sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
74bcda1fdf27444c2c3cd500e1134a06fcc45a3b58515ce374162e085a891d00 | Python | 1,063 | 52 | from abc import ABC
from typing import Iterable
from oaklib.interfaces.basic_ontology_interface import BasicOntologyInterface
from oaklib.types import CURIE
class SkosInterface(BasicOntologyInterface, ABC):
"""
presents ontology as simple SKOS vocabularies
`SKOS <https://www.w3.org/2004/02/skos/>`_
... |
fd156ad5d1e55f482054f664458b03b7d96309c3ba8eb4c217d784b5b0d6acdd | Python | 1,063 | 55 | from builtins import object
import abc
from future.utils import with_metaclass
class Transform(with_metaclass(abc.ABCMeta, object)):
"""Abstract class for geometric transforms."""
@abc.abstractmethod
def apply(self, source, grid=None):
"""Apply the transform to raw source data.
Paramete... |
164d8a6f581068a3dc856abc6d914ad34cc5cfec2c29678112883e7856a9e065 | Python | 1,064 | 26 | """
Copyright 2020 - by Jerome Tubiana (jertubiana@gmail.com)
All rights reserved
Permission is granted for anyone to copy, use, or modify this
software for any uncommercial purposes, provided this copyright
notice is retained, and note is made of any changes that have
been made. This softwar... |
6f5616f7b2e6b20d331f322492253d508e0f7a9239aa2006a24cf82fc0a17aa8 | Python | 1,064 | 29 | # %%
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)
from contools import Promat
from data_settings import data_date, pairs_path
# %%
neurons = pymaid... |
95b944fe4ccbd0db76467d87e87f20baa3bbded14ab313499fe27a95bbb26503 | Python | 1,064 | 22 | import random
# Very simple fake genotype file to showcase how to run Decon method
# Also write the snp-gene file for which combination needs to be tested
with open('count.table.simulated.txt') as input_file, open('gene_snp_file.txt','w') as out, open('fake_genotype_dosages.txt','w') as out2:
x = 0
out.write('... |
715996bfc8abba95ac0fc33d94116d2b4a3b78a4a76cab7b97436edd556d9249 | Python | 1,065 | 36 | # -*- coding: utf-8 -*-
from collections import OrderedDict
import torch.nn as nn
import torchvision.models as tv_models
from utils.model_summary import model_summary
class CCustomNet(nn.Module):
def __init__(self):
super(CCustomNet, self).__init__()
a = list()
a.append(('conv_0', nn.Co... |
bccc44c33f77df89433cff29062252d0b0709e7ef118e4086fcaad4a9fa65f27 | Python | 1,065 | 36 | # 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 a... |
357cd4571878d93ae0199d3e4f6bfab4ca0765b150c559173d78118c94e7e1ce | Python | 1,066 | 27 | # 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... |
f600a68e4e3a2477fefcf9f803b3c318331b2adb9545c1187895c979496edc84 | Python | 1,066 | 21 | ####################################################################################################
# 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... |
f8c59f4ed985cc19d340d268efe9769f9f09cb8c22b7c84cbb7efba8dea71ef6 | Python | 1,066 | 27 | # 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... |
d26ede75343aebea73cb2dd02a31a90bffec663ef801d23856aa825812638050 | Python | 1,067 | 37 | # 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 a... |
155f82efa7b17418866710dabacb1b30f59275d9fdef2c7f47fb9bf14ae8f74d | Python | 1,068 | 27 | from glob import glob
import shutil
import os
from sphinx_gallery.scrapers import figure_rst
class PNGScraper(object):
def __init__(self):
self.seen = set()
def __repr__(self):
return 'PNGScraper'
def __call__(self, block, block_vars, gallery_conf):
# Find all PNG files in the dire... |
37accdb6d2c47794eb31fdc2c9d35a8a34a8811e4b46fbd2226b4db07d09dbc0 | Python | 1,070 | 37 | _base_ = '/home/Thanaporn/mmdetection_v2_2/mmdetection/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='torchvision://resnet101',
backbone=dict(
type='ResNet_MD',
depth=101,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm... |
8eaecea4ed3cefd7e32ae57c407054a379aa2debb350a1350ce8802f18c35c91 | Python | 1,070 | 41 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2016, Johannes Köster"
__email__ = "koester@jimmy.harvard.edu"
__license__ = "MIT"
from snakemake.shell import shell
from os import popen
outfile = snakemake.output[0]
compress_flags = ""
if outfile.endswith("vcf.gz"):
compress_flags = "-Oz"
elif outfil... |
b2edb96b498fd4f8fb95a38c119e89996b9530b57f49c02d4c892c5de78a2760 | Python | 1,070 | 26 | rule preprocess:
