sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
402eb8b28891333f06a459918209dd8f7119f36f35febafbb82186306b0cffa0 | Python | 2,935 | 110 | #%%
import os
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
#%%
import sys
sys.path.append("/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/")
import pandas as pd
import numpy as np
import math
import matplotlib.pyplot as plt
impo... |
8329017f02883bd2840406d6bff8835c5d375156980aafe6863c027f769c50dd | Python | 2,936 | 88 | #!/usr/bin/env python3
import glob
import itertools
import os
import pytz
import click
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy.signal as sg
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
SRC_DATA_DIR = "./00-PREPROCESSED-D... |
f404234506a64f8b41923c5a70f7b708ceca63a7440625091a6b48850143725b | Python | 2,936 | 81 | import torch
import torch.nn as nn
import math
class se_block(nn.Module):
def __init__(self, channel, ratio=16):
super(se_block, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.fc = nn.Sequential(
nn.Linear(channel, channel // ratio, bias=False),
... |
ec1e45bc2e9d6cd07b778c08320bb0b865d3478d2c926a55dd8eb3aed9feea33 | Python | 2,937 | 69 | #!/usr/bin/env python3
"""Compile and sample .scenic files with NO simulator. Triage before you run.
A `--simulate` failure conflates three very different causes. This separates them:
COMPILE-FAIL syntax, model import, missing .xodr, or a blueprint category
Scenic has no entries for on this client ... |
f35e9b009dce7e271d02c1eba4c414f79cf7b8631bb0124d87a0d6e8202e5184 | Python | 2,937 | 131 | # Copyright 2020-2022 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 agre... |
ae5d8892dd083d83c21b58b9b7186577335f3ca2c8d048ca007e3c412a665854 | Python | 2,938 | 118 | # Copyright (c) Open-MMLab. All rights reserved.
from time import time
class TimerError(Exception):
def __init__(self, message):
self.message = message
super(TimerError, self).__init__(message)
class Timer:
"""A flexible Timer class.
:Example:
>>> import time
>>> import mmcv
... |
0d5dbb7b8247e04554dc549dde2b30a08c6735b7184a52852692a1c283602f95 | Python | 2,940 | 156 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
from tmkit.topology.pdbtm.Segment import Segment as fetchfasids
class toFastaId:
def __init__(self, type="tmh"):
self.type = ty... |
390f14128d7b8dd904983020264738b4e855fed50df2306e9a1d38a41ea59d4a | Python | 2,940 | 89 | """
HeartENN architecture (Richter et al., 2020).
"""
import numpy as np
import torch
import torch.nn as nn
class HeartENN(nn.Module):
def __init__(self, sequence_length, n_genomic_features):
"""
Parameters
----------
sequence_length : int
Length of sequence context on ... |
69e7533b9f41d898cb5cd1c69aa11860afd39a230e5293a49fd77d5c3c75174a | Python | 2,940 | 114 | '''
download_s2.py
Download Sentinel-2 imagery over dump sites
'''
from argparse import ArgumentParser
import geemap
import geopandas as gpd
import ee
import os
from shapely.geometry import mapping
# initialize GEE
ee.Initialize()
# set some defaults
S2_ID = 'COPERNICUS/S2'
S2CLOUDLESS_ID = 'COPERNICUS/S2_CLOUD_... |
c07e27192af5943cb53772bf389de6d54e4d3174ac6d4f355ce3910f28c8f632 | Python | 2,940 | 95 | # Copyright 2017 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... |
d1b14e4a769435e8838222c14ce954c3717c6875b8e72cfa23defca4e486bcf4 | Python | 2,941 | 83 | """
© 2022, ETH Zurich
"""
import os
import chemprop
from rescoss_logp_ml.two_d_models.chemprop_tools import run_training
from rescoss_logp_ml.utils import SEED, get_output_dir
class ChempropModel:
def __init__(self, random_state=SEED, **h_params):
self.random_state = random_state
super().__init... |
adedbd1e96e23787270c0e274b783268f9ab1fc6dde0c7d95eb253d5570befdb | Python | 2,942 | 117 | import copy
import json
import pickle
import tempfile
import weakref as _weakref
from io import StringIO
from pathlib import Path
from types import TracebackType
from typing import Any
import numpy as np
class WorkDir(tempfile.TemporaryDirectory):
"""Like TemporaryDirectory, with the possiblity of keeping log fi... |
e31a951b98d31397a1a029817a494ff4b42ff87abb91d82463b60ccdcb45671a | Python | 2,942 | 82 | """
Description:
Used for the _in silico_ mutagenesis section in this case study.
Randomly selects some sequences from the test set to use.
Output:
Saves randomly selected sequences to a FASTA file.
