sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1fbcc2d21b9ad101199266ea3a61af840c2570c8652f37e2d53e44a198618776 | Python | 663 | 30 |
class SearchResults:
def __init__(self):
self.Keywords = []
self.Relationships = []
self.KeywordRelations = []
self.DirectRelationshipAnalogues = []
def GetNeuroLexUris(self):
result = []
result.extend(self.Keywords.GetKeywordAndSubregionUris())
fo... |
5cedf56f66b886c4f77090af4b8500bc15be4b47de61bdb7e6decc2649523276 | Python | 663 | 27 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
from typing import Optional
def Style(sm_style: Optional[str] = "sticks") -> None:
"""
Change the representation style of the 'sm' ... |
139cdddd9a3c5a2d1dc20de1f287707c20091f91aa659156b32aac06dd79ccd2 | Python | 665 | 20 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2018, Johannes Köster"
__email__ = "johannes.koester@protonmail.com"
__license__ = "MIT"
from snakemake.shell import shell
extra = snakemake.params.get("extra", "")
java_opts = snakemake.params.get("java_opts", "")
filters = [
"--filter-name {} --filter-e... |
52f2729a027e0462c1fc8e947f98834b9f2a28067fe99c5efad797d2cf6c4005 | Python | 665 | 25 | setup = """
from hyppo.ksample import KSample
from sklearn.datasets import make_blobs
n_samples = 1000
X1, y1 = make_blobs(n_samples=n_samples, n_features=3, centers=10)
X2, y2 = make_blobs(n_samples=n_samples, n_features=3, centers=9)
def broadcast_dcorr(data1, data2):
ksamp = KSample("Dcorr", bias=False)
s... |
f5eace4fdcac6e6cbcb9be75308b6f7008881928ad7df2d7e8452f6e75392086 | Python | 665 | 14 | # 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... |
454dd63ad81e7ddde949b8c3874ec2bf3e44ebb4ef71adefe8d23f769c2b32f9 | Python | 666 | 7 | from scicite.dataset_readers.citation_data_reader_aclarc import AclarcDatasetReader
from scicite.dataset_readers.citation_data_reader_aclarc_aux import AclSectionTitleDatasetReader, AclCiteWorthinessDatasetReader
from scicite.dataset_readers.citation_data_reader_scicite import SciciteDatasetReader
from scicite.dataset_... |
67a45b11b712da4477f597cbc2a4e492f26c7f9f7fdd54efa15bf306ab514d2c | Python | 666 | 24 | # Copyright (c) Open-MMLab. All rights reserved.
import yaml
try:
from yaml import CLoader as Loader, CDumper as Dumper
except ImportError:
from yaml import Loader, Dumper
from .base import BaseFileHandler # isort:skip
class YamlHandler(BaseFileHandler):
def load_from_fileobj(self, file, **kwargs):
... |
8e290a84f99aceb507d97ec3ee3cd7aa52b1d083c7ad7ffa08cfa09d4023bff3 | Python | 666 | 30 | __author__ = "Patrik Smeds"
__copyright__ = "Copyright 2019, Patrik Smeds"
__email__ = "patrik.smeds@gmail.com"
__license__ = "MIT"
from snakemake.shell import shell
shell.executable("bash")
log = snakemake.log_fmt_shell(stdout=False, stderr=True)
extra_params = snakemake.params.get("extra", "")
input_a = snakema... |
12a1367d1079d6e0c26b270a39badc77f50433a9a5c45956865531c12b4e8178 | Python | 667 | 24 | import socket
import logging
logging.basicConfig()
logging.getLogger().setLevel(logging.CRITICAL)
from gratin.training.callbacks import LatentSpaceSaver, Plotter
from gratin.standard import train_model, load_model, plot_demo, get_predictions
if __name__ == "__main__":
if "jbmasson" in socket.gethostname():
... |
501a0abb2c11857b1f60067061862c30f0dcc6c63c254863facd1e84fddbdf91 | Python | 667 | 19 | import os
from subprocess import check_output
__author__ = "Sebastiano Ferraris UCL"
__licence__ = "MIT"
__repository__ = "https://github.com/SebastianoF/bruker2nifti"
__all__ = ["_cores", "_getters", "_metadata", "_utils", "converter"]
# here = os.path.abspath(os.path.dirname(__file__))
# git_dir = os.path.dirname(... |
f747da196f113d7bb914fbe73276c092a9542218e230d6d6411ffdd8bbed1e54 | Python | 667 | 14 | # 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... |
78ab690b2b54b8a46ebcf8a6e5e6fb4a04eb5eacf9746a4f91efece782743403 | Python | 668 | 18 | import os.path as op
import pandas as pd
