sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
05f68eeda720a37c0b6b8b4db7a691184be8ebc0c27362bbce39325e09296fbc | Python | 7,584 | 182 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
ef0595d1df0d18efb6c8fd1e7125f5911ad21032d02f847721388023c12ebe95 | Python | 7,584 | 228 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# Contents of this file were adapted from the open source fairseq repository.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Any, Dict, List, Optional
impo... |
9966f49f888a37257fc0177592caa36d05893ea603a04e5947490c5570351910 | Python | 7,586 | 192 | import numpy as np
import math
import os
from scipy.linalg import toeplitz
import numpy as np
import math
def bilateral_filter(j, t, y_j, y_t, delta1=1.0, delta2=1.0):
idx1 = -1.0 * (math.fabs(j-t) **2.0)/(2.0*delta1**2)
idx2 = -1.0 * (math.fabs(y_j-y_t) **2.0)/(2.0*delta2**2)
weight = (math.exp(idx1)*mat... |
c7a7da59c041a831d72c1adea4739362c2abac94a51388afcb9e2ca6e6c75c2c | Python | 7,586 | 205 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
37effea720d5536133f6c53de523f2b1fe23f979980f53f0dfeaa97f7090261b | Python | 7,587 | 143 | from typing import Optional
from pathlib import Path
import math
import numpy as np
import pandas as pd
from transformers import T5Tokenizer, T5EncoderModel
import torch
import re
from tqdm.auto import tqdm
from pyproteonet.data import Dataset
import pandas as pd
from datasets import load_breast_cancer_dataset, load_... |
1d858346dfb9fcfb7c02a8cd4fcca80155f2d530c9120fe76bb7129324b8d29f | Python | 7,588 | 179 | import numpy as np
from sklearn.model_selection import KFold
from datetime import datetime
import os
import time
import csv
from model import CNN
from dataloader import DATA, DATA_TEST
from config import DEBUG, RUN_NAME, SKIP_FOLDS, RUN_PARAMETERS, TEST, DATA_AUGMENTATION, LABEL_FORMAT, BINNING, CONV_LAYERS
from helpe... |
5ae28a4a94c9882755ce246bedd2ab37714f487fe4fd71f0b659e7ca2bddb26f | Python | 7,588 | 145 | #!/usr/bin/env python3
"""Consistency checks for the ``retired_ids`` registry in ``library_data.json``.
A hedId is permanent. When an element is removed from a released schema, or an id is assigned in
a prerelease and then withdrawn before release, the id goes into ``retired_ids`` for the owning
schema and must never ... |
7cb534882dd06f03d13dc106bd5bdfc5026276b44f12fe89a37a7742481c9833 | Python | 7,588 | 227 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''Copyright (C) 2012 Computational Neuroscience Group, NMBU.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at you... |
5f7cea577bb39a8f2a691f0327601b3acc4c46f03c13bafc1074ea9d4dbc2e6e | Python | 7,591 | 234 | ##
# \file image_similarity_evaluator.py
# \brief Class to evaluate image similarity between stacks and a reference
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date February 2018
#
# Import libraries
import os
import re
import numpy as np
import SimpleITK as sitk
import nsol.observer as ... |
3aac79b5b5158069133f6169c6c11d10df9ef4d5610973dcdb9100ffc122e1a0 | Python | 7,593 | 244 | import numpy as np
from dreamcoder.task import Task
from dreamcoder.type import arrow
import dreamcoder.domains.arc.arcPrimitives as p
from dreamcoder.domains.arc.arcPrimitives import Grid, Input, tgrid, tinput, toutput
from dreamcoder.type import arrow, baseType, tint, tlist, t0, t1, t2, tbool
from dreamcoder.domains.... |
878cdc80b18027d58a8afd54218495c9a43a4eecfcd53ab21c02a8c18f27c90a | Python | 7,593 | 230 | #!/usr/bin/env python
# Copyright (c) 2018-2020 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module provides the ScenarioManager implementations.
It must not be modified and is for reference only!
"""
from __future__... |
ec096120589c6a8e339e3b9b14565beb09f6d08dee0fda57e69c9eaae4299f18 | Python | 7,593 | 191 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import math
import os
import torch
from torch import nn as nn
from torch.autograd import Function
from torch.autograd.function import once_di... |
6a732d14b1178b23a188e900dc47f2fbd896130929bfdaa7a9373d9522f2bacd | Python | 7,594 | 230 | # ----------------------------------------------------------------------
# Copyright (C) 2014-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/... |
7e5edbabe923dfae53203483f3f8b8fcbacbef4da9522e69ca57a42703b437a7 | Python | 7,596 | 137 | """
Created on 02/06/2020
:author: Mahyar Osanlouy
:summary:
"""
from SimpleITK import GetDefaultParameterMap, VectorOfParameterMap
class RegistrationParameters:
"""
We will define a general registration parameters in this class.
