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import os, sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import tensorflow as tf
# # fix result, otherwise may predict all flat
# np.random.seed(1271)
# tf.compat.v1.set_random_seed(1271)
from matplotlib import patches
from matplotlib.pyplot import figure
from sklearn.metrics import confu... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
#
# <NAME> (UNI:rb3074)
# Columbia University, New York
# ELEN E6889, Spring 2019
#
#——————————————————————————————————————————————————————————————————————————————
from __future__ import print_function
import time
import logging
from collections import namedtuple
from ppri... |
from django.shortcuts import render,redirect,get_object_or_404
from .forms import GreazeRegistrationForm,PostProjectForm,UpdateProjectForm,EditProfileForm,RateForm
from .models import Project,Profile,Rate
from django.contrib.auth.models import User
from django.views.generic import ListView,DetailView,CreateView,UpdateV... |
"""
Based on cellfinder detected cells, and amap registration, generate a heatmap
image
"""
import logging
import argparse
from pathlib import Path
import numpy as np
from skimage.filters import gaussian
from brainio import brainio
from imlib.cells.utils import get_cell_location_array
from imlib.image.scale import sc... |
import os
import sys
import json
import socket
import sqlite3
import requests
import pathlib
import time
import uuid
PATH = str(pathlib.Path(__file__).parent.absolute()) + os.path.sep
DB_FILENAME = "net_devs.db"
ip_address = None
mac_address = None
ip_mask = None
conn = None #connection variable
def get_ip_mask():
... |
# -*- coding: iso-8859-1 -*-
"""
MoinMoin - common functions for notification framework
Code for building messages informing about events (changes)
happening in the wiki.
@copyright: 2007 by <NAME> <<EMAIL>>
@license: GNU GPL, see COPYING for details.
"""
from MoinMoin import user, wikiutil
from ... |
import torch
from torch import nn
class AttentionBlock(nn.Module):
def __init__(
self,
inplanes,
planes,
win_len,
roi_num,
):
super(AttentionBlock, self).__init__()
self.inplanes = inplanes
self.planes = planes
self.wi... |
import zlx.record
import zlx.bin
import zlx.io
import zlx.wire
import zlx.int
MZ_MAGIC = 0x5A4D
PE_MAGIC = 0x4550
MACHINE_I386 = 0x014C
MACHINE_IA64 = 0x0200
MACHINE_AMD64 = 0x8664
# header flags
FH_RELOCS_STRIPPED = 0x0001
FH_EXECUTABLE_IMAGE = 0x0002
FH_LINE_NUMS_STRIPPED = 0x0004
FH_LOCAL_SYMS_STRIPPED = 0x0008
F... |
############################################################################
# Copyright 2018 <NAME> & Stanford University #
# #
# Licensed under the Apache License, Version 2.0 (the "License"); #
# you may not us... |
import vtk
import os.path
import numpy as np
import nibabel as nib
from six import iteritems
from vtk.util import numpy_support as ns
from nibabel.streamlines.tck import TckFile as tck
def read_vtk(filename):
if filename.endswith('xml') or filename.endswith('vtp'):
polydata_reader = vtk.vtkXMLPolyDataRead... |
import boto3
import cv2
import greengrasssdk
import json
import logging
import mxnet as mx
import numpy as np
import requests
import sys
import tarfile
import time
from collections import namedtuple
from datetime import datetime
from picamera import PiCamera
from sense_hat import SenseHat
#############################... |
# -*- coding: utf-8 -*-
"""Convert2rdf module.
