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from base64 import b64decode
import logging
from django.core.exceptions import SuspiciousOperation
from django.core.files.uploadedfile import SimpleUploadedFile
from django.db import transaction
from django.db.models import Q
from django.utils.crypto import get_random_string
from zentral.contrib.inventory.models import... |
import time
import shutil
import dlib
import numpy as np
import PIL.Image
import torch
from torchvision.transforms import transforms
import dnnlib
import legacy
from configs import GENERATOR_CONFIGS
from dlib_utils.face_alignment import image_align
from dlib_utils.landmarks_detector import LandmarksDetector
from tor... |
# Copyright 2016 Google Inc. 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 applicable law or a... |
import math
from collections import OrderedDict
from functools import partial
import torch.nn as nn
import torch
from torch.nn import Module as Module
from src.models.tresnet.layers.anti_aliasing import AntiAliasDownsampleLayer
from .layers.avg_pool import FastGlobalAvgPool2d
from src.models.tresnet.layers.... |
import requests
import bs4
import sqlite3
import pandas as pd
hr_db_filename = 'C:/Users/Jeff/Google Drive/research/Hampton Roads Data/Time Series/' \
'hampt_rd_data.sqlite'
def get_id(typ, data):
"""
gets either the siteid or variableid from the db
:param typ: String. Either "Site" or "... |
from sys import argv
import Base
from Base import Net
from Base import Node, Board
import Base_Test
import numpy as np
import copy
import atexit
import matplotlib.pyplot as plt
import Base_Test
from netlist_parser import parse_file
def show_graph():
# b = Board(0, nets, min_cost_placement, 12, 12)
... |
"""This module provides a generalized implementation of UNet.
See the `UNet` class docstring for more information.
"""
import attr
from typing import List, Optional, Text
from sleap.nn.architectures import encoder_decoder
from sleap.nn.config import UNetConfig
import numpy as np
import tensorflow as tf
@attr.s(auto... |
import sys, struct, random, string, meterpreter_bindings
# A stack of this stuff was stolen from the Python Meterpreter. We should look
# to find a nice way of sharing this across the two without the duplication.
#
# START OF COPY PASTE
#
# Constants
#
# these values will be patched, DO NOT CHANGE THEM
DEBUGGING = F... |
import sys
sys.path.append('..')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy.optimize
import projgrad
from scipy.stats.mstats import gmean
import matplotlib
colors = matplotlib.rcParams['axes.prop_cycle'].by_key()['color']
black = matplotlib.rcParams['axes.labelcolor']
tcellcol... |
from veroviz._common import *
from veroviz._validation import valCreateArcsFromLocSeq
from veroviz._validation import valCreateArcsFromNodeSeq
from veroviz._createEntitiesFromList import privCreateArcsFromLocSeq
def createArcsFromLocSeq(locSeq=None, initArcs=None, startArc=1, objectID=None, leafletColor=config['VRV_D... |
import numpy as np
import time
import cv2
def sample_angle():
d = np.random.binomial(1,0.5)
theta = np.random.uniform(np.pi/12, np.pi - np.pi/12) * (-1)**d
return theta
class Player():
def __init__(self, x, board_size, bat_size, dtheta = np.pi/12, dy = 3):
self.x = x
self.y = np.... |
"""
Types used to represent a full function/module as an Abstract Syntax Tree.
Most types are small, and are merely used as tokens in the AST. A tree diagram
has been included below to illustrate the relationships between the AST types.
AST Type Tree
-------------
*Basic*
|--->Assignment
| |--... |
import sys
print(sys.path)
import os
from pathlib import Path
import settings
print('os.getenv', os.getenv('LB_WORKING_FOLDER_NAME'))
print('change projects in .env')
import os
from util import Util
from app_settings import AppSettings, AppSettingsTest
#from app_settings import AppSettings
from text_file import Text... |
"""Python wrappers around TensorFlow ops.
This file is MACHINE GENERATED! Do not edit.
