sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
34d470083008e0c2fcd97ec61f5c83cd488b8c026bfd172f98751766a6f0df97 | Python | 3,117 | 92 | import pyBigWig
import traceback
import sys
import numpy as np
from .target import Target
class qGenomicFeatures(Target):
"""
Stores the dataset specifying sequence regions and features.
Accepts a path to directory containing bigWig files with feature values
Parameters
----------
features : li... |
e3b140b02d954a97de860b8cbe7153802c7e38d2a79dfccca7fef526ba7b5a36 | Python | 3,117 | 74 | import jax.numpy as jnp
import numpy as np
from jax.scipy.signal import convolve as conv
from skimage.draw import disk
from .typing import Union, List
from .utils import Box
def get_smooth_fn(beta: float, radius: float, eta: float = 0.5):
"""Using the sigmoid function and convolutional kernel provided in jax, we... |
3c23f9c858c2f6b5aa47c58e1a893702f8b179a92d177855bc6b0ac474eb7167 | Python | 3,119 | 121 | #%%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/maggot_models/')
print(os.getcwd())
except:
pass
# %%
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
from pymaid_creds import url, name, password, token
import pymaid
import matplotlib.pyplot ... |
fad4a406e6d1dd79d4068333cbb8976985b6ae0fcfaadcdf0ad073f1294d2690 | Python | 3,119 | 90 | # coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
37a81ef60d23f5751d9f3770504592b1183dc373c28e1bad7ad455046971bf3f | Python | 3,120 | 137 | # Using Skorch
import torch
import skorch
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Basic Functions in Torch
from torch import nn
from torch import optim
from torch.utils.data import DataLoader
# Basic Functions in Skorch
from skorch import NeuralNet
from skorch.callbacks import EpochTi... |
480c83b470a0b8cf6261b43db26f7eb09cad60f65992f52db90172d55bf84309 | Python | 3,120 | 96 | # Copyright 2021 Huawei Technologies Co., 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... |
35d707bff12978a2cb663c83d2df80cc709a0018ec62698bb4b81f97ee5562f3 | Python | 3,121 | 121 | import sys
from distutils.version import LooseVersion
import numpy as np
from numpy.testing import (
assert_,
assert_equal,
assert_almost_equal,
assert_array_almost_equal,
assert_raises,
assert_array_equal,
dec,
TestCase,
run_module_suite,
assert_allclose)
import os
import shut... |
b4f09634e2152cd978adaaedb6dccb4fc8c09b88477beae83a1d03c305da3a83 | Python | 3,123 | 116 | from os.path import basename
from pathlib import Path
import numpy as np
import pandas as pd
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.datasets import load_drosophila_left
from graspy.utils import binarize, symmetrize, is_fully_connected
from graspy.plot i... |
db6f001f2a8baffdb8609884e79b62c45c0d79e7e68f06fc960e2f83abfc339c | Python | 3,123 | 99 | import cv2
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import torch
import clip
class CLIPLoss(torch.nn.Module):
def __init__(self):
super(CLIPLoss, self).__init__()
self.model, self.preprocess = clip.load("ViT-B/32", device="cuda")
self.upsample = torch.nn.Upsa... |
506e2c353a47b8a8575bb8018e5991d9a511588b6dccc308b1ad546d10746d26 | Python | 3,124 | 111 | # Libraries
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from skorch import NeuralNet
class AET(nn.Module):
def __init__(self, num_units=10, nonlin=F.relu):
super(AET, self).__init__()
self.dense0 = nn.Linear(20, num_units)
se... |
bfce665b27d9988c97335609c75121d6b869c1e4f8b8e5d1b00c87c6cb10a63f | Python | 3,124 | 95 | # Copyright 2021 Huawei Technologies Co., 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... |
f7a99d40288e3e3d06887c7d6b167cad7091253814b64d634649ce4182500d5f | Python | 3,124 | 125 | # %% [markdown]
# ##
import os
import warnings
from itertools import chain
import matplotlib as mpl
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import numpy as np
import pandas as pd
import seaborn as sns
from joblib import Parallel, delayed
from sc... |
583e663135daf7fcfda9f6db6ea1a8004e9e04daf2cb0b6834ec12a49591b5b7 | Python | 3,125 | 95 | """
Command Line Interface to OMK
-----------------------------
"""
import logging
import os
import subprocess
import sys
from collections import defaultdict
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, List, Sequence, TextIO, Tuple, Any, Type
import click
from linkml_runtime.du... |