If further parameters are required to add to a specific regis... |
477108970d452095e6913137f43547b2d9fe8b8c39cd06712eff10821b9f5842 | Python | 7,598 | 296 | import numpy as np
import matplotlib.pyplot as plt
from help_funcs import load_exp_variables
# ----- #
# Hyperparameters.
metric = "rocauc"
if metric == "rocauc":
metric_str = "score"
elif metric == "accuracy":
metric_str = metric
band = "beta" # "beta", "mu"
if band == "beta":
band_letter = "β"
elif b... |
57bf6343c799fdca22fa22be3cf2939ef77e3e6a00a0044e3581f6bd83d8117a | Python | 7,599 | 174 | """
toposampling - Topology-assisted sampling and analysis of activity data
Copyright (C) 2020 Blue Brain Project / EPFL & University of Aberdeen
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... |
7bd9838c68ba31894a2b784f64ccbb1a796b7a3d7a702e87fdf7c4dd7c45223e | Python | 7,599 | 167 | import warnings
warnings.filterwarnings("ignore")
warnings.filterwarnings("ignore", category=UserWarning,
message="A NumPy version >=1.18.5 and <1.25.0 is required for this version of SciPy*")
import sys
import os
import argparse
import pandas as pd
from glob import glob
from nilearn.glm.first_l... |
9c983e002b1f3bff5b2332171196800bfc66e1cd00db7bea12ddd8d75ed1934b | Python | 7,599 | 235 | """Summarizes events in a tabular file by checking tag coverage and quality."""
from hed import TabularInput
from hed.errors import ErrorHandler
from hed.errors.error_types import TagQualityErrors
from hed.tools.analysis.event_checker import EventsChecker
class EventsSummary:
"""Summarizes HED event annotations ... |
4b3a9d411908fb0eb2aa778edd19c574828cefbecbb2e7a64273fccd806bdc44 | Python | 7,601 | 227 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
a4d960779de31ce0a3f64b3d3072dd5f7b2411ddef0761d192e50c51bf4ff01d | Python | 7,602 | 164 | import torch
from transformers import AutoModel, AutoTokenizer
import numpy as np
from rdkit import Chem
from tokenizers import Tokenizer
from tokenizers.pre_tokenizers import Split
from tokenizers import Regex
from tokenizers.models import WordLevel
import os
def predict(embedding_matrix, scaler, model, device)... |
60fd3258011d2933c61db6db44ccb32c06244880820f29493c596f357f1fe166 | Python | 7,604 | 166 | # import libraries
import numpy as np
import sys
import os
# import modules within repository
sys.path.append('C:\\Users\\dreww\\Desktop\\hyperbolic-learning\\utils')
sys.path.append('C:\\Users\\dreww\\Desktop\\hyperbolic-learning\\hyperbolic_gaussian')
from utils import *
from riemann_mean import *
from distribution... |
97669b2807b6a1e3f15955c6cb7c1ad8ef875d0a7f840ebaa1ae2fe71176d317 | Python | 7,605 | 225 | import os
import glob
import torch
import pickle
import numpy as np
import pandas as pd
import scprep as scp
import anndata as ann
import seaborn as sns
import matplotlib.pyplot as plt
import scanpy as sc, anndata as ad
from os import name
from PIL import Image
from sklearn import preprocessing
from sklearn.cluster imp... |
a8f03fe290e40335d2b9afb1753703b9867cd6deedd155e90b64a567134ace55 | Python | 7,605 | 147 |
from sklearn.linear_model import LinearRegression
from sklearn.decomposition import PCA
from sklearn.model_selection import cross_val_predict
from sklearn.metrics import mean_squared_error, r2_score
import numpy as np
def pc_multregconn(activity_matrix, target_ts=None, n_components=None, n_comp_search=False, n_compon... |
f29efc863f96765bd8c0a38f980ec6faa1d1ef1744427ce8d5b50fc90f3c3d4f | Python | 7,605 | 161 | import numpy as np
import scanpy as sc
import torch
import anndata as ad
import pandas as pd
from scHetG_master import train_scHetG
from scHetG_master import preprocess
import random
import warnings
warnings.filterwarnings('ignore')
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'
from scipy.sparse import csr_matri... |
b6e23505656e11338b10efe919bc86b23b86eb07d6612a9269f3f3171f1b3cdc | Python | 7,606 | 217 | import torch
from torch.utils.data import DataLoader
from rocf_scoring.config import (RESUME_CHECKPOINT, PATH_CHECKPOINT, SAVE_MODEL_CHECKPOINTS, RUN_NAME, TRAINING_RESULTS_DIR,
TRAINED_MODELS)
from rocf_scoring.data_preprocessing.loading_data import load_raw_data
from sklearn.model_sel... |
fc8f1318a60005339d5da0e514df6a41f1527049cbdaa2f536b97609ef358bb5 | Python | 7,606 | 195 | #!/usr/bin/python3
import os
import argparse
import tensorflow as tf
from osgeo import gdal