output:
bookmark_file='{name}/.poreplex_preprocessing_done',
adapter_inventory='{name}/adapter-dumps/inventory.h5'
threads: 40
run:
input_dir = config['data'][wildcards.name]
output_dir = os.path.dirname(output.bookmark_file)
shell('poreplex --input "... |
2bf8963f336e45a295d2f25a90a8e850936725f807cf67cf2eceeb4b3ca8c5e3 | Python | 1,071 | 25 | # 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... |
8e1be9b7adda72fd49af1cf1816687b4a9ec6bffaab64e9c91c902624e5d72df | Python | 1,071 | 48 | import unittest
import grr.ThresholdModel_testutil as tmt
from grr.GIF import GIF
# SIMULATION TESTS
class TestGIFSimulateDoesNotCrash_VectorInput(
tmt.TestSimulateDoesNotCrash_VectorInput, unittest.TestCase
):
def setUp(self):
super(TestGIFSimulateDoesNotCrash_VectorInput, self).setUp()
se... |
c2c5224590316618901e7ff5af6377a7bf07364dda45a592aef941c663e8a7b2 | Python | 1,071 | 21 | ####################################################################################################
# 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... |
b621207c93892311446a8d0819274ed8f77fb6d77b600c70a821d37569f8e62a | Python | 1,072 | 50 | '''
Fig. 11.
Collective behavior.
'''
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 = 8, 3
dt = 33*ms
duration = 200*secon... |
e384183cf57f0b39c66423fc18b8912e6f3f259d00f5ce86a0632b5ff9df5ec0 | Python | 1,072 | 16 | """montage.py OUT.webp W H MS IMG[:LABEL[:croptop]] ... -> animated webp, one still per frame."""
import sys
from PIL import Image, ImageDraw, ImageFont
F = ImageFont.truetype('/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', 30)
out, W, H, ms = sys.argv[1], int(sys.argv[2]), int(sys.argv[3]), int(sys.argv[4]); f... |
a6b937feb709c060f852ad5672b572e624db99f38e3faf2b03ecbd30333f11e6 | Python | 1,074 | 47 | """
core
Created by: Martin Sicho
On: 21.04.22, 22:03
"""
from rdkit import Chem
from drugex.molecules.interfaces import Molecule
class InitializationException(Exception):
pass
class DrExMol(Molecule):
def __init__(self, rd_mol, identifier=None):
if not rd_mol:
raise InitializationExc... |
4d07b5c02ee17bc4ce24beb3b403440a0b8a4758a843c95859192ba033d8ffc5 | Python | 1,076 | 52 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of modes and run id, e.g. python 3_get_inf_params.py 6 1")
exit()
n_modes = int(argv[1])
run = int(argv[2])
#%% Import packages
import os
import pickle
import numpy as np
from osl_dynamics.data import Data... |
5ac48c8ca3b3af7b735b57bb677648c622e33da2222174d202b56d918dfba586 | Python | 1,077 | 27 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from itertools import chain
from numpy.testing import assert_array_equal
from eelbrain import datasets, epoch_impulse_predictor
from eelbrain._trf.shared import RevCorrData
def test_segmentation():
ds = datasets.get_uts()
n_times = len(ds['uts'].time)... |
c2df004dc04f140f21f2bc9ad32a185593f05fd54a0694b8fbf29fe81feb7511 | Python | 1,078 | 24 | ####################################################################################################
# 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... |
119232aaa3fe02c051605a307629afeeb46b9a51efedac331096e653d94f1bf3 | Python | 1,079 | 35 | import torch.nn as nn
from .registry import PADDING_LAYERS
PADDING_LAYERS.register_module('zero', module=nn.ZeroPad2d)
PADDING_LAYERS.register_module('reflect', module=nn.ReflectionPad2d)
PADDING_LAYERS.register_module('replicate', module=nn.ReplicationPad2d)
def build_padding_layer(cfg, *args, **kwargs):
"""Bu... |
5f41ecce7442d6832658879c565e34b10480d80a1989e9215d0cbe6d7b087fd0 | Python | 1,081 | 20 | ####################################################################################################
# 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 ... |
ca985711a983b896baf8e8eb09974087692f0b33013ed18666c43bc0b2bebea1 | Python | 1,081 | 38 | from PrognosAIs import Pipeline
import evaluate_model
from PrognosAIs.IO import ConfigLoader
import argparse
from slurmpie import slurmpie
import os
import sys
from glob import glob
model = sys.argv[1]
input_folder = sys.argv[2]
output_folder = sys.argv[3]
config_file = sys.argv[4]
# make label file, stupid requireme... |
64ed2cf7d24c543339db612b1dc9d3dc307a6830a10aa4c1a0ea4cc890c2a3da | Python | 1,082 | 41 | from snakemake.shell import shell
import pysam