Usage:
get_test_regions.py <features-bed> <genome-fa> <output-fa>
[--seq-len=<l... |
284c6cf512dc92bb477f3dd7ee9d1dc9e76531e0305bf1b49a5256e5eae4d2ca | Python | 2,945 | 76 | import logging
import unittest
import networkx as nx
from oaklib.datamodels.vocabulary import IS_A, PART_OF
from oaklib.implementations.pronto.pronto_implementation import ProntoImplementation
from oaklib.resource import OntologyResource
from oaklib.utilities.graph.networkx_bridge import (
relationships_to_multi_... |
4619be438a9cad53de3b0a44024012721da0c87bd5dc76580164a5fadca72e48 | Python | 2,945 | 120 | import pytest
import tensorflow as tf
from typing import List, Tuple
from multi_phase.networks.components.discriminator import Discriminator
#-------------------------------------------------------------------------
@pytest.mark.parametrize(
"depth,img_dims",
[
(3, [2, 16, 16, 8, 1]),
(4, [4... |
f809d6cc55d22fefebe25da3444d4092342436c8ff151025196dc1452ef53fc6 | Python | 2,945 | 79 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
# Modifications Copyright 2017 Abigail See
#
# 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... |
c71f79a83f3c7bb4be6d3385b138b73f642d7ed6c0ad239b7a1cde8b60f54fd8 | Python | 2,946 | 102 | """
Extends the functionality of the metric axes class to include specific functions of plotting localization results
"""
import numpy as np
import pandas as pd
from lib.metric_axes import metric_axes as ma
class metric_axes(ma):
def format_by_speaker_location(self, x:bool=True, y:bool=True, withSymbol:bool=Fal... |
7c1e703b993eb080d55d5f678c58a8d771214109427414d27405597bc3cf7e86 | Python | 2,947 | 81 | #!/usr/bin/env python3
"""
Plotting functions generating all plots of the paper.
The data needed for this can be generated using the script
:py:mod:`record_experiment`.
"""
from functools import partial
from model_paper_mc_genetic.helpers import name_wrapper
from model_paper_mc_genetic.plotting import PaperPlots, se... |
c78f99a019a5443576eebf7e6fafca6d2d4b69cf947505ad9f535709c7df3989 | Python | 2,947 | 50 | IMAGENET_WEIGHTS_PATH = (
'https://github.com/Callidior/keras-applications/'
'releases/download/efficientnet/')
IMAGENET_WEIGHTS_HASHES = {
'efficientnet-b0': ('163292582f1c6eaca8e7dc7b51b01c61'
'5b0dbc0039699b4dcd0b975cc21533dc',
'c1421ad80a9fc67c2cc4000f666... |
10300476b50d871741730f74880412aff057d4e97803fa8eec818f8177f0528d | Python | 2,948 | 92 | import sys, os, urllib.request, zipfile, subprocess
#not importing because imports torch internally #FIXME
#from base.paths import path_to_main_module
assert 'torch' not in sys.modules
WHEEL_URLS = {
'torch==1.10.1+cpu' : 'https://download.pytorch.org/whl/cpu/torch-1.10.1%2Bcpu-cp37-cp37m-win_amd64.whl',
... |
72054a0ec04c345683444682d2d0fa19c9b1f30d91a41e685bd3adbd6a57b890 | Python | 2,949 | 67 | import pandas as pd
import numpy as np
import cvxpy as cp
import cplex
import slideflow as sf
from slideflow.util import log
def generate(data, category, values, crossfolds = 3, target_column = 'CV3', patient_column = sf.util.TCGA.patient, site_column = 'SITE', timelimit = 10):
"""Generates 3 site preser... |
d9b58cc7d00d20aa776177de7e294c96d1cbafdb02bd14d90e3ea6d45d4d29be | Python | 2,949 | 73 | # 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... |
ee71cef20bb0686c49ffe872091a10b922122e33329c87fe57b36a0e1c45aaf3 | Python | 2,950 | 107 | from cgtasknet.tasks.reduce import (
DMTask,
DMTaskParameters,
DMTaskRandomMod,
DMTaskRandomModParameters,
)
def test_dm_task_size():
assert DMTask().feature_and_act_size == (2, 3)
def test_dm_task_run_one_data_set():
DMTask().one_dataset()
def test_dm_task_run_just_run_some_data_set():
... |
fc103dd3cc0819fb199526a2684598f758ed7bd815a6c9b2c212771bf97d344c | Python | 2,950 | 78 | import logging
import unittest
from oaklib.implementations.pronto.pronto_implementation import ProntoImplementation
from oaklib.implementations.sqldb.sql_implementation import SqlImplementation
from oaklib.resource import OntologyResource
from oaklib.datamodels.vocabulary import IS_A, PART_OF
from oaklib.utilities.sub... |
2c502e3ead52914646d49b51178c16a8ae8c9f8fefc2b4b9c0d9dca6f21469bf | Python | 2,953 | 44 | """Side impact at the sp8 junction, recorded and filmed from a chase camera (Cinematic)."""