This module contains RDF conversion functions for determinator package
"""
import sys
import click
from io import StringIO, BytesIO
from .determinator import TbxDocument
from lxml import etree
import rdflib
import logging
import os
XML_LANG = "{http://www.w3.org/XML/... |
import os
import sys
import jinja2
import re
import json
import traceback
from dpath import util as dpath_util
from jinja2.exceptions import UndefinedError, FilterArgumentError, TemplateSyntaxError
from jsonschema import validate, ValidationError, draft4_format_checker
from json.decoder import JSONDecodeError
from e2j2... |
from math import trunc
from re import L
import lightbulb
import random
import hikari
import wikipedia
import requests
import asyncio
from hikari.colors import Color
import datetime as dt
from datetime import datetime, time, timedelta
from wikipedia import exceptions
from wikipedia.wikipedia import languages
plugin ... |
"""Summarise network-hazard intersections
Purpose
-------
Collect network-hazard intersection attributes
- Combine with boundary Polygons to collect network-hazard-boundary intersection attributes
- Write final results to an Excel sheet
Input data requirements
-----------------------
1. Correct paths to all... |
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import reduce
from base.base_model import BaseModel
from .backbones import mobilenetv2
from .backbones import resnet
class DecoderBlock(nn.Module):
def __init__(self, in_channels, out_channels, block_unit):
super(DecoderBlock, self).... |
import sys
import random
import subprocess
import os.path
import math
import os
from covpair import CovariatePair
from randfeat import Feature,Num,Cat
_PAIRWISE_INPUT = '/dev/shm/z.tab'
_R_INPUT = os.path.splitext(_PAIRWISE_INPUT)[0]+'.ref'
_MAX_K = 8
_MAX_SAMPLES = 1000
# User must explicitly set environment v... |
from __future__ import annotations
from transformers import AutoTokenizer
import torch
from sklearn.utils import class_weight
import random
from datasets import load_metric
import numpy as np
from .QA_Agent import QA_Agent
from .QA_Dataset import List_QA_Datasets
random.seed(2021)
""" Official evaluation script for ... |
import re
import os
from shutil import copy2
import subprocess
from time import time_ns
from pathlib import Path
def time_add_sub(time0, time1, sub=False):
time0 = list(map(int, time0.split(':')))
time1 = list(map(int, time1.split(':')))
time0 = time0[0] * 3600 + time0[1] * 60 + time0[2]
time1 = time1... |
# -*- coding: utf-8 -*-
"""
Created on Fri May 15 01:55:22 2020
@author: balajiramesh
"""
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 10 00:25:12 2020
@author: balajiramesh
Raw : 16,319230 2,641562
Within study timeline: 14393806 2247749
Within study area and timeline: 7892752 1246896
AFter removing washout pe... |
from logging.handlers import DEFAULT_TCP_LOGGING_PORT
import os, os.path
import random
import requests
from io import BytesIO
from ctypes import windll
import win32ui
import win32con
from PIL import Image, ImageChops
from win32 import win32gui
from flask import Flask, request, Response, render_template, jsonify, send_... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Supporting functions for scraping jaap.nl
- get_max_page finds the number of summary pages to be scraped
- read_summary_page reads the houses advertised on one page
By dr.Pep, all rights reserved
"""
# Libs
import urllib.request, urllib.parse, urllib.error
fr... |
import os
import argparse
from tqdm import tqdm
import cv2
import numpy as np
import random
from PIL import Image
import glob
parser = argparse.ArgumentParser()
parser.add_argument("--option", type=str, required=True,
help="Use resize|count|group|verify|split|resample to preprocess datasets.")
pars... |
import readline
from fractions import Fraction as frac
import sys
from .tokens import tokenise, UnknownTokenError
from .parse import parse_tokens, ParsingError
from .eval import eval_parse_tree, EvalError, EvalEnvironment
from .types import Quantity
from .functions import (FUNCTIONS, UnknownFunctionError,
NoMatchi... |
from PIL import Image
def dpix(p):
return (p << 4) | p
TRANSPARENT_IDX = 0x0
LIGHT_GREEN_IDX = 0x1
LIGHT_RED_IDX = 0x2
LIGHT_BLUE_IDX = 0x3
LIGHT_BROWN_IDX = 0x4
LIGHT_STEEL_IDX = 0x5
GREEN_IDX = 0x6
RED_IDX = 0x7
BLUE_IDX = 0x8
BROWN_IDX = 0x9
STEEL_IDX = 0xA
DARK_GREEN_IDX = 0xB
DARK_RED_IDX = 0xC
DARK_BLUE_I... |
import discord, asyncio, random
from discord import ui
from discord.ext import commands
from . import utils
LONG_TIMEOUT = 1000
def disable_dm_commands(func):
#Unprefixed commands must be disabled for certain responses
async def wrapper(*args, **kwargs):
ctx = args[0] if type(args[0]) == commands.Context else ar... |
import degooged_tube.ytApiHacking as ytapih
import degooged_tube.config as cfg
from typing import Union, Tuple
from degooged_tube.subboxChannel import SubBoxChannel, ChannelLoadIssue, loadChannel, callReload
from degooged_tube import getPool
from degooged_tube.helpers import paginationCalculator
class EndOfSubBox(Exc... |
import json
import pickle
import sys
import os
import glob
import pandas as pd
import numpy as np
from tqdm import tqdm
from allennlp.predictors.predictor import Predictor
from copy import deepcopy
import torch
from torch import nn
import heapq
import argparse
import allennlp
from allennlp.common.checks import check_... |
from itertools import product
import os
import matplotlib.pyplot as plt
from multiprocessing import Pool
import numpy as np
from palettable.colorbrewer.qualitative import Paired_12, Set2_8, Dark2_8, Pastel2_8, Pastel1_9
import pandas as pd
import seaborn as sns
from scipy.signal import argrelmax
from scipy.stats impor... |
import numpy as np
import tensorflow as tf
import pickle
import logging
logger = logging.getLogger(__name__)
class DKN:
def __init__(self, transform=False, use_bert_embeddings=None, word_embeddings_path=None,
entity_embeddings_path=None, context_embeddings_path=None, use_context=False, max_click_... |
import logging
import sys
import threading
import unittest
from time import sleep
import importlib_resources
import mock
import numpy as np
from pepper.framework.application.intention import AbstractIntention
from pepper.framework.backend.abstract.microphone import AbstractMicrophone
from pepper.framework.backend.abs... |
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 9 08:41:17 2015.
