sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
15a8e21afcbb5c4990971f2ea70bae228cfd5c2332e3df37551b9c40090c5117 | Python | 11,221 | 253 | import json
import logging
import os
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch, mock_open, MagicMock
from urllib.parse import quote
import pytest
import NDATools
from NDATools.Utils import parse_local_files, sanitize_file_path, check_read_permissions, \
sanitize_window... |
700f9b4a29e34b278b61d7127488d9812e3f294971ce790e2f13f6997d20d1c1 | Python | 11,221 | 301 | # -*- coding: utf-8 -*-
from __future__ import annotations
import os
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union, Sequence
import nltk
from supar.models.const.crf.transform import Tree
from supar.utils.logging import get_logger
from supar.utils.tokenizer import Tokenizer
from supar.util... |
3a008c8815e07ac483129a066bcc44b1218174eb2baeba6d2386103f9b0bb126 | Python | 11,223 | 424 | import click
import numpy as np
import pandas as pd
import random
import os
from sequence import SeqDreamChallange1D
from model import (
standard,
simplified,
ResNet1D_Classification,
ResNet1D_Regression,
ResidualUnit1D_BN,
ResNet1D_Classification_medium,
ResNet1D_Regression_medium,
R... |
8c7ae4051e5fa717cc22d96681bc658b9cb986718e9481c37892d9356e605771 | Python | 11,224 | 260 | # -*- coding: utf-8 -*-
#!/usr/bin/env python
# Aplicación para comprobar diferentes parámetros de la CNN.
# Se pueden modificcar los siguientesi parámetros (los valores indicados son de la configuración por defecto):
import sys
# Configuración base de la CNN
# 0. Dialecto
# 1. numCapas=2
# 2. activacionCapaSalida="so... |
4f10c0077e829f553c415bd0710021ba3821bdd02cf7c072f0bf29c5de338d23 | Python | 11,231 | 259 | import os
import argparse
import lxml.etree as ET
import math
import numpy as np
import carla
from utils import ALL_TOWNS, \
parse_annotations_file, interpolate_trajectory, scan_route_for_scenarios
ID_START = 0
SAMPLING_DISTANCE = 30
PRECISION = 2
def main(args):
route_id = ID_START
client = ... |
8cbf8239481525ed53aaa9674747a5b7f7594e210097b13acf09660630d42f92 | Python | 11,231 | 178 | """
Main run function for finding synapse cluster on assembly neurons
last modified: András Ecker 07.2023
"""
import os
import logging
from tqdm import tqdm
import numpy as np
from assemblyfire.config import Config
import assemblyfire.utils as utils
from assemblyfire.assemblies import AssemblyGroup
from assemblyfire.... |
632ad982c799f5f20a041b7f25a0ee262d8815d710d44051b99289627eaf28c2 | Python | 11,233 | 309 | # 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... |
32c75e3861061677cd62d9f6c86736cbd3a446a7ba7a505925717cb44dbeb505 | Python | 11,238 | 284 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from torch_scatter import scatter
from torch_geometric.utils.num_nodes import maybe_num_nodes
from torch_geometric.nn import GATConv
from utils.common import Device
from typing import Optional, Tuple
from t... |
4ea6d5da2997a7e1cf1b9b01dd4eb06314af5c5454cd296e1b08d69f6dfdb660 | Python | 11,246 | 236 | options = dict(
model_extensions=[
'h2o.model.extensions.Trees',
],
)
supervised_learning = False
def update_param(name, param):
if name == 'stopping_metric':
param['values'] = ['AUTO', 'anomaly_score', 'deviance', 'logloss', 'mse', 'rmse', 'mae', 'rmsle',
'auc'... |
537a7a1bae99476a25a93409d892d3416c458239553b47cc0972bfde08606497 | Python | 11,247 | 306 | # Node-group asset "Animate Action" (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_CHECKIN... |
70353269c7382767c5e57677e19264fb988f9ed88797197f4386300a95ef5407 | Python | 11,248 | 257 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class GradientBlender:
'''
Implements gradient blending outlined in What Makes Training Multi-modal Classification Networks Hard? https://arxiv.org/pdf/1905.12681.pdf , Facebook AI
Usage:
This class forms a w... |
c62920f61afacfbcc8d340dccab1b63f0e315bb1b0675c5455d999cb23265e07 | Python | 11,257 | 279 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# 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... |
bd6883b3486394206367f8385eccec87dee520ff4ce3f25a2d0e8c090dba5bd5 | Python | 11,266 | 318 | import io
import json
import logging
import os
import re
from contextlib import contextmanager
from textwrap import indent, wrap
from typing import Any, Dict, Iterator, List, Optional, Sequence, Union, cast
from .fastjsonschema_exceptions import JsonSchemaValueException
_logger = logging.getLogger(__name__)
_MESSAGE... |
5037f6c8bd088ce2fecbb3c304c0ee8ca991e65f4ddd1557295d6ddfcd4868dc | Python | 11,267 | 298 | # 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... |
b269bef28d2304a5a73bdefff648acb7c65b7c8bffc562fe663a36dcbdc7a81a | Python | 11,267 | 226 | """Qt UI plugin system: docks, events across threads, lifecycle, layout, failures, end-to-end plugin."""
