sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a77903bc894765b3d5dd975b08c3745d5ea71cd55e8fe76d3f2d85adaa27a0f5 | Python | 12,789 | 389 | from __future__ import annotations
from collections.abc import Mapping
from typing import TYPE_CHECKING
import awkward as ak
import h5py
import numpy as np
import pandas as pd
import pytest
from scipy import sparse
from zarr.storage import MemoryStore
import anndata as ad
from anndata import AnnData, concat
from ann... |
950b5eebafa1b39e3dfd72708ec12d92f9c443734b61803f4736c6ffab178197 | Python | 12,810 | 362 | #!/usr/bin/env python3
import os
import numpy as np
# -custom-written code
import main
from utils import checkattr
from params.param_stamp import get_param_stamp_from_args
from params.param_values import check_for_errors,set_default_values
from params import options
from visual import visual_plt
## Function for speci... |
b2f85026366699c6a13b0567bba27cd3a76ca3449fdc7457bba29c80e607acca | Python | 12,810 | 397 | import functools
import os
import types
from datetime import date
from sphinx_gallery.sorting import ExplicitOrder, FileNameSortKey
from intersphinx_registry import get_intersphinx_mapping
from warnings import filterwarnings
filterwarnings(
"ignore", message="Matplotlib is currently using agg", category=UserWarnin... |
6684d49586eadf32f87d894cd0bb20c5dc0fa98345d4fe8b302e2dda07cd8196 | Python | 12,815 | 354 | #!/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
import numpy as np
import numpy.typing as npt
import pandas as pd
import scipy
from ax.core.data impo... |
72366abdef8c4287c1a635f966a38c33c0ba58c7be03bf187cf3a931677f8292 | Python | 12,828 | 337 | import sys
import os
import os.path
import platform
import shutil
from optparse import OptionParser
# -------------------------------------------------------------------------------
# the main function
#
# This python script applies uncrustify (Code Beautifier) to the elastix code.
#
# Uncrustify web site: http://uncr... |
94456c9bb00ad0daaf9e209474761873d396478f04178616cc02fa9e1913bd1d | Python | 12,829 | 319 | # 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 Callable, Sequence
from unittest.mock import patch
import pandas as pd
from ax.adapter.registry ... |
5c63df4cb5ba624bc4c7ad714a294ffd0b3d9f79cacbe5f16fc2685950ea3c57 | Python | 12,836 | 405 | """
Perform Balanced PCA as well as Reproducible PCA.
A class allow user provide fitted model and just transform MCDS to adata with PCs.
"""
import anndata
import joblib
import numpy as np
import pandas as pd
import scanpy as sc
from scipy.stats import ks_2samp
from sklearn.preprocessing import RobustScaler, Standard... |
a7f6b4bca940c85519db15ef6fb93b475a3191e457e8e8635dad30764932462b | Python | 12,839 | 351 | import abc
import typing
import uuid
from dataclasses import dataclass
import numpy as np
from scipy.spatial.transform import Rotation
from bsb import pool_cache
from .. import config
from ..exceptions import EmptySelectionError
from ..morphologies import MorphologySet, RotationSet
from ..rng import RngConsumer
from... |
67534fd119cedbf89138e10fb8a9720b59ae122d174b5c06b95048fda8d3e9a6 | Python | 12,841 | 395 | """
Queries on probabilistic programs whose query atom carries constants.
The constants of a query such as ``ans(i, p) :- r(i, "pain", p)`` must
reach the rules defining ``r`` through magic sets, so that only the
``"pain"`` part of ``r`` is computed, and the result must be exactly the
one of the unrestricted query, or... |
2e5c8ede8e0419f20a30e01777c6da50eca2f91892e392bf15fecf950171c970 | Python | 12,848 | 362 | """Interfaces/mixins for transaction-like objects.
These objects describe the context around a unit of work. This unit of work
is very broad and can be anything from the response to a web request, the
scheduling of a workflow, the reloading the toolbox, etc.. Traditionally,
Galaxy has simply passed around a GalaxyWebT... |
31b88e2e7b88cbace854cbb47dcc629aff2f2c0dce2d28aff71a4448bf71d9ed | Python | 12,848 | 368 | import os
import tempfile
import pytest
import numpy as np
import pandas as pd
from neuroquery import tokenization
TEST_DATA = os.path.join(os.path.dirname(__file__), "data")
VOCABULARY_FILE = os.path.join(TEST_DATA, "vocabulary_list.csv")
def test_nltk_stop_words():
stop_words = tokenization.nltk_stop_words(... |
e913d8a8f28216d9abc30e183230ee1f30643051dd5dacf4cceff304aa5d07b3 | Python | 12,857 | 356 | """
Minimum cost flow algorithms on directed connected graphs.
