sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
23d53b064b9945d04ef281118daa4089107ffd0b9d38d609610f514822210f08 | Python | 1,810 | 48 |
#http://pymc-devs.github.io/pymc3/getting_started/#case-study-2-coal-mining-disasters
import numpy as np
import matplotlib.pyplot as plt
import pymc3
import pymc3.distributions.timeseries as ts
import pandas as pd
import scipy
disaster_data = np.ma.masked_values([4, 5, 4, 0, 1, 4, 3, 4, 0, 6, 3, 3, 4, 0, 2, 6,
... |
3d8c26e10ccce04dda99e3148c4a67b0a5d8130c99b2bc2259861a84a74dbfc5 | Python | 1,810 | 56 | import dataclasses
from abc import abstractmethod
from collections.abc import Iterable
from importlib import resources as res
from .plugin_spec import PluginMap, PluginSpec
from .read_specs_from_toml import read_plugin_dicts_from_package
class PluginLoaderBase[PS: PluginSpec, S]:
"""PluginLoader for translation ... |
40fe0edd6b2860f737c248775309d1f6a983c5d337d5db875b7bc5b34917847c | Python | 1,810 | 56 | # -*- coding: utf-8 -*-
from .. import _logging as logging
from .core import *
__all__ = [
'ROIPoolingLayer',
]
class ROIPoolingLayer(Layer):
"""
The region of interest pooling layer.
Parameters
-----------
layer : :class:`Layer`
The previous layer.
rois : tuple of int
R... |
069aa3e4d183edd34217569abd2fc8a569dda3103834737a60f8a3f530043688 | Python | 1,811 | 52 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Normal
from torch.optim import Adam
from collections import deque, namedtuple
import copy
from .initi_update import soft_update, hard_update, weights_init_
class img_conv(nn.Module):
d... |
3a6e83b64d9360be22e07374510a94d0dc9a1683ca6b6ff82e56482dac76ea98 | Python | 1,811 | 41 | # 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... |
a6d43b7c42886b8bcc035fbe80c8cfc63f5a26c7775317a6801ed207bd6b35b5 | Python | 1,811 | 49 | #----Figure_04_J_preparation----------------------------------------------------
#-------------------------------------------------------------------------------
# This is the code which has to be run in preparation for Figure 04 Panel J
# for the connectivity analysis for Reinhard and Fukuda et al. 2024
#---------... |
f05424afacde199419cafb60451ea2d6e3ee04f42b7cdff3e38a2b22c1ec1d8e | Python | 1,811 | 54 | try:
from Cython.Build import cythonize
except ImportError as e:
raise ImportError(f"{e}. Please install Cython and NumPy before installing this package.") from e
from setuptools import setup, find_packages, Extension
from pathlib import Path
# Define the directory containing this script
this_directory = Path... |
1ff181d5b881f68419378b3fcb6c29376f9dfe8c8eedcd3bcfdeade05838def9 | Python | 1,812 | 51 | from typing import Any
from torch import Tensor
from torch.nn import Linear as TorchLinear
from torch.nn import Module
from torch.nn.utils import parametrize as P
class Linear(TorchLinear):
"""A linear layer.
The weights and bias are fake quantized during initialization.
Make sure that math_ops is a modu... |
31be90b2db8290d071f818bc29c5f6f22f12f28fe5c6279b71b8fa90121ee3e9 | Python | 1,812 | 61 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DI... |
45d3912b0e9628631a8b4316e975ad15d6cf0182d9b13b65b2cacf8c581764de | Python | 1,812 | 74 | from omegaconf import DictConfig
import logging
import numpy as np
from . import cluster_factory
from . import internal_factory
log = logging.getLogger(__name__)
def apply_clustering(method: str, cfg: DictConfig, X: np.ndarray):
'''
Applies clustering to the data matrix X and returns the cluster assignment
... |
4ab10fae8fa2bd003192b44b8e0bd512f718b1b5cbc70a40b62f7d6fd031bee3 | Python | 1,813 | 49 | from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.creator.vhdl.design.design import Design, Port
from elast... |
a3a09f9d8cf19a0e5ea8679cf048fc2ea6fa461c7a761dbf44965c161f5cccc2 | Python | 1,813 | 24 | """posthoc_brian2_per_side_2026-10-02.py (post hoc re-reading of R1, after seeing the whole-brain per-side split).
