sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
64c6e63af18e92fec71c8efc804aaf6c9dd29a875981af971d2f56ec30b479c5 | Python | 8,590 | 262 | import itertools
import math
import numpy
import pandas
import pytest
import scipy.spatial
from ..euclidean_join import (
euclidean_distance,
euclidean_join,
euclidean_pairs,
)
def _brute_force(first, second, radius, strict):
result = set()
for p, q in itertools.product(map(tuple, first), map(tu... |
6355adb425d8ab32857280e86c9cdaf62845a4efb636d789b23dab519dedddce | Python | 8,594 | 232 | from datetime import timedelta
from urllib.parse import urlencode
from django.test import override_settings
from django.utils import timezone
from django.utils.dateparse import parse_datetime
from organizations.tests.factories import OrganizationFactory
from projects.tests.factories import ProjectFactory
from rest_fra... |
5561afc919251257ac77cf8c10efe63711932c4961cd66bba70db9bacb897eec | Python | 8,597 | 220 | """Galaxy file source plugin for Aspera ascp transfers.
This plugin provides download-only functionality using the Aspera ascp command-line tool.
It is designed as a configured plugin (not stock) requiring explicit configuration with
embedded SSH keys.
Architecture:
- ascp.py (this file): Galaxy plugin configuration ... |
856f0bba722cafbfd7cc667d13aca835c28c29d8b0e0f850e79b332be1d91700 | Python | 8,600 | 243 | import logging
import random
import numpy as np
from gunpowder.nodes.batch_filter import BatchFilter
from gunpowder.coordinate import Coordinate
logger = logging.getLogger(__name__)
class SimpleAugment(BatchFilter):
'''Randomly mirror and transpose all :class:`Arrays<Array>` and
:class:`Graph` in a batch.
... |
58185cf290772ebbcddce30ae5569496d3a6629a9850306bf39d40f72977bdb1 | Python | 8,603 | 225 | #!/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 plotly.graph_objs as go
from ... |
6108cbc6c667c7bfc25f6b09de7374714889cc2ee9e9487214deae7dba31e46d | Python | 8,621 | 285 | import pytest
import networkx as nx
def test_tikz_attributes():
G = nx.path_graph(4, create_using=nx.DiGraph)
pos = {n: (n, n) for n in G}
G.add_edge(0, 0)
G.edges[(0, 0)]["label"] = "Loop"
G.edges[(0, 0)]["label_options"] = "midway"
G.nodes[0]["style"] = "blue"
G.nodes[1]["style"] = "l... |
1a705ae4b984c5df70b15e47c75814dfc8a06885d47f33c913e1aa9989d5bd05 | Python | 8,623 | 214 | #!/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
import numpy as np
from ax.adapter.base import DataLoaderConfig
from ax.ada... |
b7cb80b136d0c871aa25466a58be5de20ff2195f77e2f708608f6ab619348fe0 | Python | 8,623 | 230 | # 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... |
4a8f9c9a34c91cecb2d5c76a54da1bed4759a379d7fb11c84d73c1ea8b5749ee | Python | 8,625 | 246 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
| Title:
part 3 of the preprocessing
| Date:
2021-02-01
| Author(s):
Theodor Rumetshofer
| Description:
This is doing the second part of the preprocessing for the Leiden and Lund
cohort. Subjects from the Leiden cohort w... |
7fc05270a022221a2b786cf6c30774cd18a3d45d8b8422ecf427b128f1d5dd84 | Python | 8,626 | 208 | #!/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 ax.adapter.base import Adapter, DataLoaderConfig
from ax.adapter.data_utils import extract_experi... |
e6b6400464e4f7c7dea8708b5717182b48568be1a6983710cd1f1c2935571e3d | Python | 8,629 | 238 | from brian2.synapses.synapses import SynapticPathway
from brian2.core.functions import Function
from brian2.core.variables import ArrayVariable
import numpy as np
from brian2lava.utils.utils import mode_dependent
@mode_dependent
def code_object(
self,
owner,
name,
abstract_code,
... |
1c2e0efa2b326c0885a357459039f5b04846711b72cd6569ddc965f4094c9d44 | Python | 8,635 | 232 | import unittest
import numpy as np
from bsb_test import (
NetworkFixture,
NumpyTestCase,
RandomStorageFixture,
get_test_config,
)
from bsb import Configuration, InputError, RedoError
class TestSingleTypeCompilation(
RandomStorageFixture, NetworkFixture, unittest.TestCase, engine_name="hdf5"
):
... |
1c6620ac2605dd00558a5208df0bbe94b21f788837b5b5ac89985c6aac029c3f | Python | 8,635 | 222 | import os
import numpy as np
import pandas as pd
from glob import glob
from nilearn.image import *
from nilearn.plotting import plot_stat_map, plot_glass_brain, find_cut_slices
from nistats.second_level_model import SecondLevelModel
from nistats.thresholding import map_threshold
from scipy.ndimage import binary_erosion... |
d84a790667b3e9fd4ada9b60afb7c21a0475fc809611420de510a5e96632ec9c | Python | 8,635 | 222 | import os
import numpy as np
import pandas as pd
from glob import glob
from nilearn.image import *
from nilearn.plotting import plot_stat_map, plot_glass_brain, find_cut_slices