mriqc_dir = "/home/data/abcd/abcd-hispanic-via/dset/derivatives/mriqc-0.16.1"
runs_to_exclude_qcfc_df = pd.read_csv(op.join(mriqc_dir, "runs_to_exclude_qcfc.tsv"), sep="\t")
runs_to_exclude_qcfc = runs_to_exclude_qcfc_df["bids_name"].tolist()
runs_to_exclude_FD_df = pd.read_c... |
c2e6c98c36940fd3cb6312748ff9f207f42bf792b8825c6220de992c14fc7ab9 | Python | 668 | 25 | import logging
import unittest
from oaklib.implementations.sqldb.sqlite_utils import sqlite_bulk_load
import sqlite3
from tests import INPUT_DIR, OUTPUT_DIR
TSV = INPUT_DIR / 'foo.tsv'
DB = OUTPUT_DIR / 'test.db'
TBL_NAME = 'my_tbl'
class TestSqliteUtils(unittest.TestCase):
def test_bulkload(self):
if ... |
4ccd16789a0358a1b52e678ff9356ce448146c106842f8384ec6efea1f16389b | Python | 670 | 15 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from .coco import COCODataset
from .concat_dataset import ConcatDataset
"""
For now, Pascal VOC and COCO Dataset are be supported by 2 dataload mode
| Mode | Special_Deal | Post Branch | Annotation
| 0 | False ... |
ee43737ef496a3bd678c699e89f765a6abeb116b5f236e6bad0320fcaf5d4061 | Python | 670 | 25 | """
Code adopted from pix2pixHD:
https://github.com/NVIDIA/pix2pixHD/blob/master/data/image_folder.py
"""
import os
IMG_EXTENSIONS = [
'.jpg', '.JPG', '.jpeg', '.JPEG',
'.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.tiff'
]
def is_image_file(filename):
return any(filename.endswith(extension) for exten... |
b8f1d275c26d5fcb8605e5d6a1c71285cfae4ce816bbcb7dd918d5bc5969a325 | Python | 673 | 22 | import community as community_louvain
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import networkx as nx
# load the karate club graph
G = nx.karate_club_graph()
#first compute the best partition
partition = community_louvain.best_partition(G)
# compute the best partition
partition = community_louvain.b... |
85c6d2c799afadceb0d534c664aeb43727ffafc71f7d1547770a8ac3e6cd4730 | Python | 675 | 31 | __author__ = "Patrik Smeds"
__copyright__ = "Copyright 2018, Patrik Smeds"
__email__ = "patrik.smeds@gmail.com"
__license__ = "MIT"
from snakemake.shell import shell
extra = snakemake.params.get("extra", "")
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
input = " ".join(snakemake.input.vcf)
# if one sam... |
cffac708b06e09a31225138f961ce5415d6079103a22acd2d5a62700703cb92b | Python | 675 | 21 | import setuptools
from setuptools import find_packages
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="coreg-selector",
version="1.0.0",
author="Niek de Klein",
author_email="niekdeklein@gmail.com",
description="Small package to select data from a brain c... |
3cf4d95122d3c322873bb1f4592c137c1543e1347677f3144dec02ef443eb9f6 | Python | 676 | 24 | import math
import numpy as np
def get_basis_dual(a1, a2):
'''
For the lattice
:param a1, a2: basis vectors
:return: dual basis vectors; https://en.wikipedia.org/wiki/Reciprocal_lattice
'''
R = np.array([[0, 1], [-1, 0]]) # rotation by 90deg
b1 = 2 * np.pi * (R @ a2) / (a1 @ (R @ a2))
... |
8e3dc62b9559d1609267562f28dc469d45b9d6c82fa45c231f64da6e56a90781 | Python | 676 | 32 | import numpy as np
from augmend import Augmend, Elastic
from spotipy.model import Config, SpotNetData, SpotNet
from spotipy.utils import points_to_prob
if __name__ == '__main__':
config = Config(axes = "YXC", n_channel_in=1)
model = SpotNet(config, name = None, basedir = None)
N = 200
P... |
2ca6a8418b41156cd4df2046f8c1f067b1bad12bebfd472e465e287c54ee0f42 | Python | 677 | 26 | """
Script to run the allennlp model
"""
import logging
import sys
from pathlib import Path
import os
sys.path.append(str(Path().absolute()))
# from allennlp.commands import main
from scicite.training.commands import main
logging.basicConfig(format='%(asctime)s - %(levelname)s - %(name)s - %(message)s',
... |
01c5a4ed3cf9bcd0206c49ab2b1c2e29238325a587022a636f23e319db8e3f44 | Python | 678 | 31 | import os
import sys
from pathlib import Path
from setuptools import find_packages, setup
sys.path.insert(1, os.path.join(sys.path[0], ".."))