# imports from this package
import utils
from cnn_lib import AugmentGenerator
from architectures import create_model
from visualization import visualize_detections
from cnn_exceptions import DatasetError
def main(data_dir... |
a70fbc8840e4c81632033a7529811d0730bba3f59ee6eee1126898cee106ee90 | Python | 7,607 | 161 | import numpy as np
import scanpy as sc
import torch
import anndata as ad
import pandas as pd
from scHetG_master import train_scHetG
from scHetG_master import preprocess
import random
import warnings
warnings.filterwarnings('ignore')
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'
from scipy.sparse import csr_matri... |
e5d3b26e6350def014747378595c4fde38f8d225b1715fac7d573e9dd6b9d927 | Python | 7,608 | 170 | import os
import numpy as np
import pandas as pd
import scanpy as sc
import matplotlib
import matplotlib.style
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import sparse
import anndata
from scipy import stats
def adata2numpy(adata):
if sparse.issparse(adata.X):
return adata.X.A
els... |
91596111a2d70ff26e3a9af139fde4c1006c7b0d3a781bb4e77705c16b79e478 | Python | 7,609 | 137 | import numpy as np
import nibabel as nib
import h5py
import os
import pkg_resources
dilateMM = 10
partitiondir = pkg_resources.resource_filename('ActflowToolbox.dependencies', 'ColeAnticevicNetPartition/')
defaultdlabelfile = partitiondir + 'CortexSubcortex_ColeAnticevic_NetPartition_wSubcorGSR_parcels_LR.dlabel.nii'... |
480bf1d5c5e490cf1ab7d6542fff70a509e749d7c0573c14d01de6438ab641df | Python | 7,610 | 235 | import torch
import torch.nn as nn
from elasticai.creator.nn.integer.design_creator_module import DesignCreatorModule
from elasticai.creator.nn.integer.MPQ.linear import Linear
from elasticai.creator.nn.integer.MPQ.mha.design import MHA as MHADesign
from elasticai.creator.nn.integer.MPQ.scaleddotproductattention impor... |
ccd82b49ee60e51eae97755fa17eb22028f75c483bc9e369121d2aec1cbb5e48 | Python | 7,610 | 201 | import re
import os
from pathlib import Path
from functools import reduce, partial
from operator import getitem
from datetime import datetime
from utils.logger import setup_logging
from utils.util import read_json, read_yaml, write_json
class ConfigParser(object):
def __init__(self, config, resume=None, modificat... |
16ed396034914ada92578591fa5a74f83aa0174d52eccca3e1acf49ddfba2a3b | Python | 7,613 | 205 | from typing import Any, Callable, Optional, Sequence, Union
import torch
from pytorch_lightning import LightningDataModule
from torch.utils.data import DataLoader, Dataset, random_split
import torchvision.transforms as T
from torchvision.datasets import ImageFolder
from pl_bolts.datamodules.vision_datamodule import V... |
938978c8085b05f2daef43c3a7e81d1a098842516ea6fa3dcbb16d2f8a96769c | Python | 7,613 | 296 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn.decomposition import PCA
from tqdm.auto import tqdm
import torch
from umap import UMAP
import pancancer_evaluation.config as cfg
from csd_simulations import simula... |
c0477e29e72c4bee1155468c7e72fef3e26d900f8358d352ff3c2c847a2543fc | Python | 7,615 | 221 | from __future__ import print_function
import numpy as np
# This is the "standard" transformations.py file
# https://www.lfd.uci.edu/~gohlke/code/transformations.py
# http://docs.ros.org/jade/api/tf/html/python/transformations.html
from pybullet_tools.transformations import rotation_matrix, translation_matrix
from pyb... |
d822951d8f2f15d239338ac5673e9a729ac0d758d8aeea80d8b12e3ce9db300f | Python | 7,615 | 161 | import numpy as np
import scanpy as sc
import torch
import anndata as ad
import pandas as pd
from scHetG_master import train_scHetG
from scHetG_master import preprocess
import random
import warnings
warnings.filterwarnings('ignore')
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'
from scipy.sparse import csr_matri... |
c2df979f0b87c642a62d30023d4085a821157ba5c7366fb870fc4017127bc166 | Python | 7,617 | 144 | """Deterministic behaviour capture for before/after refactoring comparisons (exact equality).
PYTHONPATH=<src> python scripts/behaviour_capture.py cpu OUT.json
PYTHONPATH=<src> CUBLAS_WORKSPACE_CONFIG=:4096:8 python scripts/behaviour_capture.py gpu OUT.json
Run it with PYTHONPATH pointing at two checkouts (e.g. a... |
25e22bcb0cd1f4f133cc3316680fd0f7d8813b14165697f475e3bfa3b1396b27 | Python | 7,618 | 238 | # -*- coding: utf-8 -*-
