sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b04332dedaa6e59b7c77feb526f26d8a91fbb6b155dba31af8e027bfbddc1bb5 | Python | 12,873 | 273 | """
Downstream task: ClinTox: Qualitative data of drugs approved by the FDA and those that have failed clinical trials for toxicity reasons
Dataset source: DeepChem
"""
import os, sys, argparse, time
import json
from tqdm import tqdm
from rdkit import Chem
import deepchem as dc
import torch
import torch.nn ... |
3cfd0e3fa076be221108ce37b2101d4a011077cf0389f4cfe76f73dacee64d9a | Python | 12,875 | 330 | #!/usr/bin/env python
from collections import Counter
from itertools import combinations
import numpy as np
import networkx as nx
from irescue.misc import get_ranges, getlen, writerr, run_shell_cmd
from irescue.network import build_substr_idx, gen_ec_pairs
from irescue.em import run_em
import gzip
import os
class Equ... |
cdf534b1a86509826c91c649395e0743743703133a99fbdaad4fe3d7fe51028a | Python | 12,875 | 313 | """
Unsupervised and deterministic classification of membrane-bound particles
Input: - The STAR file with the particles to classify
- Classification parameters
Output: - A set of STAR files with the new classes
- 2D rotational averaged around membrane normal exemplars and inter-... |
7d33655c8fa8e185e13bf2f9e5acafec04fdb2d84e2e4691d0bb3e200e85a326 | Python | 12,878 | 334 | #!/usr/bin/env python3
"""Compute segmentation metrics (Dice, HD95, volume, instance count) between
ground-truth and predicted masks, without a specialized third-party metrics
package (no medpy, MONAI, SimpleITK, or seg-metrics) -- just numpy/scipy/nibabel.
Ground truth is expected to be binary (a single "tumor" class... |
2210fd46fb6317ecc62d9bb4d595750e405fef54e4cb5435d33f31e783d99caa | Python | 12,879 | 334 | # -*- coding: utf-8 -*-
from __future__ import annotations
import os
from typing import Iterable, Optional, Union
import torch
from supar.utils.common import CACHE
from supar.utils.fn import download
from supar.utils.logging import progress_bar
from torch.distributions.utils import lazy_property
class Embedding(ob... |
1690c316f1bfed361b29ade59720498bef287886b503794ccb88d01d2c2f6789 | Python | 12,883 | 310 | """
Pre-processing for star_graph_batch.py of un-oriented membranes from TomoSegMemTV output
Input: - STAR file with 3 columns:
+ _rlnMicrographName: tomogram original
+ _rlnImageName: TomoSegMemTV density map output
+ _psSegImage: (optional) binary mask to foc... |
c20cc70e57e1bac79832c237481c6892a1bdde56082e8aae0870ae0e6568153e | Python | 12,883 | 314 |
# Import libraries
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import matplotlib.pyplot as plt
import os
import pickle
import numpy as np
from sklearn import metrics
from sklearn.mode... |
a6e2071ea9a99127f5161bad977203286a5d064790afb5cc9c35ec8f9debf292 | Python | 12,884 | 299 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 31 15:56:34 2023
@author: daltonm
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
import pickle
import dill
import os
import glob
import math
import re
import seaborn as sns
from scipy.ndimage import med... |
afb0bf6a6142280ce4256697c91dafe40869a6a19f1b52cb8bfdf112447c9ea1 | Python | 12,884 | 350 | from atom3d.filters import filters
import os
import torch
import numpy as np
import pandas as pd
import random
import torch
import torch_geometric as tg
# import e3nn.point.data_helpers as dh
from transformers import BertTokenizer, BertForMaskedLM
import os
from eudockscore.utils.interface import get_pair_interface_... |
af927e58ac20548bde1b20eabd4305f8e2b1705ce049b860753ac5e66947cb13 | Python | 12,885 | 196 | import argparse
import subprocess
import requests
import tarfile
import tempfile
import pandas as pd
import numpy as np
from functools import partial
from pathlib import Path
from tqdm import tqdm
import multiprocessing as mp
from fix_pdb import fix_pdb
MAX_DDG_STD = 1
FOLD2PDBS = [['1AO7_ABC_DE', '1B3S_A_D', '1E50... |
ce82791301c020212c2d19eedaa757c79dea420f7be9c5713eb13d50690895be | Python | 12,886 | 356 | """
Generate the "Color matplotlib" node from matplotlib's colormaps.