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
sort_cmd = ""
fq1=snakemake.output.fastq1.split(".gz")[0]
fq2=snakemake.output.fastq2.split(".gz")[0]
bamtofastq_cmd = (
" bedtools bamtofastq -i {snakemake.input.bam_file} "
"-fq {fq1} "
"-fq2 {fq2}; ... |
8f178377073bf7f839ed11cb5a6ac9ca381a71d6781aeeb3bbe4a99bfca38a02 | Python | 1,082 | 34 | from abc import ABC, abstractmethod
from torch.utils.data import DataLoader
from moses.utils import set_torch_seed_to_all_gens
class MosesTrainer(ABC):
@property
def n_workers(self):
n_workers = 1
return n_workers if n_workers != 1 else 0
def get_collate_device(self, model):
n_wor... |
e5667e438b8b75fc4a9ad22b3a0e66759817f121239b4946002877a013ea16dd | Python | 1,082 | 36 | # -*- coding: utf-8 -*-
"""
@author: Satoshi Hara
"""
import sys
sys.path.append('../')
import numpy as np
from AlternateLinearModel import AlternateLogisticLasso
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import TfidfVectorizer
# get news20 data (science)
categories = ['sc... |
e758a3773cfb19689f4b9b2b32d498731bc3d01da7655a6dec6da442c13feed1 | Python | 1,084 | 35 | """
© 2022, ETH Zurich
"""
import json
import os
ROOT_PATH = os.path.dirname(os.path.dirname(__file__))
DATA_PATH = os.path.join(ROOT_PATH, "data")
PROC_DATA_PATH = os.path.join(ROOT_PATH, "proc_data")
FOLDER_NAMES = {"az": "az_set", "inhouse": "inhouse_data"}
MODEL_FILENAMES = {"rf": "rf.joblib", "lasso": "lasso.j... |
80967dc06cf69d74480d301cf0a601af307cae3a3e701cc4d22463e018f8198e | Python | 1,085 | 21 | ####################################################################################################
# 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 ... |
81748984adb6df0cb41d1504fd852ef239387c95d9a05133618ea2b930468152 | Python | 1,085 | 36 | import torch
import torch.nn as nn
from torch.autograd import Variable
def create_var(tensor, requires_grad=None):
device = torch.device("cuda:" + "1") if torch.cuda.is_available() else torch.device("cpu")
if requires_grad is None:
return Variable(tensor).to(device)
else:
return Variable(te... |
d3f4b4b29e9f20ec53e04c5124b72c9dfda3fa0035ee6584bc9823eacffd8792 | Python | 1,086 | 20 | ####################################################################################################
# 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 ... |
fdc7cb4d957c5059578002694dc9e30533df8dee4f86648acfcda3c3f775a783 | Python | 1,086 | 37 | import argparse
from scripts.experiment_1 import Exp1
from scripts.experiment_2 import Exp2
from scripts.experiment_3 import Exp3
from scripts.experiment_4 import Exp4
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Optional app description')
parser.add_argument('--exp', type=str)
parse... |
4cd170d498066f5803b31cb317932e9b3bee9f06f485a259ef5eac523125d287 | Python | 1,087 | 36 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .models import ModelConfig, FNOGNO_Small3d
from .opt import OptimizationConfig, PatchingConfig
from .wandb import WandbConfig
class CarCFDDatasetConfig(ConfigBase):
root: str = "~/data/car-pressur... |
3a3ff4ead30adbcf56008a56b45af5de92d3d408e825c8b080fc64ad697809b8 | Python | 1,088 | 29 | # 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... |
b870d512b648f4e788b3b3f147ac36dce5fd58a615237a6bb116a5e74c7697e0 | Python | 1,088 | 21 | ####################################################################################################
# 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... |
ded12a3414a1092a64f3de9b9a4d8d490b4d9fdc80c44cd96aa04e17b6c802de | Python | 1,088 | 21 | ####################################################################################################
# Copyright (c) 2019 - 2022, 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 ... |
e77ebc67c84e530bb3f3428fce7901d2cf2a2e794c63b9d680777f80308235c0 | Python | 1,088 | 37 | #%%
import pandas as pd
import numpy as np
from pymaid_creds import url, name, password, token
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
# %%
# dennotate / remove single annotation
annot = 'something'
pymaid.remove_annotations(pymaid.get_skids_by_annotation(annot), annot)
# %%
# deanno... |
474ac354dae28235d9c6f49c1aaad29a9024e348115619b775308047715bf32c | Python | 1,089 | 40 | # global_vars.py: Global variables used by MaSIF -- mainly pointing to environment variables of programs used by MaSIF.