from nistats.second_level_model import SecondLevelModel
from nistats.thresholding import map_threshold
from scipy.ndimage import binary_erosion... |
61cf1c9d48213d3d902459a74a2d9493017baa5f6ead048ffe6bec8079ab32ee | Python | 8,638 | 209 |
import argparse
import os
import dgl
import numpy as np
import torch
import torch.nn.functional as F
from dgl.data import register_data_args
from pytorch_lightning.metrics.classification import Accuracy
from pytorch_lightning.metrics.functional import auroc
from reactome_model import *
from reactome_pro... |
41ead599fadae6407c77ae3b4a3dc19c346a9de8e8e3b1ccf35eff78f7ca00a1 | Python | 8,642 | 191 | #!/usr/bin/env python
#######################################################################
#######################################################################
## Created on April 4th 2019 to check nf-core/chipseq design file
#######################################################################
###############... |
155d412847c31081b7177d9a0d4b6a3cd6066a0ba849a9f35311d3bda64c8a1d | Python | 8,643 | 218 | # MIT License
#
# Copyright (c) 2019 Lucas K Wagner
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merg... |
9e7cbbb79835950595375293e05e342b8a706b709db29effeb4bb03826a22aae | Python | 8,645 | 239 | import matplotlib.pyplot as plt # To plot
from scipy.optimize import curve_fit
from pylab import *
import numpy as np
import random
import math
import time
import os
import glob
def rmsd(x,y):
Nx = len(x)
Ny = len(y)
if Nx!=Ny:
print('WARNING! Nx!=Ny. Could not cal... |
7f2b23891d3b809c69442784d75092d2391bfcdbb7417d0c5ab67f888a655478 | Python | 8,648 | 210 | # 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 ax.analysis.best_trials import BestTrials
from ax.api.client import Client
from ax.api.configs import RangeParameterConf... |
8fc4f4ad8d9f89f10ac2d49a4602a5984664ec721836b0c734dcf5779eb6980a | Python | 8,649 | 260 | # 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... |
fa7c70e17172ba9c00b859771ca50343fafce01233a22be7bac75d228bced090 | Python | 8,650 | 267 | import pandas as pd
import numpy as np
from tqdm.auto import tqdm
from pathlib import Path
import os,json
from dataclasses import dataclass,field
from typing import Optional
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
AutoConfig,
HfArgumentParser,
TrainingArguments,
MODEL_FOR... |
3af5c1c2c9ea75d9391fd28b993a709dcf9c0af44d88b96843bdffa89779d75f | Python | 8,652 | 225 | from nipype.interfaces import afni as afni
import os
import glob
import click
from .job_manager import BatchManager, Job
from .config_json_parser import ClpipeConfigParser
import logging
import sys
from .error_handler import exception_handler
from nipype import MapNode, Node, Workflow
import nipype.utils
import pandas ... |
d7c090c319a7d2b02e39333202fd483c976135eb9de6dc18080658ebc7853afb | Python | 8,653 | 225 | from nipype.interfaces import afni as afni
import os
import glob
import click
from .job_manager import BatchManager, Job
from .config_json_parser import ClpipeConfigParser
import logging
import sys
from .error_handler import exception_handler
from nipype import MapNode, Node, Workflow
import nipype.utils
import pandas ... |
9b5ac22fa91460cf8eddeacee9b1a06a2133a703f4c24d25f8d42f7f8a3ebe93 | Python | 8,656 | 174 | import datetime
# Usage: rename this file to experiment_config.py,
# adjust according to your needs,
# and run the experiments with `python run.py --config_file experiment_config.py`
##### variable parameters #####
# variables that define the experiments
# network or data parameters can be varied
# one experiment wil... |
5c77790f1051d22697dbe68678000f1b0a6d1e206e90c91961587b5d8b8bfd74 | Python | 8,657 | 258 | """Benchmarks for a certain set of algorithms"""
import random
import networkx as nx
from benchmarks.utils import (
benchmark_name_from_func_call,
fetch_drug_interaction_network,
weighted_graph,
)
from networkx.algorithms import community
class UndirectedAlgorithmBenchmarks:
timeout = 120
nodes ... |
f04f7bcb17c667b1f03548e3a0d318ac9f9b270a8a8dc88478237274424e4b23 | Python | 8,657 | 286 | # -*- coding: utf-8 -*-
"""Docking_GD_Parallel.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1P4GssDPNRBrGwGPIuuTlIdHmC0J2TjxJ
"""
import os
import sys
if len(sys.argv) != 7:
print('Wrong input parameters\n\n')
print(len(... |
51248b36078ea4049b54b80c91777514dc8c6588fe9c86de21bff38648b4a199 | Python | 8,662 | 284 | from pathlib import Path
from typing import AbstractSet, Tuple
from unittest.mock import patch
import numpy as np
import pandas as pd
import pytest
from .. import NeurolangDL
from ..neurosynth_utils import StudyID, get_ns_term_study_associations
@pytest.fixture
def metadata():
return pd.DataFrame(
