sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
665e4ee1b697f6b57b617b8d25af6b8d29c2f2e8b9e4bdaa78b58b63358075cb | Python | 13,639 | 327 | ###############################################################################
# Does feature extraction by spherical projection texture
# Does a user-settable projection along rays from the centroid in gauss-legendre quadrature
# Mapping the data to a 1/2D spherical surface
# This is decomposed into a spherical harmo... |
495d2f1b6841bfd6efc850bcd1257311e506f4526ebe561bf5ed8acfc67f1e8b | Python | 13,645 | 345 | """
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 software: yo... |
0c23c35cdf9e3114a0ebb98afd94821714ce875871e0ba283ee0a7a2aa410783 | Python | 13,647 | 340 | # This file contains helper functions for DEAP
# including additional mutation, crossover and selection operators.
import random
import copy
import numpy as np
# def indivAsDict_adapt(individual, ParametersInterval, paramInterval):
# """
# Convert an individual to a dictionary
# """
# return Paramete... |
8f1e667cd4ad4edf0cda2723299bf8069825ddd257b44afc36c85b82c0980b0b | Python | 13,651 | 287 | """Hemisphere geometry: crop bounds, side masks, per-point assignment.
``crop_bounds`` is deliberately a PURE function of ``(shape, plane, mode)``.
The half-brain crop is applied to the template AND the annotation, and mirrored
again downstream to keep warped output aligned; deriving the bound from the
data (say,... |
7abb364dee1e7c85864ed9d7c6afee73b4ed171e5ffbf3f71ded0284c948282f | Python | 13,654 | 358 | import matplotlib.pyplot as plt
import numpy as np
import scipy
import sys
import neurolib.utils.functions as func
def plot_outputs(model, ds=None, activity_xlim=None, bold_transient=10000, spectrum_windowsize=1, plot_fcd=None):
# check if BOLD signal is long enough for FCD
FCD_THRESHOLD = 60 # seconds
... |
7d127a2e620471e18c66fbf50c720503d6adf925a9fc1960e6513103bce64cef | Python | 13,655 | 370 |
from dolfin import *
import numpy as np
import matplotlib.pyplot as plt
import sys
import time
import os
#os.system("dijitso clean")
# Leser kommmandolinjeargumenter
start = time.time()
T = 2800
dt = 20
patient = sys.argv[1]
res = int(sys.argv[2])
order = int(sys.argv[3])
Q_in = float(sys.argv[4])
parameters["kr... |
4ecd318d6f664ae74b76505ea6bf9ef01e9e53fa28fbba5931fb7ec9520e4245 | Python | 13,660 | 320 | from __future__ import print_function
from dvn.utils import get_itk_array,write_itk_imageArray
import numpy as np
from dvn import FCN, VNET, UNET
from dvn import Network as NET
from dvn import losses as ls
import argparse
import os
import keras as K
# Defined global variables here .................................
BLO... |
2b0a0a698c3af742ec82f2d7c35e468b7e495234213b353b938b74c4bc0e1d96 | Python | 13,663 | 266 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
"""
Functions that load classification accuracies from the PCA and TriDy classification methods and formats them for plotting
authors:Daniela Egas Santander, Jānis Lazovskis
Last update: 02.2024
"""
import numpy as... |
b5c9d96c3e2710f6fe8666a7f585adc35d62169c33d983514eba623071ff9cfc | Python | 13,666 | 450 | import numpy as np
import matplotlib.pyplot as ppl
from scipy.signal import windows
from syncopy.specest import mtmfft
from syncopy.specest import mtmconvol
from syncopy.specest import superlet, wavelet
from syncopy.specest import wavelets as spywave
def gen_testdata(freqs=[20, 40, 60], cycles=11, fs=1000, eps=0):
... |
10f0c0eb2f418cbd7eecf72fa7c2939edb696f5635c0f905600aff8b101c062d | Python | 13,668 | 295 | from typing import Callable, Dict, List, Union
import numpy as np
import torch
from scipy.signal import hilbert
from ..base_transform import EEGTransform
from ...utils import LazyLoader
pyg = LazyLoader(
'torch_geometric',
install_hint='See https://pytorch-geometric.readthedocs.io/en/latest/notes/installa... |
72b3ae188962d7abc1fc6b3ed145e03da66c5e498f175bbe8610d1032ef2dc0d | Python | 13,670 | 378 | import os
import sys
import torch
from torch import autograd
from torchdrug import utils
module = sys.modules[__name__]
path = os.path.join(os.path.dirname(__file__), "extension")
spmm = utils.load_extension("spmm", [os.path.join(path, "spmm.cpp"), os.path.join(path, "rspmm.cpp"),
... |
354d9b977a79744e4e0271f6b7d5f3ddeb7f57e6e799008c0d2307a6c289912d | Python | 13,673 | 425 | # 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... |
5cfa5ac4c90042817eae1a4b802af16f2c9433b68fdf55ec6fc46c76ade2cb1c | Python | 13,684 | 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... |
d936de86afeab3b450250116a81cb48f1f323db7c99305e509c6a4f5f04d7db9 | Python | 13,684 | 350 | # Copyright (c) 2020, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and t... |
a074244ced0958fff7183863422f122eef737c7ed40685c4dd1592308c72d6f0 | Python | 13,685 | 647 | """Workflow decorators."""