"""
import collections as _collections
from tensorflow.python.eager import execute as _execute
from tensorflow.python.eager import context as _context
from tensorflow.python.eager import core as _core
from tensorflow.python.framew... |
from pytororo.pytororo import stone_board, black_stone, white_stone, sticky_rice_cake, sticky_rice_cake_board, print_stone_board, print_cake_board
def go():
print('Trace | Start.')
board = """\
.x...o......./
ooxxxxoo...../
.oox..x..o.../
o.oox..x...../
oooox....o.../
xxxx..x.o..../
............./
.......x... |
"""Helper functions for finding and plotting a pareto front."""
from os.path import join
from typing import Dict, MutableMapping, Optional
# import sys
# from PyQt5.QtWidgets import QApplication
import numpy as np
from plotly import offline
import plotly.express as px
import plotly.graph_objects as go
import matplotl... |
#!/usr/bin/env python3
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
import rospy
import rospkg
from visualization_msgs.msg import Marker, MarkerArray
from sensor_msgs.msg import Image
from statek_ml.msg import Dyna... |
import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
import torch.nn.init as weight_init
import torch
__all__ = ['MultipleBasicBlock','MultipleBasicBlock_4']
def conv3x3(in_planes, out_planes, dilation = 1, stride=1):
"3x3 convolution with padding"
return nn.Conv2d(in_planes, out_planes, ... |
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 15 01:45:23 2018
@author: JAE
"""
import torch
import torch.multiprocessing as mp
import random
import numpy as np
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from collections import namedtuple, deque
import gym
import copy
import ... |
##
## © Copyright 2021- IBM Inc. All rights reserved
# SPDX-License-Identifier: MIT
##
# example of accessing the module structure API https://jazz.net/wiki/bin/view/Main/DNGModuleAPI
# prints the module content with indenting corresponding to headings and calculated section number
# NOTE NOTE NOTE the section number ... |
# ------------------------------------------------------------------------------
# Experiment class that tracks experiments with different configurations.
# The idea is that if multiple experiments are performed, all intermediate
# stored files and model states are within a directory for that experiment. In
# addition,... |
import os
import re
import csv
import codecs
import numpy as np
import pandas as pd
from nltk.corpus import stopwords
from nltk.stem import SnowballStemmer
from string import punctuation
from gensim.models import KeyedVectors
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_... |
import functools
import ipaddress
import json
import logging
import re
import operator
import testinfra
import time
from typing import Optional, Dict
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
import pytest
LOGGER = logging.getLogger(__name__)
... |
import os
import torch
from PIL import Image
from skimage import io
from torch.utils.data import Dataset
import h5py
from .upna_preprocess import *
from .utils import *
from bingham_distribution import BinghamDistribution
def make_hdf5_file(config, image_transform):
dataset_path = config["preprocess_path"]
csv... |
import operator
import re
from datetime import date, datetime, timedelta
from crispy_forms.bootstrap import FormActions
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Field, Layout, Submit
from django import forms
from django.contrib.auth import get_user_model
from django.contrib.auth.model... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to implement the network in Google Colab for access to hardware
accelerator i.e. GPUs. With GPUs, the training is accelerated manifold.
@author: rpm1412
"""
#%% Cell 1: Import libraries
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axe... |
#!/usr/bin/env python
# coding: utf-8
"""script that generates source data csvs for searchstims training history figures"""
from argparse import ArgumentParser
from pathlib import Path
import pandas as pd
import pyprojroot
from searchnets.tensorboard import logdir2df
def get_net_number_from_dirname(dirname):
re... |
"""
pilots.py
Methods to create, use, save and load pilots. Pilots
contain the highlevel logic used to determine the angle
and throttle of a vehicle. Pilots can include one or more
models to help direct the vehicles motion.
