sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6d697813882b10db6b8619db58b05f0c78e0b6640c254bf88d9d4b5c10d2d395 | Python | 13,311 | 353 | from __future__ import annotations
from functools import reduce
from importlib.util import find_spec
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import pytest
from zarr.storage import MemoryStore
import anndata as ad
from anndata._core.file_backing import to_memory
from anndata.experiment... |
0960de051054048f3b4030e0335c270215c6ad5710b4297b203f41c33afa8c9b | Python | 13,313 | 288 |
from fig_utils import *
import matplotlib.patheffects as pe
def fig1(imgs_norm, masks_true, dat, timings, save_fig=False):
fig = plt.figure(figsize=(14, 5.5))
thresholds = dat["thresholds"]
grid = plt.GridSpec(2, 5, figure=fig, left=0.05, right=0.98, top=0.94, bottom=0.09,
wsp... |
6c813dc23649dbbe6a4779ad5c88505d92807f4f12854401aedf394ff66685ef | Python | 13,324 | 368 | #!/usr/bin/env python
"""
searches for tests for packages in the bioconda-recipes repo and on Anaconda, looking in different file locations. If no test can be found for the specified version, it will look for tests for other versions of the same package.
A shallow search (default for singularity and conda generation ... |
a482dcb26c497e780433b77d00f3608379457c0dc60d16fa782a4544a73d26f2 | Python | 13,335 | 365 | import logging
import os
from typing import (
Any,
cast,
Literal,
Union,
)
# Playwright browser type names (matches BrowserType.name property)
PlaywrightBrowserName = Literal["chromium", "firefox", "webkit"]
try:
from pyvirtualdisplay import Display
except ImportError:
Display = None
try:
... |
76a268bf6ea2e4a2dc19ac2651c8a9f5ce2838613e698912f41ae19d037d9a15 | Python | 13,336 | 449 | """
Module for additional needed types
"""
import copy
import functools
import heapq as hp
import random
class SetDict(object):
"""
Type which implements the following operations with a runtime better than O(n):
- adding of items (once)
- removal of items
- random access
additional the operat... |
366b95da40e8e2787631e3748707097f44120eda8c0f475f49e78a4ac601b50f | Python | 13,342 | 431 | """Unit testing for time dependent algorithms."""
from datetime import datetime, timedelta
import pytest
import networkx as nx
_delta = timedelta(days=5 * 365)
class TestCdIndex:
"""Unit testing for the cd index function."""
def test_common_graph(self):
G = nx.DiGraph()
G.add_nodes_from([... |
279bf9ff457855e42ebb72044f6748d9d082bcc7c3f1d9cec64890bec47dc644 | Python | 13,345 | 233 | # -*- coding: utf-8 -*-
"""Auto-generated by geocode_institutions.py. INSTITUTION study coords.
Resolve a raw sheet token with: COORDS.get(ALIASES.get(tok, tok)).
"""
INSTITUTION_ALIASES = {
'Brain Mind Institute': 'EPFL',
"Children's Hospital of Philadelphia": 'Children’s Hospital of Philadelphia',
'Colum... |
d48a857ad4c6e4da650fbf2074c2740c4f65ac7af0ca093233dff3c53f3b9c4c | Python | 13,351 | 349 | import pytest
import networkx as nx
from networkx.utils import edges_equal, graphs_equal, nodes_equal
np = pytest.importorskip("numpy")
pd = pytest.importorskip("pandas")
class TestConvertPandas:
def setup_method(self):
self.rng = np.random.RandomState(seed=5)
ints = self.rng.randint(1, 11, size... |
ae565456bd6a6bdac477a2ef17c8fc99b3c78dfd45b7f06b9e8283f817525611 | Python | 13,355 | 282 | import socket
import os
import numpy as np
import pandas as pd
import re
import martian
import tenkit.reference as tk_ref
import tenkit.preflight as tk_preflight
from constants import ALLOWED_FACTORIZATIONS, FRAGMENTS_SCAN_SIZE, NO_BARCODE
from utils import motif_format_checker
from tools.regions import bed_format_che... |
c03a7c6b8874f8e060b94511d13d2a49af79db9716afc0f6e5f7abecdb670136 | Python | 13,355 | 309 | """Plot the zero-shot identification analysis results.
Parameters
----------
rank_correct : int
Accepted correlation rank of the correct synthetic data image condition.
project_dir : str
Directory of the project folder.