@author: mje
"""
import numpy as np
import numpy.random as npr
import os
import socket
import mne
# import pandas as pd
from mne.connectivity import spectral_connectivity
from mne.minimum_norm import (apply_inverse_epochs, read_inverse_operator)
# Pe... |
from pathlib import Path
import numpy as np
import torch
from torch.nn import functional as nnfunc
from torchvision import transforms
from models.utils import get_bboxes
from utils.edge_detector import sobel
from utils.nms import nms, nms2
from pympler import asizeof
def print_state(idx, epoch, size, loss_cls, loss... |
# Python
import unittest
from unittest.mock import Mock
# ATS
from pyats.topology import Device, loader
# Metaparser
from genie.metaparser.util.exceptions import SchemaEmptyParserError
from genie.libs.parser.junos.show_mpls import (
ShowMPLSLSPNameDetail, ShowMPLSLSPNameExtensive)
class TestShowMPLSLSPNameDeta... |
import numpy as np
import torch
import torch.nn as nn
import hyper_parameters as parameters
import parameter_calculator as calculator
from torch.utils.data import DataLoader, Dataset
# The path to save the trained generator model.
GEN_PATH = 'saved_models/generator_net.pt'
# The element compositions of the 278 existin... |
"""This module contains class Declensor which allow you to use declension
model.
The model is a list of multidimensional lists (rules) with declensed suffixes.
Properties for declension are given by coordinates. Suffix for infinitive form
should always be placed with zero coordinates.
Example:
---------
| a | b | 1 c... |
# Copyright 2022 Google LLC.
#
# 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, ... |
'''
This package provides generic "IO templates."
There are two kinds of IO templates:
Cable-independent IO templates are built using higher-level JTAG or SPI code.
They are then transformed into cable-specific IO templates.
This init file contains the base class for the cable independent IO template.
This ba... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: <NAME>
# email: <EMAIL>
"""
Group astronomical images by fields and epochs.