"""
import os
import shutil
import numpy as np
import keras
import matplotlib
matplotlib.use... |
import math
import torch
import torch.nn as nn
from .ocean import Ocean_
from .oceanplus import OceanPlus_
from .oceanTRT import OceanTRT_
from .siamfc import SiamFC_
from .connect import box_tower, AdjustLayer, AlignHead, Corr_Up, MultiDiCorr, OceanCorr
from .backbones import ResNet50, ResNet22W
from .mask import MMS,... |
import os
import math
import numpy as np
#import itertools
#import open3d as o3d
# import pandas as pd
# from tqdm import tqdm
# import joblib
# import time
import rosbag
import sensor_msgs.point_cloud2 as pc2
import torch
import yaml
'''
-
name: "x"
offset: 0
datatype: 7
count: 1
-
name: "y"
offset: 4
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from mock import MagicMock, patch
from ...config import settings
from .. import DataCollection, Data, SubsetGroup
from .. import subset
from ..subset import SubsetState
from ..subset_group import coerce_subset_groups
from .test_state ... |
# Released under The MIT License (MIT)
# http://opensource.org/licenses/MIT
# Copyright (c) 2013-2015 SCoT Development Team
import unittest
from importlib import import_module
import numpy as np
from numpy.testing import assert_allclose
import scot
from scot import varica, datatools
from scot.var import VAR
class ... |
from __future__ import annotations
import re
from abc import abstractmethod, ABCMeta
from collections.abc import Sequence
from email.headerregistry import Address, AddressHeader
from re import Pattern
from pymap.mime import MessageContent
from pymap.parsing.message import AppendMessage
from sievelib.commands import ... |
# -*- coding: utf-8 -*-
from ctypes import addressof
import cv2
import numpy as np
import pickle
import requests
import json
import urllib
import hashlib
import urllib.parse
from hashlib import md5
import sys
from xlrd import open_workbook # xlrd用于读取xld
import xlwt # 用于写入xls
import PIL
from PIL import ImageFile
Imag... |
""" Helper class and functions for loading KITTI objects
Author: <NAME>
Date: September 2017
"""
import os
import sys
import numpy as np
import cv2
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
ROOT_DIR = os.path.dirname(BASE_DIR)
sys.path.append(os.path.join(ROOT_DIR, "mayavi"))
import kitti_util as utils
i... |
#!/usr/bin/python3
import os
import sys
import numpy as np
import rospy
import ros_numpy
import tf2_ros
from shapely.geometry import Point
from geometry_msgs.msg import PoseWithCovarianceStamped
from sensor_msgs.msg import PointCloud2
from nav_msgs.msg import Odometry
from darknet_ros_msgs.msg import B... |
# Copyright (c) 2013 Tencent Inc.
# All rights reserved.
#
# Author: <NAME> <<EMAIL>>
# Created: September 27, 2013
"""
This module defines cu_library, cu_binary and cu_test rules
for cuda development.
"""
from __future__ import absolute_import
from __future__ import print_function
import os
from blade import bu... |
#!/usr/bin/env python
#%%
import pandas as pd
import regex as re
import argparse, os, csv
import unicodedata
#%%
def validate_file(f):
if not os.path.exists(f):
raise argparse.ArgumentTypeError("{0} does not exist".format(f))
return f
#%%
tags=list('.?!,;:-—…')
parentheses=r'\([^)(]+[^)( ] *\)'