from __future__ import annotations
from functools import partial, wraps
from typing import Any, Callable
from quacc.settings import change_settings_wrap
Job = Callable[..., Any]
Flow = Callable[..., Any]
Subflow = Callable[..., Any]
def job(_func: Callable[..., Any] | None = None, **kwa... |
a9edb45e31effe5c1601b547f86e144323c98b572bf695e14f303a0978ee2875 | Python | 13,685 | 405 | from dreamcoder.type import *
from dreamcoder.program import *
from dreamcoder.frontier import *
from collections import Counter
class MatchFailure(Exception):
pass
class Matcher(object):
def __init__(self, context):
self.context = context
self.variableBindings = {}
@staticmethod
d... |
0cf4ac9476aeedb32db09ba67d54a628dd18c6710428b8d73928ee16ff9a5108 | Python | 13,688 | 385 | # 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... |
82abb93ddc3bc4af6e99d0d293d52d86691ee77c91a6b5b88c575c806ac7ca38 | Python | 13,690 | 355 | #!/usr/bin/python
# Gogulan Karunanithy, UCL, 2023
import tensorflow as tf
import time
import os, copy
from tensorflow import keras
import tensorflow.keras.backend as K
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.mixed_precision import experimental as mixed_precision
polic... |
07588de713ea18ac91269f29218c6ad9b50c4c795a285803c6c712e1b356863f | Python | 13,691 | 282 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
d052d054843de8870129fa2516cda584b012ba0080213b79c0a4cbfc5fb39044 | Python | 13,693 | 358 | # 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... |
13a4bb2840a3b510e41368c3e525f6da35deca3eec20b3aa6978c56f5ff6c135 | Python | 13,694 | 460 | import numpy as np
import torch
from skimage import io
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
from torch.utils.data import Dataset
from torchvision.transforms import GaussianBlur
import source.network_collection as nc
class BaseDataset(Dataset):
def... |
7c34bfe7c48143461b9c4a852d56300dd8ffcca4d3e9b09733596bca39fe2182 | Python | 13,695 | 304 | from __future__ import print_function
import os
from collections import namedtuple, defaultdict, deque, Counter
from time import time
from pddlstream.algorithms.downward import get_literals, get_precondition, get_fluents, get_function_assignments, \
TRANSLATE_OUTPUT, parse_sequential_domain, parse_problem, task_f... |
88bfc0ceb398826c290af65ff5dbd51a342e0c01d9ad18f0ccc300c33b4490e7 | Python | 13,696 | 354 | import os
import napari
import numpy as np
from skimage.measure import label
from skimage.segmentation import find_boundaries, watershed
from skimage.filters import gaussian
from plantsegtools.utils import create_h5, smart_load, load_h5, H5_FORMATS, relabel_segmentation
from plantsegtools.postprocess.seg_nuclei_consis... |
df71325afea7a7eff4c46e781dcf0d6e9708a60e91f8d61fdf0033930c6af10e | Python | 13,696 | 325 | #!/usr/bin/env python
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
Module used to parse all the route and scenario configuration parameters.
"""
import json
import math
import xml.etree.ElementTree as ET
import carla
from agents.navigation.... |
3772c214b7b288b026325f06f5c67cbc3b862ea6b36d0d21af8642720db8b0f5 | Python | 13,697 | 361 | from tensorflow.python.keras import backend
from tensorflow.python.keras.applications import imagenet_utils
from tensorflow.python.keras.engine import training
from tensorflow.python.keras.layers import VersionAwareLayers, GlobalMaxPooling1D, MaxPooling1D
from tensorflow.python.keras.layers import Input, Conv1D, Ba... |
d41c89f3913dc04e208b8fcab581b22260fd2447cd0a36fad5462bf4a4c8ef3d | Python | 13,700 | 205 | from pathlib import Path
import random
import numpy as np
import pandas as pd
from pyproteonet.io import load_maxquant, read_multiple_mapped_dataframes, read_mapped_dataframe
from pyproteonet.processing import logarithmize
from pyproteonet.normalization import normalize_sum
def load_breast_cancer_dataset(path: Path =... |
c28bbd6de0218ce39e28c64216cd716084048a93d7e9d6ac71ce51149dd42273 | Python | 13,703 | 445 | import argparse
import cv2
import time
import numpy as np
import threading
from control.dcam import Dcam, Dcamapi
from control.dcamapi4 import *
from control._def import *
def get_sn_by_model(model_name):
try:
_, count = Dcamapi.init()
except TypeError:
print('Cannot init Hamamatsu Camera.')