with open("requirements.txt") as f:
required = f.read().splitlines()
os.chdir(Path(__file__).parent.absolute())
setup(
name="cgtasknet",
version="0.0.1",
pack... |
5d5ece1e65ff0fc8538c5942ab9a7ed5a6b1653f4facac4a88172ceceaed031f | Python | 679 | 22 | import numpy as np
def ntf_local(param,freq):
gei = param[0]
gii = param[1]
tau_e = param[2]
tau_i = param[3]
w = 2 * np.pi * freq
gee = 1
Fe = np.divide(1 / tau_e ** 2, (1j * w + 1 / tau_e) ** 2)
Fi = np.divide(1 / tau_i ** 2, (1j * w + 1 / tau_i) ** 2)
Hed = (1 + (F... |
8023e29f5e48534b7771f19e904438f4b53c72a55b3b0807066b7e25903af4ce | Python | 679 | 26 | '''
Solve a system of a moving sphere and a no-slip wall
'''
import mesh
import FBEM
folder = 'data/sphere_plane'
# Sphere parameters
sphere_position = (0, 0, 5)
radius = 1
velocity = (2, 0, 0)
angular = (0, 0, 3)
sphere_grid = 4 # Mesh consisting on 4x4 nodes
# Plane parameters
plane_position = (0,0,0)
plane_radius... |
dc3f052278993c0b1be7accb3c5999e307bcace772aad5eaaaf6fe13baf49dc8 | Python | 679 | 24 | from PeptideBuilder import Geometry
import PeptideBuilder
import Bio.PDB
def generate_peptide_alpha(sequence, filepath):
alpha_phi = -60
alpha_psi_im1 = -40
# create a geometry for initialization of structure
geo = Geometry.geometry(sequence[0])
geo.phi = alpha_phi
geo.psi_im1 = alpha_psi_im... |
fcc521eb696c21aadd3aed08dbaf8221cea75c6be869f393aa46716f794779d5 | Python | 679 | 20 | """Snakemake wrapper for GATK4 Mutect2"""
__author__ = "Thibault Dayris"
__copyright__ = "Copyright 2019, Dayris Thibault"
__email__ = "thibault.dayris@gustaveroussy.fr"
__license__ = "MIT"
from snakemake.shell import shell
from snakemake.utils import makedirs
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
... |
7bb181e35fdef865094e4900da364d1dd1d5137809cfd86c8fa9d1fbd94e5101 | Python | 681 | 18 | import torch
import numpy as np
import glob
from gssc.train.DataManage import SeqDataSet
from os.path import join
### basic example of how to make a Sequential Dataset. There wrap around a list
### of the more fundamental PSG DataSets, allowing one to grab a random PSG
### out of the entire dataset for training
# we ... |
91251ec9548a5db1303834b8a9532dc06a3c8e0de387d81159eeee0ce49c2ee3 | Python | 682 | 14 | # 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... |
aad38c04fa00ac51293783ca0a441a9e089bd07ffa893b801b5aeb67db8d3f89 | Python | 682 | 29 | """Deep learning and Reinforcement learning library for Researchers and Engineers"""
from __future__ import absolute_import
try:
install_instr = "Please make sure you install a recent enough version of TensorFlow."
import tensorflow
except ImportError:
raise ImportError("__init__.py : Could not import Tens... |
f507c730accb630f31c3170cc56e6472ebbc38fdd6e1462eff508c20c76858f8 | Python | 682 | 36 | '''
Angle vs. calcium concentration
'''
from pylab import *
width, height = 2, 2
K_electromotor = 1.4e-6 #2.4e-6 # in uM
n_electromotor_coupling = 2
theta_min = 13.
theta_max = 90.
fig = figure('Angle', (width,height))
ax = fig.add_subplot(111)
x = 1e-7*exp(linspace(0,6,100))
theta = theta_min + 2*(theta_max-thet... |
2ac78ac435ff3b9f82aa27cb8df6a240606d7309f10898d6a94d62241547fc29 | Python | 683 | 28 | from typing import Any
import oaklib.datamodels.oxo as oxo
from linkml_runtime.loaders import json_loader
def fix_json_payload(obj: Any) -> None:
"""
changes payload in place
- self --> link_to_self
:param obj:
:return:
"""
if isinstance(obj, dict):
for k, v in obj.items():
... |
c00b9d982066a64de2947364b8a4e2b7192cb739c9ae8bf15feef01bdb730be5 | Python | 683 | 23 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
from pdf2image import convert_from_path
from pdf2image.exceptions import (
PDFInfoNotInstalledError,
PDFPageCountError,
PDFSyntaxError
)
PatientNumber = 311; #Insert patient number
images = convert_from_path('Patient' + str(PatientNum... |
6f0bb29dfe8ac2bf0c2c9beafbbf0935c48d8b7a8d4cc7bcadcf5b2e44100934 | Python | 684 | 16 | import tensorflow as tf
S = lambda x, y: tf.reduce_sum(x * y, axis=-1, keepdims=True)
A = lambda x, k=-1: tf.expand_dims(x, axis=k)
def cdist_tf_batch(A, B):
na = tf.reduce_sum(tf.square(A), axis=-1, keepdims=True)
nb = tf.transpose(tf.reduce_sum(tf.square(B), axis=-1, keepdims=True), [0, 2, 1])
return tf... |
f2358ce099c25f1a33aee863e5bf7ae48f8d3184c6b13ef1ff6d405298c6eb3c | Python | 684 | 19 | import sys
if sys.version_info[:2] >= (3, 8):
# TODO: Import directly (no need for conditional) when `python_requires = >= 3.8`
from importlib.metadata import PackageNotFoundError, version # pragma: no cover
else:
from importlib_metadata import PackageNotFoundError, version # pragma: no cover#
try:
... |
6a886e43bdfd7c9d0875690bdfcb620963868ff243ffabdbbbe070daef79c656 | Python | 685 | 20 | from setuptools import setup, find_packages
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name='Catactor',
version='0.1.2',
description="scATAC-seq analysis using meta-analytic marker genes",
long_description=long_description,
long_description_content_type="text/markdo... |
086ec7874f3c4cab57d51c3e84b970f6688abf1a84dacf1544a2fca28f0be462 | Python | 686 | 33 | # Unit tests for sima/normcut.py