parenthe... |
import argparse
import os
import cv2
import csv
import sys
import operator
import numpy as np
import config as cf
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision
from torchvision import datasets, models, transforms
from networks import *
from torch.autograd import Variable
f... |
# Copyright 1996-2019 Cyberbotics Ltd.
#
# 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... |
import networkx as nx
import matplotlib.pyplot as plt
#######################################################################
class Node:
def __init__(self, value):
self.value = value
self.next = None
class Queue():
def __init__(self):
self.front = None
self.rear = None
... |
#!/usr/bin/env python
# mirto_code_main.py
import numpy as np
from scipy.linalg import lu , solve
import cProfile, pstats
import mirto_code_configuration
import mirto_code_compute_F
import sys
import ctypes
# Empty class to store result
class mirto_state:
pass
class mirto_residuals:
pass
class mirto_history:
d... |
import time
import numpy as np
import matplotlib.pyplot as plt
import torch
from torch import nn
from torch.utils.data import TensorDataset, DataLoader
from torchvision.utils import save_image
class Generator(nn.Module):
def __init__(self, n_noise=62, n_disc=10, n_cont=2):
super().__init__()
... |
from pyiron_atomistics import Project as PyironProject
import numpy as np
from collections import defaultdict
from spin_space_averaging.sqs import SQSInteractive
from pyiron_contrib.atomistics.atomistics.master.qha import QuasiHarmonicApproximation
def get_bfgs(s, y, H):
dH = np.einsum('...i,...j,...->...ij', *2 ... |
import json
import logging
import time
from datetime import timedelta, datetime
from aliyunsdkcore.client import AcsClient
from aliyunsdkpolardb.request.v20170801.DescribeSlowLogRecordsRequest import DescribeSlowLogRecordsRequest
from component import mymysql
from config import app_conf
from service import serious_sq... |
import datetime
import urllib.request, urllib.parse, urllib.error
from http.cookiejar import CookieJar
import os
import re
from .central import CentralBase
from ..utils import utils
class CSLWeekly(CentralBase):
def __init__(self, name, storage):
CentralBase.__init__(self, name, storage)
self.base... |
import json
import os
from tqdm import tqdm
import datetime
from hackathon.utils import to_datetime, read_data_from_file
from enum import Enum
WORLD_TICK_PER_SECONDS = 20
MISSION_TIME_IN_SECONDS = 600
OBSERVATIONS_FILENAME = "observations.txt"
LEVER_FILENAME = "lever_event.txt"
TRIAGE_FILENAME = "triage_event.txt"
ROO... |
from tslearn.utils import to_time_series_dataset
from tslearn.clustering import silhouette_score
import tslearn.clustering as clust
from scipy import signal
import itertools
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from gippy import GeoImage
import gippy.algorithms as alg
import re
from os... |
#!/usr/bin/env python3
"""
comic_snagger
Scrapes https://www.readcomics.io for comic book images
"""
import os
import shutil
import textwrap
from collections import namedtuple
from types import ModuleType
from typing import List, NamedTuple, Tuple
import requests
from bs4 import BeautifulSoup # type: ignore
from req... |
import argparse
import numpy as np
import pandas as pd
import os
import pickle
import langdetect as lang
import time
from datetime import datetime
import json
directory = 'data/twitter'
outfile = 'output.csv'
verbose = False
def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument('direct... |
# -*- coding: utf-8 -*-
import json
import datetime
import requests
from django.conf import settings
from django.contrib.gis.geos import Point
from django.utils.translation import ugettext as _
from geotrek.common.parsers import (AttachmentParserMixin, Parser,
GlobalImportError)
f... |
import subprocess
import pandas as pd
import io
import random
from multiprocessing import Pool, Value, cpu_count
import time
import os
import json
import numpy as np
PARAM_DIR = "./params"
GENERATION_SIZE = 4*12
MUTATION_SCALE = .5
N_ELITE = 2
POTTS_SEED = 1
CHANGE_POTTS_SEED_PER_GEN = True
GENERATION_NO = 1
np.random... |
from bisect import bisect
from biicode.common.utils.bii_logging import logger
import difflib
from biicode.common.exception import BiiException
def _lcs_unique(a, b):
# set index[line in a] = position of line in a unless
# a is a duplicate, in which case it's set to None
index = {}
for i in xrange(len(... |
""" nftfwls - List data from nftfw blacklist database
"""
import sys
import datetime
from signal import signal, SIGPIPE, SIG_DFL
from pathlib import Path
import argparse
import logging
from prettytable import PrettyTable
from .fwdb import FwDb
from .config import Config
from .geoipcountry import GeoIPCountry
from .sta... |
import numpy as np
import tensorflow as tf
from collections import deque, namedtuple
from typing import Tuple
import random
Transition = namedtuple('Transition',
('actions', 'rewards', 'gradients', 'data', 'targets'))
logs_path = '/tmp/tensorflow_logs/example/'
class ReplayMemory(object):
... |
from flask import Flask, flash, redirect, render_template, request, session, abort, g
import os
import json
import pandas as pd
import ngs_player_tracking
import math
app = Flask(__name__)