... |
0c5d6488eeafafa162cb22fa67b08c48d1f3cecb868833bd2ee8ff6ce5c6937e | Python | 13,706 | 412 | # 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... |
22a32c209c65d22c5f52dda7e5920981cdf03c3e09659534beaafd22623d024c | Python | 13,706 | 306 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 28 21:00:17 2021
@author: CY
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributed import get_world_size
import numpy as np
class BaseModel(nn.Module):
"""
Base model with: a encoder
"""
def ... |
cd6224ca5778b4560a1c1acc3f19219d379ec9169adb157c8b16e2bb5fd246e6 | Python | 13,707 | 462 | from datetime import datetime
from logging import getLogger
from os import SEEK_CUR
from pathlib import Path
from struct import unpack
from xml.etree.ElementTree import parse
from numpy import (append, asarray, cumsum, diff, empty, nan, sum,
where, ndarray, unique)
from .utils import DEFAULT_DATETI... |
e54de642001e6a0b3fc8787f422c0a589f35211913b2b6154aef9dc5a9dd5817 | Python | 13,708 | 380 | import functools
import pandas as pd
import numpy as np
from tqdm.auto import trange
from ..datasets.core import DataSet
from ..datasets.ds_utils import _add_types
from ..utils import printv
from ..mappers import GraphMapper, BaseMapper, extract_mappings
__all__ = ["GroundTruthModel"]
"""
TODOs:
Refactor this mo... |
3c6078bde8488291a554ced3928cf67c5c74ec439ba60f6a43effb0103b287b6 | Python | 13,710 | 98 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMAR... |
9970af5c8a8471067cac4e8fc48a63a6d545f769067241939a98b7cc3f260db0 | Python | 13,710 | 310 | # 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... |
49985bbe331f763ab1262d12ee8fbd9dc3f035c251418f189f8aeb611cb56463 | Python | 13,715 | 458 | from itertools import chain
import pytest
from hypothesis import given, settings, strategies
from elasticai.creator.arithmetic.fxp_converter import FxpConverter, FxpParams
@pytest.mark.parametrize(
"total_bits, frac_bits, signed, number, check",
list(
chain(
[
(total, fra... |
ace2893c1bee2d28c495f62e3b08eef7903347712fe65bc9a0226f23f5ef67d8 | Python | 13,715 | 371 | """distutils.filelist
Provides the FileList class, used for poking about the filesystem
and building lists of files.
"""
import os
import re
import fnmatch
import functools
from .util import convert_path
from .errors import DistutilsTemplateError, DistutilsInternalError
from ._log import log
class FileList:
""... |
4071d3d6f750f7c1c149bfe5d9e9508ec32e1c035f937a854fc4e13845dadb3d | Python | 13,716 | 329 | """
Script for extracting the graphs for analyzing quantitatively a synapse
(or any other junction between two membranes)
Input: - Density map tomogram
- Segmentation tomogram of the synapse
Output: - A graph
"""
__author__ = 'Antonio Martinez-Sanchez'
# ################ Package impor... |
8c7aa4bc8d98dc3cc1763a631ba6af50fedfe00fb5db8676ae5c7ee52516386c | Python | 13,717 | 275 | import os
from typing import Callable, Dict, Tuple, Union
import numpy as np
from scipy.io import loadmat
from ....utils import get_random_dir_path
from ..base_dataset import BaseDataset
class KULProcessedDataset(BaseDataset):
r'''
This dataset contains EEG recordings from 16 subjects listening to one of tw... |
058fd67aac22cd2fb4a0c144aea95eed7bcf0fb2f161b569cc0747852c8f2fa8 | Python | 13,718 | 390 | ##