uv run docs/dev/colormap_node.py
uv run -m nodebpy.assets build && uv run -m nodebpy.assets dump
Writes ``molecularnodes/nodes/geometry/color_matplotlib.py`` with the ramp data
inline; build + dump turns it into the literal tree source that... |
ad4022b95f3b74a35dc9d1f28eedaa897485d652e2d716f9c9637a2c404ae8b2 | Python | 12,888 | 288 | # -*- coding: utf-8 -*-
import time
import numpy as np
import six
import tensorflow as tf
from tfsnippet.scaffold import TrainLoop
from tfsnippet.shortcuts import VarScopeObject
from tfsnippet.utils import (reopen_variable_scope,
get_default_session_or_error,
e... |
7d986dd9f7173048fb11b09381d0339f5d36c6b74e9c506dcaa0dfcdc33d8e0d | Python | 12,889 | 369 | import os
import torch
from utils.lr_scheduler import WarmupMultiStepLR
from config import *
import datetime
import torch.distributed as dist
from datasets.operators import result_compute, normalize_exp
from func_timeout import func_timeout
import random
import gc
def save_checkpoint(state, is_best, dump_path=None):
... |
c207779e2e7fd88a7021396ac6998f736e405e669ec9d149718dbd617112992e | Python | 12,892 | 350 | from atom3d.filters import filters
import os
import torch
import numpy as np
import pandas as pd
import random
import torch
import torch_geometric as tg
# import e3nn.point.data_helpers as dh
from transformers import BertTokenizer, BertForMaskedLM
import os
from eudockscore.utils.interface import get_pair_interface_... |
062ed1d596412e7a5a5a149ac5854ecb2c27e86df01a592c81b00d630119cdbb | Python | 12,897 | 301 | import os
import shutil
from multiprocessing import Manager
from typing import Any, Dict
from joblib import Parallel, delayed
from torch.utils.data import Dataset
from tqdm import tqdm
from torcheeg.io import EEGSignalIO, MetaInfoIO
MAX_QUEUE_SIZE = 1024
class MockLock():
def __enter__(self):
pass
... |
6a8368e0bf26502f1850d9d709beba3ee72258c676545a00438aa45ebcedf16f | Python | 12,899 | 386 | """
SimpleICPOptimization class.
"""
from __future__ import (
annotations,
)
from dataclasses import dataclass, fields
from typing import List, Optional, Tuple
import lmfit
import numpy as np
from . import corrpts, utils
class SimpleICPOptimization:
"""
Class for setting up and solve least squares
... |
a8181ca24d1b679d11d7bf4e93fd114cbe494336144844a84392f32d307bb9f4 | Python | 12,899 | 273 | """
Downstream task: ToxCast: Toxicology data for a large library of compounds based on in vitro high-throughput screening, including experiments on over 600 tasks
Dataset source: DeepChem
"""
import os, sys, argparse, time
import json
from tqdm import tqdm
from rdkit import Chem
import deepchem as dc
import... |
131f1bff371eeccf030f97a48723bc138c3708b222d5a5f02a790632127be854 | Python | 12,900 | 473 | #!/usr/bin/env python
# coding: utf-8
# ## Download and preprocess drug response data from GDSC
#
# * Drug responses come from processed data in [Sharifi-Noghabi et al. 2019](https://doi.org/10.1093/bioinformatics/btz318)
# * Cell lines are binarized into resistant/sensitive for each drug as described in [Iorio et al... |
12acffe1a4cdebfd9f44150fe1c5bf7d11888a3f8d98fae21382449f0fcf99cb | Python | 12,901 | 377 | import hashlib
import numpy as np
import re
import tifffile
from typing import List
from merlin.util import dataportal
# The following code is adopted from github.com/ZhuangLab/storm-analysis and
# is subject to the following license:
#
# The MIT License
#
# Copyright (c) 2013 Zhuang Lab, Harvard University
#
# Perm... |
eac90bea751c01d43d2198808c5e01319639b05ca1984e7b06261957f18a9f88 | Python | 12,902 | 323 | # 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... |
7eedaabb7d800c7209cfafbabbc887ddfb604148f8c1345e811b1081c2221bd2 | Python | 12,903 | 319 | import numpy as np
import pandas as pd
from data_loader import mapping_DK_vEK
from data_loader.voneconomokoskinas import VonEconomoKoskinas
from data_loader.ratio_exc_to_inh import ratio_exc_to_inh
# TODO __repr__(self)
class NeuronNumbers():
"""
Provides neuron numbers.
Parameters
-... |
d687d8ed85edb993a294bd411e122c05f61362c5a4202814cf808e1ca7f97e88 | Python | 12,905 | 288 | from itertools import chain
import numpy as np
from scipy.sparse import csr_matrix
from scipy.spatial import KDTree
from ..utils.misc import atom_number2name
from ..utils.supercell import minimum_supercell
from .matao import PairsInfo
def neighbors_csr(iat1: np.ndarray, iat2: np.ndarray, iorb2, n_nodes_uc, n_nodes_s... |
edd6460121e89d93f4d33decbb4678fca03b605a179889aef0b78bec9ebf7443 | Python | 12,912 | 332 | # 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... |
0c01a851209abaf770560a0eb206dde6b35a01a8e2e28d735db3461e8d5ac759 | Python | 12,915 | 283 | # set QT_API environment variable
import os
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
import control.utils as utils
from control._def import *
from control.core import *
import control.tracking as tracking
from queue imp... |
2b209a291ca2ffe0fa563b7dafdc47cc1c3828572c631e5c97d752846d9cb584 | Python | 12,917 | 362 | #
# 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,... |
1fa87f7b9b250c9789f195cfa02af0dd65b8fa08297ff97434cde7c2d507dac7 | Python | 12,918 | 340 | # 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... |
2e1461e1c52c4932abab5b561b87fbc08aca5a21a847921776c72132cf753caa | Python | 12,921 | 266 | import numpy as np
from scipy.special import expit as sigmoid
from typing import Optional
class NeuralMassModel:
"""
Refactored code for running the neural mass simulation from:
Cole MW, Ito T, Schultz D, Mill R, Chen R, Cocuzza C (2019).