import json
import sys
import types
from pathlib import Path
from types import SimpleNamespace
import numpy as np
import pandas as pd
import pytest
import shiboken6
from PySide6.QtCore import QCoreApplication, QEve... |
f203838da3900007b2c194155ba742aa5bd307f62994d7ae3dbeaea9f1adf846 | Python | 11,269 | 448 | # Node-group asset "Menu Atom Name" (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_CHECKIN... |
f22abcff2942335f48c3df98ca74e3e3d79a522341e17637f45a4a505b6b0c25 | Python | 11,271 | 208 | """
READOUT_COMPARE_D04_ARMC_STRAT.py - written 2026-09-16. Closes V-47 / D-04.
WHAT THIS IS AND WHY IT IS A SEPARATE FILE.
V-47 ends: *"the V-50 construction (size-stratified decile matching, 0 of 18 draws) is
the cleaner one and is what should be quoted. To close this properly: re-run
READOUT_COMPARE_D04_AR... |
8b808630fa49490e3e9c5b3515762870c5ffbfa52c05d0cdfbdc1bd8717146b7 | Python | 11,272 | 340 | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 14 10:17:02 2020
@author: JiaLi
"""
import numpy as np
import networkx as nx
from scripts import basic_comp as bcomp
# from adjactent matrix to graph
def convert_from_adj2networkX(A,weighted=True):
edges_ind = np.where(A>0)
num_edges = len(edges_ind[0])
G =... |
5a7710ff337d675d3b9ec0ddb357b6e2a73bdb608da1d95149a073ae1e303298 | Python | 11,275 | 269 | #!/usr/bin/python
# -*- coding:utf-8 -*-
import logging
import os
import time
import warnings
import torch
from torch import nn
from torch import optim
import numpy as np
import models
import datasets
def apply_dropout(m):
if type(m) == nn.Dropout:
m.eval()
class train_utils(object):
def __init__(se... |
f0903e8736a83eab7353072eb3bf93b84f8f8d4f97ac4c9523c4325f11b58d9e | Python | 11,276 | 259 | # Copyright (C) 2019 Computational Science Lab, UPF <http://www.compscience.org/>
# Copying and distribution is allowed under AGPLv3 license
# This script defines various functions and classes for generating molecular compounds from SMILES representations.
# It includes SMILES decoding, filtering valid molecules, sequ... |
b55de68eb57760734093dc1c653d2bbda66bd1eec72502419cffdef11a3de46b | Python | 11,282 | 183 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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
#
# ht... |
dc1efb435cbf3778dbac566728ce3345ddc14211c907866764616339632da6c7 | Python | 11,285 | 214 | import unittest
from hed import HedTag, load_schema_version
from hed.errors import DefinitionErrors, ErrorHandler, ErrorSeverity, ValidationErrors
from hed.models.definition_dict import DefinitionDict
from hed.models.hed_string import HedString
from tests.validator.test_tag_validator_base import TestHedBase
# The nam... |
6e42ed6767649632c258c8b2a6982f6db1ae305fd6200785dbc85a4d6a91f303 | Python | 11,290 | 272 | # -*- coding: utf-8 -*-
from sklearn import base
import lib.spectgr
import lib.spectgrList
import os
import numpy as np
from keras.utils import to_categorical
import lib.tensores as tensores
import tensorflow as tf
import keras.losses as losses
import keras.optimizers as optimizers
from sklearn.model_selection import K... |
1dd30be6a132b169b4dd393efc6adf5650117888c5f93e5723af5a678f5893fc | Python | 11,294 | 284 | from collections import Counter
from pddlstream.algorithms.common import compute_complexity
from pddlstream.language.constants import get_args, is_parameter, get_prefix, Fact
from pddlstream.language.conversion import values_from_objects, substitute_fact, obj_from_value_expression
from pddlstream.language.object impor... |
703d52aa412d86d6dcab9f0db399ceadb456ddc027594b3973fcd051226d5d5f | Python | 11,294 | 293 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 17 11:45:50 2021
@author: mpolonenko
"""
import numpy as np
from expyfun import ExperimentController, decimals_to_binary
from expyfun.visual import ProgressBar
from expyfun.stimuli import TrackerDealer, TrackerUD
from expyfun.io import read_wav, rea... |
f890a9156e88ffcea6d032140967b0ba40b6170a51600fe949947a26b2d790ac | Python | 11,296 | 361 | import os
import sys
import platform
import numpy as np
from time import time
from pyclamp.dsp.lsfunc import *
from pyclamp.dsp.dtypes import *
from pyclamp.gui.display import DISPLAY
PLATFORM = platform.platform()
CONSOLECOL = {'w':97, 'm':95, 'r':91, 'y':93, 'g':92, 'c':96, 'b':94, 'k':30, 'e':1,
'W':9... |
7b0975efa3d5bbd1d221eada59e835e5ef6d99e81366d672971cfcfe025423a0 | Python | 11,299 | 338 | """
Estimate T2 and S0, and optimally combine data across TEs.