8c1476aa7c6707e5b53fbe9b54784f04ee4f0ee163a9eafc7cd653df51d49789 | Python | 3,125 | 87 | from utils.ArticlesHandler import ArticlesHandler
from utils import solve, embedding_matrix_2_kNN, get_rate, accuracy, precision, recall, f1_score
from utils.Trainer_graph import TrainerGraph
from utils import Config, accuracy_sentence_based
import time
import numpy as np
# from utils.postprocessing.SelectLabelsPostpro... |
e9c7e37b3fc22357c7aaeb0c323d32b0290356a58542b1423ff0608d855329e1 | Python | 3,125 | 89 | """
File: cmd_line_arguments.py
Created: 2020/10/19
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version... |
687471f03897cd46f8207ff53e6920ac5c6c27dbc5bf456601c0cb8085c30403 | Python | 3,126 | 100 | import asyncio
import os
import shutil
import urllib
import mmcv
import torch
from mmdet.apis import (async_inference_detector, inference_detector,
init_detector, show_result)
from mmdet.utils.contextmanagers import concurrent
from mmdet.utils.profiling import profile_time
async def main():
... |
968957ae5df1e51aa02b4c4d2308c59550533ea08e1a0bc7948c1d80901e8455 | Python | 3,126 | 84 | # Copyright 2020 Huawei Technologies Co., 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... |
a97f767188294e8a5c70bbec3df089561ddf3c132fdd79e42afcf85b98e6ebe4 | Python | 3,126 | 84 | # Copyright 2022 Huawei Technologies Co., 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... |
b3c1cc4dfc1cecb2d62304537b52d5d53ed6ce5017ed2abcf414195a902fb027 | Python | 3,126 | 83 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from maskrcnn_benchmark.structures.bounding_box import BoxList
from .roi_mask_feature_extractors import make_roi_mask_feature_extractor
from .roi_mask_predictors import make_roi_mask_predictor
from .inference imp... |
d00530b94025841cc7e14f0219efc92473768f9d859b66c7ddba44259406ec49 | Python | 3,126 | 114 | '''
Reads the all-vs-all.tsv file from the BLAST scan output to
find the best hits for all the sequences in the query set.
Output: Performance of the BLAST model. (Bootstrapped)
'''
# libraries
import pandas as pd
import numpy as np
import pickle
from Bio import SeqIO
from sklearn.metrics import confusion_matrix, ... |
f18eaf6dc8a08078b4823ab562f7a91ef78b657bd18c19932318f7bdf580af51 | Python | 3,127 | 66 |
# loop through all subdirs to find all fastq files
import os.path
import glob
import os
import re
import argparse
parser = argparse.ArgumentParser(description='Make Molgenis Compute samplesheet for CMC.')
parser.add_argument('samplesheet', help='CMC samplesheet from synapse')
parser.add_argument('fastq_dir', help='p... |
0c2243cb9c1c8948b3b5d3a65544cf224081b583fbe93b42a0ab468c6bfce12a | Python | 3,128 | 86 | # Copyright 2020 Huawei Technologies Co., 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... |
1779452f44729c158159136873d4fd2984877c2ddfe44486b44b847105d52d46 | Python | 3,128 | 86 | # Copyright 2021 Huawei Technologies Co., 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... |
4e283234d4efdb88084acd1469fc0ddd76bf2a7c150884eb094699b4dd61ae21 | Python | 3,128 | 94 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Variational Animal Motion Embedding 1.0-alpha Toolbox
© K. Luxem & P. Bauer, Department of Cellular Neuroscience
Leibniz Institute for Neurobiology, Magdeburg, Germany
https://github.com/LINCellularNeuroscience/VAME
Licensed under GNU General Public License v3.0
"""
... |
994b3999a80d196ea8505d416e214ea02207180f35171cd36d4c01e71a5e1c3b | Python | 3,129 | 38 | '''
Author: Naiyuan liu
Github: https://github.com/NNNNAI
Date: 2021-11-23 17:03:58
LastEditors: Naiyuan liu
LastEditTime: 2021-11-23 17:08:08
Description:
'''
from .base_options import BaseOptions
class TestOptions(BaseOptions):
def initialize(self):
BaseOptions.initialize(self)
self.parser.add_a... |
9ed1314a153ac671f61f001fbb4d38a067f2fb02804d04cccd40ae463d54fa5f | Python | 3,130 | 88 | # -*- coding: utf-8 -*-
import click
import unetsl.management
import pathlib
import itertools
def getGpusFromParameter(p):
return [int(i) for i in p.split(",")]
@click.command()
@click.argument("model_folders", type=click.Path(exists=True), nargs=-1)
@click.option("-s", "--sample_folder", type=click.Pat... |
94c4f5fadbe06d5cb0d9743290e083c1f2ccc9216018f5a5149a359b6452b737 | Python | 3,133 | 120 | '''
Reads the all-vs-all.tsv file from the BLAST scan output to
find the best hits for all the sequences in the query set.