import os, sys, queue, math
import numpy as np, carla
sys.path.insert(0, os.path.dirname(__file__)); import scene
OUT = sys.argv[1]; os.makedirs(OUT, exist_ok=True)
c, w = scene.connect(); tm = c.get_trafficmanager(8000); lib = ... |
88bb16111aca9a638272ca6bde11488f74255242503fc3dc80c3d15242b08ea5 | Python | 2,954 | 105 | import numpy as np
from torchvision import transforms
# from utils.build_vocab import Vocabulary
from recurrent_rsa.train.image_captioning.char_model import EncoderCNN, DecoderRNN
import torch
from recurrent_rsa.rsa_utils.numpy_functions import softmax
class Model(torch.nn.Module):
def __init__(self,path,dictionari... |
bf9db3c3292f807aca96bd6e83be02e23b874cb0e81ea2ab5e3a2f57e04534c4 | Python | 2,954 | 84 | """
File: covariate_clustermap.py
Created: 2020/06/02
Last Changed: 2020/06/19
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, ei... |
eb9a9a48d2cbab7fbf28a878b3ffd1286c1758d527715d09d790d42eda8b5d41 | Python | 2,954 | 54 | from .basic_params import BasicParams
class TrainTestParams(BasicParams):
"""
This class is a son class of BasicParams.
This class includes parameters for training & testing and parameters inherited from the father class.
"""
def initialize(self, parser):
parser = BasicParams.initialize(se... |
8491f98b37188e2cb1cf90aa504beaeb419abd46f1d307727666d7fdd18b7c8a | Python | 2,956 | 77 | import os
import pickle
import pandas as pd
import numpy as np
import sklearn.preprocessing
import matplotlib
import utils_Florian as utils
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
matplotlib.rcParams['font.sans-serif'] = "Arial"
matplotlib.rcParams['font.family'] = "sans-serif"... |
052e25b143ebc6c2728e067fb00b93509ab18d1634da7bbf3339c958db78efb9 | Python | 2,957 | 87 | # 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... |
a57e77f3cf6b15e304bf90b355e84c8883513238fc01a220cb767e0dbb5c429c | Python | 2,957 | 95 | import tensorflow.keras.layers as layers
def add_layer(x, ch, drop, architecture, arch_params):
"""
Passes the input tensor layer to the model according to the arcitechture specified
"""
if architecture == 'conv_1D':
conv_size = arch_params.conv_size
x = conv_bn_activate(x, ch, conv_s... |
4fd03b1d4851a202f9a1c05898b79bd1b5434e9d57a07af8d6bf2a59c5962665 | Python | 2,962 | 61 | from utils.decomposition import Decomposition
import sparse
from tensorly.contrib.sparse.decomposition import tucker
class ParafacDecomposition(Decomposition):
def apply(self):
tensor = self.get_tensor_coocurrence(self.config.embedding.size_word_co_occurrence_window,
... |
3babe95f1bd104fdb1f54e49e68e2a12478933058d6a09c2a46401e80fab06c9 | Python | 2,963 | 80 | # 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... |
352297c1cc44196fd6c713a3137072995524fd23d3bb3c1f81f0b5645c06eece | Python | 2,967 | 106 | """
File: storage_container.py
Created: 2020/10/14
Last Changed: 2020/10/21
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, eith... |
6b2cef18adcbb84623874b728f3d6b6b1b3cd9378d5820045d81d8d96e8af5e9 | Python | 2,968 | 75 | #%%
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from tqdm import tqdm
import pymaid
from pymaid_creds import url, name, password, token
from data_settings import data_date_projectome
rm = pymaid.CatmaidInstance(url, token, name, password)
# this CSV comes from a script... |
0d274c20a7cab3a4511ac45ae204bd4a31bb45640768b4e04a52045c3edb1cb4 | Python | 2,969 | 93 | '''
Written by Nathan Neeteson.
A class for creating a csv file with a header and then writing data to it.
Initially created for logging training results, but also turned out to be
useful for recording results from test data and morphological analysis.