#
# LFPy documentation build configuration file, created by
# sphinx-quickstart on Mon Oct 3 13:36:41 2011.
#
# This file is execfile()d with the current dir. set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configu... |
741021000230130d837609ef958768b9c6b008f189aa46e29071df26db631ebb | Python | 7,618 | 205 | import torch
from torch import nn
from torch.nn import functional as F
from elasticai.creator.nn.integer.conv1d.design import Conv1d as Conv1dDesign
from elasticai.creator.nn.integer.design_creator_module import DesignCreatorModule
from elasticai.creator.nn.integer.math_operations import (
get_padded_q_inputs,
... |
8597e9611341843b7da406617e4ecb3bc9b6cabba4c1c5fe4f1a01b19d09698e | Python | 7,619 | 177 | import json
import os
import xml.etree.ElementTree as ET
import numpy as np
from ..constants import bohr2ang, hartree2ev
from .. import config as CFG
from ..utils.structure import Structure
from ..utils.misc import atom_name2number, atom_number2name, unique_nosort
from .bgwio import bgw_wfn, bgw_vsc, bgw_vkb, bgw_fil... |
8a99a843f84f6ab721385fd1570be1afef8d9e5d1affc063c1fdd6ac5c723045 | Python | 7,619 | 187 | """
Generates a ListTomoOMSegmentations object from a input STAR file
Input: - STAR file with the list of segmentations, each list pairs membrane and lumen segmentations
Output: - A ListTomoOMSegmentations pickled object for every STAR file row
"""
################# Package import
import os
impor... |
a30d7d69d5765f8a0ba75437e4ea4a45005f99aba816af02c086580ad16124c4 | Python | 7,620 | 161 | import numpy as np
import scanpy as sc
import torch
import anndata as ad
import pandas as pd
from scHetG_master import train_scHetG
from scHetG_master import preprocess
import random
import warnings
warnings.filterwarnings('ignore')
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'
from scipy.sparse import csr_matri... |
45187c9d6fa426cb499a3309ed0d6956a5180ed2ec3e853438c14351952e33fe | Python | 7,622 | 172 | from functools import reduce
from operator import __add__
import torch
import torch.nn as nn
class Conv2dSamePadding(nn.Conv2d):
def __init__(self, *args, **kwargs):
super(Conv2dSamePadding, self).__init__(*args, **kwargs)
self.zero_pad_2d = nn.ZeroPad2d(reduce(__add__,
... |
23151fb52b6357489b51890d8468503277fdbe041333f61616e271e1f548f97d | Python | 7,623 | 170 | '''
Description:
Test scNODE when using different number of pre-training timepoints.
Author:
Jiaqi Zhang <jiaqi_zhang2@brown.edu>
'''
import os.path
import sys
import matplotlib.pyplot as plt
import torch
import torch.distributions as dist
import numpy as np
import pandas as pd
from datetime import datetime
f... |
00c89cd893be3a03655efcb6e95ac7cdce25aae0fddb0ed0de443a68f89aba7d | Python | 7,624 | 114 | import numpy
import modules.io as io
import modules.plot_func as pltt
import modules.traj_analysis as tran
import modules.helper_func_class as misc
#import modules.process_mouse_trials_lib as plib
import matplotlib.pyplot as plt
import scipy.io
import scipy.stats
import os
import datetime
import time
#import matplotlib... |
faf1fde0b1b67aab399e0c9ef6bdf77fe11ea29b2019664b28a2327616c8f944 | Python | 7,625 | 236 | import sys
from collections import defaultdict as d
import re
from optparse import OptionParser, OptionGroup
import math
import gzip
#Author: Martin Kapun
######################################################### HELP #########################################################################
usage="""python %prog ... |
0631ad979d6d37f1e12c23287fa6e050fee2e919a92dc85974fe1aacc4ea16c1 | Python | 7,628 | 154 | from itertools import combinations, product, islice
import numpy as np
from control_tools.ik.pr2_ik import get_arm_ik_generator
from control_tools.common import get_arm_prefix
from plan_tools.common import Conf, COLLISION_BUFFER, get_pr2_safety_limits, get_weights_resolutions
from plan_tools.samplers.collision import... |
69367f11bb5635b60be979642caea4e280b1f61c44474113a967953cdc5eff48 | Python | 7,628 | 293 | # Settings for connectivity
# p - probability of connection (divergence)
# strength - base synaptic weight scaling factor
# delay mean - mean delay for AP conduction
# delay std - standard deviation for AP conduction delay
# syn_types - synapse types for connection
params = {}
params["conduction_velocity"] = 570 # un... |
896123305069938a7d891bcfbbb6ff178eaaf6799ba9afb79ab6fcf490e9e875 | Python | 7,628 | 161 | import os
import re
from typing import Iterator, Callable, Dict, Tuple, Union
import pandas as pd
from sklearn import model_selection
from torcheeg.datasets.module.base_dataset import BaseDataset
from .base_model_selection import BaseModelSelection
from .utils import create_subset, read_indices, write_indices
class... |
4ee00323eb4fc23ab8ccf305c955aae009fa55167532e513b1e1c302f2cb45dc | Python | 7,631 | 258 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
b22512c2acafb44ccdd1e1fecb3b1670c32fedff9077e490a93b9203c1cdb8a2 | Python | 7,631 | 147 | """
OXASL - Structural data module
Copyright (c) 2008 University of Nottingham
"""
import os
import glob
import numpy as np
import fsl.wrappers as fsl
from fsl.data.image import Image
from fsl.utils.path import PathError
from oxasl.options import OptionCategory, OptionGroup
from oxasl.reporting import LightboxImage... |
084e93836bbad7929a73fcb9ff3e3eb61293e23d500cdf25c86b9e13008bf035 | Python | 7,632 | 181 | import math
import torch
from torch import nn
import time
from warnings import warn
from collections import OrderedDict
import numpy as np
class RNN_Net(nn.Module):
def __init__(self, dim_in, dim_hid, dim_out,
n_layers=2, nonlin=torch.nn.Tanh(),
bias=False, out_scale="small", g=... |
d46569fc450b412438dda132ae6f4de2de145e08b2e4dc1405278e3144f523e6 | Python | 7,633 | 281 | #!/usr/bin/env python