[
... |
8eea96bf29aec1e75969496ec46bd3a1c3ec831286c2c5a2ea8c5322ce7af9ee | Python | 8,662 | 177 | import natsort
import numpy as np
import mdtraj
from pathlib import Path
import argparse
import os
import concurrent.futures
from tqdm import tqdm
import csv
def quickly_list_pdb_files(path):
file_list = []
with os.scandir(path) as entries:
for entry in entries:
if entry.is_file() and entr... |
20b4601527d431b510f0f1b733e1e0950cce559957a5fe58b745177bf617009e | Python | 8,663 | 242 | """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 hashlib
import logging
import os
import shutil
from copy import deepcopy
from datetime import datetime
import ujson as json
from core.utils... |
2a3a5a12f6b27aee92a8231e9eff1068c53adba598906d1abd55c935a88124cf | Python | 8,670 | 204 | # 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... |
e29e9b4033db80f0ad56f9c95bb99df6f554430606ffa245a013ed575de50165 | Python | 8,672 | 306 | import operator
import typing
import pytest
from ....datalog.basic_representation import DatalogProgram
from ....datalog.expressions import Fact
from ....datalog.negation import DatalogProgramNegationMixin
from nl_expr.exceptions import (
ForbiddenDisjunctionError,
ForbiddenExpressionError,
ProtectedKeywo... |
b2385b48b7354bad37f91a5800193d00f5b89c424c42225ef4c5cdc85c6652c4 | Python | 8,673 | 234 | # 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... |
e859d8274599c1f34f26ff77f335e0015391d596d09b4a2b5d18754d3b580e41 | Python | 8,676 | 206 | import logging
import os
import random
import time
from abc import abstractmethod
from typing import List, Optional
import numpy as np
import sqlalchemy
from sqlalchemy import exc
from rlmolecule.alphazero.alphazero_vertex import AlphaZeroVertex
from rlmolecule.mcts.mcts_problem import MCTSProblem
from rlmolecule.sql... |
4d0c5e9ff0afed923e7a549af941403862a3060239f71e653cb703fcb9b4818c | Python | 8,677 | 222 | # #!/usr/bin/env python
# """
# Compare predictions with Neuroglancer using Dask for parallel data loading.
#
# This script loads prediction probability maps (and optional labels) from a Zarr container,
# adds them as layers (with a chosen shader) to a neuroglancer viewer, and sets up an
# interactive grid layout... |
b85592cde6552b869521136b1de364320f1f661d2eb1822c6aaae2174e8e9be6 | Python | 8,677 | 204 | #!/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.mock import MagicMock
import numpy as np
from ax.adapter.base... |
7b505f74b74c554fb626c5415e2a15447908e856ea2e2d2c6f32359eb1901267 | Python | 8,681 | 258 | from numpy import random
from ..interval_algebra import (
converse, meets, before, starts, during,
finishes, equals, overlaps, negate,
get_intervals_relations
)
from ..regions import Region
from copy import deepcopy
def app(x, z, first, second, elements):
elements.remove(x)
elements.remove(z)
... |
304e8bd0e8ccba34a1088c8c4b19922157edc5a9348818a875e531ec7b0f5d4d | Python | 8,688 | 219 | from meld_classifier.evaluation import Evaluator
from meld_classifier.experiment import Experiment, load_config
from meld_classifier.meld_cohort import MeldCohort
import argparse
import numpy as np
import json
import os
import importlib
import sys
import h5py
from meld_classifier.paths import EXPERIMENT_PATH
import sub... |
742fa434eb58bf309b6550c2ff5cb526660c6d4e2c19bf38d50c4b5de2cc6d9f | Python | 8,691 | 200 | # -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import tqdm
import os
from .native_api import NativeAPI
from .rcc import rcc, rcc3D
def dme_estimate(positions, framenum, crlb, framesperbin, imgshape,
coarseFramesPerBin=None,
coarseSigma=None,
perSpotC... |
cbeb1c52fbf94e32c7abb207697ea821ddd62607e37a3093d5d49c962d3521a7 | Python | 8,696 | 265 | import torch
import torch.nn as nn
import torch.nn.functional as F
from cogdl.utils.srgcn_utils import act_attention, act_map, act_normalization
from cogdl.utils import spmm, add_remaining_self_loops
from torch_sparse import spspmm
from .. import BaseModel
class NodeAdaptiveEncoder(nn.Module):
def __init__(self,... |
2463b0a8fd5a7f4eb3ea4ae96f93b1e4f040f6aafbc4c63cc2987ad83e9d52ab | Python | 8,701 | 224 | import os
import inspect
import importlib
import torch
import random
import numpy as np
import pandas as pd
import tensorflow as tf
import pathlib
import easypheno.model
def get_list_of_implemented_models() -> list:
"""
Create a list of all implemented models based on files existing in 'model' subdirectory o... |
9db64677e217eb44b5d510466e89543272f23932dfdb831616562cc946ea1fad | Python | 8,705 | 292 | import argparse
import os
import csv
import math
import matplotlib.pyplot as plt
RESULTS_FILE = "results.csv"
EPOCH_IDX = 0
LR_IDX = 1
EVAL_LOSS_IDX = 4
EVAL_ACC_IDX = 5
SPLITTER = '?'