"""
import argparse
import os
import numpy as np
import matplotlib
from matplotlib import pyplo... |
3a018af86082ddab46d4bcf40658e962bda34ef957c0e21e6d1ab729f83dcc8e | Python | 13,364 | 424 | from abc import abstractmethod
import torch
import numpy as np
try:
import cuhals
use_cuhals = True
except ImportError:
use_cuhals = False
from .base import VideoFactorizer
from .factor import TensorFactor
def native_update(Beta,
Delta,
Sigma,
nonneg... |
77c675c5570a1de8b1c634f1aa08b73a1a46840159c22bdbe0b00ed17037783e | Python | 13,396 | 250 | # generated by datamodel-codegen:
# filename: openapi.yaml
# timestamp: 2023-08-03T18:47:00+00:00
from __future__ import annotations
from datetime import datetime
from enum import Enum
from typing import (
List,
Optional,
)
from pydantic import (
AnyUrl,
BaseModel,
Field,
)
class ServiceTy... |
958ea62026673809dd7d9541a238cc3e7fae3b59def58b1e296b039f8540824d | Python | 13,405 | 424 | from abc import abstractmethod
import torch
import numpy as np
try:
import cuhals
use_cuhals = True
except ImportError:
use_cuhals = False
from .base import VideoFactorizer
from .factor import TensorFactor
def native_update(Beta,
Delta,
Sigma,
nonneg... |
ccefbf8ce6bb6da0ff63acbfcc3150561612bdcd638270c4037d3bcbd2c04c00 | Python | 13,407 | 369 | from __future__ import absolute_import
import logging
import os.path
import re
from pip._vendor.packaging.version import parse as parse_version
from pip._vendor.six.moves.urllib import parse as urllib_parse
from pip._vendor.six.moves.urllib import request as urllib_request
from pip._internal.exceptions import BadCom... |
83df90eeb339860be3c90d5795ac4c01b2edbb2841f0eca8445ac502dcd921a1 | Python | 13,408 | 359 | import torch
import networkx as nx
import numpy as np
import os.path as osp
import pickle as pkl
import sys
import scipy.sparse as sp
from cogdl.data import Dataset, Graph
from cogdl.utils import download_url, untar, Accuracy, CrossEntropyLoss
def read_geom_data(folder, dataset_name):
graph_adjacency_list_file_p... |
ae6fb0544b1d8201422ad516a08953df9fdd2213fb6c1a8b9c284a57b711bbb0 | Python | 13,417 | 431 | import numpy as np
import matplotlib.pyplot as plt
import math
import power_law
import matplotlib as mpl
from cycler import cycler
from tqdm import tqdm
mpl.rcParams['axes.prop_cycle'] = cycler(color='bgrcmyk')
myfont = 6
myaxis_font = 8
plt.rcParams.update({'font.size': myfont})
line_width = 1
def nonlin(z, act = '... |
f8ff9f5e9ea23a3e5b0f087e2dcbc11a8ce2fd38d0099f11045b9b3b8119ba19 | Python | 13,448 | 322 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
154a40eebdc47ce6ced7601bf0cea391244d792f9e8be6a30f9a50c4bd0b805c | Python | 13,451 | 400 | """Functions for estimating the small-world-ness of graphs.
A small world network is characterized by a small average shortest path length,
and a large clustering coefficient.
Small-worldness is commonly measured with the coefficient sigma or omega.
Both coefficients compare the average clustering coefficient and sh... |
51cafd5c87ccf6bbf7341aa09f63a461436ab459a598400f39c4d1109d63e212 | Python | 13,454 | 276 | import os
import sys
import tensorflow as tf
import numpy as np
import learnMSA.protein_language_models.legacy_pretraining.DataPipeline as data
import learnMSA.protein_language_models.common as common
from learnMSA.protein_language_models.bilinear_symmetric import make_scoring_model
from learnMSA.protein_language_model... |
97d3f88e19a183ff6e60154c35298b616f1bb47247d3bf92976488289b4ed4b0 | Python | 13,466 | 413 | """Functions for encoding and decoding trees.
Since a tree is a highly restricted form of graph, it can be represented
concisely in several ways. This module includes functions for encoding
and decoding trees in the form of nested tuples and Prüfer
sequences. The former requires a rooted tree, whereas the latter can b... |
40664563d322644b2d8404f5a83c148476c3843b45fc3df0ee572849455fc5b3 | Python | 13,470 | 281 | import numpy as np
import pandas as pd
def MichaelisMenten(K_i, C): # K_i: affinity ligand, C: concentration ligand
act = C/(K_i+C)
return act
def CompetitiveBinding(K_A, C_A, K_B, C_B): # K_A: affinity ligand A, C_A: concentration ligand A
a = K_A + K_B + C_A + C_B - 1
b = K_B*(C_A - 1) + K_A*(C_B ... |
0025676afad3fa16b94e4e928b4f9c079d041825d157d71a6467dc826ae7d75d | Python | 13,489 | 331 | import os
import os.path
import tempfile
import numpy as np
import pytest
import test_utils
import xarray as xr
from alpineer import image_utils
from alpineer.test_utils import make_images_xarray, make_labels_xarray
from skimage.measure import regionprops
import ark.settings as settings
from ark.segmentation import s... |
a8a8fdf05583e089487d1c914d31237ccab1b20ef21e9d9d8ef2f661ccc1c978 | Python | 13,490 | 507 | # -*- coding: utf-8 -*-
"""
Plot3d Module
=============
Plotting routines for 3d display of data.
Note
----
This module is using vispy.