"""
__all__ = ["min_cost_flow_cost", "min_cost_flow", "cost_of_flow", "max_flow_min_cost"]
import networkx as nx
@nx._dispatchable(
node_attrs="demand", edge_attrs={"capacity": float("inf"), "weight": 0}
)
def min_cost_flow_cost(G, demand="demand", ... |
9712c02dcf52248d291b07b27ba89920a55d7d607d15e598ddce3b1ec8cf0ac6 | Python | 12,858 | 246 | import os
import sys
import argparse
# os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
import torch
import torch.nn as nn
import numpy as np
import pandas as pd
from utils import *
from Model.DRPreter import DRPreter
from Model.Similarity import Similarity
from torch_scatter import scatter_add
def arg_pa... |
f1617eb8892cf5c762cf299db72a0daa50cd1eceb1a8a575c4df731059efe3f7 | Python | 12,865 | 455 | """Fixtures for populating model stores."""
from typing import (
Any,
Literal,
)
from uuid import uuid4
from galaxy.util import now
TEST_SOURCE_URI = "https://raw.githubusercontent.com/galaxyproject/galaxy/dev/test-data/2.bed"
TEST_SOURCE_URI_SIMPLE_LINE = "https://raw.githubusercontent.com/galaxyproject/gal... |
46a5a893de09bdeb60b2074a27ae1e45d12978e2b110c4acf0eb0a26bb89be0d | Python | 12,879 | 254 | # Original code Copyright 2021 Leo Hiselius
# Modified code Copyright 2021 Andrew Lehr
# The MIT License
from brian2_loihi import *
import numpy as np
from scipy import interpolate
import warnings
from .perlin import generate_perlin
from .torus_distance import torus_distance
from .params import *
class LoihiSpreizerN... |
6b39a9cbdd8b30145449fd7185d1303a6b5e74c6b47803341035bc2834d9d514 | Python | 12,881 | 299 | import utils
from utils import checkattr
##-------------------------------------------------------------------------------------------------------------------##
def define_classifier(args, config, device, depth=0, stream=False):
if checkattr(args, 'separate_networks'):
model = define_separate_classifiers(... |
81ff7e4e2ae103d8de234e4aed062bdf7489713a27e5fbea47f4ba42f16cf7ed | Python | 12,899 | 299 | import utils
from utils import checkattr
##-------------------------------------------------------------------------------------------------------------------##
def define_classifier(args, config, device, depth=0, stream=False):
if checkattr(args, 'separate_networks'):
model = define_separate_classifiers(... |
c638a5f3928fbaf400bb5a1ae89a9d19e7260ccb901b2a02059fe3de3c839571 | Python | 12,917 | 309 | """This module describes the :class:`ExplicitContainerResolver` ContainerResolver plugin."""
import copy
import logging
import os
from typing import (
Container,
Optional,
TYPE_CHECKING,
)
from galaxy.util.commands import shell
from . import ContainerResolver
from .mulled import (
CacheDirectory,
... |
47cdd86300a67c2b9526505fdd174396c4fad80a70531bf8b81eabfc90baa99c | Python | 12,925 | 321 | # Contains parameters that are used in Display Applications
import mimetypes
from collections.abc import Callable
from dataclasses import dataclass
from typing import (
Optional,
TYPE_CHECKING,
Union,
)
from urllib.parse import quote_plus
from galaxy.datatypes.data import Data
from galaxy.model import Data... |
8368507d660ce13dc960f249a48d6ef132c842a64743b269409ece793bcbc18c | Python | 12,926 | 339 | import functools
import sys
import numpy as np
import psutil
from bsb import (
AdapterError,
ConnectionModel,
ConnectionParameter,
compose_nodes,
config,
expand_to,
options,
types,
)
from tqdm import tqdm
from ._kernel_proxy import NestModelTypeHandler, query_kernel
from ._parameters i... |
7a4a30fa1f329a527d2665dde1d5ddeb5e5f0992ea0433fb50db420a53c33f60 | Python | 12,927 | 316 | # 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... |
ddeded04f19461f34cc8abfd8634103ff17308a381b4c86b8743857e74cff9d6 | Python | 12,935 | 333 | """
Tools for managing metrics with metadata attached.
Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
"""
from __future__ import division
import pandas as pd
import numpy as np
import os
import martian
# Constants for computing CTCF footprinting score
UPSTR_CTCF_PEAK_POS = '-23'
DOWNSTR_CTCF_PEAK_POS = '... |
86ecb8963777ca3e67f9dce434a6dadaca741a3940b6108098f02dedd3f247a2 | Python | 12,942 | 371 | """
Created on Feb 2, 2023.
@author: voodoocode
"""
import os
import shutil
import numpy as np
import scipy.ndimage
import pyvista
import ctypes
def _convert_vti_vdb(path, f_name, vti_vdb_conv_path, tmp_dir = None):
"""
Convert a vti object (not blender readable) into a vdb object (blender readable).