# Tests follow conventions for NumPy/SciPy avialble at
# https://github.com/numpy/numpy/blob/master/doc/TESTS.rst.txt
# use assert_() and related functions over the built in assert to ensure tests
# run properly, regaurdless of how python is started.
from numpy.testing import (
ass... |
7fc102ba67a233e1486a11f0bed8b99adf4ba5ba214a75f23730d9d7246a7e96 | Python | 686 | 31 | from typing import Any
from linkml_runtime.loaders import json_loader
import oaklib.datamodels.oxo as oxo
def fix_json_payload(obj: Any) -> None:
"""
changes payload in place
- self --> link_to_self
:param obj:
:return:
"""
if isinstance(obj, dict):
for _, v in obj.items():
... |
c82ab1a5526e63d01c61800b36f8872681961e4479e771d4bab4338a63d6c86e | Python | 686 | 20 | from scipy.stats import combine_pvalues, ks_2samp
def degree_test(A1, A2, method="ks"):
in_degrees1 = A1.sum(axis=0)
out_degrees1 = A1.sum(axis=1)
in_degrees2 = A2.sum(axis=0)
out_degrees2 = A2.sum(axis=1)
# # this is dumb in the sense that p-values aren't independent
# in_stat, in_pvalue = ... |
39fb1fff65b818bf934467efbb26f9047651ad19ac5bd8fbb27fdb67d6b63fdb | Python | 688 | 24 | import torch.nn.functional as F
import torch
def nll_loss(output, target):
return F.nll_loss(output, target)
def ce_loss(output, target):
return F.cross_entropy(output, target)
def ce_loss_weighted(output, target):
weighted_loss = torch.tensor([0.34, 0.66])
return F.cross_entropy(output, target, wei... |
e510cbab04ee808a13b2683213a42c06bc84a7a44c2dbfedc146d6d3ef54e6c6 | Python | 688 | 15 | # 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... |
e951a06cc11b7f6bfac9ee93b8bf7147891684106d249d32043be63271dc1dd5 | Python | 689 | 25 | # Copyright (c) Open-MMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
class BaseFileHandler(metaclass=ABCMeta):
@abstractmethod
def load_from_fileobj(self, file, **kwargs):
pass
@abstractmethod
def dump_to_fileobj(self, obj, file, **kwargs):
pass
@abstractmeth... |
0f77cf42ed9fd19d7bb3ab46a9ef644c2ca4d37498010da5fec72aa0e83bb08e | Python | 690 | 23 | """
Utilities used for annotation and lexmatch processes.
"""
from pathlib import Path
from typing import List, Union
def get_exclusion_token_list(exclude_tokens: Union[str, Path]) -> List[str]:
"""
Return a list of token to be excluded from NER analysis.
:param exclude_tokens: Either a file path or the... |
ccf85a7c0accd7b24b6c48e24fd5589d3c4a69fb683ae8509bba8b3cd011b19a | Python | 690 | 25 | import argparse
import glob
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', help='')
parser.add_argument('output', help='')
args = parser.parse_args()
ref = []
for f in glob.glob(args.input + '/**/*.ref', recursive=True):
with open(f) as fin:
ref... |
9acfeec89bf2df8a416a6f663c193843ca45b5c40dcad02d40bd2a2264e0cac3 | Python | 692 | 29 |
import unittest
import h5py
from deeprank_gnn.tools.BioWrappers import get_bio_model, get_depth_res, get_depth_contact_res, get_hse
class TestBioWrappers(unittest.TestCase):
def setUp(self):
self.pdb = 'tests/data/pdb/1ATN/1ATN_1w.pdb'
def test_hse(self):
model = get_bio_model(self.pdb)
... |
8ce08aacde429d2ae25b81ac2d4b5e037a3f801ecd88a6fdbeec320748138575 | Python | 693 | 32 | import subprocess
from argparse import ArgumentParser
import os
from glob import glob
from warnings import filterwarnings
filterwarnings("ignore")
my_parser = ArgumentParser(description="Run analysis on a group of images")
my_parser.add_argument(
"Path",
metavar="path",
type=str,
help="the path to ... |
0b0ec868ed9dc3dc2c1a80c38610f3fa445fa75034be21095cb2e00ec62c92cc | Python | 696 | 24 | import unittest
from oaklib import get_adapter
from oaklib.interfaces.association_provider_interface import (
AssociationProviderInterface,
)
# TODO: use mock tests
class TestAmiGO(unittest.TestCase):
"""
Tests :ref:`AmiGOImplementation`
"""
def setUp(self) -> None:
self.adapter = get_ad... |
98cd7e84ea3505a60aff21abeb1253c8f931b45bbdd3511328d5ab9a70d83996 | Python | 696 | 26 | #!/usr/bin/env python
import os
from setuptools import find_packages, setup
def read(fname):
with open(os.path.join(os.path.dirname(__file__), fname)) as f:
return f.read()
setup(
name='ranger',
version='0.1.dev0',
packages=find_packages(
exclude=['tests', '*.tests', '*.tests.*', 't... |
a5bcb5bc52a05c8c993c0a1ea180ec0ff396584b8c819cb49cff982899fa6cbc | Python | 696 | 25 | import torch
import cv2
from PIL import Image
import torch.utils.data
import numpy as np
class Dataset(torch.utils.data.Dataset):
def __init__(self, imList, labelList, transform=None):
self.imList = imList
self.labelList = labelList
self.transform = transform
def __len__(self):
... |
c76f9483047ee63b1b7601de767d7074b7dea28a664c71031cc9bbc17bdeed8d | Python | 697 | 19 | """Parser for GAF association formats"""
from dataclasses import dataclass, field
from oaklib.parsers.parser_base import ColumnReference
from oaklib.parsers.xaf_association_parser import XafAssociationParser
@dataclass
class HpoaG2PAssociationParser(XafAssociationParser):
"""Parsers for Hpoa G2P format."""