# \file residual_evaluator.py
# \brief Class to evaluate computed residuals between a
# simulated/projected and original/acquired slices of stacks
#
# Should help to assess the registration accuracy.
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date January 2018
#
# Import lib... |
81b28487577b0879c8e031b55e1896c6f422a16c8049aa7d7f4633528181ea21 | Python | 13,721 | 365 | # 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... |
77a6ec09194b0a67c47380f8fd6eee9c472fd9933bc3923093fc2ba75f8a3d92 | Python | 13,735 | 357 | from PIL import Image
from scipy.ndimage import zoom
from wsilearn.wsi.wsd_image import ImageReader
from wsilearn.utils.asap_links import make_asap_link
from wsilearn.utils.cool_utils import *
from wsilearn.utils.io_utils import move_file, copy_from_to
def px_to_um2(px, spacing):
return px*(spacing**2)
def write... |
548fef3ee1151551292bad22dcf4b742ccd9428e3b14a81900891236f458474b | Python | 13,739 | 330 | #! /usr/bin/python
# -*- coding: utf-8 -*-
import json
import os
import time
import tensorflow as tf
from tensorflow.python.training import session_run_hook
__all__ = ['TaskSpecDef', 'TaskSpec', 'DistributedSession', 'StopAtTimeHook', 'LoadCheckpoint']
class TaskSpecDef(object):
"""Specification for a distribu... |
378ff459ebf3083aba1943ca91159da447cb8355185a1a9d3e9a0b734e7278f2 | Python | 13,741 | 400 | # data generator code for training disperseNN2
import sys
import numpy as np
import tensorflow as tf
import msprime
import tskit
import warnings
from attrs import define
from disperseNN2.read_input import parse_provenance
import gc
@define
class DataGenerator(tf.keras.utils.Sequence):
"Generates data for Keras"
... |
93009ab142d79da382953e618d2f22abcb3f97a20b37766871df4aefe93794e9 | Python | 13,741 | 277 | #!/usr/bin/env python
"""
Helper module to load whisker and neuropixels data, based on info about
condition, cortex depth, CNO time drop, animal ID.
"""
# Ensure /data_analysis is in path
import os
import sys
if not ('data_analysis' in os.getcwd()):
sys.path.append(os.path.join(os.getcwd(), 'data_analysis'))
# Im... |
54f1e2a7f20cb33b0933e182388d7f85657ead4bf2cb2c5948fb16b0383224c1 | Python | 13,743 | 499 | from sklearn.cluster import KMeans, AgglomerativeClustering, estimate_bandwidth, MeanShift, OPTICS, SpectralClustering
from sklearn.mixture import GaussianMixture
import logging
import matplotlib.pyplot as plt
import pandas as pd
from .metric_factory import internal_factory
from .graph import CKNNGraph
log = logging.... |
cfb7650ec645c132c5885ce7a14104fd4f2465aad635fde709c1c719c39ce1cc | Python | 13,751 | 323 | try:
import binutil # required to import from dreamcoder modules
except ModuleNotFoundError:
import bin.binutil # alt import if called as module
import pregex as pre
from dreamcoder.utilities import *
from dreamcoder.domains.regex.groundtruthRegexes import *
from dreamcoder.program import Abstraction, Appli... |
4fbab75f9f1aac11cdab5d253f598601ce39263ce5ab0169ecdbde6c09872e90 | Python | 13,752 | 458 | from __future__ import print_function,division
import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
class ResidMultiScaleBlock(nn.Module):
def __init__(self, nin, ng, nout, scales=[1,2,4], pooling='max', padding=False):
super(ResidMultiScaleBlock, self).__init__()
self.... |
e4226e4f616497012ffcdf197ce6adece5e248178eb46a377509b51028809529 | Python | 13,756 | 342 | import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from collections import OrderedDict
model_urls = {
'densenet121': 'https://download.pytorch.org/models/densenet121-a639ec97.pth',
'densenet169': 'https://download.pytorch.org/models/densenet1... |
6a3babbd2700376e3f248968e44dc4edff23d40080e5b9a9e792e2183d7a21d6 | Python | 13,760 | 311 | # -*- coding: utf-8 -*-
"""Script for removig double picked partiles in STAR file."""
import os
import math
import logging
import time
import csv
import itertools
import operator
import copy as cp
import scipy as sp
import numpy as np
from datetime import timedelta
# import pyseg as ps
from pyorg import sub, disper... |
7a860d88756322b6fe1a4a2463baf1be05b1cc865985e9177bc853da0d2a2934 | Python | 13,763 | 336 | #!/usr/bin/env python3
## Importing libraries
import tqdm
import sys
import numpy as np
from itertools import combinations
from scipy.io import loadmat,savemat
import glob
import pickle as pk
import os
import h5py
import pickle as pkl
def upper_tri_masking(A):
'''Extract the upper triangular
values of a matr... |