"""
import argparse
import logging
import os
import os.path as op
import numpy as np
from scipy import stats
from threadpoolctl import threadpool_limits
from tedana import __version__, combine, decay, io, utils
from tedana.workflows.parser_utils import is... |
3886adc4eae4d931fb65b6bcf9bf0d89623e7c2cb1073e54eaf7d37f325db019 | Python | 11,303 | 308 | # Node group "Curve Split Splines" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are rege... |
c74996fa920fa1d24ce2bcba82b82698bae5f15669f7d92a72676705eef46180 | Python | 11,303 | 376 | from typing import Any, Generic, List, Optional, TextIO, TypeVar, Union, overload
from . import get_console
from .console import Console
from .text import Text, TextType
PromptType = TypeVar("PromptType")
DefaultType = TypeVar("DefaultType")
class PromptError(Exception):
"""Exception base class for prompt relat... |
8c0be1c22ffdbacc60e3a58daa810a888d128009bd057f5ce29b0d4c87424eeb | Python | 11,304 | 225 | import os
import sys
import argparse
import copy
import glob
import json
import pdb
import numpy as np
def prepare_localization_example(example,
nervegram_slice_length=10000,
signal_slice_length=50000,
rate_in=44100,
... |
4208dfbefaeb43a372ee92ac3d4e8b1a0e08bd042e7ef1e67956480f71432009 | Python | 11,307 | 256 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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
#
# ht... |
9fcff99f8c0e517747f43e41132711ccde209427950ef0b71a21c0a6adcfff8b | Python | 11,309 | 264 | '''
author: matthias wilms
'''
import numpy as np
import scipy as sp
import kernels
import scipy.integrate as integrate
import scipy.interpolate as interpolate
import scipy.sparse.csgraph as csgraph
from numpy import matlib
def mean_error_2d_contour(gt,pred):
return np.mean(np.sqrt(np.square(gt[0::2,:]-pred[0::2,... |
6bba91bd15354f7ae034a76b3dfbda852b9999d19b6a7e69ff3fa64f3c9656fa | Python | 11,315 | 345 | #!/usr/bin/env python
# coding: utf-8
# ### TCGA <-> CCLE mutation prediction: LASSO parameter range experiments
#
# Here, we're interested in:
#
# * Training mutation status models on data from TCGA (human tumor samples) and testing on data from CCLE (cancer cell lines), or
# * Training mutation status models on da... |
e5322739c75390c89fbe370795355f96128347a9d0698903177c758154219bbf | Python | 11,315 | 312 | import os
import time
import numpy as np
import torch
import torch.multiprocessing
import torch.multiprocessing as mp
from src import config
from src.Mapper import Mapper
from src.Tracker import Tracker
from src.utils.datasets import get_dataset
from src.utils.Logger import Logger
from src.utils.Mesher import Mesher
... |
503ef5df0412dcaacd0f0b9b6ab8ff457e032073c92212bf513a18dbf0c57abe | Python | 11,323 | 377 | # levenshtein.py
import sys
import dnaio
from itertools import combinations
from polyleven import levenshtein
from fba.utils import open_by_suffix, get_logger
logger = get_logger(logger_name=__name__)
# In-memory implementation of TinyFastSS
# https://github.com/fujimotos/TinyFastSS
def indexkeys(word, max_dist)... |
491b3f642a5706e4aab414319d059c1bcba8ee7ede87905bd27bcc3f7934d861 | Python | 11,328 | 346 | from __future__ import annotations
import io
from unittest.mock import patch
from colorama import Fore
from bayes_opt import BayesianOptimization
from bayes_opt.logger import ScreenLogger
def target_func(**kwargs):
"""Simple target function for testing."""
return sum(kwargs.values())
PBOUNDS = {"p1": (0,... |
dc9fa9e8e66792e8389cd158b7ec84bb62fbba86aef58e10ca0465e2798d710f | Python | 11,333 | 368 | # 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... |
d17c7c10b61ed0ad213701f1b714f9855bf3c34ce34d11341b1ccbd100c60507 | Python | 11,340 | 379 | # 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... |
fa54e8dae5664a5b066edfb35bf528f7e5fc9ec21ed50c451481135c8f675ca9 | Python | 11,342 | 264 | """
AMBIGUITY_REPRODUCIBILITY.py - written 2026-09-17.