... |
9604d52c09ae3332de223e7ef732900c67ab83600dbd885247dd77992ba63c2f | Python | 12,943 | 309 | from cellpose import io, metrics, utils, models
import pytest
from subprocess import check_output, STDOUT
from pathlib import Path
import os
import numpy as np
import torch
try:
import matplotlib.pyplot as plt
MATPLOTLIB = True
except:
MATPLOTLIB = False
r_tol, a_tol = 1e-2, 1e-2
def clear_output(data_... |
126e143fb510fd04aa11e303f66639d596fd9a2b6e280f2852a5598951135b35 | Python | 12,944 | 376 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 11:35:36 2019
@author: aaussel
"""
from cells.RE_mdPul import *
from cells.TC_mdPul import *
#from cells.HTC_mdPul import *
from cells.HTC_buffer_mdPul_Destxhe_tests import *
from scipy import signal
prefs.codegen.target = 'numpy'
defaultclock.dt = 0.01*ms
runtime... |
beb5251b84d768889b40bdbc65dc8a7f2f058487a05aba1d7c89b23558ecf002 | Python | 12,946 | 354 | # 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... |
dda738d35d7e24cb75317c019d77bd9ed21f9f0900111b29f7f9b994e77772f0 | Python | 12,947 | 429 | """
Algorithms for chordal graphs.
A graph is chordal if every cycle of length at least 4 has a chord
(an edge joining two nodes not adjacent in the cycle).
https://en.wikipedia.org/wiki/Chordal_graph
"""
import sys
import networkx as nx
from networkx.algorithms.components import connected_components
from networkx.u... |
a7051ad40dce81f65f9f7c4f9350ea59fcc2c1c167670a56e2b90a8a82dfdb46 | Python | 12,953 | 353 | # 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 itemge... |
b6793297e86d6d6300ba2f66ec835ba9925f8056df36af071a957578b0390d16 | Python | 12,955 | 438 | """Functions for computing clustering of pairs"""
from collections import defaultdict
import networkx as nx
from networkx.utils.decorators import not_implemented_for
__all__ = [
"clustering",
"average_clustering",
"latapy_clustering",
"robins_alexander_clustering",
"butterflies",
]
def cc_dot(n... |
504f0622ba34862ed0289cad7fa69878ee5f79b69f49dc9dceb4edfb27370631 | Python | 12,962 | 305 | import importlib
import logging
from collections.abc import Callable
from inspect import getfullargspec
from types import ModuleType
from typing import (
TYPE_CHECKING,
Union,
)
import galaxy.jobs.rules
from galaxy.jobs import stock_rules
from galaxy.jobs.dynamic_tool_destination import map_tool_to_destination... |
a64da3ed6faaf121aed538cd2914714f6c45c84ce5f794e5ee914a13c3597b83 | Python | 12,964 | 348 | import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from spikingjelly.activation_based import neuron, functional, surrogate, layer
from torch.utils.tensorboard import SummaryWriter
import os
import time
import argparse
from torch.cuda import amp
import s... |
e0a56222fe2e43309ca68a0e79e40314f103921b3ef2f8c96ce247ec4a0614cb | Python | 12,967 | 441 | # -*- coding: utf-8 -*-
"""
Label and annotation info from Allen Brain Atlas (v2)
Notes:
- The annotation file is assumed to be in './Data/Annotation/annotation_25_right.tif'
but can be set in the constant :const:`DefaultLabeledImageFile`
- The mapping between labels and brain area information is ... |
d0f4b26e192191767d7721d3be94ca2952f1b91b9c32d371e9e87f230e9a3f04 | Python | 12,970 | 367 | from fanc.general import FileGroup
from abc import abstractmethod
import tables as t
from collections import defaultdict
from future.utils import string_types
import inspect
def _get_pytables_data_type(value):
"""
Convert a value or class to a PyTables data type.
:param value: Primitive value
:return:... |
d1b2aef9e1a671a6619d88639d81c17c88beaf3355d68833674ae0858bdbc902 | Python | 12,971 | 344 | """
TULIP: TUmor CLassIfication Predictor
This tool predicts the primary tumor type (17 or 32 types) based on RNA-seq data.
Authors: Satish RG, Sara Jones
"""
from __future__ import print_function
import os, warnings
warnings.simplefilter(action="ignore", category=FutureWarning)
os.environ["TF_CPP_MIN_LOG_LEVEL"] =... |
701761e23b4dd5d03f59c06fc6e8995630d43fe9517a7cfdbc1da2822b6d1290 | Python | 12,983 | 313 | #!/usr/bin/env python