Output: Performance of the BLAST model. (Bootstrapped)
'''
# libraries
import pandas as pd
import numpy as np
import pickle
from Bio import SeqIO
from sklearn.metrics import confusion_matrix, ... |
2b4b3b7719bf67895972cc5ee8fee85d12d52b09ea0f222bf9507b181cb809da | Python | 3,135 | 84 | # Copyright 2020-2021 Huawei Technologies Co., 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 agre... |
3096ead4d9f61c09c6b79019655c6d37a0798801bd462d76eb58b653ea7387e1 | Python | 3,135 | 84 | import sys
import subprocess
import logging
import os
import FBEM.write_input as write
# Default location of the executable file
if os.name == 'posix': # Linux
exe_path = os.path.dirname(__file__) + '/exe/3D_Stokes_Flow_FMM_linux.exe'
else: # Windows
exe_path = os.path.dirname(__file__) + '/exe/3D_Stokes_Fl... |
77b0e31c58d2677e4655ba44971844af31081669dfdb614d3b1e0b82712ed054 | Python | 3,135 | 102 | # Copyright (c) Open-MMLab. All rights reserved.
import numbers
import os.path as osp
import numpy as np
import torch
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook
def is_scalar(val, include_np=True, include_torch=True):
"""Tell the input variable is a scalar or not... |
8af0488747b993d16cd2138135c3b2d5dbdceb3e88dbb35c20eb927ed21ccc96 | Python | 3,135 | 94 | import logging
import sys
import warnings
from dataclasses import asdict
from functools import partial
import chika
import numpy as np
import pandas as pd
import spiketrainn as spknn
from imblearn.metrics import geometric_mean_score
from sklearn.metrics import cohen_kappa_score
from sklearn.neighbors import KNeighbors... |
9d85f9cf8cab2592c88e5c37c71b39f2cfd47230f09e6864bf3698650e4510c5 | Python | 3,135 | 106 | import torch
from torch import nn
from torch.autograd import Function
from torch.nn import functional as F
from torch.utils.cpp_extension import load
fused = load(
'fused',
sources=['/apdcephfs/share_1330077/starksun/projects/pi-GAN/siren/op/fused_bias_act.cpp', '/apdcephfs/share_1330077/starksun/projects/pi-G... |
d7eaa8ea62b3063c31ad662b73d2d9c8c32ac09c80f7485fc47534687b9c7a14 | Python | 3,136 | 94 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Hyper-parameters
input_size = 784
hidden_size = 500
num_classes = 10
num_epochs = 5
batch_size = 100
learning_rate = 0.001
... |
fea30cd49bff1dbd2a10eadf49cb8c18b29f98ca20904d21a16609055dae8c45 | Python | 3,136 | 125 | """Example script for running HMM_Dirchlet inference on simulated HMM-Dirichlet data.
This script should take less than a couple minutes to run and
currently the dice coefficient is ~0.99.
"""
import os
import pickle
import numpy as np
from osl_dynamics.simulation import HMM_Dirichlet
from osl_dynamics.data import ... |
2815275ac59eb3ec8460401e59edc2a169450d1b73361012c9bf0660228d59a8 | Python | 3,137 | 87 | ####################################################################################################
# Copyright (c) 2019 - 2021, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free ... |
d14b86880c71a8b97639f8b2c4315cc131f99a4c2e4b30d3419260a421d4ecf0 | Python | 3,138 | 101 | import difflib
import nltk
from nltk.corpus import stopwords
from Classes.Keyword import Keyword
from Classes.KeywordCollection import KeywordCollection
from Classes.QueryStopwords import QueryStopwords
import re
from Classes.SearchComponent import SearchComponent
import indexing
class QueryParser(SearchComponent):
... |
0183ade186d08a177383d40a10478709dacb556fc3cfa33df4a213a33c273b28 | Python | 3,139 | 107 | from abc import ABCMeta, abstractmethod
import torch.nn as nn
from ..builder import build_shared_head
class BaseRoIHead(nn.Module, metaclass=ABCMeta):
"""Base class for RoIHeads."""
def __init__(self,
bbox_roi_extractor=None,
bbox_head=None,
mask_roi_extra... |
2344a6d083839cf9f34c1a4a374d910e23c146aca1afce38856da953d03816bc | Python | 3,139 | 81 | # Copyright 2022 Huawei Technologies Co., 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... |
49dd1d070d55828e227a32a825968fb79328dfa718a2bde2729d85c60e0e604a | Python | 3,139 | 60 | # MIT License
#
# Copyright (c) 2020 Tomáš Nekvinda
#
# 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, modif... |
ebf0ec845269041e96f6545d5ffb0026d78086065e9255b2a4d4a45eccee6db6 | Python | 3,139 | 66 | # %%
import pymaid
import contools
from contools import generate_adjs
import numpy as np
from datetime import datetime
from pymaid_creds import url, name, password, token
from data_settings import data_date, pairs_path
data_date = datetime.today().strftime('%Y-%m-%d')
rm = pymaid.CatmaidInstance(url, token, name, pas... |
7d1556374b639081bdd8f1831f5c069990a5a8825aff93bc1aa15c3b00eb6fbe | Python | 3,140 | 90 | import synapseclient
import argparse
import getpass
import synapseutils
parser = argparse.ArgumentParser(description='Download RNAseq and genotypes of CMC.')