THE QUESTION. The transmitter classifier outputs a distribution over six transmitters and
everyone downstream keeps the argmax. This project has spent a month on what the discarded
uncertainty costs. This script asks the opposite question:
is the SECOND... |
2ef93190bd0cb1c81429d17c33ff15563494def54eba712cc809be36d5251e3f | Python | 11,344 | 254 | import io
import json
import os
import unittest
import numpy as np
import pandas as pd
from hed.errors import HedFileError
from hed.models.sidecar import HedString, Sidecar
from hed.models.tabular_input import TabularInput
from hed.schema.hed_schema_io import load_schema_version
from hed.tools.analysis.event_manager ... |
5bb11d24e075283bc4bd894f087c181d61cdf5dbad575e8b8f19727b2b3b35c7 | Python | 11,346 | 336 | from typing import Optional, Union, List
import numpy as np
import inspect
from sella.peswrapper import PES, InternalPES
from .stepper import get_stepper, BaseStepper, NaiveStepper
from sella._constants import _LSTSQ_RCOND
class _CoordinateSelectionTranspose:
def __init__(self, selection):
self.selecti... |
941ff2f2acbc6fda91964f2470441763548ea28a627b5b0661c78525b9446ced | Python | 11,349 | 225 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Compute the logistic weights of priors and sensory likelihood at each trial around the change points.
This script gather, for each subject, trials with the same distance to a change point
and compute for each distance, a logistic regression of the sensory likelihood... |
14f958a3235a5d8c2daf6eb5aace3c4ba1f5d3f6cce65a3ab055b1c0feb63a98 | Python | 11,350 | 282 | from .nbo_data_point import NboDataPoint
from .tools import Tools
from .enums.nbo_type import NboType
class QmData():
"""Class for storing relevant QM data."""
def __init__(self,
id: str,
stoichiometry: str,
n_atoms: int,
atomic_numbers: li... |
f55a99296e890948ab3931b5aa7d4da5a1379a6963f320f151a28896a59a1d5a | Python | 11,351 | 293 | """
Generates a ListTomoParticle object from a input STAR file
Input: - STAR file for pairing STAR files with particles and particles shapes
Output: - A ListTomoPaticles pickled object for every STAR file row
"""
################# Package import
import os
import numpy as np
import scipy as sp
import ... |
71ca756c355ffe99641cf3c22a09a23376b9f78c35552b5afc2af4814c6cd929 | Python | 11,354 | 256 | """Error codes used in different error messages."""
from enum import IntEnum
class ErrorSeverity(IntEnum):
"""Severity codes for errors."""
ERROR = 1
WARNING = 10
class ErrorContext:
"""Context this error took place in, each error potentially having multiple contexts."""
# Use this one to dis... |
af7c0a9c578e7039b0c5225c543905dc10cf08ccd4dc4005e70f1ee416c6c9ab | Python | 11,359 | 248 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 21 15:00:46 2021
@author: CY
"""
import torch
from torch.utils.tensorboard import SummaryWriter
from typing import List, Callable, Dict
import time
from tqdm import tqdm
from nnunet.training.ssl import eval_metrices
import copy
from pathlib import Path
DIR... |
a7692898ae213cdd163fae2c82be04d262f271d04d77ef493a0412f642ba6e6d | Python | 11,365 | 294 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 17 11:45:50 2021
@author: mpolonenko
"""
import numpy as np
from expyfun import ExperimentController, decimals_to_binary
from expyfun.visual import ProgressBar
from expyfun.stimuli import TrackerDealer, TrackerUD
from expyfun.io import read_hdf5 # ... |
eabf1491820f696b7b263e62ab8bf588e29107c28acb9172f85f4be658b0df34 | Python | 11,366 | 230 | import argparse
import random
import sys
from timeit import default_timer as timer
import numpy as np
import torch
from scipy import stats
from torch.utils.data import DataLoader
from utils import data_setup, model, engine, utils, loss_function, data_preprocess, augmentation_utils
if __name__ == "__main__":
# se... |
ab6a5e78869204b09473b0dc4b9d1068ac8969537e65b330267aa3dd53f1c5ab | Python | 11,367 | 350 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : common_utils.py
# Author : Yufeng Liu
# Date : 2022-09-12
# Description :
#
#==================... |
532eae0b29f74bbc2a1d907097febd33f0d3278c3644d2bcd956878858c6998b | Python | 11,369 | 302 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Marius Pachitariu.