fc72cc8c1835bd3c5b3e879097ce6cc400cab01861839b0c2a36a5a4eb2ed1d3 | Python | 13,769 | 375 | from __future__ import annotations
from functools import cached_property
from typing import Collection, Iterable, Optional
import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator
from numpy.typing import NDArray
from cuppa.constants import DEFAULT_KEYWORDS_MALE_CLASSES, DEFAULT_KEYWORDS_FEMALE_CL... |
63dc16904046c1f2172e54e2e67e06ca2125c8b0be4062a7a6e610e857d5fe5a | Python | 13,770 | 119 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.absolute import AbsoluteReport
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BE... |
c3b51ef7cb3ded026e8d97ad5233bbb3490dd230eceb7c656b44177ac6d9cc9d | Python | 13,770 | 119 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.absolute import AbsoluteReport
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BE... |
52d5102c21f46fa27e246d7990c3349bd77f0d6219d40f741c5c4233d973e5d2 | Python | 13,772 | 427 | #!/home/dingml/anaconda3/envs/expressBert/bin/python3
import argparse
import shutil
from argparse import Namespace
from collections import OrderedDict
import time
import os
import torch
import torch.nn as nn
import sys
import gzip
import numpy as np
import logging
import warnings
from io import TextIOWrapper
from typi... |
27a7713e30b79161e4dd7faa7b84fca0f0973fabf0661f793dfd6ae07df164e4 | Python | 13,775 | 347 | import math
from typing import Callable, Dict, List, Set, Tuple
import numpy as np
from rdkit import Chem
from chemprop.args import InterpretArgs
from chemprop.data import get_data_from_smiles, get_header, get_smiles, MoleculeDataLoader, MoleculeDataset
from chemprop.train import predict
from chemprop.utils import lo... |
832e7c802384c90d4a1ce7776ecf82edf9a1a510b887faa9011c66b569e9845c | Python | 13,777 | 431 | # 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... |
3cc0a0698ae134140faba05cac80a084d73fc49f346a5629f7941f65e2e10c06 | Python | 13,781 | 331 | """
Unsupervised and deterministic classification test for PCA-KMEANS 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 mem... |
edb45e6f6d5ae85d450ba983906ee60458be8e4af5193b37ef6a66fc35638cb7 | Python | 13,781 | 395 | import numpy as np
from skimage.transform import resize
from skimage import filters
# import pandas as pd
# from math import floor
# # import decimal
# from skimage.morphology import erosion
# from scipy.ndimage.filters import minimum_filter
# from skimage.exposure import adjust_gamma
# from sklearn.preprocessing im... |
3df1cd5b4f9701a7a8c389b1244f59bc1495051a84b5349a458f4cf6e3630efd | Python | 13,782 | 350 | import os
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import KFold
from sklearn.svm import SVC
from sklearn.decomposition import PCA
from params import SUBJECTS as subjects
from params import PLOT_DIR as plot_dir
from params import BIDS_ROOT as root
from utils... |
9e700a3df5e0915327c08a95bf06bbf0f56938ce86866f34844a742e979b3259 | Python | 13,782 | 343 | """
Image I/O utilities and axis alignment for the registration module.
Metric functions have moved to :mod:`metrics` - they are re-exported
here for backward compatibility.
"""
import gc
import numpy as np
import scipy
from scipy.ndimage import affine_transform
# Re-export all metrics so existing ``from... |
b81cfd41c9dc771745596d948e0052cb150057f3e44b991915e43f331c7245ad | Python | 13,785 | 411 | from __future__ import annotations
import os
import sys
from pathlib import Path
from types import ModuleType, SimpleNamespace
from typing import TYPE_CHECKING
import pytest
from ase.atoms import Atoms
from ase.build import bulk
torch = pytest.importorskip("torch")
ts = pytest.importorskip("torch_sim")
mace = pytest... |
f154065f7803c68720705b912cefb44abcb9f5341f68f0a0a1c9c2a99a306044 | Python | 13,787 | 418 | """
==============
MVPA functions
==============
Utility functions for estimation and statistical analysis of MVPA parameters.
Authors: Functions retrieved and adapted from
https://github.com/heikele/GAT_n4-p6, also see:
Heikel, E., Sassenhagen, J., & Fiebach, C. J. (2018).
Time-generalized m... |
761ee10b01052d2c8c605c4190d9c5b6bb823c028232ebb4c9cfcacb553aebc7 | Python | 13,794 | 232 | # ------------------------------------------------------------------------
#
# 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
#
# Unle... |
ae3234aef7d8180896c212bd4e06b0ad0719689eccca1e182f00c74fe14573ad | Python | 13,799 | 338 | """Utilities for assembly and conversion of HED strings to different forms."""