args = parser.parse_args()
user = input("Synapse username:")
password = getpass.getpass('Synapse password:')
syn = synapseclient.Synapse()
syn.login(user,pas... |
adfb6011951ea3f0cc1052978be20f9f5d20df89136ab9882f427db8ab42ef51 | Python | 3,141 | 54 | import roboscientist.equation.equation as rs_equation
import numpy as np
EQUATIONS = {
'N1': (['add', 'x1', 'add', 'mul', 'x1', 'x1', 'mul', 'mul', 'x1', 'x1', 'x1'], ['x1']),
'N2': (['mul', 'add', 'x1', '1.0', 'mul', 'x1', 'add', '1.0', 'mul', 'x1', 'x1'], ['x1']),
'N3': (['add', 'x1', 'mul', 'add', 'x1'... |
0c01493d269f8c693d8d7642184c94d6b424de924762e37642c0e3d28af6a14f | Python | 3,142 | 84 | ####################################################################################################
# Copyright (c) 2019 - 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This library is free ... |
50855ec15a9cbc8eb456018883c030ce626ef56f9d83615e1ad44a83c1315e5f | Python | 3,142 | 110 | import abc
import copy
import logging
from collections import ChainMap
from pathlib import Path
from typing import Any
from ppqm import chembridge, constants
from ppqm.chembridge import Mol
_logger = logging.getLogger(__name__)
class BaseCalculator(abc.ABC):
"""Base class for quantum calculators
This class... |
862cc7750185c3f2a4749bc668dc58bbe0fcfab05f2fa28acfc28ff58478d659 | Python | 3,143 | 112 | """
.. _small_darcy_vis :
A simple Darcy-Flow dataset
===========================
An introduction to the small Darcy-Flow example dataset we ship with the package.
The Darcy-Flow problem is a fundamental partial differential equation (PDE) in fluid mechanics
that describes the flow of a fluid through a porous medium.... |
c5e5744ec33d8bc5bf7c645686ba1e97866be6a773760715fc5e14363a49a21b | Python | 3,143 | 111 | import sys
import os
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
import glob
from scipy.ndimage import median_filter
from utils import getCSFprior,normalizeProb,tumorDetection,saveMaps,largestAfterOpen
from scipy import ndimage
import random
from shutil import copy2
n_tissue=int(sys.argv[... |
337667199f8c1e5a2b327da5820f32af6834deae4a0c44f39161567e2dac687a | Python | 3,145 | 118 | '''
Figure 11.
Trajectories with an obstacle and torus topology.
'''
from brian2 import *
from pylab import *
import matplotlib.font_manager as fm
from plotting import *
from matplotlib import gridspec
from behavior import *
import imageio
import numpy as np
fontprops = fm.FontProperties(size=18)
width, height = 4, 8... |
a0d7f97b184c06b6e9efb6145e59b543f6825f3155ed20ac2a86b47bc7196a51 | Python | 3,145 | 84 | import tensorflow as tf
import tensorflow.keras as keras
import numpy as np
class InceptionNet:
def __init__(self, input_shape, nb_classes, nb_filters=32, use_residual=True, use_bottleneck=True,
depth=6, kernel_size=41, verbose=False, build=True, is_train=True):
self.nb_filters = nb_fil... |
1b979baec3b4ac364844013c68a32783791b813c249dc8790a0ce20eca3aa22c | Python | 3,146 | 81 | import numpy as np
import sys
import time
import shutil
import subprocess
import os
#import pyflann
from IPython.core.debugger import set_trace
# Script to block all atoms that are not in the target site-- used to block everything in ZDOCK outside the target site.
# This is done by adding a 19 to column 55-56 for ato... |
1098c1f6e689a5b13b441c4ca54f48c5d47e21f8f0dfd3b5b37a265af8480bef | Python | 3,147 | 99 | import random
import ipdb
import torch
import matplotlib.pyplot as plt
from sklearn.metrics import f1_score
from graphxai.gnn_models.node_classification import BA_Houses, GCN, train, test
from graphxai.datasets.feature import make_network_stats_feature
from graphxai.explainers import GNNExplainer
from graphxai.visual... |
1119b247fa51a0d8e250f4fd9a0e654f1cb0ee1257eef046f523269f31271f3e | Python | 3,147 | 102 | import numpy as np
import AFQ.recognition.roi as abr
import nibabel as nib
import numpy.testing as npt
import numpy as np
from scipy.spatial.distance import cdist
from AFQ.recognition.roi import (
check_sls_with_inclusion,
check_sl_with_inclusion,
check_sl_with_exclusion)
streamline1 = np.array([[1, 2, 3]... |
a86415a98d94af4119c2d4bd4f6708ae9e10df5e2d22e390daed628f3dff381e | Python | 3,147 | 89 | # Copyright 2022 Huawei Technologies Co., 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... |
0f3f30a06adbe6460ece9868d7c3fb9e662170ffbc88765db74dc031f410e65f | Python | 3,148 | 127 | # %% [markdown]
# #
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from ast import literal_eval
import pymaid
from src.data import load_metagraph
from src.io import savecsv, savefig, saveskels
from src.pymaid import start_instance
from itertools import chain
... |
fae4fe62834d24d3bf101e4231cbedca144f6fee77d14a5517c054db01402aef | Python | 3,149 | 105 | #!/usr/bin/env python
# plotPSD ver 0.0 - a command line utility to plot a wildcarded argument
# list of files containing time series data, and plot the
# Power Spectral Density (PSD) of them.
# This version averages the data from multiple files.
import sys, os
import numpy as np
import matplotlib.pyplot as ... |
85f1056ebf903eb5b8810b670fd21b4974e955af36541d909fcd384b4dbbe648 | Python | 3,150 | 120 | '''
Figure 11.