##ext_file_path = 'D:/Sports Analytics/sportradar/'
data_file_path = '../big_data_bowl_2021/' #'../../NFL/big_data_bowl_2021/'
df_... |
import logging
from datetime import timedelta
from typing import Optional, Iterable, List
from homeassistant.components.climate import SUPPORT_TARGET_TEMPERATURE, SUPPORT_PRESET_MODE, HVAC_MODE_OFF, \
HVAC_MODE_HEAT
from homeassistant.components.climate.const import HVAC_MODE_AUTO, HVAC_MODE_COOL, CURRENT_HVAC_IDL... |
from __future__ import annotations
import math
from typing import List, Tuple
import numpy as np
class last_touch:
def __init__(self):
self.location = Vector()
self.normal = Vector()
self.time = -1
self.car = None
def update(self, packet: GameTickPacket):
touch =... |
import html
import os
import re
from itertools import chain
import mistletoe
import mistletoe.block_token as block_token
import mistletoe.span_token as span_token
from mistletoe.html_renderer import HTMLRenderer
from ..constants.code_extensions import Extensions
from ..parse.parse_markdown.file_imports import process... |
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 10 15:31:17 2016
Last update on Saturday 17 March 2018
@author: michielstock
Kruskal's algorithm for finding the maximum spanning tree
"""
from union_set_forest import USF
import heapq
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
blue ... |
import ast
from functools import partial
from syn.base_utils import setitem, pyversion
from syn.type.a import List
from syn.five import STR, xrange
from .base import PythonNode, Attr, AST, ACO, CC, Statement, Expression, \
resolve_progn, GenSym, ProgN, AsValue, ResolveProgN, logging
from .literals import Tuple, Lis... |
import argparse
import contextlib
import math
import os
import random
import shutil
import uuid
from pathlib import Path
from typing import Tuple
import cv2
import imageio
import joblib
import numpy as np
from matplotlib import pyplot as plt
from numba import njit, prange
from tqdm import tqdm
# Parameters
brightness... |
#<NAME>
#ilk değer x=0 noktası olarak alındı
from math import sqrt
#verilen sayıları m.dereceden polinoma yaklaştırır
def yaklastir(sayi_dizisi,m=2):
n = len(sayi_dizisi)
x_uzeri_toplamlari=[]# [0]->xtoplam [1]->x**2toplam [2]->x**3toplam...
for i in range(2*m):#toplamları ekleneceğinden tüm elema... |
#
# Copyright 2015 <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, sof... |
import bpy
from mathutils import Vector, Matrix
from math import radians
from .properties import *
from ..tools.blenderhelper import find_parent
def can_draw_gizmos(context):
aobj = context.active_object
selected_archetype = get_selected_archetype(context)
if aobj and selected_archetype:
if not se... |
# Run this app with `python app.py` and visit http://127.0.0.1:8050/ in your web browser.
# This is the main file. It contains the dash setup and callbacks.
from os import environ
import dash
import pandas as pd
import plotly.graph_objects as go
from dash import dash_table, dcc, html
from dash.dependencies import In... |
import torch
import torch.nn as nn
import torch.nn.functional as F
def weights_init(m):
if isinstance(m, nn.Conv2d) or isinstance(m, nn.Linear):
nn.init.xavier_uniform(m.weight.data)
nn.init.constant(m.bias, 0.1)
class LossFn:
def __init__(self, cls_factor=1, box_factor=1, landmark_factor=1... |
import argparse
import logging
import ipdb
import os
import sys
import torch
import random
import importlib
import yaml
from box import Box
from pathlib import Path
import resource
rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
resource.setrlimit(resource.RLIMIT_NOFILE, (2048, rlimit[1]))
import src
def main(ar... |
"""Runs' on-db store."""
from collections import defaultdict
from dataclasses import dataclass
from datetime import datetime
from functools import lru_cache
from typing import Any, Dict, List, Optional, cast
import sqlalchemy
from pydantic import parse_obj_as
from opentrons.util.helpers import utc_now
from opentrons.... |
# nuScenes dev-kit.
# Code written by <NAME>, 2020.
import colorsys
from typing import Any, Dict, List, Tuple, Callable
import cv2
import numpy as np
from pyquaternion import Quaternion
from nuscenes.prediction import PredictHelper
from nuscenes.prediction.helper import quaternion_yaw
from nuscenes.prediction.input_r... |
import unittest
import sys
import os
import numpy as np
import SciFiReaders as sr
import sidpy
import wget
wget.download("https://github.com/pycroscopy/SciFiDatasets/raw/main/data/Bias-Spectroscopy041.dat",
out = 'Bias-Spectroscopy.dat')
wget.download("https://github.com/pycroscopy/SciFiDatasets/blob/main/data/COOx_... |
import pandas as pd
import numpy as np
import category_encoders as ce
import datetime
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
# Make NumPy printouts easier to read.
np.set_printoptions(precision=3, suppress=True)
def rearrange_date(df):
"""
Merges ... |
import hashlib
import shutil
import sys
import os
import tarfile
import zipfile
from urllib.error import HTTPError, URLError
from urllib.request import urlopen
from shutil import copyfileobj
if sys.version_info >= (3, 6):
def _path_to_string(path):
if isinstance(path, os.PathLike):
return os.f... |
"""Calculate morris indices for models with dependent parameters.