# Pablo Gainza - LPDI STI EPFL 2018-2019
# Released under an Apache License 2.0
import os
from IPython.core.debugger import set_trace
epsilon = 1.0e-6
msms_bin= ""
if 'MSMS_BIN' in os.environ:
m... |
a1b3853c62d85b6896a2758f992e8b6926f6fd0eb6937c9c8571b216e43e1c18 | Python | 1,089 | 42 | import seaborn as sns
import matplotlib.pyplot as plt
colors = {
'ser': sns.color_palette()[0],
'som': sns.color_palette()[1],
'pyr': 'gray',
'fit': 'black',
'm': sns.color_palette()[2],
'h': sns.color_palette()[3],
'n': sns.color_palette()[4],
'4AP': (207./255., 2./255., 52./255.), # ... |
d0547e796bb9b7713b49a4916adc9af6595842ab9c8a2a46e3c00259f093c2ea | Python | 1,089 | 34 | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from config import cfg
import torch.nn as nn
from math import sqrt
import torch
from torch.autograd.function import InplaceFunction
from itertoo... |
3c19020d69ea493b076bf67b95b5bf1dc33216164cc31d2706f1adface2d7487 | Python | 1,090 | 31 | import random
import torch
from torch.autograd import Variable
class ImagePool():
def __init__(self, pool_size):
self.pool_size = pool_size
if self.pool_size > 0:
self.num_imgs = 0
self.images = []
def query(self, images):
if self.pool_size == 0:
retu... |
420af966fef2f9e630b0fc6e809fb0918e8bf69e647a569b2410fd180cc78cf3 | Python | 1,090 | 30 | import unittest
from deeprank_gnn.GraphGenMP import GraphHDF5
class TestCreateGraph(unittest.TestCase):
def setUp(self):
self.pdb_path = './tests/data/pdb/1ATN/'
self.pssm_path = './tests/data/pssm/1ATN/'
self.ref = './tests/data/ref/1ATN/'
def test_create_serial_with_bio(self):
... |
61687f5f7980dddee03f0ab6c0e7f845fa7c6c3d08ddc254a5ee4314bebf1a13 | Python | 1,090 | 49 | '''
Figure 11.
Shows snapshots of chemotactic trajectories.
'''
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 = 8, 3
dt = ... |
67a7c67b7a9fe97d5078555b5d5b23e2254f7950b0d272406791298bd43eddc2 | Python | 1,090 | 37 | import os
import sys
import numpy as np
root_path = os.path.realpath("./")
sys.path.append(root_path)
import pytest # noqa E402
from hebbcl.parameters import parser # noqa E402
from utils import eval, choicemodel # noqa E402
def parse_args(args):
return parser.parse_args(args)
class TestSampling:
def t... |
652b44607dba9293b1ca7cbb173171c7bf91c54ef22f3385a0a0ac1e77c50fda | Python | 1,091 | 26 | # 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... |
6dd534a67ec40c171099571045da9af5a00f6001c0b1845314364564dd78e617 | Python | 1,091 | 44 | """MedMNIST-NAS-Bench: tabular NAS benchmark on MedMNIST v2.
Quick start
-----------
>>> from medmnist_nas_bench import load_metrics
>>> df = load_metrics("breastmnist", search_space="tiny")
>>> df[df["epoch"] == 100].nlargest(5, "test_accuracy")
Get raw predictions (for custom metrics)
------------------------------... |
81601dac4f79daa4873d46d139b706769feae703f23c8abf5e2e82733e2706d1 | Python | 1,091 | 40 | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the gradunwarp package for the
# copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
import logging
VERSION = 'HCP-1.0.3'
usage = '''... |
845b2d16b51084cc7ec66ce735ab8f7f8d29bc9782e30578de39d235a2b3c4c9 | Python | 1,091 | 29 | #!/usr/bin/env python