"""
__author__ = 'Christoph Kirst <ckirst@rockefeller.edu>'
__license__ = 'MIT License <http://www.opensource.org/licenses/mit-license.php>'
__copyright__ = 'Copyright (c) 2017 ... |
fe1e1d442829e5b20a739df857befe0b2331be11b5dd9ce13a5cc72af13cd1a3 | Python | 13,503 | 374 | import abc
import ast
import inspect
import itertools
import re
import typing
from collections import defaultdict
from copy import copy
from pathlib import Path
import black
from ..assets import Mod, Package, SupportedDialect
from ..exceptions import ModSourceError, PackageApiError, PackageFileError
if typing.TYPE_C... |
ee81decc6300b4eacdd39be1606f8befae168bc8f56e0db82d3a468301f8c4cf | Python | 13,528 | 380 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# 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, m... |
4c567b07ddf072165e273e96e75f64062a1db0a778c6faef281644b1b5bf83b4 | Python | 13,548 | 302 | # Copyright 2020 DeepMind Technologies Limited.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
5f21cee47acd9e0d982f4058ad17c8b81299354a052d58eb30be211fde4f7920 | Python | 13,549 | 382 | import copy
import pytest
import torch
from spikingjelly.activation_based import functional, layer, quantize
from spikingjelly.activation_based.functional.misc import (
delay,
first_spike_index,
redundant_one_hot,
)
from spikingjelly.activation_based.layer.container import StepModeContainer
from spikingje... |
4468269da988d2df71c3463c8ed4ca1b4d90c6b561498cf321c57b151ceace2f | Python | 13,557 | 437 | """
HDF5 storage engine for the BSB framework.
"""
import importlib.metadata
import json
import os
import shutil
import time
from datetime import datetime
import h5py
import shortuuid
from bsb import (
BsbProvenanceUpgradeWarning,
Engine,
MPILock,
ScaffoldWarning,
config,
report,
warn,
)
f... |
703c8269b75fe5bdbf386700d92c958b7af1c940a3962469365e193c4f372e0e | Python | 13,557 | 412 | import json
import pathlib
from typing import Union
import dask
import numpy as np
import pandas as pd
import xarray as xr
from cooler import binnify, read_chromsizes
from scipy import ndimage
def _get_chrom_offsets(bins):
_co = {chrom: bins[bins["chrom"] == chrom].index[0] for chrom in bins["chrom"].cat.categor... |
cb86e5905e6e9db28196108fbef3db28b9a16828f8eb44d66ca1081f2b622004 | Python | 13,560 | 325 | """This file and its contents are licensed under the Apache License 2.0. Please see the included NOTICE for copyright information and LICENSE for a copy of the license."""
import json
import logging
import re
from datetime import timedelta
from typing import Union
from urllib.parse import urlparse
from azure.core.exc... |
1e92bb662ab7518958c8c0699e92bf498f0c78ec5a4825acaf8e436ba69dbf00 | Python | 13,564 | 377 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
import copy
from collections.abc import Callable, Mapping
from dataclasses import dataclass
from typing import Any
from ax.b... |
36ebb698a091ff023b94d8ac6e80f64f3fc79dccc5ac2437efd927470b21e6d4 | Python | 13,565 | 341 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# 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, m... |
12d18d4dcfb2175322ea24562afc177543452c98d5365b0c1b72b6906173d825 | Python | 13,566 | 466 | # -*- coding: utf-8 -*-
"""
ConvolvePointList
=================
Convolution on a subset of points only.
Paralllel convolution of a kernel at specified points of the source only.
Useful to speed up processing in large arrays and only a smaller number of
convolution points.
Note
----
This module is heavily used in... |
7cd0df4b1f7582a678dc44e4263349361c73b4030ffe05893fe0aaae18c0824d | Python | 13,566 | 332 | # Copyright 2020 DeepMind Technologies Limited.
#
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
c4270347c8b7543cadfa090f016234c59e97140b4a62163c9a50497a09142ed3 | Python | 13,583 | 399 | import pytest
import torch
import torch.nn as nn
import torch.nn.functional as F
from spikingjelly.activation_based import functional, neuron, surrogate
from spikingjelly.activation_based.ann2snn.operators import (
SNNElementWiseProduct,
SNNMatrixOperator,
TDLinear,
)
def _table(scale=1.0):
return ne... |
c6bbd424e64fbdaa0ea96820333b2f1c669082c8b7bd18d4c107967461eab39c | Python | 13,594 | 545 | import torch
import torch.nn.functional as F
from cogdl.options import get_default_args
from cogdl.experiments import train
cuda_available = torch.cuda.is_available()
default_dict = {
"hidden_size": 16,
"dropout": 0.5,
"patience": 2,
"epochs": 3,
"sampler": "none",
"num_layers": 2,
"cpu":... |
a0bd5a62aa4fd4bbd651fc2386d1563e5bf1614f3533c0d91620e222a68c28f0 | Python | 13,595 | 338 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: chrisarcadia
@created: 2018/06/04
"""
# libraries
import Chemical
###############################################################################
# Periodic Table Of Elements
## ways of instantiating the periodic table of elements
elements = Chemical.Peri... |
e5cfe0639e591b42fd68f5d5fa3ac87b656668f0a15b7d6e5d90eb23e524aa53 | Python | 13,600 | 227 | #!/usr/bin/env python3
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# ... |
ae2ae725608b92a43480a7d30fab7902c45e4c28cacb38cf8150ca5fdac4e950 | Python | 13,604 | 302 | """Functions to provide variable documentation."""