R1 (PREREG-2026-10-02-KEYSTONE-ROBUST) ran Shiu et al.'s unmodified Brian2 code on the whole brain, 8 channels x 2 trials,
F4 and F4 with v2LN30 root 720575940635945919 (the LEFT one; the prereg called it ... |
f7040cbaf677d33b7ec25f8ec54203b1f3a699ca5d52cf172fef4e6a8a39c315 | Python | 1,813 | 46 | import numpy as np
from utils import signed_stats, pickle_dump
from joblib import Parallel, delayed
from joblib.externals.loky import set_loky_pickler
set_loky_pickler('pickle')
import os
os.environ['OPENBLAS_NUM_THREADS'] = "1"
os.environ['MKL_NUM_THREADS'] = "1"
NNULLS = 100
signed_conns = {}
for filename in os.... |
fa10a9fdc7e8bc77bbb275d249c2ff96daa60be7322723e0e2e9ac9d24fcfae9 | Python | 1,813 | 71 | from __future__ import annotations
import shutil
import stat
from importlib.metadata import version as package_version
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
APP = ROOT / "MorphoGlia.app"
CONTENTS = APP / "Contents"
MACOS = CONTENTS / "MacOS"
VERSION = package_version("morphoglia")
if AP... |
52c9f05e5197a2f07087428311a5c48c96c6947f233944799c68b4b801fba189 | Python | 1,814 | 62 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2023 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : generate_pkl.py
# Author : Yufeng Liu
# Date : 2023-05-11
# Description :
#
#==================... |
79112c561fd3ed2fc8408b69a68028cca57c5bcf9e3dc898ef78d36130936e3d | Python | 1,814 | 50 | #! /usr/bin/env python
"""Dump per-read statistics
This script takes a per-read statistics file and dumps its contents out into a tab-separated values file. The columns in the file are 'chrm', 'pos', 'strand', 'read_id' and 'stat'.
"""
from tombo import tombo_stats
from tombo.tombo_helper import intervalData
import ar... |
d1e31b98423196954936703585ece9ea13450404c818a829f6d55f8e0637c927 | Python | 1,814 | 52 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue635-base", "issue635-v1"]
CONFIGS = [
IssueConfig(
... |
188814378ada35653978dc40287f895f392f2a49027d819d299541ffd203fb0d | Python | 1,815 | 63 | """
Download and build the agfusion database for a range of releases.
"""
import logging
import os
import subprocess
import boto3
from botocore.exceptions import ClientError
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
logger = logging.getLogger(__name__)
S3_BUCKET = "... |
28bd6016e248be2e00d3ffa736ced1fad7eaf23acddf571b2325504b6b54e798 | Python | 1,815 | 53 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not available, scatter plots... |
693f16dc26d209c651604a5d892164eeecad3c39a73514141e8abc220d100239 | Python | 1,815 | 62 | # This script runs the pipeline on all folders in a directory
import warnings
import os
import glob
import shutil
warnings.filterwarnings("ignore")
os.environ["TF_CPP_MIN_LOG_LEVEL"]="2"
# Here you can choose which GPU to use
os.environ["CUDA_VISIBLE_DEVICES"]="3"
import cryovesnet
# Set up the directory where the... |
cfd8ab5f2e011944ee898aecae93dc764cc677021057f62a41e26a562ee5e572 | Python | 1,815 | 54 | from nilearn import datasets
import ABIDEParser2 as Reader
import os
import shutil
# Selected pipeline
pipeline = 'cpac'
# Input data variables
num_subjects = 871 # Number of subjects
#root_folder = '/bigdata/fMRI/ABIDE/'
root_folder = '/media/pjc/expriment/mdd_exam/pjc/DATA/ABIEDE_AAL/'
data_folder = os.path.join(r... |
adb51d08cac8adabe5d6e770495c5f19deccca94f30274f75954a7ab564ef8d8 | Python | 1,816 | 38 | #!/usr/bin/env python
import os
import pandas as pd
import matplotlib.pyplot as plt
from nltools.data import Brain_Data
from nltools.mask import expand_mask, roi_to_brain
from nltools.stats import threshold
from nilearn import plotting as nplot
## location of main project directory on HPC
proj_path = '/project/30111... |
9125aee66f43084008628573025153e453d63720f25afb9b84c96eeede173adf | Python | 1,817 | 84 | #!/usr/bin/env python
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
Collection of TrafficEvents
"""
from enum import Enum
class TrafficEventType(Enum):
"""
This enum represents different traffic events that occur during driving.