# Copyright (C) 2011 Genome Research Limited -- See full notice at end
# of module.
# Create a Python logger with the right parameters.
import sys
import logging
logLevel = logging.DEBUG
logFormat = '[%(levelname)s] %(asctime)-15s [%(module)s %(lineno)d] %(message)s'
logging.basicConfig( strea... |
b76c72325a4423c04e7bc4c9d1998f2b4c66d2b45e591d69d40b571b24028890 | Python | 1,091 | 31 | import pytest
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from pycpd import gaussian_kernel, deformable_registration
def test_2D():
X = np.loadtxt('data/fish_target.txt')
Y = np.loadtxt('data/fish_source.txt')
reg = deformable_registration(**{ 'X': X, 'Y': Y... |
4c65b4d965c8811d310196c4a4b5bba8f626dd6ae5d2d2e851342e40e7a6dde1 | Python | 1,092 | 17 | #!/usr/bin/env python3
"""Insert captions under images: add_captions.py CAPTIONS.json [--root CARLA_ROOT]
CAPTIONS.json maps page -> {image path as written in the page: caption html}. An image that already has
a caption line under it is left alone. Use <code>/<b> inside the caption (it is already italic, so a
nested <... |
962c7c5cfc541234f417548049feb4cfe0275d1750f0f8c27294e83e11370fa9 | Python | 1,092 | 52 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 3_get_inf_params.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
import os
import pickle
import numpy as np
from osl_dynamics.data import Da... |
09984a2009b4e2b8aee991d5c9d688557be09e93aedbd19d19d2ee343354c28a | Python | 1,093 | 27 | # 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 a... |
e9986a14de24133b246081f7d078f7e0bb6b7e7f785c1d3a05c1aaac9b75cd4f | Python | 1,093 | 50 | # -*- 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.neural_network import MLPRegressor
from sklearn import metrics
import pickle
import uuid
df = pd.... |
eba16e8f911671d088cab3b07f1a5fda61635622c72bb7cc36fa25241030c61e | Python | 1,093 | 37 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .models import ModelConfig, GINO_Small3d
from .opt import PatchingConfig
from .wandb import WandbConfig
class CarCFDDatasetConfig(ConfigBase):
root: str = "~/data/car-pressure-data/processed-car-p... |
0d98209319b6dba69425a8e4647f9be23a6ffb644bca83d2ae778d12987eef89 | Python | 1,094 | 37 | import jax
jax.config.update('jax_platform_name', 'cpu')
import matplotlib as mpl;mpl.use('Agg')
from matplotlib import rcParams
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Liberation Sans']
from matplotlib import pyplot as plt
import corticostriatal as cs
import numpy as np
from functools im... |
9958f0c4ecf2f53fb3ff2fa4efa0745fdaa903c5de41a92c69a517048a973d2b | Python | 1,094 | 31 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
class FrozenBatchNorm2d(nn.Module):
"""
BatchNorm2d where the batch statistics and the affine parameters
are fixed
"""
def __init__(self, n):
super(FrozenBatchNorm2d, self).__init__()... |
1e28339ce611ab1b440f49b16c2f148e17d969ee94ed3b2f32baa5c3f68ab6ca | Python | 1,096 | 50 | # -*- 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.neural_network import MLPRegressor
from sklearn import metrics
import pickle
import uuid
df = pd.... |
2f36ea36d4a0d23b15ce468a7def86578ef17c8cc54b731e996f1f41aeb0a7f1 | Python | 1,096 | 50 | # -*- 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.neural_network import MLPRegressor
from sklearn import metrics
import pickle
import uuid
df = pd.... |
3664abe70818bbbf31e21fb8b49b8adb6a400a3c6f3eef0ebd0e28e6be42612e | Python | 1,097 | 40 | import matplotlib.pyplot as plt
import numpy as np
from polychrom import forcekits, simulation, starting_conformations
sim = simulation.Simulation(
platform="cuda", # Switch to platform="OpenCL" if you don't have cuda
integrator="variableLangevin",
error_tol=0.003,
collision_rate=0.04,
N=8000,
... |
56c4f69c14cac7d4ebe6f963825972a0a522dd04bba203f18ed8e079dc09b73a | Python | 1,098 | 28 | import os
import numpy as np
import pandas as pd
def calculate_degree_centrality(embeddings=None,recon_loss=None,logdir_FA=None):
## 3 options ()
# 1. Distance from origin in gene embedding
if embeddings is not None:
siVAE_gene_score = -np.sqrt(np.square(embeddings).sum(1))
# 2. Reco... |
7325b3cfc36b2d0a40554845ab2bf8f5813ecd20ad696396d4df9d275c5cfcef | Python | 1,099 | 53 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 3_get_inf_params.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
import os
import pickle
import numpy as np
from osl_dynamics.data import Da... |
fc62d2222c139cc5460f71566479e2caba962ab7c9fb709fc59b086f8153dba4 | Python | 1,099 | 32 | import torch