import os
import os.path as op
import json
from shutil import copyfile
from collections import OrderedDict
import sp_experiment
from sp_experiment.define_ttl_triggers import provide_trigger_dict
def make_events_json_dict():
"""Provide a dict to describe all coll... |
8f090c5e132f781c6a526ff73a6689638c0b42f14de9f67b2f3e79545988c47a | Python | 13,615 | 384 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
79594ea42fab73e54cb493e6575394cd173b0f0de9f19882b7addf7ee4663e20 | Python | 13,617 | 324 | import logging
import math
from typing import (
Any,
)
from galaxy import (
exceptions,
model,
)
from galaxy.model.dataset_collections.types.sample_sheet_util import validate_column_definitions
from galaxy.util import string_as_bool
log = logging.getLogger(__name__)
ERROR_MESSAGE_UNKNOWN_SRC = "Unknown d... |
178ae14c091afed2cc77474d583a3af61696f07b9fa5c55b401e7fb76cf2e09b | Python | 13,620 | 320 | import contextlib
import copy
import importlib.metadata
import os
import pathlib
import tempfile
import unittest
from unittest import mock
import toml
from bsb import OptionError, ReadOnlyOptionError, option, options
from bsb._options import QuietFlag
from bsb.cli import handle_command
from bsb.option import _clear_p... |
2c0c55a9a4f72e6b90c36d3ffedd4aae02ca3c5d42cfe3e44da892ae03c2d455 | Python | 13,623 | 357 | """Functions for computing eigenvector centrality."""
import math
import networkx as nx
from networkx.utils import not_implemented_for
__all__ = ["eigenvector_centrality", "eigenvector_centrality_numpy"]
@not_implemented_for("multigraph")
@nx._dispatchable(edge_attrs="weight")
def eigenvector_centrality(G, max_ite... |
1da2662600a81ce92e133d101bcb144038e501cdb6577419550323dac7e0ab9c | Python | 13,625 | 351 | """
Multiple-kernel ridge solvers
=============================
This example demonstrates the different strategies to solve the multiple kernel
ridge regression: the *random search*, and the *hyper-gradient descent*.
The *random-search* strategy samples some kernel weights vectors from a
Dirichlet distribution, then f... |
5a0f3644d75516ccc34127a00e89742d7073727bf2b331616faf44b65aee40a5 | Python | 13,632 | 400 | from pathlib import Path
from rich.progress import track
from rich import print
import os
import numpy as np
from myterial import amber, orange, salmon
from loguru import logger
from brainrender.camera import check_camera_param, get_camera_params
from brainrender._video import Video
import brainrender as br
from brain... |
a48ed57970aee0423b6ebd956f25411d85b40ac7165a637060bdbae86e2f5df7 | Python | 13,636 | 303 | """Mark scikit-learn classes as configurable"""
import gin
# Clustering
import sklearn.cluster
# TODO: Delete when https://github.com/google/gin-config/pull/49 gets merged
# Most of the classes mentioned in the docs:
# https://scikit-learn.org/stable/modules/classes.html
gin.external_configurable(sklearn.cluster.Af... |
320457994832aaaa2ac841e69358506f9f0e58001e6738da7d286310ad470e7e | Python | 13,640 | 355 | # This code is based on decagon from
#
# https://github.com/mims-harvard/decagon
#
# Our contribution is the incorporation of GAT
# encoder into the bipartite network.
from __future__ import division
from __future__ import print_function
import os
import pickle
import time
from operator import itemgett... |
6ec233edb33ec74b8570448eb39e2436a70d7282eb435ea96692e433f3c51080 | Python | 13,640 | 364 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from __future__ import annotations
import warnings
import numpy as np
import numpy.typing as npt
fro... |
f00db2a32351b590f63e38d93a6e57843b0b2777b5e1fe89bf342a87af9d0484 | Python | 13,643 | 358 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from collections.abc import Mapping, Sequence
from typing import final, Literal
import pandas as pd
from ax.adapter.base impo... |
2260139f4aff3fe8ec0083c8bc7c8effb4244c181234d3d770961c827ca4e01d | Python | 13,649 | 336 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
b290c13d2303f835f2482d7be76fff0008107f59c6ee3f7028beec9082ca31c8 | Python | 13,649 | 435 | """
********************
Bipartite Edge Lists
********************
Read and write NetworkX graphs as bipartite edge lists.
Format
------
You can read or write three formats of edge lists with these functions.