... |
cdb41e52d7e9af15d1baeb929df954378763830c3676f0b5152047a6d8179464 | Python | 1,817 | 56 | from ase import Atoms
from ase.calculators.lj import LennardJones
from sella import Sella
def test_sella_logs_hessian_force_evaluation_progress(tmp_path):
atoms = Atoms('Ar2', positions=[[0, 0, 0], [1.5, 0, 0]])
atoms.calc = LennardJones()
logfile = tmp_path / 'sella.log'
opt = Sella(
atoms,... |
e3517ee3524a40ab91779caba58539ec2ad97c27b207db2447c0ad5d48109165 | Python | 1,817 | 61 | # Plots probability of winning recursive feature selection to classify
# preferred corticospinal wave for Fig 7C
from os.path import join
from get_paths import *
import pickle
import matplotlib.pyplot as plt
import numpy as np
from colors_paultol import *
save_flag = 0
## Load data
fname = "data_svc_r... |
ed0523ee86df533d992a4f462bfb1459f052459cf29fc8342bd2456625b40cee | Python | 1,817 | 27 | import os
import shutil
muscle_cell_names = ["MCDR01", "MCDR02", "MCDR03", "MCDR04", "MCDR05", "MCDR06", "MCDR07", "MCDR08", "MCDR09", "MCDR10", "MCDR11", "MCDR12", "MCDR13", "MCDR14", "MCDR15", "MCDR16", "MCDR17", "MCDR18", "MCDR19", "MCDR20", "MCDR21", "MCDR22", "MCDR23", "MCDR24", "MCVR01", "MCVR02", "MCVR03", "MC... |
ed845e5de5746881ac0881879863fcff0cb89447d97ec83544b947ce22e0d25c | Python | 1,817 | 62 | # -*- coding: utf-8 -*-
from __future__ import annotations
import torch
import torch.nn as nn
from supar.modules.dropout import SharedDropout
class MLP(nn.Module):
r"""
Applies a linear transformation together with a non-linear activation to the incoming tensor:
:math:`y = \mathrm{Activation}(x A^T + b)... |
9b2f5fc17610319656fc3efe55d625242439f77161b3c33b3f1be96ac9734a0b | Python | 1,818 | 68 | # 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... |
b77d890dd1258841782f94776ea4aa30326647d074168de0e814745861225e41 | Python | 1,818 | 48 | """Numerical checks for integrated interval-censored Brier scores."""
import pytest
from SurvivalEVAL import IntervalCenEvaluator
@pytest.mark.parametrize(
"integration_method, early_weight, late_weight",
[("trapz", 1 / 2, 1 / 3), ("simpson", 3 / 4, 1 / 4)],
)
@pytest.mark.parametrize(
"left, right, met... |
cd6b41b1ca87d1f146956592395ecc1b46092b0fcb02aff95097348e4c3a2791 | Python | 1,818 | 75 | #!/usr/bin/env python
# coding: utf-8
# In[ ]:
#!/usr/bin/env python3
# Author: Francois Aguet
import numpy as np
import pandas as pd
import scipy.stats as stats
import warnings
# In[ ]:
def normalize_quantiles(df):
"""
Quantile normalization to the average empirical distribution
Note: replicates be... |
0deb1c1de5f38fbd79f4c6c131e1021abbf1d9074e23fea89d0f55d49b72ccbe | Python | 1,819 | 54 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
suite = suites.suite_optimal_with_ipc11()
configs = {
IssueConfig('astar-blind', ['--search... |
8fb9b455c24547002f202dd91defe98c47a2593b8ec81290c153607bbdeb2e7e | Python | 1,819 | 67 | import os
import glob
import sys
def load_results(dir_file, header = True):
with open(dir_file, mode='r') as f:
if header:
next(f)
gene_id = []
gene_score = []
for line in f:
nid, nscore = line.strip("\n").split("\t")
gene_id.append(nid)
... |
95ab48ba49963252d7c12376ded2a9966082627744d26f909fc82db7b93d72ef | Python | 1,819 | 52 | # 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... |
5ac76424967546d980a012cba4e35679110e0f0da48a8db47025f85865afe077 | Python | 1,820 | 73 | import math
import meep as mp
from meep import mpb
# A honeycomb lattice of dielectric rods in air. (This structure has
# a complete (overlapping TE/TM) band gap.) A honeycomb lattice is really
# just a triangular lattice with two rods per unit cell, so we just
# take the lattice, k_points, etcetera from mpb_tri_ro... |
5b33c3a8ee760eb0f20c4dcacfa2381521e1ba1eca774e8235a1c81ab0790b17 | Python | 1,820 | 40 | """
toposampling - Topology-assisted sampling and analysis of activity data
Copyright (C) 2020 Blue Brain Project / EPFL & University of Aberdeen
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation... |
8cd84f2c90d181f702698dcb3d8efe35e3222be02de43406bdfc2902fc7bc8ea | Python | 1,820 | 68 | import re
import torch.nn as nn
class BaseObject(nn.Module):
def __init__(self, name=None):
super().__init__()
self._name = name
@property
def __name__(self):
if self._name is None:
name = self.__class__.__name__
s1 = re.sub("(.)([A-Z][a-z]+)", r"\1_\2", na... |
9840f8e18bc7e2b836717f9e8b1dd04fc36c051168cb805a7c5f57f48cb8f4a6 | Python | 1,820 | 33 | # 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... |
e32311deaaf730de97228b9cf4fd18189778979fe0d37e9ae3b18a4598aa9204 | Python | 1,820 | 42 | """Export publication plots directly from a genuine portable session recording."""