... |
e88dc2de5730011c4c37b8e08350d32189506cdb583312d9c069ea962e8b5989 | Python | 697 | 31 | # add my own enviromment to the registry, and thus make it available for gym.make()
import logging
from gym.envs.registration import register
logger = logging.getLogger(__name__)
register(
id='FdtdEnv-v0',
entry_point='DRL.envs:FdtdEnv',
max_episode_steps=300,
reward_threshold=150,
)
'... |
eb0b79645161e88664594a3f9edfbd0f6cd0916ab65d99b78b2ccdce48e2cf00 | Python | 697 | 34 | import sys
import gzip
if len(sys.argv) < 5:
print("Usage: chr sta sto out")
else:
chr = int(sys.argv[1])
sta = int(sys.argv[2])
sto = int(sys.argv[3])
outp = sys.argv[4]
fh = gzip.open('./SNPQCLog.txt.gz','rt')
fho = gzip.open(outp,'wt')
ctr = 0
written = 0
for line in fh:
line = line.strip()
if ctr ... |
02369d214e6bed4ed6566ab4b6974709946d7d6aede8824e93feb991e8c2eac5 | Python | 698 | 21 | import mesh.plot.vedo_viewer as plot3D
path = 'data/sphere_wall'
# Plot with random colors for each object
m = plot3D.MeshViewer(path, group='.')
plotter = m.show(axes=1)
plotter.close() # important to close plotter afterwards!
# Plot with pre-defined colors
names = ['sphere', 'plane']
colors = [None, 'grey'] # Non... |
b87af7542f656569d4641f0294b0720f9f1bb9cb669e36253ccc775956e890b7 | Python | 698 | 25 | import cv2
import numpy as np
from cenfind.core.detectors import extract_cilia
def test_extract_cilia_detects_elongated_blob(make_field):
data = np.zeros((2, 300, 300), dtype="uint16")
cv2.ellipse(data[1], (150, 150), (60, 10), 30, 0, 360, 4000, -1)
field = make_field(data=data)
cilia = extract_cili... |
bdd28a6e662edb2f1146cce02432853bfe3ca5253d8c5ef170178fa2a7650911 | Python | 699 | 34 | __author__ = "Jan Forster"
__copyright__ = "Copyright 2020, Jan Forster"
__email__ = "j.forster@dkfz.de"
__license__ = "MIT"
from snakemake.shell import shell
## Extract arguments
header = snakemake.input.get("header", "")
if header:
header_cmd = "-h " + header
else:
header_cmd = ""
samples = snakemake.inpu... |
2c7fe699c8a28563f445ec85b9f8ab6d631254b9b87a724a3ae637a9a0c04ae5 | Python | 700 | 19 | #!/usr/bin/env python
# Copyright 2015 David Snyder
# Apache 2.0.
#
# This script prints out lines of the form:
# <score> <target-type>.
# Its output is meant to be used as input to the binary
# compute-eer. The Broadcast News utterances have either
# "music" or "speech" in the utterance name, and so we
# can simply ... |
da2cc9347f1cb0e9336c0ab5df1fe11f1a9b8584f256d776a86300eae14e4a99 | Python | 701 | 25 | import torch
import torch.nn as nn
class separation_loss(nn.Module):
""" Separation constraint
"""
def __init__(self, n_kpts=8, weight=0.01):
super(separation_loss, self).__init__()
self.weight = weight
self.K = n_kpts
def forward(self, input):
input_1 = t... |
4d014c530545c497afdca6712926e90bac88c24a50c0b08d63daa137e490fcd5 | Python | 702 | 14 | """Fail unless a built wheel carries the three models and the 138 example tests, and no junk."""
import sys
import zipfile
names = zipfile.ZipFile(sys.argv[1]).namelist()
models = sorted(n for n in names if n.startswith('pyoxynet/models/') and n.endswith('.tflite'))
examples = [n for n in names if '/data_test/' in n a... |
7aaf64b4afd8ed7a71d900268dfb195d508d3f38952139c1433b82b7d23faa79 | Python | 703 | 31 | # libraries
import numpy as np
from bio_embeddings.embed import ProtTransT5BFDEmbedder
import pandas as pd
embedder = ProtTransT5BFDEmbedder()
ds = pd.read_csv('Dataset.csv')
sequences_Example = list(ds["Sequence"])
num_seq = len(sequences_Example)
i = 0
length = 1000
while i < num_seq:
print("Doing", i, num_seq)... |
ced5e67672a6e1be51fffa37ac77acdb8426a87a416fdd917d6984b134ff645e | Python | 703 | 20 | import torch
import torch.nn as nn
import torch.nn.functional as F
# adopted from https://github.com/pytorch/pytorch/issues/8985#issuecomment-405080775
class ConditionalBatchNorm1d(nn.Module):
def __init__(self, num_features, condition_dim):
super().__init__()
self.num_features = num_features
... |
6c3113b179aac7e580516d8ab3c011043b72a3aeb86df064546019fbea36636c | Python | 704 | 33 | import sys
import torch
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from graphxai.datasets import ShapeGGen
try:
nclusters = int(sys.argv[1])
except:
print('usage: python3 test_clusters.py <n_clusters_per_class>')
exit()
SG = ShapeGGen(
model_layers = 3,
make_explanations=Fa... |
d903e28bd5f0c824650b98bde2a40177918c644dd33496832e8364c6cc30c931 | Python | 704 | 16 | # 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... |
0cbddc516691e48a4eb53f5b9a0f0b2f0287d29f009ba715aed0cee311d101cd | Python | 705 | 28 | import os
from polychrom.polymerutils import load, save
class LegacyReporter(object):
def __init__(self, folder):
""" """
if not os.path.exists(folder):
os.mkdir(folder)
if len(os.listdir(folder)) != 0:
raise RuntimeError(f"folder {folder} is not empty")
se... |
53a6217f26e53425a7b1066b86c87f808b44b733b5b05a10a5140bb969688233 | Python | 708 | 21 | """
Setup file for palm-tools.