Trajectories with an obstacle and torus topology.
'''
from brian2 import *
from pylab import *
import matplotlib.font_manager as fm
from plotting import *
from matplotlib import gridspec
from behavior import *
import imageio
import numpy as np
fontprops = fm.FontProperties(size=18)
width, height = 4, 8... |
a88c23b0603e8cd2cfd2d661e2230f1a1636d19c36a177f6aa83d84029544aa0 | Python | 3,150 | 86 | # Copyright 2022 Huawei Technologies Co., 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... |
e8248bde257b82e482f275bcb5985695288c3ff48bd2e3817737184adf1608ee | Python | 3,150 | 95 | from functools import partial
import torch
from .env import TORCH_VERSION
def _get_cuda_home():
if TORCH_VERSION == 'parrots':
from parrots.utils.build_extension import CUDA_HOME
else:
from torch.utils.cpp_extension import CUDA_HOME
return CUDA_HOME
def get_build_config():
if TORCH... |
73af6c05849aa5a5d0e4bd818f9a122a70a6919cf342fcc496ab6ffab9139895 | Python | 3,151 | 81 | import os
import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
def flin(x, A, B): #linear fit
return A*x + B
def filter_df_numstart(df_cond, numstart, df_path):
# filter df with list of conditions per number of targets
df_cond_starters = df_cond[df_cond['targets'] == numstart]
... |
a519bed19af2ed06f3c8bc31b2bf06cef9ee5bb374353b17b3969358a17d0717 | Python | 3,151 | 107 | '''
Properties of the graded avoided reaction.
In 2D.
Angle is calculated as average over 1 s (= 1 cycle).
'''
from brian2 import *
from behavior import *
from scipy.linalg import norm
from pylab import *
from scipy.stats import circmean
width, height = 2, 4
t1 = 1000*ms
t2 = 1002*ms
N = 300
halfN = int(N/2)
# Lif... |
c3839e067733879ccd351f27a80a477e286ccc86b933642a835609b249fe9328 | Python | 3,151 | 112 | # %% [markdown]
# ##
import matplotlib.pyplot as plt
import seaborn as sns
from graspy.plot import gridplot, heatmap
from graspy.utils import binarize, pass_to_ranks
from src.data import load_metagraph
from src.visualization import CLASS_COLOR_DICT, adjplot
sns.set_context("talk")
mg = load_metagraph("G", version="2... |
e3b84071772b661e124ef5d352d3457fc7133ffd75f23291d76ff7eeea7cf8bb | Python | 3,151 | 88 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
32a0ce0289c58881859562ce4ee85e790aa9c243e7f8ac325a2be7982d2b8992 | Python | 3,152 | 75 | # Copyright 2022 Huawei Technologies Co., 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... |
66a19f0257b6bab3ad2485ffd52dbdc562a4d83aac5d47f7209746a446ed7d78 | Python | 3,153 | 109 | """
Measures of distance of two distributions
"""
import numpy as np
from ortools.linear_solver import pywraplp
from scipy.special import gamma
def kl_divergence(p, q, k):
"""
k-nearest-neighbor estimation of Kullback-Leibler divergence between samples from two multivariate distributions.
See: Pérez-Cruz... |
f337bfe80620dbfc21f5eeeedc1e54e20ef4365b9e7497d685b36fd803744699 | Python | 3,153 | 78 | # import the necessary packages
from keras.models import Sequential
from keras.layers.normalization import BatchNormalization
from keras.layers.convolutional import Conv2D
from keras.layers.convolutional import MaxPooling2D
from keras.layers.convolutional import AveragePooling2D
from keras.layers import GlobalAveragePo... |
f53eede7b86871fcb6b97b8806c39c486fc4a26623a2b395f9e4206db0a5beb6 | Python | 3,153 | 100 | """
HMM: Plotting fMRI Networks
===========================
We normally plot networks from an HMM trained on fMRI directly from the dual-estimated means/covariances. This tutorial covers:
1. Load means/covariances
2. Spatial maps
3. Functional connectivity networks
Note, we assume a group ICA parcellation was used a... |
302c88a58d0a56f8682c3617d2ee3da79164fc443efebe79c6e41ee4dc97a631 | Python | 3,155 | 121 | # %%
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import scipy.io
from pathlib import Path
from box import Box
# %%
all_events = pd.read_csv("all_combined_with_80_20_taus.csv",index_col=0)
#%%
fix_scalar = lambda x : x.item() if x.ndim==0 else x
def read_npz_MAD(file_name):
data= np.lo... |
bd0fbdd5c90c3e43e3251e797bba327b1ea72d15561f6e85d818a2350ac5c132 | Python | 3,156 | 78 | # dataset: mne_sample
"""
This example demonstrates how to load and plot MEG data
It uses the mne sample dataset which included presentaton of simple (A)uditory
and (V)isual stimuli to the (L)eft and (R)ight ear/visual hemifield, as well as
presentation of smiley faces and button presses by the subject.