import math
import re
from collections import defaultdict
from functools import partial
import pandas as pd
from hed.errors.exceptions import HedFileError
from hed.models.definition_dict import DefinitionDict
from hed.models.hed_string im... |
d05c3ee85c2ba96368d1f6cef1415185e29473f57446389b4f18f08ddc9c1754 | Python | 13,812 | 273 | import numpy as np
import ast
import pdb
# import spiking function
from spiking_ulils import label_encoder
from spiking_ulils import Conv2d, BatchNorm2d, Relu
from spiking_ulils import Flatten
from spiking_ulils import Linear
import argparse
parser = argparse.ArgumentParser()
# quantization level
parser.add_argument(... |
866b470c9b20245091960be0c7ab01a2c06a50c44418fafd88f893fef46b509b | Python | 13,820 | 305 | import torch
import numpy as np
import torch.nn as nn
from einops import rearrange
class LayerGIN(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim, epsilon=True):
super().__init__()
if epsilon: self.epsilon = nn.Parameter(torch.Tensor([[0.0]]))
else: self.epsilon = ... |
c6af7c82c13af8615c51e73d2c4a0edf065fa5db682716b3d6fdebca4dcc83aa | Python | 13,821 | 331 |
# -*- coding: utf-8 -*-
"""
Created on Jun 22 2023
@author: Jonas A. Thiele
"""
### Apply models build in the HCP sample to
### predict intelligence scores in the replication sample (PIOP1 and PIOP2 combined)
### for models that were trained with different numbers of most relevant links (determined by step... |
19e8024a7411246706e40529cbae8d030e5d898c125935c4fc3d2a975ad05127 | Python | 13,826 | 324 | ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Hang Zhang
## Email: zhanghang0704@gmail.com
## Copyright (c) 2020
##
## LICENSE file in the root directory of this source tree
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
"""ResNet variants"""
im... |
56b617a2b9f9f1b320c71783cb053a7fe14b8dbb7293a3411cc4ba869cced9b6 | Python | 13,827 | 119 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.absolute import AbsoluteReport
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BE... |
6c9f763d76bcb7aec72221585179f35f4afbacd43923bbcd66eca8eeaae730e1 | Python | 13,827 | 280 | from __future__ import annotations
import warnings
from typing import TYPE_CHECKING, Literal
import numpy as np
import scanpy as sc
from fast_array_utils.conv import to_dense
from fast_array_utils.stats import mean, mean_var
from numba import njit, prange
from pandas.errors import PerformanceWarning
from scanpy.tools... |
850e766766a9dbfef3d1d87a90459f42570c24833dd89e55a8497a69f063b98a | Python | 13,831 | 396 | #!/usr/bin/env python3
"""
Command-line script for extracting tabular summaries from datasets without BIDS organization.
This script processes TSV (tab-separated values) files and generates summary statistics about
the columns and their values. Unlike hed_extract_bids_sidecar, this script does not assume
BIDS dataset ... |
de9738b9147d023495cd05ed1a5b5a3e9986f14ca900df2156866e29bee2662e | Python | 13,831 | 307 | import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
import torch.nn.functional as F
from resnet_features import resnet18_features, resnet34_features, resnet50_features, resnet101_features, resnet152_features
from densenet_features import densenet121_features, densenet161_features, densenet169_... |
bf0e465d3d3eb3ccf41446970d82513b833d263f259ce1feec269c6f9569b0f4 | Python | 13,834 | 412 | """
Pool of useful functions for processing surfaces
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 1.05.17
"""
import vtk
import math
import numpy as np
from pyorg import disperse_io
__author__ = 'Antonio Martinez-Sanchez'
# Iso-surface on an input 3D volume
# tomo: input 3D nu... |
8bf75e3c92a774f032ee17f8f1297a66e3f2977b453c213aef3d1235ab70bb01 | Python | 13,839 | 381 | """Configuration management setup
Some terminology:
- name
As written in config files.
- value
Value associated with a name
- key
Name combined with it's section (section.name)
- variant
A single word describing where the configuration key-value pair came from
"""
import configparser
import locale
import os
i... |
018bb0bf5eeb42487cca302b87ce5bdb11f0575478f484e97009e547a22623b5 | Python | 13,850 | 373 | """
Test for the backend integrator.
"""
import json
import os
import pickle
import unittest
from copy import deepcopy
from shutil import rmtree
import numpy as np
import pytest
import symengine as se
import sympy as sp
import xarray as xr
from jitcdde import t as time_vector
from jitcdde import y as state_vector
from... |
4c207c888fd52f444b6bc0a924591dd4c85b8365d10ace272443f5db97cf6ddd | Python | 13,850 | 352 | import torch
import torch.nn as nn
from torch.autograd import Variable
import time as t
import matplotlib.pyplot as plt
import sys
plt.switch_backend('agg')
sys.path.append('/home/jmwang/WorkSpace/GENiPPI/gPPMol/models_3d')
import os
from torchvision import utils
from tensorboard_logger import Logger
from tqdm import t... |
710b5156e0904abdbbd82a083910689c88de4d6dd9600546790f6eb340b9fec3 | Python | 13,853 | 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... |
7ad74fb5ce28cd2d628f2eda1733c93ce16c0f833d4a2edb0c8cb488e212ca46 | Python | 13,853 | 450 | # 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... |
7fcb061b115ad2fc1e146e4ec9e062a665a315d778f44d7ce8c5899ae2ce37e1 | Python | 13,854 | 336 | #!/usr/bin/env python3
## Importing libraries
import tqdm
import sys
import numpy as np
sys.path.append('/home/andrea/research/')
sys.path.append('.')