from mmdet.models.registry import BACKBONES
from .fna_base_backbone import BaseBackbone
@BACKBONES.register_module
class RetinaNetBackbone(BaseBackbone):
def __init__(self, search_params, output_indices=[2, 3, 5, 7]):
super(RetinaNetBackbone, self).__init__(search_params, output_i... |
3d604eefc1d84bf5352fbb52dc3b2e2252fa3b39e804ca02c405b498ce7627af | Python | 1,100 | 32 | from .atss import ATSS
from .base import BaseDetector
from .cascade_rcnn import CascadeRCNN
from .cornernet import CornerNet
from .fast_rcnn import FastRCNN
from .faster_rcnn import FasterRCNN
from .fcos import FCOS
from .fovea import FOVEA
from .fsaf import FSAF
from .gfl import GFL
from .grid_rcnn import GridRCNN
fro... |
ecf4e4008b8c6eae71a45657d787430ed3c516c0b72869563e2b532bf2ea5324 | Python | 1,101 | 20 | ####################################################################################################
# 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... |
f66e539164b13a17ce0f936c3d5ead5ba140562fcd4a6582b64ceae325b9c26a | Python | 1,102 | 34 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_error
from pandas.api.types import is_string_dtype, is_numeric_dtype, is_object_dtype, is_cat... |
041637fafa6a2e0e766bc4ba5c7d39e92195ddafcd7eec2b8d30d1d5f28c0571 | Python | 1,105 | 40 | ################################
### Some tools
##################################
import numpy as np
def stokeeinstein(radius,kb=1.3806488e-23 , Tcelsius= 35, viscosity=0.693e-3 ):
"""
Compute the diffusion coefficient from the radius of the particle using the stokes-einstein relationship.
"""
... |
1e68d3144b619f14c2e5bb7de6f2e96f45b7b8d12d7a008c44e485d00e4bc465 | Python | 1,105 | 28 | import tqdm
import ipdb
import argparse, sys; sys.path.append('../..')
import random as rand
import torch
from graphxai.gnn_models.node_classification.testing import GIN_3layer_basic, GCN_3layer_basic, GSAGE_3layer
def get_model(name):
if name.lower() == 'gcn':
model = GCN_3layer_basic(16, input_feat = 11... |
43485cdbf3c0da4658646e2e7614423474c837601f85a6ade634db44a8db6abc | Python | 1,105 | 28 | import os, sys; sys.path.append('..')
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_mo... |
a8f95a09dd8ce7610e560a38e9c14de614cfc2f862b946126144c0d61f9d16b7 | Python | 1,105 | 32 | from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.loggers import WandbLogger
from datasources import paths_manager
class TrainerCallbacksFactory:
@staticmethod
def create_earlystopping() -> EarlyStopping:
return EarlyStopping(monitor='val_loss',
... |
c57e6a88faff8128b06a8313aa864052f17320ec38164a0c7f86700266d7dfaa | Python | 1,106 | 27 | from scripting.spectrum.dataset import extract
from scripting.spectrum import metadata
from scripting.spectrum.metrics import band_powers
from scripting.spectrum.io import persist
DPATH = '/home/guest/Desktop/dataset_pickles/new/8wp3/dataset.pkl'
GROUP = 'b' #or 'b','c','d'
CHS = [0, 1, 2]
BANDS = [(1,4),(4,8),(8,13),... |
4b5984ec23c5ffc87221f6a9db4353f3d1f4c19ae376a9b2dc80e168b87786fc | Python | 1,107 | 27 | import torch
import wandb
from pytorch_lightning import Callback
class ImagePredictionLogger(Callback):
def __init__(self, val_samples, num_samples=32):
super().__init__()
self.num_samples = num_samples
self.val_imgs, self.val_labels = val_samples
def on_validation_epoch_end(self, tra... |
58ac9d7044e64e69a4db9921d70566832261964e4ca51063781f05478ee9fc55 | Python | 1,107 | 45 | import csv
import os
import sys
def read_cases(path):
cases = []
outcomes = []
headers = []
with open(path, 'rb') as csvfile:
reader = csvfile.readlines()
n = len(reader[0].split())
for i, row in enumerate(reader):
cases.append(row.split()[1:])
outcomes.a... |
f1fce7fd6dc7100179c898208f7e95635afb2cd1e298f310f3c4a2ca918ebe8a | Python | 1,108 | 31 | __author__ = 'duarte'
"""
===========================================================================
Modules Package
===========================================================================
Collection of modules comprising all the tools and objects necessary
to set up complex network simulations, input properties,... |
1564a02f8f2b6e7378157222a294a556a74530685d237d51b791984219fc4ba4 | Python | 1,110 | 20 | ####################################################################################################
# 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 ... |
63a323b70447798ad0a3ef42ac6cf62ce3c83a23bcb8a4e6756600ad52ac29e1 | Python | 1,110 | 28 | import os, sys; sys.path.append('..')
