib
from ...models.main import AlphaException
from ._parameter import Parameter
f... |
"""
Cluster
=======
This filter will identify clusters of atoms in the system. It uses a recursive
algorithm to build the clusters using a fixed cut-off. There are options to
calculate the volumes of the clusters and also to draw convex hulls around the
clusters to highlight them.
Parameters are:
.. glossary::
... |
"""FFmpeg writer tests of moviepy."""
import multiprocessing
import os
from PIL import Image
import pytest
from moviepy.video.compositing.concatenate import concatenate_videoclips
from moviepy.video.io.ffmpeg_writer import ffmpeg_write_image, ffmpeg_write_video
from moviepy.video.io.gif_writers import write_gif
fro... |
#
# Analytics server
#
import pickle
import jsonpickle
import platform
import json
import io
import os
import sys
import pika
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import datetime
sns.set()
from sklearn.metrics import r2_score, median_absolu... |
import numpy as np
import math
import random
import h5py
A=0.01
class act:#激活函数
def sigmoid(x):
return 1.0/(1.0+np.exp(-x))
def tanh(x):
return (np.exp(x)-np.exp(-x))/(np.exp(x)+np.exp(-x))
def none(x):
return x
def relu(x):
return 1 * (x > 0) * x
def leaky_relu(x):
... |
import datetime
import requests
from django.shortcuts import render, redirect
from django.http import request, HttpResponse, HttpResponseRedirect
from django.contrib.auth.decorators import login_required, user_passes_test
from django.contrib import messages
from django.core.paginator import Paginator
from django.contr... |
"""
Module description ...
Reference:
- Surename1, Forename1 Initials., Surename2, Forename2 Initials, YEAR. Publication/Book title
Publisher, Number(Volume No), pp.142-161.
"""
import sys
import numpy as np
import numpy.ma as ma
from operator import itemgetter
from scipy.integrate import solve_ivp
from functools imp... |
import sifutil
import numpy as np
import re
import requests
from bs4 import BeautifulSoup
import pandas as pd
import warnings
import numpy as np
# from mpl_toolkits.basemap import Basemap, cm
import math
from math import sin, cos, sqrt
from pyproj import Proj, transform
# requires netcdf4-python (netcdf4-py... |
"""Build_Cloudtrail_Table
Create the CloudTrail Logs table for Athena use.
See the AWS documentation for Athena here:
http://docs.aws.amazon.com/athena/latest/ug/getting-started.html
"""
import os
import sys
import json
from datetime import datetime, timedelta
import logging
import boto3
from botocore.exception... |
import cv2, os, sys
import numpy as np
import imutils as iu
import sudoku_solver as solver
class ocrClass:
def __init__(self):
samples = np.loadtxt('ml/generalsamples.data',np.float32)
responses = np.loadtxt('ml/generalresponses.data',np.float32)
responses = responses.reshape((responses.si... |
import asyncio
import datetime
import json
import logging
import pathlib
import ssl
import sys
import traceback
import urllib
import websockets
from os import path
MAX_SYMBOLS = 50 # Hard limit imposed by FinnHub
class FinnhubClient:
"""
Maintains a websocket connection with the FinnHub data source.
Keeps track... |
"""
LIP predictor
This script allows the user to train and/or test a classifier
of Linear Interacting Peptides in protein structures (PDBs).