#
# Copyright M4Depth authors 2021. All rights reserved.
# ==============================================================================
import tensorflow as tf
from utils import dense_image_warp
def wrap_feature_block(feature_block, opt_flow):
with tf.compat.v1.name_scope("wrap_feature_blo... |
45700f3de735fc0f089337d50a6fdcd597ec28354b964570bd4f8354d2d64b00 | Python | 12,984 | 275 | import math
import unittest as ut
# noinspection SpellCheckingInspection
from pysbm import test_ground as sbmt
from sklearn.metrics.cluster import adjusted_mutual_info_score
class TestSimplePartition(ut.TestCase):
"""Test SimplePartition"""
def setUp(self):
"""Prepare some simple partitions"""
... |
e14a51e4f9f41d1671cc580ef4e6eb7bc96ad0743d37b7cfa0554ef1917eaab2 | Python | 12,984 | 278 | # 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... |
ba9c614f62eb1046ee29c534cf81d41fdd07ede0c59545ae1b240e6595bb1d5a | Python | 12,992 | 346 | from .helpers import dimensions, origin
import numpy as np
from scipy import ndimage
from time import sleep
from sklearn.neighbors import KDTree
from .functions import get_distances
class VoxelCloud:
def __init__(self, bounds, voxels, grid_size, map, occupancies=None):
from rtree import index
sel... |
af1faed5a42e4cb98b90bc88dc959c54e4fdde7312a919a14425079f7b0563c4 | Python | 12,997 | 436 | import pytest
import numpy as np
import warnings
from .. import iterative_wiener_deconv
# ============================================================================
# BACKWARD COMPATIBILITY TESTS
# ============================================================================
def test_rsHRF_iterative_wiener_deconv()... |
1959ec14f78f4699610d2f19fb01d950cece56cb012fcde5a465581e7a24f554 | Python | 13,014 | 349 | # 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 Iterable
from datetime import datetime, timedelta
from typing import Any
import pandas as pd
fro... |
aa6aec8bc3ec3d6604e0ba56dbcb3299ec12c51d495a114bb54bd33c5e44a7c6 | Python | 13,018 | 304 | """
ISA datatype
See https://github.com/ISA-tools
"""
import json
import logging
import os
import os.path
import re
import shutil
import tempfile
from typing import (
Optional,
TYPE_CHECKING,
)
logger = logging.getLogger(__name__)
# Imports isatab after turning off warnings inside logger settings to avoid p... |
5211c8c4c5a9c84385bd3b567a6094b661dbb68214466329e5c0811480c2fc0e | Python | 13,031 | 341 | import pathlib
import subprocess
from concurrent.futures import ProcessPoolExecutor, as_completed
import cooler
import numpy as np
import pandas as pd
import pyBigWig
def _activity_score_atac_mcg(all_values):
activity_score = all_values["ATAC"] * (1 - all_values["mCG"])
return activity_score
def _scan_sing... |
b52264a787793f38d14b2931786c081ce8d97c6dccecf1f4cd1d2e14d5075612 | Python | 13,032 | 379 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
GraphVisualization
==================
Module providing tools to create meshes and visualize graphs.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE)'
__copyright__ = 'Copyright © ... |
dcc997d1f73d9174862231ef0d3451e77eb325b517a94492b9baa300dbe2605b | Python | 13,032 | 290 | import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import scipy
import seaborn as sns
from similarity_measures import dissimilarity_euclidean, dissimilarity_pearson
os.makedirs('results/python_plot/RDMs_per_child', exist_ok = True)
# sorted by category
classes = ['class-F', 'class-F', ... |
c13d52b4e9015ccf97293ab74c543a90f620e714d27e7357b25e1e762feec09b | Python | 13,038 | 329 | """Run with python -m benchmark.benchmark_tempotron, in three fresh processes."""
import argparse
import hashlib
import importlib.util
import json
import os
import platform
import resource
import statistics
import subprocess
import time
from pathlib import Path
import torch
from spikingjelly._ops import tempotron as... |
e42204f9d842487117a3367906dcacddaa5914d27e31c111cb38942f7cf404bb | Python | 13,043 | 327 | #!/usr/bin/env python3
import os
import numpy as np
from matplotlib.pyplot import get_cmap
from param_stamp import get_param_stamp_from_args
from visual import visual_plt as my_plt
import main
from param_values import check_for_errors,set_default_values
import options
import utils
## Parameter-values to compare
lamda... |
8cfe507bd5494372ff2be15fad90cc86edea8626333870c83943d3c31a694702 | Python | 13,055 | 340 | import pathlib
import numpy as np
from scipy import sparse
import pandas as pd
from sklearn.preprocessing import normalize
from sklearn.utils.extmath import safe_sparse_dot
from nilearn import image
from neuroquery.img_utils import get_masker
from neuroquery import tokenization, smoothed_regression, ridge
_MAX_SIMIL... |
662b17b77b539a807e1602b4731e12070819c7bd407c96b43169533785e125d9 | Python | 13,056 | 331 | import os
import tempfile
import feather
import numpy as np
import pandas as pd
import pytest
from alpineer import misc_utils
import ark.phenotyping.cell_cluster_utils as cell_cluster_utils
import ark.phenotyping.cell_som_clustering as cell_som_clustering
import ark.phenotyping.cluster_helpers as cluster_helpers
par... |
7d228bfba77639a53fabe957325d646c662d8b7919a9ecbd0a87a3a4303fc5cf | Python | 13,061 | 436 | # -*- coding: utf-8 -*-
"""
Statistics
==========
Create some statistics to test significant changes in voxelized and labeled
data.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE.txt)'
__copyright__ = 'Copyright © 2020 by Christo... |
b5bb14f23f41fd9aaac1c7af826942d35a093abd92bd4247fcd2dddcd2ad9b1d | Python | 13,063 | 371 | # 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... |
960a88ee9bf1c738184ec75f7a8b944ec93c1312f6af3493c098cebb7dc3ef8e | Python | 13,064 | 326 | #!/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
from collections import defaultdict
from logging import Logger
fro... |
93378111f29c924ea8d6b9b7a5106f5a61f37abbb1d7d230a312472f754d3391 | Python | 13,066 | 371 | import abc
import logging
import re
from typing import Optional
import yaml
from pydantic import (
BaseModel,
field_validator,
)
from galaxy.config import GalaxyAppConfiguration
from galaxy.exceptions import ConfigDoesNotAllowException
log = logging.getLogger(__name__)
class UrlHeadersConfigurationExceptio... |
a3d727ffc1b3027d0d1ce042cfcebb06ad56cc936d18b3ef7ba645df61ca623d | Python | 13,082 | 350 | """
Copyright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Marius Pachitariu.