from utils_plotting import *
from utils_brain_analysis import *
from utils_analyse_HOtimeseries import find_frames_pctl,find_peaks
from utils_identifiability import *
... |
f66b2c92c9ae00b440dcf35c2bdc28583e8cc5883c618df7ad36d16bc8285b02 | Python | 13,857 | 319 | import os
import json
import argparse
import math
from utils import interpolate_trajectory, gen_skeleton_dict, gen_scenarios
DOT_PROD_SLACK = 0.02
PRECISION = 2
DISTANCE = 380 # length in meters
NUM_WAYPOINTS_DISTANCE = int(DISTANCE / PRECISION)
PRUNE_ROUTES_MIN_LEN = 20 #set this to prune shorter routes
MIN_ROUTE_LEN... |
a463dc0c2c4ac19e93d8334c6d5aedb8d83afe9d9dcd4c83dce92b620c7be7b2 | Python | 13,859 | 346 | import torch
import torch.nn as nn
import math
import copy
from torch.nn import Linear
from .so3 import SO3_Embedding
from .radial_function import RadialFunction
class SO2_m_Convolution(torch.nn.Module):
"""
SO(2) Conv: Perform an SO(2) convolution on features corresponding to +- m
Args:
... |
a094b746e6ec92bc5d1311498ba931684d466e5553ebfdbe8b7a77335d341d2b | Python | 13,862 | 334 | from __future__ import print_function
import numpy as np
from examples.discrete_belief.dist import DDist
from examples.pybullet.utils.pybullet_tools.pr2_primitives import Command, Pose, Conf, Trajectory, \
create_trajectory, Attach, Detach, get_target_path, SELF_COLLISIONS
from examples.pybullet.utils.pybullet_to... |
d60c85a45ae74f665bb99c5cf4461352bc1e64afff4264981abe94bd21af85ba | Python | 13,866 | 343 | ########################################################################################
# C. Jarne 2024 Analysis Group of D. Vidaurre @cfin #
# #
# Code performs a Kernel Ridge regression (called KRR... |
f710a00bf73fc8b11663024854e5e2c432955b4bd057a1635f3ef51917c41f8d | Python | 13,873 | 281 | import os
import pandas as pd
import torch
import numpy as np
# Labels
def get_possible_classes(database, cancer):
possible = {}
possible['pancan-pancan'] = ["type",]
possible['gdc-BRCA'] = ['pathologic_M', 'pathologic_N', 'pathologic_T', 'tumor_stage.diagnoses',
'age_at_initia... |
1575a9a542c576abc0d1839f01e998e785ff5ddc90df7f6b56e03345cc5017af | Python | 13,877 | 384 | # -*- coding: utf-8 -*-
import operator
from typing import Iterable, Tuple, Union
import torch
from torch.autograd import Function
from supar.utils.common import MIN
from supar.utils.fn import pad
def tarjan(sequence: Iterable[int]) -> Iterable[int]:
r"""
Tarjan algorithm for finding Strongly Connected Com... |
7b38d17a6ace903a4f05e8745de3bf78babc0c99ed3a9a9426a12d26cd7deef3 | Python | 13,877 | 335 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 8 10:39:20 2022
This script is used to generate a summary table of m6A sites from tagged SAM file
@author: heavens
"""
import os
import re
import sys
import pysam
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
from iter... |
e7f99a455205999961bc7838c82a6e6b5a78a19a1929dd2da46893e9040fb209 | Python | 13,878 | 362 | """
March 2021 by Oliver Gurney-Champion and Matthew Orton
o.j.gurney-champion@amsterdamumc.nl
https://www.github.com/ochampion
Solves the Extended Tofts model for each voxel and returns model parameters using the computationally efficient AIF as described by Orton et al. 2008 in https://doi.org/10.1088/0031-9155/5... |
7a2228cccb8d53e8ca95b3ee0466a05fad70942776015ea15e9b3a970a60d014 | Python | 13,879 | 325 | #!/usr/bin/env python
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
Module used to parse all the route and scenario configuration parameters.
"""
from collections import OrderedDict
import json
import math
import xml.etree.ElementTree as ET
i... |
43b6889ac6747c26491f2d061bbf20f87665eb0e32dcb398e7111291911fc745 | Python | 13,881 | 361 | """Tests for the self-contained HTML registration report builder.
The builder (:mod:`regtools.registration.report`) is pure/stdlib-only and
Qt-free, so these tests need no GUI.
"""
import base64
import os
import struct
import zlib
import pytest
from regtools.registration.report import (
build_html... |
30fb6688112e8dace94c70ae47fa22e1bc9a19c9f3478ff581013d87388123a8 | Python | 13,884 | 402 | #!/usr/bin/env python3
"""
openmm_proteinwater_colab.py
Chunked OpenMM protein-in-water MD with robust resume and Colab-safe I/O.