All the lines... |
3a9de10a187d278d362b4b3c4667ef4dafb3ad9b36f4fe9e99b5b75a75fd2de0 | Python | 3,157 | 95 | import math
import torch
import torch.nn as nn
from networks.drn import drn_c_26
def fill_up_weights(up):
w = up.weight.data
f = math.ceil(w.size(2) / 2)
c = (2 * f - 1 - f % 2) / (2. * f)
for i in range(w.size(2)):
for j in range(w.size(3)):
w[0, 0, i, j] = \
(1 - ... |
765a2b9a0f287cf019eefb5fbab4c7a9b012158a457086ec46f5615ba5dff4bd | Python | 3,157 | 92 | # Copyright 2021 Huawei Technologies Co., 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... |
131818d03288f96cdf09b9d87e56b4a825f03b9d27c09b667cd98431f1a3aa68 | Python | 3,158 | 83 | """Simulations for time series data.
This subpackage provides tools for generating synthetic time series data
with known ground truth dynamics. Simulations are built by combining a
**state model** (how states evolve over time) with an **observation model**
(how data is generated given the active state).
State models
... |
c3ff8818b5dc910a6c3571ccfa8b19fad993bd09b07de1bee6ef72ce7be46524 | Python | 3,158 | 97 | from lab.nilm_experiments import *
from constants.constants import *
from constants.enumerates import *
experiment_parameters = {
EPOCHS: 100,
ITERATIONS: 10,
INFERENCE_CPU: False,
SAMPLE_PERIOD: 6,
BATCH_SIZE: 1024,
ITERABLE_DATASET: False,
PREPROCESSING_METHOD: SupportedPreprocessingMethod... |
5082f71af7b6354e34ebfe18c18eb7851130bcfe26eb9248048fbd04af835c67 | Python | 3,160 | 69 | """Module contains BrainFMRIDataset class for dataloading and preprocessing."""
import torch
import scipy.io as iom
from typing import Tuple
from torch.utils.data.dataset import Dataset
from torchvision import transforms
from tools.utils import fmri_masking, tuple_prod
def _transformation():
"""Implementation of... |
7048fb2a19b846f0bfc69388a68aaa21a9eff67b19b49b8ff5757e2b61d298b2 | Python | 3,160 | 59 | #!/usr/bin/env python3
"""Spawn and destroy a 1920x1080 rgb_fisheye N times on a live server and read the server's GPU
memory (nvidia-smi) between iterations. It must return to within ~200 MB of the post-first-spawn
baseline; before the EndPlay release fix each sensor left ~2-6 GB behind until garbage collection.
usag... |
f205c7459575c0923d712c46f14dd8ac4c73566568848dd34cf0a5dc6974179b | Python | 3,160 | 79 | #!/usr/bin/env python
# Copyright 2014 Gaurav Kumar. Apache 2.0
import os
import sys
files = [
open('/export/a04/gkumar/kaldi-trunk/egs/fishcall_es/j-1/exp/tri5a/decode_test/scoring/13.tra'),
open('/export/a04/gkumar/kaldi-trunk/egs/fishcall_es/j-2/exp/tri5a/decode_test/scoring/13.tra'),
open('/export/a04/gkumar/k... |
16111173afebf73d9c47be7d5533d21b2d1b303a8ce587f93c117fbf5c1e98f6 | Python | 3,161 | 83 | from experiment import setup_seed, one_dim_data
from train import train
from utils.dataTrans import get_dataloader
from sklearn.model_selection import train_test_split
from model import SoundNet, SoundNet_no_padding
import numpy as np
import torch
from sklearn.model_selection import StratifiedKFold
# 参数
BATC... |
40568d2323b0037361786330710fa0093785668698a5257682679f7c634d021d | Python | 3,161 | 97 | import torch
import torch.nn as nn
import torchvision
from torchvision import transforms
from logger import Logger
# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# MNIST dataset
dataset = torchvision.datasets.MNIST(root='../../data',
... |
e659d9358729794b8fd7b9a8b11cb16008df382110fb37f911b47d47128fd768 | Python | 3,162 | 141 | import gzip
import sys
if len(sys.argv) < 3:
print("Usage: eqtls1.txt.gz eqtls2.txt.gz output.txt.gz [name1 name2]")
exit()
file1=sys.argv[1]
file2=sys.argv[2]
output=sys.argv[3]
name1="Dataset1"
name2="Dataset2"
if len(sys.argv) > 5:
name1 = sys.argv[4]
name2 = sys.argv[5]
def countSharedAlleles(al1, al2):
#... |
5a21fa94fc45a2b54fa1964d406b873b833d6875124cd74dcb763df90fc09cb3 | Python | 3,163 | 106 | # Copyright 2022 Huawei Technologies Co., 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... |
7bb9a842979ec4cb0f3a8a6c83b935bdf794da531e6eeff9537fd0bad5ae042e | Python | 3,165 | 121 | from neuron import h, gui
import numpy
"""This functino sets up recording for soma and D4 location and return them in a tuple of list of vectors"""
def set_up_full_recording(h,dendnum,OU=False):
v_vecD4 = h.Vector()
v_vecD4.record(h.dend[dendnum](0)._ref_v)
IhD4 = h.Vector()
IhD4.record... |
3e69094dbd7a99108cf424e9e78775489bce1ddb8152e89acd67c3b20daf2c93 | Python | 3,166 | 76 | import os.path
import argparse
parser = argparse.ArgumentParser(description='Make Molgenis Compute samplesheet for Braineac.')