Node pairs with no data::
1 2
Python dictionary as data::
1 2 {'weight':7, 'color':'green'}
Arbitrary d... |
ed6c49e31b89cf5326d54499f5124a55d543412ce303c2907596b06538428cff | Python | 13,652 | 351 | """
Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
Put the sample index barcode and 10X barcode into read tags in a BAM file.
Screen each 10X barcode against the given barcode whitelist
"""
import itertools
import json
import random
import martian
import numpy as np
import tenkit.bam as tk_bam
import te... |
d26e2546db6faf6fc54fa5ec84ff125f2eb0e8f1d235caba0f36a54b9ff71dab | Python | 13,664 | 341 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
e432540798e7251961186e767f4eb5e10e8e1186869c896f4fe27d8013dd4cd8 | Python | 13,665 | 239 | import re
import sys
import os
import math
from scipy import stats
print("MIPPI_mutation_sites_mapping_by_category")
Disease_list = []
Category_list =[]
Disease_category = {}
with open(r'E:\OneDrive\学术\PPI article\data\de novo mutation data\20190514_MasterFile_allDNMs-codingLoc_v1.5.txt') as fp:
text = ... |
8883246c776d26c80395c76986113fb944c9d15193185cca215bcc77ba1a9a85 | Python | 13,669 | 371 | import pytest
import networkx as nx
from networkx.utils import edges_equal
class TestSubGraphView:
gview = staticmethod(nx.subgraph_view)
graph = nx.Graph
hide_edges_filter = staticmethod(nx.filters.hide_edges)
show_edges_filter = staticmethod(nx.filters.show_edges)
@classmethod
def setup_cl... |
a15e133612988d3a5b28a0363b4f105c62d77da9ef4f4d4680ffa413d2939775 | Python | 13,682 | 257 | import argparse
from utils import load_architecture, evaluate, ArgsStruct
import torch
import os
import json
from training.covid_torch_dataset import CovidDataset, CovidData, DatasetBuilder
from torch.utils.data.dataloader import DataLoader
import logging
import shutil
import time
import numpy as np
from statistics imp... |
630c4add5df15378f612faf2abd08faf97b0ee72ddd44982cc00752239e998be | Python | 13,695 | 344 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
4e3c939e4021c2c58309ab8ad2ecd18c0219836ad36a63204195931c533ee2d5 | Python | 13,696 | 344 | import pytest
import torch
from spikingjelly.activation_based import functional, neuron, surrogate
def _node(kind, **kwargs):
node_type = neuron.TernaryIFNode if kind == "if" else neuron.TernaryLIFNode
return node_type(**kwargs)
def _scalar_rollout(x_seq, kind, threshold, reset, tau=2.5, decay_input=True):... |
53b83e6308b34363b935180afcc66b785d67b4ce04e3d0b73ee177a1df95c33e | Python | 13,698 | 367 | """
The httplib2 algorithms ported for use with requests.
"""
import logging
import re
import calendar
import time
from email.utils import parsedate_tz
from pip._vendor.requests.structures import CaseInsensitiveDict
from .cache import DictCache
from .serialize import Serializer
logger = logging.getLogger(__name__)
... |
e8a8ea1c1dabb366d2d20c5517810222332ae8f4d44081d91bf3d0059d02595e | Python | 13,700 | 400 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
import math
from typing import final
import pandas as pd
from ax.adapter.base import Adapter
from ax.analysis.analysis impor... |
e7716b3d23381a6edfa2532e9069b388b548079e191ed9fe2d968b1fc68c8f2f | Python | 13,706 | 308 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from copy import deepcopy
from unittest import mock
import numpy as np
from ax.adapter.base import Da... |
14334cf6df52096fc36e85859ebabdabb47930f748e53e739d169f89f48acb57 | Python | 13,711 | 233 | """Functions for working with generic files.
Functions
---------
get_model_name(settings)
get_netcdf_da(filename)
save_pred_obs(pred_vector, filename)
save_tf_model(model, model_name, directory, settings)
get_cmip_filenames(settings, verbose=0)
"""
import xarray as xr
import json
import pickle
import tensorflow as tf... |
ca60de1452939a364c52b1427ab43c96f850a6fe2958eda3461e989a7a9c5182 | Python | 13,725 | 307 | """Run the MEMOTE test suite and record the total score for tracking.
MEMOTE only computes a total score when it builds a report; the raw `memote run`
result JSON contains per-test results but no score. So this runs MEMOTE in-process
through its Python API and then builds the snapshot report to obtain the score,
rathe... |
3a7abdc6a7acd51d6aa6d9640143a196f18ed8964bbd5bce040eda3bbd9821f7 | Python | 13,730 | 382 | """
Requirements file parsing
"""
from __future__ import absolute_import
import optparse
import os
import re
import shlex
import sys
from pip._vendor.six.moves import filterfalse
from pip._vendor.six.moves.urllib import parse as urllib_parse
from pip._internal.cli import cmdoptions
from pip._internal.download impor... |
9fa13d8b0bbf085fb1ff34c31a3488c7d820c1fb6448f9f0cebb3931d4f03c07 | Python | 13,732 | 281 | # generated by datamodel-codegen:
# filename: https://raw.githubusercontent.com/ga4gh/workflow-execution-service-schemas/develop/openapi/workflow_execution_service.openapi.yaml
# timestamp: 2025-11-18T17:23:28+00:00
from __future__ import annotations
from enum import Enum
from typing import (
Any,
Option... |
a6a7fd48cc1dc31b312011472c7551f06baffd95faaeacc018c968cf8766bfb1 | Python | 13,735 | 445 | """
Neural dynamics library
=======================
.. module:: lib_NeuroDyn
:platform: Linux
:synopsis: a miscellaneous of neural activity related methods.