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_mo... |
8d8d2c26be73878df66e3cbce95bd3451acdf378379e5ae5dff71d71988eca56 | Python | 1,110 | 21 | #
# Copyright (c) 2018 Institute for Basic Science
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge... |
c4741e554884ee901d9dcf6df229ef26f82d49fef831004aed71ce69879b9220 | Python | 1,110 | 43 | import os
import json
import pandas as pd
import pickle
def handle_dir(path):
if not os.path.isdir(path):
os.mkdir(path)
def export_json(dict, path, print_json=False):
with open(path, "w") as outfile:
json.dump(dict, outfile, indent=4)
if print_json:
print("config")
print... |
a05af4202594450955e5a9d1990a50d00082acc9b970e1f381c488d6db89118d | Python | 1,113 | 28 | import os, sys; sys.path.append('..')
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_mo... |
059380f46693f256be1485251ed551bb0ce0429b3474b91b6fec569d6f5a6728 | Python | 1,114 | 29 | import numpy as np
import matplotlib.pyplot as plt
x, y = np.loadtxt('TSSA_tri_trace_1D.dat', unpack=True, usecols=[0,1])
plt.plot(x, y, label="1D diffusion", color='blue', linestyle='solid', linewidth = 4, marker='o', markerfacecolor='blue', markeredgecolor="navy", markersize=12)
x, y = np.loadtxt('TSSA_tri_trace_2... |
714d3b91daa551ad75f83ee116312924c28e08eaf968bc79de0bf18988115b5e | Python | 1,114 | 46 | import numpy as np
import carpet
import carpet.lattice.triangular as lattice
## Parameters
# Geometry
nx = 16
ny = 16 # even number
N = nx * ny
a = 18 # [um] lattice spacing
## Initialize
# Geometry
distances = [1]
# pre save coordinates
try:
coords = np.load('coords.npy')
lattice_ids = np.load('lattice_i... |
8793ae6efa40b3ac3f07d5bb5dcb644591e7a11c5fed27feadd2a634a8337e2a | Python | 1,114 | 39 | # This updates usage/config.rst to the latest cli
# Developers can run this after modifying any arguments the user can see
from AFQ.utils.bin import func_dict_to_arg_dict, dict_to_toml
prologue = """
The pyAFQ configuration file
----------------------------
This file should be a `toml <https://github.com/toml-lang/t... |
a6cf8939f60c4cd3ac8c68ef0b4048b163265f1cf86d1840c13f09ccade64531 | Python | 1,114 | 37 | # Resume all interrupted trainings in yolov5/ dir including DDP trainings
# Usage: $ python utils/aws/resume.py
import os
import sys
from pathlib import Path
import torch
import yaml
sys.path.append('./') # to run '$ python *.py' files in subdirectories
port = 0 # --master_port
path = Path('').resolve()
for last ... |
3d602fb49fb07d965ab322f97cc9469bb954f3592191b11443fa8162575fd3a0 | Python | 1,115 | 28 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from numpy.testing import assert_array_equal, assert_array_almost_equal
from eelbrain import datasets
from eelbrain.mne_fixes import _interpolate_bads_meg
from eelbrain.testing import requires_mne_sample_data
@requires_mne_sample_data
def test_interpolation():... |
770e656c073faa7405b805ea5b5febc341855a67f3ca471cb016cd4cd404f63e | Python | 1,116 | 22 | ####################################################################################################
# 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 ... |
a8e7544e0a46d59a91bce6b74fd06ee85eebc99adb332d1a37848cdc03fec540 | Python | 1,116 | 21 | ####################################################################################################
# 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 ... |
63453cfc22f7da2064c7fb12d6a97c94e6d82e4f040df3ef13cea5a6a2b40444 | Python | 1,117 | 33 | from dataclasses import dataclass
from typing import Iterable
from linkml_runtime.dumpers import json_dumper
from oaklib.datamodels.obograph import GraphDocument
from oaklib.interfaces.obograph_interface import OboGraphInterface
from oaklib.io.streaming_writer import StreamingWriter
from oaklib.types import CURIE
@... |