# coding: utf-8
# ## Generalization of selected features to non-carcinoma data types
#
# Do the pan-cancer/median univariate correlations correspond to high correlations on non-carcinoma data types?
# In[1]:
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot... |
c0e419032840714b5b72a4cba4d3b960fd0eec43d985c412aca6821bb8993702 | Python | 7,634 | 224 | # filter.py
import regex
from fba.utils import open_by_suffix, get_logger
logger = get_logger(logger_name=__name__)
def compile_regex_ref_barcodes_single(sequence, num_mismatches=1):
"""Compiles a regular expression pattern, returning a pattern object.
Parameters
----------
sequence : str
... |
da5dd8778bb5127b7e865ac81ca286bf39942b9ce53e323645b88aace99765df | Python | 7,636 | 158 | import contextlib
import copy
import io
import json
import os
import shutil
import unittest
from hed import load_schema, load_schema_version
from hed.schema import HedKey, HedSectionKey
from hed.scripts.hed_convert_schema import convert_and_update, format_removed_row
from hed.scripts.schema_script_util import add_exte... |
93b5170f487e03064a2e9de757b175c7ac6ca9b0b2b9782da4233b70813b425d | Python | 7,637 | 247 | """
Integration tests for "real" data
"""
import glob
import os
import re
import shutil
import tarfile
from gzip import GzipFile
from io import BytesIO
import pandas as pd
import pytest
import requests
from pkg_resources import resource_filename
from tedana.workflows import t2smap as t2smap_cli
from tedana.workflows... |
04e96855be470a8f9f55116fd0ab9f3f107359d5c2df542f07f5f77d13713159 | Python | 7,638 | 225 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Written by Tong He and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
"""
import os
import time
import random
import argparse
import numpy as np
from pathlib import PurePath
import torch
import torch.utils.data
import torch.nn as ... |
d8f5d576e6193c23d99244057b527519b7c725678253ef855e89c6c887f0f5e5 | Python | 7,638 | 210 | """Lazy ZIP over HTTP"""
__all__ = ["HTTPRangeRequestUnsupported", "dist_from_wheel_url"]
from bisect import bisect_left, bisect_right
from contextlib import contextmanager
from tempfile import NamedTemporaryFile
from typing import Any, Dict, Generator, List, Optional, Tuple
from zipfile import BadZipFile, ZipFile
f... |
4fe75caa6e51c6b7aad3ca1d83d5288e92d7f86c685e619377c7ac2df518aac5 | Python | 7,641 | 183 | from pathlib import Path
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import sys
#********************************** PLOT Utils******************************************
PALETTE = sns.cubehelix_palette(start=0.3, hue=1,
gamma=0.4,dark=0.1, light=0.9,
rot=-0.6... |
6a57dfc47ba293c52e892dcf40f73b1b6604d28081a9af9105d9c8a4dc62c0fb | Python | 7,641 | 188 | # Extract and separately save out TVAT surfaces used in Fig 5A-B
# from full dataset
from os.path import join
from get_paths import *
import h5py
import numpy as np
import pickle
if __name__ == "__main__":
## File names
fname_regressions = "data_tvat_polynomialregressions.pickle"
fname_tvat ... |
5fe275edcf8ee9298dbcdad9122e264e61e83a3acbcb5ee74b03f87d91e89b91 | Python | 7,642 | 213 | import itertools
import re
import bpy
import databpy as db
import numpy as np
import pytest
import molecularnodes as mn
from molecularnodes.nodes.geometry import (
StyleBallAndStick,
StyleCartoon,
StyleRibbon,
StyleSpheres,
StyleSurface,
)
from .constants import codes, data_dir
from .utils import Ge... |
ce669c78263f6e844903a94937e2f2c5d54ea25928f78cdd3ccf512ec8b1fbb2 | Python | 7,644 | 292 | import os
from pathlib import Path
import numpy as np
from typing_extensions import Annotated
from ._ctyped import Library
try:
lib = Library("libcudaDecon")
except FileNotFoundError:
raise FileNotFoundError(
"Unable to find library 'lidbcudaDecon'\n"
"Please try `conda install -c conda-forge... |
44cc31d845e45a5592032145d54859a3f5074ee8314aa59c609ad32b2829d217 | Python | 7,650 | 204 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Copyright (C) 2014-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you ca... |
756ab8d68c59d1521242eb3c2929fe9bc118ff251e4819c2e5759b99d736749a | Python | 7,650 | 174 | #!/usr/bin/env python
import os
import argparse
import sys
sys.path.append(os.path.dirname(__file__)+'/..')