.. moduleauthor:: Jose M. Esnaola-Acebes <josemesnaola@gmail.com>
Noisy signals
-------------
.. autosummary::
:toctree: generated/
ou_process ... |
b97abb8757c29af714c89861dc3ba3c99bc91f6486960a3e25174b6df7f76ca2 | Python | 13,735 | 400 | from math import sqrt
import pytest
import networkx as nx
np = pytest.importorskip("numpy")
methods = ("tracemin_pcg", "tracemin_lu", "lanczos", "lobpcg")
def test_algebraic_connectivity_tracemin_chol():
"""Test that "tracemin_chol" raises an exception."""
pytest.importorskip("scipy")
G = nx.barbell_gr... |
590eaebb37a56dd6c3612a6d34804b61025577949003ae4269ed17214f567617 | Python | 13,754 | 383 | # -*- coding: utf-8 -*-
"""
Class will handle the images in terms of folders
Moves images to train, test, val folders as needed
Separates images *DM.jpg and *CM.jpg
"""
import fnmatch
import glob
import os
import random
from pathlib import Path
from shutil import copyfile
import cv2
import numpy as np
import pandas... |
93050437f8481c3ecdddd1d9b8a5b0da7df363dc5beb0a4ba1fdb36d31eaae21 | Python | 13,761 | 462 | from funlib import evaluate
import math
import networkx
import unittest
class TestRandVoi(unittest.TestCase):
def test_skeleton_lengths(self):
skeletons = networkx.Graph()
# length of 2*sqrt(2)
skeletons.add_node(1, skeleton_id=1, z=0, y=0, x=0)
skeletons.add_node(2, skeleton_id... |
5613d98bf7e357ccb41a68527ba294fa528598c5ddfa9f2890d0e0d406615c65 | Python | 13,763 | 426 | """
Scene
- Create a scene, add root and inset if necessary
- add actor method
- special methods
"""
import sys
from pathlib import Path
from vedo import Mesh, Text2D, Assembly
import pyinspect as pi
from rich import print
from loguru import logger
from myterial import amber, orange, orange_darker, salmon
... |
87939aee8ac56a36d34ea2c8fa3683aee10236cd92aeb297b35847484d5c0de2 | Python | 13,764 | 440 | """
Unit tests for inhibitory cell density computation
(linear program minimizing distances to initial estimates)
"""
import numpy as np
import numpy.testing as npt
import pandas as pd
import pandas.testing as pdt
import pytest
import atlas_densities.densities.inhibitory_neuron_densities_optimization as tested
from a... |
b60aeab4b82fb56ec445a93c0a7166e69b70402736ff27a187f805a73459547d | Python | 13,764 | 247 | import torch
from nidn.utils.global_constants import EPS_0, PI, SPEED_OF_LIGHT, UNIT_MAGNITUDE
from nidn.fdtd_integration.constants import FDTD_GRID_SCALE
from nidn.fdtd_integration.compute_fdtd_grid_scaling import _compute_fdtd_grid_scaling
from ..fdtd_integration.init_fdtd import init_fdtd
from ..fdtd_integration.c... |
ad827f9c28b962b5e1dfd22673301de5478b4170279b608dbc305919bbfd6bde | Python | 13,772 | 213 | from utils import checkattr
def set_method_options(args, **kwargs):
# If the 'convenience' option for a specific method is selected, select the corresponding defaults
if checkattr(args, 'ewc'):
args.weight_penalty = True
args.importance_weighting = 'fisher'
args.offline = True
if c... |
7c1e62db024c3e4c33538264f8ae573240fa7eccbce0d6b1a397b79803215977 | Python | 13,774 | 305 | # -*- coding: utf-8 -*-
"""
Created on 2021.08.19
@author: Jiahua Rao
"""
import os
import json
import numpy as np
import pandas as pd
from rdkit import Chem
from pathlib import Path
from sklearn.model_selection import train_test_split
from MolRep.Featurization.Graph_embeddings import GraphEmbeddings
from MolRep... |
759ae5f65a55dcaefcc13f1655967f402344d56b73c2daae0795827b3dd13476 | Python | 13,776 | 340 | import unittest
import numpy as np
from bsb_test import RandomStorageFixture
from bsb import MPI, CastError, CfgReferenceError, NumpyRng, Scaffold
from bsb.config import Configuration
from bsb.rng import _stable_ints
class _NetworkMixin:
"""Builds networks whose only interesting configuration is their randomnes... |
2aa62cf38f84eafe960ec9136a1db1b5a719ffbb1487e92724e56e5f1f102521 | Python | 13,789 | 314 | import h5py
import tifffile as tiff
import importlib.util
from ..utils import *
cp, np, convolve, gpuAvailable, freeMemory, e = checkForCupy()
class Writer:
"""
A writing object for saving processed images as they are reconstructed
"""
def __init__(self):
# For MGH
self.metaLengthbytes... |
d5889b6c1b3bd115311cd38dcd11483fa58cc906ca79137770c0068d2433b176 | Python | 13,793 | 379 | """
Boykov-Kolmogorov algorithm for maximum flow problems.