"""
import matplotlib.pyplot as plt
from matplotlib import patches
import os
import numpy as np
from fig_utils import *
ccolor = [[0,1,0], [0,0,0.8]]
def panel_neuron_pos(fig, grid, il, yratio, xpos0, ypos0, isort... |
19a50a0edd1f39c0cedab8d82f36117b228f8f8093f4c6751be71df5b5ddb005 | Python | 11,370 | 351 | from functools import partial
import numpy.linalg as npla
from autograd import builtins
from autograd.extend import defjvp, defvjp
from . import numpy_wrapper as anp
from .numpy_wrapper import wrap_namespace
wrap_namespace(npla.__dict__, globals())
# Store the primitive-wrapped norm for internal use; see numpy_wr... |
5bb232f23ef0453fab329c6dfd97083bf3691810d43165100550467ed4d6a5ba | Python | 11,370 | 292 | import numpy as np
import probayes as pb
import scipy as sp
import scipy.stats
try:
import scipy.misc
comb = scipy.misc.comb
except AttributeError:
import scipy.special
comb = scipy.special.comb
import tqdm
import multiprocessing
import h5py
from joblib import Parallel, delayed
NEARLY_ZERO = 1e-300
MINIMUM_GAM... |
70d5ea7ae37f9fd6997d4b86c8da1b986a09f7afe5c228fd065abf8ea8047a4a | Python | 11,370 | 305 | import os
import io
import re
import json
import tarfile
from pathlib import Path
from collections import OrderedDict
import requests
from requests.adapters import HTTPAdapter, Retry
TCGA_API_BASEURL = 'https://api.gdc.cancer.gov'
TCGA_CASE_ENDPOINT = '/'.join([TCGA_API_BASEURL, 'cases'])
TCGA_PROJECT_ENDPOINT = '/'.j... |
ae592ebe5e61e53a4a1108881489dc3eb26200f76216303af045d7d259c9b637 | Python | 11,370 | 281 | """Test the find_noisy_channels module."""
import numpy as np
import pytest
from numpy.random import RandomState
from pyprep.find_noisy_channels import NoisyChannels
from pyprep.removeTrend import removeTrend
# Set a fixed random seed for reproducible test results
RNG = RandomState(30)
# Define some fixtures and u... |
5a147f6f26d871a7c89f7fd9f89c278f259969851a5e7dd8e36bfb721025f68a | Python | 11,371 | 289 | # -*- coding: utf-8 -*-
import numpy as np
import tensorflow as tf
from six.moves import xrange
from .. import _logging as logging
from .core import *
__all__ = [
'transformer',
'batch_transformer',
'SpatialTransformer2dAffineLayer',
]
def transformer(U, theta, out_size, name='SpatialTransformer2dAffin... |
e5e15ee0b7b996f6a43ebf7fc58d3519ee13413f7af2b70797da4fa2349f73c8 | Python | 11,374 | 285 | import torch
import torch.nn.functional as F
from prettytable import PrettyTable
import numpy as np
import random
from sklearn import metrics
import wandb
from tqdm import tqdm
from utils import *
import wandb
import pickle
from sklearn.metrics import precision_recall_curve
def normalized_laplacian(A):
"""
Inp... |
0f0f6b4057674a04e15c7b3de898d09dfaac6f9761639d1ffec1394587a12ea6 | Python | 11,376 | 299 | import logging
from typing import Any, Dict, List, Tuple, Union
import pytorch_lightning as pl
import torch
import torch.nn as nn
import torchmetrics
from torch.utils.data import DataLoader
from torchmetrics import MetricCollection
_EVALUATE_OUTPUT = List[Dict[str, float]] # 1 dict per DataLoader
_log = logging.get... |
4fb94a57de2b79b2137e5f2b7500e62907f84d28d2e62ebedc70c257348ca725 | Python | 11,377 | 256 | import math
import numpy as np
from pybullet_tools.utils import clip, INF, \
waypoints_from_path, adjust_path, get_difference, get_pairs, get_max_velocities, get_duration_fn, wait_if_gui
#ARM_SPEED = 0.15*np.pi # radians / sec
ARM_SPEED = 0.2 # percent
DEFAULT_SPEED_FRACTION = 0.3
###############################... |
df0eeea076d2ff642d1abd029b1e898b54e813666b77c75b40d050738c4ca166 | Python | 11,380 | 323 | import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
import matplotlib.pyplot as plt
import operator
from functools import reduce
from functools import partial
from timeit import default_timer
from utilities3 import *
import scipy
fr... |
7563d0b1720779be10a2c6d7af426c3c2a6b860e403df5e0b097e2cb02f0dbcd | Python | 11,384 | 310 | import warnings
from typing import Dict, Generator, List, Tuple
import numpy as onp
import meep as mp
def is_leaf_node(partition: mp.BinaryPartition) -> bool:
"""Returns True if the partition has no children.