# graph_results
def graph_results(input_dirs="./saved_models/results", output_dir=None, model_names=None, epoch_start... |
58bab65da4b394ec231bf893cebe8243fe8521b2a1908fe1967c5df172b31bbe | Python | 8,706 | 219 | """
General functions for training an experiment.
"""
import numpy as np
import torch
import torch.nn as nn
import time
import settings
import roblib
from models import BCSLayer, Memorynet, set_seed
from datasets import load_aux_patterns, load_traintest_patterns
import experiments
import os.path
import uti... |
386ea6a2a9ab3f5cea6ec73e1d25f2c7f977427faca120b3578b829592b4c820 | Python | 8,708 | 274 | from typing import Optional
from itertools import chain
from functools import partial
import torch
import torch.nn as nn
from .gin import GIN
from .gat import GAT
from .gcn import GCN
# from .dot_gat import DotGAT
from .loss_func import sce_loss
from graphmae.utils import create_norm, drop_edge
def setup_module(m_t... |
200f7552a41abf33553bd0b87abd4bd0af3b8a98a1726423647fbbfefef268bf | Python | 8,709 | 239 | import pathlib
import subprocess
from concurrent.futures import ProcessPoolExecutor, as_completed
import numpy as np
import pandas as pd
import xarray as xr
from Bio import SeqIO, motifs
from ..mcds import RegionDS
from ..mcds.utilities import write_ordered_chunks
def _get_motif_threshold(motif, method, threshold_v... |
781022c000d6260080232263805dfece7f3d54f2067ed896316c9c729167c8c5 | Python | 8,717 | 263 | import collections
import pickle
import pytest
import networkx as nx
from networkx.utils.configs import BackendPriorities, Config
# Define this at module level so we can test pickling
class ExampleConfig(Config):
"""Example configuration."""
x: int
y: str
def _on_setattr(self, key, value):
... |
13a373b93bdf68e88259652b6a4fd05034fe3d6b7c31570c47353f63816cd253 | Python | 8,718 | 280 | import numpy as np
import scipy.sparse as sp
import scipy.io as spio
import isolearn.io as isoio
from scipy.stats import pearsonr
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib as mpl
from matplotlib.text import TextPath
from matplotlib.patches impo... |
99074c5d7cbbec352375ffa1642ac09601795e0a0ab63e17c51101231bcdefbe | Python | 8,720 | 258 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Functions used to preprocess data and initialize things
Created on Wed May 19 09:56:01 2021
@author: townesf
"""
import numpy as np
from os import path
from math import ceil
from copy import deepcopy
from scipy import sparse
from contextlib import suppress
from scan... |
7261c9a9ca66320e3d54baa0493be6c85824e57e412988d0700d766d2f362c23 | Python | 8,722 | 269 | """ The objects to place in the grid.
Objects define all the regions in the grid with a modified update equation,
such as for example regions with anisotropic permittivity etc.
Available Objects:
- Object
- AnisotropicObject
"""
## Imports
# typing
from ..utils.global_constants import ETA_0
from .typing_ import ... |
2e627b33f898a9561f453b021a6972380b23391f6e0cfd207e0b3575a59c497d | Python | 8,723 | 278 | """ The original fdtd module supports several backends. In NIDN, however, we only support torch.
The ``cuda`` backends are only available for computers with a GPU.
"""
## Imports
# Numpy Backend
import numpy # numpy has to be present
from functools import wraps
# used only by test runner.
# default must be idx ... |
56ca6a9728744fc423f549f00155ecc25adcb3508e3c4fc7355bca5374f7e887 | Python | 8,723 | 212 | from collections import defaultdict
import pyBigWig
import pysam
from ._doc import *
from .utilities import parse_chrom_size, parse_mc_pattern
class ContextCounter:
def __init__(self, mc_contexts):
self.mc_counts = defaultdict(float) # key is context pattern like CHN, CGN
self.cov_counts = defa... |
7b3654b3e97c95a8d5264d644eabc359cc028e5eb82f3cafc58f81f5259b3170 | Python | 8,723 | 213 | #!/usr/bin/env python
# Identification of potential RNA G-quadruplexes by G4RNA screener.
# Copyright (C) 2018 Jean-Michel Garant
#
# 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 Foundatio... |
33f1d2eb5ec28da3f69fe10f597385e560820670801ddc498992a2262a3ac180 | Python | 8,724 | 203 | #!/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 dataclasses import dataclass
from typing import Any
from ax.adapter.registry import Generators
f... |
d9a8ad84b9c71bb2f02ce7f2bca050d74f9ec0986a2ebd58b0adfb7ced78182d | Python | 8,735 | 248 | # 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... |
172fe674d3aa1256c29c9076726e0263ff59d4f1bb5add98573d92b4c0d1a34d | Python | 8,742 | 259 | # -*- coding: utf-8 -*-
# Author: Florian Boudin
# Date: 09-10-2018
"""Kea keyphrase extraction model.