Example of usage:
python stacking.py --path_data pathtoyourdata/ --radius 10 --deltaT 1
will stack all images in pathtoyourdata/ whose referenced RA and Dec
(CRVAL1 and CRVAL2) are... |
import argparse
import os
import pickle
import numpy as np
import pandas as pd
import torch
from PIL import PngImagePlugin
from torch.utils.data import DataLoader
from tqdm import tqdm
from benchmarks.wit.dataset_class import FoodiMLDataset
from benchmarks.wit.evaluator import adapter, compute_valid_answers
from benc... |
# Roulette.py was created by Redjumpman for Redbot
# This will create a rrgame.JSON file and a data folder
# This will modify values your bank.json from economy.py
import os
import random
import asyncio
from dataIO import dataIO
from discord.ext import commands
import Checker
class Russianroulette:
"""Allows 6... |
import tensorflow as tf
import utils.util as util
import sys
def flat_config(config):
"""flat config to a dict"""
f_config = {}
category = ['data', 'model', 'train', 'info']
for cate in category:
for key, val in config[cate].items():
f_config[key] = val
return f_config
def cre... |
from argparse import ArgumentParser
from collections import defaultdict
import glob
from importlib import import_module
import logging
from pathlib import Path
import re
import string
import time
from gensim import corpora
from gensim.models.doc2vec import Doc2Vec, TaggedDocument
from gensim.models.callbacks import Ca... |
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
# This file (neurone.py) is part of neurone_loader -
# (https://www.github.com/heilerich/neurone_loader) -
# Copyright © 2019 <NAME>. ... |
#!/usr/bin/python3 -W ignore
import gzip
import math
import pickle
from functools import partial
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pyproj
from matplotlib.collections import PatchCollection
from matplotlib.colors import LinearSegmentedColormap, Normalize
from matplotlib.patche... |
import argparse
import numpy as np
import matplotlib.pyplot as plt
from randomwalk import RandomWalk
from utils import vhat_st_agg, nab_vhat_st_agg
from off_lam_ret import OffLamRet
# from on_lam_ret import OnLamRet
from semi_grad_td_lam import SemiGradTDLam
from true_online_td import TrueOnlineTD
from mountain_car imp... |
from enum import Enum
from collections import namedtuple
import numpy as np
from PIL import Image
import networkx as nx
import matplotlib.pyplot as plt
#---------- Globals ----------
class ACTION_ENUM(Enum):
NORTH = 0
SOUTH = 1
EAST = 2
WEST = 3
inverse_action = np.array((1, 0, 3, 2), dtype=int)
Point = na... |
"""
This module is included to have a standard
text-based serialization format for the output
of Freki, namely:
A :FrekiDoc: is a collection of lines, as well as
the :FrekiBlock: elements that group lines.
A :FrekiBlock: also contains metadata regarding page
number in the original PDF and x,y coordinate positions
wit... |
#%%
from functools import partial
import jax
import jax.numpy as np
from jax import random, vmap, jit, grad
from jax.experimental import stax, optimizers
from jax.experimental.stax import Dense, Relu
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm
#%%
# Use stax to set up network initialization and ... |
# _*_ coding: utf-8 _*_
from datetime import datetime
from forms import *
import forms
from flask import render_template, url_for, redirect, flash, session, request, current_app
from flask.ext.login import login_required, current_user
from . import main
from ..models import User, Topic, City, Conference, Comment, Pe... |
import models.baselines.DNN as DNN
import _settings
import numpy as np
import torch
import pandas as pd
import os
import utils.utils as utils
import datetime
import shutil
import tqdm
import ipdb
import data.dataloader as dld
TRAIN, VALID, TEST = 'train', 'val', 'test'
def pretrain_general(X, Y, seed=_settings.RANDOM... |
import algorithms.graphical.algo_one as a1
import algorithms.graphical.algo_two as a2
import algorithms.graphical.algo_three as a3
import algorithms.graphical.algo_four as a4
import algorithms.graphical.algo_five as a5
import algorithms.graphical.algo_six as a6
import paho.mqtt.client as mqtt
import pickle
import subpr... |
from .models import db, User, Pdf
import json
from mimetypes import MimeTypes
import base64
import os
from time import perf_counter
import requests
from flask_cors import cross_origin
import jwt
from functools import wraps
from datetime import datetime, timedelta
from werkzeug import secure_filename
from flask import B... |
"""
Entrypoint for running the bot a single time.
"""
import asyncio
import json
from typing import Any, Dict, List, Tuple
from dydx3 import Client
from dydx3.constants import API_HOST_ROPSTEN, API_HOST_MAINNET
from dydx3.constants import NETWORK_ID_ROPSTEN, NETWORK_ID_MAINNET
from constants import ApiNames, DEFAULT... |
from googleapiclient.http import _should_retry_response
# import itertools
import logging
from threading import Thread, Lock
# import queue
import atexit
import time
from gdriveshare import ipipe
MAX_RETRY_PER_REQUEST = 5
log = logging.getLogger(__name__)
'''
class BatchRequestSender(Thread):
def __init__(self... |
import os
import pathlib
import random
import string
from typing import Optional, Tuple
import capstone
import keystone
import unicorn
from PyQt6.QtWidgets import QTextEdit
import cemu.core
from cemu.arch import (Architecture, Architectures, Endianness, is_aarch64,
is_arm, is_arm_thumb, is_mips... |
import torch
from torch import nn, optim
from torch.nn import functional as F
from torchvision import transforms
import math
import kornia.augmentation as K
def sinc(x):
return torch.where(x != 0, torch.sin(math.pi * x) / (math.pi * x), x.new_ones([]))
def lanczos(x, a):
cond = torch.logical_and(-a < x, x < ... |
# -*- coding: utf-8 -*-
"""
Functions for transforming between color spaces.