"""
import sys, os, argparse
from tifffile import imread, imsave
import numpy as np
from matplotlib import pyplot as plt
from glob import glob
from cellpose import models
from cellpose.io import logger_setup
from c... |
63baa280bc50c0526a0a52620ab2961a470e1c3e3aed6d1be82e6005bd2b1548 | Python | 13,085 | 354 | import pytest
import networkx as nx
class TestSubsetBetweennessCentrality:
def test_K5(self):
"""Betweenness Centrality Subset: K5"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality_subset(
G, sources=[0], targets=[1, 3], weight=None
)
b_answer = {0: 0.0... |
9aa4db5d2f7636f640098c8ea4069e19fb7cff6e1a7e8285e1447b87673072b8 | Python | 13,088 | 370 | import time
import copy
import itertools
import os
import inspect
from collections import defaultdict, namedtuple
import warnings
import torch
import torch.nn as nn
import torch.multiprocessing as mp
import optuna
from tabulate import tabulate
from cogdl.utils import set_random_seed, tabulate_results, build_model_pat... |
3a60ebcdbcc164c9ab12764955480a2dbaf641e0fea3aff8d0a94d91a6dc4b76 | Python | 13,092 | 276 | """Build the split and scaled training, validation and testing data.
Functions
---------
get_members(settings)
get_observations(directory, settings)
get_cmip_data(directory, rng, settings)
get_labels(da, settings, plot=False)
preprocess_data(da, MEMBERS, settings)
make_data_split(da, data, f_labels, f_years, labels, y... |
f65b448098bb49d4a0779de8fd7116c11cd7d60302a773b1e2ad7cc5a141da98 | Python | 13,094 | 281 | #!/usr/bin/env python
#
# Copyright (c) 2014 10X Genomics, Inc. All rights reserved.
#
# Functions for preflight checks
#
import os
import re
import resource
import socket
import subprocess
import tenkit.constants as tk_constants
import tenkit.seq as tk_seq
import tenkit.reference
import martian
def is_int(s):
tr... |
b691b2d67a9a40dd478dd540c03d8286a77d8c3885d1267f8f95a8a0c575ab90 | Python | 13,095 | 328 | #!/usr/bin/env python3
import os
import numpy as np
from matplotlib.pyplot import get_cmap
# -custom-written code
import main
import utils
from params.param_stamp import get_param_stamp_from_args
from params.param_values import check_for_errors,set_default_values
from params import options
from visual import visual_plt... |
2c1f646f296f13036e9698392cde8ba7e1743e01821606f0f27973e19cdeaa8f | Python | 13,113 | 338 | import os
import json
import numpy as np
import copy
import torch
import random
from tqdm import tqdm
import scipy.sparse as sp
from utils import UnionFindSet, get_bfs_sub_graph, get_dfs_sub_graph
from torch_geometric.data import Data, Dataset, InMemoryDataset, DataLoader
class GNN_DATA:
def __init__(self, ppi_p... |
219f406c94db9020ef99e0ba5d2ca15f6ba3055ff55c443f7b23385323b4a14a | Python | 13,120 | 412 | """Fast approximation for node connectivity"""
import itertools
from operator import itemgetter
import networkx as nx
__all__ = [
"local_node_connectivity",
"node_connectivity",
"all_pairs_node_connectivity",
]
@nx._dispatchable(name="approximate_local_node_connectivity")
def local_node_connectivity(G,... |
acc6da42295a39623917c5989aeeb81353d7e86eb06bfb5187cdbf437a933439 | Python | 13,120 | 365 | # -*- coding: utf-8 -*-
"""
Collection of routines to detect maxima
Used for finding cells or intensity peaks.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
import numpy
#from scipy.ndimage import maximum_filter
... |
1cfd910a464684bf13f2c3270895169e1c9887afa183a2449fc4bdbb9f0d05d1 | Python | 13,124 | 442 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Graph analysis module
---------------------
Module provides basic Graph classes.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE)'
__copyright__ = 'Copyright © 2020 by Christoph K... |
21976e75f11867cf083eaad4041563af430f7938c466b003ad0f1787a4f1fe0e | Python | 13,124 | 399 | """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 glob
import importlib
import io
import ipaddress
import itertools
import os
import shutil
import socket
import sys
from contextlib import co... |
e619c4b3cbb5bc26db6a99e8f5d852d5aa24cc068a039d284ecd5f6069f13079 | Python | 13,125 | 284 | """
Created on Oct 21, 2022.