We convert frequently between iid uniform, iid standard normal and multivariate
normal variables. To not get confused, we use the following naming conventions:
-u refers to to uniform variables
-z refers to standard normal variables
-x refers to multiv... |
from contextlib import ContextDecorator
from collections import defaultdict
import copy
import threading
class OptPipelines:
pipelines = defaultdict(None)
@classmethod
def register_pipeline(cls, name, func):
assert name not in cls.pipelines, f"The pipeline {name} had already registered"
c... |
import sys, getopt, json, os, shutil, re
from urllib import parse
class JournalDirectory:
id = ''
name = ''
parent = None
path = ''
class JournalEntry:
id = ''
name = ''
content = ''
directory = ''
path = ''
# Core
def run_export(pathToWorldDirectory, shouldBeS... |
import unittest
import numpy as np
from cdbw import CDbw
epsilon = 1e-16
# 1 - 3D DATA TEST 1
data_3d_1 = np.load("xyz.npy")
labels_3d_1 = np.load("labels.npy")
# 2 - 3D DATA TEST 2
data_3d_2 = np.load("xyz1.npy")
labels_3d_2 = np.load("labels1.npy")
# 3 - 2D BLOBS DATA TEST
data_2d_bl = np.load("xyzbl.npy")
labels... |
# -*- coding: utf-8 -*-
from PyQt4 import QtTest
from acq4.devices.OptomechDevice import OptomechDevice
from .FilterWheelTaskTemplate import Ui_Form
from acq4.devices.Microscope import Microscope
from acq4.util.SequenceRunner import SequenceRunner
from acq4.devices.Device import *
from acq4.devices.Device import TaskGu... |
from functools import lru_cache
import json
import logging
import math
import re
from typing import Generator, List, Tuple, Union
import boto3
import humanfriendly
from .qc_resources import handle_qc_check
from .util import CoreStack, Step, Resource, State, make_logical_name, do_param_substitution,\
time_string_t... |
class BST_TreeNode:
def __init__(self,val):
self.data = val
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self):
self.root = None
def isNode(self,val):
tempNode = self.root
while(tempNode!=None):
... |
from django.db import models
from django.core.exceptions import ValidationError
class TabSettings(models.Model):
key = models.CharField(max_length=20)
value = models.IntegerField()
def __unicode__(self):
return "%s => %s" % (self.key,self.value)
@classmethod
def get(cls, key, default=None)... |
import six
from libtaxii.constants import (
CT_DATA_FEED, CT_DATA_SET,
SS_ACTIVE, SS_PAUSED, SS_UNSUBSCRIBED,
RT_FULL, RT_COUNT_ONLY
)
from .utils import is_content_supported
class Entity(object):
'''Abstract TAXII entity class.
'''
def __repr__(self):
pairs = ["%s=%s" % (k, v) for k... |
import os
import h5py
import pandas as pd
import copy
from RAMAC import extract_feature
import torchvision
import torchvision.transforms as transforms
import torch.utils.data as data
import numpy as np
from PIL import Image, ImageChops
import torch
from diffusion import Diffusion
from resnet import resnet101
from cirto... |
from __future__ import absolute_import, division, print_function, unicode_literals
__metaclass__ = type
import random
import os
import math
import h5py
import cv2
import numpy as np
import sqlite3
from .util import static_vars
from .task import DEBUG
from .google_storage import downloadIfAvailable
POSITIVE_IMAGE_DA... |
# Author: <NAME>
import h5py
import json
import librosa
import numpy as np
import os
import scipy
import time
import sys
import re
from collections import Counter
from pathlib import Path
from PIL import Image
from torchvision.transforms import transforms
from dataloaders.utils import WINDOWS, compute_spectrogram
"... |
import warnings
import numpy as np
from scipy.spatial.distance import cosine as cos_distance
from .utils import compute_fragments, average_agg_tanimoto, \
compute_scaffolds, fingerprints, \
get_mol, canonic_smiles, mol_passes_filters, \
logP, QED, SA, NP, weight
from moses.utils import mapper
from multiproc... |
#!/usr/bin/python
# -*- coding: utf8 -*-
'''
Inputs:
* pbf file
* bbox
* output folder
Generate
* Some gpkg files for basemap: landuse,water,highways, etc...