from maggie import score, utils, visual, simulate
import numpy as np
import pandas as pd
def check_positive(value):
ivalue = int(value)
if ivalue <= 0:
raise argparse.ArgumentTypeError("%s is ... |
83467e1387f053723b331c7c2f1d8c5585dfa1908eb39740c74690e999d57914 | Python | 7,650 | 225 | """
Lovasz-Softmax and Jaccard hinge loss in PyTorch
Maxim Berman 2018 ESAT-PSI KU Leuven (MIT License)
"""
from __future__ import print_function, division
from typing import Optional
import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from .constants import BINARY_MODE, MULTICLASS_MO... |
d682a8e29f6d33677345347b23084f7266a9411ccf6cffdc4d03a38b84979edb | Python | 7,650 | 218 | import numpy as np
import math
from examples.drake.utils import get_random_positions, get_joint_limits, set_joint_positions, exists_colliding_pair, \
create_transform, solve_inverse_kinematics, get_unit_vector, get_body_pose
from examples.pybullet.utils.motion.motion_planners.rrt_connect import birrt
from examples... |
f346b420dc4251905101d267a797dfba620386a3df5bdc702fe847225d791f33 | Python | 7,651 | 199 |
#============================
# merge two plink filesets
#============================
def tmp_file(bfile, suffix=''):
return tmp_path + "/" + os.path.basename(bfile) + suffix
def strip_a1a2(bfile, suffix):
# strips the A1:A2 suffixes from variant rsIDs
out_path = tmp_file(bfile, suffix)
with open(ou... |
527e30e9a07a25c40a445d37f6820da2c79e37e0f6c5a072a410f3e81de0f8e0 | Python | 7,652 | 203 | # \file TestStack.py
# \brief Class containing unit tests for module Stack
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date December 2015
import SimpleITK as sitk
import numpy as np
import unittest
import random
import os
import niftymic.base.stack as st
import niftymic.base.data_reader as dr
impor... |
599f531dec7d2e07b6db122e506ba7d468268ca72d2f322d8f2e7024a930d444 | Python | 7,652 | 243 | import logging
import time
import unittest
from shutil import rmtree
import neurolib.utils.functions as func
import numpy as np
from neurolib.models.aln import ALNModel
from neurolib.models.multimodel import MultiModel
from neurolib.models.multimodel.builder.fitzhugh_nagumo import FitzHughNagumoNode
from neurolib.opti... |
dc39021d7049e9c5f6c274d6b2e5fa0416910e586faca9a4f695519df05770a2 | Python | 7,652 | 176 | """Volume-to-affine alignment via longitudinal fissure detection."""
import numpy as np
from tqdm import tqdm
from .align_utils import load, preprocess, bbox, find_lines, process_lines, svd_fit, get_affine
def vol2affine(
moving: np.ndarray = "data/brain_25.nii.gz",
template: np.ndarray = "data/temp... |
4f5c8b2a12a0bec8eb6d3e23c2b6549b1993c13e11e90bf13779ea25412cb52e | Python | 7,653 | 249 | # https://www.lammps.org/workshops/Aug17/pdf/tranchida.pdf
import numpy as np
from ase import Atoms
from hotpp.data.utils import atoms_collate_fn, AtomsDataset
from typing import Dict
import types
from ase.io import read, write
import torch
from copy import deepcopy
from datetime import datetime
import cupy as cp
from... |
7490d4fb76505c6f8287969049af44b868a02901c525fc237586e704fa570270 | Python | 7,654 | 231 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
9b7005dca6266d3fbd01fa38cecfc1f20fa984aaf82132970192dc3ff9a551b2 | Python | 7,655 | 291 | # Environments for the Simulations
import numpy as np
import matplotlib.pyplot as plt
from copy import deepcopy
import math
# Base Env class for subclassing to define the environment interface
class BaseEnv(object):
def __init__(self):
pass
def init(self):
pass
def reset(self):
pass
def step(se... |
0d8b5263da4079b8b968dff6de40eb419608d49916e661bc8557fe918652b145 | Python | 7,656 | 245 | #!/bin/env python3
'''
Define a Feynman diagram
'''
import numpy as np
import pdlfeynman as fy
import pdlfeynman.particle as fyp
import pdlfeynman.reaction as fyr
import yaml
def determine_particle(node:fy.diagram.Node, key:str='products') -> fyp.Particle|None:
match node.nodetype:
case fy.diagram.NodeType... |
0e480fd893d53be9a71f70598c6bad4fde2990ec48b6ca291b5a99f281469dac | Python | 7,658 | 183 | '''
Created on 1 May 2018
High level class containing the necessary methods.