"""
import argparse
from os import mkdir, path
from os.path import isdir, isfile, abspath
import logging
import configparser
import pandas as pd
import numpy as np
from lip_fea... |
import os,time
import numpy as np
import rawpy
import glob, scipy.io
import torch
import torch.nn as nn
import torch.optim as optim
from tensorboardX import SummaryWriter
from model import SeeInDark
from net_canny import Net
from pytorch_msssim import MSSSIM
saveimg = True
ps = 512 #patch size for training
device =... |
from .utils import decompress_mesh_data
from ..skeleton import Skeleton
from ..trimesh_io import Mesh
import h5py
import os
import orjson
import pandas as pd
import warnings
import numpy as np
from dataclasses import asdict
warnings.simplefilter(action="ignore", category=pd.errors.PerformanceWarning)
NULL_VERSION = 1... |
# Lint as: python2, python3
# Copyright 2018 The TensorFlow Authors 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
#
#... |
# 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
# distributed under th... |
import os
import re
import sys
import ast
import astor
import nbformat
from nbconvert import PythonExporter
from scalpel.core.mnode import MNode
from scalpel.SSA.ssa import SSA
from scalpel.util import get_path_by_ext
# we need to define cretieras for variables
def filter_line(line):
if len(line)==0:
retu... |
"""
"""
import os, shutil
from .ModuleLoader import ModuleLoader # copied from McUtils since I don't want a dependency here (yet)
__all__ = ["Config", "ConfigManager", "ConfigSerializer"]
class ConfigSerializer:
loader = ModuleLoader(rootpkg="Configs")
@classmethod
def get_serialization_mode(cls, fil... |
from django.shortcuts import render
from django.http import HttpResponseRedirect, HttpResponse
from django.core.urlresolvers import reverse
from .models import *
from .forms import *
from django.template.defaulttags import register
@register.filter
def get_item(dictionary, key):
return dictionary.get(key)
# Create y... |
# !/usr/bin/env python
# coding=utf-8
# @Time : 2019-07-02 21:00
# @Author : <EMAIL>
# @File : io_utils.py
import sys
import collections
import csv
import json
import logging
import os.path
import pickle
import random
import tarfile
import zipfile
from six.moves import urllib
import requests
import h5py
import ... |
#!/usr/bin/env python
# encoding: utf-8
import subprocess
import numpy as np
import pandas as pd
import os
import fire
from keras.layers import Input, Embedding
from keras.layers import Flatten, Dense, concatenate, Dropout, Reshape
from keras.models import Model
from keras.layers.normalization import BatchNormalizatio... |
from django.contrib.auth.decorators import login_required
from django.contrib.auth.forms import AdminPasswordChangeForm, PasswordChangeForm, UserCreationForm
from django.contrib.auth import update_session_auth_hash, authenticate, login
from django.contrib import messages
from django.contrib.auth.models import User
from... |
""" batch mode """
# TODO look into Mesa's BatchRunner class...
import json
import time
import pandas as pd
import argparse
from collections import Counter
# suppress deprecation warning we can't do anything about
import warnings
warnings.filterwarnings(action='ignore', category=FutureWarning, module=r'.*pyproj' )
... |
from abc import abstractmethod
import numpy as np
from intervaltree import IntervalTree
from loguru import logger
from vimms.Common import ScanParameters
########################################################################################################################
# DEW Exclusions
########################... |
# coding: utf-8
# # Mask R-CNN - Train on Shapes Dataset
#
#
# This notebook shows how to train Mask R-CNN on your own dataset. To keep things simple we use a synthetic dataset of shapes (squares, triangles, and circles) which enables fast training. You'd still need a GPU, though, because the network backbone is a R... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import json
import logging
import argparse
import torch
from source.inputter.corpus import KnowledgeCorpus
from source.model.seq2seq import Seq2Seq
from source.utils.engine import Trainer
from source.utils.generator import BeamGenerator
from source.utils.misc imp... |
import tkinter as tk # Used for main gui
import tkinter.ttk as ttk # Used for pretty widgets
import tkinter.messagebox as msg # Used for gui messages
import tkinter.filedialog # Used for gui filedialog
import os # Create files, search directories
import shutil ... |
"""Este módulo contém o conjunto de operações utilizadas pelos módulos
principais como por exemplo, o método
:func:`QApedia.io.load_templates` que utiliza o método
:func:`QApedia.utils.extract_variables` desse módulo para extrair o conjunto
de variáveis presentes na query geradora (``generator_query``).
Neste módulo, ... |
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