"Task activations produce spurious but systematic inflation
... |
dc6274ed31d0a5d1ad21260c92938a9dce431921060683183593e9ff604f9e17 | Python | 12,938 | 310 | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
pd.options.mode.chained_assignment = None
import pyabf
import sys
import os
import datetime
from scipy.signal import find_peaks
from scipy.signal import peak_widths
from scipy import optimize
from... |
eee1fd56de4839985ee048b335d761599258b9f5d6f2ebd81d3e924835254c3b | Python | 12,939 | 230 | # A python script for managing the pre-requisites and steps involved in running TrAnnoScope pipeline.
from snakemake.utils import min_version
import yaml
import os
import sys
import argparse
import subprocess
import logging
# Set minimum Snakemake version
min_version('6.0')
# Configure logging
logging.basicConfig(le... |
580e3ecfb5a813c0d944519715f7fc8e75a51c8c441c51b9e8d7a3d2121e7de6 | Python | 12,943 | 326 | from matplotlib.cm import get_cmap
from IPython import embed
import sys
import matplotlib.pyplot as plt
import numpy as np
from clean_data import clean_velocity_data
import os
import matplotlib
regions = ["parenchyma", "grey_matter", "white_matter", "cingulum", "amygdala", "hippocampus"]
region_names = ["parenchyma", ... |
1789d00186b87cf70c5ce46e6797ce71e8bc4e4ed4508baca7cba140ad620e2c | Python | 12,945 | 312 | """Tests for regtools.atlas.contours functions.
Many of these were untested per audit; this file fills the gap.
Covers: load_parcellation_indices, get_default_target_region_ids,
build_parcellation_label_map, identify_contour_regions,
find_closest_correspondences, find_ordered_correspondences.
"""
import numpy... |
8a7509f800db289f6f65d77c39cb0e537cc7350bdeb3c83744c67bb1657118d6 | Python | 12,948 | 283 | import random
import numpy as np
from collections import defaultdict
from dimensions.common import BOWLS
from dimensions.bowls.dimensions import BOWL, BOWL_PROPERTIES
from learn_tools.collectors.common import INFEASIBLE, get_contained_beads, fill_with_beads, InitialRanges, \
create_table_bodies, randomize_dynamic... |
3940cadfe7e612545308b95d54cd5772a136e66a10b6f8c525b9c9085786f6c2 | Python | 12,949 | 382 | import os
import sys
import pdb
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import util_figures
import util
def make_plot_kell_like_recognition(
ax,
df,
key_task='word',
restrict_background_condition=None,
restrict_snr=[-9, -6, -3, 0, 3, np.inf],
... |
c3bf0aceaaae7a9f6af293240c33d223e7161f468ca0cc70e5a583e6c2c6d666 | Python | 12,950 | 302 | import os
import shutil
from multiprocessing import Manager
from typing import Any, Dict
from joblib import Parallel, delayed
from torch.utils.data import Dataset
from tqdm import tqdm
from torcheeg.io import EEGSignalIO, MetaInfoIO
MAX_QUEUE_SIZE = 1024
class MockLock():
def __enter__(self):
pass
... |
d49c5c8702b39310529fb47fa02135da806edde56ec74573771a2598869ddb83 | Python | 12,950 | 400 | from . import idnadata
import bisect
import unicodedata
import re
from typing import Union, Optional
from .intranges import intranges_contain
_virama_combining_class = 9
_alabel_prefix = b'xn--'
_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]')
class IDNAError(UnicodeError):
""" Base exception for all I... |
4bc7ec7f29ef0a322dcecb51f3829fa1bc10598474cbeed913fb6c53bbcdeced | Python | 12,951 | 321 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
class ChannelAttention(nn.Module):
def __init__(self, in_channelsnel, ratio=2):
super(ChannelAttention, self).__init__()
self.max_pool... |
f5d09aec970259706b7c652cbfb673bea9be32b7fbc9a2ba702e71473c778aa8 | Python | 12,951 | 357 | #
# distutils/version.py
#
# Implements multiple version numbering conventions for the
# Python Module Distribution Utilities.
#
# $Id$
#
"""Provides classes to represent module version numbers (one class for
each style of version numbering). There are currently two such classes
implemented: StrictVersion and LooseVe... |
9ee31ef6ae8c181ea6f408460f02fe578df636e9d7b3236a2e198e2cda433610 | Python | 12,954 | 292 | """Poisson-Gaussian mixture model for gRNA assignment.