Key improvements vs the original:
- Platform fallback: CUDA -> OpenCL -> CPU
- Atomic trajectory/log writes: write *.tmp then rename only if chunk finished
- Cleans up 0-byte files automat... |
e89048b00658de6369cb1cdb37ed56bae44ea865366c947c72c4a6b9e9e62e10 | Python | 13,885 | 236 | import sys, os, h5py, pickle
import pandas as pd
from optparse import OptionParser
from scipy import stats
import tensorflow as tf
from tensorflow import keras
from keras.optimizers import Adam
from keras.models import Model, load_model
from keras.layers import *
from keras.metrics import *
from keras.utils import plot... |
5087fe8d759e5f472700cfd80d623f69b23afbcfff78c2f84e00906372bcf547 | Python | 13,893 | 317 | """Tests for regtools.ccf_boundary_editor.contour_edit."""
import numpy as np
import pytest
class TestEditStateDataclasses:
def test_component_not_dragged_when_source_equals_current(self):
from regtools.ccf_boundary_editor.contour_edit import ContourComponent
pts = np.array([[1.0, 2.0]... |
694d948b1c71cbf091cae04daeef664f3ec9c871e521969717dc1e9bdf46964f | Python | 13,897 | 248 | import pandas as pd
import numpy as np
from pyfaidx import Fasta
import argparse
import vcf as pyvcf
from pyensembl import Genome
import tqdm
import os
from tasks_annotate_mutations import SpTransformerDriver, annotate_VCF_general, SNPInterval
class Annotator():
def __init__(self, limit_protein_coding=False) -> N... |
08816c8263b177e25f8ba514e15a59191012a73de8fbc8d8951d57ac3b3efa5e | Python | 13,898 | 328 | # -*- coding: utf-8 -*-
# ORIGINAL DOCUMENTATION:
# TheVirtualBrain-Scientific Package. This package holds all simulators, and
# analysers necessary to run brain-simulations. You can use it stand alone or
# in conjunction with TheVirtualBrain-Framework Package. See content of the
# documentation-folder for more detail... |
6a82388514f8a9a6e67a5636277df5e7a5864421f392b45f3da80717500c57d9 | Python | 13,900 | 418 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# 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 Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from .multihead_attention import ... |
d089d6fbc7cd49819ca347f7120bf9c075f0715ab3f6e8c65ad7d7affdc54d7d | Python | 13,900 | 387 | import tensorflow as tf
# Helper layers
# ========================================================================================================
class _TransformerEncoderLayer(tf.keras.layers.Layer):
def __init__(self, d_model, nhead, dim_feedforward):
super(_TransformerEncoderLayer, self).__init__()
... |
27cfe003b14830cc5a85d6b08624edad7d520c1a717c2bb51088ae7b0f11a740 | Python | 13,909 | 509 | """Parameter classes for Bayesian optimization."""
from __future__ import annotations
import abc
from collections.abc import Callable, Sequence
from inspect import signature
from numbers import Number
from typing import TYPE_CHECKING, Any
import numpy as np
from sklearn.gaussian_process import kernels
from bayes_op... |
bbd309625e9ec43576b9b0de38d0f25fe3fafc1ae4d2dceaa598aa15d9703931 | Python | 13,910 | 280 | """Utilities to support HED validation."""
import warnings
from hed.errors.error_reporter import ErrorHandler
from hed.errors.error_types import ValidationErrors
from hed.validator.util.char_util import UNCLASSED_VALUE_SETS, CharRexValidator
from hed.validator.util.character_sets import code_point
class UnitValueVa... |
291ea937c8e0af3b17427ad2a9c38354cd7304035ffccd660c46845f15d2b872 | Python | 13,913 | 278 | import BEBE.visualization as visualization
import BEBE.evaluation.metrics as metrics
import os
import numpy as np
import pandas as pd
import tqdm
import yaml
import warnings
from sklearn.metrics import homogeneity_score
def perform_evaluation(y_true, y_pred, metadata, num_clusters, unsupervised, output_fp = None, conf... |
977adb946cbede5f4edf24a34b9c7e31fbcb1da5a1ff25fc02801438fc7b88f0 | Python | 13,915 | 247 | """Command-line interface to package treem."""
# pylint: disable=too-many-statements
import argparse
import sys
from treem.io import SWC
from treem.commands.check import check
from treem.commands.view import view
from treem.commands.find import find
from treem.commands.modify import modify
from treem.commands.repai... |
54a660286fde1cda263bb1659f05d2edbec9b576ac01bfc12e5780bb3f4f25a7 | Python | 13,923 | 292 | import site
from typing import Callable, List, Dict, Optional, Literal
from numpy import squeeze
import torch
from torch import nn
from hotpp.layer.radial import ChebyshevPoly
from .base import AtomicModule
from ..layer import EmbeddingLayer, RadialLayer, ReadoutLayer
from ..layer.equivalent import NonLinearLayer, Gra... |
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