Change log:
2015/10/09 -- compand, inverse_compand added; <EMAIL>
"""
import copy
import numpy
import imageutils
import whitepoint
#
# module constants
#
_lab_epsilon = 0.008856
_lab_kappa = 903.3
#
# module utilities
#
def _safe_divid... |
import errno
from functools import partial
import glob
import os
import uuid
import numpy as np
import pathlib2 as pathlib
import renderapi
from asap.utilities.pillow_utils import Image
from asap.materialize.render_downsample_sections import (
RenderSectionAtScale)
from asap.dataimport.schemas import (
MakeMo... |
import os, copy
import sys
from Bio.PDB import *
import chainfunctions, modelfunctions
################
# Functions employed for processing the different input files
################
##### Input file parsing functions
## These are different functions that retrieve the uploaded files, be it multiple interacting chai... |
# -------------------------------#
# Env variables assigned
# GIN_SERVER=http://172.19.0.2:3000
# GIT_SSH_COMMAND=ssh -i gin-proc/ssh/gin_id_rsa
# -------------------------------#
import requests
import os
from shutil import rmtree
import tempfile
from config import ensureConfig
from subprocess import call
from cr... |
#!/usr/bin/env python3
# -*- coding: utf8 -*-
from bookmarks import Bookmarks, Record, StanzaFormatter
import os, re, sys, stat, dateutil.parser, configargparse, webbrowser
import urllib.parse, urllib.request, urllib.error, datetime
def html_unescape(string):
try:
import html
except ImportError:
... |
'''
Train the double-prong model on t_1 mode
Input data: evidential grids produced from subsampling the waymo dataset for moving objects
'''
import importlib
import os
import tensorflow as tf
import random as rn
import matplotlib.pyplot as plt
import hickle as hkl
import numpy as np
import pdb
import argparse
impor... |
# -------------------------------------------------------------------------------------------------
# scientific
from PyQuantum.Tools.PlotBuilder2D import *
from math import sqrt, exp, pi
import plotly.graph_objs as go
import numpy as np
# --------------------------------------------------------------------------------... |
import tensorflow.keras.backend as K
import tensorflow as tf
import numpy as np
# alpha = 1, beta = 0.03, margin = {0.5, 1, 2, 4, 8}
class modals(tf.keras.Model):
def make_feature_extractor(self, layers, input_dim, hidden_size):
inputs = tf.keras.Input(shape=(None, input_dim))
x = inputs
f... |
from datetime import date
from functools import partial
from os import remove
from os.path import exists
import matplotlib.pyplot as plt
from kivy.app import App
from kivy.core.window import Window
from kivy.uix.behaviors import ToggleButtonBehavior
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.button import ... |
import logging
import math
import os
from abc import abstractmethod, ABC
from typing import Sequence, Tuple, List, Union
import numpy as np
import pandas as pd
from .util import cache
from .util.cache import DelayedUpdateHook
from .util.string import objectRepr
from .util.typing import PandasNamedTuple
log = loggin... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Module: inference
Created: 2020-08-19
Description:
inference functions for pytorch serving container
"""
import datetime
import json
import os
import sys
import tempfile
import boto3
import torch
import yaml
from sagemaker_inference import content_types, error... |
__version__ = '0.1.5'
import argparse
import cleanlog
import warnings
import sys
import time
import os
import numpy as np
import pandas as pd
from . import util
from . import diffusion
from collections import defaultdict
from .const import DIRECTION
from scipy.stats import beta
from scipy.stats import combine_pvalu... |
"""
Image alignment.
:func:`~apply_transform_wcs()`: align an image based on WCS.
:func:`~apply_transform_stars()`: align an image based on pixel coordinates of
1, 2, or more stars.
"""
from typing import List as TList, Tuple, Union
from numpy import (
array, empty, float32, full, indices, ma, mgrid, ndarray, on... |
"""
Deep Galerkin Method: https://arxiv.org/abs/1708.07469
"""
import torch
import torch.nn as nn
import numpy as np
import tqdm
from lib.options import BaseOption
class DGM_Layer(nn.Module):
def __init__(self, dim_x, dim_S, activation='Tanh'):
super(DGM_Layer, self).__init__()
if a... |
"""
Module for computing mask defining great circle arc between two endpoints
Specifically for stereographic projection!