Implements the model of ``crispat.ga_poisson_gauss`` (Velten group, https://github.com/velten-group/crispat).
For every guide, the log2 of its non-zero UMI counts is modelled as a mixture of a continuous Poisson background and a Gaussian on-target component with p... |
55217d51f3a4b5ae61f7b9ada0c20d385611e0a0ed35c63c4aaebf8b90d7c8be | Python | 12,965 | 358 | # -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Pr... |
765f239612b88145010e3e385e3d44845d059cf4b5ae04b828a1418b1b3a5ddf | Python | 12,966 | 265 | import torch
import torch.nn.functional as F
from .dcs import DCS_multi_lay_resolution
from .attention import Gate_Attention
class Stream1(torch.nn.Module):
def __init__(
self,
input_channels: int = 1,
kernel_size: int = 3,
embedding_dim: int = 128,
dcs_num_layers: int = 3... |
9c7dab8ca9ba2976831794dc7dfc074fe0e97fa104311b8008ece9d29ca30c25 | Python | 12,966 | 300 | # OWNER : SUBINOY ADHIKARI
# EMAIL : subinoyadhikari@tifrh.res.in
import sys
import os
import pickle
import numpy as np
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
from tensorflow.keras import Model
from tensorflow.keras import backend as K
from tensorflow.keras.optimizers import Adam
fro... |
7f90cbd4cd45bf1ae90be5f050ec5cc160ec14bf9c09239f8392202ae7a98078 | Python | 12,967 | 375 | """Utility functions for dealing with slabs."""
from __future__ import annotations
import logging
from copy import deepcopy
from typing import TYPE_CHECKING
import numpy as np
from pymatgen.analysis.adsorption import AdsorbateSiteFinder
from pymatgen.core.structure import Structure
from pymatgen.core.surface import ... |
9de4eeeeaec3051d25aa1a5a8e76ece45baa25afb91f44742bda065bce0e54e5 | Python | 12,968 | 389 | # 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... |
42ce196db0f4e28d681dfeb996d5ec1a0f8993a5c886c842e93675bfd2aa9314 | Python | 12,970 | 331 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
e95997af0895775d143fb61bbb9f6cc6778e4ea8db9620e38f6b8ccfa89a26d4 | Python | 12,971 | 378 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 24 23:36:06 2018
@author: Carlos A Ariza
"""
import base64
import numpy as np
import os
from urllib.parse import quote as urlquote
import dash
from PIL import Image, ImageOps
from flask import Flask, send_from_directory
from tflite_pred import tflit... |
a90c8f36a5ade3978c8a2bebc716a0ad6db2adc0ec16474e8856546e303f2b66 | Python | 12,974 | 422 | import numpy as np
import numba
from ...utils import model_utils as mu
def timeIntegration(params):
"""Sets up the parameters for time integration
:param params: Parameter dictionary of the model
:type params: dict
:return: Integrated activity variables of the model
:rtype: (numpy.ndarray,)
... |
f56c9b05729f96dd430b3ae4d2a2dee7da7f1cf344bffa4903c6069e0acf34a6 | Python | 12,975 | 342 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
44eb496b15085dd2886ac4f9d51f0168223f901260bd9acf819dec66c7c4869c | Python | 12,980 | 349 | #!/bin/env python3
'''
Create flowchart for PDL topology paper introducing Feynman diagrams.
'''
import numpy as np
import matplotlib.pyplot as plt
import ithildin as ith
import yaml
import sys
import pdlfeynman as fy
import zeus
from matplotlib.colors import ListedColormap, BoundaryNorm
from matplotlib.ticker import N... |
1ee436c74965c0b326d22b115541b347ca7ec2842af9d879a55d2eeb3738e9ce | Python | 12,984 | 324 | ##
# \file linear_operators.py
# \brief Implementation of linear operations associated with the physical
# slice acquisition model.
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date October 2017
# Import libraries
import itk
import numpy as np
import pysitk.simple_itk_helper as sitkh
... |
4b41baef8af2d68c8c928fc37aa2c5e148b6692b41c046af9a1e199807d0eeaa | Python | 12,985 | 346 | #!/usr/bin/env python
import sys, os
import logging
VERSION = "version 1.4 (20140115)"
# all is a keyword since Python 2.7
try:
all
except:
def all(iterable):
for element in iterable:
if not element:
return False
return True
# convenient functions
def myopen(fn... |
68a225244c6f080ef677bb5a3c58a0071927fb9b8b9c44db24042e007602660e | Python | 12,988 | 358 | # -*- coding: utf-8 -*-
#
# Test Syncopy's parsers for consistency
#
# Builtin/3rd party package imports
import os
import platform
import tempfile
import pytest
import numpy as np
# Local imports
from syncopy.shared.parsers import (
io_parser,
scalar_parser,
array_parser,
filename_par... |
3fd24688ae45bc5d87f41008a6f775388e7027792c280aa24fdc6f0e06c39049 | Python | 12,991 | 329 | """Custom pyqtgraph graphics items + Qt widgets for the CCF boundary editor.