'''
import csv
from datetime import datetime
class LogWriter(obj... |
11f9715a887691b8e64d762b28846b6bffa86854bc98e649beb49e1bd1da57ae | Python | 2,970 | 89 | """
Utilities for traversing Ontology Graphs
====================
"""
import logging
from copy import copy
from typing import Iterable, List, Union
from oaklib.interfaces.basic_ontology_interface import (
RELATIONSHIP,
BasicOntologyInterface,
)
from oaklib.types import CURIE, PRED_CURIE
# PATH = Tuple[CURI... |
58978498f3eca8b5c2e51cd246fb9fe15c6baa8c96efae61d03cb7dc90bb7e69 | Python | 2,971 | 81 | # 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... |
c48bd0bab008925633289934af894ff217c30d3d07d1726a0a8f774714eaf287 | Python | 2,971 | 71 | from tempfile import TemporaryDirectory
import shutil
import os
import sys
class Module():
def __init__(self, module_pointer):
self._ptr = module_pointer # ptr to module function
def run(self, simulation):
return self._ptr(simulation)
class Simulation():
class SharedFiles(): # Contains ... |
dfe04f07938d375f0acf1b6b3ed1376826a700d1389b972ad5d180eb7e66d856 | Python | 2,972 | 80 | import logging
import unittest
from oaklib.datamodels.vocabulary import IS_A, PART_OF
from oaklib.implementations.pronto.pronto_implementation import ProntoImplementation
from oaklib.resource import OntologyResource
from oaklib.utilities.graph.networkx_bridge import relationships_to_multi_digraph, transitive_reduction... |
1927d7c155eec85ee169c12f949309d4f7ef71d00407d865f48e6e5dae0ed044 | Python | 2,974 | 86 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
70fd712f9032ffb4a0fbef48e37eee1dcfe24d2ff9a86eda038cc49b789ec4d9 | Python | 2,974 | 102 | import os
import sys
import glob
import numpy as np
import matplotlib
import socket
MACHINE = socket.gethostname().lower()
datadir = '/home/satsingh/plume/plumedata/'
if MACHINE == 'mycroft':
datadir = '/data/users/satsingh/plumedata/'
if (MACHINE == 'salarian') or (MACHINE == 'cylon'):
datadir = '/data1/users/satsi... |
16f3465ce16e0fd6464d46bb31471b9ff87afcb348d82e90e1fc1ba88534997c | Python | 2,975 | 104 | import unittest
from oaklib.implementations.pronto.pronto_implementation import ProntoImplementation
from oaklib.resource import OntologyResource
from oaklib.utilities.axioms.logical_definition_summarizer import (
logical_definitions_to_matrix,
parse_axes_to_config,
)
from tests import INPUT_DIR
TEST_ONT = IN... |
798e4cb8d57db803b8b5ce32b389aae0ba69819d1ad94699cfbd9db6b19a6d48 | Python | 2,977 | 102 | #!/usr/bin/env python
# coding: utf-8
# Transformer Dose Calculation
## Import libraries and define auxiliary functions
import h5py
import json
import random
import sys
sys.path.append('./src')
import numpy as np
from generators import DataGenerator
from models import dota_energies
from preprocessing import DataResca... |
9929ebfa07551d0b0fbb5e13bcc615d949a95b21381c51e7c6d07c39a6e30486 | Python | 2,977 | 65 | import numpy as np
from cenfind.core.measure import Assigner
from cenfind.core.structures import Centriole, Nucleus
def _square_contour(x0, y0, size):
return np.array(
[[[x0, y0]], [[x0, y0 + size]], [[x0 + size, y0 + size]], [[x0 + size, y0]]],
dtype=np.int32,
)
def test_assign_centrioles_... |
f1268f099453a9067810df601dd9a7bc2a2c952d972c7b4b2fc4ae336fc728c5 | Python | 2,978 | 55 | # 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... |
6ed76abb4cdd6ef1f10ceaa4c9e2a87c3544323d15ba3430b2d1362be8cf8180 | Python | 2,979 | 88 | import os
import time
import pandas as pd
import numpy as np
from arboreto.utils import load_tf_names
from arboreto.algo import grnboost2
from sklearn.preprocessing import scale
## Plots
import matplotlib
# matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors
impo... |
d78ba973b6665bd9f3f031344895b5967d35f6e28f223e05b87c6b485f42f70c | Python | 2,983 | 103 | # Copyright 2017 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... |
11496fcdebe24eceb665084c33c77943f11aab3c61ad7d0344958e650ff0be92 | Python | 2,984 | 54 | from __future__ import print_function
from cmseq.cmseq import CMSEQ_DEFAULTS
from cmseq.cmseq import BamFile
from cmseq import __version__
import pandas as pd
import numpy as np
import argparse
def bd_from_file():
parser = argparse.ArgumentParser(description="calculate the Breadth and Depth of coverage of BAMFILE... |
233e8149044a329a58f996f7931549d0b9535fbad5e6a8a8889f20b596ce4eb4 | Python | 2,984 | 103 | import torch.nn as nn
import torch.nn.functional as F
import torch
class U_Net(nn.Module):
def __init__(self, classes=2, aux=True):
super(U_Net, self).__init__()
n1 = 64
filters = [n1, n1 * 2, n1 * 4, n1 * 8, n1 * 16]
self.Maxpool1 = nn.MaxPool2d(kernel_size=2, stride=2)
... |
cbac50884ea798d8a0de5f2f25f88490fe2247b6d005a395a170d66126e31fb9 | Python | 2,985 | 95 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