from __future__ import annotations
import argparse
from pathlib import Path
import json
import numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
def main():
parser = argparse.ArgumentParser()
... |
234e2f4e035b19530062d54003cf708379c45a09cab58339639a94754d80bdfd | Python | 1,821 | 66 | """
Simulation parameters that are common to all simulations
Created and modified by: K Dusterwald; C Currin; EF Shorer
"""
###########################
# Constants
###########################
R = 8.31446
F: float = 96485.33 # Faraday's constant C mol-1
k = 1.38e-23 # Boltzmann constant J K-1
q = 1.60... |
2b6190699f1ea0fe5d82b90fa0949b0664c46d575592e6daec1288613d3a5860 | Python | 1,821 | 60 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DI... |
ccee42a2df617ad941fe857f749ed5cacaa5ce1dac9b3ef6ac0149e99cca58d8 | Python | 1,822 | 54 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
#from torch import Generator
from typing import Any
from ..prixfixe import FirstLayersBlock
#from .utils import initialize_weights
class UnlockDNAFirstLayersBlock(FirstLayersBlock):
def __init__(self,
in_channels: int... |
29d4e69a9fd64bbec74063d4e607be087a69a44cb48c56680bbd9d934e60fc72 | Python | 1,823 | 51 | import torch
from fairscale.nn.data_parallel import FullyShardedDataParallel as FSDP
from fairscale.nn.wrap import enable_wrap, wrap
import esm
# init the distributed world with world_size 1
url = "tcp://localhost:23456"
torch.distributed.init_process_group(backend="nccl", init_method=url, world_size=1, rank=0)
# do... |
40494ab826c84119cd0675ba2ca897dc1f72125f017eb679b0be8668a528e606 | Python | 1,823 | 53 | """Entry-point script to label radiology reports."""
import pandas as pd
from args import ArgParser
from loader import Loader
from stages import Extractor, Classifier, Aggregator
from constants import *
def write(reports, labels, output_path, verbose=False):
"""Write labeled reports to specified path."""
lab... |
6902a35ed57be9745182da5cfb5eb8cfb1cdde6345445f2a4ddf1cf5a460cfe4 | Python | 1,823 | 50 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
import json
import numpy as np
import pandas as pd
import conntility
import sys
sys.path.append('../../../library')
from preprocess import load_spike_trains, extract_binned_spike_signals
from dimensionality import... |
727fe1e1fb1474720aa4abe39f34bd9d8f5ca0d752e449932e5262814fbb43a9 | Python | 1,823 | 44 | # 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... |
d2bce013446b906268809958a22ebcb9cdba7827d1297347e12e4d75315e64b5 | Python | 1,823 | 56 | import bct
import numpy as np
from time import process_time
from strength_preserving_rand_rs import strength_preserving_rand_rs
from strength_preserving_rand_sa import strength_preserving_rand_sa
import os
from utils import make_dir, pickle_dump
direc = os.path.abspath('../../data/preprocessed_data/')
scaling_path =... |
879e98a0a054abf54b463c272394325915e9e2df5d9a0c4f12671b3019fe9d81 | Python | 1,824 | 55 | # -*- coding: utf-8 -*-
from __future__ import annotations
from torch.optim import Optimizer
from torch.optim.lr_scheduler import _LRScheduler
class InverseSquareRootLR(_LRScheduler):
def __init__(
self,
optimizer: Optimizer,
warmup_steps: int,
last_epoch: int = -1
) -> Inve... |
944c300128d7b4d8882daea98967344d48cd4b6f7cfc0d5f099682f29edabb46 | Python | 1,824 | 55 | import math
DEFAULT_PAGE_SIZE = 10
PAGE_SIZE_OPTIONS = [
1 * DEFAULT_PAGE_SIZE,
2 * DEFAULT_PAGE_SIZE,
5 * DEFAULT_PAGE_SIZE,
10 * DEFAULT_PAGE_SIZE,
]
PAGE_LINKS_RANGE = [-3, -2, -1, 0, 1, 2, 3]
def pagination_data(items_list, page_number, page_size):
if page_size not in PAGE_SIZE_OPTIONS:
... |
980b032a96b3466c4ee4adb92573cefbb8a18af7854dbbd0d1015bf8af681374 | Python | 1,824 | 68 | import sys, os
import numpy as np
from collections import Counter
import pandas as pd
import pysam
### Initialize ###
try:
inputBamFile = sys.argv[1]
except:
sys.exit('Please, give input bamfile')
if not os.path.isfile(inputBamFile):
sys.exit('bamfile not found')
bamfile = pysam.AlignmentFile(inputBamFi... |
02dcf5c8dd5d25ed52415198a2c468aa712d4933d2cb11ab6dc53724e9888b00 | Python | 1,826 | 48 | import sys, os
from pandas.io.parsers import read_csv
import numpy as np
import pandas as pd
try:
gtffile = sys.argv[1]
outputfile = sys.argv[2]
except:
sys.exit("Please, give: (1) gtf file; (2) exons")
#### Convert gtf file in an easy to handle data frame ####
df = read_csv(gtffile, comment='#', header=N... |
171ef714909b8e3da4fee50608039981c393075e4fae4f957286165c9a7ead50 | Python | 1,826 | 59 | from typing import Any
import torch
import torch.nn.functional as F
from torch import nn, Generator
from ..prixfixe import FinalLayersBlock
from .utils import initialize_weights
class AutosomeFinalLayersBlock(FinalLayersBlock):
def __init__(self, in_channels=64, seqsize = 230):
super(AutosomeFinalLayersB... |
251cda044c25084ebd2cd9e35fbdfbeeb83fb34efdd888ddc384772567354185 | Python | 1,826 | 51 | """
LSTM FUNCTIONS
Designed for the AnDePeD and AnDePeD Pro algorithms.