These are intentionally self-contained - no dependency on the viewer
module - so they can be unit-tested or re-used independently:
* :class:`BrushCurveItem` - a draggable polyline contour with a
Wendland C² radius falloff (the soft-r... |
86bdeeeae69a6a0a81fa3c262894567ce591b0fda401497b8323ef392e4fb74f | Python | 12,997 | 271 | import torch
import torch.nn.functional as F
import numpy as np
import ABIDEParser as Reader
import argparse
import random
from torch_geometric.data import Data
from sklearn.model_selection import StratifiedKFold
from scipy.spatial import distance
from model_RGAT import RGAT
from sklearn.metrics import roc_au... |
8e57147f7fa4b91d91bedd9e2587e57638a97379ba8604d7fd28cc326e95a1c5 | Python | 13,001 | 312 | import argparse
import random
import time
from sklearn.svm import LinearSVC
import numpy as np
from sklearn.model_selection import StratifiedKFold, train_test_split
from sklearn.metrics import accuracy_score, cohen_kappa_score, f1_score, precision_score, recall_score, confusion_matrix
import os
import joblib
import h5p... |
c70ec631602e6ac785b7204c15e4e0ba4940fce289ac8d53c1ed3d4b3d893829 | Python | 13,001 | 355 | import numpy as np
import pytest
from SurvivalEVAL.nonparametric_estimator.single_event import (
CopulaGraphic,
KaplanMeier,
KaplanMeierArea,
NelsonAalen,
TurnbullEstimator,
)
@pytest.mark.parametrize(
"estimator_class, kwargs",
[
(KaplanMeier, {}),
(NelsonAalen, {}),
... |
d737380b16773a7e52c4272cb67aba1f502009b2ae59d293303480bf956ea4b4 | Python | 13,001 | 387 | # 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... |
98ed019097c7e171a4bf579bd9f268873c2d20b555d4fc0ff54fdc00e7616960 | Python | 13,011 | 397 | from __future__ import annotations
import Levenshtein
import numpy as np
from deepdiff import DeepDiff
from google.protobuf import json_format
from ord_schema import reaction_pb2
from pydantic import BaseModel
from .base import MessageType, DeltaType, CompoundLeafType
from ..utils import parse_deepdiff, flatten, find... |
0b152e5b218a665955cd67e88e3d9f4e7d8805558d54c92c01fc5a71bd9b1e42 | Python | 13,013 | 399 | import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
from numba import jit
# @jit()
def lifac(
time: np.ndarray,
stimulus: np.ndarray,
taum=0.01,
tref=0.003,
noisedv=0.01,
vreset=0.0,
vthresh=1.0,
taua=0.1,
alpha=0.05,
noiseda=0.0,
rng=n... |
77bf438f291caf6b6a10a68619584c1a0a6b2584ffdbfabaaef1dc7f76c90212 | Python | 13,020 | 351 | #================================================================================
#= Import
#================================================================================
import os
import time
tic = time.perf_counter()
from os.path import join
import sys
import zipfile
import matplotlib
import matplotlib.pyplot as p... |
858404f5a7f3d66a437e074ea066d459e76bc8b4d524e01d3579c82911569b7d | Python | 13,022 | 309 | import os
import logging
import platform
import warnings
import torch
import pystow
from MolNexTR.model import molnextr
# Suppress unnecessary warnings
logging.getLogger("absl").setLevel("ERROR")
# Control level of debug output
DEBUG_LEVEL = os.environ.get("MOLNEXTR_DEBUG", "INFO").upper()
# Filter specific PyTorch ... |
79cf7308adf354be18c391713793592836782cf8cbc045cd1f18ae04068a3653 | Python | 13,023 | 283 | """LANGUAGE MODEL selector and MODEL COUPLING (Neural Bypass list) controls.
The panel only displays what the engine reports and requests changes; the engine validates
and applies them between operations. Layer indices are zero-based.
"""
from __future__ import annotations
from PySide6.QtCore import Signal
from PySid... |
e65dc91e121d84140885734b1a147a617ff5326c22553f1f26bfb31cd6dff5d0 | Python | 13,028 | 348 | """
Introduction to the trainers Module
===================================
Welcome to the guide on TorchEEG's ``trainers`` Module! This module provides you with a suite of trainers, built on Pytorch-lightning, for
model training. These trainers are designed to handle a wide array of
models, ranging from discriminativ... |
6669d5a7fd9b4b9fe1e68e857109be2dad88065532f9397e0a1e95f8af457a83 | Python | 13,040 | 354 | from atom3d.filters import filters
import os
import torch
import numpy as np
import pandas as pd
import random
import torch
import torch_geometric as tg
# import e3nn.point.data_helpers as dh
from transformers import BertTokenizer, BertForMaskedLM
import os
from eudockscore.utils.interface import get_pair_interface_... |
28120bd334eea00a0ec09424f07eb6f58c0176b4ecaf54d5f8ac910591fe78f8 | Python | 13,043 | 340 | ##