8098a348fdc7887cd5326ab6712179dfb7bfc61f223c85a565c16b9326226d0f | Python | 2,987 | 69 | BaseCase = __import__('base_case').BaseCase
import pytest, os, subprocess
class TrackingTest(BaseCase):
@pytest.mark.slow
def test_basic_tracking_success(self):
self.open_main(static=False)
#open the tracking tab
self.click('a:contains("Tracking")')
filenames = [
... |
b0bde087df68b1c249fa9b2705acd5ec8cff7a75a3dea62ea49247db5320b207 | Python | 2,987 | 96 | import time
import torch
import pandas as pd
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
from torch_geometric.utils import from_networkx
from sklearn.model_selection import train_test_split
from graphxai.datasets.utils.bound_graph import build_bound_graph
from graphxai.gnn_models.node_cla... |
c10c0d24ffa94ff8677466cf899a0d0323c1a391a8ed6539e2f2579525f1a2f1 | Python | 2,989 | 101 | # This script is part of navis (http://www.github.com/schlegelp/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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 3 of... |
1cd03bcb6208658d9e084d0c24d03f4934d4e0a3fb47dd7ab95aed49ba8e081e | Python | 2,990 | 82 | import requests
import gzip
import nibabel as nib
import numpy as np
from os.path import isfile
def init_brainweb():
"""
Download the Brainweb Phantoms if they do not already exist in the current directory
"""
if not isfile('classes.mnc'):
print('Downloading classes')
params = {'downlo... |
9a1a6506f530cbc0cd603ce125aa9372db4d17296cd6ce49c8b7da1fb632f0e2 | Python | 2,990 | 82 | import csv
import pickle
import numpy as np
from tqdm import tqdm
from chemprop.args import SklearnPredictArgs, SklearnTrainArgs
from chemprop.data import get_data
from chemprop.features import get_features_generator
from chemprop.sklearn_train import predict
from chemprop.utils import makedirs, timeit
@timeit()
de... |
ae97d4b5c7cb3d2c7a4b4b0af8899dcaedc7fd3ff7373c8248e7467cce7aa343 | Python | 2,990 | 71 | ##########################################################
## ccAF: sensitivityAnalysis_plot.py ##
## ______ ______ __ __ ##
## /\ __ \ /\ ___\ /\ \/\ \ ##
## \ \ __ \ \ \___ \ \ \ \_\ \ ##
## \ \_\ \_\ \/\_____\ ... |
65ed40a741b94b4e7606ef5645b8c2584749c8ee0defc0982acf0475af857c18 | Python | 2,992 | 70 | def parse_info(seq):
info = {'SVTYPE': '', 'SVLEN': 0, 'END': 0}
for i in seq.split(';'): # SVTYPE=INV;END=139008588;SUPPORT=13;STD_SPAN=4.4;STD_POS=1.5
if i.split('=')[0] in ['SVLEN', 'END']:
try:
info[i.split('=')[0]] = abs(int(i.split('=')[1]))
except:
... |
de9669856bf299de6efd687be45c8ca1d6968a43a81d1ab3f7d3368a387457db | Python | 2,992 | 97 | import math
import glob
import argparse
parser = argparse.ArgumentParser(description='Create slurm jobs to call genotype on merged gVCFs (all batches within the directory)')
parser.add_argument('merged_vcf_dir', help='Directory that contains the merged gVCFs')
parser.add_argument('jobs_dir', help='directory to write... |
e45057721dd1d229aec9c1240f7eb3b45226a6c6f08a68531bdb9cf3a3242ef8 | Python | 2,993 | 85 | import gzip
import argparse
parser = argparse.ArgumentParser(description='Get top SNPs for metabrain and eqtlgen')
parser.add_argument('metaBrain', help='File with the metaBrain results')
parser.add_argument('eqtlGen', help='File with the eqtlGen results')
parser.add_argument('output', help='Output file name')
parser.... |
6b60a589eccae3703db576ff1e53ea66760a1cb2a1c455625a3af3b9b7e9950c | Python | 2,995 | 87 | # 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... |
924a682540a3ad790eb93121d9a22096a150679b0cb7fa1dc991b1ef85186210 | Python | 2,996 | 82 | # 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... |
b5d8d0126ed0d9668db54252e29594b2978ba9829995b11b213058118da923e2 | Python | 2,996 | 113 | # 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... |
1d20b8bfea61f3a8d266e7ab5be2a8f87ef92037e18adefca429665fd2a6911a | Python | 2,997 | 84 | import os.path
import torch
from torch import nn
import torch.optim as optim
from base import BaseModel
import copy
class Forward(nn.Module):
def __init__(self, in_dim: int):
super().__init__()
self.fwd = nn.Sequential(nn.Linear(in_dim, 2*in_dim), nn.LeakyReLU(), nn.Linear(2*in_dim, in_dim), nn.L... |
4d31298ba04b3616e310dee1f97436569fa6cb85690e9228350561c5c2056d75 | Python | 3,000 | 86 | # coding: utf-8
## Import libraries and define auxiliary functions
import h5py
import json
import numpy as np
import time
import sys
sys.path.append('../src')
from models import dota_energies
from preprocessing import DataRescaler
from evaluation import gamma_analysis
start = time.perf_counter()
# Load model and data... |
95faae74d2f9104671efb28dcc0048724e24401a3a43fbea1e4e2944250637ab | Python | 3,000 | 99 | '''
Loads data sets
magic_load_data: only useful for data with old formats.