1a7a6059fda882be771eaf7922416b9a2224bc32c9b92a9e8c755f7928804da4 | Python | 1,118 | 30 | # 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... |
47e54360dca8d620dec7b484ebb20fedf7c5c94ee4cf638dc0f237a972a29e83 | Python | 1,119 | 21 | ####################################################################################################
# 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 ... |
9089d46bf56050acf1a8bd94580e4e3201230c9dc1fcdd9246d004a17beaf0a1 | Python | 1,119 | 39 |
import argparse
import os
import gzip
parser = argparse.ArgumentParser(description='Check if genes in first column have a version number and if so, remove')
parser.add_argument('matrix',
help='Matrix to remove versions of genes (inplace)')
args = parser.parse_args()
if not os.path.exists(args.m... |
e9e062c2d35fe7a15574fff9c045ce484920674159dc0135772431f521d251b3 | Python | 1,120 | 27 | # 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... |
1ae63a2327e53cd469934bd118dba137dda2c00fbff9083e4e03bce27429ba30 | Python | 1,121 | 33 | import numpy as np
import nibabel as nib
import sys
import os
from utils import largestAfterOpen
from scipy import ndimage
img_name = sys.argv[1]
template_name = sys.argv[2]
roi_th = int(sys.argv[3])
print(f'roi_th: {roi_th}')
f_name = img_name.split('/')[-1]
out_path = img_name.replace(f_name,'')
img = nib.load(img_n... |
8aad232bb1926affdec7e4a895020787171d3fde45359f9784495e1b3596dd2d | Python | 1,121 | 55 | from abc import ABC
from typing import Dict, List, Tuple, Iterable
from oaklib.interfaces.basic_ontology_interface import BasicOntologyInterface
from oaklib.types import CURIE, LABEL, URI
from rdflib import Graph
class SkosInterface(BasicOntologyInterface, ABC):
"""
presents ontology as simple SKOS vocabular... |
79e30ebbb7a57b5c819b7336d34c9335be5295fba9591f9bdfe38e50af83074b | Python | 1,123 | 34 | """
scorers
Created by: Martin Sicho
On: 03.06.22, 13:28
"""
import numpy as np
import pandas as pd
from rdkit import Chem
class SmilesChecker:
@staticmethod
def checkSmiles(smiles, frags=None):
shape = (len(smiles), 1) if frags is None else (len(smiles), 2)
valids = np.zeros(shape)
f... |
7b65bb7cab755a62df43d25c78c890a3a3d0d441b8c99145f9693a7ad82ac6fb | Python | 1,125 | 41 | from sklearn.cluster import KMeans
import numpy as np
import csv
import os
import sys
if __name__ == '__main__':
path = 'Justice.csv'
justices = []
ideology = []
qualification = []
with open(path, 'rb') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='"')
for i, ro... |
9969afed5e91b63d9b85f5edcce42027309b71306fff637be0b26ac87982f1dc | Python | 1,125 | 36 | import unittest
from typing import Any, List, Type, Union
from oaklib import BasicOntologyInterface
from oaklib.io.streaming_csv_writer import StreamingCsvWriter
from oaklib.io.streaming_json_writer import StreamingJsonWriter
from oaklib.io.streaming_writer import StreamingWriter
class AbstractDatamodelTestCase(unit... |
3220b3184e1197ace7799d09e7d325886e52e2d2c6e55300b9d3cccebc93ccd3 | Python | 1,126 | 35 | """
EQUATIONS: Documentation
"""
from brian2 import Equations, units
###########################################
# CELLS Equations
###########################################
eqs_LIF = Equations('''dvm/dt = ((El - vm) + I_synEX + I_synIN + I_noise)/tau : volt (unless refractory)
I_noise : volt
... |
618632ecf8f5f6d6d404adb8a64e4d7c4f08f1ca206e94c830ba5da2d27b1376 | Python | 1,126 | 38 | import numpy as np
import os, sys, brian2
nrun = int(sys.argv[1])
rate = int(sys.argv[2])
brian2.seed(nrun)
print ('RUN: ' + str(nrun))
foldername = 'rate'+str(rate)+'/run_'+str(nrun)
os.system('mkdir -p -v '+foldername)
N = 10000 # number of neurons
time_input = 4000 * brian2.ms # simulation time
P = brian2.Pois... |
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