"""
import warnings
import numpy as np
import xarray as xr
try:
from ecco_v4_py import scalar_calc
except ImportError:
pass
# ---------------------------------------------------------------... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 22 11:08:12 2018
@author: irhamta
Based on Leaf & Melia (2018) paper
"""
# import necessary modules
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# read lensing data which is taken from Leaf et al. (2018)
data = pd.read_... |
#!/usr/bin/env python
import ast
import os
import numpy as np
from scipy.stats import gamma
import mapel.elections.models.mallows as mallows
from mapel.main._glossary import *
from mapel.main._inner_distances import hamming
from mapel.elections.models_ import generate_approval_votes, store_votes_in_a_file
from mape... |
import os
import pygame
import unicodedata
from pygame.locals import *
pygame.init()
FRAME_SIZE = (750, 560)
FRAME_PADDING = (10, 10)
mainFrame = pygame.display.set_mode(FRAME_SIZE)
pygame.display.set_caption('Play Fair Cipher')
SQUARE_SIZE = 100
SQUARE_MARGIN = 10
SQUARE_FONT = pygame.font.Font(None, 65)
TEXT_FONT... |
"""
panoptes executable
Created on 02/05/2020
@author: RH
"""
import os
import sys
import tensorflow as tf
import pandas as pd
from openslide import OpenSlide
import numpy as np
import cv2
import time
import matplotlib
import panoptes.prep as prep
import panoptes.cnn as cnn
import panoptes.sample_prep as sample_prep
... |
import json
import requests
import pykintone.structure as ps
from pykintone.application_settings.base_administration_api import BaseAdministrationAPI
import pykintone.application_settings.setting_result as sr
class Administrator(BaseAdministrationAPI):
def __init__(self, account, api_token="", requests_options=(... |
import math
import cv2
import base64
import numpy as np
from ndu_gate_camera.utility import geometry_helper
from ndu_gate_camera.utility.ndu_utility import NDUUtility
def image_h_w(image):
# h, w = image.shape[:2]
return image.shape[:2]
# Boyut değişikliğine en uygun interpolation yöntemi ile resize eder.
... |
from random import shuffle
import glob
import sys
import numpy as np
import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.models import model_from_json
from tensorflow.keras.optimizers import Adam
dirsep = '/'
csvdelim = ','
pathData='./ogle/data'
pathWeight = './models/cnn.h5' # Th... |
import numpy as np
import json
import matplotlib.pyplot as plt
from PIL import Image
import seaborn as sns
sns.set(font_scale=1.5, style='white')
from sklearn.utils import compute_class_weight
from sklearn.metrics import classification_report, confusion_matrix, roc_curve, roc_auc_score, precision_recall_curve, auc, f1... |
'''
Create BIO annotations from struct file
'''
import os
import json
import codecs
# NER
def struct_to_bio(args):
struct_ann_path = args.struct_ann_path
output_dir = args.output_dir
oversampling_rate = args.oversampling_rate
separate_docs = args.separate_docs
bio_dict = struct_to_bio_dict(stru... |
import torch
from transformers import MarianMTModel, MarianTokenizer
import string
import pandas as pd
import spacy
from spacy import displacy
import difflib
from difflib import Differ, SequenceMatcher
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
en_ROMANCE_model_name = 'Helsinki-NLP/opus-mt-e... |
"""
Content uploaded to amazon Glacier is tar-zipped and encrypted.
For large files, tar a dummy and restore the content in chunks of the original.
"""
import os
import datetime
from abc import ABC
from collections import OrderedDict, namedtuple
from contextlib import contextmanager
import sqlite3
from .datatypes impor... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import datetime
import numpy as np
from pyorbital import tlefile, orbital
from pyorbital.tlefile import Tle
#def read_all_tles_from_file(platform, tles_file):
# platform = platform.strip().upper()
# tles = []
# fp = open(tles_file)
# for l0 in fp:
# l1, l2 = fp.next(),... |
import sys
import os
import numpy as np
import random
import time
import pickle
import fitness
from display_room import display_room
import fitness
from utils import print_iter_msg
from utils import stopwatch
# ----------------------------------------------------------------
# Generate the room, from the specified pa... |
from tqdm import tqdm
from utils.utils1 import *
import data.common.eval_cal as eval_cal
import torch
def step(split, opt, actions, dataLoader, model, criterion, optimizer=None):#, key_index=None
# initialize some definitions
num_data_all = 0
loss_all_sum = {'loss_gt':AccumLoss(), 'loss_diff':AccumLos... |
"""Operates on data from AEMO. The first step was to read the source data and
construct a single file for further analysis. That single file was intended to
be an Apache Parquet but I have wasted a couple of hours trying to make that
work (the datetime field made it very difficult).