# \file reconstruct_volume_from_slices.py
# \brief Script to reconstruct an isotropic, high-resolution volume from
# multiple motion-corrected (or static) stacks of low-resolution 2D
# slices.
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date March 2017
#
import o... |
d203cc52543aa7bf6bf26f7f2dab4ebbff5177f5a16e7a91c143de331d658a09 | Python | 13,043 | 448 | #!/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
import torch
from umap import UMAP
import pancancer_evaluation.config as cfg
from csd_simulations import simulate_csd
from preprocess_and_... |
4370f3540f7e9282b531834cee31201de485bb2c902aff0673f8e014a593ca7c | Python | 13,044 | 256 | import os
import pickle as pkl
from typing import Callable, Dict, Tuple, Union
import numpy as np
from ....utils import get_random_dir_path
from ..base_dataset import BaseDataset
from .faced import _EMOTION_DICT, _VALENCE_DICT
class FACEDFeatureDataset(BaseDataset):
r'''
The FACED dataset was provided by th... |
aee94fbb11364214254fb1ad659e95efe95bf3b2978b31df3038c266005b00ea | Python | 13,044 | 334 | #%%
# Imports
import os
import sys
import numpy as np
import pandas as pd
import datatable as dt
from pathlib import Path
from sklearn import metrics
from scipy.stats import zscore
from func.utils import filter_outliers, sort_files, transform2SD, cor_true_pred_pearson, cor_true_pred_spearman, prep_confs
from func.mod... |
ae673b9923fa417a42a0c5b3790345eade9620d49bc22e900acf1b9340ef1466 | Python | 13,047 | 313 | import torch.nn.functional as F
from typing import Tuple, Optional
import torch
import torch.nn as nn
from .fbcnet import VarLayer, MaxLayer, StdLayer, LogVarLayer, LinearWithConstraint, MeanLayer, swish, Conv2dWithConstraint
## CONV_SAME_PADDING
def _calc_same_pad(i: int, k: int, s: int, d: int):
return max((-(i... |
88106d6b4e815dd83f51bb6ba1cb4840892bdb5ddc26901116d5ba253b805297 | Python | 13,051 | 277 | """
Script to run pan-cancer classification experiments for all chosen combinations
of gene and cancer type.
Output files are identified by {gene}_{cancer_type} (in this order).
"""
import sys
import argparse
import itertools as it
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
... |
03a44baa3a1cca2047d930c8ca24997927f1119647de03ea9ac1fbe7d54bc074 | Python | 13,055 | 332 | """Widget tests for InputAtlasPreviewPanel (plain _qapp; pyqtgraph headless)."""
import numpy as np
import pytest
@pytest.fixture(scope="module")
def _qapp():
try:
from PySide6.QtWidgets import QApplication
except Exception as exc: # pragma: no cover
pytest.skip(f"PySide6 unavaila... |
bbddd59b87aac1b2241ee3181a51190c951c09d8b9c6dbc55e1f71feaa876bc9 | Python | 13,059 | 293 | import rdkit
import rdkit.Chem as Chem
from typing import List, Union, Tuple
import pandas as pd
import torch
import numpy as np
class MolecularFeaturizer():
"""
Featurizer to represent molecular datasets. Given molecules in SMILES format, it
creates a Pytorch with the following attributes:
- atoms: ... |
bcac8af0f34033320dbf9073c753329b46569020261eecb0bf774e78ed63a60e | Python | 13,059 | 240 | import os
import unittest
from pandas import DataFrame
from hed.models import DefinitionDict
from hed.models.hed_string import HedString
from hed.models.tabular_input import TabularInput
from hed.schema.hed_schema_io import load_schema_version
from hed.tools.analysis.event_manager import EventManager
from hed.tools.a... |
ec6f7406ce3d673d784a1a3191f61e8a169be45c96211ef2c7ff8cbf3117fdbb | Python | 13,060 | 266 | import copy
import unittest
from hed import HedString, load_schema_version
from hed.models.string_util import cleanup_empties, gather_descriptions, split_base_tags, split_def_tags
hed_schema_global = load_schema_version("8.4.0")
class TestHedStringSplit(unittest.TestCase):
@classmethod
def setUpClass(cls):
... |
985cccce9942bf44cc799291fa9788e45cb74dd4d4f4255d271b711a231c1b0a | Python | 13,061 | 290 | import torch
import torch.utils.data
import time
import os
import numpy as np
import csv
import dgl
from dgl.data.utils import load_graphs
import networkx as nx
from tqdm import tqdm
import random
random.seed(42)
from sklearn.model_selection import StratifiedKFold, train_test_split
class DGLFormDataset(torch.utils.da... |
02d11aff584c36eacb7143f46c9ea76ad12b056349b97a66933a1da095cdad20 | Python | 13,065 | 315 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
'''Description: Functions to pre-process spike trains via gaussian kernel and mean centering
Author: C. Pokorny
Created: 11/2022
Last modified: 10/2023
'''
import h5py
import json
import multiprocessing
im... |
4dd2e2f32c9bf0de39b715b68c5f424a76039bcd8132832e3990913cb87ac5ce | Python | 13,065 | 294 | import numpy as np