"""
from collections import deque
from operator import itemgetter
import networkx as nx
from networkx.algorithms.flow.utils import build_residual_network
__all__ = ["boykov_kolmogorov"]
@nx._dispatchable(
edge_attrs={"capacity": float("inf")}, returns_... |
b6bbe9e9853f1cae7e5bb3c641fc10f72e0743197151640c0cdf7016e256cb84 | Python | 13,805 | 262 | #!/usr/bin/env python
#
# Copyright (c) 2016 10X Genomics, Inc. All rights reserved.
#
import cellranger.analysis.constants as analysis_constants
import cellranger.library_constants as lib_constants
import cellranger.io as cr_io
import csv
import json
import numpy as np
import os
import scipy.stats
import sys
import te... |
b534eef7bbc154d81c54d9b4544a413a1bca1eb8d40dea51faa1ec51b7108e86 | Python | 13,806 | 391 | """
Unit tests for densities utils
"""
from pathlib import Path
from unittest.mock import patch
import numpy as np
import numpy.testing as npt
import pandas as pd
import pandas.testing as pdt
import pytest
from voxcell import RegionMap
import atlas_densities.densities.utils as tested
from atlas_densities.exceptions i... |
ee33ab940f790b9b0458ab7da19d011c30999e363a987028d45ded97581bbaee | Python | 13,806 | 397 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# 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, m... |
0de3ce58d6a785330eeebc4d15725a239c8911baaf6d493e5818efff94682a87 | Python | 13,810 | 380 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from copy import deepcopy
from ax.adapter.base import DataLoaderConfig
from ax.adapter.data_utils imp... |
e47558c5a45629fd1c2a5fcef802658a91aba52c18ee44fe5b8db877682ef1f9 | Python | 13,816 | 289 | """Collection type descriptions and the compatibility algebra.
Three operations on collection types, each answering a distinct question:
- ``accepts(other)``: asymmetric direct-edge check. True iff an output
collection of type ``other`` can be connected to an input slot whose
declared type is ``self``. Used at wo... |
3bdb73f9fd95e66f4f8e79f6c33908ec81644cb016c00c671fb689bd57b73794 | Python | 13,819 | 360 | from __future__ import annotations
from typing import Any, Literal
import dask.array as da
import geopandas as gpd
import numpy as np
import xarray as xr
from shapely import box
from spatialdata import SpatialData
from spatialdata._logging import logger
from spatialdata.models import Labels2DModel, ShapesModel
from s... |
6123ffd819d012324b75df6826b496e0ef02b0fc25f0c6ecb329a1b2ba4876db | Python | 13,826 | 416 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from typing import Sequence, Tuple, List, Union
import pickle
import re
import shutil
import torch
from pathlib import Path
RawMSA ... |
f1a0f138de91f4a308c83bd347650e36e67295969bd02fc5648f2a5ea3d4c86b | Python | 13,828 | 241 | import re
import sys
import os
import math
from scipy import stats
print("MIPPI_mutation_sites_mapping_by_disease")
Disease_list = []
Category_list =[]
Disease_category = {}
with open(r'E:\OneDrive\学术\PPI article\data\de novo mutation data\20190514_MasterFile_allDNMs-codingLoc_v1.5.txt') as fp:
text = f... |
e89feac76820e0047c56757409f5fd0b9d6dcd3dbed020833ecc1b833feabcf3 | Python | 13,829 | 230 |
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 5 10:27:05 2019
@author: schelskim
"""
from .generaltools import generalTools
from .analyzers import Analyzers
from .neuriteconstructor import neuriteConstructor
#from tools.dataframecleanup import DataframeCleanup
import numpy as np
import copy
import pandas as pd
f... |
6de74867d06879c5fdf2b8445fccdcc8498a5888004f06cd02557968569696c3 | Python | 13,830 | 389 | import logging
from typing import Tuple, Union
import dask.array as da
import dask.dataframe as dd
import dask_distance as ddst
import numpy as np
import scipy.spatial.distance as dst
from sklearn.base import (
BaseEstimator,
ClusterMixin,
TransformerMixin,
)
from sklearn.utils.validation import check_is_f... |
19276fb33efee7353b7c77edb7870000ddee5973cfec6a8eafab2546a8ed7fd7 | Python | 13,832 | 339 | import tensorflow as tf
from src.factory import Factory
from src.custom_layers.cs_layers import CompressedSensing, CompressedSensingInception
from src.utility import get_root_path
from astropy.convolution import Gaussian2DKernel
import numpy as np
import os
import matplotlib.pyplot as plt