@author: voodoocode
"""
import nibabel.freesurfer
import numpy as np
import scipy.spatial
import finnpy.src_rec.utils # @UnresolvedImport
class Cort_mdl():
"""
Container populated with the following cortical surface (MRI) based items.
Parameters
----------
lh_... |
7fe6a140dbd62809269c59ce030c5d0a7bd24383b2aa411b6d9af6497cf964d0 | Python | 13,127 | 413 | import pytest
from ...datalog.expressions import Fact
from nl_expr.exceptions import (
ForbiddenRecursivityError,
UnsupportedProgramError,
)
from nl_expr.expressions import Constant, Symbol
from nl_expr.logic import TRUE, Conjunction, Implication, Union
from ..cplogic.program import CPLogicProgram
from ..expre... |
28226a6623522af74769384a29f43706b6319ef2815f4f40f2c85a8590072b05 | Python | 13,131 | 405 | from pathlib import Path
import h5py
import numpy as np
import pytest
import torch
from torch.utils.data import DataLoader
from spikingjelly.datasets import base
from spikingjelly.datasets.es_imagenet import (
ESImageNetFrameFixedNumberBuilder,
)
from spikingjelly.datasets.shd import (
SHDFrameCustomIntegrate... |
8c69dedfc00fc3f0ad2e5da0b50becd3fe73296d7bdc62081bc34f309b07b527 | Python | 13,140 | 371 | import torch
import torchvision as tv
import torchvision.transforms as transforms
import torch.nn as nn
import numpy as np
import pandas as pd
from torch.utils.data import DataLoader
import os.path as op
from os.path import join as opj
import sys
import os
import matplotlib.pyplot as plt
from torch.utils.tensorboard i... |
b7454a88cbe07755587137497b81ffebf55878207a3cc0f09ea66b13af45607d | Python | 13,142 | 381 | """Generate and work with PEP 425 Compatibility Tags."""
from __future__ import absolute_import
import distutils.util
import logging
import platform
import re
import sys
import sysconfig
import warnings
from collections import OrderedDict
import pip._internal.utils.glibc
from pip._internal.utils.compat import get_ext... |
f3210add5a71e1429b0acf404fb874356fb589d66210a61f1dbbbb2dea24615f | Python | 13,145 | 410 | # ----------------------------------------------------------------------------
# build_voxel_matrix.py
# Author: Antoine Beauchamp
# Created: June 19th, 2020
"""
Build a gene-by-voxel expression matrix
Description
-----------
This script imports in-situ hybridization (ISH) MINC images from the
Allen Mouse Brain Atla... |
87389208b0c8548a1358f579e9f103e60235a44ace7722ce43767f13f373f40b | Python | 13,150 | 468 | """
Operations on graphs including union, intersection, difference.
"""
import networkx as nx
__all__ = [
"union",
"compose",
"disjoint_union",
"intersection",
"difference",
"symmetric_difference",
"full_join",
]
_G_H = {"G": 0, "H": 1}
@nx._dispatchable(graphs=_G_H, preserve_all_attrs=T... |
e00d87854e13d8de206c8475b6672e7cf9c27c9b59b785516f000de12e0f1891 | Python | 13,157 | 378 | from typing import Optional
import torch
from .. import functional, surrogate
from .base_node import BaseNode
__all__ = ["AdaptBaseNode", "IzhikevichNode"]
class AdaptBaseNode(BaseNode):
def __init__(
self,
v_threshold: float = 1.0,
v_reset: Optional[float] = 0.0,
v_rest: float... |
ad89863b0bde737eff30b83b613897c24951b3e86f17c66a7de6a67e14d1e109 | Python | 13,159 | 330 | from tensorflow.keras.models import load_model
import getopt
import sys
from scipy.stats import pearsonr, spearmanr
from utils import get_input_size, make_prediction, set_data_size, one_hot_enc
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.linear_model import LinearRegression
impor... |
a00798e9d193d55ef1a2c82a4f5050885ebbe266cd50018d730d5bbb218e706b | Python | 13,169 | 375 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 11:35:36 2019
@author: aaussel
"""
from cells.RE_mdPul import *
from cells.TC_mdPul import *
#from cells.HTC_mdPul import *
from cells.HTC_buffer_mdPul_Destxhe_tests import *
from scipy import signal
prefs.codegen.target = 'numpy'
defaultclock.dt = 0.01*ms
runtime... |
e2aa810ccf366ee7e1aaa11dd1bfbdf6c39bcfde579845445c3562e6203209e1 | Python | 13,172 | 381 | from __future__ import absolute_import
import errno
import warnings
import hmac
import socket
from binascii import hexlify, unhexlify
from hashlib import md5, sha1, sha256
from ..exceptions import SSLError, InsecurePlatformWarning, SNIMissingWarning
from ..packages import six
SSLContext = None
HAS_SNI = False
IS_PY... |
58d1b4ed16a05c50cb70f406d4eb4b9bef5b9369618f6658b519af1fecb3649d | Python | 13,179 | 333 | # 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... |
23babe2f69ae61cb8ee96ac7620f8b3deae88be97b7c6986ab832135aa3345cb | Python | 13,181 | 251 | # -*- coding: utf-8 -*-
"""
Generate docs/_generated/usecase_table.html — a searchable, filterable table of every
published SimBA use-case, built from the same public Google Sheet as the use-case map.