parser.add_argument('samplesheet', help='Braineac samplesheet')
parser.add_argument('cram_dir', help='path to cram file dir for input')
parser.add_argument('fastq_dir', help='path to fastq fi... |
57b93ad2454a41613cd0aadb726d214aa45dc86e6d7558ee0fdb5a17a0764cff | Python | 3,166 | 63 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import subprocess
import os
import sys
import time
import shutil
import shlex
INPUT_DIR = os.path.abspath("../data")
OUTPUT_DIR = os.path.expanduser("~/data/pix2pix/test")
def main():
start = time.time()... |
26dee9aebd80a4ef9f2ea7007067644cd8294bd5bc8a91f0c8d6e8710f453e4a | Python | 3,167 | 110 | import tensorflow as tf
import numpy as np
from gd.gd_nn import GD_NN
from helper.data import load_data, get_architecture
from helper.misc import infer_and_accuracy, clear_print
tf.logging.set_verbosity(tf.logging.ERROR)
def test_stuff():
random_seed = 31567478618
tf.set_random_seed(random_seed)
#seed = 5369
... |
9b5d4b50e9100e78120196d71155c7a81ad842f815c9047a39af1ff13eca9dfa | Python | 3,170 | 77 | import copy
import os.path as osp
import numpy as np
from mmdet.datasets.pipelines import (LoadImageFromFile,
LoadMultiChannelImageFromFiles)
class TestLoading(object):
@classmethod
def setup_class(cls):
cls.data_prefix = osp.join(osp.dirname(__file__), '../dat... |
1cde7ff40d6a40503ab4da7f435bf10e719c1f26cab83bfbf34d308c74d9c7a2 | Python | 3,171 | 80 | #!/usr/bin/env python
from __future__ import print_function
from collections import OrderedDict
import re
regexes = {
'nf-core/atacseq': ['v_pipeline.txt', r"(\S+)"],
'Nextflow': ['v_nextflow.txt', r"(\S+)"],
'FastQC': ['v_fastqc.txt', r"FastQC v(\S+)"],
'Trim Galore!': ['v_trim_galore.txt', r"version ... |
b18526fb93b0551a82e3fefdf420cdda4bd4b07f33b71df6553df7054b7a4751 | Python | 3,171 | 128 | # %% [markdown]
# ##
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from graspy.utils import binarize
from src.data import load_metagraph
from src.io import savefig
from src.visualization import set_ax... |
d5bcb534d2067c829005943b366163d318e6f77f6efffc19a09101d61f5ffc95 | Python | 3,171 | 115 | '''
Logistic Regression Model trained on the protbert embeddings
'''
# libraries
import pandas as pd
import numpy as np
from sklearn import preprocessing
import biovec
import math
import pickle
from sklearn.model_selection import train_test_split, KFold, cross_val_score, StratifiedKFold
from sklearn.preprocessing i... |
f17079d07643b413f625077805e0e9646460274d7eaaba0054f5247005463d75 | Python | 3,171 | 88 | import argparse
from tensorflow import keras
import matplotlib.pyplot as plt
import numpy as np
import os
from scripts import dl_utils
from scripts.viz_tools import normalize
def make_predictions(patches, model):
pred_stack = []
for patch in patches:
h, w, c = patch.shape
preds = model.predict... |
bbaee23e4caccc665f9e2565e7eb2e151496f93499a201162a14cff41754cb30 | Python | 3,173 | 108 | import pytest
import torch
from tltorch import FactorizedTensor
try:
import torch_harmonics
except ModuleNotFoundError:
pytest.skip(
"Skipping because torch_harmonics is not installed", allow_module_level=True
)
from ..spherical_convolution import SphericalConv
from ..spherical_convolution import ... |
cbc352d213916c88c007ef1359c6ff3562bae6d835b1e09d4a452d8450fcfa2e | Python | 3,173 | 91 | import random, sys
from typing import Union, List
import os
from networkx.classes.function import to_undirected
import networkx as nx
import ipdb
import torch
import numpy as np
import matplotlib.pyplot as plt
import torch.nn.functional as F
from numpy import ndarray
from torch_geometric.utils import to_networkx, conve... |
20113ff191ce47f5a5e38c0035716c39d5e70f3b8eeb1daf53b82aa3001ca57a | Python | 3,175 | 87 | ####################################################################################################