Supervised approach to keyphrase extraction described in:
* Thuy Dung Nguyen and Minh-Thang Luong.
WINGNUS: Keyphrase Extraction Utilizing Document Logical Structure.
*Proceedings of SemEval*, pages 166–169, 20... |
892118225d5708ad10ca6afb01eea20118f565bcd1ea820d32d5640dec3e222f | Python | 8,743 | 176 | import datetime
# Usage: rename this file to experiment_config.py,
# adjust according to your needs,
# and run the experiments with `python run.py --config_file experiment_config.py`
##### variable parameters #####
# variables that define the experiments
# network or data parameters can be varied
# one experiment wil... |
bf58162b1f32887459e289365c693a7a5b57280b204861fd100a26e9062c5b05 | Python | 8,752 | 299 | import os, fnmatch
import numpy as np
import scipy.io
import tifffile as tiff
import h5py
class Processed:
"""
A class used to load and save already processed datasets (or image files) in .mgh,.tif,.h5 or .mat format
"""
def __init__(self):
self.nMetaBytes = int(1024 * 1024)
self.stor... |
8f407a8b5d510b1e8d0d10b2751b2a2aeadd6f5eb89fa9f414233444d2814ac0 | Python | 8,754 | 267 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import csv
import json
import os
import random
import sys
from itertools import product
NAME = "comments"
def read_rules(name):
rules = []
with open(os.path.join(sys.argv[1], f"{name}.csv")) as f:
reader = csv.DictReader(f)
... |
d95e87688e4b4e1d2bb91dc82208dfb379f2347768f2f927b1a426ce786171bc | Python | 8,754 | 270 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 5 11:24:49 2020
@author: amelie
"""
from brian2 import *
from scipy import signal
from cells.RS_FEF import *
from cells.FS_FEF import *
from cells.SI_FEF import *
from cells.VIP_FEF import *
from FEF_visuomotor_tests import *
from FEF_contrast_d... |
35d4708a4b8b2a8c86d03b580dc30277f4de1ad127b3137d1ab407ea5bcef261 | Python | 8,759 | 216 | import contextlib
import sys
import typing
import nest
from bsb import (
AdapterError,
SimulationData,
SimulationResult,
SimulatorAdapter,
options,
report,
warn,
)
from tqdm import tqdm
from .exceptions import (
KernelWarning,
NestConnectError,
NestKernelError,
NestModelErr... |
f9126dbb46eb23942c592aaff49f579d02de56c4509852c98c8b1119e2479aeb | Python | 8,759 | 261 | """Tests for the :mod:`networkx.algorithms.triads` module."""
import itertools
from collections import defaultdict
from random import sample
import pytest
import networkx as nx
def test_triadic_census():
"""Tests the triadic_census function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04",... |
7c14ddf49cc3913a8d433ec6050092f654a15353f7956450ecbf84e568527650 | Python | 8,765 | 274 | import math
import pytest
import networkx as nx
from networkx.algorithms.planar_drawing import triangulate_embedding
def test_graph1():
embedding_data = {0: [1, 2, 3], 1: [2, 0], 2: [3, 0, 1], 3: [2, 0]}
check_embedding_data(embedding_data)
def test_graph2():
embedding_data = {
0: [8, 6],
... |
79ffb1629e36a2c72f25cb00e342c3ea5d9c577cc72b1172c2ee19819b6f28b6 | Python | 8,773 | 238 | import pytest
from himalaya.backend import ALL_BACKENDS, set_backend
from himalaya.backend._utils import _dtype_to_str
from himalaya.utils import assert_array_almost_equal
@pytest.mark.parametrize('backend', ALL_BACKENDS)
def test_apply_argmax(backend):
backend = set_backend(backend)
for array in [
... |
9cc9d168fe873133abc89cc0f5aee89574c1f79240256956ddf68f0246f7db7b | Python | 8,778 | 166 | import re
import sys
import os
import math
from scipy import stats
print("ALL_PPI_mutation_sites_mapping_with_allonco")
output = open(r'E:\OneDrive\学术\PPI article\data\mapped data\3. DNM_complex_mapping\ALL_Complex_PPI_mutation_sites_allonco.txt','w+')
with open(r'E:\OneDrive\学术\PPI article\data\mapped data\... |
e3cc1408e506df74b595c5a1f4c0ac84883fd0bde26546948ca50f933903c40a | Python | 8,778 | 245 | from itertools import chain, tee
from nl_expr.exceptions import NeuroLangException
from nl_expr.expressions import Constant
from nl_expr.logic.unification import (
apply_substitution_arguments,
compose_substitutions,
most_general_unifier_arguments,
)
from nl_expr.utils.orderedset import OrderedSet
from .. ... |
26e9ce641c90ef5dcf25868b64b7397adb131f9bb0048f0817008c39f8604a5f | Python | 8,780 | 230 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# 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 Licen... |
9a29c7495ecac93cf47775f2ce39af129de47bd22a11a563827fbd38be4a6e75 | Python | 8,785 | 321 | import neuroglancer
import operator
import logging
import numpy as np
logger = logging.getLogger(__name__)
class ScalePyramid(neuroglancer.LocalVolume):
"""A neuroglancer layer that provides volume data on different scales.