Args:
partition: the BinaryPartition node
Returns:
A boolean indicating whether p... |
1878b45a1249d79b2c83af47733d3efa64c67511ad4269650a225b73e5947e4a | Python | 11,387 | 282 | """
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-p... |
2493dd0992046b08097c338fc432a7ea3efe9af18f4e1f4b4d411bfe2ac6f60c | Python | 11,393 | 320 | import argparse
from datetime import datetime
import random
import shutil
import numpy as np
import os
import time
from utils import *
from params import *
import sys
from datetime import date
import pickle
import train_inductive
from trials.hyperparam_config import config
import pickle
import optuna
import copy
from u... |
2f5d5bb0736dbea25fcd93c5f6fe555ded1f9db27c00b21ae7ee392bd7a0c312 | Python | 11,393 | 292 | """
Unsupervised and deterministic classification test for PCA-KMEAS algorithm
Input: - The STAR file with the particles to classify
- Ground truth mask
- Classification parameters
Output: - A set of STAR files with the new classes
- 2D rotational averaged around memb... |
66d575b1e5a11d45ab9d10e3261976d4e0d69ec4cf20e98a4bbfab1101094e3a | Python | 11,393 | 282 | import numpy as np
from pandas import DataFrame
from scipy.stats import f
from numpy.typing import NDArray
def sumsq_total(df_long: DataFrame, values: str) -> NDArray:
"""
Calculate the total sum of squares for a given column in a DataFrame.
The total sum of squares is the sum of the squared differences b... |
e1bd46fbc1a21a0fb5e884159908829875ee421ac081687e58ce50bcf29d3787 | Python | 11,396 | 313 | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... |
5e1ad484d60fe1a210312c04df8f8ae68b689c1b2e4e1ce2ce4d78dcf2646943 | Python | 11,398 | 205 | """SIGN_FROM_FUNCTION.py 2026-09-25. Pre-registration: 04-NOTES/PREREG-2026-09-25d-SIGN-FROM-FUNCTION.md (sha e348b2c4...)
Is the sign of an antennal-lobe local neuron (LN) type readable from projection-neuron (PN) responses to real odours?
Hidden truth = laboratory prior at type level; recording = glomerular PN spik... |
9de74c2c7497735dc38ab1af02016e7465d01c1448b18a10a378b91d3abe008c | Python | 11,399 | 295 | from __future__ import division
import logging
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from IterativeMethod import iterativeTCCT
"""
Created on Sat Nov 17 19:48:14 2018
@author: Hannah Choi
"""
"""
This code genereates shuffled versions of the CT connectitivity data and
c... |
45e5519575ef02300773a9eea59ff52a79f4df61acfe376203349988d2296cf7 | Python | 11,401 | 299 | # 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... |
7e575bf0b209f7df707c56a253fa3f6bfd1e0e02cb107241ee1b1f8cea9b7969 | Python | 11,401 | 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... |
5e2cb7beff918becf045048707d4e2df76c5737c084cecd098ae3ea19b4e3518 | Python | 11,402 | 260 | import numpy as np
import scipy as sp
import kernels
import scipy.integrate as integrate
import scipy.interpolate as interpolate
import scipy.sparse.csgraph as csgraph
from numpy import matlib
def mean_error_2d_contour(gt,pred):
return np.mean(np.sqrt(np.square(gt[0::2,:]-pred[0::2,:])+np.square(gt[1::2,:]-pred[1:... |
a82cf80c530d6646fa4ad914315459c74312d839733bf6da4bd6f2657cdf8f5b | Python | 11,404 | 306 | """
This module, 'bands.py', contains recipes for performing bands and fermi surface calculations using the
bands.x and fs.x binaries from Quantum ESPRESSO via the quacc library.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from ase.dft.kpoints import bandpath
from pymatgen.io.ase import A... |
b3a3c3a93af60361f959010b2caa5fa8f4512d83f86470e9a73a022188b94774 | Python | 11,406 | 278 | """
Download Allen Mouse Brain CCF **2017** reference files at one or more resolutions.
This script intentionally targets the publicly-released *CCF 2017* (a.k.a.