* gpkg with land and oceans polygons (clipped by bbox too)
'''
import os
import argparse
import logging
'''
Usage
python3 /home/trolleway/tmp/OSMTram/core/pro... |
#===============================================================================
# Copyright (c) 2016, <NAME>, <NAME>
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of sourc... |
# Keep-Sabbath Copyright (c) 2019-2020 <NAME>, Correct Syntax.
# Redistribution and use in source and binary forms, with or without modification,
# are permitted provided that the following conditions are met:
# 1. Redistributions of source code must retain the above copyright notice,
# this list of condit... |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
from scipy.stats import binom
from scipy import linalg
from scipy.sparse.linalg import expm_multiply
from scipy.sparse import csc_matrix
from scipy.special import comb
import math
import time
def get_2sat_... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import json
import logging
import os
import sys
LEVEL = logging.INFO
class Build:
BUILD = 'build'
DESCRIPTION = 'description'
build = [
Build.DESCRIPTION,
Build.BUILD
]
def write(name, data):
"""
JSON FORMAT:
{
"init... |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
fro... |
import pytest
from diofant import (I, O, Rational, Symbol, atanh, conjugate, elliptic_e,
elliptic_f, elliptic_k, elliptic_pi, gamma, hyper,
meijerg, oo, pi, sin, sqrt, tan, zoo)
from diofant.abc import m, n, z
from diofant.core.function import ArgumentIndexError
from diofant.u... |
"""
Utilities for running tests for db, logging, etc.
"""
import datetime
import json
import os
from anchore_engine.services.policy_engine.engine.feeds import (
IFeedSource,
FeedGroupList,
FeedList,
GroupData,
)
from anchore_engine.db.entities.policy_engine import FeedMetadata
from anchore_engine.subs... |
'''
fuck rna
fuck deep learning
'''
# -*- coding: utf-8 -*-
import numpy as np
from keras.models import Model
from keras.layers import Input, Dropout, Embedding, LSTM
from keras.layers import Activation, dot, TimeDistributed
from keras.layers import concatenate, Dense, Bidirectional
from keras.models import model_fr... |
"""Module with scared experiment for hyperparameter search."""
import os
import math
from tempfile import NamedTemporaryFile
from collections import defaultdict
from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sacred import Experiment
from sacred.observers import ... |
# -*- coding: utf-8 -*-
"""
Author
------
<NAME>
Email
-----
<EMAIL>
Created on
----------
- Tue Mar 8 15:26:00 2016 read_spectrum
Modifications
-------------
- Fri Jul 15 16:08:00 2016 migrate read_spectrum from lamost.py
Aims
----
- read various kinds of spectra
"""
import os
from collections import Ord... |
"""Utilities for submitting to Argoverse tracking and forecasting competitions"""
import json
import math
import os
import shutil
import tempfile
import uuid
import zipfile
from typing import Dict, List, Optional, Tuple, Union
import h5py
import numpy as np
import quaternion
from scipy.spatial import ConvexHull
from ... |
import os
import sys
from . import arguments, commands
from . import git_utils
from . import docums_utils
from .app_version import version as app_version
description = """
dvci is a utility to make it easy to deploy multiple versions of your
Docums-powered docs to a Git branch, suitable for deploying to Github via
gh... |
from abc import ABCMeta
import numpy as np
import torch
import torch.nn as nn
from torch.nn.modules.batchnorm import _BatchNorm
from mmcv.cnn import normal_init, constant_init
from core.gdrn_selfocc_modeling.tools.layers.layer_utils import resize
from core.gdrn_selfocc_modeling.tools.layers.conv_module import ConvModu... |
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