# Copyright (c) 2019, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free softwar... |
be7d969532936c311e3b7f868d4d3941cd02de1f5189bf7113278bbd031d621f | Python | 3,175 | 84 | # Copyright 2020 Google Research. 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... |
f6ed6675eb63dada7a9785bc3f1d5737213f7737b3f9921beca1bce04c217f38 | Python | 3,175 | 87 | #!/usr/bin/env python
"""Example ROI transform script
To transform ROIs from a source dataset to target datasets:
>> python transform_rois.py /path/to/source/dataset /path/to/target/datasets
SOURCE_LABEL
For help and additional arguments:
>> python transform_rois.py --help
"""
import os
import argparse
from si... |
618b777eb8fc054af6fb5eefc65dfbc92438253655afcd9caa4543f2f33a51a5 | Python | 3,176 | 91 | #!/usr/env/bin python3.6
# NOTES: this repository do not used in current release, I will add more loss function in future
from typing import List
import torch
from torch import Tensor, einsum
from utils import simplex, one_hot
class CrossEntropy():
def __init__(self, **kwargs):
# Self.idc is used to fil... |
31878ea2ba1dd32de9a9ab43cc4ab142c4131276c9ae5df2f9c614db93f39a97 | Python | 3,177 | 84 | #! /usr/bin/env python3
# Copyright 2019 Ashish Arora
# Apache 2.0.
"""This script finds best matching of reference and hypothesis speakers.
For the best matching speakers,it provides the WER for the reference session
(eg:S02) and hypothesis recording (eg: S02_U02)"""
import itertools
import numpy as np
import... |
d7e3d5b3ded77a29245050533c2b06debe337e45c25ddf54371bdd1f8bb6b981 | Python | 3,178 | 83 | #!/usr/bin/env python3
# Copyright 2020 Audio, Speech and Language Processing Group (ASLP@NPU), Northwestern Polytechnical University (Authors: Zhuoyuan Yao, Xiong Wang, Jingyong Hou, Lei Xie)
# 2020 AIShell-Foundation (Author: Bengu WU)
# 2020 Beijing Shell Shell Tech. Co. Ltd. (Author: Hui BU)
#... |
8414585169ba356c25bc26b241a21a1ca10fb2eb3b4ed4b1d7fbd460b4ebaeae | Python | 3,182 | 79 | """Tests for mesh volume.
Trimesh measures a volume by summing, over the faces, the tetrahedron each one
makes with the *origin*. On a closed surface the anchor cancels exactly, so that
costs only precision. On an open one the cone to the anchor is real geometry and
grows with the distance to it, which for a mesh in d... |
e75186e12ad97548f3f357021335f3ca0ec8ff76ac1af6a5879560cc74512815 | Python | 3,185 | 82 |
import math
import torch
import torch.nn as nn
from functools import partial, reduce
from operator import mul
from timm.models.vision_transformer import VisionTransformer, _cfg
from timm.models.layers.helpers import to_2tuple
from timm.models.layers import PatchEmbed
__all__ = [
'vit_small',
'vit_base',
]
... |
2d79742eee486eb54640c8e75b0e0ec8c35b613ded29d541fefc209a3dc8fd25 | Python | 3,186 | 68 | import os
import argparse
import torch
import warnings
from corrupter import BernCorrupter
from utils import DataLoader
from base_model import BaseModel
parser = argparse.ArgumentParser(description="Parser for Knowledge Graph Embedding")
parser.add_argument('--task_dir', type=str, default='./KG_Data/DRKG_v3', help='t... |
29858eeaaebeefe2f24426c25739d36679b8ed3f334cf171aeba8d50a6e471f2 | Python | 3,189 | 79 | #!/usr/bin/env python
# Copyright 2014 Gaurav Kumar. Apache 2.0
import os
import sys
files = [
open('/export/a04/gkumar/kaldi-trunk/egs/fishcall_es/j-1/exp/tri5a/decode_test/oracle/oracle.tra'),
open('/export/a04/gkumar/kaldi-trunk/egs/fishcall_es/j-2/exp/tri5a/decode_test/oracle/oracle.tra'),
open('/export/a04/gk... |
fb817d6233757421d97cf5a91396387653d17b07f98316179c8333c9b33ccd95 | Python | 3,189 | 78 | import unittest
from unittest.mock import MagicMock, patch
from xml.etree import ElementTree # noqa S405
from oaklib import get_adapter
from oaklib.implementations import NCBIGeneImplementation
from oaklib.interfaces.association_provider_interface import (
AssociationProviderInterface,
)
from tests import CYTOPLA... |
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