"""
from keras.models import Sequential
from keras.layers import Input
from keras.layers import LSTM
from keras.layers import Dense
class Lstm:
def __init__(self, b, num_neurons):
self.model = Sequential()
self.model.add(Inp... |
ba69e5a5ce3b7063eb7e32fbf09584b768a0996456bb37d5f1a45b5a90fc99f2 | Python | 1,826 | 52 | from dataclasses import dataclass
from inspect import signature as _signature
@dataclass
class PluginSpec:
"""The specification of a plugin.
Typically built by reading a dictionary from a toml file and
building the spec using <<build_plugin_spec, `build_plugin_spec()`>>.
The dataclass is only used to... |
08d1bc6d16b64c3694a88f146a82b4bcb5183c12bc1a681f905122f0d2147f4f | Python | 1,827 | 52 | # 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... |
eb7a435da84895ce50c242442afda405a1133e0d3cf20a75602d8fd12c3cb00d | Python | 1,827 | 59 | # pylint: disable=too-many-function-args, invalid-name
""" UKB ICA (with age bins (X) sex) labels dataset loading script"""
import numpy as np
import pandas as pd
from omegaconf import DictConfig
def load_data(
cfg: DictConfig,
dataset_path: str = "/data/users2/ppopov1/datasets/ukb/UKB_",
indices_path: st... |
15f529df3cd19ed3f96c546464d165a6006efbd30bd6a4e0e18d39a0c0fbee92 | Python | 1,828 | 57 | import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
from statsmodels.tsa.stattools import adfuller
import seaborn as sns
sns.set_style("ticks",{'axes.grid' : True, 'grid.linestyle': ':','font.family': ['Arial'],})
path = "/u/68/trianaa1/unix/tr... |
c0be99aff9573bac174d7f69bfebf5fd5d4351631b2874e9c3c8d68c62f582ad | Python | 1,828 | 56 | import bct
import numpy as np
from time import process_time
from strength_preserving_rand_rs import strength_preserving_rand_rs
from strength_preserving_rand_sa import strength_preserving_rand_sa
import os
from utils import make_dir, pickle_dump
direc = os.path.abspath('../../data/preprocessed_data/')
scaling_path =... |
0b77f228045cbb4c2787b553e466647d66f1da72c5eb54081034aaba2ccc5f43 | Python | 1,830 | 46 | import numpy as np
from pycm import ConfusionMatrix
from sklearn.metrics import confusion_matrix, cohen_kappa_score
def create_pycm(cm, class_names):
matrix = {}
for i,cl_true in enumerate(class_names):
cl_matrix = {}
matrix[cl_true] = cl_matrix
for j,cl_pred in enumerate(class_names):... |
f0baf33a683127267d1b2b4f4ab15426f53088765e29dc7f874724fd2067d3ad | Python | 1,831 | 71 | """Processes ECoG and LFP data to generate Granger causality values."""
import os
import sys
from pathlib import Path
cd_path = Path(__file__).absolute().parent.parent
sys.path.append(os.path.join(cd_path, "coherence"))
from coh_connectivity_processing import granger_processing
from coh_handle_files import load_file... |
200d4ae716d44c0d9c65c38043cfd47e83a517eaf684477afaa9a2cd57711d94 | Python | 1,832 | 59 | import numpy as np
import pickle as pkl
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib as mpl
import os
from matplotlib import rc
#rc('font',**{'family':'serif','serif':['Computer Modern Roman']})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino... |
20ac982516a94cb34abb2d177f24abf18abe53a8dddf9f0c5cd1505f90024d02 | Python | 1,832 | 84 | # 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... |
4fc0094876defca81c17dc20fd60263ed190ea4951d8bc0135f052c2ab919b96 | Python | 1,832 | 57 | """
Modified by Mayank Kabra
Adapted from DeepLabCut2.0 Toolbox (deeplabcut.org)
DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General P... |
843213aa1c25bbfdc2636e53d2717526099fe726d42a4caeb7799b0614bc69c5 | Python | 1,832 | 46 | import unittest
from torcheeg.transforms import Select, Binary, BinariesToCategory, StringToInt, BinaryOneVSRest, FixCategory
class TestLabelTransforms(unittest.TestCase):
def test_select(self):
info = {'valence': 4.5, 'arousal': 5.5, 'subject_id': 7}
transformed_label = Select(key='valence')(y=i... |
4be1c0cc785777c0bc613469cb9fedf3ca6a34e974e4cc905ceb8a74fd1bb4b0 | Python | 1,833 | 68 | """"""
from pupil_recording_interface.base import BaseConfigurable
class _base_decorator:
""" Base class for decorators. """
registry: dict
name: str
config_attr: str
ignore = tuple()
add = tuple()
add_kwargs = dict()
def __init__(self, type_name, optional=None):
""" Construc... |
753327e60ad91843bfbc8835012bc95754598d1908346fb029578a06eeed3c47 | Python | 1,833 | 56 | # 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 pytest
from pathlib import Path
import torch
import esm