'''
from brian2 import *
from clampy import *
import os
from .data_preparation import merge_data
from .file_utils import up_dir
__all__ = ['rename_electrophysiology_data', 'magic_load_data', 'load_multiple_data']
def load_multiple_data(path,... |
1391d9e85dd68563563e2dfb788b1c6d4df8ad87e5d2cd1839a03cc70c6c8b29 | Python | 3,001 | 104 | import os, errno
import sys
import time
from random import shuffle
import random
def read_cases(path):
cases = []
headers = []
with open(path, 'rb') as csvfile:
reader = csvfile.readlines()
n = len(reader[0].split())
for i, row in enumerate(reader):
case = row.split()[:]... |
2dd011e76764847d818294a08d9d469cb492a9e377195a5e3488be10d433f827 | Python | 3,002 | 68 | import numpy as np
import numpy.testing as npt
import nibabel as nib
from AFQ.utils import streamlines as aus
import dipy.tracking.streamline as dts
from dipy.io.stateful_tractogram import StatefulTractogram, Space
def test_SegmentedSFT():
affine = np.array([[2., 0., 0., -80.],
[0., 2., 0.... |
a848852574bba443f7c8e4f808790602fe93a6c5e175f8416d73de4ffa80a6da | Python | 3,002 | 80 | import torch
import torch.nn as nn
from typing import List
import numpy as np
from torch.autograd import Variable
def cal_distance(m: torch.Tensor, n: torch.Tensor) -> torch.Tensor:
vector = m - n
distance = torch.norm(vector, p=2, dim=1)
torch.clamp_(distance, min=0.1)
return distance
... |
197fb2a3b6eb122a306947001504c13e6f47b7a992a842ebf04e0d27de41d173 | Python | 3,004 | 91 | # This script is part of navis (http://www.github.com/schlegelp/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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 3 of... |
85061e32a0828c0427a2b11a4e98b51b434c096c849e1985b9928f380bd862e8 | Python | 3,004 | 95 | """
PARAMETERS: Documentation
This module specifies all the parameters necessary for a neuronal papopulation made up of:
- Excitatory cells
- Inhibitory cells
"""
from brian2 import *
cm_fig_conv = 1/2.54
rc('font', size=6)
###########################################
# User defined parameters
###################... |
f3441002cb6aaa59c6d68c58e155a178c51c2a768f5b5691151cc226707d9216 | Python | 3,004 | 98 | import pytest
import torch
# Skip tests if torch_harmonics is not installed
try:
import torch_harmonics
except ModuleNotFoundError:
pytest.skip(
"Skipping because torch_harmonics is not installed", allow_module_level=True
)
from ..discrete_continuous_convolution import (
DiscreteContinuousConv... |
fac8b2c040fb50e8c5df54558410c73f4284a2567b91bb090fcaa036481ac9de | Python | 3,005 | 86 | import h5py
import numpy as np
class ImageDataset():
def __init__(self):
self.velocity_colnames = ['u', 'v', 'w']
self.venc_colnames = ['venc_u', 'venc_v', 'venc_w']
self.mag_colnames = ['mag_u', 'mag_v', 'mag_w']
self.dx_colname = 'dx'
def _set_images(self, velocity_images,... |
763960f1c2757c3c2900a536a2395f07d6be17ba1f5ec99bab46fc767b8ab0c5 | Python | 3,008 | 81 | #!/usr/bin/env python3
"""``uvx`` stand-in installed as ``/usr/local/bin/uvx`` in the image.