Use setup.cfg to configure your project.
This file was generated with PyScaffold 4.1.3.
PyScaffold helps you to put up the scaffold of your new Python project.
Learn more under: https://pyscaffold.org/
"""
from setuptools import setup
if __name__ == "__main__":
t... |
c41f897f5935808519113111c5d97f31c6c855d3ac86bd2006b5b311d1c73974 | Python | 708 | 19 | """Parser for PomBase PHAF association formats"""
from dataclasses import dataclass, field
from oaklib.parsers.parser_base import ColumnReference
from oaklib.parsers.xaf_association_parser import XafAssociationParser
@dataclass
class PhafAssociationParser(XafAssociationParser):
"""Parsers for PHAF format."""
... |
da7129a92e64184618e09fc3b632b977af76bab6980614157432e94699953221 | Python | 708 | 42 | import sys
import gzip
if len(sys.argv) < 4:
ctr = 0
for arg in sys.argv:
print("{}\t{}".format(ctr,arg))
ctr = ctr + 1
print("Usage: input.txt.gz output.txt.gz filter.txt")
exit()
input=sys.argv[1]
output=sys.argv[2]
filter=sys.argv[3]
print("Input "+input)
print("Output "+output)
print("Filter "+filter)... |
f0b71cccdb12623a0a8607fe582617be91b4b65a26c83b529c4f29a8f116d7fd | Python | 708 | 20 | from mip.min_w import MIN_W
from mip.max_correct import MAX_CORRECT
from mip.min_hinge import MIN_HINGE
from mip.sat_margin import SAT_MARGIN
from mip.max_m import MAX_M
def get_nn(loss, data, architecture, bound, reg, fair):
if loss == "min_w":
return MIN_W(data, architecture, bound, reg, fair)
elif loss == ... |
48f73b58e745eb07b759c02892f2e59997d3268f0aaa5b6cece43581ee4e009b | Python | 709 | 25 | """Snakemake wrapper for picard CollectHSMetrics."""
__author__ = "Julian de Ruiter"
__copyright__ = "Copyright 2017, Julian de Ruiter"
__email__ = "julianderuiter@gmail.com"
__license__ = "MIT"
from snakemake.shell import shell
inputs = " ".join("INPUT={}".format(in_) for in_ in snakemake.input)
extra = snakemake... |
62d56eee5d97596bcc069fd26bda6099a05f1f23f11259b28e0f24091807486c | Python | 709 | 20 | # Copyright (c) Open-MMLab. All rights reserved.
from .registry import MODULE_WRAPPERS
def is_module_wrapper(module):
"""Check if a module is a module wrapper.
The following 3 modules in MMCV (and their subclasses) are regarded as
module wrappers: DataParallel, DistributedDataParallel,
MMDistributedD... |
8b949284e3dc9500e74bc049b16ce5b8c66cd1df7e5d8f0edb189a559226ad0a | Python | 709 | 16 | # 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... |
c3fd72ec20c6c04cf008fd482f35ffebcb0d712401ecac7fa3f814786591ef58 | Python | 709 | 20 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Variational Animal Motion Embedding 0.1 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
"""
import ... |
55a6d0335354432fd8d56e094a08bc2100cda65b3220116114e1955203bf0ec3 | Python | 710 | 27 | '''
Manages the configuration file
'''
import os
import yaml
__all__ = ['data_folders', 'config', 'python_binary']
def load_configuration():
with open(os.path.expanduser('~/.paramecium_model_fitting.yaml'), 'r') as fp:
config = yaml.safe_load(fp)
return config
def data_folders(year=None):
if year... |
8b87063f21764df7ac8365d4cc81ef0d8a1fb5f8d528023c36479e46b1d911d7 | Python | 710 | 23 | import numpy.testing as npt
import AFQ.data.fetch as afd
from AFQ.utils.conversion import matlab_tractography, matlab_mori_groups
import os.path as op
DATA_PATH = op.join(op.abspath(op.dirname(__file__)), "../../tests/data")
def test_matlab_tractography():
sft = matlab_tractography(
op.join(DATA_PATH, ... |
858883e71f9b38863975704dba5b20205a70d0d4a8458cbf587a9ab78dc8c2c6 | Python | 711 | 21 | import numpy as np
from numba import jit, prange
@jit(nopython=True, parallel=True)
def bootstrap_ci(data, n_boots=1000):
'''data = M x N matrix, where M is the number of trials, N is the number of observations
Returns:
mus: n_boots x N matrix'''
mus = np.zeros((n_boots, data.shape[1]))
n_tria... |
86ed52e3ccc6448f10b5ad31d806ee78a1f4818687ff9bd88cbc95babd5260f2 | Python | 711 | 18 | """Shared between the AV socket worker and the torchrun rank loop."""