# Directly from hubconf.py
model_names = """
esm1_t6_43M_UR50S,
esm1_t... |
84d1fc2d73cb5edda024bd74d16960868e4426a6bd675528143c95518edd0722 | Python | 1,833 | 62 | import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.mace.ts import ts_job, irc_job, geodesic_job
# Load configuration from TOML file
config = toml.load('inputs_using_mace.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = config['paths']['react... |
5bbd3d9201a1f16ecc4b16be14bb4dddf6c75baf591f692dcb5d2f6c37eccecf | Python | 1,834 | 66 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 13 11:46:36 2020
@author: usingh
"""
import setuptools
#import os
import sys
#from distutils.core import setup
from distutils.extension import Extension
#try cython
try:
from Cython.Distutils import build_ext
from Cython.Build import cython... |
7ca741f4706e4ddaa31cafd7343db16090aebae67b31b9e79a7ad67185dc12be | Python | 1,834 | 60 | # Step 2 of 4: Create 'paramaters' for use in the TriDy pipeline
# These are binary vectors of length 31346, with 1 in the positions of neurons to select, and 0 otherwise
# An input partition is necessary to create these parameters
##
## Load packages
##
print('Loading packages', flush=True)
import json
import sys
i... |
9a048cef66ca8fa0d38b47c68e84898c5db3e5fe627aed58ca190e0257738b4b | Python | 1,834 | 64 | # built-in
from math import isclose
# external
import hypothesis
import pytest
# project
import textdistance
ALG = textdistance.entropy_ncd
@pytest.mark.parametrize('left, right, expected', [
('test', 'test', 1),
('aaa', 'bbb', 0),
('test', 'nani', 0.6),
])
def test_similarity(left, right, expected):
... |
ce0f8deb098f47892e008ad96da3bd19e1e0096cc9540903df7f43bf759830b3 | Python | 1,834 | 55 | from collections.abc import Iterator, Sequence
from typing import Protocol
from elasticai.creator.vhdl.design.design import Design
class SequentialSubmodule(Protocol):
def create_design(self, name: str) -> Design: ...
class SequentialDesignFactory(Protocol):
def create_sequential_design(
self, sub_... |
ea0b594cd22d2c7d432e3f66ac60cbce009e67abd0ea09cce450fa8d98625665 | Python | 1,834 | 67 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterP... |
7da91199cb22d90dc959e47f4b8e435051e702a4d748462bd9bf3dd559381abf | Python | 1,835 | 61 | from numpy import isnan, dtype
from numpy.testing import assert_almost_equal
from pytest import raises
from wonambi import Dataset
from wonambi.utils import create_data
from wonambi.ioeeg.brainvision import _parse_ini
from .paths import brainvision_dir, brainvision_file
def test_brainvision_dataset_01():
d = Da... |
7e3040af4998e112d73a537ea0f46f1195e90af124c4caf609eae9e92bc74603 | Python | 1,836 | 54 | # from .dataset import GoProDataset, MixDataset, VideoDataset
from .data_sampler import DistIterSampler
import torch
import torch.utils.data
def create_dataloader(dataset, args, sampler=None):
phase = args.phase
if phase == 'train':
if args.dist:
world_size = torch.distributed.get_world_si... |
c2dc94b7df7ec89bbd0c143a8a36a93feda81e895538aac1826b8292b98b0d6d | Python | 1,836 | 65 | #!/usr/bin/env python3
import subprocess
import sys
from importlib import resources
def _py():
return sys.executable
def _run(argv: list[str]):
script = resources.files("colabmda.modeller").joinpath("engine.py")
if not script.exists():
raise SystemExit(
"ERROR: bundled modeller6.py n... |
81b88ab512a8f7d21e92270aa062bae64a0ee233ff9cfa3c042e46f8fd053d72 | Python | 1,837 | 62 | """Constants used for JSON schema format."""
from hed.schema.hed_schema_constants import HedSectionKey
# Top-level JSON keys
VERSION_KEY = "version"
LIBRARY_KEY = "library"
WITH_STANDARD_KEY = "withStandard"
UNMERGED_KEY = "unmerged"
PROLOGUE_KEY = "prologue"
EPILOGUE_KEY = "epilogue"
TAGS_KEY = "tags"
UNITS_KEY = "u... |
81e83f91ba17a912418002b1ab0fa19a17d6289632a15ceb6bafe07c56088374 | Python | 1,837 | 69 | from math import log10
import torch
import numpy as np
from sklearn.metrics import roc_auc_score, precision_recall_fscore_support
import torch.nn.functional as F
from scipy.special import softmax
import scipy.stats
def PSNR(mse, peak=1.):
return 10 * log10((peak ** 2) / mse)
class AverageMeter(object):
"""Computes... |
bd6d0bd1f239779b59540bdd1564f3908f470c107a027b16ef74b7a25310839b | Python | 1,837 | 55 | """The GUI preview overlay must render .h5ad points using the stored field
mapping (regression: the preview loaders dropped the mapping, so h5ad cells
silently never appeared on the panel)."""