import torch
from typing import List, Union
def after_hook_normalize(
data: List[Union[np.ndarray, torch.Tensor]],
eps: float = 1e-6) -> List[Union[np.ndarray, torch.Tensor]]:
r'''
A common hook function used to normalize the signal of the whole trial/session/subject after ... |
ee00a88682e2f874a44f6b0505792fd8d7e156a2929c1257567a95328c88aad5 | Python | 13,065 | 292 | import numpy as np
from scipy.sparse import csr_matrix
from .. import config as CFG
from ..utils.supercell import minimum_supercell
from .matao import PairsInfo, MatAO
class OrbInfo:
def __init__(self, aodata, structure=None):
if structure is None:
self.structure = stru = aodata.structure
... |
2f0d3412b67b5f7e093f04fc7a4fe063f6a9a4b96148a662241fe4eb2761e798 | Python | 13,076 | 268 | import torch
import torch.nn.functional as F
from .dcs import DCS_multi_lay_resolution
from .attention import Gate_Attention
class Stream1(torch.nn.Module):
def __init__(
self,
input_channels: int = 1,
kernel_size: int = 3,
embedding_dim: int = 128,
dcs_num_layers: int = 3... |
9c1c30facef8e99bcc6b71b6abfee81eb2e2bb9f15abc9837f2e334391e7c78b | Python | 13,076 | 343 | import tensorflow as tf
import numpy as np
import os
import datetime
import random
from tensorflow.keras import losses
from shutil import copyfile
import tensorflow_addons as tfa
import models
import utils
import data_augmentation
def run_once(f):
"""
Wrapper for functions that should only run once every run... |
154f2401a9e902f69a79c05b4594ef67b95ca31c415eae7f9d3b9fc0ec995178 | Python | 13,077 | 376 | """distutils.command.config
Implements the Distutils 'config' command, a (mostly) empty command class
that exists mainly to be sub-classed by specific module distributions and
applications. The idea is that while every "config" command is different,
at least they're all named the same, and users always see "config" i... |
507aa1acdf4b4a9b340d9f4a39d8ac192bfbbfb1e9300508ad1d4bc561d4e7b8 | Python | 13,077 | 305 | import os
import shutil
from multiprocessing import Manager
from typing import Any, Dict
from joblib import Parallel, delayed
from torch.utils.data import Dataset
from tqdm import tqdm
from torcheeg.io import EEGSignalIO, MetaInfoIO
MAX_QUEUE_SIZE = 1024
class MockLock():
def __enter__(self):
pass
... |
652b96c41819ee85c4663464d9599e042c6c860ebfd6f6f32359563b4345d6ac | Python | 13,080 | 397 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from plot_methods import plot_signal_sum, calc_signal_power, plotting_correlation
from cellsim16popsParams_modified_spontan import multicompartment_params
import analysis_params
import plotting_helpers as phlp
from hybridLFPy import CachedNetwork, GDF
import h5py
import os
... |
e76557c90c0ac0d4b121893e308d9111489959d213d45a8de1b0831b8bfb5356 | Python | 13,083 | 323 | """Educational help content for registration options (Qt-free).
One OptionHelp per selectable value, grouped by GUI control. Rendered into
tooltips and a help dialog by regtools.registration.gui.help_widgets. Kept
Qt-free so it imports headlessly (tests, CLI, docs). Option keys mirror the
combo `data` keys in reg... |
ba67f6ab7e52a2a848f55a38e960bcfd19eac4b539780e1935d674a00e2a811f | Python | 13,085 | 353 | #================================================================================
#= Import
#================================================================================
import os
import time
tic = time.perf_counter()
from os.path import join
import sys
import zipfile
import matplotlib
import matplotlib.pyplot as p... |
cdb591db66c828e73dfeebf93e4f6d960771e258499e84b72711475db09e69e4 | Python | 13,088 | 279 | from __future__ import division
import logging
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from func_unsupervised_CC import fit
from IterativeMethod import iterativeCC
"""
Created on Sun Mar 10 17:16:12 2019
@author: Hannah Choi
"""
"""
This code genereates shuffled versions o... |
649f416bb00e03d81b1e97591d60df225dabd79d8e12ba061d97b9b7e9f5985a | Python | 13,089 | 355 | """
PCA and related signal decomposition methods for tedana
"""
import logging
from numbers import Number
import numpy as np
import pandas as pd
from mapca import ma_pca
from scipy import stats
from sklearn.decomposition import PCA
from tedana import io, metrics, utils
from tedana.selection import kundu_tedpca
from t... |
89d904f61af258d1eb334a67a9d7c554b9d7587bbd0de100d0cc5dad5c5af59b | Python | 13,092 | 372 | import re
import types
import inspect
from collections import defaultdict
from contextlib import contextmanager
from decorator import decorator
class _MetaContainer(object):
"""
Meta container that maintains meta types about members.