from __future__ import annotations
from ..common.ranks import READY_FILE, SHUTDOWN_FILE # noqa: F401 - re-exported for callers
CAMERA_KEYS: dict[str, str] = {
"camera:front:wide:120fov": "front_wide",
"camera:cross:left:120fov": "cross_le... |
80f7495b35217ad12e3f6cc1ab3fdfd33d738fa884f3898ff3e768e03610b634 | Python | 712 | 16 | import yaml
from oaklib import get_adapter
from oaklib.interfaces.semsim_interface import SemanticSimilarityInterface
from oaklib.utilities.subsets.subset_validator import SubsetValidationConfig, validate_subset
from tests import EXAMPLE_ONTOLOGY_DB, INPUT_DIR
def test_validate_subset():
adapter: SemanticSimilar... |
9c91fdf842a8f29b77f82f68422cbad3d5d44b2f56a19608825bcbe35cd654f3 | Python | 713 | 34 | import torch
import matplotlib.pyplot as plt
from tqdm import tqdm
def get_edge_index(fname):
L = []
with open(fname, 'r') as f:
for l in f:
line = [float(g) for g in l.split()]
L.append(line)
#L.append()
edge_index = torch.tensor(L).transpose(0,1)
return edge_... |
a8dd56c0251416b0ded980aaa252b62ee2e85c0cc0a6ac5dfb30ba54f6c40619 | Python | 713 | 17 | # 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... |
6f463283c57c8a8b4793414723ebfccac84daa8c96d70a28c596eb9317d9d396 | Python | 714 | 32 | import os
import sys
from datetime import datetime
from importlib.metadata import version
sys.path.insert(0, os.path.abspath(os.path.join('..', '..')))
project = 'CenFind'
author = 'Leo Burgy'
copyright = f'{datetime.now().year}, {author}'
version = version("cenfind")
release = version
extensions = [
'sphinx.ext... |
87cd31b95af280ec7162b650c254253e891cc2c7f5bc0735a43ba5c46734a5a2 | Python | 714 | 19 | # This recipe turns on deterministic collisions, so that a synchronous
# simulation with crashes in it repeats exactly from one run to the next.
# The setting applies when the map loads, so reload it keeping the settings.
settings = world.get_settings()
settings.synchronous_mode = True
settings.fixed_delta_seconds = 0... |
6f215ff28eef0563f44e9e8a5e10a411514927a6e58187915a77b777e8c0bb00 | Python | 715 | 27 | import mesh.plot.flowfield as ff
import matplotlib.pyplot as plt
import matplotlib as mpl
folder = 'data/cilia_plane2'
flowfield = ff.extract_flowfield(folder)
projection = 'yz'
x1range = -15, 15
x2range = -1, 10
grid_color = 30
grid_arrows = 10
offset = 0
# Normalize
velocity_max = 0.1 # vectors_max[0]
norm = mp... |
09a9185dfa1b19fecae788bbd3bf73cf03edde4219d5a94b38177e8b7cb26632 | Python | 717 | 23 | from typing import Any, List, Optional
from zencfg import ConfigBase
from config.distributed import DistributedConfig
from config.models import ModelConfig, FNO_Small2d
from config.opt import OptimizationConfig, PatchingConfig
from config.wandb import WandbConfig
class Data(ConfigBase):
train_resolution: int = 1... |
4e6a9231fd47af3011889a21c81d26dc8ef7597fee728ee93519a5607698c176 | Python | 717 | 17 | from drugex.data.corpus.vocabulary import VocSmiles
from drugex.data.datasets import SmilesDataSet
from drugex.training.models import SequenceRNN
from drugex.training.monitors import FileMonitor
from ..settings import *
def main():
data_sets = [SmilesDataSet(f'{OUTPUT_FILE}_{split}.tsv', rewrite=False) for split i... |
5e51cea6388fec780b3b11fe952a2cb89c8c39517505856152c2452ed43a7b80 | Python | 718 | 16 | # 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... |
9fb3518e054a38d1865efbdf89285a306ce3510a9ee28502715bb34e7c3a109f | Python | 718 | 17 | import numpy as np
class SampleStandardizer(object):
# this transformation object is very simple. At creation, a mean and
# standard deviation are specified. When a sample is passed through, the
# image portion of the sample is normalized so that the intensity values
# are capped to the given range, t... |
1e8f0a8b39f964754798088e776fad15d4b1823b2037aa13954cb851ccf04103 | Python | 721 | 37 | # Unit tests for sima/oPCA.py