import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import numpy as np
import pandas as pd
import annd... |
e0033b19486b18a5f9be0a332c481e492c7d569f8023c0be93435e5c3aaf8c5e | Python | 1,838 | 61 | import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.mace.ts import ts_job, irc_job, neb_job
# Load configuration from TOML file
config = toml.load('inputs_using_mace.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = config['paths']['reactant']
... |
f2717b9eebc0e5755cdb668d5d464964d980d1c414095659456d2ff0803f2271 | Python | 1,838 | 34 | import argparse
from feature_compression.compress_features import run_compression
# from feature_compression.train_autoencoder import fit_autoencoder
def generate_and_compress(activations_dir,model_type: str, filter_config: dict,
trafo_type: str, num_components: list):
save_dir = (f'E:/L... |
12cddee68aeed16dd1bd1597fb9ddb002ee60feb24b817c674ceb534c1ed28a3 | Python | 1,839 | 56 | import torch
from . import initialization as init
class SegmentationModel(torch.nn.Module):
def initialize(self):
init.initialize_decoder(self.decoder)
init.initialize_head(self.segmentation_head)
if self.classification_head is not None:
init.initialize_head(self.classification... |
419cfbe800f9d98602ac1e2de43b5fa32b4f7b621685a6e31e87fa4a3a7d4506 | Python | 1,839 | 51 | import torch
import torch.nn as nn
def patch_first_conv(model, new_in_channels, default_in_channels=3, pretrained=True):
"""Change first convolution layer input channels.
In case:
in_channels == 1 or in_channels == 2 -> reuse original weights
in_channels > 3 -> make random kaiming normal initi... |
634862430004b48f27ac304849479689fde3b0b5ccac4de08572664822129733 | Python | 1,839 | 56 | from typing import Dict, List, Union
from ..base_transform import LabelTransform
class Select(LabelTransform):
r'''
Select part of the value from the information dictionary.
.. code-block:: python
transform = Select(key='valence')
transform(y={'valence': 4.5, 'arousal': 5.5, 'subject_id... |
c5f57ff6dd1283aaf38a69ab0ebbbc7c25665256a56007072c37eb2599db6f04 | Python | 1,840 | 56 | import re
from typing import Iterable, List, Tuple
from ._loop import loop_last
from .cells import cell_len, chop_cells
re_word = re.compile(r"\s*\S+\s*")
def words(text: str) -> Iterable[Tuple[int, int, str]]:
position = 0
word_match = re_word.match(text, position)
while word_match is not None:
... |
c7014af464ededccccccae6a2d06e7450c3300fa3c7985d2cbc319053876aa24 | Python | 1,840 | 49 | """
Standalone GUI launcher for Cellpose-SAM cell detection.
Lives beside the package rather than in ``__main__.py`` because
``python -m regtools.cellpose_sam`` is the **CLI** (it takes an input path and
runs detection headlessly). The GUI is ``python -m regtools.cellpose_sam.launch``,
matching regtools.nii_cre... |
12898040fdb0bdbd77641a0c9e3466ae9d43482949e9e893b74fb56931d67275 | Python | 1,842 | 62 | from __future__ import annotations
import subprocess
from subprocess import Popen, PIPE, STDOUT, CalledProcessError
from cuppa.logger import LoggerMixin
class RscriptExecutor(LoggerMixin):
def __init__(
self,
args: list[str],
ignore_error: bool = False, ## Used for testing
verbose... |
5886f147be039278504b825465c809fc352e7f43b45a03bf4939385c83445cfc | Python | 1,842 | 49 | from typing import Literal, cast
import numpy as np
import pandas as pd
from scipy import sparse
CSBase = sparse.csr_matrix | sparse.csc_matrix | sparse.csr_array | sparse.csc_array
CSRBase = sparse.csr_matrix
CSCBase = sparse.csc_matrix
SpBase = sparse.spmatrix
RandomStateLike = int | np.random.Generator | np.rando... |
b574322fd7639f79af00139b6a822a57c57967b88c60ed965b3b626a27aea231 | Python | 1,842 | 34 | import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.svm import LinearSVC
from BEBE.models.supervised_classic_utils import ClassicBehaviorModel
class RandomForest(ClassicBehaviorModel):
def __init__(self, config):
super().__init__(c... |
3201be0789233fafb9016bd6f44e87ff6a0123aaf97a9ad59c2aa9b244eb9fea | Python | 1,843 | 62 | from typing import Optional, Protocol
import torch
from .lstm_cell import LSTMCell
class LayerFactory(Protocol):
def lstm(self, input_size: int, hidden_size: int, bias: bool) -> LSTMCell: ...