Mimics a LocalVolume.
Args:
volume_layers (``list`` of ``LocalVol... |
204bbca6c867cfa3c55a1a66697f5d42b507ce471f86328bba7a2d166f7b91d4 | Python | 8,786 | 186 | """A setuptools based setup module.
See:
https://packaging.python.org/guides/distributing-packages-using-setuptools/
https://github.com/pypa/sampleproject
"""
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
import pathlib
here = pathlib.Path(__file__).parent.resolve()
# Get the... |
25e86454792e98358c9f1c15e50fede410e23af581290ab04de520b007c358f7 | Python | 8,793 | 198 | """Implements the Time-Aware PC (TPC) Algorithm for finding Causal Functional Connectivity from Time Series.
"""
import time
import numpy as np
import pandas as pd
from timeawarepc.tpc_helpers import *
from timeawarepc.pcalg import estimate_skeleton, estimate_cpdag, ci_test_gauss
import rpy2.robjects as robjects
from r... |
83636090b07526245918a7921e06ba7d72041ff1b9b51e6fbc93876d40393387 | Python | 8,795 | 164 | import os
from os.path import join as opj
import subprocess
from subprocess import Popen
import shutil
import argparse
import numpy as np
import nibabel as nb
from scripts.data_preparation.extract_features import io_meld
from scripts.data_preparation.extract_features.create_identity_reg import create_identity
from meld... |
d9a7ebcd3fd71930b654e898b3a6130c6d836d788b2681a26e2f5d4c703634b7 | Python | 8,795 | 244 | import subprocess
from concurrent.futures import ProcessPoolExecutor, as_completed
import numpy as np
import pandas as pd
import xarray as xr
from ..mcds import RegionDS
from ..mcds.utilities import update_dataset_config, write_ordered_chunks
def _call_dmr_single_chrom(
dms_dir,
output_dir,
chrom,
p... |
ea5e2cbbbbdc095029910fba2b9691d15d6b8009b4ce96877d63d35a58f92bb8 | Python | 8,795 | 250 | import re
from unittest import mock
import numpy as np
import pytest
from zarr.core import Array
from zarr.util import (all_equal, flatten, guess_chunks, human_readable_size,
info_html_report, info_text_report, is_total_slice,
json_dumps, normalize_chunks,
... |
9adfbed0051cffca9ecf64a36ae1075677ad0b70ccc0c0252cc13a9206fc2dcd | Python | 8,796 | 302 | """Test trophic levels, trophic differences and trophic coherence"""
import pytest
import networkx as nx
np = pytest.importorskip("numpy")
pytest.importorskip("scipy")
def test_trophic_levels():
"""Trivial example"""
G = nx.DiGraph()
G.add_edge("a", "b")
G.add_edge("b", "c")
d = nx.trophic_lev... |
70a979a030d8ec4a57508575421a4c39805d3ef8be6c25b7c2ac2e2c9bc727a1 | Python | 8,797 | 287 | import os
import os.path as osp
import numpy as np
from collections import defaultdict
import torch
from cogdl.data import Graph, Dataset
from cogdl.utils import download_url
from cogdl.utils import Accuracy, CrossEntropyLoss
class GCCDataset(Dataset):
url = "https://github.com/cenyk1230/gcc-data/raw/master"
... |
996cdc8ca99473b9444eabc343ab13455431aad468f96ee5f688fb4c58f4744c | Python | 8,798 | 229 | #!/usr/bin/env python
#
# Copyright (c) 2017 10X Genomics, Inc. All rights reserved.
#
import collections
import cPickle
import errno
import h5py
import itertools
import numpy as np
import os
import scipy.sparse as sp_sparse
import sklearn.neighbors as sk_neighbors
import subprocess
import tables
import time
import ten... |
fd22d0d646f40200476b5ed3da37eaeef73d98e941ba575c8d5f05c53d0b6136 | Python | 8,800 | 247 | """
Dinitz' algorithm for maximum flow problems.