cosmos-transfer2.5 resolves every checkpoint with
``uvx 'hf>=1.3.5' download <repo> [<file>] --revision <sha> [--include ..] [--exclude ..] [--quiet]``
(``cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py``). Inside the... |
d99ee6651034ae0c19df997d97f752de96b207b77defd82839afdf270b86eabb | Python | 3,008 | 81 | # 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... |
589ba2b3dee88d0236886fc898e662528abf1a66f0df57f4611d9d895119317a | Python | 3,009 | 98 | # -*- coding: utf-8 -*-
from .core import *
from .. import _logging as logging
import tensorflow as tf
__all__ = [
'ExpandDimsLayer',
'TileLayer',
]
class ExpandDimsLayer(Layer):
"""
The :class:`ExpandDimsLayer` class inserts a dimension of 1 into a tensor's shape,
see `tf.expand_dims() <https:/... |
5e77a643b144c7cf6d8204878f1fa1764717a525fa69d48fd9c605d56687dca1 | Python | 3,009 | 89 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 13 11:54:09 2020
@author: Sandi
"""
import pandas as pd
import numpy as np
from datetime import datetime
from sklearn.model_selection import train_test_split
from sklearn.model_selection import GridSearchCV
from sklearn.neural_network import MLPRegressor
from sklearn imp... |
292a2565b226bff6caccc198c193ba201581adbe9f5ec67866dda53ca12f7845 | Python | 3,011 | 44 | import pandas as pd
import numpy as np
import argparse
import sys
from cmseq import __version__
from .cmseq import CMSEQ_DEFAULTS
from .cmseq import BamFile
def polymut_from_file():
parser = argparse.ArgumentParser(description="Reports the polymorpgic rate of each reference (polymorphic bases / total bases). Focuses... |
e1d3ab4aa201451f725fc9c18ef6d2e1376b87b3be0a75300ee4f29b42d98e41 | Python | 3,012 | 116 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import datetime
import timeit
class Timer(object):
"""A timer as a context manager.
Modified from https://github.com/brouberol/contexttimer/blob/master/contexttimer/__init__.py.
Wraps around a t... |
587f31cd2e3a449928e45b2300d2f9a1971cfd83d88bb09dcb50da2c254de07d | Python | 3,014 | 82 | import csv
import sys
import numpy as np
import pandas as pd
from scipy import stats
## Tests for significantly higher mean validation R^2 after adding data manipulations when compared to (a) the results of Dadi et al. in the
## 10k UKB release and (b) our replication of those results in the 20k UKB release.
def sig... |
c4a60c164277dc158fdbd53dd6de6ab36bf0acde8770eb7231250eb64cb6aaf4 | Python | 3,015 | 87 | ####################################################################################################
# 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 program is free ... |
05f99feca74f9e929df61c0672dc2d569d8cc6368ae7510c97a480ab021fe14d | Python | 3,016 | 72 | import nibabel.tmpdirs as nbtmp
import nibabel as nib
from nibabel.streamlines import ArraySequence as Streamlines
import numpy as np
import os.path as op
import numpy.testing as npt
import dipy.core.gradients as dpg
from dipy.data import default_sphere
from dipy.reconst.gqi import GeneralizedQSamplingModel
from AF... |
0879075a89476e6001ae41eaee0a80dbbb478c54565ca76757f101881790a231 | Python | 3,016 | 84 | from rdkit import Chem
from drugex.logs import logger
from drugex.data.corpus.interfaces import Corpus
from drugex.data.corpus.vocabulary import VocSmiles, VocGraph
class SequenceCorpus(Corpus):
"""
A `Corpus` to encode molecules for the sequence-based models.
"""
def __init__(self, molecules, vocab... |
09414b7eb1a81f0533e6a07fd2b1acbd28e447c74193cc4e8f348b65e7a37548 | Python | 3,016 | 77 | # 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... |
6cd30224d26a0c7e00c6da57321a67fbe6b2db1aeabe4e14c6b8a7418db75758 | Python | 3,016 | 139 | # %%
import numpy as np
import pandas as pd
import logging
from box import Box
import matplotlib.pyplot as plt
import pathlib
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("offset", type=int,
help="processing_offset_filenum")
args = parser.parse_args()
print(f"proc... |
df8fcc3b1efa5cacb04ccf7d364b30917e1b5f782662358d93398431c36bd5dc | Python | 3,016 | 81 | """CARLA left-handed to Alpamayo right-handed coordinate conversions."""