# Tests follow conventions for NumPy/SciPy avialble at
# https://github.com/numpy/numpy/blob/master/doc/TESTS.rst.txt
# use assert_() and related functions over the built in assert to ensure tests
# run properly, regaurdless of how python is started.
from numpy.testing import (
assert... |
d44f724bad66abb0be7a273aba69d87b80e46013372c3292aa487a199929aa0f | Python | 722 | 26 | import torch
def correct_predictions(model, data, data_mask = None, get_mask = False):
'''
Get all indices of nodes that were correctly predicted by model
'''
model.eval()
with torch.no_grad():
out = model(data.x, data.edge_index)
pred = out.softmax(dim=1).argmax(dim=1) # Use th... |
2d399c75b2ccbf9170f57802daf6870d342d778b28270bcd2f14e9e8be497417 | Python | 723 | 24 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
import ast
FLOAT_PATTERN = "^[-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?$"
POS_FLOAT_PATTERN = "^[+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?$"
INT_PATTERN = "^-?\d+$"
# matches float as well as NaN:
FLOAT_NAN_PATTERN = "^([Nn][Aa][Nn]$)|([-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9... |
2260afddc3a1833d90074eff0ad66ab2c80ed6816966cc96a17226cf68a0be08 | Python | 724 | 31 |
import unittest
import h5py
from deeprank_gnn.Graph import Graph
class TestGraph(unittest.TestCase):
def setUp(self):
self.graph = Graph()
self.graph.h52nx('tests/hdf5/1ATN_residue.hdf5', '1ATN_1w')
self.graph.pdb = 'tests/data/pdb/1ATN/1ATN_1w.pdb'
self.ref = 'tests/data/pdb/1A... |
d2322686ba90126c4065d404778c928f9bc0a3e6a9c4b20a9dea63ea1240f25a | Python | 725 | 25 | #!/usr/bin/env python
# encoding=utf-8
# Copyright 2018 AIShell-Foundation(Authors:Jiayu DU, Xingyu NA, Bengu WU, Hao ZHENG)
# 2018 Beijing Shell Shell Tech. Co. Ltd. (Author: Hui BU)
# Apache 2.0
from __future__ import print_function
import sys
import jieba
reload(sys)
sys.setdefaultencoding('utf-8')
if le... |
f9372d48c462bee24e69c39dfc4004e12925e950c02591e09dca2cead1b34dae | Python | 725 | 21 | from tensorflow.keras import backend as K
def recall_m(y_true, y_pred):
true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))
recall = true_positives / (possible_positives + K.epsilon())
return recall
def precision_m(y_true, y_pred):... |
dc6e708f25f03f4fe4e8adb8efde5a78bdb868c85cb9f6ff45e39abdd9b78c99 | Python | 726 | 33 | import numpy as np
# Kyte Doolittle scale
kd_scale = {}
kd_scale["ILE"] = 4.5
kd_scale["VAL"] = 4.2
kd_scale["LEU"] = 3.8
kd_scale["PHE"] = 2.8
kd_scale["CYS"] = 2.5
kd_scale["MET"] = 1.9
kd_scale["ALA"] = 1.8
kd_scale["GLY"] = -0.4
kd_scale["THR"] = -0.7
kd_scale["SER"] = -0.8
kd_scale["TRP"] = -0.9
kd_scale["TYR"] =... |
72250c0a92b348c13326985b2c768d2b8d1dee15302bcbe57993e80ee0098bc5 | Python | 727 | 21 | from .basic_params import BasicParams
class TestParams(BasicParams):
"""
This class is a son class of BasicParams.
This class includes parameters for testing and parameters inherited from the father class.
"""
def initialize(self, parser):
parser = BasicParams.initialize(self, parser)
... |
bae63d1e68ad370f10f2b07b8137ce08e5059f34db95e95e2c307f5954f39c6e | Python | 727 | 30 | #!/usr/bin/env python
from __future__ import print_function
import subprocess
import sys
from distutils.command.install import install as DistutilsInstall
from distutils.core import setup
try:
import tensorflow
except ImportError:
print("Please install tensorflow 0.12.0 or later")
sys.exit()
class MyIn... |
f92e31cb529a80cf97c72dd12059bb838f9354d5d5bfde64d9cdea27e4371efb | Python | 729 | 34 | from backend.startup import ensure_torch
#needs to be called before the first 'import torch'
ensure_torch()
#needed for upstream
from base.backend import *
from . import root_detection as processing
import PIL.Image
import numpy as np
def write_as_png(path,x):
x = np.asarray(x).astype('float32')
x = x*255... |
a02c2aa5c206da36035d2cc5a1ea088a670946c19af887c2317d395aabcf58b2 | Python | 730 | 28 | import logging
import numpy as np
import torch
import math
from torch import nn, Tensor
import torch.nn.functional as F
class regressoionHead(nn.Module):
def __init__(self, d_embedding: int):
super().__init__()
self.layer1 = nn.Linear(d_embedding, 512)
self.layer2 = nn.Linear(512, 256)
... |
58538a98a305964d5c5b69e357d4d59d43ca1ac54a2ec9b360ab234b7429bd23 | Python | 731 | 39 |
if __name__ == '__main__':
# ------------------
# Libraries
# ------------------
# Generic libraries
import pandas as pd
import numpy as np
# Own
from ls2d.utils import format_workbench
from ls2d.utils import format_pipeline
from ls2d.utils import format_demographics
# ... |
a6926d37478dd93e777563e7529cd674e72963deb3bf573441fccd06e44e77c9 | Python | 731 | 25 | """Snakemake wrapper for samtools fixmate"""
__author__ = "Thibault Dayris"
__copyright__ = "Copyright 2019, Dayris Thibault"
__email__ = "thibault.dayris@gustaveroussy.fr"
__license__ = "MIT"
import os.path as op
from snakemake.shell import shell
from snakemake.utils import makedirs
log = snakemake.log_fmt_shell(s... |
ebdfc0519732c224012355e2f7854d2d26ded0a68f1749dae588eb6e0fd66414 | Python | 732 | 32 | """Snakemake wrapper for verifybamid2."""
__author__ = "Delvin So"
__copyright__ = "Copyright 2020, Delvin So"
__email__ = "delvin.so@sickkids.ca"
__license__ = "MIT"
import os
from snakemake.shell import shell
log = snakemake.log_fmt_shell(stdout=False, stderr=True)
out_dir = snakemake.params.get("out_dir")
extra =... |
0c850cb20615c062e7fab76a9509de40cfe0be6093fb9e4d37704c452d458a5a | Python | 735 | 25 | #%%
from pymaid_creds import url, name, password, token
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
import numpy as np
import pandas as pd
import connectome_tools.process_matrix as pm
pairs = pm.Promat.get_pairs()
# %%
# identify brain neurons in pair-list; brain neurons not in pair-list
#... |
aa1f831b0584167981992a94c25f0e5ccb732525e3ed46649d43a3282ba9b1ef | Python | 735 | 16 | # 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... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.