@author: Miguel Molina Romero, Technical University of Munich
@contact: miguel.molina@tum.de
@License: LPGL
'''
from dry.utils import generate_synthetic_data
from keras.layers import Dense
from keras.models import Sequential
from keras.opti... |
797b8e975f549cb4c8deeb68b0176c5caddae6e7015c3d47302fbeb664598cf8 | Python | 7,659 | 198 | # Node-group asset "Color Sample Grid" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHEC... |
6a46f64a629cdcee036a0d6330283759db1facce2bc0f26cc8d68720b34ceea2 | Python | 7,661 | 199 |
#============================
# merge two plink filesets
#============================
def tmp_file(pfile, suffix=''):
return tmp_path + "/" + os.path.basename(pfile) + suffix
def strip_a1a2(pfile, suffix):
# strips the A1:A2 suffixes from variant rsIDs
out_path = tmp_file(pfile, suffix)
with open(ou... |
33f74bfc6d0209e4e0713a4fd50eb8fd07966436edd2becf1bde5133c4c388ca | Python | 7,662 | 157 | import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import re
from scipy import stats
def one_sample_ttest(sample_data, null_hypothesis_mean=0.0, significance_level=0.01):
# Calculate the T-test for the mean of ONE group of scores
t_statistic, p_value = stats.ttest_1samp(sample_dat... |
dfc75a803e213145a8e556aa647b6c5c7f7f03be76957146ba01d41676ec1a9a | Python | 7,662 | 234 | import re
from collections.abc import Iterable
import pytest
from elasticai.creator import ir
from elasticai.creator.ir2vhdl import Node as VhdlNode
from elasticai.creator.ir2vhdl import Shape, factory
from elasticai.creator.ir2vhdl.language import Instance
from ..vhdl_nodes.node_factory import (
InstanceFactory... |
27f3a274d10da6f6e96d9987731a6e62e19af5db0499ca42f3069d451a3db31e | Python | 7,666 | 184 | """The input pane keeps the loaded volume's affine, for orientation labelling.
A plain 3D NIfTI preview is loaded ``reorient=None`` - raw on-disk axis order -
so only its affine can say what is actually on screen. It has to reach the panel.
"""
import numpy as np
import pytest
nib = pytest.importorskip("nib... |
d684ed8833b7c584fda6a9cd0d00d19434b19e77bda05dc10d8cd5b198b4c89c | Python | 7,666 | 238 | """Materials Project-compatible recipes using the MP24 sets."""
from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
from monty.dev import requires
from quacc import flow, job
from quacc.calculators.vasp.params import MPtoASEConverter
from quacc.recipes.vasp._base... |
e6bb2a4e7f8a791a6f190792ad6edc7bdf4b3f619371b6f7d7d7b76c309ab7f6 | Python | 7,666 | 194 | ##
# \file data_preprocessing.py
# \brief Performs preprocessing steps
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date May 2017
#
import numpy as np
import niftymic.base.stack as st
import niftymic.utilities.intensity_correction as ic
import niftymic.utilities.n4_bias_field_correction as... |
730b7e6a8447e921caa3a5af7f66f8a57365916422dfb7a13d3440224d95544d | Python | 7,671 | 208 | import torch
from torch import nn
from torch.nn import functional as F
from elasticai.creator.nn.integer.design_creator_module import DesignCreatorModule
from elasticai.creator.nn.integer.fusedffn.fc1relu.design import (
Linear as LinearReLUDesign,
)
from elasticai.creator.nn.integer.math_operations import MathOpe... |
0930beb5aa1117c69412057e4a5f1b2d0ce94cf956005674b1b8f3304fbf54bd | Python | 7,679 | 245 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
8f2355b547cc21fd26b7263e5e9d66f7243c8b0102a334955459a390df5adb2c | Python | 7,680 | 213 | import logging
import os
import sys
import sysconfig
import typing
from pip._internal.exceptions import InvalidSchemeCombination, UserInstallationInvalid
from pip._internal.models.scheme import SCHEME_KEYS, Scheme
from pip._internal.utils.virtualenv import running_under_virtualenv
from .base import change_root, get_m... |
a1a46df422dc811e213e5b1d00a2e0a9608a2f1cb68f2b6e13bf5fde94d5b5c5 | Python | 7,680 | 202 | import xml.etree.ElementTree as ET
import h5py
import numpy as np
from scipy.sparse import coo_array, diags_array
from ..constants import hartree2ev
from ..utils.structure import Structure
from ..utils.misc import mytqdm, KGData
from ..utils.mpi import one_by_one, distrib_vec, is_master
from ..utils.math import make_k... |
e32890dc2e501bf1eaf6ed03302b95b5906823fa373e2ff5f54b35d64730f476 | Python | 7,682 | 216 |
#!/usr/bin/env python
#Main function scanning BAM
import pysam
import sys
from collections import defaultdict
import numpy as np
import pandas as pd
import itertools
from scipy.sparse import csr_matrix
import scipy.sparse
from SCanSNP.GenUtils import CountData
from SCanSNP.VCFUtils import *
from SCanSNP.DBLsutils i... |
43896737a445d7004deb871005dc8f71ad7b27a7f94d8022922d29548a578f55 | Python | 7,684 | 243 | from typing import Callable, List, Dict, Optional, Literal
import torch
from torch import nn
from .base import AtomicModule
from ..layer import EmbeddingLayer, RadialLayer, ReadoutLayer
from ..layer.equivalent import MultiBodyLayer, GraphConvLayer, NonLinearLayer, GraphNorm
from ..utils import find_distances, _scatter_... |
b2d473813ea07573139ac122f0fcae7443b7d990c2ee23fefac75412b70cb8eb | Python | 7,684 | 207 | """distutils.command.build_clib
Implements the Distutils 'build_clib' command, to build a C/C++ library
that is included in the module distribution and needed by an extension
module."""