Allen CCFv3) atlas - the latest revision Allen distributes through their open
data archive. Any newer internal revision (sometimes referred to as
"CC... |
4d7c225993cc01335703f8255507863c61a05fe57a822e789aace08eb87bf041 | Python | 11,408 | 351 | #
# 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,... |
79858a7af05e08d75be6197b5a0ff4a69da4c968e59cd00c5f830cdee557455a | Python | 11,409 | 288 | #!/usr/bin/env python3
# Runs spin permutation with for within and between network dispersion analyses with lmer controling for total surface area
### Define parameters
surface_name='fsa5'
parcellation_name='schaefer_400'
n_rot=1000
### Load required packages
import os
import sys
import numpy as np
import pandas ... |
4b8a45a4001a1a2e2df0c9dd8c6ab58357a9a1d0c56b19536b4219ebb6fed159 | Python | 11,416 | 336 | #!/usr/bin/env python
# This script computes the Gabor filter response in a simulation
# Uses multiprocessing
# Make sure current directory is added in the PATH variable
import h5py
import math
import multiprocessing
from multiprocessing import Pool, RawArray
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LE... |
0104e0989b1e03d7adf62d17d925f10b6ec2e9eba7817422a39bb362f8f067dc | Python | 11,419 | 262 | import pandas as pd
import numpy as np
import os
import pysam
chr_list = ['chr1', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15',
'chr16', 'chr17', 'chr18', 'chr19', 'chr2', 'chr20', 'chr21',
'chr22', 'chr3', 'chr4', 'chr5', 'chr6', 'chr7', 'chr8', 'chr9', 'chrX']
chrom_size = pd.read_c... |
4ffb378f0fd00198b2c064180da749f863bc453fe8ed9f44c471bc935e2e343b | Python | 11,419 | 296 | from typing import Optional, Tuple, Mapping
import pandas as pd
import math
import subprocess
import pickle
import sys
import shutil
from pathlib import Path
from argparse import ArgumentParser
from Bio.SeqUtils import seq1
from Bio.PDB import PDBParser
from Bio.PDB.Structure import Structure
from pymol import cmd, st... |
fcce4f90d1b73946b3dacd6f919791906d36b51158b29b8b62b11a37a61009c1 | Python | 11,420 | 311 | from __future__ import print_function
import os
from collections import Counter
from pddlstream.language.constants import is_plan
from pddlstream.utils import INF, read_pickle, ensure_dir, write_pickle, get_python_version
LOAD_STATISTICS = True
SAVE_STATISTICS = True
DATA_DIR = 'statistics/py{:d}/'
DEFAULT_SEARCH_... |
ec8afeeda48ae413df5cc2f3f6fa6796b4331150dfaa5aebe1e60ca2c2fb0777 | Python | 11,423 | 325 | """Qt tests for AtlasSelectorDialog.
Uses the same qapp / settings-isolation pattern as
test_ccf_boundary_viewer_qt.py."""
import pytest
@pytest.fixture
def qapp():
from PySide6.QtWidgets import QApplication
app = QApplication.instance() or QApplication([])
yield app
def _force_status... |
1672cea2921072b62f556ffda5d68efc89c9209b2ffea39e024e1cb505b3e2d4 | Python | 11,433 | 239 | import numpy as np
import pandas as pd
import xgboost as xgb
import datetime
import math
import multiprocessing as mp
from mipt import mipt, mipt_full, LHS_maximin
sample_size = 100 # the number of samples to be selected
repeat_times = 5 # the number of ML models to be trained for each parameter combination,
... |
99a23a41469439425649c0063833bde1c6e4aad9943815ac0b43713051849154 | Python | 11,433 | 337 | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# 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 a... |
bc0167f3b72bf61f8575bc17024e90b06d75bb7ab563365f0bdb1b5bf78ed745 | Python | 11,434 | 313 | """
Script for segmenting the filaments in a tomogram without assuming any geometric constrain
Input: - Original tomogram (density map)
- Mask tomogram (0-fg, otherwise-bg)
Output: - vtkPolyData with the filaments
- Segmentation tomogram
"""
__author__ = 'Antonio Martinez-Sanch... |
934788b504865ef687c3b97669f40992869e3fc341d3418f7216c483cd10396f | Python | 11,437 | 371 | # 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... |
64b124f342754178eba101d5b45a36f29e8268c897d3152b2d0c8fa7ec90f737 | Python | 11,441 | 145 | # C. Cocuzza, 2021
# Function to compute category selectivity: quantifying the selective responsiveness of a
# given set of nodes (vertices, functional ROIs, etc) to a semantic category.
# EX: the regions comprising the FFA to images of faces. NOTE: this may also be applicable
# to non-semantic-category conditions. ... |
a82290a74c845c2fa5c4f4764dc263492a1f445c7f6245ad9b09e044a79e9108 | Python | 11,444 | 275 | """
Tests that correspondence.py has no module-level imports of config or io_utils.
This ensures the Laplacian refinement code can be extracted as a standalone
package without pulling in ANSI color constants or NIfTI loader utilities.