"""
from collections import deque
import networkx as nx
from networkx.algorithms.flow.utils import build_residual_network
from networkx.utils import pairwise
__all__ = ["dinitz"]
@nx._dispatchable(
edge_attrs={"capacity": float("inf")}, returns_graph=True, prese... |
bfb0b91585517ad61b93702bf9ac47765f0dd93ccf20551fbbf2ecc198639165 | Python | 8,803 | 218 | import copy
from inspect import getmembers, isfunction
import matplotlib
import numpy as np
class EditorTool(object):
def __init__(self, canvas, editor_gui, ax, figure_panel):
self.canvas = canvas
self.ax = ax
self.figure_panel = figure_panel
self.active = False
# self.chil... |
3b934599b06f9c62266a60f8c1519dc279faa85fe57b73ecf535be7b89c2bcc9 | Python | 8,807 | 281 | import pytest
import networkx as nx
def test_modularity_increase():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
partition = [{u} for u in G.nodes()]
mod = nx.community.modularity(G, partition)
partition = nx.community.louvain_communities(G... |
270693d9fe14a20c60af1d7bdd806363d3bdf72861cf88882094aeeaa944348f | Python | 8,809 | 209 | # -*- coding: utf-8 -*-
import pandas as pd
import os
import re
import copy
import numpy as np
import time
def goDeeper(props,this_path,a,max_a,conditions,folders):
a += 1
for newFolder in os.listdir(this_path):
print(newFolder)
if conditions[a-1] != "":
if newFold... |
518f72b5010fd29b3bc99ebf40cc69c6feaaf8ed407edc2810ca9f3170dd2627 | Python | 8,812 | 238 | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 22 10:46:47 2019
@author: Amelie Aussel
"""
from brian2 import *
defaultclock.dt = 0.01*ms
eq_HTC_buffer_mdPul='''
dV/dt=(-INa-IK-IL-IKL-IH-ITLT-ITHT-IAHP-IGJ-Iapp-Iapp2-J-Isyn)/Cm_HTC : volt
J : amp * meter ** -2
Iapp = randn() * gapp : amp * mete... |
298bca2baef8ecdfb47c60f7e223f65fe9785184efcf7ef70eee4ce0c5848226 | Python | 8,814 | 197 | # 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... |
e7a5ffa3e6c3ae5b834660fddd12524d174ed2232a5643d2c56b2cdef0558c95 | Python | 8,814 | 245 |
'''
CUDA_VISIBLE_DEVICES=2 python Explainer_Experiments.py --model_name CMPNN \
--attribution_name GradInput \
--data_path ../MolRep/Datasets/Metabolism/admet_exp_hlm_t1-2_20210412_TriCLF.csv \
... |
6731206b4d4034a1699b38f7beb764e09c5b7b0a59d8b321b8c210112e300262 | Python | 8,815 | 205 | """
Tools for analyzing motifs in the genome.
Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
"""
import tempfile
import pyfasta
import MOODS
import MOODS.scan
import MOODS.tools
import MOODS.parsers
from Bio import motifs
from tools import ReferenceManager
ALLOWED_FORMATS = ['bed', 'motif', 'position',... |
97c781094374dfa4dfac36412be9fa8dcc3a4013226628ec3a8db9f4d0ccdbf2 | Python | 8,816 | 298 | from nl_expr.logic.unification import most_general_unifier, apply_substitution
from nl_expr.logic.expression_processing import extract_logic_free_variables
from nl_expr.expressions import Symbol, Constant, Expression
from nl_expr.expression_walker import ReplaceSymbolWalker
from .exceptions import (
ParseException,... |
8bd818545b45403e6f43ba70fcdf91946830b5041b4ef3ffe70d3bb8863a776d | Python | 8,823 | 210 | from collections.abc import Sequence
import sys
if sys.version_info >= (3, 12):
from typing import override
else:
from typing_extensions import override
import numpy as np
import tensorflow as tf
from hidten.tf.emitter.multivariate_normal import (T_shapelike, T_TFTensor,
... |
f1d3eb144bf2a48ffa36a3e6381ab5904e4e62c39cf6769ec751f798a257e370 | Python | 8,824 | 210 | # -*- coding: utf-8 -*-
import pandas as pd
import os
import re
import copy
import numpy as np
import time
def goDeeper(props,this_path,a,max_a,conditions,folders):
a += 1
for newFolder in os.listdir(this_path):
print(newFolder)
if conditions[a-1] != "":
if newFo... |
108c953e91ef7b33a29df401025acc75ba232b69394e01f5ffffe263ffecc6fc | Python | 8,825 | 222 | import math
from typing import Optional
import torch
import torch.nn as nn
from .. import functional, surrogate
from .base_node import BaseNode
__all__ = ["ParametricLIFNode"]
class ParametricLIFNode(BaseNode):
def __init__(
self,
init_tau: float = 2.0,
decay_input: bool = True,
... |
8627fbd81a794b204ba9ecca58b0ced4b7a80806b2d07ef93eb42f6895f1782b | Python | 8,828 | 275 | """test annotations_combinator"""
import numpy as np
import numpy.testing as npt
import voxcell
import atlas_densities.combination.annotations_combinator as tested
def test_is_ancestor():
hierachy = {
"id": 1,
"acronym": "root",
"children": [
{
"id": 2,
... |
482c6408b5819f90e89e09f47b0c2210e1655d17dee9bd0a4e1b69282cf4aa9a | Python | 8,831 | 228 | #!/usr/bin/env python
"""Create a mask to ignore predictions at the boundary of objects using Dask.