# XXX this module has *lots* of code ripped-off quite transparently from
# build_ext.py -- not surprisingly really, as the work req... |
c730affa671c9e3b4e4d48b8a79e69dd6601ccabcc15f122a32208b67020a5b0 | Python | 7,684 | 233 | # ----------------------------------------------------------------------
# Copyright (C) 2014-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/... |
d07886276b7aa576c8f39f0a25b5c74cb6f5bd0e107b69d99fae072102de185e | Python | 7,684 | 172 | #!/usr/bin/env python
"""
Script to plot example whisker (wsk) and spike (spk) trace of selected clusters
from choosen recording. Contains the following:
- plot_wskspk: loads metadata, retrieve whisker and spike data through
align_fun, then plot clusters of interest and example of whisking bout;
"""
# Ensure /data_an... |
112cf8878609c3d06b2d29f67b5e9ee82e03193b160abada0f3eaef3222e7976 | Python | 7,688 | 216 | from itertools import islice, product
import numpy as np
from examples.pybullet.utils.pybullet_tools.pr2_primitives import State, Pose, Conf, create_trajectory
from examples.pybullet.utils.pybullet_tools.utils import get_subtree_aabb, link_from_name, joints_from_names, \
get_joint_positions, set_joint_positions, ... |
ea9a7aefe9af765058e35d69e599491f367738a0bd228d181f1af5c581012a56 | Python | 7,689 | 259 | import numpy as np
from pyclamp.dsp.lsfunc import *
#-------------------------------------------------------------------------------
def intravel(X):
x = np.array(X.ravel(), dtype = int)
if x.ndim:
return x
return x.reshape(1)
#-------------------------------------------------------------------------------... |
0c533855f4e12c6c757847fc7ccbe7c88176b9f9eeee45083ec59df82d81ec7a | Python | 7,690 | 222 | import os.path as osp
import numpy as np
import torch
import pandas as pd
from torch_geometric.data import InMemoryDataset
from torch_geometric import data as DATA
from rdkit import Chem
from rdkit.Chem import MolFromSmiles
import networkx as nx
from rdkit import Chem
from rdkit.Chem import ChemicalFeatures
from rdkit ... |
fd6ade62936dad9d96b156685223376d405009361c1c94833c4cb2d279c16da7 | Python | 7,692 | 210 | # pylint: disable=invalid-name, line-too-long
"""Functions for extracting dataset features and labels"""
from importlib import import_module
import numpy as np
from scipy import stats
from sklearn.model_selection import StratifiedKFold
from omegaconf import OmegaConf, DictConfig, open_dict
def data_factory(cfg: Dic... |
1fb44cc9350a31ce26bad08b450d0d79bf27a4ca4dec43349e3dab7ce598c1e7 | Python | 7,693 | 204 | from __future__ import annotations
from dataclasses import dataclass
@dataclass
class InstanceRefinementConfig:
"""
Optional refinement of canonical 2D instance maps.
Public controls
---------------
remove_small
Remove statistically suspicious small objects after repair/splitting.
t... |
23a58728ed36c30921b1632509c8798080c2ca890ee9a0729f994bf445386651 | Python | 7,694 | 256 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 17 11:55:01 2025
@author: deeperthought
"""
GPU = 0
import tensorflow as tf
if tf.__version__[0] == '1':
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.gpu_options.visible_device_list="0"
tf.keras.backend.s... |
e62732f6f6d4da51462a4f4834ad548096483ad30db1271f0340f9ee25d452b4 | Python | 7,695 | 315 | # Benchmark suites from the Fast Downward benchmark collection.
def suite_alternative_formulations():
return ['airport-adl', 'no-mprime', 'no-mystery']
def suite_ipc98_to_ipc04_adl():
return [
'assembly', 'miconic-fulladl', 'miconic-simpleadl',
'optical-telegraphs', 'philosophers', 'psr-large... |
2ec9e58e79228f9fbf0d8886a72db02ca4b74b15d715a787b2789244f03c7cf9 | Python | 7,700 | 230 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
45189ced0e6ab7f26a989fb3c2623031b8526bad1044a545e6279a2ebfb08883 | Python | 7,700 | 268 | """Base jobs for espresso."""
from __future__ import annotations
from pathlib import Path
from typing import TYPE_CHECKING
from ase.atoms import Atoms
from ase.io.espresso import Namelist
from ase.io.espresso_namelist.keys import ALL_KEYS
from quacc.calculators.espresso.espresso import (
Espresso,
EspressoP... |
0394331ddddca4306a0c4afc3ba47a8eac0b2a2aa42e575ee958df81d417a394 | Python | 7,701 | 196 | from __future__ import annotations
import csv
import hashlib
import os.path
import re
import stat
import time
from io import StringIO, TextIOWrapper
from zipfile import ZIP_DEFLATED, ZipFile, ZipInfo
from wheel.cli import WheelError
from wheel.util import log, urlsafe_b64decode, urlsafe_b64encode
# Non-greedy matchi... |
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