The rows are embedded as JSON and rendered client-side (plain JS, no libraries), so the
page works offline once built.... |
1ba007740dccb73758ef06ad1465f305a191c550418cca660d191f9fe63322c1 | Python | 13,188 | 393 | import unittest
import _shared
import patch.objects
from patch import is_density_mechanism, is_point_process, p
from patch.exceptions import HocRecordError
class TestPatchRegistration(_shared.NeuronTestCase):
"""
Check that the registration of PythonHocObjects works. (Will almost never be relevan... |
95a8776c4743153aaef21c53da675e0d9eb1f8b576ed4bb7019368225d335f2a | Python | 13,202 | 313 | """
Created on Oct 17, 2022.
@author: voodoocode
"""
import numpy as np
import pickle
import warnings
import sklearn.covariance
import sklearn.decomposition
import finnpy.src_rec.utils # @UnresolvedImport
def _empirically_estimate_cov(cov_data, epoch_splits, signal_type, valid_ch_indices, ch_types = None):
"""... |
05e85153a4909d6ccab00168b21acddafa7170f0722c0562a1f19eab7f2fdb71 | Python | 13,203 | 407 | import numbers
import pytest
import networkx as nx
from ..generators import (
alternating_havel_hakimi_graph,
complete_bipartite_graph,
configuration_model,
gnmk_random_graph,
havel_hakimi_graph,
preferential_attachment_graph,
random_graph,
reverse_havel_hakimi_graph,
)
"""
Generator... |
d57bdfe937f71d152e49c1f444424c05b8fbcdf4a5d123e37d1097b07c5e2aae | Python | 13,209 | 276 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@title: PlateSheet class
@description: class for loading "_platesheet.csv" files
@author: chrisarcadia
@created: 2018/05/31
"""
import os, csv, copy, datetime
# class for handling Plate Sheet (_platesheet.csv) files
class PlateSheet(object):
def __init__(s... |
898782b65490d5bd9990b8fcbfec229c1e01541884795eee0936e9186bd1af48 | Python | 13,214 | 239 | import logging
import os
import shutil
from sqlalchemy import and_
from galaxy import util
log = logging.getLogger(__name__)
def get_tool_dependency(app, id):
"""Get a tool_dependency from the database via id"""
return app.install_model.context.query(app.install_model.ToolDependency).get(app.security.decod... |
d3cfc312522bbbb85f61eb231c34d4dc19e087c964cd32329d6b5e682b51d218 | Python | 13,215 | 316 | # 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... |
16e7a726cc2f2bd07facd2f8821397d8f7e54caabc196019fad9eebe4e87d868 | Python | 13,217 | 313 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Twokenize -- a tokenizer designed for Twitter text in English and some other European languages.
This tokenizer code has gone through a long history:
(1) Brendan O'Connor wrote original version in Python, http://github.com/brendano/tweetmotif
TweetMotif: Explor... |
dbddabad4b2c8876123f1b05f1154f8343d0964f93b72fed92ee395feca51480 | Python | 13,222 | 376 | import logging
import os
from collections.abc import Iterable
from typing import (
cast,
NamedTuple,
NewType,
NoReturn,
Optional,
)
import alembic
from alembic import command
from sqlalchemy import (
create_engine,
MetaData,
)
from sqlalchemy.engine import Engine
from sqlalchemy.exc import ... |
1e3e3a0c43f0221e5106c2ea8807e65e679617853824dcf4805919dcf4d84914 | Python | 13,224 | 365 | """
Manager and Serializer for HDCAs.
HistoryDatasetCollectionAssociations (HDCAs) are datasets contained or created in a
history.