This script replicates the original behavior exactly by dividing the input labels
volume (stored in a Zarr container) into blocks of a specified chunk size, growing
each block by a context (set by the maximum of th... |
498dccb228d7cb374d3dcf1a2b9210b2ea41a0cf09ebbcb9e8380db46bec6fd8 | Python | 8,835 | 236 | from __future__ import absolute_import, division, unicode_literals
from collections import MutableMapping
from xml.dom import minidom, Node
import weakref
from . import base
from .. import constants
from ..constants import namespaces
from .._utils import moduleFactoryFactory
def getDomBuilder(DomImplementation):
... |
38d4e022e8a1b6a8a924a33784f1a852bd31b657655be81dff157c5ae3c0feb1 | Python | 8,841 | 282 | """
SkeletonProcessing
==================
Utils to post process skeletons.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE.txt)'
__copyright__ = 'Copyright © 2020 by Christoph Kirst'
__webpage__ = 'http://idisco.info'
__download_... |
a2d28314f52a71a537d721c19d4c92229ea38228c53dba81429c5080cc602638 | Python | 8,841 | 256 | import copy
import os
import torch
import torch.nn as nn
import numpy as np
from .. import ModelWrapper
from cogdl.wrappers.tools.memory_moco import MemoryMoCo, NCESoftmaxLoss, moment_update
from cogdl.utils.optimizer import LinearOptimizer
from collections import defaultdict
from sklearn.model_selection import Stra... |
44c1920f0608f07be95c7c46c87609aead643981d5dbe9381114e5b7c2353841 | Python | 8,842 | 186 | import argparse
from loader import BioDataset
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from tqdm import tqdm
import numpy as np
from model import GNN
from sklearn.metrics import roc_auc_score
import pandas as pd
from util import ExtractSubstru... |
b828fd7529944c65a6c59f813558e7f17fef568050f073dc476cfe89777b7198 | Python | 8,842 | 214 | """Dynamo capture of FlexSN's callable scan body."""
import torch
from ..._ops.flexsn.hop import _hop_scan
__all__: list[str] = []
def _flatten_result(value) -> tuple:
if isinstance(value, torch.Tensor):
return (value,)
if isinstance(value, (tuple, list)):
return tuple(leaf for item in valu... |
4c87efa34c5541acda5cdea83e26500aa4e564330efcb00ca30fc5a483769e56 | Python | 8,846 | 211 | import os
import time
import numpy as np
from math import sqrt
class DANN(object):
def __init__(self, learning_rate=0.05, hidden_layer_size=25, lambda_adapt=1., maxiter=200,
epsilon_init=None, adversarial_representation=True, seed=12342, verbose=False):
"""
Domain Adversari... |
3f1f387139cdcb54da3eceedc67cdffe84a118db95fe1eee073e1d23a8253317 | Python | 8,850 | 314 | from typing import Optional
import torch
import triton
import triton.language as tl
from ..triton_layout import (
_block_minor,
_neuron_grid,
_neuron_indices,
_spatial_offsets,
_time_offset,
_triton_layout_args,
)
from ..triton_surrogate import _surrogate_gradient
from .autograd import _check,... |
4ab46b13c77d47130e00003c61f15df2b12b4994fc93d1ba819c9eb0bc493de3 | Python | 8,850 | 211 | # -*- coding: utf-8 -*-
import pandas as pd
import os
import re
import copy
import numpy as np
import time
def goDeeper(props,this_path,a,max_a,conditions,folders):
a += 1
for newFolder in os.listdir(this_path):
print(newFolder)
if conditions[a-1] != "":
if newFo... |
438983c6eb497d0b55dc54196632cdb19c58f2ec0644fb5858eabfe26c386535 | Python | 8,854 | 219 | import hashlib
import logging
import random
from datetime import datetime
from sqlalchemy import func
from galaxy import (
model,
util,
)
from galaxy.tool_util.deps.dependencies import ToolInfo
log = logging.getLogger(__name__)
VALID_JOB_HASH_STRATEGIES = ["job", "user", "history", "workflow_invocation"]
... |
5fbf3d09b956cae29321b08a65d04193cc897392ae584eb12e3d523ad76995a8 | Python | 8,858 | 228 | # 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... |
53cca8cff78d4194f0acef8beb7fffb8ad35b5c459085724834e2fbd7987232a | Python | 8,860 | 218 | from dotmap import DotMap
from tqdm import tqdm
from loguru import logger
import torch
from nidn.fdtd_integration.constants import FDTD_GRID_SCALE
from nidn.fdtd_integration.compute_fdtd_grid_scaling import _compute_fdtd_grid_scaling
from nidn.utils.global_constants import UNIT_MAGNITUDE
from ..trcwa.get_frequency_po... |
7614ebedf774918d87b2254ec8ad76c970b678090c9a3c14492ba78823e77df7 | Python | 8,860 | 206 | #!/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 logging import Logger
from typing import TYPE_CHECKING
from ... |
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