"""
import ast
import os
import numpy as np
import pytest
CORRESPOND... |
de56a6ebf08270a05144aee05249c3441255962c71eaffbd4620d4325d913d6d | Python | 11,444 | 254 | import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
import warnings
warnings.simplefilter("ignore")
import time
import tqdm
import util
import pprint
import random
import torch
import numpy as np
import pandas as pd
from datetime import datetime
from torch.optim import lr_sc... |
b9aaa6686490653426793c75db519a2e1b3e0b7566f0f9a35f0d29b274dca219 | Python | 11,446 | 335 | # -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compa... |
ef3457b1220bfd3354a921455d83d468f31be4151b171263a358dc7f0cc9ec36 | Python | 11,447 | 267 | # Script to run CCA on the data
# Using the meet package https://github.com/neurophysics/meet.git to run the CCA
import os
import mne
import numpy as np
from meet import spatfilt
from scipy.io import loadmat
from Functions.get_channels import get_channels
from Functions.IsopotentialFunctions_CbarLabel import mrmr_esg... |
82aca25564475d9ea40743f69c5ff124249473464cc431b43d104368903e5117 | Python | 11,450 | 291 | # 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... |
9269ef5b464af080de0f9eb65f687103e6a3da2cd51b067c375add894485e5c2 | Python | 11,450 | 314 | '''This module handles task-dependent operations (A) and noises (n) to simulate a measurement y=Ax+n.'''
from abc import ABC, abstractmethod
import torch
from ConditionalNeuralField.cnf.inference_function import pass_through_model_batch
from ConditionalNeuralField.cnf.utils.normalize import Normalizer_ts
from Conditio... |
cbe7de6ebc9e1485e87af21aa071c0be80736de8f7069cc8a7868e6c2788507c | Python | 11,451 | 249 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from Temporal_components import WindowTransformerBlock, STFeatureExtractionLayer
from Graph_learning_representations_module import SpatialCell, BGraphConvolutionalNetwork
from Graph_learning_module import AdaptiveGraphStructureL... |
17efa37d441cb57a3ce6b3ea846be2d293e6c76173efe678f11bcacc2d21d5bc | Python | 11,453 | 302 | #!/usr/bin/env python3
# ******************************************
#
# SHARC Program Suite
#
# Copyright (c) 2023 University of Vienna
#
# This file is part of SHARC.
#
# SHARC is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by... |
4d9ba3360031f2216404c9ae11bb649e9356218d02b42e513db0b006a63d7cd9 | Python | 11,454 | 435 | #!/usr/bin/env python
# coding: utf-8
# ## Preprocessing and Datahandling
# In[1]:
import sys
sys.path.append("../scripts")
# In[2]:
import os
import pandas as pd
import Utils_00 as utils
import Paths as paths
from monai.data import DataLoader, PersistentDataset
from monai.transforms import (
Compose,
... |
a19cec86065dd3e48fcc921b375fec7b4c2798bd94b06fd496eaf60e058dce3e | Python | 11,457 | 264 | import os
import copy
from collections import defaultdict
import numpy as np
import networkx as nx
from tqdm import tqdm
from rdkit import Chem
import torch
from torch.utils import data as torch_data
from torch_scatter import scatter_max
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R... |
489d87db5db8143aaa5e8d567f7c972ab5b32c0fa554b4ed0780fb5a662394cf | Python | 11,458 | 323 | """
Utility functions for visualizing SMART meshes using pyvista.
"""
import dolfin
try:
from ufl_legacy import vertex
except ImportError:
from ufl import vertex
from typing import Tuple
import numpy.typing as npt
import numpy as np
import functools
import pathlib
from typing import Optional
import warnings
im... |
b9725bf9330004da1f60e60567fbc55b80ea36963ae68605368db44cac89b415 | Python | 11,458 | 313 | import torch
from torch import nn
from torchvision.transforms import ToTensor
from torch.optim import *
from models import *
from torchvision import datasets, transforms
from torch.utils.data import DataLoader
import os
from utils import Logger, AverageMeter, accuracy
import time
from PIDAO_SI import PIDAccOptimizer_... |
29fbaa1e426a987503176add4207d6f26df543ae4d83290fc8cb787dcf01a628 | Python | 11,459 | 317 | import os
import csv
import numpy as np
import scipy.io as sio
import torch.nn.functional as F
import torch.nn.functional
from matplotlib import pyplot as plt
from sklearn.feature_selection import RFE
from sklearn.linear_model import RidgeClassifier
from sklearn.feature_selection import RFE
from nilearn import connecto... |
7d787f2ed12330048758f81be905eccc75ef45495bf877b2acfe55c8d533f20a | Python | 11,462 | 360 | import typing
import bpy
from bpy.props import (
BoolProperty,
EnumProperty,
FloatProperty,
FloatVectorProperty,
IntProperty,
StringProperty,
)
from ..blender.utils import viewport_tag_redraw
from ..entities.base import MolecularEntity
from .base import BaseAnnotation
from .utils import get_all_... |
e456776c61d13acc3730d78f418b71cc2ddc8a4fbab16c11a52c3e4cdb91954d | Python | 11,464 | 393 | # 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... |
6f44bd60f6e6b4bb242f3370852523c06d88dc758a6f6959e059d7004cc8352c | Python | 11,467 | 335 | # -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compa... |
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