class LSTM(torch.nn.Module):
def __init__(
self,
input_size: int,
hidden_size,
bia... |
47fa807bd41afb83754a5b44884f5c07b5ee8e2c8923cb78edeb9fce21d3502f | Python | 1,843 | 66 | from typing import List
from src.data_analysis import ReyFigure
from src.data_analysis import Assessment
from src.data_analysis.item import Item
class Dataset:
def __init__(self):
self.__figures = {}
self.__persons = {}
def all_figures(self) -> List[ReyFigure]:
return [self.__figure... |
8b75a37cce8bd89e3fa6dcdfd89fb6b65eb3e0f1c835d95e8316260e16ed6e7e | Python | 1,843 | 64 | # pylint: disable=too-many-function-args, invalid-name
""" COBRE ICA dataset loading script"""
import h5py
import numpy as np
import pandas as pd
from omegaconf import DictConfig
from src.settings import DATA_ROOT
def load_data(
cfg: DictConfig,
dataset_path: str = DATA_ROOT.joinpath("cobre/COBRE_AllData.h5... |
a690039878ebac1e1f83e5e5de24b36f38734527540045d90856607beeeb30c4 | Python | 1,843 | 68 | import dataclasses
import yaml
import collections
@dataclasses.dataclass
class Params():
def get_bounds(self):
param_dict = self.to_dict()
bounds = []
for key in param_dict.keys():
if 'tau' in key or 'sigma' in key:
bounds.append((0, 10_000))
elif '... |
fd364f4d8150e2aed48a46f08611821423c9a3cc5cb9375698ee7044ee1d513f | Python | 1,843 | 45 | import os, sys
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
from regtools.hub.registry import REGISTRY
from regtools.hub import launch as L
def test_python_exe_swaps_pythonw(monkeypatch):
monkeypatch.... |
79ea07176d5ae91eb2a219a1482ec64e4f3032db91f47e4018e7c53a58451a02 | Python | 1,844 | 53 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Step 1: Load the CSV file
archivo_csv = 'data.csv' # Make sure the CSV file is in the same directory or provide the full path
df = pd.read_csv(archivo_csv)
# Step 2: Verify the first few rows of the DataFrame
print(df.head())
# Step 3: Tran... |
778f45d52701a83cf3ab478322476ed496b250fae442fde98b72673a481eee67 | Python | 1,845 | 46 | import os
from typing import List
from torchvision.datasets.utils import download_and_extract_archive
def download(root: str, file_name: str, archive_name: str, url_link: str):
"""
Download file from internet url link.
Args:
root (str) The directory to put downloaded files.
file_name: (st... |
00acf0ff3b08135f9a70db047812d488bec560a635594ab3e337ebc8f6bd9408 | Python | 1,846 | 62 | import os
import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.mace.ts import ts_job, irc_job, geodesic_job
# Load configuration from TOML file
config = toml.load('inputs_using_mace.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = config['paths... |
90bb48c1ec6cab0478bc851e95446b085e0fe7cc05957cde7d96e638ed2d1878 | Python | 1,846 | 56 | import os
from typing import Optional, List
import IPython
import IPython.display as ipython_display
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
def peek_df(df: pd.DataFrame, n_peek: int = 2) -> None:
print(f'DF shape: {df.shape}')
print(f'Columns: {list... |
c08995784b76d92a6d21a3ec78a4ead33721aba39a5ca0e98bb105902f12ee4a | Python | 1,846 | 60 | """
Generate quasi-random numbers using Halton, Hammerseley, and Sobol sequences.
"""
from __future__ import division, print_function
import numpy as np
from soundsig.thirdparty.sobol_lib import i4_sobol_generate
def quasirand(M, N, type='sobol', spherical=False):
"""Generate N quasi-random M dimensional vector... |
1bcc2995d73709f70e3f83f59c202653d611be43341e65e18b3cde77838ad4f1 | Python | 1,847 | 43 | # coding: utf-8
import sys
import os.path as osp
import torch
def check_keys(model, pretrained_state_dict):
ckpt_keys = set(pretrained_state_dict.keys())
model_keys = set(model.state_dict().keys())
used_pretrained_keys = model_keys & ckpt_keys
unused_pretrained_keys = ckpt_keys - model_keys
missin... |
397798be94b35fffd310cdcfb087ec737c528044c8b58dc5bcab095316f7d512 | Python | 1,847 | 63 | import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.mace.ts import ts_job, irc_job, neb_job
# Load configuration from TOML file
config = toml.load('inputs_using_mace.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = config['paths']['reactant']
... |
685f671884686bd7427356647e4bfb2ed78425953030e309bb530f4c6a5aedab | Python | 1,848 | 56 | import os
import numpy as np
import nibabel as nib
import pytest
from unittest.mock import MagicMock
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
def test_save_atlas_edit_mask_writes_grid(tmp_path):
from PySide6.QtWidgets import QApplication
QApplication.instance() or QApplication([])
... |
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