from __future__ import annotations
import math
from collections.abc import Sequence
import numpy as np
Y_REFLECTION = np.diag([1.0, -1.0, 1.0])
def carla_rotation_matrix(pitch_deg: float, yaw_deg: float, roll_deg: float) -> np.ndarray:
... |
5b5c1a28f58864bf3603e0ad6901771dffa6211b81d330de6809a8c906f1b79a | Python | 3,023 | 94 | from __future__ import annotations
from bonelab.util.aim_calibration_header import get_aim_density_equation
from bonelab.util.vtk_util import vtkImageData_to_numpy
import numpy as np
from enum import Enum
# create an ImageType Enum with two options: density image or mask
ImageType = Enum("ImageType", "DENSITY MASK")
... |
d98b7877b340fe64b3b5faf5d397cf80762d0e61886bafef68845a4f8a492681 | Python | 3,023 | 91 | from scipy.special import expit
import numpy as np
import os
def mean_squared_error(prediction, target, exclude_diagonal=False):
"""Calculate the mean squared difference between two numpy arrays
:param prediction: Predicted values
:param target: Target values
:param exclude_diagonal: If True, ignore... |
2301fde4a056de4c1922106727ab3aa4e63c04dae5f3c4afe8848013895c9114 | Python | 3,024 | 87 | # %%
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from pymaid_creds import url, name, password, token
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
import connectome_tools.process_matrix as pm
import connectome_tools.celltype as ct
import navis
... |
43ca3a9b52dc13c8efb5484a35225d3299f4b5484e1e636ce652771f221671ed | Python | 3,024 | 82 | # 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... |
9b88a8ca3fa322db422648a8eabda787f155495f6d93ae5c22cba758a52121c7 | Python | 3,024 | 54 | # Usage: python3 multiple_fasta.py -i Fastas/ --cpu 4 --parallel 2
# (run 2 parallel instances of Porter5 on 4 cores - total of 8 cores)
import os, sys
import argparse
from multiprocessing import Pool
### parallel code ##
def loop(line):
if args.fast and args.tmp:
os.system('python3 %s -i %s --cpu %d --fa... |
a59887f95e9e47e492c5d4508fb0e837ff79a9f4b9b61f6fc95f98728919d7d5 | Python | 3,025 | 68 | #!/usr/bin/env python3
import wget
import os
import pandas as pd
import re
'''
Download the AAIndex from the official website, https://www.genome.jp/ftp/db/community/aaindex/aaindex1
And format it into CSV:
$ cat AAIndex.csv
A,R,N,D,C,Q,E,G,H,I,L,K,M,F,P,S,T,W,Y,V,AAIndex
4.35,4.38,4.75,4.76,4.65,4.37,4.29... |
b881706ff6966e23f75328175645b66e6d36f2a5b7ab0d76fd72315315a553bc | Python | 3,025 | 84 | # 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... |
d217f3b45d4f0177c10cdbe02ba4420a92fe597dfe29ade94260bc7ff32bc18d | Python | 3,025 | 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... |
697e3ed0f86b5713a2e2f574f2ab2d15c6fa2b1b9e6640a4969da9ac26b795d1 | Python | 3,026 | 47 | #Import necessary functions, set number of measurements to perform for mammalian cortical area development network
from functions import *
GiacoPath = "./28nets_rules/Giacomantonio2010.txt"
nrshots=10000
#Print a circuit for performing a synchronous state transition:
syncTransitionCircuit = synthesizeFullNetworkUpdate... |
131ceb837b3ff24a89d7a3b9ae7c7b30e0be01264207f2b179974428853bc729 | Python | 3,028 | 83 | # Copyright 2021 Xiaomi Corporation (Author: Junbo Zhang, Yongqing Wang)
# Apache 2.0
# This script trains a simple polynomial regression model to convert GOP into
# human expert scores.
import sys
import argparse
import pickle
import kaldi_io
import numpy as np
from concurrent.futures import ProcessPoolExecutor
fr... |
be003dd60267bf5090b4aa806b30ab17069f05c452116a753848c977853e188d | Python | 3,028 | 74 | import sys
import numpy as np
import n5_metadata_utils as n5mu
from glob import glob
from os.path import split
def read_coords(path):
with open(path, 'r') as f:
offset = np.array(f.readline().split(' ')).astype(np.float64)
extent = np.array(f.readline().split(' ')).astype(np.float64)
index ... |
4e0f91189d38af760e637b40e00fbaa5b9d88696dd5d3a0f1433c6a7047f1b98 | Python | 3,029 | 75 | # Copyright 2020-2022 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 agre... |
6635e9d529bb69c25ed70262877d60ca2ba74ad534cdfb02fec3072883dc8045 | Python | 3,029 | 80 | import torch
import matplotlib.pyplot as plt
import numpy as np
import argparse
import pickle
import os
from torchvision import transforms
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from PIL import Image
# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() e... |
f086a84863c4621ebb05e2215d47fa899023cea8329f0ff0c7cbb36b4f594451 | Python | 3,029 | 96 | """
This module provides the NonStrandSpecific class.
"""
import torch
from torch.nn.modules import Module
from . import _is_lua_trained_model
def _flip(x, dim):
"""
Reverses the elements in a given dimension `dim` of the Tensor.
source: https://github.com/pytorch/pytorch/issues/229
"""
xsize = ... |
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