The meta type of each member is tracked when a member is assigned.
... |
42be2bd11b2199bc366bb0ccfc9619c39979c21c85e69fe68bb490e71a4f3f7b | Python | 13,105 | 263 | '''
Here we compare the ML regression on the first part of the samples to the regression on the second part of the samples,
where the even is uut of the tableau (i.e. its info cannot be conveyed by self pulsing)
'''
import numpy as np
from matplotlib import pyplot as plt
# import scipy.io as sio
# load data
... |
70d619c354f3677152fe4a7e4d04a9aeccc75b8dd88f01d4f3a2c07df27601da | Python | 13,107 | 288 | from __future__ import unicode_literals, absolute_import
import sys
from . import _option_parsers
from ._version import TOMBO_VERSION
import argparse
class SubcommandHelpFormatter(argparse.RawDescriptionHelpFormatter):
def _format_action(self, action):
parts = super(SubcommandHelpFormatter, self)._format... |
3fa7ab286d998a1f5bda378a129dff81c10dc727a05ea3d2b72de3d140e46dca | Python | 13,108 | 284 | import numpy as np
from scipy.integrate import odeint
def mechanotransduction_ode_calc(timeSpan, stiffness, geoParam):
# # YAP/TAZ and MRTF mechanotransduction model, originally implemented in
# # VCell
# #
# # input:
# # timeSpan is a vector of start and stop times (e.g. timeSpan = [0 10.0])
... |
31177da3cc5aa054667cec7b8bc266bfc18d6849513ad0184ac4c05faac08348 | Python | 13,111 | 367 | from __future__ import division, unicode_literals, absolute_import
from builtins import int, range, dict, map, zip
import sys
# Future warning from cython in h5py
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import h5py
import numpy as np
from operator import itemgetter
if sys.ve... |
67d1b2a36ccc59a5e8c9f2e79cf1ceec514723ed5d2c9cce4c22c0ae69e47439 | Python | 13,112 | 361 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: emma
"""
import os
import pickle
import cv2
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from datagenerator_3d import DataGenerator
import pandas as pd
import keras.backend as K
from pathlib import Path
import SimpleITK as sitk
f... |
bc9a35b8842bd3f546e833be522238d39335d591a7ff40cfd075882eb83785c9 | Python | 13,113 | 355 | from atom3d.filters import filters
import os
import torch
import numpy as np
import pandas as pd
import random
import torch
import torch_geometric as tg
# import e3nn.point.data_helpers as dh
from transformers import BertTokenizer, BertForMaskedLM
import os
from eudockscore.utils.interface import get_pair_interface_... |
4afc091c73daebd9e1e8493dc90cfd6323f22aa32a61034ff7d86d66f038f8de | Python | 13,115 | 344 | # 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... |
52ea444acd087848d2fbcb9b0a464c76b55dea098fdf3b0f549b3595cc3985b1 | Python | 13,117 | 395 | from collections.abc import Callable
from itertools import chain, starmap
from typing import Protocol, cast
from elasticai.creator import ir
from elasticai.creator.graph import dfs_iter
from elasticai.creator.ir2vhdl import (
DataGraph,
IrFactory,
Node,
Registry,
Shape,
type_handler,
)
from ela... |
8a2a57a09f6db10d4c097685a2dc46fe4cf79eb8000e16f42ac99bbf62c43d1c | Python | 13,131 | 354 | import torch
from torch_geometric.nn import MessagePassing
from torch_geometric.utils import add_self_loops, degree, softmax
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from loader import BioDataset
from dataloader import Da... |
0fdcd3e814754ad3fb713a1c3aee0b26fd066bdae8900de0ef3cf1981f8b8ac0 | Python | 13,132 | 452 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.datasets import make_classification
from sklearn.decomposition import PCA
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.metrics im... |
522cf32390443ea150af51829f2b584ca6087ef8cea4c961b2b2872afe95a64b | Python | 13,133 | 343 | # 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... |
fc8a507dcf9f6d0f5983b52a17ca31cd2fbef0f757de3db97fac1449ab3ece4b | Python | 13,133 | 212 | '''
This script is used to dock compounds using DiffDock.
NOTE: Currently this script requires that the argument --protein_ligand_csv is used.
'''
import copy
import os
import torch
from argparse import ArgumentParser, Namespace
from rdkit.Chem import RemoveHs
from functools import partial
import numpy as np
import pa... |
efd69b4929c75f5df61ff12b9b64397ac58735ad4292901e394a9fa81f2557a1 | Python | 13,134 | 359 | import h5py
import numpy as np
from scipy.ndimage import distance_transform_edt
from wsilearn.utils.cool_utils import *
from wsilearn.utils.df_utils import print_df, df_merge_check
from wsilearn.utils.files_utils import FilesInfo
from wsilearn.utils.path_utils import PathUtils
import pandas as pd
from wsilearn.utils.... |
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