Definition files: https://visualisa... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# <NAME>
# Department of Political Science
# University of California, Davis
"""
judges.LoadData v2.0
This script takes the Federal Judicial Center's Biographical Directory of
Article III Federal Judges and generates a json file formatted for easy
import/use in other fed... |
import requests
import json
from sys import stdout
from math import ceil
from datetime import datetime
import os
_ERROR_LOG_FILE = 'portal_error_log.txt'
_MB_PER_CHUNK = 64
_B_PER_MB = 1048576
_CHUNK_SIZE = _MB_PER_CHUNK * _B_PER_MB # Download 128 MB at a time
## Utility function to write to the error log file
de... |
import math
import torch
import random
import numpy as np
from pathlib import Path
from typing import Tuple
from torch.optim.optimizer import Optimizer
from torch.optim.rmsprop import RMSprop
from torch.utils.tensorboard.writer import SummaryWriter
from datetime import datetime, timezone
from copy import deepcopy
fro... |
# coding: utf8
import os
import sys
import ssl
import re
import logging
from string import punctuation
from urllib.request import Request, urlopen, quote
from bs4 import BeautifulSoup
import requests
import socket
import json
from genius.song import Song
from genius.artist import Artist
logger = logging.getLogger(_... |
# -*- coding: utf-8 -*-
'''
Code for ground truth evaluation of sybil detection with photos with Residual Network model
The implementation of the Residual-50 model is based on
https://github.com/flyyufelix/cnn_finetune/blob/master/resnet_50.py
* For ground truth evaluation, large vendors will be split into two pesudo... |
# Author: <NAME>
from kernel.type import TyInst
from kernel import term
from kernel.term import Term, Var, Bound, Inst
from kernel.thm import Thm, InvalidDerivationException
from kernel import theory
from kernel.proofterm import ProofTerm, refl
from logic import matcher
from util import typecheck
class ConvException... |
import numpy as np
import matplotlib.pyplot as plt
def plot_data(xs, ys, c, lw, label, linestyle, **kwargs):
if ys is not None:
plt.plot(xs, ys, c=c, lw=lw, linestyle=linestyle, label=label, **kwargs)
else:
plt.plot(xs, c=c, lw=lw, linestyle=linestyle, label=label, **kwargs)
def plot_measure... |
# Copyright (c) 2015, The MITRE Corporation. All rights reserved.
# See LICENSE.txt for complete terms.
# builtin
import sys
import json
import collections
# external
import lxml.etree
from mixbox.vendor.six import iteritems, itervalues
# internal
import sdv
import sdv.codes as codes
import sdv.utils as utils
import... |
#!/usr/bin/env python3
# coding=utf-8
# vim: ai ts=4 sts=4 et sw=4 ft=python
#
# # Released under MIT License
#
# Copyright (c) 2017 Slavfox.
#
# 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... |
#!/usr/bin/env python3
# part of the Appeal software package
# Copyright 2021 by <NAME>
# All rights reserved.
#
# 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, includi... |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... |
"""
LUNAR
Lunar landing simulation
Ported by <NAME>
"""
import collections
import math
PAGE_WIDTH = 64
COLUMN_WIDTH = 2
SECONDS_WIDTH = 4
MPH_WIDTH = 6
ALT_MI_WIDTH = 6
ALT_FT_WIDTH = 4
MPH_WIDTH = 6
FUEL_WIDTH = 8
BURN_WIDTH = 10
SECONDS_LEFT = 0
SECONDS_RIGHT = SECONDS_LEFT + SECONDS_WIDTH
ALT_LEFT = SECONDS_RI... |
from django.db import connection
from django.contrib.gis.gdal import GDAL_VERSION
from django.contrib.gis.tests.utils import mysql, no_mysql, oracle, postgis, spatialite
from django.utils import unittest
test_srs = ({'srid' : 4326,
'auth_name' : ('EPSG', True),
'auth_srid' : 4326,
... |
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