"""
import logging
from typing import Optional
from galaxy import model
from galaxy.exceptions import RequestParameterInvalidException
from galaxy.managers import (
annotatable,
... |
52c41bb3da233619d44779415bec97621889638acb7ad76665144f89992e8b80 | Python | 13,229 | 326 | # NICE
# Copyright (C) 2017 - Authors of NICE
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program ... |
12f697649972363be3758e66ba9a434ee617c5291bb672047f3f0d735cffcb01 | Python | 13,235 | 340 | import base64
import fnmatch
import json
import logging
import re
from datetime import timedelta
from enum import Enum
from functools import lru_cache
from json import JSONDecodeError
from typing import Optional, Union
from urllib.parse import urlparse
import google.auth
import google.cloud.storage as gcs
from core.ut... |
5f005aa171edb96951dbaaef828e97caba258a6a71f13007b0aa3d98ba7efe6f | Python | 13,239 | 367 | import torch
import torch.nn as nn
from spikingjelly.activation_based import neuron, op_counter
class ToyCLIFNode(neuron.BaseNode):
def __init__(self):
super().__init__(v_threshold=1.0, v_reset=None, step_mode="s")
self.register_memory("m", 0.0)
def neuronal_charge(self, x: torch.Tensor):
... |
4fb8d8e46eadc3ee86fefbe6b3f4d2b156a86e310c0e898868c80d387085769f | Python | 13,243 | 365 | # -*- coding: utf-8 -*-
"""
Collection of routines to detect maxima
Used for finding cells or intensity peaks.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
import numpy
#from scipy.ndimage import maximum_filter
... |
ff720647c46a5aef1544f47fd18507dde033a30bf9218a80bddc50a35795a8cf | Python | 13,243 | 368 | """Fast approximation for k-component structure"""
import itertools
from collections import defaultdict
from collections.abc import Mapping
from functools import cached_property
import networkx as nx
from networkx.algorithms.approximation import local_node_connectivity
from networkx.utils import not_implemented_for
... |
73e0a0919dbac1f3356583857d64c82f795df7dca309c13d01a29f6129dd0ba6 | Python | 13,248 | 330 | import os
import numpy as np
import pandas as pd
from alpineer import io_utils, misc_utils
from ark.phenotyping import cell_cluster_utils, cluster_helpers
def cell_consensus_cluster(base_dir, cell_som_cluster_cols, cell_som_input_data,
cell_som_expr_col_avg_name, max_k=20, cap=3, seed=42,... |
69f7091ad5035256330a37b87f151f24311119de7263da900d95bb1a6357085d | Python | 13,251 | 279 | """
Managers, serializers for Galaxy config file data. ConfigSerializer for all users
and a more expanded set of data for admin in AdminConfigSerializer.
Used by both the API and bootstrapped data.
"""
import logging
import sys
from typing import (
Any,
)
from galaxy.managers import base
from galaxy.managers.con... |
e43822f0f8cc649cff52e9f64972f96ba9b1b407dd6e6de43c875b8334935e03 | Python | 13,251 | 435 | """Views of core data structures such as nested Mappings (e.g. dict-of-dicts).
These ``Views`` often restrict element access, with either the entire view or
layers of nested mappings being read-only.
"""
from collections.abc import Mapping
__all__ = [
"AtlasView",
"AdjacencyView",
"MultiAdjacencyView",
... |
fdf5669fdec509111033e6597fe03ce44eb5c5f5e6d0fda444dcf35dc3c34152 | Python | 13,251 | 331 |
### Generate decorations and compute the reward for each one
import argparse
import logging
import os
import sys
from tqdm.auto import tqdm
import random
import json
import gzip
import pathlib
import numpy as np
import pandas as pd
import tensorflow as tf
import tensorflow_addons as tfa
from nfp import custom_objects... |
f1dd5e60afd1a24f66c1a9dce9cf49bb5eed9867f7572fd91017fd815a3ae866 | Python | 13,263 | 345 | import copy
import importlib.util
import pytest
import torch
import torch.nn as nn
from spikingjelly.activation_based import base, layer
from spikingjelly.activation_based import neuron
from spikingjelly.activation_based.functional.net_config import detach_net, reset_net
from spikingjelly.activation_based.learning.on... |
a2204e249db06ac63cf25ecb67833e0a46df33068bd422742ca9ea21685a42cc | Python | 13,274 | 319 | import math
import random
from copy import deepcopy
import torch
from torch import nn
USE_CUDA = torch.cuda.is_available()
MAX_OUTPUT_LENGTH = 46
class Beam: # the class save the beam node
def __init__(self, score, input_var, hidden, feed_hidden, all_output):
self.score = score
se... |
e0fd0d2eaec677d44f3d7848febc7447085393f2445b2a41b6c63c5ea919c717 | Python | 13,278 | 335 | import math, numpy as np, random
from .morphologies import Compartment
def depth_first_branches(adjacency_list, node=0, return_visited=False):
branches = []
visited = set([])
def dfs_branch(branch, node):
# Grow the branch with current node.
branch.append(node)
# Mark this node as... |
bff92ab33dbcd73e2fdd6b4fc9e4898283c215544eca5ee76f6f1c87fcad7df3 | Python | 13,279 | 285 | # -*- coding: utf-8 -*-
"""
Example script to set up the parameters for the image processing pipeline
"""
######################### Import modules
import os, numpy, math
import ClearMap.Settings as settings
import ClearMap.IO as io
from ClearMap.Alignment.Resampling import resampleData;
from ClearMap.Alignment.Elas... |
54f5bfdf3c016b5c648f9e4a46f3434fda7b8ab46a727a22d10052d0ae1c33bb | Python | 13,287 | 332 | import argparse
import shutil
import os
from collections import defaultdict
import os.path as op
import tempfile
import subprocess
import numpy as np
import nibabel as nb
import pandas as pd
from tqdm import tqdm
import h5py
def find_mrconvert():
program = 'mrconvert'
def is_exe(fpath):
return op.exis... |
21b622bd838a4b1a34c402bd2c72fff4a81bf7213d8016404454d0a678619d08 | Python | 13,291 | 297 | """
OBJECTIVES:
Analyze microtubule (MT) spread from kymographs
with maximum intensity projections.
There are two different measures:
1) Length in the neurite in um over which 90/95% of the
MT intensity is spread out.
2) The percentage of MT spread retrograde and anterograde.
Steps:
1) Get background v... |
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