from scipy import interpolate
... |
68e0071bd1c34251de90b429cfbee345909cebd2ef472834780920762664aae4 | Python | 13,838 | 445 | import sys
import numpy as np
from copy import deepcopy
from ...misc.status import Status
from ....utils.default_parameters import default_parameters
class Parameters:
"""
rsHRF-Toolbox Parameters
For more information, visit https://github.com/BIDS-Apps/rsHRF/tree/master/rsHRF
"""
def __init__(se... |
28b16f9272e096570c92027ecd4b058c2cceb7d3f4ddf0e82294cfcffbea5c2c | Python | 13,839 | 391 | from __future__ import absolute_import
import datetime
import logging
import os
import socket
from socket import error as SocketError, timeout as SocketTimeout
import warnings
from .packages import six
from .packages.six.moves.http_client import HTTPConnection as _HTTPConnection
from .packages.six.moves.http_client imp... |
429ffdb416027f03a0188475c5d3bb2916214de7f8acc2d44f9ba1dbd2b32692 | Python | 13,848 | 310 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
f3a50ccafd69992f7434c249a24da0bb4aa2c119e47b6c47a944df93d48de701 | Python | 13,853 | 411 | """
Unit tests for overall cell density computation
"""
from pathlib import Path
import numpy as np
import pandas as pd
import pandas.testing as pdt
import pytest
from voxcell import RegionMap # type: ignore
import atlas_densities.densities.measurement_to_density as tested
from atlas_densities.exceptions import Atla... |
0daa2c59e40ea66bddd7a4ad75fc9eb4c28af7eb26118ac4cec33406323d3997 | Python | 13,885 | 318 | import math
import os
import tempfile
import numpy as np
import pandas as pd
import pytest
import test_utils
import ark.settings as settings
from ark.analysis import neighborhood_analysis
def test_create_neighborhood_matrix():
# get positive expression and distance matrices
all_data_pos, dist_mat_pos = test... |
d95eca37c9592b61672cfdda15bf0e26b1d2c284c622306a8047ce088ec4d734 | Python | 13,886 | 347 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
"""
References
.. [Papenmeier2025hd]
L. Papenmeier, M. Poloczek, and L. Nardi. Understanding High... |
8450534fa3f1a834d378b92cd7156accf19d9cad55c1e2ee088758ba46ea0aff | Python | 13,905 | 288 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
6264cf4f9faed13df6f0f89c410f46d712812a864093d68a8fda1ef4e305731e | Python | 13,908 | 328 | import math
import numpy as np
import torch
from matplotlib import pyplot as plt
from torch import nn
import pytorch_lightning as pl
# It's a convolutional neural network that takes in signals, passes it through a series of convolutional
# layers, and then ends in a linear layer that represents the class scores
clas... |
5c0b8bcbc004090537c716e4299a7188bb97680fe85441bcd1a3a1c8f99b2653 | Python | 13,931 | 335 | import os
import json
import concurrent.futures
import torch
import numpy as np
from skopt import gp_minimize
from skopt.utils import use_named_args
from skopt.space import Real, Categorical, Integer
from MolRep.Utils.utils import NumpyEncoder
from MolRep.Utils.logger import Logger
from MolRep.Utils.config_from_dict ... |
550b9352f7b89352497edde8caa9643dcae955148c835ada86f4c382c801e1ae | Python | 13,933 | 338 | import abc
import functools
import logging
import os
from typing import (
Annotated,
Any,
cast,
ClassVar,
Optional,
TypeVar,
)
from fsspec import AbstractFileSystem
from pydantic import Field
from galaxy.exceptions import (
AuthenticationRequired,
MessageException,
)
from galaxy.files.... |
e113a631362264d7e5d8c8bb6ef861293d71e9e3bdd1aa8b4e856ceac925852a | Python | 13,935 | 310 | # -*- coding: utf-8 -*-
"""
Created on 2020.05.19
@author: Jiahua Rao, Weiming Li, Hui Yang, Jiancong Xie
Code based on:
Yang et al "Analyzing Learned Molecular Representations for Property Prediction" & "A Deep Learning Approach to Antibiotic Discovery" -> https://github.com/chemprop/chemprop
"""
from argparse impo... |
a8627d0fffd417779606f994a5a149b2ce5fc2a5e18fc68972ec1ac932f291d3 | Python | 13,955 | 423 | #THE CODE WAS SET UP FOR GOOGLE COLAB. THE INITIAL PORTION OF THE CODE HELPS COMFIRMING GPU USAGE
"""
#this is for testing purposes, for getting the most out of GPU
import tensorflow as tf
tf.test.gpu_device_name()
# memory footprint support libraries/code
!ln -sf /opt/bin/nvidia-smi /usr/bin/nvidia... |
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